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 中文|[英文](README.md)
 # MindX SDK Reference Apps
 
-[MindX SDK](https://www.hiascend.com/software/mindx-sdk) 是华为推出的软件开发套件(SDK)，提供极简易用、高性能的API和工具，助力昇腾AI处理器赋能各应用场景。
+[MindX SDK](https://www.hiascend.com/software/mindx-sdk) 是华为推出的软件开发套件(SDK)，提供极简易用、高性能的API和工具，包含mxVision（视觉分析）、mxRAG（知识增强）、mxIndex（特征检索）、mxRec（搜索推荐）等多个SDK，助力昇腾AI处理器赋能各应用场景。
 
-mxSdkReferenceApps是基于MindX SDK开发的参考样例。
+为助力开发者快速掌握mxVision和mxRAG接口的使用、快速实现业务功能，本代码仓（mxSdkReferenceApps）提供了基于mxVision和mxRAG开发的各类参考样例。用户可以根据自身需求选择相应案例代码。
 
 
-## 版本说明
 
-**请在[SDK产品选择页面](https://www.hiascend.com/software/mindx-sdk)选择您使用的产品后，通过下拉框选择支持的SDK版本并查看配套关系。**
+## 主要目录结构与说明
+| 目录                     | 说明             |
+|------------------------|----------------|
+| [mxVision](./mxVision) | mxVision参考样例目录 |
+| [mxRAG](./mxRAG)       | mxRAG参考样例目录    | 
 
->目前SDK分为：制造质检 [mxManufacture](https://www.hiascend.com/software/mindx-sdk/mxManufacture/community)、视觉分析 [mxVision](https://www.hiascend.com/software/mindx-sdk/mxVision/community)、检索聚类 [mxIndex](https://www.hiascend.com/software/mindx-sdk/mxIndex/community)。  
-以上分支版本号相同，为适配不同的方向的SDK组件。
-
-- **当前分支样例版本适配说明如下：**    
-    | SDK版本 | CANN版本 |
-    |---|---|
-    | 2.0.4 | [5.0.4](https://www.hiascend.com/software/cann/commercial) | 
-
-## 目录结构与说明
-| 目录 | 说明 |
-|---|---|
-| [build](./build) | 用户贡献样例构建目录 |
-| [contrib](./contrib) | 用户贡献样例目录 |
-| [docs](./docs) | 文档目录 |
-| [mxVision](./mxVision) | 官方应用样例目录 | 
-| [tools](./tools) | 开发测试相关工具 | 
-| [tutorials](./tutorials) | 官方开发样例和文档参考工程目录 | 
-
-## 安装
-**按照如下步骤搭建环境：**      
-     (1) 在[昇腾文档](https://www.hiascend.com/document?tag=commercial-developere)中选择**CANN 软件安装指南**，点击进入文档。  
-     (2) 根据文档了解整体流程并根据文档进行硬件及CANN软件安装。  
-     (3) 在SDK下载页面中选择**MindX SDK {版本} {产品} 用户指南**。  
-     (4) mxManufacture和mxVision需根据不同开发(使用MindStudio开发/使用命令行方式开发)中对应**环境准备**章节完成安装。
-
-## 开发样例  
-**根据以下表单，选择需要运行的样例，并按照readme部署相关样例和参考工程**
-| 样例名称 | 简介 |
-|---|---|
-| [DvppWrapper接口样例](./tutorials/DvppWrapperSample) | 对图片实现编码，解码，缩放，抠图，以及把样例图片编码为264视频文件 |
-| [图像检测样例](./tutorials/ImageDetectionSample) | c++和python版本的图像检测样例，可刷输出检测结果 |
-| [c++图片输入yolov3样例](./tutorials/mxBaseSample) | c++语言的yolov3图像检测样例及yolov3的后处理模块开发 |
-| [c++视频输入yolov3样例](./tutorials/mxBaseVideoSample) | 针对视频输入的c++版本yolov3样例 |
-| [绘图单元使用样例](./tutorials/OsdSample) | 使用osd对图像进行自定义绘图的样例 |
-| [输入输出插件使用演示](./tutorials/PipelineInputOutputSample) | 对多种输入输出方式进行演示的样例 |
-| [元数据输出输出样例](./tutorials/protocolSample) | 如何自行编解码元数据的演示样例 |
-| [SDK插件开发](./tutorials/mindx_sdk_plugin) | [4-1](docs/quickStart/4-1插件开发调试指导.md)章节对应的样例代码 |
-| [模型后处理插件开发](./tutorials/SamplePostProcess) | [4-2](docs/quickStart/4-2模型后处理库(内置类型)开发调试指导.md)章节对应的演示代码 |
-| [自定义proto结构体](./tutorials/sampleCustomProto) | [4-3](docs/quickStart/4-3挂载自定义proto结构体.md)章节对应的演示代码 |
-| [自定义后处理插件开发](./tutorials/samplePluginPostProc) | [4-4](docs/quickStart/4-4模型Tensor数据处理&自定义模型后处理.md)章节对应的演示代码 |
-1. SDK已支持的模型直接使用**mxpi_{类型}postprocessor**插件([SDK2.0.4后处理](https://support.huawei.com/enterprise/zh/doc/EDOC1100234263/cab50573))配置对应参数即可([SDK2.0.4模型支持列表](https://support.huawei.com/enterprise/zh/doc/EDOC1100234263/8c42df9f))
-2. 未支持的模型根据任务类型，选择SDK已经支持的后处理基类(目标检测，分类任务，语义分割，文本生成)([SDK2.0.4后处理基类](https://support.huawei.com/enterprise/zh/doc/EDOC1100234263/51b8b606))去派生一个新的子类，参考**模型后处理插件开发**进行开发。
-3. 如果当前后处理基类所采用的数据结构无法满足需求，用户需要自行开发**自定义后处理插件开发**，或将tensor数据通过**元数据输出输出样例**输出至外部来处理
-
-## 运行  
-**根据以下表单，选择需要运行的样例，并按照readme进行第三方依赖的安装及样例下载运行**      
-| 样例名称 | 语言 | 适配SDK版本 | 简介 |
-|---|---|---|---|
-| [动作识别](./contrib/ActionRecognition) | python | >=2.0.4 | 单人独处、逗留超时、快速移动、剧烈运动、离床检测、攀高检测六种应用场景 |
-| [AI风景画](./contrib/ai_paint) | python | >=2.0.4 | 从结构化描述生成对应风景照片 |
-| [自动语音识别](./contrib/ASR&KWR) | python | >=2.0.4 |端到端的自动语音识别(AutoSpeechRecognition)+文本关键词识别(KeyWordRecognition) |
-| [文本分类](./contrib/BertTextClassification) | c++ | >=2.0.4 | 新闻文本分类类别：体育、健康、军事、教育、汽车 |
-| [车牌识别](./contrib/CarPlateRecognition) | c++ | >=2.0.4 | 对图像中的车牌进行检测，并对检测到每一个车牌进行识别 |
-| [卡通图像生成](./contrib/CartoonGANPicture) | c++ | >=2.0.4 | 通用场景下的jpg图片卡通化 |
-| [黑白图像上色](./contrib/Colorization) | python | >=2.0.4 | 输入黑白图像，自动对黑白图像进行上色，还原彩色图像 |
-| [人群计数](./contrib/CrowdCounting) | c++ | >=2.0.4 | 人群计数目标检测，输出可视化结果 |
-| [驾驶员状态识别](./contrib/DriverStatusRecognition) | python | >=2.0.4 | 识别视频中的驾驶员状态 |
-| [边缘检测](./contrib/EdgeDetectionPicture) | c++ | >=2.0.4 | 图像边缘提取，输出可视化结果 |
-| [EfficientDet](./contrib/EfficientDet) | python | >=2.0.4 | 使用 EfficientDet 模型进行目标检测 |
-| [目标检测](./contrib/FaceBoxes) | python | >=2.0.4 | 对图像中的目标进行画框并且标注置信度 |
-| [口罩识别](./contrib/facemaskdetection) | python | >=2.0.4 | 对原图像的目标以及口罩进行识别画框 |
-| [目标替换](./contrib/faceswap) | python | >=2.0.4 | 进行目标检测，脸部关键点推理以及目标替换，将替换结果可视化并保存 |
-| [情绪识别](./contrib/FacialExpressionRecognition) | python | >=2.0.4 | 采集图片中的目标图像，然后利用情绪识别模型推理情绪类别 |
-| [目标跟踪](./contrib/FairMOT) | python | >=2.0.4 | 视频目标检测和跟踪，对行人进行画框和编号 |
-| [语义分割](./contrib/FastSCNN) | python | >=2.0.4 | 对图片实现语义分割功能 |
-| [疲劳驾驶识别](./contrib/FatigueDrivingRecognition) | python | >=2.0.4 | 对视频中驾驶人员疲劳状态识别与预警 |
-| [火灾识别](./contrib/FireDetection) | python | >=2.0.4 | 对视频中高速公路车辆火灾和烟雾的识别告警 |
-| [手势关键点](./contrib/GestureKeypointDetection) | python | >=2.0.4 | 检测图像中所有的人手，输出手势关键点连接成的手势骨架 |
-| [头部姿态识别](./contrib/HeadPoseEstimation) | python | >=2.0.4 | 对图像中的头部进行姿态识别，输出可视化结果 |
-| [安全帽识别](./contrib/HelmetIdentification) | python | >=2.0.4 | 两路视频的安全帽去重识别，并对为佩戴行为告警 |
-| [人体语义分割](./contrib/human_segmentation) | c++ | >=2.0.4 | 对输入图片中的人像进行语义分割操作，然后输出mask掩膜图，将其与原图结合，生成标注出人体部分的人体语义分割图片 |
-| [个体属性识别](./contrib/Individual) | python | >=2.0.4 | 识别多种目标属性信息，包括年龄、性别、颜值、情绪、脸型、胡须、发色、是否闭眼、是否配戴眼镜、目标质量信息及类型等 |
-| [语音关键词检测](./contrib/kws) | python | >=2.0.4 | 对语音进行关键词检测 |
-| [人像分割](./contrib/MMNET) | python | >=2.0.4 | 基于MMNET解决移动设备上人像抠图的问题，旨在以最小的模型性能降级在移动设备上获得实时推断 |
-| [单目深度估计](./contrib/MonocularDepthEstimation) | python | >=2.0.4 | 基于AdaBins室内模型的单目深度估计，输出目标图像的深度图 |
-| [多路视频检测](./contrib/MultiChannelVideoDetection) | c++ | >=2.0.4 | 同时对两路本地视频或RTSP视频流(H264或H265)进行YOLOv3目标检测，生成可视化结果 |
-| [小麦检测](./contrib/mxBase_wheatDetection) | c++ | >=2.0.4 | 使用yolov5对图像中的小麦进行识别检测 |
-| [OCR身份证检测识别](./contrib/OCR/IDCardRecognition) | python | >=2.0.4 | 对身份证进行识别和检测 |
-| [OCR关键词检测](./contrib/OCR/KeywordDetection) | python | >=2.0.4 | 对图片进行识别并检测是否包含指定关键词 |
-| [人体关键点检测](./contrib/OpenposeKeypointDetection) | python | >=2.0.4 | 输入一幅图像，可以检测得到图像中所有行人的关键点并连接成人体骨架 |
-| [行人属性检测](./contrib/PedestrianAttributeRecognition) | python | >=2.0.4 | 对检测图片中行人的定位和属性进行识别 |
-| [人群密度计数](./contrib/PersonCount) | python | >=2.0.4 | 输入一幅人群图像，输出图像当中人的计数（估计）的结果 |
-| [文本检测](./contrib/PixelLink) | python | >=2.0.4 | 识别图像文本的位置信息，将识别到的文本位置用线条框选出来 |
-| [人像分割与背景替换](./contrib/PortraitSegmentation) | python | >=2.0.4 | 使用Portrait模型对输入图片中的人像进行分割，然后与背景图像融合，实现背景替换 |
-| [行人重识别](./contrib/ReID) | python | >=2.0.4 | 检索给定照片中的行人ID，并与特征库对比展示 |
-| [遥感影像地块分割检测样例](./contrib/RemoteSensingSegmentation) | python | >=2.0.4 | 输出遥感图像的可视化语义分割图 |
-| [无人机遥感旋转目标检测](./contrib/RotateObjectDetection) | python | >=2.0.4 | 输入一张待检测图片，可以输出目标旋转角度检测框，并有可视化呈现 |
-| [3D目标检测](./contrib/RTM3DTargetDetection) | python | >=2.0.4 | 对道路单色RGB图像进行三维目标检测 |
-| [情感极性分类](./contrib/SentimentAnalysis) | python | >=2.0.4 | 输入一段句子，可以判断该句子属于哪个情感极性 |
-| [发言者识别](./contrib/SpeakerRecog) | python | >=2.0.4 | 对发言者进行识别。如果声纹库中不包含当前说话人，则对当前说话人进行注册并保存至声纹库，否则给出识别结果 |
-| [图像超分辨率](./contrib/SuperResolution) | python | >=2.0.4 | 对输入的图片利用VDSR模型进行超分辨率重建 |
-| [车道线检测](./contrib/UltraFastLaneDetection) | python | >=2.0.4 | 对图像中的车道线进行检测，并对检测到的图像中的每一条车道线进行识别 |
-| [车流量统计](./contrib/VehicleCounting) | c++ | >=2.0.4 | 对视频中的车辆进行计数，实现对本地视频（H264）进行车辆动向并计数，最后生成可视化结果 |
-| [视频手势识别运行](./contrib/VideoGestureRecognition) | c++ | >=2.0.4 | 对本地视频（H264）进行手势识别并分类，生成可视化结果 |
-| [伪装目标分割](./contrib/CamouflagedObjectDetection) | python | >=2.0.4 | 对图像中的伪装目标进行识别检测，生成可视化分割结果 |
-
-## 插件使用
-**以下表单描述了各插件在哪些样例中有使用，供用户查找参考**   
-|             插件名称             |                         参考设计位置                         |                         具体样例名称                         |
-| :------------------------------: | :----------------------------------------------------------: | :----------------------------------------------------------: |
-|              appsrc              |                            run包                             |                             通用                             |
-|           mxpi_rtspsrc           |                            run包                             | SampleOsdVideo2Channels.pipeline<br>VideoObjectDetection.pipeline<br>SampleMotsimplesortv2.pipeline<br>SampleSkipframe.pipeline |
-|        mxpi_dataserialize        |                            run包                             |                             通用                             |
-|             appsink              |                            run包                             |                             通用                             |
-|             fakesink             |                            run包                             |                             通用                             |
-|             filesink             |                            run包                             |                      SampleOsd.pipeline                      |
-|       mxpi_parallel2serial       |                            run包                             | SampleNmsoverLapedroiv2.pipeline<br>SampleOsdVideo2Channels.pipeline |
-|         mxpi_distributor         |                            run包                             | SampleNmsoverLapedroiv2.pipeline<br/>SampleOsdVideo2Channels.pipeline |
-|         mxpi_synchronize         | [gitee-mxVision](https://gitee.com/ascend/mindxsdk-referenceapps/tree/master/mxVision/AllObjectsStructuring) |                    AllObjectsStructuring                     |
-|        mxpi_datatransfer         | [gitee-mxVision](https://gitee.com/ascend/mindxsdk-referenceapps/tree/master/mxVision/MultiThread) |                         MultiThread                          |
-|       mxpi_nmsoverlapedroi       |                             弃用                             |                                                              |
-|      mxpi_nmsoverlapedroiV2      |                            run包                             |               SampleNmsoverLapedroiv2.pipeline               |
-|        mxpi_roigenerator         |                            run包                             |              SemanticSegPostProcessor.pipeline               |
-|     mxpi_semanticsegstitcher     |                            run包                             |              SemanticSegPostProcessor.pipeline               |
-|       mxpi_objectselector        |                            run包                             |                SampleObjectSelector.pipeline                 |
-|          mxpi_skipframe          |                            run包                             |                   SampleSkipframe.pipeline                   |
-|        mxpi_imagedecoder         |                            run包                             |                             通用                             |
-|         mxpi_imageresize         |                            run包                             |                             通用                             |
-|          mxpi_imagecrop          |                            run包                             | Sample.pipeline<br>SampleNmsoverLapedroiv2.pipeline<br>SampleObjectSelector.pipeline<br>SampleOsdVideo2Channels.pipeline |
-|        mxpi_videodecoder         |                            run包                             |                             通用                             |
-|        mxpi_videoencoder         |                            run包                             |               SampleOsdVideo2Channels.pipeline               |
-|        mxpi_imageencoder         |                            run包                             |                      SampleOsd.pipeline                      |
-|       mxpi_imagenormalize        |                            run包                             |                SampleImageNormalize.pipeline                 |
-|      mxpi_opencvcentercrop       |                            run包                             |               SampleOpencvCenterCrop.pipeline                |
-|       mxpi_warpperspective       |                    mindxsdk-referenceapps                    |                    GeneralTextRecognition                    |
-|          mxpi_rotation           |                    mindxsdk-referenceapps                    |                    GeneralTextRecognition                    |
-|         mxpi_modelinfer          |                             弃用                             |                                                              |
-|         mxpi_tensorinfer         |                            run包                             |                             通用                             |
-|     mxpi_objectpostprocessor     |                            run包                             |      SampleObjectSelector.pipeline<br/>Sample.pipeline       |
-|     mxpi_classpostprocessor      |                            run包                             | Sample.pipeline<br>SampleOsdVideo2Channels.pipeline<br>BertMultiPorts.pipeline |
-|  mxpi_semanticsegpostprocessor   |                            run包                             |              SemanticSegPostProcessor.pipeline               |
-| mxpi_textgenerationpostprocessor |                            run包                             |             TextGenerationPostProcessor.pipeline             |
-|   mxpi_textobjectpostprocessor   |                    mindxsdk-referenceapps                    |                    GeneralTextRecognition                    |
-|    mxpi_keypointpostprocessor    |                            run包                             |                KeyPointPostProcessor.pipeline                |
-|        mxpi_motsimplesort        |                             弃用                             |                                                              |
-|       mxpi_motsimplesortV2       |                            run包                             |                                                              |
-|        mxpi_facealignment        |                    mindxsdk-referenceapps                    |                    FaceFeatureExtraction                     |
-|      mxpi_qualitydetection       | [gitee-mxVision](https://gitee.com/ascend/mindxsdk-referenceapps/tree/master/mxVision/VideoQualityDetection) |                    VideoQualityDetection                     |
-|          mxpi_dumpdata           | [用户指南](https://support.huawei.com/enterprise/zh/doc/EDOC1100234263/ba172876) |                                                              |
-|          mxpi_loaddata           | [用户指南](https://support.huawei.com/enterprise/zh/doc/EDOC1100234263/ba172876) |                                                              |
-|          mxpi_opencvosd          |                            run包                             |                      SampleOsd.pipeline                      |
-|     mxpi_object2osdinstances     |                            run包                             |               SampleOsdVideo2Channels.pipeline               |
-|     mxpi_class2osdinstances      |                            run包                             |               SampleOsdVideo2Channels.pipeline               |
-|      mxpi_osdinstancemerger      |                            run包                             |               SampleOsdVideo2Channels.pipeline               |
-|       mxpi_channelselector       |                            run包                             |               SampleOsdVideo2Channels.pipeline               |
-|    mxpi_channelimagesstitcher    |                            run包                             |               SampleOsdVideo2Channels.pipeline               |
-|  mxpi_channelosdcoordsconverter  |                            run包                             |               SampleOsdVideo2Channels.pipeline               |
-|       mxpi-bufferstablizer       |                            run包                             |               SampleOsdVideo2Channels.pipeline               |
-
-
-
-## 文档
-
-参考各组件：制造质检 [mxManufacture](https://www.hiascend.com/software/mindx-sdk/mxManufacture/community)、视觉分析 [mxVision](https://www.hiascend.com/software/mindx-sdk/mxVision/community)、检索聚类 [mxIndex](https://www.hiascend.com/software/mindx-sdk/mxIndex/community)内的**用户手册**链接获取相关文档。
 
 ## 社区
 
-昇腾社区鼓励开发者多交流，共学习。开发者可以通过以下渠道进行交流和学习。
-
-昇腾社区网站：hiascend.com
-
-昇腾论坛：https://bbs.huaweicloud.com/forum/forum-726-1.html
->SDK专属空间位于**MindX应用使能**子目录下
+昇腾社区鼓励开发者多交流，共学习。开发者可以通过昇腾社区网站获取最新的MindX SDK的软件、文档等资源；可以通过昇腾论坛与其他开发者交流开发经验。
 
-昇腾官方qq群：965804873
+昇腾社区网站：https://www.hiascend.com/
 
-## 贡献代码
+昇腾论坛：https://www.hiascend.com/forum/
 
-欢迎参与贡献。更多详情，请参阅我们的[CONTRIBUTING.md](./contrib/CONTRIBUTING.md)
 
 ## 免责声明
 
diff --git a/build/build.sh b/build/build.sh
deleted file mode 100644
index db8341850829891c7edb063fab4d5ef10a4d4563..0000000000000000000000000000000000000000
--- a/build/build.sh
+++ /dev/null
@@ -1,26 +0,0 @@
-#!/bin/bash
-# Copyright 2021 Huawei Technologies Co., Ltd
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-# http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.mitations under the License.
- 
-set -e 
-current_folder="$( cd "$(dirname "$0")" ;pwd -P )"
-
-export MX_SDK_HOME=/opt/buildtools/mindxsdk/mxVision
-
-bash $current_folder/../contrib/build_all.sh
-
-exit 0
-
-
-
diff --git a/contrib/CONTRIBUTING.md b/contrib/CONTRIBUTING.md
deleted file mode 100644
index 82ce68f2cc4232019329bad849fbf3e19f664f70..0000000000000000000000000000000000000000
--- a/contrib/CONTRIBUTING.md
+++ /dev/null
@@ -1,197 +0,0 @@
-### 介绍
-
-mindxsdk-referenceapps欢迎各位开发者的加入，希望各位开发者遵循社区的行为准则，共同建立一个开放和受欢迎的社区 [ Ascend社区行为准则 1.0 版本]([code-of-conduct_zh_cn.md · Ascend/community - 码云 - 开源中国 (gitee.com)](https://gitee.com/ascend/community/blob/master/code-of-conduct_zh_cn.md))
-
-### 贡献要求
-
-请贡献者在提交代码之前签署CLA协议，“个人签署”，[链接](https://clasign.osinfra.cn/sign/Z2l0ZWUlMkZhc2NlbmQ=)
-
-如您完成签署，可在自己提交的PR评论区输入/check-cla进行核实校验
-
-开发者提交的内容包括项目源码、配置文件、readme、启动脚本等文件，并遵循以下标准提交：
-
-### 一、提交内容
-
-- **提交清单**
-
-| 文件         | 描述                                                         |
-| ------------ | ------------------------------------------------------------ |
-| **README**   | 包含第三方依赖安装、模型转换、编译、运行指导等内容，能指导端到端使用 |
-| 代码         | 包含插件开发的C++代码、CMakeLists.txt、python/C++推理运行代码、精度与性能测试代码 |
-| 配置文件     | 运行时相关配置文件，用于加载相关运行参数的文件               |
-| pipeline文件 | MindX SDK的编排文件                                          |
-| 启动脚本     | 包括编译、运行、测试、模型转换等脚本                         |
-
-- **典型的目录结构**
-
-```bash
-├── config #配置文件目录
-│   └── configure.cfg
-├── model #模型目录
-├── pipeline
-│   └── test.pipeline
-├── Plugin1 #插件1工程目录
-│   ├── CMakeLists.txt
-│   ├── Plugin1.cpp
-│   └── Plugin1.h
-├── Plugin2 #插件2工程目录
-│   ├── CMakeLists.txt
-│   ├── Plugin2.cpp
-│   └── Plugin2.h
-├── main.cpp
-├── main.py
-├── README.md
-├── build.sh
-└── run.sh
-```
-
-**注意**：相关输入的数据（图像、视频等）请不要上传到代码仓，在README注明如何获取即可
-
-### 二、源码
-
-1、MindX SDK离线推理请使用`C++`或`python`代码，符合第四部分编码规范
-
-2、贡献者参考设计代码目录命名规则
-
-```shell
-mindxsdk-referenceapps/contrib/参考设计名称(英文)
-```
-
-### 三、License规则
-
-涉及的代码、启动脚本都均需要在开始位置添加华为公司 License [华为公司 License链接](https://gitee.com/mindspore/mindspore/blob/master/LICENSE)
-
-- **C++**
-
-```c++
-/*
- * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-```
-
-- **python**&**shell**
-
-```python
-# Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-# http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-```
-
-> 关于License声明时间，应注意： 2021年新建的文件，应该是Copyright 2021 Huawei Technologies Co., Ltd 2020年创建年份，2020年修改年份，应该是Copyright 2020 Huawei Technologies Co., Ltd
-
-### 四、编程规范
-
-- 规范标准
-
-  C++遵循Google编程规范，Python代码均遵循PEP 8编码规范
-
-  规范参考链接：[zh-cn/contribute/OpenHarmony-cpp-coding-style-guide.md · OpenHarmony/docs - Gitee.com](https://gitee.com/openharmony/docs/blob/master/zh-cn/contribute/OpenHarmony-cpp-coding-style-guide.md)
-
-- 规范备注（前4条规则C++适用）
-
-1、优先使用string类型，避免使用char*；
-
-2、禁止使用printf，一律使用cout；
-
-3、内存管理尽量使用智能指针；
-
-4、不准在函数里调用exit；
-
-5、禁止使用IDE等工具自动生成代码；
-
-6、控制第三方库依赖，如果引入第三方依赖，则需要提供第三方依赖安装和使用指导书；
-
-7、一律使用英文注释，注释率30%--40%，鼓励自注释；
-
-8、函数头必须有注释，说明函数作用，入参、出参；
-
-9、统一错误码，通过错误码可以确认那个分支返回错误；
-
-10、禁止出现打印一堆无影响的错误级别的日志；
-
-### 五、代码提交规范
-
-- 关键要求：
-
-1、请将**`mindxsdk-referenceapps`**仓**fork**到个人分支，基于个人分支提交代码到个人**fork仓**，并创建**`Pull Requests`**，提交合并请求到主仓上
-
-**参考Fork+Pull Requests 模式**：https://gitee.com/help/articles/4128#article-header0
-
-> pr提交后请不要再关闭pr，一切操作都在不关pr的条件下进行操作
-
-2、PR标题模板
-
-```
- [xxx学校] [xxx参考设计]
-```
-
-3、PR内容模板
-
-```
-### 相关的Issue
-
-### 原因（目的、解决的问题等）
-
-### 描述（做了什么，变更了什么）
-
-### 测试用例（新增、改动、可能影响的功能）
-```
-
-### 六、ISSUE提交规范
-
-1、ISSUE提交内容需包含三部分：当前行为、预期行为、复现步骤
-
-2、ISSUE提交模板：
-
-```
-一、问题现象（附报错日志上下文）：
-### 当前现象
-    xxxx
-    
-### 预期现象
-    xxxx
-
-二、软件版本:
--- CANN 版本 (e.g., CANN 3.0.x，5.x.x):  
---Tensorflow/Pytorch/MindSpore 版本:
---Python 版本 (e.g., Python 3.9.2):
--- MindStudio版本 (e.g., MindStudio 2.0.0 (beta3)):
---操作系统版本 (e.g., Ubuntu 18.04):
-
-三、复现步骤：
-xxxx
-
-
-四、日志信息:
-xxxx
-### 请根据自己的运行环境参考以下方式搜集日志信息，如果涉及到算子开发相关的问题，建议也提供UT/ST测试和单算子集成测试相关的日志。
-
-日志提供方式:
-### 将日志打包后作为附件上传。若日志大小超出附件限制，则可上传至外部网盘后提供链接。
-
-### 获取方法请参考wiki：
-https://gitee.com/ascend/modelzoo/wikis/%E5%A6%82%E4%BD%95%E8%8E%B7%E5%8F%96%E6%97%A5%E5%BF%97%E5%92%8C%E8%AE%A1%E7%AE%97%E5%9B%BE?sort_id=4097825
-```
-
diff --git a/contrib/build_all.sh b/contrib/build_all.sh
deleted file mode 100644
index 0c861ba6a8a76f053c2999d66bd4afd204f0517a..0000000000000000000000000000000000000000
--- a/contrib/build_all.sh
+++ /dev/null
@@ -1,73 +0,0 @@
-#!/bin/bash
-# Copyright 2021 Huawei Technologies Co., Ltd
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-# http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
- 
-set -e 
-current_folder="$( cd "$(dirname "$0")" ;pwd -P )"
-
-
-SAMPLE_FOLDER=(
-    # ActionRecognition/
-    # CrowdCounting/
-    # mxBase_wheatDetection/
-    # EdgeDetectionPicture/
-    HelmetIdentification/
-    Individual/
-    # human_segmentation/
-    # OpenposeKeypointDetection/
-    PersonCount/
-    # FatigueDrivingRecognition/
-    # CartoonGANPicture/
-    # HeadPoseEstimation/
-    FaceBoxes/
-    BertTextClassification/
-    # RTM3DTargetDetection/
-    EfficientDet/
-    SentimentAnalysis/
-    # RotateObjectDetection/
-    # FairMOT/
-    UltraFastLaneDetection/
-    VehicleIdentification/
-    yunet/
-    # RoadSegmentation/
-    # PassengerflowEstimation/
-    # VehicleRetrogradeRecognition/
-    # Collision/
-    # PassengerflowEstimation/
-    CenterFace/
-    YOLOX/
-    PicoDet/
-    SOLOV2/
-    # OpenCVPlugin/
-    RefineDet/
-    FCOS
-    Faster_R-CNN/
-    MeterReader/
-    # RTMHumanKeypointsDetection/
-)
-
-err_flag=0
-for sample in ${SAMPLE_FOLDER[@]};do
-    cd ${current_folder}/${sample}
-    bash build.sh || {
-        echo -e "Failed to build ${sample}"
-        err_flag=1
-    }
-done
-
-
-if [ ${err_flag} -eq 1 ]; then
-    exit 1
-fi
-exit 0
diff --git a/mindxsdk-referenceapps b/mindxsdk-referenceapps
deleted file mode 160000
index 4eb4770587ad2ce9f9ed643b8e4874992c3c0398..0000000000000000000000000000000000000000
--- a/mindxsdk-referenceapps
+++ /dev/null
@@ -1 +0,0 @@
-Subproject commit 4eb4770587ad2ce9f9ed643b8e4874992c3c0398
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diff --git a/contrib/ADNet/README.md b/mxVision/mxVision-referenceapps/ADNet/README.md
similarity index 97%
rename from contrib/ADNet/README.md
rename to mxVision/mxVision-referenceapps/ADNet/README.md
index 8ece88ef63a13477e99b0e3e42fd1102db9d1c85..57ff88c6c8aba1be8e308efe904d97453358ff6e 100644
--- a/contrib/ADNet/README.md
+++ b/mxVision/mxVision-referenceapps/ADNet/README.md
@@ -1,201 +1,201 @@
-# ADNet图像去噪参考设计
-
-## 1  介绍
-使用 ADNet 模型，在 MindX SDK 环境下实现图像去噪功能。
-由用户设置测试图片，传入到 pipeline 中先后实现前处理，模型推理，后处理等功能，最终输出结果图片实现可视化及模型精度计算。
-
-```
-ADNet 是一种包含注意力模块的卷积神经网络，主要包括用于图像去噪的稀疏块（SB）、特征增强块（FEB）、注意力块（AB）和重建块（RB）。
-
-其中，SB 模块通过使用扩张卷积和公共卷积来去除噪声，在性能和效率之间进行权衡。FEB 模块通过长路径整合全局和局部特征信息，以增强去噪模型的表达能力。 
-
-AB 模块用于精细提取复杂背景中的噪声信息，对于复杂噪声图像，尤其是真实噪声图像非常有效。 此外，FEB 模块与 AB 模块集成以提高效率并降低训练去噪模型的复杂度。
-
-最后，RB 模块通过获得的噪声映射和给定的噪声图像来构造干净的图像。
-```
-
-### 1.1 支持的产品
-
-以昇腾 Atlas310 卡为主要的硬件平台
-
-### 1.2 支持的版本
-
-CANN：7.0.RC1
-
-SDK：mxVision 5.0.RC3（可通过cat SDK目录下的 version.info 查看）
-
-### 1.3 软件方案介绍
-
-项目主要由主函数，pipeline 文件，模型及其配置文件，测试数据集组成。
-主函数中构建业务流 stream 读取图片，通过 pipeline 在 SDK 环境下先后实现图像解码，图像缩放，模型推理的功能，
-最后从流中取出相应的输出数据完成图像保存并测试精度。
-
-表1.1 系统方案中各模块功能：
-
-| 序号 | 模块          | 功能描述                                                     |
-| ---- | ------------- | ------------------------------------------------------------ |
-| 1    | appsrc        | 向stream中发送数据，appsrc将数据发给下游元件                 |
-| 2    | imagedecoder  | 用于图像解码，当前只支持JPG/JPEG/BMP格式                     |
-| 3    | imageresize   | 对解码后的YUV格式的图像进行指定宽高的缩放，暂时只支持YUV格式的图像 |
-| 4    | tensorinfer   | 对输入的张量进行推理                                         |
-| 5    | dataserialize | 将stream结果组装成json字符串输出                             |
-| 6    | appsink       | 从stream中获取数据                                           |
-| 7    | evaluate      | 模型精度计算，输出图像降噪效果评估值PSNR                        |
-| 8    | transform     | 对测试图像进行格式转换,evaluate 运行前需要进行尺寸调整           |
-
-
-### 1.4 代码目录结构与说明
-
-本工程名称为ADNet，工程目录如下图所示：     
-
-```
-├── main.py  //运行工程项目的主函数
-├── evaluate.py   //精度计算
-├── transform.py   //图像转换
-├── t.pipeline      //pipeline
-├── model   //存放模型文件
-|   ├──aipp_adnet.cfg     //预处理配置文件
-├── result.jpg          //输出结果
-├── 流程.png          //流程图
-├── pipeline.png      //pipeline流程图
-└──README.md          
-```
-
-### 1.5 技术实现流程图
-
-ADNet图像去噪模型的后处理的输入是 pipeline 中 mxpi_tensorinfer0 推理结束后通过 appsink0 输出的 tensor 数据，尺寸为[1 * 1 * 321 * 481]，将张量数据通过 pred 取出推测的结果值，将像素点组成的图片保存成result.jpg，同时通过提供的 BSD68 数据集完成模型 PSNR 的精度计算。
-
-实现流程图如下图所示：
-
-![流程](./流程.png)
-
-
-pipeline流程如下图所示：
-
-![pipeline](./pipeline.png)
-
-
-### 1.6 特性及适应场景
-        
-本案例中的 ADNet 模型适用于灰度图像的去噪，并可以返回测试图像的PSNR精度值。
-
-本模型在以下几种情况去噪效果良好：含有目标数量多、含有目标数量少、前景目标面积占比图像较大、前景目标面积占比图像较小、各目标边界清晰。
-
-在以下两种情况去噪效果不太好：1. 图像中各目标之间的边界不清晰，可能会出现过度去噪、目标模糊的情况。 2. 图像中前景目标较多，可能会出现无法完成目标精确化降噪的情况。
-
-
-## 2  环境依赖
-推荐系统为ubuntu 18.04，环境依赖软件和版本如下表
-
-| 软件名称 | 版本   |
-| -------- | ------ |
-| MindX SDK | 5.0.RC3    |
-| CANN | 7.0.RC1 |
-| ubuntu | 18.04.1 LTS |
-| python   | 3.9.2  |
-| cv2   | 4.5.5  |
-| numpy   | 1.22.3 |
-| scikit-image| 0.16.2 |
-
-
-在编译运行项目前，需要设置环境变量
-- 环境变量介绍
-
-- MX_SDK_HOME 指向SDK安装包路径
-- LD_LIBRARY_PATH  用于指定查找共享库（动态链接库）时除了默认路径之外的其他路径。
-- PYTHONPATH   Python中一个重要的环境变量，用于在导入模块的时候搜索路径
-- GST_PLUGIN_SCANNER   用于查找plugin相关的依赖和库
-- GST_PLUGIN_PATH      用于查找plugin相关的依赖和库
-  
-具体执行命令
-
-```
-. ${MX_SDK_HOME}/set_env.sh
-	
-. ${ascend-toolkit-path}/set_env.sh
-```
-
-## 3  模型转换
-
-本项目使用的模型是ADNet模型。
-    
-选用的模型为 pytorch 模型，可从 Ascend modelzoo 获取模型压缩包，在运行项目之前需要将 pytorch 模型转为 onnx 模型，再由 onnx 模型转为 om 模型。
-
-pth 权重文件和 onnx 文件的[下载链接](https://www.hiascend.com/zh/software/modelzoo/detail/1/d360c03430f04185a4fe1aa74250bfea) [备份链接](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/ADNet/ATC%20ADNet.zip)
-
-    
-模型转换工具（ATC）相关介绍如下
-https://gitee.com/ascend/docs-openmind/blob/master/guide/mindx/sdk/tutorials/%E5%8F%82%E8%80%83%E8%B5%84%E6%96%99.md
-    
-具体步骤如下
-
-1. 下载上述模型压缩包，获取 ADNet_bs1.onnx 模型文件放置 ADNet/model 目录下。
-
-2. 进入ADNet/model文件夹下执行命令
-
-```
-atc --framework=5 --model=ADNet.onnx --insert_op_conf=./aipp_adnet.cfg --output=ADNet_bs1 --input_format=NCHW -input_shape="image:1,1,321,481" --log=debug --soc_version=Ascend310 --output_type=FP32
- ```
-
-3. 执行该命令会在当前目录下生成项目需要的模型文件ADNet_bs1.om。执行后终端输出为
-
- ```
-ATC start working now, please wait for a moment.
-ATC run success, welcome to the next use.
-```
-
-   表示命令执行成功。
-
-## 4  编译与运行
-
-当已有模型的om文件，保存在ADNet/model/下
-
-**步骤 1**  将任意一张jpg格式的图片存到当前目录下(./ADNet），命名为test.jpg。如果 pipeline 文件（或测试图片）不在当前目录下（./ADNet），需要修改 main.py 的pipeline（或测试图片）路径指向到所在目录。
-
-**步骤 2**   按照模型转换获取om模型，放置在 ADNet/model 路径下。若未从 pytorch 模型自行转换模型，使用的是上述链接提供的 onnx 模型或者 om 模型，则无需修改相关文件，否则修改 main.py 中pipeline的相关配置，将 mxpi_tensorinfer0 插件 modelPath 属性值中的 om 模型名改成实际使用的 om 模型名；将 mxpi_imageresize0 插件中的 resizeWidth 和 resizeHeight 属性改成转换模型过程中设置的模型输入尺寸值。
-
-**步骤 3**  在命令行输入 如下命令运行整个工程
-
-```
-python3 main.py
-```
-
-**步骤 4** 图片检测。运行结束输出result.jpg。
-
-
-## 5  测试精度
-
-**步骤 1** 安装数据集用以测试精度。数据集 BSD68 需要自行下载。
-[下载链接](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/ADNet/BSD68.zip)
-
-在./ADNet目录下新建 dataset 文件夹与 BSD68文件夹，并将数据集下载至BSD68文件夹解压。我们运行以下命令对数据集完成格式与尺寸转换，将处理好的数据集保存在dataset文件夹中，此时ADNet文件夹的目录结构为如下所示。
-
-```
-python3 transform.py
-```
-
-```
-├── main.py  //运行工程项目的主函数
-├── evaluate.py   //精度计算
-├── transform.py   //图像转换
-├── t.pipeline      //pipeline
-├── model   //存放模型文件
-|   ├──aipp_adnet.cfg     //预处理配置文件
-├── test.jpg          //测试图像
-├── result.jpg          //输出结果
-├── 流程.png          //流程图
-├── pipeline.png          //pipeline流程图
-├── BSD68          //原始数据集
-├── dataset          //完成转换后的待测试数据集
-└──README.md           
-```
-
-**步骤 2** 修改 evaluate.py 中的 pipeline 路径与数据集路径与目录结构保持一致。修改完毕后运行如下命令完成精度测试，输出模型平均 PSNR 值。
-
-```
-python3 evaluate.py
-```
-
-模型在BSD68数据集上的精度达标，最终模型平均PSNR输出值为30.054，满足精度要求（PSNR ≥ 29.27）。
-
-![PSNR](./PSNR.png)
+# ADNet图像去噪参考设计
+
+## 1  介绍
+使用 ADNet 模型，在 MindX SDK 环境下实现图像去噪功能。
+由用户设置测试图片，传入到 pipeline 中先后实现前处理，模型推理，后处理等功能，最终输出结果图片实现可视化及模型精度计算。
+
+```
+ADNet 是一种包含注意力模块的卷积神经网络，主要包括用于图像去噪的稀疏块（SB）、特征增强块（FEB）、注意力块（AB）和重建块（RB）。
+
+其中，SB 模块通过使用扩张卷积和公共卷积来去除噪声，在性能和效率之间进行权衡。FEB 模块通过长路径整合全局和局部特征信息，以增强去噪模型的表达能力。 
+
+AB 模块用于精细提取复杂背景中的噪声信息，对于复杂噪声图像，尤其是真实噪声图像非常有效。 此外，FEB 模块与 AB 模块集成以提高效率并降低训练去噪模型的复杂度。
+
+最后，RB 模块通过获得的噪声映射和给定的噪声图像来构造干净的图像。
+```
+
+### 1.1 支持的产品
+
+以昇腾 Atlas310 卡为主要的硬件平台
+
+### 1.2 支持的版本
+
+CANN：7.0.RC1
+
+SDK：mxVision 5.0.RC3（可通过cat SDK目录下的 version.info 查看）
+
+### 1.3 软件方案介绍
+
+项目主要由主函数，pipeline 文件，模型及其配置文件，测试数据集组成。
+主函数中构建业务流 stream 读取图片，通过 pipeline 在 SDK 环境下先后实现图像解码，图像缩放，模型推理的功能，
+最后从流中取出相应的输出数据完成图像保存并测试精度。
+
+表1.1 系统方案中各模块功能：
+
+| 序号 | 模块          | 功能描述                                                     |
+| ---- | ------------- | ------------------------------------------------------------ |
+| 1    | appsrc        | 向stream中发送数据，appsrc将数据发给下游元件                 |
+| 2    | imagedecoder  | 用于图像解码，当前只支持JPG/JPEG/BMP格式                     |
+| 3    | imageresize   | 对解码后的YUV格式的图像进行指定宽高的缩放，暂时只支持YUV格式的图像 |
+| 4    | tensorinfer   | 对输入的张量进行推理                                         |
+| 5    | dataserialize | 将stream结果组装成json字符串输出                             |
+| 6    | appsink       | 从stream中获取数据                                           |
+| 7    | evaluate      | 模型精度计算，输出图像降噪效果评估值PSNR                        |
+| 8    | transform     | 对测试图像进行格式转换,evaluate 运行前需要进行尺寸调整           |
+
+
+### 1.4 代码目录结构与说明
+
+本工程名称为ADNet，工程目录如下图所示：     
+
+```
+├── main.py  //运行工程项目的主函数
+├── evaluate.py   //精度计算
+├── transform.py   //图像转换
+├── t.pipeline      //pipeline
+├── model   //存放模型文件
+|   ├──aipp_adnet.cfg     //预处理配置文件
+├── result.jpg          //输出结果
+├── 流程.png          //流程图
+├── pipeline.png      //pipeline流程图
+└──README.md          
+```
+
+### 1.5 技术实现流程图
+
+ADNet图像去噪模型的后处理的输入是 pipeline 中 mxpi_tensorinfer0 推理结束后通过 appsink0 输出的 tensor 数据，尺寸为[1 * 1 * 321 * 481]，将张量数据通过 pred 取出推测的结果值，将像素点组成的图片保存成result.jpg，同时通过提供的 BSD68 数据集完成模型 PSNR 的精度计算。
+
+实现流程图如下图所示：
+
+![流程](./流程.png)
+
+
+pipeline流程如下图所示：
+
+![pipeline](./pipeline.png)
+
+
+### 1.6 特性及适应场景
+        
+本案例中的 ADNet 模型适用于灰度图像的去噪，并可以返回测试图像的PSNR精度值。
+
+本模型在以下几种情况去噪效果良好：含有目标数量多、含有目标数量少、前景目标面积占比图像较大、前景目标面积占比图像较小、各目标边界清晰。
+
+在以下两种情况去噪效果不太好：1. 图像中各目标之间的边界不清晰，可能会出现过度去噪、目标模糊的情况。 2. 图像中前景目标较多，可能会出现无法完成目标精确化降噪的情况。
+
+
+## 2  环境依赖
+推荐系统为ubuntu 18.04，环境依赖软件和版本如下表
+
+| 软件名称 | 版本   |
+| -------- | ------ |
+| MindX SDK | 5.0.RC3    |
+| CANN | 7.0.RC1 |
+| ubuntu | 18.04.1 LTS |
+| python   | 3.9.2  |
+| cv2   | 4.5.5  |
+| numpy   | 1.22.3 |
+| scikit-image| 0.16.2 |
+
+
+在编译运行项目前，需要设置环境变量
+- 环境变量介绍
+
+- MX_SDK_HOME 指向SDK安装包路径
+- LD_LIBRARY_PATH  用于指定查找共享库（动态链接库）时除了默认路径之外的其他路径。
+- PYTHONPATH   Python中一个重要的环境变量，用于在导入模块的时候搜索路径
+- GST_PLUGIN_SCANNER   用于查找plugin相关的依赖和库
+- GST_PLUGIN_PATH      用于查找plugin相关的依赖和库
+  
+具体执行命令
+
+```
+. ${MX_SDK_HOME}/set_env.sh
+	
+. ${ascend-toolkit-path}/set_env.sh
+```
+
+## 3  模型转换
+
+本项目使用的模型是ADNet模型。
+    
+选用的模型为 pytorch 模型，可从 Ascend modelzoo 获取模型压缩包，在运行项目之前需要将 pytorch 模型转为 onnx 模型，再由 onnx 模型转为 om 模型。
+
+pth 权重文件和 onnx 文件的[下载链接](https://www.hiascend.com/zh/software/modelzoo/detail/1/d360c03430f04185a4fe1aa74250bfea) [备份链接](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/ADNet/ATC%20ADNet.zip)
+
+    
+模型转换工具（ATC）相关介绍如下
+https://gitee.com/ascend/docs-openmind/blob/master/guide/mindx/sdk/tutorials/%E5%8F%82%E8%80%83%E8%B5%84%E6%96%99.md
+    
+具体步骤如下
+
+1. 下载上述模型压缩包，获取 ADNet_bs1.onnx 模型文件放置 ADNet/model 目录下。
+
+2. 进入ADNet/model文件夹下执行命令
+
+```
+atc --framework=5 --model=ADNet.onnx --insert_op_conf=./aipp_adnet.cfg --output=ADNet_bs1 --input_format=NCHW -input_shape="image:1,1,321,481" --log=debug --soc_version=Ascend310 --output_type=FP32
+ ```
+
+3. 执行该命令会在当前目录下生成项目需要的模型文件ADNet_bs1.om。执行后终端输出为
+
+ ```
+ATC start working now, please wait for a moment.
+ATC run success, welcome to the next use.
+```
+
+   表示命令执行成功。
+
+## 4  编译与运行
+
+当已有模型的om文件，保存在ADNet/model/下
+
+**步骤 1**  将任意一张jpg格式的图片存到当前目录下(./ADNet），命名为test.jpg。如果 pipeline 文件（或测试图片）不在当前目录下（./ADNet），需要修改 main.py 的pipeline（或测试图片）路径指向到所在目录。
+
+**步骤 2**   按照模型转换获取om模型，放置在 ADNet/model 路径下。若未从 pytorch 模型自行转换模型，使用的是上述链接提供的 onnx 模型或者 om 模型，则无需修改相关文件，否则修改 main.py 中pipeline的相关配置，将 mxpi_tensorinfer0 插件 modelPath 属性值中的 om 模型名改成实际使用的 om 模型名；将 mxpi_imageresize0 插件中的 resizeWidth 和 resizeHeight 属性改成转换模型过程中设置的模型输入尺寸值。
+
+**步骤 3**  在命令行输入 如下命令运行整个工程
+
+```
+python3 main.py
+```
+
+**步骤 4** 图片检测。运行结束输出result.jpg。
+
+
+## 5  测试精度
+
+**步骤 1** 安装数据集用以测试精度。数据集 BSD68 需要自行下载。
+[下载链接](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/ADNet/BSD68.zip)
+
+在./ADNet目录下新建 dataset 文件夹与 BSD68文件夹，并将数据集下载至BSD68文件夹解压。我们运行以下命令对数据集完成格式与尺寸转换，将处理好的数据集保存在dataset文件夹中，此时ADNet文件夹的目录结构为如下所示。
+
+```
+python3 transform.py
+```
+
+```
+├── main.py  //运行工程项目的主函数
+├── evaluate.py   //精度计算
+├── transform.py   //图像转换
+├── t.pipeline      //pipeline
+├── model   //存放模型文件
+|   ├──aipp_adnet.cfg     //预处理配置文件
+├── test.jpg          //测试图像
+├── result.jpg          //输出结果
+├── 流程.png          //流程图
+├── pipeline.png          //pipeline流程图
+├── BSD68          //原始数据集
+├── dataset          //完成转换后的待测试数据集
+└──README.md           
+```
+
+**步骤 2** 修改 evaluate.py 中的 pipeline 路径与数据集路径与目录结构保持一致。修改完毕后运行如下命令完成精度测试，输出模型平均 PSNR 值。
+
+```
+python3 evaluate.py
+```
+
+模型在BSD68数据集上的精度达标，最终模型平均PSNR输出值为30.054，满足精度要求（PSNR ≥ 29.27）。
+
+![PSNR](./PSNR.png)
diff --git a/contrib/ADNet/evaluate.py b/mxVision/mxVision-referenceapps/ADNet/evaluate.py
similarity index 97%
rename from contrib/ADNet/evaluate.py
rename to mxVision/mxVision-referenceapps/ADNet/evaluate.py
index 86bbf3aa94bb3ab156283fc31319e2ec37c538cf..61b26a43fae5813b4d2924353d5a47417ac4c8b1 100644
--- a/contrib/ADNet/evaluate.py
+++ b/mxVision/mxVision-referenceapps/ADNet/evaluate.py
@@ -1,112 +1,112 @@
-#!/usr/bin/env python
-# coding=utf-8
-
-# Copyright 2022 Huawei Technologies Co., Ltd
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-import json
-import os
-import math
-import cv2
-import numpy as np
-import MxpiDataType_pb2 as MxpiDataType
-from StreamManagerApi import StreamManagerApi, MxDataInput, StringVector
-
-SUM_PSNR = 0
-NUM = 0
-MAX_PIXEL = 255.0
-HEIGHT = 320
-WIDTH = 480
-DE_NORM = 255
-
-if __name__ == '__main__':
-    streamManagerApi = StreamManagerApi()
-    # 新建一个流管理StreamManager对象并初始化
-    ret = streamManagerApi.InitManager()
-    if ret != 0:
-        print("Failed to init Stream manager, ret=%s" % str(ret))
-        exit()
-
-    # 构建pipeline
-    PIPELINE_PATH = "./t.pipeline"
-    if os.path.exists(PIPELINE_PATH) != 1:
-        print("pipeline does not exist !")
-        exit()
-    with open(PIPELINE_PATH, 'rb') as f:
-        pipelineStr = f.read()
-        ret = streamManagerApi.CreateMultipleStreams(pipelineStr)
-        if ret != 0:
-            print("Failed to create Stream, ret=%s" % str(ret))
-            exit()
-
-    # 构建流的输入对象--检测目标
-    dataInput = MxDataInput()
-    FILEPATH = "./dataset/"
-    if os.path.exists(FILEPATH) != 1:
-        print("The filepath does not exist !")
-        exit()
-    for filename in os.listdir(FILEPATH):
-        image_path = FILEPATH + filename
-        if image_path.split('.')[-1] != 'jpg':
-            continue
-        with open(image_path, 'rb') as f:
-            dataInput.data = f.read()
-            begin_array = cv2.imread(image_path, cv2.IMREAD_GRAYSCALE)
-            STREAMNAME = b'detection'
-            INPLUGINID = 0
-    # 根据流名将检测目标传入流中
-        uniqueId = streamManagerApi.SendData(STREAMNAME, INPLUGINID, dataInput)
-        if uniqueId < 0:
-            print("Failed to send data to stream.")
-            exit()
-        keys = [b"mxpi_tensorinfer0"]
-        keyVec = StringVector()
-        for key in keys:
-            keyVec.push_back(key)
-    # 从流中取出对应插件的输出数据
-        infer = streamManagerApi.GetResult(STREAMNAME, b'appsink0', keyVec)
-        if(infer.metadataVec.size() == 0):
-            print("Get no data from stream !")
-            exit()
-        infer_result = infer.metadataVec[0]
-        if infer_result.errorCode != 0:
-            print("GetResult error. errorCode=%d , errMsg=%s" % (infer_result.errorCode, infer_result.errMsg))
-            exit()
-        result = MxpiDataType.MxpiTensorPackageList()
-        result.ParseFromString(infer_result.serializedMetadata)
-        pred = np.frombuffer(result.tensorPackageVec[0].tensorVec[0].dataStr, dtype=np.float32)
-        pred.resize(HEIGHT + 1, WIDTH + 1)
-        preds = np.zeros((HEIGHT, WIDTH))
-        for i in range(HEIGHT):
-            for j in range(WIDTH):
-                if(pred[i+1][j+1] < 0):
-                    preds[i][j] = 0
-                elif(pred[i+1][j+1] > 1):
-                    preds[i][j] = DE_NORM
-                else:
-                    preds[i][j] = pred[i+1][j+1] * DE_NORM
-        end_array = np.array(preds, dtype=int)
-        SUM = 0
-        for i in range(HEIGHT):
-            for j in range(WIDTH):
-                SUM += (begin_array[i][j] - end_array[i][j]) ** 2
-        mse = SUM / (HEIGHT * WIDTH)
-        psnr = 10 * math.log10(MAX_PIXEL**2/mse) 
-        SUM_PSNR += psnr
-        NUM += 1
-        print(filename.split('.')[0] + " PSNR RESULT: " , psnr)
-        print("-------------------------------------------------")
-    print("Model Average PSNR: " , SUM_PSNR / NUM)
-    # destroy streams
+#!/usr/bin/env python
+# coding=utf-8
+
+# Copyright 2022 Huawei Technologies Co., Ltd
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import json
+import os
+import math
+import cv2
+import numpy as np
+import MxpiDataType_pb2 as MxpiDataType
+from StreamManagerApi import StreamManagerApi, MxDataInput, StringVector
+
+SUM_PSNR = 0
+NUM = 0
+MAX_PIXEL = 255.0
+HEIGHT = 320
+WIDTH = 480
+DE_NORM = 255
+
+if __name__ == '__main__':
+    streamManagerApi = StreamManagerApi()
+    # 新建一个流管理StreamManager对象并初始化
+    ret = streamManagerApi.InitManager()
+    if ret != 0:
+        print("Failed to init Stream manager, ret=%s" % str(ret))
+        exit()
+
+    # 构建pipeline
+    PIPELINE_PATH = "./t.pipeline"
+    if os.path.exists(PIPELINE_PATH) != 1:
+        print("pipeline does not exist !")
+        exit()
+    with open(PIPELINE_PATH, 'rb') as f:
+        pipelineStr = f.read()
+        ret = streamManagerApi.CreateMultipleStreams(pipelineStr)
+        if ret != 0:
+            print("Failed to create Stream, ret=%s" % str(ret))
+            exit()
+
+    # 构建流的输入对象--检测目标
+    dataInput = MxDataInput()
+    FILEPATH = "./dataset/"
+    if os.path.exists(FILEPATH) != 1:
+        print("The filepath does not exist !")
+        exit()
+    for filename in os.listdir(FILEPATH):
+        image_path = FILEPATH + filename
+        if image_path.split('.')[-1] != 'jpg':
+            continue
+        with open(image_path, 'rb') as f:
+            dataInput.data = f.read()
+            begin_array = cv2.imread(image_path, cv2.IMREAD_GRAYSCALE)
+            STREAMNAME = b'detection'
+            INPLUGINID = 0
+    # 根据流名将检测目标传入流中
+        uniqueId = streamManagerApi.SendData(STREAMNAME, INPLUGINID, dataInput)
+        if uniqueId < 0:
+            print("Failed to send data to stream.")
+            exit()
+        keys = [b"mxpi_tensorinfer0"]
+        keyVec = StringVector()
+        for key in keys:
+            keyVec.push_back(key)
+    # 从流中取出对应插件的输出数据
+        infer = streamManagerApi.GetResult(STREAMNAME, b'appsink0', keyVec)
+        if(infer.metadataVec.size() == 0):
+            print("Get no data from stream !")
+            exit()
+        infer_result = infer.metadataVec[0]
+        if infer_result.errorCode != 0:
+            print("GetResult error. errorCode=%d , errMsg=%s" % (infer_result.errorCode, infer_result.errMsg))
+            exit()
+        result = MxpiDataType.MxpiTensorPackageList()
+        result.ParseFromString(infer_result.serializedMetadata)
+        pred = np.frombuffer(result.tensorPackageVec[0].tensorVec[0].dataStr, dtype=np.float32)
+        pred.resize(HEIGHT + 1, WIDTH + 1)
+        preds = np.zeros((HEIGHT, WIDTH))
+        for i in range(HEIGHT):
+            for j in range(WIDTH):
+                if(pred[i+1][j+1] < 0):
+                    preds[i][j] = 0
+                elif(pred[i+1][j+1] > 1):
+                    preds[i][j] = DE_NORM
+                else:
+                    preds[i][j] = pred[i+1][j+1] * DE_NORM
+        end_array = np.array(preds, dtype=int)
+        SUM = 0
+        for i in range(HEIGHT):
+            for j in range(WIDTH):
+                SUM += (begin_array[i][j] - end_array[i][j]) ** 2
+        mse = SUM / (HEIGHT * WIDTH)
+        psnr = 10 * math.log10(MAX_PIXEL**2/mse) 
+        SUM_PSNR += psnr
+        NUM += 1
+        print(filename.split('.')[0] + " PSNR RESULT: " , psnr)
+        print("-------------------------------------------------")
+    print("Model Average PSNR: " , SUM_PSNR / NUM)
+    # destroy streams
     streamManagerApi.DestroyAllStreams()
\ No newline at end of file
diff --git a/contrib/ADNet/main.py b/mxVision/mxVision-referenceapps/ADNet/main.py
similarity index 97%
rename from contrib/ADNet/main.py
rename to mxVision/mxVision-referenceapps/ADNet/main.py
index 05200f122170c48de1721ba8d24a521e81c827ff..abdee6fc97121699b3213f6dd41347c209f843cf 100644
--- a/contrib/ADNet/main.py
+++ b/mxVision/mxVision-referenceapps/ADNet/main.py
@@ -1,95 +1,95 @@
-#!/usr/bin/env python
-# coding=utf-8
-
-# Copyright 2022 Huawei Technologies Co., Ltd
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-import json
-import os
-import cv2
-import numpy as np
-import MxpiDataType_pb2 as MxpiDataType
-from StreamManagerApi import StreamManagerApi, MxDataInput, StringVector
-
-HEIGHT = 320
-WIDTH = 480
-DE_NORM = 255
-
-if __name__ == '__main__':
-    streamManagerApi = StreamManagerApi()
-    # 新建一个流管理StreamManager对象并初始化
-    ret = streamManagerApi.InitManager()
-    if ret != 0:
-        print("Failed to init Stream manager, ret=%s" % str(ret))
-        exit()
-
-    # 构建pipeline
-    PIPELINE_PATH = "./t.pipeline"
-    if os.path.exists(PIPELINE_PATH) != 1:
-        print("Pipeline does not exist !")
-        exit()
-    with open(PIPELINE_PATH, 'rb') as f:
-        pipelineStr = f.read()
-        ret = streamManagerApi.CreateMultipleStreams(pipelineStr)
-        if ret != 0:
-            print("Failed to create Stream, ret=%s" % str(ret))
-            exit()
-
-    # 构建流的输入对象--检测目标
-    dataInput = MxDataInput()
-    IMAGE_PATH = './test.jpg'
-    with open(IMAGE_PATH, 'rb') as f:
-        dataInput.data = f.read()
-        begin_array = cv2.imread(IMAGE_PATH, cv2.IMREAD_GRAYSCALE)
-        h, w = begin_array.shape[:2]
-        STREAMNAME = b'detection'
-        INPLUGINID = 0
-    # 根据流名将检测目标传入流中
-    uniqueId = streamManagerApi.SendData(STREAMNAME, INPLUGINID, dataInput)
-    if uniqueId < 0:
-        print("Failed to send data to stream.")
-        exit()
-    keys = [b"mxpi_tensorinfer0"]
-    keyVec = StringVector()
-    for key in keys:
-        keyVec.push_back(key)
-    # 从流中取出对应插件的输出数据
-    infer = streamManagerApi.GetResult(STREAMNAME, b'appsink0', keyVec)
-    if(infer.metadataVec.size() == 0):
-        print("Get no data from stream !")
-        exit()
-    print("result.metadata size: ", infer.metadataVec.size())
-    infer_result = infer.metadataVec[0]
-    if infer_result.errorCode != 0:
-        print("GetResult error. errorCode=%d , errMsg=%s" % (infer_result.errorCode, infer_result.errMsg))
-        exit()
-    result = MxpiDataType.MxpiTensorPackageList()
-    result.ParseFromString(infer_result.serializedMetadata)
-    pred = np.frombuffer(result.tensorPackageVec[0].tensorVec[0].dataStr, dtype=np.float32)
-    pred.resize(HEIGHT+1, WIDTH+1)
-    preds = np.zeros((HEIGHT, WIDTH))
-    for i in range(HEIGHT):
-        for j in range(WIDTH):
-            if(pred[i+1][j+1] < 0):
-                preds[i][j] = 0
-            elif(pred[i+1][j+1] > 1):
-                preds[i][j] = DE_NORM
-            else:
-                preds[i][j] = pred[i+1][j+1] * DE_NORM
-    end_array = np.array(preds, dtype=int)
-    SAVE_PATH = './result.jpg'
-    img_resize = cv2.resize(end_array, (w, h), interpolation = cv2.INTER_NEAREST)
-    cv2.imwrite(SAVE_PATH, img_resize)
-    # destroy streams
+#!/usr/bin/env python
+# coding=utf-8
+
+# Copyright 2022 Huawei Technologies Co., Ltd
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import json
+import os
+import cv2
+import numpy as np
+import MxpiDataType_pb2 as MxpiDataType
+from StreamManagerApi import StreamManagerApi, MxDataInput, StringVector
+
+HEIGHT = 320
+WIDTH = 480
+DE_NORM = 255
+
+if __name__ == '__main__':
+    streamManagerApi = StreamManagerApi()
+    # 新建一个流管理StreamManager对象并初始化
+    ret = streamManagerApi.InitManager()
+    if ret != 0:
+        print("Failed to init Stream manager, ret=%s" % str(ret))
+        exit()
+
+    # 构建pipeline
+    PIPELINE_PATH = "./t.pipeline"
+    if os.path.exists(PIPELINE_PATH) != 1:
+        print("Pipeline does not exist !")
+        exit()
+    with open(PIPELINE_PATH, 'rb') as f:
+        pipelineStr = f.read()
+        ret = streamManagerApi.CreateMultipleStreams(pipelineStr)
+        if ret != 0:
+            print("Failed to create Stream, ret=%s" % str(ret))
+            exit()
+
+    # 构建流的输入对象--检测目标
+    dataInput = MxDataInput()
+    IMAGE_PATH = './test.jpg'
+    with open(IMAGE_PATH, 'rb') as f:
+        dataInput.data = f.read()
+        begin_array = cv2.imread(IMAGE_PATH, cv2.IMREAD_GRAYSCALE)
+        h, w = begin_array.shape[:2]
+        STREAMNAME = b'detection'
+        INPLUGINID = 0
+    # 根据流名将检测目标传入流中
+    uniqueId = streamManagerApi.SendData(STREAMNAME, INPLUGINID, dataInput)
+    if uniqueId < 0:
+        print("Failed to send data to stream.")
+        exit()
+    keys = [b"mxpi_tensorinfer0"]
+    keyVec = StringVector()
+    for key in keys:
+        keyVec.push_back(key)
+    # 从流中取出对应插件的输出数据
+    infer = streamManagerApi.GetResult(STREAMNAME, b'appsink0', keyVec)
+    if(infer.metadataVec.size() == 0):
+        print("Get no data from stream !")
+        exit()
+    print("result.metadata size: ", infer.metadataVec.size())
+    infer_result = infer.metadataVec[0]
+    if infer_result.errorCode != 0:
+        print("GetResult error. errorCode=%d , errMsg=%s" % (infer_result.errorCode, infer_result.errMsg))
+        exit()
+    result = MxpiDataType.MxpiTensorPackageList()
+    result.ParseFromString(infer_result.serializedMetadata)
+    pred = np.frombuffer(result.tensorPackageVec[0].tensorVec[0].dataStr, dtype=np.float32)
+    pred.resize(HEIGHT+1, WIDTH+1)
+    preds = np.zeros((HEIGHT, WIDTH))
+    for i in range(HEIGHT):
+        for j in range(WIDTH):
+            if(pred[i+1][j+1] < 0):
+                preds[i][j] = 0
+            elif(pred[i+1][j+1] > 1):
+                preds[i][j] = DE_NORM
+            else:
+                preds[i][j] = pred[i+1][j+1] * DE_NORM
+    end_array = np.array(preds, dtype=int)
+    SAVE_PATH = './result.jpg'
+    img_resize = cv2.resize(end_array, (w, h), interpolation = cv2.INTER_NEAREST)
+    cv2.imwrite(SAVE_PATH, img_resize)
+    # destroy streams
     streamManagerApi.DestroyAllStreams()
\ No newline at end of file
diff --git a/contrib/ADNet/model/aipp_adnet.cfg b/mxVision/mxVision-referenceapps/ADNet/model/aipp_adnet.cfg
similarity index 95%
rename from contrib/ADNet/model/aipp_adnet.cfg
rename to mxVision/mxVision-referenceapps/ADNet/model/aipp_adnet.cfg
index d48fd8f4d91f670004f4841a91e7a660bf668ca7..5d9d1a48682b944517994b1be217825f6b042441 100644
--- a/contrib/ADNet/model/aipp_adnet.cfg
+++ b/mxVision/mxVision-referenceapps/ADNet/model/aipp_adnet.cfg
@@ -1,35 +1,35 @@
-aipp_op {
-    aipp_mode: static
-    input_format : YUV420SP_U8
-    src_image_size_w:480
-    src_image_size_h:320
-    crop:false
-    padding:true
-    left_padding_size:1
-    right_padding_size:0
-    top_padding_size:1
-    bottom_padding_size:0
-    csc_switch : true
-    rbuv_swap_switch : false
-    matrix_r0c0 : 256
-    matrix_r0c1 : 0
-    matrix_r0c2 : 0
-    matrix_r1c0 : 0
-    matrix_r1c1 : 0
-    matrix_r1c2 : 0
-    matrix_r2c0 : 0
-    matrix_r2c1 : 0
-    matrix_r2c2 : 0
-    input_bias_0 : 0
-    input_bias_1 : 0
-    input_bias_2 : 0
-    mean_chn_0 : 0
-    mean_chn_1 : 0
-    mean_chn_2 : 0
-    min_chn_0 : 0.0
-    min_chn_1 : 0.0
-    min_chn_2 : 0.0
-    var_reci_chn_0 : 0.00392
-    var_reci_chn_1 : 0.00392
-    var_reci_chn_2 : 0.00392
+aipp_op {
+    aipp_mode: static
+    input_format : YUV420SP_U8
+    src_image_size_w:480
+    src_image_size_h:320
+    crop:false
+    padding:true
+    left_padding_size:1
+    right_padding_size:0
+    top_padding_size:1
+    bottom_padding_size:0
+    csc_switch : true
+    rbuv_swap_switch : false
+    matrix_r0c0 : 256
+    matrix_r0c1 : 0
+    matrix_r0c2 : 0
+    matrix_r1c0 : 0
+    matrix_r1c1 : 0
+    matrix_r1c2 : 0
+    matrix_r2c0 : 0
+    matrix_r2c1 : 0
+    matrix_r2c2 : 0
+    input_bias_0 : 0
+    input_bias_1 : 0
+    input_bias_2 : 0
+    mean_chn_0 : 0
+    mean_chn_1 : 0
+    mean_chn_2 : 0
+    min_chn_0 : 0.0
+    min_chn_1 : 0.0
+    min_chn_2 : 0.0
+    var_reci_chn_0 : 0.00392
+    var_reci_chn_1 : 0.00392
+    var_reci_chn_2 : 0.00392
 }
\ No newline at end of file
diff --git a/contrib/ADNet/pipeline.png b/mxVision/mxVision-referenceapps/ADNet/pipeline.png
similarity index 100%
rename from contrib/ADNet/pipeline.png
rename to mxVision/mxVision-referenceapps/ADNet/pipeline.png
diff --git a/contrib/ADNet/t.pipeline b/mxVision/mxVision-referenceapps/ADNet/t.pipeline
similarity index 96%
rename from contrib/ADNet/t.pipeline
rename to mxVision/mxVision-referenceapps/ADNet/t.pipeline
index d2076be68e0c86fc5e83d2cda69394e3343a7f85..c9d81801f851d801eb96c64ea4ce8ac53e12ecdb 100644
--- a/contrib/ADNet/t.pipeline
+++ b/mxVision/mxVision-referenceapps/ADNet/t.pipeline
@@ -1,51 +1,51 @@
-{
-  "detection": {
-      "stream_config": {
-          "deviceId": "0"
-      },
-      "appsrc0": {
-          "props": {
-              "blocksize": "409600"
-          },
-          "factory": "appsrc",
-          "next": "mxpi_imagedecoder0"
-      },
-      "mxpi_imagedecoder0": {
-          "props": {
-              "deviceId": "0"
-          },
-          "factory": "mxpi_imagedecoder",
-          "next": "mxpi_imageresize0"
-      },
-      "mxpi_imageresize0": {
-          "props": {
-              "dataSource": "mxpi_imagedecoder0",
-              "resizeHeight": "320",
-              "resizeWidth": "480"
-          },
-          "factory": "mxpi_imageresize",
-          "next": "mxpi_tensorinfer0"
-      },
-      "mxpi_tensorinfer0": {
-          "props": {
-              "dataSource": "mxpi_imageresize0",
-              "modelPath": "./model/ADNet_bs1.om"
-          },
-          "factory": "mxpi_tensorinfer",
-          "next": "mxpi_dataserialize0"
-      },
-      "mxpi_dataserialize0": {
-          "props": {
-              "outputDataKeys": "mxpi_tensorinfer0"
-          },
-          "factory": "mxpi_dataserialize",
-          "next": "appsink0"
-      },
-      "appsink0": {
-          "props": {
-              "blocksize": "4096000"
-          },
-          "factory": "appsink"
-      }
-  }
+{
+  "detection": {
+      "stream_config": {
+          "deviceId": "0"
+      },
+      "appsrc0": {
+          "props": {
+              "blocksize": "409600"
+          },
+          "factory": "appsrc",
+          "next": "mxpi_imagedecoder0"
+      },
+      "mxpi_imagedecoder0": {
+          "props": {
+              "deviceId": "0"
+          },
+          "factory": "mxpi_imagedecoder",
+          "next": "mxpi_imageresize0"
+      },
+      "mxpi_imageresize0": {
+          "props": {
+              "dataSource": "mxpi_imagedecoder0",
+              "resizeHeight": "320",
+              "resizeWidth": "480"
+          },
+          "factory": "mxpi_imageresize",
+          "next": "mxpi_tensorinfer0"
+      },
+      "mxpi_tensorinfer0": {
+          "props": {
+              "dataSource": "mxpi_imageresize0",
+              "modelPath": "./model/ADNet_bs1.om"
+          },
+          "factory": "mxpi_tensorinfer",
+          "next": "mxpi_dataserialize0"
+      },
+      "mxpi_dataserialize0": {
+          "props": {
+              "outputDataKeys": "mxpi_tensorinfer0"
+          },
+          "factory": "mxpi_dataserialize",
+          "next": "appsink0"
+      },
+      "appsink0": {
+          "props": {
+              "blocksize": "4096000"
+          },
+          "factory": "appsink"
+      }
+  }
 }
\ No newline at end of file
diff --git a/contrib/ADNet/transform.py b/mxVision/mxVision-referenceapps/ADNet/transform.py
similarity index 97%
rename from contrib/ADNet/transform.py
rename to mxVision/mxVision-referenceapps/ADNet/transform.py
index 2f32a19fad95669faa6bc1d4bf0432163a49e454..9b503a0f5bfb56da6c7313adcc04a9e7d171c031 100644
--- a/contrib/ADNet/transform.py
+++ b/mxVision/mxVision-referenceapps/ADNet/transform.py
@@ -1,25 +1,25 @@
-# Copyright 2022 Huawei Technologies Co., Ltd
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-import os
-import cv2
-
-FILE_PATH = './BSD68/'
-for file in os.listdir(FILE_PATH):
-    img_path = FILE_PATH + file
-    img = cv2.imread(img_path)
-    # evaluate运行前需要执行下面的resize；main运行前注释掉下面一行代码
-    img = cv2.resize(img, (480, 320))
-    save_path = './dataset/' + file.split('.')[0] + '.jpg'
+# Copyright 2022 Huawei Technologies Co., Ltd
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import os
+import cv2
+
+FILE_PATH = './BSD68/'
+for file in os.listdir(FILE_PATH):
+    img_path = FILE_PATH + file
+    img = cv2.imread(img_path)
+    # evaluate运行前需要执行下面的resize；main运行前注释掉下面一行代码
+    img = cv2.resize(img, (480, 320))
+    save_path = './dataset/' + file.split('.')[0] + '.jpg'
     cv2.imwrite(save_path, img)
\ No newline at end of file
diff --git "a/contrib/ADNet/\346\265\201\347\250\213.png" "b/mxVision/mxVision-referenceapps/ADNet/\346\265\201\347\250\213.png"
similarity index 100%
rename from "contrib/ADNet/\346\265\201\347\250\213.png"
rename to "mxVision/mxVision-referenceapps/ADNet/\346\265\201\347\250\213.png"
diff --git a/contrib/ActionRecognition/README.md b/mxVision/mxVision-referenceapps/ActionRecognition/README.md
similarity index 97%
rename from contrib/ActionRecognition/README.md
rename to mxVision/mxVision-referenceapps/ActionRecognition/README.md
index a3eb616799b5843626e64f2f7b9fa87c2684a3c5..c27eba5a485f7faa905169947279e1088b82fc52 100644
--- a/contrib/ActionRecognition/README.md
+++ b/mxVision/mxVision-referenceapps/ActionRecognition/README.md
@@ -1,477 +1,477 @@
-# ActionRecgnition
-
-## 1 介绍
-
-本开发样例演示动作识别系统 ActionRecgnition，供用户参考。
-本系统基于mxVision SDK进行开发，以昇腾Atlas300卡为主要的硬件平台，主要应用于单人独处、逗留超时、快速移动、剧烈运动、离床检测、攀高检测六种应用场景。
-
-1. 单人独处：识别出单个人独处场景后报警。
-2. 逗留超时：识别出单人或多人在区域内长时间逗留的情况并发出警报。
-3. 快速移动：检测出视频中单人或多人行进速度大于阈值的情况，并发出警报。
-4. 剧烈运动：检测到视频流中有剧烈运动并进行报警。
-5. 离床检测：检测出视频中行人离开指定区域的情况并报警。
-6. 攀高检测：检测出行人中心点向上移动的情况，并发出警报。
-
-## 2 环境依赖
-
-* 支持的硬件形态和操作系统版本
-
-  | 硬件形态                              | 操作系统版本   |
-  | ------------------------------------- | -------------- |
-  | x86_64+Atlas 300I 推理卡（型号3010）  | Ubuntu 18.04.1 |
-  | x86_64+Atlas 300I 推理卡 （型号3010） | CentOS 7.6     |
-  | ARM+Atlas 300I 推理卡 （型号3000）    | Ubuntu 18.04.1 |
-  | ARM+Atlas 300I 推理卡 （型号3000）    | CentOS 7.6     |
-
-* 软件依赖
-
-  | 软件名称 | 版本  |
-  | -------- | ----- |
-  | cmake    | 3.5.+ |
-  | mxVision | 2.0.4 |
-  | Python   | 3.9.2 |
-  | OpenCV   | 3.4.0 |
-  | gcc      | 7.5.0 |
-  | ffmpeg   | 4.3.2 |
-
-## ３ 代码主要目录介绍
-
-本Sample工程名称为Actionrecognition，工程目录如下图所示：
-
-```
-.
-├── data
-│   ├── roi
-│   │   ├── Climbup
-│   │   └── ...
-│   └── video
-│   │   ├── Alone
-│   │   └── ...
-├── models
-│   ├── ECONet
-│   │   └── ...
-│   └── yolov3
-│   │   └── ...
-├── pipeline
-│   ├── plugin_all.pipeline
-│   ├── plugin_alone.pipeline
-│   ├── plugin_climb.pipeline
-│   ├── plugin_outofbed.pipeline
-│   ├── plugin_overspeed.pipeline
-│   ├── plugin_overstay.pipeline
-│   └── plugin_violentaction.pipeline
-├── plugins
-│   ├── MxpiStackFrame // 堆帧插件
-│   │   ├── CMakeLists.txt
-│   │   ├── MxpiStackFrame.cpp
-│   │   ├── MxpiStackFrame.h
-│   │   ├── BlockingMap.cpp
-│   │   ├── BlockingMap.h
-│   │   └── build.sh
-│   ├── PluginAlone // 单人独处插件
-│   │   ├── CMakeLists.txt
-│   │   ├── PluginAlone.cpp
-│   │   ├── PluginAlone.h
-│   │   └── build.sh
-│   ├── PluginClimb // 攀高检测插件
-│   │   ├── CMakeLists.txt
-│   │   ├── PluginClimb.cpp
-│   │   ├── PluginClimb.h
-│   │   └── build.sh
-│   ├── PluginOutOfBed // 离床检测插件
-│   │   ├── CMakeLists.txt
-│   │   ├── PluginOutOfBed.cpp
-│   │   ├── PluginOutOfBed.h
-│   │   └── build.sh
-│   ├── PluginOverSpeed // 快速移动插件
-│   │   ├── CMakeLists.txt
-│   │   ├── PluginOverSpeed.cpp
-│   │   ├── PluginOverSpeed.h
-│   │   └── build.sh
-│   ├── PluginOverStay // 逗留超时插件
-│   │   ├── CMakeLists.txt
-│   │   ├── PluginOverStay.cpp
-│   │   ├── PluginOverStay.h
-│   │   └── build.sh
-│   ├── PluginCounter // 计时插件
-│   │   ├── CMakeLists.txt
-│   │   ├── PluginCounter.cpp
-│   │   ├── PluginCounter.h
-│   │   └── build.sh
-│   ├── PluginViolentAction // 剧烈运动插件
-│   │   ├── CMakeLists.txt
-│   │   ├── Plugin_ViolentAction.cpp
-│   │   ├── Plugin_ViolentAction.h
-│   │   └── build.sh
-├── main.py
-├── README.md
-└── run.sh
-```
-
-## 4 软件方案介绍
-
-为了完成上述六种应用场景中的行为识别，系统需要检测出同一目标短时间内状态的变化以及是否存在剧烈运动，因此系统中需要包含目标检测、目标跟踪、动作识别与逻辑后处理。其中目标检测模块选取Yolov3，得到行人候选框；目标跟踪模块使用IOU匹配，关联连续帧中的同一目标。将同一目标在连续帧的区域抠图组成视频序列，输入动作识别模块ECONet，模型输出动作类别，判断是否为剧烈运动。逻辑后处理通过判断同一目标在连续帧内的空间位置变化判断难以被定义为运动的其余五种应用场景。系统方案中各模块功能如表1.1 所示。
-
-表1.1 系统方案中个模块功能：
-
-| 序号 | 子系统         | 功能描述                                                     |
-| ---- | -------------- | ------------------------------------------------------------ |
-| 1    | 初始化配置     | 主要用于初始化资源，如线程数量、共享内存等。                 |
-| 2    | 视频流         | 从多路IPC相机拉流，并传输入Device进行计算。                  |
-| 3    | 视频解码       | 通过硬件（DVPP）对视频进行解码，转换为YUV数据进行后续处理。  |
-| 4    | 图像预处理     | 在进行基于深度神经网络的图像处理之前，需要将图像缩放到固定的尺寸和格式。 |
-| 5    | 目标检测       | 基于深度学习的目标检测算法是该系统的核心模块之一，本方案选用基于Yolov3的目标检测。 |
-| 6    | 目标跟踪       | 基于卡尔曼滤波与匈牙利算法的目标跟踪算法是该系统的核心模块之一，本方案选用IOU匹配。 |
-| 7    | 图像抠图       | 将同一目标在连续帧所在区域抠图，并组成图像序列，输入动作识别模块。 |
-| 8    | 动作识别       | 基于深度学习的动作识别算法是该系统的核心模块之一，本方案选用基于ECONet的动作识别模型。 |
-| 9    | 单人独处后处理 | 当连续m帧只出现一个目标ID时，则判断为单人独处并报警，如果单人独处报警之前n帧内已经报警过，则不重复报警。 |
-| 10   | 快速移动后处理 | 当同一目标在连续m帧中心点平均位移高于阈值v，则判断为快速移动，如果快速移动报警之前n帧内已经报警过，则不重复报警。 |
-| 11   | 逗留超时后处理 | 当同一目标在连续m帧中心点平均位移低于阈值v，则判断为快速移动，如果快速移动报警之前n帧内已经报警过，则不重复报警。 |
-| 12   | 离床检测后处理 | 当同一目标在连续m帧内从给定区域roi内离开，则判断为离床，如果离床报警之前n帧内已经报警过，则不重复报警。 |
-| 13   | 攀高检测后处理 | 当同一目标在连续m帧内从给定区域roi内中心点上升，并且中心点位移大于阈值h，则判断为离床，如果离床报警之前n帧内已经报警过，则不重复报警。 |
-| 14   | 剧烈运动后处理 | 动作识别模块输出类别为关注的动作类别时，则判断为剧烈运动，如果剧烈运动之前n帧内已经报警过，则不重复报警。 |
-
-## 5 准备
-
-**步骤1：** 参考安装教程《mxVision 用户指南》安装 mxVision SDK。
-
-**步骤2：** 配置 mxVision SDK 环境变量。
-
-`export MX_SDK_HOME=${安装路径}/mxVision `
-
-注：本例中mxVision SDK安装路径为 /root/work/MindX_SDK/mxVision。
-
-**步骤3：** 推荐在${MX_SDK_HOME}/samples下创建ActionRecognition根目录，在项目根目录下创建目录models `mkdir models`，分别为yolov3和ECONet创建一个文件夹，将两个离线模型及各自的配置文件放入文件夹下。[下载地址](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/ActionRecognition/models.zip)。创建完成后models文件夹下的目录结构如下：
-
-```
-.models
-├── ECONet
-│   ├── eco_aipp.cfg // 模型转换aipp配置文件
-│   ├── eco_post.cfg // 模型后处理配置文件
-│   ├── ECONet.om // 离线模型
-│   ├── ucf101.names // label文件
-│   ├── ucf101_best.pb // 冻结pb模型
-│   └── trans_pb2om.sh // 模型转换脚本
-├── yolov3
-│   ├── coco.names // label文件
-│   ├── yolov3_tf_bs1_fp16.om // 离线模型
-│   └── yolov3_tf_bs1_fp16.cfg // 模型后处理配置文件
-```
-
-**步骤4：** 编译程序前提需要先交叉编译好第三方依赖库。
-
-**步骤5：** 配置环境变量MX_SDK_HOME：
-
-```bash
-export MX_SDK_HOME=/MindX_SDK/mxVision/								
-# 此处MX_SDK_HOME请使用MindX_SDK的实际路径
-```
-
-**步骤6**：在插件代码目录下创建build文件夹，使用cmake命令进行编译，生成.so文件。下面以单人独处插件的编译过程作为范例：
-
-```bash
-## 进入目录 /plugins/plugin_Alone
-## 创建build目录
-mkdir build
-## 使用cmake命令进行编译
-cmake ..
-make -j
-```
-
-或者使用插件代码目录下的build.sh脚本，例：
-
-```bash
-## 前提条件是正确设置export MX_SDK_HOME
-chmod +x build.sh
-./build.sh
-```
-
-编译好的插件会自动存放到SDK的插件库中，可以直接在pipiline中使用。
-
-**步骤7:** 配置pipeline
-
-1.  插件参数介绍
-
-   * MxpiStackFrame
-
-     | 参数名称     | 参数解释             |
-     | :----------- | -------------------- |
-     | visionSource | 抠图插件名称         |
-     | trackSource  | 跟踪插件名称         |
-     | frameNum     | 跳帧间隔（为1不跳）  |
-     | timeOut      | 某个目标堆帧超时时间 |
-     | sleepTime    | 检查线程休眠时间     |
-   
-   * PluginAlone
-   
-     | 参数名称            | 参数解释               |
-     | :------------------ | ---------------------- |
-     | dataSourceDetection | 目标检测后处理插件名称 |
-     | dataSourceTrack     | 跟踪插件名称           |
-     | detectThresh        | 检测帧数               |
-     | detectRatio         | 警报帧阈值             |
-     | detectSleep         | 警报间隔               |
-   
-   * PluginClimb
-   
-     | 参数名称            | 参数解释               |
-     | :------------------ | ---------------------- |
-     | dataSourceTrack     | 跟踪插件名称           |
-     | dataSourceDetection | 目标检测后处理插件名称 |
-     | detectRatio         | 警报帧阈值             |
-     | filePath            | ROI配置txt文件         |
-     | detectSleep         | 警报间隔               |
-     | bufferLength        | 检测帧数窗口大小       |
-     | highThresh          | 高度阈值               |
-   
-   * PluginCounter
-   
-     | 参数名称           | 参数解释     |
-     | :----------------- | ------------ |
-     | dataSourceTrack    | 跟踪插件名称 |
-     | descriptionMessage | 插件描述信息 |
-   
-   * PluginOutOfBed
-   
-     | 参数名称            | 参数解释               |
-     | :------------------ | ---------------------- |
-     | dataSourceTrack     | 跟踪插件名称           |
-     | dataSourceDetection | 目标检测后处理插件名称 |
-     | configPath          | ROI配置txt文件         |
-     | detectThresh        | 检测帧数窗口大小       |
-     | detectSleep         | 警报间隔               |
-     | detectRatio         | 警报帧阈值             |
-   
-   * PluginOverSpeed
-   
-     | 参数名称            | 参数解释               |
-     | :------------------ | ---------------------- |
-     | dataSourceTrack     | 跟踪插件名称           |
-     | dataSourceDetection | 目标检测后处理插件名称 |
-     | speedThresh         | 速度阈值               |
-     | frames              | 检测帧数窗口大小       |
-     | detectSleep         | 警报间隔               |
-   
-   * PluginOverStay
-   
-     | 参数名称            | 参数解释               |
-     | :------------------ | ---------------------- |
-     | dataSourceTrack     | 跟踪插件名称           |
-     | dataSourceDetection | 目标检测后处理插件名称 |
-     | stayThresh          | 逗留时间阈值           |
-     | frames              | 检测间隔帧数           |
-     | distanceThresh      | 逗留范围               |
-     | detectRatio         | 警报帧阈值             |
-     | detectSleep         | 警报间隔               |
-   
-   * PluginViolentAction
-   
-     | 参数名称        | 参数解释              |
-     | :-------------- | --------------------- |
-     | classSource     | 分类后处理插件名称    |
-     | filePath        | 感兴趣动作类别txt文件 |
-     | detectSleep     | 警报间隔              |
-     | actionThreshold | 动作阈值              |
-   
-2. 配置范例
-
-   ```
-   ## PluginClimb
-   "mxpi_pluginclimb0": {
-               "props": {
-                   "dataSourceTrack": "mxpi_motsimplesort0",
-                   "dataSourceDetection": "mxpi_objectpostprocessor0",
-                   "detectRatio":  "0.6",
-                   "filePath": "./data/roi/Climbup/*.txt",
-                   "detectSleep": "30",
-                   "bufferLength": "8",
-                   "highThresh": "10"
-               },
-               "factory": "mxpi_pluginclimb",
-               "next": "mxpi_dataserialize0"
-           }
-   ## /*Yolov3*/
-   "mxpi_tensorinfer0":{
-               "props": {
-                   "dataSource": "mxpi_imageresize0",
-                   "modelPath": "./models/yolov3/yolov3_tf_bs1_fp16.om"
-                   },
-               "factory": "mxpi_tensorinfer",
-                "next": "mxpi_objectpostprocessor0"
-           }，
-   "mxpi_objectpostprocessor0": {
-               "props": {
-                   "dataSource": "mxpi_tensorinfer0",
-                   "funcLanguage":"c++",
-                   "postProcessConfigPath": "./models/yolov3/yolov3_tf_bs1_fp16.cfg",
-                   "labelPath": "./models/yolov3/coco.names",
-                   "postProcessLibPath": "../../lib/modelpostprocessors/libyolov3postprocess.so"
-               },
-               "factory": "mxpi_objectpostprocessor",
-               "next": "mxpi_distributor0"
-           },
-   ## ECONet
-   "mxpi_tensorinfer1":{
-               "props": {
-                   "dataSource": "mxpi_stackframe0",
-                   "skipModelCheck": "1",
-                   "modelPath": "./models/ECONet/ECONet.om"
-                   },
-               "factory": "mxpi_tensorinfer",
-               "next": "mxpi_classpostprocessor0"
-           },
-   "mxpi_classpostprocessor0":{
-               "props": {
-                   "dataSource": "mxpi_tensorinfer1",
-                   "postProcessConfigPath": "./models/ECONet/eco_post.cfg",
-                   "labelPath":"./models/ECONet/ucf101.names",
-                 "postProcessLibPath":"../../lib/modelpostprocessors/libresnet50postprocess.so"
-                   },
-               "factory": "mxpi_classpostprocessor",
-               "next": "mxpi_violentaction0"
-          },
-   ```
-
-   根据所需场景，配置pipeline文件，调整路径参数以及插件阈值参数。例如"filePath"字段替换为roi/Climb目录下的感兴趣区域txt文件，“postProcessLibPath”字段是SDK模型后处理插件库路径。
-
-3. 将pipeline中“rtspUrl”字段值替换为可用的 rtsp 流源地址（需要自行准备可用的视频流，视频流格式为H264），[自主搭建rtsp视频流教程](###7.3-数据下载与RTSP)。
-
-**步骤8：** 在main.py中，修改pipeline路径、对应的流名称以及需要获取结果的插件名称。
-
-```python
-## 插件位置
-with open("./pipeline/plugin_outofbed.pipeline", 'rb') as f:
-        pipelineStr = f.read()
-## pipeline中的流名称
-streamName = b'classification+detection'
-## 想要获取结果的插件名称
-key = b'mxpi_pluginalone0'
-```
-
-## 6 运行
-
-修改 run.sh 文件中的环境路径和项目路径。
-
-```bash
-export MX_SDK_HOME=${CUR_PATH}/../../..
-## 注意当前目录CUR_PATH与MX_SDK_HOME环境目录的相对位置
-```
-
-直接运行
-
-```bash
-chmod +x run.sh
-bash run.sh
-```
-
-## 7 常见问题
-### 7.1 未配置ROI
-
-#### 问题描述：
-
-攀高检测与离床检测出现如下报错：
-```bash
-terminate called after throwing an instance of 'cv::Exception'
-  what():  OpenCV(4.2.0) /usr1/workspace/MindX_SDK_Multi_DailyBuild/opensource/opensource-scl7/opencv/modules/imgproc/src/geometry.cpp:103: error: (-215:Assertion failed) total >= 0 && (depth == CV_32S || depth == CV_32F) in function 'pointPolygonTest'
-```
-#### 解决方案：
-在pipeline处没有配置roi区域的txt文件，进行配置即可。
-
-示例：
-
-```json
-"mxpi_pluginoutofbed0": {
-            "props": {
-                "dataSourceTrack": "mxpi_motsimplesort0",
-                "dataSourceDetect": "mxpi_objectpostprocessor0",
-                "configPath":  "./data/roi/OutofBed/*.txt",
-                "detectThresh": "8",
-                "detectSleep": "15",
-	              "detectRatio": "0.25"
-            },
-            "factory": "mxpi_pluginoutofbed",
-            "next": "mxpi_dataserialize0"
-}
-```
-
-### 7.2 模型路径配置
-
-#### 问题描述：
-
-检测过程中用到的模型以及模型后处理插件需配置路径属性。
-
-#### 后处理插件配置范例：
-
-```json
-"mxpi_objectpostprocessor0": {
-	"props": {
-    	"dataSource": "mxpi_tensorinfer0",
-        "funcLanguage":"c++",
-        "postProcessConfigPath": "./models/yolov3/yolov3_tf_bs1_fp16.cfg",
-        "labelPath": "./models/yolov3/coco.names",
-        "postProcessLibPath": "../../../lib/modelpostprocessors/libyolov3postprocess.so"
-    },
-    "factory": "mxpi_objectpostprocessor",
-    "next": "mxpi_motsimplesort0"
-}
-```
-
-### 7.3 数据下载与RTSP
-
-H264视频文件及ROI文件：[下载地址](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/ActionRecognition/data.zip) ；
-
-RTSP取流地址（可以从网络摄像机获取，也可通过Live555等工具将本地视频文 件转换为rtsp流）。自主搭建RTSP拉流教程：[live555链接](https://gitee.com/ascend/docs-openmind/blob/master/guide/mindx/sdk/tutorials/reference_material/Live555%E7%A6%BB%E7%BA%BF%E8%A7%86%E9%A2%91%E8%BD%ACRTSP%E8%AF%B4%E6%98%8E%E6%96%87%E6%A1%A3.md)，需要注意的是在搭建RTSP时，使用./genMakefiles <os-platform>命令生成编译文件时，输入的<os-platform>参数是根据cofig.<后缀>获取的，与服务器架构等有关。
-
-RTSP视频拉流插件配置范例：
-
-```json
-"mxpi_rtspsrc0": {
-	"props": {
-    	"rtspUrl": "rtsp_Url"
-    },
-    "factory": "mxpi_rtspsrc",
-    "next": "mxpi_videodecoder0"
-}
-```
-
-其中rtsp_Url的格式是 rtsp:://host:port/Data，host:port/路径映射到mediaServer/目录下，Data为视频文件的路径。
-
-RTSP拉流教程：[live555链接](https://gitee.com/ascend/docs-openmind/blob/master/guide/mindx/sdk/tutorials/reference_material/Live555%E7%A6%BB%E7%BA%BF%E8%A7%86%E9%A2%91%E8%BD%ACRTSP%E8%AF%B4%E6%98%8E%E6%96%87%E6%A1%A3.md)中第七步视频循环推流，按照提示修改cpp文件可以使自主搭建的rtsp循环推流，如果不作更改，则为有限的视频流；同时第六步高分辨率帧花屏，修改mediaServer/DynamicRTSPServer.cpp文件，将OutPacketBuffer::maxSize增大，例如"500000"，避免出现”The input frame data was too large for our buffer“问题，导致丢帧。修改完后，需要重新运行以下命令：
-
-```cmake
-./genMakefiles <os-platform>
-make
-```
-
-### 7.4 运行Shell脚本
-
-在linux平台下运行shell脚本时，例如build.sh/run.sh，出现如下错误：
-
-```bash
-build.sh: Line 15: $'\r': command not found
-```
-
-是由于不同系统平台之间的行结束符不同，使用如下命令去除shell脚本的特殊字符：
-
-```bash
-sed -i 's/\r//g' xxx.sh
-```
-
-## 8 模型转换
-
-本项目中用到的模型有：ECONet，yolov3 [备份链接](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/ActionRecognition/models.zip)
-
-yolov3模型下载参考华为昇腾社区[ModelZoo](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/ActionRecognition/ATC%20YOLOv3%28FP16%29%20from%20TensorFlow%20-%20Ascend310.zip)  
-使用以下命令进行转换，请注意aipp配置文件名，此处使用的为自带sample中的相关文件（{Mind_SDK安装路径}/mxVision/samples/mxVision/models/yolov3/）
-```bash
-atc --model=./yolov3_tf.pb --framework=3 --output=./yolov3_tf_bs1_fp16 --soc_version=Ascend310 --insert_op_conf=./aipp_yolov3_416_416.aippconfig --input_shape="input:1,416,416,3" --out_nodes="yolov3/yolov3_head/Conv_6/BiasAdd:0;yolov3/yolov3_head/Conv_14/BiasAdd:0;yolov3/yolov3_head/Conv_22/BiasAdd:0"
-```
-
-ECONet离线模型转换参考 [昇腾Gitee](https://www.hiascend.com/zh/software/modelzoo/models/detail/1/0d7d0413cf89404d882d69e695a9bc4b/1)：下载冻结pb模型ucf101_best.pb，编辑trans_pb2om.sh文件，将--model 配置为ECONet模型所在目录，--output配置为模型输出路径，--insert_op_conf配置为aipp文件路径，在命令行输入
-
-```bash
-chmod +x trans_pb2om.sh
-./trans_pb2om.sh
-```
-
-完成ECONet模型转换。模型下载或转换完成后，按照目录结构放置模型。
+# ActionRecgnition
+
+## 1 介绍
+
+本开发样例演示动作识别系统 ActionRecgnition，供用户参考。
+本系统基于mxVision SDK进行开发，以昇腾Atlas300卡为主要的硬件平台，主要应用于单人独处、逗留超时、快速移动、剧烈运动、离床检测、攀高检测六种应用场景。
+
+1. 单人独处：识别出单个人独处场景后报警。
+2. 逗留超时：识别出单人或多人在区域内长时间逗留的情况并发出警报。
+3. 快速移动：检测出视频中单人或多人行进速度大于阈值的情况，并发出警报。
+4. 剧烈运动：检测到视频流中有剧烈运动并进行报警。
+5. 离床检测：检测出视频中行人离开指定区域的情况并报警。
+6. 攀高检测：检测出行人中心点向上移动的情况，并发出警报。
+
+## 2 环境依赖
+
+* 支持的硬件形态和操作系统版本
+
+  | 硬件形态                              | 操作系统版本   |
+  | ------------------------------------- | -------------- |
+  | x86_64+Atlas 300I 推理卡（型号3010）  | Ubuntu 18.04.1 |
+  | x86_64+Atlas 300I 推理卡 （型号3010） | CentOS 7.6     |
+  | ARM+Atlas 300I 推理卡 （型号3000）    | Ubuntu 18.04.1 |
+  | ARM+Atlas 300I 推理卡 （型号3000）    | CentOS 7.6     |
+
+* 软件依赖
+
+  | 软件名称 | 版本  |
+  | -------- | ----- |
+  | cmake    | 3.5.+ |
+  | mxVision | 2.0.4 |
+  | Python   | 3.9.2 |
+  | OpenCV   | 3.4.0 |
+  | gcc      | 7.5.0 |
+  | ffmpeg   | 4.3.2 |
+
+## ３ 代码主要目录介绍
+
+本Sample工程名称为Actionrecognition，工程目录如下图所示：
+
+```
+.
+├── data
+│   ├── roi
+│   │   ├── Climbup
+│   │   └── ...
+│   └── video
+│   │   ├── Alone
+│   │   └── ...
+├── models
+│   ├── ECONet
+│   │   └── ...
+│   └── yolov3
+│   │   └── ...
+├── pipeline
+│   ├── plugin_all.pipeline
+│   ├── plugin_alone.pipeline
+│   ├── plugin_climb.pipeline
+│   ├── plugin_outofbed.pipeline
+│   ├── plugin_overspeed.pipeline
+│   ├── plugin_overstay.pipeline
+│   └── plugin_violentaction.pipeline
+├── plugins
+│   ├── MxpiStackFrame // 堆帧插件
+│   │   ├── CMakeLists.txt
+│   │   ├── MxpiStackFrame.cpp
+│   │   ├── MxpiStackFrame.h
+│   │   ├── BlockingMap.cpp
+│   │   ├── BlockingMap.h
+│   │   └── build.sh
+│   ├── PluginAlone // 单人独处插件
+│   │   ├── CMakeLists.txt
+│   │   ├── PluginAlone.cpp
+│   │   ├── PluginAlone.h
+│   │   └── build.sh
+│   ├── PluginClimb // 攀高检测插件
+│   │   ├── CMakeLists.txt
+│   │   ├── PluginClimb.cpp
+│   │   ├── PluginClimb.h
+│   │   └── build.sh
+│   ├── PluginOutOfBed // 离床检测插件
+│   │   ├── CMakeLists.txt
+│   │   ├── PluginOutOfBed.cpp
+│   │   ├── PluginOutOfBed.h
+│   │   └── build.sh
+│   ├── PluginOverSpeed // 快速移动插件
+│   │   ├── CMakeLists.txt
+│   │   ├── PluginOverSpeed.cpp
+│   │   ├── PluginOverSpeed.h
+│   │   └── build.sh
+│   ├── PluginOverStay // 逗留超时插件
+│   │   ├── CMakeLists.txt
+│   │   ├── PluginOverStay.cpp
+│   │   ├── PluginOverStay.h
+│   │   └── build.sh
+│   ├── PluginCounter // 计时插件
+│   │   ├── CMakeLists.txt
+│   │   ├── PluginCounter.cpp
+│   │   ├── PluginCounter.h
+│   │   └── build.sh
+│   ├── PluginViolentAction // 剧烈运动插件
+│   │   ├── CMakeLists.txt
+│   │   ├── Plugin_ViolentAction.cpp
+│   │   ├── Plugin_ViolentAction.h
+│   │   └── build.sh
+├── main.py
+├── README.md
+└── run.sh
+```
+
+## 4 软件方案介绍
+
+为了完成上述六种应用场景中的行为识别，系统需要检测出同一目标短时间内状态的变化以及是否存在剧烈运动，因此系统中需要包含目标检测、目标跟踪、动作识别与逻辑后处理。其中目标检测模块选取Yolov3，得到行人候选框；目标跟踪模块使用IOU匹配，关联连续帧中的同一目标。将同一目标在连续帧的区域抠图组成视频序列，输入动作识别模块ECONet，模型输出动作类别，判断是否为剧烈运动。逻辑后处理通过判断同一目标在连续帧内的空间位置变化判断难以被定义为运动的其余五种应用场景。系统方案中各模块功能如表1.1 所示。
+
+表1.1 系统方案中个模块功能：
+
+| 序号 | 子系统         | 功能描述                                                     |
+| ---- | -------------- | ------------------------------------------------------------ |
+| 1    | 初始化配置     | 主要用于初始化资源，如线程数量、共享内存等。                 |
+| 2    | 视频流         | 从多路IPC相机拉流，并传输入Device进行计算。                  |
+| 3    | 视频解码       | 通过硬件（DVPP）对视频进行解码，转换为YUV数据进行后续处理。  |
+| 4    | 图像预处理     | 在进行基于深度神经网络的图像处理之前，需要将图像缩放到固定的尺寸和格式。 |
+| 5    | 目标检测       | 基于深度学习的目标检测算法是该系统的核心模块之一，本方案选用基于Yolov3的目标检测。 |
+| 6    | 目标跟踪       | 基于卡尔曼滤波与匈牙利算法的目标跟踪算法是该系统的核心模块之一，本方案选用IOU匹配。 |
+| 7    | 图像抠图       | 将同一目标在连续帧所在区域抠图，并组成图像序列，输入动作识别模块。 |
+| 8    | 动作识别       | 基于深度学习的动作识别算法是该系统的核心模块之一，本方案选用基于ECONet的动作识别模型。 |
+| 9    | 单人独处后处理 | 当连续m帧只出现一个目标ID时，则判断为单人独处并报警，如果单人独处报警之前n帧内已经报警过，则不重复报警。 |
+| 10   | 快速移动后处理 | 当同一目标在连续m帧中心点平均位移高于阈值v，则判断为快速移动，如果快速移动报警之前n帧内已经报警过，则不重复报警。 |
+| 11   | 逗留超时后处理 | 当同一目标在连续m帧中心点平均位移低于阈值v，则判断为快速移动，如果快速移动报警之前n帧内已经报警过，则不重复报警。 |
+| 12   | 离床检测后处理 | 当同一目标在连续m帧内从给定区域roi内离开，则判断为离床，如果离床报警之前n帧内已经报警过，则不重复报警。 |
+| 13   | 攀高检测后处理 | 当同一目标在连续m帧内从给定区域roi内中心点上升，并且中心点位移大于阈值h，则判断为离床，如果离床报警之前n帧内已经报警过，则不重复报警。 |
+| 14   | 剧烈运动后处理 | 动作识别模块输出类别为关注的动作类别时，则判断为剧烈运动，如果剧烈运动之前n帧内已经报警过，则不重复报警。 |
+
+## 5 准备
+
+**步骤1：** 参考安装教程《mxVision 用户指南》安装 mxVision SDK。
+
+**步骤2：** 配置 mxVision SDK 环境变量。
+
+`export MX_SDK_HOME=${安装路径}/mxVision `
+
+注：本例中mxVision SDK安装路径为 /root/work/MindX_SDK/mxVision。
+
+**步骤3：** 推荐在${MX_SDK_HOME}/samples下创建ActionRecognition根目录，在项目根目录下创建目录models `mkdir models`，分别为yolov3和ECONet创建一个文件夹，将两个离线模型及各自的配置文件放入文件夹下。[下载地址](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/ActionRecognition/models.zip)。创建完成后models文件夹下的目录结构如下：
+
+```
+.models
+├── ECONet
+│   ├── eco_aipp.cfg // 模型转换aipp配置文件
+│   ├── eco_post.cfg // 模型后处理配置文件
+│   ├── ECONet.om // 离线模型
+│   ├── ucf101.names // label文件
+│   ├── ucf101_best.pb // 冻结pb模型
+│   └── trans_pb2om.sh // 模型转换脚本
+├── yolov3
+│   ├── coco.names // label文件
+│   ├── yolov3_tf_bs1_fp16.om // 离线模型
+│   └── yolov3_tf_bs1_fp16.cfg // 模型后处理配置文件
+```
+
+**步骤4：** 编译程序前提需要先交叉编译好第三方依赖库。
+
+**步骤5：** 配置环境变量MX_SDK_HOME：
+
+```bash
+export MX_SDK_HOME=/MindX_SDK/mxVision/								
+# 此处MX_SDK_HOME请使用MindX_SDK的实际路径
+```
+
+**步骤6**：在插件代码目录下创建build文件夹，使用cmake命令进行编译，生成.so文件。下面以单人独处插件的编译过程作为范例：
+
+```bash
+## 进入目录 /plugins/plugin_Alone
+## 创建build目录
+mkdir build
+## 使用cmake命令进行编译
+cmake ..
+make -j
+```
+
+或者使用插件代码目录下的build.sh脚本，例：
+
+```bash
+## 前提条件是正确设置export MX_SDK_HOME
+chmod +x build.sh
+./build.sh
+```
+
+编译好的插件会自动存放到SDK的插件库中，可以直接在pipiline中使用。
+
+**步骤7:** 配置pipeline
+
+1.  插件参数介绍
+
+   * MxpiStackFrame
+
+     | 参数名称     | 参数解释             |
+     | :----------- | -------------------- |
+     | visionSource | 抠图插件名称         |
+     | trackSource  | 跟踪插件名称         |
+     | frameNum     | 跳帧间隔（为1不跳）  |
+     | timeOut      | 某个目标堆帧超时时间 |
+     | sleepTime    | 检查线程休眠时间     |
+   
+   * PluginAlone
+   
+     | 参数名称            | 参数解释               |
+     | :------------------ | ---------------------- |
+     | dataSourceDetection | 目标检测后处理插件名称 |
+     | dataSourceTrack     | 跟踪插件名称           |
+     | detectThresh        | 检测帧数               |
+     | detectRatio         | 警报帧阈值             |
+     | detectSleep         | 警报间隔               |
+   
+   * PluginClimb
+   
+     | 参数名称            | 参数解释               |
+     | :------------------ | ---------------------- |
+     | dataSourceTrack     | 跟踪插件名称           |
+     | dataSourceDetection | 目标检测后处理插件名称 |
+     | detectRatio         | 警报帧阈值             |
+     | filePath            | ROI配置txt文件         |
+     | detectSleep         | 警报间隔               |
+     | bufferLength        | 检测帧数窗口大小       |
+     | highThresh          | 高度阈值               |
+   
+   * PluginCounter
+   
+     | 参数名称           | 参数解释     |
+     | :----------------- | ------------ |
+     | dataSourceTrack    | 跟踪插件名称 |
+     | descriptionMessage | 插件描述信息 |
+   
+   * PluginOutOfBed
+   
+     | 参数名称            | 参数解释               |
+     | :------------------ | ---------------------- |
+     | dataSourceTrack     | 跟踪插件名称           |
+     | dataSourceDetection | 目标检测后处理插件名称 |
+     | configPath          | ROI配置txt文件         |
+     | detectThresh        | 检测帧数窗口大小       |
+     | detectSleep         | 警报间隔               |
+     | detectRatio         | 警报帧阈值             |
+   
+   * PluginOverSpeed
+   
+     | 参数名称            | 参数解释               |
+     | :------------------ | ---------------------- |
+     | dataSourceTrack     | 跟踪插件名称           |
+     | dataSourceDetection | 目标检测后处理插件名称 |
+     | speedThresh         | 速度阈值               |
+     | frames              | 检测帧数窗口大小       |
+     | detectSleep         | 警报间隔               |
+   
+   * PluginOverStay
+   
+     | 参数名称            | 参数解释               |
+     | :------------------ | ---------------------- |
+     | dataSourceTrack     | 跟踪插件名称           |
+     | dataSourceDetection | 目标检测后处理插件名称 |
+     | stayThresh          | 逗留时间阈值           |
+     | frames              | 检测间隔帧数           |
+     | distanceThresh      | 逗留范围               |
+     | detectRatio         | 警报帧阈值             |
+     | detectSleep         | 警报间隔               |
+   
+   * PluginViolentAction
+   
+     | 参数名称        | 参数解释              |
+     | :-------------- | --------------------- |
+     | classSource     | 分类后处理插件名称    |
+     | filePath        | 感兴趣动作类别txt文件 |
+     | detectSleep     | 警报间隔              |
+     | actionThreshold | 动作阈值              |
+   
+2. 配置范例
+
+   ```
+   ## PluginClimb
+   "mxpi_pluginclimb0": {
+               "props": {
+                   "dataSourceTrack": "mxpi_motsimplesort0",
+                   "dataSourceDetection": "mxpi_objectpostprocessor0",
+                   "detectRatio":  "0.6",
+                   "filePath": "./data/roi/Climbup/*.txt",
+                   "detectSleep": "30",
+                   "bufferLength": "8",
+                   "highThresh": "10"
+               },
+               "factory": "mxpi_pluginclimb",
+               "next": "mxpi_dataserialize0"
+           }
+   ## /*Yolov3*/
+   "mxpi_tensorinfer0":{
+               "props": {
+                   "dataSource": "mxpi_imageresize0",
+                   "modelPath": "./models/yolov3/yolov3_tf_bs1_fp16.om"
+                   },
+               "factory": "mxpi_tensorinfer",
+                "next": "mxpi_objectpostprocessor0"
+           }，
+   "mxpi_objectpostprocessor0": {
+               "props": {
+                   "dataSource": "mxpi_tensorinfer0",
+                   "funcLanguage":"c++",
+                   "postProcessConfigPath": "./models/yolov3/yolov3_tf_bs1_fp16.cfg",
+                   "labelPath": "./models/yolov3/coco.names",
+                   "postProcessLibPath": "../../lib/modelpostprocessors/libyolov3postprocess.so"
+               },
+               "factory": "mxpi_objectpostprocessor",
+               "next": "mxpi_distributor0"
+           },
+   ## ECONet
+   "mxpi_tensorinfer1":{
+               "props": {
+                   "dataSource": "mxpi_stackframe0",
+                   "skipModelCheck": "1",
+                   "modelPath": "./models/ECONet/ECONet.om"
+                   },
+               "factory": "mxpi_tensorinfer",
+               "next": "mxpi_classpostprocessor0"
+           },
+   "mxpi_classpostprocessor0":{
+               "props": {
+                   "dataSource": "mxpi_tensorinfer1",
+                   "postProcessConfigPath": "./models/ECONet/eco_post.cfg",
+                   "labelPath":"./models/ECONet/ucf101.names",
+                 "postProcessLibPath":"../../lib/modelpostprocessors/libresnet50postprocess.so"
+                   },
+               "factory": "mxpi_classpostprocessor",
+               "next": "mxpi_violentaction0"
+          },
+   ```
+
+   根据所需场景，配置pipeline文件，调整路径参数以及插件阈值参数。例如"filePath"字段替换为roi/Climb目录下的感兴趣区域txt文件，“postProcessLibPath”字段是SDK模型后处理插件库路径。
+
+3. 将pipeline中“rtspUrl”字段值替换为可用的 rtsp 流源地址（需要自行准备可用的视频流，视频流格式为H264），[自主搭建rtsp视频流教程](###7.3-数据下载与RTSP)。
+
+**步骤8：** 在main.py中，修改pipeline路径、对应的流名称以及需要获取结果的插件名称。
+
+```python
+## 插件位置
+with open("./pipeline/plugin_outofbed.pipeline", 'rb') as f:
+        pipelineStr = f.read()
+## pipeline中的流名称
+streamName = b'classification+detection'
+## 想要获取结果的插件名称
+key = b'mxpi_pluginalone0'
+```
+
+## 6 运行
+
+修改 run.sh 文件中的环境路径和项目路径。
+
+```bash
+export MX_SDK_HOME=${CUR_PATH}/../../..
+## 注意当前目录CUR_PATH与MX_SDK_HOME环境目录的相对位置
+```
+
+直接运行
+
+```bash
+chmod +x run.sh
+bash run.sh
+```
+
+## 7 常见问题
+### 7.1 未配置ROI
+
+#### 问题描述：
+
+攀高检测与离床检测出现如下报错：
+```bash
+terminate called after throwing an instance of 'cv::Exception'
+  what():  OpenCV(4.2.0) /usr1/workspace/MindX_SDK_Multi_DailyBuild/opensource/opensource-scl7/opencv/modules/imgproc/src/geometry.cpp:103: error: (-215:Assertion failed) total >= 0 && (depth == CV_32S || depth == CV_32F) in function 'pointPolygonTest'
+```
+#### 解决方案：
+在pipeline处没有配置roi区域的txt文件，进行配置即可。
+
+示例：
+
+```json
+"mxpi_pluginoutofbed0": {
+            "props": {
+                "dataSourceTrack": "mxpi_motsimplesort0",
+                "dataSourceDetect": "mxpi_objectpostprocessor0",
+                "configPath":  "./data/roi/OutofBed/*.txt",
+                "detectThresh": "8",
+                "detectSleep": "15",
+	              "detectRatio": "0.25"
+            },
+            "factory": "mxpi_pluginoutofbed",
+            "next": "mxpi_dataserialize0"
+}
+```
+
+### 7.2 模型路径配置
+
+#### 问题描述：
+
+检测过程中用到的模型以及模型后处理插件需配置路径属性。
+
+#### 后处理插件配置范例：
+
+```json
+"mxpi_objectpostprocessor0": {
+	"props": {
+    	"dataSource": "mxpi_tensorinfer0",
+        "funcLanguage":"c++",
+        "postProcessConfigPath": "./models/yolov3/yolov3_tf_bs1_fp16.cfg",
+        "labelPath": "./models/yolov3/coco.names",
+        "postProcessLibPath": "../../../lib/modelpostprocessors/libyolov3postprocess.so"
+    },
+    "factory": "mxpi_objectpostprocessor",
+    "next": "mxpi_motsimplesort0"
+}
+```
+
+### 7.3 数据下载与RTSP
+
+H264视频文件及ROI文件：[下载地址](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/ActionRecognition/data.zip) ；
+
+RTSP取流地址（可以从网络摄像机获取，也可通过Live555等工具将本地视频文 件转换为rtsp流）。自主搭建RTSP拉流教程：[live555链接](https://gitee.com/ascend/docs-openmind/blob/master/guide/mindx/sdk/tutorials/reference_material/Live555%E7%A6%BB%E7%BA%BF%E8%A7%86%E9%A2%91%E8%BD%ACRTSP%E8%AF%B4%E6%98%8E%E6%96%87%E6%A1%A3.md)，需要注意的是在搭建RTSP时，使用./genMakefiles <os-platform>命令生成编译文件时，输入的<os-platform>参数是根据cofig.<后缀>获取的，与服务器架构等有关。
+
+RTSP视频拉流插件配置范例：
+
+```json
+"mxpi_rtspsrc0": {
+	"props": {
+    	"rtspUrl": "rtsp_Url"
+    },
+    "factory": "mxpi_rtspsrc",
+    "next": "mxpi_videodecoder0"
+}
+```
+
+其中rtsp_Url的格式是 rtsp:://host:port/Data，host:port/路径映射到mediaServer/目录下，Data为视频文件的路径。
+
+RTSP拉流教程：[live555链接](https://gitee.com/ascend/docs-openmind/blob/master/guide/mindx/sdk/tutorials/reference_material/Live555%E7%A6%BB%E7%BA%BF%E8%A7%86%E9%A2%91%E8%BD%ACRTSP%E8%AF%B4%E6%98%8E%E6%96%87%E6%A1%A3.md)中第七步视频循环推流，按照提示修改cpp文件可以使自主搭建的rtsp循环推流，如果不作更改，则为有限的视频流；同时第六步高分辨率帧花屏，修改mediaServer/DynamicRTSPServer.cpp文件，将OutPacketBuffer::maxSize增大，例如"500000"，避免出现”The input frame data was too large for our buffer“问题，导致丢帧。修改完后，需要重新运行以下命令：
+
+```cmake
+./genMakefiles <os-platform>
+make
+```
+
+### 7.4 运行Shell脚本
+
+在linux平台下运行shell脚本时，例如build.sh/run.sh，出现如下错误：
+
+```bash
+build.sh: Line 15: $'\r': command not found
+```
+
+是由于不同系统平台之间的行结束符不同，使用如下命令去除shell脚本的特殊字符：
+
+```bash
+sed -i 's/\r//g' xxx.sh
+```
+
+## 8 模型转换
+
+本项目中用到的模型有：ECONet，yolov3 [备份链接](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/ActionRecognition/models.zip)
+
+yolov3模型下载参考华为昇腾社区[ModelZoo](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/ActionRecognition/ATC%20YOLOv3%28FP16%29%20from%20TensorFlow%20-%20Ascend310.zip)  
+使用以下命令进行转换，请注意aipp配置文件名，此处使用的为自带sample中的相关文件（{Mind_SDK安装路径}/mxVision/samples/mxVision/models/yolov3/）
+```bash
+atc --model=./yolov3_tf.pb --framework=3 --output=./yolov3_tf_bs1_fp16 --soc_version=Ascend310 --insert_op_conf=./aipp_yolov3_416_416.aippconfig --input_shape="input:1,416,416,3" --out_nodes="yolov3/yolov3_head/Conv_6/BiasAdd:0;yolov3/yolov3_head/Conv_14/BiasAdd:0;yolov3/yolov3_head/Conv_22/BiasAdd:0"
+```
+
+ECONet离线模型转换参考 [昇腾Gitee](https://www.hiascend.com/zh/software/modelzoo/models/detail/1/0d7d0413cf89404d882d69e695a9bc4b/1)：下载冻结pb模型ucf101_best.pb，编辑trans_pb2om.sh文件，将--model 配置为ECONet模型所在目录，--output配置为模型输出路径，--insert_op_conf配置为aipp文件路径，在命令行输入
+
+```bash
+chmod +x trans_pb2om.sh
+./trans_pb2om.sh
+```
+
+完成ECONet模型转换。模型下载或转换完成后，按照目录结构放置模型。
diff --git a/contrib/ActionRecognition/build.sh b/mxVision/mxVision-referenceapps/ActionRecognition/build.sh
similarity index 100%
rename from contrib/ActionRecognition/build.sh
rename to mxVision/mxVision-referenceapps/ActionRecognition/build.sh
diff --git a/contrib/.gitkeep b/mxVision/mxVision-referenceapps/ActionRecognition/data/roi/Climbup/.gitkeep
similarity index 100%
rename from contrib/.gitkeep
rename to mxVision/mxVision-referenceapps/ActionRecognition/data/roi/Climbup/.gitkeep
diff --git a/contrib/ActionRecognition/data/roi/Climbup/.gitkeep b/mxVision/mxVision-referenceapps/ActionRecognition/data/roi/OutOfBed/.gitkeep
similarity index 100%
rename from contrib/ActionRecognition/data/roi/Climbup/.gitkeep
rename to mxVision/mxVision-referenceapps/ActionRecognition/data/roi/OutOfBed/.gitkeep
diff --git a/contrib/ActionRecognition/data/roi/OutOfBed/.gitkeep b/mxVision/mxVision-referenceapps/ActionRecognition/data/roi/ViolentAction/.gitkeep
similarity index 100%
rename from contrib/ActionRecognition/data/roi/OutOfBed/.gitkeep
rename to mxVision/mxVision-referenceapps/ActionRecognition/data/roi/ViolentAction/.gitkeep
diff --git a/contrib/ActionRecognition/data/roi/ViolentAction/.gitkeep b/mxVision/mxVision-referenceapps/ActionRecognition/data/video/Alone/.gitkeep
similarity index 100%
rename from contrib/ActionRecognition/data/roi/ViolentAction/.gitkeep
rename to mxVision/mxVision-referenceapps/ActionRecognition/data/video/Alone/.gitkeep
diff --git a/contrib/ActionRecognition/data/video/Alone/.gitkeep b/mxVision/mxVision-referenceapps/ActionRecognition/data/video/Climbup/.gitkeep
similarity index 100%
rename from contrib/ActionRecognition/data/video/Alone/.gitkeep
rename to mxVision/mxVision-referenceapps/ActionRecognition/data/video/Climbup/.gitkeep
diff --git a/contrib/ActionRecognition/data/video/Climbup/.gitkeep b/mxVision/mxVision-referenceapps/ActionRecognition/data/video/OutOfBed/.gitkeep
similarity index 100%
rename from contrib/ActionRecognition/data/video/Climbup/.gitkeep
rename to mxVision/mxVision-referenceapps/ActionRecognition/data/video/OutOfBed/.gitkeep
diff --git a/contrib/ActionRecognition/data/video/OutOfBed/.gitkeep b/mxVision/mxVision-referenceapps/ActionRecognition/data/video/Over_staying/.gitkeep
similarity index 100%
rename from contrib/ActionRecognition/data/video/OutOfBed/.gitkeep
rename to mxVision/mxVision-referenceapps/ActionRecognition/data/video/Over_staying/.gitkeep
diff --git a/contrib/ActionRecognition/data/video/Over_staying/.gitkeep b/mxVision/mxVision-referenceapps/ActionRecognition/data/video/Speed_up/.gitkeep
similarity index 100%
rename from contrib/ActionRecognition/data/video/Over_staying/.gitkeep
rename to mxVision/mxVision-referenceapps/ActionRecognition/data/video/Speed_up/.gitkeep
diff --git a/contrib/ActionRecognition/data/video/Speed_up/.gitkeep b/mxVision/mxVision-referenceapps/ActionRecognition/data/video/Violent_action/.gitkeep
similarity index 100%
rename from contrib/ActionRecognition/data/video/Speed_up/.gitkeep
rename to mxVision/mxVision-referenceapps/ActionRecognition/data/video/Violent_action/.gitkeep
diff --git a/contrib/ActionRecognition/main.py b/mxVision/mxVision-referenceapps/ActionRecognition/main.py
similarity index 97%
rename from contrib/ActionRecognition/main.py
rename to mxVision/mxVision-referenceapps/ActionRecognition/main.py
index 43592e6f1d6fc5e48422a557395115a666f0ca65..9198dabf9534db74718ee440b8e659f06325016b 100644
--- a/contrib/ActionRecognition/main.py
+++ b/mxVision/mxVision-referenceapps/ActionRecognition/main.py
@@ -1,62 +1,62 @@
-#!/usr/bin/env python
-# coding=utf-8
-
-"""
-
- Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
-
- Licensed under the Apache License, Version 2.0 (the "License");
- you may not use this file except in compliance with the License.
- You may obtain a copy of the License at
-
- http://www.apache.org/licenses/LICENSE-2.0
-
- Unless required by applicable law or agreed to in writing, software
- distributed under the License is distributed on an "AS IS" BASIS,
- WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- See the License for the specific language governing permissions and
- limitations under the License.
-
-"""
-
-from StreamManagerApi import StreamManagerApi, StringVector
-
-if __name__ == '__main__':
-    # init stream manager
-    streamManagerApi = StreamManagerApi()
-    ret = streamManagerApi.InitManager()
-    if ret != 0:
-        print("Failed to init Stream manager, ret=%s" % str(ret))
-        exit()
-
-    # create streams by pipeline config file
-    with open("./pipeline/plugin_alone.pipeline", 'rb') as f:
-        pipelineStr = f.read()
-    ret = streamManagerApi.CreateMultipleStreams(pipelineStr)
-    if ret != 0:
-        print("Failed to create Stream, ret=%s" % str(ret))
-        exit()
-
-    # Inputs data to a specified stream based on streamName.
-    streamName = b'detection+tracking'
-    inPluginId = 0
-
-    retStr = ''
-    key = b'mxpi_pluginalone0'
-    keyVec = StringVector()
-    keyVec.push_back(key)
-    while True:
-        # Obtain the inference result by specifying streamName and uniqueId.
-        inferResult = streamManagerApi.GetResult(streamName, 0, 10000)
-        if inferResult is None:
-            break
-        if inferResult.errorCode != 0:
-            print("GetResultWithUniqueId error. errorCode=%d, errorMsg=%s" % (
-                inferResult.errorCode, inferResult.data.decode()))
-            break
-        retStr = inferResult.data.decode()
-        print(retStr)
-
-    # destroy streams
-    streamManagerApi.DestroyAllStreams()
-
+#!/usr/bin/env python
+# coding=utf-8
+
+"""
+
+ Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
+
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License.
+
+"""
+
+from StreamManagerApi import StreamManagerApi, StringVector
+
+if __name__ == '__main__':
+    # init stream manager
+    streamManagerApi = StreamManagerApi()
+    ret = streamManagerApi.InitManager()
+    if ret != 0:
+        print("Failed to init Stream manager, ret=%s" % str(ret))
+        exit()
+
+    # create streams by pipeline config file
+    with open("./pipeline/plugin_alone.pipeline", 'rb') as f:
+        pipelineStr = f.read()
+    ret = streamManagerApi.CreateMultipleStreams(pipelineStr)
+    if ret != 0:
+        print("Failed to create Stream, ret=%s" % str(ret))
+        exit()
+
+    # Inputs data to a specified stream based on streamName.
+    streamName = b'detection+tracking'
+    inPluginId = 0
+
+    retStr = ''
+    key = b'mxpi_pluginalone0'
+    keyVec = StringVector()
+    keyVec.push_back(key)
+    while True:
+        # Obtain the inference result by specifying streamName and uniqueId.
+        inferResult = streamManagerApi.GetResult(streamName, 0, 10000)
+        if inferResult is None:
+            break
+        if inferResult.errorCode != 0:
+            print("GetResultWithUniqueId error. errorCode=%d, errorMsg=%s" % (
+                inferResult.errorCode, inferResult.data.decode()))
+            break
+        retStr = inferResult.data.decode()
+        print(retStr)
+
+    # destroy streams
+    streamManagerApi.DestroyAllStreams()
+
diff --git a/contrib/ActionRecognition/models/ECONet/eco_aipp.cfg b/mxVision/mxVision-referenceapps/ActionRecognition/models/ECONet/eco_aipp.cfg
similarity index 94%
rename from contrib/ActionRecognition/models/ECONet/eco_aipp.cfg
rename to mxVision/mxVision-referenceapps/ActionRecognition/models/ECONet/eco_aipp.cfg
index f01079fbee26c7a20ee5b6b11d1473fd81a8970e..8b7d1178233b8df4f3283b62415b907e9ee0ddbd 100644
--- a/contrib/ActionRecognition/models/ECONet/eco_aipp.cfg
+++ b/mxVision/mxVision-referenceapps/ActionRecognition/models/ECONet/eco_aipp.cfg
@@ -1,29 +1,29 @@
-aipp_op { 
-aipp_mode : static
-related_input_rank : 0
-input_format : YUV420SP_U8
-crop : false
-csc_switch : true
-rbuv_swap_switch : false
-matrix_r0c0 : 256
-matrix_r0c1 : 0
-matrix_r0c2 : 359
-matrix_r1c0 : 256
-matrix_r1c1 : -88
-matrix_r1c2 : -183
-matrix_r2c0 : 256
-matrix_r2c1 : 454
-matrix_r2c2 : 0
-input_bias_0 : 0
-input_bias_1 : 128
-input_bias_2 : 128
-mean_chn_0 : 104
-mean_chn_1 : 117
-mean_chn_2 : 128
-min_chn_0 : 0.0
-min_chn_1 : 0.0
-min_chn_2 : 0.0
-var_reci_chn_0 : 1.0
-var_reci_chn_1 : 1.0
-var_reci_chn_2 : 1.0
-}
+aipp_op { 
+aipp_mode : static
+related_input_rank : 0
+input_format : YUV420SP_U8
+crop : false
+csc_switch : true
+rbuv_swap_switch : false
+matrix_r0c0 : 256
+matrix_r0c1 : 0
+matrix_r0c2 : 359
+matrix_r1c0 : 256
+matrix_r1c1 : -88
+matrix_r1c2 : -183
+matrix_r2c0 : 256
+matrix_r2c1 : 454
+matrix_r2c2 : 0
+input_bias_0 : 0
+input_bias_1 : 128
+input_bias_2 : 128
+mean_chn_0 : 104
+mean_chn_1 : 117
+mean_chn_2 : 128
+min_chn_0 : 0.0
+min_chn_1 : 0.0
+min_chn_2 : 0.0
+var_reci_chn_0 : 1.0
+var_reci_chn_1 : 1.0
+var_reci_chn_2 : 1.0
+}
diff --git a/contrib/ActionRecognition/models/ECONet/trans_pb2om.sh b/mxVision/mxVision-referenceapps/ActionRecognition/models/ECONet/trans_pb2om.sh
similarity index 100%
rename from contrib/ActionRecognition/models/ECONet/trans_pb2om.sh
rename to mxVision/mxVision-referenceapps/ActionRecognition/models/ECONet/trans_pb2om.sh
diff --git a/contrib/ActionRecognition/data/video/Violent_action/.gitkeep b/mxVision/mxVision-referenceapps/ActionRecognition/models/yolov3/.gitkeep
similarity index 100%
rename from contrib/ActionRecognition/data/video/Violent_action/.gitkeep
rename to mxVision/mxVision-referenceapps/ActionRecognition/models/yolov3/.gitkeep
diff --git a/contrib/ActionRecognition/pipeline/plugin_all.pipeline b/mxVision/mxVision-referenceapps/ActionRecognition/pipeline/plugin_all.pipeline
similarity index 97%
rename from contrib/ActionRecognition/pipeline/plugin_all.pipeline
rename to mxVision/mxVision-referenceapps/ActionRecognition/pipeline/plugin_all.pipeline
index 2bc55c013f1d8a5e6fc17b6b02261091e7d0ac0e..dbf1c5cb91bbcc70f1570b96bf9c5f6a1dd9d3d4 100644
--- a/contrib/ActionRecognition/pipeline/plugin_all.pipeline
+++ b/mxVision/mxVision-referenceapps/ActionRecognition/pipeline/plugin_all.pipeline
@@ -1,137 +1,137 @@
-{
-    "detection+tracking": {
-        "stream_config": {
-            "deviceId": "0"
-        },
-        "mxpi_rtspsrc0": {
-            "props": {
-                "rtspUrl": "rtsp_Url"
-                },
-            "factory": "mxpi_rtspsrc",
-            "next": "mxpi_videodecoder0"
-        },
-        "mxpi_videodecoder0":{
-            "props": {
-                "vdecChannelId": "0"
-                },
-            "factory": "mxpi_videodecoder",
-            "next": "mxpi_imageresize0"
-        },
-        "mxpi_imageresize0":{            
-            "props": {
-                "dataSource": "mxpi_videodecoder0",
-                "resizeHeight": "416",
-                "resizeWidth": "416"
-            },
-            "factory": "mxpi_imageresize",
-            "next": "mxpi_tensorinfer0"
-        },
-        "mxpi_tensorinfer0":{
-            "props": {
-                "dataSource": "mxpi_imageresize0",
-                "modelPath": "./models/yolov3/yolov3_tf_bs1_fp16.om"
-            },
-            "factory": "mxpi_tensorinfer",
-            "next": "mxpi_objectpostprocessor0"
-        },
-        "mxpi_objectpostprocessor0": {
-            "props": {
-                "dataSource": "mxpi_tensorinfer0",
-                "funcLanguage":"c++",
-                "postProcessConfigPath": "./models/yolov3/yolov3_tf_bs1_fp16.cfg",
-                "labelPath": "./models/yolov3/coco.names",
-                "postProcessLibPath": "../../lib/modelpostprocessors/libyolov3postprocess.so"
-            },
-            "factory": "mxpi_objectpostprocessor",
-            "next": "mxpi_motsimplesort0"
-        },
-        "mxpi_motsimplesort0": {
-            "props": {
-                "dataSourceDetection": "mxpi_objectpostprocessor0"
-            },
-            "factory": "mxpi_motsimplesort",
-            "next": "mxpi_plugincounter0"
-        },
-        "mxpi_plugincounter0": {
-            "props": {
-                "dataSourceTrack": "mxpi_motsimplesort0"
-            },
-            "factory": "mxpi_plugincounter",
-            "next": "mxpi_pluginalone0"
-        },
-        "mxpi_pluginalone0": {
-            "props": {
-                "dataSourceTrack": "mxpi_motsimplesort0",
-				"dataSourceDetection": "mxpi_objectpostprocessor0",
-                "detectThresh":"8",
-                "detectRatio":"0.8",
-                "detectSleep":"270"
-            },
-            "factory": "mxpi_pluginalone",
-            "next": "mxpi_pluginoverspeed0"
-        },
-        "mxpi_pluginoverspeed0": {
-            "props": {
-                "dataSourceTrack": "mxpi_motsimplesort0",
-                "dataSourceDetection": "mxpi_objectpostprocessor0",
-                "speedThresh":  "1",
-                "frames": "8",
-                "detectSleep": "270"
-            },
-            "factory": "mxpi_pluginoverspeed",
-            "next": "mxpi_pluginoverstay0"
-        },
-        "mxpi_pluginoverstay0": {
-            "props": {
-                "status": "1",
-                "dataSourceTrack": "mxpi_motsimplesort0",
- 	            "dataSourceDetection": "mxpi_objectpostprocessor0",
-                "stayThresh":"90",
-	            "frames":"90",
-	            "distanceThresh":"100",
-                "detectRatio":"0.7",
-                "detectSleep":"90"
-            },
-            "factory": "mxpi_pluginoverstay",
-            "next": "mxpi_pluginclimb0"
-        },
-        "mxpi_pluginclimb0": {
-            "props": {
-                "dataSourceTrack": "mxpi_motsimplesort0",
-                "dataSourceDetection": "mxpi_objectpostprocessor0",
-                "detectRatio":  "0.6",
-                "filePath": "./data/roi/Climbup/*.txt",
-                "detectSleep": "30",
-                "bufferLength": "8",
-                "highThresh": "10"
-            },
-            "factory": "mxpi_pluginclimb",
-            "next": "mxpi_pluginoutofbed0"
-        },
-        "mxpi_pluginoutofbed0": {
-            "props": {
-                "dataSourceTrack": "mxpi_motsimplesort0",
-                "dataSourceDetection": "mxpi_objectpostprocessor0",
-                "configPath":  "./data/roi/OutofBed/*.txt",
-                "detectThresh": "8",
-                "detectSleep": "15",
-	            "detectRatio": "0.25"
-            },
-            "factory": "mxpi_pluginoutofbed",
-            "next": "mxpi_dataserialize0"
-        },
-        "mxpi_dataserialize0": {
-            "props": {
-                "outputDataKeys": "mxpi_pluginoverstay0"
-            },
-            "factory": "mxpi_dataserialize",
-            "next": "appsink0"
-        },
-        "appsink0": {
-            "props": {
-                "blocksize": "4096000"
-            },
-            "factory": "appsink"
-        }
-	}
+{
+    "detection+tracking": {
+        "stream_config": {
+            "deviceId": "0"
+        },
+        "mxpi_rtspsrc0": {
+            "props": {
+                "rtspUrl": "rtsp_Url"
+                },
+            "factory": "mxpi_rtspsrc",
+            "next": "mxpi_videodecoder0"
+        },
+        "mxpi_videodecoder0":{
+            "props": {
+                "vdecChannelId": "0"
+                },
+            "factory": "mxpi_videodecoder",
+            "next": "mxpi_imageresize0"
+        },
+        "mxpi_imageresize0":{            
+            "props": {
+                "dataSource": "mxpi_videodecoder0",
+                "resizeHeight": "416",
+                "resizeWidth": "416"
+            },
+            "factory": "mxpi_imageresize",
+            "next": "mxpi_tensorinfer0"
+        },
+        "mxpi_tensorinfer0":{
+            "props": {
+                "dataSource": "mxpi_imageresize0",
+                "modelPath": "./models/yolov3/yolov3_tf_bs1_fp16.om"
+            },
+            "factory": "mxpi_tensorinfer",
+            "next": "mxpi_objectpostprocessor0"
+        },
+        "mxpi_objectpostprocessor0": {
+            "props": {
+                "dataSource": "mxpi_tensorinfer0",
+                "funcLanguage":"c++",
+                "postProcessConfigPath": "./models/yolov3/yolov3_tf_bs1_fp16.cfg",
+                "labelPath": "./models/yolov3/coco.names",
+                "postProcessLibPath": "../../lib/modelpostprocessors/libyolov3postprocess.so"
+            },
+            "factory": "mxpi_objectpostprocessor",
+            "next": "mxpi_motsimplesort0"
+        },
+        "mxpi_motsimplesort0": {
+            "props": {
+                "dataSourceDetection": "mxpi_objectpostprocessor0"
+            },
+            "factory": "mxpi_motsimplesort",
+            "next": "mxpi_plugincounter0"
+        },
+        "mxpi_plugincounter0": {
+            "props": {
+                "dataSourceTrack": "mxpi_motsimplesort0"
+            },
+            "factory": "mxpi_plugincounter",
+            "next": "mxpi_pluginalone0"
+        },
+        "mxpi_pluginalone0": {
+            "props": {
+                "dataSourceTrack": "mxpi_motsimplesort0",
+				"dataSourceDetection": "mxpi_objectpostprocessor0",
+                "detectThresh":"8",
+                "detectRatio":"0.8",
+                "detectSleep":"270"
+            },
+            "factory": "mxpi_pluginalone",
+            "next": "mxpi_pluginoverspeed0"
+        },
+        "mxpi_pluginoverspeed0": {
+            "props": {
+                "dataSourceTrack": "mxpi_motsimplesort0",
+                "dataSourceDetection": "mxpi_objectpostprocessor0",
+                "speedThresh":  "1",
+                "frames": "8",
+                "detectSleep": "270"
+            },
+            "factory": "mxpi_pluginoverspeed",
+            "next": "mxpi_pluginoverstay0"
+        },
+        "mxpi_pluginoverstay0": {
+            "props": {
+                "status": "1",
+                "dataSourceTrack": "mxpi_motsimplesort0",
+ 	            "dataSourceDetection": "mxpi_objectpostprocessor0",
+                "stayThresh":"90",
+	            "frames":"90",
+	            "distanceThresh":"100",
+                "detectRatio":"0.7",
+                "detectSleep":"90"
+            },
+            "factory": "mxpi_pluginoverstay",
+            "next": "mxpi_pluginclimb0"
+        },
+        "mxpi_pluginclimb0": {
+            "props": {
+                "dataSourceTrack": "mxpi_motsimplesort0",
+                "dataSourceDetection": "mxpi_objectpostprocessor0",
+                "detectRatio":  "0.6",
+                "filePath": "./data/roi/Climbup/*.txt",
+                "detectSleep": "30",
+                "bufferLength": "8",
+                "highThresh": "10"
+            },
+            "factory": "mxpi_pluginclimb",
+            "next": "mxpi_pluginoutofbed0"
+        },
+        "mxpi_pluginoutofbed0": {
+            "props": {
+                "dataSourceTrack": "mxpi_motsimplesort0",
+                "dataSourceDetection": "mxpi_objectpostprocessor0",
+                "configPath":  "./data/roi/OutofBed/*.txt",
+                "detectThresh": "8",
+                "detectSleep": "15",
+	            "detectRatio": "0.25"
+            },
+            "factory": "mxpi_pluginoutofbed",
+            "next": "mxpi_dataserialize0"
+        },
+        "mxpi_dataserialize0": {
+            "props": {
+                "outputDataKeys": "mxpi_pluginoverstay0"
+            },
+            "factory": "mxpi_dataserialize",
+            "next": "appsink0"
+        },
+        "appsink0": {
+            "props": {
+                "blocksize": "4096000"
+            },
+            "factory": "appsink"
+        }
+	}
 }
\ No newline at end of file
diff --git a/contrib/ActionRecognition/pipeline/plugin_alone.pipeline b/mxVision/mxVision-referenceapps/ActionRecognition/pipeline/plugin_alone.pipeline
similarity index 96%
rename from contrib/ActionRecognition/pipeline/plugin_alone.pipeline
rename to mxVision/mxVision-referenceapps/ActionRecognition/pipeline/plugin_alone.pipeline
index c8ed69cd2cebd62e838559892b0aa42877e49641..922fc085334e990fdb8fbe89127ff0c0b7af1d22 100644
--- a/contrib/ActionRecognition/pipeline/plugin_alone.pipeline
+++ b/mxVision/mxVision-referenceapps/ActionRecognition/pipeline/plugin_alone.pipeline
@@ -1,80 +1,80 @@
-{
-    "detection+tracking": {
-        "stream_config": {
-            "deviceId": "0"
-        },
-        "mxpi_rtspsrc0": {
-            "props": {
-                "rtspUrl": "rtsp_Url"
-                },
-            "factory": "mxpi_rtspsrc",
-            "next": "mxpi_videodecoder0"
-        },
-        "mxpi_videodecoder0":{
-            "props": {
-                "vdecChannelId": "0"
-                },
-            "factory": "mxpi_videodecoder",
-            "next": "mxpi_imageresize0"
-        },
-        "mxpi_imageresize0":{            
-            "props": {
-                "dataSource": "mxpi_videodecoder0",
-                "resizeHeight": "416",
-                "resizeWidth": "416"
-            },
-            "factory": "mxpi_imageresize",
-            "next": "mxpi_tensorinfer0"
-        },
-        "mxpi_tensorinfer0":{
-            "props": {
-                "dataSource": "mxpi_imageresize0",
-                "modelPath": "./models/yolov3/yolov3_tf_bs1_fp16.om"
-            },
-            "factory": "mxpi_tensorinfer",
-            "next": "mxpi_objectpostprocessor0"
-        },
-        "mxpi_objectpostprocessor0": {
-            "props": {
-                "dataSource": "mxpi_tensorinfer0",
-                "funcLanguage":"c++",
-                "postProcessConfigPath": "./models/yolov3/yolov3_tf_bs1_fp16.cfg",
-                "labelPath": "./models/yolov3/coco.names",
-                "postProcessLibPath": "../../lib/modelpostprocessors/libyolov3postprocess.so"
-            },
-            "factory": "mxpi_objectpostprocessor",
-            "next": "mxpi_motsimplesort0"
-        },
-        "mxpi_motsimplesort0": {
-             "props": {
-                "dataSourceDetection": "mxpi_objectpostprocessor0"
-            },
-            "factory": "mxpi_motsimplesort",
-            "next": "mxpi_pluginalone0"
-        },
-        "mxpi_pluginalone0": {
-            "props": {
-                "dataSourceTrack": "mxpi_motsimplesort0",
-				"dataSourceDetection": "mxpi_objectpostprocessor0",
-                "detectThresh": "8",
-                "detectRatio": "0.8",
-                "detectSleep": "270"
-            },
-            "factory": "mxpi_pluginalone",
-            "next": "mxpi_dataserialize0"
-        },
-        "mxpi_dataserialize0": {
-            "props": {
-                "outputDataKeys": "mxpi_pluginalone0"
-            },
-            "factory": "mxpi_dataserialize",
-            "next": "appsink0"
-        },
-        "appsink0": {
-            "props": {
-                "blocksize": "4096000"
-            },
-            "factory": "appsink"
-        }
-    }
-}
+{
+    "detection+tracking": {
+        "stream_config": {
+            "deviceId": "0"
+        },
+        "mxpi_rtspsrc0": {
+            "props": {
+                "rtspUrl": "rtsp_Url"
+                },
+            "factory": "mxpi_rtspsrc",
+            "next": "mxpi_videodecoder0"
+        },
+        "mxpi_videodecoder0":{
+            "props": {
+                "vdecChannelId": "0"
+                },
+            "factory": "mxpi_videodecoder",
+            "next": "mxpi_imageresize0"
+        },
+        "mxpi_imageresize0":{            
+            "props": {
+                "dataSource": "mxpi_videodecoder0",
+                "resizeHeight": "416",
+                "resizeWidth": "416"
+            },
+            "factory": "mxpi_imageresize",
+            "next": "mxpi_tensorinfer0"
+        },
+        "mxpi_tensorinfer0":{
+            "props": {
+                "dataSource": "mxpi_imageresize0",
+                "modelPath": "./models/yolov3/yolov3_tf_bs1_fp16.om"
+            },
+            "factory": "mxpi_tensorinfer",
+            "next": "mxpi_objectpostprocessor0"
+        },
+        "mxpi_objectpostprocessor0": {
+            "props": {
+                "dataSource": "mxpi_tensorinfer0",
+                "funcLanguage":"c++",
+                "postProcessConfigPath": "./models/yolov3/yolov3_tf_bs1_fp16.cfg",
+                "labelPath": "./models/yolov3/coco.names",
+                "postProcessLibPath": "../../lib/modelpostprocessors/libyolov3postprocess.so"
+            },
+            "factory": "mxpi_objectpostprocessor",
+            "next": "mxpi_motsimplesort0"
+        },
+        "mxpi_motsimplesort0": {
+             "props": {
+                "dataSourceDetection": "mxpi_objectpostprocessor0"
+            },
+            "factory": "mxpi_motsimplesort",
+            "next": "mxpi_pluginalone0"
+        },
+        "mxpi_pluginalone0": {
+            "props": {
+                "dataSourceTrack": "mxpi_motsimplesort0",
+				"dataSourceDetection": "mxpi_objectpostprocessor0",
+                "detectThresh": "8",
+                "detectRatio": "0.8",
+                "detectSleep": "270"
+            },
+            "factory": "mxpi_pluginalone",
+            "next": "mxpi_dataserialize0"
+        },
+        "mxpi_dataserialize0": {
+            "props": {
+                "outputDataKeys": "mxpi_pluginalone0"
+            },
+            "factory": "mxpi_dataserialize",
+            "next": "appsink0"
+        },
+        "appsink0": {
+            "props": {
+                "blocksize": "4096000"
+            },
+            "factory": "appsink"
+        }
+    }
+}
diff --git a/contrib/ActionRecognition/pipeline/plugin_climb.pipeline b/mxVision/mxVision-referenceapps/ActionRecognition/pipeline/plugin_climb.pipeline
similarity index 97%
rename from contrib/ActionRecognition/pipeline/plugin_climb.pipeline
rename to mxVision/mxVision-referenceapps/ActionRecognition/pipeline/plugin_climb.pipeline
index f07068b38d8dd43f48621c1aee7adbf714396cac..64c6d88365a08e7cc097c43ed29011c5d1f8f093 100644
--- a/contrib/ActionRecognition/pipeline/plugin_climb.pipeline
+++ b/mxVision/mxVision-referenceapps/ActionRecognition/pipeline/plugin_climb.pipeline
@@ -1,82 +1,82 @@
-{
-    "detection+tracking": {
-        "stream_config": {
-            "deviceId": "0"
-        },
-        "mxpi_rtspsrc0": {
-            "props": {
-                "rtspUrl": "rtsp_Url"
-                },
-            "factory": "mxpi_rtspsrc",
-            "next": "mxpi_videodecoder0"
-        },
-        "mxpi_videodecoder0":{
-            "props": {
-                "vdecChannelId": "0"
-                },
-            "factory": "mxpi_videodecoder",
-            "next": "mxpi_imageresize0"
-        },
-        "mxpi_imageresize0":{            
-            "props": {
-                "dataSource": "mxpi_videodecoder0",
-                "resizeHeight": "416",
-                "resizeWidth": "416"
-            },
-            "factory": "mxpi_imageresize",
-            "next": "mxpi_tensorinfer0"
-        },
-        "mxpi_tensorinfer0":{
-            "props": {
-                "dataSource": "mxpi_imageresize0",
-                "modelPath": "./models/yolov3/yolov3_tf_bs1_fp16.om"
-            },
-            "factory": "mxpi_tensorinfer",
-            "next": "mxpi_objectpostprocessor0"
-        },
-        "mxpi_objectpostprocessor0": {
-            "props": {
-                "dataSource": "mxpi_tensorinfer0",
-                "funcLanguage":"c++",
-                "postProcessConfigPath": "./models/yolov3/yolov3_tf_bs1_fp16.cfg",
-                "labelPath": "./models/yolov3/coco.names",
-                "postProcessLibPath": "../../lib/modelpostprocessors/libyolov3postprocess.so"
-            },
-            "factory": "mxpi_objectpostprocessor",
-            "next": "mxpi_motsimplesort0"
-        },
-        "mxpi_motsimplesort0": {
-            "props": {
-                "dataSourceDetection": "mxpi_objectpostprocessor0"
-            },
-            "factory": "mxpi_motsimplesort",
-            "next": "mxpi_pluginclimb0"
-        },
-        "mxpi_pluginclimb0": {
-            "props": {
-                "dataSourceTrack": "mxpi_motsimplesort0",
-                "dataSourceDetection": "mxpi_objectpostprocessor0",
-                "detectRatio":  "0.6",
-                "filePath": "./data/roi/Climbup/*.txt",
-                "detectSleep": "30",
-                "bufferLength": "8",
-                "highThresh": "10"
-            },
-            "factory": "mxpi_pluginclimb",
-            "next": "mxpi_dataserialize0"
-        },
-        "mxpi_dataserialize0": {
-            "props": {
-                "outputDataKeys": "mxpi_pluginclimb0"
-            },
-            "factory": "mxpi_dataserialize",
-            "next": "appsink0"
-        },
-        "appsink0": {
-            "props": {
-                "blocksize": "4096000"
-            },
-            "factory": "appsink"
-        }
-    }
-}
+{
+    "detection+tracking": {
+        "stream_config": {
+            "deviceId": "0"
+        },
+        "mxpi_rtspsrc0": {
+            "props": {
+                "rtspUrl": "rtsp_Url"
+                },
+            "factory": "mxpi_rtspsrc",
+            "next": "mxpi_videodecoder0"
+        },
+        "mxpi_videodecoder0":{
+            "props": {
+                "vdecChannelId": "0"
+                },
+            "factory": "mxpi_videodecoder",
+            "next": "mxpi_imageresize0"
+        },
+        "mxpi_imageresize0":{            
+            "props": {
+                "dataSource": "mxpi_videodecoder0",
+                "resizeHeight": "416",
+                "resizeWidth": "416"
+            },
+            "factory": "mxpi_imageresize",
+            "next": "mxpi_tensorinfer0"
+        },
+        "mxpi_tensorinfer0":{
+            "props": {
+                "dataSource": "mxpi_imageresize0",
+                "modelPath": "./models/yolov3/yolov3_tf_bs1_fp16.om"
+            },
+            "factory": "mxpi_tensorinfer",
+            "next": "mxpi_objectpostprocessor0"
+        },
+        "mxpi_objectpostprocessor0": {
+            "props": {
+                "dataSource": "mxpi_tensorinfer0",
+                "funcLanguage":"c++",
+                "postProcessConfigPath": "./models/yolov3/yolov3_tf_bs1_fp16.cfg",
+                "labelPath": "./models/yolov3/coco.names",
+                "postProcessLibPath": "../../lib/modelpostprocessors/libyolov3postprocess.so"
+            },
+            "factory": "mxpi_objectpostprocessor",
+            "next": "mxpi_motsimplesort0"
+        },
+        "mxpi_motsimplesort0": {
+            "props": {
+                "dataSourceDetection": "mxpi_objectpostprocessor0"
+            },
+            "factory": "mxpi_motsimplesort",
+            "next": "mxpi_pluginclimb0"
+        },
+        "mxpi_pluginclimb0": {
+            "props": {
+                "dataSourceTrack": "mxpi_motsimplesort0",
+                "dataSourceDetection": "mxpi_objectpostprocessor0",
+                "detectRatio":  "0.6",
+                "filePath": "./data/roi/Climbup/*.txt",
+                "detectSleep": "30",
+                "bufferLength": "8",
+                "highThresh": "10"
+            },
+            "factory": "mxpi_pluginclimb",
+            "next": "mxpi_dataserialize0"
+        },
+        "mxpi_dataserialize0": {
+            "props": {
+                "outputDataKeys": "mxpi_pluginclimb0"
+            },
+            "factory": "mxpi_dataserialize",
+            "next": "appsink0"
+        },
+        "appsink0": {
+            "props": {
+                "blocksize": "4096000"
+            },
+            "factory": "appsink"
+        }
+    }
+}
diff --git a/contrib/ActionRecognition/pipeline/plugin_outofbed.pipeline b/mxVision/mxVision-referenceapps/ActionRecognition/pipeline/plugin_outofbed.pipeline
similarity index 97%
rename from contrib/ActionRecognition/pipeline/plugin_outofbed.pipeline
rename to mxVision/mxVision-referenceapps/ActionRecognition/pipeline/plugin_outofbed.pipeline
index 7e8500a5356f8dae41c075fa7256ed9a32543f56..459053b9ee5a91bc783b1ee0c549ba22bdec1724 100644
--- a/contrib/ActionRecognition/pipeline/plugin_outofbed.pipeline
+++ b/mxVision/mxVision-referenceapps/ActionRecognition/pipeline/plugin_outofbed.pipeline
@@ -1,81 +1,81 @@
-{
-    "detection+tracking": {
-        "stream_config": {
-            "deviceId": "0"
-        },
-        "mxpi_rtspsrc0": {
-            "props": {
-                "rtspUrl": "rtsp_Url"
-                },
-            "factory": "mxpi_rtspsrc",
-            "next": "mxpi_videodecoder0"
-        },
-        "mxpi_videodecoder0":{
-            "props": {
-                "vdecChannelId": "0"
-                },
-            "factory": "mxpi_videodecoder",
-            "next": "mxpi_imageresize0"
-        },
-        "mxpi_imageresize0":{            
-            "props": {
-                "dataSource": "mxpi_videodecoder0",
-                "resizeHeight": "416",
-                "resizeWidth": "416"
-            },
-            "factory": "mxpi_imageresize",
-            "next": "mxpi_tensorinfer0"
-        },
-        "mxpi_tensorinfer0":{
-            "props": {
-                "dataSource": "mxpi_imageresize0",
-                "modelPath": "./models/yolov3/yolov3_tf_bs1_fp16.om"
-            },
-            "factory": "mxpi_tensorinfer",
-            "next": "mxpi_objectpostprocessor0"
-        },
-        "mxpi_objectpostprocessor0": {
-            "props": {
-                "dataSource": "mxpi_tensorinfer0",
-                "funcLanguage":"c++",
-                "postProcessConfigPath": "./models/yolov3/yolov3_tf_bs1_fp16.cfg",
-                "labelPath": "./models/yolov3/coco.names",
-                "postProcessLibPath": "../../lib/modelpostprocessors/libyolov3postprocess.so"
-            },
-            "factory": "mxpi_objectpostprocessor",
-            "next": "mxpi_motsimplesort0"
-        },
-        "mxpi_motsimplesort0": {
-             "props": {
-                "dataSourceDetection": "mxpi_objectpostprocessor0"
-            },
-            "factory": "mxpi_motsimplesort",
-            "next": "mxpi_pluginoutofbed0"
-        },
-       "mxpi_pluginoutofbed0": {
-            "props": {
-                "dataSourceTrack": "mxpi_motsimplesort0",
-                "dataSourceDetection": "mxpi_objectpostprocessor0",
-                "configPath":  "./datas/OutofBed/*.txt",
-                "detectThresh": "8",
-                "detectSleep": "15",
-	            "detectRatio": "0.25"
-            },
-            "factory": "mxpi_pluginoutofbed",
-            "next": "mxpi_dataserialize0"
-        },
-        "mxpi_dataserialize0": {
-            "props": {
-                "outputDataKeys": "mxpi_pluginoutofbed0"
-            },
-            "factory": "mxpi_dataserialize",
-            "next": "appsink0"
-        },
-        "appsink0": {
-            "props": {
-                "blocksize": "4096000"
-            },
-            "factory": "appsink"
-        }
-    }
-}
+{
+    "detection+tracking": {
+        "stream_config": {
+            "deviceId": "0"
+        },
+        "mxpi_rtspsrc0": {
+            "props": {
+                "rtspUrl": "rtsp_Url"
+                },
+            "factory": "mxpi_rtspsrc",
+            "next": "mxpi_videodecoder0"
+        },
+        "mxpi_videodecoder0":{
+            "props": {
+                "vdecChannelId": "0"
+                },
+            "factory": "mxpi_videodecoder",
+            "next": "mxpi_imageresize0"
+        },
+        "mxpi_imageresize0":{            
+            "props": {
+                "dataSource": "mxpi_videodecoder0",
+                "resizeHeight": "416",
+                "resizeWidth": "416"
+            },
+            "factory": "mxpi_imageresize",
+            "next": "mxpi_tensorinfer0"
+        },
+        "mxpi_tensorinfer0":{
+            "props": {
+                "dataSource": "mxpi_imageresize0",
+                "modelPath": "./models/yolov3/yolov3_tf_bs1_fp16.om"
+            },
+            "factory": "mxpi_tensorinfer",
+            "next": "mxpi_objectpostprocessor0"
+        },
+        "mxpi_objectpostprocessor0": {
+            "props": {
+                "dataSource": "mxpi_tensorinfer0",
+                "funcLanguage":"c++",
+                "postProcessConfigPath": "./models/yolov3/yolov3_tf_bs1_fp16.cfg",
+                "labelPath": "./models/yolov3/coco.names",
+                "postProcessLibPath": "../../lib/modelpostprocessors/libyolov3postprocess.so"
+            },
+            "factory": "mxpi_objectpostprocessor",
+            "next": "mxpi_motsimplesort0"
+        },
+        "mxpi_motsimplesort0": {
+             "props": {
+                "dataSourceDetection": "mxpi_objectpostprocessor0"
+            },
+            "factory": "mxpi_motsimplesort",
+            "next": "mxpi_pluginoutofbed0"
+        },
+       "mxpi_pluginoutofbed0": {
+            "props": {
+                "dataSourceTrack": "mxpi_motsimplesort0",
+                "dataSourceDetection": "mxpi_objectpostprocessor0",
+                "configPath":  "./datas/OutofBed/*.txt",
+                "detectThresh": "8",
+                "detectSleep": "15",
+	            "detectRatio": "0.25"
+            },
+            "factory": "mxpi_pluginoutofbed",
+            "next": "mxpi_dataserialize0"
+        },
+        "mxpi_dataserialize0": {
+            "props": {
+                "outputDataKeys": "mxpi_pluginoutofbed0"
+            },
+            "factory": "mxpi_dataserialize",
+            "next": "appsink0"
+        },
+        "appsink0": {
+            "props": {
+                "blocksize": "4096000"
+            },
+            "factory": "appsink"
+        }
+    }
+}
diff --git a/contrib/ActionRecognition/pipeline/plugin_overspeed.pipeline b/mxVision/mxVision-referenceapps/ActionRecognition/pipeline/plugin_overspeed.pipeline
similarity index 97%
rename from contrib/ActionRecognition/pipeline/plugin_overspeed.pipeline
rename to mxVision/mxVision-referenceapps/ActionRecognition/pipeline/plugin_overspeed.pipeline
index 8ab1739c87b78a9557d605344abeed37069edc67..046f7017f41318167375b548d2aeef5161bf463f 100644
--- a/contrib/ActionRecognition/pipeline/plugin_overspeed.pipeline
+++ b/mxVision/mxVision-referenceapps/ActionRecognition/pipeline/plugin_overspeed.pipeline
@@ -1,80 +1,80 @@
-{
-    "detection+tracking": {
-        "stream_config": {
-            "deviceId": "0"
-        },
-        "mxpi_rtspsrc0": {
-            "props": {
-                "rtspUrl": "rtsp_Url"
-                },
-            "factory": "mxpi_rtspsrc",
-            "next": "mxpi_videodecoder0"
-        },
-        "mxpi_videodecoder0":{
-            "props": {
-                "vdecChannelId": "0"
-                },
-            "factory": "mxpi_videodecoder",
-            "next": "mxpi_imageresize0"
-        },
-        "mxpi_imageresize0":{            
-            "props": {
-                "dataSource": "mxpi_videodecoder0",
-                "resizeHeight": "416",
-                "resizeWidth": "416"
-            },
-            "factory": "mxpi_imageresize",
-            "next": "mxpi_tensorinfer0"
-        },
-        "mxpi_tensorinfer0":{
-            "props": {
-                "dataSource": "mxpi_imageresize0",
-                "modelPath": "./models/yolov3/yolov3_tf_bs1_fp16.om"
-            },
-            "factory": "mxpi_tensorinfer",
-            "next": "mxpi_objectpostprocessor0"
-        },
-        "mxpi_objectpostprocessor0": {
-            "props": {
-                "dataSource": "mxpi_tensorinfer0",
-                "funcLanguage":"c++",
-                "postProcessConfigPath": "./models/yolov3/yolov3_tf_bs1_fp16.cfg",
-                "labelPath": "./models/yolov3/coco.names",
-                "postProcessLibPath": "../../lib/modelpostprocessors/libyolov3postprocess.so"
-            },
-            "factory": "mxpi_objectpostprocessor",
-            "next": "mxpi_motsimplesort0"
-        },
-        "mxpi_motsimplesort0": {
-            "props": {
-                "dataSourceDetection": "mxpi_objectpostprocessor0"
-            },
-            "factory": "mxpi_motsimplesort",
-            "next": "mxpi_pluginoverspeed0"
-        },
-        "mxpi_pluginoverspeed0": {
-            "props": {
-                "dataSourceTrack": "mxpi_motsimplesort0",
-                "dataSourceDetection": "mxpi_objectpostprocessor0",
-                "speedThresh":  "10",
-                "frames": "8",
-                "detectSleep": "270"
-            },
-            "factory": "mxpi_pluginoverspeed",
-            "next": "mxpi_dataserialize0"
-        },
-        "mxpi_dataserialize0": {
-            "props": {
-                "outputDataKeys": "mxpi_pluginoverspeed0"
-            },
-            "factory": "mxpi_dataserialize",
-            "next": "appsink0"
-        },
-        "appsink0": {
-            "props": {
-                "blocksize": "4096000"
-            },
-            "factory": "appsink"
-        }
-    }
-}
+{
+    "detection+tracking": {
+        "stream_config": {
+            "deviceId": "0"
+        },
+        "mxpi_rtspsrc0": {
+            "props": {
+                "rtspUrl": "rtsp_Url"
+                },
+            "factory": "mxpi_rtspsrc",
+            "next": "mxpi_videodecoder0"
+        },
+        "mxpi_videodecoder0":{
+            "props": {
+                "vdecChannelId": "0"
+                },
+            "factory": "mxpi_videodecoder",
+            "next": "mxpi_imageresize0"
+        },
+        "mxpi_imageresize0":{            
+            "props": {
+                "dataSource": "mxpi_videodecoder0",
+                "resizeHeight": "416",
+                "resizeWidth": "416"
+            },
+            "factory": "mxpi_imageresize",
+            "next": "mxpi_tensorinfer0"
+        },
+        "mxpi_tensorinfer0":{
+            "props": {
+                "dataSource": "mxpi_imageresize0",
+                "modelPath": "./models/yolov3/yolov3_tf_bs1_fp16.om"
+            },
+            "factory": "mxpi_tensorinfer",
+            "next": "mxpi_objectpostprocessor0"
+        },
+        "mxpi_objectpostprocessor0": {
+            "props": {
+                "dataSource": "mxpi_tensorinfer0",
+                "funcLanguage":"c++",
+                "postProcessConfigPath": "./models/yolov3/yolov3_tf_bs1_fp16.cfg",
+                "labelPath": "./models/yolov3/coco.names",
+                "postProcessLibPath": "../../lib/modelpostprocessors/libyolov3postprocess.so"
+            },
+            "factory": "mxpi_objectpostprocessor",
+            "next": "mxpi_motsimplesort0"
+        },
+        "mxpi_motsimplesort0": {
+            "props": {
+                "dataSourceDetection": "mxpi_objectpostprocessor0"
+            },
+            "factory": "mxpi_motsimplesort",
+            "next": "mxpi_pluginoverspeed0"
+        },
+        "mxpi_pluginoverspeed0": {
+            "props": {
+                "dataSourceTrack": "mxpi_motsimplesort0",
+                "dataSourceDetection": "mxpi_objectpostprocessor0",
+                "speedThresh":  "10",
+                "frames": "8",
+                "detectSleep": "270"
+            },
+            "factory": "mxpi_pluginoverspeed",
+            "next": "mxpi_dataserialize0"
+        },
+        "mxpi_dataserialize0": {
+            "props": {
+                "outputDataKeys": "mxpi_pluginoverspeed0"
+            },
+            "factory": "mxpi_dataserialize",
+            "next": "appsink0"
+        },
+        "appsink0": {
+            "props": {
+                "blocksize": "4096000"
+            },
+            "factory": "appsink"
+        }
+    }
+}
diff --git a/contrib/ActionRecognition/pipeline/plugin_overstay.pipeline b/mxVision/mxVision-referenceapps/ActionRecognition/pipeline/plugin_overstay.pipeline
similarity index 97%
rename from contrib/ActionRecognition/pipeline/plugin_overstay.pipeline
rename to mxVision/mxVision-referenceapps/ActionRecognition/pipeline/plugin_overstay.pipeline
index bd2c611f63a5bc6b34ab03ecb984c6cac2196c54..377407ee5f5febd6bfcaaefee9887f481272cf86 100644
--- a/contrib/ActionRecognition/pipeline/plugin_overstay.pipeline
+++ b/mxVision/mxVision-referenceapps/ActionRecognition/pipeline/plugin_overstay.pipeline
@@ -1,82 +1,82 @@
-{
-    "detection+tracking": {
-        "stream_config": {
-            "deviceId": "0"
-        },
-        "mxpi_rtspsrc0": {
-            "props": {
-                "rtspUrl": "rtsp_Url"
-                },
-            "factory": "mxpi_rtspsrc",
-            "next": "mxpi_videodecoder0"
-        },
-        "mxpi_videodecoder0":{
-            "props": {
-                "vdecChannelId": "0"
-                },
-            "factory": "mxpi_videodecoder",
-            "next": "mxpi_imageresize0"
-        },
-        "mxpi_imageresize0":{            
-            "props": {
-                "dataSource": "mxpi_videodecoder0",
-                "resizeHeight": "416",
-                "resizeWidth": "416"
-            },
-            "factory": "mxpi_imageresize",
-            "next": "mxpi_tensorinfer0"
-        },
-        "mxpi_tensorinfer0":{
-            "props": {
-                "dataSource": "mxpi_imageresize0",
-                "modelPath": "./models/yolov3/yolov3_tf_bs1_fp16.om"
-            },
-            "factory": "mxpi_tensorinfer",
-            "next": "mxpi_objectpostprocessor0"
-        },
-        "mxpi_objectpostprocessor0": {
-            "props": {
-                "dataSource": "mxpi_tensorinfer0",
-                "funcLanguage":"c++",
-                "postProcessConfigPath": "./models/yolov3/yolov3_tf_bs1_fp16.cfg",
-                "labelPath": "./models/yolov3/coco.names",
-                "postProcessLibPath": "../../lib/modelpostprocessors/libyolov3postprocess.so"
-            },
-            "factory": "mxpi_objectpostprocessor",
-            "next": "mxpi_motsimplesort0"
-        },
-        "mxpi_motsimplesort0": {
-            "props": {
-                "dataSourceDetection": "mxpi_objectpostprocessor0"
-            },
-            "factory": "mxpi_motsimplesort",
-            "next": "mxpi_pluginoverstay0"
-        },
-        "mxpi_pluginoverstay0": {
-            "props": {
-                "dataSourceTrack": "mxpi_motsimplesort0",
- 	            "dataSourceDetection": "mxpi_objectpostprocessor0",
-                "stayThresh":"90",
-	            "frames":"90",
-	            "distanceThresh":"100",
-                "detectRatio":"0.7",
-                "detectSleep":"90"
-            },
-            "factory": "mxpi_pluginoverstay",
-            "next": "mxpi_dataserialize0"
-        },
-        "mxpi_dataserialize0": {
-            "props": {
-                "outputDataKeys": "mxpi_pluginoverstay0"
-            },
-            "factory": "mxpi_dataserialize",
-            "next": "appsink0"
-        },
-        "appsink0": {
-            "props": {
-                "blocksize": "4096000"
-            },
-            "factory": "appsink"
-        }
-    }
-}
+{
+    "detection+tracking": {
+        "stream_config": {
+            "deviceId": "0"
+        },
+        "mxpi_rtspsrc0": {
+            "props": {
+                "rtspUrl": "rtsp_Url"
+                },
+            "factory": "mxpi_rtspsrc",
+            "next": "mxpi_videodecoder0"
+        },
+        "mxpi_videodecoder0":{
+            "props": {
+                "vdecChannelId": "0"
+                },
+            "factory": "mxpi_videodecoder",
+            "next": "mxpi_imageresize0"
+        },
+        "mxpi_imageresize0":{            
+            "props": {
+                "dataSource": "mxpi_videodecoder0",
+                "resizeHeight": "416",
+                "resizeWidth": "416"
+            },
+            "factory": "mxpi_imageresize",
+            "next": "mxpi_tensorinfer0"
+        },
+        "mxpi_tensorinfer0":{
+            "props": {
+                "dataSource": "mxpi_imageresize0",
+                "modelPath": "./models/yolov3/yolov3_tf_bs1_fp16.om"
+            },
+            "factory": "mxpi_tensorinfer",
+            "next": "mxpi_objectpostprocessor0"
+        },
+        "mxpi_objectpostprocessor0": {
+            "props": {
+                "dataSource": "mxpi_tensorinfer0",
+                "funcLanguage":"c++",
+                "postProcessConfigPath": "./models/yolov3/yolov3_tf_bs1_fp16.cfg",
+                "labelPath": "./models/yolov3/coco.names",
+                "postProcessLibPath": "../../lib/modelpostprocessors/libyolov3postprocess.so"
+            },
+            "factory": "mxpi_objectpostprocessor",
+            "next": "mxpi_motsimplesort0"
+        },
+        "mxpi_motsimplesort0": {
+            "props": {
+                "dataSourceDetection": "mxpi_objectpostprocessor0"
+            },
+            "factory": "mxpi_motsimplesort",
+            "next": "mxpi_pluginoverstay0"
+        },
+        "mxpi_pluginoverstay0": {
+            "props": {
+                "dataSourceTrack": "mxpi_motsimplesort0",
+ 	            "dataSourceDetection": "mxpi_objectpostprocessor0",
+                "stayThresh":"90",
+	            "frames":"90",
+	            "distanceThresh":"100",
+                "detectRatio":"0.7",
+                "detectSleep":"90"
+            },
+            "factory": "mxpi_pluginoverstay",
+            "next": "mxpi_dataserialize0"
+        },
+        "mxpi_dataserialize0": {
+            "props": {
+                "outputDataKeys": "mxpi_pluginoverstay0"
+            },
+            "factory": "mxpi_dataserialize",
+            "next": "appsink0"
+        },
+        "appsink0": {
+            "props": {
+                "blocksize": "4096000"
+            },
+            "factory": "appsink"
+        }
+    }
+}
diff --git a/contrib/ActionRecognition/pipeline/plugin_violentaction.pipeline b/mxVision/mxVision-referenceapps/ActionRecognition/pipeline/plugin_violentaction.pipeline
similarity index 97%
rename from contrib/ActionRecognition/pipeline/plugin_violentaction.pipeline
rename to mxVision/mxVision-referenceapps/ActionRecognition/pipeline/plugin_violentaction.pipeline
index b95253140e72e72b86229d0f835f687021b0ccd3..9c8e75eef59db337cc4523a24f137e8c06d903c1 100644
--- a/contrib/ActionRecognition/pipeline/plugin_violentaction.pipeline
+++ b/mxVision/mxVision-referenceapps/ActionRecognition/pipeline/plugin_violentaction.pipeline
@@ -1,125 +1,125 @@
-{
-    "detection+action recognition": {
-        "stream_config": {
-            "deviceId": "0"
-        },
-        "mxpi_rtspsrc0": {
-            "props": {
-                "rtspUrl": "rtsp_Url"
-                },
-            "factory": "mxpi_rtspsrc",
-            "next": "mxpi_videodecoder0"
-        },
-        "mxpi_videodecoder0":{
-            "props": {
-                "vdecChannelId": "0"
-                },
-            "factory": "mxpi_videodecoder",
-            "next": "mxpi_imageresize0"
-        },
-        "mxpi_imageresize0":{            
-            "props": {
-                "dataSource": "mxpi_videodecoder0",
-                "resizeHeight": "416",
-                "resizeWidth": "416"
-            },
-            "factory": "mxpi_imageresize",
-            "next": "mxpi_tensorinfer0"
-        },
-        "mxpi_tensorinfer0":{
-            "props": {
-                "dataSource": "mxpi_imageresize0",
-                "modelPath": "./models/yolov3/yolov3_tf_bs1_fp16.om"
-                },
-            "factory": "mxpi_tensorinfer",
-             "next": "mxpi_objectpostprocessor0"
-        },
-        "mxpi_objectpostprocessor0": {
-            "props": {
-                "dataSource": "mxpi_tensorinfer0",
-                "funcLanguage":"c++",
-                "postProcessConfigPath": "./models/yolov3/yolov3_tf_bs1_fp16.cfg",
-                "labelPath": "./models/yolov3/coco.names",
-                "postProcessLibPath": "../../lib/modelpostprocessors/libyolov3postprocess.so"
-            },
-            "factory": "mxpi_objectpostprocessor",
-            "next": "mxpi_distributor0"
-        },
-        "mxpi_distributor0": {
-             "props": {
-                "dataSource": "mxpi_objectpostprocessor0",
-                "classIds": "0"
-            },
-            "factory": "mxpi_distributor",
-            "next": "mxpi_motsimplesort0"
-        },
-        "mxpi_motsimplesort0": {
-             "props": {
-                "dataSourceDetection": "mxpi_distributor0_0"
-            },
-            "factory": "mxpi_motsimplesort",
-            "next": "mxpi_imagecrop0"
-        },
-        "mxpi_imagecrop0": {
-            "props": {
-                "dataSource": "mxpi_distributor0_0",
-                "dataSourceImage": "mxpi_videodecoder0",
-                "resizeHeight": "224",
-                "resizeWidth": "224",
-                "resizeType": "Resizer_KeepAspectRatio_Fit"
-            },
-            "factory": "mxpi_imagecrop",
-            "next": "mxpi_stackframe0"
-        },
-        "mxpi_stackframe0":{
-            "props": {
-                "visionSource": "mxpi_imagecrop0",
-                "trackSource": "mxpi_motsimplesort0",
-                "frameNum": "3"
-                },
-            "factory": "mxpi_stackframe",
-            "next": "mxpi_tensorinfer1"
-        },
-        "mxpi_tensorinfer1":{
-            "props": {
-                "dataSource": "mxpi_stackframe0",
-                "skipModelCheck": "1",
-                "modelPath": "./models/ECONet/ECONet.om"
-                },
-            "factory": "mxpi_tensorinfer",
-            "next": "mxpi_classpostprocessor0"
-        },
-        "mxpi_classpostprocessor0":{
-            "props": {
-                "dataSource": "mxpi_tensorinfer1",
-                "postProcessConfigPath": "./models/ECONet/eco_post.cfg",
-                "labelPath": "./models/ECONet/ucf101.names",
-                "postProcessLibPath": "../../lib/modelpostprocessors/libresnet50postprocess.so"
-                },
-            "factory": "mxpi_classpostprocessor",
-            "next": "mxpi_violentaction0"
-       },
-       "mxpi_violentaction0":{
-            "props": {
-                "classSource": "mxpi_classpostprocessor0",
-                "filePath": "./data/roi/ViolentAction/aoi.txt",
-                "detectSleep": "5"
-                },
-            "factory": "mxpi_violentaction",
-            "next": "mxpi_dataserialize0"
-        },
-        "mxpi_dataserialize0": {
-            "props": {
-                "outputDataKeys": "mxpi_violentaction0"
-            },
-            "factory": "mxpi_dataserialize",
-            "next": "appsink0"
-        },
-        "appsink0": {
-            "props": {
-                "blocksize": "4096000"
-            },
-            "factory": "appsink"
-        }
-    }
-}
+{
+    "detection+action recognition": {
+        "stream_config": {
+            "deviceId": "0"
+        },
+        "mxpi_rtspsrc0": {
+            "props": {
+                "rtspUrl": "rtsp_Url"
+                },
+            "factory": "mxpi_rtspsrc",
+            "next": "mxpi_videodecoder0"
+        },
+        "mxpi_videodecoder0":{
+            "props": {
+                "vdecChannelId": "0"
+                },
+            "factory": "mxpi_videodecoder",
+            "next": "mxpi_imageresize0"
+        },
+        "mxpi_imageresize0":{            
+            "props": {
+                "dataSource": "mxpi_videodecoder0",
+                "resizeHeight": "416",
+                "resizeWidth": "416"
+            },
+            "factory": "mxpi_imageresize",
+            "next": "mxpi_tensorinfer0"
+        },
+        "mxpi_tensorinfer0":{
+            "props": {
+                "dataSource": "mxpi_imageresize0",
+                "modelPath": "./models/yolov3/yolov3_tf_bs1_fp16.om"
+                },
+            "factory": "mxpi_tensorinfer",
+             "next": "mxpi_objectpostprocessor0"
+        },
+        "mxpi_objectpostprocessor0": {
+            "props": {
+                "dataSource": "mxpi_tensorinfer0",
+                "funcLanguage":"c++",
+                "postProcessConfigPath": "./models/yolov3/yolov3_tf_bs1_fp16.cfg",
+                "labelPath": "./models/yolov3/coco.names",
+                "postProcessLibPath": "../../lib/modelpostprocessors/libyolov3postprocess.so"
+            },
+            "factory": "mxpi_objectpostprocessor",
+            "next": "mxpi_distributor0"
+        },
+        "mxpi_distributor0": {
+             "props": {
+                "dataSource": "mxpi_objectpostprocessor0",
+                "classIds": "0"
+            },
+            "factory": "mxpi_distributor",
+            "next": "mxpi_motsimplesort0"
+        },
+        "mxpi_motsimplesort0": {
+             "props": {
+                "dataSourceDetection": "mxpi_distributor0_0"
+            },
+            "factory": "mxpi_motsimplesort",
+            "next": "mxpi_imagecrop0"
+        },
+        "mxpi_imagecrop0": {
+            "props": {
+                "dataSource": "mxpi_distributor0_0",
+                "dataSourceImage": "mxpi_videodecoder0",
+                "resizeHeight": "224",
+                "resizeWidth": "224",
+                "resizeType": "Resizer_KeepAspectRatio_Fit"
+            },
+            "factory": "mxpi_imagecrop",
+            "next": "mxpi_stackframe0"
+        },
+        "mxpi_stackframe0":{
+            "props": {
+                "visionSource": "mxpi_imagecrop0",
+                "trackSource": "mxpi_motsimplesort0",
+                "frameNum": "3"
+                },
+            "factory": "mxpi_stackframe",
+            "next": "mxpi_tensorinfer1"
+        },
+        "mxpi_tensorinfer1":{
+            "props": {
+                "dataSource": "mxpi_stackframe0",
+                "skipModelCheck": "1",
+                "modelPath": "./models/ECONet/ECONet.om"
+                },
+            "factory": "mxpi_tensorinfer",
+            "next": "mxpi_classpostprocessor0"
+        },
+        "mxpi_classpostprocessor0":{
+            "props": {
+                "dataSource": "mxpi_tensorinfer1",
+                "postProcessConfigPath": "./models/ECONet/eco_post.cfg",
+                "labelPath": "./models/ECONet/ucf101.names",
+                "postProcessLibPath": "../../lib/modelpostprocessors/libresnet50postprocess.so"
+                },
+            "factory": "mxpi_classpostprocessor",
+            "next": "mxpi_violentaction0"
+       },
+       "mxpi_violentaction0":{
+            "props": {
+                "classSource": "mxpi_classpostprocessor0",
+                "filePath": "./data/roi/ViolentAction/aoi.txt",
+                "detectSleep": "5"
+                },
+            "factory": "mxpi_violentaction",
+            "next": "mxpi_dataserialize0"
+        },
+        "mxpi_dataserialize0": {
+            "props": {
+                "outputDataKeys": "mxpi_violentaction0"
+            },
+            "factory": "mxpi_dataserialize",
+            "next": "appsink0"
+        },
+        "appsink0": {
+            "props": {
+                "blocksize": "4096000"
+            },
+            "factory": "appsink"
+        }
+    }
+}
diff --git a/contrib/ActionRecognition/plugins/MxpiStackFrame/BlockingMap.cpp b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/MxpiStackFrame/BlockingMap.cpp
similarity index 97%
rename from contrib/ActionRecognition/plugins/MxpiStackFrame/BlockingMap.cpp
rename to mxVision/mxVision-referenceapps/ActionRecognition/plugins/MxpiStackFrame/BlockingMap.cpp
index 7b44f51e92a7438ef9860078722275c551441586..94ba48b231ddab5e3358abae60d56867e6a3a8cc 100644
--- a/contrib/ActionRecognition/plugins/MxpiStackFrame/BlockingMap.cpp
+++ b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/MxpiStackFrame/BlockingMap.cpp
@@ -1,138 +1,138 @@
-/*
- * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#include "BlockingMap.h"
-
-namespace MxPlugins {
-    BlockingMap::BlockingMap() {}
-
-    BlockingMap::~BlockingMap() {}
-
-    void BlockingMap::Insert(const uint32_t &id, MxBase::MemoryData newData) {
-        // add std::lock_guard
-        std::lock_guard<std::mutex> guard(mtx_);
-        // get current timestamp
-        using Time = std::chrono::high_resolution_clock;
-        auto currentTime = Time::now();
-        std::pair<std::chrono::high_resolution_clock::time_point,
-                std::shared_ptr<MxTools::MxpiVisionList>> time_MxpiVisionList;
-        // set MxpiVisionInfo and MxpiVisionData
-        auto mxpiVisionList = copyList(newData);
-        time_MxpiVisionList = std::make_pair(currentTime, mxpiVisionList);
-        blockingMap_[id] = time_MxpiVisionList;
-        keys_.insert(id);
-    }
-
-    void BlockingMap::Update(const uint32_t &id, MxBase::MemoryData newData) {
-        // add std::lock_guard
-        std::lock_guard<std::mutex> guard(mtx_);
-        std::pair<std::chrono::high_resolution_clock::time_point, std::shared_ptr<MxTools::MxpiVisionList>>
-                time_MxpiVisionList = blockingMap_[id];
-        auto mxpiVisionList = time_MxpiVisionList.second;
-        // set MxpiVisionInfo and MxpiVisionData
-        MxTools::MxpiVision *dstMxpivision = mxpiVisionList->add_visionvec();
-        MxTools::MxpiVisionInfo *mxpiVisionInfo = dstMxpivision->mutable_visioninfo();
-        mxpiVisionInfo->set_format(1);
-        mxpiVisionInfo->set_height(224);
-        mxpiVisionInfo->set_width(224);
-        mxpiVisionInfo->set_heightaligned(224);
-        mxpiVisionInfo->set_widthaligned(224);
-        // set MxpiVisionData by MemoryData
-        MxTools::MxpiVisionData *mxpiVisionData = dstMxpivision->mutable_visiondata();
-        mxpiVisionData->set_dataptr((uint64_t) newData.ptrData);
-        mxpiVisionData->set_datasize(newData.size);
-        mxpiVisionData->set_deviceid(newData.deviceId);
-        mxpiVisionData->set_memtype((MxTools::MxpiMemoryType) newData.type);
-        // visionlist->pair
-        time_MxpiVisionList = std::make_pair(time_MxpiVisionList.first, mxpiVisionList);
-        blockingMap_[id] = time_MxpiVisionList;
-    }
-
-    std::pair<std::chrono::high_resolution_clock::time_point, std::shared_ptr<MxTools::MxpiVisionList>>
-    BlockingMap::Get(const uint32_t &id) {
-        // add std::lock_guard
-        std::lock_guard<std::mutex> guard(mtx_);
-        if (blockingMap_.find(id) != blockingMap_.end()) {
-            return blockingMap_[id];
-        } else {
-            // If can't find the element, manually assign nullptr
-            std::pair<std::chrono::high_resolution_clock::time_point, std::shared_ptr<MxTools::MxpiVisionList>> empty;
-            using Time = std::chrono::high_resolution_clock;
-            auto currentTime = Time::now();
-            empty = std::make_pair(currentTime, nullptr);
-            return empty;
-        }
-    }
-
-    void BlockingMap::Clear(const uint32_t &id) {
-        std::lock_guard<std::mutex> guard(mtx_);
-        blockingMap_.erase(id);
-        keys_.erase(id);
-    }
-
-    void BlockingMap::Reinsert(const uint32_t &id, std::shared_ptr<MxTools::MxpiVisionList> &mxpiVisionList) {
-        // add std::lock_guard
-        std::lock_guard<std::mutex> guard(mtx_);
-        // get current timestamp
-        using Time = std::chrono::high_resolution_clock;
-        auto currentTime = Time::now();
-        std::pair<std::chrono::high_resolution_clock::time_point,
-                std::shared_ptr<MxTools::MxpiVisionList>> time_MxpiVisionList;
-        // set MxpiVisionInfo and MxpiVisionData
-        time_MxpiVisionList = std::make_pair(currentTime, mxpiVisionList);
-        blockingMap_[id] = time_MxpiVisionList;
-        keys_.insert(id);
-    }
-
-    std::uint32_t BlockingMap::count(const uint32_t &id) {
-        std::lock_guard<std::mutex> guard(mtx_);
-        return blockingMap_.count(id);
-    }
-
-    size_t BlockingMap::Size() const {
-        return blockingMap_.size();
-    }
-
-    std::vector<uint32_t> BlockingMap::Keys() {
-        // id<->key
-        std::vector<uint32_t> keys;
-        std::lock_guard<std::mutex> guard(mtx_);
-        for (auto iter = keys_.begin(); iter != keys_.end(); iter++) {
-            keys.push_back(*iter);
-        }
-        return keys;
-    }
-
-    std::shared_ptr<MxTools::MxpiVisionList> BlockingMap::copyList(MxBase::MemoryData newData) {
-        // new shared_ptr MxpiVisionList;
-        std::shared_ptr<MxTools::MxpiVisionList> dstMxpiVisionListSptr(new MxTools::MxpiVisionList,
-                                                                       MxTools::g_deleteFuncMxpiVisionList);
-        MxTools::MxpiVision *dstMxpivision = dstMxpiVisionListSptr->add_visionvec();
-        MxTools::MxpiVisionInfo *mxpiVisionInfo = dstMxpivision->mutable_visioninfo();
-        mxpiVisionInfo->set_format(1);
-        mxpiVisionInfo->set_height(224);
-        mxpiVisionInfo->set_width(224);
-        mxpiVisionInfo->set_heightaligned(224);
-        mxpiVisionInfo->set_widthaligned(224);
-        // set MxpiVisionData by MemoryData
-        MxTools::MxpiVisionData *mxpiVisionData = dstMxpivision->mutable_visiondata();
-        mxpiVisionData->set_dataptr((uint64_t) newData.ptrData);
-        mxpiVisionData->set_datasize(newData.size);
-        mxpiVisionData->set_deviceid(newData.deviceId);
-        mxpiVisionData->set_memtype((MxTools::MxpiMemoryType) newData.type);
-        return dstMxpiVisionListSptr;
-    }
+/*
+ * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "BlockingMap.h"
+
+namespace MxPlugins {
+    BlockingMap::BlockingMap() {}
+
+    BlockingMap::~BlockingMap() {}
+
+    void BlockingMap::Insert(const uint32_t &id, MxBase::MemoryData newData) {
+        // add std::lock_guard
+        std::lock_guard<std::mutex> guard(mtx_);
+        // get current timestamp
+        using Time = std::chrono::high_resolution_clock;
+        auto currentTime = Time::now();
+        std::pair<std::chrono::high_resolution_clock::time_point,
+                std::shared_ptr<MxTools::MxpiVisionList>> time_MxpiVisionList;
+        // set MxpiVisionInfo and MxpiVisionData
+        auto mxpiVisionList = copyList(newData);
+        time_MxpiVisionList = std::make_pair(currentTime, mxpiVisionList);
+        blockingMap_[id] = time_MxpiVisionList;
+        keys_.insert(id);
+    }
+
+    void BlockingMap::Update(const uint32_t &id, MxBase::MemoryData newData) {
+        // add std::lock_guard
+        std::lock_guard<std::mutex> guard(mtx_);
+        std::pair<std::chrono::high_resolution_clock::time_point, std::shared_ptr<MxTools::MxpiVisionList>>
+                time_MxpiVisionList = blockingMap_[id];
+        auto mxpiVisionList = time_MxpiVisionList.second;
+        // set MxpiVisionInfo and MxpiVisionData
+        MxTools::MxpiVision *dstMxpivision = mxpiVisionList->add_visionvec();
+        MxTools::MxpiVisionInfo *mxpiVisionInfo = dstMxpivision->mutable_visioninfo();
+        mxpiVisionInfo->set_format(1);
+        mxpiVisionInfo->set_height(224);
+        mxpiVisionInfo->set_width(224);
+        mxpiVisionInfo->set_heightaligned(224);
+        mxpiVisionInfo->set_widthaligned(224);
+        // set MxpiVisionData by MemoryData
+        MxTools::MxpiVisionData *mxpiVisionData = dstMxpivision->mutable_visiondata();
+        mxpiVisionData->set_dataptr((uint64_t) newData.ptrData);
+        mxpiVisionData->set_datasize(newData.size);
+        mxpiVisionData->set_deviceid(newData.deviceId);
+        mxpiVisionData->set_memtype((MxTools::MxpiMemoryType) newData.type);
+        // visionlist->pair
+        time_MxpiVisionList = std::make_pair(time_MxpiVisionList.first, mxpiVisionList);
+        blockingMap_[id] = time_MxpiVisionList;
+    }
+
+    std::pair<std::chrono::high_resolution_clock::time_point, std::shared_ptr<MxTools::MxpiVisionList>>
+    BlockingMap::Get(const uint32_t &id) {
+        // add std::lock_guard
+        std::lock_guard<std::mutex> guard(mtx_);
+        if (blockingMap_.find(id) != blockingMap_.end()) {
+            return blockingMap_[id];
+        } else {
+            // If can't find the element, manually assign nullptr
+            std::pair<std::chrono::high_resolution_clock::time_point, std::shared_ptr<MxTools::MxpiVisionList>> empty;
+            using Time = std::chrono::high_resolution_clock;
+            auto currentTime = Time::now();
+            empty = std::make_pair(currentTime, nullptr);
+            return empty;
+        }
+    }
+
+    void BlockingMap::Clear(const uint32_t &id) {
+        std::lock_guard<std::mutex> guard(mtx_);
+        blockingMap_.erase(id);
+        keys_.erase(id);
+    }
+
+    void BlockingMap::Reinsert(const uint32_t &id, std::shared_ptr<MxTools::MxpiVisionList> &mxpiVisionList) {
+        // add std::lock_guard
+        std::lock_guard<std::mutex> guard(mtx_);
+        // get current timestamp
+        using Time = std::chrono::high_resolution_clock;
+        auto currentTime = Time::now();
+        std::pair<std::chrono::high_resolution_clock::time_point,
+                std::shared_ptr<MxTools::MxpiVisionList>> time_MxpiVisionList;
+        // set MxpiVisionInfo and MxpiVisionData
+        time_MxpiVisionList = std::make_pair(currentTime, mxpiVisionList);
+        blockingMap_[id] = time_MxpiVisionList;
+        keys_.insert(id);
+    }
+
+    std::uint32_t BlockingMap::count(const uint32_t &id) {
+        std::lock_guard<std::mutex> guard(mtx_);
+        return blockingMap_.count(id);
+    }
+
+    size_t BlockingMap::Size() const {
+        return blockingMap_.size();
+    }
+
+    std::vector<uint32_t> BlockingMap::Keys() {
+        // id<->key
+        std::vector<uint32_t> keys;
+        std::lock_guard<std::mutex> guard(mtx_);
+        for (auto iter = keys_.begin(); iter != keys_.end(); iter++) {
+            keys.push_back(*iter);
+        }
+        return keys;
+    }
+
+    std::shared_ptr<MxTools::MxpiVisionList> BlockingMap::copyList(MxBase::MemoryData newData) {
+        // new shared_ptr MxpiVisionList;
+        std::shared_ptr<MxTools::MxpiVisionList> dstMxpiVisionListSptr(new MxTools::MxpiVisionList,
+                                                                       MxTools::g_deleteFuncMxpiVisionList);
+        MxTools::MxpiVision *dstMxpivision = dstMxpiVisionListSptr->add_visionvec();
+        MxTools::MxpiVisionInfo *mxpiVisionInfo = dstMxpivision->mutable_visioninfo();
+        mxpiVisionInfo->set_format(1);
+        mxpiVisionInfo->set_height(224);
+        mxpiVisionInfo->set_width(224);
+        mxpiVisionInfo->set_heightaligned(224);
+        mxpiVisionInfo->set_widthaligned(224);
+        // set MxpiVisionData by MemoryData
+        MxTools::MxpiVisionData *mxpiVisionData = dstMxpivision->mutable_visiondata();
+        mxpiVisionData->set_dataptr((uint64_t) newData.ptrData);
+        mxpiVisionData->set_datasize(newData.size);
+        mxpiVisionData->set_deviceid(newData.deviceId);
+        mxpiVisionData->set_memtype((MxTools::MxpiMemoryType) newData.type);
+        return dstMxpiVisionListSptr;
+    }
 }
\ No newline at end of file
diff --git a/contrib/ActionRecognition/plugins/MxpiStackFrame/BlockingMap.h b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/MxpiStackFrame/BlockingMap.h
similarity index 97%
rename from contrib/ActionRecognition/plugins/MxpiStackFrame/BlockingMap.h
rename to mxVision/mxVision-referenceapps/ActionRecognition/plugins/MxpiStackFrame/BlockingMap.h
index afca5a48da14f7b3e8f2fb8efad27db7a162ab08..6d0c81fc16998e326f7454f7c2d9020a7184c08a 100644
--- a/contrib/ActionRecognition/plugins/MxpiStackFrame/BlockingMap.h
+++ b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/MxpiStackFrame/BlockingMap.h
@@ -1,84 +1,84 @@
-/*
- * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#ifndef INC_FACE_BLOCKING_MAP_H
-#define INC_FACE_BLOCKING_MAP_H
-
-#include <map>
-#include <set>
-#include <iostream>
-#include <mutex>
-#include <thread>
-#include <chrono>
-#include <string>
-#include "MxBase/Tensor/TensorBase/TensorBase.h"
-#include "MxBase/Log/Log.h"
-#include "MxBase/MemoryHelper/MemoryHelper.h"
-#include "MxStream/StreamManager/MxStreamManager.h"
-#include "MxTools/Proto/MxpiDataType.pb.h"
-#include "MxTools/Proto/MxpiDataTypeDeleter.h"
-
-/**
- * This is a thread safe map. All functions use std::lock_guard<std::mutex>.
-*/
-
-namespace MxPlugins {
-    class BlockingMap {
-    public:
-        /**
-         * @api
-         * @brief Initialize a new mxpivisionlist for this id, and
-         * insert the visiondata passed from upstream into the mxpivisionlist.
-         * @param trackID, MemoryData
-         */
-        void Insert(const uint32_t &id, const MxBase::MemoryData newData);
-
-        /**
-         * @api
-         * @brief Update mxpivisionlist and insert the visiondata for this id.
-         * @param trackID, MemoryData
-         */
-        void Update(const uint32_t &id, const MxBase::MemoryData newData);
-
-        /**
-         * @api
-         * @brief Reinsert mxpivisionlist and timestamp for this id.
-         * @param trackID, MxpivisionList
-         */
-        void Reinsert(const uint32_t &id, std::shared_ptr<MxTools::MxpiVisionList> &mxpiVisionList);
-
-        std::pair<std::chrono::high_resolution_clock::time_point, std::shared_ptr<MxTools::MxpiVisionList>>
-        Get(const uint32_t &id);  // get std::pair instance
-        void Clear(const uint32_t &id);  // erase map and id
-        std::vector<uint32_t> Keys(); // save tackId into keys set
-        size_t Size() const;
-
-        std::uint32_t count(const uint32_t &id);   // return the number of elements of this id
-        std::shared_ptr<MxTools::MxpiVisionList>
-        copyList(const MxBase::MemoryData newData);     // set MxpiVisionInfo and MxpiVisionData
-        BlockingMap();
-
-        ~BlockingMap();
-
-    private:
-        std::mutex mtx_ = {};
-        std::map<uint32_t, std::pair<std::chrono::high_resolution_clock::time_point,
-                std::shared_ptr<MxTools::MxpiVisionList>>> blockingMap_ = {};
-        std::set<uint32_t> keys_ = {};
-    };
-}
-#endif
-
+/*
+ * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef INC_FACE_BLOCKING_MAP_H
+#define INC_FACE_BLOCKING_MAP_H
+
+#include <map>
+#include <set>
+#include <iostream>
+#include <mutex>
+#include <thread>
+#include <chrono>
+#include <string>
+#include "MxBase/Tensor/TensorBase/TensorBase.h"
+#include "MxBase/Log/Log.h"
+#include "MxBase/MemoryHelper/MemoryHelper.h"
+#include "MxStream/StreamManager/MxStreamManager.h"
+#include "MxTools/Proto/MxpiDataType.pb.h"
+#include "MxTools/Proto/MxpiDataTypeDeleter.h"
+
+/**
+ * This is a thread safe map. All functions use std::lock_guard<std::mutex>.
+*/
+
+namespace MxPlugins {
+    class BlockingMap {
+    public:
+        /**
+         * @api
+         * @brief Initialize a new mxpivisionlist for this id, and
+         * insert the visiondata passed from upstream into the mxpivisionlist.
+         * @param trackID, MemoryData
+         */
+        void Insert(const uint32_t &id, const MxBase::MemoryData newData);
+
+        /**
+         * @api
+         * @brief Update mxpivisionlist and insert the visiondata for this id.
+         * @param trackID, MemoryData
+         */
+        void Update(const uint32_t &id, const MxBase::MemoryData newData);
+
+        /**
+         * @api
+         * @brief Reinsert mxpivisionlist and timestamp for this id.
+         * @param trackID, MxpivisionList
+         */
+        void Reinsert(const uint32_t &id, std::shared_ptr<MxTools::MxpiVisionList> &mxpiVisionList);
+
+        std::pair<std::chrono::high_resolution_clock::time_point, std::shared_ptr<MxTools::MxpiVisionList>>
+        Get(const uint32_t &id);  // get std::pair instance
+        void Clear(const uint32_t &id);  // erase map and id
+        std::vector<uint32_t> Keys(); // save tackId into keys set
+        size_t Size() const;
+
+        std::uint32_t count(const uint32_t &id);   // return the number of elements of this id
+        std::shared_ptr<MxTools::MxpiVisionList>
+        copyList(const MxBase::MemoryData newData);     // set MxpiVisionInfo and MxpiVisionData
+        BlockingMap();
+
+        ~BlockingMap();
+
+    private:
+        std::mutex mtx_ = {};
+        std::map<uint32_t, std::pair<std::chrono::high_resolution_clock::time_point,
+                std::shared_ptr<MxTools::MxpiVisionList>>> blockingMap_ = {};
+        std::set<uint32_t> keys_ = {};
+    };
+}
+#endif
+
diff --git a/contrib/ActionRecognition/plugins/MxpiStackFrame/CMakeLists.txt b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/MxpiStackFrame/CMakeLists.txt
similarity index 100%
rename from contrib/ActionRecognition/plugins/MxpiStackFrame/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/ActionRecognition/plugins/MxpiStackFrame/CMakeLists.txt
diff --git a/contrib/ActionRecognition/plugins/MxpiStackFrame/MxpiStackFrame.cpp b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/MxpiStackFrame/MxpiStackFrame.cpp
similarity index 97%
rename from contrib/ActionRecognition/plugins/MxpiStackFrame/MxpiStackFrame.cpp
rename to mxVision/mxVision-referenceapps/ActionRecognition/plugins/MxpiStackFrame/MxpiStackFrame.cpp
index 5a50a45d5c508bc6df1bc9d586045618b128aa2b..0667e5568611592fdeacbdf2a227edd0b7f80e76 100644
--- a/contrib/ActionRecognition/plugins/MxpiStackFrame/MxpiStackFrame.cpp
+++ b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/MxpiStackFrame/MxpiStackFrame.cpp
@@ -1,381 +1,381 @@
-/*
- * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#include "MxpiStackFrame.h"
-
-using namespace MxBase;
-using namespace MxTools;
-using namespace MxPlugins;
-using namespace std;
-
-namespace {
-    bool isStop_ = true;
-    std::shared_ptr<BlockingMap> ObjectFrame = std::make_shared<BlockingMap>();
-}
-
-APP_ERROR MxpiStackFrame::Init(std::map<std::string, std::shared_ptr<void>> &configParamMap) {
-    LogInfo << "Begin to initialize MxpiStackFrame(" << pluginName_ << ").";
-    std::shared_ptr<std::string> visionSource = std::static_pointer_cast<std::string>(configParamMap["visionSource"]);
-    visionsource_ = *visionSource;
-
-    std::shared_ptr<std::string> trackSource = std::static_pointer_cast<std::string>(configParamMap["trackSource"]);
-    tracksource_ = *trackSource;
-
-    std::shared_ptr<std::uint32_t> framenum = std::static_pointer_cast<std::uint32_t>(configParamMap["frameNum"]);
-    skipFrameNum_ = *framenum;
-
-    std::shared_ptr<std::double_t> timeout = std::static_pointer_cast<double_t>(configParamMap["timeOut"]);
-    timeout_ = *timeout;
-
-    std::shared_ptr<std::uint32_t> sleeptime = std::static_pointer_cast<uint32_t>(configParamMap["sleepTime"]);
-    sleepTime_ = *sleeptime;
-
-    isStop_ = false;
-    // crate CheckFrame thread in Init function
-    CreateThread();
-    LogInfo << "End to initialize MxpiStackFrame(" << pluginName_ << ").";
-    return APP_ERR_OK;
-}
-
-APP_ERROR MxpiStackFrame::DeInit() {
-    LogInfo << "Begin to deinitialize MxpiStackFrame(" << pluginName_ << ").";
-    // Block the current thread until the thread identified by *this ends its execution
-    stopFlag_ = true;
-    if (thread_->joinable()) {
-        thread_->join();
-    }
-    ObjectFrame.reset();
-    LogInfo << "End to deinitialize MxpiStackFrame(" << pluginName_ << ").";
-    return APP_ERR_OK;
-}
-
-APP_ERROR MxpiStackFrame::CheckDataSource(MxTools::MxpiMetadataManager &mxpiMetadataManager) {
-    if (mxpiMetadataManager.GetMetadata(visionsource_) == nullptr) {
-        LogDebug << GetError(APP_ERR_METADATA_IS_NULL, pluginName_)
-                 << "vision metadata is null. please check"
-                 << "Your property visionSource(" << visionsource_ << ").";
-        return APP_ERR_METADATA_IS_NULL;
-    }
-    if (mxpiMetadataManager.GetMetadata(tracksource_) == nullptr) {
-        LogDebug << GetError(APP_ERR_METADATA_IS_NULL, pluginName_)
-                 << "track metadata is null. please check"
-                 << "Your property dataSourceFeature(" << tracksource_ << ").";
-        return APP_ERR_METADATA_IS_NULL;
-    }
-    return APP_ERR_OK;
-}
-
-void MxpiStackFrame::StackFrame(const std::shared_ptr<MxTools::MxpiVisionList> &visionList,
-                                const std::shared_ptr<MxTools::MxpiTrackLetList> &trackLetList,
-                                std::shared_ptr<BlockingMap> &blockingMap) {
-    for (int32_t i = 0; i < (int32_t) trackLetList->trackletvec_size(); i++) {
-        auto &trackObject = trackLetList->trackletvec(i);
-        uint32_t trackId = trackObject.trackid();
-        // lost object has no header vector; no object ;
-        if (trackObject.headervec_size() == 0 || visionList->visionvec_size() == 0) {
-            continue;
-        }
-        // get the visionvec by memberid
-        int32_t memberId = trackObject.headervec(0).memberid();
-        // filter out images not cropped
-        int32_t j = 0;
-        for (; j < visionList->visionvec_size(); j++) {
-            int32_t visionMemberId = visionList->visionvec(j).headervec(0).memberid();
-            if (visionMemberId == memberId) {
-                break;
-            }
-        }
-        if (j >= visionList->visionvec_size()) {
-            continue;
-        }
-        auto vision = visionList->visionvec(memberId);
-        // convert visiondata to memorydata
-        MxBase::MemoryData memoryData = ConvertMemoryData(vision.visiondata());
-        // add the vision to the blockingMap by trackId
-        if (blockingMap->count(trackId) == 0) {
-            // Initialize a new Mxpivisionlist
-            blockingMap->Insert(trackId, memoryData);
-        } else {
-            auto time_visionlist = blockingMap->Get(trackId);
-            LogInfo << "time_visionlist.second->visionvec_size() " << time_visionlist.second->visionvec_size();
-            if (time_visionlist.second->visionvec_size() >= 8) {
-                continue;
-            } else {
-                blockingMap->Update(trackId, memoryData);
-            }
-        }
-    }
-    visionList->clear_visionvec();
-}
-
-void MxpiStackFrame::CreateThread() {
-    thread_.reset(new std::thread(&MxpiStackFrame::WatchThread, this));
-}
-
-void MxpiStackFrame::WatchThread() {
-    // set current device context ; same as deviceId in pipeline
-    DeviceContext context = {};
-    context.devId = 0;
-    APP_ERROR ret = DeviceManager::GetInstance()->SetDevice(context);
-    if (ret != APP_ERR_OK) {
-        LogError << "SetDevice failed";
-    }
-    while (!stopFlag_) {
-        std::this_thread::sleep_for(std::chrono::milliseconds(sleepTime_));
-        CheckFrames(ObjectFrame);
-    }
-}
-
-std::shared_ptr<MxpiTensorPackageList> MxpiStackFrame::ConvertVisionList2TensorPackageList(
-        std::shared_ptr<MxpiVisionList> &mxpiVisionList) {
-    // use make_shared with caution
-    std::shared_ptr<MxpiTensorPackageList> tensorPackageList(new MxpiTensorPackageList,
-                                                             g_deleteFuncMxpiTensorPackageList);
-    MxBase::MemoryData concatData = {};
-    concatData.deviceId = mxpiVisionList->visionvec(0).visiondata().deviceid();
-    concatData.type = (MxBase::MemoryData::MemoryType) 1;
-    concatData.size =
-            mxpiVisionList->visionvec_size() * (uint32_t) mxpiVisionList->visionvec(0).visiondata().datasize();
-    // malloc new memory
-    APP_ERROR ret = MxBase::MemoryHelper::MxbsMalloc(concatData);
-    if (ret != APP_ERR_OK) {
-        LogError << "MxbsMalloc failed";
-        LogError << "concatData.size:" << concatData.size << " concatData.type:" << concatData.type
-                 << "concatData.deviceId:" << concatData.deviceId;
-        return tensorPackageList;
-    }
-    for (int i = 0; i < mxpiVisionList->visionvec_size(); i++) {
-        MxBase::MemoryData memoryData = ConvertMemoryData(mxpiVisionList->visionvec(i).visiondata());
-        // memory copy
-        MxBase::MemoryData newData = {};
-        newData.deviceId = mxpiVisionList->visionvec(i).visiondata().deviceid();
-        newData.type = (MxBase::MemoryData::MemoryType) 1;
-        newData.size = (uint32_t) mxpiVisionList->visionvec(i).visiondata().datasize();
-        newData.ptrData = (void *) ((uint8_t *) concatData.ptrData + i * newData.size);
-        // MxbsMallocAndCopy cannot be used here, cause npu memory leak
-        ret = MxBase::MemoryHelper::MxbsMemcpy(newData, memoryData, memoryData.size);
-        if (ret != APP_ERR_OK) {
-            LogError << "MxbsMemcpy failed";
-            MxBase::MemoryHelper::Free(concatData);
-            return tensorPackageList;
-        }
-    }
-    auto tensorPackage = tensorPackageList->add_tensorpackagevec();
-    auto tensorVector = tensorPackage->add_tensorvec();
-    tensorVector->set_tensordataptr((uint64) concatData.ptrData);
-    tensorVector->set_tensordatasize(concatData.size);
-    tensorVector->set_deviceid(concatData.deviceId);
-    tensorVector->set_memtype((MxpiMemoryType) concatData.type);
-    // explicitly specify tenspr shape
-    tensorVector->add_tensorshape(8);
-    tensorVector->add_tensorshape(224);
-    tensorVector->add_tensorshape(224);
-    tensorVector->add_tensorshape(3);
-    return tensorPackageList;
-}
-
-void MxpiStackFrame::CheckFrames(std::shared_ptr<BlockingMap> &blockingMap) {
-    // Get current timestamp
-    LogInfo << "Begin to check frames";
-    using Time = std::chrono::high_resolution_clock;
-    using Duration = std::chrono::duration<float>;
-    using Millisecond = std::chrono::duration<double, std::ratio<1, 1000>>;
-    auto currentTime = Time::now();
-    std::vector<uint32_t> keys = blockingMap->Keys();
-    for (uint32_t key : keys) {            // key <-> trackId
-        auto TimeMxpiVisionList = blockingMap->Get(key);
-        if (TimeMxpiVisionList.second == nullptr) {
-            continue;
-        }
-        Duration duration = currentTime - TimeMxpiVisionList.first;
-        double lastTime = std::chrono::duration_cast<Millisecond>(duration).count();
-        if (lastTime > timeout_) {
-            LogInfo << "Object:" << key << " is TimeOut";
-            blockingMap->Clear(key);
-            continue;
-        }
-        if (TimeMxpiVisionList.second->visionvec_size() == 8) {
-            // Add MxpiTensorPackageList to metadata and Send data to downstream plugin
-            const string metaKey = pluginName_;
-            auto dstMxpiVisionLitsSptr = TimeMxpiVisionList.second;
-            auto tensorPackageListPtr = ConvertVisionList2TensorPackageList(dstMxpiVisionLitsSptr);
-            blockingMap->Clear(key);
-            // sliding window
-            std::vector<MxTools::MxpiVisionData> slidingWindow = {};
-            uint32_t size = dstMxpiVisionLitsSptr->visionvec_size();
-            for (uint32_t i = 0; i < size; i++) {
-                auto mxpiVision = dstMxpiVisionLitsSptr->visionvec(i);
-                auto mxpiVisionData = mxpiVision.visiondata();
-                if (i < size / 2) {
-                    MxBase::MemoryData memoryData = ConvertMemoryData(mxpiVisionData);
-                    APP_ERROR ret = MemoryHelper::MxbsFree(memoryData);
-                    if (ret != APP_ERR_OK) {
-                        LogError << "MxbsFree failed";
-                    }
-                } else {
-                    slidingWindow.emplace_back(mxpiVisionData);
-                }
-            }
-            dstMxpiVisionLitsSptr->clear_visionvec();
-            auto mxpiVisionList = ConstructMxpiVisionList(slidingWindow);
-            blockingMap->Reinsert(key, mxpiVisionList);
-            // CreateDeviceBuffer; need inputParam
-            auto *outbuffer = MxpiBufferManager::CreateHostBuffer(inputParam);
-            MxpiMetadataManager mxpiMetadataManager(*outbuffer);
-            auto ret = mxpiMetadataManager.AddProtoMetadata(metaKey,
-                                                            static_pointer_cast<void>(tensorPackageListPtr));
-            if (ret != APP_ERR_OK) {
-                LogError << ErrorInfo_.str();
-                SendMxpiErrorInfo(*outbuffer, pluginName_, ret, ErrorInfo_.str());
-                SendData(0, *outbuffer);
-            }
-            LogInfo << "Object:" << key << " has stacked enough frames and begin to send data to downstream plugin";
-            SendData(0, *outbuffer);
-        }
-    }
-}
-
-std::shared_ptr<MxTools::MxpiVisionList> MxpiStackFrame::ConstructMxpiVisionList(
-        std::vector<MxTools::MxpiVisionData> &slidingWindow) {
-    std::shared_ptr<MxTools::MxpiVisionList> dstMxpiVisionListSptr(new MxTools::MxpiVisionList,
-                                                                   MxTools::g_deleteFuncMxpiVisionList);
-    for (auto iter = slidingWindow.begin(); iter != slidingWindow.end(); iter++) {
-        MxTools::MxpiVision *dstMxpivision = dstMxpiVisionListSptr->add_visionvec();
-        MxTools::MxpiVisionInfo *mxpiVisionInfo = dstMxpivision->mutable_visioninfo();
-        mxpiVisionInfo->set_format(1);
-        mxpiVisionInfo->set_height(224);
-        mxpiVisionInfo->set_width(224);
-        mxpiVisionInfo->set_heightaligned(224);
-        mxpiVisionInfo->set_widthaligned(224);
-        // set MxpiVisionData by MemoryData
-        MxTools::MxpiVisionData *mxpiVisionData = dstMxpivision->mutable_visiondata();
-        mxpiVisionData->set_dataptr((uint64_t) iter->dataptr());
-        mxpiVisionData->set_datasize(iter->datasize());
-        mxpiVisionData->set_deviceid(iter->deviceid());
-        mxpiVisionData->set_memtype(iter->memtype());
-    }
-    return dstMxpiVisionListSptr;
-}
-
-MxBase::MemoryData MxpiStackFrame::ConvertMemoryData(const MxTools::MxpiVisionData &mxpiVisionData) {
-    MxBase::MemoryData memoryData = {};
-    memoryData.deviceId = mxpiVisionData.deviceid();
-    memoryData.type = (MxBase::MemoryData::MemoryType) 1;
-    memoryData.size = (uint32_t) mxpiVisionData.datasize();
-    memoryData.ptrData = (void *) mxpiVisionData.dataptr();
-    return memoryData;
-}
-
-APP_ERROR MxpiStackFrame::Process(std::vector<MxpiBuffer *> &mxpiBuffer) {
-    LogInfo << "Begin to process MxpiStackFrame(" << elementName_ << ").";
-    // Get MxpiVisionList and MxpiTrackletList from mxpibuffer
-    MxpiBuffer *inputMxpiBuffer = mxpiBuffer[0];
-    MxpiMetadataManager mxpiMetadataManager(*inputMxpiBuffer);
-    ErrorInfo_.str("");
-    // check data source
-    APP_ERROR ret = CheckDataSource(mxpiMetadataManager);
-    if (ret != APP_ERR_OK) {
-        SendData(0, *inputMxpiBuffer);
-        return ret;
-    }
-    // Get metadata by key
-    std::shared_ptr<void> vision_metadata = mxpiMetadataManager.GetMetadata(visionsource_);
-    std::shared_ptr<MxpiVisionList> srcVisionListPtr = std::static_pointer_cast<MxpiVisionList>(vision_metadata);
-    std::shared_ptr<void> track_metadata = mxpiMetadataManager.GetMetadata(tracksource_);
-    std::shared_ptr<MxpiTrackLetList> srcTrackLetListPtr = std::static_pointer_cast<MxpiTrackLetList>(track_metadata);
-    // Stacking frames by track ID ; Choose skipFrameNum_ to skip frame
-    // DestroyBuffer (Get buffer to Host if needed)
-    if (count % skipFrameNum_ == 0) {
-        count = 1;
-        LogInfo << "Begin to stack frames";
-        StackFrame(srcVisionListPtr, srcTrackLetListPtr, ObjectFrame);
-        MxpiBufferManager::DestroyBuffer(inputMxpiBuffer);
-    } else {
-        count++;
-        MxpiBufferManager::DestroyBuffer(inputMxpiBuffer);
-    }
-    LogInfo << "End to process MxpiStackFrame(" << elementName_ << ").";
-    return APP_ERR_OK;
-}
-
-std::vector<std::shared_ptr<void>> MxpiStackFrame::DefineProperties() {
-    std::vector<std::shared_ptr<void>> properties;
-    // the cropped image
-    auto visionsource = std::make_shared<ElementProperty<string>>(ElementProperty<string>{
-            STRING,
-            "visionSource",
-            "imageSource",
-            "the name of cropped image source",
-            "default", "NULL", "NULL"
-    });
-    // the tracklet information
-    auto tracksource = std::make_shared<ElementProperty<string>>(ElementProperty<string>{
-            STRING,
-            "trackSource",
-            "objectSource",
-            "tracklelist to get the responding id",
-            "defalut", "NULL", "NULL"
-    });
-    // skip frame number
-    auto framenum = std::make_shared<ElementProperty<uint>>(ElementProperty<uint>{
-            UINT,
-            "frameNum",
-            "frameNum",
-            "the number of skip frame",
-            1, 1, 10
-    });
-    auto timeout = std::make_shared<ElementProperty<std::double_t>>(ElementProperty<std::double_t>{
-            DOUBLE,
-            "timeOut",
-            "timeOut",
-            "Time to discard the frames",
-            5000., 500., 10000.
-    });
-    auto sleeptime = std::make_shared<ElementProperty<uint>>(ElementProperty<uint>{
-            UINT,
-            "sleepTime",
-            "sleepTime",
-            "The Time CheckFrames thread hangs",
-            100, 100, 1000
-    });
-    properties.push_back(visionsource);
-    properties.push_back(tracksource);
-    properties.push_back(framenum);
-    properties.push_back(timeout);
-    properties.push_back(sleeptime);
-    return properties;
-}
-
-MxpiPortInfo MxpiStackFrame::DefineInputPorts() {
-    MxpiPortInfo inputPortInfo;
-    // Input: {{Mxpivisionlist}, {MxpiTrackLetList}}
-    std::vector<std::vector<std::string>> value = {{"ANY"}};
-    GenerateStaticInputPortsInfo(value, inputPortInfo);
-    return inputPortInfo;
-}
-
-MxpiPortInfo MxpiStackFrame::DefineOutputPorts() {
-    MxpiPortInfo outputPortInfo;
-    // Output: {{MxpiTensorPackageList}}
-    std::vector<std::vector<std::string>> value = {{"ANY"}};
-    GenerateStaticOutputPortsInfo(value, outputPortInfo);
-    return outputPortInfo;
-}
-
-namespace {
-    MX_PLUGIN_GENERATE(MxpiStackFrame)
-}
-
+/*
+ * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "MxpiStackFrame.h"
+
+using namespace MxBase;
+using namespace MxTools;
+using namespace MxPlugins;
+using namespace std;
+
+namespace {
+    bool isStop_ = true;
+    std::shared_ptr<BlockingMap> ObjectFrame = std::make_shared<BlockingMap>();
+}
+
+APP_ERROR MxpiStackFrame::Init(std::map<std::string, std::shared_ptr<void>> &configParamMap) {
+    LogInfo << "Begin to initialize MxpiStackFrame(" << pluginName_ << ").";
+    std::shared_ptr<std::string> visionSource = std::static_pointer_cast<std::string>(configParamMap["visionSource"]);
+    visionsource_ = *visionSource;
+
+    std::shared_ptr<std::string> trackSource = std::static_pointer_cast<std::string>(configParamMap["trackSource"]);
+    tracksource_ = *trackSource;
+
+    std::shared_ptr<std::uint32_t> framenum = std::static_pointer_cast<std::uint32_t>(configParamMap["frameNum"]);
+    skipFrameNum_ = *framenum;
+
+    std::shared_ptr<std::double_t> timeout = std::static_pointer_cast<double_t>(configParamMap["timeOut"]);
+    timeout_ = *timeout;
+
+    std::shared_ptr<std::uint32_t> sleeptime = std::static_pointer_cast<uint32_t>(configParamMap["sleepTime"]);
+    sleepTime_ = *sleeptime;
+
+    isStop_ = false;
+    // crate CheckFrame thread in Init function
+    CreateThread();
+    LogInfo << "End to initialize MxpiStackFrame(" << pluginName_ << ").";
+    return APP_ERR_OK;
+}
+
+APP_ERROR MxpiStackFrame::DeInit() {
+    LogInfo << "Begin to deinitialize MxpiStackFrame(" << pluginName_ << ").";
+    // Block the current thread until the thread identified by *this ends its execution
+    stopFlag_ = true;
+    if (thread_->joinable()) {
+        thread_->join();
+    }
+    ObjectFrame.reset();
+    LogInfo << "End to deinitialize MxpiStackFrame(" << pluginName_ << ").";
+    return APP_ERR_OK;
+}
+
+APP_ERROR MxpiStackFrame::CheckDataSource(MxTools::MxpiMetadataManager &mxpiMetadataManager) {
+    if (mxpiMetadataManager.GetMetadata(visionsource_) == nullptr) {
+        LogDebug << GetError(APP_ERR_METADATA_IS_NULL, pluginName_)
+                 << "vision metadata is null. please check"
+                 << "Your property visionSource(" << visionsource_ << ").";
+        return APP_ERR_METADATA_IS_NULL;
+    }
+    if (mxpiMetadataManager.GetMetadata(tracksource_) == nullptr) {
+        LogDebug << GetError(APP_ERR_METADATA_IS_NULL, pluginName_)
+                 << "track metadata is null. please check"
+                 << "Your property dataSourceFeature(" << tracksource_ << ").";
+        return APP_ERR_METADATA_IS_NULL;
+    }
+    return APP_ERR_OK;
+}
+
+void MxpiStackFrame::StackFrame(const std::shared_ptr<MxTools::MxpiVisionList> &visionList,
+                                const std::shared_ptr<MxTools::MxpiTrackLetList> &trackLetList,
+                                std::shared_ptr<BlockingMap> &blockingMap) {
+    for (int32_t i = 0; i < (int32_t) trackLetList->trackletvec_size(); i++) {
+        auto &trackObject = trackLetList->trackletvec(i);
+        uint32_t trackId = trackObject.trackid();
+        // lost object has no header vector; no object ;
+        if (trackObject.headervec_size() == 0 || visionList->visionvec_size() == 0) {
+            continue;
+        }
+        // get the visionvec by memberid
+        int32_t memberId = trackObject.headervec(0).memberid();
+        // filter out images not cropped
+        int32_t j = 0;
+        for (; j < visionList->visionvec_size(); j++) {
+            int32_t visionMemberId = visionList->visionvec(j).headervec(0).memberid();
+            if (visionMemberId == memberId) {
+                break;
+            }
+        }
+        if (j >= visionList->visionvec_size()) {
+            continue;
+        }
+        auto vision = visionList->visionvec(memberId);
+        // convert visiondata to memorydata
+        MxBase::MemoryData memoryData = ConvertMemoryData(vision.visiondata());
+        // add the vision to the blockingMap by trackId
+        if (blockingMap->count(trackId) == 0) {
+            // Initialize a new Mxpivisionlist
+            blockingMap->Insert(trackId, memoryData);
+        } else {
+            auto time_visionlist = blockingMap->Get(trackId);
+            LogInfo << "time_visionlist.second->visionvec_size() " << time_visionlist.second->visionvec_size();
+            if (time_visionlist.second->visionvec_size() >= 8) {
+                continue;
+            } else {
+                blockingMap->Update(trackId, memoryData);
+            }
+        }
+    }
+    visionList->clear_visionvec();
+}
+
+void MxpiStackFrame::CreateThread() {
+    thread_.reset(new std::thread(&MxpiStackFrame::WatchThread, this));
+}
+
+void MxpiStackFrame::WatchThread() {
+    // set current device context ; same as deviceId in pipeline
+    DeviceContext context = {};
+    context.devId = 0;
+    APP_ERROR ret = DeviceManager::GetInstance()->SetDevice(context);
+    if (ret != APP_ERR_OK) {
+        LogError << "SetDevice failed";
+    }
+    while (!stopFlag_) {
+        std::this_thread::sleep_for(std::chrono::milliseconds(sleepTime_));
+        CheckFrames(ObjectFrame);
+    }
+}
+
+std::shared_ptr<MxpiTensorPackageList> MxpiStackFrame::ConvertVisionList2TensorPackageList(
+        std::shared_ptr<MxpiVisionList> &mxpiVisionList) {
+    // use make_shared with caution
+    std::shared_ptr<MxpiTensorPackageList> tensorPackageList(new MxpiTensorPackageList,
+                                                             g_deleteFuncMxpiTensorPackageList);
+    MxBase::MemoryData concatData = {};
+    concatData.deviceId = mxpiVisionList->visionvec(0).visiondata().deviceid();
+    concatData.type = (MxBase::MemoryData::MemoryType) 1;
+    concatData.size =
+            mxpiVisionList->visionvec_size() * (uint32_t) mxpiVisionList->visionvec(0).visiondata().datasize();
+    // malloc new memory
+    APP_ERROR ret = MxBase::MemoryHelper::MxbsMalloc(concatData);
+    if (ret != APP_ERR_OK) {
+        LogError << "MxbsMalloc failed";
+        LogError << "concatData.size:" << concatData.size << " concatData.type:" << concatData.type
+                 << "concatData.deviceId:" << concatData.deviceId;
+        return tensorPackageList;
+    }
+    for (int i = 0; i < mxpiVisionList->visionvec_size(); i++) {
+        MxBase::MemoryData memoryData = ConvertMemoryData(mxpiVisionList->visionvec(i).visiondata());
+        // memory copy
+        MxBase::MemoryData newData = {};
+        newData.deviceId = mxpiVisionList->visionvec(i).visiondata().deviceid();
+        newData.type = (MxBase::MemoryData::MemoryType) 1;
+        newData.size = (uint32_t) mxpiVisionList->visionvec(i).visiondata().datasize();
+        newData.ptrData = (void *) ((uint8_t *) concatData.ptrData + i * newData.size);
+        // MxbsMallocAndCopy cannot be used here, cause npu memory leak
+        ret = MxBase::MemoryHelper::MxbsMemcpy(newData, memoryData, memoryData.size);
+        if (ret != APP_ERR_OK) {
+            LogError << "MxbsMemcpy failed";
+            MxBase::MemoryHelper::Free(concatData);
+            return tensorPackageList;
+        }
+    }
+    auto tensorPackage = tensorPackageList->add_tensorpackagevec();
+    auto tensorVector = tensorPackage->add_tensorvec();
+    tensorVector->set_tensordataptr((uint64) concatData.ptrData);
+    tensorVector->set_tensordatasize(concatData.size);
+    tensorVector->set_deviceid(concatData.deviceId);
+    tensorVector->set_memtype((MxpiMemoryType) concatData.type);
+    // explicitly specify tenspr shape
+    tensorVector->add_tensorshape(8);
+    tensorVector->add_tensorshape(224);
+    tensorVector->add_tensorshape(224);
+    tensorVector->add_tensorshape(3);
+    return tensorPackageList;
+}
+
+void MxpiStackFrame::CheckFrames(std::shared_ptr<BlockingMap> &blockingMap) {
+    // Get current timestamp
+    LogInfo << "Begin to check frames";
+    using Time = std::chrono::high_resolution_clock;
+    using Duration = std::chrono::duration<float>;
+    using Millisecond = std::chrono::duration<double, std::ratio<1, 1000>>;
+    auto currentTime = Time::now();
+    std::vector<uint32_t> keys = blockingMap->Keys();
+    for (uint32_t key : keys) {            // key <-> trackId
+        auto TimeMxpiVisionList = blockingMap->Get(key);
+        if (TimeMxpiVisionList.second == nullptr) {
+            continue;
+        }
+        Duration duration = currentTime - TimeMxpiVisionList.first;
+        double lastTime = std::chrono::duration_cast<Millisecond>(duration).count();
+        if (lastTime > timeout_) {
+            LogInfo << "Object:" << key << " is TimeOut";
+            blockingMap->Clear(key);
+            continue;
+        }
+        if (TimeMxpiVisionList.second->visionvec_size() == 8) {
+            // Add MxpiTensorPackageList to metadata and Send data to downstream plugin
+            const string metaKey = pluginName_;
+            auto dstMxpiVisionLitsSptr = TimeMxpiVisionList.second;
+            auto tensorPackageListPtr = ConvertVisionList2TensorPackageList(dstMxpiVisionLitsSptr);
+            blockingMap->Clear(key);
+            // sliding window
+            std::vector<MxTools::MxpiVisionData> slidingWindow = {};
+            uint32_t size = dstMxpiVisionLitsSptr->visionvec_size();
+            for (uint32_t i = 0; i < size; i++) {
+                auto mxpiVision = dstMxpiVisionLitsSptr->visionvec(i);
+                auto mxpiVisionData = mxpiVision.visiondata();
+                if (i < size / 2) {
+                    MxBase::MemoryData memoryData = ConvertMemoryData(mxpiVisionData);
+                    APP_ERROR ret = MemoryHelper::MxbsFree(memoryData);
+                    if (ret != APP_ERR_OK) {
+                        LogError << "MxbsFree failed";
+                    }
+                } else {
+                    slidingWindow.emplace_back(mxpiVisionData);
+                }
+            }
+            dstMxpiVisionLitsSptr->clear_visionvec();
+            auto mxpiVisionList = ConstructMxpiVisionList(slidingWindow);
+            blockingMap->Reinsert(key, mxpiVisionList);
+            // CreateDeviceBuffer; need inputParam
+            auto *outbuffer = MxpiBufferManager::CreateHostBuffer(inputParam);
+            MxpiMetadataManager mxpiMetadataManager(*outbuffer);
+            auto ret = mxpiMetadataManager.AddProtoMetadata(metaKey,
+                                                            static_pointer_cast<void>(tensorPackageListPtr));
+            if (ret != APP_ERR_OK) {
+                LogError << ErrorInfo_.str();
+                SendMxpiErrorInfo(*outbuffer, pluginName_, ret, ErrorInfo_.str());
+                SendData(0, *outbuffer);
+            }
+            LogInfo << "Object:" << key << " has stacked enough frames and begin to send data to downstream plugin";
+            SendData(0, *outbuffer);
+        }
+    }
+}
+
+std::shared_ptr<MxTools::MxpiVisionList> MxpiStackFrame::ConstructMxpiVisionList(
+        std::vector<MxTools::MxpiVisionData> &slidingWindow) {
+    std::shared_ptr<MxTools::MxpiVisionList> dstMxpiVisionListSptr(new MxTools::MxpiVisionList,
+                                                                   MxTools::g_deleteFuncMxpiVisionList);
+    for (auto iter = slidingWindow.begin(); iter != slidingWindow.end(); iter++) {
+        MxTools::MxpiVision *dstMxpivision = dstMxpiVisionListSptr->add_visionvec();
+        MxTools::MxpiVisionInfo *mxpiVisionInfo = dstMxpivision->mutable_visioninfo();
+        mxpiVisionInfo->set_format(1);
+        mxpiVisionInfo->set_height(224);
+        mxpiVisionInfo->set_width(224);
+        mxpiVisionInfo->set_heightaligned(224);
+        mxpiVisionInfo->set_widthaligned(224);
+        // set MxpiVisionData by MemoryData
+        MxTools::MxpiVisionData *mxpiVisionData = dstMxpivision->mutable_visiondata();
+        mxpiVisionData->set_dataptr((uint64_t) iter->dataptr());
+        mxpiVisionData->set_datasize(iter->datasize());
+        mxpiVisionData->set_deviceid(iter->deviceid());
+        mxpiVisionData->set_memtype(iter->memtype());
+    }
+    return dstMxpiVisionListSptr;
+}
+
+MxBase::MemoryData MxpiStackFrame::ConvertMemoryData(const MxTools::MxpiVisionData &mxpiVisionData) {
+    MxBase::MemoryData memoryData = {};
+    memoryData.deviceId = mxpiVisionData.deviceid();
+    memoryData.type = (MxBase::MemoryData::MemoryType) 1;
+    memoryData.size = (uint32_t) mxpiVisionData.datasize();
+    memoryData.ptrData = (void *) mxpiVisionData.dataptr();
+    return memoryData;
+}
+
+APP_ERROR MxpiStackFrame::Process(std::vector<MxpiBuffer *> &mxpiBuffer) {
+    LogInfo << "Begin to process MxpiStackFrame(" << elementName_ << ").";
+    // Get MxpiVisionList and MxpiTrackletList from mxpibuffer
+    MxpiBuffer *inputMxpiBuffer = mxpiBuffer[0];
+    MxpiMetadataManager mxpiMetadataManager(*inputMxpiBuffer);
+    ErrorInfo_.str("");
+    // check data source
+    APP_ERROR ret = CheckDataSource(mxpiMetadataManager);
+    if (ret != APP_ERR_OK) {
+        SendData(0, *inputMxpiBuffer);
+        return ret;
+    }
+    // Get metadata by key
+    std::shared_ptr<void> vision_metadata = mxpiMetadataManager.GetMetadata(visionsource_);
+    std::shared_ptr<MxpiVisionList> srcVisionListPtr = std::static_pointer_cast<MxpiVisionList>(vision_metadata);
+    std::shared_ptr<void> track_metadata = mxpiMetadataManager.GetMetadata(tracksource_);
+    std::shared_ptr<MxpiTrackLetList> srcTrackLetListPtr = std::static_pointer_cast<MxpiTrackLetList>(track_metadata);
+    // Stacking frames by track ID ; Choose skipFrameNum_ to skip frame
+    // DestroyBuffer (Get buffer to Host if needed)
+    if (count % skipFrameNum_ == 0) {
+        count = 1;
+        LogInfo << "Begin to stack frames";
+        StackFrame(srcVisionListPtr, srcTrackLetListPtr, ObjectFrame);
+        MxpiBufferManager::DestroyBuffer(inputMxpiBuffer);
+    } else {
+        count++;
+        MxpiBufferManager::DestroyBuffer(inputMxpiBuffer);
+    }
+    LogInfo << "End to process MxpiStackFrame(" << elementName_ << ").";
+    return APP_ERR_OK;
+}
+
+std::vector<std::shared_ptr<void>> MxpiStackFrame::DefineProperties() {
+    std::vector<std::shared_ptr<void>> properties;
+    // the cropped image
+    auto visionsource = std::make_shared<ElementProperty<string>>(ElementProperty<string>{
+            STRING,
+            "visionSource",
+            "imageSource",
+            "the name of cropped image source",
+            "default", "NULL", "NULL"
+    });
+    // the tracklet information
+    auto tracksource = std::make_shared<ElementProperty<string>>(ElementProperty<string>{
+            STRING,
+            "trackSource",
+            "objectSource",
+            "tracklelist to get the responding id",
+            "defalut", "NULL", "NULL"
+    });
+    // skip frame number
+    auto framenum = std::make_shared<ElementProperty<uint>>(ElementProperty<uint>{
+            UINT,
+            "frameNum",
+            "frameNum",
+            "the number of skip frame",
+            1, 1, 10
+    });
+    auto timeout = std::make_shared<ElementProperty<std::double_t>>(ElementProperty<std::double_t>{
+            DOUBLE,
+            "timeOut",
+            "timeOut",
+            "Time to discard the frames",
+            5000., 500., 10000.
+    });
+    auto sleeptime = std::make_shared<ElementProperty<uint>>(ElementProperty<uint>{
+            UINT,
+            "sleepTime",
+            "sleepTime",
+            "The Time CheckFrames thread hangs",
+            100, 100, 1000
+    });
+    properties.push_back(visionsource);
+    properties.push_back(tracksource);
+    properties.push_back(framenum);
+    properties.push_back(timeout);
+    properties.push_back(sleeptime);
+    return properties;
+}
+
+MxpiPortInfo MxpiStackFrame::DefineInputPorts() {
+    MxpiPortInfo inputPortInfo;
+    // Input: {{Mxpivisionlist}, {MxpiTrackLetList}}
+    std::vector<std::vector<std::string>> value = {{"ANY"}};
+    GenerateStaticInputPortsInfo(value, inputPortInfo);
+    return inputPortInfo;
+}
+
+MxpiPortInfo MxpiStackFrame::DefineOutputPorts() {
+    MxpiPortInfo outputPortInfo;
+    // Output: {{MxpiTensorPackageList}}
+    std::vector<std::vector<std::string>> value = {{"ANY"}};
+    GenerateStaticOutputPortsInfo(value, outputPortInfo);
+    return outputPortInfo;
+}
+
+namespace {
+    MX_PLUGIN_GENERATE(MxpiStackFrame)
+}
+
diff --git a/contrib/ActionRecognition/plugins/MxpiStackFrame/MxpiStackFrame.h b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/MxpiStackFrame/MxpiStackFrame.h
similarity index 97%
rename from contrib/ActionRecognition/plugins/MxpiStackFrame/MxpiStackFrame.h
rename to mxVision/mxVision-referenceapps/ActionRecognition/plugins/MxpiStackFrame/MxpiStackFrame.h
index e4425a0176ba2f9431fb2bb2018a311276f81eba..b343b655a723550d64b668241abed6d6dda23afd 100644
--- a/contrib/ActionRecognition/plugins/MxpiStackFrame/MxpiStackFrame.h
+++ b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/MxpiStackFrame/MxpiStackFrame.h
@@ -1,147 +1,147 @@
-/*
- * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- * imitations under the License.
- */
-
-#ifndef MXPLUGINS_MXPIFRAMESTACK_H
-#define MXPLUGINS_MXPIFRAMESTACK_H
-
-#include <chrono>
-#include <string>
-#include "opencv2/opencv.hpp"
-#include "MxBase/Log/Log.h"
-#include "MxBase/ErrorCode/ErrorCode.h"
-#include "MxBase/MemoryHelper/MemoryHelper.h"
-#include "MxBase/DvppWrapper/DvppWrapper.h"
-#include "MxBase/Tensor/TensorBase/TensorBase.h"
-#include "MxStream/StreamManager/MxStreamManager.h"
-#include "MxTools/PluginToolkit/base/MxPluginGenerator.h"
-#include "MxTools/PluginToolkit/base/MxPluginBase.h"
-#include "MxTools/PluginToolkit/buffer/MxpiBufferManager.h"
-#include "MxTools/PluginToolkit/metadata/MxpiMetadataManager.h"
-#include "MxTools/Proto/MxpiDataType.pb.h"
-#include "MxTools/Proto/MxpiDataTypeDeleter.h"
-#include "MxTools/Proto/MxpiDataType.pb.h"
-#include "BlockingMap.h"
-
-/**
- * This plugin is to stack frames based on detected objects.
-*/
-
-namespace MxPlugins {
-    class MxpiStackFrame : public MxTools::MxPluginBase {
-    public:
-        /**
-        * @description: Init configs.
-        * @param configParamMap: config.
-        * @return: Error code.
-        */
-        APP_ERROR Init(std::map<std::string, std::shared_ptr<void>> &configParamMap) override;
-
-        /**
-        * @description: DeInit device.
-        * @return: Error code.
-        */
-        APP_ERROR DeInit() override;
-
-        /**
-        * @description: MxpiStackFrame plugin process.
-        * @param mxpiBuffer: data receive from the previous.
-        * @return: Error code.
-        */
-        APP_ERROR Process(std::vector<MxTools::MxpiBuffer *> &mxpiBuffer) override;
-
-        /**
-        * @description: MxpiStackFrame plugin define properties.
-        * @return: properties.
-        */
-        static std::vector<std::shared_ptr<void>> DefineProperties();
-
-        /**
-        * @api
-        * @brief Define the number and data type of input ports.
-        * @return MxTools::MxpiPortInfo.
-        */
-        static MxTools::MxpiPortInfo DefineInputPorts();
-
-        /**
-        * @api
-        * @brief Define the number and data type of output ports.
-        * @return MxTools::MxpiPortInfo.
-        */
-        static MxTools::MxpiPortInfo DefineOutputPorts();
-
-        /**
-         * @api
-         * @brief Transfer MxpiVisionList to MxpiTensorPackageList.
-         * @param shared_ptr <MxpiVisionList>.
-         * @return shared_ptr <MxpiTensorPackageList>.
-         */
-        static std::shared_ptr<MxTools::MxpiTensorPackageList>
-        ConvertVisionList2TensorPackageList(std::shared_ptr<MxTools::MxpiVisionList> &mxpiVisionList);
-
-        /**
-         * @api
-         * @brief Reconstruct MxpiVisionList according to MxpiVisionData.
-         * @param std::vector<MxTools::MxpiVisionData>.
-         * @return shared_ptr <MxTools::MxpiVisionList>.
-         */
-        static std::shared_ptr<MxTools::MxpiVisionList>
-        ConstructMxpiVisionList(std::vector<MxTools::MxpiVisionData> &slidingWindow);
-
-        /**
-         * @api
-         * @brief Convert MxpiVisionData to MemoryData.
-         * @param MxTools::MxpiVisionData.
-         * @return MxBase::MemoryData.
-         */
-        static MxBase::MemoryData ConvertMemoryData(const MxTools::MxpiVisionData &mxpiVisionData);
-
-    private:
-        /**
-         * @api
-         * @brief Check metadata.
-         * @param MxTools::MxpiMetadataManager.
-         * @return Error Code.
-         */
-        APP_ERROR CheckDataSource(MxTools::MxpiMetadataManager &mxpiMetadataManager);
-
-        /**
-         * @api
-         * @brief Stack frames for each human object.
-         * @param MxpiVisionList, MxpiTrackLetList, BlockingMap
-         */
-        void StackFrame(const std::shared_ptr<MxTools::MxpiVisionList> &visionList,
-                        const std::shared_ptr<MxTools::MxpiTrackLetList> &trackLetList,
-                        std::shared_ptr<BlockingMap> &blockingMap);
-
-        // Check Thread function; Check whether a object is 8 frames
-        void CheckFrames(std::shared_ptr<BlockingMap> &blockingMap);
-
-        void CreateThread();       // create CheckFrame thread
-        void WatchThread();        // Watch CheckFrame thread
-        std::string visionsource_ = ""; // cropped image from crop plugin
-        std::string tracksource_ = "";  // track result
-        uint32_t skipFrameNum_ = 0;
-        uint32_t count = 1;
-        double timeout_ = 500.; //Millisecond
-        uint32_t sleepTime_ = 0;
-        std::ostringstream ErrorInfo_;
-        std::unique_ptr<std::thread> thread_ = nullptr;
-        bool stopFlag_ = false;
-        MxTools::InputParam inputParam;      // to create buffer
-    };
-}
+/*
+ * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ * imitations under the License.
+ */
+
+#ifndef MXPLUGINS_MXPIFRAMESTACK_H
+#define MXPLUGINS_MXPIFRAMESTACK_H
+
+#include <chrono>
+#include <string>
+#include "opencv2/opencv.hpp"
+#include "MxBase/Log/Log.h"
+#include "MxBase/ErrorCode/ErrorCode.h"
+#include "MxBase/MemoryHelper/MemoryHelper.h"
+#include "MxBase/DvppWrapper/DvppWrapper.h"
+#include "MxBase/Tensor/TensorBase/TensorBase.h"
+#include "MxStream/StreamManager/MxStreamManager.h"
+#include "MxTools/PluginToolkit/base/MxPluginGenerator.h"
+#include "MxTools/PluginToolkit/base/MxPluginBase.h"
+#include "MxTools/PluginToolkit/buffer/MxpiBufferManager.h"
+#include "MxTools/PluginToolkit/metadata/MxpiMetadataManager.h"
+#include "MxTools/Proto/MxpiDataType.pb.h"
+#include "MxTools/Proto/MxpiDataTypeDeleter.h"
+#include "MxTools/Proto/MxpiDataType.pb.h"
+#include "BlockingMap.h"
+
+/**
+ * This plugin is to stack frames based on detected objects.
+*/
+
+namespace MxPlugins {
+    class MxpiStackFrame : public MxTools::MxPluginBase {
+    public:
+        /**
+        * @description: Init configs.
+        * @param configParamMap: config.
+        * @return: Error code.
+        */
+        APP_ERROR Init(std::map<std::string, std::shared_ptr<void>> &configParamMap) override;
+
+        /**
+        * @description: DeInit device.
+        * @return: Error code.
+        */
+        APP_ERROR DeInit() override;
+
+        /**
+        * @description: MxpiStackFrame plugin process.
+        * @param mxpiBuffer: data receive from the previous.
+        * @return: Error code.
+        */
+        APP_ERROR Process(std::vector<MxTools::MxpiBuffer *> &mxpiBuffer) override;
+
+        /**
+        * @description: MxpiStackFrame plugin define properties.
+        * @return: properties.
+        */
+        static std::vector<std::shared_ptr<void>> DefineProperties();
+
+        /**
+        * @api
+        * @brief Define the number and data type of input ports.
+        * @return MxTools::MxpiPortInfo.
+        */
+        static MxTools::MxpiPortInfo DefineInputPorts();
+
+        /**
+        * @api
+        * @brief Define the number and data type of output ports.
+        * @return MxTools::MxpiPortInfo.
+        */
+        static MxTools::MxpiPortInfo DefineOutputPorts();
+
+        /**
+         * @api
+         * @brief Transfer MxpiVisionList to MxpiTensorPackageList.
+         * @param shared_ptr <MxpiVisionList>.
+         * @return shared_ptr <MxpiTensorPackageList>.
+         */
+        static std::shared_ptr<MxTools::MxpiTensorPackageList>
+        ConvertVisionList2TensorPackageList(std::shared_ptr<MxTools::MxpiVisionList> &mxpiVisionList);
+
+        /**
+         * @api
+         * @brief Reconstruct MxpiVisionList according to MxpiVisionData.
+         * @param std::vector<MxTools::MxpiVisionData>.
+         * @return shared_ptr <MxTools::MxpiVisionList>.
+         */
+        static std::shared_ptr<MxTools::MxpiVisionList>
+        ConstructMxpiVisionList(std::vector<MxTools::MxpiVisionData> &slidingWindow);
+
+        /**
+         * @api
+         * @brief Convert MxpiVisionData to MemoryData.
+         * @param MxTools::MxpiVisionData.
+         * @return MxBase::MemoryData.
+         */
+        static MxBase::MemoryData ConvertMemoryData(const MxTools::MxpiVisionData &mxpiVisionData);
+
+    private:
+        /**
+         * @api
+         * @brief Check metadata.
+         * @param MxTools::MxpiMetadataManager.
+         * @return Error Code.
+         */
+        APP_ERROR CheckDataSource(MxTools::MxpiMetadataManager &mxpiMetadataManager);
+
+        /**
+         * @api
+         * @brief Stack frames for each human object.
+         * @param MxpiVisionList, MxpiTrackLetList, BlockingMap
+         */
+        void StackFrame(const std::shared_ptr<MxTools::MxpiVisionList> &visionList,
+                        const std::shared_ptr<MxTools::MxpiTrackLetList> &trackLetList,
+                        std::shared_ptr<BlockingMap> &blockingMap);
+
+        // Check Thread function; Check whether a object is 8 frames
+        void CheckFrames(std::shared_ptr<BlockingMap> &blockingMap);
+
+        void CreateThread();       // create CheckFrame thread
+        void WatchThread();        // Watch CheckFrame thread
+        std::string visionsource_ = ""; // cropped image from crop plugin
+        std::string tracksource_ = "";  // track result
+        uint32_t skipFrameNum_ = 0;
+        uint32_t count = 1;
+        double timeout_ = 500.; //Millisecond
+        uint32_t sleepTime_ = 0;
+        std::ostringstream ErrorInfo_;
+        std::unique_ptr<std::thread> thread_ = nullptr;
+        bool stopFlag_ = false;
+        MxTools::InputParam inputParam;      // to create buffer
+    };
+}
 #endif
\ No newline at end of file
diff --git a/contrib/ActionRecognition/plugins/MxpiStackFrame/build.sh b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/MxpiStackFrame/build.sh
similarity index 100%
rename from contrib/ActionRecognition/plugins/MxpiStackFrame/build.sh
rename to mxVision/mxVision-referenceapps/ActionRecognition/plugins/MxpiStackFrame/build.sh
diff --git a/contrib/ActionRecognition/plugins/PluginAlone/CMakeLists.txt b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginAlone/CMakeLists.txt
similarity index 100%
rename from contrib/ActionRecognition/plugins/PluginAlone/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginAlone/CMakeLists.txt
diff --git a/contrib/ActionRecognition/plugins/PluginAlone/PluginAlone.cpp b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginAlone/PluginAlone.cpp
similarity index 97%
rename from contrib/ActionRecognition/plugins/PluginAlone/PluginAlone.cpp
rename to mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginAlone/PluginAlone.cpp
index ca7b022c3e40f2a47d98a6cc2cd4f10e90862960..5466c05ceb2cdb6c3213a47d4323eaee8b2b282b 100644
--- a/contrib/ActionRecognition/plugins/PluginAlone/PluginAlone.cpp
+++ b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginAlone/PluginAlone.cpp
@@ -1,253 +1,253 @@
-/*
-* Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-* http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-
-#include "MxBase/Log/Log.h"
-#include "PluginAlone.h"
-
-using namespace MxPlugins;
-using namespace MxTools;
-using namespace std;
-
-namespace MxPlugins {
-    APP_ERROR PluginAlone::Init(std::map<std::string, std::shared_ptr<void>> &configParamMap) {
-        LogInfo << "PluginAlone::Init start.";
-        APP_ERROR ret = APP_ERR_OK;
-        // Get the property values by key
-        // Data from track plugin
-        std::shared_ptr<string> tracksourcePropSptr =
-                std::static_pointer_cast<string>(configParamMap["dataSourceTrack"]);
-        tracksource_ = *tracksourcePropSptr.get();
-        std::shared_ptr<string> dataSourceDetection =
-                std::static_pointer_cast<string>(configParamMap["dataSourceDetection"]);
-        detectionsource_ = *dataSourceDetection.get();
-        // Description message
-        std::shared_ptr<string> descriptionMessageProSptr =
-                std::static_pointer_cast<string>(configParamMap["descriptionMessage"]);
-        descriptionMessage_ = *descriptionMessageProSptr.get();
-        // Configuration parameter
-        confthres_ = *std::static_pointer_cast<uint>(configParamMap["detectThresh"]);
-        confratio_ = *std::static_pointer_cast<float>(configParamMap["detectRatio"]);
-        confsleep_ = *std::static_pointer_cast<uint>(configParamMap["detectSleep"]);
-
-        return APP_ERR_OK;
-    }
-
-    APP_ERROR PluginAlone::DeInit() {
-        LogInfo << "PluginAlone::DeInit end.";
-        return APP_ERR_OK;
-    }
-
-    APP_ERROR PluginAlone::SetMxpiErrorInfo(MxpiBuffer &buffer, const std::string pluginName,
-                                            const MxpiErrorInfo mxpiErrorInfo) {
-        APP_ERROR ret = APP_ERR_OK;
-        // Define an object of MxpiMetadataManager
-        MxpiMetadataManager mxpiMetadataManager(buffer);
-        ret = mxpiMetadataManager.AddErrorInfo(pluginName, mxpiErrorInfo);
-        if (ret != APP_ERR_OK) {
-            LogError << "Failed to AddErrorInfo.";
-            return ret;
-        }
-        ret = SendData(0, buffer);
-        return ret;
-    }
-
-    APP_ERROR PluginAlone::Process(std::vector<MxpiBuffer *> &mxpiBuffer) {
-        LogInfo << "PluginAlone::Process start";
-        MxpiBuffer *buffer = mxpiBuffer[0];
-        MxpiMetadataManager mxpiMetadataManager(*buffer);
-        MxpiErrorInfo mxpiErrorInfo;
-        ErrorInfo_.str("");
-        auto errorInfoPtr = mxpiMetadataManager.GetErrorInfo();
-        if (errorInfoPtr != nullptr) {
-            ErrorInfo_ << GetError(APP_ERR_COMM_FAILURE, pluginName_)
-                       << "PluginAlone process is not implemented";
-            mxpiErrorInfo.ret = APP_ERR_COMM_FAILURE;
-            mxpiErrorInfo.errorInfo = ErrorInfo_.str();
-            SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
-            LogError << "PluginAlone process is not implemented";
-            return APP_ERR_COMM_FAILURE;
-        }
-        // Get the data from buffer
-        shared_ptr<void> metadata = mxpiMetadataManager.GetMetadata(tracksource_);
-        shared_ptr<void> Detect = mxpiMetadataManager.GetMetadata(detectionsource_);
-        if (metadata == nullptr || Detect == nullptr) {
-            ErrorInfo_ << GetError(APP_ERR_METADATA_IS_NULL, pluginName_)
-                       << "Metadata is NULL, failed";
-            mxpiErrorInfo.ret = APP_ERR_METADATA_IS_NULL;
-            mxpiErrorInfo.errorInfo = ErrorInfo_.str();
-            SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
-            return APP_ERR_METADATA_IS_NULL;
-        }
-        // get trackletlist
-        std::shared_ptr<MxpiTrackLetList> srcTrackLetListSptr = std::static_pointer_cast<MxpiTrackLetList>(metadata);
-        std::shared_ptr<MxpiObjectList> srcObjectListSptr = std::static_pointer_cast<MxpiObjectList>(Detect);
-        // Data processing
-        std::shared_ptr<MxTools::MxpiAttributeList> result = std::make_shared<MxTools::MxpiAttributeList>();
-        MxpiAttribute *mxpiAttribute = result->add_attributevec();
-        if (sleeptime == 0) {
-            LogInfo << "PluginAlone start";
-            int alarm = calculate(data_queue, confthres_, confratio_,
-                                  srcTrackLetListSptr, srcObjectListSptr);
-            if (alarm == 1) {
-                LogInfo << "Alarm alone";
-                alarm_count++;
-                LogInfo << "Alarmed " << alarm_count << " times";
-                sleeptime = confsleep_;
-                data_queue.clear();
-                // Send the data to downstream plugin
-                mxpiAttribute->set_attrname("Alarm Alone");
-                APP_ERROR ret = mxpiMetadataManager.AddProtoMetadata(pluginName_,
-                                                                     static_pointer_cast<void>(result));
-                if (ret != APP_ERR_OK) {
-                    ErrorInfo_ << GetError(ret, pluginName_) << "PluginAlone add metadata failed.";
-                    mxpiErrorInfo.ret = ret;
-                    mxpiErrorInfo.errorInfo = ErrorInfo_.str();
-                    SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
-                    return ret;
-                }
-            } else {
-                mxpiAttribute->set_attrname("No Alarm");
-                APP_ERROR ret = mxpiMetadataManager.AddProtoMetadata(pluginName_,
-                                                                     static_pointer_cast<void>(result));
-                if (ret != APP_ERR_OK) {
-                    ErrorInfo_ << GetError(ret, pluginName_) << "PluginAlone add metadata failed.";
-                    mxpiErrorInfo.ret = ret;
-                    mxpiErrorInfo.errorInfo = ErrorInfo_.str();
-                    SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
-                    return ret;
-                }
-            }
-        } else {
-            mxpiAttribute->set_attrname("Alarmed in a short period of time");
-            APP_ERROR ret = mxpiMetadataManager.AddProtoMetadata(pluginName_,
-                                                                 static_pointer_cast<void>(result));
-            if (ret != APP_ERR_OK) {
-                ErrorInfo_ << GetError(ret, pluginName_) << "PluginAlone add metadata failed.";
-                mxpiErrorInfo.ret = ret;
-                mxpiErrorInfo.errorInfo = ErrorInfo_.str();
-                SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
-                return ret;
-            }
-            sleeptime--;
-        }
-        // Send the data to downstream plugin
-        SendData(0, *buffer);
-        LogInfo << "PluginAlone::Process end";
-        return APP_ERR_OK;
-    }
-
-    int PluginAlone::calculate(std::vector<int> &data_queue, int confthres_, float confratio_,
-                               std::shared_ptr<MxpiTrackLetList> srcTrackLetListSptr,
-                               std::shared_ptr<MxpiObjectList> srcObjectListSptr) {
-        uint32_t count = 0;
-        uint32_t thresh_ = (int) (confthres_ * confratio_);
-        // update data
-        for (uint32_t i = 0; i < (uint32_t) srcTrackLetListSptr->trackletvec_size(); i++) {
-            auto &trackObject = srcTrackLetListSptr->trackletvec(i);
-            if (trackObject.headervec_size() == 0) {
-                continue;
-            }
-            auto &detectObject = srcObjectListSptr->objectvec(trackObject.headervec(0).memberid());
-            if (detectObject.classvec(0).classid() != 0) {
-                continue;
-            }
-            count++;
-        }
-        uint32_t result_present = 0;
-        uint32_t result_total = 0;
-        if (count == 1) {
-            result_present = 1;
-        }
-        int alarm = 0;
-        if (data_queue.size() == confthres_) {
-            for (int i = confthres_ - 1; i >= 0; i--) {
-                if (data_queue[i] == 1) {
-                    result_total++;
-                }
-                if (i != confthres_ - 1) {
-                    data_queue[i + 1] = data_queue[i];
-                }
-            }
-            data_queue[0] = result_present;
-            if (result_total >= thresh_) {
-                alarm = 1;
-            }
-        } else {
-            data_queue.push_back(result_present);
-        }
-        return alarm;
-    }
-
-    std::vector<std::shared_ptr<void>> PluginAlone::DefineProperties() {
-        // Define an A to store properties
-        std::vector<std::shared_ptr<void>> properties;
-        // Set the type and related information of the properties, and the key is the name
-        auto tracksourceProSptr =
-                std::make_shared<ElementProperty<string >>(ElementProperty<string>{
-                        STRING, "dataSourceTrack", "detect",
-                        "the name of previous plugin", "mxpi_motsimplesort0",
-                        "NULL", "NULL"});
-
-        auto detectsourceProSptr =
-                std::make_shared<ElementProperty<string >>(ElementProperty<string>{
-                        STRING, "dataSourceDetection", "name",
-                        "the name of previous plugin", "mxpi_objectpostprocessor0",
-                        "NULL", "NULL"});
-
-        auto threshProSptr =
-                std::make_shared<ElementProperty<uint32_t >>(ElementProperty<uint32_t>{
-                        UINT, "detectThresh", "thresh",
-                        "the number of frame when judging",
-                        100, 0, 1000});
-
-        auto ratioProSptr =
-                std::make_shared<ElementProperty<float >>(ElementProperty<float>{
-                        FLOAT, "detectRatio", "ratio",
-                        "the ratio of judging",
-                        0.8, 0.0, 1.0});
-
-        auto sleepProSptr =
-                std::make_shared<ElementProperty<uint32_t >>(ElementProperty<uint32_t>{
-                        UINT, "detectSleep", "sleep",
-                        "the time of stop detection",
-                        8, 0, 300});
-
-        auto descriptionMessageProSptr =
-                std::make_shared<ElementProperty<string >>(ElementProperty<string>{
-                        STRING, "descriptionMessage", "message",
-                        "Description mesasge of plugin",
-                        "This is PluginAlone", "NULL", "NULL"});
-        properties.push_back(tracksourceProSptr);
-        properties.push_back(detectsourceProSptr);
-        properties.push_back(threshProSptr);
-        properties.push_back(ratioProSptr);
-        properties.push_back(sleepProSptr);
-        properties.push_back(descriptionMessageProSptr);
-        return properties;
-    }
-
-    // Register the Sample plugin through macro
-    MxpiPortInfo PluginAlone::DefineInputPorts() {
-        MxpiPortInfo inputPortInfo;
-        std::vector<std::vector<std::string>> value = {{"ANY"}};
-        MxPluginBase::GenerateStaticInputPortsInfo(value, inputPortInfo);
-        return inputPortInfo;
-    };
-}
-
-namespace {
-    MX_PLUGIN_GENERATE(PluginAlone)
-}
+/*
+* Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "MxBase/Log/Log.h"
+#include "PluginAlone.h"
+
+using namespace MxPlugins;
+using namespace MxTools;
+using namespace std;
+
+namespace MxPlugins {
+    APP_ERROR PluginAlone::Init(std::map<std::string, std::shared_ptr<void>> &configParamMap) {
+        LogInfo << "PluginAlone::Init start.";
+        APP_ERROR ret = APP_ERR_OK;
+        // Get the property values by key
+        // Data from track plugin
+        std::shared_ptr<string> tracksourcePropSptr =
+                std::static_pointer_cast<string>(configParamMap["dataSourceTrack"]);
+        tracksource_ = *tracksourcePropSptr.get();
+        std::shared_ptr<string> dataSourceDetection =
+                std::static_pointer_cast<string>(configParamMap["dataSourceDetection"]);
+        detectionsource_ = *dataSourceDetection.get();
+        // Description message
+        std::shared_ptr<string> descriptionMessageProSptr =
+                std::static_pointer_cast<string>(configParamMap["descriptionMessage"]);
+        descriptionMessage_ = *descriptionMessageProSptr.get();
+        // Configuration parameter
+        confthres_ = *std::static_pointer_cast<uint>(configParamMap["detectThresh"]);
+        confratio_ = *std::static_pointer_cast<float>(configParamMap["detectRatio"]);
+        confsleep_ = *std::static_pointer_cast<uint>(configParamMap["detectSleep"]);
+
+        return APP_ERR_OK;
+    }
+
+    APP_ERROR PluginAlone::DeInit() {
+        LogInfo << "PluginAlone::DeInit end.";
+        return APP_ERR_OK;
+    }
+
+    APP_ERROR PluginAlone::SetMxpiErrorInfo(MxpiBuffer &buffer, const std::string pluginName,
+                                            const MxpiErrorInfo mxpiErrorInfo) {
+        APP_ERROR ret = APP_ERR_OK;
+        // Define an object of MxpiMetadataManager
+        MxpiMetadataManager mxpiMetadataManager(buffer);
+        ret = mxpiMetadataManager.AddErrorInfo(pluginName, mxpiErrorInfo);
+        if (ret != APP_ERR_OK) {
+            LogError << "Failed to AddErrorInfo.";
+            return ret;
+        }
+        ret = SendData(0, buffer);
+        return ret;
+    }
+
+    APP_ERROR PluginAlone::Process(std::vector<MxpiBuffer *> &mxpiBuffer) {
+        LogInfo << "PluginAlone::Process start";
+        MxpiBuffer *buffer = mxpiBuffer[0];
+        MxpiMetadataManager mxpiMetadataManager(*buffer);
+        MxpiErrorInfo mxpiErrorInfo;
+        ErrorInfo_.str("");
+        auto errorInfoPtr = mxpiMetadataManager.GetErrorInfo();
+        if (errorInfoPtr != nullptr) {
+            ErrorInfo_ << GetError(APP_ERR_COMM_FAILURE, pluginName_)
+                       << "PluginAlone process is not implemented";
+            mxpiErrorInfo.ret = APP_ERR_COMM_FAILURE;
+            mxpiErrorInfo.errorInfo = ErrorInfo_.str();
+            SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
+            LogError << "PluginAlone process is not implemented";
+            return APP_ERR_COMM_FAILURE;
+        }
+        // Get the data from buffer
+        shared_ptr<void> metadata = mxpiMetadataManager.GetMetadata(tracksource_);
+        shared_ptr<void> Detect = mxpiMetadataManager.GetMetadata(detectionsource_);
+        if (metadata == nullptr || Detect == nullptr) {
+            ErrorInfo_ << GetError(APP_ERR_METADATA_IS_NULL, pluginName_)
+                       << "Metadata is NULL, failed";
+            mxpiErrorInfo.ret = APP_ERR_METADATA_IS_NULL;
+            mxpiErrorInfo.errorInfo = ErrorInfo_.str();
+            SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
+            return APP_ERR_METADATA_IS_NULL;
+        }
+        // get trackletlist
+        std::shared_ptr<MxpiTrackLetList> srcTrackLetListSptr = std::static_pointer_cast<MxpiTrackLetList>(metadata);
+        std::shared_ptr<MxpiObjectList> srcObjectListSptr = std::static_pointer_cast<MxpiObjectList>(Detect);
+        // Data processing
+        std::shared_ptr<MxTools::MxpiAttributeList> result = std::make_shared<MxTools::MxpiAttributeList>();
+        MxpiAttribute *mxpiAttribute = result->add_attributevec();
+        if (sleeptime == 0) {
+            LogInfo << "PluginAlone start";
+            int alarm = calculate(data_queue, confthres_, confratio_,
+                                  srcTrackLetListSptr, srcObjectListSptr);
+            if (alarm == 1) {
+                LogInfo << "Alarm alone";
+                alarm_count++;
+                LogInfo << "Alarmed " << alarm_count << " times";
+                sleeptime = confsleep_;
+                data_queue.clear();
+                // Send the data to downstream plugin
+                mxpiAttribute->set_attrname("Alarm Alone");
+                APP_ERROR ret = mxpiMetadataManager.AddProtoMetadata(pluginName_,
+                                                                     static_pointer_cast<void>(result));
+                if (ret != APP_ERR_OK) {
+                    ErrorInfo_ << GetError(ret, pluginName_) << "PluginAlone add metadata failed.";
+                    mxpiErrorInfo.ret = ret;
+                    mxpiErrorInfo.errorInfo = ErrorInfo_.str();
+                    SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
+                    return ret;
+                }
+            } else {
+                mxpiAttribute->set_attrname("No Alarm");
+                APP_ERROR ret = mxpiMetadataManager.AddProtoMetadata(pluginName_,
+                                                                     static_pointer_cast<void>(result));
+                if (ret != APP_ERR_OK) {
+                    ErrorInfo_ << GetError(ret, pluginName_) << "PluginAlone add metadata failed.";
+                    mxpiErrorInfo.ret = ret;
+                    mxpiErrorInfo.errorInfo = ErrorInfo_.str();
+                    SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
+                    return ret;
+                }
+            }
+        } else {
+            mxpiAttribute->set_attrname("Alarmed in a short period of time");
+            APP_ERROR ret = mxpiMetadataManager.AddProtoMetadata(pluginName_,
+                                                                 static_pointer_cast<void>(result));
+            if (ret != APP_ERR_OK) {
+                ErrorInfo_ << GetError(ret, pluginName_) << "PluginAlone add metadata failed.";
+                mxpiErrorInfo.ret = ret;
+                mxpiErrorInfo.errorInfo = ErrorInfo_.str();
+                SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
+                return ret;
+            }
+            sleeptime--;
+        }
+        // Send the data to downstream plugin
+        SendData(0, *buffer);
+        LogInfo << "PluginAlone::Process end";
+        return APP_ERR_OK;
+    }
+
+    int PluginAlone::calculate(std::vector<int> &data_queue, int confthres_, float confratio_,
+                               std::shared_ptr<MxpiTrackLetList> srcTrackLetListSptr,
+                               std::shared_ptr<MxpiObjectList> srcObjectListSptr) {
+        uint32_t count = 0;
+        uint32_t thresh_ = (int) (confthres_ * confratio_);
+        // update data
+        for (uint32_t i = 0; i < (uint32_t) srcTrackLetListSptr->trackletvec_size(); i++) {
+            auto &trackObject = srcTrackLetListSptr->trackletvec(i);
+            if (trackObject.headervec_size() == 0) {
+                continue;
+            }
+            auto &detectObject = srcObjectListSptr->objectvec(trackObject.headervec(0).memberid());
+            if (detectObject.classvec(0).classid() != 0) {
+                continue;
+            }
+            count++;
+        }
+        uint32_t result_present = 0;
+        uint32_t result_total = 0;
+        if (count == 1) {
+            result_present = 1;
+        }
+        int alarm = 0;
+        if (data_queue.size() == confthres_) {
+            for (int i = confthres_ - 1; i >= 0; i--) {
+                if (data_queue[i] == 1) {
+                    result_total++;
+                }
+                if (i != confthres_ - 1) {
+                    data_queue[i + 1] = data_queue[i];
+                }
+            }
+            data_queue[0] = result_present;
+            if (result_total >= thresh_) {
+                alarm = 1;
+            }
+        } else {
+            data_queue.push_back(result_present);
+        }
+        return alarm;
+    }
+
+    std::vector<std::shared_ptr<void>> PluginAlone::DefineProperties() {
+        // Define an A to store properties
+        std::vector<std::shared_ptr<void>> properties;
+        // Set the type and related information of the properties, and the key is the name
+        auto tracksourceProSptr =
+                std::make_shared<ElementProperty<string >>(ElementProperty<string>{
+                        STRING, "dataSourceTrack", "detect",
+                        "the name of previous plugin", "mxpi_motsimplesort0",
+                        "NULL", "NULL"});
+
+        auto detectsourceProSptr =
+                std::make_shared<ElementProperty<string >>(ElementProperty<string>{
+                        STRING, "dataSourceDetection", "name",
+                        "the name of previous plugin", "mxpi_objectpostprocessor0",
+                        "NULL", "NULL"});
+
+        auto threshProSptr =
+                std::make_shared<ElementProperty<uint32_t >>(ElementProperty<uint32_t>{
+                        UINT, "detectThresh", "thresh",
+                        "the number of frame when judging",
+                        100, 0, 1000});
+
+        auto ratioProSptr =
+                std::make_shared<ElementProperty<float >>(ElementProperty<float>{
+                        FLOAT, "detectRatio", "ratio",
+                        "the ratio of judging",
+                        0.8, 0.0, 1.0});
+
+        auto sleepProSptr =
+                std::make_shared<ElementProperty<uint32_t >>(ElementProperty<uint32_t>{
+                        UINT, "detectSleep", "sleep",
+                        "the time of stop detection",
+                        8, 0, 300});
+
+        auto descriptionMessageProSptr =
+                std::make_shared<ElementProperty<string >>(ElementProperty<string>{
+                        STRING, "descriptionMessage", "message",
+                        "Description mesasge of plugin",
+                        "This is PluginAlone", "NULL", "NULL"});
+        properties.push_back(tracksourceProSptr);
+        properties.push_back(detectsourceProSptr);
+        properties.push_back(threshProSptr);
+        properties.push_back(ratioProSptr);
+        properties.push_back(sleepProSptr);
+        properties.push_back(descriptionMessageProSptr);
+        return properties;
+    }
+
+    // Register the Sample plugin through macro
+    MxpiPortInfo PluginAlone::DefineInputPorts() {
+        MxpiPortInfo inputPortInfo;
+        std::vector<std::vector<std::string>> value = {{"ANY"}};
+        MxPluginBase::GenerateStaticInputPortsInfo(value, inputPortInfo);
+        return inputPortInfo;
+    };
+}
+
+namespace {
+    MX_PLUGIN_GENERATE(PluginAlone)
+}
diff --git a/contrib/ActionRecognition/plugins/PluginAlone/PluginAlone.h b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginAlone/PluginAlone.h
similarity index 96%
rename from contrib/ActionRecognition/plugins/PluginAlone/PluginAlone.h
rename to mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginAlone/PluginAlone.h
index 488234f1dcd3858f317c586b5f029ba8eb933fa2..960e570f54a571dfece5c35a227f1779a1335a55 100644
--- a/contrib/ActionRecognition/plugins/PluginAlone/PluginAlone.h
+++ b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginAlone/PluginAlone.h
@@ -1,103 +1,103 @@
-/*
-* Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-* http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-
-#ifndef SDKMEMORY_PLUGINALONE_H
-#define SDKMEMORY_PLUGINALONE_H
-
-#include "MxTools/PluginToolkit/base/MxPluginGenerator.h"
-#include "MxTools/PluginToolkit/base/MxPluginBase.h"
-#include "MxTools/PluginToolkit/metadata/MxpiMetadataManager.h"
-#include "MxTools/Proto/MxpiDataType.pb.h"
-#include "MxBase/ErrorCode/ErrorCode.h"
-
-/**
-* @api
-* @brief Definition of PluginAlone class.
-*/
-
-namespace MxPlugins {
-    class PluginAlone : public MxTools::MxPluginBase {
-    public:
-        /**
-        * @api
-        * @brief Initialize configure parameter.
-        * @param configParamMap
-        * @return APP_ERROR
-        */
-        APP_ERROR Init(std::map<std::string, std::shared_ptr<void>> &configParamMap) override;
-
-        /**
-        * * @api
-        * @brief DeInitialize configure parameter.
-        * @return APP_ERROR
-        */
-        APP_ERROR DeInit() override;
-
-        /**
-        * @api
-        * @brief Process the data of MxpiBuffer.
-        * @param mxpiBuffer
-        * @return APP_ERROR
-        */
-        APP_ERROR Process(std::vector<MxTools::MxpiBuffer *> &mxpiBuffer) override;
-
-        /**
-        * @api
-        * @brief Definition the parameter of configure properties.
-        * @return std::vector<std::shared_ptr<void>>
-        */
-        static std::vector<std::shared_ptr<void>> DefineProperties();
-
-        /**
-        * @api
-        * @brief Get the number of class id and confidence from model inference.
-        * @param key
-        * @param buffer
-        * @return APP_ERROR
-        */
-        static MxTools::MxpiPortInfo DefineInputPorts();
-
-        /**
-        * @api
-        * @brief Define the input ports.
-        * @return MxpiPortInfo
-        */
-        static int calculate(std::vector<int> &data_queue, int confthres_, float confratio_,
-                             std::shared_ptr<MxTools::MxpiTrackLetList> srcTrackLetListSptr,
-                             std::shared_ptr<MxTools::MxpiObjectList> srcObjectListSptr);
-        /**
-        * @api
-        * @brief Data processing.
-        * @return int
-        */
-    private:
-        APP_ERROR SetMxpiErrorInfo(MxTools::MxpiBuffer &buffer,
-                                   const std::string pluginName,
-                                   const MxTools::MxpiErrorInfo mxpiErrorInfo);
-
-        std::string tracksource_;
-        std::string detectionsource_;
-        std::string descriptionMessage_;
-        std::ostringstream ErrorInfo_;
-        int confthres_;
-        float confratio_;
-        int confsleep_;
-        int sleeptime = 0;
-        std::vector<int> data_queue;
-        int alarm_count = 0;
-    };
-}
-#endif // SDKMEMORY_PLUGINALONE_H
+/*
+* Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#ifndef SDKMEMORY_PLUGINALONE_H
+#define SDKMEMORY_PLUGINALONE_H
+
+#include "MxTools/PluginToolkit/base/MxPluginGenerator.h"
+#include "MxTools/PluginToolkit/base/MxPluginBase.h"
+#include "MxTools/PluginToolkit/metadata/MxpiMetadataManager.h"
+#include "MxTools/Proto/MxpiDataType.pb.h"
+#include "MxBase/ErrorCode/ErrorCode.h"
+
+/**
+* @api
+* @brief Definition of PluginAlone class.
+*/
+
+namespace MxPlugins {
+    class PluginAlone : public MxTools::MxPluginBase {
+    public:
+        /**
+        * @api
+        * @brief Initialize configure parameter.
+        * @param configParamMap
+        * @return APP_ERROR
+        */
+        APP_ERROR Init(std::map<std::string, std::shared_ptr<void>> &configParamMap) override;
+
+        /**
+        * * @api
+        * @brief DeInitialize configure parameter.
+        * @return APP_ERROR
+        */
+        APP_ERROR DeInit() override;
+
+        /**
+        * @api
+        * @brief Process the data of MxpiBuffer.
+        * @param mxpiBuffer
+        * @return APP_ERROR
+        */
+        APP_ERROR Process(std::vector<MxTools::MxpiBuffer *> &mxpiBuffer) override;
+
+        /**
+        * @api
+        * @brief Definition the parameter of configure properties.
+        * @return std::vector<std::shared_ptr<void>>
+        */
+        static std::vector<std::shared_ptr<void>> DefineProperties();
+
+        /**
+        * @api
+        * @brief Get the number of class id and confidence from model inference.
+        * @param key
+        * @param buffer
+        * @return APP_ERROR
+        */
+        static MxTools::MxpiPortInfo DefineInputPorts();
+
+        /**
+        * @api
+        * @brief Define the input ports.
+        * @return MxpiPortInfo
+        */
+        static int calculate(std::vector<int> &data_queue, int confthres_, float confratio_,
+                             std::shared_ptr<MxTools::MxpiTrackLetList> srcTrackLetListSptr,
+                             std::shared_ptr<MxTools::MxpiObjectList> srcObjectListSptr);
+        /**
+        * @api
+        * @brief Data processing.
+        * @return int
+        */
+    private:
+        APP_ERROR SetMxpiErrorInfo(MxTools::MxpiBuffer &buffer,
+                                   const std::string pluginName,
+                                   const MxTools::MxpiErrorInfo mxpiErrorInfo);
+
+        std::string tracksource_;
+        std::string detectionsource_;
+        std::string descriptionMessage_;
+        std::ostringstream ErrorInfo_;
+        int confthres_;
+        float confratio_;
+        int confsleep_;
+        int sleeptime = 0;
+        std::vector<int> data_queue;
+        int alarm_count = 0;
+    };
+}
+#endif // SDKMEMORY_PLUGINALONE_H
diff --git a/contrib/ActionRecognition/plugins/PluginAlone/build.sh b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginAlone/build.sh
similarity index 100%
rename from contrib/ActionRecognition/plugins/PluginAlone/build.sh
rename to mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginAlone/build.sh
diff --git a/contrib/ActionRecognition/plugins/PluginClimb/CMakeLists.txt b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginClimb/CMakeLists.txt
similarity index 100%
rename from contrib/ActionRecognition/plugins/PluginClimb/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginClimb/CMakeLists.txt
diff --git a/contrib/ActionRecognition/plugins/PluginClimb/PluginClimb.cpp b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginClimb/PluginClimb.cpp
similarity index 97%
rename from contrib/ActionRecognition/plugins/PluginClimb/PluginClimb.cpp
rename to mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginClimb/PluginClimb.cpp
index 36a958f53e11c6931d1894e84352ca260c5f3030..489a36a5fae30d3cc4100dd2df96039920da5889 100644
--- a/contrib/ActionRecognition/plugins/PluginClimb/PluginClimb.cpp
+++ b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginClimb/PluginClimb.cpp
@@ -1,341 +1,341 @@
-/*
-* Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-* http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-
-#include <fstream>
-#include "math.h"
-#include <opencv2/opencv.hpp>
-#include "MxBase/Log/Log.h"
-#include "MxTools/PluginToolkit/base/MxPluginBase.h"
-#include "PluginClimb.h"
-
-using namespace MxPlugins;
-using namespace MxTools;
-using namespace std;
-
-namespace {
-    const int indx_num = 4;
-    const int y_indx = 3;
-    const int up_indx = 2;
-    const int in_indx = 1;
-}
-
-namespace MxPlugins {
-    APP_ERROR PluginClimb::Init(std::map<std::string, std::shared_ptr<void>> &configParamMap) {
-        LogInfo << "PluginClimb::Init start.";
-        APP_ERROR ret = APP_ERR_OK;
-        // Get the property values by key
-        std::shared_ptr<string> tracksourcePropSptr =
-                std::static_pointer_cast<string>(configParamMap["dataSourceTrack"]);
-        tracksource_ = *tracksourcePropSptr.get();
-        LogInfo << "PluginClimb::Init start.";
-        std::shared_ptr<string> dataSourceDetection =
-                std::static_pointer_cast<string>(configParamMap["dataSourceDetection"]);
-        detectionsource_ = *dataSourceDetection.get();
-        LogInfo << "PluginClimb::Init start.";
-        std::shared_ptr<string> descriptionMessageProSptr =
-                std::static_pointer_cast<string>(configParamMap["descriptionMessage"]);
-        descriptionMessage_ = *descriptionMessageProSptr.get();
-        LogInfo << "PluginClimb::Init start.";
-        // Configuration parameter
-        highthresh_ = *std::static_pointer_cast<int>(configParamMap["highThresh"]);
-        LogInfo << "PluginClimb::Init start.";
-        bufferlength_ = *std::static_pointer_cast<int>(configParamMap["bufferLength"]);
-        LogInfo << "PluginClimb::Init start.";
-        ratio_ = *std::static_pointer_cast<float>(configParamMap["detectRatio"]);
-        LogInfo << "PluginClimb::Init start.";
-        detectsleep_ = *std::static_pointer_cast<int>(configParamMap["detectSleep"]);
-        LogInfo << "PluginClimb::Init start.";
-        filepath_ = *std::static_pointer_cast<string>(configParamMap["filePath"]);
-        LogInfo << "PluginClimb::Init end.";
-        return APP_ERR_OK;
-    }
-
-    APP_ERROR PluginClimb::DeInit() {
-        LogInfo << "PluginClimb::DeInit end.";
-        return APP_ERR_OK;
-    }
-
-    APP_ERROR PluginClimb::SetMxpiErrorInfo(MxpiBuffer &buffer, const std::string pluginName,
-                                            const MxpiErrorInfo mxpiErrorInfo) {
-        APP_ERROR ret = APP_ERR_OK;
-        // Define an object of MxpiMetadataManager
-        MxpiMetadataManager mxpiMetadataManager(buffer);
-        ret = mxpiMetadataManager.AddErrorInfo(pluginName, mxpiErrorInfo);
-        if (ret != APP_ERR_OK) {
-            LogError << "Failed to AddErrorInfo.";
-            return ret;
-        }
-        ret = SendData(0, buffer);
-        return ret;
-    }
-
-    APP_ERROR PluginClimb::Process(std::vector<MxpiBuffer *> &mxpiBuffer) {
-        LogInfo << "PluginClimb::Process start";
-        MxpiBuffer *buffer = mxpiBuffer[0];
-        MxpiMetadataManager mxpiMetadataManager(*buffer);
-        MxpiErrorInfo mxpiErrorInfo;
-        ErrorInfo_.str("");
-        auto errorInfoPtr = mxpiMetadataManager.GetErrorInfo();
-        if (errorInfoPtr != nullptr) {
-            ErrorInfo_ << GetError(APP_ERR_COMM_FAILURE, pluginName_)
-                       << "PluginClimb process is not implemented";
-            mxpiErrorInfo.ret = APP_ERR_COMM_FAILURE;
-            mxpiErrorInfo.errorInfo = ErrorInfo_.str();
-            SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
-            LogError << "PluginClimb process is not implemented";
-            return APP_ERR_COMM_FAILURE;
-        }
-        // Get the data from buffer
-        shared_ptr<void> metadata = mxpiMetadataManager.GetMetadata(tracksource_);
-        shared_ptr<void> Detect = mxpiMetadataManager.GetMetadata(detectionsource_);
-        if (metadata == nullptr) {
-            ErrorInfo_ << GetError(APP_ERR_METADATA_IS_NULL, pluginName_)
-                       << "Metadata is NULL, failed";
-            mxpiErrorInfo.ret = APP_ERR_METADATA_IS_NULL;
-            mxpiErrorInfo.errorInfo = ErrorInfo_.str();
-            SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
-            return APP_ERR_METADATA_IS_NULL; // self define the error code
-        }
-        // get trackletlist
-        std::shared_ptr<MxpiTrackLetList> srcTrackLetListSptr = std::static_pointer_cast<MxpiTrackLetList>(metadata);
-        std::shared_ptr<MxpiObjectList> srcObjectListSptr = std::static_pointer_cast<MxpiObjectList>(Detect);
-        // update data
-        if (pathflag == 0) {
-            readTxt(filepath_, roi);
-            pathflag = 1;
-        }
-        std::shared_ptr<MxTools::MxpiAttributeList> result = std::make_shared<MxTools::MxpiAttributeList>();
-        MxpiAttribute *mxpiAttribute = result->add_attributevec();
-        if (sleeptime == 0) {
-            LogInfo << "PluginClimb start";
-            int alarm = calculate(bufferlength_, highthresh_, ratio_, roi, srcTrackLetListSptr,
-                                  srcObjectListSptr);
-            if (alarm == 1) {
-                alarm_count++;
-                LogInfo << "Alarmed " << alarm_count << " times";
-                trackdata.clear();
-                sleeptime = detectsleep_;
-                // Send the data to downstream plugin
-                mxpiAttribute->set_attrname("Alarm Climb up");
-                APP_ERROR ret = mxpiMetadataManager.AddProtoMetadata(pluginName_,
-                                                                     static_pointer_cast<void>(result));
-                if (ret != APP_ERR_OK) {
-                    ErrorInfo_ << GetError(ret, pluginName_) << "PluginClimb add metadata failed.";
-                    mxpiErrorInfo.ret = ret;
-                    mxpiErrorInfo.errorInfo = ErrorInfo_.str();
-                    SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
-                    return ret;
-                }
-            } else {
-                mxpiAttribute->set_attrname("No Alarm");
-                APP_ERROR ret = mxpiMetadataManager.AddProtoMetadata(pluginName_,
-                                                                     static_pointer_cast<void>(result));
-                if (ret != APP_ERR_OK) {
-                    ErrorInfo_ << GetError(ret, pluginName_) << "PluginClimb add metadata failed.";
-                    mxpiErrorInfo.ret = ret;
-                    mxpiErrorInfo.errorInfo = ErrorInfo_.str();
-                    SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
-                    return ret;
-                }
-            }
-        } else {
-            mxpiAttribute->set_attrname("Alarmed in a short period of time");
-            APP_ERROR ret = mxpiMetadataManager.AddProtoMetadata(pluginName_,
-                                                                 static_pointer_cast<void>(result));
-            if (ret != APP_ERR_OK) {
-                ErrorInfo_ << GetError(ret, pluginName_) << "PluginClimb add metadata failed.";
-                mxpiErrorInfo.ret = ret;
-                mxpiErrorInfo.errorInfo = ErrorInfo_.str();
-                SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
-                return ret;
-            }
-            sleeptime--;
-        }
-        LogInfo << "PluginClimb end";
-        SendData(0, *buffer);
-        LogInfo << "PluginClimb::Process end";
-        return APP_ERR_OK;
-    }
-
-    int PluginClimb::calculate(int bufferlength_, int highthresh_, float ratio_,
-                               vector<cv::Point> roi,
-                               std::shared_ptr<MxpiTrackLetList> srcTrackLetListSptr,
-                               std::shared_ptr<MxpiObjectList> srcObjectListSptr) {
-        int alarm = 0;
-        for (uint32_t i = 0; i < (uint32_t) srcTrackLetListSptr->trackletvec_size(); i++) {
-            auto &trackObject = srcTrackLetListSptr->trackletvec(i);
-            if (trackObject.headervec_size() == 0) {
-                continue;
-                // As long as the person who has appeared will have a trackobject.
-                // Determine whether this id appears in the current frame.
-            }
-            auto &detectObject = srcObjectListSptr->objectvec(trackObject.headervec(0).memberid());
-            if (detectObject.classvec(0).classid() != 0) {
-                continue;
-            }
-            int cnt_x = (detectObject.x0() + detectObject.x1()) / 2;
-            int cnt_y = (detectObject.y0() + detectObject.y1()) / 2;
-            if (trackdata.count(trackObject.trackid()) == 0) {
-                int up_num = 0;
-                int in_num = 0;
-                if (cv::pointPolygonTest(roi, cv::Point(cnt_x, cnt_y), false) > 0) {
-                    in_num += 1;
-                }
-                trackdata[trackObject.trackid()].push_back(cnt_x); // store cnt_x
-                trackdata[trackObject.trackid()].push_back(cnt_y); // store cnt_y
-                trackdata[trackObject.trackid()].push_back(up_num); // store up_num
-                trackdata[trackObject.trackid()].push_back(in_num); // store in_num
-            } else {
-                int up_num = trackdata[trackObject.trackid()][trackdata[trackObject.trackid()].size() - up_indx];
-                int in_num = trackdata[trackObject.trackid()].back();
-                if (cv::pointPolygonTest(roi, cv::Point(cnt_x, cnt_y), false) > 0) {
-                    in_num = trackdata[trackObject.trackid()].back() + 1;
-                }  // if the target is in the area, in_num ++
-                if (cnt_y > trackdata[trackObject.trackid()][trackdata[trackObject.trackid()].size() - y_indx]) {
-                    up_num = trackdata[trackObject.trackid()][trackdata[trackObject.trackid()].size() - up_indx] + 1;
-                } // if the target is rising, up_num ++
-                trackdata[trackObject.trackid()].push_back(cnt_x); // store cnt_x
-                trackdata[trackObject.trackid()].push_back(cnt_y); // store cnt_y
-                trackdata[trackObject.trackid()].push_back(up_num); // store up_num
-                trackdata[trackObject.trackid()].push_back(in_num); // store in_num     
-            }
-            if (trackdata[trackObject.trackid()].size() == indx_num * bufferlength_) {
-                if (trackdata[trackObject.trackid()][indx_num * bufferlength_ - up_indx] >
-                    (int) (bufferlength_ * ratio_)
-                    && (trackdata[trackObject.trackid()][indx_num * bufferlength_ - in_indx] >
-                        (int) (bufferlength_ * ratio_))
-                    && trackdata[trackObject.trackid()][indx_num * bufferlength_ - y_indx] -
-                       trackdata[trackObject.trackid()][1] > highthresh_) {
-                    alarm = 1;
-                } else {
-                    // Climbing up judgment failed, delete the last frame of the queue, continue to load data
-                    std::vector<int> tmp(trackdata[trackObject.trackid()].begin() + indx_num,
-                                         trackdata[trackObject.trackid()].end());
-                    trackdata[trackObject.trackid()] = tmp;
-                }
-            }
-        }
-        return alarm;
-    }
-
-    std::vector<std::shared_ptr<void>> PluginClimb::DefineProperties() {
-        // Define an A to store properties
-        std::vector<std::shared_ptr<void>> properties;
-        // Set the type and related information of the properties, and the key is the name
-        auto tracksourceProSptr =
-                std::make_shared<ElementProperty<string >>(ElementProperty<string>{
-                        STRING, "dataSourceTrack", "name",
-                        "the name of previous plugin", "mxpi_motsimplesort0", "NULL",
-                        "NULL"});
-
-        auto detectsourceProSptr =
-                std::make_shared<ElementProperty<string >>(ElementProperty<string>{
-                        STRING, "dataSourceDetection", "name",
-                        "the name of previous plugin", "mxpi_fairmot0",
-                        "NULL", "NULL"});
-
-        auto highthreshProSptr =
-                std::make_shared<ElementProperty<int >>(ElementProperty<int>{
-                        UINT, "highThresh", "name",
-                        "the name of previous plugin", 8,
-                        0, 1000});
-
-        auto bufferlengthProSptr =
-                std::make_shared<ElementProperty<int >>(ElementProperty<int>{
-                        UINT, "bufferLength", "name",
-                        "the name of previous plugin", 10,
-                        8, 1000});
-
-        auto ratioProSptr =
-                std::make_shared<ElementProperty<float >>(ElementProperty<float>{
-                        FLOAT, "detectRatio", "name",
-                        "the name of previous plugin", 0.75,
-                        0, 1});
-
-        auto sleepProSptr =
-                std::make_shared<ElementProperty<int >>(ElementProperty<int>{
-                        UINT, "detectSleep", "name", " ", 8, 0,
-                        100});
-
-        auto filepathProSptr =
-                std::make_shared<ElementProperty<string >>(ElementProperty<string>{
-                        STRING, "filePath", "name",
-                        "the name of previous plugin", "mxpi_fairmot0",
-                        "NULL", "NULL"});
-
-        auto descriptionMessageProSptr =
-                std::make_shared<ElementProperty<string >>(ElementProperty<string>{
-                        STRING, "descriptionMessage", "message",
-                        "Description mesasge of plugin",
-                        "This is PluginClimb", "NULL", "NULL"});
-        properties.push_back(tracksourceProSptr);
-        properties.push_back(detectsourceProSptr);
-        properties.push_back(highthreshProSptr);
-        properties.push_back(bufferlengthProSptr);
-        properties.push_back(ratioProSptr);
-        properties.push_back(sleepProSptr);
-        properties.push_back(filepathProSptr);
-        properties.push_back(descriptionMessageProSptr);
-        return properties;
-    }
-
-    // Register the Sample plugin through macro
-    MxpiPortInfo PluginClimb::DefineInputPorts() {
-        MxpiPortInfo inputPortInfo;
-        std::vector<std::vector<std::string>> value = {{"ANY"}};
-        MxPluginBase::GenerateStaticInputPortsInfo(value, inputPortInfo);
-        return inputPortInfo;
-    };
-
-    MxpiPortInfo PluginClimb::DefineOutputPorts() {
-        MxpiPortInfo outputPortInfo;
-        std::vector<std::vector<std::string>> value = {{"ANY"}};
-        MxPluginBase::GenerateStaticOutputPortsInfo(value, outputPortInfo);
-        return outputPortInfo;
-    }
-    // log in the txt of roi
-
-    void PluginClimb::readTxt(string file, vector<cv::Point> &roi) {
-        ifstream infile;
-        infile.open(file);
-        string str;
-        while (getline(infile, str)) {
-            int i = 0;
-            cv::Point p;
-            int count = 1;
-            while (i < str.length()) {
-                int j = i;
-                while (j < str.length() && str[j] != ';') {
-                    j++;
-                }
-                string s = str.substr(i, j - i);
-                if (count == 1) {
-                    p.x = atoi(s.c_str());
-                    count++;
-                } else if (count == 2) {
-                    p.y = atoi(s.c_str());
-                }
-                i = j + 1;
-            }
-            roi.push_back(p);
-        }
-        infile.close();
-    }
-}
-
-namespace {
-    MX_PLUGIN_GENERATE(PluginClimb)
-}
+/*
+* Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include <fstream>
+#include "math.h"
+#include <opencv2/opencv.hpp>
+#include "MxBase/Log/Log.h"
+#include "MxTools/PluginToolkit/base/MxPluginBase.h"
+#include "PluginClimb.h"
+
+using namespace MxPlugins;
+using namespace MxTools;
+using namespace std;
+
+namespace {
+    const int indx_num = 4;
+    const int y_indx = 3;
+    const int up_indx = 2;
+    const int in_indx = 1;
+}
+
+namespace MxPlugins {
+    APP_ERROR PluginClimb::Init(std::map<std::string, std::shared_ptr<void>> &configParamMap) {
+        LogInfo << "PluginClimb::Init start.";
+        APP_ERROR ret = APP_ERR_OK;
+        // Get the property values by key
+        std::shared_ptr<string> tracksourcePropSptr =
+                std::static_pointer_cast<string>(configParamMap["dataSourceTrack"]);
+        tracksource_ = *tracksourcePropSptr.get();
+        LogInfo << "PluginClimb::Init start.";
+        std::shared_ptr<string> dataSourceDetection =
+                std::static_pointer_cast<string>(configParamMap["dataSourceDetection"]);
+        detectionsource_ = *dataSourceDetection.get();
+        LogInfo << "PluginClimb::Init start.";
+        std::shared_ptr<string> descriptionMessageProSptr =
+                std::static_pointer_cast<string>(configParamMap["descriptionMessage"]);
+        descriptionMessage_ = *descriptionMessageProSptr.get();
+        LogInfo << "PluginClimb::Init start.";
+        // Configuration parameter
+        highthresh_ = *std::static_pointer_cast<int>(configParamMap["highThresh"]);
+        LogInfo << "PluginClimb::Init start.";
+        bufferlength_ = *std::static_pointer_cast<int>(configParamMap["bufferLength"]);
+        LogInfo << "PluginClimb::Init start.";
+        ratio_ = *std::static_pointer_cast<float>(configParamMap["detectRatio"]);
+        LogInfo << "PluginClimb::Init start.";
+        detectsleep_ = *std::static_pointer_cast<int>(configParamMap["detectSleep"]);
+        LogInfo << "PluginClimb::Init start.";
+        filepath_ = *std::static_pointer_cast<string>(configParamMap["filePath"]);
+        LogInfo << "PluginClimb::Init end.";
+        return APP_ERR_OK;
+    }
+
+    APP_ERROR PluginClimb::DeInit() {
+        LogInfo << "PluginClimb::DeInit end.";
+        return APP_ERR_OK;
+    }
+
+    APP_ERROR PluginClimb::SetMxpiErrorInfo(MxpiBuffer &buffer, const std::string pluginName,
+                                            const MxpiErrorInfo mxpiErrorInfo) {
+        APP_ERROR ret = APP_ERR_OK;
+        // Define an object of MxpiMetadataManager
+        MxpiMetadataManager mxpiMetadataManager(buffer);
+        ret = mxpiMetadataManager.AddErrorInfo(pluginName, mxpiErrorInfo);
+        if (ret != APP_ERR_OK) {
+            LogError << "Failed to AddErrorInfo.";
+            return ret;
+        }
+        ret = SendData(0, buffer);
+        return ret;
+    }
+
+    APP_ERROR PluginClimb::Process(std::vector<MxpiBuffer *> &mxpiBuffer) {
+        LogInfo << "PluginClimb::Process start";
+        MxpiBuffer *buffer = mxpiBuffer[0];
+        MxpiMetadataManager mxpiMetadataManager(*buffer);
+        MxpiErrorInfo mxpiErrorInfo;
+        ErrorInfo_.str("");
+        auto errorInfoPtr = mxpiMetadataManager.GetErrorInfo();
+        if (errorInfoPtr != nullptr) {
+            ErrorInfo_ << GetError(APP_ERR_COMM_FAILURE, pluginName_)
+                       << "PluginClimb process is not implemented";
+            mxpiErrorInfo.ret = APP_ERR_COMM_FAILURE;
+            mxpiErrorInfo.errorInfo = ErrorInfo_.str();
+            SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
+            LogError << "PluginClimb process is not implemented";
+            return APP_ERR_COMM_FAILURE;
+        }
+        // Get the data from buffer
+        shared_ptr<void> metadata = mxpiMetadataManager.GetMetadata(tracksource_);
+        shared_ptr<void> Detect = mxpiMetadataManager.GetMetadata(detectionsource_);
+        if (metadata == nullptr) {
+            ErrorInfo_ << GetError(APP_ERR_METADATA_IS_NULL, pluginName_)
+                       << "Metadata is NULL, failed";
+            mxpiErrorInfo.ret = APP_ERR_METADATA_IS_NULL;
+            mxpiErrorInfo.errorInfo = ErrorInfo_.str();
+            SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
+            return APP_ERR_METADATA_IS_NULL; // self define the error code
+        }
+        // get trackletlist
+        std::shared_ptr<MxpiTrackLetList> srcTrackLetListSptr = std::static_pointer_cast<MxpiTrackLetList>(metadata);
+        std::shared_ptr<MxpiObjectList> srcObjectListSptr = std::static_pointer_cast<MxpiObjectList>(Detect);
+        // update data
+        if (pathflag == 0) {
+            readTxt(filepath_, roi);
+            pathflag = 1;
+        }
+        std::shared_ptr<MxTools::MxpiAttributeList> result = std::make_shared<MxTools::MxpiAttributeList>();
+        MxpiAttribute *mxpiAttribute = result->add_attributevec();
+        if (sleeptime == 0) {
+            LogInfo << "PluginClimb start";
+            int alarm = calculate(bufferlength_, highthresh_, ratio_, roi, srcTrackLetListSptr,
+                                  srcObjectListSptr);
+            if (alarm == 1) {
+                alarm_count++;
+                LogInfo << "Alarmed " << alarm_count << " times";
+                trackdata.clear();
+                sleeptime = detectsleep_;
+                // Send the data to downstream plugin
+                mxpiAttribute->set_attrname("Alarm Climb up");
+                APP_ERROR ret = mxpiMetadataManager.AddProtoMetadata(pluginName_,
+                                                                     static_pointer_cast<void>(result));
+                if (ret != APP_ERR_OK) {
+                    ErrorInfo_ << GetError(ret, pluginName_) << "PluginClimb add metadata failed.";
+                    mxpiErrorInfo.ret = ret;
+                    mxpiErrorInfo.errorInfo = ErrorInfo_.str();
+                    SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
+                    return ret;
+                }
+            } else {
+                mxpiAttribute->set_attrname("No Alarm");
+                APP_ERROR ret = mxpiMetadataManager.AddProtoMetadata(pluginName_,
+                                                                     static_pointer_cast<void>(result));
+                if (ret != APP_ERR_OK) {
+                    ErrorInfo_ << GetError(ret, pluginName_) << "PluginClimb add metadata failed.";
+                    mxpiErrorInfo.ret = ret;
+                    mxpiErrorInfo.errorInfo = ErrorInfo_.str();
+                    SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
+                    return ret;
+                }
+            }
+        } else {
+            mxpiAttribute->set_attrname("Alarmed in a short period of time");
+            APP_ERROR ret = mxpiMetadataManager.AddProtoMetadata(pluginName_,
+                                                                 static_pointer_cast<void>(result));
+            if (ret != APP_ERR_OK) {
+                ErrorInfo_ << GetError(ret, pluginName_) << "PluginClimb add metadata failed.";
+                mxpiErrorInfo.ret = ret;
+                mxpiErrorInfo.errorInfo = ErrorInfo_.str();
+                SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
+                return ret;
+            }
+            sleeptime--;
+        }
+        LogInfo << "PluginClimb end";
+        SendData(0, *buffer);
+        LogInfo << "PluginClimb::Process end";
+        return APP_ERR_OK;
+    }
+
+    int PluginClimb::calculate(int bufferlength_, int highthresh_, float ratio_,
+                               vector<cv::Point> roi,
+                               std::shared_ptr<MxpiTrackLetList> srcTrackLetListSptr,
+                               std::shared_ptr<MxpiObjectList> srcObjectListSptr) {
+        int alarm = 0;
+        for (uint32_t i = 0; i < (uint32_t) srcTrackLetListSptr->trackletvec_size(); i++) {
+            auto &trackObject = srcTrackLetListSptr->trackletvec(i);
+            if (trackObject.headervec_size() == 0) {
+                continue;
+                // As long as the person who has appeared will have a trackobject.
+                // Determine whether this id appears in the current frame.
+            }
+            auto &detectObject = srcObjectListSptr->objectvec(trackObject.headervec(0).memberid());
+            if (detectObject.classvec(0).classid() != 0) {
+                continue;
+            }
+            int cnt_x = (detectObject.x0() + detectObject.x1()) / 2;
+            int cnt_y = (detectObject.y0() + detectObject.y1()) / 2;
+            if (trackdata.count(trackObject.trackid()) == 0) {
+                int up_num = 0;
+                int in_num = 0;
+                if (cv::pointPolygonTest(roi, cv::Point(cnt_x, cnt_y), false) > 0) {
+                    in_num += 1;
+                }
+                trackdata[trackObject.trackid()].push_back(cnt_x); // store cnt_x
+                trackdata[trackObject.trackid()].push_back(cnt_y); // store cnt_y
+                trackdata[trackObject.trackid()].push_back(up_num); // store up_num
+                trackdata[trackObject.trackid()].push_back(in_num); // store in_num
+            } else {
+                int up_num = trackdata[trackObject.trackid()][trackdata[trackObject.trackid()].size() - up_indx];
+                int in_num = trackdata[trackObject.trackid()].back();
+                if (cv::pointPolygonTest(roi, cv::Point(cnt_x, cnt_y), false) > 0) {
+                    in_num = trackdata[trackObject.trackid()].back() + 1;
+                }  // if the target is in the area, in_num ++
+                if (cnt_y > trackdata[trackObject.trackid()][trackdata[trackObject.trackid()].size() - y_indx]) {
+                    up_num = trackdata[trackObject.trackid()][trackdata[trackObject.trackid()].size() - up_indx] + 1;
+                } // if the target is rising, up_num ++
+                trackdata[trackObject.trackid()].push_back(cnt_x); // store cnt_x
+                trackdata[trackObject.trackid()].push_back(cnt_y); // store cnt_y
+                trackdata[trackObject.trackid()].push_back(up_num); // store up_num
+                trackdata[trackObject.trackid()].push_back(in_num); // store in_num     
+            }
+            if (trackdata[trackObject.trackid()].size() == indx_num * bufferlength_) {
+                if (trackdata[trackObject.trackid()][indx_num * bufferlength_ - up_indx] >
+                    (int) (bufferlength_ * ratio_)
+                    && (trackdata[trackObject.trackid()][indx_num * bufferlength_ - in_indx] >
+                        (int) (bufferlength_ * ratio_))
+                    && trackdata[trackObject.trackid()][indx_num * bufferlength_ - y_indx] -
+                       trackdata[trackObject.trackid()][1] > highthresh_) {
+                    alarm = 1;
+                } else {
+                    // Climbing up judgment failed, delete the last frame of the queue, continue to load data
+                    std::vector<int> tmp(trackdata[trackObject.trackid()].begin() + indx_num,
+                                         trackdata[trackObject.trackid()].end());
+                    trackdata[trackObject.trackid()] = tmp;
+                }
+            }
+        }
+        return alarm;
+    }
+
+    std::vector<std::shared_ptr<void>> PluginClimb::DefineProperties() {
+        // Define an A to store properties
+        std::vector<std::shared_ptr<void>> properties;
+        // Set the type and related information of the properties, and the key is the name
+        auto tracksourceProSptr =
+                std::make_shared<ElementProperty<string >>(ElementProperty<string>{
+                        STRING, "dataSourceTrack", "name",
+                        "the name of previous plugin", "mxpi_motsimplesort0", "NULL",
+                        "NULL"});
+
+        auto detectsourceProSptr =
+                std::make_shared<ElementProperty<string >>(ElementProperty<string>{
+                        STRING, "dataSourceDetection", "name",
+                        "the name of previous plugin", "mxpi_fairmot0",
+                        "NULL", "NULL"});
+
+        auto highthreshProSptr =
+                std::make_shared<ElementProperty<int >>(ElementProperty<int>{
+                        UINT, "highThresh", "name",
+                        "the name of previous plugin", 8,
+                        0, 1000});
+
+        auto bufferlengthProSptr =
+                std::make_shared<ElementProperty<int >>(ElementProperty<int>{
+                        UINT, "bufferLength", "name",
+                        "the name of previous plugin", 10,
+                        8, 1000});
+
+        auto ratioProSptr =
+                std::make_shared<ElementProperty<float >>(ElementProperty<float>{
+                        FLOAT, "detectRatio", "name",
+                        "the name of previous plugin", 0.75,
+                        0, 1});
+
+        auto sleepProSptr =
+                std::make_shared<ElementProperty<int >>(ElementProperty<int>{
+                        UINT, "detectSleep", "name", " ", 8, 0,
+                        100});
+
+        auto filepathProSptr =
+                std::make_shared<ElementProperty<string >>(ElementProperty<string>{
+                        STRING, "filePath", "name",
+                        "the name of previous plugin", "mxpi_fairmot0",
+                        "NULL", "NULL"});
+
+        auto descriptionMessageProSptr =
+                std::make_shared<ElementProperty<string >>(ElementProperty<string>{
+                        STRING, "descriptionMessage", "message",
+                        "Description mesasge of plugin",
+                        "This is PluginClimb", "NULL", "NULL"});
+        properties.push_back(tracksourceProSptr);
+        properties.push_back(detectsourceProSptr);
+        properties.push_back(highthreshProSptr);
+        properties.push_back(bufferlengthProSptr);
+        properties.push_back(ratioProSptr);
+        properties.push_back(sleepProSptr);
+        properties.push_back(filepathProSptr);
+        properties.push_back(descriptionMessageProSptr);
+        return properties;
+    }
+
+    // Register the Sample plugin through macro
+    MxpiPortInfo PluginClimb::DefineInputPorts() {
+        MxpiPortInfo inputPortInfo;
+        std::vector<std::vector<std::string>> value = {{"ANY"}};
+        MxPluginBase::GenerateStaticInputPortsInfo(value, inputPortInfo);
+        return inputPortInfo;
+    };
+
+    MxpiPortInfo PluginClimb::DefineOutputPorts() {
+        MxpiPortInfo outputPortInfo;
+        std::vector<std::vector<std::string>> value = {{"ANY"}};
+        MxPluginBase::GenerateStaticOutputPortsInfo(value, outputPortInfo);
+        return outputPortInfo;
+    }
+    // log in the txt of roi
+
+    void PluginClimb::readTxt(string file, vector<cv::Point> &roi) {
+        ifstream infile;
+        infile.open(file);
+        string str;
+        while (getline(infile, str)) {
+            int i = 0;
+            cv::Point p;
+            int count = 1;
+            while (i < str.length()) {
+                int j = i;
+                while (j < str.length() && str[j] != ';') {
+                    j++;
+                }
+                string s = str.substr(i, j - i);
+                if (count == 1) {
+                    p.x = atoi(s.c_str());
+                    count++;
+                } else if (count == 2) {
+                    p.y = atoi(s.c_str());
+                }
+                i = j + 1;
+            }
+            roi.push_back(p);
+        }
+        infile.close();
+    }
+}
+
+namespace {
+    MX_PLUGIN_GENERATE(PluginClimb)
+}
diff --git a/contrib/ActionRecognition/plugins/PluginClimb/PluginClimb.h b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginClimb/PluginClimb.h
similarity index 96%
rename from contrib/ActionRecognition/plugins/PluginClimb/PluginClimb.h
rename to mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginClimb/PluginClimb.h
index 0c94534913558f485b60af53040970cf5df70687..151449e952b06538a2becb4aeb8d551866feca77 100644
--- a/contrib/ActionRecognition/plugins/PluginClimb/PluginClimb.h
+++ b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginClimb/PluginClimb.h
@@ -1,127 +1,127 @@
-/*
-* Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-* http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-#ifndef SDKMEMORY_PLUGINCLIMB_H
-#define SDKMEMORY_PLUGINCLIMB_H
-
-#include <opencv2/opencv.hpp>
-#include "MxBase/ErrorCode/ErrorCode.h"
-#include "MxTools/PluginToolkit/base/MxPluginGenerator.h"
-#include "MxTools/PluginToolkit/base/MxPluginBase.h"
-#include "MxTools/PluginToolkit/metadata/MxpiMetadataManager.h"
-#include "MxTools/Proto/MxpiDataType.pb.h"
-
-/**
-* @api
-* @brief Definition of PluginClimb class.
-*/
-
-namespace MxPlugins {
-    class PluginClimb : public MxTools::MxPluginBase {
-    public:
-        /**
-        * @api
-        * @brief Initialize configure parameter.
-        * @param configParamMap
-        * @return APP_ERROR
-        */
-        APP_ERROR Init(std::map<std::string, std::shared_ptr<void>> &configParamMap) override;
-
-        /**
-        * * @api
-        * @brief DeInitialize configure parameter.
-        * @return APP_ERROR
-        */
-        APP_ERROR DeInit() override;
-
-        /**
-        * @api
-        * @brief Process the data of MxpiBuffer.
-        * @param mxpiBuffer
-        * @return APP_ERROR
-        */
-        APP_ERROR Process(std::vector<MxTools::MxpiBuffer *> &mxpiBuffer) override;
-
-        /**
-        * @api
-        * @brief Definition the parameter of configure properties.
-        * @return std::vector<std::shared_ptr<void>>
-        */
-        static std::vector<std::shared_ptr<void>> DefineProperties();
-
-        /**
-        * @api
-        * @brief Get the number of class id and confidence from model inference.
-        * @param key
-        * @param buffer
-        * @return APP_ERROR
-        */
-        static MxTools::MxpiPortInfo DefineInputPorts();
-
-        static MxTools::MxpiPortInfo DefineOutputPorts();
-
-        static void readTxt(std::string file, std::vector<cv::Point> &roi);
-
-        /**
-        * @api
-        * @brief log in the txt of roi.
-        * @param std::string file
-        * @return td::vector <cv::Point> &roi
-        */
-        static int distance(int x0, int y0, int x1, int y1);
-
-        /**
-        * @api
-        * @brief Calculate the distance between two points.
-        * @param int
-        * @return int
-        */
-        int calculate(int bufferlength_, int highthresh_, float ratio_, std::vector<cv::Point> roi,
-                      std::shared_ptr<MxTools::MxpiTrackLetList> srcTrackLetListSptr,
-                      std::shared_ptr<MxTools::MxpiObjectList> srcObjectListSptr);
-        /**
-        * @api
-        * @brief Data processing.
-        * @return int
-        */
-    private:
-        APP_ERROR SetMxpiErrorInfo(MxTools::MxpiBuffer &buffer,
-                                   const std::string pluginName,
-                                   const MxTools::MxpiErrorInfo mxpiErrorInfo);
-
-        std::string tracksource_;
-        std::string detectionsource_;
-        std::string descriptionMessage_;
-        std::ostringstream ErrorInfo_;
-        std::map<int, std::vector<int>> trackdata;
-        int confthresh_;
-        int confframes_;
-        int confsleep_;
-        int confhigh_;
-        int frame_num = 0;
-        int sleeptime = 0;
-        int pathflag = 0;
-
-        int test_framenum = 0;
-        int highthresh_;
-        int bufferlength_;
-        float ratio_;
-        int detectsleep_;
-        int alarm_count = 0;
-        std::string filepath_;
-        std::vector<cv::Point> roi;
-    };
-}
-#endif
+/*
+* Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+#ifndef SDKMEMORY_PLUGINCLIMB_H
+#define SDKMEMORY_PLUGINCLIMB_H
+
+#include <opencv2/opencv.hpp>
+#include "MxBase/ErrorCode/ErrorCode.h"
+#include "MxTools/PluginToolkit/base/MxPluginGenerator.h"
+#include "MxTools/PluginToolkit/base/MxPluginBase.h"
+#include "MxTools/PluginToolkit/metadata/MxpiMetadataManager.h"
+#include "MxTools/Proto/MxpiDataType.pb.h"
+
+/**
+* @api
+* @brief Definition of PluginClimb class.
+*/
+
+namespace MxPlugins {
+    class PluginClimb : public MxTools::MxPluginBase {
+    public:
+        /**
+        * @api
+        * @brief Initialize configure parameter.
+        * @param configParamMap
+        * @return APP_ERROR
+        */
+        APP_ERROR Init(std::map<std::string, std::shared_ptr<void>> &configParamMap) override;
+
+        /**
+        * * @api
+        * @brief DeInitialize configure parameter.
+        * @return APP_ERROR
+        */
+        APP_ERROR DeInit() override;
+
+        /**
+        * @api
+        * @brief Process the data of MxpiBuffer.
+        * @param mxpiBuffer
+        * @return APP_ERROR
+        */
+        APP_ERROR Process(std::vector<MxTools::MxpiBuffer *> &mxpiBuffer) override;
+
+        /**
+        * @api
+        * @brief Definition the parameter of configure properties.
+        * @return std::vector<std::shared_ptr<void>>
+        */
+        static std::vector<std::shared_ptr<void>> DefineProperties();
+
+        /**
+        * @api
+        * @brief Get the number of class id and confidence from model inference.
+        * @param key
+        * @param buffer
+        * @return APP_ERROR
+        */
+        static MxTools::MxpiPortInfo DefineInputPorts();
+
+        static MxTools::MxpiPortInfo DefineOutputPorts();
+
+        static void readTxt(std::string file, std::vector<cv::Point> &roi);
+
+        /**
+        * @api
+        * @brief log in the txt of roi.
+        * @param std::string file
+        * @return td::vector <cv::Point> &roi
+        */
+        static int distance(int x0, int y0, int x1, int y1);
+
+        /**
+        * @api
+        * @brief Calculate the distance between two points.
+        * @param int
+        * @return int
+        */
+        int calculate(int bufferlength_, int highthresh_, float ratio_, std::vector<cv::Point> roi,
+                      std::shared_ptr<MxTools::MxpiTrackLetList> srcTrackLetListSptr,
+                      std::shared_ptr<MxTools::MxpiObjectList> srcObjectListSptr);
+        /**
+        * @api
+        * @brief Data processing.
+        * @return int
+        */
+    private:
+        APP_ERROR SetMxpiErrorInfo(MxTools::MxpiBuffer &buffer,
+                                   const std::string pluginName,
+                                   const MxTools::MxpiErrorInfo mxpiErrorInfo);
+
+        std::string tracksource_;
+        std::string detectionsource_;
+        std::string descriptionMessage_;
+        std::ostringstream ErrorInfo_;
+        std::map<int, std::vector<int>> trackdata;
+        int confthresh_;
+        int confframes_;
+        int confsleep_;
+        int confhigh_;
+        int frame_num = 0;
+        int sleeptime = 0;
+        int pathflag = 0;
+
+        int test_framenum = 0;
+        int highthresh_;
+        int bufferlength_;
+        float ratio_;
+        int detectsleep_;
+        int alarm_count = 0;
+        std::string filepath_;
+        std::vector<cv::Point> roi;
+    };
+}
+#endif
diff --git a/contrib/ActionRecognition/plugins/PluginClimb/build.sh b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginClimb/build.sh
similarity index 100%
rename from contrib/ActionRecognition/plugins/PluginClimb/build.sh
rename to mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginClimb/build.sh
diff --git a/contrib/ActionRecognition/plugins/PluginCounter/CMakeLists.txt b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginCounter/CMakeLists.txt
similarity index 100%
rename from contrib/ActionRecognition/plugins/PluginCounter/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginCounter/CMakeLists.txt
diff --git a/contrib/ActionRecognition/plugins/PluginCounter/PluginCounter.cpp b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginCounter/PluginCounter.cpp
similarity index 97%
rename from contrib/ActionRecognition/plugins/PluginCounter/PluginCounter.cpp
rename to mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginCounter/PluginCounter.cpp
index b3916bcba78dc36d600d83226751b3bc822282e3..8cbef7341d83acd429737e488b9c505dfb74d75d 100644
--- a/contrib/ActionRecognition/plugins/PluginCounter/PluginCounter.cpp
+++ b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginCounter/PluginCounter.cpp
@@ -1,156 +1,156 @@
-/*
-* Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-* http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-
-#include "math.h"
-#include "MxBase/Log/Log.h"
-#include "MxTools/Proto/MxpiDumpData.pb.h"
-#include "MxTools/Proto/MxpiDataType.pb.h"
-#include "MxTools/PluginToolkit/base/MxPluginBase.h"
-#include "PluginCounter.h"
-
-using namespace MxPlugins;
-using namespace MxTools;
-using namespace std;
-
-namespace {
-    const string SAMPLE_KEY = "MxpiObjectList";
-}
-
-namespace MxPlugins {
-    APP_ERROR PluginCounter::Init(std::map<std::string, std::shared_ptr<void>> &configParamMap) {
-        LogInfo << "PluginCounter::Init start.";
-        APP_ERROR ret = APP_ERR_OK;
-
-        // Get the property values by key
-        std::shared_ptr<string> tracksourcePropSptr =
-                std::static_pointer_cast<string>(configParamMap["dataSourceTrack"]);
-        tracksource_ = *tracksourcePropSptr.get();
-
-        std::shared_ptr<string> descriptionMessageProSptr =
-                std::static_pointer_cast<string>(configParamMap["descriptionMessage"]);
-        descriptionMessage_ = *descriptionMessageProSptr.get();
-
-        return APP_ERR_OK;
-    }
-
-    APP_ERROR PluginCounter::DeInit() {
-        LogInfo << "PluginCounter::DeInit end.";
-        return APP_ERR_OK;
-    }
-
-    APP_ERROR PluginCounter::SetMxpiErrorInfo(MxpiBuffer &buffer, const std::string pluginName,
-                                              const MxpiErrorInfo mxpiErrorInfo) {
-        APP_ERROR ret = APP_ERR_OK;
-        // Define an object of MxpiMetadataManager
-        MxpiMetadataManager mxpiMetadataManager(buffer);
-        ret = mxpiMetadataManager.AddErrorInfo(pluginName, mxpiErrorInfo);
-        if (ret != APP_ERR_OK) {
-            LogError << "Failed to AddErrorInfo.";
-            return ret;
-        }
-        ret = SendData(0, buffer);
-        return ret;
-    }
-
-    APP_ERROR PluginCounter::Process(std::vector<MxpiBuffer *> &mxpiBuffer) {
-        LogInfo << "PluginCounter::Process start";
-        MxpiBuffer *buffer = mxpiBuffer[0];
-
-        MxpiMetadataManager mxpiMetadataManager(*buffer);
-        MxpiErrorInfo mxpiErrorInfo;
-        ErrorInfo_.str("");
-        auto errorInfoPtr = mxpiMetadataManager.GetErrorInfo();
-        frame++;
-        LogInfo << "当前帧号 :" << frame;
-        if (errorInfoPtr != nullptr) {
-            ErrorInfo_ << GetError(APP_ERR_COMM_FAILURE, pluginName_) << "PluginCounter process is not implemented";
-            mxpiErrorInfo.ret = APP_ERR_COMM_FAILURE;
-            mxpiErrorInfo.errorInfo = ErrorInfo_.str();
-            SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
-            LogError << "PluginCounter process is not implemented";
-            return APP_ERR_COMM_FAILURE;
-        }
-        // Get the data from buffer
-        shared_ptr<void> metadata = mxpiMetadataManager.GetMetadata(tracksource_);
-
-        if (metadata == nullptr) {
-            ErrorInfo_ << GetError(APP_ERR_METADATA_IS_NULL, pluginName_) << "Metadata is NULL, failed";
-            mxpiErrorInfo.ret = APP_ERR_METADATA_IS_NULL;
-            mxpiErrorInfo.errorInfo = ErrorInfo_.str();
-            SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
-            return APP_ERR_METADATA_IS_NULL; // self define the error code
-        }
-        // check whether the proto struct name is MxpiObjectList
-        google::protobuf::Message *msg = (google::protobuf::Message *) metadata.get();
-
-        // get trackletlist
-        std::shared_ptr<MxpiTrackLetList> srcTrackLetListSptr = std::static_pointer_cast<MxpiTrackLetList>(metadata);
-        // Send the data to downstream plugin
-        std::shared_ptr<MxTools::MxpiAttribute> result = std::make_shared<MxTools::MxpiAttribute>();
-        result->set_attrname("PluginCounter");
-        APP_ERROR ret = mxpiMetadataManager.AddProtoMetadata(pluginName_, result);
-
-        if (ret != APP_ERR_OK) {
-            ErrorInfo_ << GetError(ret, pluginName_) << "PluginCounter add metadata failed.";
-            mxpiErrorInfo.ret = ret;
-            mxpiErrorInfo.errorInfo = ErrorInfo_.str();
-            SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
-            return ret;
-        }
-        // Send the data to downstream plugin
-        SendData(0, *buffer);
-        LogInfo << "PluginCounter::Process end";
-        return APP_ERR_OK;
-    }
-
-    std::vector<std::shared_ptr<void>> PluginCounter::DefineProperties() {
-        // Define an A to store properties
-        std::vector<std::shared_ptr<void>> properties;
-        // Set the type and related information of the properties, and the key is the name
-        auto tracksourceProSptr =
-                std::make_shared<ElementProperty<string >>(ElementProperty<string>{
-                        STRING, "dataSourceTrack", "name",
-                        "the name of previous plugin", "mxpi_motsimplesort0", "NULL",
-                        "NULL"});
-
-        auto descriptionMessageProSptr =
-                std::make_shared<ElementProperty<string >>(ElementProperty<string>{
-                        STRING, "descriptionMessage", "message",
-                        "Description mesasge of plugin",
-                        "This is PluginCounter", "NULL", "NULL"});
-
-        properties.push_back(tracksourceProSptr);
-        properties.push_back(descriptionMessageProSptr);
-        return properties;
-    }
-    // Register the Sample plugin through macro
-    MxpiPortInfo PluginCounter::DefineInputPorts() {
-        MxpiPortInfo inputPortInfo;
-        std::vector<std::vector<std::string>> value = {{"ANY"}};
-        MxPluginBase::GenerateStaticInputPortsInfo(value, inputPortInfo);
-        return inputPortInfo;
-    };
-
-    MxpiPortInfo PluginCounter::DefineOutputPorts() {
-        MxpiPortInfo outputPortInfo;
-        std::vector<std::vector<std::string>> value = {{"ANY"}};
-        MxPluginBase::GenerateStaticOutputPortsInfo(value, outputPortInfo);
-        return outputPortInfo;
-    }
-}
-namespace {
-    MX_PLUGIN_GENERATE(PluginCounter)
-}
+/*
+* Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "math.h"
+#include "MxBase/Log/Log.h"
+#include "MxTools/Proto/MxpiDumpData.pb.h"
+#include "MxTools/Proto/MxpiDataType.pb.h"
+#include "MxTools/PluginToolkit/base/MxPluginBase.h"
+#include "PluginCounter.h"
+
+using namespace MxPlugins;
+using namespace MxTools;
+using namespace std;
+
+namespace {
+    const string SAMPLE_KEY = "MxpiObjectList";
+}
+
+namespace MxPlugins {
+    APP_ERROR PluginCounter::Init(std::map<std::string, std::shared_ptr<void>> &configParamMap) {
+        LogInfo << "PluginCounter::Init start.";
+        APP_ERROR ret = APP_ERR_OK;
+
+        // Get the property values by key
+        std::shared_ptr<string> tracksourcePropSptr =
+                std::static_pointer_cast<string>(configParamMap["dataSourceTrack"]);
+        tracksource_ = *tracksourcePropSptr.get();
+
+        std::shared_ptr<string> descriptionMessageProSptr =
+                std::static_pointer_cast<string>(configParamMap["descriptionMessage"]);
+        descriptionMessage_ = *descriptionMessageProSptr.get();
+
+        return APP_ERR_OK;
+    }
+
+    APP_ERROR PluginCounter::DeInit() {
+        LogInfo << "PluginCounter::DeInit end.";
+        return APP_ERR_OK;
+    }
+
+    APP_ERROR PluginCounter::SetMxpiErrorInfo(MxpiBuffer &buffer, const std::string pluginName,
+                                              const MxpiErrorInfo mxpiErrorInfo) {
+        APP_ERROR ret = APP_ERR_OK;
+        // Define an object of MxpiMetadataManager
+        MxpiMetadataManager mxpiMetadataManager(buffer);
+        ret = mxpiMetadataManager.AddErrorInfo(pluginName, mxpiErrorInfo);
+        if (ret != APP_ERR_OK) {
+            LogError << "Failed to AddErrorInfo.";
+            return ret;
+        }
+        ret = SendData(0, buffer);
+        return ret;
+    }
+
+    APP_ERROR PluginCounter::Process(std::vector<MxpiBuffer *> &mxpiBuffer) {
+        LogInfo << "PluginCounter::Process start";
+        MxpiBuffer *buffer = mxpiBuffer[0];
+
+        MxpiMetadataManager mxpiMetadataManager(*buffer);
+        MxpiErrorInfo mxpiErrorInfo;
+        ErrorInfo_.str("");
+        auto errorInfoPtr = mxpiMetadataManager.GetErrorInfo();
+        frame++;
+        LogInfo << "当前帧号 :" << frame;
+        if (errorInfoPtr != nullptr) {
+            ErrorInfo_ << GetError(APP_ERR_COMM_FAILURE, pluginName_) << "PluginCounter process is not implemented";
+            mxpiErrorInfo.ret = APP_ERR_COMM_FAILURE;
+            mxpiErrorInfo.errorInfo = ErrorInfo_.str();
+            SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
+            LogError << "PluginCounter process is not implemented";
+            return APP_ERR_COMM_FAILURE;
+        }
+        // Get the data from buffer
+        shared_ptr<void> metadata = mxpiMetadataManager.GetMetadata(tracksource_);
+
+        if (metadata == nullptr) {
+            ErrorInfo_ << GetError(APP_ERR_METADATA_IS_NULL, pluginName_) << "Metadata is NULL, failed";
+            mxpiErrorInfo.ret = APP_ERR_METADATA_IS_NULL;
+            mxpiErrorInfo.errorInfo = ErrorInfo_.str();
+            SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
+            return APP_ERR_METADATA_IS_NULL; // self define the error code
+        }
+        // check whether the proto struct name is MxpiObjectList
+        google::protobuf::Message *msg = (google::protobuf::Message *) metadata.get();
+
+        // get trackletlist
+        std::shared_ptr<MxpiTrackLetList> srcTrackLetListSptr = std::static_pointer_cast<MxpiTrackLetList>(metadata);
+        // Send the data to downstream plugin
+        std::shared_ptr<MxTools::MxpiAttribute> result = std::make_shared<MxTools::MxpiAttribute>();
+        result->set_attrname("PluginCounter");
+        APP_ERROR ret = mxpiMetadataManager.AddProtoMetadata(pluginName_, result);
+
+        if (ret != APP_ERR_OK) {
+            ErrorInfo_ << GetError(ret, pluginName_) << "PluginCounter add metadata failed.";
+            mxpiErrorInfo.ret = ret;
+            mxpiErrorInfo.errorInfo = ErrorInfo_.str();
+            SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
+            return ret;
+        }
+        // Send the data to downstream plugin
+        SendData(0, *buffer);
+        LogInfo << "PluginCounter::Process end";
+        return APP_ERR_OK;
+    }
+
+    std::vector<std::shared_ptr<void>> PluginCounter::DefineProperties() {
+        // Define an A to store properties
+        std::vector<std::shared_ptr<void>> properties;
+        // Set the type and related information of the properties, and the key is the name
+        auto tracksourceProSptr =
+                std::make_shared<ElementProperty<string >>(ElementProperty<string>{
+                        STRING, "dataSourceTrack", "name",
+                        "the name of previous plugin", "mxpi_motsimplesort0", "NULL",
+                        "NULL"});
+
+        auto descriptionMessageProSptr =
+                std::make_shared<ElementProperty<string >>(ElementProperty<string>{
+                        STRING, "descriptionMessage", "message",
+                        "Description mesasge of plugin",
+                        "This is PluginCounter", "NULL", "NULL"});
+
+        properties.push_back(tracksourceProSptr);
+        properties.push_back(descriptionMessageProSptr);
+        return properties;
+    }
+    // Register the Sample plugin through macro
+    MxpiPortInfo PluginCounter::DefineInputPorts() {
+        MxpiPortInfo inputPortInfo;
+        std::vector<std::vector<std::string>> value = {{"ANY"}};
+        MxPluginBase::GenerateStaticInputPortsInfo(value, inputPortInfo);
+        return inputPortInfo;
+    };
+
+    MxpiPortInfo PluginCounter::DefineOutputPorts() {
+        MxpiPortInfo outputPortInfo;
+        std::vector<std::vector<std::string>> value = {{"ANY"}};
+        MxPluginBase::GenerateStaticOutputPortsInfo(value, outputPortInfo);
+        return outputPortInfo;
+    }
+}
+namespace {
+    MX_PLUGIN_GENERATE(PluginCounter)
+}
diff --git a/contrib/ActionRecognition/plugins/PluginCounter/PluginCounter.h b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginCounter/PluginCounter.h
similarity index 96%
rename from contrib/ActionRecognition/plugins/PluginCounter/PluginCounter.h
rename to mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginCounter/PluginCounter.h
index 25200b202f964da70781ecd32f47682738002d6b..f79791fe4d4bc50728f41299b177d86f4b497ea1 100644
--- a/contrib/ActionRecognition/plugins/PluginCounter/PluginCounter.h
+++ b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginCounter/PluginCounter.h
@@ -1,96 +1,96 @@
-/*
-* Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-* http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-#ifndef SDKMEMORY_PLUGINCOUNTER_H
-#define SDKMEMORY_PLUGINCOUNTER_H
-
-#include "MxBase/ErrorCode/ErrorCode.h"
-#include "MxTools/PluginToolkit/base/MxPluginGenerator.h"
-#include "MxTools/PluginToolkit/base/MxPluginBase.h"
-#include "MxTools/PluginToolkit/metadata/MxpiMetadataManager.h"
-#include "MxTools/Proto/MxpiDataType.pb.h"
-
-/**
-* @api
-* @brief Definition of PluginCounter class.
-*/
-
-namespace MxPlugins {
-    class PluginCounter : public MxTools::MxPluginBase {
-    public:
-        /**
-        * @api
-        * @brief Initialize configure parameter.
-        * @param configParamMap
-        * @return APP_ERROR
-        */
-        APP_ERROR Init(std::map <std::string, std::shared_ptr<void>> &configParamMap) override;
-
-        /**
-        * * @api
-        * @brief DeInitialize configure parameter.
-        * @return APP_ERROR
-        */
-        APP_ERROR DeInit() override;
-
-        /**
-        * @api
-        * @brief Process the data of MxpiBuffer.
-        * @param mxpiBuffer
-        * @return APP_ERROR
-        */
-        APP_ERROR Process(std::vector<MxTools::MxpiBuffer *> &mxpiBuffer) override;
-
-        /**
-        * @api
-        * @brief Definition the parameter of configure properties.
-        * @return std::vector<std::shared_ptr<void>>
-        */
-        static std::vector <std::shared_ptr<void>> DefineProperties();
-
-        /**
-        * @api
-        * @brief Get the number of class id and confidence from model inference.
-        * @param key
-        * @param buffer
-        * @return APP_ERROR
-        */
-        static MxTools::MxpiPortInfo DefineInputPorts();
-
-        /**
-        * @api
-        * @brief Define the input ports.
-        * @return MxpiPortInfo
-        */
-        static MxTools::MxpiPortInfo DefineOutputPorts();
-        /**
-        * @api
-        * @brief Define the output ports.
-        * @return MxpiPortInfo
-        */
-    private:
-        APP_ERROR SetMxpiErrorInfo(MxTools::MxpiBuffer &buffer,
-                                   const std::string pluginName,
-                                   const MxTools::MxpiErrorInfo mxpiErrorInfo);
-
-        std::string tracksource_;
-        std::string detectionsource_;
-        std::string descriptionMessage_;
-        std::ostringstream ErrorInfo_;
-        std::map<int, std::vector<int>> trackdata;
-        int frame = 0;
-    };
-}
+/*
+* Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+#ifndef SDKMEMORY_PLUGINCOUNTER_H
+#define SDKMEMORY_PLUGINCOUNTER_H
+
+#include "MxBase/ErrorCode/ErrorCode.h"
+#include "MxTools/PluginToolkit/base/MxPluginGenerator.h"
+#include "MxTools/PluginToolkit/base/MxPluginBase.h"
+#include "MxTools/PluginToolkit/metadata/MxpiMetadataManager.h"
+#include "MxTools/Proto/MxpiDataType.pb.h"
+
+/**
+* @api
+* @brief Definition of PluginCounter class.
+*/
+
+namespace MxPlugins {
+    class PluginCounter : public MxTools::MxPluginBase {
+    public:
+        /**
+        * @api
+        * @brief Initialize configure parameter.
+        * @param configParamMap
+        * @return APP_ERROR
+        */
+        APP_ERROR Init(std::map <std::string, std::shared_ptr<void>> &configParamMap) override;
+
+        /**
+        * * @api
+        * @brief DeInitialize configure parameter.
+        * @return APP_ERROR
+        */
+        APP_ERROR DeInit() override;
+
+        /**
+        * @api
+        * @brief Process the data of MxpiBuffer.
+        * @param mxpiBuffer
+        * @return APP_ERROR
+        */
+        APP_ERROR Process(std::vector<MxTools::MxpiBuffer *> &mxpiBuffer) override;
+
+        /**
+        * @api
+        * @brief Definition the parameter of configure properties.
+        * @return std::vector<std::shared_ptr<void>>
+        */
+        static std::vector <std::shared_ptr<void>> DefineProperties();
+
+        /**
+        * @api
+        * @brief Get the number of class id and confidence from model inference.
+        * @param key
+        * @param buffer
+        * @return APP_ERROR
+        */
+        static MxTools::MxpiPortInfo DefineInputPorts();
+
+        /**
+        * @api
+        * @brief Define the input ports.
+        * @return MxpiPortInfo
+        */
+        static MxTools::MxpiPortInfo DefineOutputPorts();
+        /**
+        * @api
+        * @brief Define the output ports.
+        * @return MxpiPortInfo
+        */
+    private:
+        APP_ERROR SetMxpiErrorInfo(MxTools::MxpiBuffer &buffer,
+                                   const std::string pluginName,
+                                   const MxTools::MxpiErrorInfo mxpiErrorInfo);
+
+        std::string tracksource_;
+        std::string detectionsource_;
+        std::string descriptionMessage_;
+        std::ostringstream ErrorInfo_;
+        std::map<int, std::vector<int>> trackdata;
+        int frame = 0;
+    };
+}
 #endif // SDKMEMORY_PLUGINCOUNTER_H
\ No newline at end of file
diff --git a/contrib/ActionRecognition/plugins/PluginCounter/build.sh b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginCounter/build.sh
similarity index 100%
rename from contrib/ActionRecognition/plugins/PluginCounter/build.sh
rename to mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginCounter/build.sh
diff --git a/contrib/ActionRecognition/plugins/PluginOutOfBed/CMakeLists.txt b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginOutOfBed/CMakeLists.txt
similarity index 100%
rename from contrib/ActionRecognition/plugins/PluginOutOfBed/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginOutOfBed/CMakeLists.txt
diff --git a/contrib/ActionRecognition/plugins/PluginOutOfBed/PluginOutOfBed.cpp b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginOutOfBed/PluginOutOfBed.cpp
similarity index 97%
rename from contrib/ActionRecognition/plugins/PluginOutOfBed/PluginOutOfBed.cpp
rename to mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginOutOfBed/PluginOutOfBed.cpp
index 4a0a29bb963dd4cc8df800c362528cc55c9d8e30..b84be6404415a8f8b2e3f608691a8a31d74ddbb0 100644
--- a/contrib/ActionRecognition/plugins/PluginOutOfBed/PluginOutOfBed.cpp
+++ b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginOutOfBed/PluginOutOfBed.cpp
@@ -1,286 +1,286 @@
-/*
- * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#include <opencv2/opencv.hpp>
-#include "MxBase/Log/Log.h"
-#include "PluginOutOfBed.h"
-
-using namespace MxPlugins;
-using namespace MxTools;
-using namespace std;
-
-namespace MxPlugins {
-    APP_ERROR PluginOutOfBed::Init(std::map<std::string, std::shared_ptr<void>> &configParamMap) {
-        LogInfo << "PluginOutOfBed::Init start.";
-        APP_ERROR ret = APP_ERR_OK;
-        // Get the property values by key
-        // Data from track plugin
-        std::shared_ptr<string> tracksourcePropSptr =
-                std::static_pointer_cast<string>(configParamMap["dataSourceTrack"]);
-        tracksource_ = *tracksourcePropSptr.get();
-        // Data from detect plugin
-        std::shared_ptr<string> detectsourcePropSptr =
-                std::static_pointer_cast<string>(configParamMap["dataSourceDetection"]);
-        detectionsource_ = *detectsourcePropSptr.get();
-        // Description message
-        std::shared_ptr<string> descriptionMessageProSptr =
-                std::static_pointer_cast<string>(configParamMap["descriptionMessage"]);
-        descriptionMessage_ = *descriptionMessageProSptr.get();
-        // Configuration parameter
-        confthres_ = *std::static_pointer_cast<uint>(configParamMap["detectThresh"]);
-        confratio_ = *std::static_pointer_cast<float>(configParamMap["detectRatio"]);
-        confsleep_ = *std::static_pointer_cast<uint>(configParamMap["detectSleep"]);
-        configpath = *std::static_pointer_cast<string>(configParamMap["configPath"]);
-        return APP_ERR_OK;
-    }
-
-    APP_ERROR PluginOutOfBed::DeInit() {
-        LogInfo << "PluginOutOfBed::DeInit end.";
-        return APP_ERR_OK;
-    }
-
-    APP_ERROR PluginOutOfBed::SetMxpiErrorInfo(MxpiBuffer &buffer, const std::string pluginName,
-                                               const MxpiErrorInfo mxpiErrorInfo) {
-        APP_ERROR ret = APP_ERR_OK;
-        // Define an object of MxpiMetadataManager
-        MxpiMetadataManager mxpiMetadataManager(buffer);
-        ret = mxpiMetadataManager.AddErrorInfo(pluginName, mxpiErrorInfo);
-        if (ret != APP_ERR_OK) {
-            LogError << "Failed to AddErrorInfo.";
-            return ret;
-        }
-        ret = SendData(0, buffer);
-        return ret;
-    }
-
-    APP_ERROR PluginOutOfBed::Process(std::vector<MxTools::MxpiBuffer *> &mxpiBuffer) {
-        MxpiBuffer *buffer = mxpiBuffer[0];
-        MxpiMetadataManager mxpiMetadataManager(*buffer);
-        MxpiErrorInfo mxpiErrorInfo;
-        ErrorInfo_.str("");
-        auto errorInfoPtr = mxpiMetadataManager.GetErrorInfo();
-        framesnum++;
-        if (errorInfoPtr != nullptr) {
-            ErrorInfo_ << GetError(APP_ERR_COMM_FAILURE, pluginName_) << "PluginOutOfBed process is not implemented";
-            mxpiErrorInfo.ret = APP_ERR_COMM_FAILURE;
-            mxpiErrorInfo.errorInfo = ErrorInfo_.str();
-            SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
-            LogError << "FairMOT_Climb process is not implemented";
-            return APP_ERR_COMM_FAILURE;
-        }
-        // Get the data from buffer
-        shared_ptr<void> metadata = mxpiMetadataManager.GetMetadata(tracksource_);
-        shared_ptr<void> Detect = mxpiMetadataManager.GetMetadata(detectionsource_);
-        if (metadata == nullptr) {
-            ErrorInfo_ << GetError(APP_ERR_METADATA_IS_NULL, pluginName_) << "Metadata is NULL, failed";
-            mxpiErrorInfo.ret = APP_ERR_METADATA_IS_NULL;
-            mxpiErrorInfo.errorInfo = ErrorInfo_.str();
-            SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
-            return APP_ERR_METADATA_IS_NULL; // self define the error code
-        }
-        // get trackletlist
-        std::shared_ptr<MxpiTrackLetList> srcTrackLetListSptr = std::static_pointer_cast<MxpiTrackLetList>(metadata);
-        std::shared_ptr<MxpiObjectList> srcObjectListSptr = std::static_pointer_cast<MxpiObjectList>(Detect);
-        bool alarm = OutOfBedProcess(srcTrackLetListSptr, srcObjectListSptr);
-        LogInfo << "frame:" << framesnum;
-        std::shared_ptr<MxpiAttributeList> mxpiAttributeList = std::make_shared<MxpiAttributeList>();
-        MxTools::MxpiAttribute *result = mxpiAttributeList->add_attributevec();
-        if (alarm) {
-            result->set_attrvalue("Alarm Outofbed");
-
-        } else {
-            result->set_attrvalue("No Alarm");
-        }
-        APP_ERROR ret = mxpiMetadataManager.AddProtoMetadata(pluginName_, static_pointer_cast<void>(mxpiAttributeList));
-        if (ret != APP_ERR_OK) {
-            ErrorInfo_ << GetError(ret, pluginName_) << "PluginOutOfBed add metadata failed.";
-            mxpiErrorInfo.ret = ret;
-            mxpiErrorInfo.errorInfo = ErrorInfo_.str();
-            SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
-            return ret;
-        }
-        LogInfo << "PluginOutOfBed end";
-        // Send the data to downstream plugin
-        MxTools::MxPluginBase::SendData(0, *buffer);
-        return APP_ERR_OK;
-    }
-
-    std::vector<std::shared_ptr<void>> PluginOutOfBed::DefineProperties() {
-        // Define an A to store properties
-        std::vector<std::shared_ptr<void>> properties;
-        // Set the type and related information of the properties, and the key is the name
-        auto tracksourceProSptr =
-                std::make_shared<ElementProperty<string>>
-                        (ElementProperty<string>{
-                                STRING, "dataSourceTrack", "name",
-                                "the name of previous plugin",
-                                "mxpi_motsimplesort0", "NULL",
-                                "NULL"});
-        auto detectsourceProSptr =
-                std::make_shared<ElementProperty<string>>
-                        (ElementProperty<string>{
-                                STRING, "dataSourceDetection", "name",
-                                "the name of previous plugin",
-                                "mxpi_motsimplesort0", "NULL",
-                                "NULL"});
-        auto threshProSptr =
-                std::make_shared<ElementProperty<int>>
-                        (ElementProperty<int>{
-                                UINT, "detectThresh", "name", "123", 8, 0,
-                                100});
-        auto ratioProSptr =
-                std::make_shared<ElementProperty<float>>
-                        (ElementProperty<float>{
-                                FLOAT, "detectRatio", "name", " ", 1.0, 0.0,
-                                1.0});
-        auto sleepProSptr =
-                std::make_shared<ElementProperty<int>>
-                        (ElementProperty<int>{
-                                UINT, "detectSleep", "name", " ", 8, 0,
-                                100});
-        auto descriptionMessageProSptr =
-                std::make_shared<ElementProperty<string>>
-                        (ElementProperty<string>{
-                                STRING, "descriptionMessage", "message",
-                                "Description mesasge of plugin",
-                                "This is FairMOT_Alone", "NULL", "NULL"});
-        auto configPathSptr =
-                std::make_shared<ElementProperty<string>>
-                        (ElementProperty<string>{
-                                STRING, "configPath", "message",
-                                "Description mesasge of plugin",
-                                "This is FairMOT_Alone", "NULL", "NULL"});
-        properties.push_back(tracksourceProSptr);
-        properties.push_back(detectsourceProSptr);
-        properties.push_back(threshProSptr);
-        properties.push_back(ratioProSptr);
-        properties.push_back(sleepProSptr);
-        properties.push_back(configPathSptr);
-        properties.push_back(descriptionMessageProSptr);
-        return properties;
-    }
-
-    MxpiPortInfo PluginOutOfBed::DefineInputPorts() {
-        MxpiPortInfo inputPortInfo;
-        std::vector<std::vector<std::string>> value = {{"ANY"}};
-        MxPluginBase::GenerateStaticInputPortsInfo(value, inputPortInfo);
-        return inputPortInfo;
-    }
-
-    // Process the txt and get the location of the bed
-    void PluginOutOfBed::readTxt(std::string file, std::vector<cv::Point> &roi) {
-        ifstream infile;
-        infile.open(file);
-        string str;
-        while (getline(infile, str)) {
-            int i = 0;
-            cv::Point p;
-            int count = 1;
-            while (i < str.length()) {
-                int j = i;
-                while (j < str.length() && str[j] != ';') {
-                    j++;
-                }
-                string s = str.substr(i, j - i);
-                if (count == 1) {
-                    p.x = atoi(s.c_str());
-                    count++;
-                } else if (count == 2) {
-                    p.y = atoi(s.c_str());
-                }
-                i = j + 1;
-            }
-            roi.push_back(p);
-        }
-        infile.close();
-    }
-
-    // out of bed
-    bool PluginOutOfBed::OutOfBed(std::vector<int> queue) {
-        int length = queue.size();
-        int count_H = 0, count_T = 0;
-        for (int i = 0; i < length / 2; i++) {
-            if (queue[i]) {
-                count_H++;
-            }
-        }
-        for (int j = length - 1; j >= length / 2; j--) {
-            if (!queue[j]) {
-                count_T++;
-            }
-        }
-
-        if (count_H > length * confratio_ && count_T > length * confratio_) {
-            return 1;
-        }
-        return 0;
-    }
-
-    bool PluginOutOfBed::OutOfBedProcess(std::shared_ptr<MxpiTrackLetList> srcTrackLetListSptr,
-                                         std::shared_ptr<MxpiObjectList> srcObjectListSptr) {
-        bool flag = false;
-        if (sleeptime == 0) {
-            cv::Point2f center;
-            // read txt and get location of bed
-            if (pathflag) {
-                readTxt(configpath, bed);
-                pathflag = false;
-            }
-            for (uint32_t i = 0; i < (uint32_t) srcTrackLetListSptr->trackletvec_size(); i++) {
-                auto &trackObject = srcTrackLetListSptr->trackletvec(i);
-                if (trackObject.headervec_size() == 0) {
-                    continue;
-                }
-                auto &detectObject = srcObjectListSptr->objectvec(trackObject.headervec(0).memberid());
-                if (detectObject.classvec(0).classid() != 0) {
-                    continue;
-                }
-                if (trackdata.count(trackObject.trackid()) == 0) {
-                    center.x = (detectObject.x0() + detectObject.x1()) / 2;
-                    center.y = (detectObject.y0() + detectObject.y1()) / 2;
-                    trackdata[trackObject.trackid()].push_back(cv::pointPolygonTest(bed, center, false) > 0);
-                } else {
-                    center.x = (detectObject.x0() + detectObject.x1()) / 2;
-                    center.y = (detectObject.y0() + detectObject.y1()) / 2;
-                    trackdata[trackObject.trackid()].push_back(cv::pointPolygonTest(bed, center, false) > 0);
-                    if (trackdata[trackObject.trackid()].size() >= confthres_) {
-                        if (OutOfBed(trackdata[trackObject.trackid()])) {
-                            LogInfo << "Alarm OutOfBed";
-                            alarmcount++;
-                            LogInfo << "Alarmed" << alarmcount << "times";
-                            flag = true;
-                            sleeptime = confsleep_;
-                            frames = 0;
-                            trackdata.clear();
-                            break;
-                        } else {
-                            trackdata[trackObject.trackid()].erase(trackdata[trackObject.trackid()].begin());
-                        }
-                    }
-                }
-            }
-            frames++;
-        } else {
-            LogInfo << "Alarmed in a short period of time";
-            sleeptime--;
-        }
-        return flag;
-    }
-
-}
-namespace {
-    MX_PLUGIN_GENERATE(PluginOutOfBed)
-}
+/*
+ * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include <opencv2/opencv.hpp>
+#include "MxBase/Log/Log.h"
+#include "PluginOutOfBed.h"
+
+using namespace MxPlugins;
+using namespace MxTools;
+using namespace std;
+
+namespace MxPlugins {
+    APP_ERROR PluginOutOfBed::Init(std::map<std::string, std::shared_ptr<void>> &configParamMap) {
+        LogInfo << "PluginOutOfBed::Init start.";
+        APP_ERROR ret = APP_ERR_OK;
+        // Get the property values by key
+        // Data from track plugin
+        std::shared_ptr<string> tracksourcePropSptr =
+                std::static_pointer_cast<string>(configParamMap["dataSourceTrack"]);
+        tracksource_ = *tracksourcePropSptr.get();
+        // Data from detect plugin
+        std::shared_ptr<string> detectsourcePropSptr =
+                std::static_pointer_cast<string>(configParamMap["dataSourceDetection"]);
+        detectionsource_ = *detectsourcePropSptr.get();
+        // Description message
+        std::shared_ptr<string> descriptionMessageProSptr =
+                std::static_pointer_cast<string>(configParamMap["descriptionMessage"]);
+        descriptionMessage_ = *descriptionMessageProSptr.get();
+        // Configuration parameter
+        confthres_ = *std::static_pointer_cast<uint>(configParamMap["detectThresh"]);
+        confratio_ = *std::static_pointer_cast<float>(configParamMap["detectRatio"]);
+        confsleep_ = *std::static_pointer_cast<uint>(configParamMap["detectSleep"]);
+        configpath = *std::static_pointer_cast<string>(configParamMap["configPath"]);
+        return APP_ERR_OK;
+    }
+
+    APP_ERROR PluginOutOfBed::DeInit() {
+        LogInfo << "PluginOutOfBed::DeInit end.";
+        return APP_ERR_OK;
+    }
+
+    APP_ERROR PluginOutOfBed::SetMxpiErrorInfo(MxpiBuffer &buffer, const std::string pluginName,
+                                               const MxpiErrorInfo mxpiErrorInfo) {
+        APP_ERROR ret = APP_ERR_OK;
+        // Define an object of MxpiMetadataManager
+        MxpiMetadataManager mxpiMetadataManager(buffer);
+        ret = mxpiMetadataManager.AddErrorInfo(pluginName, mxpiErrorInfo);
+        if (ret != APP_ERR_OK) {
+            LogError << "Failed to AddErrorInfo.";
+            return ret;
+        }
+        ret = SendData(0, buffer);
+        return ret;
+    }
+
+    APP_ERROR PluginOutOfBed::Process(std::vector<MxTools::MxpiBuffer *> &mxpiBuffer) {
+        MxpiBuffer *buffer = mxpiBuffer[0];
+        MxpiMetadataManager mxpiMetadataManager(*buffer);
+        MxpiErrorInfo mxpiErrorInfo;
+        ErrorInfo_.str("");
+        auto errorInfoPtr = mxpiMetadataManager.GetErrorInfo();
+        framesnum++;
+        if (errorInfoPtr != nullptr) {
+            ErrorInfo_ << GetError(APP_ERR_COMM_FAILURE, pluginName_) << "PluginOutOfBed process is not implemented";
+            mxpiErrorInfo.ret = APP_ERR_COMM_FAILURE;
+            mxpiErrorInfo.errorInfo = ErrorInfo_.str();
+            SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
+            LogError << "FairMOT_Climb process is not implemented";
+            return APP_ERR_COMM_FAILURE;
+        }
+        // Get the data from buffer
+        shared_ptr<void> metadata = mxpiMetadataManager.GetMetadata(tracksource_);
+        shared_ptr<void> Detect = mxpiMetadataManager.GetMetadata(detectionsource_);
+        if (metadata == nullptr) {
+            ErrorInfo_ << GetError(APP_ERR_METADATA_IS_NULL, pluginName_) << "Metadata is NULL, failed";
+            mxpiErrorInfo.ret = APP_ERR_METADATA_IS_NULL;
+            mxpiErrorInfo.errorInfo = ErrorInfo_.str();
+            SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
+            return APP_ERR_METADATA_IS_NULL; // self define the error code
+        }
+        // get trackletlist
+        std::shared_ptr<MxpiTrackLetList> srcTrackLetListSptr = std::static_pointer_cast<MxpiTrackLetList>(metadata);
+        std::shared_ptr<MxpiObjectList> srcObjectListSptr = std::static_pointer_cast<MxpiObjectList>(Detect);
+        bool alarm = OutOfBedProcess(srcTrackLetListSptr, srcObjectListSptr);
+        LogInfo << "frame:" << framesnum;
+        std::shared_ptr<MxpiAttributeList> mxpiAttributeList = std::make_shared<MxpiAttributeList>();
+        MxTools::MxpiAttribute *result = mxpiAttributeList->add_attributevec();
+        if (alarm) {
+            result->set_attrvalue("Alarm Outofbed");
+
+        } else {
+            result->set_attrvalue("No Alarm");
+        }
+        APP_ERROR ret = mxpiMetadataManager.AddProtoMetadata(pluginName_, static_pointer_cast<void>(mxpiAttributeList));
+        if (ret != APP_ERR_OK) {
+            ErrorInfo_ << GetError(ret, pluginName_) << "PluginOutOfBed add metadata failed.";
+            mxpiErrorInfo.ret = ret;
+            mxpiErrorInfo.errorInfo = ErrorInfo_.str();
+            SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
+            return ret;
+        }
+        LogInfo << "PluginOutOfBed end";
+        // Send the data to downstream plugin
+        MxTools::MxPluginBase::SendData(0, *buffer);
+        return APP_ERR_OK;
+    }
+
+    std::vector<std::shared_ptr<void>> PluginOutOfBed::DefineProperties() {
+        // Define an A to store properties
+        std::vector<std::shared_ptr<void>> properties;
+        // Set the type and related information of the properties, and the key is the name
+        auto tracksourceProSptr =
+                std::make_shared<ElementProperty<string>>
+                        (ElementProperty<string>{
+                                STRING, "dataSourceTrack", "name",
+                                "the name of previous plugin",
+                                "mxpi_motsimplesort0", "NULL",
+                                "NULL"});
+        auto detectsourceProSptr =
+                std::make_shared<ElementProperty<string>>
+                        (ElementProperty<string>{
+                                STRING, "dataSourceDetection", "name",
+                                "the name of previous plugin",
+                                "mxpi_motsimplesort0", "NULL",
+                                "NULL"});
+        auto threshProSptr =
+                std::make_shared<ElementProperty<int>>
+                        (ElementProperty<int>{
+                                UINT, "detectThresh", "name", "123", 8, 0,
+                                100});
+        auto ratioProSptr =
+                std::make_shared<ElementProperty<float>>
+                        (ElementProperty<float>{
+                                FLOAT, "detectRatio", "name", " ", 1.0, 0.0,
+                                1.0});
+        auto sleepProSptr =
+                std::make_shared<ElementProperty<int>>
+                        (ElementProperty<int>{
+                                UINT, "detectSleep", "name", " ", 8, 0,
+                                100});
+        auto descriptionMessageProSptr =
+                std::make_shared<ElementProperty<string>>
+                        (ElementProperty<string>{
+                                STRING, "descriptionMessage", "message",
+                                "Description mesasge of plugin",
+                                "This is FairMOT_Alone", "NULL", "NULL"});
+        auto configPathSptr =
+                std::make_shared<ElementProperty<string>>
+                        (ElementProperty<string>{
+                                STRING, "configPath", "message",
+                                "Description mesasge of plugin",
+                                "This is FairMOT_Alone", "NULL", "NULL"});
+        properties.push_back(tracksourceProSptr);
+        properties.push_back(detectsourceProSptr);
+        properties.push_back(threshProSptr);
+        properties.push_back(ratioProSptr);
+        properties.push_back(sleepProSptr);
+        properties.push_back(configPathSptr);
+        properties.push_back(descriptionMessageProSptr);
+        return properties;
+    }
+
+    MxpiPortInfo PluginOutOfBed::DefineInputPorts() {
+        MxpiPortInfo inputPortInfo;
+        std::vector<std::vector<std::string>> value = {{"ANY"}};
+        MxPluginBase::GenerateStaticInputPortsInfo(value, inputPortInfo);
+        return inputPortInfo;
+    }
+
+    // Process the txt and get the location of the bed
+    void PluginOutOfBed::readTxt(std::string file, std::vector<cv::Point> &roi) {
+        ifstream infile;
+        infile.open(file);
+        string str;
+        while (getline(infile, str)) {
+            int i = 0;
+            cv::Point p;
+            int count = 1;
+            while (i < str.length()) {
+                int j = i;
+                while (j < str.length() && str[j] != ';') {
+                    j++;
+                }
+                string s = str.substr(i, j - i);
+                if (count == 1) {
+                    p.x = atoi(s.c_str());
+                    count++;
+                } else if (count == 2) {
+                    p.y = atoi(s.c_str());
+                }
+                i = j + 1;
+            }
+            roi.push_back(p);
+        }
+        infile.close();
+    }
+
+    // out of bed
+    bool PluginOutOfBed::OutOfBed(std::vector<int> queue) {
+        int length = queue.size();
+        int count_H = 0, count_T = 0;
+        for (int i = 0; i < length / 2; i++) {
+            if (queue[i]) {
+                count_H++;
+            }
+        }
+        for (int j = length - 1; j >= length / 2; j--) {
+            if (!queue[j]) {
+                count_T++;
+            }
+        }
+
+        if (count_H > length * confratio_ && count_T > length * confratio_) {
+            return 1;
+        }
+        return 0;
+    }
+
+    bool PluginOutOfBed::OutOfBedProcess(std::shared_ptr<MxpiTrackLetList> srcTrackLetListSptr,
+                                         std::shared_ptr<MxpiObjectList> srcObjectListSptr) {
+        bool flag = false;
+        if (sleeptime == 0) {
+            cv::Point2f center;
+            // read txt and get location of bed
+            if (pathflag) {
+                readTxt(configpath, bed);
+                pathflag = false;
+            }
+            for (uint32_t i = 0; i < (uint32_t) srcTrackLetListSptr->trackletvec_size(); i++) {
+                auto &trackObject = srcTrackLetListSptr->trackletvec(i);
+                if (trackObject.headervec_size() == 0) {
+                    continue;
+                }
+                auto &detectObject = srcObjectListSptr->objectvec(trackObject.headervec(0).memberid());
+                if (detectObject.classvec(0).classid() != 0) {
+                    continue;
+                }
+                if (trackdata.count(trackObject.trackid()) == 0) {
+                    center.x = (detectObject.x0() + detectObject.x1()) / 2;
+                    center.y = (detectObject.y0() + detectObject.y1()) / 2;
+                    trackdata[trackObject.trackid()].push_back(cv::pointPolygonTest(bed, center, false) > 0);
+                } else {
+                    center.x = (detectObject.x0() + detectObject.x1()) / 2;
+                    center.y = (detectObject.y0() + detectObject.y1()) / 2;
+                    trackdata[trackObject.trackid()].push_back(cv::pointPolygonTest(bed, center, false) > 0);
+                    if (trackdata[trackObject.trackid()].size() >= confthres_) {
+                        if (OutOfBed(trackdata[trackObject.trackid()])) {
+                            LogInfo << "Alarm OutOfBed";
+                            alarmcount++;
+                            LogInfo << "Alarmed" << alarmcount << "times";
+                            flag = true;
+                            sleeptime = confsleep_;
+                            frames = 0;
+                            trackdata.clear();
+                            break;
+                        } else {
+                            trackdata[trackObject.trackid()].erase(trackdata[trackObject.trackid()].begin());
+                        }
+                    }
+                }
+            }
+            frames++;
+        } else {
+            LogInfo << "Alarmed in a short period of time";
+            sleeptime--;
+        }
+        return flag;
+    }
+
+}
+namespace {
+    MX_PLUGIN_GENERATE(PluginOutOfBed)
+}
diff --git a/contrib/ActionRecognition/plugins/PluginOutOfBed/PluginOutOfBed.h b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginOutOfBed/PluginOutOfBed.h
similarity index 96%
rename from contrib/ActionRecognition/plugins/PluginOutOfBed/PluginOutOfBed.h
rename to mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginOutOfBed/PluginOutOfBed.h
index 89bce28c23ddfb0b0fd719d6d208838c222e5459..98f83032a04ba319e1d3d88fa8aa83ca46ff925a 100644
--- a/contrib/ActionRecognition/plugins/PluginOutOfBed/PluginOutOfBed.h
+++ b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginOutOfBed/PluginOutOfBed.h
@@ -1,122 +1,122 @@
-/*
- * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#ifndef MXPIFAIRMOT_FAIRMOT_OUTOFBED_H
-#define MXPIFAIRMOT_FAIRMOT_OUTOFBED_H
-
-#include <map>
-#include <opencv2/opencv.hpp>
-#include <fstream>
-#include "MxBase/ErrorCode/ErrorCode.h"
-#include "MxTools/PluginToolkit/base/MxPluginGenerator.h"
-#include "MxTools/PluginToolkit/base/MxPluginBase.h"
-#include "MxTools/PluginToolkit/metadata/MxpiMetadataManager.h"
-#include "MxTools/Proto/MxpiDataType.pb.h"
-
-/**
-* @api
-* @brief Definition of PluginOutOfBed class.
-*/
-
-namespace MxPlugins {
-    class PluginOutOfBed : public MxTools::MxPluginBase {
-    public:
-        /**
-            * @api
-            * @brief Initialize configure parameter.
-            * @param configParamMap
-            * @return APP_ERROR
-            */
-        APP_ERROR Init(std::map<std::string, std::shared_ptr<void>> &configParamMap) override;
-
-        /**
-            * * @api
-            * @brief DeInitialize configure parameter.
-            * @return APP_ERROR
-            */
-        APP_ERROR DeInit() override;
-
-        /**
-           * @api
-           * @brief Process the data of MxpiBuffer.
-           * @param mxpiBuffer
-           * @return APP_ERROR
-           */
-        APP_ERROR Process(std::vector<MxTools::MxpiBuffer *> &mxpiBuffer) override;
-
-        /**
-            * @api
-            * @brief Definition the parameter of configure properties.
-            * @return std::vector<std::shared_ptr<void>>
-            */
-        static std::vector<std::shared_ptr<void>> DefineProperties();
-
-        /**
-           * @api
-           * @brief Get the number of class id and confidence from model inference.
-           * @param key
-           * @param buffer
-           * @return APP_ERROR
-           */
-        static MxTools::MxpiPortInfo DefineInputPorts();
-
-        /**
-            * @api
-            * @brief read ROI
-            * @param ROI file path
-            */
-        void readTxt(std::string file, std::vector<cv::Point> &roi);
-
-        /**
-           * @api
-           * @brief Out of bed detection.
-           * @param queue
-           * @return bool
-           */
-        bool OutOfBed(std::vector<int> queue);
-
-        /**
-           * @api
-           * @brief Out of bed process.
-           * @param srcTrackLetListSptr ,srcTrackLetListSptr
-           * @return bool
-           */
-        bool OutOfBedProcess(std::shared_ptr<MxTools::MxpiTrackLetList> srcTrackLetListSptr,
-                             std::shared_ptr<MxTools::MxpiObjectList> srcObjectListSptr);
-
-    private:
-        APP_ERROR SetMxpiErrorInfo(MxTools::MxpiBuffer &buffer, const std::string pluginName,
-                                   const MxTools::MxpiErrorInfo mxpiErrorInfo);
-
-        std::string tracksource_;
-        std::string detectionsource_;
-        std::string descriptionMessage_;
-        std::string configpath;
-        std::ostringstream ErrorInfo_;
-        uint confthres_;
-        float confratio_;
-        uint confsleep_;
-        uint sleeptime = 0;
-        std::map<uint32_t, std::vector<int>> trackdata;
-        std::vector<cv::Point> bed;
-        uint frames;
-        uint framesnum = 0;
-        bool pathflag = true;
-        uint alarmcount = 0;
-    };
-
-}
-#endif // MXPIFAIRMOT_FAIRMOT_OUTOFBED_H
+/*
+ * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef MXPIFAIRMOT_FAIRMOT_OUTOFBED_H
+#define MXPIFAIRMOT_FAIRMOT_OUTOFBED_H
+
+#include <map>
+#include <opencv2/opencv.hpp>
+#include <fstream>
+#include "MxBase/ErrorCode/ErrorCode.h"
+#include "MxTools/PluginToolkit/base/MxPluginGenerator.h"
+#include "MxTools/PluginToolkit/base/MxPluginBase.h"
+#include "MxTools/PluginToolkit/metadata/MxpiMetadataManager.h"
+#include "MxTools/Proto/MxpiDataType.pb.h"
+
+/**
+* @api
+* @brief Definition of PluginOutOfBed class.
+*/
+
+namespace MxPlugins {
+    class PluginOutOfBed : public MxTools::MxPluginBase {
+    public:
+        /**
+            * @api
+            * @brief Initialize configure parameter.
+            * @param configParamMap
+            * @return APP_ERROR
+            */
+        APP_ERROR Init(std::map<std::string, std::shared_ptr<void>> &configParamMap) override;
+
+        /**
+            * * @api
+            * @brief DeInitialize configure parameter.
+            * @return APP_ERROR
+            */
+        APP_ERROR DeInit() override;
+
+        /**
+           * @api
+           * @brief Process the data of MxpiBuffer.
+           * @param mxpiBuffer
+           * @return APP_ERROR
+           */
+        APP_ERROR Process(std::vector<MxTools::MxpiBuffer *> &mxpiBuffer) override;
+
+        /**
+            * @api
+            * @brief Definition the parameter of configure properties.
+            * @return std::vector<std::shared_ptr<void>>
+            */
+        static std::vector<std::shared_ptr<void>> DefineProperties();
+
+        /**
+           * @api
+           * @brief Get the number of class id and confidence from model inference.
+           * @param key
+           * @param buffer
+           * @return APP_ERROR
+           */
+        static MxTools::MxpiPortInfo DefineInputPorts();
+
+        /**
+            * @api
+            * @brief read ROI
+            * @param ROI file path
+            */
+        void readTxt(std::string file, std::vector<cv::Point> &roi);
+
+        /**
+           * @api
+           * @brief Out of bed detection.
+           * @param queue
+           * @return bool
+           */
+        bool OutOfBed(std::vector<int> queue);
+
+        /**
+           * @api
+           * @brief Out of bed process.
+           * @param srcTrackLetListSptr ,srcTrackLetListSptr
+           * @return bool
+           */
+        bool OutOfBedProcess(std::shared_ptr<MxTools::MxpiTrackLetList> srcTrackLetListSptr,
+                             std::shared_ptr<MxTools::MxpiObjectList> srcObjectListSptr);
+
+    private:
+        APP_ERROR SetMxpiErrorInfo(MxTools::MxpiBuffer &buffer, const std::string pluginName,
+                                   const MxTools::MxpiErrorInfo mxpiErrorInfo);
+
+        std::string tracksource_;
+        std::string detectionsource_;
+        std::string descriptionMessage_;
+        std::string configpath;
+        std::ostringstream ErrorInfo_;
+        uint confthres_;
+        float confratio_;
+        uint confsleep_;
+        uint sleeptime = 0;
+        std::map<uint32_t, std::vector<int>> trackdata;
+        std::vector<cv::Point> bed;
+        uint frames;
+        uint framesnum = 0;
+        bool pathflag = true;
+        uint alarmcount = 0;
+    };
+
+}
+#endif // MXPIFAIRMOT_FAIRMOT_OUTOFBED_H
diff --git a/contrib/ActionRecognition/plugins/PluginOutOfBed/build.sh b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginOutOfBed/build.sh
similarity index 100%
rename from contrib/ActionRecognition/plugins/PluginOutOfBed/build.sh
rename to mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginOutOfBed/build.sh
diff --git a/contrib/ActionRecognition/plugins/PluginOverSpeed/CMakeLists.txt b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginOverSpeed/CMakeLists.txt
similarity index 100%
rename from contrib/ActionRecognition/plugins/PluginOverSpeed/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginOverSpeed/CMakeLists.txt
diff --git a/contrib/ActionRecognition/plugins/PluginOverSpeed/PluginOverSpeed.cpp b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginOverSpeed/PluginOverSpeed.cpp
similarity index 97%
rename from contrib/ActionRecognition/plugins/PluginOverSpeed/PluginOverSpeed.cpp
rename to mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginOverSpeed/PluginOverSpeed.cpp
index 9fbe3dda437a1ce79a51cfee19cfe265142bd877..f73281f5a6227dd595b4e605011f48f86ec66582 100644
--- a/contrib/ActionRecognition/plugins/PluginOverSpeed/PluginOverSpeed.cpp
+++ b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginOverSpeed/PluginOverSpeed.cpp
@@ -1,274 +1,274 @@
-/*
-* Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-* http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-
-#include "math.h"
-#include "MxBase/Log/Log.h"
-#include "PluginOverSpeed.h"
-
-using namespace MxPlugins;
-using namespace MxTools;
-using namespace MxPlugins;
-using namespace std;
-
-namespace {
-    const int minframe = 4;
-}
-
-namespace MxPlugins {
-    APP_ERROR PluginOverSpeed::Init(std::map<std::string, std::shared_ptr<void>> &configParamMap) {
-        LogInfo << "PluginOverSpeed::Init start.";
-        APP_ERROR ret = APP_ERR_OK;
-        // Get the property values by key
-        std::shared_ptr<std::string> tracksourcePropSptr =
-                std::static_pointer_cast<std::string>(configParamMap["dataSourceTrack"]);
-        tracksource_ = *tracksourcePropSptr.get();
-
-        std::shared_ptr<std::string> dataSourceDetection =
-                std::static_pointer_cast<std::string>(configParamMap["dataSourceDetection"]);
-        detectionsource_ = *dataSourceDetection.get();
-
-        std::shared_ptr<std::string> descriptionMessageProSptr =
-                std::static_pointer_cast<std::string>(configParamMap["descriptionMessage"]);
-        descriptionMessage_ = *descriptionMessageProSptr.get();
-
-        // Configuration parameter
-        confthresh_ = *std::static_pointer_cast<int>(configParamMap["speedThresh"]);
-        confframes_ = *std::static_pointer_cast<int>(configParamMap["frames"]);
-        confsleep_ = *std::static_pointer_cast<int>(configParamMap["detectSleep"]);
-        return APP_ERR_OK;
-    }
-
-    APP_ERROR PluginOverSpeed::DeInit() {
-        LogInfo << "PluginOverSpeed::DeInit end.";
-        return APP_ERR_OK;
-    }
-
-    APP_ERROR PluginOverSpeed::SetMxpiErrorInfo(MxpiBuffer &buffer, const std::string pluginName,
-                                                const MxpiErrorInfo mxpiErrorInfo) {
-        APP_ERROR ret = APP_ERR_OK;
-        // Define an object of MxpiMetadataManager
-        MxpiMetadataManager mxpiMetadataManager(buffer);
-        ret = mxpiMetadataManager.AddErrorInfo(pluginName, mxpiErrorInfo);
-        if (ret != APP_ERR_OK) {
-            LogError << "Failed to AddErrorInfo.";
-            return ret;
-        }
-        ret = SendData(0, buffer);
-        return ret;
-    }
-
-    APP_ERROR PluginOverSpeed::Process(std::vector<MxpiBuffer *> &mxpiBuffer) {
-        LogInfo << "PluginOverSpeed::Process start";
-        MxpiBuffer *buffer = mxpiBuffer[0];
-        MxpiMetadataManager mxpiMetadataManager(*buffer);
-        MxpiErrorInfo mxpiErrorInfo;
-        ErrorInfo_.str("");
-        auto errorInfoPtr = mxpiMetadataManager.GetErrorInfo();
-        frame++;
-        if (errorInfoPtr != nullptr) {
-            ErrorInfo_ << GetError(APP_ERR_COMM_FAILURE, pluginName_)
-                       << "PluginOverSpeed process is not implemented";
-            mxpiErrorInfo.ret = APP_ERR_COMM_FAILURE;
-            mxpiErrorInfo.errorInfo = ErrorInfo_.str();
-            SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
-            LogError << "PluginOverSpeed process is not implemented";
-            return APP_ERR_COMM_FAILURE;
-        }
-        // Get the data from buffer
-        shared_ptr<void> metadata = mxpiMetadataManager.GetMetadata(tracksource_);
-        shared_ptr<void> Detect = mxpiMetadataManager.GetMetadata(detectionsource_);
-        if (metadata == nullptr || Detect == nullptr) {
-            ErrorInfo_ << GetError(APP_ERR_METADATA_IS_NULL, pluginName_)
-                       << "Metadata is NULL, failed";
-            mxpiErrorInfo.ret = APP_ERR_METADATA_IS_NULL;
-            mxpiErrorInfo.errorInfo = ErrorInfo_.str();
-            SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
-            return APP_ERR_METADATA_IS_NULL;
-        }
-        // get trackletlist
-        std::shared_ptr<MxpiTrackLetList> srcTrackLetListSptr = std::static_pointer_cast<MxpiTrackLetList>(metadata);
-        std::shared_ptr<MxpiObjectList> srcObjectListSptr = std::static_pointer_cast<MxpiObjectList>(Detect);
-        //data processing
-        std::shared_ptr<MxTools::MxpiAttributeList> result = std::make_shared<MxTools::MxpiAttributeList>();
-        MxpiAttribute *mxpiAttribute = result->add_attributevec();
-        if (sleeptime == 0) {
-            int alarm = calculate(trackdata, confframes_, frame_num, confthresh_,
-                                  srcTrackLetListSptr,
-                                  srcObjectListSptr);
-            if (alarm == 1) {
-                alarm_count++;
-                LogInfo << "Alarmed " << alarm_count << " times";
-                sleeptime = confsleep_;
-                mxpiAttribute->set_attrname("Alarm OverSpeed");
-                APP_ERROR ret = mxpiMetadataManager.AddProtoMetadata(pluginName_,
-                                                                     static_pointer_cast<void>(result));
-                if (ret != APP_ERR_OK) {
-                    ErrorInfo_ << GetError(ret, pluginName_) << "PluginOverSpeed add metadata failed.";
-                    mxpiErrorInfo.ret = ret;
-                    mxpiErrorInfo.errorInfo = ErrorInfo_.str();
-                    SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
-                    return ret;
-                }
-            } else {
-                mxpiAttribute->set_attrname("No Alarm");
-                APP_ERROR ret = mxpiMetadataManager.AddProtoMetadata(pluginName_,
-                                                                     static_pointer_cast<void>(result));
-                if (ret != APP_ERR_OK) {
-                    ErrorInfo_ << GetError(ret, pluginName_) << "PluginOverSpeed add metadata failed.";
-                    mxpiErrorInfo.ret = ret;
-                    mxpiErrorInfo.errorInfo = ErrorInfo_.str();
-                    SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
-                    return ret;
-                }
-            }
-        } else {
-            mxpiAttribute->set_attrname("Alarmed in a short period of time");
-            APP_ERROR ret = mxpiMetadataManager.AddProtoMetadata(pluginName_,
-                                                                 static_pointer_cast<void>(result));
-            if (ret != APP_ERR_OK) {
-                ErrorInfo_ << GetError(ret, pluginName_) << "PluginOverSpeed add metadata failed.";
-                mxpiErrorInfo.ret = ret;
-                mxpiErrorInfo.errorInfo = ErrorInfo_.str();
-                SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
-                return ret;
-            }
-            sleeptime--;
-        }
-        // Send the data to downstream plugin
-        SendData(0, *buffer);
-        LogInfo << "PluginOverSpeed::Process end";
-        return APP_ERR_OK;
-    }
-
-    int PluginOverSpeed::calculate(std::map<int, std::vector<int>> &trackdata, int confframes_, int &frame_num,
-                                   int confthresh_,
-                                   std::shared_ptr<MxpiTrackLetList> srcTrackLetListSptr,
-                                   std::shared_ptr<MxpiObjectList> srcObjectListSptr) {
-        int alarm = 0;
-        for (uint32_t i = 0; i < (uint32_t) srcTrackLetListSptr->trackletvec_size(); i++) {
-            auto &trackObject = srcTrackLetListSptr->trackletvec(i);
-            if (trackObject.headervec_size() == 0) {
-                continue;
-            }
-            auto &detectObject = srcObjectListSptr->objectvec(trackObject.headervec(0).memberid());
-            if (detectObject.classvec(0).classid() != 0) {
-                continue;
-            }
-            if (trackdata.count(trackObject.trackid()) == 0) {
-                trackdata[trackObject.trackid()].push_back((int) ((detectObject.x0() + detectObject.x1()) / 2));
-                trackdata[trackObject.trackid()].push_back((int) ((detectObject.y0() + detectObject.y1()) / 2));
-                trackdata[trackObject.trackid()][2] = 0;
-                trackdata[trackObject.trackid()][3] = 0;
-            } else {
-                trackdata[trackObject.trackid()][2] += 1;
-                int x0 = trackdata[trackObject.trackid()][0];
-                int y0 = trackdata[trackObject.trackid()][1];
-                int x1 = (int) ((detectObject.x0() + detectObject.x1()) / 2);
-                int y1 = (int) ((detectObject.y0() + detectObject.y1()) / 2);
-                trackdata[trackObject.trackid()][3] += distance(x0, y0, x1, y1);
-                trackdata[trackObject.trackid()][0] = (int) ((detectObject.x0() + detectObject.x1()) / 2);
-                trackdata[trackObject.trackid()][1] = (int) ((detectObject.y0() + detectObject.y1()) / 2);
-            }
-        }
-        frame_num++;
-        // calculate data
-        if (frame_num == confframes_) {
-            frame_num = 0;
-            for (auto iter = trackdata.begin(); iter != trackdata.end(); iter++) {
-                if (trackdata[iter->first][2] == 0 || trackdata[iter->first][2] < minframe) {
-                    continue;
-                }
-                if (((int) (trackdata[iter->first][3] / trackdata[iter->first][2])) > confthresh_) {
-                    alarm = 1;
-                    break;
-                }
-            }
-            trackdata.clear();
-        }
-        return alarm;
-    }
-
-    std::vector<std::shared_ptr<void>> PluginOverSpeed::DefineProperties() {
-        // Define an A to store properties
-        std::vector<std::shared_ptr<void>> properties;
-        // Set the type and related information of the properties, and the key is the name
-        auto tracksourceProSptr =
-                std::make_shared<ElementProperty<std::string>>(ElementProperty<std::string>{
-                        STRING, "dataSourceTrack", "name",
-                        "the source of tack data", "mxpi_motsimplesort0",
-                        "NULL", "NULL"});
-
-        auto detectsourceProSptr =
-                std::make_shared<ElementProperty<std::string>>(ElementProperty<std::string>{
-                        STRING, "dataSourceDetection", "name",
-                        "the source of detect data", "mxpi_objectpostprocessor0",
-                        "NULL", "NULL"});
-
-        auto threshProSptr =
-                std::make_shared<ElementProperty<int>>(ElementProperty<int>{
-                        UINT, "speedThresh", "thresh",
-                        "the thresh of overspeed", 10,
-                        1, 1000});
-
-        auto frameProSptr =
-                std::make_shared<ElementProperty<int>>(ElementProperty<int>{
-                        UINT, "frames", "frame",
-                        "the number of frame when judging", 8,
-                        8, 100});
-
-        auto sleepProSptr =
-                std::make_shared<ElementProperty<int>>(ElementProperty<int>{
-                        UINT, "detectSleep", "sleep",
-                        "the time of stop detection", 8, 0,
-                        300});
-
-        auto descriptionMessageProSptr =
-                std::make_shared<ElementProperty<std::string>>(ElementProperty<std::string>{
-                        STRING, "descriptionMessage", "message",
-                        "Description mesasge of plugin",
-                        "This is PluginOverSpeed", "NULL", "NULL"});
-        properties.push_back(tracksourceProSptr);
-        properties.push_back(detectsourceProSptr);
-        properties.push_back(threshProSptr);
-        properties.push_back(frameProSptr);
-        properties.push_back(sleepProSptr);
-        properties.push_back(descriptionMessageProSptr);
-        return properties;
-    }
-    // Register the Sample plugin through macro
-
-    MxpiPortInfo PluginOverSpeed::DefineInputPorts() {
-        MxpiPortInfo inputPortInfo;
-        std::vector<std::vector<std::string>> value = {{"ANY"}};
-        MxPluginBase::GenerateStaticInputPortsInfo(value, inputPortInfo);
-        return inputPortInfo;
-    };
-
-    MxpiPortInfo PluginOverSpeed::DefineOutputPorts() {
-        MxpiPortInfo outputPortInfo;
-        std::vector<std::vector<std::string>> value = {{"ANY"}};
-        MxPluginBase::GenerateStaticOutputPortsInfo(value, outputPortInfo);
-        return outputPortInfo;
-    }
-
-    int PluginOverSpeed::distance(int x0, int y0, int x1, int y1) {
-        int distance = int(sqrt((x1 - x0) * (x1 - x0) + (y1 - y0) * (y1 - y0)));
-        return distance;
-    }
-}
-namespace {
-    MX_PLUGIN_GENERATE(PluginOverSpeed)
-}
+/*
+* Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "math.h"
+#include "MxBase/Log/Log.h"
+#include "PluginOverSpeed.h"
+
+using namespace MxPlugins;
+using namespace MxTools;
+using namespace MxPlugins;
+using namespace std;
+
+namespace {
+    const int minframe = 4;
+}
+
+namespace MxPlugins {
+    APP_ERROR PluginOverSpeed::Init(std::map<std::string, std::shared_ptr<void>> &configParamMap) {
+        LogInfo << "PluginOverSpeed::Init start.";
+        APP_ERROR ret = APP_ERR_OK;
+        // Get the property values by key
+        std::shared_ptr<std::string> tracksourcePropSptr =
+                std::static_pointer_cast<std::string>(configParamMap["dataSourceTrack"]);
+        tracksource_ = *tracksourcePropSptr.get();
+
+        std::shared_ptr<std::string> dataSourceDetection =
+                std::static_pointer_cast<std::string>(configParamMap["dataSourceDetection"]);
+        detectionsource_ = *dataSourceDetection.get();
+
+        std::shared_ptr<std::string> descriptionMessageProSptr =
+                std::static_pointer_cast<std::string>(configParamMap["descriptionMessage"]);
+        descriptionMessage_ = *descriptionMessageProSptr.get();
+
+        // Configuration parameter
+        confthresh_ = *std::static_pointer_cast<int>(configParamMap["speedThresh"]);
+        confframes_ = *std::static_pointer_cast<int>(configParamMap["frames"]);
+        confsleep_ = *std::static_pointer_cast<int>(configParamMap["detectSleep"]);
+        return APP_ERR_OK;
+    }
+
+    APP_ERROR PluginOverSpeed::DeInit() {
+        LogInfo << "PluginOverSpeed::DeInit end.";
+        return APP_ERR_OK;
+    }
+
+    APP_ERROR PluginOverSpeed::SetMxpiErrorInfo(MxpiBuffer &buffer, const std::string pluginName,
+                                                const MxpiErrorInfo mxpiErrorInfo) {
+        APP_ERROR ret = APP_ERR_OK;
+        // Define an object of MxpiMetadataManager
+        MxpiMetadataManager mxpiMetadataManager(buffer);
+        ret = mxpiMetadataManager.AddErrorInfo(pluginName, mxpiErrorInfo);
+        if (ret != APP_ERR_OK) {
+            LogError << "Failed to AddErrorInfo.";
+            return ret;
+        }
+        ret = SendData(0, buffer);
+        return ret;
+    }
+
+    APP_ERROR PluginOverSpeed::Process(std::vector<MxpiBuffer *> &mxpiBuffer) {
+        LogInfo << "PluginOverSpeed::Process start";
+        MxpiBuffer *buffer = mxpiBuffer[0];
+        MxpiMetadataManager mxpiMetadataManager(*buffer);
+        MxpiErrorInfo mxpiErrorInfo;
+        ErrorInfo_.str("");
+        auto errorInfoPtr = mxpiMetadataManager.GetErrorInfo();
+        frame++;
+        if (errorInfoPtr != nullptr) {
+            ErrorInfo_ << GetError(APP_ERR_COMM_FAILURE, pluginName_)
+                       << "PluginOverSpeed process is not implemented";
+            mxpiErrorInfo.ret = APP_ERR_COMM_FAILURE;
+            mxpiErrorInfo.errorInfo = ErrorInfo_.str();
+            SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
+            LogError << "PluginOverSpeed process is not implemented";
+            return APP_ERR_COMM_FAILURE;
+        }
+        // Get the data from buffer
+        shared_ptr<void> metadata = mxpiMetadataManager.GetMetadata(tracksource_);
+        shared_ptr<void> Detect = mxpiMetadataManager.GetMetadata(detectionsource_);
+        if (metadata == nullptr || Detect == nullptr) {
+            ErrorInfo_ << GetError(APP_ERR_METADATA_IS_NULL, pluginName_)
+                       << "Metadata is NULL, failed";
+            mxpiErrorInfo.ret = APP_ERR_METADATA_IS_NULL;
+            mxpiErrorInfo.errorInfo = ErrorInfo_.str();
+            SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
+            return APP_ERR_METADATA_IS_NULL;
+        }
+        // get trackletlist
+        std::shared_ptr<MxpiTrackLetList> srcTrackLetListSptr = std::static_pointer_cast<MxpiTrackLetList>(metadata);
+        std::shared_ptr<MxpiObjectList> srcObjectListSptr = std::static_pointer_cast<MxpiObjectList>(Detect);
+        //data processing
+        std::shared_ptr<MxTools::MxpiAttributeList> result = std::make_shared<MxTools::MxpiAttributeList>();
+        MxpiAttribute *mxpiAttribute = result->add_attributevec();
+        if (sleeptime == 0) {
+            int alarm = calculate(trackdata, confframes_, frame_num, confthresh_,
+                                  srcTrackLetListSptr,
+                                  srcObjectListSptr);
+            if (alarm == 1) {
+                alarm_count++;
+                LogInfo << "Alarmed " << alarm_count << " times";
+                sleeptime = confsleep_;
+                mxpiAttribute->set_attrname("Alarm OverSpeed");
+                APP_ERROR ret = mxpiMetadataManager.AddProtoMetadata(pluginName_,
+                                                                     static_pointer_cast<void>(result));
+                if (ret != APP_ERR_OK) {
+                    ErrorInfo_ << GetError(ret, pluginName_) << "PluginOverSpeed add metadata failed.";
+                    mxpiErrorInfo.ret = ret;
+                    mxpiErrorInfo.errorInfo = ErrorInfo_.str();
+                    SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
+                    return ret;
+                }
+            } else {
+                mxpiAttribute->set_attrname("No Alarm");
+                APP_ERROR ret = mxpiMetadataManager.AddProtoMetadata(pluginName_,
+                                                                     static_pointer_cast<void>(result));
+                if (ret != APP_ERR_OK) {
+                    ErrorInfo_ << GetError(ret, pluginName_) << "PluginOverSpeed add metadata failed.";
+                    mxpiErrorInfo.ret = ret;
+                    mxpiErrorInfo.errorInfo = ErrorInfo_.str();
+                    SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
+                    return ret;
+                }
+            }
+        } else {
+            mxpiAttribute->set_attrname("Alarmed in a short period of time");
+            APP_ERROR ret = mxpiMetadataManager.AddProtoMetadata(pluginName_,
+                                                                 static_pointer_cast<void>(result));
+            if (ret != APP_ERR_OK) {
+                ErrorInfo_ << GetError(ret, pluginName_) << "PluginOverSpeed add metadata failed.";
+                mxpiErrorInfo.ret = ret;
+                mxpiErrorInfo.errorInfo = ErrorInfo_.str();
+                SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
+                return ret;
+            }
+            sleeptime--;
+        }
+        // Send the data to downstream plugin
+        SendData(0, *buffer);
+        LogInfo << "PluginOverSpeed::Process end";
+        return APP_ERR_OK;
+    }
+
+    int PluginOverSpeed::calculate(std::map<int, std::vector<int>> &trackdata, int confframes_, int &frame_num,
+                                   int confthresh_,
+                                   std::shared_ptr<MxpiTrackLetList> srcTrackLetListSptr,
+                                   std::shared_ptr<MxpiObjectList> srcObjectListSptr) {
+        int alarm = 0;
+        for (uint32_t i = 0; i < (uint32_t) srcTrackLetListSptr->trackletvec_size(); i++) {
+            auto &trackObject = srcTrackLetListSptr->trackletvec(i);
+            if (trackObject.headervec_size() == 0) {
+                continue;
+            }
+            auto &detectObject = srcObjectListSptr->objectvec(trackObject.headervec(0).memberid());
+            if (detectObject.classvec(0).classid() != 0) {
+                continue;
+            }
+            if (trackdata.count(trackObject.trackid()) == 0) {
+                trackdata[trackObject.trackid()].push_back((int) ((detectObject.x0() + detectObject.x1()) / 2));
+                trackdata[trackObject.trackid()].push_back((int) ((detectObject.y0() + detectObject.y1()) / 2));
+                trackdata[trackObject.trackid()][2] = 0;
+                trackdata[trackObject.trackid()][3] = 0;
+            } else {
+                trackdata[trackObject.trackid()][2] += 1;
+                int x0 = trackdata[trackObject.trackid()][0];
+                int y0 = trackdata[trackObject.trackid()][1];
+                int x1 = (int) ((detectObject.x0() + detectObject.x1()) / 2);
+                int y1 = (int) ((detectObject.y0() + detectObject.y1()) / 2);
+                trackdata[trackObject.trackid()][3] += distance(x0, y0, x1, y1);
+                trackdata[trackObject.trackid()][0] = (int) ((detectObject.x0() + detectObject.x1()) / 2);
+                trackdata[trackObject.trackid()][1] = (int) ((detectObject.y0() + detectObject.y1()) / 2);
+            }
+        }
+        frame_num++;
+        // calculate data
+        if (frame_num == confframes_) {
+            frame_num = 0;
+            for (auto iter = trackdata.begin(); iter != trackdata.end(); iter++) {
+                if (trackdata[iter->first][2] == 0 || trackdata[iter->first][2] < minframe) {
+                    continue;
+                }
+                if (((int) (trackdata[iter->first][3] / trackdata[iter->first][2])) > confthresh_) {
+                    alarm = 1;
+                    break;
+                }
+            }
+            trackdata.clear();
+        }
+        return alarm;
+    }
+
+    std::vector<std::shared_ptr<void>> PluginOverSpeed::DefineProperties() {
+        // Define an A to store properties
+        std::vector<std::shared_ptr<void>> properties;
+        // Set the type and related information of the properties, and the key is the name
+        auto tracksourceProSptr =
+                std::make_shared<ElementProperty<std::string>>(ElementProperty<std::string>{
+                        STRING, "dataSourceTrack", "name",
+                        "the source of tack data", "mxpi_motsimplesort0",
+                        "NULL", "NULL"});
+
+        auto detectsourceProSptr =
+                std::make_shared<ElementProperty<std::string>>(ElementProperty<std::string>{
+                        STRING, "dataSourceDetection", "name",
+                        "the source of detect data", "mxpi_objectpostprocessor0",
+                        "NULL", "NULL"});
+
+        auto threshProSptr =
+                std::make_shared<ElementProperty<int>>(ElementProperty<int>{
+                        UINT, "speedThresh", "thresh",
+                        "the thresh of overspeed", 10,
+                        1, 1000});
+
+        auto frameProSptr =
+                std::make_shared<ElementProperty<int>>(ElementProperty<int>{
+                        UINT, "frames", "frame",
+                        "the number of frame when judging", 8,
+                        8, 100});
+
+        auto sleepProSptr =
+                std::make_shared<ElementProperty<int>>(ElementProperty<int>{
+                        UINT, "detectSleep", "sleep",
+                        "the time of stop detection", 8, 0,
+                        300});
+
+        auto descriptionMessageProSptr =
+                std::make_shared<ElementProperty<std::string>>(ElementProperty<std::string>{
+                        STRING, "descriptionMessage", "message",
+                        "Description mesasge of plugin",
+                        "This is PluginOverSpeed", "NULL", "NULL"});
+        properties.push_back(tracksourceProSptr);
+        properties.push_back(detectsourceProSptr);
+        properties.push_back(threshProSptr);
+        properties.push_back(frameProSptr);
+        properties.push_back(sleepProSptr);
+        properties.push_back(descriptionMessageProSptr);
+        return properties;
+    }
+    // Register the Sample plugin through macro
+
+    MxpiPortInfo PluginOverSpeed::DefineInputPorts() {
+        MxpiPortInfo inputPortInfo;
+        std::vector<std::vector<std::string>> value = {{"ANY"}};
+        MxPluginBase::GenerateStaticInputPortsInfo(value, inputPortInfo);
+        return inputPortInfo;
+    };
+
+    MxpiPortInfo PluginOverSpeed::DefineOutputPorts() {
+        MxpiPortInfo outputPortInfo;
+        std::vector<std::vector<std::string>> value = {{"ANY"}};
+        MxPluginBase::GenerateStaticOutputPortsInfo(value, outputPortInfo);
+        return outputPortInfo;
+    }
+
+    int PluginOverSpeed::distance(int x0, int y0, int x1, int y1) {
+        int distance = int(sqrt((x1 - x0) * (x1 - x0) + (y1 - y0) * (y1 - y0)));
+        return distance;
+    }
+}
+namespace {
+    MX_PLUGIN_GENERATE(PluginOverSpeed)
+}
diff --git a/contrib/ActionRecognition/plugins/PluginOverSpeed/PluginOverSpeed.h b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginOverSpeed/PluginOverSpeed.h
similarity index 96%
rename from contrib/ActionRecognition/plugins/PluginOverSpeed/PluginOverSpeed.h
rename to mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginOverSpeed/PluginOverSpeed.h
index bd26d0e9819dcf6ffb8ad69a4679c52176ce75f0..578f0e98c03b88111ae25cab5e5b64e09b9d500a 100644
--- a/contrib/ActionRecognition/plugins/PluginOverSpeed/PluginOverSpeed.h
+++ b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginOverSpeed/PluginOverSpeed.h
@@ -1,119 +1,119 @@
-/*
-* Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-* http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-#ifndef SDKMEMORY_PLUGINOVERSPEED_H
-#define SDKMEMORY_PLUGINOVERSPEED_H
-
-#include "MxTools/PluginToolkit/base/MxPluginGenerator.h"
-#include "MxTools/PluginToolkit/base/MxPluginBase.h"
-#include "MxTools/PluginToolkit/metadata/MxpiMetadataManager.h"
-#include "MxTools/Proto/MxpiDataType.pb.h"
-#include "MxBase/ErrorCode/ErrorCode.h"
-
-/**
-* @api
-* @brief Definition of PluginOverSpeed class.
-*/
-
-namespace MxPlugins {
-    class PluginOverSpeed : public MxTools::MxPluginBase {
-    public:
-        /**
-        * @api
-        * @brief Initialize configure parameter.
-        * @param configParamMap
-        * @return APP_ERROR
-        */
-        APP_ERROR Init(std::map<std::string, std::shared_ptr<void>> &configParamMap) override;
-
-        /**
-        * * @api
-        * @brief DeInitialize configure parameter.
-        * @return APP_ERROR
-        */
-        APP_ERROR DeInit() override;
-
-        /**
-        * @api
-        * @brief Process the data of MxpiBuffer.
-        * @param mxpiBuffer
-        * @return APP_ERROR
-        */
-        APP_ERROR Process(std::vector<MxTools::MxpiBuffer *> &mxpiBuffer) override;
-
-        /**
-        * @api
-        * @brief Definition the parameter of configure properties.
-        * @return std::vector<std::shared_ptr<void>>
-        */
-        static std::vector<std::shared_ptr<void>> DefineProperties();
-
-        /**
-        * @api
-        * @brief Get the number of class id and confidence from model inference.
-        * @param key
-        * @param buffer
-        * @return APP_ERROR
-        */
-        static MxTools::MxpiPortInfo DefineInputPorts();
-
-        /**
-        * @api
-        * @brief Define the input ports.
-        * @return MxpiPortInfo
-        */
-        static MxTools::MxpiPortInfo DefineOutputPorts();
-
-        /**
-        * @api
-        * @brief Define the output ports.
-        * @return MxpiPortInfo
-        */
-        static int distance(int x0, int y0, int x1, int y1);
-
-        /**
-        * @api
-        * @brief Calculate the distance between two points.
-        * @param int
-        * @return int
-        */
-        static int
-        calculate(std::map<int, std::vector<int>> &trackdata, int confframes_, int &frame_num, int confthresh_,
-                  std::shared_ptr<MxTools::MxpiTrackLetList> srcTrackLetListSptr,
-                  std::shared_ptr<MxTools::MxpiObjectList> srcObjectListSptr);
-        /**
-        * @api
-        * @brief Data processing.
-        * @return int
-        */
-    private:
-        APP_ERROR SetMxpiErrorInfo(MxTools::MxpiBuffer &buffer, const std::string pluginName,
-                                   const MxTools::MxpiErrorInfo mxpiErrorInfo);
-
-        std::string tracksource_;
-        std::string detectionsource_;
-        std::string descriptionMessage_;
-        std::ostringstream ErrorInfo_;
-        std::map<int, std::vector<int>> trackdata;
-        int confthresh_;
-        int confframes_;
-        int confsleep_;
-        int frame_num = 0;
-        int sleeptime = 0;
-        int frame = 0;
-        int alarm_count = 0;
-    };
-}
+/*
+* Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+#ifndef SDKMEMORY_PLUGINOVERSPEED_H
+#define SDKMEMORY_PLUGINOVERSPEED_H
+
+#include "MxTools/PluginToolkit/base/MxPluginGenerator.h"
+#include "MxTools/PluginToolkit/base/MxPluginBase.h"
+#include "MxTools/PluginToolkit/metadata/MxpiMetadataManager.h"
+#include "MxTools/Proto/MxpiDataType.pb.h"
+#include "MxBase/ErrorCode/ErrorCode.h"
+
+/**
+* @api
+* @brief Definition of PluginOverSpeed class.
+*/
+
+namespace MxPlugins {
+    class PluginOverSpeed : public MxTools::MxPluginBase {
+    public:
+        /**
+        * @api
+        * @brief Initialize configure parameter.
+        * @param configParamMap
+        * @return APP_ERROR
+        */
+        APP_ERROR Init(std::map<std::string, std::shared_ptr<void>> &configParamMap) override;
+
+        /**
+        * * @api
+        * @brief DeInitialize configure parameter.
+        * @return APP_ERROR
+        */
+        APP_ERROR DeInit() override;
+
+        /**
+        * @api
+        * @brief Process the data of MxpiBuffer.
+        * @param mxpiBuffer
+        * @return APP_ERROR
+        */
+        APP_ERROR Process(std::vector<MxTools::MxpiBuffer *> &mxpiBuffer) override;
+
+        /**
+        * @api
+        * @brief Definition the parameter of configure properties.
+        * @return std::vector<std::shared_ptr<void>>
+        */
+        static std::vector<std::shared_ptr<void>> DefineProperties();
+
+        /**
+        * @api
+        * @brief Get the number of class id and confidence from model inference.
+        * @param key
+        * @param buffer
+        * @return APP_ERROR
+        */
+        static MxTools::MxpiPortInfo DefineInputPorts();
+
+        /**
+        * @api
+        * @brief Define the input ports.
+        * @return MxpiPortInfo
+        */
+        static MxTools::MxpiPortInfo DefineOutputPorts();
+
+        /**
+        * @api
+        * @brief Define the output ports.
+        * @return MxpiPortInfo
+        */
+        static int distance(int x0, int y0, int x1, int y1);
+
+        /**
+        * @api
+        * @brief Calculate the distance between two points.
+        * @param int
+        * @return int
+        */
+        static int
+        calculate(std::map<int, std::vector<int>> &trackdata, int confframes_, int &frame_num, int confthresh_,
+                  std::shared_ptr<MxTools::MxpiTrackLetList> srcTrackLetListSptr,
+                  std::shared_ptr<MxTools::MxpiObjectList> srcObjectListSptr);
+        /**
+        * @api
+        * @brief Data processing.
+        * @return int
+        */
+    private:
+        APP_ERROR SetMxpiErrorInfo(MxTools::MxpiBuffer &buffer, const std::string pluginName,
+                                   const MxTools::MxpiErrorInfo mxpiErrorInfo);
+
+        std::string tracksource_;
+        std::string detectionsource_;
+        std::string descriptionMessage_;
+        std::ostringstream ErrorInfo_;
+        std::map<int, std::vector<int>> trackdata;
+        int confthresh_;
+        int confframes_;
+        int confsleep_;
+        int frame_num = 0;
+        int sleeptime = 0;
+        int frame = 0;
+        int alarm_count = 0;
+    };
+}
 #endif
\ No newline at end of file
diff --git a/contrib/ActionRecognition/plugins/PluginOverSpeed/build.sh b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginOverSpeed/build.sh
similarity index 100%
rename from contrib/ActionRecognition/plugins/PluginOverSpeed/build.sh
rename to mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginOverSpeed/build.sh
diff --git a/contrib/ActionRecognition/plugins/PluginOverStay/CMakeLists.txt b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginOverStay/CMakeLists.txt
similarity index 100%
rename from contrib/ActionRecognition/plugins/PluginOverStay/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginOverStay/CMakeLists.txt
diff --git a/contrib/ActionRecognition/plugins/PluginOverStay/PluginOverStay.cpp b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginOverStay/PluginOverStay.cpp
similarity index 97%
rename from contrib/ActionRecognition/plugins/PluginOverStay/PluginOverStay.cpp
rename to mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginOverStay/PluginOverStay.cpp
index 71f7e05b1396798c7240239d30e764d49fc144e6..cb618e1d629babd77fd31d8a9dde20263da7021d 100644
--- a/contrib/ActionRecognition/plugins/PluginOverStay/PluginOverStay.cpp
+++ b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginOverStay/PluginOverStay.cpp
@@ -1,283 +1,283 @@
-/*
-* Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-* http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-
-#include "math.h"
-#include "MxBase/Log/Log.h"
-#include "MxTools/PluginToolkit/base/MxPluginBase.h"
-#include "PluginOverStay.h"
-
-using namespace MxPlugins;
-using namespace MxTools;
-using namespace std;
-
-namespace MxPlugins {
-    APP_ERROR PluginOverStay::Init(std::map<std::string, std::shared_ptr<void>> &configParamMap) {
-        LogInfo << "PluginOverStay::Init start.";
-        APP_ERROR ret = APP_ERR_OK;
-        // Get the property values by key
-        std::shared_ptr<string> tracksourcePropSptr =
-                std::static_pointer_cast<string>(configParamMap["dataSourceTrack"]);
-        tracksource_ = *tracksourcePropSptr.get();
-
-        std::shared_ptr<string> dataSourceDetection =
-                std::static_pointer_cast<string>(configParamMap["dataSourceDetection"]);
-        detectionsource_ = *dataSourceDetection.get();
-
-        std::shared_ptr<string> descriptionMessageProSptr =
-                std::static_pointer_cast<string>(configParamMap["descriptionMessage"]);
-        descriptionMessage_ = *descriptionMessageProSptr.get();
-
-        // Configuration parameter
-        confthresh_ = *std::static_pointer_cast<int>(configParamMap["stayThresh"]);
-        confframes_ = *std::static_pointer_cast<int>(configParamMap["frames"]);
-        confsleep_ = *std::static_pointer_cast<int>(configParamMap["detectSleep"]);
-        confdistance_ = *std::static_pointer_cast<int>(configParamMap["distanceThresh"]);
-        confratio_ = *std::static_pointer_cast<float>(configParamMap["detectRatio"]);
-        return APP_ERR_OK;
-    }
-
-    APP_ERROR PluginOverStay::DeInit() {
-        LogInfo << "PluginOverStay::DeInit end.";
-        return APP_ERR_OK;
-    }
-
-    APP_ERROR PluginOverStay::SetMxpiErrorInfo(MxpiBuffer &buffer, const std::string pluginName,
-                                               const MxpiErrorInfo mxpiErrorInfo) {
-        APP_ERROR ret = APP_ERR_OK;
-        // Define an object of MxpiMetadataManager
-        MxpiMetadataManager mxpiMetadataManager(buffer);
-        ret = mxpiMetadataManager.AddErrorInfo(pluginName, mxpiErrorInfo);
-        if (ret != APP_ERR_OK) {
-            LogError << "Failed to AddErrorInfo.";
-            return ret;
-        }
-        ret = SendData(0, buffer);
-        return ret;
-    }
-
-    APP_ERROR PluginOverStay::Process(std::vector<MxpiBuffer *> &mxpiBuffer) {
-        LogInfo << "PluginOverStay::Process start";
-        MxpiBuffer *buffer = mxpiBuffer[0];
-        MxpiMetadataManager mxpiMetadataManager(*buffer);
-        MxpiErrorInfo mxpiErrorInfo;
-        ErrorInfo_.str("");
-        auto errorInfoPtr = mxpiMetadataManager.GetErrorInfo();
-        frame++;
-        if (errorInfoPtr != nullptr) {
-            ErrorInfo_ << GetError(APP_ERR_COMM_FAILURE, pluginName_)
-                       << "PluginOverStay process is not implemented";
-            mxpiErrorInfo.ret = APP_ERR_COMM_FAILURE;
-            mxpiErrorInfo.errorInfo = ErrorInfo_.str();
-            SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
-            LogError << "PluginOverStay process is not implemented";
-            return APP_ERR_COMM_FAILURE;
-        }
-        // Get the data from buffer
-        shared_ptr<void> metadata = mxpiMetadataManager.GetMetadata(tracksource_);
-        shared_ptr<void> Detect = mxpiMetadataManager.GetMetadata(detectionsource_);
-
-        if (metadata == nullptr) {
-            ErrorInfo_ << GetError(APP_ERR_METADATA_IS_NULL, pluginName_)
-                       << "Metadata is NULL, failed";
-            mxpiErrorInfo.ret = APP_ERR_METADATA_IS_NULL;
-            mxpiErrorInfo.errorInfo = ErrorInfo_.str();
-            SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
-            return APP_ERR_METADATA_IS_NULL;
-        }
-        // get trackletlist
-        std::shared_ptr<MxpiTrackLetList> srcTrackLetListSptr = std::static_pointer_cast<MxpiTrackLetList>(metadata);
-        std::shared_ptr<MxpiObjectList> srcObjectListSptr = std::static_pointer_cast<MxpiObjectList>(Detect);
-        // data processing
-        std::shared_ptr<MxTools::MxpiAttributeList> result = std::make_shared<MxTools::MxpiAttributeList>();
-        MxpiAttribute *mxpiAttribute = result->add_attributevec();
-        if (sleeptime == 0) {
-            // update data
-            int alarm = calculate(trackdata, confframes_, frame_num, confthresh_, confratio_, confdistance_,
-                                  srcTrackLetListSptr, srcObjectListSptr);
-            if (alarm == 1) {
-                alarm_count++;
-                LogInfo << "Alarmed " << alarm_count << " times";
-                sleeptime = confsleep_;
-                mxpiAttribute->set_attrname("Alarm Overstay");
-                APP_ERROR ret = mxpiMetadataManager.AddProtoMetadata(pluginName_,
-                                                                     static_pointer_cast<void>(result));
-                if (ret != APP_ERR_OK) {
-                    ErrorInfo_ << GetError(ret, pluginName_) << "PluginOverstay add metadata failed.";
-                    mxpiErrorInfo.ret = ret;
-                    mxpiErrorInfo.errorInfo = ErrorInfo_.str();
-                    SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
-                    return ret;
-                }
-            } else {
-                mxpiAttribute->set_attrname("No Alarm");
-                APP_ERROR ret = mxpiMetadataManager.AddProtoMetadata(pluginName_,
-                                                                     static_pointer_cast<void>(result));
-                if (ret != APP_ERR_OK) {
-                    ErrorInfo_ << GetError(ret, pluginName_) << "PluginOverstay add metadata failed.";
-                    mxpiErrorInfo.ret = ret;
-                    mxpiErrorInfo.errorInfo = ErrorInfo_.str();
-                    SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
-                    return ret;
-                }
-            }
-        } else {
-            mxpiAttribute->set_attrname("Alarmed in a short period of time");
-            APP_ERROR ret = mxpiMetadataManager.AddProtoMetadata(pluginName_,
-                                                                 static_pointer_cast<void>(result));
-            if (ret != APP_ERR_OK) {
-                ErrorInfo_ << GetError(ret, pluginName_) << "PluginOverstay add metadata failed.";
-                mxpiErrorInfo.ret = ret;
-                mxpiErrorInfo.errorInfo = ErrorInfo_.str();
-                SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
-                return ret;
-            }
-            sleeptime--;
-        }
-        // Send the data to downstream plugin
-        SendData(0, *buffer);
-        LogInfo << "PluginOverStay::Process end";
-        return APP_ERR_OK;
-    }
-
-    int PluginOverStay::calculate(std::map<int, std::vector<int>> &trackdata, int confframes_, int &frame_num,
-                                  int confthresh_, int confratio_, int confdistance_,
-                                  std::shared_ptr<MxpiTrackLetList> srcTrackLetListSptr,
-                                  std::shared_ptr<MxpiObjectList> srcObjectListSptr) {
-        int alarm = 0;
-        for (uint32_t i = 0; i < (uint32_t) srcTrackLetListSptr->trackletvec_size(); i++) {
-            auto &trackObject = srcTrackLetListSptr->trackletvec(i);
-            if (trackObject.headervec_size() == 0) {
-                continue;
-            }
-            auto &detectObject = srcObjectListSptr->objectvec(trackObject.headervec(0).memberid());
-            if (detectObject.classvec(0).classid() != 0) {
-                continue;
-            }
-            if (trackdata.count(trackObject.trackid()) == 0) {
-                trackdata[trackObject.trackid()].push_back((int) ((detectObject.x0() + detectObject.x1()) / 2));
-                trackdata[trackObject.trackid()].push_back((int) ((detectObject.y0() + detectObject.y1()) / 2));
-                trackdata[trackObject.trackid()][2] = 1;
-            } else {
-                int dis = distance(trackdata[trackObject.trackid()][0],
-                                   trackdata[trackObject.trackid()][1],
-                                   (int) ((detectObject.x0() + detectObject.x1()) / 2),
-                                   (int) ((detectObject.y0() + detectObject.y1()) / 2));
-                if (dis < confdistance_) {
-                    trackdata[trackObject.trackid()][2]++;
-                } else {
-                    trackdata[trackObject.trackid()][2] = 1;
-                }
-                trackdata[trackObject.trackid()][0] = (int) ((detectObject.x0() + detectObject.x1()) / 2);
-                trackdata[trackObject.trackid()][1] = (int) ((detectObject.y0() + detectObject.y1()) / 2);
-            }
-        }
-        frame_num++;
-        // calculate data
-        if (frame_num == confframes_) {
-            frame_num = 0;
-            for (auto iter = trackdata.begin(); iter != trackdata.end(); iter++) {
-                if (trackdata[iter->first][2] >= (int) (confratio_ * confthresh_)) {
-                    alarm = 1;
-                    break;
-                }
-            }
-            trackdata.clear();
-        }
-        return alarm;
-    }
-
-    std::vector<std::shared_ptr<void>> PluginOverStay::DefineProperties() {
-        // Define an A to store properties
-        std::vector<std::shared_ptr<void>> properties;
-        // Set the type and related information of the properties, and the key is the name
-        auto tracksourceProSptr =
-                std::make_shared<ElementProperty<string >>(ElementProperty<string>{
-                        STRING, "dataSourceTrack", "name",
-                        "the name of previous plugin", "mxpi_motsimplesort0", "NULL",
-                        "NULL"});
-
-        auto detectsourceProSptr =
-                std::make_shared<ElementProperty<string >>(ElementProperty<string>{
-                        STRING, "dataSourceDetection", "name",
-                        "the name of previous plugin", "mxpi_fairmot0",
-                        "NULL", "NULL"});
-
-        auto threshProSptr = // 逗留时间阈值
-                std::make_shared<ElementProperty<int >>(ElementProperty<int>{
-                        UINT, "stayThresh", "name",
-                        "the name of previous plugin", 10,
-                        10, 1000});
-
-        auto distanceProSptr = // 移动距离阈值
-                std::make_shared<ElementProperty<int >>(ElementProperty<int>{
-                        UINT, "distanceThresh", "name",
-                        "the name of previous plugin", 6,
-                        0, 100});
-
-        auto frameProSptr = // 多少帧检测一次
-                std::make_shared<ElementProperty<int >>(ElementProperty<int>{
-                        UINT, "frames", "name",
-                        "the name of previous plugin", 8,
-                        8, 100});
-
-        auto sleepProSptr = // 检测后休止时间
-                std::make_shared<ElementProperty<int >>(ElementProperty<int>{
-                        UINT, "detectSleep", "name", " ", 8, 0,
-                        100});
-
-        auto ratioProSptr = // 检出比例
-                std::make_shared<ElementProperty<float >>(ElementProperty<float>{
-                        FLOAT, "detectRatio", "name", " ", 0.8, 0.1,
-                        1.0});
-
-        auto descriptionMessageProSptr =
-                std::make_shared<ElementProperty<string >>(ElementProperty<string>{
-                        STRING, "descriptionMessage", "message",
-                        "Description mesasge of plugin",
-                        "This is PluginOverStay", "NULL", "NULL"});
-        properties.push_back(tracksourceProSptr);
-        properties.push_back(detectsourceProSptr);
-        properties.push_back(threshProSptr);
-        properties.push_back(frameProSptr);
-        properties.push_back(sleepProSptr);
-        properties.push_back(distanceProSptr);
-        properties.push_back(ratioProSptr);
-        properties.push_back(descriptionMessageProSptr);
-        return properties;
-    }
-
-    MxpiPortInfo PluginOverStay::DefineInputPorts() {
-        MxpiPortInfo inputPortInfo;
-        std::vector<std::vector<std::string>> value = {{"ANY"}};
-        MxPluginBase::GenerateStaticInputPortsInfo(value, inputPortInfo);
-        return inputPortInfo;
-    };
-
-    MxpiPortInfo PluginOverStay::DefineOutputPorts() {
-        MxpiPortInfo outputPortInfo;
-        std::vector<std::vector<std::string>> value = {{"ANY"}};
-        MxPluginBase::GenerateStaticOutputPortsInfo(value, outputPortInfo);
-        return outputPortInfo;
-    }
-
-    int PluginOverStay::distance(int x0, int y0, int x1, int y1) {
-        int distance = int(sqrt((x1 - x0) * (x1 - x0) + (y1 - y0) * (y1 - y0)));
-        return distance;
-    }
-}
-namespace {
-    MX_PLUGIN_GENERATE(PluginOverStay)
-}
+/*
+* Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "math.h"
+#include "MxBase/Log/Log.h"
+#include "MxTools/PluginToolkit/base/MxPluginBase.h"
+#include "PluginOverStay.h"
+
+using namespace MxPlugins;
+using namespace MxTools;
+using namespace std;
+
+namespace MxPlugins {
+    APP_ERROR PluginOverStay::Init(std::map<std::string, std::shared_ptr<void>> &configParamMap) {
+        LogInfo << "PluginOverStay::Init start.";
+        APP_ERROR ret = APP_ERR_OK;
+        // Get the property values by key
+        std::shared_ptr<string> tracksourcePropSptr =
+                std::static_pointer_cast<string>(configParamMap["dataSourceTrack"]);
+        tracksource_ = *tracksourcePropSptr.get();
+
+        std::shared_ptr<string> dataSourceDetection =
+                std::static_pointer_cast<string>(configParamMap["dataSourceDetection"]);
+        detectionsource_ = *dataSourceDetection.get();
+
+        std::shared_ptr<string> descriptionMessageProSptr =
+                std::static_pointer_cast<string>(configParamMap["descriptionMessage"]);
+        descriptionMessage_ = *descriptionMessageProSptr.get();
+
+        // Configuration parameter
+        confthresh_ = *std::static_pointer_cast<int>(configParamMap["stayThresh"]);
+        confframes_ = *std::static_pointer_cast<int>(configParamMap["frames"]);
+        confsleep_ = *std::static_pointer_cast<int>(configParamMap["detectSleep"]);
+        confdistance_ = *std::static_pointer_cast<int>(configParamMap["distanceThresh"]);
+        confratio_ = *std::static_pointer_cast<float>(configParamMap["detectRatio"]);
+        return APP_ERR_OK;
+    }
+
+    APP_ERROR PluginOverStay::DeInit() {
+        LogInfo << "PluginOverStay::DeInit end.";
+        return APP_ERR_OK;
+    }
+
+    APP_ERROR PluginOverStay::SetMxpiErrorInfo(MxpiBuffer &buffer, const std::string pluginName,
+                                               const MxpiErrorInfo mxpiErrorInfo) {
+        APP_ERROR ret = APP_ERR_OK;
+        // Define an object of MxpiMetadataManager
+        MxpiMetadataManager mxpiMetadataManager(buffer);
+        ret = mxpiMetadataManager.AddErrorInfo(pluginName, mxpiErrorInfo);
+        if (ret != APP_ERR_OK) {
+            LogError << "Failed to AddErrorInfo.";
+            return ret;
+        }
+        ret = SendData(0, buffer);
+        return ret;
+    }
+
+    APP_ERROR PluginOverStay::Process(std::vector<MxpiBuffer *> &mxpiBuffer) {
+        LogInfo << "PluginOverStay::Process start";
+        MxpiBuffer *buffer = mxpiBuffer[0];
+        MxpiMetadataManager mxpiMetadataManager(*buffer);
+        MxpiErrorInfo mxpiErrorInfo;
+        ErrorInfo_.str("");
+        auto errorInfoPtr = mxpiMetadataManager.GetErrorInfo();
+        frame++;
+        if (errorInfoPtr != nullptr) {
+            ErrorInfo_ << GetError(APP_ERR_COMM_FAILURE, pluginName_)
+                       << "PluginOverStay process is not implemented";
+            mxpiErrorInfo.ret = APP_ERR_COMM_FAILURE;
+            mxpiErrorInfo.errorInfo = ErrorInfo_.str();
+            SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
+            LogError << "PluginOverStay process is not implemented";
+            return APP_ERR_COMM_FAILURE;
+        }
+        // Get the data from buffer
+        shared_ptr<void> metadata = mxpiMetadataManager.GetMetadata(tracksource_);
+        shared_ptr<void> Detect = mxpiMetadataManager.GetMetadata(detectionsource_);
+
+        if (metadata == nullptr) {
+            ErrorInfo_ << GetError(APP_ERR_METADATA_IS_NULL, pluginName_)
+                       << "Metadata is NULL, failed";
+            mxpiErrorInfo.ret = APP_ERR_METADATA_IS_NULL;
+            mxpiErrorInfo.errorInfo = ErrorInfo_.str();
+            SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
+            return APP_ERR_METADATA_IS_NULL;
+        }
+        // get trackletlist
+        std::shared_ptr<MxpiTrackLetList> srcTrackLetListSptr = std::static_pointer_cast<MxpiTrackLetList>(metadata);
+        std::shared_ptr<MxpiObjectList> srcObjectListSptr = std::static_pointer_cast<MxpiObjectList>(Detect);
+        // data processing
+        std::shared_ptr<MxTools::MxpiAttributeList> result = std::make_shared<MxTools::MxpiAttributeList>();
+        MxpiAttribute *mxpiAttribute = result->add_attributevec();
+        if (sleeptime == 0) {
+            // update data
+            int alarm = calculate(trackdata, confframes_, frame_num, confthresh_, confratio_, confdistance_,
+                                  srcTrackLetListSptr, srcObjectListSptr);
+            if (alarm == 1) {
+                alarm_count++;
+                LogInfo << "Alarmed " << alarm_count << " times";
+                sleeptime = confsleep_;
+                mxpiAttribute->set_attrname("Alarm Overstay");
+                APP_ERROR ret = mxpiMetadataManager.AddProtoMetadata(pluginName_,
+                                                                     static_pointer_cast<void>(result));
+                if (ret != APP_ERR_OK) {
+                    ErrorInfo_ << GetError(ret, pluginName_) << "PluginOverstay add metadata failed.";
+                    mxpiErrorInfo.ret = ret;
+                    mxpiErrorInfo.errorInfo = ErrorInfo_.str();
+                    SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
+                    return ret;
+                }
+            } else {
+                mxpiAttribute->set_attrname("No Alarm");
+                APP_ERROR ret = mxpiMetadataManager.AddProtoMetadata(pluginName_,
+                                                                     static_pointer_cast<void>(result));
+                if (ret != APP_ERR_OK) {
+                    ErrorInfo_ << GetError(ret, pluginName_) << "PluginOverstay add metadata failed.";
+                    mxpiErrorInfo.ret = ret;
+                    mxpiErrorInfo.errorInfo = ErrorInfo_.str();
+                    SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
+                    return ret;
+                }
+            }
+        } else {
+            mxpiAttribute->set_attrname("Alarmed in a short period of time");
+            APP_ERROR ret = mxpiMetadataManager.AddProtoMetadata(pluginName_,
+                                                                 static_pointer_cast<void>(result));
+            if (ret != APP_ERR_OK) {
+                ErrorInfo_ << GetError(ret, pluginName_) << "PluginOverstay add metadata failed.";
+                mxpiErrorInfo.ret = ret;
+                mxpiErrorInfo.errorInfo = ErrorInfo_.str();
+                SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
+                return ret;
+            }
+            sleeptime--;
+        }
+        // Send the data to downstream plugin
+        SendData(0, *buffer);
+        LogInfo << "PluginOverStay::Process end";
+        return APP_ERR_OK;
+    }
+
+    int PluginOverStay::calculate(std::map<int, std::vector<int>> &trackdata, int confframes_, int &frame_num,
+                                  int confthresh_, int confratio_, int confdistance_,
+                                  std::shared_ptr<MxpiTrackLetList> srcTrackLetListSptr,
+                                  std::shared_ptr<MxpiObjectList> srcObjectListSptr) {
+        int alarm = 0;
+        for (uint32_t i = 0; i < (uint32_t) srcTrackLetListSptr->trackletvec_size(); i++) {
+            auto &trackObject = srcTrackLetListSptr->trackletvec(i);
+            if (trackObject.headervec_size() == 0) {
+                continue;
+            }
+            auto &detectObject = srcObjectListSptr->objectvec(trackObject.headervec(0).memberid());
+            if (detectObject.classvec(0).classid() != 0) {
+                continue;
+            }
+            if (trackdata.count(trackObject.trackid()) == 0) {
+                trackdata[trackObject.trackid()].push_back((int) ((detectObject.x0() + detectObject.x1()) / 2));
+                trackdata[trackObject.trackid()].push_back((int) ((detectObject.y0() + detectObject.y1()) / 2));
+                trackdata[trackObject.trackid()][2] = 1;
+            } else {
+                int dis = distance(trackdata[trackObject.trackid()][0],
+                                   trackdata[trackObject.trackid()][1],
+                                   (int) ((detectObject.x0() + detectObject.x1()) / 2),
+                                   (int) ((detectObject.y0() + detectObject.y1()) / 2));
+                if (dis < confdistance_) {
+                    trackdata[trackObject.trackid()][2]++;
+                } else {
+                    trackdata[trackObject.trackid()][2] = 1;
+                }
+                trackdata[trackObject.trackid()][0] = (int) ((detectObject.x0() + detectObject.x1()) / 2);
+                trackdata[trackObject.trackid()][1] = (int) ((detectObject.y0() + detectObject.y1()) / 2);
+            }
+        }
+        frame_num++;
+        // calculate data
+        if (frame_num == confframes_) {
+            frame_num = 0;
+            for (auto iter = trackdata.begin(); iter != trackdata.end(); iter++) {
+                if (trackdata[iter->first][2] >= (int) (confratio_ * confthresh_)) {
+                    alarm = 1;
+                    break;
+                }
+            }
+            trackdata.clear();
+        }
+        return alarm;
+    }
+
+    std::vector<std::shared_ptr<void>> PluginOverStay::DefineProperties() {
+        // Define an A to store properties
+        std::vector<std::shared_ptr<void>> properties;
+        // Set the type and related information of the properties, and the key is the name
+        auto tracksourceProSptr =
+                std::make_shared<ElementProperty<string >>(ElementProperty<string>{
+                        STRING, "dataSourceTrack", "name",
+                        "the name of previous plugin", "mxpi_motsimplesort0", "NULL",
+                        "NULL"});
+
+        auto detectsourceProSptr =
+                std::make_shared<ElementProperty<string >>(ElementProperty<string>{
+                        STRING, "dataSourceDetection", "name",
+                        "the name of previous plugin", "mxpi_fairmot0",
+                        "NULL", "NULL"});
+
+        auto threshProSptr = // 逗留时间阈值
+                std::make_shared<ElementProperty<int >>(ElementProperty<int>{
+                        UINT, "stayThresh", "name",
+                        "the name of previous plugin", 10,
+                        10, 1000});
+
+        auto distanceProSptr = // 移动距离阈值
+                std::make_shared<ElementProperty<int >>(ElementProperty<int>{
+                        UINT, "distanceThresh", "name",
+                        "the name of previous plugin", 6,
+                        0, 100});
+
+        auto frameProSptr = // 多少帧检测一次
+                std::make_shared<ElementProperty<int >>(ElementProperty<int>{
+                        UINT, "frames", "name",
+                        "the name of previous plugin", 8,
+                        8, 100});
+
+        auto sleepProSptr = // 检测后休止时间
+                std::make_shared<ElementProperty<int >>(ElementProperty<int>{
+                        UINT, "detectSleep", "name", " ", 8, 0,
+                        100});
+
+        auto ratioProSptr = // 检出比例
+                std::make_shared<ElementProperty<float >>(ElementProperty<float>{
+                        FLOAT, "detectRatio", "name", " ", 0.8, 0.1,
+                        1.0});
+
+        auto descriptionMessageProSptr =
+                std::make_shared<ElementProperty<string >>(ElementProperty<string>{
+                        STRING, "descriptionMessage", "message",
+                        "Description mesasge of plugin",
+                        "This is PluginOverStay", "NULL", "NULL"});
+        properties.push_back(tracksourceProSptr);
+        properties.push_back(detectsourceProSptr);
+        properties.push_back(threshProSptr);
+        properties.push_back(frameProSptr);
+        properties.push_back(sleepProSptr);
+        properties.push_back(distanceProSptr);
+        properties.push_back(ratioProSptr);
+        properties.push_back(descriptionMessageProSptr);
+        return properties;
+    }
+
+    MxpiPortInfo PluginOverStay::DefineInputPorts() {
+        MxpiPortInfo inputPortInfo;
+        std::vector<std::vector<std::string>> value = {{"ANY"}};
+        MxPluginBase::GenerateStaticInputPortsInfo(value, inputPortInfo);
+        return inputPortInfo;
+    };
+
+    MxpiPortInfo PluginOverStay::DefineOutputPorts() {
+        MxpiPortInfo outputPortInfo;
+        std::vector<std::vector<std::string>> value = {{"ANY"}};
+        MxPluginBase::GenerateStaticOutputPortsInfo(value, outputPortInfo);
+        return outputPortInfo;
+    }
+
+    int PluginOverStay::distance(int x0, int y0, int x1, int y1) {
+        int distance = int(sqrt((x1 - x0) * (x1 - x0) + (y1 - y0) * (y1 - y0)));
+        return distance;
+    }
+}
+namespace {
+    MX_PLUGIN_GENERATE(PluginOverStay)
+}
diff --git a/contrib/ActionRecognition/plugins/PluginOverStay/PluginOverStay.h b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginOverStay/PluginOverStay.h
similarity index 96%
rename from contrib/ActionRecognition/plugins/PluginOverStay/PluginOverStay.h
rename to mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginOverStay/PluginOverStay.h
index dcfd89b6f3f9a9a4f40a41bb7f85462885cccf72..bd5ce271d7ea74056314c228b8e9a5593b9fa679 100644
--- a/contrib/ActionRecognition/plugins/PluginOverStay/PluginOverStay.h
+++ b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginOverStay/PluginOverStay.h
@@ -1,123 +1,123 @@
-/*
-* Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-* http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-
-#ifndef SDKMEMORY_PLUGINOVERSTAY_H
-#define SDKMEMORY_PLUGINOVERSTAY_H
-
-#include "MxBase/ErrorCode/ErrorCode.h"
-#include "MxTools/PluginToolkit/base/MxPluginGenerator.h"
-#include "MxTools/PluginToolkit/base/MxPluginBase.h"
-#include "MxTools/PluginToolkit/metadata/MxpiMetadataManager.h"
-#include "MxTools/Proto/MxpiDataType.pb.h"
-
-/**
-* @api
-* @brief Definition of PluginOverStay class.
-*/
-
-namespace MxPlugins {
-    class PluginOverStay : public MxTools::MxPluginBase {
-    public:
-        /**
-        * @api
-        * @brief Initialize configure parameter.
-        * @param configParamMap
-        * @return APP_ERROR
-        */
-        APP_ERROR Init(std::map<std::string, std::shared_ptr<void>> &configParamMap) override;
-
-        /**
-        * * @api
-        * @brief DeInitialize configure parameter.
-        * @return APP_ERROR
-        */
-        APP_ERROR DeInit() override;
-
-        /**
-        * @api
-        * @brief Process the data of MxpiBuffer.
-        * @param mxpiBuffer
-        * @return APP_ERROR
-        */
-        APP_ERROR Process(std::vector<MxTools::MxpiBuffer *> &mxpiBuffer) override;
-
-        /**
-        * @api
-        * @brief Definition the parameter of configure properties.
-        * @return std::vector<std::shared_ptr<void>>
-        */
-        static std::vector<std::shared_ptr<void>> DefineProperties();
-
-        /**
-        * @api
-        * @brief Get the number of class id and confidence from model inference.
-        * @param key
-        * @param buffer
-        * @return APP_ERROR
-        */
-        static MxTools::MxpiPortInfo DefineInputPorts();
-
-        /**
-        * @api
-        * @brief Define the input ports.
-        * @return MxpiPortInfo
-        */
-        static MxTools::MxpiPortInfo DefineOutputPorts();
-
-        /**
-        * @api
-        * @brief Define the output ports.
-        * @return MxpiPortInfo
-        */
-        static int distance(int x0, int y0, int x1, int y1);
-
-        /**
-        * @api
-        * @brief Calculate the distance between two points.
-        * @param int
-        * @return int
-        */
-        static int
-        calculate(std::map<int, std::vector<int>> &trackdata, int confframes_, int &frame_num, int confthresh_,
-                  int confratio_, int confdistance_,
-                  std::shared_ptr<MxTools::MxpiTrackLetList> srcTrackLetListSptr,
-                  std::shared_ptr<MxTools::MxpiObjectList> srcObjectListSptr);
-        /**
-        * @api
-        * @brief Data processing.
-        * @return int
-        */
-    private:
-        APP_ERROR SetMxpiErrorInfo(MxTools::MxpiBuffer &buffer, const std::string pluginName,
-                                   const MxTools::MxpiErrorInfo mxpiErrorInfo);
-
-        std::string tracksource_;
-        std::string detectionsource_;
-        std::string descriptionMessage_;
-        std::ostringstream ErrorInfo_;
-        std::map<int, std::vector<int>> trackdata;
-        int confthresh_;
-        int confframes_;
-        int confsleep_;
-        int confdistance_;
-        float confratio_;
-        int frame_num = 0;
-        int sleeptime = 0;
-        int alarm_count = 0;
-        int frame = 0;
-    };
-}
+/*
+* Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#ifndef SDKMEMORY_PLUGINOVERSTAY_H
+#define SDKMEMORY_PLUGINOVERSTAY_H
+
+#include "MxBase/ErrorCode/ErrorCode.h"
+#include "MxTools/PluginToolkit/base/MxPluginGenerator.h"
+#include "MxTools/PluginToolkit/base/MxPluginBase.h"
+#include "MxTools/PluginToolkit/metadata/MxpiMetadataManager.h"
+#include "MxTools/Proto/MxpiDataType.pb.h"
+
+/**
+* @api
+* @brief Definition of PluginOverStay class.
+*/
+
+namespace MxPlugins {
+    class PluginOverStay : public MxTools::MxPluginBase {
+    public:
+        /**
+        * @api
+        * @brief Initialize configure parameter.
+        * @param configParamMap
+        * @return APP_ERROR
+        */
+        APP_ERROR Init(std::map<std::string, std::shared_ptr<void>> &configParamMap) override;
+
+        /**
+        * * @api
+        * @brief DeInitialize configure parameter.
+        * @return APP_ERROR
+        */
+        APP_ERROR DeInit() override;
+
+        /**
+        * @api
+        * @brief Process the data of MxpiBuffer.
+        * @param mxpiBuffer
+        * @return APP_ERROR
+        */
+        APP_ERROR Process(std::vector<MxTools::MxpiBuffer *> &mxpiBuffer) override;
+
+        /**
+        * @api
+        * @brief Definition the parameter of configure properties.
+        * @return std::vector<std::shared_ptr<void>>
+        */
+        static std::vector<std::shared_ptr<void>> DefineProperties();
+
+        /**
+        * @api
+        * @brief Get the number of class id and confidence from model inference.
+        * @param key
+        * @param buffer
+        * @return APP_ERROR
+        */
+        static MxTools::MxpiPortInfo DefineInputPorts();
+
+        /**
+        * @api
+        * @brief Define the input ports.
+        * @return MxpiPortInfo
+        */
+        static MxTools::MxpiPortInfo DefineOutputPorts();
+
+        /**
+        * @api
+        * @brief Define the output ports.
+        * @return MxpiPortInfo
+        */
+        static int distance(int x0, int y0, int x1, int y1);
+
+        /**
+        * @api
+        * @brief Calculate the distance between two points.
+        * @param int
+        * @return int
+        */
+        static int
+        calculate(std::map<int, std::vector<int>> &trackdata, int confframes_, int &frame_num, int confthresh_,
+                  int confratio_, int confdistance_,
+                  std::shared_ptr<MxTools::MxpiTrackLetList> srcTrackLetListSptr,
+                  std::shared_ptr<MxTools::MxpiObjectList> srcObjectListSptr);
+        /**
+        * @api
+        * @brief Data processing.
+        * @return int
+        */
+    private:
+        APP_ERROR SetMxpiErrorInfo(MxTools::MxpiBuffer &buffer, const std::string pluginName,
+                                   const MxTools::MxpiErrorInfo mxpiErrorInfo);
+
+        std::string tracksource_;
+        std::string detectionsource_;
+        std::string descriptionMessage_;
+        std::ostringstream ErrorInfo_;
+        std::map<int, std::vector<int>> trackdata;
+        int confthresh_;
+        int confframes_;
+        int confsleep_;
+        int confdistance_;
+        float confratio_;
+        int frame_num = 0;
+        int sleeptime = 0;
+        int alarm_count = 0;
+        int frame = 0;
+    };
+}
 #endif
\ No newline at end of file
diff --git a/contrib/ActionRecognition/plugins/PluginOverStay/build.sh b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginOverStay/build.sh
similarity index 100%
rename from contrib/ActionRecognition/plugins/PluginOverStay/build.sh
rename to mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginOverStay/build.sh
diff --git a/contrib/ActionRecognition/plugins/PluginViolentAction/CMakeLists.txt b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginViolentAction/CMakeLists.txt
similarity index 100%
rename from contrib/ActionRecognition/plugins/PluginViolentAction/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginViolentAction/CMakeLists.txt
diff --git a/contrib/ActionRecognition/plugins/PluginViolentAction/Plugin_ViolentAction.cpp b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginViolentAction/Plugin_ViolentAction.cpp
similarity index 100%
rename from contrib/ActionRecognition/plugins/PluginViolentAction/Plugin_ViolentAction.cpp
rename to mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginViolentAction/Plugin_ViolentAction.cpp
diff --git a/contrib/ActionRecognition/plugins/PluginViolentAction/Plugin_ViolentAction.h b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginViolentAction/Plugin_ViolentAction.h
similarity index 100%
rename from contrib/ActionRecognition/plugins/PluginViolentAction/Plugin_ViolentAction.h
rename to mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginViolentAction/Plugin_ViolentAction.h
diff --git a/contrib/ActionRecognition/plugins/PluginViolentAction/build.sh b/mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginViolentAction/build.sh
similarity index 100%
rename from contrib/ActionRecognition/plugins/PluginViolentAction/build.sh
rename to mxVision/mxVision-referenceapps/ActionRecognition/plugins/PluginViolentAction/build.sh
diff --git a/contrib/ActionRecognition/run.sh b/mxVision/mxVision-referenceapps/ActionRecognition/run.sh
similarity index 100%
rename from contrib/ActionRecognition/run.sh
rename to mxVision/mxVision-referenceapps/ActionRecognition/run.sh
diff --git a/mxVision/AiPhysicalAttackAndDetecting/ReadMe.md b/mxVision/mxVision-referenceapps/AiPhysicalAttackAndDetecting/ReadMe.md
similarity index 100%
rename from mxVision/AiPhysicalAttackAndDetecting/ReadMe.md
rename to mxVision/mxVision-referenceapps/AiPhysicalAttackAndDetecting/ReadMe.md
diff --git a/mxVision/AiPhysicalAttackAndDetecting/app.py b/mxVision/mxVision-referenceapps/AiPhysicalAttackAndDetecting/app.py
similarity index 100%
rename from mxVision/AiPhysicalAttackAndDetecting/app.py
rename to mxVision/mxVision-referenceapps/AiPhysicalAttackAndDetecting/app.py
diff --git a/mxVision/AiPhysicalAttackAndDetecting/args.py b/mxVision/mxVision-referenceapps/AiPhysicalAttackAndDetecting/args.py
similarity index 100%
rename from mxVision/AiPhysicalAttackAndDetecting/args.py
rename to mxVision/mxVision-referenceapps/AiPhysicalAttackAndDetecting/args.py
diff --git a/mxVision/AiPhysicalAttackAndDetecting/camera/camera_process.py b/mxVision/mxVision-referenceapps/AiPhysicalAttackAndDetecting/camera/camera_process.py
similarity index 100%
rename from mxVision/AiPhysicalAttackAndDetecting/camera/camera_process.py
rename to mxVision/mxVision-referenceapps/AiPhysicalAttackAndDetecting/camera/camera_process.py
diff --git a/mxVision/AiPhysicalAttackAndDetecting/config/config.ini b/mxVision/mxVision-referenceapps/AiPhysicalAttackAndDetecting/config/config.ini
similarity index 100%
rename from mxVision/AiPhysicalAttackAndDetecting/config/config.ini
rename to mxVision/mxVision-referenceapps/AiPhysicalAttackAndDetecting/config/config.ini
diff --git a/mxVision/AiPhysicalAttackAndDetecting/darknet_ob_detector/detect_ob_by_mxbase.py b/mxVision/mxVision-referenceapps/AiPhysicalAttackAndDetecting/darknet_ob_detector/detect_ob_by_mxbase.py
similarity index 100%
rename from mxVision/AiPhysicalAttackAndDetecting/darknet_ob_detector/detect_ob_by_mxbase.py
rename to mxVision/mxVision-referenceapps/AiPhysicalAttackAndDetecting/darknet_ob_detector/detect_ob_by_mxbase.py
diff --git a/contrib/VehicleIdentification/models/yolo/coco.names b/mxVision/mxVision-referenceapps/AiPhysicalAttackAndDetecting/darknet_ob_detector/model/coco.names
similarity index 100%
rename from contrib/VehicleIdentification/models/yolo/coco.names
rename to mxVision/mxVision-referenceapps/AiPhysicalAttackAndDetecting/darknet_ob_detector/model/coco.names
diff --git a/mxVision/AiPhysicalAttackAndDetecting/darknet_ob_detector/utils.py b/mxVision/mxVision-referenceapps/AiPhysicalAttackAndDetecting/darknet_ob_detector/utils.py
similarity index 100%
rename from mxVision/AiPhysicalAttackAndDetecting/darknet_ob_detector/utils.py
rename to mxVision/mxVision-referenceapps/AiPhysicalAttackAndDetecting/darknet_ob_detector/utils.py
diff --git a/mxVision/AiPhysicalAttackAndDetecting/requirements.txt b/mxVision/mxVision-referenceapps/AiPhysicalAttackAndDetecting/requirements.txt
similarity index 100%
rename from mxVision/AiPhysicalAttackAndDetecting/requirements.txt
rename to mxVision/mxVision-referenceapps/AiPhysicalAttackAndDetecting/requirements.txt
diff --git a/mxVision/AiPhysicalAttackAndDetecting/run.sh b/mxVision/mxVision-referenceapps/AiPhysicalAttackAndDetecting/run.sh
similarity index 100%
rename from mxVision/AiPhysicalAttackAndDetecting/run.sh
rename to mxVision/mxVision-referenceapps/AiPhysicalAttackAndDetecting/run.sh
diff --git a/mxVision/AiPhysicalAttackAndDetecting/templates/index.html b/mxVision/mxVision-referenceapps/AiPhysicalAttackAndDetecting/templates/index.html
similarity index 100%
rename from mxVision/AiPhysicalAttackAndDetecting/templates/index.html
rename to mxVision/mxVision-referenceapps/AiPhysicalAttackAndDetecting/templates/index.html
diff --git a/mxVision/AiPhysicalAttackAndDetecting/ultrayolo_attack_detector/detect_attack_by_mxbase.py b/mxVision/mxVision-referenceapps/AiPhysicalAttackAndDetecting/ultrayolo_attack_detector/detect_attack_by_mxbase.py
similarity index 100%
rename from mxVision/AiPhysicalAttackAndDetecting/ultrayolo_attack_detector/detect_attack_by_mxbase.py
rename to mxVision/mxVision-referenceapps/AiPhysicalAttackAndDetecting/ultrayolo_attack_detector/detect_attack_by_mxbase.py
diff --git a/mxVision/AiPhysicalAttackAndDetecting/ultrayolo_attack_detector/model/coco.yaml b/mxVision/mxVision-referenceapps/AiPhysicalAttackAndDetecting/ultrayolo_attack_detector/model/coco.yaml
similarity index 100%
rename from mxVision/AiPhysicalAttackAndDetecting/ultrayolo_attack_detector/model/coco.yaml
rename to mxVision/mxVision-referenceapps/AiPhysicalAttackAndDetecting/ultrayolo_attack_detector/model/coco.yaml
diff --git a/mxVision/AiPhysicalAttackAndDetecting/ultrayolo_attack_detector/utils.py b/mxVision/mxVision-referenceapps/AiPhysicalAttackAndDetecting/ultrayolo_attack_detector/utils.py
similarity index 100%
rename from mxVision/AiPhysicalAttackAndDetecting/ultrayolo_attack_detector/utils.py
rename to mxVision/mxVision-referenceapps/AiPhysicalAttackAndDetecting/ultrayolo_attack_detector/utils.py
diff --git a/mxVision/AllObjectsStructuring/CMakeLists.txt b/mxVision/mxVision-referenceapps/AllObjectsStructuring/CMakeLists.txt
similarity index 97%
rename from mxVision/AllObjectsStructuring/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/AllObjectsStructuring/CMakeLists.txt
index 8205309aabac5bf53bbb8ae22e4f138e657c2e90..d28fcde7155f7450467bee520a15002828c99043 100644
--- a/mxVision/AllObjectsStructuring/CMakeLists.txt
+++ b/mxVision/mxVision-referenceapps/AllObjectsStructuring/CMakeLists.txt
@@ -1,32 +1,32 @@
-cmake_minimum_required(VERSION 3.5.1)
-project(AllObjectsStructuring)
-
-add_definitions(-D_GLIBCXX_USE_CXX11_ABI=0)
-add_definitions(-Dgoogle=mindxsdk_private)
-set(CMAKE_CXX_STANDARD 11)
-set(PROJECT_DIR ${PROJECT_SOURCE_DIR})
-
-if(NOT DEFINED ENV{MX_SDK_HOME})
-    message(FATAL_ERROR "MX_SDK_HOME is not defined, please set it first.")
-else()
-    set(MX_SDK_HOME $ENV{MX_SDK_HOME})
-    message("MX_SDK_HOME=$ENV{MX_SDK_HOME}")
-endif()
-
-set(ENV{LD_LIBRARY_PATH} ${MX_SDK_HOME}/opensource/lib:$LD_LIBRARY_PATH)
-
-include_directories(${MX_SDK_HOME}/include)
-include_directories(${MX_SDK_HOME}/opensource/include)
-include_directories(${MX_SDK_HOME}/opensource/include/opencv4)
-include_directories(${MX_SDK_HOME}/opensource/include/gstreamer-1.0)
-include_directories(${MX_SDK_HOME}/opensource/include/glib-2.0)
-include_directories(${MX_SDK_HOME}/opensource/lib/glib-2.0/include)
-
-link_directories(${MX_SDK_HOME}/lib)
-link_directories(${MX_SDK_HOME}/opensource/lib)
-
-add_subdirectory(Proto)
-add_subdirectory(plugins/MpObjectSelection)
-add_subdirectory(plugins/MxpiFaceSelection)
-add_subdirectory(plugins/MxpiSkipFrame)
+cmake_minimum_required(VERSION 3.5.1)
+project(AllObjectsStructuring)
+
+add_definitions(-D_GLIBCXX_USE_CXX11_ABI=0)
+add_definitions(-Dgoogle=mindxsdk_private)
+set(CMAKE_CXX_STANDARD 11)
+set(PROJECT_DIR ${PROJECT_SOURCE_DIR})
+
+if(NOT DEFINED ENV{MX_SDK_HOME})
+    message(FATAL_ERROR "MX_SDK_HOME is not defined, please set it first.")
+else()
+    set(MX_SDK_HOME $ENV{MX_SDK_HOME})
+    message("MX_SDK_HOME=$ENV{MX_SDK_HOME}")
+endif()
+
+set(ENV{LD_LIBRARY_PATH} ${MX_SDK_HOME}/opensource/lib:$LD_LIBRARY_PATH)
+
+include_directories(${MX_SDK_HOME}/include)
+include_directories(${MX_SDK_HOME}/opensource/include)
+include_directories(${MX_SDK_HOME}/opensource/include/opencv4)
+include_directories(${MX_SDK_HOME}/opensource/include/gstreamer-1.0)
+include_directories(${MX_SDK_HOME}/opensource/include/glib-2.0)
+include_directories(${MX_SDK_HOME}/opensource/lib/glib-2.0/include)
+
+link_directories(${MX_SDK_HOME}/lib)
+link_directories(${MX_SDK_HOME}/opensource/lib)
+
+add_subdirectory(Proto)
+add_subdirectory(plugins/MpObjectSelection)
+add_subdirectory(plugins/MxpiFaceSelection)
+add_subdirectory(plugins/MxpiSkipFrame)
 add_subdirectory(plugins/MxpiFrameAlign)
\ No newline at end of file
diff --git a/mxVision/AllObjectsStructuring/Proto/CMakeLists.txt b/mxVision/mxVision-referenceapps/AllObjectsStructuring/Proto/CMakeLists.txt
similarity index 100%
rename from mxVision/AllObjectsStructuring/Proto/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/AllObjectsStructuring/Proto/CMakeLists.txt
diff --git a/mxVision/AllObjectsStructuring/Proto/MxpiAllObjectsStructuringDataType.proto b/mxVision/mxVision-referenceapps/AllObjectsStructuring/Proto/MxpiAllObjectsStructuringDataType.proto
similarity index 100%
rename from mxVision/AllObjectsStructuring/Proto/MxpiAllObjectsStructuringDataType.proto
rename to mxVision/mxVision-referenceapps/AllObjectsStructuring/Proto/MxpiAllObjectsStructuringDataType.proto
diff --git a/mxVision/AllObjectsStructuring/README.md b/mxVision/mxVision-referenceapps/AllObjectsStructuring/README.md
similarity index 100%
rename from mxVision/AllObjectsStructuring/README.md
rename to mxVision/mxVision-referenceapps/AllObjectsStructuring/README.md
diff --git a/mxVision/AllObjectsStructuring/build.sh b/mxVision/mxVision-referenceapps/AllObjectsStructuring/build.sh
similarity index 100%
rename from mxVision/AllObjectsStructuring/build.sh
rename to mxVision/mxVision-referenceapps/AllObjectsStructuring/build.sh
diff --git a/mxVision/AllObjectsStructuring/main.py b/mxVision/mxVision-referenceapps/AllObjectsStructuring/main.py
similarity index 100%
rename from mxVision/AllObjectsStructuring/main.py
rename to mxVision/mxVision-referenceapps/AllObjectsStructuring/main.py
diff --git a/mxVision/AllObjectsStructuring/main_pipeline/__init__.py b/mxVision/mxVision-referenceapps/AllObjectsStructuring/main_pipeline/__init__.py
similarity index 100%
rename from mxVision/AllObjectsStructuring/main_pipeline/__init__.py
rename to mxVision/mxVision-referenceapps/AllObjectsStructuring/main_pipeline/__init__.py
diff --git a/mxVision/AllObjectsStructuring/main_pipeline/main_pipeline.py b/mxVision/mxVision-referenceapps/AllObjectsStructuring/main_pipeline/main_pipeline.py
similarity index 100%
rename from mxVision/AllObjectsStructuring/main_pipeline/main_pipeline.py
rename to mxVision/mxVision-referenceapps/AllObjectsStructuring/main_pipeline/main_pipeline.py
diff --git a/mxVision/AllObjectsStructuring/pipeline/AllObjectsStructuring.pipeline b/mxVision/mxVision-referenceapps/AllObjectsStructuring/pipeline/AllObjectsStructuring.pipeline
similarity index 97%
rename from mxVision/AllObjectsStructuring/pipeline/AllObjectsStructuring.pipeline
rename to mxVision/mxVision-referenceapps/AllObjectsStructuring/pipeline/AllObjectsStructuring.pipeline
index b1f1785763b93b964f8d941d393aafa00d73abdb..5ddf2b3520b8e25a9d0e794c442e9257d8c78a7d 100644
--- a/mxVision/AllObjectsStructuring/pipeline/AllObjectsStructuring.pipeline
+++ b/mxVision/mxVision-referenceapps/AllObjectsStructuring/pipeline/AllObjectsStructuring.pipeline
@@ -1,1956 +1,1956 @@
-{
-    "detection":{
-        "stream_config":{
-            "deviceId":"1"
-        },
-        "mxpi_rtspsrc0":{
-            "factory":"mxpi_rtspsrc",
-            "props":{
-                "rtspUrl":"rtsp://xxx.xxx.xxx.xxx:xxxx/xxxx.264",
-                "channelId":"0"
-            },
-            "next":"mxpi_videodecoder0"
-        },
-        "mxpi_rtspsrc1":{
-            "factory":"mxpi_rtspsrc",
-            "props":{
-                "rtspUrl":"rtsp://xxx.xxx.xxx.xxx:xxxx/xxxx.264",
-                "channelId":"1"
-            },
-            "next":"mxpi_videodecoder1"
-        },
-        "mxpi_rtspsrc2":{
-            "factory":"mxpi_rtspsrc",
-            "props":{
-                "rtspUrl":"rtsp://xxx.xxx.xxx.xxx:xxxx/xxxx.264",
-                "channelId":"2"
-            },
-            "next":"mxpi_videodecoder2"
-        },
-        "mxpi_rtspsrc3":{
-            "factory":"mxpi_rtspsrc",
-            "props":{
-                "rtspUrl":"rtsp://xxx.xxx.xxx.xxx:xxxx/xxxx.264",
-                "channelId":"3"
-            },
-            "next":"mxpi_videodecoder3"
-        },
-        "mxpi_rtspsrc4":{
-            "factory":"mxpi_rtspsrc",
-            "props":{
-                "rtspUrl":"rtsp://xxx.xxx.xxx.xxx:xxxx/xxxx.264",
-                "channelId":"4"
-            },
-            "next":"mxpi_videodecoder4"
-        },
-        "mxpi_rtspsrc5":{
-            "factory":"mxpi_rtspsrc",
-            "props":{
-                "rtspUrl":"rtsp://xxx.xxx.xxx.xxx:xxxx/xxxx.264",
-                "channelId":"5"
-            },
-            "next":"mxpi_videodecoder5"
-        },
-        "mxpi_rtspsrc6":{
-            "factory":"mxpi_rtspsrc",
-            "props":{
-                "rtspUrl":"rtsp://xxx.xxx.xxx.xxx:xxxx/xxxx.264",
-                "channelId":"6"
-            },
-            "next":"mxpi_videodecoder6"
-        },
-        "mxpi_rtspsrc7":{
-            "factory":"mxpi_rtspsrc",
-            "props":{
-                "rtspUrl":"rtsp://xxx.xxx.xxx.xxx:xxxx/xxxx.264",
-                "channelId":"7"
-            },
-            "next":"mxpi_videodecoder7"
-        },
-        "mxpi_rtspsrc8":{
-            "factory":"mxpi_rtspsrc",
-            "props":{
-                "rtspUrl":"rtsp://xxx.xxx.xxx.xxx:xxxx/xxxx.264",
-                "channelId":"8"
-            },
-            "next":"mxpi_videodecoder8"
-        },
-        "mxpi_rtspsrc9":{
-            "factory":"mxpi_rtspsrc",
-            "props":{
-                "rtspUrl":"rtsp://xxx.xxx.xxx.xxx:xxxx/xxxx.264",
-                "channelId":"9"
-            },
-            "next":"mxpi_videodecoder9"
-        },
-        "mxpi_rtspsrc10":{
-            "factory":"mxpi_rtspsrc",
-            "props":{
-                "rtspUrl":"rtsp://xxx.xxx.xxx.xxx:xxxx/xxxx.264",
-                "channelId":"10"
-            },
-            "next":"mxpi_videodecoder10"
-        },
-        "mxpi_rtspsrc11":{
-            "factory":"mxpi_rtspsrc",
-            "props":{
-                "rtspUrl":"rtsp://xxx.xxx.xxx.xxx:xxxx/xxxx.264",
-                "channelId":"11"
-            },
-            "next":"mxpi_videodecoder11"
-        },
-        "mxpi_videodecoder0":{
-            "factory":"mxpi_videodecoder",
-            "props":{
-                "inputVideoFormat":"H264",
-                "outputImageFormat":"YUV420SP_NV12",
-                "vdecChannelId":"0"
-            },
-            "next":"mxpi_skipframe0"
-        },
-        "mxpi_skipframe0":{
-            "factory":"mxpi_skipframe",
-            "next":"mxpi_parallel2serial0:0",
-            "props":{
-                "frameNum":"2"
-            }
-        },
-        "mxpi_videodecoder1":{
-            "factory":"mxpi_videodecoder",
-            "props":{
-                "inputVideoFormat":"H264",
-                "outputImageFormat":"YUV420SP_NV12",
-                "vdecChannelId":"1"
-            },
-            "next":"mxpi_skipframe1"
-        },
-        "mxpi_skipframe1":{
-            "factory":"mxpi_skipframe",
-            "next":"mxpi_parallel2serial0:1",
-            "props":{
-                "frameNum":"2"
-            }
-        },
-        "mxpi_videodecoder2":{
-            "factory":"mxpi_videodecoder",
-            "props":{
-                "inputVideoFormat":"H264",
-                "outputImageFormat":"YUV420SP_NV12",
-                "vdecChannelId":"2"
-            },
-            "next":"mxpi_skipframe2"
-        },
-        "mxpi_skipframe2":{
-            "factory":"mxpi_skipframe",
-            "next":"mxpi_parallel2serial0:2",
-            "props":{
-                "frameNum":"2"
-            }
-        },
-        "mxpi_videodecoder3":{
-            "factory":"mxpi_videodecoder",
-            "props":{
-                "inputVideoFormat":"H264",
-                "outputImageFormat":"YUV420SP_NV12",
-                "vdecChannelId":"3"
-            },
-            "next":"mxpi_skipframe3"
-        },
-        "mxpi_skipframe3":{
-            "factory":"mxpi_skipframe",
-            "next":"mxpi_parallel2serial0:3",
-            "props":{
-                "frameNum":"2"
-            }
-        },
-        "mxpi_videodecoder4":{
-            "factory":"mxpi_videodecoder",
-            "props":{
-                "inputVideoFormat":"H264",
-                "outputImageFormat":"YUV420SP_NV12",
-                "vdecChannelId":"4"
-            },
-            "next":"mxpi_skipframe4"
-        },
-        "mxpi_skipframe4":{
-            "factory":"mxpi_skipframe",
-            "next":"mxpi_parallel2serial0:4",
-            "props":{
-                "frameNum":"2"
-            }
-        },
-        "mxpi_videodecoder5":{
-            "factory":"mxpi_videodecoder",
-            "props":{
-                "inputVideoFormat":"H264",
-                "outputImageFormat":"YUV420SP_NV12",
-                "vdecChannelId":"5"
-            },
-            "next":"mxpi_skipframe5"
-        },
-        "mxpi_skipframe5":{
-            "factory":"mxpi_skipframe",
-            "next":"mxpi_parallel2serial0:5",
-            "props":{
-                "frameNum":"2"
-            }
-        },
-        "mxpi_videodecoder6":{
-            "factory":"mxpi_videodecoder",
-            "props":{
-                "inputVideoFormat":"H264",
-                "outputImageFormat":"YUV420SP_NV12",
-                "vdecChannelId":"6"
-            },
-            "next":"mxpi_skipframe6"
-        },
-        "mxpi_skipframe6":{
-            "factory":"mxpi_skipframe",
-            "next":"mxpi_parallel2serial0:6",
-            "props":{
-                "frameNum":"2"
-            }
-        },
-        "mxpi_videodecoder7":{
-            "factory":"mxpi_videodecoder",
-            "props":{
-                "inputVideoFormat":"H264",
-                "outputImageFormat":"YUV420SP_NV12",
-                "vdecChannelId":"7"
-            },
-            "next":"mxpi_skipframe7"
-        },
-        "mxpi_skipframe7":{
-            "factory":"mxpi_skipframe",
-            "next":"mxpi_parallel2serial0:7",
-            "props":{
-                "frameNum":"2"
-            }
-        },
-        "mxpi_videodecoder8":{
-            "factory":"mxpi_videodecoder",
-            "props":{
-                "inputVideoFormat":"H264",
-                "outputImageFormat":"YUV420SP_NV12",
-                "vdecChannelId":"8"
-            },
-            "next":"mxpi_skipframe8"
-        },
-        "mxpi_skipframe8":{
-            "factory":"mxpi_skipframe",
-            "next":"mxpi_parallel2serial0:8",
-            "props":{
-                "frameNum":"2"
-            }
-        },
-        "mxpi_videodecoder9":{
-            "factory":"mxpi_videodecoder",
-            "props":{
-                "inputVideoFormat":"H264",
-                "outputImageFormat":"YUV420SP_NV12",
-                "vdecChannelId":"9"
-            },
-            "next":"mxpi_skipframe9"
-        },
-        "mxpi_skipframe9":{
-            "factory":"mxpi_skipframe",
-            "next":"mxpi_parallel2serial0:9",
-            "props":{
-                "frameNum":"2"
-            }
-        },
-        "mxpi_videodecoder10":{
-            "factory":"mxpi_videodecoder",
-            "props":{
-                "inputVideoFormat":"H264",
-                "outputImageFormat":"YUV420SP_NV12",
-                "vdecChannelId":"10"
-            },
-            "next":"mxpi_skipframe10"
-        },
-        "mxpi_skipframe10":{
-            "factory":"mxpi_skipframe",
-            "next":"mxpi_parallel2serial0:10",
-            "props":{
-                "frameNum":"2"
-            }
-        },
-        "mxpi_videodecoder11":{
-            "factory":"mxpi_videodecoder",
-            "props":{
-                "inputVideoFormat":"H264",
-                "outputImageFormat":"YUV420SP_NV12",
-                "vdecChannelId":"11"
-            },
-            "next":"mxpi_skipframe11"
-        },
-        "mxpi_skipframe11":{
-            "factory":"mxpi_skipframe",
-            "next":"mxpi_parallel2serial0:11",
-            "props":{
-                "frameNum":"2"
-            }
-        },
-        "mxpi_parallel2serial0":{
-            "factory":"mxpi_parallel2serial",
-            "props":{
-                "dataSource":"mxpi_videodecoder0,mxpi_videodecoder1,mxpi_videodecoder2,mxpi_videodecoder3,mxpi_videodecoder4,mxpi_videodecoder5,mxpi_videodecoder6,mxpi_videodecoder7,mxpi_videodecoder8,mxpi_videodecoder9,mxpi_videodecoder10,mxpi_videodecoder11"
-            },
-            "next":"mxpi_imageresize0"
-        },
-        "mxpi_imageresize0":{
-            "props":{
-                "dataSource":"mxpi_parallel2serial0",
-                "resizeHeight":"416",
-                "resizeWidth":"416"
-            },
-            "factory":"mxpi_imageresize",
-            "next":"queue0"
-        },
-        "queue0":{
-            "props":{
-                "max-size-buffers":"500"
-            },
-            "factory":"queue",
-            "next":"mxpi_modelinfer0"
-        },
-        "mxpi_modelinfer0":{
-            "props":{
-                "dataSource":"mxpi_imageresize0",
-                "modelPath":"./models/yolov4_improve/yolov4_detection.om",
-                "postProcessConfigPath":"./models/yolov4_improve/yolov4.cfg",
-                "labelPath":"./models/yolov4_improve/coco.names",
-                "postProcessLibPath":"libMpYOLOv3PostProcessor.so"
-            },
-            "factory":"mxpi_modelinfer",
-            "next":"mxpi_objectdistributor0"
-        },
-        "mxpi_objectdistributor0":{
-            "props":{
-                "classIds":"3,2|0",
-                "dataSource":"mxpi_modelinfer0"
-            },
-            "factory":"mxpi_distributor",
-            "next":["queue1","queue33"]
-        },
-        "queue1":{
-            "props":{
-                "max-size-buffers":"50"
-            },
-            "factory":"queue",
-            "next":"mxpi_imagecrop1"
-        },
-        "mxpi_imagecrop1":{
-            "props":{
-                "dataSource":"mxpi_objectdistributor0_0",
-                "resizeHeight":"96",
-                "resizeWidth":"96"
-            },
-            "factory":"mxpi_imagecrop",
-            "next":"mxpi_channeldistributor_pfm"
-        },
-        "mxpi_channeldistributor_pfm":{
-            "props":{
-                "channelIds":"0|1|2|3,4|5|6|7,8|9|10|11"
-            },
-            "factory":"mxpi_distributor",
-            "next":["queue_landmark0","queue_landmark1","queue_landmark2"]
-        },
-        "queue_landmark0":{
-            "props":{
-                "max-size-buffers":"50"
-            },
-            "factory":"queue",
-            "next":"mxpi_facelandmark0"
-        },
-        "mxpi_facelandmark0":{
-            "props":{
-                "dataSource":"mxpi_imagecrop1",
-                "modelPath":"./models/facequality/face_quality_improve.om",
-                "postProcessLibPath":"libfacelandmarkpostprocessor.so"
-            },
-            "factory":"mxpi_modelinfer",
-            "next":"mxpi_facelandmark:0"
-        },
-        "queue_landmark1":{
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-                "max-size-buffers":"50"
-            },
-            "factory":"queue",
-            "next":"mxpi_facelandmark1"
-        },
-        "mxpi_facelandmark1":{
-            "props":{
-                "dataSource":"mxpi_imagecrop1",
-                "modelPath":"./models/facequality/face_quality_improve.om",
-                "postProcessLibPath":"libfacelandmarkpostprocessor.so"
-            },
-            "factory":"mxpi_modelinfer",
-            "next":"mxpi_facelandmark:1"
-        },
-        "queue_landmark2":{
-            "props":{
-                "max-size-buffers":"50"
-            },
-            "factory":"queue",
-            "next":"mxpi_facelandmark2"
-        },
-        "mxpi_facelandmark2":{
-            "props":{
-                "dataSource":"mxpi_imagecrop1",
-                "modelPath":"./models/facequality/face_quality_improve.om",
-                "postProcessLibPath":"libfacelandmarkpostprocessor.so"
-            },
-            "factory":"mxpi_modelinfer",
-            "next":"mxpi_facelandmark:2"
-        },
-        "mxpi_facelandmark":{
-            "factory":"mxpi_parallel2serial",
-            "props":{
-                "dataSource":"mxpi_facelandmark0,mxpi_facelandmark1,mxpi_facelandmark2"
-            },
-            "next":"queue2"
-        },
-        "queue2":{
-            "props":{
-                "max-size-buffers":"50"
-            },
-            "factory":"queue",
-            "next":"mxpi_imagecrop0"
-        },
-        "mxpi_imagecrop0":{
-            "props":{
-                "dataSource":"mxpi_objectdistributor0_0",
-                "resizeHeight":"96",
-                "resizeWidth":"64"
-            },
-            "factory":"mxpi_imagecrop",
-            "next":"mxpi_channeldistributor_pfm2"
-        },
-        "mxpi_channeldistributor_pfm2":{
-            "props":{
-                "channelIds":"0|1|2|3|4|5,6|7|8|9|10|11"
-            },
-            "factory":"mxpi_distributor",
-            "next":["queue_embedding0","queue_embedding1"]
-        },
-        "queue_embedding0":{
-            "props":{
-                "max-size-buffers":"50"
-            },
-            "factory":"queue",
-            "next":"mxpi_FaceFeatureModelInfer0"
-        },
-        "mxpi_FaceFeatureModelInfer0":{
-            "props":{
-                "dataSource":"mxpi_imagecrop0",
-                "modelPath":"./models/faceembedding/face_embedding.om",
-                "postProcessConfigPath":"./models/facefeature/yolov3-tiny-addpad.cfg",
-                "postProcessLibPath":"libresnetfeaturepostprocessor.so"
-            },
-            "factory":"mxpi_modelinfer",
-            "next":"mxpi_FaceFeatureModelInfer:0"
-        },
-        "queue_embedding1":{
-            "props":{
-                "max-size-buffers":"50"
-            },
-            "factory":"queue",
-            "next":"mxpi_FaceFeatureModelInfer1"
-        },
-        "mxpi_FaceFeatureModelInfer1":{
-            "props":{
-                "dataSource":"mxpi_imagecrop0",
-                "modelPath":"./models/faceembedding/face_embedding.om",
-                "postProcessConfigPath":"./models/facefeature/yolov3-tiny-addpad.cfg",
-                "postProcessLibPath":"libresnetfeaturepostprocessor.so"
-            },
-            "factory":"mxpi_modelinfer",
-            "next":"mxpi_FaceFeatureModelInfer:1"
-        },
-        "mxpi_FaceFeatureModelInfer":{
-            "factory":"mxpi_parallel2serial",
-            "props":{
-                "dataSource":"mxpi_FaceFeatureModelInfer0,mxpi_FaceFeatureModelInfer1"
-            },
-            "next":"queue_test"
-        },
-        "queue_test":{
-            "props":{
-                "max-size-buffers":"100"
-            },
-            "factory":"queue",
-            "next":"mxpi_channeldistributor0"
-        },
-        "mxpi_channeldistributor0":{
-            "props":{
-                "channelIds":"0,1,2,3,4,5,6,7,8,9,10,11"
-            },
-            "factory":"mxpi_distributor",
-            "next":["mxpi_motsimplesort_face0","mxpi_motsimplesort_face1","mxpi_motsimplesort_face2","mxpi_motsimplesort_face3","mxpi_motsimplesort_face4","mxpi_motsimplesort_face5","mxpi_motsimplesort_face6","mxpi_motsimplesort_face7","mxpi_motsimplesort_face8","mxpi_motsimplesort_face9","mxpi_motsimplesort_face10","mxpi_motsimplesort_face11"]
-        },
-        "mxpi_motsimplesort_face0": {
-            "props": {
-                "dataSourceDetection": "mxpi_objectdistributor0_0",
-                "dataSourceFeature":"mxpi_FaceFeatureModelInfer"
-            },
-            "factory": "mxpi_motsimplesort",
-            "next": "queue_sel_0"
-        },
-        "queue_sel_0":{
-            "props":{
-                "max-size-buffers":"50"
-            },
-            "factory":"queue",
-            "next":"mxpi_faceselection0"
-        },
-        "mxpi_faceselection0":{
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-                "status":"1",
-                "dataSourceDetection":"mxpi_motsimplesort_face0",
-                "dataSourceKeyPoint":"mxpi_facelandmark",
-                "minScoreThreshold":"0"
-            },
-            "factory":"mxpi_faceselection",
-            "next":[
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-                "queue_crop_0"
-            ]
-        },
-        "queue_mux_0":{
-            "props":{
-                "max-size-buffers":"50"
-            },
-            "factory":"queue",
-            "next":"mxpi_parallel2serial1:0"
-        },
-        "queue_crop_0":{
-            "props":{
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-            },
-            "factory":"queue",
-            "next":"mxpi_imagecrop2"
-        },
-        "mxpi_imagecrop2":{
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-                "dataSource":"mxpi_faceselection0_0",
-                "leftExpandRatio":"0.1",
-                "rightExpandRatio":"0.1",
-                "upExpandRatio":"0.1",
-                "downExpandRatio":"0.1",
-                "resizeHeight":"112",
-                "resizeWidth":"112"
-            },
-            "factory":"mxpi_imagecrop",
-            "next":"mxpi_parallel2serial2:0"
-        },
-        "mxpi_motsimplesort_face1": {
-            "props": {
-                "dataSourceDetection": "mxpi_objectdistributor0_0",
-                "dataSourceFeature":"mxpi_FaceFeatureModelInfer"
-            },
-            "factory": "mxpi_motsimplesort",
-            "next": "queue_sel_1"
-        },
-        "queue_sel_1":{
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-            },
-            "factory":"queue",
-            "next":"mxpi_faceselection1"
-        },
-        "mxpi_faceselection1":{
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-                "dataSourceDetection":"mxpi_motsimplesort_face1",
-                "dataSourceKeyPoint":"mxpi_facelandmark",
-                "minScoreThreshold":"0"
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-                "queue_crop_1"
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-        },
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-            },
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-        },
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-            },
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-            "next":"mxpi_imagecrop3"
-        },
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-                "leftExpandRatio":"0.1",
-                "rightExpandRatio":"0.1",
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-                "downExpandRatio":"0.1",
-                "resizeHeight":"112",
-                "resizeWidth":"112"
-            },
-            "factory":"mxpi_imagecrop",
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-        },
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-                "dataSourceFeature":"mxpi_FaceFeatureModelInfer"
-            },
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-        },
-        "queue_sel_2":{
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-            },
-            "factory":"queue",
-            "next":"mxpi_faceselection2"
-        },
-        "mxpi_faceselection2":{
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-                "dataSourceDetection":"mxpi_motsimplesort_face2",
-                "dataSourceKeyPoint":"mxpi_facelandmark",
-                "minScoreThreshold":"0"
-            },
-            "factory":"mxpi_faceselection",
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-                "queue_crop_2"
-            ]
-        },
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-            },
-            "factory":"queue",
-            "next":"mxpi_parallel2serial1:2"
-        },
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-            },
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-            "next":"mxpi_imagecrop4"
-        },
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-                "leftExpandRatio":"0.1",
-                "rightExpandRatio":"0.1",
-                "upExpandRatio":"0.1",
-                "downExpandRatio":"0.1",
-                "resizeHeight":"112",
-                "resizeWidth":"112"
-            },
-            "factory":"mxpi_imagecrop",
-            "next":"mxpi_parallel2serial2:2"
-        },
-        "mxpi_motsimplesort_face3": {
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-                "dataSourceDetection": "mxpi_objectdistributor0_0",
-                "dataSourceFeature":"mxpi_FaceFeatureModelInfer"
-            },
-            "factory": "mxpi_motsimplesort",
-            "next": "queue_sel_3"
-        },
-        "queue_sel_3":{
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-            },
-            "factory":"queue",
-            "next":"mxpi_faceselection3"
-        },
-        "mxpi_faceselection3":{
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-                "dataSourceDetection":"mxpi_motsimplesort_face3",
-                "dataSourceKeyPoint":"mxpi_facelandmark",
-                "minScoreThreshold":"0"
-            },
-            "factory":"mxpi_faceselection",
-            "next":[
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-                "queue_crop_3"
-            ]
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-            },
-            "factory":"queue",
-            "next":"mxpi_parallel2serial1:3"
-        },
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-            },
-            "factory":"queue",
-            "next":"mxpi_imagecrop5"
-        },
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-                "leftExpandRatio":"0.1",
-                "rightExpandRatio":"0.1",
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-                "downExpandRatio":"0.1",
-                "resizeHeight":"112",
-                "resizeWidth":"112"
-            },
-            "factory":"mxpi_imagecrop",
-            "next":"mxpi_parallel2serial2:3"
-        },
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-                "dataSourceFeature":"mxpi_FaceFeatureModelInfer"
-            },
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-            "next": "queue_sel_4"
-        },
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-            },
-            "factory":"queue",
-            "next":"mxpi_faceselection4"
-        },
-        "mxpi_faceselection4":{
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-                "dataSourceDetection":"mxpi_motsimplesort_face4",
-                "dataSourceKeyPoint":"mxpi_facelandmark",
-                "minScoreThreshold":"0"
-            },
-            "factory":"mxpi_faceselection",
-            "next":[
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-                "queue_crop_4"
-            ]
-        },
-        "queue_mux_4":{
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-            },
-            "factory":"queue",
-            "next":"mxpi_parallel2serial1:4"
-        },
-        "queue_crop_4":{
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-            },
-            "factory":"queue",
-            "next":"mxpi_imagecrop6"
-        },
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-                "dataSource":"mxpi_faceselection4_0",
-                "leftExpandRatio":"0.1",
-                "rightExpandRatio":"0.1",
-                "upExpandRatio":"0.1",
-                "downExpandRatio":"0.1",
-                "resizeHeight":"112",
-                "resizeWidth":"112"
-            },
-            "factory":"mxpi_imagecrop",
-            "next":"mxpi_parallel2serial2:4"
-        },
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-                "dataSourceFeature":"mxpi_FaceFeatureModelInfer"
-            },
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-            "next": "queue_sel_5"
-        },
-        "queue_sel_5":{
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-            },
-            "factory":"queue",
-            "next":"mxpi_faceselection5"
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-                "dataSourceDetection":"mxpi_motsimplesort_face5",
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-            },
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-            },
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-            "next":"mxpi_imagecrop7"
-        },
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-                "resizeWidth":"112"
-            },
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-            "next":"mxpi_parallel2serial2:5"
-        },
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-                "dataSourceFeature":"mxpi_FaceFeatureModelInfer"
-            },
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-            "next": "queue_sel_6"
-        },
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-            },
-            "factory":"queue",
-            "next":"mxpi_faceselection6"
-        },
-        "mxpi_faceselection6":{
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-                "dataSourceDetection":"mxpi_motsimplesort_face6",
-                "dataSourceKeyPoint":"mxpi_facelandmark",
-                "minScoreThreshold":"0"
-            },
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-                "queue_crop_6"
-            ]
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-            },
-            "factory":"queue",
-            "next":"mxpi_parallel2serial1:6"
-        },
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-            },
-            "factory":"queue",
-            "next":"mxpi_imagecrop_6"
-        },
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-                "dataSource":"mxpi_faceselection6_0",
-                "leftExpandRatio":"0.1",
-                "rightExpandRatio":"0.1",
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-                "resizeHeight":"112",
-                "resizeWidth":"112"
-            },
-            "factory":"mxpi_imagecrop",
-            "next":"mxpi_parallel2serial2:6"
-        },
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-                "dataSourceDetection": "mxpi_objectdistributor0_0",
-                "dataSourceFeature":"mxpi_FaceFeatureModelInfer"
-            },
-            "factory": "mxpi_motsimplesort",
-            "next": "queue_sel_7"
-        },
-        "queue_sel_7":{
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-            },
-            "factory":"queue",
-            "next":"mxpi_faceselection7"
-        },
-        "mxpi_faceselection7":{
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-                "dataSourceDetection":"mxpi_motsimplesort_face7",
-                "dataSourceKeyPoint":"mxpi_facelandmark",
-                "minScoreThreshold":"0"
-            },
-            "factory":"mxpi_faceselection",
-            "next":[
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-                "queue_crop_7"
-            ]
-        },
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-            },
-            "factory":"queue",
-            "next":"mxpi_parallel2serial1:7"
-        },
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-            },
-            "factory":"queue",
-            "next":"mxpi_imagecrop_7"
-        },
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-                "leftExpandRatio":"0.1",
-                "rightExpandRatio":"0.1",
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-                "downExpandRatio":"0.1",
-                "resizeHeight":"112",
-                "resizeWidth":"112"
-            },
-            "factory":"mxpi_imagecrop",
-            "next":"mxpi_parallel2serial2:7"
-        },
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-                "dataSourceFeature":"mxpi_FaceFeatureModelInfer"
-            },
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-            "next": "queue_sel_8"
-        },
-        "queue_sel_8":{
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-            },
-            "factory":"queue",
-            "next":"mxpi_faceselection8"
-        },
-        "mxpi_faceselection8":{
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-                "dataSourceDetection":"mxpi_motsimplesort_face8",
-                "dataSourceKeyPoint":"mxpi_facelandmark",
-                "minScoreThreshold":"0"
-            },
-            "factory":"mxpi_faceselection",
-            "next":[
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-                "queue_crop_8"
-            ]
-        },
-        "queue_mux_8":{
-            "props":{
-                "max-size-buffers":"50"
-            },
-            "factory":"queue",
-            "next":"mxpi_parallel2serial1:8"
-        },
-        "queue_crop_8":{
-            "props":{
-                "max-size-buffers":"50"
-            },
-            "factory":"queue",
-            "next":"mxpi_imagecrop_8"
-        },
-        "mxpi_imagecrop_8":{
-            "props":{
-                "dataSource":"mxpi_faceselection8_0",
-                "leftExpandRatio":"0.1",
-                "rightExpandRatio":"0.1",
-                "upExpandRatio":"0.1",
-                "downExpandRatio":"0.1",
-                "resizeHeight":"112",
-                "resizeWidth":"112"
-            },
-            "factory":"mxpi_imagecrop",
-            "next":"mxpi_parallel2serial2:8"
-        },
-        "mxpi_motsimplesort_face9": {
-            "props": {
-                "dataSourceDetection": "mxpi_objectdistributor0_0",
-                "dataSourceFeature":"mxpi_FaceFeatureModelInfer"
-            },
-            "factory": "mxpi_motsimplesort",
-            "next": "queue_sel_9"
-        },
-        "queue_sel_9":{
-            "props":{
-                "max-size-buffers":"50"
-            },
-            "factory":"queue",
-            "next":"mxpi_faceselection9"
-        },
-        "mxpi_faceselection9":{
-            "props":{
-                "status":"1",
-                "dataSourceDetection":"mxpi_motsimplesort_face9",
-                "dataSourceKeyPoint":"mxpi_facelandmark",
-                "minScoreThreshold":"0"
-            },
-            "factory":"mxpi_faceselection",
-            "next":[
-                "queue_mux_9",
-                "queue_crop_9"
-            ]
-        },
-        "queue_mux_9":{
-            "props":{
-                "max-size-buffers":"50"
-            },
-            "factory":"queue",
-            "next":"mxpi_parallel2serial1:9"
-        },
-        "queue_crop_9":{
-            "props":{
-                "max-size-buffers":"50"
-            },
-            "factory":"queue",
-            "next":"mxpi_imagecrop_9"
-        },
-        "mxpi_imagecrop_9":{
-            "props":{
-                "dataSource":"mxpi_faceselection9_0",
-                "leftExpandRatio":"0.1",
-                "rightExpandRatio":"0.1",
-                "upExpandRatio":"0.1",
-                "downExpandRatio":"0.1",
-                "resizeHeight":"112",
-                "resizeWidth":"112"
-            },
-            "factory":"mxpi_imagecrop",
-            "next":"mxpi_parallel2serial2:9"
-        },
-        "mxpi_motsimplesort_face10": {
-            "props": {
-                "dataSourceDetection": "mxpi_objectdistributor0_0",
-                "dataSourceFeature":"mxpi_FaceFeatureModelInfer"
-            },
-            "factory": "mxpi_motsimplesort",
-            "next": "queue_sel_10"
-        },
-        "queue_sel_10":{
-            "props":{
-                "max-size-buffers":"50"
-            },
-            "factory":"queue",
-            "next":"mxpi_faceselection10"
-        },
-        "mxpi_faceselection10":{
-            "props":{
-                "status":"1",
-                "dataSourceDetection":"mxpi_motsimplesort_face10",
-                "dataSourceKeyPoint":"mxpi_facelandmark",
-                "minScoreThreshold":"0"
-            },
-            "factory":"mxpi_faceselection",
-            "next":[
-                "queue_mux_10",
-                "queue_crop_10"
-            ]
-        },
-        "queue_mux_10":{
-            "props":{
-                "max-size-buffers":"50"
-            },
-            "factory":"queue",
-            "next":"mxpi_parallel2serial1:10"
-        },
-        "queue_crop_10":{
-            "props":{
-                "max-size-buffers":"50"
-            },
-            "factory":"queue",
-            "next":"mxpi_imagecrop_10"
-        },
-        "mxpi_imagecrop_10":{
-            "props":{
-                "dataSource":"mxpi_faceselection10_0",
-                "leftExpandRatio":"0.1",
-                "rightExpandRatio":"0.1",
-                "upExpandRatio":"0.1",
-                "downExpandRatio":"0.1",
-                "resizeHeight":"112",
-                "resizeWidth":"112"
-            },
-            "factory":"mxpi_imagecrop",
-            "next":"mxpi_parallel2serial2:10"
-        },
-        "mxpi_motsimplesort_face11": {
-            "props": {
-                "dataSourceDetection": "mxpi_objectdistributor0_0",
-                "dataSourceFeature":"mxpi_FaceFeatureModelInfer"
-            },
-            "factory": "mxpi_motsimplesort",
-            "next": "queue_sel_11"
-        },
-        "queue_sel_11":{
-            "props":{
-                "max-size-buffers":"50"
-            },
-            "factory":"queue",
-            "next":"mxpi_faceselection11"
-        },
-        "mxpi_faceselection11":{
-            "props":{
-                "status":"1",
-                "dataSourceDetection":"mxpi_motsimplesort_face11",
-                "dataSourceKeyPoint":"mxpi_facelandmark",
-                "minScoreThreshold":"0"
-            },
-            "factory":"mxpi_faceselection",
-            "next":[
-                "queue_mux_11",
-                "queue_crop_11"
-            ]
-        },
-        "queue_mux_11":{
-            "props":{
-                "max-size-buffers":"50"
-            },
-            "factory":"queue",
-            "next":"mxpi_parallel2serial1:11"
-        },
-        "queue_crop_11":{
-            "props":{
-                "max-size-buffers":"50"
-            },
-            "factory":"queue",
-            "next":"mxpi_imagecrop_11"
-        },
-        "mxpi_imagecrop_11":{
-            "props":{
-                "dataSource":"mxpi_faceselection11_0",
-                "leftExpandRatio":"0.1",
-                "rightExpandRatio":"0.1",
-                "upExpandRatio":"0.1",
-                "downExpandRatio":"0.1",
-                "resizeHeight":"112",
-                "resizeWidth":"112"
-            },
-            "factory":"mxpi_imagecrop",
-            "next":"mxpi_parallel2serial2:11"
-        },
-        "mxpi_parallel2serial1":{
-            "factory":"mxpi_parallel2serial",
-            "props":{
-                "dataSource":"mxpi_faceselection0_1,mxpi_faceselection1_1,mxpi_faceselection2_1,mxpi_faceselection3_1,mxpi_faceselection4_1,mxpi_faceselection5_1,mxpi_faceselection6_1,mxpi_faceselection7_1,mxpi_faceselection8_1,mxpi_faceselection9_1,mxpi_faceselection10_1,mxpi_faceselection11_1"
-            },
-            "next":"mxpi_facealignment0:1"
-        },
-        "mxpi_parallel2serial2":{
-            "factory":"mxpi_parallel2serial",
-            "props":{
-                "dataSource":"mxpi_imagecrop2,mxpi_imagecrop3,mxpi_imagecrop4,mxpi_imagecrop5,mxpi_imagecrop6,mxpi_imagecrop7,mxpi_imagecrop_6,mxpi_imagecrop_7,mxpi_imagecrop_8,mxpi_imagecrop_9,mxpi_imagecrop_10,mxpi_imagecrop_11"
-            },
-            "next":"mxpi_facealignment0:0"
-        },
-        "mxpi_facealignment0":{
-            "props":{
-                "status":"1",
-                "dataSourceImage":"mxpi_parallel2serial2",
-                "dataSourceKeyPoint":"mxpi_parallel2serial1",
-                "afterFaceAlignmentHeight":"112",
-                "afterFaceAlignmentWidth":"112"
-            },
-            "factory":"mxpi_facealignment",
-            "next":"tee3"
-        },
-        "tee3":{
-            "factory":"tee",
-            "next":[
-                "queue7",
-                "queue19"
-            ]
-        },
-        "queue7":{
-            "props":{
-                "max-size-buffers":"50"
-            },
-            "factory":"queue",
-            "next":"face_attribute"
-        },
-        "face_attribute":{
-            "props":{
-                "dataSource":"mxpi_facealignment0",
-                "modelPath":"./models/faceattr/face_attribute_batch_4.om",
-                "postProcessConfigPath":"./models/faceattr/yolov3-tiny-addpad.cfg",
-                "labelPath":"./models/faceattr/coco.names",
-                "postProcessLibPath":"libresnetattrpostprocessor.so"
-            },
-            "factory":"mxpi_modelinfer",
-            "next":"mxpi_synchronize0:0"
-        },
-        "queue19":{
-            "props":{
-                "max-size-buffers":"50"
-            },
-            "factory":"queue",
-            "next":"face_feature"
-        },
-        "face_feature":{
-            "props":{
-                "dataSource":"mxpi_facealignment0",
-                "modelPath":"./models/facefeature/face_feature_batch_1.om",
-                "postProcessConfigPath":"./models/facefeature/yolov3-tiny-addpad.cfg",
-                "postProcessLibPath":"libresnetfeaturepostprocessor.so"
-            },
-            "factory":"mxpi_modelinfer",
-            "next":"mxpi_synchronize0:1"
-        },
-        "mxpi_synchronize0":{
-            "factory":"mxpi_synchronize",
-            "next":"mxpi_dataserialize0"
-        },
-        "mxpi_dataserialize0":{
-            "props":{
-                "outputDataKeys":"ReservedFrameInfo,face_attribute,face_feature"
-            },
-            "factory":"mxpi_dataserialize",
-            "next":"mxpi_parallel2serial3:0"
-        },
-        "queue33":{
-            "props":{
-                "max-size-buffers":"50"
-            },
-            "factory":"queue",
-            "next":"mxpi_imagecrop8"
-        },
-        "mxpi_imagecrop8":{
-            "props":{
-                "dataSource":"mxpi_objectdistributor0_1",
-                "resizeHeight":"224",
-                "resizeWidth":"224",
-                "leftExpandRatio":"0.1",
-                "rightExpandRatio":"0.1",
-                "upExpandRatio":"0.1",
-                "downExpandRatio":"0.1"
-            },
-            "factory":"mxpi_imagecrop",
-            "next":"mxpi_channeldistributor1"
-        },
-        "mxpi_channeldistributor1":{
-            "props":{
-                "channelIds":"0,1,2,3,4,5,6,7,8,9,10,11"
-            },
-            "factory":"mxpi_distributor",
-            "next":["queue_mot_obj0","queue_mot_obj1","queue_mot_obj2","queue_mot_obj3","queue_mot_obj4","queue_mot_obj5","queue_mot_obj6","queue_mot_obj7","queue_mot_obj8","queue_mot_obj9","queue_mot_obj10","queue_mot_obj11"]
-        },
-        "queue_mot_obj0":{
-            "props":{
-                "max-size-buffers":"50"
-            },
-            "factory":"queue",
-            "next":"mxpi_motsimplesort_obj0"
-        },
-        "mxpi_motsimplesort_obj0": {
-                "props": {
-                    "dataSourceDetection": "mxpi_objectdistributor0_1"
-                },
-                "factory": "mxpi_motsimplesort",
-                "next": "queue_ob_0"
-        },
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-            "props":{
-                "max-size-buffers":"50"
-            },
-            "factory":"queue",
-            "next":"mxpi_objectselection0:0"
-        },
-        "mxpi_objectselection0":{
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-                "status":"1",
-                "dataSourceDetection":"mxpi_motsimplesort_obj0",
-                "dataSourceImage":"mxpi_imagecrop8",
-                "tmarginValue":"0.1",
-                "weightMargin":"0.2",
-                "weightOcclude":"0.11",
-                "weightSize":"0.21",
-                "weightConf":"0.31",
-                "trackTime":"0",
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-                "outputKeys":"vision,object"
-            },
-            "factory":"mxpi_objectselection",
-            "next":"mxpi_parallel2serial4:0"
-        },
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-            },
-            "factory":"queue",
-            "next":"mxpi_motsimplesort_obj1"
-        },
-        "mxpi_motsimplesort_obj1": {
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-                "factory": "mxpi_motsimplesort",
-                "next": "queue_ob_1"
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-            },
-            "factory":"queue",
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-        },
-        "mxpi_objectselection1":{
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-                "dataSourceDetection":"mxpi_motsimplesort_obj1",
-                "dataSourceImage":"mxpi_imagecrop8",
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-                "weightOcclude":"0.11",
-                "weightSize":"0.21",
-                "weightConf":"0.31",
-                "trackTime":"0",
-                "normRadius":"0.1 ,0.2, 0.3,0.4,0. 5,0.6,0.7, 0.8,0.9,0.8,0 .7,0.6,0.5,0.4,0.3,0.2,0.1",
-                "outputKeys":"vision,object"
-            },
-            "factory":"mxpi_objectselection",
-            "next":"mxpi_parallel2serial4:1"
-        },
-        "queue_mot_obj2":{
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-            },
-            "factory":"queue",
-            "next":"mxpi_motsimplesort_obj2"
-        },
-        "mxpi_motsimplesort_obj2": {
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-                "factory": "mxpi_motsimplesort",
-                "next": "queue_ob_2"
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-            },
-            "factory":"queue",
-            "next":"mxpi_objectselection2:0"
-        },
-        "mxpi_objectselection2":{
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-                "dataSourceDetection":"mxpi_motsimplesort_obj2",
-                "dataSourceImage":"mxpi_imagecrop8",
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-                "weightOcclude":"0.11",
-                "weightSize":"0.21",
-                "weightConf":"0.31",
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-                "outputKeys":"vision,object"
-            },
-            "factory":"mxpi_objectselection",
-            "next":"mxpi_parallel2serial4:2"
-        },
-        "queue_mot_obj3":{
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-            },
-            "factory":"queue",
-            "next":"mxpi_motsimplesort_obj3"
-        },
-        "mxpi_motsimplesort_obj3": {
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-                },
-                "factory": "mxpi_motsimplesort",
-                "next": "queue_ob_3"
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-            },
-            "factory":"queue",
-            "next":"mxpi_objectselection3:0"
-        },
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-                "dataSourceDetection":"mxpi_motsimplesort_obj3",
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-            "next":"mxpi_parallel2serial4:3"
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-            },
-            "factory":"queue",
-            "next":"mxpi_motsimplesort_obj4"
-        },
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-                "factory": "mxpi_motsimplesort",
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-            "next":"mxpi_parallel2serial4:4"
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-            },
-            "factory":"queue",
-            "next":"mxpi_motsimplesort_obj5"
-        },
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-                "factory": "mxpi_motsimplesort",
-                "next": "queue_ob_5"
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-        },
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-            "factory":"mxpi_objectselection",
-            "next":"mxpi_parallel2serial4:5"
-        },
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-            },
-            "factory":"queue",
-            "next":"mxpi_motsimplesort_obj6"
-        },
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-                "factory": "mxpi_motsimplesort",
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-        },
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-            },
-            "factory":"mxpi_objectselection",
-            "next":"mxpi_parallel2serial4:6"
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-            },
-            "factory":"queue",
-            "next":"mxpi_motsimplesort_obj7"
-        },
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-                },
-                "factory": "mxpi_motsimplesort",
-                "next": "queue_ob_7"
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-        },
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-                "dataSourceDetection":"mxpi_motsimplesort_obj7",
-                "dataSourceImage":"mxpi_imagecrop8",
-                "tmarginValue":"0.1",
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-            },
-            "factory":"mxpi_objectselection",
-            "next":"mxpi_parallel2serial4:7"
-        },
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-            },
-            "factory":"queue",
-            "next":"mxpi_motsimplesort_obj8"
-        },
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-                },
-                "factory": "mxpi_motsimplesort",
-                "next": "queue_ob_8"
-        },
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-            },
-            "factory":"queue",
-            "next":"mxpi_objectselection8:0"
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-                "tmarginValue":"0.1",
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-            },
-            "factory":"mxpi_objectselection",
-            "next":"mxpi_parallel2serial4:8"
-        },
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-            },
-            "factory":"queue",
-            "next":"mxpi_motsimplesort_obj9"
-        },
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-                },
-                "factory": "mxpi_motsimplesort",
-                "next": "queue_ob_9"
-        },
-        "queue_ob_9":{
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-            },
-            "factory":"queue",
-            "next":"mxpi_objectselection9:0"
-        },
-        "mxpi_objectselection9":{
-            "props":{
-                "status":"1",
-                "dataSourceDetection":"mxpi_motsimplesort_obj9",
-                "dataSourceImage":"mxpi_imagecrop8",
-                "tmarginValue":"0.1",
-                "weightMargin":"0.2",
-                "weightOcclude":"0.11",
-                "weightSize":"0.21",
-                "weightConf":"0.31",
-                "trackTime":"0",
-                "normRadius":"0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,0.8,0.7,0.6,0.5,0.4,0.3,0.2,0.1",
-                "outputKeys":"vision,object"
-            },
-            "factory":"mxpi_objectselection",
-            "next":"mxpi_parallel2serial4:9"
-        },
-        "queue_mot_obj10":{
-            "props":{
-                "max-size-buffers":"50"
-            },
-            "factory":"queue",
-            "next":"mxpi_motsimplesort_obj10"
-        },
-        "mxpi_motsimplesort_obj10": {
-                "props": {
-                    "dataSourceDetection": "mxpi_objectdistributor0_1"
-                },
-                "factory": "mxpi_motsimplesort",
-                "next": "queue_ob_10"
-        },
-        "queue_ob_10":{
-            "props":{
-                "max-size-buffers":"50"
-            },
-            "factory":"queue",
-            "next":"mxpi_objectselection10:0"
-        },
-        "mxpi_objectselection10":{
-            "props":{
-                "status":"1",
-                "dataSourceDetection":"mxpi_motsimplesort_obj10",
-                "dataSourceImage":"mxpi_imagecrop8",
-                "tmarginValue":"0.1",
-                "weightMargin":"0.2",
-                "weightOcclude":"0.11",
-                "weightSize":"0.21",
-                "weightConf":"0.31",
-                "trackTime":"0",
-                "normRadius":"0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,0.8,0.7,0.6,0.5,0.4,0.3,0.2,0.1",
-                "outputKeys":"vision,object"
-            },
-            "factory":"mxpi_objectselection",
-            "next":"mxpi_parallel2serial4:10"
-        },
-        "queue_mot_obj11":{
-            "props":{
-                "max-size-buffers":"50"
-            },
-            "factory":"queue",
-            "next":"mxpi_motsimplesort_obj11"
-        },
-        "mxpi_motsimplesort_obj11": {
-                "props": {
-                    "dataSourceDetection": "mxpi_objectdistributor0_1"
-                },
-                "factory": "mxpi_motsimplesort",
-                "next": "queue_ob_11"
-        },
-        "queue_ob_11":{
-            "props":{
-                "max-size-buffers":"50"
-            },
-            "factory":"queue",
-            "next":"mxpi_objectselection11:0"
-        },
-        "mxpi_objectselection11":{
-            "props":{
-                "status":"1",
-                "dataSourceDetection":"mxpi_motsimplesort_obj11",
-                "dataSourceImage":"mxpi_imagecrop8",
-                "tmarginValue":"0.1",
-                "weightMargin":"0.2",
-                "weightOcclude":"0.11",
-                "weightSize":"0.21",
-                "weightConf":"0.31",
-                "trackTime":"0",
-                "normRadius":"0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,0.8,0.7,0.6,0.5,0.4,0.3,0.2,0.1",
-                "outputKeys":"vision,object"
-            },
-            "factory":"mxpi_objectselection",
-            "next":"mxpi_parallel2serial4:11"
-        },
-        "mxpi_parallel2serial4":{
-            "factory":"mxpi_parallel2serial",
-            "next":"mxpi_objectdistributor1"
-        },
-        "mxpi_objectdistributor1":{
-            "props":{
-                "classIds":"2,0",
-                "dataSource":"object"
-            },
-            "factory":"mxpi_distributor",
-            "next":[
-                "queue12",
-                "queue13"
-            ]
-        },
-        "queue12":{
-            "props":{
-                "max-size-buffers":"50"
-            },
-            "factory":"queue",
-            "next":"tee4"
-        },
-        "tee4":{
-            "factory":"tee",
-            "next":[
-                "queue20",
-                "queue21"
-            ]
-        },
-        "queue20":{
-            "props":{
-                "max-size-buffers":"50"
-            },
-            "factory":"queue",
-            "next":"mxpi_imageresize3"
-        },
-        "mxpi_imageresize3":{
-            "props":{
-                "dataSource":"vision",
-                "resizeHeight":"224",
-                "resizeWidth":"224"
-            },
-            "factory":"mxpi_imageresize",
-            "next":"queue14"
-        },
-        "queue14":{
-            "props":{
-                "max-size-buffers":"50"
-            },
-            "factory":"queue",
-            "next":"motor_attr"
-        },
-        "motor_attr":{
-            "props":{
-                "dataSource":"mxpi_imageresize3",
-                "modelPath":"./models/motorattr/vehicle_attribute.om",
-                "postProcessConfigPath":"./models/motorattr/yolov3-tiny-addpad.cfg",
-                "labelPath":"./models/motorattr/coco.names",
-                "postProcessLibPath":"libresnetattrpostprocessor.so"
-            },
-            "factory":"mxpi_modelinfer",
-            "next":"mxpi_synchronize2:0"
-        },
-        "queue21":{
-            "props":{
-                "max-size-buffers":"50"
-            },
-            "factory":"queue",
-            "next":"mxpi_imageresize6"
-        },
-        "mxpi_imageresize6":{
-            "props":{
-                "dataSource":"vision",
-                "resizeHeight": "640",
-                "resizeWidth": "480"
-            },
-            "factory":"mxpi_imageresize",
-            "next":"queue22"
-        },
-        "queue22":{
-            "props":{
-                "max-size-buffers":"50"
-            },
-            "factory":"queue",
-            "next":"mxpi_modelinfer4"
-        },
-        "mxpi_modelinfer4": {
-            "props": {
-                "parentName": "mxpi_imageresize6",
-                "modelPath": "./models/car_plate_detection/car_plate_detection.om",
-                "postProcessConfigPath": "./models/car_plate_detection/ssd_vgg16_caffe_glue_hole.cfg",
-                "labelPath": "./models/car_plate_detection/ssd_vgg16_caffe_glue_hole.names",
-	            "postProcessLibPath": "libssdvggpostprocessor.so"
-            },
-            "factory": "mxpi_modelinfer",
-            "next": "mxpi_objectdistributor2"
-        },
-        "mxpi_objectdistributor2":{
-            "props":{
-                "classIds":"0|1",
-                "dataSource":"mxpi_modelinfer4",
-                "distributeAll":"yes"
-            },
-            "factory":"mxpi_distributor",
-            "next":"mxpi_imagecrop9"
-        },
-        "mxpi_imagecrop9":{
-            "props":{
-                "dataSource":"mxpi_objectdistributor2_0",
-                "resizeHeight":"72",
-                "resizeWidth":"272"
-            },
-            "factory":"mxpi_imagecrop",
-            "next":"queue23"
-        },
-        "queue23":{
-            "props":{
-                "max-size-buffers":"50"
-            },
-            "factory":"queue",
-            "next":"car_plate"
-        },
-        "car_plate": {
-            "props": {
-                 "parentName": "mxpi_imagecrop9",
-                 "modelPath": "./models/car_plate_recognition/car_plate_recognition.om",
-                 "postProcessLibPath": "libcarplaterecognitionpostprocessor.so"
-            },
-            "factory": "mxpi_modelinfer",
-            "next": "mxpi_synchronize2:1"
-        },
-        "mxpi_synchronize2":{
-            "factory":"mxpi_synchronize",
-            "next":"mxpi_dataserialize1"
-        },
-        "mxpi_dataserialize1":{
-            "props":{
-                "outputDataKeys":"ReservedFrameInfo,motor_attr,car_plate"
-            },
-            "factory":"mxpi_dataserialize",
-            "next":"mxpi_parallel2serial3:1"
-        },
-        "queue13":{
-            "props":{
-                "max-size-buffers":"50"
-            },
-            "factory":"queue",
-            "next":"tee2"
-        },
-        "tee2":{
-            "factory":"tee",
-            "next":[
-                "queue16",
-                "queue17"
-            ]
-        },
-        "queue16":{
-            "props":{
-                "max-size-buffers":"50"
-            },
-            "factory":"queue",
-            "next":"mxpi_imageresize4"
-        },
-        "mxpi_imageresize4":{
-            "props":{
-                "dataSource":"vision",
-                "resizeHeight":"256",
-                "resizeWidth":"192"
-            },
-            "factory":"mxpi_imageresize",
-            "next":"queue15"
-        },
-        "queue15":{
-            "props":{
-                "max-size-buffers":"100"
-            },
-            "factory":"queue",
-            "next":"pedestrian_attribute"
-        },
-        "pedestrian_attribute":{
-            "props":{
-                "dataSource":"mxpi_imageresize4",
-                "modelPath":"./models/pedestrianattribute/pede_attr_4_batch.om",
-                "postProcessConfigPath":"./models/pedestrianattribute/pedes_attr.cfg",
-                "labelPath":"./models/pedestrianattribute/coco.names",
-                "postProcessLibPath":"libresnetattrpostprocessor.so"
-            },
-            "factory":"mxpi_modelinfer",
-            "next":"mxpi_synchronize1:0"
-        },
-        "queue17":{
-            "props":{
-                "max-size-buffers":"50"
-            },
-            "factory":"queue",
-            "next":"mxpi_imageresize5"
-        },
-        "mxpi_imageresize5":{
-            "props":{
-                "dataSource":"vision",
-                "resizeHeight":"384",
-                "resizeWidth":"128"
-            },
-            "factory":"mxpi_imageresize",
-            "next":"queue18"
-        },
-        "queue18":{
-            "props":{
-                "max-size-buffers":"100"
-            },
-            "factory":"queue",
-            "next":"pedestrian_reid"
-        },
-        "pedestrian_reid":{
-            "props":{
-                "dataSource":"mxpi_imageresize5",
-                "modelPath":"./models/pedereid/pede_reid_4_batch.om",
-                "postProcessConfigPath":"./models/pedereid/pedereid.cfg",
-                "labelPath":"./models/pedereid/coco.names",
-                "postProcessLibPath":"libresnetfeaturepostprocessor.so"
-            },
-            "factory":"mxpi_modelinfer",
-            "next":"mxpi_synchronize1:1"
-        },
-        "mxpi_synchronize1":{
-            "factory":"mxpi_synchronize",
-            "next":"mxpi_dataserialize2"
-        },
-        "mxpi_dataserialize2":{
-            "props":{
-                "outputDataKeys":"ReservedFrameInfo,pedestrian_attribute,pedestrian_reid"
-            },
-            "factory":"mxpi_dataserialize",
-            "next":"mxpi_parallel2serial3:2"
-        },
-        "mxpi_parallel2serial3":{
-            "factory":"mxpi_parallel2serial",
-            "next":"appsink0"
-        },
-        "appsink0":{
-            "factory":"appsink"
-        }
-    }
+{
+    "detection":{
+        "stream_config":{
+            "deviceId":"1"
+        },
+        "mxpi_rtspsrc0":{
+            "factory":"mxpi_rtspsrc",
+            "props":{
+                "rtspUrl":"rtsp://xxx.xxx.xxx.xxx:xxxx/xxxx.264",
+                "channelId":"0"
+            },
+            "next":"mxpi_videodecoder0"
+        },
+        "mxpi_rtspsrc1":{
+            "factory":"mxpi_rtspsrc",
+            "props":{
+                "rtspUrl":"rtsp://xxx.xxx.xxx.xxx:xxxx/xxxx.264",
+                "channelId":"1"
+            },
+            "next":"mxpi_videodecoder1"
+        },
+        "mxpi_rtspsrc2":{
+            "factory":"mxpi_rtspsrc",
+            "props":{
+                "rtspUrl":"rtsp://xxx.xxx.xxx.xxx:xxxx/xxxx.264",
+                "channelId":"2"
+            },
+            "next":"mxpi_videodecoder2"
+        },
+        "mxpi_rtspsrc3":{
+            "factory":"mxpi_rtspsrc",
+            "props":{
+                "rtspUrl":"rtsp://xxx.xxx.xxx.xxx:xxxx/xxxx.264",
+                "channelId":"3"
+            },
+            "next":"mxpi_videodecoder3"
+        },
+        "mxpi_rtspsrc4":{
+            "factory":"mxpi_rtspsrc",
+            "props":{
+                "rtspUrl":"rtsp://xxx.xxx.xxx.xxx:xxxx/xxxx.264",
+                "channelId":"4"
+            },
+            "next":"mxpi_videodecoder4"
+        },
+        "mxpi_rtspsrc5":{
+            "factory":"mxpi_rtspsrc",
+            "props":{
+                "rtspUrl":"rtsp://xxx.xxx.xxx.xxx:xxxx/xxxx.264",
+                "channelId":"5"
+            },
+            "next":"mxpi_videodecoder5"
+        },
+        "mxpi_rtspsrc6":{
+            "factory":"mxpi_rtspsrc",
+            "props":{
+                "rtspUrl":"rtsp://xxx.xxx.xxx.xxx:xxxx/xxxx.264",
+                "channelId":"6"
+            },
+            "next":"mxpi_videodecoder6"
+        },
+        "mxpi_rtspsrc7":{
+            "factory":"mxpi_rtspsrc",
+            "props":{
+                "rtspUrl":"rtsp://xxx.xxx.xxx.xxx:xxxx/xxxx.264",
+                "channelId":"7"
+            },
+            "next":"mxpi_videodecoder7"
+        },
+        "mxpi_rtspsrc8":{
+            "factory":"mxpi_rtspsrc",
+            "props":{
+                "rtspUrl":"rtsp://xxx.xxx.xxx.xxx:xxxx/xxxx.264",
+                "channelId":"8"
+            },
+            "next":"mxpi_videodecoder8"
+        },
+        "mxpi_rtspsrc9":{
+            "factory":"mxpi_rtspsrc",
+            "props":{
+                "rtspUrl":"rtsp://xxx.xxx.xxx.xxx:xxxx/xxxx.264",
+                "channelId":"9"
+            },
+            "next":"mxpi_videodecoder9"
+        },
+        "mxpi_rtspsrc10":{
+            "factory":"mxpi_rtspsrc",
+            "props":{
+                "rtspUrl":"rtsp://xxx.xxx.xxx.xxx:xxxx/xxxx.264",
+                "channelId":"10"
+            },
+            "next":"mxpi_videodecoder10"
+        },
+        "mxpi_rtspsrc11":{
+            "factory":"mxpi_rtspsrc",
+            "props":{
+                "rtspUrl":"rtsp://xxx.xxx.xxx.xxx:xxxx/xxxx.264",
+                "channelId":"11"
+            },
+            "next":"mxpi_videodecoder11"
+        },
+        "mxpi_videodecoder0":{
+            "factory":"mxpi_videodecoder",
+            "props":{
+                "inputVideoFormat":"H264",
+                "outputImageFormat":"YUV420SP_NV12",
+                "vdecChannelId":"0"
+            },
+            "next":"mxpi_skipframe0"
+        },
+        "mxpi_skipframe0":{
+            "factory":"mxpi_skipframe",
+            "next":"mxpi_parallel2serial0:0",
+            "props":{
+                "frameNum":"2"
+            }
+        },
+        "mxpi_videodecoder1":{
+            "factory":"mxpi_videodecoder",
+            "props":{
+                "inputVideoFormat":"H264",
+                "outputImageFormat":"YUV420SP_NV12",
+                "vdecChannelId":"1"
+            },
+            "next":"mxpi_skipframe1"
+        },
+        "mxpi_skipframe1":{
+            "factory":"mxpi_skipframe",
+            "next":"mxpi_parallel2serial0:1",
+            "props":{
+                "frameNum":"2"
+            }
+        },
+        "mxpi_videodecoder2":{
+            "factory":"mxpi_videodecoder",
+            "props":{
+                "inputVideoFormat":"H264",
+                "outputImageFormat":"YUV420SP_NV12",
+                "vdecChannelId":"2"
+            },
+            "next":"mxpi_skipframe2"
+        },
+        "mxpi_skipframe2":{
+            "factory":"mxpi_skipframe",
+            "next":"mxpi_parallel2serial0:2",
+            "props":{
+                "frameNum":"2"
+            }
+        },
+        "mxpi_videodecoder3":{
+            "factory":"mxpi_videodecoder",
+            "props":{
+                "inputVideoFormat":"H264",
+                "outputImageFormat":"YUV420SP_NV12",
+                "vdecChannelId":"3"
+            },
+            "next":"mxpi_skipframe3"
+        },
+        "mxpi_skipframe3":{
+            "factory":"mxpi_skipframe",
+            "next":"mxpi_parallel2serial0:3",
+            "props":{
+                "frameNum":"2"
+            }
+        },
+        "mxpi_videodecoder4":{
+            "factory":"mxpi_videodecoder",
+            "props":{
+                "inputVideoFormat":"H264",
+                "outputImageFormat":"YUV420SP_NV12",
+                "vdecChannelId":"4"
+            },
+            "next":"mxpi_skipframe4"
+        },
+        "mxpi_skipframe4":{
+            "factory":"mxpi_skipframe",
+            "next":"mxpi_parallel2serial0:4",
+            "props":{
+                "frameNum":"2"
+            }
+        },
+        "mxpi_videodecoder5":{
+            "factory":"mxpi_videodecoder",
+            "props":{
+                "inputVideoFormat":"H264",
+                "outputImageFormat":"YUV420SP_NV12",
+                "vdecChannelId":"5"
+            },
+            "next":"mxpi_skipframe5"
+        },
+        "mxpi_skipframe5":{
+            "factory":"mxpi_skipframe",
+            "next":"mxpi_parallel2serial0:5",
+            "props":{
+                "frameNum":"2"
+            }
+        },
+        "mxpi_videodecoder6":{
+            "factory":"mxpi_videodecoder",
+            "props":{
+                "inputVideoFormat":"H264",
+                "outputImageFormat":"YUV420SP_NV12",
+                "vdecChannelId":"6"
+            },
+            "next":"mxpi_skipframe6"
+        },
+        "mxpi_skipframe6":{
+            "factory":"mxpi_skipframe",
+            "next":"mxpi_parallel2serial0:6",
+            "props":{
+                "frameNum":"2"
+            }
+        },
+        "mxpi_videodecoder7":{
+            "factory":"mxpi_videodecoder",
+            "props":{
+                "inputVideoFormat":"H264",
+                "outputImageFormat":"YUV420SP_NV12",
+                "vdecChannelId":"7"
+            },
+            "next":"mxpi_skipframe7"
+        },
+        "mxpi_skipframe7":{
+            "factory":"mxpi_skipframe",
+            "next":"mxpi_parallel2serial0:7",
+            "props":{
+                "frameNum":"2"
+            }
+        },
+        "mxpi_videodecoder8":{
+            "factory":"mxpi_videodecoder",
+            "props":{
+                "inputVideoFormat":"H264",
+                "outputImageFormat":"YUV420SP_NV12",
+                "vdecChannelId":"8"
+            },
+            "next":"mxpi_skipframe8"
+        },
+        "mxpi_skipframe8":{
+            "factory":"mxpi_skipframe",
+            "next":"mxpi_parallel2serial0:8",
+            "props":{
+                "frameNum":"2"
+            }
+        },
+        "mxpi_videodecoder9":{
+            "factory":"mxpi_videodecoder",
+            "props":{
+                "inputVideoFormat":"H264",
+                "outputImageFormat":"YUV420SP_NV12",
+                "vdecChannelId":"9"
+            },
+            "next":"mxpi_skipframe9"
+        },
+        "mxpi_skipframe9":{
+            "factory":"mxpi_skipframe",
+            "next":"mxpi_parallel2serial0:9",
+            "props":{
+                "frameNum":"2"
+            }
+        },
+        "mxpi_videodecoder10":{
+            "factory":"mxpi_videodecoder",
+            "props":{
+                "inputVideoFormat":"H264",
+                "outputImageFormat":"YUV420SP_NV12",
+                "vdecChannelId":"10"
+            },
+            "next":"mxpi_skipframe10"
+        },
+        "mxpi_skipframe10":{
+            "factory":"mxpi_skipframe",
+            "next":"mxpi_parallel2serial0:10",
+            "props":{
+                "frameNum":"2"
+            }
+        },
+        "mxpi_videodecoder11":{
+            "factory":"mxpi_videodecoder",
+            "props":{
+                "inputVideoFormat":"H264",
+                "outputImageFormat":"YUV420SP_NV12",
+                "vdecChannelId":"11"
+            },
+            "next":"mxpi_skipframe11"
+        },
+        "mxpi_skipframe11":{
+            "factory":"mxpi_skipframe",
+            "next":"mxpi_parallel2serial0:11",
+            "props":{
+                "frameNum":"2"
+            }
+        },
+        "mxpi_parallel2serial0":{
+            "factory":"mxpi_parallel2serial",
+            "props":{
+                "dataSource":"mxpi_videodecoder0,mxpi_videodecoder1,mxpi_videodecoder2,mxpi_videodecoder3,mxpi_videodecoder4,mxpi_videodecoder5,mxpi_videodecoder6,mxpi_videodecoder7,mxpi_videodecoder8,mxpi_videodecoder9,mxpi_videodecoder10,mxpi_videodecoder11"
+            },
+            "next":"mxpi_imageresize0"
+        },
+        "mxpi_imageresize0":{
+            "props":{
+                "dataSource":"mxpi_parallel2serial0",
+                "resizeHeight":"416",
+                "resizeWidth":"416"
+            },
+            "factory":"mxpi_imageresize",
+            "next":"queue0"
+        },
+        "queue0":{
+            "props":{
+                "max-size-buffers":"500"
+            },
+            "factory":"queue",
+            "next":"mxpi_modelinfer0"
+        },
+        "mxpi_modelinfer0":{
+            "props":{
+                "dataSource":"mxpi_imageresize0",
+                "modelPath":"./models/yolov4_improve/yolov4_detection.om",
+                "postProcessConfigPath":"./models/yolov4_improve/yolov4.cfg",
+                "labelPath":"./models/yolov4_improve/coco.names",
+                "postProcessLibPath":"libMpYOLOv3PostProcessor.so"
+            },
+            "factory":"mxpi_modelinfer",
+            "next":"mxpi_objectdistributor0"
+        },
+        "mxpi_objectdistributor0":{
+            "props":{
+                "classIds":"3,2|0",
+                "dataSource":"mxpi_modelinfer0"
+            },
+            "factory":"mxpi_distributor",
+            "next":["queue1","queue33"]
+        },
+        "queue1":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_imagecrop1"
+        },
+        "mxpi_imagecrop1":{
+            "props":{
+                "dataSource":"mxpi_objectdistributor0_0",
+                "resizeHeight":"96",
+                "resizeWidth":"96"
+            },
+            "factory":"mxpi_imagecrop",
+            "next":"mxpi_channeldistributor_pfm"
+        },
+        "mxpi_channeldistributor_pfm":{
+            "props":{
+                "channelIds":"0|1|2|3,4|5|6|7,8|9|10|11"
+            },
+            "factory":"mxpi_distributor",
+            "next":["queue_landmark0","queue_landmark1","queue_landmark2"]
+        },
+        "queue_landmark0":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_facelandmark0"
+        },
+        "mxpi_facelandmark0":{
+            "props":{
+                "dataSource":"mxpi_imagecrop1",
+                "modelPath":"./models/facequality/face_quality_improve.om",
+                "postProcessLibPath":"libfacelandmarkpostprocessor.so"
+            },
+            "factory":"mxpi_modelinfer",
+            "next":"mxpi_facelandmark:0"
+        },
+        "queue_landmark1":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_facelandmark1"
+        },
+        "mxpi_facelandmark1":{
+            "props":{
+                "dataSource":"mxpi_imagecrop1",
+                "modelPath":"./models/facequality/face_quality_improve.om",
+                "postProcessLibPath":"libfacelandmarkpostprocessor.so"
+            },
+            "factory":"mxpi_modelinfer",
+            "next":"mxpi_facelandmark:1"
+        },
+        "queue_landmark2":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_facelandmark2"
+        },
+        "mxpi_facelandmark2":{
+            "props":{
+                "dataSource":"mxpi_imagecrop1",
+                "modelPath":"./models/facequality/face_quality_improve.om",
+                "postProcessLibPath":"libfacelandmarkpostprocessor.so"
+            },
+            "factory":"mxpi_modelinfer",
+            "next":"mxpi_facelandmark:2"
+        },
+        "mxpi_facelandmark":{
+            "factory":"mxpi_parallel2serial",
+            "props":{
+                "dataSource":"mxpi_facelandmark0,mxpi_facelandmark1,mxpi_facelandmark2"
+            },
+            "next":"queue2"
+        },
+        "queue2":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_imagecrop0"
+        },
+        "mxpi_imagecrop0":{
+            "props":{
+                "dataSource":"mxpi_objectdistributor0_0",
+                "resizeHeight":"96",
+                "resizeWidth":"64"
+            },
+            "factory":"mxpi_imagecrop",
+            "next":"mxpi_channeldistributor_pfm2"
+        },
+        "mxpi_channeldistributor_pfm2":{
+            "props":{
+                "channelIds":"0|1|2|3|4|5,6|7|8|9|10|11"
+            },
+            "factory":"mxpi_distributor",
+            "next":["queue_embedding0","queue_embedding1"]
+        },
+        "queue_embedding0":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_FaceFeatureModelInfer0"
+        },
+        "mxpi_FaceFeatureModelInfer0":{
+            "props":{
+                "dataSource":"mxpi_imagecrop0",
+                "modelPath":"./models/faceembedding/face_embedding.om",
+                "postProcessConfigPath":"./models/facefeature/yolov3-tiny-addpad.cfg",
+                "postProcessLibPath":"libresnetfeaturepostprocessor.so"
+            },
+            "factory":"mxpi_modelinfer",
+            "next":"mxpi_FaceFeatureModelInfer:0"
+        },
+        "queue_embedding1":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_FaceFeatureModelInfer1"
+        },
+        "mxpi_FaceFeatureModelInfer1":{
+            "props":{
+                "dataSource":"mxpi_imagecrop0",
+                "modelPath":"./models/faceembedding/face_embedding.om",
+                "postProcessConfigPath":"./models/facefeature/yolov3-tiny-addpad.cfg",
+                "postProcessLibPath":"libresnetfeaturepostprocessor.so"
+            },
+            "factory":"mxpi_modelinfer",
+            "next":"mxpi_FaceFeatureModelInfer:1"
+        },
+        "mxpi_FaceFeatureModelInfer":{
+            "factory":"mxpi_parallel2serial",
+            "props":{
+                "dataSource":"mxpi_FaceFeatureModelInfer0,mxpi_FaceFeatureModelInfer1"
+            },
+            "next":"queue_test"
+        },
+        "queue_test":{
+            "props":{
+                "max-size-buffers":"100"
+            },
+            "factory":"queue",
+            "next":"mxpi_channeldistributor0"
+        },
+        "mxpi_channeldistributor0":{
+            "props":{
+                "channelIds":"0,1,2,3,4,5,6,7,8,9,10,11"
+            },
+            "factory":"mxpi_distributor",
+            "next":["mxpi_motsimplesort_face0","mxpi_motsimplesort_face1","mxpi_motsimplesort_face2","mxpi_motsimplesort_face3","mxpi_motsimplesort_face4","mxpi_motsimplesort_face5","mxpi_motsimplesort_face6","mxpi_motsimplesort_face7","mxpi_motsimplesort_face8","mxpi_motsimplesort_face9","mxpi_motsimplesort_face10","mxpi_motsimplesort_face11"]
+        },
+        "mxpi_motsimplesort_face0": {
+            "props": {
+                "dataSourceDetection": "mxpi_objectdistributor0_0",
+                "dataSourceFeature":"mxpi_FaceFeatureModelInfer"
+            },
+            "factory": "mxpi_motsimplesort",
+            "next": "queue_sel_0"
+        },
+        "queue_sel_0":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_faceselection0"
+        },
+        "mxpi_faceselection0":{
+            "props":{
+                "status":"1",
+                "dataSourceDetection":"mxpi_motsimplesort_face0",
+                "dataSourceKeyPoint":"mxpi_facelandmark",
+                "minScoreThreshold":"0"
+            },
+            "factory":"mxpi_faceselection",
+            "next":[
+                "queue_mux_0",
+                "queue_crop_0"
+            ]
+        },
+        "queue_mux_0":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_parallel2serial1:0"
+        },
+        "queue_crop_0":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_imagecrop2"
+        },
+        "mxpi_imagecrop2":{
+            "props":{
+                "dataSource":"mxpi_faceselection0_0",
+                "leftExpandRatio":"0.1",
+                "rightExpandRatio":"0.1",
+                "upExpandRatio":"0.1",
+                "downExpandRatio":"0.1",
+                "resizeHeight":"112",
+                "resizeWidth":"112"
+            },
+            "factory":"mxpi_imagecrop",
+            "next":"mxpi_parallel2serial2:0"
+        },
+        "mxpi_motsimplesort_face1": {
+            "props": {
+                "dataSourceDetection": "mxpi_objectdistributor0_0",
+                "dataSourceFeature":"mxpi_FaceFeatureModelInfer"
+            },
+            "factory": "mxpi_motsimplesort",
+            "next": "queue_sel_1"
+        },
+        "queue_sel_1":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_faceselection1"
+        },
+        "mxpi_faceselection1":{
+            "props":{
+                "status":"1",
+                "dataSourceDetection":"mxpi_motsimplesort_face1",
+                "dataSourceKeyPoint":"mxpi_facelandmark",
+                "minScoreThreshold":"0"
+            },
+            "factory":"mxpi_faceselection",
+            "next":[
+                "queue_mux_1",
+                "queue_crop_1"
+            ]
+        },
+        "queue_mux_1":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_parallel2serial1:1"
+        },
+        "queue_crop_1":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_imagecrop3"
+        },
+        "mxpi_imagecrop3":{
+            "props":{
+                "dataSource":"mxpi_faceselection1_0",
+                "leftExpandRatio":"0.1",
+                "rightExpandRatio":"0.1",
+                "upExpandRatio":"0.1",
+                "downExpandRatio":"0.1",
+                "resizeHeight":"112",
+                "resizeWidth":"112"
+            },
+            "factory":"mxpi_imagecrop",
+            "next":"mxpi_parallel2serial2:1"
+        },
+        "mxpi_motsimplesort_face2": {
+            "props": {
+                "dataSourceDetection": "mxpi_objectdistributor0_0",
+                "dataSourceFeature":"mxpi_FaceFeatureModelInfer"
+            },
+            "factory": "mxpi_motsimplesort",
+            "next": "queue_sel_2"
+        },
+        "queue_sel_2":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_faceselection2"
+        },
+        "mxpi_faceselection2":{
+            "props":{
+                "status":"1",
+                "dataSourceDetection":"mxpi_motsimplesort_face2",
+                "dataSourceKeyPoint":"mxpi_facelandmark",
+                "minScoreThreshold":"0"
+            },
+            "factory":"mxpi_faceselection",
+            "next":[
+                "queue_mux_2",
+                "queue_crop_2"
+            ]
+        },
+        "queue_mux_2":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_parallel2serial1:2"
+        },
+        "queue_crop_2":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_imagecrop4"
+        },
+        "mxpi_imagecrop4":{
+            "props":{
+                "dataSource":"mxpi_faceselection2_0",
+                "leftExpandRatio":"0.1",
+                "rightExpandRatio":"0.1",
+                "upExpandRatio":"0.1",
+                "downExpandRatio":"0.1",
+                "resizeHeight":"112",
+                "resizeWidth":"112"
+            },
+            "factory":"mxpi_imagecrop",
+            "next":"mxpi_parallel2serial2:2"
+        },
+        "mxpi_motsimplesort_face3": {
+            "props": {
+                "dataSourceDetection": "mxpi_objectdistributor0_0",
+                "dataSourceFeature":"mxpi_FaceFeatureModelInfer"
+            },
+            "factory": "mxpi_motsimplesort",
+            "next": "queue_sel_3"
+        },
+        "queue_sel_3":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_faceselection3"
+        },
+        "mxpi_faceselection3":{
+            "props":{
+                "status":"1",
+                "dataSourceDetection":"mxpi_motsimplesort_face3",
+                "dataSourceKeyPoint":"mxpi_facelandmark",
+                "minScoreThreshold":"0"
+            },
+            "factory":"mxpi_faceselection",
+            "next":[
+                "queue_mux_3",
+                "queue_crop_3"
+            ]
+        },
+        "queue_mux_3":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_parallel2serial1:3"
+        },
+        "queue_crop_3":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_imagecrop5"
+        },
+        "mxpi_imagecrop5":{
+            "props":{
+                "dataSource":"mxpi_faceselection3_0",
+                "leftExpandRatio":"0.1",
+                "rightExpandRatio":"0.1",
+                "upExpandRatio":"0.1",
+                "downExpandRatio":"0.1",
+                "resizeHeight":"112",
+                "resizeWidth":"112"
+            },
+            "factory":"mxpi_imagecrop",
+            "next":"mxpi_parallel2serial2:3"
+        },
+        "mxpi_motsimplesort_face4": {
+            "props": {
+                "dataSourceDetection": "mxpi_objectdistributor0_0",
+                "dataSourceFeature":"mxpi_FaceFeatureModelInfer"
+            },
+            "factory": "mxpi_motsimplesort",
+            "next": "queue_sel_4"
+        },
+        "queue_sel_4":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_faceselection4"
+        },
+        "mxpi_faceselection4":{
+            "props":{
+                "status":"1",
+                "dataSourceDetection":"mxpi_motsimplesort_face4",
+                "dataSourceKeyPoint":"mxpi_facelandmark",
+                "minScoreThreshold":"0"
+            },
+            "factory":"mxpi_faceselection",
+            "next":[
+                "queue_mux_4",
+                "queue_crop_4"
+            ]
+        },
+        "queue_mux_4":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_parallel2serial1:4"
+        },
+        "queue_crop_4":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_imagecrop6"
+        },
+        "mxpi_imagecrop6":{
+            "props":{
+                "dataSource":"mxpi_faceselection4_0",
+                "leftExpandRatio":"0.1",
+                "rightExpandRatio":"0.1",
+                "upExpandRatio":"0.1",
+                "downExpandRatio":"0.1",
+                "resizeHeight":"112",
+                "resizeWidth":"112"
+            },
+            "factory":"mxpi_imagecrop",
+            "next":"mxpi_parallel2serial2:4"
+        },
+        "mxpi_motsimplesort_face5": {
+            "props": {
+                "dataSourceDetection": "mxpi_objectdistributor0_0",
+                "dataSourceFeature":"mxpi_FaceFeatureModelInfer"
+            },
+            "factory": "mxpi_motsimplesort",
+            "next": "queue_sel_5"
+        },
+        "queue_sel_5":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_faceselection5"
+        },
+        "mxpi_faceselection5":{
+            "props":{
+                "status":"1",
+                "dataSourceDetection":"mxpi_motsimplesort_face5",
+                "dataSourceKeyPoint":"mxpi_facelandmark",
+                "minScoreThreshold":"0"
+            },
+            "factory":"mxpi_faceselection",
+            "next":[
+                "queue_mux_5",
+                "queue_crop_5"
+            ]
+        },
+        "queue_mux_5":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_parallel2serial1:5"
+        },
+        "queue_crop_5":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_imagecrop7"
+        },
+        "mxpi_imagecrop7":{
+            "props":{
+                "dataSource":"mxpi_faceselection5_0",
+                "leftExpandRatio":"0.1",
+                "rightExpandRatio":"0.1",
+                "upExpandRatio":"0.1",
+                "downExpandRatio":"0.1",
+                "resizeHeight":"112",
+                "resizeWidth":"112"
+            },
+            "factory":"mxpi_imagecrop",
+            "next":"mxpi_parallel2serial2:5"
+        },
+        "mxpi_motsimplesort_face6": {
+            "props": {
+                "dataSourceDetection": "mxpi_objectdistributor0_0",
+                "dataSourceFeature":"mxpi_FaceFeatureModelInfer"
+            },
+            "factory": "mxpi_motsimplesort",
+            "next": "queue_sel_6"
+        },
+        "queue_sel_6":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_faceselection6"
+        },
+        "mxpi_faceselection6":{
+            "props":{
+                "status":"1",
+                "dataSourceDetection":"mxpi_motsimplesort_face6",
+                "dataSourceKeyPoint":"mxpi_facelandmark",
+                "minScoreThreshold":"0"
+            },
+            "factory":"mxpi_faceselection",
+            "next":[
+                "queue_mux_6",
+                "queue_crop_6"
+            ]
+        },
+        "queue_mux_6":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_parallel2serial1:6"
+        },
+        "queue_crop_6":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_imagecrop_6"
+        },
+        "mxpi_imagecrop_6":{
+            "props":{
+                "dataSource":"mxpi_faceselection6_0",
+                "leftExpandRatio":"0.1",
+                "rightExpandRatio":"0.1",
+                "upExpandRatio":"0.1",
+                "downExpandRatio":"0.1",
+                "resizeHeight":"112",
+                "resizeWidth":"112"
+            },
+            "factory":"mxpi_imagecrop",
+            "next":"mxpi_parallel2serial2:6"
+        },
+        "mxpi_motsimplesort_face7": {
+            "props": {
+                "dataSourceDetection": "mxpi_objectdistributor0_0",
+                "dataSourceFeature":"mxpi_FaceFeatureModelInfer"
+            },
+            "factory": "mxpi_motsimplesort",
+            "next": "queue_sel_7"
+        },
+        "queue_sel_7":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_faceselection7"
+        },
+        "mxpi_faceselection7":{
+            "props":{
+                "status":"1",
+                "dataSourceDetection":"mxpi_motsimplesort_face7",
+                "dataSourceKeyPoint":"mxpi_facelandmark",
+                "minScoreThreshold":"0"
+            },
+            "factory":"mxpi_faceselection",
+            "next":[
+                "queue_mux_7",
+                "queue_crop_7"
+            ]
+        },
+        "queue_mux_7":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_parallel2serial1:7"
+        },
+        "queue_crop_7":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_imagecrop_7"
+        },
+        "mxpi_imagecrop_7":{
+            "props":{
+                "dataSource":"mxpi_faceselection7_0",
+                "leftExpandRatio":"0.1",
+                "rightExpandRatio":"0.1",
+                "upExpandRatio":"0.1",
+                "downExpandRatio":"0.1",
+                "resizeHeight":"112",
+                "resizeWidth":"112"
+            },
+            "factory":"mxpi_imagecrop",
+            "next":"mxpi_parallel2serial2:7"
+        },
+        "mxpi_motsimplesort_face8": {
+            "props": {
+                "dataSourceDetection": "mxpi_objectdistributor0_0",
+                "dataSourceFeature":"mxpi_FaceFeatureModelInfer"
+            },
+            "factory": "mxpi_motsimplesort",
+            "next": "queue_sel_8"
+        },
+        "queue_sel_8":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_faceselection8"
+        },
+        "mxpi_faceselection8":{
+            "props":{
+                "status":"1",
+                "dataSourceDetection":"mxpi_motsimplesort_face8",
+                "dataSourceKeyPoint":"mxpi_facelandmark",
+                "minScoreThreshold":"0"
+            },
+            "factory":"mxpi_faceselection",
+            "next":[
+                "queue_mux_8",
+                "queue_crop_8"
+            ]
+        },
+        "queue_mux_8":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_parallel2serial1:8"
+        },
+        "queue_crop_8":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_imagecrop_8"
+        },
+        "mxpi_imagecrop_8":{
+            "props":{
+                "dataSource":"mxpi_faceselection8_0",
+                "leftExpandRatio":"0.1",
+                "rightExpandRatio":"0.1",
+                "upExpandRatio":"0.1",
+                "downExpandRatio":"0.1",
+                "resizeHeight":"112",
+                "resizeWidth":"112"
+            },
+            "factory":"mxpi_imagecrop",
+            "next":"mxpi_parallel2serial2:8"
+        },
+        "mxpi_motsimplesort_face9": {
+            "props": {
+                "dataSourceDetection": "mxpi_objectdistributor0_0",
+                "dataSourceFeature":"mxpi_FaceFeatureModelInfer"
+            },
+            "factory": "mxpi_motsimplesort",
+            "next": "queue_sel_9"
+        },
+        "queue_sel_9":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_faceselection9"
+        },
+        "mxpi_faceselection9":{
+            "props":{
+                "status":"1",
+                "dataSourceDetection":"mxpi_motsimplesort_face9",
+                "dataSourceKeyPoint":"mxpi_facelandmark",
+                "minScoreThreshold":"0"
+            },
+            "factory":"mxpi_faceselection",
+            "next":[
+                "queue_mux_9",
+                "queue_crop_9"
+            ]
+        },
+        "queue_mux_9":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_parallel2serial1:9"
+        },
+        "queue_crop_9":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_imagecrop_9"
+        },
+        "mxpi_imagecrop_9":{
+            "props":{
+                "dataSource":"mxpi_faceselection9_0",
+                "leftExpandRatio":"0.1",
+                "rightExpandRatio":"0.1",
+                "upExpandRatio":"0.1",
+                "downExpandRatio":"0.1",
+                "resizeHeight":"112",
+                "resizeWidth":"112"
+            },
+            "factory":"mxpi_imagecrop",
+            "next":"mxpi_parallel2serial2:9"
+        },
+        "mxpi_motsimplesort_face10": {
+            "props": {
+                "dataSourceDetection": "mxpi_objectdistributor0_0",
+                "dataSourceFeature":"mxpi_FaceFeatureModelInfer"
+            },
+            "factory": "mxpi_motsimplesort",
+            "next": "queue_sel_10"
+        },
+        "queue_sel_10":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_faceselection10"
+        },
+        "mxpi_faceselection10":{
+            "props":{
+                "status":"1",
+                "dataSourceDetection":"mxpi_motsimplesort_face10",
+                "dataSourceKeyPoint":"mxpi_facelandmark",
+                "minScoreThreshold":"0"
+            },
+            "factory":"mxpi_faceselection",
+            "next":[
+                "queue_mux_10",
+                "queue_crop_10"
+            ]
+        },
+        "queue_mux_10":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_parallel2serial1:10"
+        },
+        "queue_crop_10":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_imagecrop_10"
+        },
+        "mxpi_imagecrop_10":{
+            "props":{
+                "dataSource":"mxpi_faceselection10_0",
+                "leftExpandRatio":"0.1",
+                "rightExpandRatio":"0.1",
+                "upExpandRatio":"0.1",
+                "downExpandRatio":"0.1",
+                "resizeHeight":"112",
+                "resizeWidth":"112"
+            },
+            "factory":"mxpi_imagecrop",
+            "next":"mxpi_parallel2serial2:10"
+        },
+        "mxpi_motsimplesort_face11": {
+            "props": {
+                "dataSourceDetection": "mxpi_objectdistributor0_0",
+                "dataSourceFeature":"mxpi_FaceFeatureModelInfer"
+            },
+            "factory": "mxpi_motsimplesort",
+            "next": "queue_sel_11"
+        },
+        "queue_sel_11":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_faceselection11"
+        },
+        "mxpi_faceselection11":{
+            "props":{
+                "status":"1",
+                "dataSourceDetection":"mxpi_motsimplesort_face11",
+                "dataSourceKeyPoint":"mxpi_facelandmark",
+                "minScoreThreshold":"0"
+            },
+            "factory":"mxpi_faceselection",
+            "next":[
+                "queue_mux_11",
+                "queue_crop_11"
+            ]
+        },
+        "queue_mux_11":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_parallel2serial1:11"
+        },
+        "queue_crop_11":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_imagecrop_11"
+        },
+        "mxpi_imagecrop_11":{
+            "props":{
+                "dataSource":"mxpi_faceselection11_0",
+                "leftExpandRatio":"0.1",
+                "rightExpandRatio":"0.1",
+                "upExpandRatio":"0.1",
+                "downExpandRatio":"0.1",
+                "resizeHeight":"112",
+                "resizeWidth":"112"
+            },
+            "factory":"mxpi_imagecrop",
+            "next":"mxpi_parallel2serial2:11"
+        },
+        "mxpi_parallel2serial1":{
+            "factory":"mxpi_parallel2serial",
+            "props":{
+                "dataSource":"mxpi_faceselection0_1,mxpi_faceselection1_1,mxpi_faceselection2_1,mxpi_faceselection3_1,mxpi_faceselection4_1,mxpi_faceselection5_1,mxpi_faceselection6_1,mxpi_faceselection7_1,mxpi_faceselection8_1,mxpi_faceselection9_1,mxpi_faceselection10_1,mxpi_faceselection11_1"
+            },
+            "next":"mxpi_facealignment0:1"
+        },
+        "mxpi_parallel2serial2":{
+            "factory":"mxpi_parallel2serial",
+            "props":{
+                "dataSource":"mxpi_imagecrop2,mxpi_imagecrop3,mxpi_imagecrop4,mxpi_imagecrop5,mxpi_imagecrop6,mxpi_imagecrop7,mxpi_imagecrop_6,mxpi_imagecrop_7,mxpi_imagecrop_8,mxpi_imagecrop_9,mxpi_imagecrop_10,mxpi_imagecrop_11"
+            },
+            "next":"mxpi_facealignment0:0"
+        },
+        "mxpi_facealignment0":{
+            "props":{
+                "status":"1",
+                "dataSourceImage":"mxpi_parallel2serial2",
+                "dataSourceKeyPoint":"mxpi_parallel2serial1",
+                "afterFaceAlignmentHeight":"112",
+                "afterFaceAlignmentWidth":"112"
+            },
+            "factory":"mxpi_facealignment",
+            "next":"tee3"
+        },
+        "tee3":{
+            "factory":"tee",
+            "next":[
+                "queue7",
+                "queue19"
+            ]
+        },
+        "queue7":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"face_attribute"
+        },
+        "face_attribute":{
+            "props":{
+                "dataSource":"mxpi_facealignment0",
+                "modelPath":"./models/faceattr/face_attribute_batch_4.om",
+                "postProcessConfigPath":"./models/faceattr/yolov3-tiny-addpad.cfg",
+                "labelPath":"./models/faceattr/coco.names",
+                "postProcessLibPath":"libresnetattrpostprocessor.so"
+            },
+            "factory":"mxpi_modelinfer",
+            "next":"mxpi_synchronize0:0"
+        },
+        "queue19":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"face_feature"
+        },
+        "face_feature":{
+            "props":{
+                "dataSource":"mxpi_facealignment0",
+                "modelPath":"./models/facefeature/face_feature_batch_1.om",
+                "postProcessConfigPath":"./models/facefeature/yolov3-tiny-addpad.cfg",
+                "postProcessLibPath":"libresnetfeaturepostprocessor.so"
+            },
+            "factory":"mxpi_modelinfer",
+            "next":"mxpi_synchronize0:1"
+        },
+        "mxpi_synchronize0":{
+            "factory":"mxpi_synchronize",
+            "next":"mxpi_dataserialize0"
+        },
+        "mxpi_dataserialize0":{
+            "props":{
+                "outputDataKeys":"ReservedFrameInfo,face_attribute,face_feature"
+            },
+            "factory":"mxpi_dataserialize",
+            "next":"mxpi_parallel2serial3:0"
+        },
+        "queue33":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_imagecrop8"
+        },
+        "mxpi_imagecrop8":{
+            "props":{
+                "dataSource":"mxpi_objectdistributor0_1",
+                "resizeHeight":"224",
+                "resizeWidth":"224",
+                "leftExpandRatio":"0.1",
+                "rightExpandRatio":"0.1",
+                "upExpandRatio":"0.1",
+                "downExpandRatio":"0.1"
+            },
+            "factory":"mxpi_imagecrop",
+            "next":"mxpi_channeldistributor1"
+        },
+        "mxpi_channeldistributor1":{
+            "props":{
+                "channelIds":"0,1,2,3,4,5,6,7,8,9,10,11"
+            },
+            "factory":"mxpi_distributor",
+            "next":["queue_mot_obj0","queue_mot_obj1","queue_mot_obj2","queue_mot_obj3","queue_mot_obj4","queue_mot_obj5","queue_mot_obj6","queue_mot_obj7","queue_mot_obj8","queue_mot_obj9","queue_mot_obj10","queue_mot_obj11"]
+        },
+        "queue_mot_obj0":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_motsimplesort_obj0"
+        },
+        "mxpi_motsimplesort_obj0": {
+                "props": {
+                    "dataSourceDetection": "mxpi_objectdistributor0_1"
+                },
+                "factory": "mxpi_motsimplesort",
+                "next": "queue_ob_0"
+        },
+        "queue_ob_0":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_objectselection0:0"
+        },
+        "mxpi_objectselection0":{
+            "props":{
+                "status":"1",
+                "dataSourceDetection":"mxpi_motsimplesort_obj0",
+                "dataSourceImage":"mxpi_imagecrop8",
+                "tmarginValue":"0.1",
+                "weightMargin":"0.2",
+                "weightOcclude":"0.11",
+                "weightSize":"0.21",
+                "weightConf":"0.31",
+                "trackTime":"0",
+                "normRadius":"0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,0.8,0.7,0.6,0.5,0.4,0.3,0.2,0.1",
+                "outputKeys":"vision,object"
+            },
+            "factory":"mxpi_objectselection",
+            "next":"mxpi_parallel2serial4:0"
+        },
+        "queue_mot_obj1":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_motsimplesort_obj1"
+        },
+        "mxpi_motsimplesort_obj1": {
+                "props": {
+                    "dataSourceDetection": "mxpi_objectdistributor0_1"
+                },
+                "factory": "mxpi_motsimplesort",
+                "next": "queue_ob_1"
+        },
+        "queue_ob_1":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_objectselection1:0"
+        },
+        "mxpi_objectselection1":{
+            "props":{
+                "status":"1",
+                "dataSourceDetection":"mxpi_motsimplesort_obj1",
+                "dataSourceImage":"mxpi_imagecrop8",
+                "tmarginValue":"0.1",
+                "weightMargin":"0.2",
+                "weightOcclude":"0.11",
+                "weightSize":"0.21",
+                "weightConf":"0.31",
+                "trackTime":"0",
+                "normRadius":"0.1 ,0.2, 0.3,0.4,0. 5,0.6,0.7, 0.8,0.9,0.8,0 .7,0.6,0.5,0.4,0.3,0.2,0.1",
+                "outputKeys":"vision,object"
+            },
+            "factory":"mxpi_objectselection",
+            "next":"mxpi_parallel2serial4:1"
+        },
+        "queue_mot_obj2":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_motsimplesort_obj2"
+        },
+        "mxpi_motsimplesort_obj2": {
+                "props": {
+                    "dataSourceDetection": "mxpi_objectdistributor0_1"
+                },
+                "factory": "mxpi_motsimplesort",
+                "next": "queue_ob_2"
+        },
+        "queue_ob_2":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_objectselection2:0"
+        },
+        "mxpi_objectselection2":{
+            "props":{
+                "status":"1",
+                "dataSourceDetection":"mxpi_motsimplesort_obj2",
+                "dataSourceImage":"mxpi_imagecrop8",
+                "tmarginValue":"0.1",
+                "weightMargin":"0.2",
+                "weightOcclude":"0.11",
+                "weightSize":"0.21",
+                "weightConf":"0.31",
+                "trackTime":"0",
+                "normRadius":"0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,0.8,0.7,0.6,0.5,0.4,0.3,0.2,0.1",
+                "outputKeys":"vision,object"
+            },
+            "factory":"mxpi_objectselection",
+            "next":"mxpi_parallel2serial4:2"
+        },
+        "queue_mot_obj3":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_motsimplesort_obj3"
+        },
+        "mxpi_motsimplesort_obj3": {
+                "props": {
+                    "dataSourceDetection": "mxpi_objectdistributor0_1"
+                },
+                "factory": "mxpi_motsimplesort",
+                "next": "queue_ob_3"
+        },
+        "queue_ob_3":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_objectselection3:0"
+        },
+        "mxpi_objectselection3":{
+            "props":{
+                "status":"1",
+                "dataSourceDetection":"mxpi_motsimplesort_obj3",
+                "dataSourceImage":"mxpi_imagecrop8",
+                "tmarginValue":"0.1",
+                "weightMargin":"0.2",
+                "weightOcclude":"0.11",
+                "weightSize":"0.21",
+                "weightConf":"0.31",
+                "trackTime":"0",
+                "normRadius":"0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,0.8,0.7,0.6,0.5,0.4,0.3,0.2,0.1",
+                "outputKeys":"vision,object"
+            },
+            "factory":"mxpi_objectselection",
+            "next":"mxpi_parallel2serial4:3"
+        },
+        "queue_mot_obj4":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_motsimplesort_obj4"
+        },
+        "mxpi_motsimplesort_obj4": {
+                "props": {
+                    "dataSourceDetection": "mxpi_objectdistributor0_1"
+                },
+                "factory": "mxpi_motsimplesort",
+                "next": "queue_ob_4"
+        },
+        "queue_ob_4":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_objectselection4:0"
+        },
+        "mxpi_objectselection4":{
+            "props":{
+                "status":"1",
+                "dataSourceDetection":"mxpi_motsimplesort_obj4",
+                "dataSourceImage":"mxpi_imagecrop8",
+                "tmarginValue":"0.1",
+                "weightMargin":"0.2",
+                "weightOcclude":"0.11",
+                "weightSize":"0.21",
+                "weightConf":"0.31",
+                "trackTime":"0",
+                "normRadius":"0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,0.8,0.7,0.6,0.5,0.4,0.3,0.2,0.1",
+                "outputKeys":"vision,object"
+            },
+            "factory":"mxpi_objectselection",
+            "next":"mxpi_parallel2serial4:4"
+        },
+        "queue_mot_obj5":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_motsimplesort_obj5"
+        },
+        "mxpi_motsimplesort_obj5": {
+                "props": {
+                    "dataSourceDetection": "mxpi_objectdistributor0_1"
+                },
+                "factory": "mxpi_motsimplesort",
+                "next": "queue_ob_5"
+        },
+        "queue_ob_5":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_objectselection5:0"
+        },
+        "mxpi_objectselection5":{
+            "props":{
+                "status":"1",
+                "dataSourceDetection":"mxpi_motsimplesort_obj5",
+                "dataSourceImage":"mxpi_imagecrop8",
+                "tmarginValue":"0.1",
+                "weightMargin":"0.2",
+                "weightOcclude":"0.11",
+                "weightSize":"0.21",
+                "weightConf":"0.31",
+                "trackTime":"0",
+                "normRadius":"0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,0.8,0.7,0.6,0.5,0.4,0.3,0.2,0.1",
+                "outputKeys":"vision,object"
+            },
+            "factory":"mxpi_objectselection",
+            "next":"mxpi_parallel2serial4:5"
+        },
+        "queue_mot_obj6":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_motsimplesort_obj6"
+        },
+        "mxpi_motsimplesort_obj6": {
+                "props": {
+                    "dataSourceDetection": "mxpi_objectdistributor0_1"
+                },
+                "factory": "mxpi_motsimplesort",
+                "next": "queue_ob_6"
+        },
+        "queue_ob_6":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_objectselection6:0"
+        },
+        "mxpi_objectselection6":{
+            "props":{
+                "status":"1",
+                "dataSourceDetection":"mxpi_motsimplesort_obj6",
+                "dataSourceImage":"mxpi_imagecrop8",
+                "tmarginValue":"0.1",
+                "weightMargin":"0.2",
+                "weightOcclude":"0.11",
+                "weightSize":"0.21",
+                "weightConf":"0.31",
+                "trackTime":"0",
+                "normRadius":"0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,0.8,0.7,0.6,0.5,0.4,0.3,0.2,0.1",
+                "outputKeys":"vision,object"
+            },
+            "factory":"mxpi_objectselection",
+            "next":"mxpi_parallel2serial4:6"
+        },
+        "queue_mot_obj7":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_motsimplesort_obj7"
+        },
+        "mxpi_motsimplesort_obj7": {
+                "props": {
+                    "dataSourceDetection": "mxpi_objectdistributor0_1"
+                },
+                "factory": "mxpi_motsimplesort",
+                "next": "queue_ob_7"
+        },
+        "queue_ob_7":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_objectselection7:0"
+        },
+        "mxpi_objectselection7":{
+            "props":{
+                "status":"1",
+                "dataSourceDetection":"mxpi_motsimplesort_obj7",
+                "dataSourceImage":"mxpi_imagecrop8",
+                "tmarginValue":"0.1",
+                "weightMargin":"0.2",
+                "weightOcclude":"0.11",
+                "weightSize":"0.21",
+                "weightConf":"0.31",
+                "trackTime":"0",
+                "normRadius":"0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,0.8,0.7,0.6,0.5,0.4,0.3,0.2,0.1",
+                "outputKeys":"vision,object"
+            },
+            "factory":"mxpi_objectselection",
+            "next":"mxpi_parallel2serial4:7"
+        },
+        "queue_mot_obj8":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_motsimplesort_obj8"
+        },
+        "mxpi_motsimplesort_obj8": {
+                "props": {
+                    "dataSourceDetection": "mxpi_objectdistributor0_1"
+                },
+                "factory": "mxpi_motsimplesort",
+                "next": "queue_ob_8"
+        },
+        "queue_ob_8":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_objectselection8:0"
+        },
+        "mxpi_objectselection8":{
+            "props":{
+                "status":"1",
+                "dataSourceDetection":"mxpi_motsimplesort_obj8",
+                "dataSourceImage":"mxpi_imagecrop8",
+                "tmarginValue":"0.1",
+                "weightMargin":"0.2",
+                "weightOcclude":"0.11",
+                "weightSize":"0.21",
+                "weightConf":"0.31",
+                "trackTime":"0",
+                "normRadius":"0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,0.8,0.7,0.6,0.5,0.4,0.3,0.2,0.1",
+                "outputKeys":"vision,object"
+            },
+            "factory":"mxpi_objectselection",
+            "next":"mxpi_parallel2serial4:8"
+        },
+        "queue_mot_obj9":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_motsimplesort_obj9"
+        },
+        "mxpi_motsimplesort_obj9": {
+                "props": {
+                    "dataSourceDetection": "mxpi_objectdistributor0_1"
+                },
+                "factory": "mxpi_motsimplesort",
+                "next": "queue_ob_9"
+        },
+        "queue_ob_9":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_objectselection9:0"
+        },
+        "mxpi_objectselection9":{
+            "props":{
+                "status":"1",
+                "dataSourceDetection":"mxpi_motsimplesort_obj9",
+                "dataSourceImage":"mxpi_imagecrop8",
+                "tmarginValue":"0.1",
+                "weightMargin":"0.2",
+                "weightOcclude":"0.11",
+                "weightSize":"0.21",
+                "weightConf":"0.31",
+                "trackTime":"0",
+                "normRadius":"0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,0.8,0.7,0.6,0.5,0.4,0.3,0.2,0.1",
+                "outputKeys":"vision,object"
+            },
+            "factory":"mxpi_objectselection",
+            "next":"mxpi_parallel2serial4:9"
+        },
+        "queue_mot_obj10":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_motsimplesort_obj10"
+        },
+        "mxpi_motsimplesort_obj10": {
+                "props": {
+                    "dataSourceDetection": "mxpi_objectdistributor0_1"
+                },
+                "factory": "mxpi_motsimplesort",
+                "next": "queue_ob_10"
+        },
+        "queue_ob_10":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_objectselection10:0"
+        },
+        "mxpi_objectselection10":{
+            "props":{
+                "status":"1",
+                "dataSourceDetection":"mxpi_motsimplesort_obj10",
+                "dataSourceImage":"mxpi_imagecrop8",
+                "tmarginValue":"0.1",
+                "weightMargin":"0.2",
+                "weightOcclude":"0.11",
+                "weightSize":"0.21",
+                "weightConf":"0.31",
+                "trackTime":"0",
+                "normRadius":"0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,0.8,0.7,0.6,0.5,0.4,0.3,0.2,0.1",
+                "outputKeys":"vision,object"
+            },
+            "factory":"mxpi_objectselection",
+            "next":"mxpi_parallel2serial4:10"
+        },
+        "queue_mot_obj11":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_motsimplesort_obj11"
+        },
+        "mxpi_motsimplesort_obj11": {
+                "props": {
+                    "dataSourceDetection": "mxpi_objectdistributor0_1"
+                },
+                "factory": "mxpi_motsimplesort",
+                "next": "queue_ob_11"
+        },
+        "queue_ob_11":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_objectselection11:0"
+        },
+        "mxpi_objectselection11":{
+            "props":{
+                "status":"1",
+                "dataSourceDetection":"mxpi_motsimplesort_obj11",
+                "dataSourceImage":"mxpi_imagecrop8",
+                "tmarginValue":"0.1",
+                "weightMargin":"0.2",
+                "weightOcclude":"0.11",
+                "weightSize":"0.21",
+                "weightConf":"0.31",
+                "trackTime":"0",
+                "normRadius":"0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,0.8,0.7,0.6,0.5,0.4,0.3,0.2,0.1",
+                "outputKeys":"vision,object"
+            },
+            "factory":"mxpi_objectselection",
+            "next":"mxpi_parallel2serial4:11"
+        },
+        "mxpi_parallel2serial4":{
+            "factory":"mxpi_parallel2serial",
+            "next":"mxpi_objectdistributor1"
+        },
+        "mxpi_objectdistributor1":{
+            "props":{
+                "classIds":"2,0",
+                "dataSource":"object"
+            },
+            "factory":"mxpi_distributor",
+            "next":[
+                "queue12",
+                "queue13"
+            ]
+        },
+        "queue12":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"tee4"
+        },
+        "tee4":{
+            "factory":"tee",
+            "next":[
+                "queue20",
+                "queue21"
+            ]
+        },
+        "queue20":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_imageresize3"
+        },
+        "mxpi_imageresize3":{
+            "props":{
+                "dataSource":"vision",
+                "resizeHeight":"224",
+                "resizeWidth":"224"
+            },
+            "factory":"mxpi_imageresize",
+            "next":"queue14"
+        },
+        "queue14":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"motor_attr"
+        },
+        "motor_attr":{
+            "props":{
+                "dataSource":"mxpi_imageresize3",
+                "modelPath":"./models/motorattr/vehicle_attribute.om",
+                "postProcessConfigPath":"./models/motorattr/yolov3-tiny-addpad.cfg",
+                "labelPath":"./models/motorattr/coco.names",
+                "postProcessLibPath":"libresnetattrpostprocessor.so"
+            },
+            "factory":"mxpi_modelinfer",
+            "next":"mxpi_synchronize2:0"
+        },
+        "queue21":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_imageresize6"
+        },
+        "mxpi_imageresize6":{
+            "props":{
+                "dataSource":"vision",
+                "resizeHeight": "640",
+                "resizeWidth": "480"
+            },
+            "factory":"mxpi_imageresize",
+            "next":"queue22"
+        },
+        "queue22":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_modelinfer4"
+        },
+        "mxpi_modelinfer4": {
+            "props": {
+                "parentName": "mxpi_imageresize6",
+                "modelPath": "./models/car_plate_detection/car_plate_detection.om",
+                "postProcessConfigPath": "./models/car_plate_detection/ssd_vgg16_caffe_glue_hole.cfg",
+                "labelPath": "./models/car_plate_detection/ssd_vgg16_caffe_glue_hole.names",
+	            "postProcessLibPath": "libssdvggpostprocessor.so"
+            },
+            "factory": "mxpi_modelinfer",
+            "next": "mxpi_objectdistributor2"
+        },
+        "mxpi_objectdistributor2":{
+            "props":{
+                "classIds":"0|1",
+                "dataSource":"mxpi_modelinfer4",
+                "distributeAll":"yes"
+            },
+            "factory":"mxpi_distributor",
+            "next":"mxpi_imagecrop9"
+        },
+        "mxpi_imagecrop9":{
+            "props":{
+                "dataSource":"mxpi_objectdistributor2_0",
+                "resizeHeight":"72",
+                "resizeWidth":"272"
+            },
+            "factory":"mxpi_imagecrop",
+            "next":"queue23"
+        },
+        "queue23":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"car_plate"
+        },
+        "car_plate": {
+            "props": {
+                 "parentName": "mxpi_imagecrop9",
+                 "modelPath": "./models/car_plate_recognition/car_plate_recognition.om",
+                 "postProcessLibPath": "libcarplaterecognitionpostprocessor.so"
+            },
+            "factory": "mxpi_modelinfer",
+            "next": "mxpi_synchronize2:1"
+        },
+        "mxpi_synchronize2":{
+            "factory":"mxpi_synchronize",
+            "next":"mxpi_dataserialize1"
+        },
+        "mxpi_dataserialize1":{
+            "props":{
+                "outputDataKeys":"ReservedFrameInfo,motor_attr,car_plate"
+            },
+            "factory":"mxpi_dataserialize",
+            "next":"mxpi_parallel2serial3:1"
+        },
+        "queue13":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"tee2"
+        },
+        "tee2":{
+            "factory":"tee",
+            "next":[
+                "queue16",
+                "queue17"
+            ]
+        },
+        "queue16":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_imageresize4"
+        },
+        "mxpi_imageresize4":{
+            "props":{
+                "dataSource":"vision",
+                "resizeHeight":"256",
+                "resizeWidth":"192"
+            },
+            "factory":"mxpi_imageresize",
+            "next":"queue15"
+        },
+        "queue15":{
+            "props":{
+                "max-size-buffers":"100"
+            },
+            "factory":"queue",
+            "next":"pedestrian_attribute"
+        },
+        "pedestrian_attribute":{
+            "props":{
+                "dataSource":"mxpi_imageresize4",
+                "modelPath":"./models/pedestrianattribute/pede_attr_4_batch.om",
+                "postProcessConfigPath":"./models/pedestrianattribute/pedes_attr.cfg",
+                "labelPath":"./models/pedestrianattribute/coco.names",
+                "postProcessLibPath":"libresnetattrpostprocessor.so"
+            },
+            "factory":"mxpi_modelinfer",
+            "next":"mxpi_synchronize1:0"
+        },
+        "queue17":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_imageresize5"
+        },
+        "mxpi_imageresize5":{
+            "props":{
+                "dataSource":"vision",
+                "resizeHeight":"384",
+                "resizeWidth":"128"
+            },
+            "factory":"mxpi_imageresize",
+            "next":"queue18"
+        },
+        "queue18":{
+            "props":{
+                "max-size-buffers":"100"
+            },
+            "factory":"queue",
+            "next":"pedestrian_reid"
+        },
+        "pedestrian_reid":{
+            "props":{
+                "dataSource":"mxpi_imageresize5",
+                "modelPath":"./models/pedereid/pede_reid_4_batch.om",
+                "postProcessConfigPath":"./models/pedereid/pedereid.cfg",
+                "labelPath":"./models/pedereid/coco.names",
+                "postProcessLibPath":"libresnetfeaturepostprocessor.so"
+            },
+            "factory":"mxpi_modelinfer",
+            "next":"mxpi_synchronize1:1"
+        },
+        "mxpi_synchronize1":{
+            "factory":"mxpi_synchronize",
+            "next":"mxpi_dataserialize2"
+        },
+        "mxpi_dataserialize2":{
+            "props":{
+                "outputDataKeys":"ReservedFrameInfo,pedestrian_attribute,pedestrian_reid"
+            },
+            "factory":"mxpi_dataserialize",
+            "next":"mxpi_parallel2serial3:2"
+        },
+        "mxpi_parallel2serial3":{
+            "factory":"mxpi_parallel2serial",
+            "next":"appsink0"
+        },
+        "appsink0":{
+            "factory":"appsink"
+        }
+    }
 }
\ No newline at end of file
diff --git a/mxVision/AllObjectsStructuring/pipeline/face_registry.pipeline b/mxVision/mxVision-referenceapps/AllObjectsStructuring/pipeline/face_registry.pipeline
similarity index 100%
rename from mxVision/AllObjectsStructuring/pipeline/face_registry.pipeline
rename to mxVision/mxVision-referenceapps/AllObjectsStructuring/pipeline/face_registry.pipeline
diff --git a/mxVision/AllObjectsStructuring/plugins/MpObjectSelection/CMakeLists.txt b/mxVision/mxVision-referenceapps/AllObjectsStructuring/plugins/MpObjectSelection/CMakeLists.txt
similarity index 100%
rename from mxVision/AllObjectsStructuring/plugins/MpObjectSelection/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/AllObjectsStructuring/plugins/MpObjectSelection/CMakeLists.txt
diff --git a/mxVision/AllObjectsStructuring/plugins/MpObjectSelection/MpObjectSelection.cpp b/mxVision/mxVision-referenceapps/AllObjectsStructuring/plugins/MpObjectSelection/MpObjectSelection.cpp
similarity index 100%
rename from mxVision/AllObjectsStructuring/plugins/MpObjectSelection/MpObjectSelection.cpp
rename to mxVision/mxVision-referenceapps/AllObjectsStructuring/plugins/MpObjectSelection/MpObjectSelection.cpp
diff --git a/mxVision/AllObjectsStructuring/plugins/MpObjectSelection/MpObjectSelection.h b/mxVision/mxVision-referenceapps/AllObjectsStructuring/plugins/MpObjectSelection/MpObjectSelection.h
similarity index 100%
rename from mxVision/AllObjectsStructuring/plugins/MpObjectSelection/MpObjectSelection.h
rename to mxVision/mxVision-referenceapps/AllObjectsStructuring/plugins/MpObjectSelection/MpObjectSelection.h
diff --git a/mxVision/AllObjectsStructuring/plugins/MxpiFaceSelection/CMakeLists.txt b/mxVision/mxVision-referenceapps/AllObjectsStructuring/plugins/MxpiFaceSelection/CMakeLists.txt
similarity index 100%
rename from mxVision/AllObjectsStructuring/plugins/MxpiFaceSelection/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/AllObjectsStructuring/plugins/MxpiFaceSelection/CMakeLists.txt
diff --git a/mxVision/AllObjectsStructuring/plugins/MxpiFaceSelection/MxpiFaceSelection.cpp b/mxVision/mxVision-referenceapps/AllObjectsStructuring/plugins/MxpiFaceSelection/MxpiFaceSelection.cpp
similarity index 100%
rename from mxVision/AllObjectsStructuring/plugins/MxpiFaceSelection/MxpiFaceSelection.cpp
rename to mxVision/mxVision-referenceapps/AllObjectsStructuring/plugins/MxpiFaceSelection/MxpiFaceSelection.cpp
diff --git a/mxVision/AllObjectsStructuring/plugins/MxpiFaceSelection/MxpiFaceSelection.h b/mxVision/mxVision-referenceapps/AllObjectsStructuring/plugins/MxpiFaceSelection/MxpiFaceSelection.h
similarity index 100%
rename from mxVision/AllObjectsStructuring/plugins/MxpiFaceSelection/MxpiFaceSelection.h
rename to mxVision/mxVision-referenceapps/AllObjectsStructuring/plugins/MxpiFaceSelection/MxpiFaceSelection.h
diff --git a/mxVision/AllObjectsStructuring/plugins/MxpiFrameAlign/BlockingMap.h b/mxVision/mxVision-referenceapps/AllObjectsStructuring/plugins/MxpiFrameAlign/BlockingMap.h
similarity index 100%
rename from mxVision/AllObjectsStructuring/plugins/MxpiFrameAlign/BlockingMap.h
rename to mxVision/mxVision-referenceapps/AllObjectsStructuring/plugins/MxpiFrameAlign/BlockingMap.h
diff --git a/mxVision/AllObjectsStructuring/plugins/MxpiFrameAlign/CMakeLists.txt b/mxVision/mxVision-referenceapps/AllObjectsStructuring/plugins/MxpiFrameAlign/CMakeLists.txt
similarity index 100%
rename from mxVision/AllObjectsStructuring/plugins/MxpiFrameAlign/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/AllObjectsStructuring/plugins/MxpiFrameAlign/CMakeLists.txt
diff --git a/mxVision/AllObjectsStructuring/plugins/MxpiFrameAlign/MxpiFrameAlign.cpp b/mxVision/mxVision-referenceapps/AllObjectsStructuring/plugins/MxpiFrameAlign/MxpiFrameAlign.cpp
similarity index 100%
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rename to mxVision/mxVision-referenceapps/AllObjectsStructuring/plugins/MxpiFrameAlign/MxpiFrameAlign.cpp
diff --git a/mxVision/AllObjectsStructuring/plugins/MxpiFrameAlign/MxpiFrameAlign.h b/mxVision/mxVision-referenceapps/AllObjectsStructuring/plugins/MxpiFrameAlign/MxpiFrameAlign.h
similarity index 100%
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rename to mxVision/mxVision-referenceapps/AllObjectsStructuring/plugins/MxpiFrameAlign/MxpiFrameAlign.h
diff --git a/mxVision/AllObjectsStructuring/plugins/MxpiSkipFrame/CMakeLists.txt b/mxVision/mxVision-referenceapps/AllObjectsStructuring/plugins/MxpiSkipFrame/CMakeLists.txt
similarity index 100%
rename from mxVision/AllObjectsStructuring/plugins/MxpiSkipFrame/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/AllObjectsStructuring/plugins/MxpiSkipFrame/CMakeLists.txt
diff --git a/mxVision/AllObjectsStructuring/plugins/MxpiSkipFrame/MxpiSkipFrame.cpp b/mxVision/mxVision-referenceapps/AllObjectsStructuring/plugins/MxpiSkipFrame/MxpiSkipFrame.cpp
similarity index 100%
rename from mxVision/AllObjectsStructuring/plugins/MxpiSkipFrame/MxpiSkipFrame.cpp
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diff --git a/mxVision/AllObjectsStructuring/plugins/MxpiSkipFrame/MxpiSkipFrame.h b/mxVision/mxVision-referenceapps/AllObjectsStructuring/plugins/MxpiSkipFrame/MxpiSkipFrame.h
similarity index 100%
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rename to mxVision/mxVision-referenceapps/AllObjectsStructuring/plugins/MxpiSkipFrame/MxpiSkipFrame.h
diff --git a/mxVision/AllObjectsStructuring/requirements.txt b/mxVision/mxVision-referenceapps/AllObjectsStructuring/requirements.txt
similarity index 100%
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rename to mxVision/mxVision-referenceapps/AllObjectsStructuring/requirements.txt
diff --git a/mxVision/AllObjectsStructuring/retrieval/__init__.py b/mxVision/mxVision-referenceapps/AllObjectsStructuring/retrieval/__init__.py
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similarity index 100%
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diff --git a/mxVision/AllObjectsStructuring/retrieval/register.py b/mxVision/mxVision-referenceapps/AllObjectsStructuring/retrieval/register.py
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diff --git a/mxVision/AllObjectsStructuring/run.sh b/mxVision/mxVision-referenceapps/AllObjectsStructuring/run.sh
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diff --git a/mxVision/AllObjectsStructuringV2/postprocessor/carPlateDetectionPostProcess/CMakeLists.txt b/mxVision/mxVision-referenceapps/AllObjectsStructuringV2/postprocessor/carPlateDetectionPostProcess/CMakeLists.txt
similarity index 100%
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diff --git a/mxVision/AllObjectsStructuringV2/postprocessor/carPlateDetectionPostProcess/SsdVggPostProcess.cpp b/mxVision/mxVision-referenceapps/AllObjectsStructuringV2/postprocessor/carPlateDetectionPostProcess/SsdVggPostProcess.cpp
similarity index 100%
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diff --git a/mxVision/AllObjectsStructuringV2/postprocessor/carPlateDetectionPostProcess/SsdVggPostProcess.h b/mxVision/mxVision-referenceapps/AllObjectsStructuringV2/postprocessor/carPlateDetectionPostProcess/SsdVggPostProcess.h
similarity index 100%
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diff --git a/mxVision/AllObjectsStructuringV2/postprocessor/carPlateRecognitionPostProcess/CMakeLists.txt b/mxVision/mxVision-referenceapps/AllObjectsStructuringV2/postprocessor/carPlateRecognitionPostProcess/CMakeLists.txt
similarity index 100%
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diff --git a/mxVision/AllObjectsStructuringV2/postprocessor/carPlateRecognitionPostProcess/CarPlateRecognitionPostProcess.cpp b/mxVision/mxVision-referenceapps/AllObjectsStructuringV2/postprocessor/carPlateRecognitionPostProcess/CarPlateRecognitionPostProcess.cpp
similarity index 100%
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diff --git a/mxVision/AllObjectsStructuringV2/postprocessor/carPlateRecognitionPostProcess/CarPlateRecognitionPostProcess.h b/mxVision/mxVision-referenceapps/AllObjectsStructuringV2/postprocessor/carPlateRecognitionPostProcess/CarPlateRecognitionPostProcess.h
similarity index 100%
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diff --git a/mxVision/AllObjectsStructuringV2/postprocessor/faceAlignment/CMakeLists.txt b/mxVision/mxVision-referenceapps/AllObjectsStructuringV2/postprocessor/faceAlignment/CMakeLists.txt
similarity index 100%
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diff --git a/mxVision/AllObjectsStructuringV2/postprocessor/faceAlignment/FaceAlignment.cpp b/mxVision/mxVision-referenceapps/AllObjectsStructuringV2/postprocessor/faceAlignment/FaceAlignment.cpp
similarity index 100%
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similarity index 100%
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diff --git a/mxVision/AllObjectsStructuringV2/postprocessor/faceLandmark/CMakeLists.txt b/mxVision/mxVision-referenceapps/AllObjectsStructuringV2/postprocessor/faceLandmark/CMakeLists.txt
similarity index 100%
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diff --git a/mxVision/AllObjectsStructuringV2/postprocessor/faceLandmark/FaceLandmarkPostProcess.cpp b/mxVision/mxVision-referenceapps/AllObjectsStructuringV2/postprocessor/faceLandmark/FaceLandmarkPostProcess.cpp
similarity index 100%
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diff --git a/mxVision/AllObjectsStructuringV2/postprocessor/faceLandmark/FaceLandmarkPostProcess.h b/mxVision/mxVision-referenceapps/AllObjectsStructuringV2/postprocessor/faceLandmark/FaceLandmarkPostProcess.h
similarity index 100%
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diff --git a/mxVision/AllObjectsStructuringV2/postprocessor/resnetAttributePostProcess/CMakeLists.txt b/mxVision/mxVision-referenceapps/AllObjectsStructuringV2/postprocessor/resnetAttributePostProcess/CMakeLists.txt
similarity index 100%
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diff --git a/mxVision/Ascendffmpeg/libavcodec/aarch64/rv40dsp_init_aarch64.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/aarch64/rv40dsp_init_aarch64.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/aarch64/vc1dsp_init_aarch64.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/aarch64/vc1dsp_init_aarch64.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/aarch64/videodsp.S b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/aarch64/videodsp.S
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diff --git a/mxVision/Ascendffmpeg/libavcodec/aarch64/vp9dsp_init_10bpp_aarch64.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/aarch64/vp9dsp_init_10bpp_aarch64.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/aarch64/vp9dsp_init_12bpp_aarch64.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/aarch64/vp9dsp_init_12bpp_aarch64.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/aarch64/vp9dsp_init_16bpp_aarch64_template.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/aarch64/vp9dsp_init_16bpp_aarch64_template.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/aarch64/vp9itxfm_16bpp_neon.S b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/aarch64/vp9itxfm_16bpp_neon.S
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diff --git a/mxVision/Ascendffmpeg/libavcodec/aarch64/vp9lpf_16bpp_neon.S b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/aarch64/vp9lpf_16bpp_neon.S
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diff --git a/mxVision/Ascendffmpeg/libavcodec/aarch64/vp9mc_16bpp_neon.S b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/aarch64/vp9mc_16bpp_neon.S
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diff --git a/mxVision/Ascendffmpeg/libavcodec/alpha/idctdsp_alpha.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/alpha/idctdsp_alpha.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/alpha/idctdsp_alpha_asm.S b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/alpha/idctdsp_alpha_asm.S
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diff --git a/mxVision/Ascendffmpeg/libavcodec/alpha/me_cmp_alpha.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/alpha/me_cmp_alpha.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/alpha/me_cmp_mvi_asm.S b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/alpha/me_cmp_mvi_asm.S
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diff --git a/mxVision/Ascendffmpeg/libavcodec/alpha/mpegvideo_alpha.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/alpha/mpegvideo_alpha.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/alpha/pixblockdsp_alpha.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/alpha/pixblockdsp_alpha.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/alpha/simple_idct_alpha.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/alpha/simple_idct_alpha.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/arm/aacpsdsp_neon.S b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/arm/aacpsdsp_neon.S
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diff --git a/mxVision/Ascendffmpeg/libavcodec/arm/sbcdsp_armv6.S b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/arm/sbcdsp_armv6.S
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diff --git a/mxVision/Ascendffmpeg/libavcodec/arm/vp3dsp_neon.S b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/arm/vp3dsp_neon.S
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diff --git a/mxVision/Ascendffmpeg/libavcodec/arm/vp56_arith.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/arm/vp56_arith.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/arm/vp6dsp_init_arm.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/arm/vp6dsp_init_arm.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/arm/vp6dsp_neon.S b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/arm/vp6dsp_neon.S
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diff --git a/mxVision/Ascendffmpeg/libavcodec/arm/vp8.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/arm/vp8.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/arm/vp8_armv6.S b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/arm/vp8_armv6.S
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diff --git a/mxVision/Ascendffmpeg/libavcodec/arm/vp8dsp.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/arm/vp8dsp.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/arm/vp8dsp_armv6.S b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/arm/vp8dsp_armv6.S
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rename from mxVision/Ascendffmpeg/libavcodec/arm/vp8dsp_armv6.S
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diff --git a/mxVision/Ascendffmpeg/libavcodec/arm/vp8dsp_init_arm.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/arm/vp8dsp_init_arm.c
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rename from mxVision/Ascendffmpeg/libavcodec/arm/vp8dsp_init_arm.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/arm/vp8dsp_init_armv6.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/arm/vp8dsp_init_armv6.c
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rename from mxVision/Ascendffmpeg/libavcodec/arm/vp8dsp_init_armv6.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/arm/vp8dsp_init_neon.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/arm/vp8dsp_init_neon.c
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rename from mxVision/Ascendffmpeg/libavcodec/arm/vp8dsp_init_neon.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/arm/vp8dsp_neon.S b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/arm/vp8dsp_neon.S
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rename from mxVision/Ascendffmpeg/libavcodec/arm/vp8dsp_neon.S
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diff --git a/mxVision/Ascendffmpeg/libavcodec/arm/vp9dsp_init.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/arm/vp9dsp_init.h
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rename from mxVision/Ascendffmpeg/libavcodec/arm/vp9dsp_init.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/arm/vp9dsp_init_10bpp_arm.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/arm/vp9dsp_init_10bpp_arm.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/arm/vp9dsp_init_12bpp_arm.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/arm/vp9dsp_init_12bpp_arm.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/arm/vp9dsp_init_16bpp_arm_template.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/arm/vp9dsp_init_16bpp_arm_template.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/arm/vp9dsp_init_arm.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/arm/vp9dsp_init_arm.c
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rename from mxVision/Ascendffmpeg/libavcodec/arm/vp9dsp_init_arm.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/arm/vp9dsp_init_arm.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/arm/vp9itxfm_16bpp_neon.S b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/arm/vp9itxfm_16bpp_neon.S
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diff --git a/mxVision/Ascendffmpeg/libavcodec/arm/vp9itxfm_neon.S b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/arm/vp9itxfm_neon.S
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diff --git a/mxVision/Ascendffmpeg/libavcodec/arm/vp9lpf_16bpp_neon.S b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/arm/vp9lpf_16bpp_neon.S
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diff --git a/mxVision/Ascendffmpeg/libavcodec/arm/vp9lpf_neon.S b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/arm/vp9lpf_neon.S
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diff --git a/mxVision/Ascendffmpeg/libavcodec/arm/vp9mc_16bpp_neon.S b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/arm/vp9mc_16bpp_neon.S
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rename from mxVision/Ascendffmpeg/libavcodec/arm/vp9mc_16bpp_neon.S
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diff --git a/mxVision/Ascendffmpeg/libavcodec/arm/vp9mc_neon.S b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/arm/vp9mc_neon.S
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rename from mxVision/Ascendffmpeg/libavcodec/arm/vp9mc_neon.S
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diff --git a/mxVision/Ascendffmpeg/libavcodec/ascend_dec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/ascend_dec.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/ascend_dec.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/ascend_dec.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/ascend_enc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/ascend_enc.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/ascend_enc.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/ascend_enc.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/ass.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/ass.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/ass_split.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/ass_split.h
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/ass_split.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/assdec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/assdec.c
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/assdec.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/assenc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/assenc.c
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/assenc.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/asv.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/asv.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/asvenc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/asvenc.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/atrac.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/atrac.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/atrac1data.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/atrac1data.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/atrac3.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/atrac3.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/atrac3data.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/atrac3data.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/atrac3plus.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/atrac3plus.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/atrac3plus.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/atrac3plus.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/atrac3plus_data.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/atrac3plus_data.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/atrac3plusdec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/atrac3plusdec.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/atrac3plusdsp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/atrac3plusdsp.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/atrac9dec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/atrac9dec.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/atrac9tab.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/atrac9tab.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/atsc_a53.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/atsc_a53.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/atsc_a53.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/atsc_a53.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/audio_frame_queue.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/audio_frame_queue.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/audio_frame_queue.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/audio_frame_queue.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/audiodsp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/audiodsp.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/audiodsp.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/audiodsp.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/audiotoolboxdec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/audiotoolboxdec.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/audiotoolboxenc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/audiotoolboxenc.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/aura.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/aura.c
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/aura.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/av1.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/av1.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/av1_frame_merge_bsf.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/av1_frame_merge_bsf.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/av1_frame_split_bsf.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/av1_frame_split_bsf.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/av1_metadata_bsf.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/av1_metadata_bsf.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/cbrt_data.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbrt_data.c
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rename from mxVision/Ascendffmpeg/libavcodec/cbrt_data.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbrt_data.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/cbrt_data.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbrt_data.h
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rename from mxVision/Ascendffmpeg/libavcodec/cbrt_data.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbrt_data.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/cbrt_data_fixed.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbrt_data_fixed.c
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rename from mxVision/Ascendffmpeg/libavcodec/cbrt_data_fixed.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbrt_data_fixed.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/cbrt_fixed_tablegen.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbrt_fixed_tablegen.c
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rename from mxVision/Ascendffmpeg/libavcodec/cbrt_fixed_tablegen.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbrt_fixed_tablegen.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/cbrt_tablegen.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbrt_tablegen.c
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rename from mxVision/Ascendffmpeg/libavcodec/cbrt_tablegen.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbrt_tablegen.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/cbrt_tablegen.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbrt_tablegen.h
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rename from mxVision/Ascendffmpeg/libavcodec/cbrt_tablegen.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbrt_tablegen.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/cbrt_tablegen_template.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbrt_tablegen_template.c
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rename from mxVision/Ascendffmpeg/libavcodec/cbrt_tablegen_template.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbrt_tablegen_template.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/cbs.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs.c
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rename from mxVision/Ascendffmpeg/libavcodec/cbs.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/cbs.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs.h
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rename from mxVision/Ascendffmpeg/libavcodec/cbs.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/cbs_av1.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_av1.c
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rename from mxVision/Ascendffmpeg/libavcodec/cbs_av1.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_av1.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/cbs_av1.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_av1.h
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rename from mxVision/Ascendffmpeg/libavcodec/cbs_av1.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_av1.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/cbs_av1_syntax_template.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_av1_syntax_template.c
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rename from mxVision/Ascendffmpeg/libavcodec/cbs_av1_syntax_template.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_av1_syntax_template.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/cbs_bsf.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_bsf.c
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rename from mxVision/Ascendffmpeg/libavcodec/cbs_bsf.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_bsf.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/cbs_bsf.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_bsf.h
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rename from mxVision/Ascendffmpeg/libavcodec/cbs_bsf.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_bsf.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/cbs_h264.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_h264.h
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rename from mxVision/Ascendffmpeg/libavcodec/cbs_h264.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_h264.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/cbs_h2645.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_h2645.c
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rename from mxVision/Ascendffmpeg/libavcodec/cbs_h2645.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_h2645.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/cbs_h2645.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_h2645.h
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rename from mxVision/Ascendffmpeg/libavcodec/cbs_h2645.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_h2645.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/cbs_h264_syntax_template.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_h264_syntax_template.c
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rename from mxVision/Ascendffmpeg/libavcodec/cbs_h264_syntax_template.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_h264_syntax_template.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/cbs_h265.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_h265.h
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rename from mxVision/Ascendffmpeg/libavcodec/cbs_h265.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_h265.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/cbs_h265_syntax_template.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_h265_syntax_template.c
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rename from mxVision/Ascendffmpeg/libavcodec/cbs_h265_syntax_template.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_h265_syntax_template.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/cbs_internal.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_internal.h
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rename from mxVision/Ascendffmpeg/libavcodec/cbs_internal.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_internal.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/cbs_jpeg.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_jpeg.c
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rename from mxVision/Ascendffmpeg/libavcodec/cbs_jpeg.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_jpeg.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/cbs_jpeg.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_jpeg.h
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rename from mxVision/Ascendffmpeg/libavcodec/cbs_jpeg.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_jpeg.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/cbs_jpeg_syntax_template.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_jpeg_syntax_template.c
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rename from mxVision/Ascendffmpeg/libavcodec/cbs_jpeg_syntax_template.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_jpeg_syntax_template.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/cbs_mpeg2.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_mpeg2.c
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rename from mxVision/Ascendffmpeg/libavcodec/cbs_mpeg2.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_mpeg2.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/cbs_mpeg2.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_mpeg2.h
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rename from mxVision/Ascendffmpeg/libavcodec/cbs_mpeg2.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_mpeg2.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/cbs_mpeg2_syntax_template.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_mpeg2_syntax_template.c
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rename from mxVision/Ascendffmpeg/libavcodec/cbs_mpeg2_syntax_template.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_mpeg2_syntax_template.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/cbs_sei.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_sei.c
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rename from mxVision/Ascendffmpeg/libavcodec/cbs_sei.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_sei.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/cbs_sei.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_sei.h
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rename from mxVision/Ascendffmpeg/libavcodec/cbs_sei.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_sei.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/cbs_sei_syntax_template.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_sei_syntax_template.c
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rename from mxVision/Ascendffmpeg/libavcodec/cbs_sei_syntax_template.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_sei_syntax_template.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/cbs_vp9.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_vp9.c
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rename from mxVision/Ascendffmpeg/libavcodec/cbs_vp9.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_vp9.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/cbs_vp9.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_vp9.h
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rename from mxVision/Ascendffmpeg/libavcodec/cbs_vp9.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_vp9.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/cbs_vp9_syntax_template.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_vp9_syntax_template.c
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rename from mxVision/Ascendffmpeg/libavcodec/cbs_vp9_syntax_template.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cbs_vp9_syntax_template.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/ccaption_dec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/ccaption_dec.c
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rename from mxVision/Ascendffmpeg/libavcodec/ccaption_dec.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/ccaption_dec.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/cdgraphics.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cdgraphics.c
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rename from mxVision/Ascendffmpeg/libavcodec/cdgraphics.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cdgraphics.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/cdtoons.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cdtoons.c
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rename from mxVision/Ascendffmpeg/libavcodec/cdtoons.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cdtoons.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/cdxl.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cdxl.c
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rename from mxVision/Ascendffmpeg/libavcodec/cdxl.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cdxl.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/celp_filters.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/celp_filters.c
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rename from mxVision/Ascendffmpeg/libavcodec/celp_filters.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/celp_filters.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/celp_filters.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/celp_filters.h
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rename from mxVision/Ascendffmpeg/libavcodec/celp_filters.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/celp_filters.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/celp_math.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/celp_math.c
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rename from mxVision/Ascendffmpeg/libavcodec/celp_math.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/celp_math.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/celp_math.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/celp_math.h
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rename from mxVision/Ascendffmpeg/libavcodec/celp_math.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/celp_math.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/cfhd.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cfhd.c
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rename from mxVision/Ascendffmpeg/libavcodec/cfhd.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cfhd.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/cfhd.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cfhd.h
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rename from mxVision/Ascendffmpeg/libavcodec/cfhd.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cfhd.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/cfhddata.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cfhddata.c
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cfhddata.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/cfhddsp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cfhddsp.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/cfhddsp.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cfhddsp.h
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rename from mxVision/Ascendffmpeg/libavcodec/cfhddsp.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cfhddsp.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/cfhdenc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cfhdenc.c
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rename from mxVision/Ascendffmpeg/libavcodec/cfhdenc.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cfhdenc.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/cfhdencdsp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cfhdencdsp.c
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rename from mxVision/Ascendffmpeg/libavcodec/cfhdencdsp.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cfhdencdsp.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/cfhdencdsp.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cfhdencdsp.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/cga_data.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cga_data.c
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rename from mxVision/Ascendffmpeg/libavcodec/cga_data.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/cga_data.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cga_data.h
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cga_data.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/chomp_bsf.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/chomp_bsf.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/cinepak.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cinepak.c
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cinepak.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/cinepakenc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cinepakenc.c
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rename from mxVision/Ascendffmpeg/libavcodec/cinepakenc.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cinepakenc.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/clearvideo.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/clearvideo.c
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rename from mxVision/Ascendffmpeg/libavcodec/clearvideo.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/clearvideo.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/clearvideodata.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/clearvideodata.h
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/clearvideodata.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/cljrdec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cljrdec.c
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cljrdec.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/cljrenc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cljrenc.c
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cljrenc.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/cllc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cllc.c
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rename from mxVision/Ascendffmpeg/libavcodec/cllc.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cllc.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/cngdec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cngdec.c
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rename from mxVision/Ascendffmpeg/libavcodec/cngdec.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cngdec.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/cngenc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cngenc.c
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rename from mxVision/Ascendffmpeg/libavcodec/cngenc.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/cngenc.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/codec.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/codec.h
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rename from mxVision/Ascendffmpeg/libavcodec/codec.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/codec.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/codec2utils.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/codec2utils.c
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rename from mxVision/Ascendffmpeg/libavcodec/codec2utils.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/codec2utils.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/codec2utils.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/codec2utils.h
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rename from mxVision/Ascendffmpeg/libavcodec/codec2utils.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/codec2utils.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/codec_desc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/codec_desc.c
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rename from mxVision/Ascendffmpeg/libavcodec/codec_desc.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/codec_desc.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/codec_desc.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/codec_desc.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/diracdec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/diracdec.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/dnxhd_parser.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/dnxhd_parser.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/dnxhdenc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/dnxhdenc.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/dpcm.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/dpcm.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/dpxenc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/dpxenc.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/dsicinaudio.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/dsicinaudio.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/dsicinvideo.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/dsicinvideo.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/dss_sp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/dss_sp.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/dstdec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/dstdec.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/dump_extradata_bsf.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/dump_extradata_bsf.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/dv.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/dv.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/dv_tablegen.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/dv_tablegen.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/dv_tablegen.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/dv_tablegen.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/dvaudio.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/dvaudio.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/dvaudiodec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/dvaudiodec.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/dvbsub_parser.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/dvbsub_parser.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/dvbtxt.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/dvbtxt.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/dvd_nav_parser.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/dvd_nav_parser.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/dvdata.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/dvdata.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/dxva2_mpeg2.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/dxva2_mpeg2.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/dxva2_vc1.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/dxva2_vc1.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/dxva2_vp9.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/dxva2_vp9.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/dynamic_hdr10_plus.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/dynamic_hdr10_plus.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/eac3_core_bsf.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/eac3_core_bsf.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/eac3_data.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/eac3_data.c
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rename from mxVision/Ascendffmpeg/libavcodec/h263dsp.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h263dsp.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/h263dsp.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h263dsp.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/h263dsp.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h263dsp.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/h264.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/h264.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/h2645_parse.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h2645_parse.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/h2645_parse.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h2645_parse.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/h2645_parse.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h2645_parse.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/h2645_parse.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h2645_parse.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/h264_cabac.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264_cabac.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/h264_cabac.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264_cabac.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/h264_cavlc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264_cavlc.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/h264_cavlc.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264_cavlc.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/h264_direct.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264_direct.c
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rename from mxVision/Ascendffmpeg/libavcodec/h264_direct.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264_direct.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/h264_levels.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264_levels.c
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rename from mxVision/Ascendffmpeg/libavcodec/h264_levels.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264_levels.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/h264_levels.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264_levels.h
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rename from mxVision/Ascendffmpeg/libavcodec/h264_levels.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264_levels.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/h264_loopfilter.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264_loopfilter.c
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rename from mxVision/Ascendffmpeg/libavcodec/h264_loopfilter.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264_loopfilter.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/h264_mb.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264_mb.c
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rename from mxVision/Ascendffmpeg/libavcodec/h264_mb.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264_mb.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/h264_mb_template.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264_mb_template.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/h264_mb_template.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264_mb_template.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/h264_mc_template.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264_mc_template.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/h264_mc_template.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264_mc_template.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/h264_metadata_bsf.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264_metadata_bsf.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/h264_metadata_bsf.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264_metadata_bsf.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/h264_mp4toannexb_bsf.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264_mp4toannexb_bsf.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/h264_mp4toannexb_bsf.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264_mp4toannexb_bsf.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/h264_mvpred.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264_mvpred.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/h264_mvpred.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264_mvpred.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/h264_parse.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264_parse.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/h264_parse.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264_parse.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/h264_parse.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264_parse.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/h264_parse.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264_parse.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/h264_parser.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264_parser.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/h264_parser.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264_parser.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/h264_picture.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264_picture.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/h264_picture.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264_picture.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/h264_ps.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264_ps.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/h264_ps.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264_ps.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/h264_ps.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264_ps.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/h264_ps.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264_ps.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/h264_redundant_pps_bsf.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264_redundant_pps_bsf.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/h264_redundant_pps_bsf.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264_redundant_pps_bsf.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/h264_refs.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264_refs.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/h264_refs.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264_refs.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/h264_sei.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264_sei.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/h264_sei.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264_sei.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/h264_sei.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264_sei.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/h264_sei.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264_sei.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/h264_slice.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264_slice.c
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rename from mxVision/Ascendffmpeg/libavcodec/h264_slice.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264_slice.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/h264addpx_template.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264addpx_template.c
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rename from mxVision/Ascendffmpeg/libavcodec/h264addpx_template.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264addpx_template.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/h264chroma.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264chroma.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/h264chroma.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264chroma.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/h264chroma.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264chroma.h
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rename from mxVision/Ascendffmpeg/libavcodec/h264chroma.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264chroma.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/h264chroma_template.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264chroma_template.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/h264chroma_template.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264chroma_template.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/h264data.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264data.c
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rename from mxVision/Ascendffmpeg/libavcodec/h264data.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264data.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/h264data.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264data.h
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rename from mxVision/Ascendffmpeg/libavcodec/h264data.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264data.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/h264dec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264dec.c
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rename from mxVision/Ascendffmpeg/libavcodec/h264dec.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264dec.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/h264dec.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264dec.h
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rename from mxVision/Ascendffmpeg/libavcodec/h264dec.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264dec.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/h264dsp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264dsp.c
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rename from mxVision/Ascendffmpeg/libavcodec/h264dsp.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264dsp.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/h264dsp.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264dsp.h
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rename from mxVision/Ascendffmpeg/libavcodec/h264dsp.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264dsp.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/h264dsp_template.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264dsp_template.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/h264dsp_template.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264dsp_template.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/h264idct.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264idct.c
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rename from mxVision/Ascendffmpeg/libavcodec/h264idct.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264idct.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/h264idct.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264idct.h
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rename from mxVision/Ascendffmpeg/libavcodec/h264idct.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264idct.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/h264idct_template.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264idct_template.c
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rename from mxVision/Ascendffmpeg/libavcodec/h264idct_template.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264idct_template.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/h264pred.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264pred.c
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rename from mxVision/Ascendffmpeg/libavcodec/h264pred.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264pred.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/h264pred.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264pred.h
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rename from mxVision/Ascendffmpeg/libavcodec/h264pred.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264pred.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/h264pred_template.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264pred_template.c
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rename from mxVision/Ascendffmpeg/libavcodec/h264pred_template.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264pred_template.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/h264qpel.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264qpel.c
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rename from mxVision/Ascendffmpeg/libavcodec/h264qpel.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264qpel.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/h264qpel.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264qpel.h
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rename from mxVision/Ascendffmpeg/libavcodec/h264qpel.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264qpel.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/h264qpel_template.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264qpel_template.c
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rename from mxVision/Ascendffmpeg/libavcodec/h264qpel_template.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h264qpel_template.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/h265_metadata_bsf.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h265_metadata_bsf.c
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rename from mxVision/Ascendffmpeg/libavcodec/h265_metadata_bsf.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h265_metadata_bsf.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/h265_profile_level.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h265_profile_level.c
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rename from mxVision/Ascendffmpeg/libavcodec/h265_profile_level.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h265_profile_level.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/h265_profile_level.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h265_profile_level.h
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rename from mxVision/Ascendffmpeg/libavcodec/h265_profile_level.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/h265_profile_level.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/half2float.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/half2float.h
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rename from mxVision/Ascendffmpeg/libavcodec/half2float.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/half2float.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/hap.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hap.c
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rename from mxVision/Ascendffmpeg/libavcodec/hap.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hap.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/hap.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hap.h
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rename from mxVision/Ascendffmpeg/libavcodec/hap.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hap.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/hapdec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hapdec.c
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rename from mxVision/Ascendffmpeg/libavcodec/hapdec.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hapdec.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/hapenc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hapenc.c
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rename from mxVision/Ascendffmpeg/libavcodec/hapenc.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hapenc.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/hapqa_extract_bsf.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hapqa_extract_bsf.c
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rename from mxVision/Ascendffmpeg/libavcodec/hapqa_extract_bsf.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hapqa_extract_bsf.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/hca_data.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hca_data.h
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rename from mxVision/Ascendffmpeg/libavcodec/hca_data.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hca_data.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/hcadec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hcadec.c
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rename from mxVision/Ascendffmpeg/libavcodec/hcadec.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hcadec.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/hcom.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hcom.c
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rename from mxVision/Ascendffmpeg/libavcodec/hcom.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hcom.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/hevc.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hevc.h
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rename from mxVision/Ascendffmpeg/libavcodec/hevc.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hevc.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/hevc_cabac.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hevc_cabac.c
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rename from mxVision/Ascendffmpeg/libavcodec/hevc_cabac.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hevc_cabac.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/hevc_data.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hevc_data.c
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rename from mxVision/Ascendffmpeg/libavcodec/hevc_data.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hevc_data.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/hevc_data.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hevc_data.h
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rename from mxVision/Ascendffmpeg/libavcodec/hevc_data.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hevc_data.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/hevc_filter.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hevc_filter.c
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rename from mxVision/Ascendffmpeg/libavcodec/hevc_filter.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hevc_filter.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/hevc_mp4toannexb_bsf.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hevc_mp4toannexb_bsf.c
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rename from mxVision/Ascendffmpeg/libavcodec/hevc_mp4toannexb_bsf.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hevc_mp4toannexb_bsf.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/hevc_mvs.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hevc_mvs.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/hevc_parse.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hevc_parse.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/hevc_parse.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hevc_parse.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/hevc_parser.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hevc_parser.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/hevc_ps.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hevc_ps.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/hevc_ps_enc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hevc_ps_enc.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/hevc_refs.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hevc_refs.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/hevc_sei.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hevc_sei.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/hevc_sei.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hevc_sei.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/hevcdec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hevcdec.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/hevcdsp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hevcdsp.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/hevcpred.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hevcpred.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/hnm4video.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hnm4video.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/hpel_template.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hpel_template.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/hq_hqa.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hq_hqa.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/hq_hqadata.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hq_hqadata.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/hq_hqadsp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hq_hqadsp.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/hqxvlc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hqxvlc.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/htmlsubtitles.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/htmlsubtitles.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/huffman.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/huffman.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/huffyuvdsp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/huffyuvdsp.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/huffyuvenc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/huffyuvenc.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/huffyuvencdsp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/huffyuvencdsp.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/hwaccels.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/hwaccels.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/imc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/imc.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mdct_fixed_32.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mdct_fixed_32.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mdct_float.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mdct_float.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mdct_template.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mdct_template.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mdec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mdec.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/me_cmp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/me_cmp.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/me_cmp.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/me_cmp.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mediacodec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mediacodec.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mediacodec.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mediacodec.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mediacodec_surface.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mediacodec_surface.c
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mediacodec_surface.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mediacodec_surface.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mediacodec_surface.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mediacodec_sw_buffer.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mediacodec_sw_buffer.c
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rename from mxVision/Ascendffmpeg/libavcodec/mediacodec_sw_buffer.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mediacodec_sw_buffer.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mediacodec_sw_buffer.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mediacodec_wrapper.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mediacodec_wrapper.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mediacodec_wrapper.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mediacodec_wrapper.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mediacodecdec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mediacodecdec.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mediacodecdec_common.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mediacodecdec_common.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mediacodecdec_common.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mediacodecdec_common.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/metasound.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/metasound.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/metasound_data.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/metasound_data.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/metasound_data.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/metasound_data.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mf_utils.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mf_utils.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mf_utils.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mf_utils.h
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mf_utils.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/mfenc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mfenc.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/microdvddec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/microdvddec.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/midivid.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/midivid.c
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/midivid.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mimic.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mimic.c
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mimic.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/Makefile b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/Makefile
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rename from mxVision/Ascendffmpeg/libavcodec/mips/Makefile
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/Makefile
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/aaccoder_mips.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/aaccoder_mips.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/aacdec_mips.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/aacdec_mips.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/aacdec_mips.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/aacdec_mips.h
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rename from mxVision/Ascendffmpeg/libavcodec/mips/aacdec_mips.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/aacpsdsp_mips.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/aacpsdsp_mips.c
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rename from mxVision/Ascendffmpeg/libavcodec/mips/aacpsdsp_mips.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/aacpsy_mips.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/aacpsy_mips.h
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rename from mxVision/Ascendffmpeg/libavcodec/mips/aacpsy_mips.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/aacsbr_mips.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/aacsbr_mips.c
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rename from mxVision/Ascendffmpeg/libavcodec/mips/aacsbr_mips.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/aacsbr_mips.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/aacsbr_mips.h
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rename from mxVision/Ascendffmpeg/libavcodec/mips/aacsbr_mips.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/aacsbr_mips.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/ac3dsp_mips.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/ac3dsp_mips.c
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rename from mxVision/Ascendffmpeg/libavcodec/mips/ac3dsp_mips.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/ac3dsp_mips.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/acelp_filters_mips.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/acelp_filters_mips.c
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rename from mxVision/Ascendffmpeg/libavcodec/mips/acelp_filters_mips.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/acelp_filters_mips.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/acelp_vectors_mips.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/acelp_vectors_mips.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/amrwbdec_mips.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/amrwbdec_mips.c
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rename from mxVision/Ascendffmpeg/libavcodec/mips/amrwbdec_mips.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/amrwbdec_mips.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/amrwbdec_mips.h
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rename from mxVision/Ascendffmpeg/libavcodec/mips/amrwbdec_mips.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/blockdsp_init_mips.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/blockdsp_init_mips.c
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rename from mxVision/Ascendffmpeg/libavcodec/mips/blockdsp_init_mips.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/blockdsp_mips.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/blockdsp_mips.h
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rename from mxVision/Ascendffmpeg/libavcodec/mips/blockdsp_mips.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/blockdsp_mmi.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/blockdsp_mmi.c
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rename from mxVision/Ascendffmpeg/libavcodec/mips/blockdsp_mmi.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/blockdsp_msa.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/blockdsp_msa.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/cabac.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/cabac.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/celp_filters_mips.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/celp_filters_mips.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/celp_math_mips.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/celp_math_mips.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/compute_antialias_fixed.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/compute_antialias_fixed.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/compute_antialias_float.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/compute_antialias_float.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/constants.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/constants.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/constants.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/constants.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/fft_mips.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/fft_mips.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/fmtconvert_mips.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/fmtconvert_mips.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/h263dsp_init_mips.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/h263dsp_init_mips.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/h263dsp_mips.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/h263dsp_mips.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/h263dsp_msa.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/h263dsp_msa.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/h264chroma_init_mips.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/h264chroma_init_mips.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/h264chroma_mips.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/h264chroma_mips.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/h264chroma_mmi.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/h264chroma_mmi.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/h264chroma_msa.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/h264chroma_msa.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/h264dsp_init_mips.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/h264dsp_init_mips.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/h264dsp_mips.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/h264dsp_mips.h
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rename from mxVision/Ascendffmpeg/libavcodec/mips/h264dsp_mips.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/h264dsp_mips.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/h264dsp_mmi.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/h264dsp_mmi.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/h264dsp_mmi.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/h264dsp_mmi.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/h264dsp_msa.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/h264dsp_msa.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/h264dsp_msa.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/h264dsp_msa.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/h264idct_msa.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/h264idct_msa.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/h264idct_msa.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/h264idct_msa.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/h264pred_init_mips.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/h264pred_init_mips.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/h264pred_init_mips.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/h264pred_init_mips.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/h264pred_mips.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/h264pred_mips.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/h264pred_mips.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/h264pred_mips.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/h264pred_mmi.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/h264pred_mmi.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/h264pred_mmi.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/h264pred_mmi.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/h264pred_msa.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/h264pred_msa.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/h264pred_msa.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/h264pred_msa.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/h264qpel_init_mips.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/h264qpel_init_mips.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/h264qpel_init_mips.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/h264qpel_init_mips.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/h264qpel_mmi.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/h264qpel_mmi.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/h264qpel_mmi.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/h264qpel_mmi.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/h264qpel_msa.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/h264qpel_msa.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/h264qpel_msa.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/h264qpel_msa.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/hevc_idct_msa.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/hevc_idct_msa.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/hevc_idct_msa.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/hevc_idct_msa.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/hevc_lpf_sao_msa.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/hevc_lpf_sao_msa.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/hevc_lpf_sao_msa.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/hevc_lpf_sao_msa.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/hevc_macros_msa.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/hevc_macros_msa.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/hevc_macros_msa.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/hevc_macros_msa.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/hevc_mc_bi_msa.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/hevc_mc_bi_msa.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/hevc_mc_bi_msa.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/hevc_mc_bi_msa.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/hevc_mc_biw_msa.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/hevc_mc_biw_msa.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/hevc_mc_biw_msa.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/hevc_mc_biw_msa.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/hevc_mc_uni_msa.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/hevc_mc_uni_msa.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/hevc_mc_uni_msa.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/hevc_mc_uni_msa.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/hevc_mc_uniw_msa.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/hevc_mc_uniw_msa.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/hevc_mc_uniw_msa.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/hevc_mc_uniw_msa.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/hevcdsp_init_mips.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/hevcdsp_init_mips.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/hevcdsp_init_mips.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/hevcdsp_init_mips.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/hevcdsp_mips.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/hevcdsp_mips.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/hevcdsp_mips.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/hevcdsp_mips.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/hevcdsp_mmi.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/hevcdsp_mmi.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/hevcdsp_mmi.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/hevcdsp_mmi.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/hevcdsp_msa.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/hevcdsp_msa.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/hevcdsp_msa.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/hevcdsp_msa.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/hevcpred_init_mips.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/hevcpred_init_mips.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/hevcpred_init_mips.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/hevcpred_init_mips.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/hevcpred_mips.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/hevcpred_mips.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/hevcpred_mips.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/hevcpred_mips.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/hevcpred_msa.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/hevcpred_msa.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/hevcpred_msa.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/hevcpred_msa.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/hpeldsp_init_mips.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/hpeldsp_init_mips.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/hpeldsp_init_mips.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/hpeldsp_init_mips.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/hpeldsp_mips.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/hpeldsp_mips.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/hpeldsp_mips.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/hpeldsp_mips.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/hpeldsp_mmi.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/hpeldsp_mmi.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/hpeldsp_mmi.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/hpeldsp_mmi.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/hpeldsp_msa.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/hpeldsp_msa.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/hpeldsp_msa.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/hpeldsp_msa.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/idctdsp_init_mips.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/idctdsp_init_mips.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/idctdsp_init_mips.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/idctdsp_init_mips.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/idctdsp_mips.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/idctdsp_mips.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/idctdsp_mips.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/idctdsp_mips.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/idctdsp_mmi.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/idctdsp_mmi.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/idctdsp_mmi.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/idctdsp_mmi.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/idctdsp_msa.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/idctdsp_msa.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/idctdsp_msa.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/idctdsp_msa.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/iirfilter_mips.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/iirfilter_mips.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/iirfilter_mips.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/iirfilter_mips.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/lsp_mips.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/lsp_mips.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/lsp_mips.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/lsp_mips.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/mathops.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/mathops.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/mathops.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/mathops.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/me_cmp_init_mips.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/me_cmp_init_mips.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/me_cmp_init_mips.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/me_cmp_init_mips.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/me_cmp_mips.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/me_cmp_mips.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/me_cmp_mips.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/me_cmp_mips.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/me_cmp_msa.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/me_cmp_msa.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/me_cmp_msa.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/me_cmp_msa.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/mpegaudiodsp_mips_fixed.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/mpegaudiodsp_mips_fixed.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/mpegaudiodsp_mips_fixed.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/mpegaudiodsp_mips_fixed.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/mpegaudiodsp_mips_float.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/mpegaudiodsp_mips_float.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/mpegaudiodsp_mips_float.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/mpegaudiodsp_mips_float.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/mpegvideo_init_mips.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/mpegvideo_init_mips.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/mpegvideo_init_mips.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/mpegvideo_init_mips.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/mpegvideo_mips.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/mpegvideo_mips.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/mpegvideo_mips.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/mpegvideo_mips.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/mpegvideo_mmi.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/mpegvideo_mmi.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/mpegvideo_mmi.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/mpegvideo_mmi.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/mpegvideo_msa.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/mpegvideo_msa.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/mpegvideo_msa.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/mpegvideo_msa.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/mpegvideoencdsp_init_mips.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/mpegvideoencdsp_init_mips.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/mpegvideoencdsp_init_mips.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/mpegvideoencdsp_init_mips.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/mpegvideoencdsp_msa.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/mpegvideoencdsp_msa.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/mpegvideoencdsp_msa.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/mpegvideoencdsp_msa.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/pixblockdsp_init_mips.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/pixblockdsp_init_mips.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/pixblockdsp_init_mips.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/pixblockdsp_init_mips.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/pixblockdsp_mips.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/pixblockdsp_mips.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/pixblockdsp_mips.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/pixblockdsp_mips.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/pixblockdsp_mmi.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/pixblockdsp_mmi.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/pixblockdsp_mmi.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/pixblockdsp_mmi.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/pixblockdsp_msa.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/pixblockdsp_msa.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/pixblockdsp_msa.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/pixblockdsp_msa.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/qpeldsp_init_mips.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/qpeldsp_init_mips.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/qpeldsp_init_mips.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/qpeldsp_init_mips.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/qpeldsp_mips.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/qpeldsp_mips.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/qpeldsp_mips.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/qpeldsp_mips.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/qpeldsp_msa.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/qpeldsp_msa.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/qpeldsp_msa.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/qpeldsp_msa.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/sbrdsp_mips.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/sbrdsp_mips.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/sbrdsp_mips.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/sbrdsp_mips.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/simple_idct_mmi.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/simple_idct_mmi.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/simple_idct_mmi.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/simple_idct_mmi.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/simple_idct_msa.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/simple_idct_msa.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/simple_idct_msa.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/simple_idct_msa.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/vc1dsp_init_mips.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/vc1dsp_init_mips.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/vc1dsp_init_mips.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/vc1dsp_init_mips.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/vc1dsp_mips.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/vc1dsp_mips.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/vc1dsp_mips.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/vc1dsp_mips.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/vc1dsp_mmi.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/vc1dsp_mmi.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/vc1dsp_mmi.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/vc1dsp_mmi.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/vc1dsp_msa.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/vc1dsp_msa.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/vc1dsp_msa.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/vc1dsp_msa.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/videodsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/videodsp_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/videodsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/videodsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/vp3dsp_idct_mmi.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/vp3dsp_idct_mmi.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/vp3dsp_idct_mmi.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/vp3dsp_idct_mmi.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/vp3dsp_idct_msa.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/vp3dsp_idct_msa.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/vp3dsp_idct_msa.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/vp3dsp_idct_msa.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/vp3dsp_init_mips.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/vp3dsp_init_mips.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/vp3dsp_init_mips.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/vp3dsp_init_mips.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/vp3dsp_mips.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/vp3dsp_mips.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/vp3dsp_mips.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/vp3dsp_mips.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/vp8_idct_msa.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/vp8_idct_msa.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/vp8_idct_msa.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/vp8_idct_msa.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/vp8_lpf_msa.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/vp8_lpf_msa.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/vp8_lpf_msa.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/vp8_lpf_msa.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/vp8_mc_msa.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/vp8_mc_msa.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/vp8_mc_msa.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/vp8_mc_msa.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/vp8dsp_init_mips.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/vp8dsp_init_mips.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/vp8dsp_init_mips.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/vp8dsp_init_mips.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/vp8dsp_mips.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/vp8dsp_mips.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/vp8dsp_mips.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/vp8dsp_mips.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/vp8dsp_mmi.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/vp8dsp_mmi.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/vp8dsp_mmi.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/vp8dsp_mmi.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/vp9_idct_msa.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/vp9_idct_msa.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/vp9_idct_msa.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/vp9_idct_msa.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/vp9_intra_msa.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/vp9_intra_msa.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/vp9_intra_msa.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/vp9_intra_msa.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/vp9_lpf_msa.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/vp9_lpf_msa.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/vp9_lpf_msa.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/vp9_lpf_msa.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/vp9_mc_mmi.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/vp9_mc_mmi.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/vp9_mc_mmi.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/vp9_mc_mmi.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/vp9_mc_msa.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/vp9_mc_msa.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/vp9_mc_msa.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/vp9_mc_msa.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/vp9dsp_init_mips.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/vp9dsp_init_mips.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/vp9dsp_init_mips.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/vp9dsp_init_mips.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/vp9dsp_mips.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/vp9dsp_mips.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/vp9dsp_mips.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/vp9dsp_mips.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/wmv2dsp_init_mips.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/wmv2dsp_init_mips.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/wmv2dsp_init_mips.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/wmv2dsp_init_mips.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/wmv2dsp_mips.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/wmv2dsp_mips.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/wmv2dsp_mips.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/wmv2dsp_mips.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/wmv2dsp_mmi.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/wmv2dsp_mmi.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/wmv2dsp_mmi.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/wmv2dsp_mmi.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/xvid_idct_mmi.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/xvid_idct_mmi.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/xvid_idct_mmi.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/xvid_idct_mmi.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/xvididct_init_mips.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/xvididct_init_mips.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/xvididct_init_mips.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/xvididct_init_mips.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mips/xvididct_mips.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/xvididct_mips.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mips/xvididct_mips.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mips/xvididct_mips.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/mjpeg.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mjpeg.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mjpeg.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mjpeg.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/mjpeg2jpeg_bsf.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mjpeg2jpeg_bsf.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mjpeg2jpeg_bsf.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mjpeg2jpeg_bsf.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mjpeg_parser.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mjpeg_parser.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mjpeg_parser.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mjpeg_parser.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mjpega_dump_header_bsf.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mjpega_dump_header_bsf.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mjpega_dump_header_bsf.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mjpega_dump_header_bsf.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mjpegbdec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mjpegbdec.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mjpegbdec.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mjpegbdec.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mjpegdec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mjpegdec.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mjpegdec.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mjpegdec.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mjpegdec.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mjpegdec.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mjpegdec.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mjpegdec.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/mjpegdec_common.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mjpegdec_common.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mjpegdec_common.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mjpegdec_common.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mjpegenc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mjpegenc.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mjpegenc.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mjpegenc.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mjpegenc.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mjpegenc.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mjpegenc.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mjpegenc.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/mjpegenc_common.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mjpegenc_common.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mjpegenc_common.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mjpegenc_common.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mjpegenc_common.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mjpegenc_common.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mjpegenc_common.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mjpegenc_common.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/mjpegenc_huffman.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mjpegenc_huffman.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mjpegenc_huffman.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mjpegenc_huffman.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mjpegenc_huffman.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mjpegenc_huffman.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mjpegenc_huffman.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mjpegenc_huffman.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/mlp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mlp.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mlp.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mlp.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mlp.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mlp.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mlp.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mlp.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/mlp_parse.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mlp_parse.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mlp_parse.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mlp_parse.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mlp_parse.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mlp_parse.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mlp_parse.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mlp_parse.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/mlp_parser.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mlp_parser.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mlp_parser.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mlp_parser.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mlpdec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mlpdec.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mlpdec.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mlpdec.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mlpdsp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mlpdsp.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mlpdsp.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mlpdsp.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mlpdsp.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mlpdsp.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mlpdsp.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mlpdsp.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/mlpenc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mlpenc.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mlpenc.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mlpenc.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mlz.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mlz.c
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rename from mxVision/Ascendffmpeg/libavcodec/mlz.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mlz.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mlz.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mlz.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mlz.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mlz.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/mmaldec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mmaldec.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mmaldec.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mmaldec.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mmvideo.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mmvideo.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/mmvideo.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mmvideo.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mobiclip.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mobiclip.c
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rename from mxVision/Ascendffmpeg/libavcodec/mobiclip.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mobiclip.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/motion_est.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/motion_est.c
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rename from mxVision/Ascendffmpeg/libavcodec/motion_est.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/motion_est.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/motion_est.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/motion_est.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/motion_est.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/motion_est.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/motion_est_template.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/motion_est_template.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/motionpixels.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/motionpixels.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/motionpixels_tablegen.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/motionpixels_tablegen.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/movsub_bsf.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/movsub_bsf.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/movtextdec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/movtextdec.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/movtextenc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/movtextenc.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mp3_header_decompress_bsf.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mp3_header_decompress_bsf.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mpc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mpc.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mpc8.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mpc8.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mpc8huff.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mpc8huff.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mpeg12.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mpeg12.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mpeg12data.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mpeg12data.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mpeg12dec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mpeg12dec.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mpeg12enc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mpeg12enc.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mpeg12framerate.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mpeg12framerate.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mpeg12vlc.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mpeg12vlc.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mpeg2_metadata_bsf.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mpeg2_metadata_bsf.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mpeg4_unpack_bframes_bsf.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mpeg4_unpack_bframes_bsf.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mpeg4audio.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mpeg4audio.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mpeg4audio.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mpeg4audio.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mpeg4data.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mpeg4data.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mpeg4video.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mpeg4video.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mpeg4video.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mpeg4video.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mpeg4video_parser.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mpeg4video_parser.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mpeg4video_parser.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mpeg4video_parser.h
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rename from mxVision/Ascendffmpeg/libavcodec/mpeg4video_parser.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mpeg4videodec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mpeg4videodec.c
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rename from mxVision/Ascendffmpeg/libavcodec/mpeg4videodec.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mpeg4videoenc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mpeg4videoenc.c
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rename from mxVision/Ascendffmpeg/libavcodec/mpeg4videoenc.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mpeg4videoenc.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/mpeg_er.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mpeg_er.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mpeg_er.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mpeg_er.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mpegaudio.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mpegaudio.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mpegaudio_parser.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mpegaudio_parser.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mpegaudio_tablegen.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mpegaudio_tablegen.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mpegaudio_tablegen.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mpegaudio_tablegen.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mpegaudiodata.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mpegaudiodata.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mpegaudiodec_common.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mpegaudiodec_common.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mpegaudiodec_common_tablegen.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mpegaudiodec_common_tablegen.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mpegaudiodec_common_tablegen.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mpegaudiodec_common_tablegen.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mpegaudiodec_fixed.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mpegaudiodec_fixed.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mpegaudiodec_float.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mpegaudiodec_float.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mpegaudiodec_template.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mpegaudiodec_template.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mpegaudiodecheader.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mpegaudiodecheader.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mpegaudiodsp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mpegaudiodsp.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mpegaudiodsp_data.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mpegaudiodsp_data.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mpegaudiodsp_fixed.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mpegaudiodsp_fixed.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mpegaudiodsp_float.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mpegaudiodsp_float.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mpegaudiodsp_template.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mpegaudiodsp_template.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mpegaudioenc_fixed.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mpegaudioenc_fixed.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mpegaudioenc_float.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mpegaudioenc_float.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mpegaudioenc_template.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mpegaudioenc_template.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mpegaudiotab.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mpegaudiotab.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/mpegpicture.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/mpegpicture.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/nvdec_mpeg4.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/nvdec_mpeg4.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/nvdec_vc1.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/nvdec_vc1.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/nvdec_vp8.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/nvdec_vp8.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/nvdec_vp9.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/nvdec_vp9.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/nvenc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/nvenc.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/nvenc_h264.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/nvenc_h264.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/nvenc_hevc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/nvenc_hevc.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/omx.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/omx.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/on2avc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/on2avc.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/on2avcdata.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/on2avcdata.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/on2avcdata.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/on2avcdata.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/options.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/options.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/opus.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/opus.c
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rename from mxVision/Ascendffmpeg/libavcodec/opus.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/opus.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/opus.h
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rename from mxVision/Ascendffmpeg/libavcodec/opus.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/opus_celt.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/opus_celt.c
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rename from mxVision/Ascendffmpeg/libavcodec/opus_celt.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/opus_celt.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/opus_celt.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/opus_metadata_bsf.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/opus_metadata_bsf.c
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rename from mxVision/Ascendffmpeg/libavcodec/opus_metadata_bsf.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/opus_parser.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/opus_parser.c
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rename from mxVision/Ascendffmpeg/libavcodec/opus_parser.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/opus_pvq.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/opus_pvq.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/opus_pvq.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/opus_pvq.h
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/opus_pvq.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/opus_rc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/opus_rc.c
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rename from mxVision/Ascendffmpeg/libavcodec/opus_rc.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/opus_rc.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/opus_rc.h
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rename from mxVision/Ascendffmpeg/libavcodec/opus_rc.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/opus_rc.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/opus_silk.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/opus_silk.c
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/opus_silk.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/opusdec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/opusdec.c
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rename from mxVision/Ascendffmpeg/libavcodec/opusdec.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/opusdec.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/opusdsp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/opusdsp.c
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/opusdsp.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/opusdsp.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/opusdsp.h
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/opusdsp.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/opusenc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/opusenc.c
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rename from mxVision/Ascendffmpeg/libavcodec/opusenc.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/opusenc.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/opusenc.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/opusenc.h
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rename from mxVision/Ascendffmpeg/libavcodec/opusenc.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/opusenc.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/opusenc_psy.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/opusenc_psy.c
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/opusenc_psy.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/opusenc_psy.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/opusenc_psy.h
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/opusenc_psy.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/opusenc_utils.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/opusenc_utils.h
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rename from mxVision/Ascendffmpeg/libavcodec/opusenc_utils.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/opusenc_utils.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/opustab.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/opustab.c
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/opustab.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/opustab.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/opustab.h
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/opustab.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/packet.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/packet.h
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/packet.h
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/packet_internal.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/paf.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/paf.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/pafaudio.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/pafaudio.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/pafvideo.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/pafvideo.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/pamenc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/pamenc.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/parser.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/parser.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/pcm-bluray.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/pcm-bluray.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/pcm-dvd.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/pcm-dvd.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/pcm-dvdenc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/pcm-dvdenc.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/pcm.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/pcm.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/pcm_tablegen.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/pcm_tablegen.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/pcm_tablegen.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/pcm_tablegen.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/pcx.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/pcx.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/pel_template.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/pel_template.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/pgssubdec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/pgssubdec.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/pgxdec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/pgxdec.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/photocd.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/photocd.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/pictordec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/pictordec.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/pixblockdsp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/pixblockdsp.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/pixblockdsp.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/pixblockdsp.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/pixels.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/pixels.h
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/pixlet.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/png.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/png.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/pngdec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/pngdec.c
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/pngdec.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/ppc/mpegaudiodsp_altivec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/ppc/mpegaudiodsp_altivec.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/ppc/mpegvideo_altivec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/ppc/mpegvideo_altivec.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/ppc/mpegvideodsp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/ppc/mpegvideodsp.c
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rename from mxVision/Ascendffmpeg/libavcodec/v210enc.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/v210enc.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/v210enc.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/v210enc.h
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rename from mxVision/Ascendffmpeg/libavcodec/v210enc.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/v210enc.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/v210x.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/v210x.c
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rename from mxVision/Ascendffmpeg/libavcodec/v210x.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/v210x.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/v308dec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/v308dec.c
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rename from mxVision/Ascendffmpeg/libavcodec/v308dec.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/v308dec.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/v308enc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/v308enc.c
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rename from mxVision/Ascendffmpeg/libavcodec/v308enc.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/v308enc.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/v408dec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/v408dec.c
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rename from mxVision/Ascendffmpeg/libavcodec/v408dec.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/v408dec.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/v408enc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/v408enc.c
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rename from mxVision/Ascendffmpeg/libavcodec/v408enc.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/v408enc.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/v410dec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/v410dec.c
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rename from mxVision/Ascendffmpeg/libavcodec/v410dec.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/v410dec.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/v410enc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/v410enc.c
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rename from mxVision/Ascendffmpeg/libavcodec/v410enc.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/v410enc.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/v4l2_buffers.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/v4l2_buffers.c
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rename from mxVision/Ascendffmpeg/libavcodec/v4l2_buffers.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/v4l2_buffers.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/v4l2_buffers.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/v4l2_buffers.h
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rename from mxVision/Ascendffmpeg/libavcodec/v4l2_buffers.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/v4l2_buffers.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/v4l2_context.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/v4l2_context.c
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rename from mxVision/Ascendffmpeg/libavcodec/v4l2_context.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/v4l2_context.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/v4l2_context.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/v4l2_context.h
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rename from mxVision/Ascendffmpeg/libavcodec/v4l2_context.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/v4l2_context.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/v4l2_fmt.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/v4l2_fmt.c
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rename from mxVision/Ascendffmpeg/libavcodec/v4l2_fmt.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/v4l2_fmt.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/v4l2_fmt.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/v4l2_fmt.h
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rename from mxVision/Ascendffmpeg/libavcodec/v4l2_fmt.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/v4l2_fmt.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/v4l2_m2m.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/v4l2_m2m.c
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rename from mxVision/Ascendffmpeg/libavcodec/v4l2_m2m.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/v4l2_m2m.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/v4l2_m2m.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/v4l2_m2m.h
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rename from mxVision/Ascendffmpeg/libavcodec/v4l2_m2m.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/v4l2_m2m.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/v4l2_m2m_dec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/v4l2_m2m_dec.c
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rename from mxVision/Ascendffmpeg/libavcodec/v4l2_m2m_dec.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/v4l2_m2m_dec.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/v4l2_m2m_enc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/v4l2_m2m_enc.c
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rename from mxVision/Ascendffmpeg/libavcodec/v4l2_m2m_enc.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/v4l2_m2m_enc.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vaapi.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vaapi.h
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rename from mxVision/Ascendffmpeg/libavcodec/vaapi.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vaapi.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/vaapi_av1.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vaapi_av1.c
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rename from mxVision/Ascendffmpeg/libavcodec/vaapi_av1.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vaapi_av1.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vaapi_decode.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vaapi_decode.c
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rename from mxVision/Ascendffmpeg/libavcodec/vaapi_decode.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vaapi_decode.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vaapi_decode.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vaapi_decode.h
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rename from mxVision/Ascendffmpeg/libavcodec/vaapi_decode.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vaapi_decode.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/vaapi_encode.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vaapi_encode.c
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rename from mxVision/Ascendffmpeg/libavcodec/vaapi_encode.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vaapi_encode.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vaapi_encode.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vaapi_encode.h
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rename from mxVision/Ascendffmpeg/libavcodec/vaapi_encode.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vaapi_encode.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/vaapi_encode_h264.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vaapi_encode_h264.c
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rename from mxVision/Ascendffmpeg/libavcodec/vaapi_encode_h264.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vaapi_encode_h264.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vaapi_encode_h265.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vaapi_encode_h265.c
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rename from mxVision/Ascendffmpeg/libavcodec/vaapi_encode_h265.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vaapi_encode_h265.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vaapi_encode_mjpeg.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vaapi_encode_mjpeg.c
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rename from mxVision/Ascendffmpeg/libavcodec/vaapi_encode_mjpeg.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vaapi_encode_mjpeg.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vaapi_encode_mpeg2.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vaapi_encode_mpeg2.c
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rename from mxVision/Ascendffmpeg/libavcodec/vaapi_encode_mpeg2.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vaapi_encode_mpeg2.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vaapi_encode_vp8.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vaapi_encode_vp8.c
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rename from mxVision/Ascendffmpeg/libavcodec/vaapi_encode_vp8.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vaapi_encode_vp8.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vaapi_encode_vp9.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vaapi_encode_vp9.c
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rename from mxVision/Ascendffmpeg/libavcodec/vaapi_encode_vp9.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vaapi_encode_vp9.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vaapi_h264.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vaapi_h264.c
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rename from mxVision/Ascendffmpeg/libavcodec/vaapi_h264.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vaapi_h264.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vaapi_hevc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vaapi_hevc.c
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rename from mxVision/Ascendffmpeg/libavcodec/vaapi_hevc.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vaapi_hevc.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vaapi_hevc.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vaapi_hevc.h
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rename from mxVision/Ascendffmpeg/libavcodec/vaapi_hevc.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vaapi_hevc.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/vaapi_mjpeg.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vaapi_mjpeg.c
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rename from mxVision/Ascendffmpeg/libavcodec/vaapi_mjpeg.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vaapi_mjpeg.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vaapi_mpeg2.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vaapi_mpeg2.c
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rename from mxVision/Ascendffmpeg/libavcodec/vaapi_mpeg2.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vaapi_mpeg2.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vaapi_mpeg4.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vaapi_mpeg4.c
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rename from mxVision/Ascendffmpeg/libavcodec/vaapi_mpeg4.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vaapi_mpeg4.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vaapi_vc1.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vaapi_vc1.c
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rename from mxVision/Ascendffmpeg/libavcodec/vaapi_vc1.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vaapi_vc1.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vaapi_vp8.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vaapi_vp8.c
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rename from mxVision/Ascendffmpeg/libavcodec/vaapi_vp8.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vaapi_vp8.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vaapi_vp9.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vaapi_vp9.c
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rename from mxVision/Ascendffmpeg/libavcodec/vaapi_vp9.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vaapi_vp9.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vb.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vb.c
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rename from mxVision/Ascendffmpeg/libavcodec/vb.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vb.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vble.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vble.c
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rename from mxVision/Ascendffmpeg/libavcodec/vble.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vble.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vc1.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vc1.c
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rename from mxVision/Ascendffmpeg/libavcodec/vc1.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vc1.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vc1.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vc1.h
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rename from mxVision/Ascendffmpeg/libavcodec/vc1.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vc1.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/vc1_block.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vc1_block.c
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rename from mxVision/Ascendffmpeg/libavcodec/vc1_block.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/vc1_common.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vc1_common.h
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rename from mxVision/Ascendffmpeg/libavcodec/vc1_common.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/vc1_loopfilter.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vc1_loopfilter.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/vc1_mc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vc1_mc.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/vc1_parser.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vc1_parser.c
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vc1_parser.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vc1_pred.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vc1_pred.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/vc1_pred.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vc1_pred.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/vc1acdata.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vc1acdata.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/vc1data.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vc1data.c
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vc1data.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vc1data.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vc1data.h
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rename from mxVision/Ascendffmpeg/libavcodec/vc1data.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vc1data.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/vc1dec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vc1dec.c
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rename from mxVision/Ascendffmpeg/libavcodec/vc1dec.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vc1dec.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vc1dsp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vc1dsp.c
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vc1dsp.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vc1dsp.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vc1dsp.h
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vc1dsp.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/vc2enc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vc2enc.c
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vc2enc.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vc2enc_dwt.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vc2enc_dwt.c
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rename from mxVision/Ascendffmpeg/libavcodec/vc2enc_dwt.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/vc2enc_dwt.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vc2enc_dwt.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/vcr1.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vcr1.c
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rename from mxVision/Ascendffmpeg/libavcodec/vcr1.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vcr1.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vdpau.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vdpau.c
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vdpau.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vdpau.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vdpau.h
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vdpau.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/vdpau_h264.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vdpau_h264.c
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rename from mxVision/Ascendffmpeg/libavcodec/vdpau_h264.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vdpau_h264.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vdpau_hevc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vdpau_hevc.c
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rename from mxVision/Ascendffmpeg/libavcodec/vdpau_hevc.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vdpau_hevc.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vdpau_internal.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vdpau_internal.h
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rename from mxVision/Ascendffmpeg/libavcodec/vdpau_internal.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vdpau_internal.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/vdpau_mpeg12.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vdpau_mpeg12.c
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rename from mxVision/Ascendffmpeg/libavcodec/vdpau_mpeg12.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vdpau_mpeg12.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vdpau_mpeg4.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vdpau_mpeg4.c
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rename from mxVision/Ascendffmpeg/libavcodec/vdpau_mpeg4.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vdpau_mpeg4.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vdpau_vc1.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vdpau_vc1.c
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rename from mxVision/Ascendffmpeg/libavcodec/vdpau_vc1.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vdpau_vc1.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vdpau_vp9.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vdpau_vp9.c
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rename from mxVision/Ascendffmpeg/libavcodec/vdpau_vp9.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vdpau_vp9.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/version.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/version.h
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rename from mxVision/Ascendffmpeg/libavcodec/version.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/version.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/videodsp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/videodsp.c
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rename from mxVision/Ascendffmpeg/libavcodec/videodsp.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/videodsp.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/videodsp.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/videodsp.h
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rename from mxVision/Ascendffmpeg/libavcodec/videodsp.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/videodsp.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/videodsp_template.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/videodsp_template.c
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rename from mxVision/Ascendffmpeg/libavcodec/videodsp_template.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/videodsp_template.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/videotoolbox.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/videotoolbox.c
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rename from mxVision/Ascendffmpeg/libavcodec/videotoolbox.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/videotoolbox.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/videotoolbox.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/videotoolbox.h
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rename from mxVision/Ascendffmpeg/libavcodec/videotoolbox.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/videotoolbox.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/videotoolboxenc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/videotoolboxenc.c
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rename from mxVision/Ascendffmpeg/libavcodec/videotoolboxenc.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/videotoolboxenc.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vima.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vima.c
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rename from mxVision/Ascendffmpeg/libavcodec/vima.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vima.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vlc.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vlc.h
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rename from mxVision/Ascendffmpeg/libavcodec/vlc.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vlc.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/vmdaudio.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vmdaudio.c
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rename from mxVision/Ascendffmpeg/libavcodec/vmdaudio.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vmdaudio.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vmdvideo.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vmdvideo.c
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rename from mxVision/Ascendffmpeg/libavcodec/vmdvideo.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vmdvideo.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vmnc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vmnc.c
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rename from mxVision/Ascendffmpeg/libavcodec/vmnc.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vmnc.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vorbis.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vorbis.c
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rename from mxVision/Ascendffmpeg/libavcodec/vorbis.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vorbis.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vorbis.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vorbis.h
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rename from mxVision/Ascendffmpeg/libavcodec/vorbis.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vorbis.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/vorbis_data.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vorbis_data.c
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rename from mxVision/Ascendffmpeg/libavcodec/vorbis_data.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vorbis_data.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vorbis_enc_data.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vorbis_enc_data.h
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rename from mxVision/Ascendffmpeg/libavcodec/vorbis_enc_data.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vorbis_enc_data.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/vorbis_parser.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vorbis_parser.c
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rename from mxVision/Ascendffmpeg/libavcodec/vorbis_parser.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vorbis_parser.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vorbis_parser.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vorbis_parser.h
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rename from mxVision/Ascendffmpeg/libavcodec/vorbis_parser.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vorbis_parser.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/vorbis_parser_internal.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vorbis_parser_internal.h
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rename from mxVision/Ascendffmpeg/libavcodec/vorbis_parser_internal.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vorbis_parser_internal.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/vorbisdec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vorbisdec.c
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rename from mxVision/Ascendffmpeg/libavcodec/vorbisdec.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vorbisdec.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vorbisdsp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vorbisdsp.c
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rename from mxVision/Ascendffmpeg/libavcodec/vorbisdsp.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vorbisdsp.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vorbisdsp.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vorbisdsp.h
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rename from mxVision/Ascendffmpeg/libavcodec/vorbisdsp.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vorbisdsp.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/vorbisenc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vorbisenc.c
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rename from mxVision/Ascendffmpeg/libavcodec/vorbisenc.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vorbisenc.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vp3.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp3.c
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rename from mxVision/Ascendffmpeg/libavcodec/vp3.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp3.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vp3_parser.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp3_parser.c
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rename from mxVision/Ascendffmpeg/libavcodec/vp3_parser.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp3_parser.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vp3data.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp3data.h
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rename from mxVision/Ascendffmpeg/libavcodec/vp3data.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp3data.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/vp3dsp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp3dsp.c
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rename from mxVision/Ascendffmpeg/libavcodec/vp3dsp.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp3dsp.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vp3dsp.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp3dsp.h
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rename from mxVision/Ascendffmpeg/libavcodec/vp3dsp.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp3dsp.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/vp4data.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp4data.h
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rename from mxVision/Ascendffmpeg/libavcodec/vp4data.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp4data.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/vp5.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp5.c
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rename from mxVision/Ascendffmpeg/libavcodec/vp5.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp5.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vp56.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp56.c
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rename from mxVision/Ascendffmpeg/libavcodec/vp56.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp56.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vp56.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp56.h
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rename from mxVision/Ascendffmpeg/libavcodec/vp56.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp56.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/vp56data.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp56data.c
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rename from mxVision/Ascendffmpeg/libavcodec/vp56data.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp56data.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vp56data.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp56data.h
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rename from mxVision/Ascendffmpeg/libavcodec/vp56data.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp56data.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/vp56dsp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp56dsp.c
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rename from mxVision/Ascendffmpeg/libavcodec/vp56dsp.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp56dsp.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vp56dsp.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp56dsp.h
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rename from mxVision/Ascendffmpeg/libavcodec/vp56dsp.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp56dsp.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/vp56rac.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp56rac.c
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rename from mxVision/Ascendffmpeg/libavcodec/vp56rac.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp56rac.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vp5data.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp5data.h
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rename from mxVision/Ascendffmpeg/libavcodec/vp5data.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp5data.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/vp6.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp6.c
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rename from mxVision/Ascendffmpeg/libavcodec/vp6.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp6.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vp6data.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp6data.h
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rename from mxVision/Ascendffmpeg/libavcodec/vp6data.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp6data.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/vp6dsp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp6dsp.c
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rename from mxVision/Ascendffmpeg/libavcodec/vp6dsp.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp6dsp.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vp8.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp8.c
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rename from mxVision/Ascendffmpeg/libavcodec/vp8.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp8.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vp8.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp8.h
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rename from mxVision/Ascendffmpeg/libavcodec/vp8.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp8.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/vp8_parser.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp8_parser.c
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rename from mxVision/Ascendffmpeg/libavcodec/vp8_parser.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp8_parser.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vp8data.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp8data.h
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rename from mxVision/Ascendffmpeg/libavcodec/vp8data.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp8data.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/vp8dsp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp8dsp.c
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rename from mxVision/Ascendffmpeg/libavcodec/vp8dsp.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp8dsp.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vp8dsp.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp8dsp.h
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rename from mxVision/Ascendffmpeg/libavcodec/vp8dsp.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp8dsp.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/vp9.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp9.c
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rename from mxVision/Ascendffmpeg/libavcodec/vp9.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp9.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vp9.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp9.h
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rename from mxVision/Ascendffmpeg/libavcodec/vp9.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp9.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/vp9_mc_template.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp9_mc_template.c
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rename from mxVision/Ascendffmpeg/libavcodec/vp9_mc_template.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp9_mc_template.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vp9_metadata_bsf.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp9_metadata_bsf.c
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rename from mxVision/Ascendffmpeg/libavcodec/vp9_metadata_bsf.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp9_metadata_bsf.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vp9_parser.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp9_parser.c
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rename from mxVision/Ascendffmpeg/libavcodec/vp9_parser.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp9_parser.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vp9_raw_reorder_bsf.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp9_raw_reorder_bsf.c
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rename from mxVision/Ascendffmpeg/libavcodec/vp9_raw_reorder_bsf.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp9_raw_reorder_bsf.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vp9_superframe_bsf.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp9_superframe_bsf.c
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rename from mxVision/Ascendffmpeg/libavcodec/vp9_superframe_bsf.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp9_superframe_bsf.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vp9_superframe_split_bsf.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp9_superframe_split_bsf.c
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rename from mxVision/Ascendffmpeg/libavcodec/vp9_superframe_split_bsf.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp9_superframe_split_bsf.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vp9block.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp9block.c
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rename from mxVision/Ascendffmpeg/libavcodec/vp9block.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp9block.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vp9data.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp9data.c
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rename from mxVision/Ascendffmpeg/libavcodec/vp9data.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp9data.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vp9data.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp9data.h
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rename from mxVision/Ascendffmpeg/libavcodec/vp9data.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp9data.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/vp9dec.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp9dec.h
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rename from mxVision/Ascendffmpeg/libavcodec/vp9dec.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp9dec.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/vp9dsp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp9dsp.c
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rename from mxVision/Ascendffmpeg/libavcodec/vp9dsp.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp9dsp.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vp9dsp.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp9dsp.h
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rename from mxVision/Ascendffmpeg/libavcodec/vp9dsp.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp9dsp.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/vp9dsp_10bpp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp9dsp_10bpp.c
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rename from mxVision/Ascendffmpeg/libavcodec/vp9dsp_10bpp.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp9dsp_10bpp.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vp9dsp_12bpp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp9dsp_12bpp.c
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rename from mxVision/Ascendffmpeg/libavcodec/vp9dsp_12bpp.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp9dsp_12bpp.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/vp9dsp_8bpp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp9dsp_8bpp.c
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rename from mxVision/Ascendffmpeg/libavcodec/vp9dsp_8bpp.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/vp9dsp_template.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp9dsp_template.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/vp9lpf.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp9lpf.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/vp9mvs.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp9mvs.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/vp9prob.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp9prob.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/vp9recon.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp9recon.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/vp9shared.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp9shared.h
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rename from mxVision/Ascendffmpeg/libavcodec/vp9shared.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vp9shared.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/vqavideo.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vqavideo.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/vt_internal.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/vt_internal.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/wavpack.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/wavpack.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/wavpack.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/wavpack.h
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/wavpack.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/wavpackdata.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/wavpackdata.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/wavpackenc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/wavpackenc.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/wavpackenc.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/wavpackenc.h
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rename from mxVision/Ascendffmpeg/libavcodec/wavpackenc.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/wavpackenc.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/wcmv.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/wcmv.c
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/wcmv.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/webp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/webp.c
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rename from mxVision/Ascendffmpeg/libavcodec/webp.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/webp_parser.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/webp_parser.c
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rename from mxVision/Ascendffmpeg/libavcodec/webp_parser.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/webvttdec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/webvttdec.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/webvttenc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/webvttenc.c
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rename from mxVision/Ascendffmpeg/libavcodec/webvttenc.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/webvttenc.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/wma.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/wma.c
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rename from mxVision/Ascendffmpeg/libavcodec/wma.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/wma.c
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/wma.h
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/wma_common.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/wma_common.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/wma_common.h
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/wma_common.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/wma_freqs.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/wma_freqs.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/wma_freqs.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/wma_freqs.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/wmadata.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/wmadata.h
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/wmadata.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/wmadec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/wmadec.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/wmaenc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/wmaenc.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/wmalosslessdec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/wmalosslessdec.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/wmaprodata.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/wmaprodata.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/wmaprodec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/wmaprodec.c
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/wmaprodec.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/wmavoice.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/wmavoice.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/wmavoice_data.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/wmavoice_data.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/wmv2.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/wmv2.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/wmv2.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/wmv2.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/wmv2data.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/wmv2data.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/wmv2data.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/wmv2data.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/wmv2dec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/wmv2dec.c
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/wmv2dec.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/wmv2dsp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/wmv2dsp.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/wmv2dsp.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/wmv2dsp.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/wmv2enc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/wmv2enc.c
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/wmv2enc.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/wnv1.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/wnv1.c
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/wnv1.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/wrapped_avframe.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/wrapped_avframe.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/ws-snd1.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/ws-snd1.c
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/ws-snd1.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/Makefile b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/Makefile
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/Makefile
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/aacencdsp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/aacencdsp.asm
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rename from mxVision/Ascendffmpeg/libavcodec/x86/aacencdsp.asm
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diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/aacencdsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/aacencdsp_init.c
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rename from mxVision/Ascendffmpeg/libavcodec/x86/aacencdsp_init.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/aacpsdsp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/aacpsdsp.asm
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rename from mxVision/Ascendffmpeg/libavcodec/x86/aacpsdsp.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/aacpsdsp.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/aacpsdsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/aacpsdsp_init.c
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rename from mxVision/Ascendffmpeg/libavcodec/x86/aacpsdsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/aacpsdsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/ac3dsp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/ac3dsp.asm
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rename from mxVision/Ascendffmpeg/libavcodec/x86/ac3dsp.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/ac3dsp.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/ac3dsp_downmix.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/ac3dsp_downmix.asm
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rename from mxVision/Ascendffmpeg/libavcodec/x86/ac3dsp_downmix.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/ac3dsp_downmix.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/ac3dsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/ac3dsp_init.c
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rename from mxVision/Ascendffmpeg/libavcodec/x86/ac3dsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/ac3dsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/alacdsp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/alacdsp.asm
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rename from mxVision/Ascendffmpeg/libavcodec/x86/alacdsp.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/alacdsp.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/alacdsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/alacdsp_init.c
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rename from mxVision/Ascendffmpeg/libavcodec/x86/alacdsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/alacdsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/audiodsp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/audiodsp.asm
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diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/audiodsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/audiodsp_init.c
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rename from mxVision/Ascendffmpeg/libavcodec/x86/audiodsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/audiodsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/blockdsp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/blockdsp.asm
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/blockdsp.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/blockdsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/blockdsp_init.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/bswapdsp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/bswapdsp.asm
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rename from mxVision/Ascendffmpeg/libavcodec/x86/bswapdsp.asm
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diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/bswapdsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/bswapdsp_init.c
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rename from mxVision/Ascendffmpeg/libavcodec/x86/bswapdsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/bswapdsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/cabac.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/cabac.h
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diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/cavsdsp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/cavsdsp.c
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diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/cavsidct.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/cavsidct.asm
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rename from mxVision/Ascendffmpeg/libavcodec/x86/cavsidct.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/cavsidct.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/celt_pvq_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/celt_pvq_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/celt_pvq_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/celt_pvq_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/celt_pvq_search.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/celt_pvq_search.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/celt_pvq_search.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/celt_pvq_search.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/cfhddsp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/cfhddsp.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/cfhddsp.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/cfhddsp.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/cfhddsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/cfhddsp_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/cfhddsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/cfhddsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/cfhdencdsp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/cfhdencdsp.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/cfhdencdsp.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/cfhdencdsp.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/cfhdencdsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/cfhdencdsp_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/cfhdencdsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/cfhdencdsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/constants.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/constants.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/constants.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/constants.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/constants.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/constants.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/constants.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/constants.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/dcadsp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/dcadsp.asm
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rename from mxVision/Ascendffmpeg/libavcodec/x86/dcadsp.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/dcadsp.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/dcadsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/dcadsp_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/dcadsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/dcadsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/dct32.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/dct32.asm
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rename from mxVision/Ascendffmpeg/libavcodec/x86/dct32.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/dct32.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/dct_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/dct_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/dct_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/dct_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/dirac_dwt.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/dirac_dwt.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/dirac_dwt.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/dirac_dwt.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/dirac_dwt_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/dirac_dwt_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/dirac_dwt_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/dirac_dwt_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/diracdsp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/diracdsp.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/diracdsp.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/diracdsp.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/diracdsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/diracdsp_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/diracdsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/diracdsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/dnxhdenc.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/dnxhdenc.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/dnxhdenc.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/dnxhdenc.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/dnxhdenc_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/dnxhdenc_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/dnxhdenc_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/dnxhdenc_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/exrdsp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/exrdsp.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/exrdsp.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/exrdsp.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/exrdsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/exrdsp_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/exrdsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/exrdsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/fdct.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/fdct.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/fdct.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/fdct.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/fdct.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/fdct.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/fdct.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/fdct.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/fdctdsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/fdctdsp_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/fdctdsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/fdctdsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/fft.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/fft.asm
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rename from mxVision/Ascendffmpeg/libavcodec/x86/fft.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/fft.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/fft.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/fft.h
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rename from mxVision/Ascendffmpeg/libavcodec/x86/fft.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/fft.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/fft_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/fft_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/fft_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/fft_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/flac_dsp_gpl.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/flac_dsp_gpl.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/flac_dsp_gpl.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/flac_dsp_gpl.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/flacdsp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/flacdsp.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/flacdsp.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/flacdsp.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/flacdsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/flacdsp_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/flacdsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/flacdsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/fmtconvert.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/fmtconvert.asm
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rename from mxVision/Ascendffmpeg/libavcodec/x86/fmtconvert.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/fmtconvert.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/fmtconvert_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/fmtconvert_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/fmtconvert_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/fmtconvert_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/fpel.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/fpel.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/fpel.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/fpel.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/fpel.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/fpel.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/fpel.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/fpel.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/g722dsp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/g722dsp.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/g722dsp.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/g722dsp.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/g722dsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/g722dsp_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/g722dsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/g722dsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/h263_loopfilter.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/h263_loopfilter.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/h263_loopfilter.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/h263_loopfilter.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/h263dsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/h263dsp_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/h263dsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/h263dsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/h264_cabac.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/h264_cabac.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/h264_cabac.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/h264_cabac.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/h264_chromamc.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/h264_chromamc.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/h264_chromamc.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/h264_chromamc.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/h264_chromamc_10bit.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/h264_chromamc_10bit.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/h264_chromamc_10bit.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/h264_chromamc_10bit.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/h264_deblock.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/h264_deblock.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/h264_deblock.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/h264_deblock.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/h264_deblock_10bit.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/h264_deblock_10bit.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/h264_deblock_10bit.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/h264_deblock_10bit.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/h264_idct.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/h264_idct.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/h264_idct.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/h264_idct.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/h264_idct_10bit.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/h264_idct_10bit.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/h264_idct_10bit.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/h264_idct_10bit.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/h264_intrapred.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/h264_intrapred.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/h264_intrapred.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/h264_intrapred.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/h264_intrapred_10bit.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/h264_intrapred_10bit.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/h264_intrapred_10bit.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/h264_intrapred_10bit.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/h264_intrapred_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/h264_intrapred_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/h264_intrapred_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/h264_intrapred_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/h264_qpel.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/h264_qpel.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/h264_qpel.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/h264_qpel.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/h264_qpel_10bit.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/h264_qpel_10bit.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/h264_qpel_10bit.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/h264_qpel_10bit.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/h264_qpel_8bit.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/h264_qpel_8bit.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/h264_qpel_8bit.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/h264_qpel_8bit.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/h264_weight.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/h264_weight.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/h264_weight.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/h264_weight.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/h264_weight_10bit.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/h264_weight_10bit.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/h264_weight_10bit.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/h264_weight_10bit.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/h264chroma_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/h264chroma_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/h264chroma_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/h264chroma_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/h264dsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/h264dsp_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/h264dsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/h264dsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/hevc_add_res.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/hevc_add_res.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/hevc_add_res.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/hevc_add_res.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/hevc_deblock.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/hevc_deblock.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/hevc_deblock.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/hevc_deblock.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/hevc_idct.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/hevc_idct.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/hevc_idct.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/hevc_idct.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/hevc_mc.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/hevc_mc.asm
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rename from mxVision/Ascendffmpeg/libavcodec/x86/hevc_mc.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/hevc_mc.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/hevc_sao.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/hevc_sao.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/hevc_sao.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/hevc_sao.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/hevc_sao_10bit.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/hevc_sao_10bit.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/hevc_sao_10bit.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/hevc_sao_10bit.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/hevcdsp.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/hevcdsp.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/hevcdsp.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/hevcdsp.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/hevcdsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/hevcdsp_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/hevcdsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/hevcdsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/hpeldsp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/hpeldsp.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/hpeldsp.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/hpeldsp.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/hpeldsp.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/hpeldsp.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/hpeldsp.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/hpeldsp.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/hpeldsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/hpeldsp_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/hpeldsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/hpeldsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/hpeldsp_rnd_template.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/hpeldsp_rnd_template.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/hpeldsp_rnd_template.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/hpeldsp_rnd_template.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/hpeldsp_vp3.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/hpeldsp_vp3.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/hpeldsp_vp3.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/hpeldsp_vp3.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/hpeldsp_vp3_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/hpeldsp_vp3_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/hpeldsp_vp3_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/hpeldsp_vp3_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/huffyuvdsp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/huffyuvdsp.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/huffyuvdsp.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/huffyuvdsp.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/huffyuvdsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/huffyuvdsp_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/huffyuvdsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/huffyuvdsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/huffyuvdsp_template.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/huffyuvdsp_template.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/huffyuvdsp_template.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/huffyuvdsp_template.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/huffyuvencdsp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/huffyuvencdsp.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/huffyuvencdsp.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/huffyuvencdsp.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/huffyuvencdsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/huffyuvencdsp_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/huffyuvencdsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/huffyuvencdsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/idctdsp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/idctdsp.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/idctdsp.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/idctdsp.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/idctdsp.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/idctdsp.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/idctdsp.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/idctdsp.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/idctdsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/idctdsp_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/idctdsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/idctdsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/imdct36.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/imdct36.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/imdct36.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/imdct36.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/inline_asm.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/inline_asm.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/inline_asm.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/inline_asm.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/jpeg2000dsp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/jpeg2000dsp.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/jpeg2000dsp.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/jpeg2000dsp.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/jpeg2000dsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/jpeg2000dsp_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/jpeg2000dsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/jpeg2000dsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/lossless_audiodsp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/lossless_audiodsp.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/lossless_audiodsp.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/lossless_audiodsp.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/lossless_audiodsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/lossless_audiodsp_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/lossless_audiodsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/lossless_audiodsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/lossless_videodsp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/lossless_videodsp.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/lossless_videodsp.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/lossless_videodsp.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/lossless_videodsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/lossless_videodsp_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/lossless_videodsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/lossless_videodsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/lossless_videoencdsp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/lossless_videoencdsp.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/lossless_videoencdsp.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/lossless_videoencdsp.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/lossless_videoencdsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/lossless_videoencdsp_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/lossless_videoencdsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/lossless_videoencdsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/lpc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/lpc.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/lpc.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/lpc.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/mathops.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/mathops.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/mathops.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/mathops.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/mdct15.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/mdct15.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/mdct15.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/mdct15.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/mdct15_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/mdct15_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/mdct15_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/mdct15_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/me_cmp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/me_cmp.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/me_cmp.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/me_cmp.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/me_cmp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/me_cmp_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/me_cmp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/me_cmp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/mlpdsp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/mlpdsp.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/mlpdsp.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/mlpdsp.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/mlpdsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/mlpdsp_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/mlpdsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/mlpdsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/mpegaudiodsp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/mpegaudiodsp.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/mpegaudiodsp.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/mpegaudiodsp.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/mpegvideo.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/mpegvideo.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/mpegvideo.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/mpegvideo.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/mpegvideodsp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/mpegvideodsp.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/mpegvideodsp.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/mpegvideodsp.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/mpegvideoenc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/mpegvideoenc.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/mpegvideoenc.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/mpegvideoenc.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/mpegvideoenc_qns_template.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/mpegvideoenc_qns_template.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/mpegvideoenc_qns_template.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/mpegvideoenc_qns_template.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/mpegvideoenc_template.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/mpegvideoenc_template.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/mpegvideoenc_template.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/mpegvideoenc_template.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/mpegvideoencdsp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/mpegvideoencdsp.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/mpegvideoencdsp.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/mpegvideoencdsp.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/mpegvideoencdsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/mpegvideoencdsp_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/mpegvideoencdsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/mpegvideoencdsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/opusdsp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/opusdsp.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/opusdsp.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/opusdsp.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/opusdsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/opusdsp_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/opusdsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/opusdsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/pixblockdsp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/pixblockdsp.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/pixblockdsp.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/pixblockdsp.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/pixblockdsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/pixblockdsp_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/pixblockdsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/pixblockdsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/pngdsp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/pngdsp.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/pngdsp.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/pngdsp.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/pngdsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/pngdsp_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/pngdsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/pngdsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/proresdsp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/proresdsp.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/proresdsp.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/proresdsp.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/proresdsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/proresdsp_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/proresdsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/proresdsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/qpel.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/qpel.asm
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rename from mxVision/Ascendffmpeg/libavcodec/x86/qpel.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/qpel.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/qpeldsp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/qpeldsp.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/qpeldsp.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/qpeldsp.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/qpeldsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/qpeldsp_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/qpeldsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/qpeldsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/rnd_template.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/rnd_template.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/rnd_template.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/rnd_template.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/rv34dsp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/rv34dsp.asm
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rename from mxVision/Ascendffmpeg/libavcodec/x86/rv34dsp.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/rv34dsp.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/rv34dsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/rv34dsp_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/rv34dsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/rv34dsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/rv40dsp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/rv40dsp.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/rv40dsp.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/rv40dsp.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/rv40dsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/rv40dsp_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/rv40dsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/rv40dsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/sbcdsp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/sbcdsp.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/sbcdsp.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/sbcdsp.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/sbcdsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/sbcdsp_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/sbcdsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/sbcdsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/sbrdsp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/sbrdsp.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/sbrdsp.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/sbrdsp.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/sbrdsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/sbrdsp_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/sbrdsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/sbrdsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/simple_idct.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/simple_idct.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/simple_idct.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/simple_idct.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/simple_idct.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/simple_idct.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/simple_idct.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/simple_idct.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/simple_idct10.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/simple_idct10.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/simple_idct10.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/simple_idct10.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/simple_idct10_template.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/simple_idct10_template.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/simple_idct10_template.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/simple_idct10_template.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/snowdsp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/snowdsp.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/snowdsp.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/snowdsp.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/svq1enc.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/svq1enc.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/svq1enc.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/svq1enc.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/svq1enc_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/svq1enc_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/svq1enc_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/svq1enc_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/synth_filter.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/synth_filter.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/synth_filter.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/synth_filter.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/synth_filter_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/synth_filter_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/synth_filter_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/synth_filter_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/takdsp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/takdsp.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/takdsp.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/takdsp.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/takdsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/takdsp_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/takdsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/takdsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/ttadsp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/ttadsp.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/ttadsp.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/ttadsp.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/ttadsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/ttadsp_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/ttadsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/ttadsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/ttaencdsp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/ttaencdsp.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/ttaencdsp.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/ttaencdsp.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/ttaencdsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/ttaencdsp_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/ttaencdsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/ttaencdsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/utvideodsp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/utvideodsp.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/utvideodsp.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/utvideodsp.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/utvideodsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/utvideodsp_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/utvideodsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/utvideodsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/v210-init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/v210-init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/v210-init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/v210-init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/v210.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/v210.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/v210.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/v210.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/v210enc.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/v210enc.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/v210enc.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/v210enc.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/v210enc_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/v210enc_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/v210enc_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/v210enc_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/vc1dsp.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vc1dsp.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/vc1dsp.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vc1dsp.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/vc1dsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vc1dsp_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/vc1dsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vc1dsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/vc1dsp_loopfilter.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vc1dsp_loopfilter.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/vc1dsp_loopfilter.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vc1dsp_loopfilter.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/vc1dsp_mc.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vc1dsp_mc.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/vc1dsp_mc.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vc1dsp_mc.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/vc1dsp_mmx.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vc1dsp_mmx.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/vc1dsp_mmx.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vc1dsp_mmx.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/videodsp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/videodsp.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/videodsp.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/videodsp.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/videodsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/videodsp_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/videodsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/videodsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/vorbisdsp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vorbisdsp.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/vorbisdsp.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vorbisdsp.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/vorbisdsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vorbisdsp_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/vorbisdsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vorbisdsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/vp3dsp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vp3dsp.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/vp3dsp.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vp3dsp.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/vp3dsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vp3dsp_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/vp3dsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vp3dsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/vp56_arith.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vp56_arith.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/vp56_arith.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vp56_arith.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/vp6dsp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vp6dsp.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/vp6dsp.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vp6dsp.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/vp6dsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vp6dsp_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/vp6dsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vp6dsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/vp8dsp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vp8dsp.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/vp8dsp.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vp8dsp.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/vp8dsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vp8dsp_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/vp8dsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vp8dsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/vp8dsp_loopfilter.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vp8dsp_loopfilter.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/vp8dsp_loopfilter.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vp8dsp_loopfilter.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/vp9dsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vp9dsp_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/vp9dsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vp9dsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/vp9dsp_init.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vp9dsp_init.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/vp9dsp_init.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vp9dsp_init.h
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/vp9dsp_init_10bpp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vp9dsp_init_10bpp.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/vp9dsp_init_10bpp.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vp9dsp_init_10bpp.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/vp9dsp_init_12bpp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vp9dsp_init_12bpp.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/vp9dsp_init_12bpp.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vp9dsp_init_12bpp.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/vp9dsp_init_16bpp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vp9dsp_init_16bpp.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/vp9dsp_init_16bpp.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vp9dsp_init_16bpp.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/vp9dsp_init_16bpp_template.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vp9dsp_init_16bpp_template.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/vp9dsp_init_16bpp_template.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vp9dsp_init_16bpp_template.c
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/vp9intrapred.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vp9intrapred.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/vp9intrapred.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vp9intrapred.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/vp9intrapred_16bpp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vp9intrapred_16bpp.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/vp9intrapred_16bpp.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vp9intrapred_16bpp.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/vp9itxfm.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vp9itxfm.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/vp9itxfm.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vp9itxfm.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/vp9itxfm_16bpp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vp9itxfm_16bpp.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/vp9itxfm_16bpp.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vp9itxfm_16bpp.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/vp9itxfm_template.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vp9itxfm_template.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/vp9itxfm_template.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vp9itxfm_template.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/vp9lpf.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vp9lpf.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/vp9lpf.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vp9lpf.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/vp9lpf_16bpp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vp9lpf_16bpp.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/vp9lpf_16bpp.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vp9lpf_16bpp.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/vp9mc.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vp9mc.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavcodec/x86/vp9mc.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vp9mc.asm
diff --git a/mxVision/Ascendffmpeg/libavcodec/x86/vp9mc_16bpp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavcodec/x86/vp9mc_16bpp.asm
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_agate.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_agate.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_amerge.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_amerge.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_amix.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_amix.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_amultiply.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_amultiply.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_anequalizer.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_anequalizer.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_anlmdn.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_anlmdn.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_anlmdndsp.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_anlmdndsp.h
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_anlms.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_anlms.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_apulsator.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_apulsator.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_arnndn.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_arnndn.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_asetnsamples.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_asetnsamples.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_ashowinfo.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_ashowinfo.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_asoftclip.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_asoftclip.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_asubboost.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_asubboost.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_asupercut.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_asupercut.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_atempo.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_atempo.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_axcorrelate.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_axcorrelate.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_biquads.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_biquads.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_bs2b.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_bs2b.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_channelmap.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_channelmap.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_channelsplit.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_channelsplit.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_chorus.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_chorus.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_compand.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_compand.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_compensationdelay.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_compensationdelay.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_crossfeed.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_crossfeed.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_crystalizer.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_crystalizer.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_dcshift.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_dcshift.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_deesser.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_deesser.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_drmeter.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_drmeter.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_dynaudnorm.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_dynaudnorm.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_earwax.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_earwax.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_extrastereo.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_extrastereo.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_firequalizer.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_firequalizer.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_flanger.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_flanger.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_haas.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_haas.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_hdcd.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_hdcd.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_headphone.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_headphone.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_ladspa.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_ladspa.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_lv2.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_lv2.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_pan.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_pan.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_replaygain.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_replaygain.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_rubberband.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_rubberband.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_sidechaincompress.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_sidechaincompress.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_silencedetect.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_silencedetect.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_sofalizer.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_sofalizer.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_speechnorm.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_speechnorm.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_stereotools.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_stereotools.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/af_tremolo.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/af_tremolo.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/allfilters.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/allfilters.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/asrc_afirsrc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/asrc_afirsrc.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/asrc_anoisesrc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/asrc_anoisesrc.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/asrc_flite.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/asrc_flite.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/asrc_hilbert.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/asrc_hilbert.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/asrc_sinc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/asrc_sinc.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/asrc_sine.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/asrc_sine.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/atadenoise.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/atadenoise.h
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diff --git a/mxVision/Ascendffmpeg/libavfilter/audio.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/audio.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/avf_abitscope.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/avf_abitscope.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/avf_ahistogram.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/avf_ahistogram.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/avf_aphasemeter.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/avf_aphasemeter.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/avf_avectorscope.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/avf_avectorscope.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/avf_concat.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/avf_concat.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/avf_showcqt.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/avf_showcqt.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/avf_showcqt.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/avf_showcqt.h
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diff --git a/mxVision/Ascendffmpeg/libavfilter/avf_showfreqs.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/avf_showfreqs.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/avf_showspatial.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/avf_showspatial.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/avf_showspectrum.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/avf_showspectrum.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/avf_showvolume.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/avf_showvolume.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/avf_showwaves.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/avf_showwaves.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/avfilter.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/avfilter.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/avfilter.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/avfilter.h
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diff --git a/mxVision/Ascendffmpeg/libavfilter/avfiltergraph.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/avfiltergraph.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/avfilterres.rc b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/avfilterres.rc
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diff --git a/mxVision/Ascendffmpeg/libavfilter/bbox.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/bbox.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/blend.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/blend.h
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diff --git a/mxVision/Ascendffmpeg/libavfilter/boxblur.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/boxblur.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/bufferqueue.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/bufferqueue.h
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diff --git a/mxVision/Ascendffmpeg/libavfilter/bwdif.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/bwdif.h
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diff --git a/mxVision/Ascendffmpeg/libavfilter/colorspace.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/colorspace.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/colorspacedsp_yuv2yuv_template.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/colorspacedsp_yuv2yuv_template.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/convolution.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/convolution.h
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diff --git a/mxVision/Ascendffmpeg/libavfilter/cuda/vector_helpers.cuh b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/cuda/vector_helpers.cuh
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diff --git a/mxVision/Ascendffmpeg/libavfilter/deshake.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/deshake.h
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diff --git a/mxVision/Ascendffmpeg/libavfilter/dnn/Makefile b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/dnn/Makefile
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diff --git a/mxVision/Ascendffmpeg/libavfilter/dnn/dnn_backend_native.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/dnn/dnn_backend_native.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/dnn/dnn_backend_native.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/dnn/dnn_backend_native.h
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diff --git a/mxVision/Ascendffmpeg/libavfilter/dnn/dnn_backend_native_layer_avgpool.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/dnn/dnn_backend_native_layer_avgpool.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/dnn/dnn_backend_native_layer_avgpool.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/dnn/dnn_backend_native_layer_avgpool.h
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diff --git a/mxVision/Ascendffmpeg/libavfilter/dnn/dnn_backend_native_layer_conv2d.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/dnn/dnn_backend_native_layer_conv2d.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/dnn/dnn_backend_native_layer_conv2d.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/dnn/dnn_backend_native_layer_conv2d.h
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diff --git a/mxVision/Ascendffmpeg/libavfilter/dnn/dnn_backend_native_layer_dense.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/dnn/dnn_backend_native_layer_dense.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/dnn/dnn_backend_native_layer_dense.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/dnn/dnn_backend_native_layer_dense.h
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diff --git a/mxVision/Ascendffmpeg/libavfilter/dnn/dnn_backend_native_layer_depth2space.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/dnn/dnn_backend_native_layer_depth2space.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/dnn/dnn_backend_native_layer_depth2space.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/dnn/dnn_backend_native_layer_depth2space.h
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diff --git a/mxVision/Ascendffmpeg/libavfilter/dnn/dnn_backend_native_layer_mathbinary.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/dnn/dnn_backend_native_layer_mathbinary.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/dnn/dnn_backend_native_layer_mathbinary.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/dnn/dnn_backend_native_layer_mathbinary.h
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rename from mxVision/Ascendffmpeg/libavfilter/dnn/dnn_backend_native_layer_mathbinary.h
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diff --git a/mxVision/Ascendffmpeg/libavfilter/dnn/dnn_backend_native_layer_mathunary.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/dnn/dnn_backend_native_layer_mathunary.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/dnn/dnn_backend_native_layer_mathunary.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/dnn/dnn_backend_native_layer_mathunary.h
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rename from mxVision/Ascendffmpeg/libavfilter/dnn/dnn_backend_native_layer_mathunary.h
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diff --git a/mxVision/Ascendffmpeg/libavfilter/dnn/dnn_backend_native_layer_maximum.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/dnn/dnn_backend_native_layer_maximum.c
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rename from mxVision/Ascendffmpeg/libavfilter/dnn/dnn_backend_native_layer_maximum.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/dnn/dnn_backend_native_layer_maximum.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/dnn/dnn_backend_native_layer_maximum.h
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rename from mxVision/Ascendffmpeg/libavfilter/dnn/dnn_backend_native_layer_maximum.h
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diff --git a/mxVision/Ascendffmpeg/libavfilter/dnn/dnn_backend_native_layer_pad.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/dnn/dnn_backend_native_layer_pad.c
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rename from mxVision/Ascendffmpeg/libavfilter/dnn/dnn_backend_native_layer_pad.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/dnn/dnn_backend_native_layer_pad.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/dnn/dnn_backend_native_layer_pad.h
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rename from mxVision/Ascendffmpeg/libavfilter/dnn/dnn_backend_native_layer_pad.h
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diff --git a/mxVision/Ascendffmpeg/libavfilter/dnn/dnn_backend_native_layers.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/dnn/dnn_backend_native_layers.c
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rename from mxVision/Ascendffmpeg/libavfilter/dnn/dnn_backend_native_layers.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/dnn/dnn_backend_native_layers.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/dnn/dnn_backend_native_layers.h
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rename from mxVision/Ascendffmpeg/libavfilter/dnn/dnn_backend_native_layers.h
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diff --git a/mxVision/Ascendffmpeg/libavfilter/dnn/dnn_backend_openvino.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/dnn/dnn_backend_openvino.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/dnn/dnn_backend_openvino.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/dnn/dnn_backend_openvino.h
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rename from mxVision/Ascendffmpeg/libavfilter/dnn/dnn_backend_openvino.h
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diff --git a/mxVision/Ascendffmpeg/libavfilter/dnn/dnn_backend_tf.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/dnn/dnn_backend_tf.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/dnn/dnn_backend_tf.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/dnn/dnn_backend_tf.h
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diff --git a/mxVision/Ascendffmpeg/libavfilter/dnn/dnn_interface.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/dnn/dnn_interface.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/dnn/dnn_io_proc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/dnn/dnn_io_proc.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/dnn/dnn_io_proc.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/dnn/dnn_io_proc.h
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diff --git a/mxVision/Ascendffmpeg/libavfilter/dnn/queue.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/dnn/queue.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/dnn/safe_queue.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/dnn/safe_queue.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/dnn_filter_common.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/dnn_filter_common.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/dnn_filter_common.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/dnn_filter_common.h
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diff --git a/mxVision/Ascendffmpeg/libavfilter/dnn_interface.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/dnn_interface.h
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diff --git a/mxVision/Ascendffmpeg/libavfilter/drawutils.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/drawutils.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/ebur128.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/ebur128.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/f_bench.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/f_bench.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/f_cue.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/f_cue.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/f_drawgraph.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/f_drawgraph.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/f_ebur128.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/f_ebur128.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/f_graphmonitor.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/f_graphmonitor.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/f_interleave.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/f_interleave.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/f_loop.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/f_loop.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/f_metadata.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/f_metadata.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/f_perms.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/f_perms.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/f_realtime.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/f_realtime.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/f_reverse.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/f_reverse.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/f_select.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/f_select.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/f_sendcmd.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/f_sendcmd.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/f_sidedata.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/f_sidedata.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/f_streamselect.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/f_streamselect.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/f_zmq.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/f_zmq.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/fifo.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/fifo.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/gblur.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/gblur.h
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diff --git a/mxVision/Ascendffmpeg/libavfilter/generate_wave_table.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/generate_wave_table.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/generate_wave_table.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/generate_wave_table.h
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diff --git a/mxVision/Ascendffmpeg/libavfilter/glslang.cpp b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/glslang.cpp
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diff --git a/mxVision/Ascendffmpeg/libavfilter/gradfun.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/gradfun.h
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vaapi_vpp.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vaapi_vpp.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vaapi_vpp.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vaapi_vpp.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vaapi_vpp.h
diff --git a/mxVision/Ascendffmpeg/libavfilter/vaf_spectrumsynth.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vaf_spectrumsynth.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vaf_spectrumsynth.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vaf_spectrumsynth.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/version.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/version.h
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rename from mxVision/Ascendffmpeg/libavfilter/version.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/version.h
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_addroi.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_addroi.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_addroi.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_addroi.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_alphamerge.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_alphamerge.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_alphamerge.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_alphamerge.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_amplify.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_amplify.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_amplify.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_amplify.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_aspect.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_aspect.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_aspect.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_aspect.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_atadenoise.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_atadenoise.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_atadenoise.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_atadenoise.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_avgblur.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_avgblur.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_avgblur.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_avgblur.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_avgblur_opencl.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_avgblur_opencl.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_avgblur_opencl.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_avgblur_opencl.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_avgblur_vulkan.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_avgblur_vulkan.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_avgblur_vulkan.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_avgblur_vulkan.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_bbox.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_bbox.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_bbox.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_bbox.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_bilateral.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_bilateral.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_bilateral.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_bilateral.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_bitplanenoise.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_bitplanenoise.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_bitplanenoise.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_bitplanenoise.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_blackdetect.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_blackdetect.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_blackdetect.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_blackdetect.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_blackframe.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_blackframe.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_blackframe.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_blackframe.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_blend.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_blend.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_blend.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_blend.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_bm3d.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_bm3d.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_bm3d.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_bm3d.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_boxblur.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_boxblur.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_boxblur.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_boxblur.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_bwdif.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_bwdif.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_bwdif.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_bwdif.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_cas.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_cas.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_cas.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_cas.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_chromaber_vulkan.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_chromaber_vulkan.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_chromaber_vulkan.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_chromaber_vulkan.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_chromakey.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_chromakey.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_chromakey.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_chromakey.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_chromanr.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_chromanr.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_chromanr.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_chromanr.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_chromashift.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_chromashift.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_chromashift.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_chromashift.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_ciescope.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_ciescope.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_ciescope.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_ciescope.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_codecview.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_codecview.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_codecview.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_codecview.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_colorbalance.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_colorbalance.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_colorbalance.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_colorbalance.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_colorchannelmixer.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_colorchannelmixer.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_colorchannelmixer.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_colorchannelmixer.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_colorconstancy.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_colorconstancy.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_colorconstancy.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_colorconstancy.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_colorcontrast.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_colorcontrast.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_colorcontrast.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_colorcontrast.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_colorcorrect.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_colorcorrect.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_colorcorrect.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_colorcorrect.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_colorize.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_colorize.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_colorize.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_colorize.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_colorkey.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_colorkey.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_colorkey.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_colorkey.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_colorkey_opencl.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_colorkey_opencl.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_colorkey_opencl.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_colorkey_opencl.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_colorlevels.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_colorlevels.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_colorlevels.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_colorlevels.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_colormatrix.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_colormatrix.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_colormatrix.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_colormatrix.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_colorspace.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_colorspace.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_colorspace.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_colorspace.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_colortemperature.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_colortemperature.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_colortemperature.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_colortemperature.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_convolution.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_convolution.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_convolution.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_convolution.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_convolution_opencl.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_convolution_opencl.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_convolution_opencl.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_convolution_opencl.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_convolve.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_convolve.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_convolve.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_convolve.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_copy.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_copy.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_copy.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_copy.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_coreimage.m b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_coreimage.m
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rename from mxVision/Ascendffmpeg/libavfilter/vf_coreimage.m
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_coreimage.m
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_cover_rect.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_cover_rect.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_cover_rect.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_cover_rect.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_crop.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_crop.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_crop.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_crop.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_cropdetect.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_cropdetect.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_cropdetect.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_cropdetect.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_curves.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_curves.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_curves.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_curves.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_datascope.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_datascope.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_datascope.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_datascope.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_dblur.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_dblur.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_dblur.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_dblur.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_dctdnoiz.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_dctdnoiz.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_dctdnoiz.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_dctdnoiz.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_deband.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_deband.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_deband.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_deband.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_deblock.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_deblock.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_deblock.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_deblock.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_decimate.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_decimate.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_decimate.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_decimate.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_dedot.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_dedot.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_dedot.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_dedot.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_deflicker.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_deflicker.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_deflicker.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_deflicker.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_deinterlace_qsv.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_deinterlace_qsv.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_deinterlace_qsv.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_deinterlace_qsv.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_deinterlace_vaapi.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_deinterlace_vaapi.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_deinterlace_vaapi.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_deinterlace_vaapi.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_dejudder.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_dejudder.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_dejudder.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_dejudder.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_delogo.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_delogo.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_delogo.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_delogo.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_derain.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_derain.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_derain.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_derain.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_deshake.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_deshake.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_deshake.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_deshake.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_deshake_opencl.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_deshake_opencl.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_deshake_opencl.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_deshake_opencl.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_despill.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_despill.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_despill.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_despill.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_detelecine.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_detelecine.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_detelecine.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_detelecine.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_displace.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_displace.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_displace.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_displace.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_dnn_processing.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_dnn_processing.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_dnn_processing.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_dnn_processing.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_drawbox.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_drawbox.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_drawbox.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_drawbox.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_drawtext.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_drawtext.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_drawtext.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_drawtext.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_edgedetect.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_edgedetect.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_edgedetect.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_edgedetect.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_elbg.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_elbg.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_elbg.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_elbg.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_entropy.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_entropy.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_entropy.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_entropy.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_epx.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_epx.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_epx.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_epx.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_eq.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_eq.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_eq.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_eq.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_eq.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_eq.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_eq.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_eq.h
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_estdif.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_estdif.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_estdif.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_estdif.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_exposure.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_exposure.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_exposure.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_exposure.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_extractplanes.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_extractplanes.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_extractplanes.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_extractplanes.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_fade.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_fade.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_fade.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_fade.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_fftdnoiz.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_fftdnoiz.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_fftdnoiz.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_fftdnoiz.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_fftfilt.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_fftfilt.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_fftfilt.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_fftfilt.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_field.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_field.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_field.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_field.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_fieldhint.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_fieldhint.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_fieldhint.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_fieldhint.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_fieldmatch.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_fieldmatch.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_fieldmatch.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_fieldmatch.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_fieldorder.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_fieldorder.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_fieldorder.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_fieldorder.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_fillborders.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_fillborders.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_fillborders.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_fillborders.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_find_rect.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_find_rect.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_find_rect.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_find_rect.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_floodfill.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_floodfill.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_floodfill.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_floodfill.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_format.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_format.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_format.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_format.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_fps.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_fps.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_fps.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_fps.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_framepack.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_framepack.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_framepack.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_framepack.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_framerate.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_framerate.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_framerate.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_framerate.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_framestep.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_framestep.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_framestep.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_framestep.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_freezedetect.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_freezedetect.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_freezedetect.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_freezedetect.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_freezeframes.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_freezeframes.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_freezeframes.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_freezeframes.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_frei0r.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_frei0r.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_frei0r.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_frei0r.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_fspp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_fspp.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_fspp.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_fspp.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_fspp.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_fspp.h
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rename from mxVision/Ascendffmpeg/libavfilter/vf_fspp.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_fspp.h
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_gblur.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_gblur.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_gblur.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_gblur.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_geq.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_geq.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_geq.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_geq.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_gradfun.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_gradfun.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_gradfun.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_gradfun.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_hflip.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_hflip.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_hflip.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_hflip.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_histeq.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_histeq.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_histeq.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_histeq.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_histogram.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_histogram.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_histogram.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_histogram.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_hqdn3d.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_hqdn3d.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_hqdn3d.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_hqdn3d.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_hqdn3d.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_hqdn3d.h
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rename from mxVision/Ascendffmpeg/libavfilter/vf_hqdn3d.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_hqdn3d.h
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_hqx.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_hqx.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_hqx.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_hqx.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_hue.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_hue.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_hue.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_hue.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_hwdownload.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_hwdownload.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_hwdownload.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_hwdownload.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_hwmap.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_hwmap.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_hwmap.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_hwmap.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_hwupload.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_hwupload.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_hwupload.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_hwupload.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_hwupload_cuda.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_hwupload_cuda.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_hwupload_cuda.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_hwupload_cuda.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_hysteresis.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_hysteresis.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_hysteresis.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_hysteresis.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_identity.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_identity.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_identity.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_identity.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_idet.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_idet.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_idet.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_idet.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_idet.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_idet.h
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rename from mxVision/Ascendffmpeg/libavfilter/vf_idet.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_idet.h
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_il.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_il.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_il.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_il.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_kerndeint.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_kerndeint.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_kerndeint.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_kerndeint.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_lagfun.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_lagfun.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_lagfun.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_lagfun.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_lenscorrection.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_lenscorrection.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_lenscorrection.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_lenscorrection.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_lensfun.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_lensfun.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_lensfun.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_lensfun.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_libopencv.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_libopencv.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_libopencv.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_libopencv.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_libvmaf.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_libvmaf.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_libvmaf.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_libvmaf.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_limiter.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_limiter.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_limiter.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_limiter.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_lumakey.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_lumakey.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_lumakey.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_lumakey.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_lut.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_lut.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_lut.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_lut.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_lut2.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_lut2.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_lut2.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_lut2.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_lut3d.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_lut3d.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_lut3d.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_lut3d.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_maskedclamp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_maskedclamp.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_maskedclamp.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_maskedclamp.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_maskedmerge.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_maskedmerge.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_maskedmerge.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_maskedmerge.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_maskedminmax.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_maskedminmax.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_maskedminmax.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_maskedminmax.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_maskedthreshold.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_maskedthreshold.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_maskedthreshold.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_maskedthreshold.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_maskfun.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_maskfun.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_maskfun.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_maskfun.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_mcdeint.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_mcdeint.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_mcdeint.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_mcdeint.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_median.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_median.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_median.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_median.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_mergeplanes.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_mergeplanes.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_mergeplanes.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_mergeplanes.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_mestimate.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_mestimate.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_mestimate.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_mestimate.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_midequalizer.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_midequalizer.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_midequalizer.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_midequalizer.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_minterpolate.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_minterpolate.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_minterpolate.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_minterpolate.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_misc_vaapi.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_misc_vaapi.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_misc_vaapi.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_misc_vaapi.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_mix.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_mix.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_mix.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_mix.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_monochrome.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_monochrome.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_monochrome.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_monochrome.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_mpdecimate.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_mpdecimate.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_mpdecimate.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_mpdecimate.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_neighbor.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_neighbor.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_neighbor.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_neighbor.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_neighbor_opencl.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_neighbor_opencl.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_neighbor_opencl.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_neighbor_opencl.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_nlmeans.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_nlmeans.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_nlmeans.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_nlmeans.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_nlmeans.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_nlmeans.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_nlmeans.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_nlmeans.h
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_nlmeans_opencl.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_nlmeans_opencl.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_nlmeans_opencl.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_nlmeans_opencl.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_nnedi.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_nnedi.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_nnedi.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_nnedi.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_noise.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_noise.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_noise.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_noise.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_noise.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_noise.h
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_noise.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_noise.h
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_normalize.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_normalize.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_normalize.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_normalize.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_null.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_null.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_null.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_null.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_ocr.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_ocr.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_ocr.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_ocr.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_overlay.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_overlay.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_overlay.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_overlay.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_overlay.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_overlay.h
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rename from mxVision/Ascendffmpeg/libavfilter/vf_overlay.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_overlay.h
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_overlay_cuda.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_overlay_cuda.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_overlay_cuda.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_overlay_cuda.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_overlay_cuda.cu b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_overlay_cuda.cu
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rename from mxVision/Ascendffmpeg/libavfilter/vf_overlay_cuda.cu
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_overlay_cuda.cu
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_overlay_opencl.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_overlay_opencl.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_overlay_opencl.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_overlay_opencl.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_overlay_qsv.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_overlay_qsv.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_overlay_qsv.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_overlay_qsv.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_overlay_vulkan.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_overlay_vulkan.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_overlay_vulkan.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_overlay_vulkan.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_owdenoise.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_owdenoise.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_owdenoise.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_owdenoise.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_pad.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_pad.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_pad.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_pad.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_pad_opencl.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_pad_opencl.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_pad_opencl.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_pad_opencl.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_palettegen.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_palettegen.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_palettegen.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_palettegen.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_paletteuse.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_paletteuse.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_paletteuse.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_paletteuse.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_perspective.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_perspective.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_perspective.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_perspective.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_phase.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_phase.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_phase.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_phase.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_photosensitivity.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_photosensitivity.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_photosensitivity.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_photosensitivity.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_pixdesctest.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_pixdesctest.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_pixdesctest.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_pixdesctest.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_pp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_pp.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_pp.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_pp.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_pp7.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_pp7.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_pp7.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_pp7.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_pp7.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_pp7.h
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rename from mxVision/Ascendffmpeg/libavfilter/vf_pp7.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_pp7.h
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_premultiply.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_premultiply.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_premultiply.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_premultiply.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_procamp_vaapi.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_procamp_vaapi.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_procamp_vaapi.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_procamp_vaapi.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_program_opencl.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_program_opencl.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_program_opencl.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_program_opencl.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_pseudocolor.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_pseudocolor.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_pseudocolor.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_pseudocolor.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_psnr.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_psnr.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_psnr.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_psnr.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_pullup.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_pullup.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_pullup.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_pullup.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_pullup.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_pullup.h
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rename from mxVision/Ascendffmpeg/libavfilter/vf_pullup.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_pullup.h
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_qp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_qp.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_qp.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_qp.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_random.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_random.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_random.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_random.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_readeia608.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_readeia608.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_readeia608.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_readeia608.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_readvitc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_readvitc.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_readvitc.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_readvitc.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_remap.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_remap.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_remap.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_remap.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_removegrain.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_removegrain.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_removegrain.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_removegrain.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_removelogo.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_removelogo.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_removelogo.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_removelogo.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_repeatfields.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_repeatfields.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_repeatfields.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_repeatfields.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_rotate.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_rotate.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_rotate.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_rotate.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_sab.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_sab.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_sab.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_sab.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_scale.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_scale.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_scale.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_scale.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_scale_cuda.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_scale_cuda.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_scale_cuda.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_scale_cuda.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_scale_cuda.cu b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_scale_cuda.cu
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rename from mxVision/Ascendffmpeg/libavfilter/vf_scale_cuda.cu
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_scale_cuda.cu
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_scale_cuda.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_scale_cuda.h
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rename from mxVision/Ascendffmpeg/libavfilter/vf_scale_cuda.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_scale_cuda.h
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_scale_cuda_bicubic.cu b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_scale_cuda_bicubic.cu
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rename from mxVision/Ascendffmpeg/libavfilter/vf_scale_cuda_bicubic.cu
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_scale_cuda_bicubic.cu
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_scale_npp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_scale_npp.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_scale_npp.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_scale_npp.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_scale_qsv.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_scale_qsv.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_scale_qsv.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_scale_qsv.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_scale_vaapi.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_scale_vaapi.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_scale_vaapi.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_scale_vaapi.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_scale_vulkan.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_scale_vulkan.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_scale_vulkan.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_scale_vulkan.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_scdet.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_scdet.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_scdet.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_scdet.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_scroll.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_scroll.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_scroll.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_scroll.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_selectivecolor.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_selectivecolor.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_selectivecolor.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_selectivecolor.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_separatefields.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_separatefields.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_separatefields.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_separatefields.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_setparams.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_setparams.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_setparams.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_setparams.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_shear.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_shear.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_shear.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_shear.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_showinfo.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_showinfo.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_showinfo.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_showpalette.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_showpalette.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_showpalette.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_showpalette.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_shuffleframes.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_shuffleframes.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_shuffleframes.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_shuffleframes.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_shufflepixels.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_shufflepixels.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_shufflepixels.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_shufflepixels.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_shuffleplanes.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_shuffleplanes.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_shuffleplanes.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_signalstats.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_signalstats.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_signalstats.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_signalstats.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_signature.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_signature.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_signature.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_signature.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_smartblur.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_smartblur.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_smartblur.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_smartblur.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_spp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_spp.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_spp.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_spp.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_spp.h
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rename from mxVision/Ascendffmpeg/libavfilter/vf_spp.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_spp.h
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_sr.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_sr.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_sr.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_sr.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_ssim.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_ssim.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_ssim.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_ssim.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_stack.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_stack.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_stack.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_stack.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_stereo3d.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_stereo3d.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_stereo3d.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_subtitles.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_subtitles.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_subtitles.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_subtitles.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_super2xsai.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_super2xsai.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_super2xsai.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_swaprect.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_swaprect.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_swaprect.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_swaprect.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_swapuv.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_swapuv.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_swapuv.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_swapuv.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_telecine.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_telecine.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_telecine.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_telecine.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_threshold.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_threshold.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_threshold.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_threshold.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_thumbnail.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_thumbnail.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_thumbnail.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_thumbnail.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_thumbnail_cuda.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_thumbnail_cuda.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_thumbnail_cuda.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_thumbnail_cuda.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_thumbnail_cuda.cu b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_thumbnail_cuda.cu
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rename from mxVision/Ascendffmpeg/libavfilter/vf_thumbnail_cuda.cu
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_thumbnail_cuda.cu
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_tile.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_tile.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_tile.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_tile.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_tinterlace.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_tinterlace.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_tinterlace.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_tinterlace.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_tmidequalizer.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_tmidequalizer.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_tmidequalizer.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_tonemap.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_tonemap.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_tonemap.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_tonemap.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_tonemap_opencl.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_tonemap_opencl.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_tonemap_opencl.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_tonemap_opencl.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_tonemap_vaapi.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_tonemap_vaapi.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_tonemap_vaapi.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_tonemap_vaapi.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_tpad.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_tpad.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_tpad.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_tpad.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_transpose.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_transpose.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_transpose.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_transpose.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_transpose_npp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_transpose_npp.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_transpose_npp.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_transpose_npp.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_transpose_opencl.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_transpose_opencl.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_transpose_opencl.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_transpose_vaapi.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_transpose_vaapi.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_transpose_vaapi.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_transpose_vaapi.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_unsharp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_unsharp.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_unsharp.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_unsharp_opencl.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_unsharp_opencl.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_unsharp_opencl.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_unsharp_opencl.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_untile.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_untile.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_untile.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_untile.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_uspp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_uspp.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_uspp.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_uspp.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_v360.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_v360.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_v360.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_v360.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_vaguedenoiser.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_vaguedenoiser.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_vaguedenoiser.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_vaguedenoiser.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_vectorscope.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_vectorscope.c
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_vectorscope.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_vflip.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_vflip.c
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_vflip.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_vfrdet.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_vfrdet.c
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_vfrdet.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_vibrance.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_vibrance.c
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_vibrance.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_vidstabdetect.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_vidstabdetect.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_vidstabdetect.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_vidstabdetect.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_vidstabtransform.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_vidstabtransform.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_vidstabtransform.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_vidstabtransform.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_vif.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_vif.c
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_vif.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_vignette.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_vignette.c
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_vignette.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_vmafmotion.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_vmafmotion.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_vmafmotion.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_vmafmotion.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_vpp_qsv.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_vpp_qsv.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_vpp_qsv.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_vpp_qsv.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_w3fdif.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_w3fdif.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_w3fdif.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_w3fdif.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_waveform.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_waveform.c
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_waveform.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_weave.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_weave.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_weave.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_weave.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_xbr.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_xbr.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_xbr.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_xbr.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_xfade.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_xfade.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_xfade.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_xfade.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_xfade_opencl.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_xfade_opencl.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_xfade_opencl.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_xfade_opencl.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_xmedian.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_xmedian.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_xmedian.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_xmedian.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_yadif.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_yadif.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_yadif.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_yadif.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_yadif_cuda.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_yadif_cuda.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_yadif_cuda.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_yadif_cuda.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_yadif_cuda.cu b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_yadif_cuda.cu
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_yadif_cuda.cu
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diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_yaepblur.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_yaepblur.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/vf_yaepblur.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_yaepblur.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_zoompan.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_zoompan.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_zoompan.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_zoompan.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vf_zscale.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_zscale.c
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rename from mxVision/Ascendffmpeg/libavfilter/vf_zscale.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vf_zscale.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/video.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/video.c
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rename from mxVision/Ascendffmpeg/libavfilter/video.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/video.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/video.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/video.h
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rename from mxVision/Ascendffmpeg/libavfilter/video.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/video.h
diff --git a/mxVision/Ascendffmpeg/libavfilter/vidstabutils.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vidstabutils.c
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rename from mxVision/Ascendffmpeg/libavfilter/vidstabutils.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vidstabutils.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vidstabutils.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vidstabutils.h
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rename from mxVision/Ascendffmpeg/libavfilter/vidstabutils.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vidstabutils.h
diff --git a/mxVision/Ascendffmpeg/libavfilter/vif.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vif.h
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rename from mxVision/Ascendffmpeg/libavfilter/vif.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vif.h
diff --git a/mxVision/Ascendffmpeg/libavfilter/vmaf_motion.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vmaf_motion.h
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rename from mxVision/Ascendffmpeg/libavfilter/vmaf_motion.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vmaf_motion.h
diff --git a/mxVision/Ascendffmpeg/libavfilter/vsink_nullsink.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vsink_nullsink.c
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rename from mxVision/Ascendffmpeg/libavfilter/vsink_nullsink.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/vsrc_cellauto.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vsrc_cellauto.c
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rename from mxVision/Ascendffmpeg/libavfilter/vsrc_cellauto.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vsrc_cellauto.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vsrc_gradients.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vsrc_gradients.c
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vsrc_gradients.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vsrc_life.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vsrc_life.c
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vsrc_life.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vsrc_mandelbrot.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vsrc_mandelbrot.c
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rename from mxVision/Ascendffmpeg/libavfilter/vsrc_mandelbrot.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vsrc_mandelbrot.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vsrc_mptestsrc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vsrc_mptestsrc.c
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rename from mxVision/Ascendffmpeg/libavfilter/vsrc_mptestsrc.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vsrc_mptestsrc.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vsrc_sierpinski.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vsrc_sierpinski.c
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rename from mxVision/Ascendffmpeg/libavfilter/vsrc_sierpinski.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vsrc_sierpinski.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vsrc_testsrc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vsrc_testsrc.c
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rename from mxVision/Ascendffmpeg/libavfilter/vsrc_testsrc.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vsrc_testsrc.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vulkan.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vulkan.c
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rename from mxVision/Ascendffmpeg/libavfilter/vulkan.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vulkan.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/vulkan.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vulkan.h
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rename from mxVision/Ascendffmpeg/libavfilter/vulkan.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/vulkan.h
diff --git a/mxVision/Ascendffmpeg/libavfilter/w3fdif.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/w3fdif.h
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rename from mxVision/Ascendffmpeg/libavfilter/w3fdif.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/w3fdif.h
diff --git a/mxVision/Ascendffmpeg/libavfilter/window_func.h b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/window_func.h
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rename from mxVision/Ascendffmpeg/libavfilter/window_func.h
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/window_func.h
diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/Makefile b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/Makefile
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rename from mxVision/Ascendffmpeg/libavfilter/x86/Makefile
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/Makefile
diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/af_afir.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/af_afir.asm
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rename from mxVision/Ascendffmpeg/libavfilter/x86/af_afir.asm
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diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/af_afir_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/af_afir_init.c
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rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/af_afir_init.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/af_anlmdn.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/af_anlmdn.asm
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rename from mxVision/Ascendffmpeg/libavfilter/x86/af_anlmdn.asm
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diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/af_anlmdn_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/af_anlmdn_init.c
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rename from mxVision/Ascendffmpeg/libavfilter/x86/af_anlmdn_init.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/af_volume.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/af_volume.asm
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rename from mxVision/Ascendffmpeg/libavfilter/x86/af_volume.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/af_volume.asm
diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/af_volume_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/af_volume_init.c
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rename from mxVision/Ascendffmpeg/libavfilter/x86/af_volume_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/af_volume_init.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/avf_showcqt.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/avf_showcqt.asm
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/x86/avf_showcqt.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/avf_showcqt.asm
diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/avf_showcqt_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/avf_showcqt_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/x86/avf_showcqt_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/avf_showcqt_init.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/colorspacedsp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/colorspacedsp.asm
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rename from mxVision/Ascendffmpeg/libavfilter/x86/colorspacedsp.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/colorspacedsp.asm
diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/colorspacedsp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/colorspacedsp_init.c
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rename from mxVision/Ascendffmpeg/libavfilter/x86/colorspacedsp_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/colorspacedsp_init.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/scene_sad.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/scene_sad.asm
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rename from mxVision/Ascendffmpeg/libavfilter/x86/scene_sad.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/scene_sad.asm
diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/scene_sad_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/scene_sad_init.c
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rename from mxVision/Ascendffmpeg/libavfilter/x86/scene_sad_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/scene_sad_init.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/vf_atadenoise.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_atadenoise.asm
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rename from mxVision/Ascendffmpeg/libavfilter/x86/vf_atadenoise.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_atadenoise.asm
diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/vf_atadenoise_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_atadenoise_init.c
similarity index 100%
rename from mxVision/Ascendffmpeg/libavfilter/x86/vf_atadenoise_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_atadenoise_init.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/vf_blend.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_blend.asm
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rename from mxVision/Ascendffmpeg/libavfilter/x86/vf_blend.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_blend.asm
diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/vf_blend_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_blend_init.c
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rename from mxVision/Ascendffmpeg/libavfilter/x86/vf_blend_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_blend_init.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/vf_bwdif.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_bwdif.asm
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rename from mxVision/Ascendffmpeg/libavfilter/x86/vf_bwdif.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_bwdif.asm
diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/vf_bwdif_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_bwdif_init.c
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rename from mxVision/Ascendffmpeg/libavfilter/x86/vf_bwdif_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_bwdif_init.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/vf_convolution.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_convolution.asm
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rename from mxVision/Ascendffmpeg/libavfilter/x86/vf_convolution.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_convolution.asm
diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/vf_convolution_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_convolution_init.c
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rename from mxVision/Ascendffmpeg/libavfilter/x86/vf_convolution_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_convolution_init.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/vf_eq.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_eq.asm
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rename from mxVision/Ascendffmpeg/libavfilter/x86/vf_eq.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_eq.asm
diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/vf_eq_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_eq_init.c
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rename from mxVision/Ascendffmpeg/libavfilter/x86/vf_eq_init.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/vf_framerate.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_framerate.asm
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rename from mxVision/Ascendffmpeg/libavfilter/x86/vf_framerate.asm
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diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/vf_framerate_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_framerate_init.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/vf_fspp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_fspp.asm
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diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/vf_fspp_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_fspp_init.c
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rename from mxVision/Ascendffmpeg/libavfilter/x86/vf_fspp_init.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/vf_gblur.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_gblur.asm
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rename from mxVision/Ascendffmpeg/libavfilter/x86/vf_gblur.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_gblur.asm
diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/vf_gblur_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_gblur_init.c
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rename from mxVision/Ascendffmpeg/libavfilter/x86/vf_gblur_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_gblur_init.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/vf_gradfun.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_gradfun.asm
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rename from mxVision/Ascendffmpeg/libavfilter/x86/vf_gradfun.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_gradfun.asm
diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/vf_gradfun_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_gradfun_init.c
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rename from mxVision/Ascendffmpeg/libavfilter/x86/vf_gradfun_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_gradfun_init.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/vf_hflip.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_hflip.asm
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rename from mxVision/Ascendffmpeg/libavfilter/x86/vf_hflip.asm
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_hflip.asm
diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/vf_hflip_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_hflip_init.c
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rename from mxVision/Ascendffmpeg/libavfilter/x86/vf_hflip_init.c
rename to mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_hflip_init.c
diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/vf_hqdn3d.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_hqdn3d.asm
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rename from mxVision/Ascendffmpeg/libavfilter/x86/vf_hqdn3d.asm
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diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/vf_hqdn3d_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_hqdn3d_init.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/vf_idet.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_idet.asm
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diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/vf_interlace.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_interlace.asm
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diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/vf_maskedclamp.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_maskedclamp.asm
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diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/vf_maskedmerge.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_maskedmerge.asm
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diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/vf_noise.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_noise.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/vf_overlay.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_overlay.asm
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diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/vf_pp7.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_pp7.asm
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diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/vf_psnr.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_psnr.asm
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diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/vf_pullup.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_pullup.asm
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diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/vf_removegrain.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_removegrain.asm
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diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/vf_spp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_spp.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/vf_ssim.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_ssim.asm
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diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/vf_stereo3d.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_stereo3d.asm
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diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/vf_threshold.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_threshold.asm
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diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/vf_tinterlace_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_tinterlace_init.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/vf_transpose.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_transpose.asm
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diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/vf_v360.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_v360.asm
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diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/vf_v360_init.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_v360_init.c
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diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/vf_w3fdif.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_w3fdif.asm
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diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/vf_yadif.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/vf_yadif.asm
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diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/yadif-10.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/yadif-10.asm
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diff --git a/mxVision/Ascendffmpeg/libavfilter/x86/yadif-16.asm b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavfilter/x86/yadif-16.asm
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diff --git a/mxVision/Ascendffmpeg/libavformat/.gitignore b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavformat/.gitignore
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diff --git a/mxVision/Ascendffmpeg/libavformat/4xm.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavformat/4xm.c
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diff --git a/mxVision/Ascendffmpeg/libavformat/rtpdec_vp8.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavformat/rtpdec_vp8.c
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diff --git a/mxVision/Ascendffmpeg/libavformat/rtpdec_xiph.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavformat/rtpdec_xiph.c
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diff --git a/mxVision/Ascendffmpeg/libavformat/rtpenc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavformat/rtpenc.c
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diff --git a/mxVision/Ascendffmpeg/libavformat/rtpenc_aac.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavformat/rtpenc_aac.c
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diff --git a/mxVision/Ascendffmpeg/libavformat/rtpenc_amr.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavformat/rtpenc_amr.c
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diff --git a/mxVision/Ascendffmpeg/libavformat/rtpenc_chain.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavformat/rtpenc_chain.c
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diff --git a/mxVision/Ascendffmpeg/libavformat/rtpenc_h261.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavformat/rtpenc_h261.c
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diff --git a/mxVision/Ascendffmpeg/libavformat/rtpenc_h263.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavformat/rtpenc_h263.c
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diff --git a/mxVision/Ascendffmpeg/libavformat/rtpenc_h263_rfc2190.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavformat/rtpenc_h263_rfc2190.c
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diff --git a/mxVision/Ascendffmpeg/libavformat/rtpenc_h264_hevc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavformat/rtpenc_h264_hevc.c
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diff --git a/mxVision/Ascendffmpeg/libavformat/rtpenc_jpeg.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavformat/rtpenc_jpeg.c
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diff --git a/mxVision/Ascendffmpeg/libavformat/rtpenc_latm.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavformat/rtpenc_latm.c
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diff --git a/mxVision/Ascendffmpeg/libavformat/rtpenc_mpegts.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavformat/rtpenc_mpegts.c
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diff --git a/mxVision/Ascendffmpeg/libavformat/rtpenc_mpv.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavformat/rtpenc_mpv.c
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diff --git a/mxVision/Ascendffmpeg/libavformat/rtpenc_vc2hq.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavformat/rtpenc_vc2hq.c
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diff --git a/mxVision/Ascendffmpeg/libavformat/rtpenc_vp8.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavformat/rtpenc_vp8.c
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diff --git a/mxVision/Ascendffmpeg/libavformat/rtpenc_xiph.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavformat/rtpenc_xiph.c
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diff --git a/mxVision/Ascendffmpeg/libavformat/rtsp.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavformat/rtsp.c
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diff --git a/mxVision/Ascendffmpeg/libavformat/rtspdec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavformat/rtspdec.c
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diff --git a/mxVision/Ascendffmpeg/libavformat/rtspenc.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavformat/rtspenc.c
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diff --git a/mxVision/Ascendffmpeg/libavformat/sapdec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavformat/sapdec.c
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diff --git a/mxVision/Ascendffmpeg/libavformat/sbgdec.c b/mxVision/mxVision-referenceapps/Ascendffmpeg/libavformat/sbgdec.c
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-cabac-tudepth b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-cabac-tudepth
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-ADJUST_IPRED_ANGLE_A_RExt_Mitsubishi_1 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-ADJUST_IPRED_ANGLE_A_RExt_Mitsubishi_1
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-AMP_A_Samsung_4 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-AMP_A_Samsung_4
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-AMP_B_Samsung_4 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-AMP_B_Samsung_4
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-AMP_D_Hisilicon b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-AMP_D_Hisilicon
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-AMVP_A_MTK_4 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-AMVP_A_MTK_4
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-AMVP_B_MTK_4 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-AMVP_B_MTK_4
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-AMVP_C_Samsung_4 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-AMVP_C_Samsung_4
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-BUMPING_A_ericsson_1 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-BUMPING_A_ericsson_1
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-CAINIT_A_SHARP_4 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-CAINIT_A_SHARP_4
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-CIP_A_Panasonic_3 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-CIP_A_Panasonic_3
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-CONFWIN_A_Sony_1 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-CONFWIN_A_Sony_1
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-DBLK_A_MAIN10_VIXS_3 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-DBLK_A_MAIN10_VIXS_3
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-DBLK_A_SONY_3 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-DBLK_A_SONY_3
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-DBLK_B_SONY_3 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-DBLK_B_SONY_3
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-DBLK_C_SONY_3 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-DBLK_C_SONY_3
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-DBLK_D_VIXS_2 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-DBLK_D_VIXS_2
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-DBLK_F_VIXS_2 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-DBLK_F_VIXS_2
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-DELTAQP_A_BRCM_4 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-DELTAQP_A_BRCM_4
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-DELTAQP_B_SONY_3 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-DELTAQP_B_SONY_3
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-DELTAQP_C_SONY_3 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-DELTAQP_C_SONY_3
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-DSLICE_A_HHI_5 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-DSLICE_A_HHI_5
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-DSLICE_C_HHI_5 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-DSLICE_C_HHI_5
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-ENTP_A_Qualcomm_1 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-ENTP_A_Qualcomm_1
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-ENTP_B_Qualcomm_1 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-ENTP_B_Qualcomm_1
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-EXT_A_ericsson_4 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-EXT_A_ericsson_4
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-FILLER_A_Sony_1 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-FILLER_A_Sony_1
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-HRD_A_Fujitsu_2 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-HRD_A_Fujitsu_2
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-HRD_A_Fujitsu_3 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-HRD_A_Fujitsu_3
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-INITQP_A_Sony_1 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-INITQP_A_Sony_1
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-IPCM_A_RExt_NEC b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-IPCM_A_RExt_NEC
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-LTRPSPS_A_Qualcomm_1 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-LTRPSPS_A_Qualcomm_1
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-MERGE_A_TI_3 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-MERGE_A_TI_3
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-MVCLIP_A_qualcomm_3 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-MVCLIP_A_qualcomm_3
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-Main_422_10_A_RExt_Sony_1 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-Main_422_10_A_RExt_Sony_1
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-NUT_A_ericsson_5 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-NUT_A_ericsson_5
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-NoOutPrior_A_Qualcomm_1 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-NoOutPrior_A_Qualcomm_1
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-PERSIST_RPARAM_A_RExt_Sony_1 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-PERSIST_RPARAM_A_RExt_Sony_1
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-PICSIZE_A_Bossen_1 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-PICSIZE_A_Bossen_1
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-PMERGE_A_TI_3 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-PMERGE_A_TI_3
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-POC_A_Bossen_3 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-POC_A_Bossen_3
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-PPS_A_qualcomm_7 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-PPS_A_qualcomm_7
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-PS_A_VIDYO_3 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-PS_A_VIDYO_3
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-QMATRIX_A_RExt_Sony_1 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-QMATRIX_A_RExt_Sony_1
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-RAP_A_docomo_4 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-RAP_A_docomo_4
similarity index 100%
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-RAP_B_Bossen_1 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-RAP_B_Bossen_1
similarity index 100%
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-RPLM_A_qualcomm_4 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-RPLM_A_qualcomm_4
similarity index 100%
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-RPLM_B_qualcomm_4 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-RPLM_B_qualcomm_4
similarity index 100%
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-RPS_A_docomo_4 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-RPS_A_docomo_4
similarity index 100%
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-RPS_B_qualcomm_5 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-RPS_B_qualcomm_5
similarity index 100%
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-RPS_C_ericsson_5 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-RPS_C_ericsson_5
similarity index 100%
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-RPS_D_ericsson_6 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-RPS_D_ericsson_6
similarity index 100%
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-RPS_E_qualcomm_5 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-RPS_E_qualcomm_5
similarity index 100%
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-RPS_F_docomo_1 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-RPS_F_docomo_1
similarity index 100%
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-RQT_A_HHI_4 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-RQT_A_HHI_4
similarity index 100%
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-RQT_B_HHI_4 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-RQT_B_HHI_4
similarity index 100%
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-RQT_C_HHI_4 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-RQT_C_HHI_4
similarity index 100%
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-RQT_D_HHI_4 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-RQT_D_HHI_4
similarity index 100%
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-RQT_E_HHI_4 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-RQT_E_HHI_4
similarity index 100%
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-RQT_F_HHI_4 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-RQT_F_HHI_4
similarity index 100%
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-RQT_G_HHI_4 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-RQT_G_HHI_4
similarity index 100%
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-SAO_A_MediaTek_4 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-SAO_A_MediaTek_4
similarity index 100%
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-SAO_A_RExt_MediaTek_1 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-SAO_A_RExt_MediaTek_1
similarity index 100%
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-SAO_B_MediaTek_5 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-SAO_B_MediaTek_5
similarity index 100%
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-SAO_C_Samsung_4 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-SAO_C_Samsung_4
similarity index 100%
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-SAO_C_Samsung_5 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-SAO_C_Samsung_5
similarity index 100%
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-SAO_D_Samsung_4 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-SAO_D_Samsung_4
similarity index 100%
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-SAO_D_Samsung_5 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-SAO_D_Samsung_5
similarity index 100%
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-SAO_E_Canon_4 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-SAO_E_Canon_4
similarity index 100%
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-SAO_F_Canon_3 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-SAO_F_Canon_3
similarity index 100%
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-SAO_G_Canon_3 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-SAO_G_Canon_3
similarity index 100%
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-SDH_A_Orange_3 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-SDH_A_Orange_3
similarity index 100%
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-SLICES_A_Rovi_3 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-SLICES_A_Rovi_3
similarity index 100%
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-SLIST_A_Sony_4 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-SLIST_A_Sony_4
similarity index 100%
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-SLIST_B_Sony_8 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-SLIST_B_Sony_8
similarity index 100%
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-SLIST_C_Sony_3 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-SLIST_C_Sony_3
similarity index 100%
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-SLIST_D_Sony_9 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-SLIST_D_Sony_9
similarity index 100%
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-SLPPLP_A_VIDYO_1 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-SLPPLP_A_VIDYO_1
similarity index 100%
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-SLPPLP_A_VIDYO_2 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-SLPPLP_A_VIDYO_2
similarity index 100%
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-STRUCT_A_Samsung_5 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-STRUCT_A_Samsung_5
similarity index 100%
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-STRUCT_B_Samsung_4 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-STRUCT_B_Samsung_4
similarity index 100%
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-STRUCT_B_Samsung_6 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-STRUCT_B_Samsung_6
similarity index 100%
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-TILES_A_Cisco_2 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-TILES_A_Cisco_2
similarity index 100%
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-TILES_B_Cisco_1 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-TILES_B_Cisco_1
similarity index 100%
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-TMVP_A_MS_3 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-TMVP_A_MS_3
similarity index 100%
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-TSCL_A_VIDYO_5 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-TSCL_A_VIDYO_5
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-TSCL_B_VIDYO_4 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-TSCL_B_VIDYO_4
similarity index 100%
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-TSKIP_A_MS_3 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-TSKIP_A_MS_3
similarity index 100%
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-TUSIZE_A_Samsung_1 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-TUSIZE_A_Samsung_1
similarity index 100%
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diff --git a/mxVision/Ascendffmpeg/tests/ref/fate/hevc-conformance-VPSID_A_VIDYO_1 b/mxVision/mxVision-referenceapps/Ascendffmpeg/tests/ref/fate/hevc-conformance-VPSID_A_VIDYO_1
similarity index 100%
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rename from contrib/CenterFace/plugins/KeyPointPostProcessor/CenterfaceKeyPointPostProcessor.h
rename to mxVision/mxVision-referenceapps/CenterFace/plugins/KeyPointPostProcessor/CenterfaceKeyPointPostProcessor.h
diff --git a/contrib/CenterFace/plugins/KeyPointPostProcessor/build.sh b/mxVision/mxVision-referenceapps/CenterFace/plugins/KeyPointPostProcessor/build.sh
similarity index 100%
rename from contrib/CenterFace/plugins/KeyPointPostProcessor/build.sh
rename to mxVision/mxVision-referenceapps/CenterFace/plugins/KeyPointPostProcessor/build.sh
diff --git a/contrib/CenterNet/README.md b/mxVision/mxVision-referenceapps/CenterNet/README.md
similarity index 97%
rename from contrib/CenterNet/README.md
rename to mxVision/mxVision-referenceapps/CenterNet/README.md
index 9bf0fec7f900ede192ee9f8f80269d01cb1daf23..640bdce90a7f59a47ecfa3619a13a46b33088893 100644
--- a/contrib/CenterNet/README.md
+++ b/mxVision/mxVision-referenceapps/CenterNet/README.md
@@ -1,108 +1,108 @@
-# CenterNet 目标检测
-## 1. 介绍
-### 1.1 简介
-CenterNet 目标检测后处理插件基于 MindX SDK 开发，对图片中的不同类目标进行检测，将检测得到的不同类的目标用矩形框标记。输入一幅图像，可以检测得到图像中大部分类别目标的位置。本方案使用在 COCO2017 数据集上训练得到的 CenterNet 模型进行目标检测，数据集中共包含 80 个目标类，包括行人、自行车、公共汽车、手机、沙发、猫、狗等，可以对不同类别、不同角度、不同密集程度的目标进行检测。
-
-整体业务流程为：待检测图片通过 appsrc 插件输入，然后使用图像解码插件 mxpi_imagedecoder 对图片进行解码，再通过图像缩放插件 mxpi_imageresize 将图像缩放至满足检测模型要求的输入图像大小要求，缩放后的图像输入模型推理插件 mxpi_tensorinfer 得到推理结果，推理结果输入 mxpi_objectpostprocessor 插件进行后处理，得到输入图片中所有的目标框位置和对应的置信度。最后通过输出插件 appsink 获取检测结果，并在外部进行可视化，将检测结果标记到原图上.
-### 1.2 支持的产品
-
-本项目以昇腾Atlas 300I pro和 Atlas300V pro为主要的硬件平台。
-
-
-### 1.3 支持的版本
-
-| MxVision版本  | CANN版本  | Driver/Firmware版本 |
-  | --------- | ------------------ | -------------- |
-| 6.0.RC3 | 8.0.RC3   |  24.1.RC3  | 
-
-### 1.4 三方依赖
-
-本项目除了依赖昇腾Driver、Firmware、CANN和MxVision及其要求的配套软件外，还需额外依赖以下软件：
-
-| 软件名称   | 版本       |
-|--------|----------|
-| opencv-python | 4.9.0.80 |
-| numpy | 1.24.0   |
-| webcolors | 24.8.0   |
-| NumCpp | 2.12.1   |
-
-* NumCpp需要下载源码, 请用户至 https://github.com/dpilger26/NumCpp 进行下载。下载完成后，无需编译，仅需将NumCpp源码目录下的include/NumCpp目录拷贝至项目根目录下的postprocess/include目录（postprocess/include目录需要手动创建）。
-### 1.5 代码目录结构与说明
-
-本工程名称为 CenterNet，工程目录如下所示：
-```
-├── postprocess
-│   ├── build.sh
-│   ├── CMakeLists.txt
-│   ├── CenterNetPostProcess.cpp
-│   └── CenterNetPostProcess.h
-├── python
-│   ├── Main
-│   │   ├── pre_post.py
-│   │   └── colorlist.txt
-│   ├── models
-│   │   ├── aipp-configs
-│   │   │   └── aipp_bgr.config
-│   │   └──  centernet.cfg
-│   └── pipeline
-│       └── pre_post.pipeline
-└── README.md
-
-```
-
-## 2. 设置环境变量
-
-在执行后续步骤前，需要设置环境变量：
-
-
-```bash
-# 执行环境变量脚本使环境变量生效
-. ${ascend-toolkit-path}/set_env.sh
-. ${mxVision-path}/set_env.sh
-# mxVision: mxVision安装路径
-# ascend-toolkit-path: CANN安装路径
-```
-
-## 3. 准备模型
-**步骤1:** 下载模型相关文件
-
-根据[链接](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/CenterNet/ATC%20CenterNet.zip)下载并解压，在解压后的310P_model目录下得到CenterNet.onnx文件，并放在``python/models`` 目录下。
-
-
-根据[链接](https://gitee.com/ascend/mindxsdk-referenceapps/blob/master/contrib/Collision/model/coco.names)下载coco.names文件，并放在``python/models`` 目录下。
-
-**步骤2:** 转换模型格式
-进入到``python/models`` 目录下，将onnx格式模型转换为om格式模型。
-
-       atc --framework=5 --model=CenterNet.onnx  --output=CenterNet_pre_post --input_format=NCHW --input_shape="actual_input:1,3,512,512" --log=info --soc_version=Ascend310P3 --insert_op_conf=./aipp-configs/aipp_bgr.config
-
-若终端输出：
-```
-ATC start working now, please wait for a moment.
-ATC run success, welcome to the next use.
-```
-
-表示命令执行成功。
-
-
-## 4. 编译与运行
-
-**步骤1:** 在项目后处理目录执行命令：
-
-```
-bash build.sh  
-```
-
-**步骤2:** 放入待测图片。将一张图片放在路径``python/test_img``下，命名为 test.jpg（python/test_img目录需用户自行创建）。
-
-**步骤3:** 图片检测。在项目路径``python/Main``下运行命令：
-
-```
-python3 pre_post.py
-```
-**步骤4:** 查看结果
-
-命令执行成功后在目录``python/test_img``下生成检测结果文件 pre_post.jpg，可打开该文件观察检测结果。
-
-
-
+# CenterNet 目标检测
+## 1. 介绍
+### 1.1 简介
+CenterNet 目标检测后处理插件基于 MindX SDK 开发，对图片中的不同类目标进行检测，将检测得到的不同类的目标用矩形框标记。输入一幅图像，可以检测得到图像中大部分类别目标的位置。本方案使用在 COCO2017 数据集上训练得到的 CenterNet 模型进行目标检测，数据集中共包含 80 个目标类，包括行人、自行车、公共汽车、手机、沙发、猫、狗等，可以对不同类别、不同角度、不同密集程度的目标进行检测。
+
+整体业务流程为：待检测图片通过 appsrc 插件输入，然后使用图像解码插件 mxpi_imagedecoder 对图片进行解码，再通过图像缩放插件 mxpi_imageresize 将图像缩放至满足检测模型要求的输入图像大小要求，缩放后的图像输入模型推理插件 mxpi_tensorinfer 得到推理结果，推理结果输入 mxpi_objectpostprocessor 插件进行后处理，得到输入图片中所有的目标框位置和对应的置信度。最后通过输出插件 appsink 获取检测结果，并在外部进行可视化，将检测结果标记到原图上.
+### 1.2 支持的产品
+
+本项目以昇腾Atlas 300I pro和 Atlas300V pro为主要的硬件平台。
+
+
+### 1.3 支持的版本
+
+| MxVision版本  | CANN版本  | Driver/Firmware版本 |
+  | --------- | ------------------ | -------------- |
+| 6.0.RC3 | 8.0.RC3   |  24.1.RC3  | 
+
+### 1.4 三方依赖
+
+本项目除了依赖昇腾Driver、Firmware、CANN和MxVision及其要求的配套软件外，还需额外依赖以下软件：
+
+| 软件名称   | 版本       |
+|--------|----------|
+| opencv-python | 4.9.0.80 |
+| numpy | 1.24.0   |
+| webcolors | 24.8.0   |
+| NumCpp | 2.12.1   |
+
+* NumCpp需要下载源码, 请用户至 https://github.com/dpilger26/NumCpp 进行下载。下载完成后，无需编译，仅需将NumCpp源码目录下的include/NumCpp目录拷贝至项目根目录下的postprocess/include目录（postprocess/include目录需要手动创建）。
+### 1.5 代码目录结构与说明
+
+本工程名称为 CenterNet，工程目录如下所示：
+```
+├── postprocess
+│   ├── build.sh
+│   ├── CMakeLists.txt
+│   ├── CenterNetPostProcess.cpp
+│   └── CenterNetPostProcess.h
+├── python
+│   ├── Main
+│   │   ├── pre_post.py
+│   │   └── colorlist.txt
+│   ├── models
+│   │   ├── aipp-configs
+│   │   │   └── aipp_bgr.config
+│   │   └──  centernet.cfg
+│   └── pipeline
+│       └── pre_post.pipeline
+└── README.md
+
+```
+
+## 2. 设置环境变量
+
+在执行后续步骤前，需要设置环境变量：
+
+
+```bash
+# 执行环境变量脚本使环境变量生效
+. ${ascend-toolkit-path}/set_env.sh
+. ${mxVision-path}/set_env.sh
+# mxVision: mxVision安装路径
+# ascend-toolkit-path: CANN安装路径
+```
+
+## 3. 准备模型
+**步骤1:** 下载模型相关文件
+
+根据[链接](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/CenterNet/ATC%20CenterNet.zip)下载并解压，在解压后的310P_model目录下得到CenterNet.onnx文件，并放在``python/models`` 目录下。
+
+
+根据[链接](https://gitee.com/ascend/mindxsdk-referenceapps/blob/master/contrib/Collision/model/coco.names)下载coco.names文件，并放在``python/models`` 目录下。
+
+**步骤2:** 转换模型格式
+进入到``python/models`` 目录下，将onnx格式模型转换为om格式模型。
+
+       atc --framework=5 --model=CenterNet.onnx  --output=CenterNet_pre_post --input_format=NCHW --input_shape="actual_input:1,3,512,512" --log=info --soc_version=Ascend310P3 --insert_op_conf=./aipp-configs/aipp_bgr.config
+
+若终端输出：
+```
+ATC start working now, please wait for a moment.
+ATC run success, welcome to the next use.
+```
+
+表示命令执行成功。
+
+
+## 4. 编译与运行
+
+**步骤1:** 在项目后处理目录执行命令：
+
+```
+bash build.sh  
+```
+
+**步骤2:** 放入待测图片。将一张图片放在路径``python/test_img``下，命名为 test.jpg（python/test_img目录需用户自行创建）。
+
+**步骤3:** 图片检测。在项目路径``python/Main``下运行命令：
+
+```
+python3 pre_post.py
+```
+**步骤4:** 查看结果
+
+命令执行成功后在目录``python/test_img``下生成检测结果文件 pre_post.jpg，可打开该文件观察检测结果。
+
+
+
diff --git a/contrib/CenterNet/postprocess/CMakeLists.txt b/mxVision/mxVision-referenceapps/CenterNet/postprocess/CMakeLists.txt
similarity index 100%
rename from contrib/CenterNet/postprocess/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/CenterNet/postprocess/CMakeLists.txt
diff --git a/contrib/CenterNet/postprocess/CenterNetPostProcess.cpp b/mxVision/mxVision-referenceapps/CenterNet/postprocess/CenterNetPostProcess.cpp
similarity index 100%
rename from contrib/CenterNet/postprocess/CenterNetPostProcess.cpp
rename to mxVision/mxVision-referenceapps/CenterNet/postprocess/CenterNetPostProcess.cpp
diff --git a/contrib/CenterNet/postprocess/CenterNetPostProcess.h b/mxVision/mxVision-referenceapps/CenterNet/postprocess/CenterNetPostProcess.h
similarity index 100%
rename from contrib/CenterNet/postprocess/CenterNetPostProcess.h
rename to mxVision/mxVision-referenceapps/CenterNet/postprocess/CenterNetPostProcess.h
diff --git a/contrib/CenterNet/postprocess/build.sh b/mxVision/mxVision-referenceapps/CenterNet/postprocess/build.sh
similarity index 100%
rename from contrib/CenterNet/postprocess/build.sh
rename to mxVision/mxVision-referenceapps/CenterNet/postprocess/build.sh
diff --git a/contrib/CenterNet/python/Main/colorlist.txt b/mxVision/mxVision-referenceapps/CenterNet/python/Main/colorlist.txt
similarity index 100%
rename from contrib/CenterNet/python/Main/colorlist.txt
rename to mxVision/mxVision-referenceapps/CenterNet/python/Main/colorlist.txt
diff --git a/contrib/CenterNet/python/Main/pre_post.py b/mxVision/mxVision-referenceapps/CenterNet/python/Main/pre_post.py
similarity index 100%
rename from contrib/CenterNet/python/Main/pre_post.py
rename to mxVision/mxVision-referenceapps/CenterNet/python/Main/pre_post.py
diff --git a/contrib/CenterNet/python/models/aipp-configs/aipp_bgr.config b/mxVision/mxVision-referenceapps/CenterNet/python/models/aipp-configs/aipp_bgr.config
similarity index 100%
rename from contrib/CenterNet/python/models/aipp-configs/aipp_bgr.config
rename to mxVision/mxVision-referenceapps/CenterNet/python/models/aipp-configs/aipp_bgr.config
diff --git a/contrib/CenterNet/python/models/centernet.cfg b/mxVision/mxVision-referenceapps/CenterNet/python/models/centernet.cfg
similarity index 100%
rename from contrib/CenterNet/python/models/centernet.cfg
rename to mxVision/mxVision-referenceapps/CenterNet/python/models/centernet.cfg
diff --git a/contrib/CenterNet/python/pipeline/pre_post.pipeline b/mxVision/mxVision-referenceapps/CenterNet/python/pipeline/pre_post.pipeline
similarity index 100%
rename from contrib/CenterNet/python/pipeline/pre_post.pipeline
rename to mxVision/mxVision-referenceapps/CenterNet/python/pipeline/pre_post.pipeline
diff --git a/contrib/Collision/README.md b/mxVision/mxVision-referenceapps/Collision/README.md
similarity index 100%
rename from contrib/Collision/README.md
rename to mxVision/mxVision-referenceapps/Collision/README.md
diff --git a/contrib/Collision/build.sh b/mxVision/mxVision-referenceapps/Collision/build.sh
similarity index 100%
rename from contrib/Collision/build.sh
rename to mxVision/mxVision-referenceapps/Collision/build.sh
diff --git a/contrib/Collision/collision.pipeline b/mxVision/mxVision-referenceapps/Collision/collision.pipeline
similarity index 100%
rename from contrib/Collision/collision.pipeline
rename to mxVision/mxVision-referenceapps/Collision/collision.pipeline
diff --git a/contrib/Collision/collision.py b/mxVision/mxVision-referenceapps/Collision/collision.py
similarity index 100%
rename from contrib/Collision/collision.py
rename to mxVision/mxVision-referenceapps/Collision/collision.py
diff --git a/contrib/Collision/image/SDK_process.png b/mxVision/mxVision-referenceapps/Collision/image/SDK_process.png
similarity index 100%
rename from contrib/Collision/image/SDK_process.png
rename to mxVision/mxVision-referenceapps/Collision/image/SDK_process.png
diff --git a/contrib/Collision/image/after_collision.png b/mxVision/mxVision-referenceapps/Collision/image/after_collision.png
similarity index 100%
rename from contrib/Collision/image/after_collision.png
rename to mxVision/mxVision-referenceapps/Collision/image/after_collision.png
diff --git a/contrib/Collision/image/before_collision.png b/mxVision/mxVision-referenceapps/Collision/image/before_collision.png
similarity index 100%
rename from contrib/Collision/image/before_collision.png
rename to mxVision/mxVision-referenceapps/Collision/image/before_collision.png
diff --git a/contrib/Collision/image/collision.png b/mxVision/mxVision-referenceapps/Collision/image/collision.png
similarity index 100%
rename from contrib/Collision/image/collision.png
rename to mxVision/mxVision-referenceapps/Collision/image/collision.png
diff --git a/contrib/Collision/image/error.png b/mxVision/mxVision-referenceapps/Collision/image/error.png
similarity index 100%
rename from contrib/Collision/image/error.png
rename to mxVision/mxVision-referenceapps/Collision/image/error.png
diff --git a/contrib/Collision/image/video_conversion.png b/mxVision/mxVision-referenceapps/Collision/image/video_conversion.png
similarity index 100%
rename from contrib/Collision/image/video_conversion.png
rename to mxVision/mxVision-referenceapps/Collision/image/video_conversion.png
diff --git a/contrib/Collision/model/aipp_yolov3_416_416.aippconfig b/mxVision/mxVision-referenceapps/Collision/model/aipp_yolov3_416_416.aippconfig
similarity index 100%
rename from contrib/Collision/model/aipp_yolov3_416_416.aippconfig
rename to mxVision/mxVision-referenceapps/Collision/model/aipp_yolov3_416_416.aippconfig
diff --git a/contrib/Collision/model/coco.names b/mxVision/mxVision-referenceapps/Collision/model/coco.names
similarity index 100%
rename from contrib/Collision/model/coco.names
rename to mxVision/mxVision-referenceapps/Collision/model/coco.names
diff --git a/contrib/Collision/model/yolov3.cfg b/mxVision/mxVision-referenceapps/Collision/model/yolov3.cfg
similarity index 100%
rename from contrib/Collision/model/yolov3.cfg
rename to mxVision/mxVision-referenceapps/Collision/model/yolov3.cfg
diff --git a/contrib/Collision/plugins/MxpiCollisionClassName/CMakeLists.txt b/mxVision/mxVision-referenceapps/Collision/plugins/MxpiCollisionClassName/CMakeLists.txt
similarity index 100%
rename from contrib/Collision/plugins/MxpiCollisionClassName/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/Collision/plugins/MxpiCollisionClassName/CMakeLists.txt
diff --git a/contrib/Collision/plugins/MxpiCollisionClassName/MxpiCollisionClassName.cpp b/mxVision/mxVision-referenceapps/Collision/plugins/MxpiCollisionClassName/MxpiCollisionClassName.cpp
similarity index 100%
rename from contrib/Collision/plugins/MxpiCollisionClassName/MxpiCollisionClassName.cpp
rename to mxVision/mxVision-referenceapps/Collision/plugins/MxpiCollisionClassName/MxpiCollisionClassName.cpp
diff --git a/contrib/Collision/plugins/MxpiCollisionClassName/MxpiCollisionClassName.h b/mxVision/mxVision-referenceapps/Collision/plugins/MxpiCollisionClassName/MxpiCollisionClassName.h
similarity index 100%
rename from contrib/Collision/plugins/MxpiCollisionClassName/MxpiCollisionClassName.h
rename to mxVision/mxVision-referenceapps/Collision/plugins/MxpiCollisionClassName/MxpiCollisionClassName.h
diff --git a/contrib/Collision/plugins/MxpiCollisionClassName/build.sh b/mxVision/mxVision-referenceapps/Collision/plugins/MxpiCollisionClassName/build.sh
similarity index 100%
rename from contrib/Collision/plugins/MxpiCollisionClassName/build.sh
rename to mxVision/mxVision-referenceapps/Collision/plugins/MxpiCollisionClassName/build.sh
diff --git a/contrib/Collision/plugins/MxpiTrackIdReplaceClassName/CMakeLists.txt b/mxVision/mxVision-referenceapps/Collision/plugins/MxpiTrackIdReplaceClassName/CMakeLists.txt
similarity index 100%
rename from contrib/Collision/plugins/MxpiTrackIdReplaceClassName/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/Collision/plugins/MxpiTrackIdReplaceClassName/CMakeLists.txt
diff --git a/contrib/Collision/plugins/MxpiTrackIdReplaceClassName/MxpiTrackIdReplaceClassName.cpp b/mxVision/mxVision-referenceapps/Collision/plugins/MxpiTrackIdReplaceClassName/MxpiTrackIdReplaceClassName.cpp
similarity index 100%
rename from contrib/Collision/plugins/MxpiTrackIdReplaceClassName/MxpiTrackIdReplaceClassName.cpp
rename to mxVision/mxVision-referenceapps/Collision/plugins/MxpiTrackIdReplaceClassName/MxpiTrackIdReplaceClassName.cpp
diff --git a/contrib/Collision/plugins/MxpiTrackIdReplaceClassName/MxpiTrackIdReplaceClassName.h b/mxVision/mxVision-referenceapps/Collision/plugins/MxpiTrackIdReplaceClassName/MxpiTrackIdReplaceClassName.h
similarity index 100%
rename from contrib/Collision/plugins/MxpiTrackIdReplaceClassName/MxpiTrackIdReplaceClassName.h
rename to mxVision/mxVision-referenceapps/Collision/plugins/MxpiTrackIdReplaceClassName/MxpiTrackIdReplaceClassName.h
diff --git a/contrib/Collision/plugins/MxpiTrackIdReplaceClassName/build.sh b/mxVision/mxVision-referenceapps/Collision/plugins/MxpiTrackIdReplaceClassName/build.sh
similarity index 100%
rename from contrib/Collision/plugins/MxpiTrackIdReplaceClassName/build.sh
rename to mxVision/mxVision-referenceapps/Collision/plugins/MxpiTrackIdReplaceClassName/build.sh
diff --git a/contrib/Colorization/README.md b/mxVision/mxVision-referenceapps/Colorization/README.md
similarity index 96%
rename from contrib/Colorization/README.md
rename to mxVision/mxVision-referenceapps/Colorization/README.md
index 7578f1a8979be6b4d3c0764f2805a1078d2f6347..3f5dc1bb8903476df44e07d0d3f1915b4233afb1 100644
--- a/contrib/Colorization/README.md
+++ b/mxVision/mxVision-referenceapps/Colorization/README.md
@@ -1,89 +1,89 @@
-# 黑白图像上色
-
-## 1 介绍
-
-在智能手机越来越普及的今天，拍摄一张色彩鲜艳、清晰的照片轻而易举。但是老照片没有如此“幸运”，大多为黑白。借助人工智能，可以一定程度上帮助老照片还原原来色彩。
-
-本项目是黑白图像上色应用，旨在华为Atlas300推理芯片上实现输入黑白图像，自动对黑白图像进行上色，还原彩色图像。
-
-### 1.1 支持的产品
-
-Atlas300推理芯片
-
-### 1.2 代码目录结构与说明
-
-```
-.
-├── data         //需要手动创建
-├── model        //需要手动创建
-│   ├── colorization.caffemodel
-│   └── colorization.prototxt
-├── out          //需要手动创建
-├── pipeline
-│   └── colorization.pipeline
-├── README.md
-├── scripts
-│   ├── atc_run.sh
-│   └── run.sh
-└── src
-    └── main.py
-```
-
-## 2 环境依赖
-
-### 2.1 环境变量
-
-模型转换和工程运行的环境变量已写入对应的shell脚本中
-
-### 2.2 软件依赖
-
-|     依赖软件     | 版本  |
-|------------------|-------|
-|      CANN        | 20.2.rc1| 
-|     python       | 3.9.2 | 
-|    MindX_SDK     | 2.0.4 |
-|   opencv-python  | 4.5.3 |
-|      numpy       | 1.21.2|  
-
-## 3 运行
-
-示例步骤如下：
-### 3.1 模型转换
-
-本工程原模型是caffee模型，需要使用atc工具转换为om模型，模型和所需权重文件已上传，请使用以下命令下载并解压
-
-```
-cd model
-wget https://mindx.sdk.obs.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/Colorization/model.zip
-unzip model.zip
-```
-
-下载并解压完毕后，进入scripts目录执行模型转换脚本
-
-```
-cd ../scripts
-bash atc_run.sh
-```
-
-### 3.2 获取测试图片
-
-将待上色图片移动至data目录。本样例使用图片方式获取如下
-
-```
-cd ../data
-wget https://c7xcode.obs.cn-north-4.myhuaweicloud.com/models/colorization_picture-python/dog.png
-```
-
-### 3.3 运行推理工程
-
-进入scripts目录，修改run.sh文件中INPUT_PIC变量为输入图片的路径，本示例为"../data/dog.png"，修改MX_SDK_HOME环境变量为SDK实际安装路径。
-执行脚本
-
-```
-cd ../scripts
-bash run.sh
-```
-
-输出结果保存在out目录下，下载至本地查看图片上色是否合理
-
-
+# 黑白图像上色
+
+## 1 介绍
+
+在智能手机越来越普及的今天，拍摄一张色彩鲜艳、清晰的照片轻而易举。但是老照片没有如此“幸运”，大多为黑白。借助人工智能，可以一定程度上帮助老照片还原原来色彩。
+
+本项目是黑白图像上色应用，旨在华为Atlas300推理芯片上实现输入黑白图像，自动对黑白图像进行上色，还原彩色图像。
+
+### 1.1 支持的产品
+
+Atlas300推理芯片
+
+### 1.2 代码目录结构与说明
+
+```
+.
+├── data         //需要手动创建
+├── model        //需要手动创建
+│   ├── colorization.caffemodel
+│   └── colorization.prototxt
+├── out          //需要手动创建
+├── pipeline
+│   └── colorization.pipeline
+├── README.md
+├── scripts
+│   ├── atc_run.sh
+│   └── run.sh
+└── src
+    └── main.py
+```
+
+## 2 环境依赖
+
+### 2.1 环境变量
+
+模型转换和工程运行的环境变量已写入对应的shell脚本中
+
+### 2.2 软件依赖
+
+|     依赖软件     | 版本  |
+|------------------|-------|
+|      CANN        | 20.2.rc1| 
+|     python       | 3.9.2 | 
+|    MindX_SDK     | 2.0.4 |
+|   opencv-python  | 4.5.3 |
+|      numpy       | 1.21.2|  
+
+## 3 运行
+
+示例步骤如下：
+### 3.1 模型转换
+
+本工程原模型是caffee模型，需要使用atc工具转换为om模型，模型和所需权重文件已上传，请使用以下命令下载并解压
+
+```
+cd model
+wget https://mindx.sdk.obs.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/Colorization/model.zip
+unzip model.zip
+```
+
+下载并解压完毕后，进入scripts目录执行模型转换脚本
+
+```
+cd ../scripts
+bash atc_run.sh
+```
+
+### 3.2 获取测试图片
+
+将待上色图片移动至data目录。本样例使用图片方式获取如下
+
+```
+cd ../data
+wget https://c7xcode.obs.cn-north-4.myhuaweicloud.com/models/colorization_picture-python/dog.png
+```
+
+### 3.3 运行推理工程
+
+进入scripts目录，修改run.sh文件中INPUT_PIC变量为输入图片的路径，本示例为"../data/dog.png"，修改MX_SDK_HOME环境变量为SDK实际安装路径。
+执行脚本
+
+```
+cd ../scripts
+bash run.sh
+```
+
+输出结果保存在out目录下，下载至本地查看图片上色是否合理
+
+
diff --git a/contrib/Colorization/pipeline/colorization.pipeline b/mxVision/mxVision-referenceapps/Colorization/pipeline/colorization.pipeline
similarity index 100%
rename from contrib/Colorization/pipeline/colorization.pipeline
rename to mxVision/mxVision-referenceapps/Colorization/pipeline/colorization.pipeline
diff --git a/contrib/Colorization/scripts/atc_run.sh b/mxVision/mxVision-referenceapps/Colorization/scripts/atc_run.sh
similarity index 100%
rename from contrib/Colorization/scripts/atc_run.sh
rename to mxVision/mxVision-referenceapps/Colorization/scripts/atc_run.sh
diff --git a/contrib/Colorization/scripts/run.sh b/mxVision/mxVision-referenceapps/Colorization/scripts/run.sh
similarity index 100%
rename from contrib/Colorization/scripts/run.sh
rename to mxVision/mxVision-referenceapps/Colorization/scripts/run.sh
diff --git a/contrib/Colorization/src/main.py b/mxVision/mxVision-referenceapps/Colorization/src/main.py
similarity index 100%
rename from contrib/Colorization/src/main.py
rename to mxVision/mxVision-referenceapps/Colorization/src/main.py
diff --git a/contrib/CrowdCounting/CMakeLists.txt b/mxVision/mxVision-referenceapps/CrowdCounting/CMakeLists.txt
similarity index 100%
rename from contrib/CrowdCounting/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/CrowdCounting/CMakeLists.txt
diff --git a/contrib/CrowdCounting/CrowdCount/CrowdCount.cpp b/mxVision/mxVision-referenceapps/CrowdCounting/CrowdCount/CrowdCount.cpp
similarity index 100%
rename from contrib/CrowdCounting/CrowdCount/CrowdCount.cpp
rename to mxVision/mxVision-referenceapps/CrowdCounting/CrowdCount/CrowdCount.cpp
diff --git a/contrib/CrowdCounting/CrowdCount/CrowdCount.h b/mxVision/mxVision-referenceapps/CrowdCounting/CrowdCount/CrowdCount.h
similarity index 100%
rename from contrib/CrowdCounting/CrowdCount/CrowdCount.h
rename to mxVision/mxVision-referenceapps/CrowdCounting/CrowdCount/CrowdCount.h
diff --git a/contrib/CrowdCounting/CrowdCountPostProcess/CrowdCountPostProcess.cpp b/mxVision/mxVision-referenceapps/CrowdCounting/CrowdCountPostProcess/CrowdCountPostProcess.cpp
similarity index 100%
rename from contrib/CrowdCounting/CrowdCountPostProcess/CrowdCountPostProcess.cpp
rename to mxVision/mxVision-referenceapps/CrowdCounting/CrowdCountPostProcess/CrowdCountPostProcess.cpp
diff --git a/contrib/CrowdCounting/CrowdCountPostProcess/CrowdCountPostProcess.h b/mxVision/mxVision-referenceapps/CrowdCounting/CrowdCountPostProcess/CrowdCountPostProcess.h
similarity index 100%
rename from contrib/CrowdCounting/CrowdCountPostProcess/CrowdCountPostProcess.h
rename to mxVision/mxVision-referenceapps/CrowdCounting/CrowdCountPostProcess/CrowdCountPostProcess.h
diff --git a/contrib/CrowdCounting/README.md b/mxVision/mxVision-referenceapps/CrowdCounting/README.md
similarity index 97%
rename from contrib/CrowdCounting/README.md
rename to mxVision/mxVision-referenceapps/CrowdCounting/README.md
index 00ba8047d03450f2cd8618be01f185a3a3760f71..2878e2aa5e2179b7957ef2f000a4cac67532360f 100644
--- a/contrib/CrowdCounting/README.md
+++ b/mxVision/mxVision-referenceapps/CrowdCounting/README.md
@@ -1,107 +1,107 @@
-# C++ 基于MxBase 的人群计数图像检测样例及后处理模块开发
-
-## 1 介绍
-本开发样例是基于mxBase开发的端到端推理的C++应用程序，可在昇腾芯片上进行人群计数目标检测，并把可视化结果保存到本地。开发端到端人群计数-人群密度估计的参考设计，实现图像当中人计数的功能，并达到精度和性能要求。 该Sample的主要处理流程为： Init > ReadImage >Resize > Inference >PostProcess >DeInit
-
-### 1.1 支持的产品
-
-支持昇腾310芯片
-
-### 1.2 支持的版本
-
-在Atlas产品环境下，通过运行命令：
-
-```
-npu-smi info
-```
-
-可以查询支持SDK的版本号
-
-### 1.3 软件方案介绍
-
-人群计数项目实现：输入类型是图片数据（例如jpg格式的图片），通过调用MindX SDK mxBase提供的接口，使用DVPP进行图像解码，解码后获取图像数据，然后经过图像尺寸大小变换，满足模型的输入尺寸要求；将尺寸变换后的图像数据输入人群计数模型进行推理，模型输出经过后处理后，得到人群密度估计图和人计数估计值，输出人计数的估计值。
-
-整个流程需要参考Ascend的参考样例：crowd_count_picture 样例，详见以下链接：https://gitee.com/ascend/samples/tree/master/python/contrib/crowd_count_picture  crowd_count_picture 样例是基于ACL实现的，本任务需要参考crowd_count_picture 样例，基于MindX SDK mxBase的接口实现。MindX SDK mxBase是对ACL接口的封装，提供了极简易用的API， 使能AI应用的开发。
-
-表1.1 系统方案中各模块功能：
-
-| 序号 | 子系统            | 功能描述                                                     |
-| ---- | ----------------- | ------------------------------------------------------------ |
-| 1    | 设备初始化        | 调用mxBase::DeviceManager接口完成推理卡设备的初始化。        |
-| 2    | 图像输入          | C++文件IO读取图像文件                                        |
-| 3    | 图像解码/图像缩放 | 调用mxBase::DvppWrappe.DvppJpegDecode()函数完成图像解码，VpcResize()完成缩放。 |
-| 4    | 模型推理          | 调用mxBase:: ModelInferenceProcessor 接口完成模型推理        |
-| 5    | 后处理            | 获取模型推理输出张量BaseTensor，进行后处理。                 |
-| 6    | 保存结果          | 输出图像当中的人的数量，保存标记出人数的结果图像。           |
-| 7    | 设备去初始化      | 调用mxBase::DeviceManager接口完成推理卡设备的去初始化。      |
-
-### 1.4 代码目录结构与说明
-
-本sample工程名称为 **CrowdCounting**，工程目录如下图所示：
-
-![image-20210813152252629](image-20210813152252629.png)
-
-### 1.5 技术实现流程图
-
-![image-20210813154111508](image-20210813154111508.png)
-
-## 2 环境依赖：
-
-请列出环境依赖软件和版本。
-
-eg：推荐系统为ubuntu 18.04或centos 7.6，环境依赖软件和版本如下表：
-
-| 软件名称 | 版本         |
-| -------- | ------------ |
-| 系统软件 | ubuntu 18.04 |
-
-在编译运行项目前，需要设置环境变量：
-
-
-```
-. {cann_install_path}/ascend-toolkit/set_env.sh
-. {sdk_install_path}/mxVision/set_env.sh
-```
-
-## 3 模型转换
-
-**步骤1** 
-
-下载原始模型权重、原始模型网络、对应的cfg文件：
-
-[模型及配置文件下载链接](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/CrowdCounting/model.zip)
-
-**步骤2**
-
-将上述下载得文件统一放在CrowdCounting/model文件夹下，并使用ATC模型转换工具进行模型转换，参考如下指令:
-
-```
-atc --input_shape="blob1:1,3,800,1408" --weight="count_person.caffe.caffemodel" --input_format=NCHW --output="count_person.caffe" --soc_version=Ascend310 --insert_op_conf=insert_op.cfg --framework=0 --model="count_person.caffe.prototxt" 
-```
-
-得到count_person.caffe.om文件
-
-## 4 编译与运行
-
-**步骤1** 
-
-cd到CrowdCounting目录下，执行如下编译命令： bash build.sh
-
-
-**步骤2**
-
-下载人群计数图像，需自行在网络找图，暂支持JPG格式，任意图像分辨率。再将该下载的图片作为推理图片放入CrowdCounting目录下，执行：
-
-```
-./crowd_counting  ./xxx.jpg
-```
-
-## 5 软件依赖说明
-
-| 依赖软件 | 版本  | 说明                                                         |
-| -------- | ----- | ------------------------------------------------------------ |
-| mxVision | 5.0.0 | 封装昇腾计算语言(AscendCL)的高级编程API，简化插件和推理应用开发。 |
-| CANN  | 7.0.0 | 提供昇腾计算语言(AscendCL)的高级编程API。 |
-
-
-
+# C++ 基于MxBase 的人群计数图像检测样例及后处理模块开发
+
+## 1 介绍
+本开发样例是基于mxBase开发的端到端推理的C++应用程序，可在昇腾芯片上进行人群计数目标检测，并把可视化结果保存到本地。开发端到端人群计数-人群密度估计的参考设计，实现图像当中人计数的功能，并达到精度和性能要求。 该Sample的主要处理流程为： Init > ReadImage >Resize > Inference >PostProcess >DeInit
+
+### 1.1 支持的产品
+
+支持昇腾310芯片
+
+### 1.2 支持的版本
+
+在Atlas产品环境下，通过运行命令：
+
+```
+npu-smi info
+```
+
+可以查询支持SDK的版本号
+
+### 1.3 软件方案介绍
+
+人群计数项目实现：输入类型是图片数据（例如jpg格式的图片），通过调用MindX SDK mxBase提供的接口，使用DVPP进行图像解码，解码后获取图像数据，然后经过图像尺寸大小变换，满足模型的输入尺寸要求；将尺寸变换后的图像数据输入人群计数模型进行推理，模型输出经过后处理后，得到人群密度估计图和人计数估计值，输出人计数的估计值。
+
+整个流程需要参考Ascend的参考样例：crowd_count_picture 样例，详见以下链接：https://gitee.com/ascend/samples/tree/master/python/contrib/crowd_count_picture  crowd_count_picture 样例是基于ACL实现的，本任务需要参考crowd_count_picture 样例，基于MindX SDK mxBase的接口实现。MindX SDK mxBase是对ACL接口的封装，提供了极简易用的API， 使能AI应用的开发。
+
+表1.1 系统方案中各模块功能：
+
+| 序号 | 子系统            | 功能描述                                                     |
+| ---- | ----------------- | ------------------------------------------------------------ |
+| 1    | 设备初始化        | 调用mxBase::DeviceManager接口完成推理卡设备的初始化。        |
+| 2    | 图像输入          | C++文件IO读取图像文件                                        |
+| 3    | 图像解码/图像缩放 | 调用mxBase::DvppWrappe.DvppJpegDecode()函数完成图像解码，VpcResize()完成缩放。 |
+| 4    | 模型推理          | 调用mxBase:: ModelInferenceProcessor 接口完成模型推理        |
+| 5    | 后处理            | 获取模型推理输出张量BaseTensor，进行后处理。                 |
+| 6    | 保存结果          | 输出图像当中的人的数量，保存标记出人数的结果图像。           |
+| 7    | 设备去初始化      | 调用mxBase::DeviceManager接口完成推理卡设备的去初始化。      |
+
+### 1.4 代码目录结构与说明
+
+本sample工程名称为 **CrowdCounting**，工程目录如下图所示：
+
+![image-20210813152252629](image-20210813152252629.png)
+
+### 1.5 技术实现流程图
+
+![image-20210813154111508](image-20210813154111508.png)
+
+## 2 环境依赖：
+
+请列出环境依赖软件和版本。
+
+eg：推荐系统为ubuntu 18.04或centos 7.6，环境依赖软件和版本如下表：
+
+| 软件名称 | 版本         |
+| -------- | ------------ |
+| 系统软件 | ubuntu 18.04 |
+
+在编译运行项目前，需要设置环境变量：
+
+
+```
+. {cann_install_path}/ascend-toolkit/set_env.sh
+. {sdk_install_path}/mxVision/set_env.sh
+```
+
+## 3 模型转换
+
+**步骤1** 
+
+下载原始模型权重、原始模型网络、对应的cfg文件：
+
+[模型及配置文件下载链接](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/CrowdCounting/model.zip)
+
+**步骤2**
+
+将上述下载得文件统一放在CrowdCounting/model文件夹下，并使用ATC模型转换工具进行模型转换，参考如下指令:
+
+```
+atc --input_shape="blob1:1,3,800,1408" --weight="count_person.caffe.caffemodel" --input_format=NCHW --output="count_person.caffe" --soc_version=Ascend310 --insert_op_conf=insert_op.cfg --framework=0 --model="count_person.caffe.prototxt" 
+```
+
+得到count_person.caffe.om文件
+
+## 4 编译与运行
+
+**步骤1** 
+
+cd到CrowdCounting目录下，执行如下编译命令： bash build.sh
+
+
+**步骤2**
+
+下载人群计数图像，需自行在网络找图，暂支持JPG格式，任意图像分辨率。再将该下载的图片作为推理图片放入CrowdCounting目录下，执行：
+
+```
+./crowd_counting  ./xxx.jpg
+```
+
+## 5 软件依赖说明
+
+| 依赖软件 | 版本  | 说明                                                         |
+| -------- | ----- | ------------------------------------------------------------ |
+| mxVision | 5.0.0 | 封装昇腾计算语言(AscendCL)的高级编程API，简化插件和推理应用开发。 |
+| CANN  | 7.0.0 | 提供昇腾计算语言(AscendCL)的高级编程API。 |
+
+
+
diff --git a/contrib/CrowdCounting/build.sh b/mxVision/mxVision-referenceapps/CrowdCounting/build.sh
old mode 100755
new mode 100644
similarity index 100%
rename from contrib/CrowdCounting/build.sh
rename to mxVision/mxVision-referenceapps/CrowdCounting/build.sh
diff --git a/contrib/CrowdCounting/image-20210813152252629.png b/mxVision/mxVision-referenceapps/CrowdCounting/image-20210813152252629.png
similarity index 100%
rename from contrib/CrowdCounting/image-20210813152252629.png
rename to mxVision/mxVision-referenceapps/CrowdCounting/image-20210813152252629.png
diff --git a/contrib/CrowdCounting/image-20210813154111508.png b/mxVision/mxVision-referenceapps/CrowdCounting/image-20210813154111508.png
similarity index 100%
rename from contrib/CrowdCounting/image-20210813154111508.png
rename to mxVision/mxVision-referenceapps/CrowdCounting/image-20210813154111508.png
diff --git a/contrib/CrowdCounting/main.cpp b/mxVision/mxVision-referenceapps/CrowdCounting/main.cpp
similarity index 100%
rename from contrib/CrowdCounting/main.cpp
rename to mxVision/mxVision-referenceapps/CrowdCounting/main.cpp
diff --git a/contrib/CrowdCounting/model/count_person.names b/mxVision/mxVision-referenceapps/CrowdCounting/model/count_person.names
similarity index 100%
rename from contrib/CrowdCounting/model/count_person.names
rename to mxVision/mxVision-referenceapps/CrowdCounting/model/count_person.names
diff --git a/contrib/CrowdCounting/model/insert_op.cfg b/mxVision/mxVision-referenceapps/CrowdCounting/model/insert_op.cfg
similarity index 100%
rename from contrib/CrowdCounting/model/insert_op.cfg
rename to mxVision/mxVision-referenceapps/CrowdCounting/model/insert_op.cfg
diff --git a/contrib/DocumentLayoutAnalysis/README.md b/mxVision/mxVision-referenceapps/DocumentLayoutAnalysis/README.md
similarity index 100%
rename from contrib/DocumentLayoutAnalysis/README.md
rename to mxVision/mxVision-referenceapps/DocumentLayoutAnalysis/README.md
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diff --git a/contrib/DocumentLayoutAnalysis/infer.py b/mxVision/mxVision-referenceapps/DocumentLayoutAnalysis/infer.py
similarity index 100%
rename from contrib/DocumentLayoutAnalysis/infer.py
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diff --git a/contrib/DocumentLayoutAnalysis/model/layout.aippconfig b/mxVision/mxVision-referenceapps/DocumentLayoutAnalysis/model/layout.aippconfig
similarity index 100%
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diff --git a/contrib/DocumentLayoutAnalysis/postprocess.py b/mxVision/mxVision-referenceapps/DocumentLayoutAnalysis/postprocess.py
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rename from contrib/DocumentLayoutAnalysis/postprocess.py
rename to mxVision/mxVision-referenceapps/DocumentLayoutAnalysis/postprocess.py
diff --git a/contrib/DocumentLayoutAnalysis/utils.py b/mxVision/mxVision-referenceapps/DocumentLayoutAnalysis/utils.py
similarity index 100%
rename from contrib/DocumentLayoutAnalysis/utils.py
rename to mxVision/mxVision-referenceapps/DocumentLayoutAnalysis/utils.py
diff --git a/contrib/DriverStatusRecognition/README.md b/mxVision/mxVision-referenceapps/DriverStatusRecognition/README.md
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diff --git a/contrib/DriverStatusRecognition/convert/aipp.config b/mxVision/mxVision-referenceapps/DriverStatusRecognition/convert/aipp.config
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diff --git a/contrib/DriverStatusRecognition/convert/air2om.sh b/mxVision/mxVision-referenceapps/DriverStatusRecognition/convert/air2om.sh
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diff --git a/contrib/DriverStatusRecognition/convert/yuv_aipp.config b/mxVision/mxVision-referenceapps/DriverStatusRecognition/convert/yuv_aipp.config
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diff --git a/contrib/DriverStatusRecognition/main.py b/mxVision/mxVision-referenceapps/DriverStatusRecognition/main.py
similarity index 100%
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diff --git a/contrib/DriverStatusRecognition/models/dirver-detection_clsidx_to_label.names b/mxVision/mxVision-referenceapps/DriverStatusRecognition/models/dirver-detection_clsidx_to_label.names
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diff --git a/contrib/DriverStatusRecognition/models/resnet50.cfg b/mxVision/mxVision-referenceapps/DriverStatusRecognition/models/resnet50.cfg
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diff --git a/contrib/DriverStatusRecognition/performance.py b/mxVision/mxVision-referenceapps/DriverStatusRecognition/performance.py
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diff --git a/contrib/DriverStatusRecognition/pipeline/dirver-detection-img.pipeline b/mxVision/mxVision-referenceapps/DriverStatusRecognition/pipeline/dirver-detection-img.pipeline
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diff --git a/contrib/DriverStatusRecognition/pipeline/dirver-detection.pipeline b/mxVision/mxVision-referenceapps/DriverStatusRecognition/pipeline/dirver-detection.pipeline
similarity index 100%
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diff --git a/contrib/DriverStatusRecognition/precision.py b/mxVision/mxVision-referenceapps/DriverStatusRecognition/precision.py
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diff --git a/contrib/DriverStatusRecognition/resnet50_distracted_driver_detection_Acc_config.yaml b/mxVision/mxVision-referenceapps/DriverStatusRecognition/resnet50_distracted_driver_detection_Acc_config.yaml
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diff --git a/contrib/DriverStatusRecognition/run.sh b/mxVision/mxVision-referenceapps/DriverStatusRecognition/run.sh
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diff --git a/contrib/EdgeDetectionPicture/CMakeLists.txt b/mxVision/mxVision-referenceapps/EdgeDetectionPicture/CMakeLists.txt
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diff --git a/contrib/EdgeDetectionPicture/License b/mxVision/mxVision-referenceapps/EdgeDetectionPicture/License
similarity index 100%
rename from contrib/EdgeDetectionPicture/License
rename to mxVision/mxVision-referenceapps/EdgeDetectionPicture/License
diff --git a/contrib/EdgeDetectionPicture/README.md b/mxVision/mxVision-referenceapps/EdgeDetectionPicture/README.md
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diff --git a/contrib/EdgeDetectionPicture/build.sh b/mxVision/mxVision-referenceapps/EdgeDetectionPicture/build.sh
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diff --git a/contrib/EdgeDetectionPicture/main.cpp b/mxVision/mxVision-referenceapps/EdgeDetectionPicture/main.cpp
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diff --git a/contrib/EdgeDetectionPicture/model/aipp.cfg b/mxVision/mxVision-referenceapps/EdgeDetectionPicture/model/aipp.cfg
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diff --git a/contrib/EdgeDetectionPicture/rcfDetection/RcfDetection.cpp b/mxVision/mxVision-referenceapps/EdgeDetectionPicture/rcfDetection/RcfDetection.cpp
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diff --git a/contrib/EdgeDetectionPicture/rcfDetection/RcfDetection.h b/mxVision/mxVision-referenceapps/EdgeDetectionPicture/rcfDetection/RcfDetection.h
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diff --git a/contrib/EdgeDetectionPicture/rcfPostProcess/RcfPostProcess.cpp b/mxVision/mxVision-referenceapps/EdgeDetectionPicture/rcfPostProcess/RcfPostProcess.cpp
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diff --git a/contrib/EfficientDet/README.md b/mxVision/mxVision-referenceapps/EfficientDet/README.md
similarity index 98%
rename from contrib/EfficientDet/README.md
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index 9186dc0ed84a1e9a1086cadc2fa5720552935f8a..4e1b102f1f06c2b88811cb6619cb479c23da0928 100644
--- a/contrib/EfficientDet/README.md
+++ b/mxVision/mxVision-referenceapps/EfficientDet/README.md
@@ -1,325 +1,325 @@
-# EfficientDet 目标检测
-## 1. 介绍
-EfficientDet 目标检测后处理插件基于 MindXSDK 开发，对图片中的不同类目标进行检测，将检测得到的不同类的目标用不同颜色的矩形框标记。输入一幅图像，可以检测得到图像中大部分类别目标的位置。本方案使用在 COCO2017 数据集上训练得到的 EfficientDet 模型进行目标检测，数据集中共包含 90 个目标类，包括行人、自行车、公共汽车、手机、沙发、猫、狗等，可以对不同类别、不同角度、不同密集程度的目标进行检测。
-
-### 1.1 支持的产品
-
-本项目以昇腾Atlas310卡为主要的硬件平台。
-
-
-### 1.2 支持的版本
-
-CANN：7.0.0
-
-SDK：mxVision 5.0.0（可通过cat SDK目录下的 version.info 查看）
-
-
-### 1.3 软件方案介绍
-
-基于MindX SDK的目标检测业务流程为：待检测图片通过 appsrc 插件输入，然后使用图像解码插件 mxpi_imagedecoder 对图片进行解码，再通过图像缩放插件 mxpi_imageresize 将图像缩放至满足检测模型要求的输入图像大小要求，缩放后的图像输入模型推理插件 mxpi_tensorinfer 得到推理结果，推理结果输入 mxpi_objectpostprocessor 插件进行后处理，得到输入图片中所有的目标框位置和对应的置信度。最后通过输出插件 appsink 获取检测结果，并在外部进行可视化，将检测结果标记到原图上，本系统的各模块及功能描述如表1所示：
-
-表1 系统方案各模块功能描述：
-
-| 序号 | 子系统 | 功能描述     |
-| ---- | ------ | ------------ |
-| 1    | 图片输入    | 获取 jpg 格式输入图片 |
-| 2    | 图片解码    | 解码图片 |
-| 3    | 图片缩放    | 将输入图片放缩到模型指定输入的尺寸大小 |
-| 4    | 模型推理    | 对输入张量进行推理 |
-| 5    | 目标检测后处理    | 从模型推理结果计算检测框的位置和置信度，并保留置信度大于指定阈值的检测框作为检测结果 |
-| 6    | 结果输出    | 获取检测结果|
-| 7    | 结果可视化    | 将检测结果标注在输入图片上|
-
-
-
-### 1.4 代码目录结构与说明
-
-本工程名称为 EfficientDet，工程目录如下所示：
-```
-.
-├── build.sh
-├── images
-│   ├── DetectionPipeline.png
-│   ├── EvaluateInfo.png
-│   ├── EvaluateInfoPrevious.png
-│   └── VersionError.png
-├── postprocess
-│   ├── build.sh
-│   ├── CMakeLists.txt
-│   ├── EfficientdetPostProcess.cpp
-│   └── EfficientdetPostProcess.h
-├── python
-│   ├── evaluate.py
-│   ├── main.py
-│   ├── models
-│   │   ├── aipp-configs
-│   │   │   ├── insert_op_d0.cfg
-│   │   │   ├── insert_op_d0_previous_version.cfg
-│   │   │   ├── insert_op_d1.cfg
-│   │   │   ├── insert_op_d2.cfg
-│   │   │   ├── insert_op_d3.cfg
-│   │   │   ├── insert_op_d4.cfg
-│   │   │   ├── insert_op_d5.cfg
-│   │   │   └── insert_op_d6.cfg
-│   │   ├── coco.names
-│   │   ├── conversion-scripts
-│   │   │   ├── model_conversion_d0_previous_version.sh
-│   │   │   ├── model_conversion_d0.sh
-│   │   │   ├── model_conversion_d1.sh
-│   │   │   ├── model_conversion_d2.sh
-│   │   │   ├── model_conversion_d3.sh
-│   │   │   ├── model_conversion_d4.sh
-│   │   │   ├── model_conversion_d5.sh
-│   │   │   └── model_conversion_d6.sh
-│   │   ├── efficient-det.cfg
-│   │   ├── efficient-det-eval.cfg
-│   │   └── onnx-models
-│   └── pipeline
-│       ├── EfficientDet-d0.pipeline
-│       ├── EfficientDet-d0-previous-version.pipeline
-│       ├── EfficientDet-d1.pipeline
-│       ├── EfficientDet-d2.pipeline
-│       ├── EfficientDet-d3.pipeline
-│       ├── EfficientDet-d4.pipeline
-│       ├── EfficientDet-d5.pipeline
-│       └── EfficientDet-d6.pipeline
-└── README.md
-
-```
-
-
-### 1.5 技术实现流程图
-
-EfficientDet 的后处理插件接收模型推理插件输出的两个特征图，位置回归特征图 R 和分类特征图 C，其中 R 的形状大小为 1 x n x 4, n 表示模型在输入图片上预设的 anchors 个数，4 分别表示检测结果矩形框左上角点坐标 x, y 相对预设 anchor 的位移，以及检测框的宽、高相对预设 anchor 的比例，C 的形状大小为 1 x n x 90，90 表示每个检测框属于每个类的置信度值，该值位于 0-1 之间。后处理插件继承自 MindXSDK 的目标检测后处理插件基类，后处理插件中可以获得图片缩放插件传递的图像尺寸缩放信息 ResizedImageInfo，包括缩放前图片宽、高和缩放后图片宽、高。
-后处理插件从模型推理输出 R、C 和图像尺寸缩放信息 ResizedImageInfo 计算检测结果的整体流程如下图所示：
-<center>
-    <img src="./images/DetectionPipeline.png">
-    <br>
-</center>
-
-1. **计算预设 anchors。** 根据 ResizedImageInfo 计算不同宽高比、不同大小、在原图上不同位置的预设 anchors，anchors 的形状为 n x 4, 4 表示每个 anchor 的左上角坐标和宽、高。
-
-2. **根据 R、anchors、ResizedImageInfo、C 计算每个检测框的位置、宽高、类别以及类别置信度。** R 中的每个 4 元向量和 anchors 中每个 4 元向量是对应的，根据坐标位移和宽高比例计算得到真实的检测框位置和宽、高，同时去除置信度小于指定阈值 CT 的检测跨框。
-
-3. **NMS 去除冗余检测框。** 对步骤 2 中剩余的检测框进行筛选，首先按照置信度对保留的检测框排序，从置信度高的检测框开始，去除于其 IOU 值超过指定阈值 IT 的检测框，得到最终的检测结果。
-
-
-## 2 环境依赖
-
-推荐系统为ubuntu 18.04，环境依赖软件和版本如下表：
-
-| 软件名称 | 版本   |
-| -------- | ------ |
-| cmake    | 3.5+   |
-| MindX SDK | 5.0.0    |
-| CANN | 7.0.0 |
-| python   | 3.9.2  |
-| webcolors| 1.11.1 |
-
-确保环境中正确安装mxVision SDK。
-
-在编译运行项目前，需要设置环境变量：
-```
-. {cann_install_path}/ascend-toolkit/set_env.sh
-. {sdk_install_path}/mxVision/set_env.sh
-```
-
-
-
-## 3. 模型转换
-
-本项目中采用的模型是 EfficientDet 模型，参考实现代码：https://github.com/zylo117/Yet-Another-EfficientDet-Pytorch， 选用的模型是该 pytorch 项目中提供的模型 efficientdet-d0.pth，本项目运行前需要将 pytorch 模型转换为 onnx 模型，然后使用模型转换工具 ATC 将 onnx 模型转换为 om 模型，模型转换工具相关介绍参考链接：https://gitee.com/ascend/docs-openmind/blob/master/guide/mindx/sdk/tutorials/%E5%8F%82%E8%80%83%E8%B5%84%E6%96%99.md 。本项目中使用的 onnx 模型和 om 模型链接：https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/EfficientDet/models.zip
-
-自行转换模型步骤如下：
-1. 从上述 onnx 模型下载链接中下载 onnx 模型 simplified-efficient-det-d0-mindxsdk-order.onnx 和 simplified-efficient-det-d6-mindxsdk-order.onnx 至 ``python/models/onnx-models`` 文件夹下。
-2. 进入 ``python/models/conversion-scripts`` 文件夹下依次执行命令：
-```
-bash model_conversion_d0.sh
-bash model_conversion_d6.sh
-```
-执行后会在当前文件夹下生成项目需要的模型文件 efficient-det-d0-mindxsdk-order.om 和 efficient-det-d6-mindxsdk-order.om，转换成功的终端输出为：
-```
-ATC start working now, please wait for a moment.
-ATC run success, welcome to the next use.
-
-```
-表示命令执行成功。
-
-### 3.1 可选操作
-上述方法使用提供的 onnx 模型转换得到 om 模型，该模型的输入尺寸是 (512, 512)，若想转换得到其他输入尺寸的模型，或者想从 pytorch 模型转 onnx 模型，相关操作步骤如下：
-1. 从上述参考实现代码链接下载 pytorch 项目文件，执行：
-```
-git clone https://github.com/zylo117/Yet-Another-EfficientDet-Pytorch.git
-```
-或者下载 ZIP 压缩包再解压，在当前目录下得到 ``Yet-Another-EfficientDet-Pytorch-master`` 代码文件夹。
-
-2. 按照参考实现代码链接中的说明配置 pytorch 环境。
-
-3. 将**本项目目录下**的 ``python/models/convert_to_onnx.py`` 文件复制到 ``Yet-Another-EfficientDet-Pytorch-master`` 目录下。
-
-4. 因为源项目中的代码不支持直接从 pth 模型转换成 onnx 模型，参考链接 https://github.com/zylo117/Yet-Another-EfficientDet-Pytorch/issues/111 中的步骤修改相关代码文件。
-
-5. 从上述 github 项目页面给出的模型权重表格中下载 pytorch 模型文件，如 EfficientDet-d0 模型对应 efficientdet-d0.pth, EfficientDet-d1 模型对应 efficientdet-d1.pth，下载好的权重文件放置在 ``Yet-Another-EfficientDet-Pytorch-master/weights`` 目录下。
-
-6. 在``Yet-Another-EfficientDet-Pytorch-master`` 目录下创建 ```onnx-models``` 目录，运行命令：
-```
-python3 convert_to_onnx.py --compound_coef={compound_coef} --load_weights=weights/efficientdet-d{compound_coef}.pth --output-name=efficient-det-d{compound_coef}-mindxsdk-order.onnx
-```
-将命令中 {compound_coef} 替换成具体值，取值范围为 [0, 6]，例如想要转换 efficientdet-d0.pth 为 onnx 模型时，执行命令：
-```
-python3 convert_to_onnx.py --compound_coef=0 --load_weights=weights/efficientdet-d0.pth --output-name=efficient-det-d0-mindxsdk-order.onnx
-```
-执行成功后会 ```onnx-models``` 目录下生成从 pytorch 模型转化得到的 onnx 模型，simplified-efficient-det-d{compound_coef}-mindxsdk-order.onnx 
-
-7. 成功转换得到 onnx 文件后，将 onnx 文件拷贝到**本项目目录下** 的``python/models/onnx-models`` 目录下，然后将其转换为 om 模型，转换步骤如下：
-- 进入 ``python/models/conversion-scripts`` 目录；
-- 执行命令：
-```
-bash model_convertion_d{compound_coef}.sh
-```
-该命令执行成功后会在 ``python/models`` 文件夹下生成对应名称为 efficient-det-d{compound_coef}-mindxsdk-order的 om 模型文件。
-
-## 4. 编译与运行
-
-**步骤1** 按照第 2 小节 **环境依赖** 中的步骤设置环境变量。
-
-**步骤2** 如果使用的是上述链接提供的 onnx 模型或者 om 模型，按照第 3 小节 **模型转换** 中的步骤获得 om 模型文件，放置在 ``python/models`` 目录下。
-
-**步骤3** 编译。在项目目录下执行bash build.sh命令。
-
-此时会生成postprocess/build/libefficientdetpostprocess.so 文件
-
-**步骤4** 图片检测。将一张图片放在项目目录下，命名为 img.jpg，在该图片上进行检测
->**如提示so库异常，则需要从 ```main.py``` 中找到使用的 pipeline 文件路径，将其中 mxpi_objectpostprocessor0 插件的 postProcessLibPath 属性值改为具体路径值**
-
-执行命令：
-```
-cd python
-python3 main.py
-```
-命令执行成功后在当前目录下生成检测结果文件 img_detect_result.jpg，查看结果文件验证检测结果。
-
-**步骤5** 精度测试。
-
-1. 安装 python COCO 评测工具。执行命令：
-```
-pip3 install pycocotools
-```
-
-2. 下载 COCO VAL 2017 数据集和标注文件，下载链接：https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/EfficientDet/data.zip，  在 ``python`` 目录下创建 ``dataset`` 目录，将数据集压缩文件和标注数据压缩文件都解压至 ``python/dataset`` 目录下。确保解压后的 python 目录结构为：
-```
-.
-├── dataset
-│   ├── annotations
-│   │   └── instances_val2017.json
-│   └── val2017
-│       ├── 000000581615.jpg
-│       ├── 000000581781.jpg
-│       └── other-images
-├── evaluate.py
-├── main.py
-├── models
-│   ├── aipp-configs
-│   │   ├── insert_op_d0.cfg
-│   │   ├── insert_op_d0_previous_version.cfg
-│   │   ├── insert_op_d1.cfg
-│   │   ├── insert_op_d2.cfg
-│   │   ├── insert_op_d3.cfg
-│   │   ├── insert_op_d4.cfg
-│   │   ├── insert_op_d5.cfg
-│   │   └── insert_op_d6.cfg
-│   ├── coco.names
-│   ├── conversion-scripts
-│   │   ├── model_conversion_d0_previous_version.sh
-│   │   ├── model_conversion_d0.sh
-│   │   ├── model_conversion_d1.sh
-│   │   ├── model_conversion_d2.sh
-│   │   ├── model_conversion_d3.sh
-│   │   ├── model_conversion_d4.sh
-│   │   ├── model_conversion_d5.sh
-│   │   └── model_conversion_d6.sh
-│   ├── efficient-det.cfg
-│   ├── efficient-det-eval.cfg
-│   └── onnx-models
-└── pipeline
-    ├── EfficientDet-d0.pipeline
-    ├── EfficientDet-d0-previous-version.pipeline
-    ├── EfficientDet-d1.pipeline
-    ├── EfficientDet-d2.pipeline
-    ├── EfficientDet-d3.pipeline
-    ├── EfficientDet-d4.pipeline
-    ├── EfficientDet-d5.pipeline
-    └── EfficientDet-d6.pipeline
-
-```
-
-3. 执行验证 
-
-**从 ```evaluate.py``` 中找到使用的 pipeline 文件路径，将其中 mxpi_objectpostprocessor0 插件的 postProcessLibPath 属性值改为具体路径值，** 然后执行命令：
-```
-cd python
-python3 evaluate.py --pipeline=pipeline/EfficientDet-d0.pipeline --output=val2017_detection_result_d0.json
-```
-命令执行结束后输出 COCO 格式的评测结果，并生成 val2017_detection_result_d0.json 检测结果文件。输出结果如下图所示：
-<center>
-    <img src="./images/EvaluateInfo.png">
-    <br>
-</center>
-其中圈出来的部分为模型在 COCO VAL 2017 数据集上，IOU 阈值为 0.50:0.05:0.95 时的精度值为 0.325。
-
-该指标是基于 MindXSDK 2.0.2.1 版本的评测结果，此时 pipeline 的流程为将 ImageDecoder 插件的输出格式类型设置为 RGB，进入 ImageResize 插件，该插件要想接收 RGB 格式输入必须将 "cvProcessor" 属性设置为 "opencv"，该版本支持同时将 "resizeType" 属性设置为 "Resizer_KeepAspectRatio_Fit"，这样该插件可以实现接收 RGB 格式输入同时按照宽高比例缩放的功能，转换 om 模型时的 aippconfig 配置中 "input_format" 属性值设置为 "RGB888_U8" 即可。
-
-如果项目环境是基于 MindXSDK 2.0.2 版本时，该版本下将 ImageResize 插件的 "cvProcessor" 属性设置为 "opencv" 时，无法实现将 "resizeType" 属性设置为 "Resizer_KeepAspectRatio_Fit", 报错信息参考第 5 节常见问题中的 5.1，这种情形下无法在 pipeline 中配置模型输入为 RGB 格式同时按照宽高比例缩放，只能在转换 om 模型时设置色域转换模式为 YUV420SP_U8 to RGB，使得模型输入为 RGB 格式，同时在 pipeline 中不设置 ImageResize 插件的 "cvProcessor" 属性值，只设置 "resizeType" 属性为 "Resizer_KeepAspectRatio_Fit"，这样可以实现模型输入为 RGB 格式同时按照宽高比例缩放。这种情形下的模型转换和评测步骤为：
-1. 转换模型。进入 ``python/models/conversion-scripts`` 文件夹下执行命令：
-```
-bash model_convertion_d0_previous_version.sh
-```
-执行成功后在 ``python/models`` 文件夹下生成 efficient-det-d0-mindxsdk-order-previous-version.om 模型文件。
-
-2. 评测。将 ```python/pipeline/EfficientDet-d0-previous-version.pipeline``` 中 mxpi_objectpostprocessor0 插件的 postProcessLibPath 属性值中的 ${MX_SDK_HOME} 值改为具体路径值，然后执行命令：
-```
-python3 evaluate.py --pipeline=pipeline/EfficientDet-d0-previous-version.pipeline --output=val2017_detection_result_d0_previous_version.json
-```
-命令执行结束后输出 COCO 格式的评测结果，并生成 val2017_detection_result_d0_previous_version.json 检测结果文件。输出结果如下图所示：
-<center>
-    <img src="./images/EvaluateInfoPrevious.png">
-    <br>
-</center>
-其中圈出来的部分为模型在 COCO VAL 2017 数据集上，IOU 阈值为 0.50:0.05:0.95 时的精度值为 0.310。采用这种 pipeline 配置和模型转换方式得到的 om 模型评测指标会稍有下降，但相应的模型性能会有所提升。
-
-## 5 常见问题
-
-
-### 5.1 MindXSDK 版本问题
-
-**问题描述：**
-
-要求 MindXSDK 的版本至少为 2.0.2.1，否则出现 ImageResize 插件不能设置 "cvProcessor": "opencv" 属性问题，如下图所示：
-<center>
-    <img src="./images/VersionError.png">
-    <br>
-</center>
-
-**解决方案：**
-
-确保 MindXSDK 版本至少为 2.0.2.1。
-
-### 5.2 未修改 pipeline 文件中的 ${MX_SDK_HOME} 值为具体值
-运行检测 demo 和评测时都需要将对应 pipeline 文件中 mxpi_objectpostprocessor0 插件的 postProcessLibPath 属性值中的 ${MX_SDK_HOME} 值改为具体路径值，否则会报错，如下图所示：
-<center>
-    <img src="./images/MindXSDKValueError.png">
-    <br>
-</center>
-
-**解决方案：**
-
-检测 main.py 和 evaluate.py 里所用的 pipeline 文件, 将文件中 mxpi_objectpostprocessor0 插件的 postProcessLibPath 属性值中的 ${MX_SDK_HOME} 值改为具体路径值。
-
-### 5.3 未修改模型文件或生成so的权限
-SDK对运行库so和模型文件有要求，如出现以下报错提示请参考FASQ中相关内容使用chmod指定权限640
-```shell
-Check Owner permission failed: Current permission is 7, but required no greater than 6.
-```
-
-**解决方案：**  
+# EfficientDet 目标检测
+## 1. 介绍
+EfficientDet 目标检测后处理插件基于 MindXSDK 开发，对图片中的不同类目标进行检测，将检测得到的不同类的目标用不同颜色的矩形框标记。输入一幅图像，可以检测得到图像中大部分类别目标的位置。本方案使用在 COCO2017 数据集上训练得到的 EfficientDet 模型进行目标检测，数据集中共包含 90 个目标类，包括行人、自行车、公共汽车、手机、沙发、猫、狗等，可以对不同类别、不同角度、不同密集程度的目标进行检测。
+
+### 1.1 支持的产品
+
+本项目以昇腾Atlas310卡为主要的硬件平台。
+
+
+### 1.2 支持的版本
+
+CANN：7.0.0
+
+SDK：mxVision 5.0.0（可通过cat SDK目录下的 version.info 查看）
+
+
+### 1.3 软件方案介绍
+
+基于MindX SDK的目标检测业务流程为：待检测图片通过 appsrc 插件输入，然后使用图像解码插件 mxpi_imagedecoder 对图片进行解码，再通过图像缩放插件 mxpi_imageresize 将图像缩放至满足检测模型要求的输入图像大小要求，缩放后的图像输入模型推理插件 mxpi_tensorinfer 得到推理结果，推理结果输入 mxpi_objectpostprocessor 插件进行后处理，得到输入图片中所有的目标框位置和对应的置信度。最后通过输出插件 appsink 获取检测结果，并在外部进行可视化，将检测结果标记到原图上，本系统的各模块及功能描述如表1所示：
+
+表1 系统方案各模块功能描述：
+
+| 序号 | 子系统 | 功能描述     |
+| ---- | ------ | ------------ |
+| 1    | 图片输入    | 获取 jpg 格式输入图片 |
+| 2    | 图片解码    | 解码图片 |
+| 3    | 图片缩放    | 将输入图片放缩到模型指定输入的尺寸大小 |
+| 4    | 模型推理    | 对输入张量进行推理 |
+| 5    | 目标检测后处理    | 从模型推理结果计算检测框的位置和置信度，并保留置信度大于指定阈值的检测框作为检测结果 |
+| 6    | 结果输出    | 获取检测结果|
+| 7    | 结果可视化    | 将检测结果标注在输入图片上|
+
+
+
+### 1.4 代码目录结构与说明
+
+本工程名称为 EfficientDet，工程目录如下所示：
+```
+.
+├── build.sh
+├── images
+│   ├── DetectionPipeline.png
+│   ├── EvaluateInfo.png
+│   ├── EvaluateInfoPrevious.png
+│   └── VersionError.png
+├── postprocess
+│   ├── build.sh
+│   ├── CMakeLists.txt
+│   ├── EfficientdetPostProcess.cpp
+│   └── EfficientdetPostProcess.h
+├── python
+│   ├── evaluate.py
+│   ├── main.py
+│   ├── models
+│   │   ├── aipp-configs
+│   │   │   ├── insert_op_d0.cfg
+│   │   │   ├── insert_op_d0_previous_version.cfg
+│   │   │   ├── insert_op_d1.cfg
+│   │   │   ├── insert_op_d2.cfg
+│   │   │   ├── insert_op_d3.cfg
+│   │   │   ├── insert_op_d4.cfg
+│   │   │   ├── insert_op_d5.cfg
+│   │   │   └── insert_op_d6.cfg
+│   │   ├── coco.names
+│   │   ├── conversion-scripts
+│   │   │   ├── model_conversion_d0_previous_version.sh
+│   │   │   ├── model_conversion_d0.sh
+│   │   │   ├── model_conversion_d1.sh
+│   │   │   ├── model_conversion_d2.sh
+│   │   │   ├── model_conversion_d3.sh
+│   │   │   ├── model_conversion_d4.sh
+│   │   │   ├── model_conversion_d5.sh
+│   │   │   └── model_conversion_d6.sh
+│   │   ├── efficient-det.cfg
+│   │   ├── efficient-det-eval.cfg
+│   │   └── onnx-models
+│   └── pipeline
+│       ├── EfficientDet-d0.pipeline
+│       ├── EfficientDet-d0-previous-version.pipeline
+│       ├── EfficientDet-d1.pipeline
+│       ├── EfficientDet-d2.pipeline
+│       ├── EfficientDet-d3.pipeline
+│       ├── EfficientDet-d4.pipeline
+│       ├── EfficientDet-d5.pipeline
+│       └── EfficientDet-d6.pipeline
+└── README.md
+
+```
+
+
+### 1.5 技术实现流程图
+
+EfficientDet 的后处理插件接收模型推理插件输出的两个特征图，位置回归特征图 R 和分类特征图 C，其中 R 的形状大小为 1 x n x 4, n 表示模型在输入图片上预设的 anchors 个数，4 分别表示检测结果矩形框左上角点坐标 x, y 相对预设 anchor 的位移，以及检测框的宽、高相对预设 anchor 的比例，C 的形状大小为 1 x n x 90，90 表示每个检测框属于每个类的置信度值，该值位于 0-1 之间。后处理插件继承自 MindXSDK 的目标检测后处理插件基类，后处理插件中可以获得图片缩放插件传递的图像尺寸缩放信息 ResizedImageInfo，包括缩放前图片宽、高和缩放后图片宽、高。
+后处理插件从模型推理输出 R、C 和图像尺寸缩放信息 ResizedImageInfo 计算检测结果的整体流程如下图所示：
+<center>
+    <img src="./images/DetectionPipeline.png">
+    <br>
+</center>
+
+1. **计算预设 anchors。** 根据 ResizedImageInfo 计算不同宽高比、不同大小、在原图上不同位置的预设 anchors，anchors 的形状为 n x 4, 4 表示每个 anchor 的左上角坐标和宽、高。
+
+2. **根据 R、anchors、ResizedImageInfo、C 计算每个检测框的位置、宽高、类别以及类别置信度。** R 中的每个 4 元向量和 anchors 中每个 4 元向量是对应的，根据坐标位移和宽高比例计算得到真实的检测框位置和宽、高，同时去除置信度小于指定阈值 CT 的检测跨框。
+
+3. **NMS 去除冗余检测框。** 对步骤 2 中剩余的检测框进行筛选，首先按照置信度对保留的检测框排序，从置信度高的检测框开始，去除于其 IOU 值超过指定阈值 IT 的检测框，得到最终的检测结果。
+
+
+## 2 环境依赖
+
+推荐系统为ubuntu 18.04，环境依赖软件和版本如下表：
+
+| 软件名称 | 版本   |
+| -------- | ------ |
+| cmake    | 3.5+   |
+| MindX SDK | 5.0.0    |
+| CANN | 7.0.0 |
+| python   | 3.9.2  |
+| webcolors| 1.11.1 |
+
+确保环境中正确安装mxVision SDK。
+
+在编译运行项目前，需要设置环境变量：
+```
+. {cann_install_path}/ascend-toolkit/set_env.sh
+. {sdk_install_path}/mxVision/set_env.sh
+```
+
+
+
+## 3. 模型转换
+
+本项目中采用的模型是 EfficientDet 模型，参考实现代码：https://github.com/zylo117/Yet-Another-EfficientDet-Pytorch， 选用的模型是该 pytorch 项目中提供的模型 efficientdet-d0.pth，本项目运行前需要将 pytorch 模型转换为 onnx 模型，然后使用模型转换工具 ATC 将 onnx 模型转换为 om 模型，模型转换工具相关介绍参考链接：https://gitee.com/ascend/docs-openmind/blob/master/guide/mindx/sdk/tutorials/%E5%8F%82%E8%80%83%E8%B5%84%E6%96%99.md 。本项目中使用的 onnx 模型和 om 模型链接：https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/EfficientDet/models.zip
+
+自行转换模型步骤如下：
+1. 从上述 onnx 模型下载链接中下载 onnx 模型 simplified-efficient-det-d0-mindxsdk-order.onnx 和 simplified-efficient-det-d6-mindxsdk-order.onnx 至 ``python/models/onnx-models`` 文件夹下。
+2. 进入 ``python/models/conversion-scripts`` 文件夹下依次执行命令：
+```
+bash model_conversion_d0.sh
+bash model_conversion_d6.sh
+```
+执行后会在当前文件夹下生成项目需要的模型文件 efficient-det-d0-mindxsdk-order.om 和 efficient-det-d6-mindxsdk-order.om，转换成功的终端输出为：
+```
+ATC start working now, please wait for a moment.
+ATC run success, welcome to the next use.
+
+```
+表示命令执行成功。
+
+### 3.1 可选操作
+上述方法使用提供的 onnx 模型转换得到 om 模型，该模型的输入尺寸是 (512, 512)，若想转换得到其他输入尺寸的模型，或者想从 pytorch 模型转 onnx 模型，相关操作步骤如下：
+1. 从上述参考实现代码链接下载 pytorch 项目文件，执行：
+```
+git clone https://github.com/zylo117/Yet-Another-EfficientDet-Pytorch.git
+```
+或者下载 ZIP 压缩包再解压，在当前目录下得到 ``Yet-Another-EfficientDet-Pytorch-master`` 代码文件夹。
+
+2. 按照参考实现代码链接中的说明配置 pytorch 环境。
+
+3. 将**本项目目录下**的 ``python/models/convert_to_onnx.py`` 文件复制到 ``Yet-Another-EfficientDet-Pytorch-master`` 目录下。
+
+4. 因为源项目中的代码不支持直接从 pth 模型转换成 onnx 模型，参考链接 https://github.com/zylo117/Yet-Another-EfficientDet-Pytorch/issues/111 中的步骤修改相关代码文件。
+
+5. 从上述 github 项目页面给出的模型权重表格中下载 pytorch 模型文件，如 EfficientDet-d0 模型对应 efficientdet-d0.pth, EfficientDet-d1 模型对应 efficientdet-d1.pth，下载好的权重文件放置在 ``Yet-Another-EfficientDet-Pytorch-master/weights`` 目录下。
+
+6. 在``Yet-Another-EfficientDet-Pytorch-master`` 目录下创建 ```onnx-models``` 目录，运行命令：
+```
+python3 convert_to_onnx.py --compound_coef={compound_coef} --load_weights=weights/efficientdet-d{compound_coef}.pth --output-name=efficient-det-d{compound_coef}-mindxsdk-order.onnx
+```
+将命令中 {compound_coef} 替换成具体值，取值范围为 [0, 6]，例如想要转换 efficientdet-d0.pth 为 onnx 模型时，执行命令：
+```
+python3 convert_to_onnx.py --compound_coef=0 --load_weights=weights/efficientdet-d0.pth --output-name=efficient-det-d0-mindxsdk-order.onnx
+```
+执行成功后会 ```onnx-models``` 目录下生成从 pytorch 模型转化得到的 onnx 模型，simplified-efficient-det-d{compound_coef}-mindxsdk-order.onnx 
+
+7. 成功转换得到 onnx 文件后，将 onnx 文件拷贝到**本项目目录下** 的``python/models/onnx-models`` 目录下，然后将其转换为 om 模型，转换步骤如下：
+- 进入 ``python/models/conversion-scripts`` 目录；
+- 执行命令：
+```
+bash model_convertion_d{compound_coef}.sh
+```
+该命令执行成功后会在 ``python/models`` 文件夹下生成对应名称为 efficient-det-d{compound_coef}-mindxsdk-order的 om 模型文件。
+
+## 4. 编译与运行
+
+**步骤1** 按照第 2 小节 **环境依赖** 中的步骤设置环境变量。
+
+**步骤2** 如果使用的是上述链接提供的 onnx 模型或者 om 模型，按照第 3 小节 **模型转换** 中的步骤获得 om 模型文件，放置在 ``python/models`` 目录下。
+
+**步骤3** 编译。在项目目录下执行bash build.sh命令。
+
+此时会生成postprocess/build/libefficientdetpostprocess.so 文件
+
+**步骤4** 图片检测。将一张图片放在项目目录下，命名为 img.jpg，在该图片上进行检测
+>**如提示so库异常，则需要从 ```main.py``` 中找到使用的 pipeline 文件路径，将其中 mxpi_objectpostprocessor0 插件的 postProcessLibPath 属性值改为具体路径值**
+
+执行命令：
+```
+cd python
+python3 main.py
+```
+命令执行成功后在当前目录下生成检测结果文件 img_detect_result.jpg，查看结果文件验证检测结果。
+
+**步骤5** 精度测试。
+
+1. 安装 python COCO 评测工具。执行命令：
+```
+pip3 install pycocotools
+```
+
+2. 下载 COCO VAL 2017 数据集和标注文件，下载链接：https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/EfficientDet/data.zip，  在 ``python`` 目录下创建 ``dataset`` 目录，将数据集压缩文件和标注数据压缩文件都解压至 ``python/dataset`` 目录下。确保解压后的 python 目录结构为：
+```
+.
+├── dataset
+│   ├── annotations
+│   │   └── instances_val2017.json
+│   └── val2017
+│       ├── 000000581615.jpg
+│       ├── 000000581781.jpg
+│       └── other-images
+├── evaluate.py
+├── main.py
+├── models
+│   ├── aipp-configs
+│   │   ├── insert_op_d0.cfg
+│   │   ├── insert_op_d0_previous_version.cfg
+│   │   ├── insert_op_d1.cfg
+│   │   ├── insert_op_d2.cfg
+│   │   ├── insert_op_d3.cfg
+│   │   ├── insert_op_d4.cfg
+│   │   ├── insert_op_d5.cfg
+│   │   └── insert_op_d6.cfg
+│   ├── coco.names
+│   ├── conversion-scripts
+│   │   ├── model_conversion_d0_previous_version.sh
+│   │   ├── model_conversion_d0.sh
+│   │   ├── model_conversion_d1.sh
+│   │   ├── model_conversion_d2.sh
+│   │   ├── model_conversion_d3.sh
+│   │   ├── model_conversion_d4.sh
+│   │   ├── model_conversion_d5.sh
+│   │   └── model_conversion_d6.sh
+│   ├── efficient-det.cfg
+│   ├── efficient-det-eval.cfg
+│   └── onnx-models
+└── pipeline
+    ├── EfficientDet-d0.pipeline
+    ├── EfficientDet-d0-previous-version.pipeline
+    ├── EfficientDet-d1.pipeline
+    ├── EfficientDet-d2.pipeline
+    ├── EfficientDet-d3.pipeline
+    ├── EfficientDet-d4.pipeline
+    ├── EfficientDet-d5.pipeline
+    └── EfficientDet-d6.pipeline
+
+```
+
+3. 执行验证 
+
+**从 ```evaluate.py``` 中找到使用的 pipeline 文件路径，将其中 mxpi_objectpostprocessor0 插件的 postProcessLibPath 属性值改为具体路径值，** 然后执行命令：
+```
+cd python
+python3 evaluate.py --pipeline=pipeline/EfficientDet-d0.pipeline --output=val2017_detection_result_d0.json
+```
+命令执行结束后输出 COCO 格式的评测结果，并生成 val2017_detection_result_d0.json 检测结果文件。输出结果如下图所示：
+<center>
+    <img src="./images/EvaluateInfo.png">
+    <br>
+</center>
+其中圈出来的部分为模型在 COCO VAL 2017 数据集上，IOU 阈值为 0.50:0.05:0.95 时的精度值为 0.325。
+
+该指标是基于 MindXSDK 2.0.2.1 版本的评测结果，此时 pipeline 的流程为将 ImageDecoder 插件的输出格式类型设置为 RGB，进入 ImageResize 插件，该插件要想接收 RGB 格式输入必须将 "cvProcessor" 属性设置为 "opencv"，该版本支持同时将 "resizeType" 属性设置为 "Resizer_KeepAspectRatio_Fit"，这样该插件可以实现接收 RGB 格式输入同时按照宽高比例缩放的功能，转换 om 模型时的 aippconfig 配置中 "input_format" 属性值设置为 "RGB888_U8" 即可。
+
+如果项目环境是基于 MindXSDK 2.0.2 版本时，该版本下将 ImageResize 插件的 "cvProcessor" 属性设置为 "opencv" 时，无法实现将 "resizeType" 属性设置为 "Resizer_KeepAspectRatio_Fit", 报错信息参考第 5 节常见问题中的 5.1，这种情形下无法在 pipeline 中配置模型输入为 RGB 格式同时按照宽高比例缩放，只能在转换 om 模型时设置色域转换模式为 YUV420SP_U8 to RGB，使得模型输入为 RGB 格式，同时在 pipeline 中不设置 ImageResize 插件的 "cvProcessor" 属性值，只设置 "resizeType" 属性为 "Resizer_KeepAspectRatio_Fit"，这样可以实现模型输入为 RGB 格式同时按照宽高比例缩放。这种情形下的模型转换和评测步骤为：
+1. 转换模型。进入 ``python/models/conversion-scripts`` 文件夹下执行命令：
+```
+bash model_convertion_d0_previous_version.sh
+```
+执行成功后在 ``python/models`` 文件夹下生成 efficient-det-d0-mindxsdk-order-previous-version.om 模型文件。
+
+2. 评测。将 ```python/pipeline/EfficientDet-d0-previous-version.pipeline``` 中 mxpi_objectpostprocessor0 插件的 postProcessLibPath 属性值中的 ${MX_SDK_HOME} 值改为具体路径值，然后执行命令：
+```
+python3 evaluate.py --pipeline=pipeline/EfficientDet-d0-previous-version.pipeline --output=val2017_detection_result_d0_previous_version.json
+```
+命令执行结束后输出 COCO 格式的评测结果，并生成 val2017_detection_result_d0_previous_version.json 检测结果文件。输出结果如下图所示：
+<center>
+    <img src="./images/EvaluateInfoPrevious.png">
+    <br>
+</center>
+其中圈出来的部分为模型在 COCO VAL 2017 数据集上，IOU 阈值为 0.50:0.05:0.95 时的精度值为 0.310。采用这种 pipeline 配置和模型转换方式得到的 om 模型评测指标会稍有下降，但相应的模型性能会有所提升。
+
+## 5 常见问题
+
+
+### 5.1 MindXSDK 版本问题
+
+**问题描述：**
+
+要求 MindXSDK 的版本至少为 2.0.2.1，否则出现 ImageResize 插件不能设置 "cvProcessor": "opencv" 属性问题，如下图所示：
+<center>
+    <img src="./images/VersionError.png">
+    <br>
+</center>
+
+**解决方案：**
+
+确保 MindXSDK 版本至少为 2.0.2.1。
+
+### 5.2 未修改 pipeline 文件中的 ${MX_SDK_HOME} 值为具体值
+运行检测 demo 和评测时都需要将对应 pipeline 文件中 mxpi_objectpostprocessor0 插件的 postProcessLibPath 属性值中的 ${MX_SDK_HOME} 值改为具体路径值，否则会报错，如下图所示：
+<center>
+    <img src="./images/MindXSDKValueError.png">
+    <br>
+</center>
+
+**解决方案：**
+
+检测 main.py 和 evaluate.py 里所用的 pipeline 文件, 将文件中 mxpi_objectpostprocessor0 插件的 postProcessLibPath 属性值中的 ${MX_SDK_HOME} 值改为具体路径值。
+
+### 5.3 未修改模型文件或生成so的权限
+SDK对运行库so和模型文件有要求，如出现以下报错提示请参考FASQ中相关内容使用chmod指定权限640
+```shell
+Check Owner permission failed: Current permission is 7, but required no greater than 6.
+```
+
+**解决方案：**  
 cd到对应目录并指定相关文件权限为640
\ No newline at end of file
diff --git a/contrib/EfficientDet/build.sh b/mxVision/mxVision-referenceapps/EfficientDet/build.sh
similarity index 100%
rename from contrib/EfficientDet/build.sh
rename to mxVision/mxVision-referenceapps/EfficientDet/build.sh
diff --git a/contrib/EfficientDet/images/DetectionPipeline.png b/mxVision/mxVision-referenceapps/EfficientDet/images/DetectionPipeline.png
similarity index 100%
rename from contrib/EfficientDet/images/DetectionPipeline.png
rename to mxVision/mxVision-referenceapps/EfficientDet/images/DetectionPipeline.png
diff --git a/contrib/EfficientDet/images/EvaluateInfo.png b/mxVision/mxVision-referenceapps/EfficientDet/images/EvaluateInfo.png
similarity index 100%
rename from contrib/EfficientDet/images/EvaluateInfo.png
rename to mxVision/mxVision-referenceapps/EfficientDet/images/EvaluateInfo.png
diff --git a/contrib/EfficientDet/images/EvaluateInfoPrevious.png b/mxVision/mxVision-referenceapps/EfficientDet/images/EvaluateInfoPrevious.png
similarity index 100%
rename from contrib/EfficientDet/images/EvaluateInfoPrevious.png
rename to mxVision/mxVision-referenceapps/EfficientDet/images/EvaluateInfoPrevious.png
diff --git a/contrib/EfficientDet/images/MindXSDKValueError.png b/mxVision/mxVision-referenceapps/EfficientDet/images/MindXSDKValueError.png
similarity index 100%
rename from contrib/EfficientDet/images/MindXSDKValueError.png
rename to mxVision/mxVision-referenceapps/EfficientDet/images/MindXSDKValueError.png
diff --git a/contrib/EfficientDet/images/VersionError.png b/mxVision/mxVision-referenceapps/EfficientDet/images/VersionError.png
similarity index 100%
rename from contrib/EfficientDet/images/VersionError.png
rename to mxVision/mxVision-referenceapps/EfficientDet/images/VersionError.png
diff --git a/contrib/EfficientDet/postprocess/CMakeLists.txt b/mxVision/mxVision-referenceapps/EfficientDet/postprocess/CMakeLists.txt
similarity index 100%
rename from contrib/EfficientDet/postprocess/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/EfficientDet/postprocess/CMakeLists.txt
diff --git a/contrib/EfficientDet/postprocess/EfficientdetPostProcess.cpp b/mxVision/mxVision-referenceapps/EfficientDet/postprocess/EfficientdetPostProcess.cpp
similarity index 100%
rename from contrib/EfficientDet/postprocess/EfficientdetPostProcess.cpp
rename to mxVision/mxVision-referenceapps/EfficientDet/postprocess/EfficientdetPostProcess.cpp
diff --git a/contrib/EfficientDet/postprocess/EfficientdetPostProcess.h b/mxVision/mxVision-referenceapps/EfficientDet/postprocess/EfficientdetPostProcess.h
similarity index 100%
rename from contrib/EfficientDet/postprocess/EfficientdetPostProcess.h
rename to mxVision/mxVision-referenceapps/EfficientDet/postprocess/EfficientdetPostProcess.h
diff --git a/contrib/EfficientDet/postprocess/build.sh b/mxVision/mxVision-referenceapps/EfficientDet/postprocess/build.sh
similarity index 100%
rename from contrib/EfficientDet/postprocess/build.sh
rename to mxVision/mxVision-referenceapps/EfficientDet/postprocess/build.sh
diff --git a/contrib/EfficientDet/python/evaluate.py b/mxVision/mxVision-referenceapps/EfficientDet/python/evaluate.py
similarity index 100%
rename from contrib/EfficientDet/python/evaluate.py
rename to mxVision/mxVision-referenceapps/EfficientDet/python/evaluate.py
diff --git a/contrib/EfficientDet/python/main.py b/mxVision/mxVision-referenceapps/EfficientDet/python/main.py
similarity index 100%
rename from contrib/EfficientDet/python/main.py
rename to mxVision/mxVision-referenceapps/EfficientDet/python/main.py
diff --git a/contrib/EfficientDet/python/models/aipp-configs/insert_op_d0.cfg b/mxVision/mxVision-referenceapps/EfficientDet/python/models/aipp-configs/insert_op_d0.cfg
similarity index 95%
rename from contrib/EfficientDet/python/models/aipp-configs/insert_op_d0.cfg
rename to mxVision/mxVision-referenceapps/EfficientDet/python/models/aipp-configs/insert_op_d0.cfg
index a5a0835723febedcbb055f04fbcc3fb78cb59174..55c835aee12ec6a21a3533a8c06a5a175b4c1261 100644
--- a/contrib/EfficientDet/python/models/aipp-configs/insert_op_d0.cfg
+++ b/mxVision/mxVision-referenceapps/EfficientDet/python/models/aipp-configs/insert_op_d0.cfg
@@ -1,18 +1,18 @@
-aipp_op {
-    aipp_mode: static
-    related_input_rank: 0
-    src_image_size_w: 512
-    src_image_size_h: 512
-    input_format : RGB888_U8
-    csc_switch : false
-    rbuv_swap_switch : false
-    mean_chn_0: 124
-    mean_chn_1: 116
-    mean_chn_2: 104
-    min_chn_0: 0.0
-    min_chn_1: 0.0
-    min_chn_2: 0.0
-    var_reci_chn_0: 0.01712475
-    var_reci_chn_1: 0.01750700
-    var_reci_chn_2: 0.01742919
-}
+aipp_op {
+    aipp_mode: static
+    related_input_rank: 0
+    src_image_size_w: 512
+    src_image_size_h: 512
+    input_format : RGB888_U8
+    csc_switch : false
+    rbuv_swap_switch : false
+    mean_chn_0: 124
+    mean_chn_1: 116
+    mean_chn_2: 104
+    min_chn_0: 0.0
+    min_chn_1: 0.0
+    min_chn_2: 0.0
+    var_reci_chn_0: 0.01712475
+    var_reci_chn_1: 0.01750700
+    var_reci_chn_2: 0.01742919
+}
diff --git a/contrib/EfficientDet/python/models/aipp-configs/insert_op_d0_previous_version.cfg b/mxVision/mxVision-referenceapps/EfficientDet/python/models/aipp-configs/insert_op_d0_previous_version.cfg
similarity index 95%
rename from contrib/EfficientDet/python/models/aipp-configs/insert_op_d0_previous_version.cfg
rename to mxVision/mxVision-referenceapps/EfficientDet/python/models/aipp-configs/insert_op_d0_previous_version.cfg
index 92ddb23e6d3f43244efdff470a9011c9374bcf48..ce99b71e7522234a7c61ae1f67b702797b5667d4 100644
--- a/contrib/EfficientDet/python/models/aipp-configs/insert_op_d0_previous_version.cfg
+++ b/mxVision/mxVision-referenceapps/EfficientDet/python/models/aipp-configs/insert_op_d0_previous_version.cfg
@@ -1,31 +1,31 @@
-aipp_op {
-    aipp_mode: static
-    related_input_rank: 0
-    src_image_size_w: 512
-    src_image_size_h: 512
-    crop: false
-    input_format : YUV420SP_U8
-    csc_switch : true
-    rbuv_swap_switch : false
-    matrix_r0c0 : 256
-    matrix_r0c1 : 0
-    matrix_r0c2 : 359
-    matrix_r1c0 : 256
-    matrix_r1c1 : -88
-    matrix_r1c2 : -183
-    matrix_r2c0 : 256
-    matrix_r2c1 : 454
-    matrix_r2c2 : 0
-    input_bias_0 : 0
-    input_bias_1 : 128
-    input_bias_2 : 128
-    mean_chn_0: 124
-    mean_chn_1: 116
-    mean_chn_2: 104
-    min_chn_0: 0.0
-    min_chn_1: 0.0
-    min_chn_2: 0.0
-    var_reci_chn_0: 0.01712475
-    var_reci_chn_1: 0.01750700
-    var_reci_chn_2: 0.01742919
-}
+aipp_op {
+    aipp_mode: static
+    related_input_rank: 0
+    src_image_size_w: 512
+    src_image_size_h: 512
+    crop: false
+    input_format : YUV420SP_U8
+    csc_switch : true
+    rbuv_swap_switch : false
+    matrix_r0c0 : 256
+    matrix_r0c1 : 0
+    matrix_r0c2 : 359
+    matrix_r1c0 : 256
+    matrix_r1c1 : -88
+    matrix_r1c2 : -183
+    matrix_r2c0 : 256
+    matrix_r2c1 : 454
+    matrix_r2c2 : 0
+    input_bias_0 : 0
+    input_bias_1 : 128
+    input_bias_2 : 128
+    mean_chn_0: 124
+    mean_chn_1: 116
+    mean_chn_2: 104
+    min_chn_0: 0.0
+    min_chn_1: 0.0
+    min_chn_2: 0.0
+    var_reci_chn_0: 0.01712475
+    var_reci_chn_1: 0.01750700
+    var_reci_chn_2: 0.01742919
+}
diff --git a/contrib/EfficientDet/python/models/aipp-configs/insert_op_d1.cfg b/mxVision/mxVision-referenceapps/EfficientDet/python/models/aipp-configs/insert_op_d1.cfg
similarity index 95%
rename from contrib/EfficientDet/python/models/aipp-configs/insert_op_d1.cfg
rename to mxVision/mxVision-referenceapps/EfficientDet/python/models/aipp-configs/insert_op_d1.cfg
index 027dbf22a3da146f0b1270a33782a69ec3656763..535d7840d49c9c2b6559c369d5a0961e274c604a 100644
--- a/contrib/EfficientDet/python/models/aipp-configs/insert_op_d1.cfg
+++ b/mxVision/mxVision-referenceapps/EfficientDet/python/models/aipp-configs/insert_op_d1.cfg
@@ -1,18 +1,18 @@
-aipp_op {
-    aipp_mode: static
-    related_input_rank: 0
-    src_image_size_w: 640
-    src_image_size_h: 640
-    input_format : RGB888_U8
-    csc_switch : false
-    rbuv_swap_switch : false
-    mean_chn_0: 124
-    mean_chn_1: 116
-    mean_chn_2: 104
-    min_chn_0: 0.0
-    min_chn_1: 0.0
-    min_chn_2: 0.0
-    var_reci_chn_0: 0.01712475
-    var_reci_chn_1: 0.01750700
-    var_reci_chn_2: 0.01742919
-}
+aipp_op {
+    aipp_mode: static
+    related_input_rank: 0
+    src_image_size_w: 640
+    src_image_size_h: 640
+    input_format : RGB888_U8
+    csc_switch : false
+    rbuv_swap_switch : false
+    mean_chn_0: 124
+    mean_chn_1: 116
+    mean_chn_2: 104
+    min_chn_0: 0.0
+    min_chn_1: 0.0
+    min_chn_2: 0.0
+    var_reci_chn_0: 0.01712475
+    var_reci_chn_1: 0.01750700
+    var_reci_chn_2: 0.01742919
+}
diff --git a/contrib/EfficientDet/python/models/aipp-configs/insert_op_d2.cfg b/mxVision/mxVision-referenceapps/EfficientDet/python/models/aipp-configs/insert_op_d2.cfg
similarity index 95%
rename from contrib/EfficientDet/python/models/aipp-configs/insert_op_d2.cfg
rename to mxVision/mxVision-referenceapps/EfficientDet/python/models/aipp-configs/insert_op_d2.cfg
index 1d2ad3040b3adc47c4257928f8c1de99881b3394..0ad93dc3e38c621978b41c2d5701d84306aff241 100644
--- a/contrib/EfficientDet/python/models/aipp-configs/insert_op_d2.cfg
+++ b/mxVision/mxVision-referenceapps/EfficientDet/python/models/aipp-configs/insert_op_d2.cfg
@@ -1,18 +1,18 @@
-aipp_op {
-    aipp_mode: static
-    related_input_rank: 0
-    src_image_size_w: 768
-    src_image_size_h: 768
-    input_format : RGB888_U8
-    csc_switch : false
-    rbuv_swap_switch : false
-    mean_chn_0: 124
-    mean_chn_1: 116
-    mean_chn_2: 104
-    min_chn_0: 0.0
-    min_chn_1: 0.0
-    min_chn_2: 0.0
-    var_reci_chn_0: 0.01712475
-    var_reci_chn_1: 0.01750700
-    var_reci_chn_2: 0.01742919
-}
+aipp_op {
+    aipp_mode: static
+    related_input_rank: 0
+    src_image_size_w: 768
+    src_image_size_h: 768
+    input_format : RGB888_U8
+    csc_switch : false
+    rbuv_swap_switch : false
+    mean_chn_0: 124
+    mean_chn_1: 116
+    mean_chn_2: 104
+    min_chn_0: 0.0
+    min_chn_1: 0.0
+    min_chn_2: 0.0
+    var_reci_chn_0: 0.01712475
+    var_reci_chn_1: 0.01750700
+    var_reci_chn_2: 0.01742919
+}
diff --git a/contrib/EfficientDet/python/models/aipp-configs/insert_op_d3.cfg b/mxVision/mxVision-referenceapps/EfficientDet/python/models/aipp-configs/insert_op_d3.cfg
similarity index 95%
rename from contrib/EfficientDet/python/models/aipp-configs/insert_op_d3.cfg
rename to mxVision/mxVision-referenceapps/EfficientDet/python/models/aipp-configs/insert_op_d3.cfg
index 597ec2c6797531427b82bf40c933345fe6941b23..5eadace54f762a66a634011b5dde7dc95a0e1f8e 100644
--- a/contrib/EfficientDet/python/models/aipp-configs/insert_op_d3.cfg
+++ b/mxVision/mxVision-referenceapps/EfficientDet/python/models/aipp-configs/insert_op_d3.cfg
@@ -1,18 +1,18 @@
-aipp_op {
-    aipp_mode: static
-    related_input_rank: 0
-    src_image_size_w: 896
-    src_image_size_h: 896
-    input_format : RGB888_U8
-    csc_switch : false
-    rbuv_swap_switch : false
-    mean_chn_0: 124
-    mean_chn_1: 116
-    mean_chn_2: 104
-    min_chn_0: 0.0
-    min_chn_1: 0.0
-    min_chn_2: 0.0
-    var_reci_chn_0: 0.01712475
-    var_reci_chn_1: 0.01750700
-    var_reci_chn_2: 0.01742919
-}
+aipp_op {
+    aipp_mode: static
+    related_input_rank: 0
+    src_image_size_w: 896
+    src_image_size_h: 896
+    input_format : RGB888_U8
+    csc_switch : false
+    rbuv_swap_switch : false
+    mean_chn_0: 124
+    mean_chn_1: 116
+    mean_chn_2: 104
+    min_chn_0: 0.0
+    min_chn_1: 0.0
+    min_chn_2: 0.0
+    var_reci_chn_0: 0.01712475
+    var_reci_chn_1: 0.01750700
+    var_reci_chn_2: 0.01742919
+}
diff --git a/contrib/EfficientDet/python/models/aipp-configs/insert_op_d4.cfg b/mxVision/mxVision-referenceapps/EfficientDet/python/models/aipp-configs/insert_op_d4.cfg
similarity index 95%
rename from contrib/EfficientDet/python/models/aipp-configs/insert_op_d4.cfg
rename to mxVision/mxVision-referenceapps/EfficientDet/python/models/aipp-configs/insert_op_d4.cfg
index 1452d7f7e4cdfc27ef5f2469711d6b62d717d4fd..960500094e42a21d96f7a38523654b0da2c9ebd8 100644
--- a/contrib/EfficientDet/python/models/aipp-configs/insert_op_d4.cfg
+++ b/mxVision/mxVision-referenceapps/EfficientDet/python/models/aipp-configs/insert_op_d4.cfg
@@ -1,18 +1,18 @@
-aipp_op {
-    aipp_mode: static
-    related_input_rank: 0
-    src_image_size_w: 1024
-    src_image_size_h: 1024
-    input_format : RGB888_U8
-    csc_switch : false
-    rbuv_swap_switch : false
-    mean_chn_0: 124
-    mean_chn_1: 116
-    mean_chn_2: 104
-    min_chn_0: 0.0
-    min_chn_1: 0.0
-    min_chn_2: 0.0
-    var_reci_chn_0: 0.01712475
-    var_reci_chn_1: 0.01750700
-    var_reci_chn_2: 0.01742919
-}
+aipp_op {
+    aipp_mode: static
+    related_input_rank: 0
+    src_image_size_w: 1024
+    src_image_size_h: 1024
+    input_format : RGB888_U8
+    csc_switch : false
+    rbuv_swap_switch : false
+    mean_chn_0: 124
+    mean_chn_1: 116
+    mean_chn_2: 104
+    min_chn_0: 0.0
+    min_chn_1: 0.0
+    min_chn_2: 0.0
+    var_reci_chn_0: 0.01712475
+    var_reci_chn_1: 0.01750700
+    var_reci_chn_2: 0.01742919
+}
diff --git a/contrib/EfficientDet/python/models/aipp-configs/insert_op_d5.cfg b/mxVision/mxVision-referenceapps/EfficientDet/python/models/aipp-configs/insert_op_d5.cfg
similarity index 95%
rename from contrib/EfficientDet/python/models/aipp-configs/insert_op_d5.cfg
rename to mxVision/mxVision-referenceapps/EfficientDet/python/models/aipp-configs/insert_op_d5.cfg
index a4d822f2f2dc202724e2e83ec4f3f3b9ed9bf7b8..21a1e504fcb5fba8c541a83e1cfc22548afb52a1 100644
--- a/contrib/EfficientDet/python/models/aipp-configs/insert_op_d5.cfg
+++ b/mxVision/mxVision-referenceapps/EfficientDet/python/models/aipp-configs/insert_op_d5.cfg
@@ -1,18 +1,18 @@
-aipp_op {
-    aipp_mode: static
-    related_input_rank: 0
-    src_image_size_w: 1280
-    src_image_size_h: 1280
-    input_format : RGB888_U8
-    csc_switch : false
-    rbuv_swap_switch : false
-    mean_chn_0: 124
-    mean_chn_1: 116
-    mean_chn_2: 104
-    min_chn_0: 0.0
-    min_chn_1: 0.0
-    min_chn_2: 0.0
-    var_reci_chn_0: 0.01712475
-    var_reci_chn_1: 0.01750700
-    var_reci_chn_2: 0.01742919
-}
+aipp_op {
+    aipp_mode: static
+    related_input_rank: 0
+    src_image_size_w: 1280
+    src_image_size_h: 1280
+    input_format : RGB888_U8
+    csc_switch : false
+    rbuv_swap_switch : false
+    mean_chn_0: 124
+    mean_chn_1: 116
+    mean_chn_2: 104
+    min_chn_0: 0.0
+    min_chn_1: 0.0
+    min_chn_2: 0.0
+    var_reci_chn_0: 0.01712475
+    var_reci_chn_1: 0.01750700
+    var_reci_chn_2: 0.01742919
+}
diff --git a/contrib/EfficientDet/python/models/aipp-configs/insert_op_d6.cfg b/mxVision/mxVision-referenceapps/EfficientDet/python/models/aipp-configs/insert_op_d6.cfg
similarity index 95%
rename from contrib/EfficientDet/python/models/aipp-configs/insert_op_d6.cfg
rename to mxVision/mxVision-referenceapps/EfficientDet/python/models/aipp-configs/insert_op_d6.cfg
index a4d822f2f2dc202724e2e83ec4f3f3b9ed9bf7b8..21a1e504fcb5fba8c541a83e1cfc22548afb52a1 100644
--- a/contrib/EfficientDet/python/models/aipp-configs/insert_op_d6.cfg
+++ b/mxVision/mxVision-referenceapps/EfficientDet/python/models/aipp-configs/insert_op_d6.cfg
@@ -1,18 +1,18 @@
-aipp_op {
-    aipp_mode: static
-    related_input_rank: 0
-    src_image_size_w: 1280
-    src_image_size_h: 1280
-    input_format : RGB888_U8
-    csc_switch : false
-    rbuv_swap_switch : false
-    mean_chn_0: 124
-    mean_chn_1: 116
-    mean_chn_2: 104
-    min_chn_0: 0.0
-    min_chn_1: 0.0
-    min_chn_2: 0.0
-    var_reci_chn_0: 0.01712475
-    var_reci_chn_1: 0.01750700
-    var_reci_chn_2: 0.01742919
-}
+aipp_op {
+    aipp_mode: static
+    related_input_rank: 0
+    src_image_size_w: 1280
+    src_image_size_h: 1280
+    input_format : RGB888_U8
+    csc_switch : false
+    rbuv_swap_switch : false
+    mean_chn_0: 124
+    mean_chn_1: 116
+    mean_chn_2: 104
+    min_chn_0: 0.0
+    min_chn_1: 0.0
+    min_chn_2: 0.0
+    var_reci_chn_0: 0.01712475
+    var_reci_chn_1: 0.01750700
+    var_reci_chn_2: 0.01742919
+}
diff --git a/contrib/EfficientDet/python/models/coco.names b/mxVision/mxVision-referenceapps/EfficientDet/python/models/coco.names
similarity index 100%
rename from contrib/EfficientDet/python/models/coco.names
rename to mxVision/mxVision-referenceapps/EfficientDet/python/models/coco.names
diff --git a/contrib/EfficientDet/python/models/conversion-scripts/model_conversion_d0.sh b/mxVision/mxVision-referenceapps/EfficientDet/python/models/conversion-scripts/model_conversion_d0.sh
similarity index 100%
rename from contrib/EfficientDet/python/models/conversion-scripts/model_conversion_d0.sh
rename to mxVision/mxVision-referenceapps/EfficientDet/python/models/conversion-scripts/model_conversion_d0.sh
diff --git a/contrib/EfficientDet/python/models/conversion-scripts/model_conversion_d0_previous_version.sh b/mxVision/mxVision-referenceapps/EfficientDet/python/models/conversion-scripts/model_conversion_d0_previous_version.sh
similarity index 100%
rename from contrib/EfficientDet/python/models/conversion-scripts/model_conversion_d0_previous_version.sh
rename to mxVision/mxVision-referenceapps/EfficientDet/python/models/conversion-scripts/model_conversion_d0_previous_version.sh
diff --git a/contrib/EfficientDet/python/models/conversion-scripts/model_conversion_d1.sh b/mxVision/mxVision-referenceapps/EfficientDet/python/models/conversion-scripts/model_conversion_d1.sh
similarity index 100%
rename from contrib/EfficientDet/python/models/conversion-scripts/model_conversion_d1.sh
rename to mxVision/mxVision-referenceapps/EfficientDet/python/models/conversion-scripts/model_conversion_d1.sh
diff --git a/contrib/EfficientDet/python/models/conversion-scripts/model_conversion_d2.sh b/mxVision/mxVision-referenceapps/EfficientDet/python/models/conversion-scripts/model_conversion_d2.sh
similarity index 100%
rename from contrib/EfficientDet/python/models/conversion-scripts/model_conversion_d2.sh
rename to mxVision/mxVision-referenceapps/EfficientDet/python/models/conversion-scripts/model_conversion_d2.sh
diff --git a/contrib/EfficientDet/python/models/conversion-scripts/model_conversion_d3.sh b/mxVision/mxVision-referenceapps/EfficientDet/python/models/conversion-scripts/model_conversion_d3.sh
similarity index 100%
rename from contrib/EfficientDet/python/models/conversion-scripts/model_conversion_d3.sh
rename to mxVision/mxVision-referenceapps/EfficientDet/python/models/conversion-scripts/model_conversion_d3.sh
diff --git a/contrib/EfficientDet/python/models/conversion-scripts/model_conversion_d4.sh b/mxVision/mxVision-referenceapps/EfficientDet/python/models/conversion-scripts/model_conversion_d4.sh
similarity index 100%
rename from contrib/EfficientDet/python/models/conversion-scripts/model_conversion_d4.sh
rename to mxVision/mxVision-referenceapps/EfficientDet/python/models/conversion-scripts/model_conversion_d4.sh
diff --git a/contrib/EfficientDet/python/models/conversion-scripts/model_conversion_d5.sh b/mxVision/mxVision-referenceapps/EfficientDet/python/models/conversion-scripts/model_conversion_d5.sh
similarity index 100%
rename from contrib/EfficientDet/python/models/conversion-scripts/model_conversion_d5.sh
rename to mxVision/mxVision-referenceapps/EfficientDet/python/models/conversion-scripts/model_conversion_d5.sh
diff --git a/contrib/EfficientDet/python/models/conversion-scripts/model_conversion_d6.sh b/mxVision/mxVision-referenceapps/EfficientDet/python/models/conversion-scripts/model_conversion_d6.sh
similarity index 100%
rename from contrib/EfficientDet/python/models/conversion-scripts/model_conversion_d6.sh
rename to mxVision/mxVision-referenceapps/EfficientDet/python/models/conversion-scripts/model_conversion_d6.sh
diff --git a/contrib/EfficientDet/python/models/convert_to_onnx.py b/mxVision/mxVision-referenceapps/EfficientDet/python/models/convert_to_onnx.py
similarity index 100%
rename from contrib/EfficientDet/python/models/convert_to_onnx.py
rename to mxVision/mxVision-referenceapps/EfficientDet/python/models/convert_to_onnx.py
diff --git a/contrib/EfficientDet/python/models/efficient-det-eval.cfg b/mxVision/mxVision-referenceapps/EfficientDet/python/models/efficient-det-eval.cfg
similarity index 100%
rename from contrib/EfficientDet/python/models/efficient-det-eval.cfg
rename to mxVision/mxVision-referenceapps/EfficientDet/python/models/efficient-det-eval.cfg
diff --git a/contrib/EfficientDet/python/models/efficient-det.cfg b/mxVision/mxVision-referenceapps/EfficientDet/python/models/efficient-det.cfg
similarity index 100%
rename from contrib/EfficientDet/python/models/efficient-det.cfg
rename to mxVision/mxVision-referenceapps/EfficientDet/python/models/efficient-det.cfg
diff --git a/contrib/EfficientDet/python/pipeline/EfficientDet-d0-previous-version.pipeline b/mxVision/mxVision-referenceapps/EfficientDet/python/pipeline/EfficientDet-d0-previous-version.pipeline
similarity index 96%
rename from contrib/EfficientDet/python/pipeline/EfficientDet-d0-previous-version.pipeline
rename to mxVision/mxVision-referenceapps/EfficientDet/python/pipeline/EfficientDet-d0-previous-version.pipeline
index e42934ea14aedc13ca154c7728e4ea657b58e7c1..d9a3e6dc9236437d2506a1b2faa77992ef4277e7 100644
--- a/contrib/EfficientDet/python/pipeline/EfficientDet-d0-previous-version.pipeline
+++ b/mxVision/mxVision-referenceapps/EfficientDet/python/pipeline/EfficientDet-d0-previous-version.pipeline
@@ -1,56 +1,56 @@
-{
-    "detection": {
-        "stream_config": {
-            "deviceId": "0"
-        },
-        "appsrc0": {
-            "props": {
-                "blocksize": "409600"
-            },
-            "factory": "appsrc",
-            "next": "mxpi_imagedecoder0"
-        },
-        "mxpi_imagedecoder0": {
-            "props": {
-                "deviceId": "0"
-            },
-            "factory": "mxpi_imagedecoder",
-            "next": "mxpi_imageresize0"
-        },
-        "mxpi_imageresize0": {
-            "props": {
-                "dataSource": "mxpi_imagedecoder0",
-                "resizeType": "Resizer_KeepAspectRatio_Fit",
-                "resizeHeight": "512",
-                "resizeWidth": "512",
-                "interpolation": "3"
-            },
-            "factory": "mxpi_imageresize",
-            "next": "mxpi_tensorinfer0"
-        },
-        "mxpi_tensorinfer0": {
-            "props": {
-                "dataSource": "mxpi_imageresize0",
-                "modelPath": "models/efficient-det-d0-mindxsdk-order-previous-version.om"
-            },
-            "factory": "mxpi_tensorinfer",
-            "next": "mxpi_objectpostprocessor0"
-        },
-        "mxpi_objectpostprocessor0": {
-            "props": {
-                "dataSource": "mxpi_tensorinfer0",
-                "postProcessConfigPath": "models/efficient-det-eval.cfg",
-                "labelPath": "models/coco.names",
-                "postProcessLibPath": "postprocess/build/libefficientdetpostprocess.so"
-            },
-            "factory": "mxpi_objectpostprocessor",
-            "next": "appsink0"
-        },
-        "appsink0": {
-            "props": {
-                "blocksize": "4096000"
-            },
-            "factory": "appsink"
-        }
-    }
-}
+{
+    "detection": {
+        "stream_config": {
+            "deviceId": "0"
+        },
+        "appsrc0": {
+            "props": {
+                "blocksize": "409600"
+            },
+            "factory": "appsrc",
+            "next": "mxpi_imagedecoder0"
+        },
+        "mxpi_imagedecoder0": {
+            "props": {
+                "deviceId": "0"
+            },
+            "factory": "mxpi_imagedecoder",
+            "next": "mxpi_imageresize0"
+        },
+        "mxpi_imageresize0": {
+            "props": {
+                "dataSource": "mxpi_imagedecoder0",
+                "resizeType": "Resizer_KeepAspectRatio_Fit",
+                "resizeHeight": "512",
+                "resizeWidth": "512",
+                "interpolation": "3"
+            },
+            "factory": "mxpi_imageresize",
+            "next": "mxpi_tensorinfer0"
+        },
+        "mxpi_tensorinfer0": {
+            "props": {
+                "dataSource": "mxpi_imageresize0",
+                "modelPath": "models/efficient-det-d0-mindxsdk-order-previous-version.om"
+            },
+            "factory": "mxpi_tensorinfer",
+            "next": "mxpi_objectpostprocessor0"
+        },
+        "mxpi_objectpostprocessor0": {
+            "props": {
+                "dataSource": "mxpi_tensorinfer0",
+                "postProcessConfigPath": "models/efficient-det-eval.cfg",
+                "labelPath": "models/coco.names",
+                "postProcessLibPath": "postprocess/build/libefficientdetpostprocess.so"
+            },
+            "factory": "mxpi_objectpostprocessor",
+            "next": "appsink0"
+        },
+        "appsink0": {
+            "props": {
+                "blocksize": "4096000"
+            },
+            "factory": "appsink"
+        }
+    }
+}
diff --git a/contrib/EfficientDet/python/pipeline/EfficientDet-d0.pipeline b/mxVision/mxVision-referenceapps/EfficientDet/python/pipeline/EfficientDet-d0.pipeline
similarity index 96%
rename from contrib/EfficientDet/python/pipeline/EfficientDet-d0.pipeline
rename to mxVision/mxVision-referenceapps/EfficientDet/python/pipeline/EfficientDet-d0.pipeline
index e48fc680e03fa39154e74715b1e4fe0a47519e17..1a9ed1df73bfd2e0d0a8773df562c52286882d48 100644
--- a/contrib/EfficientDet/python/pipeline/EfficientDet-d0.pipeline
+++ b/mxVision/mxVision-referenceapps/EfficientDet/python/pipeline/EfficientDet-d0.pipeline
@@ -1,58 +1,58 @@
-{
-    "detection": {
-        "stream_config": {
-            "deviceId": "0"
-        },
-        "appsrc0": {
-            "props": {
-                "blocksize": "409600"
-            },
-            "factory": "appsrc",
-            "next": "mxpi_imagedecoder0"
-        },
-        "mxpi_imagedecoder0": {
-            "props": {
-                "deviceId": "0",
-                "cvProcessor": "opencv",
-                "outputDataFormat": "RGB"
-            },
-            "factory": "mxpi_imagedecoder",
-            "next": "mxpi_imageresize0"
-        },
-        "mxpi_imageresize0": {
-            "props": {
-                "dataSource": "mxpi_imagedecoder0",
-                "resizeType": "Resizer_KeepAspectRatio_Fit",
-                "resizeHeight": "512",
-                "resizeWidth": "512",
-                "cvProcessor": "opencv"
-            },
-            "factory": "mxpi_imageresize",
-            "next": "mxpi_tensorinfer0"
-        },
-        "mxpi_tensorinfer0": {
-            "props": {
-                "dataSource": "mxpi_imageresize0",
-                "modelPath": "models/efficient-det-d0-mindxsdk-order.om"
-            },
-            "factory": "mxpi_tensorinfer",
-            "next": "mxpi_objectpostprocessor0"
-        },
-        "mxpi_objectpostprocessor0": {
-            "props": {
-                "dataSource": "mxpi_tensorinfer0",
-                "postProcessConfigPath": "models/efficient-det-eval.cfg",
-                "labelPath": "models/coco.names",
-                "postProcessLibPath": "postprocess/build/libefficientdetpostprocess.so"
-            },
-            "factory": "mxpi_objectpostprocessor",
-            "next": "appsink0"
-        },
-        "appsink0": {
-            "props": {
-                "blocksize": "4096000"
-            },
-            "factory": "appsink"
-        }
-    }
-}
+{
+    "detection": {
+        "stream_config": {
+            "deviceId": "0"
+        },
+        "appsrc0": {
+            "props": {
+                "blocksize": "409600"
+            },
+            "factory": "appsrc",
+            "next": "mxpi_imagedecoder0"
+        },
+        "mxpi_imagedecoder0": {
+            "props": {
+                "deviceId": "0",
+                "cvProcessor": "opencv",
+                "outputDataFormat": "RGB"
+            },
+            "factory": "mxpi_imagedecoder",
+            "next": "mxpi_imageresize0"
+        },
+        "mxpi_imageresize0": {
+            "props": {
+                "dataSource": "mxpi_imagedecoder0",
+                "resizeType": "Resizer_KeepAspectRatio_Fit",
+                "resizeHeight": "512",
+                "resizeWidth": "512",
+                "cvProcessor": "opencv"
+            },
+            "factory": "mxpi_imageresize",
+            "next": "mxpi_tensorinfer0"
+        },
+        "mxpi_tensorinfer0": {
+            "props": {
+                "dataSource": "mxpi_imageresize0",
+                "modelPath": "models/efficient-det-d0-mindxsdk-order.om"
+            },
+            "factory": "mxpi_tensorinfer",
+            "next": "mxpi_objectpostprocessor0"
+        },
+        "mxpi_objectpostprocessor0": {
+            "props": {
+                "dataSource": "mxpi_tensorinfer0",
+                "postProcessConfigPath": "models/efficient-det-eval.cfg",
+                "labelPath": "models/coco.names",
+                "postProcessLibPath": "postprocess/build/libefficientdetpostprocess.so"
+            },
+            "factory": "mxpi_objectpostprocessor",
+            "next": "appsink0"
+        },
+        "appsink0": {
+            "props": {
+                "blocksize": "4096000"
+            },
+            "factory": "appsink"
+        }
+    }
+}
diff --git a/contrib/EfficientDet/python/pipeline/EfficientDet-d1.pipeline b/mxVision/mxVision-referenceapps/EfficientDet/python/pipeline/EfficientDet-d1.pipeline
similarity index 96%
rename from contrib/EfficientDet/python/pipeline/EfficientDet-d1.pipeline
rename to mxVision/mxVision-referenceapps/EfficientDet/python/pipeline/EfficientDet-d1.pipeline
index 9f06101d16ea21f572ffadf64265f1f6e3946add..4659c85b9a3b06d4f9f4650288f19843f458e42a 100644
--- a/contrib/EfficientDet/python/pipeline/EfficientDet-d1.pipeline
+++ b/mxVision/mxVision-referenceapps/EfficientDet/python/pipeline/EfficientDet-d1.pipeline
@@ -1,58 +1,58 @@
-{
-    "detection": {
-        "stream_config": {
-            "deviceId": "0"
-        },
-        "appsrc0": {
-            "props": {
-                "blocksize": "409600"
-            },
-            "factory": "appsrc",
-            "next": "mxpi_imagedecoder0"
-        },
-        "mxpi_imagedecoder0": {
-            "props": {
-                "deviceId": "0",
-                "cvProcessor": "opencv",
-                "outputDataFormat": "RGB"
-            },
-            "factory": "mxpi_imagedecoder",
-            "next": "mxpi_imageresize0"
-        },
-        "mxpi_imageresize0": {
-            "props": {
-                "dataSource": "mxpi_imagedecoder0",
-                "resizeType": "Resizer_KeepAspectRatio_Fit",
-                "resizeHeight": "640",
-                "resizeWidth": "640",
-                "cvProcessor": "opencv"
-            },
-            "factory": "mxpi_imageresize",
-            "next": "mxpi_tensorinfer0"
-        },
-        "mxpi_tensorinfer0": {
-            "props": {
-                "dataSource": "mxpi_imageresize0",
-                "modelPath": "models/efficient-det-d1-mindxsdk-order.om"
-            },
-            "factory": "mxpi_tensorinfer",
-            "next": "mxpi_objectpostprocessor0"
-        },
-        "mxpi_objectpostprocessor0": {
-            "props": {
-                "dataSource": "mxpi_tensorinfer0",
-                "postProcessConfigPath": "models/efficient-det.cfg",
-                "labelPath": "models/coco.names",
-                "postProcessLibPath": "postprocess/build/libefficientdetpostprocess.so"
-            },
-            "factory": "mxpi_objectpostprocessor",
-            "next": "appsink0"
-        },
-        "appsink0": {
-            "props": {
-                "blocksize": "4096000"
-            },
-            "factory": "appsink"
-        }
-    }
-}
+{
+    "detection": {
+        "stream_config": {
+            "deviceId": "0"
+        },
+        "appsrc0": {
+            "props": {
+                "blocksize": "409600"
+            },
+            "factory": "appsrc",
+            "next": "mxpi_imagedecoder0"
+        },
+        "mxpi_imagedecoder0": {
+            "props": {
+                "deviceId": "0",
+                "cvProcessor": "opencv",
+                "outputDataFormat": "RGB"
+            },
+            "factory": "mxpi_imagedecoder",
+            "next": "mxpi_imageresize0"
+        },
+        "mxpi_imageresize0": {
+            "props": {
+                "dataSource": "mxpi_imagedecoder0",
+                "resizeType": "Resizer_KeepAspectRatio_Fit",
+                "resizeHeight": "640",
+                "resizeWidth": "640",
+                "cvProcessor": "opencv"
+            },
+            "factory": "mxpi_imageresize",
+            "next": "mxpi_tensorinfer0"
+        },
+        "mxpi_tensorinfer0": {
+            "props": {
+                "dataSource": "mxpi_imageresize0",
+                "modelPath": "models/efficient-det-d1-mindxsdk-order.om"
+            },
+            "factory": "mxpi_tensorinfer",
+            "next": "mxpi_objectpostprocessor0"
+        },
+        "mxpi_objectpostprocessor0": {
+            "props": {
+                "dataSource": "mxpi_tensorinfer0",
+                "postProcessConfigPath": "models/efficient-det.cfg",
+                "labelPath": "models/coco.names",
+                "postProcessLibPath": "postprocess/build/libefficientdetpostprocess.so"
+            },
+            "factory": "mxpi_objectpostprocessor",
+            "next": "appsink0"
+        },
+        "appsink0": {
+            "props": {
+                "blocksize": "4096000"
+            },
+            "factory": "appsink"
+        }
+    }
+}
diff --git a/contrib/EfficientDet/python/pipeline/EfficientDet-d2.pipeline b/mxVision/mxVision-referenceapps/EfficientDet/python/pipeline/EfficientDet-d2.pipeline
similarity index 96%
rename from contrib/EfficientDet/python/pipeline/EfficientDet-d2.pipeline
rename to mxVision/mxVision-referenceapps/EfficientDet/python/pipeline/EfficientDet-d2.pipeline
index dbe86eb7c2bf6c94b0eebf1c05e60f253da6224a..91aa85c59b2f3f51cbbd357b45af59a6374d21b0 100644
--- a/contrib/EfficientDet/python/pipeline/EfficientDet-d2.pipeline
+++ b/mxVision/mxVision-referenceapps/EfficientDet/python/pipeline/EfficientDet-d2.pipeline
@@ -1,58 +1,58 @@
-{
-    "detection": {
-        "stream_config": {
-            "deviceId": "0"
-        },
-        "appsrc0": {
-            "props": {
-                "blocksize": "409600"
-            },
-            "factory": "appsrc",
-            "next": "mxpi_imagedecoder0"
-        },
-        "mxpi_imagedecoder0": {
-            "props": {
-                "deviceId": "0",
-                "cvProcessor": "opencv",
-                "outputDataFormat": "RGB"
-            },
-            "factory": "mxpi_imagedecoder",
-            "next": "mxpi_imageresize0"
-        },
-        "mxpi_imageresize0": {
-            "props": {
-                "dataSource": "mxpi_imagedecoder0",
-                "resizeType": "Resizer_KeepAspectRatio_Fit",
-                "resizeHeight": "768",
-                "resizeWidth": "768",
-                "cvProcessor": "opencv"
-            },
-            "factory": "mxpi_imageresize",
-            "next": "mxpi_tensorinfer0"
-        },
-        "mxpi_tensorinfer0": {
-            "props": {
-                "dataSource": "mxpi_imageresize0",
-                "modelPath": "models/efficient-det-d2-mindxsdk-order.om"
-            },
-            "factory": "mxpi_tensorinfer",
-            "next": "mxpi_objectpostprocessor0"
-        },
-        "mxpi_objectpostprocessor0": {
-            "props": {
-                "dataSource": "mxpi_tensorinfer0",
-                "postProcessConfigPath": "models/efficient-det.cfg",
-                "labelPath": "models/coco.names",
-                "postProcessLibPath": "postprocess/build/libefficientdetpostprocess.so"
-            },
-            "factory": "mxpi_objectpostprocessor",
-            "next": "appsink0"
-        },
-        "appsink0": {
-            "props": {
-                "blocksize": "4096000"
-            },
-            "factory": "appsink"
-        }
-    }
-}
+{
+    "detection": {
+        "stream_config": {
+            "deviceId": "0"
+        },
+        "appsrc0": {
+            "props": {
+                "blocksize": "409600"
+            },
+            "factory": "appsrc",
+            "next": "mxpi_imagedecoder0"
+        },
+        "mxpi_imagedecoder0": {
+            "props": {
+                "deviceId": "0",
+                "cvProcessor": "opencv",
+                "outputDataFormat": "RGB"
+            },
+            "factory": "mxpi_imagedecoder",
+            "next": "mxpi_imageresize0"
+        },
+        "mxpi_imageresize0": {
+            "props": {
+                "dataSource": "mxpi_imagedecoder0",
+                "resizeType": "Resizer_KeepAspectRatio_Fit",
+                "resizeHeight": "768",
+                "resizeWidth": "768",
+                "cvProcessor": "opencv"
+            },
+            "factory": "mxpi_imageresize",
+            "next": "mxpi_tensorinfer0"
+        },
+        "mxpi_tensorinfer0": {
+            "props": {
+                "dataSource": "mxpi_imageresize0",
+                "modelPath": "models/efficient-det-d2-mindxsdk-order.om"
+            },
+            "factory": "mxpi_tensorinfer",
+            "next": "mxpi_objectpostprocessor0"
+        },
+        "mxpi_objectpostprocessor0": {
+            "props": {
+                "dataSource": "mxpi_tensorinfer0",
+                "postProcessConfigPath": "models/efficient-det.cfg",
+                "labelPath": "models/coco.names",
+                "postProcessLibPath": "postprocess/build/libefficientdetpostprocess.so"
+            },
+            "factory": "mxpi_objectpostprocessor",
+            "next": "appsink0"
+        },
+        "appsink0": {
+            "props": {
+                "blocksize": "4096000"
+            },
+            "factory": "appsink"
+        }
+    }
+}
diff --git a/contrib/EfficientDet/python/pipeline/EfficientDet-d3.pipeline b/mxVision/mxVision-referenceapps/EfficientDet/python/pipeline/EfficientDet-d3.pipeline
similarity index 96%
rename from contrib/EfficientDet/python/pipeline/EfficientDet-d3.pipeline
rename to mxVision/mxVision-referenceapps/EfficientDet/python/pipeline/EfficientDet-d3.pipeline
index 73064227c73a0d57d09b39b1d7a3ab80e2e1c5d0..210846c7d82438d35cb7bc81aaaca9885a6b54f0 100644
--- a/contrib/EfficientDet/python/pipeline/EfficientDet-d3.pipeline
+++ b/mxVision/mxVision-referenceapps/EfficientDet/python/pipeline/EfficientDet-d3.pipeline
@@ -1,58 +1,58 @@
-{
-    "detection": {
-        "stream_config": {
-            "deviceId": "0"
-        },
-        "appsrc0": {
-            "props": {
-                "blocksize": "409600"
-            },
-            "factory": "appsrc",
-            "next": "mxpi_imagedecoder0"
-        },
-        "mxpi_imagedecoder0": {
-            "props": {
-                "deviceId": "0",
-                "cvProcessor": "opencv",
-                "outputDataFormat": "RGB"
-            },
-            "factory": "mxpi_imagedecoder",
-            "next": "mxpi_imageresize0"
-        },
-        "mxpi_imageresize0": {
-            "props": {
-                "dataSource": "mxpi_imagedecoder0",
-                "resizeType": "Resizer_KeepAspectRatio_Fit",
-                "resizeHeight": "896",
-                "resizeWidth": "896",
-                "cvProcessor": "opencv"
-            },
-            "factory": "mxpi_imageresize",
-            "next": "mxpi_tensorinfer0"
-        },
-        "mxpi_tensorinfer0": {
-            "props": {
-                "dataSource": "mxpi_imageresize0",
-                "modelPath": "models/efficient-det-d3-mindxsdk-order.om"
-            },
-            "factory": "mxpi_tensorinfer",
-            "next": "mxpi_objectpostprocessor0"
-        },
-        "mxpi_objectpostprocessor0": {
-            "props": {
-                "dataSource": "mxpi_tensorinfer0",
-                "postProcessConfigPath": "models/efficient-det.cfg",
-                "labelPath": "models/coco.names",
-                "postProcessLibPath": "postprocess/build/libefficientdetpostprocess.so"
-            },
-            "factory": "mxpi_objectpostprocessor",
-            "next": "appsink0"
-        },
-        "appsink0": {
-            "props": {
-                "blocksize": "4096000"
-            },
-            "factory": "appsink"
-        }
-    }
-}
+{
+    "detection": {
+        "stream_config": {
+            "deviceId": "0"
+        },
+        "appsrc0": {
+            "props": {
+                "blocksize": "409600"
+            },
+            "factory": "appsrc",
+            "next": "mxpi_imagedecoder0"
+        },
+        "mxpi_imagedecoder0": {
+            "props": {
+                "deviceId": "0",
+                "cvProcessor": "opencv",
+                "outputDataFormat": "RGB"
+            },
+            "factory": "mxpi_imagedecoder",
+            "next": "mxpi_imageresize0"
+        },
+        "mxpi_imageresize0": {
+            "props": {
+                "dataSource": "mxpi_imagedecoder0",
+                "resizeType": "Resizer_KeepAspectRatio_Fit",
+                "resizeHeight": "896",
+                "resizeWidth": "896",
+                "cvProcessor": "opencv"
+            },
+            "factory": "mxpi_imageresize",
+            "next": "mxpi_tensorinfer0"
+        },
+        "mxpi_tensorinfer0": {
+            "props": {
+                "dataSource": "mxpi_imageresize0",
+                "modelPath": "models/efficient-det-d3-mindxsdk-order.om"
+            },
+            "factory": "mxpi_tensorinfer",
+            "next": "mxpi_objectpostprocessor0"
+        },
+        "mxpi_objectpostprocessor0": {
+            "props": {
+                "dataSource": "mxpi_tensorinfer0",
+                "postProcessConfigPath": "models/efficient-det.cfg",
+                "labelPath": "models/coco.names",
+                "postProcessLibPath": "postprocess/build/libefficientdetpostprocess.so"
+            },
+            "factory": "mxpi_objectpostprocessor",
+            "next": "appsink0"
+        },
+        "appsink0": {
+            "props": {
+                "blocksize": "4096000"
+            },
+            "factory": "appsink"
+        }
+    }
+}
diff --git a/contrib/EfficientDet/python/pipeline/EfficientDet-d4.pipeline b/mxVision/mxVision-referenceapps/EfficientDet/python/pipeline/EfficientDet-d4.pipeline
similarity index 96%
rename from contrib/EfficientDet/python/pipeline/EfficientDet-d4.pipeline
rename to mxVision/mxVision-referenceapps/EfficientDet/python/pipeline/EfficientDet-d4.pipeline
index b024f1244ce75620b340e9437d589fe82f183a20..be9c974a19a1215ed6e033cd64396479a3182829 100644
--- a/contrib/EfficientDet/python/pipeline/EfficientDet-d4.pipeline
+++ b/mxVision/mxVision-referenceapps/EfficientDet/python/pipeline/EfficientDet-d4.pipeline
@@ -1,58 +1,58 @@
-{
-    "detection": {
-        "stream_config": {
-            "deviceId": "0"
-        },
-        "appsrc0": {
-            "props": {
-                "blocksize": "409600"
-            },
-            "factory": "appsrc",
-            "next": "mxpi_imagedecoder0"
-        },
-        "mxpi_imagedecoder0": {
-            "props": {
-                "deviceId": "0",
-                "cvProcessor": "opencv",
-                "outputDataFormat": "RGB"
-            },
-            "factory": "mxpi_imagedecoder",
-            "next": "mxpi_imageresize0"
-        },
-        "mxpi_imageresize0": {
-            "props": {
-                "dataSource": "mxpi_imagedecoder0",
-                "resizeType": "Resizer_KeepAspectRatio_Fit",
-                "resizeHeight": "1024",
-                "resizeWidth": "1024",
-                "cvProcessor": "opencv"
-            },
-            "factory": "mxpi_imageresize",
-            "next": "mxpi_tensorinfer0"
-        },
-        "mxpi_tensorinfer0": {
-            "props": {
-                "dataSource": "mxpi_imageresize0",
-                "modelPath": "models/efficient-det-d4-mindxsdk-order.om"
-            },
-            "factory": "mxpi_tensorinfer",
-            "next": "mxpi_objectpostprocessor0"
-        },
-        "mxpi_objectpostprocessor0": {
-            "props": {
-                "dataSource": "mxpi_tensorinfer0",
-                "postProcessConfigPath": "models/efficient-det.cfg",
-                "labelPath": "models/coco.names",
-                "postProcessLibPath": "postprocess/build/libefficientdetpostprocess.so"
-            },
-            "factory": "mxpi_objectpostprocessor",
-            "next": "appsink0"
-        },
-        "appsink0": {
-            "props": {
-                "blocksize": "4096000"
-            },
-            "factory": "appsink"
-        }
-    }
-}
+{
+    "detection": {
+        "stream_config": {
+            "deviceId": "0"
+        },
+        "appsrc0": {
+            "props": {
+                "blocksize": "409600"
+            },
+            "factory": "appsrc",
+            "next": "mxpi_imagedecoder0"
+        },
+        "mxpi_imagedecoder0": {
+            "props": {
+                "deviceId": "0",
+                "cvProcessor": "opencv",
+                "outputDataFormat": "RGB"
+            },
+            "factory": "mxpi_imagedecoder",
+            "next": "mxpi_imageresize0"
+        },
+        "mxpi_imageresize0": {
+            "props": {
+                "dataSource": "mxpi_imagedecoder0",
+                "resizeType": "Resizer_KeepAspectRatio_Fit",
+                "resizeHeight": "1024",
+                "resizeWidth": "1024",
+                "cvProcessor": "opencv"
+            },
+            "factory": "mxpi_imageresize",
+            "next": "mxpi_tensorinfer0"
+        },
+        "mxpi_tensorinfer0": {
+            "props": {
+                "dataSource": "mxpi_imageresize0",
+                "modelPath": "models/efficient-det-d4-mindxsdk-order.om"
+            },
+            "factory": "mxpi_tensorinfer",
+            "next": "mxpi_objectpostprocessor0"
+        },
+        "mxpi_objectpostprocessor0": {
+            "props": {
+                "dataSource": "mxpi_tensorinfer0",
+                "postProcessConfigPath": "models/efficient-det.cfg",
+                "labelPath": "models/coco.names",
+                "postProcessLibPath": "postprocess/build/libefficientdetpostprocess.so"
+            },
+            "factory": "mxpi_objectpostprocessor",
+            "next": "appsink0"
+        },
+        "appsink0": {
+            "props": {
+                "blocksize": "4096000"
+            },
+            "factory": "appsink"
+        }
+    }
+}
diff --git a/contrib/EfficientDet/python/pipeline/EfficientDet-d5.pipeline b/mxVision/mxVision-referenceapps/EfficientDet/python/pipeline/EfficientDet-d5.pipeline
similarity index 96%
rename from contrib/EfficientDet/python/pipeline/EfficientDet-d5.pipeline
rename to mxVision/mxVision-referenceapps/EfficientDet/python/pipeline/EfficientDet-d5.pipeline
index 5ac1a0d6ec21c2646ccd98e242dc843bbdfc71c9..a90869a7c7e0045b7f8fcfb7220ee5e115f4746e 100644
--- a/contrib/EfficientDet/python/pipeline/EfficientDet-d5.pipeline
+++ b/mxVision/mxVision-referenceapps/EfficientDet/python/pipeline/EfficientDet-d5.pipeline
@@ -1,58 +1,58 @@
-{
-    "detection": {
-        "stream_config": {
-            "deviceId": "0"
-        },
-        "appsrc0": {
-            "props": {
-                "blocksize": "409600"
-            },
-            "factory": "appsrc",
-            "next": "mxpi_imagedecoder0"
-        },
-        "mxpi_imagedecoder0": {
-            "props": {
-                "deviceId": "0",
-                "cvProcessor": "opencv",
-                "outputDataFormat": "RGB"
-            },
-            "factory": "mxpi_imagedecoder",
-            "next": "mxpi_imageresize0"
-        },
-        "mxpi_imageresize0": {
-            "props": {
-                "dataSource": "mxpi_imagedecoder0",
-                "resizeType": "Resizer_KeepAspectRatio_Fit",
-                "resizeHeight": "1280",
-                "resizeWidth": "1280",
-                "cvProcessor": "opencv"
-            },
-            "factory": "mxpi_imageresize",
-            "next": "mxpi_tensorinfer0"
-        },
-        "mxpi_tensorinfer0": {
-            "props": {
-                "dataSource": "mxpi_imageresize0",
-                "modelPath": "models/efficient-det-d5-mindxsdk-order.om"
-            },
-            "factory": "mxpi_tensorinfer",
-            "next": "mxpi_objectpostprocessor0"
-        },
-        "mxpi_objectpostprocessor0": {
-            "props": {
-                "dataSource": "mxpi_tensorinfer0",
-                "postProcessConfigPath": "models/efficient-det.cfg",
-                "labelPath": "models/coco.names",
-                "postProcessLibPath": "postprocess/build/libefficientdetpostprocess.so"
-            },
-            "factory": "mxpi_objectpostprocessor",
-            "next": "appsink0"
-        },
-        "appsink0": {
-            "props": {
-                "blocksize": "4096000"
-            },
-            "factory": "appsink"
-        }
-    }
-}
+{
+    "detection": {
+        "stream_config": {
+            "deviceId": "0"
+        },
+        "appsrc0": {
+            "props": {
+                "blocksize": "409600"
+            },
+            "factory": "appsrc",
+            "next": "mxpi_imagedecoder0"
+        },
+        "mxpi_imagedecoder0": {
+            "props": {
+                "deviceId": "0",
+                "cvProcessor": "opencv",
+                "outputDataFormat": "RGB"
+            },
+            "factory": "mxpi_imagedecoder",
+            "next": "mxpi_imageresize0"
+        },
+        "mxpi_imageresize0": {
+            "props": {
+                "dataSource": "mxpi_imagedecoder0",
+                "resizeType": "Resizer_KeepAspectRatio_Fit",
+                "resizeHeight": "1280",
+                "resizeWidth": "1280",
+                "cvProcessor": "opencv"
+            },
+            "factory": "mxpi_imageresize",
+            "next": "mxpi_tensorinfer0"
+        },
+        "mxpi_tensorinfer0": {
+            "props": {
+                "dataSource": "mxpi_imageresize0",
+                "modelPath": "models/efficient-det-d5-mindxsdk-order.om"
+            },
+            "factory": "mxpi_tensorinfer",
+            "next": "mxpi_objectpostprocessor0"
+        },
+        "mxpi_objectpostprocessor0": {
+            "props": {
+                "dataSource": "mxpi_tensorinfer0",
+                "postProcessConfigPath": "models/efficient-det.cfg",
+                "labelPath": "models/coco.names",
+                "postProcessLibPath": "postprocess/build/libefficientdetpostprocess.so"
+            },
+            "factory": "mxpi_objectpostprocessor",
+            "next": "appsink0"
+        },
+        "appsink0": {
+            "props": {
+                "blocksize": "4096000"
+            },
+            "factory": "appsink"
+        }
+    }
+}
diff --git a/contrib/EfficientDet/python/pipeline/EfficientDet-d6.pipeline b/mxVision/mxVision-referenceapps/EfficientDet/python/pipeline/EfficientDet-d6.pipeline
similarity index 96%
rename from contrib/EfficientDet/python/pipeline/EfficientDet-d6.pipeline
rename to mxVision/mxVision-referenceapps/EfficientDet/python/pipeline/EfficientDet-d6.pipeline
index c6f267c5046919ed70fe8ef5fe2ce542ab6e38a0..26c5dc0f327fb4b25e9d85e8ddd8ef3940b95938 100644
--- a/contrib/EfficientDet/python/pipeline/EfficientDet-d6.pipeline
+++ b/mxVision/mxVision-referenceapps/EfficientDet/python/pipeline/EfficientDet-d6.pipeline
@@ -1,58 +1,58 @@
-{
-    "detection": {
-        "stream_config": {
-            "deviceId": "0"
-        },
-        "appsrc0": {
-            "props": {
-                "blocksize": "409600"
-            },
-            "factory": "appsrc",
-            "next": "mxpi_imagedecoder0"
-        },
-        "mxpi_imagedecoder0": {
-            "props": {
-                "deviceId": "0",
-                "cvProcessor": "opencv",
-                "outputDataFormat": "RGB"
-            },
-            "factory": "mxpi_imagedecoder",
-            "next": "mxpi_imageresize0"
-        },
-        "mxpi_imageresize0": {
-            "props": {
-                "dataSource": "mxpi_imagedecoder0",
-                "resizeType": "Resizer_KeepAspectRatio_Fit",
-                "resizeHeight": "1280",
-                "resizeWidth": "1280",
-                "cvProcessor": "opencv"
-            },
-            "factory": "mxpi_imageresize",
-            "next": "mxpi_tensorinfer0"
-        },
-        "mxpi_tensorinfer0": {
-            "props": {
-                "dataSource": "mxpi_imageresize0",
-                "modelPath": "models/efficient-det-d6-mindxsdk-order.om"
-            },
-            "factory": "mxpi_tensorinfer",
-            "next": "mxpi_objectpostprocessor0"
-        },
-        "mxpi_objectpostprocessor0": {
-            "props": {
-                "dataSource": "mxpi_tensorinfer0",
-                "postProcessConfigPath": "models/efficient-det.cfg",
-                "labelPath": "models/coco.names",
-                "postProcessLibPath": "postprocess/build/libefficientdetpostprocess.so"
-            },
-            "factory": "mxpi_objectpostprocessor",
-            "next": "appsink0"
-        },
-        "appsink0": {
-            "props": {
-                "blocksize": "4096000"
-            },
-            "factory": "appsink"
-        }
-    }
-}
+{
+    "detection": {
+        "stream_config": {
+            "deviceId": "0"
+        },
+        "appsrc0": {
+            "props": {
+                "blocksize": "409600"
+            },
+            "factory": "appsrc",
+            "next": "mxpi_imagedecoder0"
+        },
+        "mxpi_imagedecoder0": {
+            "props": {
+                "deviceId": "0",
+                "cvProcessor": "opencv",
+                "outputDataFormat": "RGB"
+            },
+            "factory": "mxpi_imagedecoder",
+            "next": "mxpi_imageresize0"
+        },
+        "mxpi_imageresize0": {
+            "props": {
+                "dataSource": "mxpi_imagedecoder0",
+                "resizeType": "Resizer_KeepAspectRatio_Fit",
+                "resizeHeight": "1280",
+                "resizeWidth": "1280",
+                "cvProcessor": "opencv"
+            },
+            "factory": "mxpi_imageresize",
+            "next": "mxpi_tensorinfer0"
+        },
+        "mxpi_tensorinfer0": {
+            "props": {
+                "dataSource": "mxpi_imageresize0",
+                "modelPath": "models/efficient-det-d6-mindxsdk-order.om"
+            },
+            "factory": "mxpi_tensorinfer",
+            "next": "mxpi_objectpostprocessor0"
+        },
+        "mxpi_objectpostprocessor0": {
+            "props": {
+                "dataSource": "mxpi_tensorinfer0",
+                "postProcessConfigPath": "models/efficient-det.cfg",
+                "labelPath": "models/coco.names",
+                "postProcessLibPath": "postprocess/build/libefficientdetpostprocess.so"
+            },
+            "factory": "mxpi_objectpostprocessor",
+            "next": "appsink0"
+        },
+        "appsink0": {
+            "props": {
+                "blocksize": "4096000"
+            },
+            "factory": "appsink"
+        }
+    }
+}
diff --git a/contrib/ErfnetSegmentation/README.md b/mxVision/mxVision-referenceapps/ErfnetSegmentation/README.md
similarity index 100%
rename from contrib/ErfnetSegmentation/README.md
rename to mxVision/mxVision-referenceapps/ErfnetSegmentation/README.md
diff --git a/contrib/ErfnetSegmentation/main.py b/mxVision/mxVision-referenceapps/ErfnetSegmentation/main.py
similarity index 100%
rename from contrib/ErfnetSegmentation/main.py
rename to mxVision/mxVision-referenceapps/ErfnetSegmentation/main.py
diff --git a/contrib/ErfnetSegmentation/model/erfnet.aippconfig b/mxVision/mxVision-referenceapps/ErfnetSegmentation/model/erfnet.aippconfig
similarity index 100%
rename from contrib/ErfnetSegmentation/model/erfnet.aippconfig
rename to mxVision/mxVision-referenceapps/ErfnetSegmentation/model/erfnet.aippconfig
diff --git a/contrib/ErfnetSegmentation/model/onnx2om.sh b/mxVision/mxVision-referenceapps/ErfnetSegmentation/model/onnx2om.sh
similarity index 100%
rename from contrib/ErfnetSegmentation/model/onnx2om.sh
rename to mxVision/mxVision-referenceapps/ErfnetSegmentation/model/onnx2om.sh
diff --git a/contrib/ErfnetSegmentation/pipeline/erfnet_pipeline.pipeline b/mxVision/mxVision-referenceapps/ErfnetSegmentation/pipeline/erfnet_pipeline.pipeline
similarity index 100%
rename from contrib/ErfnetSegmentation/pipeline/erfnet_pipeline.pipeline
rename to mxVision/mxVision-referenceapps/ErfnetSegmentation/pipeline/erfnet_pipeline.pipeline
diff --git a/contrib/ErfnetSegmentation/plugin/postprocess/CMakeLists.txt b/mxVision/mxVision-referenceapps/ErfnetSegmentation/plugin/postprocess/CMakeLists.txt
similarity index 100%
rename from contrib/ErfnetSegmentation/plugin/postprocess/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/ErfnetSegmentation/plugin/postprocess/CMakeLists.txt
diff --git a/contrib/ErfnetSegmentation/plugin/postprocess/Postprocess.cpp b/mxVision/mxVision-referenceapps/ErfnetSegmentation/plugin/postprocess/Postprocess.cpp
similarity index 100%
rename from contrib/ErfnetSegmentation/plugin/postprocess/Postprocess.cpp
rename to mxVision/mxVision-referenceapps/ErfnetSegmentation/plugin/postprocess/Postprocess.cpp
diff --git a/contrib/ErfnetSegmentation/plugin/postprocess/Postprocess.h b/mxVision/mxVision-referenceapps/ErfnetSegmentation/plugin/postprocess/Postprocess.h
similarity index 100%
rename from contrib/ErfnetSegmentation/plugin/postprocess/Postprocess.h
rename to mxVision/mxVision-referenceapps/ErfnetSegmentation/plugin/postprocess/Postprocess.h
diff --git a/contrib/ErfnetSegmentation/plugin/postprocess/build.sh b/mxVision/mxVision-referenceapps/ErfnetSegmentation/plugin/postprocess/build.sh
similarity index 100%
rename from contrib/ErfnetSegmentation/plugin/postprocess/build.sh
rename to mxVision/mxVision-referenceapps/ErfnetSegmentation/plugin/postprocess/build.sh
diff --git a/contrib/ErfnetSegmentation/test_metric.py b/mxVision/mxVision-referenceapps/ErfnetSegmentation/test_metric.py
similarity index 100%
rename from contrib/ErfnetSegmentation/test_metric.py
rename to mxVision/mxVision-referenceapps/ErfnetSegmentation/test_metric.py
diff --git a/contrib/FCOS/README.md b/mxVision/mxVision-referenceapps/FCOS/README.md
similarity index 100%
rename from contrib/FCOS/README.md
rename to mxVision/mxVision-referenceapps/FCOS/README.md
diff --git a/contrib/FCOS/build.sh b/mxVision/mxVision-referenceapps/FCOS/build.sh
similarity index 100%
rename from contrib/FCOS/build.sh
rename to mxVision/mxVision-referenceapps/FCOS/build.sh
diff --git a/contrib/FCOS/colorlist.txt b/mxVision/mxVision-referenceapps/FCOS/colorlist.txt
similarity index 100%
rename from contrib/FCOS/colorlist.txt
rename to mxVision/mxVision-referenceapps/FCOS/colorlist.txt
diff --git a/contrib/FCOS/evaluate.py b/mxVision/mxVision-referenceapps/FCOS/evaluate.py
similarity index 100%
rename from contrib/FCOS/evaluate.py
rename to mxVision/mxVision-referenceapps/FCOS/evaluate.py
diff --git a/contrib/FCOS/image/image1.png b/mxVision/mxVision-referenceapps/FCOS/image/image1.png
similarity index 100%
rename from contrib/FCOS/image/image1.png
rename to mxVision/mxVision-referenceapps/FCOS/image/image1.png
diff --git a/contrib/FCOS/image/image2.png b/mxVision/mxVision-referenceapps/FCOS/image/image2.png
similarity index 100%
rename from contrib/FCOS/image/image2.png
rename to mxVision/mxVision-referenceapps/FCOS/image/image2.png
diff --git a/contrib/FCOS/main.py b/mxVision/mxVision-referenceapps/FCOS/main.py
similarity index 100%
rename from contrib/FCOS/main.py
rename to mxVision/mxVision-referenceapps/FCOS/main.py
diff --git a/contrib/FCOS/models/Fcos_tf_bs.cfg b/mxVision/mxVision-referenceapps/FCOS/models/Fcos_tf_bs.cfg
similarity index 100%
rename from contrib/FCOS/models/Fcos_tf_bs.cfg
rename to mxVision/mxVision-referenceapps/FCOS/models/Fcos_tf_bs.cfg
diff --git a/contrib/FCOS/pipeline/FCOSdetection.pipeline b/mxVision/mxVision-referenceapps/FCOS/pipeline/FCOSdetection.pipeline
similarity index 100%
rename from contrib/FCOS/pipeline/FCOSdetection.pipeline
rename to mxVision/mxVision-referenceapps/FCOS/pipeline/FCOSdetection.pipeline
diff --git a/contrib/FCOS/plugin/FCOSPostprocess/CMakeLists.txt b/mxVision/mxVision-referenceapps/FCOS/plugin/FCOSPostprocess/CMakeLists.txt
similarity index 100%
rename from contrib/FCOS/plugin/FCOSPostprocess/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/FCOS/plugin/FCOSPostprocess/CMakeLists.txt
diff --git a/contrib/FCOS/plugin/FCOSPostprocess/FCOSDetectionPostProcess.cpp b/mxVision/mxVision-referenceapps/FCOS/plugin/FCOSPostprocess/FCOSDetectionPostProcess.cpp
similarity index 100%
rename from contrib/FCOS/plugin/FCOSPostprocess/FCOSDetectionPostProcess.cpp
rename to mxVision/mxVision-referenceapps/FCOS/plugin/FCOSPostprocess/FCOSDetectionPostProcess.cpp
diff --git a/contrib/FCOS/plugin/FCOSPostprocess/FCOSDetectionPostProcess.h b/mxVision/mxVision-referenceapps/FCOS/plugin/FCOSPostprocess/FCOSDetectionPostProcess.h
similarity index 100%
rename from contrib/FCOS/plugin/FCOSPostprocess/FCOSDetectionPostProcess.h
rename to mxVision/mxVision-referenceapps/FCOS/plugin/FCOSPostprocess/FCOSDetectionPostProcess.h
diff --git a/contrib/FCOS/plugin/FCOSPostprocess/build.sh b/mxVision/mxVision-referenceapps/FCOS/plugin/FCOSPostprocess/build.sh
similarity index 100%
rename from contrib/FCOS/plugin/FCOSPostprocess/build.sh
rename to mxVision/mxVision-referenceapps/FCOS/plugin/FCOSPostprocess/build.sh
diff --git a/contrib/FaceBoxes/README.md b/mxVision/mxVision-referenceapps/FaceBoxes/README.md
similarity index 100%
rename from contrib/FaceBoxes/README.md
rename to mxVision/mxVision-referenceapps/FaceBoxes/README.md
diff --git a/contrib/FaceBoxes/build.sh b/mxVision/mxVision-referenceapps/FaceBoxes/build.sh
similarity index 100%
rename from contrib/FaceBoxes/build.sh
rename to mxVision/mxVision-referenceapps/FaceBoxes/build.sh
diff --git a/contrib/FaceBoxes/config/FaceBoxes.aippconfig b/mxVision/mxVision-referenceapps/FaceBoxes/config/FaceBoxes.aippconfig
similarity index 100%
rename from contrib/FaceBoxes/config/FaceBoxes.aippconfig
rename to mxVision/mxVision-referenceapps/FaceBoxes/config/FaceBoxes.aippconfig
diff --git a/contrib/FaceBoxes/config/faceboxes-b0_bs1.cfg b/mxVision/mxVision-referenceapps/FaceBoxes/config/faceboxes-b0_bs1.cfg
similarity index 100%
rename from contrib/FaceBoxes/config/faceboxes-b0_bs1.cfg
rename to mxVision/mxVision-referenceapps/FaceBoxes/config/faceboxes-b0_bs1.cfg
diff --git a/contrib/FaceBoxes/main.py b/mxVision/mxVision-referenceapps/FaceBoxes/main.py
similarity index 100%
rename from contrib/FaceBoxes/main.py
rename to mxVision/mxVision-referenceapps/FaceBoxes/main.py
diff --git a/contrib/FaceBoxes/pipeline/Faceboxes.pipeline b/mxVision/mxVision-referenceapps/FaceBoxes/pipeline/Faceboxes.pipeline
similarity index 100%
rename from contrib/FaceBoxes/pipeline/Faceboxes.pipeline
rename to mxVision/mxVision-referenceapps/FaceBoxes/pipeline/Faceboxes.pipeline
diff --git a/contrib/FaceBoxes/plugin/FaceBoxesPostProcess/CMakeLists.txt b/mxVision/mxVision-referenceapps/FaceBoxes/plugin/FaceBoxesPostProcess/CMakeLists.txt
similarity index 100%
rename from contrib/FaceBoxes/plugin/FaceBoxesPostProcess/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/FaceBoxes/plugin/FaceBoxesPostProcess/CMakeLists.txt
diff --git a/contrib/FaceBoxes/plugin/FaceBoxesPostProcess/FaceBoxesPostProcess.cpp b/mxVision/mxVision-referenceapps/FaceBoxes/plugin/FaceBoxesPostProcess/FaceBoxesPostProcess.cpp
similarity index 100%
rename from contrib/FaceBoxes/plugin/FaceBoxesPostProcess/FaceBoxesPostProcess.cpp
rename to mxVision/mxVision-referenceapps/FaceBoxes/plugin/FaceBoxesPostProcess/FaceBoxesPostProcess.cpp
diff --git a/contrib/FaceBoxes/plugin/FaceBoxesPostProcess/FaceBoxesPostProcess.h b/mxVision/mxVision-referenceapps/FaceBoxes/plugin/FaceBoxesPostProcess/FaceBoxesPostProcess.h
similarity index 100%
rename from contrib/FaceBoxes/plugin/FaceBoxesPostProcess/FaceBoxesPostProcess.h
rename to mxVision/mxVision-referenceapps/FaceBoxes/plugin/FaceBoxesPostProcess/FaceBoxesPostProcess.h
diff --git a/contrib/FaceBoxes/plugin/FaceBoxesPostProcess/build.sh b/mxVision/mxVision-referenceapps/FaceBoxes/plugin/FaceBoxesPostProcess/build.sh
similarity index 100%
rename from contrib/FaceBoxes/plugin/FaceBoxesPostProcess/build.sh
rename to mxVision/mxVision-referenceapps/FaceBoxes/plugin/FaceBoxesPostProcess/build.sh
diff --git a/contrib/FaceBoxes/run.sh b/mxVision/mxVision-referenceapps/FaceBoxes/run.sh
similarity index 100%
rename from contrib/FaceBoxes/run.sh
rename to mxVision/mxVision-referenceapps/FaceBoxes/run.sh
diff --git a/contrib/FaceBoxes/script/convert.py b/mxVision/mxVision-referenceapps/FaceBoxes/script/convert.py
similarity index 97%
rename from contrib/FaceBoxes/script/convert.py
rename to mxVision/mxVision-referenceapps/FaceBoxes/script/convert.py
index a3068698577db3207fa6d54f84ca7c6a51c04f9b..85d89d390f724f5e02d5dff31c91d0b8b3eba7b2 100644
--- a/contrib/FaceBoxes/script/convert.py
+++ b/mxVision/mxVision-referenceapps/FaceBoxes/script/convert.py
@@ -1,38 +1,38 @@
-# Copyright 2021 Huawei Technologies Co., Ltd
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-import os
-path = os.getcwd()
-
-if not os.path.exists('../data/1'):
-    os.makedirs('../data/1')
-
-with open('../data/FDDB_Evaluation/FDDB_dets.txt', 'r') as f:
-    while(True):
-        img_name = f.readline().strip('\n').replace('/', '_')
-        if img_name:
-            pass
-        else:
-            break
-        
-        raw = f.readline().strip('\n').split('.')[0]
-        file_name = ''.join([img_name, '.txt'])
-        
-        os.chdir('../data/1')
-        with open(file_name, 'w') as new_file:
-            new_file.write(img_name+'\n')
-            new_file.write(raw+'\n')
-            for i in range(int(raw)):
-                new_file.write(f.readline())
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import os
+path = os.getcwd()
+
+if not os.path.exists('../data/1'):
+    os.makedirs('../data/1')
+
+with open('../data/FDDB_Evaluation/FDDB_dets.txt', 'r') as f:
+    while(True):
+        img_name = f.readline().strip('\n').replace('/', '_')
+        if img_name:
+            pass
+        else:
+            break
+        
+        raw = f.readline().strip('\n').split('.')[0]
+        file_name = ''.join([img_name, '.txt'])
+        
+        os.chdir('../data/1')
+        with open(file_name, 'w') as new_file:
+            new_file.write(img_name+'\n')
+            new_file.write(raw+'\n')
+            for i in range(int(raw)):
+                new_file.write(f.readline())
         os.chdir(path)
\ No newline at end of file
diff --git a/contrib/FaceBoxes/script/evaluate.py b/mxVision/mxVision-referenceapps/FaceBoxes/script/evaluate.py
similarity index 97%
rename from contrib/FaceBoxes/script/evaluate.py
rename to mxVision/mxVision-referenceapps/FaceBoxes/script/evaluate.py
index 56c0650f2b81aff23e1b821fab21debc8e64cb18..7b9d669f62d5998d05efd2e273d589ca511624b4 100644
--- a/contrib/FaceBoxes/script/evaluate.py
+++ b/mxVision/mxVision-referenceapps/FaceBoxes/script/evaluate.py
@@ -1,271 +1,271 @@
-# Copyright 2021 Huawei Technologies Co., Ltd
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-import os
-import tqdm
-import pickle
-import argparse
-import numpy as np
-import cv2
-from bbox import bbox_overlaps
-import pickle
-
-def get_gt_boxes(gt_dir):
-    """ gt dir: (wider_face_val.mat, wider_easy_val.mat, wider_medium_val.mat, wider_hard_val.mat)"""
-    cache_file = os.path.join(gt_dir, 'gt_box.cache')
-    if os.path.exists(cache_file):
-        with open(cache_file, 'rb') as f:
-            return pickle.load(f)
-
-    gt_dict = {}
-    for i in range(1, 11):
-        filename = os.path.join(gt_dir, 'FDDB-fold-{}-ellipseList.txt'.format('%02d' % i))
-        assert os.path.exists(filename)
-        gt_sub_dict = {}
-        annotationfile = open(filename)
-        while True:
-            filename = annotationfile.readline()[:-1].replace('/', '_')
-            if not filename:
-                break
-            line = annotationfile.readline()
-            if not line:
-                break
-            facenum = int(line)
-            face_loc = []
-            for j in range(facenum):
-                line = annotationfile.readline().strip().split()
-                major_axis_radius = float(line[0])
-                minor_axis_radius = float(line[1])
-                angle = float(line[2])
-                center_x = float(line[3])
-                center_y = float(line[4])
-                score = float(line[5])
-                angle = angle / 3.1415926 * 180
-                mask = np.zeros((1000, 1000), dtype=np.uint8)
-                cv2.ellipse(mask, ((int)(center_x), (int)(center_y)),
-                            ((int)(major_axis_radius), (int)(minor_axis_radius)), angle, 0., 360., (255, 255, 255))
-                contours, hierarchy = cv2.findContours(mask, cv2.RETR_LIST, cv2.CHAIN_APPROX_NONE)[-2:]
-                r = cv2.boundingRect(contours[0])
-                x_min = r[0]
-                y_min = r[1]
-                x_max = r[0] + r[2]
-                y_max = r[1] + r[3]
-                face_loc.append([x_min, y_min, x_max, y_max])
-            face_loc = np.array(face_loc)
-
-            gt_sub_dict[filename] = face_loc
-        gt_dict[i] = gt_sub_dict
-
-    with open(cache_file, 'wb') as f:
-        pickle.dump(gt_dict, f, pickle.HIGHEST_PROTOCOL)
-
-    return gt_dict
-
-
-def read_pred_file(filepath):
-    with open(filepath, 'r') as f:
-        lines = f.readlines()
-        img_file = lines[0].rstrip('\n\r')
-        lines = lines[2:]
-    boxes = []
-    for line in lines:
-        line = line.rstrip('\r\n').split(' ')
-        if line[0] == '':
-            continue
-        boxes.append([float(line[0]), float(line[1]), float(line[2]), float(line[3]), float(line[4])])
-    boxes = np.array(boxes)
-    return img_file.split('/')[-1], boxes
-
-
-def get_preds(pred_dir):
-    events = os.listdir(pred_dir)
-    boxes = dict()
-    pbar = tqdm.tqdm(events)
-    for event in pbar:
-        pbar.set_description('Reading Predictions ')
-        event_dir = os.path.join(pred_dir, event)
-        event_images = os.listdir(event_dir)
-        current_event = dict()
-        for imgtxt in event_images:
-            imgname, _boxes = read_pred_file(os.path.join(event_dir, imgtxt))
-            current_event[imgname.rstrip('.jpg')] = _boxes
-        boxes[event] = current_event
-    return boxes
-
-
-def norm_score(pred):
-    """ norm score
-    pred {key: [[x1,y1,x2,y2,s]]}
-    """
-
-    max_score = 0
-    min_score = 1
-
-    for _, k in pred.items():
-        for _, v in k.items():
-            if len(v) == 0:
-                continue
-            _min = np.min(v[:, -1])
-            _max = np.max(v[:, -1])
-            max_score = max(_max, max_score)
-            min_score = min(_min, min_score)
-
-    diff = max_score - min_score
-    for _, k in pred.items():
-        for _, v in k.items():
-            if len(v) == 0:
-                continue
-            v[:, -1] = (v[:, -1] - min_score) / diff
-
-
-def image_eval(pred, gt, ignore, iou_thresh):
-    """ single image evaluation
-    pred: Nx5
-    gt: Nx4
-    ignore:
-    """
-
-    _pred = pred.copy()
-    _gt = gt.copy()
-    pred_recall = np.zeros(_pred.shape[0])
-    recall_list = np.zeros(_gt.shape[0])
-    proposal_list = np.ones(_pred.shape[0])
-
-    _pred[:, 2] = _pred[:, 2] + _pred[:, 0]
-    _pred[:, 3] = _pred[:, 3] + _pred[:, 1]
-
-    overlaps = bbox_overlaps(_pred[:, :4], _gt)
-
-    for h in range(_pred.shape[0]):
-        gt_overlap = overlaps[h]
-        max_overlap, max_idx = gt_overlap.max(), gt_overlap.argmax()
-        if max_overlap >= iou_thresh:
-            if ignore[max_idx] == 0:
-                recall_list[max_idx] = -1
-                proposal_list[h] = -1
-            elif recall_list[max_idx] == 0:
-                recall_list[max_idx] = 1
-
-        r_keep_index = np.where(recall_list == 1)[0]
-        pred_recall[h] = len(r_keep_index)
-    return pred_recall, proposal_list
-
-
-def img_pr_info(thresh_num, pred_info, proposal_list, pred_recall):
-    pr_info = np.zeros((thresh_num, 2)).astype('float')
-    for t in range(thresh_num):
-
-        thresh = 1 - (t + 1) / thresh_num
-        r_index = np.where(pred_info[:, 4] >= thresh)[0]
-        if len(r_index) == 0:
-            pr_info[t, 0] = 0
-            pr_info[t, 1] = 0
-        else:
-            r_index = r_index[-1]
-            p_index = np.where(proposal_list[:r_index + 1] == 1)[0]
-            pr_info[t, 0] = len(p_index)
-            pr_info[t, 1] = pred_recall[r_index]
-    return pr_info
-
-
-def dataset_pr_info(thresh_num, pr_curve, count_face):
-    _pr_curve = np.zeros((thresh_num, 2))
-
-    for i in range(thresh_num):
-        _pr_curve[i, 0] = pr_curve[i, 1] / pr_curve[i, 0]
-        _pr_curve[i, 1] = pr_curve[i, 1] / count_face
-    return _pr_curve
-
-
-def voc_ap(rec, prec):
-    # correct AP calculation
-    # first append sentinel values at the end
-    mrec = np.concatenate(([0.], rec, [1.]))
-    mpre = np.concatenate(([0.], prec, [0.]))
-
-    # compute the precision envelope
-    for i in range(mpre.size - 1, 0, -1):
-        mpre[i - 1] = np.maximum(mpre[i - 1], mpre[i])
-
-    # to calculate area under PR curve, look for points
-    # where X axis (recall) changes value
-    i = np.where(mrec[1:] != mrec[:-1])[0]
-
-    # and sum (\Delta recall) * prec
-    ap = np.sum((mrec[i + 1] - mrec[i]) * mpre[i + 1])
-    return ap
-
-
-def evaluation(pred, gt_path, iou_thresh=0.5):
-    pred = get_preds(pred)
-    norm_score(pred)
-    gt_box_dict = get_gt_boxes(gt_path)
-    num_boxes = 0
-    for i in range(10):
-        num_boxes += len(gt_box_dict[i+1])
-    event = list(pred.keys())
-    event = [int(e) for e in event]
-    event.sort()  #event = [1]
-    thresh_num = 1000
-    aps = []
-
-    pbar = tqdm.tqdm(range(len(event)))
-    for setting_id in pbar:
-        pbar.set_description('Predicting ... ')
-        # different setting
-        for id in range(1,11):
-            count_face = 0
-            pr_curve = np.zeros((thresh_num, 2)).astype('float')
-            gt = gt_box_dict[id]
-            pred_list = pred[str(event[setting_id])]
-            gt_list = list(gt.keys())
-            for j in range(len(gt_list)):
-                gt_boxes = gt[gt_list[j]].astype('float')  # from image name get gt boxes
-                pred_info = pred_list[gt_list[j]]
-                keep_index = np.array(range(1, len(gt_boxes) + 1))
-                count_face += len(keep_index)
-                ignore = np.zeros(gt_boxes.shape[0])
-                if len(gt_boxes) == 0 or len(pred_info) == 0:
-                    continue
-                if len(keep_index) != 0:
-                    ignore[keep_index - 1] = 1
-                pred_recall, proposal_list = image_eval(pred_info, gt_boxes, ignore, iou_thresh)
-
-                _img_pr_info = img_pr_info(thresh_num, pred_info, proposal_list, pred_recall)
-                pr_curve += _img_pr_info
-            pr_curve = dataset_pr_info(thresh_num, pr_curve, count_face)
-
-            propose = pr_curve[:, 0]
-            recall = pr_curve[:, 1]
-
-            ap = voc_ap(recall, propose)
-            aps.append(ap)
-
-    print("==================== Results ====================")
-    fw = open('results.txt', 'w')
-    for i in range(len(aps)):
-        print("FDDB-fold-{} Val AP: {}".format(int(i+1), aps[i]))
-        fw.write("FDDB-fold-{} Val AP: {}\n".format(int(i+1), aps[i]))
-    print("FDDB Dataset Average AP: {}".format(sum(aps)/len(aps)))
-    fw.write("FDDB Dataset Average AP: {}\n".format(sum(aps)/len(aps)))
-    print("=================================================")
-
-
-if __name__ == '__main__':
-    parser = argparse.ArgumentParser()
-    parser.add_argument('-p', '--pred', default="../data/pred_sample/")
-    parser.add_argument('-g', '--gt', default='../data/ground_truth/')
-
-    args = parser.parse_args()
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import os
+import tqdm
+import pickle
+import argparse
+import numpy as np
+import cv2
+from bbox import bbox_overlaps
+import pickle
+
+def get_gt_boxes(gt_dir):
+    """ gt dir: (wider_face_val.mat, wider_easy_val.mat, wider_medium_val.mat, wider_hard_val.mat)"""
+    cache_file = os.path.join(gt_dir, 'gt_box.cache')
+    if os.path.exists(cache_file):
+        with open(cache_file, 'rb') as f:
+            return pickle.load(f)
+
+    gt_dict = {}
+    for i in range(1, 11):
+        filename = os.path.join(gt_dir, 'FDDB-fold-{}-ellipseList.txt'.format('%02d' % i))
+        assert os.path.exists(filename)
+        gt_sub_dict = {}
+        annotationfile = open(filename)
+        while True:
+            filename = annotationfile.readline()[:-1].replace('/', '_')
+            if not filename:
+                break
+            line = annotationfile.readline()
+            if not line:
+                break
+            facenum = int(line)
+            face_loc = []
+            for j in range(facenum):
+                line = annotationfile.readline().strip().split()
+                major_axis_radius = float(line[0])
+                minor_axis_radius = float(line[1])
+                angle = float(line[2])
+                center_x = float(line[3])
+                center_y = float(line[4])
+                score = float(line[5])
+                angle = angle / 3.1415926 * 180
+                mask = np.zeros((1000, 1000), dtype=np.uint8)
+                cv2.ellipse(mask, ((int)(center_x), (int)(center_y)),
+                            ((int)(major_axis_radius), (int)(minor_axis_radius)), angle, 0., 360., (255, 255, 255))
+                contours, hierarchy = cv2.findContours(mask, cv2.RETR_LIST, cv2.CHAIN_APPROX_NONE)[-2:]
+                r = cv2.boundingRect(contours[0])
+                x_min = r[0]
+                y_min = r[1]
+                x_max = r[0] + r[2]
+                y_max = r[1] + r[3]
+                face_loc.append([x_min, y_min, x_max, y_max])
+            face_loc = np.array(face_loc)
+
+            gt_sub_dict[filename] = face_loc
+        gt_dict[i] = gt_sub_dict
+
+    with open(cache_file, 'wb') as f:
+        pickle.dump(gt_dict, f, pickle.HIGHEST_PROTOCOL)
+
+    return gt_dict
+
+
+def read_pred_file(filepath):
+    with open(filepath, 'r') as f:
+        lines = f.readlines()
+        img_file = lines[0].rstrip('\n\r')
+        lines = lines[2:]
+    boxes = []
+    for line in lines:
+        line = line.rstrip('\r\n').split(' ')
+        if line[0] == '':
+            continue
+        boxes.append([float(line[0]), float(line[1]), float(line[2]), float(line[3]), float(line[4])])
+    boxes = np.array(boxes)
+    return img_file.split('/')[-1], boxes
+
+
+def get_preds(pred_dir):
+    events = os.listdir(pred_dir)
+    boxes = dict()
+    pbar = tqdm.tqdm(events)
+    for event in pbar:
+        pbar.set_description('Reading Predictions ')
+        event_dir = os.path.join(pred_dir, event)
+        event_images = os.listdir(event_dir)
+        current_event = dict()
+        for imgtxt in event_images:
+            imgname, _boxes = read_pred_file(os.path.join(event_dir, imgtxt))
+            current_event[imgname.rstrip('.jpg')] = _boxes
+        boxes[event] = current_event
+    return boxes
+
+
+def norm_score(pred):
+    """ norm score
+    pred {key: [[x1,y1,x2,y2,s]]}
+    """
+
+    max_score = 0
+    min_score = 1
+
+    for _, k in pred.items():
+        for _, v in k.items():
+            if len(v) == 0:
+                continue
+            _min = np.min(v[:, -1])
+            _max = np.max(v[:, -1])
+            max_score = max(_max, max_score)
+            min_score = min(_min, min_score)
+
+    diff = max_score - min_score
+    for _, k in pred.items():
+        for _, v in k.items():
+            if len(v) == 0:
+                continue
+            v[:, -1] = (v[:, -1] - min_score) / diff
+
+
+def image_eval(pred, gt, ignore, iou_thresh):
+    """ single image evaluation
+    pred: Nx5
+    gt: Nx4
+    ignore:
+    """
+
+    _pred = pred.copy()
+    _gt = gt.copy()
+    pred_recall = np.zeros(_pred.shape[0])
+    recall_list = np.zeros(_gt.shape[0])
+    proposal_list = np.ones(_pred.shape[0])
+
+    _pred[:, 2] = _pred[:, 2] + _pred[:, 0]
+    _pred[:, 3] = _pred[:, 3] + _pred[:, 1]
+
+    overlaps = bbox_overlaps(_pred[:, :4], _gt)
+
+    for h in range(_pred.shape[0]):
+        gt_overlap = overlaps[h]
+        max_overlap, max_idx = gt_overlap.max(), gt_overlap.argmax()
+        if max_overlap >= iou_thresh:
+            if ignore[max_idx] == 0:
+                recall_list[max_idx] = -1
+                proposal_list[h] = -1
+            elif recall_list[max_idx] == 0:
+                recall_list[max_idx] = 1
+
+        r_keep_index = np.where(recall_list == 1)[0]
+        pred_recall[h] = len(r_keep_index)
+    return pred_recall, proposal_list
+
+
+def img_pr_info(thresh_num, pred_info, proposal_list, pred_recall):
+    pr_info = np.zeros((thresh_num, 2)).astype('float')
+    for t in range(thresh_num):
+
+        thresh = 1 - (t + 1) / thresh_num
+        r_index = np.where(pred_info[:, 4] >= thresh)[0]
+        if len(r_index) == 0:
+            pr_info[t, 0] = 0
+            pr_info[t, 1] = 0
+        else:
+            r_index = r_index[-1]
+            p_index = np.where(proposal_list[:r_index + 1] == 1)[0]
+            pr_info[t, 0] = len(p_index)
+            pr_info[t, 1] = pred_recall[r_index]
+    return pr_info
+
+
+def dataset_pr_info(thresh_num, pr_curve, count_face):
+    _pr_curve = np.zeros((thresh_num, 2))
+
+    for i in range(thresh_num):
+        _pr_curve[i, 0] = pr_curve[i, 1] / pr_curve[i, 0]
+        _pr_curve[i, 1] = pr_curve[i, 1] / count_face
+    return _pr_curve
+
+
+def voc_ap(rec, prec):
+    # correct AP calculation
+    # first append sentinel values at the end
+    mrec = np.concatenate(([0.], rec, [1.]))
+    mpre = np.concatenate(([0.], prec, [0.]))
+
+    # compute the precision envelope
+    for i in range(mpre.size - 1, 0, -1):
+        mpre[i - 1] = np.maximum(mpre[i - 1], mpre[i])
+
+    # to calculate area under PR curve, look for points
+    # where X axis (recall) changes value
+    i = np.where(mrec[1:] != mrec[:-1])[0]
+
+    # and sum (\Delta recall) * prec
+    ap = np.sum((mrec[i + 1] - mrec[i]) * mpre[i + 1])
+    return ap
+
+
+def evaluation(pred, gt_path, iou_thresh=0.5):
+    pred = get_preds(pred)
+    norm_score(pred)
+    gt_box_dict = get_gt_boxes(gt_path)
+    num_boxes = 0
+    for i in range(10):
+        num_boxes += len(gt_box_dict[i+1])
+    event = list(pred.keys())
+    event = [int(e) for e in event]
+    event.sort()  #event = [1]
+    thresh_num = 1000
+    aps = []
+
+    pbar = tqdm.tqdm(range(len(event)))
+    for setting_id in pbar:
+        pbar.set_description('Predicting ... ')
+        # different setting
+        for id in range(1,11):
+            count_face = 0
+            pr_curve = np.zeros((thresh_num, 2)).astype('float')
+            gt = gt_box_dict[id]
+            pred_list = pred[str(event[setting_id])]
+            gt_list = list(gt.keys())
+            for j in range(len(gt_list)):
+                gt_boxes = gt[gt_list[j]].astype('float')  # from image name get gt boxes
+                pred_info = pred_list[gt_list[j]]
+                keep_index = np.array(range(1, len(gt_boxes) + 1))
+                count_face += len(keep_index)
+                ignore = np.zeros(gt_boxes.shape[0])
+                if len(gt_boxes) == 0 or len(pred_info) == 0:
+                    continue
+                if len(keep_index) != 0:
+                    ignore[keep_index - 1] = 1
+                pred_recall, proposal_list = image_eval(pred_info, gt_boxes, ignore, iou_thresh)
+
+                _img_pr_info = img_pr_info(thresh_num, pred_info, proposal_list, pred_recall)
+                pr_curve += _img_pr_info
+            pr_curve = dataset_pr_info(thresh_num, pr_curve, count_face)
+
+            propose = pr_curve[:, 0]
+            recall = pr_curve[:, 1]
+
+            ap = voc_ap(recall, propose)
+            aps.append(ap)
+
+    print("==================== Results ====================")
+    fw = open('results.txt', 'w')
+    for i in range(len(aps)):
+        print("FDDB-fold-{} Val AP: {}".format(int(i+1), aps[i]))
+        fw.write("FDDB-fold-{} Val AP: {}\n".format(int(i+1), aps[i]))
+    print("FDDB Dataset Average AP: {}".format(sum(aps)/len(aps)))
+    fw.write("FDDB Dataset Average AP: {}\n".format(sum(aps)/len(aps)))
+    print("=================================================")
+
+
+if __name__ == '__main__':
+    parser = argparse.ArgumentParser()
+    parser.add_argument('-p', '--pred', default="../data/pred_sample/")
+    parser.add_argument('-g', '--gt', default='../data/ground_truth/')
+
+    args = parser.parse_args()
     evaluation(args.pred, args.gt)
\ No newline at end of file
diff --git a/contrib/FaceBoxes/script/split.py b/mxVision/mxVision-referenceapps/FaceBoxes/script/split.py
similarity index 97%
rename from contrib/FaceBoxes/script/split.py
rename to mxVision/mxVision-referenceapps/FaceBoxes/script/split.py
index 6d23b9cb4372e9d75461e242e6aa49f6560c90d1..8f257f9dca871fa1581b122614123d0b603ab44e 100644
--- a/contrib/FaceBoxes/script/split.py
+++ b/mxVision/mxVision-referenceapps/FaceBoxes/script/split.py
@@ -1,30 +1,30 @@
-# Copyright 2021 Huawei Technologies Co., Ltd
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-import os
-import shutil
-
-pre_dir = '../data/1'
-cur_path = '../data/pred_sample'
-cur_path_dir = '../data/pred_sample/1'
-if not os.path.exists(cur_path):
-        os.makedirs(cur_path)
-if not os.path.exists(cur_path_dir):
-        os.makedirs(cur_path_dir)
-for dir_name in os.listdir(cur_path):
-    tmp_path = os.path.join(cur_path, dir_name.strip('\n'))
-    for data in os.listdir(pre_dir):
-        pre_file = os.path.join(pre_dir, data)
-        cur_file = os.path.join(tmp_path, data)
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import os
+import shutil
+
+pre_dir = '../data/1'
+cur_path = '../data/pred_sample'
+cur_path_dir = '../data/pred_sample/1'
+if not os.path.exists(cur_path):
+        os.makedirs(cur_path)
+if not os.path.exists(cur_path_dir):
+        os.makedirs(cur_path_dir)
+for dir_name in os.listdir(cur_path):
+    tmp_path = os.path.join(cur_path, dir_name.strip('\n'))
+    for data in os.listdir(pre_dir):
+        pre_file = os.path.join(pre_dir, data)
+        cur_file = os.path.join(tmp_path, data)
         shutil.move(pre_file, cur_file)
\ No newline at end of file
diff --git a/contrib/FaceBoxes/test.py b/mxVision/mxVision-referenceapps/FaceBoxes/test.py
similarity index 100%
rename from contrib/FaceBoxes/test.py
rename to mxVision/mxVision-referenceapps/FaceBoxes/test.py
diff --git a/contrib/FairMOT/CMakeLists.txt b/mxVision/mxVision-referenceapps/FairMOT/CMakeLists.txt
similarity index 96%
rename from contrib/FairMOT/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/FairMOT/CMakeLists.txt
index 93f834b328d5114fb0aa8d69a4253833f47b4f4f..d77e60050a3210a4d0da9f4dcc4d3c5fbb697a6d 100644
--- a/contrib/FairMOT/CMakeLists.txt
+++ b/mxVision/mxVision-referenceapps/FairMOT/CMakeLists.txt
@@ -1,49 +1,49 @@
-# Copyright (c) Huawei Technologies Co., Ltd. 2019-2021. All rights reserved.
-
-# CMake lowest version requirement
-cmake_minimum_required(VERSION 3.5.0)
-
-# project information
-project(FairMOT)   
-
-set(MX_SDK_HOME "$ENV{MX_SDK_HOME}")   
-
-if (NOT DEFINED ENV{MX_SDK_HOME})      
-    string(REGEX REPLACE "(.*)/(.*)/(.*)/(.*)" "\\1" MX_SDK_HOME  ${CMAKE_CURRENT_SOURCE_DIR})
-    message(STATUS "set default MX_SDK_HOME: ${MX_SDK_HOME}")
-else ()
-    message(STATUS "env MX_SDK_HOME: ${MX_SDK_HOME}")
-endif()
-
-# Compile options
-add_definitions(-D_GLIBCXX_USE_CXX11_ABI=0)  
-add_definitions(-Dgoogle=mindxsdk_private)      
-add_compile_options(-std=c++11 -fPIC -fstack-protector-all -Wall)   
-
-set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR})       
-set(CMAKE_CXX_FLAGS_DEBUG "-g")                                      
-set(CMAKE_EXE_LINKER_FLAGS "${CMAKE_EXE_LINKER_FLAGS} -Wl,-z,relro,-z,now,-z,noexecstack -pie")
-
-# Header path  
-include_directories(
-    ${MX_SDK_HOME}/include/     
-    ${MX_SDK_HOME}/opensource/include/
-)
-
-# add host lib path   
-link_directories(
-    ${MX_SDK_HOME}/lib/
-    ${MX_SDK_HOME}/opensource/lib/
-    ${MX_SDK_HOME}/opensource/lib64/
-)
-
-add_executable(main main.cpp)
-
-target_link_libraries(main glog cpprest mxbase plugintoolkit mxpidatatype streammanager mindxsdk_protobuf)
-
-install(TARGETS main DESTINATION ${CMAKE_RUNTIME_OUTPUT_DIRECTORY})
-
-
-
-
-
+# Copyright (c) Huawei Technologies Co., Ltd. 2019-2021. All rights reserved.
+
+# CMake lowest version requirement
+cmake_minimum_required(VERSION 3.5.0)
+
+# project information
+project(FairMOT)   
+
+set(MX_SDK_HOME "$ENV{MX_SDK_HOME}")   
+
+if (NOT DEFINED ENV{MX_SDK_HOME})      
+    string(REGEX REPLACE "(.*)/(.*)/(.*)/(.*)" "\\1" MX_SDK_HOME  ${CMAKE_CURRENT_SOURCE_DIR})
+    message(STATUS "set default MX_SDK_HOME: ${MX_SDK_HOME}")
+else ()
+    message(STATUS "env MX_SDK_HOME: ${MX_SDK_HOME}")
+endif()
+
+# Compile options
+add_definitions(-D_GLIBCXX_USE_CXX11_ABI=0)  
+add_definitions(-Dgoogle=mindxsdk_private)      
+add_compile_options(-std=c++11 -fPIC -fstack-protector-all -Wall)   
+
+set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR})       
+set(CMAKE_CXX_FLAGS_DEBUG "-g")                                      
+set(CMAKE_EXE_LINKER_FLAGS "${CMAKE_EXE_LINKER_FLAGS} -Wl,-z,relro,-z,now,-z,noexecstack -pie")
+
+# Header path  
+include_directories(
+    ${MX_SDK_HOME}/include/     
+    ${MX_SDK_HOME}/opensource/include/
+)
+
+# add host lib path   
+link_directories(
+    ${MX_SDK_HOME}/lib/
+    ${MX_SDK_HOME}/opensource/lib/
+    ${MX_SDK_HOME}/opensource/lib64/
+)
+
+add_executable(main main.cpp)
+
+target_link_libraries(main glog cpprest mxbase plugintoolkit mxpidatatype streammanager mindxsdk_protobuf)
+
+install(TARGETS main DESTINATION ${CMAKE_RUNTIME_OUTPUT_DIRECTORY})
+
+
+
+
+
diff --git a/contrib/FairMOT/README.md b/mxVision/mxVision-referenceapps/FairMOT/README.md
similarity index 98%
rename from contrib/FairMOT/README.md
rename to mxVision/mxVision-referenceapps/FairMOT/README.md
index 4edb7969475093dbd5dd307a2aa4e9f23003df5a..1b5eb787d12956f096e469ebb389854efc4b39ba 100644
--- a/contrib/FairMOT/README.md
+++ b/mxVision/mxVision-referenceapps/FairMOT/README.md
@@ -1,240 +1,240 @@
-# FairMOT目标跟踪
-
-## 1 介绍
-### 1.1 简介
-
-FairMOT目标跟踪后处理插件基于MindX SDK开发，在昇腾芯片上进行目标检测和跟踪，可以对行人进行画框和编号，将检测结果可视化并保存。项目主要流程为：通过live555服务器进行拉流输入视频，然后进行视频解码将264格式的视频解码为YUV格式的图片，图片缩放后经过模型推理进行行人识别，识别结果经过FairMOT后处理后得到识别框，对识别框进行跟踪并编号，用编号覆盖原有的类别信息，再将识别框和类别信息分别转绘到图片上，最后将图片编码成视频进行输出。 
-
-基于MindX SDK的FairMOT目标识别业务流程为：待检测视频存放在live555服务器上经mxpi_rtspsrc拉流插件输入，然后使用视频解码插件mxpi_videodecoder将视频解码成图片，再通过图像缩放插件mxpi_imageresize将图像缩放至满足检测模型要求的输入图像大小要求，缩放后的图像输入模型推理插件mxpi_tensorinfer得到检测结果，本项目开发的FairMOT后处理插件处理推理结果，得到识别框。再接入跟踪插件中识别框进行目标跟踪，得到目标的跟踪编号，然后在使用本项目开发的mxpi_trackidreplaceclassname插件将跟踪编号覆盖类名信息，使用mxpi_object2osdinstances和mxpi_opencvosd分别将识别框和类名（存储跟踪编号）绘制到原图片，再通过mxpi_videoencoder将图片合成视频。
-
-表1.1 系统方案各子系统功能描述：
-
-| 序号 | 子系统               | 功能描述                                                     |
-| ---- | -------------------- | :----------------------------------------------------------- |
-| 1    | 视频输入             | 接收外部调用接口的输入视频路径，对视频进行拉流，并将拉取的裸流存储到缓冲区（buffer）中，并发送到下游插件。 |
-| 2    | 视频解码             | 用于视频解码，当前只支持H264/H265格式。                      |
-| 3    | 数据分发             | 对单个输入数据分发多次。                                     |
-| 4    | 数据缓存             | 输出时为后续处理过程另创建一个线程，用于将输入数据与输出数据解耦，并创建缓存队列，存储尚未输出到下流插件的数据。 |
-| 5    | 图像处理             | 对解码后的YUV格式的图像进行指定宽高的缩放，暂时只支持YUV格式 的图像。 |
-| 6    | 模型推理插件         | 目标分类或检测，目前只支持单tensor输入（图像数据）的推理模型。 |
-| 7    | 模型后处理插件       | 实现对FairMOT模型输出的tensor解析，获取目标检测框以及对应的ReID向量，传输到跟踪模块。 |
-| 8    | 跟踪插件             | 实现多目标（包括机非人、目标）路径记录功能。                 |
-| 9    | 跟踪编号取代类名插件 | 用跟踪插件产生的编号信息取代后处理插件产生的类名信息，再将数据传入数据流中。 |
-| 10   | 目标框转绘插件       | 将流中传进的MxpiObjectList数据类型转换可用于OSD插件绘图所使用的 MxpiOsdInstancesList数据类型。 |
-| 11   | OSD可视化插件        | 主要实现对每帧图像标注跟踪结果。                             |
-| 12   | 视频编码插件         | 用于将OSD可视化插件输出的图片进行视频编码，输出视频。        |
-
-流程图如下：
-
-![](https://gitee.com/seven-day/mindxsdk-referenceapps/raw/master/contrib/FairMOT/image/image1.png)
-
-### 1.2 支持的产品
-
-x86_64 Atlas 300I（型号3010）和arm Atlas 300I（型号3000）。
-
-### 1.3 支持的版本
-
-本样例配套的MxVision版本、CANN版本、Driver/Firmware版本：
-
-| MxVision版本  | CANN版本  | Driver/Firmware版本  |
-| --------- | ------------------ | -------------- |
-| 5.0.0 | 7.0.0   |  23.0.0  |
-
-### 1.4 三方依赖
-| 依赖软件 | 版本       | 说明                           | 使用教程                                                     |
-| -------- | ---------- | ------------------------------ | ------------------------------------------------------------ |
-| live555  | 1.10       | 实现视频转rstp进行推流         | [链接](https://gitee.com/ascend/mindxsdk-referenceapps/blob/master/docs/%E5%8F%82%E8%80%83%E8%B5%84%E6%96%99/Live555%E7%A6%BB%E7%BA%BF%E8%A7%86%E9%A2%91%E8%BD%ACRTSP%E8%AF%B4%E6%98%8E%E6%96%87%E6%A1%A3.md) |
-| ffmpeg   | 4.4.4 | 实现mp4格式视频转为264格式视频 | [链接](https://gitee.com/ascend/mindxsdk-referenceapps/blob/master/docs/%E5%8F%82%E8%80%83%E8%B5%84%E6%96%99/pc%E7%AB%AFffmpeg%E5%AE%89%E8%A3%85%E6%95%99%E7%A8%8B.md#https://ffmpeg.org/download.html) |
-
-### 1.5 代码目录结构说明
-
-本工程名称为FairMOT，工程目录如下图所示：
-
-```
-├── models
-│   ├── aipp_FairMOT.config            # 模型转换aipp配置文件
-│   ├── mot_v2.onnx      # onnx模型
-│   └── mot_v2.om               # om模型
-├── pipeline
-│   └── fairmot.pipeline        # pipeline文件
-├── plugins
-│   ├── FairmotPostProcess     # Fairmot后处理插件
-│   │   ├── CMakeLists.txt        
-│   │   ├── FairmotPostProcess.cpp  
-│   │   ├── FairmotPostProcess.h
-│   │   └── build.sh
-│   └── MxpiTrackIdReplaceClassName  # 跟踪编号取代类名插件
-│       ├── CMakeLists.txt
-│       ├── MxpiTrackIdReplaceClassName.cpp
-│       ├── MxpiTrackIdReplaceClassName.h
-│       └── build.sh
-├── CMakeLists.txt
-├── build.sh
-├── main.cpp
-├── test
-│   └── main.cpp
-└── run.sh
-```
-
-## 2 设置环境变量
-
-
-```bash
-# 设置环境变量（请确认install_path路径是否正确）
-. /usr/local/Ascend/ascend-toolkit/set_env.sh #toolkit默认安装路径，根据实际安装路径修改
-. ${SDK_INSTALL_PATH}/mxVision/set_env.sh
-```
-## 3 准备模型
-
-### 3.1 FairMOT模型转换
-本项目中适用的模型是FairMOT模型，onnx模型可以直接[下载](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/FairMOT/mot_v2.onnx)。下载后使用模型转换工具 ATC 将 onnx 模型转换为 om 模型。
-原始ATC样例：https://gitee.com/ascend/samples/tree/master/python/contrib/object_tracking_video
-
-模型转换，步骤如下：
-
-**步骤1**. 从上述 onnx 模型下载链接中下载 onnx 模型至 `FairMOT/models` 文件夹下，文件名为：mot_v2.onnx 。
-
-**步骤2**. 进入 `FairMOT/models` 文件夹下执行命令：
-
-```
-atc --input_shape="input.1:1,3,608,1088" --check_report=./network_analysis.report --input_format=NCHW --output=./mot_v2 --soc_version=Ascend310 --insert_op_conf=./aipp_FairMOT.config --framework=5 --model=./mot_v2.onnx
-```
-
-执行该命令后会在当前文件夹下生成项目需要的模型文件 mot_v2.om。执行后终端输出为：
-
-```
-ATC start working now, please wait for a moment.
-ATC run success, welcome to the next use.
-```
-
-表示命令执行成功。
-
-### 3.2 osd相关的模型转换
-
-请执行mxVision软件包安装目录下operators/opencvosd/generate_osd_om.sh脚本生成所需模型文件。执行后终端输出为：
-
-```
-ATC start working now, please wait for a moment.
-ATC run success, welcome to the next use.
-```
-
-表示命令执行成功。
-
-## 4 编译与运行
-### 4.1 视频推流
-
-本项目通过mxpi_rtspsrc拉流输入数据，推流过程如下：
-
-首先通过[live555](https://gitee.com/ascend/mindxsdk-referenceapps/blob/master/docs/参考资料/Live555离线视频转RTSP说明文档.md)进行推流，进入到live555安装目录下mediaServer路径，上传要推流的视频在本目录下然后推流。 live555只支持特定几种格式文件，不支持MP4。 所以本地文件先要转成live555支持的格式。选择使用[ffmpeg](https://gitee.com/ascend/mindxsdk-referenceapps/blob/master/docs/参考资料/pc端ffmpeg安装教程.md)进行格式转换。
-
-转换命令如下：
-
-```shell
-ffmpeg -i xxx1.mp4 -vcodec h264 -bf 0 -g 25 -r 24 -s 1280*720 -an -f h264 xxx2.264
-```
-
-注：参数如下：
-
-| 参数    | 作用                                                   |
-| ------- | ------------------------------------------------------ |
-| -i      | 表示输入的音视频路径需要转换视频                       |
-| -f      | 强迫采用特定格式输出                                   |
-| -r      | 指定帧率输出                                           |
-| -an     | 关闭音频                                               |
-| -s      | 分辨率控制                                             |
-| -g      | 关键帧间隔控制                                         |
-| -vcodec | 设定视频编解码器，未设定时则使用与输入流相同的编解码器 |
-
-转换完成后上传视频至live555安装目录下mediaServer。输入命令进行推流：
-
-```shell
-./live555MediaServer port-id  //port-id为用户推流的端口号
-```
-
-test.264可替换成任意上传至当前目录的[264格式文件](https://gitee.com/ascend/mindxsdk-referenceapps/blob/master/docs/参考资料/pc端ffmpeg安装教程.md)。
-
-
-### 4.2 编译后处理插件
-
-进入 `FairMOT` 目录，在 `FairMOT` 目录下执行命令：
-
-```
-bash build.sh
-```
-
-命令执行成功后会在`FairMOT/plugins/FairmotPostProcess`和`FairMOT/plugins/MxpiTrackIdReplaceClassName`目录下分别生成build文件夹。将`FairMOT/plugins/MxpiTrackIdReplaceClassName/build`目录下生成的libmxpi_trackidreplaceclassname.so移动到`${SDK安装路径}/mxVision/lib/plugins`目录下，同时将`FairMOT/plugins/FairmotPostProcess/build`目录下生成的libfairmotpostprocess.so移动到`${SDK安装路径}/mxVision/lib/plugins`目录下。注意，**需要将生成的so的权限改为440**。
-
-```
-chmod 440 FairMOT/plugins/MxpiTrackIdReplaceClassName/build/libmxpi_trackidreplaceclassname.so
-chmod 440 FairMOT/plugins/FairmotPostProcess/build/libfairmotpostprocess.so
-```
-### 4.3 修改pipline文件
-
-**步骤1**. 修改`FairMOT/pipeline`目录下的fairmot.pipeline文件中mxpi_rtspsrc0的内容。
-
-```
-        "mxpi_rtspsrc0": {
-            "factory": "mxpi_rtspsrc",
-            "props": {
-                "rtspUrl":"rtsp://xxx.xxx.xxx.xxx:xxxx/xxx.264",      // 修改为自己所使用的服务器和文件名
-                "channelId": "0"
-            },
-            "next": "mxpi_videodecoder0"
-        },
-```
-
-**步骤2**. 根据使用的device修改deviceId。
-
-```
-        "stream_config": {
-                    "deviceId": "0"      //修改为实际使用的device
-                },
-```
-**步骤3**. 根据输入的视频宽高修改mxpi_videoencoder0的宽高配置。
-
-```
-        "mxpi_videoencoder0": {
-            "props": {
-                "inputFormat": "YUV420SP_NV12",
-                "outputFormat": "H264",
-                "fps": "1",
-                "iFrameInterval": "50",
-                "imageWidth":"1920", // 修改为自己所使用的视频宽度
-                "imageHeight":"1080" // 修改为自己所使用的视频高度
-            },
-            "factory": "mxpi_videoencoder",
-            "next": "queue7"
-        },
-```
-### 4.4 运行推理
-回到FairMOT目录下，在FairMOT目录下执行命令：
-
-```
-bash run.sh
-```
-### 4.5 查看结果
-命令执行成功后会在当前目录下生成检测结果的视频文件out.h264，查看文件验证目标跟踪结果。
-
-## 5 性能验证
-
-**测试帧率：**
-
-使用`FairMOT/test`目录下的main.cpp替换`FairMOT`目录下的main.cpp，然后按照第4小节编译与运行中的步骤进行编译运行，服务器会输出运行到该帧的平均帧率。
-```
-I20240823 22:20:14.038271 52568 main.cpp:117] Dealing frame id:85
-fps: 12.7977
-```
-## 6 常见问题
-
-### 6.1 视频编码参数配置错误
-
-**问题描述：**
-
-`FairMOT/pipeline/fairmot.pipeline`中视频编码分辨率参数目前配置为1280*720。  
-该参数通过imageHeight 和 imageWidth 属性配置，且需要和视频输入分配率相同，否则会报如下类型的错：
-
-![](https://gitee.com/seven-day/mindxsdk-referenceapps/raw/master/contrib/FairMOT/image/image3.png)
-
-**解决方案：**
-
-确保`FairMOT/pipeline/fairmot.pipeline`中 mxpi_videoencoder0 插件的 imageHeight 和 imageWidth 属性值是输入264视频的高和宽。
+# FairMOT目标跟踪
+
+## 1 介绍
+### 1.1 简介
+
+FairMOT目标跟踪后处理插件基于MindX SDK开发，在昇腾芯片上进行目标检测和跟踪，可以对行人进行画框和编号，将检测结果可视化并保存。项目主要流程为：通过live555服务器进行拉流输入视频，然后进行视频解码将264格式的视频解码为YUV格式的图片，图片缩放后经过模型推理进行行人识别，识别结果经过FairMOT后处理后得到识别框，对识别框进行跟踪并编号，用编号覆盖原有的类别信息，再将识别框和类别信息分别转绘到图片上，最后将图片编码成视频进行输出。 
+
+基于MindX SDK的FairMOT目标识别业务流程为：待检测视频存放在live555服务器上经mxpi_rtspsrc拉流插件输入，然后使用视频解码插件mxpi_videodecoder将视频解码成图片，再通过图像缩放插件mxpi_imageresize将图像缩放至满足检测模型要求的输入图像大小要求，缩放后的图像输入模型推理插件mxpi_tensorinfer得到检测结果，本项目开发的FairMOT后处理插件处理推理结果，得到识别框。再接入跟踪插件中识别框进行目标跟踪，得到目标的跟踪编号，然后在使用本项目开发的mxpi_trackidreplaceclassname插件将跟踪编号覆盖类名信息，使用mxpi_object2osdinstances和mxpi_opencvosd分别将识别框和类名（存储跟踪编号）绘制到原图片，再通过mxpi_videoencoder将图片合成视频。
+
+表1.1 系统方案各子系统功能描述：
+
+| 序号 | 子系统               | 功能描述                                                     |
+| ---- | -------------------- | :----------------------------------------------------------- |
+| 1    | 视频输入             | 接收外部调用接口的输入视频路径，对视频进行拉流，并将拉取的裸流存储到缓冲区（buffer）中，并发送到下游插件。 |
+| 2    | 视频解码             | 用于视频解码，当前只支持H264/H265格式。                      |
+| 3    | 数据分发             | 对单个输入数据分发多次。                                     |
+| 4    | 数据缓存             | 输出时为后续处理过程另创建一个线程，用于将输入数据与输出数据解耦，并创建缓存队列，存储尚未输出到下流插件的数据。 |
+| 5    | 图像处理             | 对解码后的YUV格式的图像进行指定宽高的缩放，暂时只支持YUV格式 的图像。 |
+| 6    | 模型推理插件         | 目标分类或检测，目前只支持单tensor输入（图像数据）的推理模型。 |
+| 7    | 模型后处理插件       | 实现对FairMOT模型输出的tensor解析，获取目标检测框以及对应的ReID向量，传输到跟踪模块。 |
+| 8    | 跟踪插件             | 实现多目标（包括机非人、目标）路径记录功能。                 |
+| 9    | 跟踪编号取代类名插件 | 用跟踪插件产生的编号信息取代后处理插件产生的类名信息，再将数据传入数据流中。 |
+| 10   | 目标框转绘插件       | 将流中传进的MxpiObjectList数据类型转换可用于OSD插件绘图所使用的 MxpiOsdInstancesList数据类型。 |
+| 11   | OSD可视化插件        | 主要实现对每帧图像标注跟踪结果。                             |
+| 12   | 视频编码插件         | 用于将OSD可视化插件输出的图片进行视频编码，输出视频。        |
+
+流程图如下：
+
+![](https://gitee.com/seven-day/mindxsdk-referenceapps/raw/master/contrib/FairMOT/image/image1.png)
+
+### 1.2 支持的产品
+
+x86_64 Atlas 300I（型号3010）和arm Atlas 300I（型号3000）。
+
+### 1.3 支持的版本
+
+本样例配套的MxVision版本、CANN版本、Driver/Firmware版本：
+
+| MxVision版本  | CANN版本  | Driver/Firmware版本  |
+| --------- | ------------------ | -------------- |
+| 5.0.0 | 7.0.0   |  23.0.0  |
+
+### 1.4 三方依赖
+| 依赖软件 | 版本       | 说明                           | 使用教程                                                     |
+| -------- | ---------- | ------------------------------ | ------------------------------------------------------------ |
+| live555  | 1.10       | 实现视频转rstp进行推流         | [链接](https://gitee.com/ascend/mindxsdk-referenceapps/blob/master/docs/%E5%8F%82%E8%80%83%E8%B5%84%E6%96%99/Live555%E7%A6%BB%E7%BA%BF%E8%A7%86%E9%A2%91%E8%BD%ACRTSP%E8%AF%B4%E6%98%8E%E6%96%87%E6%A1%A3.md) |
+| ffmpeg   | 4.4.4 | 实现mp4格式视频转为264格式视频 | [链接](https://gitee.com/ascend/mindxsdk-referenceapps/blob/master/docs/%E5%8F%82%E8%80%83%E8%B5%84%E6%96%99/pc%E7%AB%AFffmpeg%E5%AE%89%E8%A3%85%E6%95%99%E7%A8%8B.md#https://ffmpeg.org/download.html) |
+
+### 1.5 代码目录结构说明
+
+本工程名称为FairMOT，工程目录如下图所示：
+
+```
+├── models
+│   ├── aipp_FairMOT.config            # 模型转换aipp配置文件
+│   ├── mot_v2.onnx      # onnx模型
+│   └── mot_v2.om               # om模型
+├── pipeline
+│   └── fairmot.pipeline        # pipeline文件
+├── plugins
+│   ├── FairmotPostProcess     # Fairmot后处理插件
+│   │   ├── CMakeLists.txt        
+│   │   ├── FairmotPostProcess.cpp  
+│   │   ├── FairmotPostProcess.h
+│   │   └── build.sh
+│   └── MxpiTrackIdReplaceClassName  # 跟踪编号取代类名插件
+│       ├── CMakeLists.txt
+│       ├── MxpiTrackIdReplaceClassName.cpp
+│       ├── MxpiTrackIdReplaceClassName.h
+│       └── build.sh
+├── CMakeLists.txt
+├── build.sh
+├── main.cpp
+├── test
+│   └── main.cpp
+└── run.sh
+```
+
+## 2 设置环境变量
+
+
+```bash
+# 设置环境变量（请确认install_path路径是否正确）
+. /usr/local/Ascend/ascend-toolkit/set_env.sh #toolkit默认安装路径，根据实际安装路径修改
+. ${SDK_INSTALL_PATH}/mxVision/set_env.sh
+```
+## 3 准备模型
+
+### 3.1 FairMOT模型转换
+本项目中适用的模型是FairMOT模型，onnx模型可以直接[下载](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/FairMOT/mot_v2.onnx)。下载后使用模型转换工具 ATC 将 onnx 模型转换为 om 模型。
+原始ATC样例：https://gitee.com/ascend/samples/tree/master/python/contrib/object_tracking_video
+
+模型转换，步骤如下：
+
+**步骤1**. 从上述 onnx 模型下载链接中下载 onnx 模型至 `FairMOT/models` 文件夹下，文件名为：mot_v2.onnx 。
+
+**步骤2**. 进入 `FairMOT/models` 文件夹下执行命令：
+
+```
+atc --input_shape="input.1:1,3,608,1088" --check_report=./network_analysis.report --input_format=NCHW --output=./mot_v2 --soc_version=Ascend310 --insert_op_conf=./aipp_FairMOT.config --framework=5 --model=./mot_v2.onnx
+```
+
+执行该命令后会在当前文件夹下生成项目需要的模型文件 mot_v2.om。执行后终端输出为：
+
+```
+ATC start working now, please wait for a moment.
+ATC run success, welcome to the next use.
+```
+
+表示命令执行成功。
+
+### 3.2 osd相关的模型转换
+
+请执行mxVision软件包安装目录下operators/opencvosd/generate_osd_om.sh脚本生成所需模型文件。执行后终端输出为：
+
+```
+ATC start working now, please wait for a moment.
+ATC run success, welcome to the next use.
+```
+
+表示命令执行成功。
+
+## 4 编译与运行
+### 4.1 视频推流
+
+本项目通过mxpi_rtspsrc拉流输入数据，推流过程如下：
+
+首先通过[live555](https://gitee.com/ascend/mindxsdk-referenceapps/blob/master/docs/参考资料/Live555离线视频转RTSP说明文档.md)进行推流，进入到live555安装目录下mediaServer路径，上传要推流的视频在本目录下然后推流。 live555只支持特定几种格式文件，不支持MP4。 所以本地文件先要转成live555支持的格式。选择使用[ffmpeg](https://gitee.com/ascend/mindxsdk-referenceapps/blob/master/docs/参考资料/pc端ffmpeg安装教程.md)进行格式转换。
+
+转换命令如下：
+
+```shell
+ffmpeg -i xxx1.mp4 -vcodec h264 -bf 0 -g 25 -r 24 -s 1280*720 -an -f h264 xxx2.264
+```
+
+注：参数如下：
+
+| 参数    | 作用                                                   |
+| ------- | ------------------------------------------------------ |
+| -i      | 表示输入的音视频路径需要转换视频                       |
+| -f      | 强迫采用特定格式输出                                   |
+| -r      | 指定帧率输出                                           |
+| -an     | 关闭音频                                               |
+| -s      | 分辨率控制                                             |
+| -g      | 关键帧间隔控制                                         |
+| -vcodec | 设定视频编解码器，未设定时则使用与输入流相同的编解码器 |
+
+转换完成后上传视频至live555安装目录下mediaServer。输入命令进行推流：
+
+```shell
+./live555MediaServer port-id  //port-id为用户推流的端口号
+```
+
+test.264可替换成任意上传至当前目录的[264格式文件](https://gitee.com/ascend/mindxsdk-referenceapps/blob/master/docs/参考资料/pc端ffmpeg安装教程.md)。
+
+
+### 4.2 编译后处理插件
+
+进入 `FairMOT` 目录，在 `FairMOT` 目录下执行命令：
+
+```
+bash build.sh
+```
+
+命令执行成功后会在`FairMOT/plugins/FairmotPostProcess`和`FairMOT/plugins/MxpiTrackIdReplaceClassName`目录下分别生成build文件夹。将`FairMOT/plugins/MxpiTrackIdReplaceClassName/build`目录下生成的libmxpi_trackidreplaceclassname.so移动到`${SDK安装路径}/mxVision/lib/plugins`目录下，同时将`FairMOT/plugins/FairmotPostProcess/build`目录下生成的libfairmotpostprocess.so移动到`${SDK安装路径}/mxVision/lib/plugins`目录下。注意，**需要将生成的so的权限改为440**。
+
+```
+chmod 440 FairMOT/plugins/MxpiTrackIdReplaceClassName/build/libmxpi_trackidreplaceclassname.so
+chmod 440 FairMOT/plugins/FairmotPostProcess/build/libfairmotpostprocess.so
+```
+### 4.3 修改pipline文件
+
+**步骤1**. 修改`FairMOT/pipeline`目录下的fairmot.pipeline文件中mxpi_rtspsrc0的内容。
+
+```
+        "mxpi_rtspsrc0": {
+            "factory": "mxpi_rtspsrc",
+            "props": {
+                "rtspUrl":"rtsp://xxx.xxx.xxx.xxx:xxxx/xxx.264",      // 修改为自己所使用的服务器和文件名
+                "channelId": "0"
+            },
+            "next": "mxpi_videodecoder0"
+        },
+```
+
+**步骤2**. 根据使用的device修改deviceId。
+
+```
+        "stream_config": {
+                    "deviceId": "0"      //修改为实际使用的device
+                },
+```
+**步骤3**. 根据输入的视频宽高修改mxpi_videoencoder0的宽高配置。
+
+```
+        "mxpi_videoencoder0": {
+            "props": {
+                "inputFormat": "YUV420SP_NV12",
+                "outputFormat": "H264",
+                "fps": "1",
+                "iFrameInterval": "50",
+                "imageWidth":"1920", // 修改为自己所使用的视频宽度
+                "imageHeight":"1080" // 修改为自己所使用的视频高度
+            },
+            "factory": "mxpi_videoencoder",
+            "next": "queue7"
+        },
+```
+### 4.4 运行推理
+回到FairMOT目录下，在FairMOT目录下执行命令：
+
+```
+bash run.sh
+```
+### 4.5 查看结果
+命令执行成功后会在当前目录下生成检测结果的视频文件out.h264，查看文件验证目标跟踪结果。
+
+## 5 性能验证
+
+**测试帧率：**
+
+使用`FairMOT/test`目录下的main.cpp替换`FairMOT`目录下的main.cpp，然后按照第4小节编译与运行中的步骤进行编译运行，服务器会输出运行到该帧的平均帧率。
+```
+I20240823 22:20:14.038271 52568 main.cpp:117] Dealing frame id:85
+fps: 12.7977
+```
+## 6 常见问题
+
+### 6.1 视频编码参数配置错误
+
+**问题描述：**
+
+`FairMOT/pipeline/fairmot.pipeline`中视频编码分辨率参数目前配置为1280*720。  
+该参数通过imageHeight 和 imageWidth 属性配置，且需要和视频输入分配率相同，否则会报如下类型的错：
+
+![](https://gitee.com/seven-day/mindxsdk-referenceapps/raw/master/contrib/FairMOT/image/image3.png)
+
+**解决方案：**
+
+确保`FairMOT/pipeline/fairmot.pipeline`中 mxpi_videoencoder0 插件的 imageHeight 和 imageWidth 属性值是输入264视频的高和宽。
diff --git a/contrib/FairMOT/build.sh b/mxVision/mxVision-referenceapps/FairMOT/build.sh
similarity index 100%
rename from contrib/FairMOT/build.sh
rename to mxVision/mxVision-referenceapps/FairMOT/build.sh
diff --git a/contrib/FairMOT/image/image1.png b/mxVision/mxVision-referenceapps/FairMOT/image/image1.png
similarity index 100%
rename from contrib/FairMOT/image/image1.png
rename to mxVision/mxVision-referenceapps/FairMOT/image/image1.png
diff --git a/contrib/FairMOT/image/image2.png b/mxVision/mxVision-referenceapps/FairMOT/image/image2.png
similarity index 100%
rename from contrib/FairMOT/image/image2.png
rename to mxVision/mxVision-referenceapps/FairMOT/image/image2.png
diff --git a/contrib/FairMOT/image/image3.png b/mxVision/mxVision-referenceapps/FairMOT/image/image3.png
similarity index 100%
rename from contrib/FairMOT/image/image3.png
rename to mxVision/mxVision-referenceapps/FairMOT/image/image3.png
diff --git a/contrib/FairMOT/main.cpp b/mxVision/mxVision-referenceapps/FairMOT/main.cpp
similarity index 100%
rename from contrib/FairMOT/main.cpp
rename to mxVision/mxVision-referenceapps/FairMOT/main.cpp
diff --git a/contrib/FairMOT/models/aipp_FairMOT.config b/mxVision/mxVision-referenceapps/FairMOT/models/aipp_FairMOT.config
similarity index 100%
rename from contrib/FairMOT/models/aipp_FairMOT.config
rename to mxVision/mxVision-referenceapps/FairMOT/models/aipp_FairMOT.config
diff --git a/contrib/FairMOT/pipeline/fairmot.pipeline b/mxVision/mxVision-referenceapps/FairMOT/pipeline/fairmot.pipeline
similarity index 96%
rename from contrib/FairMOT/pipeline/fairmot.pipeline
rename to mxVision/mxVision-referenceapps/FairMOT/pipeline/fairmot.pipeline
index f3f8f88fe8b8ff54def6a8fc60dccaff9eadc627..aeabf2e79a4c1ab82c9f0080ab87d834afae4ceb 100644
--- a/contrib/FairMOT/pipeline/fairmot.pipeline
+++ b/mxVision/mxVision-referenceapps/FairMOT/pipeline/fairmot.pipeline
@@ -1,165 +1,165 @@
-{
-    "encoder": {
-        "stream_config": {
-            "deviceId": "0"
-        },
-        "mxpi_rtspsrc0": {
-            "factory": "mxpi_rtspsrc",
-            "props": {
-                "rtspUrl":"rtsp://xxx.xxx.xxx.xxx:xxxx/xxx.264",
-                "channelId": "0"
-            },
-            "next": "queue0"
-        },
-        "queue0": {
-            "props": {
-                "max-size-buffers": "200"
-            },
-            "factory": "queue",
-            "next": "mxpi_videodecoder0"
-        },
-        "mxpi_videodecoder0": {
-            "factory": "mxpi_videodecoder",
-            "props": {
-                "inputVideoFormat": "H264",
-                "outputImageFormat": "YUV420SP_NV12",
-                "vdecChannelId": "0"
-            },
-            "next": "tee0"
-        },
-        "tee0": {
-            "factory": "tee",
-            "next": [
-                "queue1",
-                "queue2"
-            ]
-        },
-        "queue1": {
-            "props": {
-                "max-size-buffers": "200"
-            },
-            "factory": "queue",
-            "next": "mxpi_imageresize0"
-        },
-        "queue2": {
-            "props": {
-                "max-size-buffers": "200"
-            },
-            "factory": "queue",
-            "next": "mxpi_opencvosd0:0"
-        },
-        "mxpi_imageresize0": {
-            "props": {
-                "resizeHeight": "608",
-                "resizeWidth": "1088",
-                "resizeType": "Resizer_KeepAspectRatio_Fit"
-            },
-            "factory": "mxpi_imageresize",
-            "next": "queue3"
-        },
-        "queue3": {
-            "props": {
-                "max-size-buffers": "200"
-            },
-            "factory": "queue",
-            "next": "mxpi_tensorinfer0"
-        },
-        "mxpi_tensorinfer0": {
-            "props": {
-                "dataSource": "mxpi_imageresize0",
-                "outputHasBatchDim":"0",
-                "modelPath": "./models/mot_v2.om"
-            },
-            "factory": "mxpi_tensorinfer",
-            "next": "fairmotpostprocess0"
-        },
-
-        "fairmotpostprocess0": {
-            "props": {
-                "dataSource": "mxpi_tensorinfer0"
-            },
-            "factory": "fairmotpostprocess",
-            "next": "mxpi_motsimplesortV20"
-        },
-
-        "mxpi_motsimplesortV20": {
-            "props": {
-                "dataSourceDetection": "mxpi_fairmot_obj",
-                "dataSourceFeature": "mxpi_fairmot_fea"
-            },
-            "factory": "mxpi_motsimplesortV2",
-            "next": "mxpi_trackidreplaceclassname0"
-        },
-
-        "mxpi_trackidreplaceclassname0": {
-            "props": {
-                    "dataSource": "mxpi_fairmot_obj",
-                    "motSource": "mxpi_motsimplesortV20"
-            },
-            "factory": "mxpi_trackidreplaceclassname",
-            "next": "queue4"
-        },
-        "queue4": {
-            "props": {
-                "max-size-buffers": "200"
-            },
-            "factory": "queue",
-            "next": "mxpi_object2osdinstances0"
-        },
-        "mxpi_object2osdinstances0": {
-            "props": {
-                "dataSource": "mxpi_trackidreplaceclassname0",
-                "colorMap": "255,100,100|100,255,100|100,100,255|255,128,0",
-                "fontFace": "1",
-                "fontScale": "1",
-                "fontThickness": "1",
-                "fontLineType": "8",
-                "rectThickness": "3",
-                "rectLineType": "8"
-            },
-            "factory": "mxpi_object2osdinstances",
-            "next": "queue5"
-        },
-        "queue5": {
-            "props": {
-                "max-size-buffers": "200"
-            },
-            "factory": "queue",
-            "next": "mxpi_opencvosd0:1"
-        },
-        "mxpi_opencvosd0": {
-            "factory": "mxpi_opencvosd",
-            "next": "queue6"
-        },
-        "queue6": {
-            "props": {
-                "max-size-buffers": "200"
-            },
-            "factory": "queue",
-            "next": "mxpi_videoencoder0"
-        },
-        "mxpi_videoencoder0": {
-            "props": {
-                "inputFormat": "YUV420SP_NV12",
-                "outputFormat": "H264",
-                "fps": "1",
-                "iFrameInterval": "50",
-                "imageWidth":"1280",
-                "imageHeight":"720"
-            },
-            "factory": "mxpi_videoencoder",
-            "next": "queue7"
-        },
-        "queue7": {
-            "props": {
-                "max-size-buffers": "200"
-            },
-            "factory": "queue",
-            "next": "appsink0"
-        },
-        "appsink0": {
-            "factory": "appsink",
-            "former": "mxpi_videoencoder0"
-        }
-    }
+{
+    "encoder": {
+        "stream_config": {
+            "deviceId": "0"
+        },
+        "mxpi_rtspsrc0": {
+            "factory": "mxpi_rtspsrc",
+            "props": {
+                "rtspUrl":"rtsp://xxx.xxx.xxx.xxx:xxxx/xxx.264",
+                "channelId": "0"
+            },
+            "next": "queue0"
+        },
+        "queue0": {
+            "props": {
+                "max-size-buffers": "200"
+            },
+            "factory": "queue",
+            "next": "mxpi_videodecoder0"
+        },
+        "mxpi_videodecoder0": {
+            "factory": "mxpi_videodecoder",
+            "props": {
+                "inputVideoFormat": "H264",
+                "outputImageFormat": "YUV420SP_NV12",
+                "vdecChannelId": "0"
+            },
+            "next": "tee0"
+        },
+        "tee0": {
+            "factory": "tee",
+            "next": [
+                "queue1",
+                "queue2"
+            ]
+        },
+        "queue1": {
+            "props": {
+                "max-size-buffers": "200"
+            },
+            "factory": "queue",
+            "next": "mxpi_imageresize0"
+        },
+        "queue2": {
+            "props": {
+                "max-size-buffers": "200"
+            },
+            "factory": "queue",
+            "next": "mxpi_opencvosd0:0"
+        },
+        "mxpi_imageresize0": {
+            "props": {
+                "resizeHeight": "608",
+                "resizeWidth": "1088",
+                "resizeType": "Resizer_KeepAspectRatio_Fit"
+            },
+            "factory": "mxpi_imageresize",
+            "next": "queue3"
+        },
+        "queue3": {
+            "props": {
+                "max-size-buffers": "200"
+            },
+            "factory": "queue",
+            "next": "mxpi_tensorinfer0"
+        },
+        "mxpi_tensorinfer0": {
+            "props": {
+                "dataSource": "mxpi_imageresize0",
+                "outputHasBatchDim":"0",
+                "modelPath": "./models/mot_v2.om"
+            },
+            "factory": "mxpi_tensorinfer",
+            "next": "fairmotpostprocess0"
+        },
+
+        "fairmotpostprocess0": {
+            "props": {
+                "dataSource": "mxpi_tensorinfer0"
+            },
+            "factory": "fairmotpostprocess",
+            "next": "mxpi_motsimplesortV20"
+        },
+
+        "mxpi_motsimplesortV20": {
+            "props": {
+                "dataSourceDetection": "mxpi_fairmot_obj",
+                "dataSourceFeature": "mxpi_fairmot_fea"
+            },
+            "factory": "mxpi_motsimplesortV2",
+            "next": "mxpi_trackidreplaceclassname0"
+        },
+
+        "mxpi_trackidreplaceclassname0": {
+            "props": {
+                    "dataSource": "mxpi_fairmot_obj",
+                    "motSource": "mxpi_motsimplesortV20"
+            },
+            "factory": "mxpi_trackidreplaceclassname",
+            "next": "queue4"
+        },
+        "queue4": {
+            "props": {
+                "max-size-buffers": "200"
+            },
+            "factory": "queue",
+            "next": "mxpi_object2osdinstances0"
+        },
+        "mxpi_object2osdinstances0": {
+            "props": {
+                "dataSource": "mxpi_trackidreplaceclassname0",
+                "colorMap": "255,100,100|100,255,100|100,100,255|255,128,0",
+                "fontFace": "1",
+                "fontScale": "1",
+                "fontThickness": "1",
+                "fontLineType": "8",
+                "rectThickness": "3",
+                "rectLineType": "8"
+            },
+            "factory": "mxpi_object2osdinstances",
+            "next": "queue5"
+        },
+        "queue5": {
+            "props": {
+                "max-size-buffers": "200"
+            },
+            "factory": "queue",
+            "next": "mxpi_opencvosd0:1"
+        },
+        "mxpi_opencvosd0": {
+            "factory": "mxpi_opencvosd",
+            "next": "queue6"
+        },
+        "queue6": {
+            "props": {
+                "max-size-buffers": "200"
+            },
+            "factory": "queue",
+            "next": "mxpi_videoencoder0"
+        },
+        "mxpi_videoencoder0": {
+            "props": {
+                "inputFormat": "YUV420SP_NV12",
+                "outputFormat": "H264",
+                "fps": "1",
+                "iFrameInterval": "50",
+                "imageWidth":"1280",
+                "imageHeight":"720"
+            },
+            "factory": "mxpi_videoencoder",
+            "next": "queue7"
+        },
+        "queue7": {
+            "props": {
+                "max-size-buffers": "200"
+            },
+            "factory": "queue",
+            "next": "appsink0"
+        },
+        "appsink0": {
+            "factory": "appsink",
+            "former": "mxpi_videoencoder0"
+        }
+    }
 }
\ No newline at end of file
diff --git a/contrib/FairMOT/plugins/FairmotPostProcess/CMakeLists.txt b/mxVision/mxVision-referenceapps/FairMOT/plugins/FairmotPostProcess/CMakeLists.txt
similarity index 97%
rename from contrib/FairMOT/plugins/FairmotPostProcess/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/FairMOT/plugins/FairmotPostProcess/CMakeLists.txt
index 5c5305a27986d52dc8f481aae4ed301c17a9d1ce..53956237d707eeeb2eba27b25d5dd511313da90d 100644
--- a/contrib/FairMOT/plugins/FairmotPostProcess/CMakeLists.txt
+++ b/mxVision/mxVision-referenceapps/FairMOT/plugins/FairmotPostProcess/CMakeLists.txt
@@ -1,31 +1,31 @@
-cmake_minimum_required(VERSION 3.5.2)
-project(fairmotpostprocess)
-
-add_definitions(-D_GLIBCXX_USE_CXX11_ABI=0)
-add_definitions(-Dgoogle=mindxsdk_private)
-set(PLUGIN_NAME "fairmotpostprocess")
-set(TARGET_LIBRARY ${PLUGIN_NAME})
-
-set(MX_SDK_HOME "$ENV{MX_SDK_HOME}")
-
-include_directories(${CMAKE_CURRENT_BINARY_DIR})
-include_directories(${MX_SDK_HOME}/include)
-include_directories(${MX_SDK_HOME}/opensource/include)
-include_directories(${MX_SDK_HOME}/opensource/include/gstreamer-1.0)
-include_directories(${MX_SDK_HOME}/opensource/include/glib-2.0)
-include_directories(${MX_SDK_HOME}/opensource/lib/glib-2.0/include)
-include_directories(${MX_SDK_HOME}/opensource/include/opencv4)
-
-link_directories(${MX_SDK_HOME}/lib)
-link_directories(${MX_SDK_HOME}/opensource/lib)
-
-add_compile_options(-std=c++11 -fPIC -fstack-protector-all -pie -Wno-deprecated-declarations)
-add_compile_options("-DPLUGIN_NAME=${PLUGIN_NAME}")
-
-add_definitions(-DENABLE_DVPP_INTERFACE)
-
-add_library(${TARGET_LIBRARY} SHARED FairmotPostProcess.cpp)
-
-target_link_libraries(${TARGET_LIBRARY} glib-2.0 gstreamer-1.0 gobject-2.0 gstbase-1.0 gmodule-2.0 glog)
-
+cmake_minimum_required(VERSION 3.5.2)
+project(fairmotpostprocess)
+
+add_definitions(-D_GLIBCXX_USE_CXX11_ABI=0)
+add_definitions(-Dgoogle=mindxsdk_private)
+set(PLUGIN_NAME "fairmotpostprocess")
+set(TARGET_LIBRARY ${PLUGIN_NAME})
+
+set(MX_SDK_HOME "$ENV{MX_SDK_HOME}")
+
+include_directories(${CMAKE_CURRENT_BINARY_DIR})
+include_directories(${MX_SDK_HOME}/include)
+include_directories(${MX_SDK_HOME}/opensource/include)
+include_directories(${MX_SDK_HOME}/opensource/include/gstreamer-1.0)
+include_directories(${MX_SDK_HOME}/opensource/include/glib-2.0)
+include_directories(${MX_SDK_HOME}/opensource/lib/glib-2.0/include)
+include_directories(${MX_SDK_HOME}/opensource/include/opencv4)
+
+link_directories(${MX_SDK_HOME}/lib)
+link_directories(${MX_SDK_HOME}/opensource/lib)
+
+add_compile_options(-std=c++11 -fPIC -fstack-protector-all -pie -Wno-deprecated-declarations)
+add_compile_options("-DPLUGIN_NAME=${PLUGIN_NAME}")
+
+add_definitions(-DENABLE_DVPP_INTERFACE)
+
+add_library(${TARGET_LIBRARY} SHARED FairmotPostProcess.cpp)
+
+target_link_libraries(${TARGET_LIBRARY} glib-2.0 gstreamer-1.0 gobject-2.0 gstbase-1.0 gmodule-2.0 glog)
+
 target_link_libraries(${TARGET_LIBRARY} mxpidatatype plugintoolkit mxbase mindxsdk_protobuf)
\ No newline at end of file
diff --git a/contrib/FairMOT/plugins/FairmotPostProcess/FairmotPostProcess.cpp b/mxVision/mxVision-referenceapps/FairMOT/plugins/FairmotPostProcess/FairmotPostProcess.cpp
similarity index 97%
rename from contrib/FairMOT/plugins/FairmotPostProcess/FairmotPostProcess.cpp
rename to mxVision/mxVision-referenceapps/FairMOT/plugins/FairmotPostProcess/FairmotPostProcess.cpp
index 92270f85ef52c90b901842718e9d906164422fd0..497b0a805e2fbdb961589541790008280fd5391e 100644
--- a/contrib/FairMOT/plugins/FairmotPostProcess/FairmotPostProcess.cpp
+++ b/mxVision/mxVision-referenceapps/FairMOT/plugins/FairmotPostProcess/FairmotPostProcess.cpp
@@ -1,597 +1,597 @@
-/*
- * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#include "FairmotPostProcess.h"
-#include "MxBase/Log/Log.h"
-#include "MxBase/Maths/FastMath.h"
-#include "MxBase/CV/ObjectDetection/Nms/Nms.h"
-#include "MxTools/Proto/MxpiDataType.pb.h"
-#include "MxTools/PluginToolkit/buffer/MxpiBufferManager.h"
-#include <typeinfo>
-
-using namespace MxBase;
-using namespace MxPlugins;
-using namespace MxTools;
-using namespace std;
-namespace {
-    const string INPUT_SHAPE_TYPE = "MxpiTensorPackageList";
-    const string METADATA_KEY_OBJ = "mxpi_fairmot_obj";
-    const string METADATA_KEY_FEA = "mxpi_fairmot_fea";
-    // confidence thresh for tracking     
-    const float CONF_THRES = 0.35;
-    auto uint8Deleter = [] (uint8_t* p) { };
-}
-
-// decode MxpiTensorPackageList
-void GetTensors(const MxTools::MxpiTensorPackageList tensorPackageList,
-                std::vector<MxBase::TensorBase> &tensors) {
-    for (int i = 0; i < tensorPackageList.tensorpackagevec_size(); ++i) {
-        for (int j = 0; j < tensorPackageList.tensorpackagevec(i).tensorvec_size(); j++) {
-            MxBase::MemoryData memoryData = {};
-            memoryData.deviceId = tensorPackageList.tensorpackagevec(i).tensorvec(j).deviceid();
-            memoryData.type = (MxBase::MemoryData::MemoryType)tensorPackageList.
-                    tensorpackagevec(i).tensorvec(j).memtype();
-            memoryData.size = (uint32_t) tensorPackageList.
-                    tensorpackagevec(i).tensorvec(j).tensordatasize();
-            memoryData.ptrData = (void *) tensorPackageList.
-                    tensorpackagevec(i).tensorvec(j).tensordataptr();
-            std::vector<uint32_t> outputShape = {};
-            for (int k = 0; k < tensorPackageList.
-            tensorpackagevec(i).tensorvec(j).tensorshape_size(); ++k) {
-                outputShape.push_back((uint32_t) tensorPackageList.
-                tensorpackagevec(i).tensorvec(j).tensorshape(k));
-            }
-            MxBase::TensorBase tmpTensor(memoryData, true, outputShape,
-                                         (MxBase::TensorDataType)tensorPackageList.
-                                         tensorpackagevec(i).tensorvec(j).tensordatatype());
-            tensors.push_back(tmpTensor);
-        }
-    }
-}
-void FairmotPostProcess::CoordinatesReduction(const uint32_t index, 
-                                              const ResizedImageInfo &resizedImageInfo,
-                                              vector<ObjectInfo> &objInfos,
-                                              bool normalizedFlag)
-{
-    if (!normalizedFlag)
-    {
-        LogError << "Error CoordinatesReduction type in this example.";
-    }
-    int imgWidth = resizedImageInfo.widthOriginal;
-    int imgHeight = resizedImageInfo.heightOriginal;
-    // only for keepAspectRatioScaling
-    float ratio = resizedImageInfo.keepAspectRatioScaling;
-    for (auto objInfo = objInfos.begin(); objInfo != objInfos.end();) {
-        objInfo->x0 *= resizedImageInfo.widthResize / ratio;
-        objInfo->y0 *= resizedImageInfo.heightResize / ratio;
-        objInfo->x1 *= resizedImageInfo.widthResize / ratio;    
-        objInfo->y1 *= resizedImageInfo.heightResize / ratio;
-
-        if (objInfo->x0 > imgWidth || objInfo->y0 > imgHeight) {
-            objInfo = objInfos.erase(objInfo);
-            continue;
-        }
-        if (objInfo->x1 > imgWidth) {
-            objInfo->x1 = imgWidth;
-        }
-        if (objInfo->y1 > imgHeight) {
-            objInfo->y1 = imgHeight;
-        }
-        ++objInfo;
-    }
-           
-}
-APP_ERROR FairmotPostProcess::Init(std::map<std::string, std::shared_ptr<void>>& configParamMap)
-{
-    LogInfo << "FairmotPostProcess::Init start.";
-    APP_ERROR ret = APP_ERR_OK;
-    // Get the property values by key
-    parentName_ = dataSource_;
-    std::shared_ptr<string> descriptionMessageProSptr = 
-        std::static_pointer_cast<string>(configParamMap["descriptionMessage"]);
-    descriptionMessage_ = *descriptionMessageProSptr.get();
-    return APP_ERR_OK;
-}
-
-APP_ERROR FairmotPostProcess::DeInit()
-{
-    LogInfo << "FairmotPostProcess::DeInit end.";
-    return APP_ERR_OK;
-}
-
-// Judge whether the input from tensorinfer is valid
-bool FairmotPostProcess::IsValidTensors(const std::vector <TensorBase> &tensors)
-{
-    int fairmotType_ = 4;
-    if (tensors.size() != (size_t) fairmotType_) {               
-        LogError << "number of tensors (" << tensors.size() << ") " << "is unequal to fairmotType_("
-                << fairmotType_ << ")";
-        return false;
-    }    
-    return true;
-}
-
-APP_ERROR FairmotPostProcess::SetMxpiErrorInfo(MxpiBuffer& buffer, const std::string pluginName,
-    const MxpiErrorInfo mxpiErrorInfo)
-{
-    APP_ERROR ret = APP_ERR_OK;
-    // Define an object of MxpiMetadataManager
-    MxpiMetadataManager mxpiMetadataManager(buffer);
-    ret = mxpiMetadataManager.AddErrorInfo(pluginName, mxpiErrorInfo);
-    if (ret != APP_ERR_OK) {
-        LogError << "Failed to AddErrorInfo.";
-        return ret;
-    }
-    ret = SendData(0, buffer);
-    return ret;
-}
-
-APP_ERROR FairmotPostProcess::PrintMxpiErrorInfo(MxpiBuffer& buffer, const std::string pluginName,
-    MxpiErrorInfo mxpiErrorInfo, APP_ERROR app_error, std::string errorName)
-{
-    ErrorInfo_ << GetError(app_error, pluginName_) << errorName;
-    LogError << errorName;
-    mxpiErrorInfo.ret = app_error;
-    mxpiErrorInfo.errorInfo = ErrorInfo_.str();
-    SetMxpiErrorInfo(buffer, pluginName_, mxpiErrorInfo);
-    return app_error;
-}
-
-APP_ERROR FairmotPostProcess::GenerateresizedImageInfos(vector<MxpiBuffer*> mxpiBuffer,
-                                                        const MxpiTensorPackageList srcMxpiTensorPackage,
-                                                        vector <ResizedImageInfo> &resizedImageInfos)
-{
-    auto dataSourceResize = srcMxpiTensorPackage.tensorpackagevec(0).headervec(0).datasource();
-    MxTools::MxpiMetadataManager mxpiMxpiMetadataManager(*mxpiBuffer[0]);
-    auto mxpiVisionList = std::static_pointer_cast<MxTools::MxpiVisionList>(
-        mxpiMxpiMetadataManager.GetMetadataWithType(dataSourceResize, "MxpiVisionList"));
-    if (mxpiVisionList == nullptr)
-    {
-        LogWarn << "Get mxpiVisionList failed from " << dataSourceResize;
-        return APP_ERR_OK;
-    }
-    else
-    {
-        for (size_t i = 0; i < mxpiVisionList->visionvec_size(); i++)
-        {
-            auto info = mxpiVisionList->visionvec(i).visioninfo();
-            MxBase::ResizedImageInfo reseizedImageInfo{
-                info.width(), info.height(), 0, 0, (MxBase::ResizeType)info.resizetype(), info.keepaspectratioscaling()
-            };
-            MxTools::MxpiFrame frameData = MxpiBufferManager::GetDeviceDataInfo(*mxpiBuffer[0]);
-            if (frameData.visionlist().visionvec_size() == 0)
-            {
-                reseizedImageInfo.widthOriginal = info.width();
-                reseizedImageInfo.heightOriginal = info.height();
-            }
-            else
-            {
-                reseizedImageInfo.widthOriginal = frameData.visionlist().visionvec(0).visioninfo().width();
-                reseizedImageInfo.heightOriginal = frameData.visionlist().visionvec(0).visioninfo().height();
-            }
-            resizedImageInfos.push_back(reseizedImageInfo);
-            }
-        }
-    return APP_ERR_OK;
-} 
-
-/*
- * @description: Post-process the network output and calculate coordinates:bbox_top_left x, y; bbox_bottom_right x, y; conf_score;class (all zeros [only human])
- */
-int FairmotPostProcess::ObjectDetectionOutput(const vector <TensorBase> &tensors,
-                                              vector <vector<ObjectInfo>> &objectInfos,
-                                              vector<vector<float>> &ID_feature,
-                                              const vector <ResizedImageInfo> &resizedImageInfos) 
-{
-    LogDebug << "FairmotPostProcess start to write results.";
-    // Judge whether the input from tensorinfer is empty
-    if (tensors.size() == 0) {              
-        return 0;
-    }
-    auto shape = tensors[0].GetShape();     
-    if (shape.size() == 0) {
-        return 0;
-    }     
-
-    // @param featLayerData  Vector of 4 output feature data        
-    std::vector <std::shared_ptr<void>> featLayerData = {};             
-    std::vector <std::vector<size_t>> featLayerShapes = {}; 
-    for (uint32_t j = 0; j < tensors.size(); j++) {
-        auto dataPtr = (uint8_t *)tensors[j].GetBuffer(); 
-        std::shared_ptr<void> tmpPointer;
-        tmpPointer.reset(dataPtr, uint8Deleter);
-        // featLayerData stores the head address of 4 output feature data
-        featLayerData.push_back(tmpPointer);                                
-        shape = tensors[j].GetShape();
-
-        std::vector <size_t> featLayerShape = {};
-        for (auto s : shape) {
-            featLayerShape.push_back((size_t) s);
-        }
-        // featLayerShapes stores the shapes of 4 output feature data
-        featLayerShapes.push_back(featLayerShape);             
-    }
-
-    // tensors[0] matchs hm
-    // tensors[1] matchs wh
-    // tensors[2] matchs reg
-    // tensors[3] matchs id_feature
-    // Get the head address of hm
-    std::shared_ptr<void> hm_addr = featLayerData[0];
-    // Create a vector container XY to store coordinate information
-    std::vector<std::vector<int>> XY;
-    for(uint32_t i = 0;i < featLayerShapes[0][1] * featLayerShapes[0][2];i++){
-        // Compared with the threshold CONF_THRES to obtain coordinate information
-        if(static_cast<float *>(hm_addr.get())[i] > CONF_THRES)
-        {
-            std::vector<int>xy;                
-            int x = i / featLayerShapes[0][2];
-            int y = i - featLayerShapes[0][2] * x;
-            xy.push_back(x);
-            xy.push_back(y); 
-            XY.push_back(xy);  
-        }
-    }
-    // Output 1 when no pedestrian is detected
-    if(XY.size() == 0){
-        return 1;
-    }
-    // Create a vector container scores to store the information in the corresponding coordinate XY in hm
-    std::vector<float>scores;
-    for(uint32_t i = 0;i < XY.size();i++){
-        scores.push_back(static_cast<float *>(hm_addr.get())[XY[i][0] * featLayerShapes[0][2] + XY[i][1]]);
-    }
-    // Get the head address of wh and reg
-    std::shared_ptr<void> wh_addr = featLayerData[1];
-    std::shared_ptr<void> reg_addr = featLayerData[2];
-
-    // WH: n*4
-    std::vector<std::vector<float>>WH;
-    for(int i = 0; i < XY.size();i++){
-        std::vector<float>wh;
-        // featLayerShapes[1][3]: the third dimension of tensor[2]
-        for(int j = 0;j < featLayerShapes[1][3];j++){
-            wh.push_back(static_cast<float *>(wh_addr.get())[(XY[i][0] * featLayerShapes[0][2] + XY[i][1]) * featLayerShapes[1][3] + j]);
-        }
-        WH.push_back(wh);
-    }
-
-    // REG: n*2
-    std::vector<std::vector<float>>REG;
-    for(int i = 0; i < XY.size();i++){
-        std::vector<float>reg;
-        // featLayerShapes[2][3]: the third dimension of tensor[1]
-        for(int j = 0;j < featLayerShapes[2][3];j++){
-            reg.push_back(static_cast<float *>(reg_addr.get())[(XY[i][0] * featLayerShapes[0][2] + XY[i][1]) * featLayerShapes[2][3] + j]);
-        }
-        REG.push_back(reg);
-    }
-
-    // ID_feature: n*128
-    std::shared_ptr<void> id_addr = featLayerData[3];
-    for(int i = 0; i < XY.size();i++){
-        // featLayerShapes[3][3]: the third dimension of tensor[0]
-        std::vector<float>id_feature;
-        for(int j = 0;j < featLayerShapes[3][3];j++){
-            id_feature.push_back(static_cast<float *>(id_addr.get())[(XY[i][0] * featLayerShapes[0][2] + XY[i][1]) * featLayerShapes[3][3] + j]);
-        }
-        ID_feature.push_back(id_feature);
-    }
-    // XY_f changes the data in XY from int to float
-    std::vector<std::vector<float>> XY_f;
-    for(int i = 0;i < XY.size();i++){
-        std::vector<float>xy_f;
-        xy_f.push_back(XY[i][0]);
-        xy_f.push_back(XY[i][1]);
-        XY_f.push_back(xy_f);
-    }
-
-    for(int i = 0;i < XY_f.size();i++){                
-        XY_f[i][1] = XY_f[i][1] + REG[i][0];
-        XY_f[i][0] = XY_f[i][0] + REG[i][1];
-    }
-    // dets: n*6
-    std::vector<std::vector<float>>dets;
-    for(int i = 0;i < XY.size();i++){
-        std::vector<float>det;
-        det.push_back(XY_f[i][1] - WH[i][0]);
-        det.push_back(XY_f[i][0] - WH[i][1]);
-        det.push_back(XY_f[i][1] + WH[i][2]);
-        det.push_back(XY_f[i][0] + WH[i][3]);
-        det.push_back(scores[i]);
-        det.push_back(0);
-        dets.push_back(det);
-    }
-
-    // Width and height of initial video
-    int width = resizedImageInfos[0].widthOriginal;          
-    int height = resizedImageInfos[0].heightOriginal; 
-    // Scaled width and height           
-    int inp_height = resizedImageInfos[0].heightResize;      
-    int inp_width = resizedImageInfos[0].widthResize; 
-
-    // Create a vector container center to store the center point of the original picture
-    std::vector<float>c;
-    int half = 2;
-    c.push_back(width / half);
-    c.push_back(height / half);
-    std::vector<float>center(c);
-    // max_dets 
-    float scale = 0;
-    scale = std::max(float(inp_width) / float(inp_height) * height, float(width)) * 1.0 ;
-    std::vector<float>Scale;
-    Scale.push_back(scale);
-    Scale.push_back(scale);
-    // output_size
-    int down_ratio = 4;
-    int h = inp_height / down_ratio ;
-    int w = inp_width / down_ratio ;
-    std::vector<int>output_size;
-    output_size.push_back(w);
-    output_size.push_back(h);
-
-    int rot = 0;
-    std::vector<float>shift(2,0);        
-    int inv = 1;
-    // Input of get_affine_transform used to calculate trans: center, scale, rot, output_size, shift, inv
-    // get_affine_transform
-    std::vector<float>scale_tmp(Scale);
-    float src_w = scale_tmp[0];
-    int dst_w = output_size[0];
-    int dst_h = output_size[1];
-
-    float pi = 3.1415926;
-    int dir = 180;
-    float rot_rad = pi * rot / dir;
-
-    std::vector<float>src_point;
-    src_point.push_back(0);
-    src_point.push_back(src_w * (-0.5));
-
-    float sn = sin(rot_rad);
-    float cs = cos(rot_rad);
-    // get_dir
-    // src_dir and dst_dir are used to calculate trans
-    std::vector<float>src_dir(2,0);
-    src_dir[0] = src_point[0] * cs - src_point[1] * sn ;
-    src_dir[1] = src_point[0] * sn + src_point[1] * cs ;  
-    std::vector<float>dst_dir;
-    dst_dir.push_back(0);
-    dst_dir.push_back(dst_w * (-0.5));
-    // src and dst are calculated to calculate trans
-    float src[3][2] = {0};
-    float dst[3][2] = {0};
-    src[0][0] = center[0] + scale_tmp[0] * shift[0];
-    src[0][1] = center[1] + scale_tmp[1] * shift[1];
-    src[1][0] = center[0] + src_dir[0] + scale_tmp[0] * shift[0];
-    src[1][1] = center[1] + src_dir[1] + scale_tmp[1] * shift[1];
-    dst[0][0] = dst_w * 0.5;
-    dst[0][1] = dst_h * 0.5;
-    dst[1][0] = dst_w * 0.5 + dst_dir[0];
-    dst[1][1] = dst_h * 0.5 + dst_dir[1];        
-    // get_3rd_point
-    std::vector<float>direct;
-    direct.push_back(src[0][0]-src[1][0]);
-    direct.push_back(src[0][1]-src[1][1]);
-    src[2][0] = src[1][0] - direct[1];
-    src[2][1] = src[1][1] + direct[0];
-    // get_3rd_point
-    direct[0] = dst[0][0] - dst[1][0];
-    direct[1] = dst[0][1] - dst[1][1];
-    dst[2][0] = dst[1][0] - direct[1];
-    dst[2][1] = dst[1][1] + direct[0];
-
-    // change data in src and dst to point2f format  
-    cv::Point2f SRC[3];
-    cv::Point2f DST[3];
-    SRC[0] = cv::Point2f(src[0][0],src[0][1]);
-    SRC[1] = cv::Point2f(src[1][0],src[1][1]);
-    SRC[2] = cv::Point2f(src[2][0],src[2][1]);
-    DST[0] = cv::Point2f(dst[0][0],dst[0][1]);
-    DST[1] = cv::Point2f(dst[1][0],dst[1][1]);
-    DST[2] = cv::Point2f(dst[2][0],dst[2][1]);
-    // Calculate trans
-    cv::Mat trans(2, 3, CV_64FC1);
-    if(inv == 1){
-        trans = cv::getAffineTransform(DST,SRC);
-    }
-    else{
-        trans = cv::getAffineTransform(SRC,DST);
-    }
-    // Get data from mat type trans to array Trans
-    float Trans[2][3];
-    for(int i = 0;i < 2;i++){
-        for(int j = 0;j < 3;j++){
-            Trans[i][j] = trans.at<double>(i,j);
-        }
-    }
-    // affine_transform
-    // Calculate the coordinates of bbox_top_left x, y
-    for(int i = 0;i < dets.size();i++){
-        float new_pt[3] = {dets[i][0], dets[i][1], 1 };
-        dets[i][0] = Trans[0][0]* new_pt[0] + Trans[0][1]* new_pt[1] + Trans[0][2]* new_pt[2]; 
-        dets[i][1] = Trans[1][0]* new_pt[0] + Trans[1][1]* new_pt[1] + Trans[1][2]* new_pt[2]; 
-    }
-    // Calculate the coordinates of bbox_bottom_right x, y
-    for(int i = 0;i < dets.size();i++){
-        float new_pt[3] = {dets[i][2], dets[i][3], 1 };
-        dets[i][2] = Trans[0][0]* new_pt[0] + Trans[0][1]* new_pt[1] + Trans[0][2]* new_pt[2]; 
-        dets[i][3] = Trans[1][0]* new_pt[0] + Trans[1][1]* new_pt[1] + Trans[1][2]* new_pt[2]; 
-    }
-    // output
-    std::vector <ObjectInfo> objectInfo;        
-    for(int i = 0;i < dets.size();i++){
-        ObjectInfo objInfo;
-        objInfo.classId = 0;
-        objInfo.confidence = dets[i][4];
-        objInfo.className = " ";
-        // Normalization
-        objInfo.x0 = dets[i][0] / resizedImageInfos[0].widthOriginal;
-        objInfo.y0 = dets[i][1] / resizedImageInfos[0].heightOriginal;
-        objInfo.x1 = dets[i][2] / resizedImageInfos[0].widthOriginal;
-        objInfo.y1 = dets[i][3] / resizedImageInfos[0].heightOriginal;
-        objectInfo.push_back(objInfo);
-    }
-
-    objectInfos.push_back(objectInfo);
-    
-    LogDebug << "FairmotPostProcess write results successed."; 
-    // Output 2 when pedestrian is detected  
-    return 2;
-}
-
-APP_ERROR FairmotPostProcess::GenerateOutput(const MxTools::MxpiTensorPackageList srcMxpiTensorPackage,
-                                             std::vector <ResizedImageInfo> &resizedImageInfos,
-                                             MxTools::MxpiObjectList& dstMxpiObjectList, 
-                                             MxpiFeatureVectorList& dstMxpiFeatureVectorList)
-{
-    // Get Tensor
-    std::vector<MxBase::TensorBase> tensors = {};
-    GetTensors(srcMxpiTensorPackage, tensors);
-
-    // Check Tensor
-    bool isValid = IsValidTensors(tensors);
-    if (!isValid)
-    {
-        LogError << "Is unValid Tensors";
-        return APP_ERR_ACL_OP_INPUT_NOT_MATCH;
-    }
-
-    // Compute objects
-    std::vector<std::vector<ObjectInfo>> objectInfos;
-    std::vector<std::vector<float>> ID_feature;
-    int flag = ObjectDetectionOutput(tensors, objectInfos, ID_feature, resizedImageInfos);
-    if(flag == 1){
-        // flag: 1 represents no pedestrians are detected
-        MxpiObject* dstMxpiObject = dstMxpiObjectList.add_objectvec();   
-        MxpiClass* dstMxpiClass = dstMxpiObject->add_classvec();  
-        MxpiFeatureVector* mxpiFeature = dstMxpiFeatureVectorList.add_featurevec();
-        MxpiMetaHeader* dstMxpiMetaHeaderList = mxpiFeature->add_headervec();
-        return APP_ERR_OK;
-    }
-    else if(flag == 2){
-        // flag: 2 represents pedestrian detected
-        for (uint32_t i = 0; i < resizedImageInfos.size(); i++) {
-            CoordinatesReduction(i, resizedImageInfos[i], objectInfos[i]);
-        }
-        
-        // Generate ObjectList
-        for (size_t i = 0; i < objectInfos[0].size(); i++)
-        {
-            auto objInfo = objectInfos[0][i];
-            MxpiObject* dstMxpiObject = dstMxpiObjectList.add_objectvec();
-            MxpiMetaHeader* dstMxpiMetaHeaderList = dstMxpiObject->add_headervec();
-            dstMxpiMetaHeaderList->set_datasource(parentName_);
-            dstMxpiMetaHeaderList->set_memberid(0);
-
-            dstMxpiObject->set_x0(objInfo.x0);
-            dstMxpiObject->set_y0(objInfo.y0);
-            dstMxpiObject->set_x1(objInfo.x1);
-            dstMxpiObject->set_y1(objInfo.y1);
-
-            // Generate ClassList
-            MxpiClass* dstMxpiClass = dstMxpiObject->add_classvec();
-            MxpiMetaHeader* dstMxpiMetaHeaderList_c = dstMxpiClass->add_headervec();
-            dstMxpiMetaHeaderList_c->set_datasource(parentName_);
-            dstMxpiMetaHeaderList_c->set_memberid(0);
-            dstMxpiClass->set_classid(objInfo.classId);
-            dstMxpiClass->set_confidence(objInfo.confidence);
-            dstMxpiClass->set_classname(objInfo.className);
-        }
-
-        // Generate FeatureVectorList
-        for (size_t i = 0; i < ID_feature[0].size(); i++)
-        {
-            float feaInfo = ID_feature[0][i];
-            MxpiFeatureVector* mxpiFeature = dstMxpiFeatureVectorList.add_featurevec();
-            MxpiMetaHeader* dstMxpiMetaHeaderList = mxpiFeature->add_headervec();
-            dstMxpiMetaHeaderList->set_datasource(parentName_);
-            dstMxpiMetaHeaderList->set_memberid(0);
-
-            mxpiFeature->add_featurevalues(feaInfo);
-        }
-        return APP_ERR_OK;
-    }
-    else{
-        // flag: 0 represents the input from tensorinfer is empty
-        LogError << "Is unValid Tensors";
-        return APP_ERR_ACL_OP_INPUT_NOT_MATCH;
-    }
-}
-
-APP_ERROR FairmotPostProcess::Process(std::vector<MxpiBuffer*>& mxpiBuffer) {
-    LogInfo << "FairmotPostProcess::Process start";
-    MxpiBuffer* buffer = mxpiBuffer[0];
-    MxpiMetadataManager mxpiMetadataManager(*buffer);
-    MxpiErrorInfo mxpiErrorInfo;
-    ErrorInfo_.str("");
-    auto errorInfoPtr = mxpiMetadataManager.GetErrorInfo();
-    if (errorInfoPtr != nullptr) {
-        return PrintMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo, APP_ERR_COMM_FAILURE, "FairmotPostProcess process is not implemented");
-    }
-    // Get the data from buffer
-    shared_ptr<void> metadata = mxpiMetadataManager.GetMetadata(parentName_);
-    if (metadata == nullptr) {
-        return PrintMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo, APP_ERR_METADATA_IS_NULL, "Metadata is NULL, failed");
-    }
-    // check the proto struct name
-    google::protobuf::Message* msg = (google::protobuf::Message*)metadata.get();
-    const google::protobuf::Descriptor* desc = msg->GetDescriptor();
-    if (desc->name() != INPUT_SHAPE_TYPE) {
-        return PrintMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo, APP_ERR_PROTOBUF_NAME_MISMATCH, "Proto struct name is not MxpiTensorPackageList, failed");
-    }
-    shared_ptr<MxpiTensorPackageList> srcMxpiTensorPackageListSptr = static_pointer_cast<MxpiTensorPackageList>(metadata);
-    shared_ptr<MxpiObjectList> dstMxpiObjectList = make_shared<MxpiObjectList>();
-    shared_ptr<MxpiFeatureVectorList> dstMxpiFeatureVectorList = make_shared<MxpiFeatureVectorList>();
-    std::vector <ResizedImageInfo> resizedImageInfos;
-    // Get resizedImageInfos
-    APP_ERROR ret = GenerateresizedImageInfos(mxpiBuffer, *srcMxpiTensorPackageListSptr, resizedImageInfos);
-    if (ret != APP_ERR_OK) {
-        return PrintMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo, ret, "Generate resizedImageInfos failed");
-    }
-    // Generate sample output
-    ret = GenerateOutput(*srcMxpiTensorPackageListSptr, resizedImageInfos, *dstMxpiObjectList, *dstMxpiFeatureVectorList);
-    if (ret != APP_ERR_OK) {
-        return PrintMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo, ret, "FairmotPostProcess gets inference information failed. Checkc tensor value!");
-    }
-    // Add Generated data to metedata
-    ret = mxpiMetadataManager.AddProtoMetadata(METADATA_KEY_OBJ, static_pointer_cast<void>(dstMxpiObjectList));
-    if (ret != APP_ERR_OK) {
-        return PrintMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo, ret, "FairmotPostProcess add MxpiObjectList metadata failed.");
-    }
-    ret = mxpiMetadataManager.AddProtoMetadata(METADATA_KEY_FEA, static_pointer_cast<void>(dstMxpiFeatureVectorList));
-    if (ret != APP_ERR_OK) {
-        return PrintMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo, ret, "FairmotPostProcess add MxpiFeatureVectorList metadata failed.");
-    }
-    // Send the data to downstream plugin
-    SendData(0, *buffer);
-    LogInfo << "FairmotPostProcess::Process end";
-    return APP_ERR_OK;
-}
-
-std::vector<std::shared_ptr<void>> FairmotPostProcess::DefineProperties()
-{
-    // Define an A to store properties
-    std::vector<std::shared_ptr<void>> properties;
-    // Set the type and related information of the properties, and the key is the name
-    auto descriptionMessageProSptr = std::make_shared<ElementProperty<string>>(ElementProperty<string>{
-        STRING, "descriptionMessage", "message", "Description mesasge of plugin", "This is FairmotPostProcess", "NULL", "NULL"});
-    properties.push_back(descriptionMessageProSptr);
-    return properties;
-}
-
-// Register the Sample plugin through macro
-MX_PLUGIN_GENERATE(FairmotPostProcess)
+/*
+ * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "FairmotPostProcess.h"
+#include "MxBase/Log/Log.h"
+#include "MxBase/Maths/FastMath.h"
+#include "MxBase/CV/ObjectDetection/Nms/Nms.h"
+#include "MxTools/Proto/MxpiDataType.pb.h"
+#include "MxTools/PluginToolkit/buffer/MxpiBufferManager.h"
+#include <typeinfo>
+
+using namespace MxBase;
+using namespace MxPlugins;
+using namespace MxTools;
+using namespace std;
+namespace {
+    const string INPUT_SHAPE_TYPE = "MxpiTensorPackageList";
+    const string METADATA_KEY_OBJ = "mxpi_fairmot_obj";
+    const string METADATA_KEY_FEA = "mxpi_fairmot_fea";
+    // confidence thresh for tracking     
+    const float CONF_THRES = 0.35;
+    auto uint8Deleter = [] (uint8_t* p) { };
+}
+
+// decode MxpiTensorPackageList
+void GetTensors(const MxTools::MxpiTensorPackageList tensorPackageList,
+                std::vector<MxBase::TensorBase> &tensors) {
+    for (int i = 0; i < tensorPackageList.tensorpackagevec_size(); ++i) {
+        for (int j = 0; j < tensorPackageList.tensorpackagevec(i).tensorvec_size(); j++) {
+            MxBase::MemoryData memoryData = {};
+            memoryData.deviceId = tensorPackageList.tensorpackagevec(i).tensorvec(j).deviceid();
+            memoryData.type = (MxBase::MemoryData::MemoryType)tensorPackageList.
+                    tensorpackagevec(i).tensorvec(j).memtype();
+            memoryData.size = (uint32_t) tensorPackageList.
+                    tensorpackagevec(i).tensorvec(j).tensordatasize();
+            memoryData.ptrData = (void *) tensorPackageList.
+                    tensorpackagevec(i).tensorvec(j).tensordataptr();
+            std::vector<uint32_t> outputShape = {};
+            for (int k = 0; k < tensorPackageList.
+            tensorpackagevec(i).tensorvec(j).tensorshape_size(); ++k) {
+                outputShape.push_back((uint32_t) tensorPackageList.
+                tensorpackagevec(i).tensorvec(j).tensorshape(k));
+            }
+            MxBase::TensorBase tmpTensor(memoryData, true, outputShape,
+                                         (MxBase::TensorDataType)tensorPackageList.
+                                         tensorpackagevec(i).tensorvec(j).tensordatatype());
+            tensors.push_back(tmpTensor);
+        }
+    }
+}
+void FairmotPostProcess::CoordinatesReduction(const uint32_t index, 
+                                              const ResizedImageInfo &resizedImageInfo,
+                                              vector<ObjectInfo> &objInfos,
+                                              bool normalizedFlag)
+{
+    if (!normalizedFlag)
+    {
+        LogError << "Error CoordinatesReduction type in this example.";
+    }
+    int imgWidth = resizedImageInfo.widthOriginal;
+    int imgHeight = resizedImageInfo.heightOriginal;
+    // only for keepAspectRatioScaling
+    float ratio = resizedImageInfo.keepAspectRatioScaling;
+    for (auto objInfo = objInfos.begin(); objInfo != objInfos.end();) {
+        objInfo->x0 *= resizedImageInfo.widthResize / ratio;
+        objInfo->y0 *= resizedImageInfo.heightResize / ratio;
+        objInfo->x1 *= resizedImageInfo.widthResize / ratio;    
+        objInfo->y1 *= resizedImageInfo.heightResize / ratio;
+
+        if (objInfo->x0 > imgWidth || objInfo->y0 > imgHeight) {
+            objInfo = objInfos.erase(objInfo);
+            continue;
+        }
+        if (objInfo->x1 > imgWidth) {
+            objInfo->x1 = imgWidth;
+        }
+        if (objInfo->y1 > imgHeight) {
+            objInfo->y1 = imgHeight;
+        }
+        ++objInfo;
+    }
+           
+}
+APP_ERROR FairmotPostProcess::Init(std::map<std::string, std::shared_ptr<void>>& configParamMap)
+{
+    LogInfo << "FairmotPostProcess::Init start.";
+    APP_ERROR ret = APP_ERR_OK;
+    // Get the property values by key
+    parentName_ = dataSource_;
+    std::shared_ptr<string> descriptionMessageProSptr = 
+        std::static_pointer_cast<string>(configParamMap["descriptionMessage"]);
+    descriptionMessage_ = *descriptionMessageProSptr.get();
+    return APP_ERR_OK;
+}
+
+APP_ERROR FairmotPostProcess::DeInit()
+{
+    LogInfo << "FairmotPostProcess::DeInit end.";
+    return APP_ERR_OK;
+}
+
+// Judge whether the input from tensorinfer is valid
+bool FairmotPostProcess::IsValidTensors(const std::vector <TensorBase> &tensors)
+{
+    int fairmotType_ = 4;
+    if (tensors.size() != (size_t) fairmotType_) {               
+        LogError << "number of tensors (" << tensors.size() << ") " << "is unequal to fairmotType_("
+                << fairmotType_ << ")";
+        return false;
+    }    
+    return true;
+}
+
+APP_ERROR FairmotPostProcess::SetMxpiErrorInfo(MxpiBuffer& buffer, const std::string pluginName,
+    const MxpiErrorInfo mxpiErrorInfo)
+{
+    APP_ERROR ret = APP_ERR_OK;
+    // Define an object of MxpiMetadataManager
+    MxpiMetadataManager mxpiMetadataManager(buffer);
+    ret = mxpiMetadataManager.AddErrorInfo(pluginName, mxpiErrorInfo);
+    if (ret != APP_ERR_OK) {
+        LogError << "Failed to AddErrorInfo.";
+        return ret;
+    }
+    ret = SendData(0, buffer);
+    return ret;
+}
+
+APP_ERROR FairmotPostProcess::PrintMxpiErrorInfo(MxpiBuffer& buffer, const std::string pluginName,
+    MxpiErrorInfo mxpiErrorInfo, APP_ERROR app_error, std::string errorName)
+{
+    ErrorInfo_ << GetError(app_error, pluginName_) << errorName;
+    LogError << errorName;
+    mxpiErrorInfo.ret = app_error;
+    mxpiErrorInfo.errorInfo = ErrorInfo_.str();
+    SetMxpiErrorInfo(buffer, pluginName_, mxpiErrorInfo);
+    return app_error;
+}
+
+APP_ERROR FairmotPostProcess::GenerateresizedImageInfos(vector<MxpiBuffer*> mxpiBuffer,
+                                                        const MxpiTensorPackageList srcMxpiTensorPackage,
+                                                        vector <ResizedImageInfo> &resizedImageInfos)
+{
+    auto dataSourceResize = srcMxpiTensorPackage.tensorpackagevec(0).headervec(0).datasource();
+    MxTools::MxpiMetadataManager mxpiMxpiMetadataManager(*mxpiBuffer[0]);
+    auto mxpiVisionList = std::static_pointer_cast<MxTools::MxpiVisionList>(
+        mxpiMxpiMetadataManager.GetMetadataWithType(dataSourceResize, "MxpiVisionList"));
+    if (mxpiVisionList == nullptr)
+    {
+        LogWarn << "Get mxpiVisionList failed from " << dataSourceResize;
+        return APP_ERR_OK;
+    }
+    else
+    {
+        for (size_t i = 0; i < mxpiVisionList->visionvec_size(); i++)
+        {
+            auto info = mxpiVisionList->visionvec(i).visioninfo();
+            MxBase::ResizedImageInfo reseizedImageInfo{
+                info.width(), info.height(), 0, 0, (MxBase::ResizeType)info.resizetype(), info.keepaspectratioscaling()
+            };
+            MxTools::MxpiFrame frameData = MxpiBufferManager::GetDeviceDataInfo(*mxpiBuffer[0]);
+            if (frameData.visionlist().visionvec_size() == 0)
+            {
+                reseizedImageInfo.widthOriginal = info.width();
+                reseizedImageInfo.heightOriginal = info.height();
+            }
+            else
+            {
+                reseizedImageInfo.widthOriginal = frameData.visionlist().visionvec(0).visioninfo().width();
+                reseizedImageInfo.heightOriginal = frameData.visionlist().visionvec(0).visioninfo().height();
+            }
+            resizedImageInfos.push_back(reseizedImageInfo);
+            }
+        }
+    return APP_ERR_OK;
+} 
+
+/*
+ * @description: Post-process the network output and calculate coordinates:bbox_top_left x, y; bbox_bottom_right x, y; conf_score;class (all zeros [only human])
+ */
+int FairmotPostProcess::ObjectDetectionOutput(const vector <TensorBase> &tensors,
+                                              vector <vector<ObjectInfo>> &objectInfos,
+                                              vector<vector<float>> &ID_feature,
+                                              const vector <ResizedImageInfo> &resizedImageInfos) 
+{
+    LogDebug << "FairmotPostProcess start to write results.";
+    // Judge whether the input from tensorinfer is empty
+    if (tensors.size() == 0) {              
+        return 0;
+    }
+    auto shape = tensors[0].GetShape();     
+    if (shape.size() == 0) {
+        return 0;
+    }     
+
+    // @param featLayerData  Vector of 4 output feature data        
+    std::vector <std::shared_ptr<void>> featLayerData = {};             
+    std::vector <std::vector<size_t>> featLayerShapes = {}; 
+    for (uint32_t j = 0; j < tensors.size(); j++) {
+        auto dataPtr = (uint8_t *)tensors[j].GetBuffer(); 
+        std::shared_ptr<void> tmpPointer;
+        tmpPointer.reset(dataPtr, uint8Deleter);
+        // featLayerData stores the head address of 4 output feature data
+        featLayerData.push_back(tmpPointer);                                
+        shape = tensors[j].GetShape();
+
+        std::vector <size_t> featLayerShape = {};
+        for (auto s : shape) {
+            featLayerShape.push_back((size_t) s);
+        }
+        // featLayerShapes stores the shapes of 4 output feature data
+        featLayerShapes.push_back(featLayerShape);             
+    }
+
+    // tensors[0] matchs hm
+    // tensors[1] matchs wh
+    // tensors[2] matchs reg
+    // tensors[3] matchs id_feature
+    // Get the head address of hm
+    std::shared_ptr<void> hm_addr = featLayerData[0];
+    // Create a vector container XY to store coordinate information
+    std::vector<std::vector<int>> XY;
+    for(uint32_t i = 0;i < featLayerShapes[0][1] * featLayerShapes[0][2];i++){
+        // Compared with the threshold CONF_THRES to obtain coordinate information
+        if(static_cast<float *>(hm_addr.get())[i] > CONF_THRES)
+        {
+            std::vector<int>xy;                
+            int x = i / featLayerShapes[0][2];
+            int y = i - featLayerShapes[0][2] * x;
+            xy.push_back(x);
+            xy.push_back(y); 
+            XY.push_back(xy);  
+        }
+    }
+    // Output 1 when no pedestrian is detected
+    if(XY.size() == 0){
+        return 1;
+    }
+    // Create a vector container scores to store the information in the corresponding coordinate XY in hm
+    std::vector<float>scores;
+    for(uint32_t i = 0;i < XY.size();i++){
+        scores.push_back(static_cast<float *>(hm_addr.get())[XY[i][0] * featLayerShapes[0][2] + XY[i][1]]);
+    }
+    // Get the head address of wh and reg
+    std::shared_ptr<void> wh_addr = featLayerData[1];
+    std::shared_ptr<void> reg_addr = featLayerData[2];
+
+    // WH: n*4
+    std::vector<std::vector<float>>WH;
+    for(int i = 0; i < XY.size();i++){
+        std::vector<float>wh;
+        // featLayerShapes[1][3]: the third dimension of tensor[2]
+        for(int j = 0;j < featLayerShapes[1][3];j++){
+            wh.push_back(static_cast<float *>(wh_addr.get())[(XY[i][0] * featLayerShapes[0][2] + XY[i][1]) * featLayerShapes[1][3] + j]);
+        }
+        WH.push_back(wh);
+    }
+
+    // REG: n*2
+    std::vector<std::vector<float>>REG;
+    for(int i = 0; i < XY.size();i++){
+        std::vector<float>reg;
+        // featLayerShapes[2][3]: the third dimension of tensor[1]
+        for(int j = 0;j < featLayerShapes[2][3];j++){
+            reg.push_back(static_cast<float *>(reg_addr.get())[(XY[i][0] * featLayerShapes[0][2] + XY[i][1]) * featLayerShapes[2][3] + j]);
+        }
+        REG.push_back(reg);
+    }
+
+    // ID_feature: n*128
+    std::shared_ptr<void> id_addr = featLayerData[3];
+    for(int i = 0; i < XY.size();i++){
+        // featLayerShapes[3][3]: the third dimension of tensor[0]
+        std::vector<float>id_feature;
+        for(int j = 0;j < featLayerShapes[3][3];j++){
+            id_feature.push_back(static_cast<float *>(id_addr.get())[(XY[i][0] * featLayerShapes[0][2] + XY[i][1]) * featLayerShapes[3][3] + j]);
+        }
+        ID_feature.push_back(id_feature);
+    }
+    // XY_f changes the data in XY from int to float
+    std::vector<std::vector<float>> XY_f;
+    for(int i = 0;i < XY.size();i++){
+        std::vector<float>xy_f;
+        xy_f.push_back(XY[i][0]);
+        xy_f.push_back(XY[i][1]);
+        XY_f.push_back(xy_f);
+    }
+
+    for(int i = 0;i < XY_f.size();i++){                
+        XY_f[i][1] = XY_f[i][1] + REG[i][0];
+        XY_f[i][0] = XY_f[i][0] + REG[i][1];
+    }
+    // dets: n*6
+    std::vector<std::vector<float>>dets;
+    for(int i = 0;i < XY.size();i++){
+        std::vector<float>det;
+        det.push_back(XY_f[i][1] - WH[i][0]);
+        det.push_back(XY_f[i][0] - WH[i][1]);
+        det.push_back(XY_f[i][1] + WH[i][2]);
+        det.push_back(XY_f[i][0] + WH[i][3]);
+        det.push_back(scores[i]);
+        det.push_back(0);
+        dets.push_back(det);
+    }
+
+    // Width and height of initial video
+    int width = resizedImageInfos[0].widthOriginal;          
+    int height = resizedImageInfos[0].heightOriginal; 
+    // Scaled width and height           
+    int inp_height = resizedImageInfos[0].heightResize;      
+    int inp_width = resizedImageInfos[0].widthResize; 
+
+    // Create a vector container center to store the center point of the original picture
+    std::vector<float>c;
+    int half = 2;
+    c.push_back(width / half);
+    c.push_back(height / half);
+    std::vector<float>center(c);
+    // max_dets 
+    float scale = 0;
+    scale = std::max(float(inp_width) / float(inp_height) * height, float(width)) * 1.0 ;
+    std::vector<float>Scale;
+    Scale.push_back(scale);
+    Scale.push_back(scale);
+    // output_size
+    int down_ratio = 4;
+    int h = inp_height / down_ratio ;
+    int w = inp_width / down_ratio ;
+    std::vector<int>output_size;
+    output_size.push_back(w);
+    output_size.push_back(h);
+
+    int rot = 0;
+    std::vector<float>shift(2,0);        
+    int inv = 1;
+    // Input of get_affine_transform used to calculate trans: center, scale, rot, output_size, shift, inv
+    // get_affine_transform
+    std::vector<float>scale_tmp(Scale);
+    float src_w = scale_tmp[0];
+    int dst_w = output_size[0];
+    int dst_h = output_size[1];
+
+    float pi = 3.1415926;
+    int dir = 180;
+    float rot_rad = pi * rot / dir;
+
+    std::vector<float>src_point;
+    src_point.push_back(0);
+    src_point.push_back(src_w * (-0.5));
+
+    float sn = sin(rot_rad);
+    float cs = cos(rot_rad);
+    // get_dir
+    // src_dir and dst_dir are used to calculate trans
+    std::vector<float>src_dir(2,0);
+    src_dir[0] = src_point[0] * cs - src_point[1] * sn ;
+    src_dir[1] = src_point[0] * sn + src_point[1] * cs ;  
+    std::vector<float>dst_dir;
+    dst_dir.push_back(0);
+    dst_dir.push_back(dst_w * (-0.5));
+    // src and dst are calculated to calculate trans
+    float src[3][2] = {0};
+    float dst[3][2] = {0};
+    src[0][0] = center[0] + scale_tmp[0] * shift[0];
+    src[0][1] = center[1] + scale_tmp[1] * shift[1];
+    src[1][0] = center[0] + src_dir[0] + scale_tmp[0] * shift[0];
+    src[1][1] = center[1] + src_dir[1] + scale_tmp[1] * shift[1];
+    dst[0][0] = dst_w * 0.5;
+    dst[0][1] = dst_h * 0.5;
+    dst[1][0] = dst_w * 0.5 + dst_dir[0];
+    dst[1][1] = dst_h * 0.5 + dst_dir[1];        
+    // get_3rd_point
+    std::vector<float>direct;
+    direct.push_back(src[0][0]-src[1][0]);
+    direct.push_back(src[0][1]-src[1][1]);
+    src[2][0] = src[1][0] - direct[1];
+    src[2][1] = src[1][1] + direct[0];
+    // get_3rd_point
+    direct[0] = dst[0][0] - dst[1][0];
+    direct[1] = dst[0][1] - dst[1][1];
+    dst[2][0] = dst[1][0] - direct[1];
+    dst[2][1] = dst[1][1] + direct[0];
+
+    // change data in src and dst to point2f format  
+    cv::Point2f SRC[3];
+    cv::Point2f DST[3];
+    SRC[0] = cv::Point2f(src[0][0],src[0][1]);
+    SRC[1] = cv::Point2f(src[1][0],src[1][1]);
+    SRC[2] = cv::Point2f(src[2][0],src[2][1]);
+    DST[0] = cv::Point2f(dst[0][0],dst[0][1]);
+    DST[1] = cv::Point2f(dst[1][0],dst[1][1]);
+    DST[2] = cv::Point2f(dst[2][0],dst[2][1]);
+    // Calculate trans
+    cv::Mat trans(2, 3, CV_64FC1);
+    if(inv == 1){
+        trans = cv::getAffineTransform(DST,SRC);
+    }
+    else{
+        trans = cv::getAffineTransform(SRC,DST);
+    }
+    // Get data from mat type trans to array Trans
+    float Trans[2][3];
+    for(int i = 0;i < 2;i++){
+        for(int j = 0;j < 3;j++){
+            Trans[i][j] = trans.at<double>(i,j);
+        }
+    }
+    // affine_transform
+    // Calculate the coordinates of bbox_top_left x, y
+    for(int i = 0;i < dets.size();i++){
+        float new_pt[3] = {dets[i][0], dets[i][1], 1 };
+        dets[i][0] = Trans[0][0]* new_pt[0] + Trans[0][1]* new_pt[1] + Trans[0][2]* new_pt[2]; 
+        dets[i][1] = Trans[1][0]* new_pt[0] + Trans[1][1]* new_pt[1] + Trans[1][2]* new_pt[2]; 
+    }
+    // Calculate the coordinates of bbox_bottom_right x, y
+    for(int i = 0;i < dets.size();i++){
+        float new_pt[3] = {dets[i][2], dets[i][3], 1 };
+        dets[i][2] = Trans[0][0]* new_pt[0] + Trans[0][1]* new_pt[1] + Trans[0][2]* new_pt[2]; 
+        dets[i][3] = Trans[1][0]* new_pt[0] + Trans[1][1]* new_pt[1] + Trans[1][2]* new_pt[2]; 
+    }
+    // output
+    std::vector <ObjectInfo> objectInfo;        
+    for(int i = 0;i < dets.size();i++){
+        ObjectInfo objInfo;
+        objInfo.classId = 0;
+        objInfo.confidence = dets[i][4];
+        objInfo.className = " ";
+        // Normalization
+        objInfo.x0 = dets[i][0] / resizedImageInfos[0].widthOriginal;
+        objInfo.y0 = dets[i][1] / resizedImageInfos[0].heightOriginal;
+        objInfo.x1 = dets[i][2] / resizedImageInfos[0].widthOriginal;
+        objInfo.y1 = dets[i][3] / resizedImageInfos[0].heightOriginal;
+        objectInfo.push_back(objInfo);
+    }
+
+    objectInfos.push_back(objectInfo);
+    
+    LogDebug << "FairmotPostProcess write results successed."; 
+    // Output 2 when pedestrian is detected  
+    return 2;
+}
+
+APP_ERROR FairmotPostProcess::GenerateOutput(const MxTools::MxpiTensorPackageList srcMxpiTensorPackage,
+                                             std::vector <ResizedImageInfo> &resizedImageInfos,
+                                             MxTools::MxpiObjectList& dstMxpiObjectList, 
+                                             MxpiFeatureVectorList& dstMxpiFeatureVectorList)
+{
+    // Get Tensor
+    std::vector<MxBase::TensorBase> tensors = {};
+    GetTensors(srcMxpiTensorPackage, tensors);
+
+    // Check Tensor
+    bool isValid = IsValidTensors(tensors);
+    if (!isValid)
+    {
+        LogError << "Is unValid Tensors";
+        return APP_ERR_ACL_OP_INPUT_NOT_MATCH;
+    }
+
+    // Compute objects
+    std::vector<std::vector<ObjectInfo>> objectInfos;
+    std::vector<std::vector<float>> ID_feature;
+    int flag = ObjectDetectionOutput(tensors, objectInfos, ID_feature, resizedImageInfos);
+    if(flag == 1){
+        // flag: 1 represents no pedestrians are detected
+        MxpiObject* dstMxpiObject = dstMxpiObjectList.add_objectvec();   
+        MxpiClass* dstMxpiClass = dstMxpiObject->add_classvec();  
+        MxpiFeatureVector* mxpiFeature = dstMxpiFeatureVectorList.add_featurevec();
+        MxpiMetaHeader* dstMxpiMetaHeaderList = mxpiFeature->add_headervec();
+        return APP_ERR_OK;
+    }
+    else if(flag == 2){
+        // flag: 2 represents pedestrian detected
+        for (uint32_t i = 0; i < resizedImageInfos.size(); i++) {
+            CoordinatesReduction(i, resizedImageInfos[i], objectInfos[i]);
+        }
+        
+        // Generate ObjectList
+        for (size_t i = 0; i < objectInfos[0].size(); i++)
+        {
+            auto objInfo = objectInfos[0][i];
+            MxpiObject* dstMxpiObject = dstMxpiObjectList.add_objectvec();
+            MxpiMetaHeader* dstMxpiMetaHeaderList = dstMxpiObject->add_headervec();
+            dstMxpiMetaHeaderList->set_datasource(parentName_);
+            dstMxpiMetaHeaderList->set_memberid(0);
+
+            dstMxpiObject->set_x0(objInfo.x0);
+            dstMxpiObject->set_y0(objInfo.y0);
+            dstMxpiObject->set_x1(objInfo.x1);
+            dstMxpiObject->set_y1(objInfo.y1);
+
+            // Generate ClassList
+            MxpiClass* dstMxpiClass = dstMxpiObject->add_classvec();
+            MxpiMetaHeader* dstMxpiMetaHeaderList_c = dstMxpiClass->add_headervec();
+            dstMxpiMetaHeaderList_c->set_datasource(parentName_);
+            dstMxpiMetaHeaderList_c->set_memberid(0);
+            dstMxpiClass->set_classid(objInfo.classId);
+            dstMxpiClass->set_confidence(objInfo.confidence);
+            dstMxpiClass->set_classname(objInfo.className);
+        }
+
+        // Generate FeatureVectorList
+        for (size_t i = 0; i < ID_feature[0].size(); i++)
+        {
+            float feaInfo = ID_feature[0][i];
+            MxpiFeatureVector* mxpiFeature = dstMxpiFeatureVectorList.add_featurevec();
+            MxpiMetaHeader* dstMxpiMetaHeaderList = mxpiFeature->add_headervec();
+            dstMxpiMetaHeaderList->set_datasource(parentName_);
+            dstMxpiMetaHeaderList->set_memberid(0);
+
+            mxpiFeature->add_featurevalues(feaInfo);
+        }
+        return APP_ERR_OK;
+    }
+    else{
+        // flag: 0 represents the input from tensorinfer is empty
+        LogError << "Is unValid Tensors";
+        return APP_ERR_ACL_OP_INPUT_NOT_MATCH;
+    }
+}
+
+APP_ERROR FairmotPostProcess::Process(std::vector<MxpiBuffer*>& mxpiBuffer) {
+    LogInfo << "FairmotPostProcess::Process start";
+    MxpiBuffer* buffer = mxpiBuffer[0];
+    MxpiMetadataManager mxpiMetadataManager(*buffer);
+    MxpiErrorInfo mxpiErrorInfo;
+    ErrorInfo_.str("");
+    auto errorInfoPtr = mxpiMetadataManager.GetErrorInfo();
+    if (errorInfoPtr != nullptr) {
+        return PrintMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo, APP_ERR_COMM_FAILURE, "FairmotPostProcess process is not implemented");
+    }
+    // Get the data from buffer
+    shared_ptr<void> metadata = mxpiMetadataManager.GetMetadata(parentName_);
+    if (metadata == nullptr) {
+        return PrintMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo, APP_ERR_METADATA_IS_NULL, "Metadata is NULL, failed");
+    }
+    // check the proto struct name
+    google::protobuf::Message* msg = (google::protobuf::Message*)metadata.get();
+    const google::protobuf::Descriptor* desc = msg->GetDescriptor();
+    if (desc->name() != INPUT_SHAPE_TYPE) {
+        return PrintMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo, APP_ERR_PROTOBUF_NAME_MISMATCH, "Proto struct name is not MxpiTensorPackageList, failed");
+    }
+    shared_ptr<MxpiTensorPackageList> srcMxpiTensorPackageListSptr = static_pointer_cast<MxpiTensorPackageList>(metadata);
+    shared_ptr<MxpiObjectList> dstMxpiObjectList = make_shared<MxpiObjectList>();
+    shared_ptr<MxpiFeatureVectorList> dstMxpiFeatureVectorList = make_shared<MxpiFeatureVectorList>();
+    std::vector <ResizedImageInfo> resizedImageInfos;
+    // Get resizedImageInfos
+    APP_ERROR ret = GenerateresizedImageInfos(mxpiBuffer, *srcMxpiTensorPackageListSptr, resizedImageInfos);
+    if (ret != APP_ERR_OK) {
+        return PrintMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo, ret, "Generate resizedImageInfos failed");
+    }
+    // Generate sample output
+    ret = GenerateOutput(*srcMxpiTensorPackageListSptr, resizedImageInfos, *dstMxpiObjectList, *dstMxpiFeatureVectorList);
+    if (ret != APP_ERR_OK) {
+        return PrintMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo, ret, "FairmotPostProcess gets inference information failed. Checkc tensor value!");
+    }
+    // Add Generated data to metedata
+    ret = mxpiMetadataManager.AddProtoMetadata(METADATA_KEY_OBJ, static_pointer_cast<void>(dstMxpiObjectList));
+    if (ret != APP_ERR_OK) {
+        return PrintMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo, ret, "FairmotPostProcess add MxpiObjectList metadata failed.");
+    }
+    ret = mxpiMetadataManager.AddProtoMetadata(METADATA_KEY_FEA, static_pointer_cast<void>(dstMxpiFeatureVectorList));
+    if (ret != APP_ERR_OK) {
+        return PrintMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo, ret, "FairmotPostProcess add MxpiFeatureVectorList metadata failed.");
+    }
+    // Send the data to downstream plugin
+    SendData(0, *buffer);
+    LogInfo << "FairmotPostProcess::Process end";
+    return APP_ERR_OK;
+}
+
+std::vector<std::shared_ptr<void>> FairmotPostProcess::DefineProperties()
+{
+    // Define an A to store properties
+    std::vector<std::shared_ptr<void>> properties;
+    // Set the type and related information of the properties, and the key is the name
+    auto descriptionMessageProSptr = std::make_shared<ElementProperty<string>>(ElementProperty<string>{
+        STRING, "descriptionMessage", "message", "Description mesasge of plugin", "This is FairmotPostProcess", "NULL", "NULL"});
+    properties.push_back(descriptionMessageProSptr);
+    return properties;
+}
+
+// Register the Sample plugin through macro
+MX_PLUGIN_GENERATE(FairmotPostProcess)
diff --git a/contrib/FairMOT/plugins/FairmotPostProcess/FairmotPostProcess.h b/mxVision/mxVision-referenceapps/FairMOT/plugins/FairmotPostProcess/FairmotPostProcess.h
similarity index 97%
rename from contrib/FairMOT/plugins/FairmotPostProcess/FairmotPostProcess.h
rename to mxVision/mxVision-referenceapps/FairMOT/plugins/FairmotPostProcess/FairmotPostProcess.h
index 47fd153c3ef3b484da191d467b2bc7f873dcbc6e..1825ac4e36113a5f81427fea44173a1df0f3f58e 100644
--- a/contrib/FairMOT/plugins/FairmotPostProcess/FairmotPostProcess.h
+++ b/mxVision/mxVision-referenceapps/FairMOT/plugins/FairmotPostProcess/FairmotPostProcess.h
@@ -1,100 +1,100 @@
-/*
- * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#ifndef SDKMEMORY_FairmotPostProcess_H
-#define SDKMEMORY_FairmotPostProcess_H
-#include "MxTools/PluginToolkit/base/MxPluginGenerator.h"
-#include "MxTools/PluginToolkit/base/MxPluginBase.h"
-#include "MxTools/PluginToolkit/metadata/MxpiMetadataManager.h"
-#include "MxTools/Proto/MxpiDataType.pb.h"
-#include "MxBase/ErrorCode/ErrorCode.h"
-#include "MxBase/Tensor/TensorBase/TensorBase.h"
-#include "opencv2/opencv.hpp"
-
-#include "MxTools/PluginToolkit/PostProcessPluginBases/MxImagePostProcessorBase.h"
-
-/**
-* @api
-* @brief Definition of FairmotPostProcess class.
-*/
-namespace MxPlugins {
-class FairmotPostProcess : public MxTools::MxPluginBase {
-public:
-    /**
-     * @api
-     * @brief Initialize configure parameter.
-     * @param configParamMap
-     * @return APP_ERROR
-     */
-    APP_ERROR Init(std::map<std::string, std::shared_ptr<void>>& configParamMap) override;
-    /**
-     * @api
-     * @brief DeInitialize configure parameter.
-     * @return APP_ERROR
-     */
-    APP_ERROR DeInit() override;
-    /**
-     * @api
-     * @brief Process the data of MxpiBuffer.
-     * @param mxpiBuffer
-     * @return APP_ERROR
-     */
-    APP_ERROR Process(std::vector<MxTools::MxpiBuffer*>& mxpiBuffer) override;
-    /**
-     * @api
-     * @brief Definition the parameter of configure properties.
-     * @return std::vector<std::shared_ptr<void>>
-     */
-    static std::vector<std::shared_ptr<void>> DefineProperties();
-    /**
-     * @api
-     * @brief Get the number of class id and confidence from model inference.
-     * @param key
-     * @param buffer
-     * @return APP_ERROR
-     */
-    
-protected:        
-    bool IsValidTensors(const std::vector <MxBase::TensorBase> &tensors);
-
-    APP_ERROR GenerateresizedImageInfos(std::vector<MxTools::MxpiBuffer*> mxpiBuffer,
-                                        const MxTools::MxpiTensorPackageList srcMxpiTensorPackage,
-                                        std::vector <MxBase::ResizedImageInfo> &resizedImageInfos); 
-
-    APP_ERROR GenerateOutput(const MxTools::MxpiTensorPackageList srcMxpiTensorPackage,
-                             std::vector <MxBase::ResizedImageInfo> &resizedImageInfos,
-                             MxTools::MxpiObjectList& dstMxpiObjectList, 
-                             MxTools::MxpiFeatureVectorList& dstMxpiFeatureVectorList);
-
-    int ObjectDetectionOutput(const std::vector <MxBase::TensorBase> &tensors,
-                               std::vector <std::vector<MxBase::ObjectInfo>> &objectInfos,
-                               std::vector<std::vector<float>> &ID_feature,
-                               const std::vector <MxBase::ResizedImageInfo> &resizedImageInfos = {});
-    void CoordinatesReduction(const uint32_t index,
-                              const MxBase::ResizedImageInfo &resizedImageInfo,
-                              std::vector<MxBase::ObjectInfo> &objInfos,
-                              bool normalizedFlag = true);
-private:
-    APP_ERROR SetMxpiErrorInfo(MxTools::MxpiBuffer& buffer, const std::string pluginName,
-    const MxTools::MxpiErrorInfo mxpiErrorInfo);
-    APP_ERROR PrintMxpiErrorInfo(MxTools::MxpiBuffer& buffer, const std::string pluginName,
-    const MxTools::MxpiErrorInfo mxpiErrorInfo, APP_ERROR app_error, std::string errorName);
-    std::string parentName_;
-    std::string descriptionMessage_;
-    std::ostringstream ErrorInfo_;
-};
-}
-#endif // SDKMEMORY_FairmotPostProcess_H
+/*
+ * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef SDKMEMORY_FairmotPostProcess_H
+#define SDKMEMORY_FairmotPostProcess_H
+#include "MxTools/PluginToolkit/base/MxPluginGenerator.h"
+#include "MxTools/PluginToolkit/base/MxPluginBase.h"
+#include "MxTools/PluginToolkit/metadata/MxpiMetadataManager.h"
+#include "MxTools/Proto/MxpiDataType.pb.h"
+#include "MxBase/ErrorCode/ErrorCode.h"
+#include "MxBase/Tensor/TensorBase/TensorBase.h"
+#include "opencv2/opencv.hpp"
+
+#include "MxTools/PluginToolkit/PostProcessPluginBases/MxImagePostProcessorBase.h"
+
+/**
+* @api
+* @brief Definition of FairmotPostProcess class.
+*/
+namespace MxPlugins {
+class FairmotPostProcess : public MxTools::MxPluginBase {
+public:
+    /**
+     * @api
+     * @brief Initialize configure parameter.
+     * @param configParamMap
+     * @return APP_ERROR
+     */
+    APP_ERROR Init(std::map<std::string, std::shared_ptr<void>>& configParamMap) override;
+    /**
+     * @api
+     * @brief DeInitialize configure parameter.
+     * @return APP_ERROR
+     */
+    APP_ERROR DeInit() override;
+    /**
+     * @api
+     * @brief Process the data of MxpiBuffer.
+     * @param mxpiBuffer
+     * @return APP_ERROR
+     */
+    APP_ERROR Process(std::vector<MxTools::MxpiBuffer*>& mxpiBuffer) override;
+    /**
+     * @api
+     * @brief Definition the parameter of configure properties.
+     * @return std::vector<std::shared_ptr<void>>
+     */
+    static std::vector<std::shared_ptr<void>> DefineProperties();
+    /**
+     * @api
+     * @brief Get the number of class id and confidence from model inference.
+     * @param key
+     * @param buffer
+     * @return APP_ERROR
+     */
+    
+protected:        
+    bool IsValidTensors(const std::vector <MxBase::TensorBase> &tensors);
+
+    APP_ERROR GenerateresizedImageInfos(std::vector<MxTools::MxpiBuffer*> mxpiBuffer,
+                                        const MxTools::MxpiTensorPackageList srcMxpiTensorPackage,
+                                        std::vector <MxBase::ResizedImageInfo> &resizedImageInfos); 
+
+    APP_ERROR GenerateOutput(const MxTools::MxpiTensorPackageList srcMxpiTensorPackage,
+                             std::vector <MxBase::ResizedImageInfo> &resizedImageInfos,
+                             MxTools::MxpiObjectList& dstMxpiObjectList, 
+                             MxTools::MxpiFeatureVectorList& dstMxpiFeatureVectorList);
+
+    int ObjectDetectionOutput(const std::vector <MxBase::TensorBase> &tensors,
+                               std::vector <std::vector<MxBase::ObjectInfo>> &objectInfos,
+                               std::vector<std::vector<float>> &ID_feature,
+                               const std::vector <MxBase::ResizedImageInfo> &resizedImageInfos = {});
+    void CoordinatesReduction(const uint32_t index,
+                              const MxBase::ResizedImageInfo &resizedImageInfo,
+                              std::vector<MxBase::ObjectInfo> &objInfos,
+                              bool normalizedFlag = true);
+private:
+    APP_ERROR SetMxpiErrorInfo(MxTools::MxpiBuffer& buffer, const std::string pluginName,
+    const MxTools::MxpiErrorInfo mxpiErrorInfo);
+    APP_ERROR PrintMxpiErrorInfo(MxTools::MxpiBuffer& buffer, const std::string pluginName,
+    const MxTools::MxpiErrorInfo mxpiErrorInfo, APP_ERROR app_error, std::string errorName);
+    std::string parentName_;
+    std::string descriptionMessage_;
+    std::ostringstream ErrorInfo_;
+};
+}
+#endif // SDKMEMORY_FairmotPostProcess_H
diff --git a/contrib/FairMOT/plugins/FairmotPostProcess/build.sh b/mxVision/mxVision-referenceapps/FairMOT/plugins/FairmotPostProcess/build.sh
similarity index 100%
rename from contrib/FairMOT/plugins/FairmotPostProcess/build.sh
rename to mxVision/mxVision-referenceapps/FairMOT/plugins/FairmotPostProcess/build.sh
diff --git a/contrib/FairMOT/plugins/MxpiTrackIdReplaceClassName/CMakeLists.txt b/mxVision/mxVision-referenceapps/FairMOT/plugins/MxpiTrackIdReplaceClassName/CMakeLists.txt
similarity index 100%
rename from contrib/FairMOT/plugins/MxpiTrackIdReplaceClassName/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/FairMOT/plugins/MxpiTrackIdReplaceClassName/CMakeLists.txt
diff --git a/contrib/FairMOT/plugins/MxpiTrackIdReplaceClassName/MxpiTrackIdReplaceClassName.cpp b/mxVision/mxVision-referenceapps/FairMOT/plugins/MxpiTrackIdReplaceClassName/MxpiTrackIdReplaceClassName.cpp
similarity index 100%
rename from contrib/FairMOT/plugins/MxpiTrackIdReplaceClassName/MxpiTrackIdReplaceClassName.cpp
rename to mxVision/mxVision-referenceapps/FairMOT/plugins/MxpiTrackIdReplaceClassName/MxpiTrackIdReplaceClassName.cpp
diff --git a/contrib/FairMOT/plugins/MxpiTrackIdReplaceClassName/MxpiTrackIdReplaceClassName.h b/mxVision/mxVision-referenceapps/FairMOT/plugins/MxpiTrackIdReplaceClassName/MxpiTrackIdReplaceClassName.h
similarity index 100%
rename from contrib/FairMOT/plugins/MxpiTrackIdReplaceClassName/MxpiTrackIdReplaceClassName.h
rename to mxVision/mxVision-referenceapps/FairMOT/plugins/MxpiTrackIdReplaceClassName/MxpiTrackIdReplaceClassName.h
diff --git a/contrib/FairMOT/plugins/MxpiTrackIdReplaceClassName/build.sh b/mxVision/mxVision-referenceapps/FairMOT/plugins/MxpiTrackIdReplaceClassName/build.sh
similarity index 100%
rename from contrib/FairMOT/plugins/MxpiTrackIdReplaceClassName/build.sh
rename to mxVision/mxVision-referenceapps/FairMOT/plugins/MxpiTrackIdReplaceClassName/build.sh
diff --git a/contrib/FairMOT/run.sh b/mxVision/mxVision-referenceapps/FairMOT/run.sh
similarity index 100%
rename from contrib/FairMOT/run.sh
rename to mxVision/mxVision-referenceapps/FairMOT/run.sh
diff --git a/contrib/FairMOT/test/main.cpp b/mxVision/mxVision-referenceapps/FairMOT/test/main.cpp
similarity index 96%
rename from contrib/FairMOT/test/main.cpp
rename to mxVision/mxVision-referenceapps/FairMOT/test/main.cpp
index 384f275b22e135d922b461cbf9c891030e741495..6f14a4f5c2c7432316355a31fa46450b81c37f04 100644
--- a/contrib/FairMOT/test/main.cpp
+++ b/mxVision/mxVision-referenceapps/FairMOT/test/main.cpp
@@ -1,140 +1,140 @@
-/*
- * Copyright (c) 2021.Huawei Technologies Co., Ltd. All rights reserved.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *     http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#include <fstream>
-#include <iostream>
-#include <string>
-#include <vector>
-#include <cstring>
-#include <sys/time.h>
-#include <ctime>
-#include <stdio.h> 
-#include <chrono> 
-#include "MxBase/Log/Log.h"
-#include "MxStream/StreamManager/MxStreamManager.h"
-#include <sys/time.h>
-#include <ctime>
-#include <stdio.h> 
-#include <chrono> 
-
-namespace {
-std::string ReadPipelineConfig(const std::string& pipelineConfigPath)
-{
-    std::ifstream file(pipelineConfigPath.c_str(), std::ifstream::binary);
-    if (!file) {
-        LogError << pipelineConfigPath << " file dose not exist.";
-        return "";
-    }
-    file.seekg(0, std::ifstream::end);
-    uint32_t fileSize = file.tellg();
-    file.seekg(0);
-    std::unique_ptr<char[]> data(new char[fileSize]);
-    file.read(data.get(), fileSize);
-    file.close();
-    std::string pipelineConfig(data.get(), fileSize);
-    return pipelineConfig;
-}
-}
-
-int main(int argc, char* argv[])
-{
-    std::string pipelineConfigPath = "./pipeline/fairmot.pipeline";
-    std::string pipelineConfig = ReadPipelineConfig(pipelineConfigPath);
-    if (pipelineConfig == "") {
-        LogError << "Read pipeline failed.";
-        return APP_ERR_COMM_INIT_FAIL;
-    }
-
-    // init stream manager
-    MxStream::MxStreamManager mxStreamManager;
-    APP_ERROR ret = mxStreamManager.InitManager();
-    if (ret != APP_ERR_OK) {
-        LogError << "Failed to init Stream manager, ret = " << ret << ".";
-        return ret;
-    }
-
-    // create stream by pipeline config file
-    ret = mxStreamManager.CreateMultipleStreams(pipelineConfig);
-    if (ret != APP_ERR_OK) {
-        LogError << "Failed to create Stream, ret = " << ret << ".";
-        return ret;
-    }
-
-    // create h264 file
-    FILE *fp = fopen("./out.h264", "wb");
-    if (fp == nullptr) {
-        LogError << "Failed to open file.";
-        return APP_ERR_COMM_OPEN_FAIL;
-    }
-
-    bool m_bFoundFirstIDR = false;
-    bool bIsIDR = false;
-    uint32_t frameCount = 0;
-    uint32_t MaxframeCount = 5000;
-
-    std::string streamName = "encoder";
-    int inPluginId = 0;
-    int msTimeOut = 200000;
-
-    auto start = std::chrono::system_clock::now();
-
-    while (1) {
-        // get stream output
-        MxStream::MxstDataOutput* output = mxStreamManager.GetResult(streamName, inPluginId, msTimeOut);
-        if (output == nullptr) {
-            LogError << "Failed to get pipeline output.";
-            return ret;
-        }
-
-        // write to file first frame must IDR frame
-        bIsIDR = (output->dataSize > 1);
-        if(!m_bFoundFirstIDR)
-        {
-            if(!bIsIDR) {
-                continue;
-            } else {
-                m_bFoundFirstIDR = true;
-            }
-        }
-
-        // write frame to file
-        if (fwrite(output->dataPtr, output->dataSize, 1, fp) != 1) {
-            LogInfo << "write frame to file fail";
-        }
-        LogInfo << "Dealing frame id:" << frameCount;
-        frameCount++;
-        if (frameCount > MaxframeCount) {
-
-            LogInfo << "write frame to file done";
-            break;
-        }
-
-        delete output;
-
-        auto end = std::chrono::system_clock::now();
-        auto duration = std::chrono::duration_cast<std::chrono::microseconds>(end - start);
-        double average = (double)(duration.count()) * std::chrono::microseconds::period::num / std::chrono::microseconds::period::den / frameCount;
-        std::cout << "fps: " << 1 / average << std::endl;
-
-    }
-
-    fclose(fp);
-
-    // destroy streams
-    mxStreamManager.DestroyAllStreams();
-    return 0;
-}
-
+/*
+ * Copyright (c) 2021.Huawei Technologies Co., Ltd. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include <fstream>
+#include <iostream>
+#include <string>
+#include <vector>
+#include <cstring>
+#include <sys/time.h>
+#include <ctime>
+#include <stdio.h> 
+#include <chrono> 
+#include "MxBase/Log/Log.h"
+#include "MxStream/StreamManager/MxStreamManager.h"
+#include <sys/time.h>
+#include <ctime>
+#include <stdio.h> 
+#include <chrono> 
+
+namespace {
+std::string ReadPipelineConfig(const std::string& pipelineConfigPath)
+{
+    std::ifstream file(pipelineConfigPath.c_str(), std::ifstream::binary);
+    if (!file) {
+        LogError << pipelineConfigPath << " file dose not exist.";
+        return "";
+    }
+    file.seekg(0, std::ifstream::end);
+    uint32_t fileSize = file.tellg();
+    file.seekg(0);
+    std::unique_ptr<char[]> data(new char[fileSize]);
+    file.read(data.get(), fileSize);
+    file.close();
+    std::string pipelineConfig(data.get(), fileSize);
+    return pipelineConfig;
+}
+}
+
+int main(int argc, char* argv[])
+{
+    std::string pipelineConfigPath = "./pipeline/fairmot.pipeline";
+    std::string pipelineConfig = ReadPipelineConfig(pipelineConfigPath);
+    if (pipelineConfig == "") {
+        LogError << "Read pipeline failed.";
+        return APP_ERR_COMM_INIT_FAIL;
+    }
+
+    // init stream manager
+    MxStream::MxStreamManager mxStreamManager;
+    APP_ERROR ret = mxStreamManager.InitManager();
+    if (ret != APP_ERR_OK) {
+        LogError << "Failed to init Stream manager, ret = " << ret << ".";
+        return ret;
+    }
+
+    // create stream by pipeline config file
+    ret = mxStreamManager.CreateMultipleStreams(pipelineConfig);
+    if (ret != APP_ERR_OK) {
+        LogError << "Failed to create Stream, ret = " << ret << ".";
+        return ret;
+    }
+
+    // create h264 file
+    FILE *fp = fopen("./out.h264", "wb");
+    if (fp == nullptr) {
+        LogError << "Failed to open file.";
+        return APP_ERR_COMM_OPEN_FAIL;
+    }
+
+    bool m_bFoundFirstIDR = false;
+    bool bIsIDR = false;
+    uint32_t frameCount = 0;
+    uint32_t MaxframeCount = 5000;
+
+    std::string streamName = "encoder";
+    int inPluginId = 0;
+    int msTimeOut = 200000;
+
+    auto start = std::chrono::system_clock::now();
+
+    while (1) {
+        // get stream output
+        MxStream::MxstDataOutput* output = mxStreamManager.GetResult(streamName, inPluginId, msTimeOut);
+        if (output == nullptr) {
+            LogError << "Failed to get pipeline output.";
+            return ret;
+        }
+
+        // write to file first frame must IDR frame
+        bIsIDR = (output->dataSize > 1);
+        if(!m_bFoundFirstIDR)
+        {
+            if(!bIsIDR) {
+                continue;
+            } else {
+                m_bFoundFirstIDR = true;
+            }
+        }
+
+        // write frame to file
+        if (fwrite(output->dataPtr, output->dataSize, 1, fp) != 1) {
+            LogInfo << "write frame to file fail";
+        }
+        LogInfo << "Dealing frame id:" << frameCount;
+        frameCount++;
+        if (frameCount > MaxframeCount) {
+
+            LogInfo << "write frame to file done";
+            break;
+        }
+
+        delete output;
+
+        auto end = std::chrono::system_clock::now();
+        auto duration = std::chrono::duration_cast<std::chrono::microseconds>(end - start);
+        double average = (double)(duration.count()) * std::chrono::microseconds::period::num / std::chrono::microseconds::period::den / frameCount;
+        std::cout << "fps: " << 1 / average << std::endl;
+
+    }
+
+    fclose(fp);
+
+    // destroy streams
+    mxStreamManager.DestroyAllStreams();
+    return 0;
+}
+
diff --git a/contrib/FastSCNN/README.md b/mxVision/mxVision-referenceapps/FastSCNN/README.md
similarity index 100%
rename from contrib/FastSCNN/README.md
rename to mxVision/mxVision-referenceapps/FastSCNN/README.md
diff --git a/contrib/FastSCNN/evaluate.py b/mxVision/mxVision-referenceapps/FastSCNN/evaluate.py
similarity index 100%
rename from contrib/FastSCNN/evaluate.py
rename to mxVision/mxVision-referenceapps/FastSCNN/evaluate.py
diff --git a/contrib/FastSCNN/evaluation_100.png b/mxVision/mxVision-referenceapps/FastSCNN/evaluation_100.png
similarity index 100%
rename from contrib/FastSCNN/evaluation_100.png
rename to mxVision/mxVision-referenceapps/FastSCNN/evaluation_100.png
diff --git a/contrib/FastSCNN/evaluation_150.png b/mxVision/mxVision-referenceapps/FastSCNN/evaluation_150.png
similarity index 100%
rename from contrib/FastSCNN/evaluation_150.png
rename to mxVision/mxVision-referenceapps/FastSCNN/evaluation_150.png
diff --git a/contrib/FastSCNN/evaluation_50.png b/mxVision/mxVision-referenceapps/FastSCNN/evaluation_50.png
similarity index 100%
rename from contrib/FastSCNN/evaluation_50.png
rename to mxVision/mxVision-referenceapps/FastSCNN/evaluation_50.png
diff --git a/contrib/FastSCNN/label.py b/mxVision/mxVision-referenceapps/FastSCNN/label.py
similarity index 100%
rename from contrib/FastSCNN/label.py
rename to mxVision/mxVision-referenceapps/FastSCNN/label.py
diff --git a/contrib/FastSCNN/main.py b/mxVision/mxVision-referenceapps/FastSCNN/main.py
similarity index 100%
rename from contrib/FastSCNN/main.py
rename to mxVision/mxVision-referenceapps/FastSCNN/main.py
diff --git a/contrib/FastSCNN/model/aipp_FastSCnn.aippconfig b/mxVision/mxVision-referenceapps/FastSCNN/model/aipp_FastSCnn.aippconfig
similarity index 100%
rename from contrib/FastSCNN/model/aipp_FastSCnn.aippconfig
rename to mxVision/mxVision-referenceapps/FastSCNN/model/aipp_FastSCnn.aippconfig
diff --git a/contrib/FastSCNN/pipeline.png b/mxVision/mxVision-referenceapps/FastSCNN/pipeline.png
similarity index 100%
rename from contrib/FastSCNN/pipeline.png
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diff --git a/contrib/FastSCNN/text.pipeline b/mxVision/mxVision-referenceapps/FastSCNN/text.pipeline
similarity index 100%
rename from contrib/FastSCNN/text.pipeline
rename to mxVision/mxVision-referenceapps/FastSCNN/text.pipeline
diff --git "a/contrib/FastSCNN/\346\265\201\347\250\213.png" "b/mxVision/mxVision-referenceapps/FastSCNN/\346\265\201\347\250\213.png"
similarity index 100%
rename from "contrib/FastSCNN/\346\265\201\347\250\213.png"
rename to "mxVision/mxVision-referenceapps/FastSCNN/\346\265\201\347\250\213.png"
diff --git a/contrib/MediaCodeV2/logs/.keep b/mxVision/mxVision-referenceapps/Faster_R-CNN/.keep
similarity index 100%
rename from contrib/MediaCodeV2/logs/.keep
rename to mxVision/mxVision-referenceapps/Faster_R-CNN/.keep
diff --git a/contrib/Faster_R-CNN/README.md b/mxVision/mxVision-referenceapps/Faster_R-CNN/README.md
similarity index 100%
rename from contrib/Faster_R-CNN/README.md
rename to mxVision/mxVision-referenceapps/Faster_R-CNN/README.md
diff --git a/contrib/Faster_R-CNN/build.sh b/mxVision/mxVision-referenceapps/Faster_R-CNN/build.sh
similarity index 100%
rename from contrib/Faster_R-CNN/build.sh
rename to mxVision/mxVision-referenceapps/Faster_R-CNN/build.sh
diff --git a/contrib/Faster_R-CNN/images/1.png b/mxVision/mxVision-referenceapps/Faster_R-CNN/images/1.png
similarity index 100%
rename from contrib/Faster_R-CNN/images/1.png
rename to mxVision/mxVision-referenceapps/Faster_R-CNN/images/1.png
diff --git a/contrib/Faster_R-CNN/images/3.png b/mxVision/mxVision-referenceapps/Faster_R-CNN/images/3.png
similarity index 100%
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similarity index 100%
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rename to mxVision/mxVision-referenceapps/Faster_R-CNN/images/W0003_0001.jpg
diff --git a/contrib/Faster_R-CNN/images/permissionerror.png b/mxVision/mxVision-referenceapps/Faster_R-CNN/images/permissionerror.png
similarity index 100%
rename from contrib/Faster_R-CNN/images/permissionerror.png
rename to mxVision/mxVision-referenceapps/Faster_R-CNN/images/permissionerror.png
diff --git a/contrib/Faster_R-CNN/postprocess/CMakeLists.txt b/mxVision/mxVision-referenceapps/Faster_R-CNN/postprocess/CMakeLists.txt
similarity index 100%
rename from contrib/Faster_R-CNN/postprocess/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/Faster_R-CNN/postprocess/CMakeLists.txt
diff --git a/contrib/Faster_R-CNN/postprocess/FasterRcnnMindsporePost.cpp b/mxVision/mxVision-referenceapps/Faster_R-CNN/postprocess/FasterRcnnMindsporePost.cpp
similarity index 100%
rename from contrib/Faster_R-CNN/postprocess/FasterRcnnMindsporePost.cpp
rename to mxVision/mxVision-referenceapps/Faster_R-CNN/postprocess/FasterRcnnMindsporePost.cpp
diff --git a/contrib/Faster_R-CNN/postprocess/FasterRcnnMindsporePost.h b/mxVision/mxVision-referenceapps/Faster_R-CNN/postprocess/FasterRcnnMindsporePost.h
similarity index 100%
rename from contrib/Faster_R-CNN/postprocess/FasterRcnnMindsporePost.h
rename to mxVision/mxVision-referenceapps/Faster_R-CNN/postprocess/FasterRcnnMindsporePost.h
diff --git a/contrib/Faster_R-CNN/postprocess/build.sh b/mxVision/mxVision-referenceapps/Faster_R-CNN/postprocess/build.sh
similarity index 100%
rename from contrib/Faster_R-CNN/postprocess/build.sh
rename to mxVision/mxVision-referenceapps/Faster_R-CNN/postprocess/build.sh
diff --git a/contrib/Faster_R-CNN/python/Main/config.py b/mxVision/mxVision-referenceapps/Faster_R-CNN/python/Main/config.py
similarity index 100%
rename from contrib/Faster_R-CNN/python/Main/config.py
rename to mxVision/mxVision-referenceapps/Faster_R-CNN/python/Main/config.py
diff --git a/contrib/Faster_R-CNN/python/Main/draw_predict.py b/mxVision/mxVision-referenceapps/Faster_R-CNN/python/Main/draw_predict.py
similarity index 100%
rename from contrib/Faster_R-CNN/python/Main/draw_predict.py
rename to mxVision/mxVision-referenceapps/Faster_R-CNN/python/Main/draw_predict.py
diff --git a/contrib/Faster_R-CNN/python/Main/eval.py b/mxVision/mxVision-referenceapps/Faster_R-CNN/python/Main/eval.py
similarity index 100%
rename from contrib/Faster_R-CNN/python/Main/eval.py
rename to mxVision/mxVision-referenceapps/Faster_R-CNN/python/Main/eval.py
diff --git a/contrib/Faster_R-CNN/python/Main/eval_by_sdk.py b/mxVision/mxVision-referenceapps/Faster_R-CNN/python/Main/eval_by_sdk.py
similarity index 100%
rename from contrib/Faster_R-CNN/python/Main/eval_by_sdk.py
rename to mxVision/mxVision-referenceapps/Faster_R-CNN/python/Main/eval_by_sdk.py
diff --git a/contrib/Faster_R-CNN/python/Main/infer.py b/mxVision/mxVision-referenceapps/Faster_R-CNN/python/Main/infer.py
similarity index 100%
rename from contrib/Faster_R-CNN/python/Main/infer.py
rename to mxVision/mxVision-referenceapps/Faster_R-CNN/python/Main/infer.py
diff --git a/contrib/Faster_R-CNN/python/Main/main.py b/mxVision/mxVision-referenceapps/Faster_R-CNN/python/Main/main.py
similarity index 100%
rename from contrib/Faster_R-CNN/python/Main/main.py
rename to mxVision/mxVision-referenceapps/Faster_R-CNN/python/Main/main.py
diff --git a/contrib/Faster_R-CNN/python/Main/postprocess.py b/mxVision/mxVision-referenceapps/Faster_R-CNN/python/Main/postprocess.py
similarity index 100%
rename from contrib/Faster_R-CNN/python/Main/postprocess.py
rename to mxVision/mxVision-referenceapps/Faster_R-CNN/python/Main/postprocess.py
diff --git a/contrib/Faster_R-CNN/python/Main/util.py b/mxVision/mxVision-referenceapps/Faster_R-CNN/python/Main/util.py
similarity index 100%
rename from contrib/Faster_R-CNN/python/Main/util.py
rename to mxVision/mxVision-referenceapps/Faster_R-CNN/python/Main/util.py
diff --git a/contrib/Faster_R-CNN/python/models/aipp-configs/aipp.cfg b/mxVision/mxVision-referenceapps/Faster_R-CNN/python/models/aipp-configs/aipp.cfg
similarity index 100%
rename from contrib/Faster_R-CNN/python/models/aipp-configs/aipp.cfg
rename to mxVision/mxVision-referenceapps/Faster_R-CNN/python/models/aipp-configs/aipp.cfg
diff --git a/contrib/Faster_R-CNN/python/models/aipp-configs/aipp_rgb.cfg b/mxVision/mxVision-referenceapps/Faster_R-CNN/python/models/aipp-configs/aipp_rgb.cfg
similarity index 100%
rename from contrib/Faster_R-CNN/python/models/aipp-configs/aipp_rgb.cfg
rename to mxVision/mxVision-referenceapps/Faster_R-CNN/python/models/aipp-configs/aipp_rgb.cfg
diff --git a/contrib/Faster_R-CNN/python/models/coco2017.names b/mxVision/mxVision-referenceapps/Faster_R-CNN/python/models/coco2017.names
similarity index 100%
rename from contrib/Faster_R-CNN/python/models/coco2017.names
rename to mxVision/mxVision-referenceapps/Faster_R-CNN/python/models/coco2017.names
diff --git a/contrib/Faster_R-CNN/python/models/convert_om.sh b/mxVision/mxVision-referenceapps/Faster_R-CNN/python/models/convert_om.sh
similarity index 100%
rename from contrib/Faster_R-CNN/python/models/convert_om.sh
rename to mxVision/mxVision-referenceapps/Faster_R-CNN/python/models/convert_om.sh
diff --git a/contrib/Faster_R-CNN/python/models/fasterrcnn_coco2017.cfg b/mxVision/mxVision-referenceapps/Faster_R-CNN/python/models/fasterrcnn_coco2017.cfg
similarity index 100%
rename from contrib/Faster_R-CNN/python/models/fasterrcnn_coco2017.cfg
rename to mxVision/mxVision-referenceapps/Faster_R-CNN/python/models/fasterrcnn_coco2017.cfg
diff --git a/contrib/Faster_R-CNN/python/models/fasterrcnn_coco2017_acc_test.cfg b/mxVision/mxVision-referenceapps/Faster_R-CNN/python/models/fasterrcnn_coco2017_acc_test.cfg
similarity index 100%
rename from contrib/Faster_R-CNN/python/models/fasterrcnn_coco2017_acc_test.cfg
rename to mxVision/mxVision-referenceapps/Faster_R-CNN/python/models/fasterrcnn_coco2017_acc_test.cfg
diff --git a/contrib/Faster_R-CNN/python/pipeline/fasterrcnn_ms_acc_test.pipeline b/mxVision/mxVision-referenceapps/Faster_R-CNN/python/pipeline/fasterrcnn_ms_acc_test.pipeline
similarity index 100%
rename from contrib/Faster_R-CNN/python/pipeline/fasterrcnn_ms_acc_test.pipeline
rename to mxVision/mxVision-referenceapps/Faster_R-CNN/python/pipeline/fasterrcnn_ms_acc_test.pipeline
diff --git a/contrib/Faster_R-CNN/python/pipeline/fasterrcnn_ms_dvpp.pipeline b/mxVision/mxVision-referenceapps/Faster_R-CNN/python/pipeline/fasterrcnn_ms_dvpp.pipeline
similarity index 100%
rename from contrib/Faster_R-CNN/python/pipeline/fasterrcnn_ms_dvpp.pipeline
rename to mxVision/mxVision-referenceapps/Faster_R-CNN/python/pipeline/fasterrcnn_ms_dvpp.pipeline
diff --git a/contrib/FatigueDrivingRecognition/ModelTransformation/aipp_pfld_112_112.aippconfig b/mxVision/mxVision-referenceapps/FatigueDrivingRecognition/ModelTransformation/aipp_pfld_112_112.aippconfig
similarity index 100%
rename from contrib/FatigueDrivingRecognition/ModelTransformation/aipp_pfld_112_112.aippconfig
rename to mxVision/mxVision-referenceapps/FatigueDrivingRecognition/ModelTransformation/aipp_pfld_112_112.aippconfig
diff --git a/contrib/FatigueDrivingRecognition/ModelTransformation/atc_env.sh b/mxVision/mxVision-referenceapps/FatigueDrivingRecognition/ModelTransformation/atc_env.sh
similarity index 100%
rename from contrib/FatigueDrivingRecognition/ModelTransformation/atc_env.sh
rename to mxVision/mxVision-referenceapps/FatigueDrivingRecognition/ModelTransformation/atc_env.sh
diff --git a/contrib/FatigueDrivingRecognition/ModelTransformation/pytorch2onnx.py b/mxVision/mxVision-referenceapps/FatigueDrivingRecognition/ModelTransformation/pytorch2onnx.py
similarity index 100%
rename from contrib/FatigueDrivingRecognition/ModelTransformation/pytorch2onnx.py
rename to mxVision/mxVision-referenceapps/FatigueDrivingRecognition/ModelTransformation/pytorch2onnx.py
diff --git a/contrib/FatigueDrivingRecognition/Plugin1/CMakeLists.txt b/mxVision/mxVision-referenceapps/FatigueDrivingRecognition/Plugin1/CMakeLists.txt
similarity index 100%
rename from contrib/FatigueDrivingRecognition/Plugin1/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/FatigueDrivingRecognition/Plugin1/CMakeLists.txt
diff --git a/contrib/FatigueDrivingRecognition/Plugin1/MxpiPFLDPostProcessPlugin.cpp b/mxVision/mxVision-referenceapps/FatigueDrivingRecognition/Plugin1/MxpiPFLDPostProcessPlugin.cpp
similarity index 100%
rename from contrib/FatigueDrivingRecognition/Plugin1/MxpiPFLDPostProcessPlugin.cpp
rename to mxVision/mxVision-referenceapps/FatigueDrivingRecognition/Plugin1/MxpiPFLDPostProcessPlugin.cpp
diff --git a/contrib/FatigueDrivingRecognition/Plugin1/MxpiPFLDPostProcessPlugin.h b/mxVision/mxVision-referenceapps/FatigueDrivingRecognition/Plugin1/MxpiPFLDPostProcessPlugin.h
similarity index 100%
rename from contrib/FatigueDrivingRecognition/Plugin1/MxpiPFLDPostProcessPlugin.h
rename to mxVision/mxVision-referenceapps/FatigueDrivingRecognition/Plugin1/MxpiPFLDPostProcessPlugin.h
diff --git a/contrib/FatigueDrivingRecognition/Plugin1/build.sh b/mxVision/mxVision-referenceapps/FatigueDrivingRecognition/Plugin1/build.sh
similarity index 100%
rename from contrib/FatigueDrivingRecognition/Plugin1/build.sh
rename to mxVision/mxVision-referenceapps/FatigueDrivingRecognition/Plugin1/build.sh
diff --git a/contrib/FatigueDrivingRecognition/README.md b/mxVision/mxVision-referenceapps/FatigueDrivingRecognition/README.md
similarity index 97%
rename from contrib/FatigueDrivingRecognition/README.md
rename to mxVision/mxVision-referenceapps/FatigueDrivingRecognition/README.md
index 06631a311dbe3c8430643578ae3caaee0b8ffd31..3e8ad8de4f74a4784dbd13a4642c24d361b5c253 100644
--- a/contrib/FatigueDrivingRecognition/README.md
+++ b/mxVision/mxVision-referenceapps/FatigueDrivingRecognition/README.md
@@ -1,307 +1,307 @@
-# 疲劳驾驶识别（Fatigue driving recognition）
-
-## 1 介绍
-本开发样例演示驾驶人员疲劳状态识别系统（Fatigue driving recognition），供用户参考。本系统基于mxVision SDK进行开发，以昇腾Atlas300卡为主要的硬件平台，实现在驾驶环境下驾驶人员疲劳状态识别与预警。
-
-项目的整体流程如下：
-
-1. 利用目标检测模型采集视频中的目标图像
-2. 利用PFLD模型进行目标关键点检测，获取眼部位置信息
-3. 通过计算度量疲劳/瞌睡的物理量识别驾驶人员的疲劳状态
-
-### 1.1 支持的产品
-
-本项目以昇腾Atlas310卡为主要的硬件平台。
-
-### 1.2 支持的版本
-
-SDK版本为2.0.4，查询方法
-```
-cat ${SDK安装路径}/mxVision/version.info
-```
-CANN版本为22.0.2，查询方法：在Atlas产品环境下，运行命令：
-
-```
-npu-smi info
-```
-
-### 1.3 软件方案介绍
-
-请先总体介绍项目的方案架构。如果项目设计方案中涉及子系统，请详细描述各子系统功能。如果设计了不同的功能模块，则请详细描述各模块功能。
-
-表1.1 系统方案中各模块功能描述：
-
-| 序号 |      子系统      | 功能描述                                                     |
-| :--: | :--------------: | :----------------------------------------------------------- |
-|  1   |     视频输入     | 调用MindX SDK的mxpi_rtspsrc插件对视频数据进行拉流            |
-|  2   |     视频解码     | 调用MindX SDK的mxpi_videodecoder进行视频解码                 |
-|  3   |     图像放缩     | 调用MindX SDK的mxpi_imageresize进行图像缩放                  |
-|  4   |     目标检测     | 利用yolov4的检测模型检测出图片中的目标                       |
-|  5   |  目标检测后处理  | 调用yolov4模型后处理插件对检测结果进行后处理                 |
-|  6   |     裁剪图片     | 调用MindX SDK的mxpi_imagecrop进行图像裁剪                    |
-|  7   |  目标关键点检测  | 利用PFLD检测模型检测出图片中目标的106个关键点                |
-|  8   | 目标关键点后处理 | 根据PFLD模型的检测结果进行后处理，获取嘴部相关关键点以及嘴部纵横比信息 |
-|  9   |     结果输出     | 输出驾驶人员的疲劳状态并进行可视化输出                       |
-
-### 1.4 代码目录结构与说明
-
-本sample工程名称为 **FatigueDrivingRecognition**，工程目录如下所示：
-
-```she&#39;l&#39;l
-├── images #readme图片
-│   ├── diagram.png
-│   ├── Q1.png
-│   ├── Q2.png
-│   └── Q4.png
-├── model #模型目录
-│   ├── coco.names
-│   ├── pfld_106.om
-│   ├── yolov4.cfg
-│   └── yolov4_detection.om
-├── ModelTransformation #转换模型
-│   ├── aipp_pfld_112_112.aippconfig
-│   ├── atc_env.sh
-│   ├── pfld_106.onnx
-│   └── pytorch2onnx.py
-├── pipeline
-│   ├── parallel_pipeline.pipeline
-│   ├── test.pipeline
-│   └── test_video.pipeline
-├── Plugin1 #插件1工程目录
-│   ├── build.sh
-│   ├── CMakeLists.txt
-│   ├── MxpiPFLDPostProcessPlugin.cpp
-│   └── MxpiPFLDPostProcessPlugin.h
-├── build.sh
-├── evaluate.py
-├── parallel_update.py
-├── README.md
-├── run.sh
-├── test.py
-└── test_video.py
-```
-
-
-
-### 1.5 技术实现流程图
-
-本项目实现在驾驶环境下驾驶人员疲劳状态识别与预警，首先利用目标检测模型采集视频中的目标图像，然后利用PFLD模型进行目标关键点检测，获取嘴部位置信息，并通过计算度量疲劳/瞌睡的物理量识别驾驶人员的疲劳状态，从而实现有效的疲劳驾驶预警。整体流程如下图所示。
-
-![](images/diagram.png)
-
-## 2 环境依赖
-
-推荐系统为ubuntu 18.04，环境依赖软件和版本如下表：
-
-| 软件名称 | 版本  |
-| -------- | ----- |
-| cmake    | 3.5+  |
-| mxVision | 2.0.4 |
-| python   | 3.9.2 |
-
-确保环境中正确安装mxVision SDK。
-
-在编译运行项目前，需要设置环境变量：
-
-```
-export MX_SDK_HOME=${SDK安装路径}/mxVision
-export LD_LIBRARY_PATH="${MX_SDK_HOME}/lib:${MX_SDK_HOME}/opensource/lib:${LD_LIBRARY_PATH}"
-export PYTHONPATH="${MX_SDK_HOME}/python:${PYTHONPATH}"
-export GST_PLUGIN_SCANNER="${MX_SDK_HOME}/opensource/libexec/gstreamer-1.0/gst-plugin-scanner"
-export GST_PLUGIN_PATH="${MX_SDK_HOME}/opensource/lib/gstreamer-1.0:${MX_SDK_HOME}/lib/plugins"
-```
-
-- 环境变量介绍
-
-```
-MX_SDK_HOME: mxVision SDK 安装路径
-LD_LIBRARY_PATH: lib库路径
-PYTHONPATH: python环境路径
-```
-
-## 3 模型转换
-
-##### 3.1 模型与软件依赖
-
-所用模型为yolov4模型与PFLD模型：[下载链接](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/FatigueDrivingRecognition/model.zip)
-
-* yolov4模型为已经转换好的om模型，解压后的yolov4文件夹中包含yolov4模型及其相应的coco.names和cfg文件。将om模型和coco.names以及cfg文件放置到model文件夹中。
-* PFLD模型为[github项目](https://github.com/Hsintao/pfld_106_face_landmarks)中提供的模型
-
-转换PFLD模型所需软件依赖如下表所示。
-
-| 软件名称 | 版本  | 获取方式                                                     |
-| -------- | ----- | ------------------------------------------------------------ |
-| pytorch  | 1.2.0 | [pytorch官网](https://pytorch.org/get-started/previous-versions/) |
-| ONNX     | 1.7.0 | pip install onnx==1.7.0                                      |
-
-##### 3.2 pth文件转换为onnx文件
-
-1. 若尝试pth文件转换为onnx文件，可获取[原项目](https://github.com/Hsintao/pfld_106_face_landmarks)代码，下载至本地。安装环境依赖**requirements.txt**在原项目中已给出。
-2. 将原项目中的pytorch2onnx.py文件替换成本项目中的ModelTransformation/pytorch2onnx.py文件。运行：
-
-```
-python pytorch2onnx.py
-```
-
-转换完成后权重文件pfld_106.onnx上传至服务器任意目录下。
-
-##### 3.3 onnx文件转换为om文件
-
-将atc_env.sh中的HOME修改为onnx模型所在目录，运行atc_env.sh将onnx转为om模型，脚本中包含atc命令：
-
-```
-atc --framework=5 --model="${Home}"/pfld_106.onnx --output="${Home}"/pfld_106 --input_format=NCHW --insert_op_conf=./aipp_pfld_112_112.aippconfig  --input_shape="input_1:1,3,112,112" --log=debug --soc_version=Ascend310
-```
-
-运行命令如下：
-
-```
-bash atc-env.sh
-```
-
-提示 **ATC run success** 说明转换成功
-
-## 4 编译与运行
-**步骤1** 按照第 2 小节 **环境依赖** 中的步骤设置环境变量。
-
-**步骤2** 按照第 3 小节 **模型转换** 中的步骤获得 om 模型文件，放置在本项目的 `model` 目录下。
-
-**步骤3** 编译。在项目目录下执行命令：
-
-```
-bash build.sh
-```
-
-**步骤4** 单个视频疲劳驾驶识别。
-
-1. 按照第5小节 **软件依赖说明** 中的步骤安装live555并运行，将准备测试的264文件放到 `${Home_live555}/live/mediaServer/` 目录下，其中`Home_live555`为live555安装路径。
-2. 根据[live555使用教程](https://gitee.com/ascend/mindxsdk-referenceapps/blob/master/docs/%E5%8F%82%E8%80%83%E8%B5%84%E6%96%99/Live555%E7%A6%BB%E7%BA%BF%E8%A7%86%E9%A2%91%E8%BD%ACRTSP%E8%AF%B4%E6%98%8E%E6%96%87%E6%A1%A3.md)确定264文件的rtsp_Url，将`pipeline/test_video.pipeline` 中`mxpi_rtspsrc0`中的`rtspUrl`属性中的264file_path修改为rtsp_Url。
-3. 将`pipeline/test_video.pipeline` 中`mxpi_objectpostprocessor0`中的`postProcessLibPath`属性里的MX_SDK_HOME替换为mxVision SDK 安装路径。
-4. 如果为离线视频，将下面命令中frame_num替换为测试的视频的帧数，并执行命令：
-
-```
-python3 test_video.py --frame_num ${frame_num}
-```
-
-如果为在线视频，执行命令：
-
-```
-python3 test_video.py --online_flag True
-```
-
-执行成功后终端会输出视频中是否存在疲劳驾驶，输出`Normal`为正常驾驶，输出`Fatigue!!!`为疲劳驾驶。可视化结果保存在`fatigue`文件夹中。
-
-**步骤5** 性能测试。
-
-1. 按照第5小节 **软件依赖说明** 中的步骤安装live555并运行，将准备测试的2个264文件放到 `${Home_live555}/live/mediaServer/` 目录下，其中`Home_live555`为live555安装路径。
-2. 根据[live555使用教程](https://gitee.com/ascend/mindxsdk-referenceapps/blob/master/docs/%E5%8F%82%E8%80%83%E8%B5%84%E6%96%99/Live555%E7%A6%BB%E7%BA%BF%E8%A7%86%E9%A2%91%E8%BD%ACRTSP%E8%AF%B4%E6%98%8E%E6%96%87%E6%A1%A3.md)确定264文件的rtsp_Url，将`pipeline/parallel_pipeline.pipeline` 中`mxpi_rtspsrc0`和`mxpi_rtspsrc1`中的`rtspUrl`属性中的264file_path1和264file_path2分别修改为两个264文件的rtsp_Url。
-3. 将`pipeline/parallel_pipeline.pipeline` 中`mxpi_objectpostprocessor0`中的`postProcessLibPath`属性里的MX_SDK_HOME替换为mxVision SDK 安装路径。
-4. parallel_update.py测试的是一定时间内每秒处理视频的平均帧数，根据需要修改parallel_update.py中的时间参数。
-5. 如果为离线视频，将下面命令中的time替换为自己限制的测试时间，将frame_num1，frame_num2分别替换为两个测试的视频的帧数，并执行命令：
-
-```
-python3 parallel_update.py  --limit_of_time ${time} --frame_num_1 ${frame_num1} --frame_num_2  ${frame_num2} 
-```
-
-如果为在线视频，将下面命令中的time替换为自己限制的测试时间，并执行命令：
-
-```
-python3 parallel_update.py  --limit_of_time ${time} --online_flag True
-```
-
-执行成功后终端会输出视频中是否存在疲劳驾驶，输出`Normal`为正常驾驶
-
-命令执行成功后在当前目录下生成检测结果文件 performance.txt，查看结果文件查看处理速度信息。
-
-**步骤6** 精度测试。
-
-1. 下载测试数据集，[下载链接](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/FatigueDrivingRecognition/data.zip)，解压后包含一个txt文件，一个test文件夹和一个video文件夹。将解压出的label.txt文件上传到项目的当前目录。
-2. 按照第5小节 **软件依赖说明** 中的步骤安装live555并运行，并新建一个文件夹`${Home_live555}/live/mediaServer/dataset/` ，将上一步解压出的video文件夹中的264文件上传到 dataset文件夹下。其中`Home_live555`为live555安装路径。
-3. 将`pipeline/test.pipeline` 中`mxpi_objectpostprocessor0`中的`postProcessLibPath`属性里的MX_SDK_HOME替换为mxVision SDK 安装路径。
-4. 修改`run.sh`中的RTSP_URL修改为`rtsp://${host}:${port}/dataset`，其中`host`为服务器ip地址，`port`根据运行live555后终端显示的最后一行的提示进行确定。
-5. 执行命令：
-
-```
-bash run.sh
-```
-
-命令执行成功后在当前目录下生成测试结果result.txt，终端显示precision和recall。
-
-## 5 软件依赖说明
-
-推理中涉及到第三方软件依赖如下表所示。
-
-| 依赖软件 | 版本                      | 说明                                   |
-| -------- | ------------------------- | -------------------------------------- |
-| live555  | 1.09                      | 实现视频转rstp进行推流                 |
-| ffmpeg   | 2021-08-08-git-ac0408522a | 实现mp4格式/avi格式视频转为264格式视频 |
-
-注：1.[live555使用教程](https://gitee.com/ascend/mindxsdk-referenceapps/blob/master/docs/%E5%8F%82%E8%80%83%E8%B5%84%E6%96%99/Live555%E7%A6%BB%E7%BA%BF%E8%A7%86%E9%A2%91%E8%BD%ACRTSP%E8%AF%B4%E6%98%8E%E6%96%87%E6%A1%A3.md)
-
- 2.[ffmpeg使用教程](https://gitee.com/ascend/mindxsdk-referenceapps/blob/master/docs/%E5%8F%82%E8%80%83%E8%B5%84%E6%96%99/pc%E7%AB%AFffmpeg%E5%AE%89%E8%A3%85%E6%95%99%E7%A8%8B.md)
-
-## 6 常见问题
-
-### 6.1 第一帧解码失败问题
-
-**问题描述：**
-
-运行测试代码后，会出现如下图所示的警告信息：
-
-![Q1](images/Q1.png)
-
-**解决方案：**
-
-live555推流工具导致，不影响测试。
-
-### 6.2 数据集问题
-
-**问题描述：**
-
-运行测试代码测试部分视频文件时，会出现如下图所示的警告信息：
-
-![Q2](images/Q2.png)
-
-**解决方案：**
-
-部分视频文件中有不止一个人，目标检测模型能检测出不止一个目标，而除了驾驶人员之外的目标较小，受mxpi_imagecrop插件对裁剪尺寸的限制，无法将小目标裁剪出来，因此在测试时要注意测试视频中只包含驾驶人员一个人。
-
-### 6.3 性能测试问题
-
-**问题描述：**
-
-性能测试时，修改测试时间运行python代码后，无输出结果。
-
-**解决方案：**
-
-测试代码测试的是一定时间内每秒平均可以处理的视频帧数，因此视频的长度要大于设置的时间。
-
-### 6.4 每一帧解码失败问题
-
-**问题描述：**
-
-运行测试代码测试自己的视频时，出现每一帧都解码失败的警告。
-
-![Q4](images/Q4.png)
-
-**解决方案：**
-
-测试的视频需要是yuv420编码的264文件，需要对测试的文件进行修改。
-
-### 6.5 测试场景限制
-
-**问题描述：**
-
-部分场景测试时预测结果与预期不符。
-
-**解决方案：**
-
-由于模型训练与采用的疲劳度计算方法问题，本项目测试时具有一定限制条件：
-
-（1）不适合嘴巴微张但未打哈欠且眼部被遮挡的场景
-
-（2）不适合驾驶人员疲劳驾驶，双眼紧闭但未打哈欠的场景
-
-
-
+# 疲劳驾驶识别（Fatigue driving recognition）
+
+## 1 介绍
+本开发样例演示驾驶人员疲劳状态识别系统（Fatigue driving recognition），供用户参考。本系统基于mxVision SDK进行开发，以昇腾Atlas300卡为主要的硬件平台，实现在驾驶环境下驾驶人员疲劳状态识别与预警。
+
+项目的整体流程如下：
+
+1. 利用目标检测模型采集视频中的目标图像
+2. 利用PFLD模型进行目标关键点检测，获取眼部位置信息
+3. 通过计算度量疲劳/瞌睡的物理量识别驾驶人员的疲劳状态
+
+### 1.1 支持的产品
+
+本项目以昇腾Atlas310卡为主要的硬件平台。
+
+### 1.2 支持的版本
+
+SDK版本为2.0.4，查询方法
+```
+cat ${SDK安装路径}/mxVision/version.info
+```
+CANN版本为22.0.2，查询方法：在Atlas产品环境下，运行命令：
+
+```
+npu-smi info
+```
+
+### 1.3 软件方案介绍
+
+请先总体介绍项目的方案架构。如果项目设计方案中涉及子系统，请详细描述各子系统功能。如果设计了不同的功能模块，则请详细描述各模块功能。
+
+表1.1 系统方案中各模块功能描述：
+
+| 序号 |      子系统      | 功能描述                                                     |
+| :--: | :--------------: | :----------------------------------------------------------- |
+|  1   |     视频输入     | 调用MindX SDK的mxpi_rtspsrc插件对视频数据进行拉流            |
+|  2   |     视频解码     | 调用MindX SDK的mxpi_videodecoder进行视频解码                 |
+|  3   |     图像放缩     | 调用MindX SDK的mxpi_imageresize进行图像缩放                  |
+|  4   |     目标检测     | 利用yolov4的检测模型检测出图片中的目标                       |
+|  5   |  目标检测后处理  | 调用yolov4模型后处理插件对检测结果进行后处理                 |
+|  6   |     裁剪图片     | 调用MindX SDK的mxpi_imagecrop进行图像裁剪                    |
+|  7   |  目标关键点检测  | 利用PFLD检测模型检测出图片中目标的106个关键点                |
+|  8   | 目标关键点后处理 | 根据PFLD模型的检测结果进行后处理，获取嘴部相关关键点以及嘴部纵横比信息 |
+|  9   |     结果输出     | 输出驾驶人员的疲劳状态并进行可视化输出                       |
+
+### 1.4 代码目录结构与说明
+
+本sample工程名称为 **FatigueDrivingRecognition**，工程目录如下所示：
+
+```she&#39;l&#39;l
+├── images #readme图片
+│   ├── diagram.png
+│   ├── Q1.png
+│   ├── Q2.png
+│   └── Q4.png
+├── model #模型目录
+│   ├── coco.names
+│   ├── pfld_106.om
+│   ├── yolov4.cfg
+│   └── yolov4_detection.om
+├── ModelTransformation #转换模型
+│   ├── aipp_pfld_112_112.aippconfig
+│   ├── atc_env.sh
+│   ├── pfld_106.onnx
+│   └── pytorch2onnx.py
+├── pipeline
+│   ├── parallel_pipeline.pipeline
+│   ├── test.pipeline
+│   └── test_video.pipeline
+├── Plugin1 #插件1工程目录
+│   ├── build.sh
+│   ├── CMakeLists.txt
+│   ├── MxpiPFLDPostProcessPlugin.cpp
+│   └── MxpiPFLDPostProcessPlugin.h
+├── build.sh
+├── evaluate.py
+├── parallel_update.py
+├── README.md
+├── run.sh
+├── test.py
+└── test_video.py
+```
+
+
+
+### 1.5 技术实现流程图
+
+本项目实现在驾驶环境下驾驶人员疲劳状态识别与预警，首先利用目标检测模型采集视频中的目标图像，然后利用PFLD模型进行目标关键点检测，获取嘴部位置信息，并通过计算度量疲劳/瞌睡的物理量识别驾驶人员的疲劳状态，从而实现有效的疲劳驾驶预警。整体流程如下图所示。
+
+![](images/diagram.png)
+
+## 2 环境依赖
+
+推荐系统为ubuntu 18.04，环境依赖软件和版本如下表：
+
+| 软件名称 | 版本  |
+| -------- | ----- |
+| cmake    | 3.5+  |
+| mxVision | 2.0.4 |
+| python   | 3.9.2 |
+
+确保环境中正确安装mxVision SDK。
+
+在编译运行项目前，需要设置环境变量：
+
+```
+export MX_SDK_HOME=${SDK安装路径}/mxVision
+export LD_LIBRARY_PATH="${MX_SDK_HOME}/lib:${MX_SDK_HOME}/opensource/lib:${LD_LIBRARY_PATH}"
+export PYTHONPATH="${MX_SDK_HOME}/python:${PYTHONPATH}"
+export GST_PLUGIN_SCANNER="${MX_SDK_HOME}/opensource/libexec/gstreamer-1.0/gst-plugin-scanner"
+export GST_PLUGIN_PATH="${MX_SDK_HOME}/opensource/lib/gstreamer-1.0:${MX_SDK_HOME}/lib/plugins"
+```
+
+- 环境变量介绍
+
+```
+MX_SDK_HOME: mxVision SDK 安装路径
+LD_LIBRARY_PATH: lib库路径
+PYTHONPATH: python环境路径
+```
+
+## 3 模型转换
+
+##### 3.1 模型与软件依赖
+
+所用模型为yolov4模型与PFLD模型：[下载链接](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/FatigueDrivingRecognition/model.zip)
+
+* yolov4模型为已经转换好的om模型，解压后的yolov4文件夹中包含yolov4模型及其相应的coco.names和cfg文件。将om模型和coco.names以及cfg文件放置到model文件夹中。
+* PFLD模型为[github项目](https://github.com/Hsintao/pfld_106_face_landmarks)中提供的模型
+
+转换PFLD模型所需软件依赖如下表所示。
+
+| 软件名称 | 版本  | 获取方式                                                     |
+| -------- | ----- | ------------------------------------------------------------ |
+| pytorch  | 1.2.0 | [pytorch官网](https://pytorch.org/get-started/previous-versions/) |
+| ONNX     | 1.7.0 | pip install onnx==1.7.0                                      |
+
+##### 3.2 pth文件转换为onnx文件
+
+1. 若尝试pth文件转换为onnx文件，可获取[原项目](https://github.com/Hsintao/pfld_106_face_landmarks)代码，下载至本地。安装环境依赖**requirements.txt**在原项目中已给出。
+2. 将原项目中的pytorch2onnx.py文件替换成本项目中的ModelTransformation/pytorch2onnx.py文件。运行：
+
+```
+python pytorch2onnx.py
+```
+
+转换完成后权重文件pfld_106.onnx上传至服务器任意目录下。
+
+##### 3.3 onnx文件转换为om文件
+
+将atc_env.sh中的HOME修改为onnx模型所在目录，运行atc_env.sh将onnx转为om模型，脚本中包含atc命令：
+
+```
+atc --framework=5 --model="${Home}"/pfld_106.onnx --output="${Home}"/pfld_106 --input_format=NCHW --insert_op_conf=./aipp_pfld_112_112.aippconfig  --input_shape="input_1:1,3,112,112" --log=debug --soc_version=Ascend310
+```
+
+运行命令如下：
+
+```
+bash atc-env.sh
+```
+
+提示 **ATC run success** 说明转换成功
+
+## 4 编译与运行
+**步骤1** 按照第 2 小节 **环境依赖** 中的步骤设置环境变量。
+
+**步骤2** 按照第 3 小节 **模型转换** 中的步骤获得 om 模型文件，放置在本项目的 `model` 目录下。
+
+**步骤3** 编译。在项目目录下执行命令：
+
+```
+bash build.sh
+```
+
+**步骤4** 单个视频疲劳驾驶识别。
+
+1. 按照第5小节 **软件依赖说明** 中的步骤安装live555并运行，将准备测试的264文件放到 `${Home_live555}/live/mediaServer/` 目录下，其中`Home_live555`为live555安装路径。
+2. 根据[live555使用教程](https://gitee.com/ascend/mindxsdk-referenceapps/blob/master/docs/%E5%8F%82%E8%80%83%E8%B5%84%E6%96%99/Live555%E7%A6%BB%E7%BA%BF%E8%A7%86%E9%A2%91%E8%BD%ACRTSP%E8%AF%B4%E6%98%8E%E6%96%87%E6%A1%A3.md)确定264文件的rtsp_Url，将`pipeline/test_video.pipeline` 中`mxpi_rtspsrc0`中的`rtspUrl`属性中的264file_path修改为rtsp_Url。
+3. 将`pipeline/test_video.pipeline` 中`mxpi_objectpostprocessor0`中的`postProcessLibPath`属性里的MX_SDK_HOME替换为mxVision SDK 安装路径。
+4. 如果为离线视频，将下面命令中frame_num替换为测试的视频的帧数，并执行命令：
+
+```
+python3 test_video.py --frame_num ${frame_num}
+```
+
+如果为在线视频，执行命令：
+
+```
+python3 test_video.py --online_flag True
+```
+
+执行成功后终端会输出视频中是否存在疲劳驾驶，输出`Normal`为正常驾驶，输出`Fatigue!!!`为疲劳驾驶。可视化结果保存在`fatigue`文件夹中。
+
+**步骤5** 性能测试。
+
+1. 按照第5小节 **软件依赖说明** 中的步骤安装live555并运行，将准备测试的2个264文件放到 `${Home_live555}/live/mediaServer/` 目录下，其中`Home_live555`为live555安装路径。
+2. 根据[live555使用教程](https://gitee.com/ascend/mindxsdk-referenceapps/blob/master/docs/%E5%8F%82%E8%80%83%E8%B5%84%E6%96%99/Live555%E7%A6%BB%E7%BA%BF%E8%A7%86%E9%A2%91%E8%BD%ACRTSP%E8%AF%B4%E6%98%8E%E6%96%87%E6%A1%A3.md)确定264文件的rtsp_Url，将`pipeline/parallel_pipeline.pipeline` 中`mxpi_rtspsrc0`和`mxpi_rtspsrc1`中的`rtspUrl`属性中的264file_path1和264file_path2分别修改为两个264文件的rtsp_Url。
+3. 将`pipeline/parallel_pipeline.pipeline` 中`mxpi_objectpostprocessor0`中的`postProcessLibPath`属性里的MX_SDK_HOME替换为mxVision SDK 安装路径。
+4. parallel_update.py测试的是一定时间内每秒处理视频的平均帧数，根据需要修改parallel_update.py中的时间参数。
+5. 如果为离线视频，将下面命令中的time替换为自己限制的测试时间，将frame_num1，frame_num2分别替换为两个测试的视频的帧数，并执行命令：
+
+```
+python3 parallel_update.py  --limit_of_time ${time} --frame_num_1 ${frame_num1} --frame_num_2  ${frame_num2} 
+```
+
+如果为在线视频，将下面命令中的time替换为自己限制的测试时间，并执行命令：
+
+```
+python3 parallel_update.py  --limit_of_time ${time} --online_flag True
+```
+
+执行成功后终端会输出视频中是否存在疲劳驾驶，输出`Normal`为正常驾驶
+
+命令执行成功后在当前目录下生成检测结果文件 performance.txt，查看结果文件查看处理速度信息。
+
+**步骤6** 精度测试。
+
+1. 下载测试数据集，[下载链接](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/FatigueDrivingRecognition/data.zip)，解压后包含一个txt文件，一个test文件夹和一个video文件夹。将解压出的label.txt文件上传到项目的当前目录。
+2. 按照第5小节 **软件依赖说明** 中的步骤安装live555并运行，并新建一个文件夹`${Home_live555}/live/mediaServer/dataset/` ，将上一步解压出的video文件夹中的264文件上传到 dataset文件夹下。其中`Home_live555`为live555安装路径。
+3. 将`pipeline/test.pipeline` 中`mxpi_objectpostprocessor0`中的`postProcessLibPath`属性里的MX_SDK_HOME替换为mxVision SDK 安装路径。
+4. 修改`run.sh`中的RTSP_URL修改为`rtsp://${host}:${port}/dataset`，其中`host`为服务器ip地址，`port`根据运行live555后终端显示的最后一行的提示进行确定。
+5. 执行命令：
+
+```
+bash run.sh
+```
+
+命令执行成功后在当前目录下生成测试结果result.txt，终端显示precision和recall。
+
+## 5 软件依赖说明
+
+推理中涉及到第三方软件依赖如下表所示。
+
+| 依赖软件 | 版本                      | 说明                                   |
+| -------- | ------------------------- | -------------------------------------- |
+| live555  | 1.09                      | 实现视频转rstp进行推流                 |
+| ffmpeg   | 2021-08-08-git-ac0408522a | 实现mp4格式/avi格式视频转为264格式视频 |
+
+注：1.[live555使用教程](https://gitee.com/ascend/mindxsdk-referenceapps/blob/master/docs/%E5%8F%82%E8%80%83%E8%B5%84%E6%96%99/Live555%E7%A6%BB%E7%BA%BF%E8%A7%86%E9%A2%91%E8%BD%ACRTSP%E8%AF%B4%E6%98%8E%E6%96%87%E6%A1%A3.md)
+
+ 2.[ffmpeg使用教程](https://gitee.com/ascend/mindxsdk-referenceapps/blob/master/docs/%E5%8F%82%E8%80%83%E8%B5%84%E6%96%99/pc%E7%AB%AFffmpeg%E5%AE%89%E8%A3%85%E6%95%99%E7%A8%8B.md)
+
+## 6 常见问题
+
+### 6.1 第一帧解码失败问题
+
+**问题描述：**
+
+运行测试代码后，会出现如下图所示的警告信息：
+
+![Q1](images/Q1.png)
+
+**解决方案：**
+
+live555推流工具导致，不影响测试。
+
+### 6.2 数据集问题
+
+**问题描述：**
+
+运行测试代码测试部分视频文件时，会出现如下图所示的警告信息：
+
+![Q2](images/Q2.png)
+
+**解决方案：**
+
+部分视频文件中有不止一个人，目标检测模型能检测出不止一个目标，而除了驾驶人员之外的目标较小，受mxpi_imagecrop插件对裁剪尺寸的限制，无法将小目标裁剪出来，因此在测试时要注意测试视频中只包含驾驶人员一个人。
+
+### 6.3 性能测试问题
+
+**问题描述：**
+
+性能测试时，修改测试时间运行python代码后，无输出结果。
+
+**解决方案：**
+
+测试代码测试的是一定时间内每秒平均可以处理的视频帧数，因此视频的长度要大于设置的时间。
+
+### 6.4 每一帧解码失败问题
+
+**问题描述：**
+
+运行测试代码测试自己的视频时，出现每一帧都解码失败的警告。
+
+![Q4](images/Q4.png)
+
+**解决方案：**
+
+测试的视频需要是yuv420编码的264文件，需要对测试的文件进行修改。
+
+### 6.5 测试场景限制
+
+**问题描述：**
+
+部分场景测试时预测结果与预期不符。
+
+**解决方案：**
+
+由于模型训练与采用的疲劳度计算方法问题，本项目测试时具有一定限制条件：
+
+（1）不适合嘴巴微张但未打哈欠且眼部被遮挡的场景
+
+（2）不适合驾驶人员疲劳驾驶，双眼紧闭但未打哈欠的场景
+
+
+
diff --git a/contrib/FatigueDrivingRecognition/build.sh b/mxVision/mxVision-referenceapps/FatigueDrivingRecognition/build.sh
similarity index 100%
rename from contrib/FatigueDrivingRecognition/build.sh
rename to mxVision/mxVision-referenceapps/FatigueDrivingRecognition/build.sh
diff --git a/contrib/FatigueDrivingRecognition/evaluate.py b/mxVision/mxVision-referenceapps/FatigueDrivingRecognition/evaluate.py
similarity index 100%
rename from contrib/FatigueDrivingRecognition/evaluate.py
rename to mxVision/mxVision-referenceapps/FatigueDrivingRecognition/evaluate.py
diff --git a/contrib/FatigueDrivingRecognition/images/Q1.png b/mxVision/mxVision-referenceapps/FatigueDrivingRecognition/images/Q1.png
similarity index 100%
rename from contrib/FatigueDrivingRecognition/images/Q1.png
rename to mxVision/mxVision-referenceapps/FatigueDrivingRecognition/images/Q1.png
diff --git a/contrib/FatigueDrivingRecognition/images/Q2.png b/mxVision/mxVision-referenceapps/FatigueDrivingRecognition/images/Q2.png
similarity index 100%
rename from contrib/FatigueDrivingRecognition/images/Q2.png
rename to mxVision/mxVision-referenceapps/FatigueDrivingRecognition/images/Q2.png
diff --git a/contrib/FatigueDrivingRecognition/images/Q4.png b/mxVision/mxVision-referenceapps/FatigueDrivingRecognition/images/Q4.png
similarity index 100%
rename from contrib/FatigueDrivingRecognition/images/Q4.png
rename to mxVision/mxVision-referenceapps/FatigueDrivingRecognition/images/Q4.png
diff --git a/contrib/FatigueDrivingRecognition/images/diagram.png b/mxVision/mxVision-referenceapps/FatigueDrivingRecognition/images/diagram.png
similarity index 100%
rename from contrib/FatigueDrivingRecognition/images/diagram.png
rename to mxVision/mxVision-referenceapps/FatigueDrivingRecognition/images/diagram.png
diff --git a/contrib/faceswap/model/coco.names b/mxVision/mxVision-referenceapps/FatigueDrivingRecognition/model/coco.names
similarity index 100%
rename from contrib/faceswap/model/coco.names
rename to mxVision/mxVision-referenceapps/FatigueDrivingRecognition/model/coco.names
diff --git a/contrib/faceswap/model/yolov4.cfg b/mxVision/mxVision-referenceapps/FatigueDrivingRecognition/model/yolov4.cfg
similarity index 100%
rename from contrib/faceswap/model/yolov4.cfg
rename to mxVision/mxVision-referenceapps/FatigueDrivingRecognition/model/yolov4.cfg
diff --git a/contrib/FatigueDrivingRecognition/parallel_update.py b/mxVision/mxVision-referenceapps/FatigueDrivingRecognition/parallel_update.py
similarity index 97%
rename from contrib/FatigueDrivingRecognition/parallel_update.py
rename to mxVision/mxVision-referenceapps/FatigueDrivingRecognition/parallel_update.py
index 4ad3272c589c0aa34468c087899616c7970ebc22..ffe038fb2978b412e012485b4bcf8a6963579bfa 100644
--- a/contrib/FatigueDrivingRecognition/parallel_update.py
+++ b/mxVision/mxVision-referenceapps/FatigueDrivingRecognition/parallel_update.py
@@ -1,335 +1,335 @@
-"""
-# Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-# http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-"""
-
-import json
-import sys
-import os
-import signal
-import argparse
-import time
-import threading
-import cv2
-import numpy as np
-import MxpiDataType_pb2 as MxpiDataType
-from StreamManagerApi import StreamManagerApi, MxDataInput, StringVector
-
-index = 0
-index_second = 0
-
-parser = argparse.ArgumentParser(description="hello")
-parser.add_argument('--limit_of_time', type = int, default = 10, help = 'time of test.')
-parser.add_argument('--frame_num_1', type = int, default = 40, help = 'length of video1.')
-parser.add_argument('--frame_num_2', type = int, default = 40, help = 'length of video2.')
-parser.add_argument('--frame_threshold', type = int, default = 30, help = 'threshold of frame num.')
-parser.add_argument('--perclos_threshold', type = int, default = 0.7, help = 'threshold of perclos.')
-parser.add_argument('--mar_threshold', type = int, default = 0.14, help = 'threshold of mar.')
-parser.add_argument('--online_flag', type = bool, default = False, help = 'if the video is online.')
-
-def fun_timer(time_limit):
-    """
-    # set timer
-    # input parameter:
-    #       time:Length of time to be measured
-    # return: 
-    #       void
-    """
-    print("frame_num", index + index_second)
-    speed = (index + index_second) / time_limit
-    print("speed:", speed)
-    f = open("performance.txt", "w")
-    str1 = "Time:" + str(time_limit) + "s\n"
-    str2 = "Speed:" + str(speed) + "fps\n"
-    f.write(str1)
-    f.write(str2)
-    f.close()
-
-
-def get_args(sys_args):
-    """
-    # obtain the parameters
-    # input parameter:
-    #         sys_args:input variables
-    # return: 
-    #         global_args: key-value dictionary of variables.
-    """
-    global_args = parser.parse_args(sys_args)
-    return global_args
-
-
-def quit_ctrlc(signum, frame):
-    """
-    # obtain the Keyboard Interrupt
-    """
-    print('Keyboard Interrupt.Program forced termination.')
-    sys.exit()    
-
-
-if __name__ == '__main__':
-    args = get_args(sys.argv[1:])
-    limit_time = args.limit_of_time
-    frame_num1 = args.frame_num_1
-    frame_num2 = args.frame_num_2
-    streamManagerApi = StreamManagerApi()
-    # init stream manager
-    ret = streamManagerApi.InitManager()
-    if ret != 0:
-        print("Failed to init Stream manager, ret=%s" % str(ret))
-        exit()
-
-    # create streams by pipeline config file
-    pipeline_path = b"pipeline/parallel_pipeline.pipeline"
-    ret = streamManagerApi.CreateMultipleStreamsFromFile(pipeline_path)
-    if ret != 0:
-        print("Failed to create Stream, ret=%s" % str(ret))
-        exit()
-    # The name of the plugin to get the results from  
-    streamName = b"detection"
-    
-    keyVec = StringVector()
-    keyVec.push_back(b"ReservedFrameInfo")
-    keyVec.push_back(b"mxpi_tensorinfer1")
-    keyVec.push_back(b"mxpi_videodecoder0")
-    keyVec.push_back(b"mxpi_distributor0_0")
-    keyVec.push_back(b"mxpi_pfldpostprocess0")
-    keyVec.push_back(b"mxpi_videodecoder1")
-    keyVec0 = StringVector()
-    keyVec0.push_back(b"ReservedFrameInfo")
-
-    # Init the list and counting variable
-    img_yuv_list = []
-    heightAligned_list = []
-    widthAligned_list = []
-    isFatigue = 0
-    img_yuv_list_1 = []
-    isFatigue_1 = 0
-    nobody_flag = 0
-    nobody_num = 0
-    nobody_threshold = 30
-    nobody_flag1 = 0
-    nobody_num1 = 0
-    YUV_BYTES_NU = 3
-    YUV_BYTES_DE = 2
-    img_yuv_list_2 = []
-    heightAligned_list_2 = []
-    widthAligned_list_2 = []
-    frame_num_list = [frame_num1, frame_num2]
-    MARS_1 = []
-    MARS_2 = []
-    err_code = 2017
-    signal.signal(signal.SIGINT, quit_ctrlc)
-    signal.signal(signal.SIGTERM, quit_ctrlc)
-    while True:
-        if index >= frame_num_list[0] and index_second >= frame_num_list[1] and args.online_flag == False:
-            break
-        # Set timer
-        if index == 0 and index_second == 0:
-            timer = threading.Timer(limit_time, fun_timer, (limit_time, ))
-            timer.start()
-        
-        
-        infer_result = streamManagerApi.GetProtobuf(streamName, 0, keyVec0)
-        FrameList = MxpiDataType.MxpiFrameInfo()
-        FrameList.ParseFromString(infer_result[0].messageBuf)
-        # Obtain the inference result
-        infer = streamManagerApi.GetResult(streamName, b'appsink0', keyVec)
-        if infer.errorCode == err_code:
-            if FrameList.channelId == 0:
-                index = index + 1
-                nobody_num = nobody_num + 1
-                if nobody_num >= nobody_threshold:
-                    nobody_flag = 1
-                    print('Nobody is detected in video1.')                    
-                continue
-            if FrameList.channelId == 1:
-                index_second = index_second + 1
-                nobody_num1 = nobody_num1 + 1
-                if nobody_num1 >= nobody_threshold:
-                    nobody_flag1 = 1
-                    print('Nobody is detected in video2.')
-                continue
-        if infer.errorCode != 0:
-            print("GetResult error. errorCode=%d, errorMsg=%s" % (infer.errorCode, infer.errorMsg))
-        # Obtain the PFLD inference results
-        infer_result_1 = infer.metadataVec[1]
-        tensorList = MxpiDataType.MxpiTensorPackageList()
-        tensorList.ParseFromString(infer_result_1.serializedMetadata)
-        ids = np.frombuffer(tensorList.tensorPackageVec[0].tensorVec[0].dataStr, dtype=np.float32)
-        if ids.shape[0] == 0:
-            continue
-        # Obtain the frame information
-        infer_result_0 = infer.metadataVec[0]
-        FrameList0 = MxpiDataType.MxpiFrameInfo()
-        FrameList0.ParseFromString(infer_result_0.serializedMetadata)
-        if index == frame_num_list[0] and FrameList0.channelId == 0:
-            continue
-        elif index_second == frame_num_list[1] and FrameList0.channelId == 1:
-            continue
-        # Channel 0
-        if FrameList0.channelId == 0:
-            nobody_num = 0
-            # Obtain the PFLD post-processing plugin results
-            infer_result_4 = infer.metadataVec[4]
-            objectList = MxpiDataType.MxpiObjectList()
-            objectList.ParseFromString(infer_result_4.serializedMetadata)
-            MAR = objectList.objectVec[0].x0
-            height_left = objectList.objectVec[0].y0
-            height_right = objectList.objectVec[0].y1
-            # Obtain the the original image
-            infer_result_2 = infer.metadataVec[2]
-            visionList = MxpiDataType.MxpiVisionList()
-            visionList.ParseFromString(infer_result_2.serializedMetadata)
-            visionData = visionList.visionVec[0].visionData.dataStr
-            visionInfo = visionList.visionVec[0].visionInfo
-            img_yuv = np.frombuffer(visionData, dtype=np.uint8)
-            heightAligned = visionInfo.heightAligned
-            widthAligned = visionInfo.widthAligned
-            # Add the result of the current frame to the list
-            MARS_1.append(MAR)
-            img_yuv_list.append(img_yuv)
-            heightAligned_list.append(heightAligned)
-            widthAligned_list.append(widthAligned)
-            # number of frame
-            if len(MARS_1) >= args.frame_threshold:
-                cut_list_num = -1 * args.frame_threshold
-                aim_MARS = MARS_1[cut_list_num:]
-                max_index = 0
-                max_mar = aim_MARS[0]
-                num = 0
-                for index_mar, mar in enumerate(aim_MARS):
-                    # Judge the threshold
-                    if mar >= args.mar_threshold:
-                        num += 1
-                    if mar > max_mar:
-                        max_mar = mar
-                        max_index = index_mar
-                
-                perclos = num / args.frame_threshold
-                
-                # Conform to the fatigue driving conditions
-                if perclos >= args.perclos_threshold:
-                    isFatigue = 1
-                    print('Fatigue in video1!!!')
-                    # visualization
-                    img_yuv_fatigue = img_yuv_list[max_index]
-                    h = heightAligned_list[max_index] * YUV_BYTES_NU // YUV_BYTES_DE
-                    w = widthAligned_list[max_index]
-                    img_yuv_fatigue = img_yuv_fatigue.reshape(h, w)
-                    img_fatigue = cv2.cvtColor(img_yuv_fatigue, cv2.COLOR_YUV2BGR_NV12)
-                    cv2.putText(img_fatigue, "Warning!!! Fatigue!!!", (5, 50), 
-                              cv2.FONT_HERSHEY_SIMPLEX, 1.3, (0, 0, 255), 2)
-                    index_print = index - 30 + max_index
-                    image_path = "fatigue/"
-                    if not os.path.exists(image_path):
-                        os.mkdir(image_path)
-                    image_path = "fatigue/0/"
-                    if not os.path.exists(image_path):
-                        os.mkdir(image_path)
-                    image_name = image_path + str(index_print) + ".jpg"
-                    cv2.imwrite(image_name, img_fatigue)
-                heightAligned_list.pop(0)
-                widthAligned_list.pop(0)
-                img_yuv_list.pop(0)
-
-
-            index = index + 1
-
-        # Channel 0
-        elif FrameList0.channelId == 1:
-            nobody_num1 = 0
-            # Obtain the PFLD post-processing plugin results
-            infer_result_3 = infer.metadataVec[3]
-            objectList = MxpiDataType.MxpiObjectList()
-            objectList.ParseFromString(infer_result_3.serializedMetadata)
-            MAR = objectList.objectVec[0].x0
-            height_left = objectList.objectVec[0].y0
-            height_right = objectList.objectVec[0].y1
-            # Obtain the the original image
-            infer_result_4 = infer.metadataVec[4]
-            visionList = MxpiDataType.MxpiVisionList()
-            visionList.ParseFromString(infer_result_4.serializedMetadata)
-            visionData = visionList.visionVec[0].visionData.dataStr
-            visionInfo = visionList.visionVec[0].visionInfo
-            
-
-            img_yuv = np.frombuffer(visionData, dtype=np.uint8)
-            heightAligned = visionInfo.heightAligned
-            widthAligned = visionInfo.widthAligned
-            # Add the result of the current frame to the list
-            MARS_2.append(MAR)
-            img_yuv_list_2.append(img_yuv)
-            heightAligned_list_2.append(heightAligned)
-            widthAligned_list_2.append(widthAligned)
-            # Judge the threshold
-            if len(MARS_2) >= args.frame_threshold:
-                cut_list_num = -1 * args.frame_threshold
-                aim_MARS = MARS_2[cut_list_num:]
-                max_index = 0
-                max_mar = aim_MARS[0]
-                num = 0
-                for index_mar, mar in enumerate(aim_MARS):
-                    if mar >= args.mar_threshold:
-                        num += 1
-                    if mar < max_mar:
-                        max_mar = mar
-                        max_index = index_mar
-                
-                perclos = num / args.frame_threshold
-                
-                # Conform to the fatigue driving conditions
-                if perclos >= args.perclos_threshold:
-                    isFatigue_1 = 1
-                    print('Fatigue in video2!!!')
-                    # visualization
-                    img_yuv_fatigue = img_yuv_list_2[max_index]
-                    h = heightAligned_list_2[max_index] * YUV_BYTES_NU // YUV_BYTES_DE
-                    w = widthAligned_list_2[max_index]
-                    img_yuv_fatigue = img_yuv_fatigue.reshape(h, w)
-                    img_fatigue = cv2.cvtColor(img_yuv_fatigue, cv2.COLOR_YUV2BGR_NV12)
-                    cv2.putText(img_fatigue, "Warning!!! Fatigue!!!", (5, 50), 
-                              cv2.FONT_HERSHEY_SIMPLEX, 1.3, (0, 0, 255), 2)
-                    index_print = index_second - 30 + max_index
-                    image_path = "fatigue/"
-                    if not os.path.exists(image_path):
-                        os.mkdir(image_path)
-                    image_path = "fatigue/1/"
-                    if not os.path.exists(image_path):
-                        os.mkdir(image_path)
-                    image_name = image_path + str(index_print) + ".jpg"
-                    cv2.imwrite(image_name, img_fatigue)
-                heightAligned_list_2.pop(0)
-                widthAligned_list_2.pop(0)
-                img_yuv_list_2.pop(0)
-
-
-            index_second = index_second + 1
-
-    # print the result
-    if nobody_flag == 1:
-        print('No one was detected for some time in video1.')
-    if nobody_flag1 == 1:
-        print('No one was detected for some time in video2.')
-    if isFatigue == 0:
-        print('Video1 is Normal')
-        
-    else:
-        print('Video1 is Fatigue!!!')
-    if isFatigue_1 == 0:
-        print('Video2 is Normal')
-        
-    else:
-        print('Video2 isFatigue!!!')
-    # destroy streams
-    streamManagerApi.DestroyAllStreams()
+"""
+# Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""
+
+import json
+import sys
+import os
+import signal
+import argparse
+import time
+import threading
+import cv2
+import numpy as np
+import MxpiDataType_pb2 as MxpiDataType
+from StreamManagerApi import StreamManagerApi, MxDataInput, StringVector
+
+index = 0
+index_second = 0
+
+parser = argparse.ArgumentParser(description="hello")
+parser.add_argument('--limit_of_time', type = int, default = 10, help = 'time of test.')
+parser.add_argument('--frame_num_1', type = int, default = 40, help = 'length of video1.')
+parser.add_argument('--frame_num_2', type = int, default = 40, help = 'length of video2.')
+parser.add_argument('--frame_threshold', type = int, default = 30, help = 'threshold of frame num.')
+parser.add_argument('--perclos_threshold', type = int, default = 0.7, help = 'threshold of perclos.')
+parser.add_argument('--mar_threshold', type = int, default = 0.14, help = 'threshold of mar.')
+parser.add_argument('--online_flag', type = bool, default = False, help = 'if the video is online.')
+
+def fun_timer(time_limit):
+    """
+    # set timer
+    # input parameter:
+    #       time:Length of time to be measured
+    # return: 
+    #       void
+    """
+    print("frame_num", index + index_second)
+    speed = (index + index_second) / time_limit
+    print("speed:", speed)
+    f = open("performance.txt", "w")
+    str1 = "Time:" + str(time_limit) + "s\n"
+    str2 = "Speed:" + str(speed) + "fps\n"
+    f.write(str1)
+    f.write(str2)
+    f.close()
+
+
+def get_args(sys_args):
+    """
+    # obtain the parameters
+    # input parameter:
+    #         sys_args:input variables
+    # return: 
+    #         global_args: key-value dictionary of variables.
+    """
+    global_args = parser.parse_args(sys_args)
+    return global_args
+
+
+def quit_ctrlc(signum, frame):
+    """
+    # obtain the Keyboard Interrupt
+    """
+    print('Keyboard Interrupt.Program forced termination.')
+    sys.exit()    
+
+
+if __name__ == '__main__':
+    args = get_args(sys.argv[1:])
+    limit_time = args.limit_of_time
+    frame_num1 = args.frame_num_1
+    frame_num2 = args.frame_num_2
+    streamManagerApi = StreamManagerApi()
+    # init stream manager
+    ret = streamManagerApi.InitManager()
+    if ret != 0:
+        print("Failed to init Stream manager, ret=%s" % str(ret))
+        exit()
+
+    # create streams by pipeline config file
+    pipeline_path = b"pipeline/parallel_pipeline.pipeline"
+    ret = streamManagerApi.CreateMultipleStreamsFromFile(pipeline_path)
+    if ret != 0:
+        print("Failed to create Stream, ret=%s" % str(ret))
+        exit()
+    # The name of the plugin to get the results from  
+    streamName = b"detection"
+    
+    keyVec = StringVector()
+    keyVec.push_back(b"ReservedFrameInfo")
+    keyVec.push_back(b"mxpi_tensorinfer1")
+    keyVec.push_back(b"mxpi_videodecoder0")
+    keyVec.push_back(b"mxpi_distributor0_0")
+    keyVec.push_back(b"mxpi_pfldpostprocess0")
+    keyVec.push_back(b"mxpi_videodecoder1")
+    keyVec0 = StringVector()
+    keyVec0.push_back(b"ReservedFrameInfo")
+
+    # Init the list and counting variable
+    img_yuv_list = []
+    heightAligned_list = []
+    widthAligned_list = []
+    isFatigue = 0
+    img_yuv_list_1 = []
+    isFatigue_1 = 0
+    nobody_flag = 0
+    nobody_num = 0
+    nobody_threshold = 30
+    nobody_flag1 = 0
+    nobody_num1 = 0
+    YUV_BYTES_NU = 3
+    YUV_BYTES_DE = 2
+    img_yuv_list_2 = []
+    heightAligned_list_2 = []
+    widthAligned_list_2 = []
+    frame_num_list = [frame_num1, frame_num2]
+    MARS_1 = []
+    MARS_2 = []
+    err_code = 2017
+    signal.signal(signal.SIGINT, quit_ctrlc)
+    signal.signal(signal.SIGTERM, quit_ctrlc)
+    while True:
+        if index >= frame_num_list[0] and index_second >= frame_num_list[1] and args.online_flag == False:
+            break
+        # Set timer
+        if index == 0 and index_second == 0:
+            timer = threading.Timer(limit_time, fun_timer, (limit_time, ))
+            timer.start()
+        
+        
+        infer_result = streamManagerApi.GetProtobuf(streamName, 0, keyVec0)
+        FrameList = MxpiDataType.MxpiFrameInfo()
+        FrameList.ParseFromString(infer_result[0].messageBuf)
+        # Obtain the inference result
+        infer = streamManagerApi.GetResult(streamName, b'appsink0', keyVec)
+        if infer.errorCode == err_code:
+            if FrameList.channelId == 0:
+                index = index + 1
+                nobody_num = nobody_num + 1
+                if nobody_num >= nobody_threshold:
+                    nobody_flag = 1
+                    print('Nobody is detected in video1.')                    
+                continue
+            if FrameList.channelId == 1:
+                index_second = index_second + 1
+                nobody_num1 = nobody_num1 + 1
+                if nobody_num1 >= nobody_threshold:
+                    nobody_flag1 = 1
+                    print('Nobody is detected in video2.')
+                continue
+        if infer.errorCode != 0:
+            print("GetResult error. errorCode=%d, errorMsg=%s" % (infer.errorCode, infer.errorMsg))
+        # Obtain the PFLD inference results
+        infer_result_1 = infer.metadataVec[1]
+        tensorList = MxpiDataType.MxpiTensorPackageList()
+        tensorList.ParseFromString(infer_result_1.serializedMetadata)
+        ids = np.frombuffer(tensorList.tensorPackageVec[0].tensorVec[0].dataStr, dtype=np.float32)
+        if ids.shape[0] == 0:
+            continue
+        # Obtain the frame information
+        infer_result_0 = infer.metadataVec[0]
+        FrameList0 = MxpiDataType.MxpiFrameInfo()
+        FrameList0.ParseFromString(infer_result_0.serializedMetadata)
+        if index == frame_num_list[0] and FrameList0.channelId == 0:
+            continue
+        elif index_second == frame_num_list[1] and FrameList0.channelId == 1:
+            continue
+        # Channel 0
+        if FrameList0.channelId == 0:
+            nobody_num = 0
+            # Obtain the PFLD post-processing plugin results
+            infer_result_4 = infer.metadataVec[4]
+            objectList = MxpiDataType.MxpiObjectList()
+            objectList.ParseFromString(infer_result_4.serializedMetadata)
+            MAR = objectList.objectVec[0].x0
+            height_left = objectList.objectVec[0].y0
+            height_right = objectList.objectVec[0].y1
+            # Obtain the the original image
+            infer_result_2 = infer.metadataVec[2]
+            visionList = MxpiDataType.MxpiVisionList()
+            visionList.ParseFromString(infer_result_2.serializedMetadata)
+            visionData = visionList.visionVec[0].visionData.dataStr
+            visionInfo = visionList.visionVec[0].visionInfo
+            img_yuv = np.frombuffer(visionData, dtype=np.uint8)
+            heightAligned = visionInfo.heightAligned
+            widthAligned = visionInfo.widthAligned
+            # Add the result of the current frame to the list
+            MARS_1.append(MAR)
+            img_yuv_list.append(img_yuv)
+            heightAligned_list.append(heightAligned)
+            widthAligned_list.append(widthAligned)
+            # number of frame
+            if len(MARS_1) >= args.frame_threshold:
+                cut_list_num = -1 * args.frame_threshold
+                aim_MARS = MARS_1[cut_list_num:]
+                max_index = 0
+                max_mar = aim_MARS[0]
+                num = 0
+                for index_mar, mar in enumerate(aim_MARS):
+                    # Judge the threshold
+                    if mar >= args.mar_threshold:
+                        num += 1
+                    if mar > max_mar:
+                        max_mar = mar
+                        max_index = index_mar
+                
+                perclos = num / args.frame_threshold
+                
+                # Conform to the fatigue driving conditions
+                if perclos >= args.perclos_threshold:
+                    isFatigue = 1
+                    print('Fatigue in video1!!!')
+                    # visualization
+                    img_yuv_fatigue = img_yuv_list[max_index]
+                    h = heightAligned_list[max_index] * YUV_BYTES_NU // YUV_BYTES_DE
+                    w = widthAligned_list[max_index]
+                    img_yuv_fatigue = img_yuv_fatigue.reshape(h, w)
+                    img_fatigue = cv2.cvtColor(img_yuv_fatigue, cv2.COLOR_YUV2BGR_NV12)
+                    cv2.putText(img_fatigue, "Warning!!! Fatigue!!!", (5, 50), 
+                              cv2.FONT_HERSHEY_SIMPLEX, 1.3, (0, 0, 255), 2)
+                    index_print = index - 30 + max_index
+                    image_path = "fatigue/"
+                    if not os.path.exists(image_path):
+                        os.mkdir(image_path)
+                    image_path = "fatigue/0/"
+                    if not os.path.exists(image_path):
+                        os.mkdir(image_path)
+                    image_name = image_path + str(index_print) + ".jpg"
+                    cv2.imwrite(image_name, img_fatigue)
+                heightAligned_list.pop(0)
+                widthAligned_list.pop(0)
+                img_yuv_list.pop(0)
+
+
+            index = index + 1
+
+        # Channel 0
+        elif FrameList0.channelId == 1:
+            nobody_num1 = 0
+            # Obtain the PFLD post-processing plugin results
+            infer_result_3 = infer.metadataVec[3]
+            objectList = MxpiDataType.MxpiObjectList()
+            objectList.ParseFromString(infer_result_3.serializedMetadata)
+            MAR = objectList.objectVec[0].x0
+            height_left = objectList.objectVec[0].y0
+            height_right = objectList.objectVec[0].y1
+            # Obtain the the original image
+            infer_result_4 = infer.metadataVec[4]
+            visionList = MxpiDataType.MxpiVisionList()
+            visionList.ParseFromString(infer_result_4.serializedMetadata)
+            visionData = visionList.visionVec[0].visionData.dataStr
+            visionInfo = visionList.visionVec[0].visionInfo
+            
+
+            img_yuv = np.frombuffer(visionData, dtype=np.uint8)
+            heightAligned = visionInfo.heightAligned
+            widthAligned = visionInfo.widthAligned
+            # Add the result of the current frame to the list
+            MARS_2.append(MAR)
+            img_yuv_list_2.append(img_yuv)
+            heightAligned_list_2.append(heightAligned)
+            widthAligned_list_2.append(widthAligned)
+            # Judge the threshold
+            if len(MARS_2) >= args.frame_threshold:
+                cut_list_num = -1 * args.frame_threshold
+                aim_MARS = MARS_2[cut_list_num:]
+                max_index = 0
+                max_mar = aim_MARS[0]
+                num = 0
+                for index_mar, mar in enumerate(aim_MARS):
+                    if mar >= args.mar_threshold:
+                        num += 1
+                    if mar < max_mar:
+                        max_mar = mar
+                        max_index = index_mar
+                
+                perclos = num / args.frame_threshold
+                
+                # Conform to the fatigue driving conditions
+                if perclos >= args.perclos_threshold:
+                    isFatigue_1 = 1
+                    print('Fatigue in video2!!!')
+                    # visualization
+                    img_yuv_fatigue = img_yuv_list_2[max_index]
+                    h = heightAligned_list_2[max_index] * YUV_BYTES_NU // YUV_BYTES_DE
+                    w = widthAligned_list_2[max_index]
+                    img_yuv_fatigue = img_yuv_fatigue.reshape(h, w)
+                    img_fatigue = cv2.cvtColor(img_yuv_fatigue, cv2.COLOR_YUV2BGR_NV12)
+                    cv2.putText(img_fatigue, "Warning!!! Fatigue!!!", (5, 50), 
+                              cv2.FONT_HERSHEY_SIMPLEX, 1.3, (0, 0, 255), 2)
+                    index_print = index_second - 30 + max_index
+                    image_path = "fatigue/"
+                    if not os.path.exists(image_path):
+                        os.mkdir(image_path)
+                    image_path = "fatigue/1/"
+                    if not os.path.exists(image_path):
+                        os.mkdir(image_path)
+                    image_name = image_path + str(index_print) + ".jpg"
+                    cv2.imwrite(image_name, img_fatigue)
+                heightAligned_list_2.pop(0)
+                widthAligned_list_2.pop(0)
+                img_yuv_list_2.pop(0)
+
+
+            index_second = index_second + 1
+
+    # print the result
+    if nobody_flag == 1:
+        print('No one was detected for some time in video1.')
+    if nobody_flag1 == 1:
+        print('No one was detected for some time in video2.')
+    if isFatigue == 0:
+        print('Video1 is Normal')
+        
+    else:
+        print('Video1 is Fatigue!!!')
+    if isFatigue_1 == 0:
+        print('Video2 is Normal')
+        
+    else:
+        print('Video2 isFatigue!!!')
+    # destroy streams
+    streamManagerApi.DestroyAllStreams()
diff --git a/contrib/FatigueDrivingRecognition/pipeline/parallel_pipeline.pipeline b/mxVision/mxVision-referenceapps/FatigueDrivingRecognition/pipeline/parallel_pipeline.pipeline
similarity index 97%
rename from contrib/FatigueDrivingRecognition/pipeline/parallel_pipeline.pipeline
rename to mxVision/mxVision-referenceapps/FatigueDrivingRecognition/pipeline/parallel_pipeline.pipeline
index 67f7cba2d2b80996852855b44b07179ca99054a8..ae2b297a4df4709264779358f3734c4660e29c96 100644
--- a/contrib/FatigueDrivingRecognition/pipeline/parallel_pipeline.pipeline
+++ b/mxVision/mxVision-referenceapps/FatigueDrivingRecognition/pipeline/parallel_pipeline.pipeline
@@ -1,118 +1,118 @@
-{
-    "detection": {
-        "stream_config": {
-            "deviceId": "0"
-        },
-        "mxpi_rtspsrc0": {
-            "factory": "mxpi_rtspsrc",
-            "props": {
-                "rtspUrl": "${264file_path1}",
-                "channelId": "0"
-            },
-            "next": "mxpi_videodecoder0"
-        },
-        "mxpi_rtspsrc1": {
-            "factory": "mxpi_rtspsrc",
-            "props": {
-                "rtspUrl": "${264file_path2}",
-                "channelId": "1"
-            },
-            "next": "mxpi_videodecoder1"
-        },
-        "mxpi_videodecoder0": {
-            "factory": "mxpi_videodecoder",
-            "props": {
-                "inputVideoFormat": "H264",
-                "outputImageFormat": "YUV420SP_NV12",
-                "vdecChannelId": "0"
-            },
-            "next": "mxpi_parallel2serial0:0"
-        },
-        "mxpi_videodecoder1": {
-            "factory": "mxpi_videodecoder",
-            "props": {
-                "inputVideoFormat": "H264",
-                "outputImageFormat": "YUV420SP_NV12",
-                "vdecChannelId": "1"
-            },
-            "next": "mxpi_parallel2serial0:1"
-        },
-        "mxpi_parallel2serial0":{
-            "factory": "mxpi_parallel2serial",
-            "props": {
-                "dataSource": "mxpi_videodecoder0,mxpi_videodecoder1"
-            },
-            "next": "mxpi_imageresize0"
-        },
-        "mxpi_imageresize0": {
-            "props": {
-                "dataSource": "mxpi_parallel2serial0",
-                "resizeHeight": "416",
-                "resizeWidth": "416",
-                "resizeType": "Resizer_KeepAspectRatio_Fit"
-            },
-            "factory": "mxpi_imageresize",
-            "next": "mxpi_tensorinfer0"
-        },
-        "mxpi_tensorinfer0": {
-            "props": {
-                "dataSource":"mxpi_imageresize0",
-                "modelPath": "model/yolov4_detection.om"
-            },
-            "factory": "mxpi_tensorinfer",
-            "next": "mxpi_objectpostprocessor0"
-        },
-        "mxpi_objectpostprocessor0": {
-            "props": {
-                "dataSource": "mxpi_tensorinfer0",
-                "postProcessConfigPath": "model/yolov4.cfg",
-                "labelPath": "model/coco.names",
-                "postProcessLibPath": "${MX_SDK_HOME}/lib/modelpostprocessors/libyolov3postprocess.so"
-            },
-            "factory": "mxpi_objectpostprocessor",
-            "next": "mxpi_distributor0"
-        },
-        "mxpi_distributor0": {
-            "props": {
-                "dataSource": "mxpi_objectpostprocessor0",
-                "classIds": "3"
-            },
-            "factory": "mxpi_distributor",
-            "next": "mxpi_imagecrop0"
-        },
-        "mxpi_imagecrop0": {
-            "props": {
-                "dataSource": "mxpi_distributor0_0",
-                "dataSourceImage": "mxpi_imagedecoder0",
-                "resizeWidth": "112",
-                "resizeHeight": "112",
-                "leftExpandRatio": "0.2",
-                "rightExpandRatio": "0.2",
-                "resizeType": "Resizer_Stretch"
-            },
-            "factory": "mxpi_imagecrop",
-            "next": "mxpi_tensorinfer1"
-        },
-        "mxpi_tensorinfer1": {
-            "props": {
-                "dataSource":"mxpi_imagecrop0",
-                "modelPath": "model/pfld_106.om"
-            },
-            "factory": "mxpi_tensorinfer",
-            "next": "mxpi_pfldpostprocess0"
-        },
-        "mxpi_pfldpostprocess0": {
-            "props": {
-                "dataSource":"mxpi_tensorinfer1"
-            },
-            "factory": "mxpi_pfldpostprocess",
-            "next": "appsink0"
-        },
-        "appsink0": {
-            "props": {
-                "blocksize": "4096000"
-            },
-            "factory": "appsink"
-        }
-    }
+{
+    "detection": {
+        "stream_config": {
+            "deviceId": "0"
+        },
+        "mxpi_rtspsrc0": {
+            "factory": "mxpi_rtspsrc",
+            "props": {
+                "rtspUrl": "${264file_path1}",
+                "channelId": "0"
+            },
+            "next": "mxpi_videodecoder0"
+        },
+        "mxpi_rtspsrc1": {
+            "factory": "mxpi_rtspsrc",
+            "props": {
+                "rtspUrl": "${264file_path2}",
+                "channelId": "1"
+            },
+            "next": "mxpi_videodecoder1"
+        },
+        "mxpi_videodecoder0": {
+            "factory": "mxpi_videodecoder",
+            "props": {
+                "inputVideoFormat": "H264",
+                "outputImageFormat": "YUV420SP_NV12",
+                "vdecChannelId": "0"
+            },
+            "next": "mxpi_parallel2serial0:0"
+        },
+        "mxpi_videodecoder1": {
+            "factory": "mxpi_videodecoder",
+            "props": {
+                "inputVideoFormat": "H264",
+                "outputImageFormat": "YUV420SP_NV12",
+                "vdecChannelId": "1"
+            },
+            "next": "mxpi_parallel2serial0:1"
+        },
+        "mxpi_parallel2serial0":{
+            "factory": "mxpi_parallel2serial",
+            "props": {
+                "dataSource": "mxpi_videodecoder0,mxpi_videodecoder1"
+            },
+            "next": "mxpi_imageresize0"
+        },
+        "mxpi_imageresize0": {
+            "props": {
+                "dataSource": "mxpi_parallel2serial0",
+                "resizeHeight": "416",
+                "resizeWidth": "416",
+                "resizeType": "Resizer_KeepAspectRatio_Fit"
+            },
+            "factory": "mxpi_imageresize",
+            "next": "mxpi_tensorinfer0"
+        },
+        "mxpi_tensorinfer0": {
+            "props": {
+                "dataSource":"mxpi_imageresize0",
+                "modelPath": "model/yolov4_detection.om"
+            },
+            "factory": "mxpi_tensorinfer",
+            "next": "mxpi_objectpostprocessor0"
+        },
+        "mxpi_objectpostprocessor0": {
+            "props": {
+                "dataSource": "mxpi_tensorinfer0",
+                "postProcessConfigPath": "model/yolov4.cfg",
+                "labelPath": "model/coco.names",
+                "postProcessLibPath": "${MX_SDK_HOME}/lib/modelpostprocessors/libyolov3postprocess.so"
+            },
+            "factory": "mxpi_objectpostprocessor",
+            "next": "mxpi_distributor0"
+        },
+        "mxpi_distributor0": {
+            "props": {
+                "dataSource": "mxpi_objectpostprocessor0",
+                "classIds": "3"
+            },
+            "factory": "mxpi_distributor",
+            "next": "mxpi_imagecrop0"
+        },
+        "mxpi_imagecrop0": {
+            "props": {
+                "dataSource": "mxpi_distributor0_0",
+                "dataSourceImage": "mxpi_imagedecoder0",
+                "resizeWidth": "112",
+                "resizeHeight": "112",
+                "leftExpandRatio": "0.2",
+                "rightExpandRatio": "0.2",
+                "resizeType": "Resizer_Stretch"
+            },
+            "factory": "mxpi_imagecrop",
+            "next": "mxpi_tensorinfer1"
+        },
+        "mxpi_tensorinfer1": {
+            "props": {
+                "dataSource":"mxpi_imagecrop0",
+                "modelPath": "model/pfld_106.om"
+            },
+            "factory": "mxpi_tensorinfer",
+            "next": "mxpi_pfldpostprocess0"
+        },
+        "mxpi_pfldpostprocess0": {
+            "props": {
+                "dataSource":"mxpi_tensorinfer1"
+            },
+            "factory": "mxpi_pfldpostprocess",
+            "next": "appsink0"
+        },
+        "appsink0": {
+            "props": {
+                "blocksize": "4096000"
+            },
+            "factory": "appsink"
+        }
+    }
 }
\ No newline at end of file
diff --git a/contrib/FatigueDrivingRecognition/pipeline/test.pipeline b/mxVision/mxVision-referenceapps/FatigueDrivingRecognition/pipeline/test.pipeline
similarity index 97%
rename from contrib/FatigueDrivingRecognition/pipeline/test.pipeline
rename to mxVision/mxVision-referenceapps/FatigueDrivingRecognition/pipeline/test.pipeline
index 1d1db3fc5d31b2e57106c7897c0bf316d50e6722..1ba0add4fd858cd0ae3c449ab3bc7765b195feba 100644
--- a/contrib/FatigueDrivingRecognition/pipeline/test.pipeline
+++ b/mxVision/mxVision-referenceapps/FatigueDrivingRecognition/pipeline/test.pipeline
@@ -1,94 +1,94 @@
-{
-    "detection": {
-        "stream_config": {
-            "deviceId": "0"
-        },
-        "mxpi_rtspsrc0": {
-            "factory": "mxpi_rtspsrc",
-            "props": {
-                "rtspUrl": "rtsp_url",
-                "channelId": "0"
-            },
-            "next": "mxpi_videodecoder0"
-        },
-        "mxpi_videodecoder0": {
-            "factory": "mxpi_videodecoder",
-            "props": {
-                "inputVideoFormat": "H264",
-                "outputImageFormat": "YUV420SP_NV12",
-                "vdecChannelId": "0"
-            },
-            "next": "mxpi_imageresize0"
-        },
-        "mxpi_imageresize0": {
-            "props": {
-                "dataSource": "mxpi_videodecoder0",
-                "resizeHeight": "416",
-                "resizeWidth": "416",
-                "resizeType": "Resizer_KeepAspectRatio_Fit"
-            },
-            "factory": "mxpi_imageresize",
-            "next": "mxpi_tensorinfer0"
-        },
-        "mxpi_tensorinfer0": {
-            "props": {
-                "dataSource":"mxpi_imageresize0",
-                "modelPath": "model/yolov4_detection.om"
-            },
-            "factory": "mxpi_tensorinfer",
-            "next": "mxpi_objectpostprocessor0"
-        },
-        "mxpi_objectpostprocessor0": {
-            "props": {
-                "dataSource": "mxpi_tensorinfer0",
-                "postProcessConfigPath": "model/yolov4.cfg",
-                "labelPath": "model/coco.names",
-                "postProcessLibPath": "${MX_SDK_HOME}/lib/modelpostprocessors/libyolov3postprocess.so"
-            },
-            "factory": "mxpi_objectpostprocessor",
-            "next": "mxpi_distributor0"
-        },
-        "mxpi_distributor0": {
-            "props": {
-                "dataSource": "mxpi_objectpostprocessor0",
-                "classIds": "3"
-            },
-            "factory": "mxpi_distributor",
-            "next": "mxpi_imagecrop0"
-        },
-        "mxpi_imagecrop0": {
-            "props": {
-                "dataSource": "mxpi_distributor0_0",
-                "dataSourceImage": "mxpi_imagedecoder0",
-                "resizeWidth": "112",
-                "resizeHeight": "112",
-                "leftExpandRatio": "0.2",
-                "rightExpandRatio": "0.2",
-                "resizeType": "Resizer_Stretch"
-            },
-            "factory": "mxpi_imagecrop",
-            "next": "mxpi_tensorinfer1"
-        },
-        "mxpi_tensorinfer1": {
-            "props": {
-                "dataSource":"mxpi_imagecrop0",
-                "modelPath": "model/pfld_106.om"
-            },
-            "factory": "mxpi_tensorinfer",
-            "next": "mxpi_pfldpostprocess0"
-        },
-        "mxpi_pfldpostprocess0": {
-            "props": {
-                "dataSource":"mxpi_tensorinfer1"
-            },
-            "factory": "mxpi_pfldpostprocess",
-            "next": "appsink0"
-        },
-        "appsink0": {
-            "props": {
-                "blocksize": "4096000"
-            },
-            "factory": "appsink"
-        }
-    }
+{
+    "detection": {
+        "stream_config": {
+            "deviceId": "0"
+        },
+        "mxpi_rtspsrc0": {
+            "factory": "mxpi_rtspsrc",
+            "props": {
+                "rtspUrl": "rtsp_url",
+                "channelId": "0"
+            },
+            "next": "mxpi_videodecoder0"
+        },
+        "mxpi_videodecoder0": {
+            "factory": "mxpi_videodecoder",
+            "props": {
+                "inputVideoFormat": "H264",
+                "outputImageFormat": "YUV420SP_NV12",
+                "vdecChannelId": "0"
+            },
+            "next": "mxpi_imageresize0"
+        },
+        "mxpi_imageresize0": {
+            "props": {
+                "dataSource": "mxpi_videodecoder0",
+                "resizeHeight": "416",
+                "resizeWidth": "416",
+                "resizeType": "Resizer_KeepAspectRatio_Fit"
+            },
+            "factory": "mxpi_imageresize",
+            "next": "mxpi_tensorinfer0"
+        },
+        "mxpi_tensorinfer0": {
+            "props": {
+                "dataSource":"mxpi_imageresize0",
+                "modelPath": "model/yolov4_detection.om"
+            },
+            "factory": "mxpi_tensorinfer",
+            "next": "mxpi_objectpostprocessor0"
+        },
+        "mxpi_objectpostprocessor0": {
+            "props": {
+                "dataSource": "mxpi_tensorinfer0",
+                "postProcessConfigPath": "model/yolov4.cfg",
+                "labelPath": "model/coco.names",
+                "postProcessLibPath": "${MX_SDK_HOME}/lib/modelpostprocessors/libyolov3postprocess.so"
+            },
+            "factory": "mxpi_objectpostprocessor",
+            "next": "mxpi_distributor0"
+        },
+        "mxpi_distributor0": {
+            "props": {
+                "dataSource": "mxpi_objectpostprocessor0",
+                "classIds": "3"
+            },
+            "factory": "mxpi_distributor",
+            "next": "mxpi_imagecrop0"
+        },
+        "mxpi_imagecrop0": {
+            "props": {
+                "dataSource": "mxpi_distributor0_0",
+                "dataSourceImage": "mxpi_imagedecoder0",
+                "resizeWidth": "112",
+                "resizeHeight": "112",
+                "leftExpandRatio": "0.2",
+                "rightExpandRatio": "0.2",
+                "resizeType": "Resizer_Stretch"
+            },
+            "factory": "mxpi_imagecrop",
+            "next": "mxpi_tensorinfer1"
+        },
+        "mxpi_tensorinfer1": {
+            "props": {
+                "dataSource":"mxpi_imagecrop0",
+                "modelPath": "model/pfld_106.om"
+            },
+            "factory": "mxpi_tensorinfer",
+            "next": "mxpi_pfldpostprocess0"
+        },
+        "mxpi_pfldpostprocess0": {
+            "props": {
+                "dataSource":"mxpi_tensorinfer1"
+            },
+            "factory": "mxpi_pfldpostprocess",
+            "next": "appsink0"
+        },
+        "appsink0": {
+            "props": {
+                "blocksize": "4096000"
+            },
+            "factory": "appsink"
+        }
+    }
 }
\ No newline at end of file
diff --git a/contrib/FatigueDrivingRecognition/pipeline/test_video.pipeline b/mxVision/mxVision-referenceapps/FatigueDrivingRecognition/pipeline/test_video.pipeline
similarity index 97%
rename from contrib/FatigueDrivingRecognition/pipeline/test_video.pipeline
rename to mxVision/mxVision-referenceapps/FatigueDrivingRecognition/pipeline/test_video.pipeline
index b78b7fc4ecb37dfe9ffca8ce7f2dcd5797fae206..ce7b9ce26283ec1d983fc142e1544e5115cdbd6f 100644
--- a/contrib/FatigueDrivingRecognition/pipeline/test_video.pipeline
+++ b/mxVision/mxVision-referenceapps/FatigueDrivingRecognition/pipeline/test_video.pipeline
@@ -1,94 +1,94 @@
-{
-    "detection": {
-        "stream_config": {
-            "deviceId": "0"
-        },
-        "mxpi_rtspsrc0": {
-            "factory": "mxpi_rtspsrc",
-            "props": {
-                "rtspUrl": "${264file_path}",
-                "channelId": "0"
-            },
-            "next": "mxpi_videodecoder0"
-        },
-        "mxpi_videodecoder0": {
-            "factory": "mxpi_videodecoder",
-            "props": {
-                "inputVideoFormat": "H264",
-                "outputImageFormat": "YUV420SP_NV12",
-                "vdecChannelId": "0"
-            },
-            "next": "mxpi_imageresize0"
-        },
-        "mxpi_imageresize0": {
-            "props": {
-                "dataSource": "mxpi_videodecoder0",
-                "resizeHeight": "416",
-                "resizeWidth": "416",
-                "resizeType": "Resizer_KeepAspectRatio_Fit"
-            },
-            "factory": "mxpi_imageresize",
-            "next": "mxpi_tensorinfer0"
-        },
-        "mxpi_tensorinfer0": {
-            "props": {
-                "dataSource":"mxpi_imageresize0",
-                "modelPath": "model/yolov4_detection.om"
-            },
-            "factory": "mxpi_tensorinfer",
-            "next": "mxpi_objectpostprocessor0"
-        },
-        "mxpi_objectpostprocessor0": {
-            "props": {
-                "dataSource": "mxpi_tensorinfer0",
-                "postProcessConfigPath": "model/yolov4.cfg",
-                "labelPath": "model/coco.names",
-                "postProcessLibPath": "${MX_SDK_HOME}/lib/modelpostprocessors/libyolov3postprocess.so"
-            },
-            "factory": "mxpi_objectpostprocessor",
-            "next": "mxpi_distributor0"
-        },
-        "mxpi_distributor0": {
-            "props": {
-                "dataSource": "mxpi_objectpostprocessor0",
-                "classIds": "3"
-            },
-            "factory": "mxpi_distributor",
-            "next": "mxpi_imagecrop0"
-        },
-        "mxpi_imagecrop0": {
-            "props": {
-                "dataSource": "mxpi_distributor0_0",
-                "dataSourceImage": "mxpi_imagedecoder0",
-                "resizeWidth": "112",
-                "resizeHeight": "112",
-                "leftExpandRatio": "0.2",
-                "rightExpandRatio": "0.2",
-                "resizeType": "Resizer_Stretch"
-            },
-            "factory": "mxpi_imagecrop",
-            "next": "mxpi_tensorinfer1"
-        },
-        "mxpi_tensorinfer1": {
-            "props": {
-                "dataSource":"mxpi_imagecrop0",
-                "modelPath": "model/pfld_106.om"
-            },
-            "factory": "mxpi_tensorinfer",
-            "next": "mxpi_pfldpostprocess0"
-        },
-        "mxpi_pfldpostprocess0": {
-            "props": {
-                "dataSource":"mxpi_tensorinfer1"
-            },
-            "factory": "mxpi_pfldpostprocess",
-            "next": "appsink0"
-        },
-        "appsink0": {
-            "props": {
-                "blocksize": "4096000"
-            },
-            "factory": "appsink"
-        }
-    }
+{
+    "detection": {
+        "stream_config": {
+            "deviceId": "0"
+        },
+        "mxpi_rtspsrc0": {
+            "factory": "mxpi_rtspsrc",
+            "props": {
+                "rtspUrl": "${264file_path}",
+                "channelId": "0"
+            },
+            "next": "mxpi_videodecoder0"
+        },
+        "mxpi_videodecoder0": {
+            "factory": "mxpi_videodecoder",
+            "props": {
+                "inputVideoFormat": "H264",
+                "outputImageFormat": "YUV420SP_NV12",
+                "vdecChannelId": "0"
+            },
+            "next": "mxpi_imageresize0"
+        },
+        "mxpi_imageresize0": {
+            "props": {
+                "dataSource": "mxpi_videodecoder0",
+                "resizeHeight": "416",
+                "resizeWidth": "416",
+                "resizeType": "Resizer_KeepAspectRatio_Fit"
+            },
+            "factory": "mxpi_imageresize",
+            "next": "mxpi_tensorinfer0"
+        },
+        "mxpi_tensorinfer0": {
+            "props": {
+                "dataSource":"mxpi_imageresize0",
+                "modelPath": "model/yolov4_detection.om"
+            },
+            "factory": "mxpi_tensorinfer",
+            "next": "mxpi_objectpostprocessor0"
+        },
+        "mxpi_objectpostprocessor0": {
+            "props": {
+                "dataSource": "mxpi_tensorinfer0",
+                "postProcessConfigPath": "model/yolov4.cfg",
+                "labelPath": "model/coco.names",
+                "postProcessLibPath": "${MX_SDK_HOME}/lib/modelpostprocessors/libyolov3postprocess.so"
+            },
+            "factory": "mxpi_objectpostprocessor",
+            "next": "mxpi_distributor0"
+        },
+        "mxpi_distributor0": {
+            "props": {
+                "dataSource": "mxpi_objectpostprocessor0",
+                "classIds": "3"
+            },
+            "factory": "mxpi_distributor",
+            "next": "mxpi_imagecrop0"
+        },
+        "mxpi_imagecrop0": {
+            "props": {
+                "dataSource": "mxpi_distributor0_0",
+                "dataSourceImage": "mxpi_imagedecoder0",
+                "resizeWidth": "112",
+                "resizeHeight": "112",
+                "leftExpandRatio": "0.2",
+                "rightExpandRatio": "0.2",
+                "resizeType": "Resizer_Stretch"
+            },
+            "factory": "mxpi_imagecrop",
+            "next": "mxpi_tensorinfer1"
+        },
+        "mxpi_tensorinfer1": {
+            "props": {
+                "dataSource":"mxpi_imagecrop0",
+                "modelPath": "model/pfld_106.om"
+            },
+            "factory": "mxpi_tensorinfer",
+            "next": "mxpi_pfldpostprocess0"
+        },
+        "mxpi_pfldpostprocess0": {
+            "props": {
+                "dataSource":"mxpi_tensorinfer1"
+            },
+            "factory": "mxpi_pfldpostprocess",
+            "next": "appsink0"
+        },
+        "appsink0": {
+            "props": {
+                "blocksize": "4096000"
+            },
+            "factory": "appsink"
+        }
+    }
 }
\ No newline at end of file
diff --git a/contrib/FatigueDrivingRecognition/run.sh b/mxVision/mxVision-referenceapps/FatigueDrivingRecognition/run.sh
similarity index 100%
rename from contrib/FatigueDrivingRecognition/run.sh
rename to mxVision/mxVision-referenceapps/FatigueDrivingRecognition/run.sh
diff --git a/contrib/FatigueDrivingRecognition/test.py b/mxVision/mxVision-referenceapps/FatigueDrivingRecognition/test.py
similarity index 100%
rename from contrib/FatigueDrivingRecognition/test.py
rename to mxVision/mxVision-referenceapps/FatigueDrivingRecognition/test.py
diff --git a/contrib/FatigueDrivingRecognition/test_video.py b/mxVision/mxVision-referenceapps/FatigueDrivingRecognition/test_video.py
similarity index 100%
rename from contrib/FatigueDrivingRecognition/test_video.py
rename to mxVision/mxVision-referenceapps/FatigueDrivingRecognition/test_video.py
diff --git a/contrib/FireDetection/c++/BlockingQueue/BlockingQueue.h b/mxVision/mxVision-referenceapps/FireDetection/c++/BlockingQueue/BlockingQueue.h
similarity index 96%
rename from contrib/FireDetection/c++/BlockingQueue/BlockingQueue.h
rename to mxVision/mxVision-referenceapps/FireDetection/c++/BlockingQueue/BlockingQueue.h
index 656bcd9d2baaa088ca79bc54934a603a7e2e2c2e..e581590baa1aee77fd66938fe2db25c4569ecbe0 100644
--- a/contrib/FireDetection/c++/BlockingQueue/BlockingQueue.h
+++ b/mxVision/mxVision-referenceapps/FireDetection/c++/BlockingQueue/BlockingQueue.h
@@ -1,181 +1,181 @@
-/*
- * Copyright(C) 2024. Huawei Technologies Co.,Ltd. All rights reserved.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#ifndef BLOCKING_QUEUE_H
-#define BLOCKING_QUEUE_H
-
-#include "MxBase/ErrorCode/ErrorCode.h"
-#include <condition_variable>
-#include <list>
-#include <mutex>
-#include <stdint.h>
-
-namespace MxBase {
-static const int DEFAULT_MAX_QUEUE_SIZE = 50000;
-
-template<typename T> class BlockingQueue {
-public:
-    BlockingQueue(uint32_t maxSize = DEFAULT_MAX_QUEUE_SIZE) : maxSize_(maxSize), isStoped_(false) {}
-
-    ~BlockingQueue() {}
-
-    APP_ERROR Push(const T& item, bool isWait = false)
-    {
-        std::unique_lock<std::mutex> lck(mutex_);
-        while (queue_.size() >= maxSize_ && isWait && !isStoped_) {
-            fullCond_.wait(lck);
-        }
-        if (isStoped_) {
-            return APP_ERR_QUEUE_STOPED;
-        }
-        if (queue_.size() >= maxSize_) {
-            return APP_ERR_QUEUE_FULL;
-        }
-        queue_.push_back(item);
-        emptyCond_.notify_one();
-        return APP_ERR_OK;
-    }
-
-    APP_ERROR Push_Front(const T &item, bool isWait = false)
-    {
-        std::unique_lock<std::mutex> lck(mutex_);
-        while (queue_.size() >= maxSize_ && isWait && !isStoped_) {
-            fullCond_.wait(lck);
-        }
-        if (isStoped_) {
-            return APP_ERR_QUEUE_STOPED;
-        }
-        if (queue_.size() >= maxSize_) {
-            return APP_ERR_QUEUE_FULL;
-        }
-        queue_.push_front(item);
-        emptyCond_.notify_one();
-        return APP_ERR_OK;
-    }
-
-    APP_ERROR Pop(T &item)
-    {
-        std::unique_lock<std::mutex> lck(mutex_);
-        while (queue_.empty() && !isStoped_) {
-            emptyCond_.wait(lck);
-        }
-        if (isStoped_) {
-            return APP_ERR_QUEUE_STOPED;
-        }
-        if (queue_.empty()) {
-            return APP_ERR_QUEUE_EMPTY;
-        } else {
-            item = queue_.front();
-            queue_.pop_front();
-        }
-        fullCond_.notify_one();
-        return APP_ERR_OK;
-    }
-
-    APP_ERROR Pop(T& item, unsigned int timeOutMs)
-    {
-        std::unique_lock<std::mutex> lck(mutex_);
-        auto realTime = std::chrono::milliseconds(timeOutMs);
-        if (queue_.empty() && !isStoped_) {
-            emptyCond_.wait_until(lck, std::chrono::steady_clock::now() + realTime);
-        }
-        if (isStoped_) {
-            return APP_ERR_QUEUE_STOPED;
-        }
-        if (queue_.empty()) {
-            return APP_ERR_QUEUE_EMPTY;
-        } else {
-            item = queue_.front();
-            queue_.pop_front();
-        }
-        fullCond_.notify_one();
-        return APP_ERR_OK;
-    }
-
-    void Stop()
-    {
-        {
-            std::unique_lock<std::mutex> lck(mutex_);
-            isStoped_ = true;
-        }
-        fullCond_.notify_all();
-        emptyCond_.notify_all();
-    }
-
-    void Restart()
-    {
-        std::unique_lock<std::mutex> lck(mutex_);
-        isStoped_ = false;
-    }
-
-    APP_ERROR GetBackItem(T &item)
-    {
-        std::unique_lock<std::mutex> lck(mutex_);
-        if (isStoped_) {
-            return APP_ERR_QUEUE_STOPED;
-        }
-        if (queue_.empty()) {
-            return APP_ERR_QUEUE_EMPTY;
-        }
-        item = queue_.back();
-        return APP_ERR_OK;
-    }
-
-    // if the queue is stoped ,need call this function to release the unprocessed items
-    std::list<T> GetRemainItems()
-    {
-        std::unique_lock<std::mutex> lck(mutex_);
-        if (!isStoped_) {
-            return std::list<T>();
-        }
-        return queue_;
-    }
-
-    APP_ERROR IsEmpty()
-    {
-        std::unique_lock<std::mutex> lck(mutex_);
-        return queue_.empty();
-    }
-
-    APP_ERROR IsFull()
-    {
-        std::unique_lock<std::mutex> lck(mutex_);
-        return queue_.size() >= maxSize_;
-    }
-
-    int GetSize()
-    {
-        std::unique_lock<std::mutex> lck(mutex_);
-        return queue_.size();
-    }
-
-    void Clear()
-    {
-        std::unique_lock<std::mutex> lck(mutex_);
-        queue_.clear();
-    }
-
-private:
-    std::list<T> queue_;
-    std::condition_variable fullCond_;
-    std::condition_variable emptyCond_;
-    std::mutex mutex_;
-    uint32_t maxSize_;
-
-    bool isStoped_;
-};
-}
-#endif // __INC_BLOCKING_QUEUE_H__
+/*
+ * Copyright(C) 2024. Huawei Technologies Co.,Ltd. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef BLOCKING_QUEUE_H
+#define BLOCKING_QUEUE_H
+
+#include "MxBase/ErrorCode/ErrorCode.h"
+#include <condition_variable>
+#include <list>
+#include <mutex>
+#include <stdint.h>
+
+namespace MxBase {
+static const int DEFAULT_MAX_QUEUE_SIZE = 50000;
+
+template<typename T> class BlockingQueue {
+public:
+    BlockingQueue(uint32_t maxSize = DEFAULT_MAX_QUEUE_SIZE) : maxSize_(maxSize), isStoped_(false) {}
+
+    ~BlockingQueue() {}
+
+    APP_ERROR Push(const T& item, bool isWait = false)
+    {
+        std::unique_lock<std::mutex> lck(mutex_);
+        while (queue_.size() >= maxSize_ && isWait && !isStoped_) {
+            fullCond_.wait(lck);
+        }
+        if (isStoped_) {
+            return APP_ERR_QUEUE_STOPED;
+        }
+        if (queue_.size() >= maxSize_) {
+            return APP_ERR_QUEUE_FULL;
+        }
+        queue_.push_back(item);
+        emptyCond_.notify_one();
+        return APP_ERR_OK;
+    }
+
+    APP_ERROR Push_Front(const T &item, bool isWait = false)
+    {
+        std::unique_lock<std::mutex> lck(mutex_);
+        while (queue_.size() >= maxSize_ && isWait && !isStoped_) {
+            fullCond_.wait(lck);
+        }
+        if (isStoped_) {
+            return APP_ERR_QUEUE_STOPED;
+        }
+        if (queue_.size() >= maxSize_) {
+            return APP_ERR_QUEUE_FULL;
+        }
+        queue_.push_front(item);
+        emptyCond_.notify_one();
+        return APP_ERR_OK;
+    }
+
+    APP_ERROR Pop(T &item)
+    {
+        std::unique_lock<std::mutex> lck(mutex_);
+        while (queue_.empty() && !isStoped_) {
+            emptyCond_.wait(lck);
+        }
+        if (isStoped_) {
+            return APP_ERR_QUEUE_STOPED;
+        }
+        if (queue_.empty()) {
+            return APP_ERR_QUEUE_EMPTY;
+        } else {
+            item = queue_.front();
+            queue_.pop_front();
+        }
+        fullCond_.notify_one();
+        return APP_ERR_OK;
+    }
+
+    APP_ERROR Pop(T& item, unsigned int timeOutMs)
+    {
+        std::unique_lock<std::mutex> lck(mutex_);
+        auto realTime = std::chrono::milliseconds(timeOutMs);
+        if (queue_.empty() && !isStoped_) {
+            emptyCond_.wait_until(lck, std::chrono::steady_clock::now() + realTime);
+        }
+        if (isStoped_) {
+            return APP_ERR_QUEUE_STOPED;
+        }
+        if (queue_.empty()) {
+            return APP_ERR_QUEUE_EMPTY;
+        } else {
+            item = queue_.front();
+            queue_.pop_front();
+        }
+        fullCond_.notify_one();
+        return APP_ERR_OK;
+    }
+
+    void Stop()
+    {
+        {
+            std::unique_lock<std::mutex> lck(mutex_);
+            isStoped_ = true;
+        }
+        fullCond_.notify_all();
+        emptyCond_.notify_all();
+    }
+
+    void Restart()
+    {
+        std::unique_lock<std::mutex> lck(mutex_);
+        isStoped_ = false;
+    }
+
+    APP_ERROR GetBackItem(T &item)
+    {
+        std::unique_lock<std::mutex> lck(mutex_);
+        if (isStoped_) {
+            return APP_ERR_QUEUE_STOPED;
+        }
+        if (queue_.empty()) {
+            return APP_ERR_QUEUE_EMPTY;
+        }
+        item = queue_.back();
+        return APP_ERR_OK;
+    }
+
+    // if the queue is stoped ,need call this function to release the unprocessed items
+    std::list<T> GetRemainItems()
+    {
+        std::unique_lock<std::mutex> lck(mutex_);
+        if (!isStoped_) {
+            return std::list<T>();
+        }
+        return queue_;
+    }
+
+    APP_ERROR IsEmpty()
+    {
+        std::unique_lock<std::mutex> lck(mutex_);
+        return queue_.empty();
+    }
+
+    APP_ERROR IsFull()
+    {
+        std::unique_lock<std::mutex> lck(mutex_);
+        return queue_.size() >= maxSize_;
+    }
+
+    int GetSize()
+    {
+        std::unique_lock<std::mutex> lck(mutex_);
+        return queue_.size();
+    }
+
+    void Clear()
+    {
+        std::unique_lock<std::mutex> lck(mutex_);
+        queue_.clear();
+    }
+
+private:
+    std::list<T> queue_;
+    std::condition_variable fullCond_;
+    std::condition_variable emptyCond_;
+    std::mutex mutex_;
+    uint32_t maxSize_;
+
+    bool isStoped_;
+};
+}
+#endif // __INC_BLOCKING_QUEUE_H__
diff --git a/contrib/FireDetection/c++/CMakeLists.txt b/mxVision/mxVision-referenceapps/FireDetection/c++/CMakeLists.txt
similarity index 97%
rename from contrib/FireDetection/c++/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/FireDetection/c++/CMakeLists.txt
index d8eda34d464207727aca17b51d4ebb49089d2391..2e8001898cbf031b4b57a43b8d659b1f747789b8 100644
--- a/contrib/FireDetection/c++/CMakeLists.txt
+++ b/mxVision/mxVision-referenceapps/FireDetection/c++/CMakeLists.txt
@@ -1,80 +1,80 @@
-# Copyright (c) Huawei Technologies Co., Ltd. 2024-2024. All rights reserved.
-
-# CMake lowest version requirement
-cmake_minimum_required(VERSION 3.5.2)
-
-# project information
-project(MindX_SDK_Fire_Detection)
-
-set(MX_SDK_HOME $ENV{MX_SDK_HOME})
-set(FFMPEG_PATH $ENV{FFMPEG_PATH})
-set(ASCEND_TOOLKIT_HOME $ENV{ASCEND_TOOLKIT_HOME})
-
-set(PROJECT_SRC_ROOT ${CMAKE_CURRENT_LIST_DIR})
-set(CMAKE_MODULE_PATH ${PROJECT_SRC_ROOT}/CMake)
-set(CMAKE_SKIP_BUILD_RPATH True)
-
-if (NOT DEFINED ENV{MX_SDK_HOME})
-    string(REGEX REPLACE "(.*)/(.*)/(.*)/(.*)" "\\1" MX_SDK_HOME  ${CMAKE_CURRENT_SOURCE_DIR})
-    message(STATUS "set default MX_SDK_HOME: ${MX_SDK_HOME}")
-else ()
-    message(STATUS "env MX_SDK_HOME: ${MX_SDK_HOME}")
-endif()
-
-# Compile options
-add_definitions(-D_GLIBCXX_USE_CXX11_ABI=0)
-add_definitions(-Dgoogle=mindxsdk_private)
-add_compile_options(-fPIC -fstack-protector-all -Wall -g -O0)
-
-# 设置c++编译版本
-execute_process(
-    COMMAND awk "/MindX SDK mxVision:/ {print \$NF}" ${MX_SDK_HOME}/version.info
-    OUTPUT_VARIABLE MXVISION_VERSION
-    OUTPUT_STRIP_TRAILING_WHITESPACE
-)
-
-if("${MXVISION_VERSION}" STREQUAL "mxVision:6.0.RC3")
-    set(CMAKE_CXX_STANDARD 14)
-    message(STATUS "C++14 standard is set.")
-else()
-    set(CMAKE_CXX_STANDARD 11)
-    message(STATUS "C++11 standard is set.")
-endif()
-
-
-set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR})
-set(CMAKE_CXX_FLAGS_DEBUG "-g")
-set(CMAKE_EXE_LINKER_FLAGS "${CMAKE_EXE_LINKER_FLAGS} -Wl,-z,relro,-z,now,-z,noexecstack -pie")
-set(CMAKE_SKIP_RPATH TRUE)
-
-# Header path
-include_directories(
-        ${ASCEND_TOOLKIT_HOME}/include/
-        ${MX_SDK_HOME}/include/
-        ${MX_SDK_HOME}/opensource/include/
-        ${MX_SDK_HOME}/opensource/include/opencv4
-        ${FFMPEG_PATH}/include/
-)
-
-set(OPENSOURCE_DIR ${MX_SDK_HOME}/opensource)
-
-include_directories(
-        ${OPENSOURCE_DIR}/include
-)
-link_directories(${OPENSOURCE_DIR}/lib)
-
-# add host lib path
-link_directories(
-        ${ASCEND_TOOLKIT_HOME}/lib64/
-        ${MX_SDK_HOME}/lib/
-        ${MX_SDK_HOME}/opensource/lib/
-        ${MX_SDK_HOME}/opensource/lib64/
-        ${FFMPEG_PATH}/lib/
-)
-
-add_executable(main main.cpp ConfigParser/ConfigParser.h ConfigParser/ConfigParser.cpp VideoDecoder/VideoDecoder.h
-               VideoDecoder/VideoDecoder.cpp FrameAnalyzer/FrameAnalyzer.h FrameAnalyzer/FrameAnalyzer.cpp )
-
-#target_link_libraries(main glog mxbase gstrtp-1.0 -lpthread -lm avformat avcodec avdevice avutil swresample opencv_world ascendcl)
-target_link_libraries(main glog mxbase  -lpthread -lm avformat avcodec avdevice avutil ascendcl)
+# Copyright (c) Huawei Technologies Co., Ltd. 2024-2024. All rights reserved.
+
+# CMake lowest version requirement
+cmake_minimum_required(VERSION 3.5.2)
+
+# project information
+project(MindX_SDK_Fire_Detection)
+
+set(MX_SDK_HOME $ENV{MX_SDK_HOME})
+set(FFMPEG_PATH $ENV{FFMPEG_PATH})
+set(ASCEND_TOOLKIT_HOME $ENV{ASCEND_TOOLKIT_HOME})
+
+set(PROJECT_SRC_ROOT ${CMAKE_CURRENT_LIST_DIR})
+set(CMAKE_MODULE_PATH ${PROJECT_SRC_ROOT}/CMake)
+set(CMAKE_SKIP_BUILD_RPATH True)
+
+if (NOT DEFINED ENV{MX_SDK_HOME})
+    string(REGEX REPLACE "(.*)/(.*)/(.*)/(.*)" "\\1" MX_SDK_HOME  ${CMAKE_CURRENT_SOURCE_DIR})
+    message(STATUS "set default MX_SDK_HOME: ${MX_SDK_HOME}")
+else ()
+    message(STATUS "env MX_SDK_HOME: ${MX_SDK_HOME}")
+endif()
+
+# Compile options
+add_definitions(-D_GLIBCXX_USE_CXX11_ABI=0)
+add_definitions(-Dgoogle=mindxsdk_private)
+add_compile_options(-fPIC -fstack-protector-all -Wall -g -O0)
+
+# 设置c++编译版本
+execute_process(
+    COMMAND awk "/MindX SDK mxVision:/ {print \$NF}" ${MX_SDK_HOME}/version.info
+    OUTPUT_VARIABLE MXVISION_VERSION
+    OUTPUT_STRIP_TRAILING_WHITESPACE
+)
+
+if("${MXVISION_VERSION}" STREQUAL "mxVision:6.0.RC3")
+    set(CMAKE_CXX_STANDARD 14)
+    message(STATUS "C++14 standard is set.")
+else()
+    set(CMAKE_CXX_STANDARD 11)
+    message(STATUS "C++11 standard is set.")
+endif()
+
+
+set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR})
+set(CMAKE_CXX_FLAGS_DEBUG "-g")
+set(CMAKE_EXE_LINKER_FLAGS "${CMAKE_EXE_LINKER_FLAGS} -Wl,-z,relro,-z,now,-z,noexecstack -pie")
+set(CMAKE_SKIP_RPATH TRUE)
+
+# Header path
+include_directories(
+        ${ASCEND_TOOLKIT_HOME}/include/
+        ${MX_SDK_HOME}/include/
+        ${MX_SDK_HOME}/opensource/include/
+        ${MX_SDK_HOME}/opensource/include/opencv4
+        ${FFMPEG_PATH}/include/
+)
+
+set(OPENSOURCE_DIR ${MX_SDK_HOME}/opensource)
+
+include_directories(
+        ${OPENSOURCE_DIR}/include
+)
+link_directories(${OPENSOURCE_DIR}/lib)
+
+# add host lib path
+link_directories(
+        ${ASCEND_TOOLKIT_HOME}/lib64/
+        ${MX_SDK_HOME}/lib/
+        ${MX_SDK_HOME}/opensource/lib/
+        ${MX_SDK_HOME}/opensource/lib64/
+        ${FFMPEG_PATH}/lib/
+)
+
+add_executable(main main.cpp ConfigParser/ConfigParser.h ConfigParser/ConfigParser.cpp VideoDecoder/VideoDecoder.h
+               VideoDecoder/VideoDecoder.cpp FrameAnalyzer/FrameAnalyzer.h FrameAnalyzer/FrameAnalyzer.cpp )
+
+#target_link_libraries(main glog mxbase gstrtp-1.0 -lpthread -lm avformat avcodec avdevice avutil swresample opencv_world ascendcl)
+target_link_libraries(main glog mxbase  -lpthread -lm avformat avcodec avdevice avutil ascendcl)
 install(TARGETS main DESTINATION ${CMAKE_RUNTIME_OUTPUT_DIRECTORY})
\ No newline at end of file
diff --git a/contrib/FireDetection/c++/ConfigParser/ConfigParser.cpp b/mxVision/mxVision-referenceapps/FireDetection/c++/ConfigParser/ConfigParser.cpp
similarity index 97%
rename from contrib/FireDetection/c++/ConfigParser/ConfigParser.cpp
rename to mxVision/mxVision-referenceapps/FireDetection/c++/ConfigParser/ConfigParser.cpp
index e78f8ed8f89ecfa44696ccdffcdbed07f8e1756d..98f7a92a0d5f440aad555e1914db608720b0e7e7 100644
--- a/contrib/FireDetection/c++/ConfigParser/ConfigParser.cpp
+++ b/mxVision/mxVision-referenceapps/FireDetection/c++/ConfigParser/ConfigParser.cpp
@@ -1,110 +1,110 @@
-/*
- * Copyright(C) 2024. Huawei Technologies Co.,Ltd. All rights reserved.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#include <sstream>
-#include <algorithm>
-#include <fstream>
-#include "MxBase/Log/Log.h"
-#include "ConfigParser.h"
-
-namespace ascendVideoDecoder {
-namespace {
-    const char COMMENT_CHARATER = '#';
-}
-
-// Remove spaces from both left and right based on the string
-inline void ConfigParser::Trim(std::string &str) const
-{
-    str.erase(str.begin(), std::find_if(str.begin(), str.end(), std::not1(std::ptr_fun(::isspace))));
-    str.erase(std::find_if(str.rbegin(), str.rend(), std::not1(std::ptr_fun(::isspace))).base(), str.end());
-    return;
-}
-
-APP_ERROR ConfigParser::ParseConfig(const std::string &fileName)
-{
-    // Open the input file
-    std::ifstream inFile(fileName);
-    if (!inFile.is_open()) {
-        LogError << "cannot read setup.config file!";
-        return APP_ERR_COMM_EXIST;
-    }
-    std::string line, newLine;
-    int startPos, endPos, pos;
-    // Cycle all the line
-    while (getline(inFile, line)) {
-        if (line.empty()) {
-            continue;
-        }
-        startPos = 0;
-        endPos = line.size() - 1;
-        pos = line.find(COMMENT_CHARATER); // Find the position of comment
-        if (pos != -1) {
-            if (pos == 0) {
-                continue;
-            }
-            endPos = pos - 1;
-        }
-        newLine = line.substr(startPos, (endPos - startPos) + 1); // delete comment
-        pos = newLine.find('=');
-        if (pos == -1) {
-            continue;
-        }
-        std::string na = newLine.substr(0, pos);
-        Trim(na);      // Delete the space of the key name
-        std::string value = newLine.substr(pos + 1, endPos + 1 - (pos + 1));
-        Trim(value);                                   // Delete the space of value
-        configData_.insert(std::make_pair(na, value));       // Insert the key-value pairs into configData_
-    }
-    inFile.close();
-    return APP_ERR_OK;
-}
-
-// Get the string value by key name
-APP_ERROR ConfigParser::GetStringValue(const std::string &name, std::string &value) const
-{
-    if (configData_.count(name) == 0) {
-        return APP_ERR_COMM_NO_EXIST;
-    }
-    value = configData_.find(name)->second;
-    return APP_ERR_OK;
-}
-
-// Get the unsigned integer value by key name
-APP_ERROR ConfigParser::GetUnsignedIntValue(const std::string &name, unsigned int &value) const
-{
-    if (configData_.count(name) == 0) {
-        return APP_ERR_COMM_NO_EXIST;
-    }
-    std::string str = configData_.find(name)->second;
-    if (!(std::stringstream(str) >> value)) {
-        return APP_ERR_COMM_INVALID_PARAM;
-    }
-    return APP_ERR_OK;
-}
-
-// Get the int value by key name
-APP_ERROR ConfigParser::GetIntValue(const std::string &name, int &value) const
-{
-    if (configData_.count(name) == 0) {
-        return APP_ERR_COMM_NO_EXIST;
-    }
-    std::string str = configData_.find(name)->second;
-    if (!(std::stringstream(str) >> value)) {
-        return APP_ERR_COMM_INVALID_PARAM;
-    }
-    return APP_ERR_OK;
-}
+/*
+ * Copyright(C) 2024. Huawei Technologies Co.,Ltd. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include <sstream>
+#include <algorithm>
+#include <fstream>
+#include "MxBase/Log/Log.h"
+#include "ConfigParser.h"
+
+namespace ascendVideoDecoder {
+namespace {
+    const char COMMENT_CHARATER = '#';
+}
+
+// Remove spaces from both left and right based on the string
+inline void ConfigParser::Trim(std::string &str) const
+{
+    str.erase(str.begin(), std::find_if(str.begin(), str.end(), std::not1(std::ptr_fun(::isspace))));
+    str.erase(std::find_if(str.rbegin(), str.rend(), std::not1(std::ptr_fun(::isspace))).base(), str.end());
+    return;
+}
+
+APP_ERROR ConfigParser::ParseConfig(const std::string &fileName)
+{
+    // Open the input file
+    std::ifstream inFile(fileName);
+    if (!inFile.is_open()) {
+        LogError << "cannot read setup.config file!";
+        return APP_ERR_COMM_EXIST;
+    }
+    std::string line, newLine;
+    int startPos, endPos, pos;
+    // Cycle all the line
+    while (getline(inFile, line)) {
+        if (line.empty()) {
+            continue;
+        }
+        startPos = 0;
+        endPos = line.size() - 1;
+        pos = line.find(COMMENT_CHARATER); // Find the position of comment
+        if (pos != -1) {
+            if (pos == 0) {
+                continue;
+            }
+            endPos = pos - 1;
+        }
+        newLine = line.substr(startPos, (endPos - startPos) + 1); // delete comment
+        pos = newLine.find('=');
+        if (pos == -1) {
+            continue;
+        }
+        std::string na = newLine.substr(0, pos);
+        Trim(na);      // Delete the space of the key name
+        std::string value = newLine.substr(pos + 1, endPos + 1 - (pos + 1));
+        Trim(value);                                   // Delete the space of value
+        configData_.insert(std::make_pair(na, value));       // Insert the key-value pairs into configData_
+    }
+    inFile.close();
+    return APP_ERR_OK;
+}
+
+// Get the string value by key name
+APP_ERROR ConfigParser::GetStringValue(const std::string &name, std::string &value) const
+{
+    if (configData_.count(name) == 0) {
+        return APP_ERR_COMM_NO_EXIST;
+    }
+    value = configData_.find(name)->second;
+    return APP_ERR_OK;
+}
+
+// Get the unsigned integer value by key name
+APP_ERROR ConfigParser::GetUnsignedIntValue(const std::string &name, unsigned int &value) const
+{
+    if (configData_.count(name) == 0) {
+        return APP_ERR_COMM_NO_EXIST;
+    }
+    std::string str = configData_.find(name)->second;
+    if (!(std::stringstream(str) >> value)) {
+        return APP_ERR_COMM_INVALID_PARAM;
+    }
+    return APP_ERR_OK;
+}
+
+// Get the int value by key name
+APP_ERROR ConfigParser::GetIntValue(const std::string &name, int &value) const
+{
+    if (configData_.count(name) == 0) {
+        return APP_ERR_COMM_NO_EXIST;
+    }
+    std::string str = configData_.find(name)->second;
+    if (!(std::stringstream(str) >> value)) {
+        return APP_ERR_COMM_INVALID_PARAM;
+    }
+    return APP_ERR_OK;
+}
 }
\ No newline at end of file
diff --git a/contrib/FireDetection/c++/ConfigParser/ConfigParser.h b/mxVision/mxVision-referenceapps/FireDetection/c++/ConfigParser/ConfigParser.h
similarity index 100%
rename from contrib/FireDetection/c++/ConfigParser/ConfigParser.h
rename to mxVision/mxVision-referenceapps/FireDetection/c++/ConfigParser/ConfigParser.h
diff --git a/contrib/FireDetection/c++/FrameAnalyzer/FrameAnalyzer.cpp b/mxVision/mxVision-referenceapps/FireDetection/c++/FrameAnalyzer/FrameAnalyzer.cpp
similarity index 97%
rename from contrib/FireDetection/c++/FrameAnalyzer/FrameAnalyzer.cpp
rename to mxVision/mxVision-referenceapps/FireDetection/c++/FrameAnalyzer/FrameAnalyzer.cpp
index 46e31e01fac3f7f25e331655461c89818976d52a..34341dc16230c1c1ea142cdee6871a2920b2ff94 100644
--- a/contrib/FireDetection/c++/FrameAnalyzer/FrameAnalyzer.cpp
+++ b/mxVision/mxVision-referenceapps/FireDetection/c++/FrameAnalyzer/FrameAnalyzer.cpp
@@ -1,164 +1,164 @@
-/*
- * Copyright(C) 2024. Huawei Technologies Co.,Ltd. All rights reserved.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-#include <algorithm>
-#include <map>
-#include <iostream>
-#include <string>
-#include <ctime>
-#include <chrono>
-#include "MxBase/Log/Log.h"
-#include "./FrameAnalyzer.h"
-using namespace std;
-using namespace MxBase;
-
-const int ANCHOR_DIM = 3;
-const std::vector<int> STRIDE_LIST = {80*80, 40*40, 20*20};
-const std::vector<int> LAYER_SIZE_LIST = {80, 40, 20};
-const int INFO_NUMBER_PER_BOX = 7;
-const int BBOX_INFO_NUMBER_PER_BOX = 4;
-const float OBJECT_THRESHOLD = 0.1;
-const float CLASS_THRESHOLD = 0.4;
-const float NMS_THRESHOLD = 0.6;
-const int CLASS_NUMBER = 2;
-const int MODEL_LENGTH = 640;
-const int DECODE_NUMBER = 2;
-std::map<int, std::string> INDEX_TO_CLASS = {{0, "Fire"}, {1, "Smoke"}};
-MxBase::Size modelSize(MODEL_LENGTH, MODEL_LENGTH);
-std::vector<std::vector<std::vector<int>>> ANCHORS_SIZE =
-        {{{10, 13}, {16, 30}, {33, 23}}, {{30, 61}, {62, 45}, {59, 119}}, {{116, 90}, {156, 198}, {373, 326}}};
-
-
-FrameAnalyzeModel::FrameAnalyzeModel(std::string modelPath, int deviceId) {
-    model_ = std::make_shared<Model>(modelPath, deviceId);
-    imageProcessor_ = std::make_shared<ImageProcessor>(deviceId);
-}
-
-
-APP_ERROR FrameAnalyzeModel::DecodeBox(std::vector<MxBase::Tensor>& outputs, std::vector<MxBase::ObjectInfo>& detBoxes) {
-    for (int layer = 0; layer < outputs.size(); layer++) {
-        int anchorNumber = outputs[layer].GetShape()[1];
-        int tensorHeight = outputs[layer].GetShape()[2];
-        int tensorWidth = outputs[layer].GetShape()[3];
-        float *tensor = static_cast<float *>(outputs[layer].GetData());
-        for (int heightIndex = 0; heightIndex < tensorHeight; ++heightIndex) {
-            for (int widthIndex = 0; widthIndex < tensorWidth; ++widthIndex) {
-                for (int anchorIndex = 0; anchorIndex < anchorNumber; ++anchorIndex) {
-                    int bIdx = anchorIndex * tensorWidth * tensorHeight * INFO_NUMBER_PER_BOX + heightIndex *
-                            tensorWidth * INFO_NUMBER_PER_BOX + widthIndex * INFO_NUMBER_PER_BOX;
-                    int oIdx = bIdx + BBOX_INFO_NUMBER_PER_BOX;
-                    int cIdx = bIdx + BBOX_INFO_NUMBER_PER_BOX + 1;
-                    // 取目标框得分和分类得分
-                    float objectness = fastmath::sigmoid(tensor[oIdx]);
-                    if (objectness <= OBJECT_THRESHOLD) {
-                        continue;
-                    }
-                    float classScore1 = fastmath::sigmoid(tensor[cIdx]) * objectness;
-                    float classScore2 = fastmath::sigmoid(tensor[cIdx+1]) * objectness;
-                    if (classScore1 < CLASS_THRESHOLD && classScore2 < CLASS_THRESHOLD) {
-                        continue;
-                    }
-                    float tempScore = classScore1;
-                    int tempClassId = 0;
-                    if (classScore1 < classScore2) {
-                        tempScore = classScore2;
-                        tempClassId = 1;
-                    }
-                    float x = (widthIndex + fastmath::sigmoid(tensor[bIdx]) * DECODE_NUMBER - 0.5);
-                    float y = (heightIndex + fastmath::sigmoid(tensor[bIdx + 1]) * DECODE_NUMBER - 0.5);
-                    auto widthTempValue = fastmath::sigmoid(tensor[bIdx + 2]);
-                    float width = widthTempValue * widthTempValue * 4 * ANCHORS_SIZE[layer][anchorIndex][0];
-                    auto heightTempValue = fastmath::sigmoid(tensor[bIdx + 3]);
-                    float height = heightTempValue * heightTempValue * 4 * ANCHORS_SIZE[layer][anchorIndex][1];
-                    MxBase::ObjectInfo objInfo;
-                    objInfo.x0 = max(x / LAYER_SIZE_LIST[layer] * modelSize.width - width / DECODE_NUMBER, 0.0f);
-                    objInfo.y0 = max(y / LAYER_SIZE_LIST[layer] * modelSize.height - height / DECODE_NUMBER, 0.0f);
-                    objInfo.x1 = min(x / LAYER_SIZE_LIST[layer] * modelSize.width + width /DECODE_NUMBER, static_cast<float>(modelSize.width));
-                    objInfo.y1 = min(y / LAYER_SIZE_LIST[layer] * modelSize.height + height / DECODE_NUMBER, static_cast<float>(modelSize.height));
-                    objInfo.confidence = tempScore;
-                    objInfo.classId = tempClassId;
-                    objInfo.className = INDEX_TO_CLASS[tempClassId];
-                    detBoxes.emplace_back(objInfo);
-                }
-            }
-        }
-    }
-    if (detBoxes.size() > 0){
-        MxBase::NmsSort(detBoxes,NMS_THRESHOLD);
-    }
-    return APP_ERR_OK;
-}
-
-APP_ERROR FrameAnalyzeModel::Infer(MxBase::Image &image, std::vector<ObjectInfo>& detBoxes) {
-    Size imageSize = image.GetOriginalSize();
-    float heightRatio = imageSize.height / modelSize.height;
-    float widthRatio = imageSize.width / modelSize.width;
-    if (imageSize.height != modelSize.height or imageSize.width != modelSize.width) {
-        APP_ERROR ret = imageProcessor_->Resize(image, modelSize, modelInputImage_);
-        if (ret != APP_ERR_OK) {
-            LogError << "Fail to resize the image";
-            return ret;
-        }
-    } else {
-        modelInputImage_ = image;
-    }
-    // Model infer
-    Tensor imageTensor = modelInputImage_.ConvertToTensor(true, false);
-    std::vector<uint32_t> newShape = imageTensor.GetShape();
-    newShape.insert(newShape.begin(), 1);
-    imageTensor.SetShape(newShape);
-    std::vector<Tensor> inferInputs = {};
-    inferInputs.push_back(imageTensor);
-    std::vector<Tensor> inferOutputs = model_->Infer(inferInputs);
-    // Move tensor form host to device
-    std::vector<Tensor> outputs = {};
-    for (Tensor tensor: inferOutputs) {
-        APP_ERROR ret = tensor.ToHost();
-        if (ret != APP_ERR_OK) {
-            LogError << "Fail to move tensor to host";
-        }
-        outputs.push_back(tensor);
-    }
-    APP_ERROR ret = DecodeBox(outputs, detBoxes);
-    if (ret != APP_ERR_OK) {
-        LogError << "Fail to decode bounding box.";
-        return ret;
-    }
-    if (detBoxes.size() > 0){
-        MxBase::NmsSort(detBoxes,NMS_THRESHOLD);
-    }
-    for (int i = 0; i < detBoxes.size(); ++i) {
-        detBoxes[i].x1 = detBoxes[i].x1 * widthRatio;
-        detBoxes[i].x0 = detBoxes[i].x0 * widthRatio;
-        detBoxes[i].y1 = detBoxes[i].y1 * heightRatio;
-        detBoxes[i].y0 = detBoxes[i].y0 * heightRatio;
-    }
-    return APP_ERR_OK;
-}
-
-
-APP_ERROR FrameAnalyzer::Alarm(std::vector<ObjectInfo>& detBoxes, int frameId) {
-    for (int i = 0; i < detBoxes.size(); ++i) {
-        std::cout << "Frame " << frameId << " detect " << detBoxes[i].className << "! Confidence: "
-                << detBoxes[i].confidence << ", x0: " << detBoxes[i].x0 << ", y0: " << detBoxes[i].y0
-                << ", x1: " << detBoxes[i].x1 << ", y1: " << detBoxes[i].y1 << std::endl;
-    }
-    return APP_ERR_OK;
-}
-
-
-APP_ERROR FrameAnalyzer::Analyze(Image &image, std::vector<ObjectInfo>& detBoxes) {
-    return frameAnalyzeModel_.Infer(image, detBoxes);
+/*
+ * Copyright(C) 2024. Huawei Technologies Co.,Ltd. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#include <algorithm>
+#include <map>
+#include <iostream>
+#include <string>
+#include <ctime>
+#include <chrono>
+#include "MxBase/Log/Log.h"
+#include "./FrameAnalyzer.h"
+using namespace std;
+using namespace MxBase;
+
+const int ANCHOR_DIM = 3;
+const std::vector<int> STRIDE_LIST = {80*80, 40*40, 20*20};
+const std::vector<int> LAYER_SIZE_LIST = {80, 40, 20};
+const int INFO_NUMBER_PER_BOX = 7;
+const int BBOX_INFO_NUMBER_PER_BOX = 4;
+const float OBJECT_THRESHOLD = 0.1;
+const float CLASS_THRESHOLD = 0.4;
+const float NMS_THRESHOLD = 0.6;
+const int CLASS_NUMBER = 2;
+const int MODEL_LENGTH = 640;
+const int DECODE_NUMBER = 2;
+std::map<int, std::string> INDEX_TO_CLASS = {{0, "Fire"}, {1, "Smoke"}};
+MxBase::Size modelSize(MODEL_LENGTH, MODEL_LENGTH);
+std::vector<std::vector<std::vector<int>>> ANCHORS_SIZE =
+        {{{10, 13}, {16, 30}, {33, 23}}, {{30, 61}, {62, 45}, {59, 119}}, {{116, 90}, {156, 198}, {373, 326}}};
+
+
+FrameAnalyzeModel::FrameAnalyzeModel(std::string modelPath, int deviceId) {
+    model_ = std::make_shared<Model>(modelPath, deviceId);
+    imageProcessor_ = std::make_shared<ImageProcessor>(deviceId);
+}
+
+
+APP_ERROR FrameAnalyzeModel::DecodeBox(std::vector<MxBase::Tensor>& outputs, std::vector<MxBase::ObjectInfo>& detBoxes) {
+    for (int layer = 0; layer < outputs.size(); layer++) {
+        int anchorNumber = outputs[layer].GetShape()[1];
+        int tensorHeight = outputs[layer].GetShape()[2];
+        int tensorWidth = outputs[layer].GetShape()[3];
+        float *tensor = static_cast<float *>(outputs[layer].GetData());
+        for (int heightIndex = 0; heightIndex < tensorHeight; ++heightIndex) {
+            for (int widthIndex = 0; widthIndex < tensorWidth; ++widthIndex) {
+                for (int anchorIndex = 0; anchorIndex < anchorNumber; ++anchorIndex) {
+                    int bIdx = anchorIndex * tensorWidth * tensorHeight * INFO_NUMBER_PER_BOX + heightIndex *
+                            tensorWidth * INFO_NUMBER_PER_BOX + widthIndex * INFO_NUMBER_PER_BOX;
+                    int oIdx = bIdx + BBOX_INFO_NUMBER_PER_BOX;
+                    int cIdx = bIdx + BBOX_INFO_NUMBER_PER_BOX + 1;
+                    // 取目标框得分和分类得分
+                    float objectness = fastmath::sigmoid(tensor[oIdx]);
+                    if (objectness <= OBJECT_THRESHOLD) {
+                        continue;
+                    }
+                    float classScore1 = fastmath::sigmoid(tensor[cIdx]) * objectness;
+                    float classScore2 = fastmath::sigmoid(tensor[cIdx+1]) * objectness;
+                    if (classScore1 < CLASS_THRESHOLD && classScore2 < CLASS_THRESHOLD) {
+                        continue;
+                    }
+                    float tempScore = classScore1;
+                    int tempClassId = 0;
+                    if (classScore1 < classScore2) {
+                        tempScore = classScore2;
+                        tempClassId = 1;
+                    }
+                    float x = (widthIndex + fastmath::sigmoid(tensor[bIdx]) * DECODE_NUMBER - 0.5);
+                    float y = (heightIndex + fastmath::sigmoid(tensor[bIdx + 1]) * DECODE_NUMBER - 0.5);
+                    auto widthTempValue = fastmath::sigmoid(tensor[bIdx + 2]);
+                    float width = widthTempValue * widthTempValue * 4 * ANCHORS_SIZE[layer][anchorIndex][0];
+                    auto heightTempValue = fastmath::sigmoid(tensor[bIdx + 3]);
+                    float height = heightTempValue * heightTempValue * 4 * ANCHORS_SIZE[layer][anchorIndex][1];
+                    MxBase::ObjectInfo objInfo;
+                    objInfo.x0 = max(x / LAYER_SIZE_LIST[layer] * modelSize.width - width / DECODE_NUMBER, 0.0f);
+                    objInfo.y0 = max(y / LAYER_SIZE_LIST[layer] * modelSize.height - height / DECODE_NUMBER, 0.0f);
+                    objInfo.x1 = min(x / LAYER_SIZE_LIST[layer] * modelSize.width + width /DECODE_NUMBER, static_cast<float>(modelSize.width));
+                    objInfo.y1 = min(y / LAYER_SIZE_LIST[layer] * modelSize.height + height / DECODE_NUMBER, static_cast<float>(modelSize.height));
+                    objInfo.confidence = tempScore;
+                    objInfo.classId = tempClassId;
+                    objInfo.className = INDEX_TO_CLASS[tempClassId];
+                    detBoxes.emplace_back(objInfo);
+                }
+            }
+        }
+    }
+    if (detBoxes.size() > 0){
+        MxBase::NmsSort(detBoxes,NMS_THRESHOLD);
+    }
+    return APP_ERR_OK;
+}
+
+APP_ERROR FrameAnalyzeModel::Infer(MxBase::Image &image, std::vector<ObjectInfo>& detBoxes) {
+    Size imageSize = image.GetOriginalSize();
+    float heightRatio = imageSize.height / modelSize.height;
+    float widthRatio = imageSize.width / modelSize.width;
+    if (imageSize.height != modelSize.height or imageSize.width != modelSize.width) {
+        APP_ERROR ret = imageProcessor_->Resize(image, modelSize, modelInputImage_);
+        if (ret != APP_ERR_OK) {
+            LogError << "Fail to resize the image";
+            return ret;
+        }
+    } else {
+        modelInputImage_ = image;
+    }
+    // Model infer
+    Tensor imageTensor = modelInputImage_.ConvertToTensor(true, false);
+    std::vector<uint32_t> newShape = imageTensor.GetShape();
+    newShape.insert(newShape.begin(), 1);
+    imageTensor.SetShape(newShape);
+    std::vector<Tensor> inferInputs = {};
+    inferInputs.push_back(imageTensor);
+    std::vector<Tensor> inferOutputs = model_->Infer(inferInputs);
+    // Move tensor form host to device
+    std::vector<Tensor> outputs = {};
+    for (Tensor tensor: inferOutputs) {
+        APP_ERROR ret = tensor.ToHost();
+        if (ret != APP_ERR_OK) {
+            LogError << "Fail to move tensor to host";
+        }
+        outputs.push_back(tensor);
+    }
+    APP_ERROR ret = DecodeBox(outputs, detBoxes);
+    if (ret != APP_ERR_OK) {
+        LogError << "Fail to decode bounding box.";
+        return ret;
+    }
+    if (detBoxes.size() > 0){
+        MxBase::NmsSort(detBoxes,NMS_THRESHOLD);
+    }
+    for (int i = 0; i < detBoxes.size(); ++i) {
+        detBoxes[i].x1 = detBoxes[i].x1 * widthRatio;
+        detBoxes[i].x0 = detBoxes[i].x0 * widthRatio;
+        detBoxes[i].y1 = detBoxes[i].y1 * heightRatio;
+        detBoxes[i].y0 = detBoxes[i].y0 * heightRatio;
+    }
+    return APP_ERR_OK;
+}
+
+
+APP_ERROR FrameAnalyzer::Alarm(std::vector<ObjectInfo>& detBoxes, int frameId) {
+    for (int i = 0; i < detBoxes.size(); ++i) {
+        std::cout << "Frame " << frameId << " detect " << detBoxes[i].className << "! Confidence: "
+                << detBoxes[i].confidence << ", x0: " << detBoxes[i].x0 << ", y0: " << detBoxes[i].y0
+                << ", x1: " << detBoxes[i].x1 << ", y1: " << detBoxes[i].y1 << std::endl;
+    }
+    return APP_ERR_OK;
+}
+
+
+APP_ERROR FrameAnalyzer::Analyze(Image &image, std::vector<ObjectInfo>& detBoxes) {
+    return frameAnalyzeModel_.Infer(image, detBoxes);
 }
\ No newline at end of file
diff --git a/contrib/FireDetection/c++/FrameAnalyzer/FrameAnalyzer.h b/mxVision/mxVision-referenceapps/FireDetection/c++/FrameAnalyzer/FrameAnalyzer.h
similarity index 96%
rename from contrib/FireDetection/c++/FrameAnalyzer/FrameAnalyzer.h
rename to mxVision/mxVision-referenceapps/FireDetection/c++/FrameAnalyzer/FrameAnalyzer.h
index 43e4a4aa4d0d33b4da43554222ced1aab9c3c84b..9fb226b7fc7da85b851fc52064c005385f6609cd 100644
--- a/contrib/FireDetection/c++/FrameAnalyzer/FrameAnalyzer.h
+++ b/mxVision/mxVision-referenceapps/FireDetection/c++/FrameAnalyzer/FrameAnalyzer.h
@@ -1,53 +1,53 @@
-/*
- * Copyright(C) 2024. Huawei Technologies Co.,Ltd. All rights reserved.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-#ifndef __FRAMEANALYZER_H
-#define __FRAMEANALYZER_H
-#include <vector>
-#include "MxBase/MxBase.h"
-#include "MxBase/E2eInfer/Image/Image.h"
-#include "MxBase/Maths/FastMath.h"
-#include "MxBase/PostProcessBases/PostProcessDataType.h"
-#include "MxBase/CV/ObjectDetection/Nms/Nms.h"
-using namespace MxBase;
-
-class FrameAnalyzeModel {
-public:
-    FrameAnalyzeModel(std::string modelPath, int deviceId);
-
-    APP_ERROR Infer(Image &image, std::vector<ObjectInfo>& detBoxes);
-
-private:
-    APP_ERROR DecodeBox(std::vector<Tensor>& outputs, std::vector<ObjectInfo>& detBoxes);
-    std::shared_ptr <MxBase::Model> model_;
-    std::shared_ptr <MxBase::ImageProcessor> imageProcessor_;
-    Image modelInputImage_;
-
-};
-
-class FrameAnalyzer {
-public:
-    FrameAnalyzer(std::string modelPath, int deviceId) : frameAnalyzeModel_(modelPath, deviceId) {};
-
-    APP_ERROR Analyze(Image& image, std::vector<ObjectInfo>& detBoxes);
-
-    APP_ERROR Alarm(std::vector<ObjectInfo>& detBoxes, int frameId);
-
-private:
-    FrameAnalyzeModel frameAnalyzeModel_;
-
-};
-
+/*
+ * Copyright(C) 2024. Huawei Technologies Co.,Ltd. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#ifndef __FRAMEANALYZER_H
+#define __FRAMEANALYZER_H
+#include <vector>
+#include "MxBase/MxBase.h"
+#include "MxBase/E2eInfer/Image/Image.h"
+#include "MxBase/Maths/FastMath.h"
+#include "MxBase/PostProcessBases/PostProcessDataType.h"
+#include "MxBase/CV/ObjectDetection/Nms/Nms.h"
+using namespace MxBase;
+
+class FrameAnalyzeModel {
+public:
+    FrameAnalyzeModel(std::string modelPath, int deviceId);
+
+    APP_ERROR Infer(Image &image, std::vector<ObjectInfo>& detBoxes);
+
+private:
+    APP_ERROR DecodeBox(std::vector<Tensor>& outputs, std::vector<ObjectInfo>& detBoxes);
+    std::shared_ptr <MxBase::Model> model_;
+    std::shared_ptr <MxBase::ImageProcessor> imageProcessor_;
+    Image modelInputImage_;
+
+};
+
+class FrameAnalyzer {
+public:
+    FrameAnalyzer(std::string modelPath, int deviceId) : frameAnalyzeModel_(modelPath, deviceId) {};
+
+    APP_ERROR Analyze(Image& image, std::vector<ObjectInfo>& detBoxes);
+
+    APP_ERROR Alarm(std::vector<ObjectInfo>& detBoxes, int frameId);
+
+private:
+    FrameAnalyzeModel frameAnalyzeModel_;
+
+};
+
 #endif
\ No newline at end of file
diff --git a/contrib/FireDetection/c++/README.md b/mxVision/mxVision-referenceapps/FireDetection/c++/README.md
similarity index 97%
rename from contrib/FireDetection/c++/README.md
rename to mxVision/mxVision-referenceapps/FireDetection/c++/README.md
index 233571bfc003e6ced1be3883384bf5240a01fe5c..a0f7fcd386c0f965ca4e23f85559a25333211d6d 100644
--- a/contrib/FireDetection/c++/README.md
+++ b/mxVision/mxVision-referenceapps/FireDetection/c++/README.md
@@ -1,128 +1,128 @@
-# 基于mxBase的高速公路车辆火灾识别(C++)
-
-## 1 介绍
-
-### 1.1 简介
-高速公路车辆火灾识别基于 mxVision SDK 开发，在 Atlas 300V、Atlas 300V Pro 上进行目标检测。项目主要流程为：通过ffmpeg打开本地视频文件、模拟视频流，然后进行视频解码，解码结果经过模型推理进行火灾和烟雾检测，如果检测到烟雾和火灾则在日志中进行告警。解码后的视频图像会编码保存至指定位置。
-
-### 1.2 支持的产品
-支持Atlas 300V和Atlas 300V Pro。
-
-### 1.3 支持的版本
-
-  | MxVision版本  | CANN版本  | Driver/Firmware版本 |
-  | --------- | ------------------ | -------------- | 
-  | 6.0.RC2 | 8.0.RC2   |  24.1.RC2  | 
-  | 6.0.RC3 | 8.0.RC3   |  24.1.RC3  | 
-
-### 1.4 三方依赖
-
-本项目除了依赖昇腾Driver、Firmware、CANN和MxVision及其要求的配套软件外，还需额外依赖以下软件：
-
-| 软件名称   | 版本   |
-|--------| ------ |
-| ffmpeg | 3.4.11 |
-
-* ffmpeg需要下载源码、手动编译。请用户参考ffmpeg官网及相关网络教程进行操作。
-
-### 1.5 代码目录结构说明
-
-本项目目录如下图所示：
-
-```
-├── aipp_yolov5.cfg
-├── BlockingQueue
-│  └── BlockingQueue.h
-├── ConfigParser    # 配置文件解析类
-│   ├── ConfigParser.cpp
-│   └── ConfigParser.h
-├── FrameAnalyzer       # 视频帧分析类
-│   ├── FrameAnalyzer.cpp
-│   └── FrameAnalyzer.h
-├── main.cpp
-├── README.md
-├── CMakeLists.txt
-├── setup.config
-└── VideoDecoder     # 视频解码类
-    ├── VideoDecoder.cpp
-    └── VideoDecoder.h
-```
-## 2 设置环境变量
-
-在执行后续步骤前，需要设置环境变量：
-
-
-
-```bash
-# 执行环境变量脚本使环境变量生效
-. ${ascend-toolkit-path}/set_env.sh
-. ${mxVision-path}/set_env.sh
-export FFMPEG_PATH=${ffmpeg-path}
-export LD_LIBRARY_PATH=${ffmpeg-lib-path}:$LD_LIBRARY_PATH
-# mxVision: mxVision安装路径
-# ascend-toolkit-path: CANN安装路径
-# ffmpeg-path: ffmpeg安装路径，通常为/usr/local/ffmpeg
-# ffmpeg-lib-path: ffmpeg的lib库安装路径，通常为/usr/local/ffmpeg/lib
-```
-## 3 准备模型
-步骤1 下载模型相关文件 
-
-根据[链接](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/FireDetection/models.zip)下载并解压得到firedetection.onnx文件，并放在项目根目录下。
-
-步骤2 转换模型格式
-进入到项目根目录下，将onnx格式模型转换为om格式模型(--soc_version的参数需根据实际NPU型号设置，Atlas 300V和Atlas 300V Pro设备下该参数为Ascend310P3)。
-
-       atc --model=./firedetection.onnx --framework=5 --output=./firedetection --input_format=NCHW --input_shape="images:1,3,640,640"  --out_nodes="Transpose_217:0;Transpose_233:0;Transpose_249:0"  --enable_small_channel=1 --insert_op_conf=./aipp_yolov5.cfg --soc_version=Ascend310P3 --log=info
-
-##  4 编译与运行
-步骤1 编译
-
-- 在项目根目录创建cmakeDir目录并进入该目录。
-- 执行cmake.. && make编译项目。编译的二进制文件main保存在项目根目录下。
-
-步骤2 设置配置项
-
-在setup.config文件中设置配置项，配置项含义如下表所示：
-
-|      配置项字段      | 配置项含义           |
-|:---------------:|-----------------|
-|    videoPath    | 用于火灾识别的视频文件路径   |
-|    modelPath    | om模型的路径         |
-|    deviceId     | 运行服务时使用的NPU设备编号 |
-| skipFrameNumber | 指定两次推理的帧间隔数量    |
-| videoSavedPath  | 指定编码后视频保存的文件路径  |
-|      width      | 用于火灾识别的视频文件的宽度  |
-|     height      | 用于火灾识别的视频文件的高度  |
-
-
-*deviceId需为整数，取值范围为[0, NPU设备个数-1]，`npu-smi info` 命令可以查看NPU设备个数；skipFrameNumber需为整数，建议根据实际业务需求设置，推荐设置为3；width和height需为整数，取值范围为[128, 4096]；videoPath所指定的视频文件需为H264编码；videoSavedPath所指定的文件每次服务启动时会被覆盖重写。
-
-步骤3 运行高速公路火灾识别服务
-
-进入项目根目录，执行如下指令：
-
-      ./main
-火灾检测结果在标准输出中体现；编码视频文件保存在配置文件指定的路径下。
-
-步骤4 停止高速公路火灾识别服务
-停止服务有如下两种方式：
-
-- 视频文件分析完毕后可自动停止服务。
-- 命令行输入Ctrl+C组合键可手动停止服务。
-
-步骤5 查看结果
-
-用户可在标准输出中查看火灾检测结果，在配置项videoSavedPath所指定的文件中查看视频编码结果。
-
-##  5 常见问题
-### 5.1 模型加载失败问题
-问题描述：模型路径正常，但是运行时提示模型加载错误。
-
-解决方案：排查模型路径中是否包含加号等特殊符号。如有，则需要将特殊符号去掉。
-
-### 5.2 模型转换失败问题
-问题描述：模型转换失败，提示模型路径包含非法字符或提示NumPy版本不匹配。
-
-解决方案：1.若提示模型路径包含非法字符，则检查模型路径中是否包含非法字符（如+、-等特殊符号）、修改相关目录名或文件名，从而使得模型路径中不包含非法字符；
-2.若提示NumPy版本不匹配，则检查NumPy版本是否过高，建议安装1.23.5版本的NumPy供模型转换工具调用。
-
+# 基于mxBase的高速公路车辆火灾识别(C++)
+
+## 1 介绍
+
+### 1.1 简介
+高速公路车辆火灾识别基于 mxVision SDK 开发，在 Atlas 300V、Atlas 300V Pro 上进行目标检测。项目主要流程为：通过ffmpeg打开本地视频文件、模拟视频流，然后进行视频解码，解码结果经过模型推理进行火灾和烟雾检测，如果检测到烟雾和火灾则在日志中进行告警。解码后的视频图像会编码保存至指定位置。
+
+### 1.2 支持的产品
+支持Atlas 300V和Atlas 300V Pro。
+
+### 1.3 支持的版本
+
+  | MxVision版本  | CANN版本  | Driver/Firmware版本 |
+  | --------- | ------------------ | -------------- | 
+  | 6.0.RC2 | 8.0.RC2   |  24.1.RC2  | 
+  | 6.0.RC3 | 8.0.RC3   |  24.1.RC3  | 
+
+### 1.4 三方依赖
+
+本项目除了依赖昇腾Driver、Firmware、CANN和MxVision及其要求的配套软件外，还需额外依赖以下软件：
+
+| 软件名称   | 版本   |
+|--------| ------ |
+| ffmpeg | 3.4.11 |
+
+* ffmpeg需要下载源码、手动编译。请用户参考ffmpeg官网及相关网络教程进行操作。
+
+### 1.5 代码目录结构说明
+
+本项目目录如下图所示：
+
+```
+├── aipp_yolov5.cfg
+├── BlockingQueue
+│  └── BlockingQueue.h
+├── ConfigParser    # 配置文件解析类
+│   ├── ConfigParser.cpp
+│   └── ConfigParser.h
+├── FrameAnalyzer       # 视频帧分析类
+│   ├── FrameAnalyzer.cpp
+│   └── FrameAnalyzer.h
+├── main.cpp
+├── README.md
+├── CMakeLists.txt
+├── setup.config
+└── VideoDecoder     # 视频解码类
+    ├── VideoDecoder.cpp
+    └── VideoDecoder.h
+```
+## 2 设置环境变量
+
+在执行后续步骤前，需要设置环境变量：
+
+
+
+```bash
+# 执行环境变量脚本使环境变量生效
+. ${ascend-toolkit-path}/set_env.sh
+. ${mxVision-path}/set_env.sh
+export FFMPEG_PATH=${ffmpeg-path}
+export LD_LIBRARY_PATH=${ffmpeg-lib-path}:$LD_LIBRARY_PATH
+# mxVision: mxVision安装路径
+# ascend-toolkit-path: CANN安装路径
+# ffmpeg-path: ffmpeg安装路径，通常为/usr/local/ffmpeg
+# ffmpeg-lib-path: ffmpeg的lib库安装路径，通常为/usr/local/ffmpeg/lib
+```
+## 3 准备模型
+步骤1 下载模型相关文件 
+
+根据[链接](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/FireDetection/models.zip)下载并解压得到firedetection.onnx文件，并放在项目根目录下。
+
+步骤2 转换模型格式
+进入到项目根目录下，将onnx格式模型转换为om格式模型(--soc_version的参数需根据实际NPU型号设置，Atlas 300V和Atlas 300V Pro设备下该参数为Ascend310P3)。
+
+       atc --model=./firedetection.onnx --framework=5 --output=./firedetection --input_format=NCHW --input_shape="images:1,3,640,640"  --out_nodes="Transpose_217:0;Transpose_233:0;Transpose_249:0"  --enable_small_channel=1 --insert_op_conf=./aipp_yolov5.cfg --soc_version=Ascend310P3 --log=info
+
+##  4 编译与运行
+步骤1 编译
+
+- 在项目根目录创建cmakeDir目录并进入该目录。
+- 执行cmake.. && make编译项目。编译的二进制文件main保存在项目根目录下。
+
+步骤2 设置配置项
+
+在setup.config文件中设置配置项，配置项含义如下表所示：
+
+|      配置项字段      | 配置项含义           |
+|:---------------:|-----------------|
+|    videoPath    | 用于火灾识别的视频文件路径   |
+|    modelPath    | om模型的路径         |
+|    deviceId     | 运行服务时使用的NPU设备编号 |
+| skipFrameNumber | 指定两次推理的帧间隔数量    |
+| videoSavedPath  | 指定编码后视频保存的文件路径  |
+|      width      | 用于火灾识别的视频文件的宽度  |
+|     height      | 用于火灾识别的视频文件的高度  |
+
+
+*deviceId需为整数，取值范围为[0, NPU设备个数-1]，`npu-smi info` 命令可以查看NPU设备个数；skipFrameNumber需为整数，建议根据实际业务需求设置，推荐设置为3；width和height需为整数，取值范围为[128, 4096]；videoPath所指定的视频文件需为H264编码；videoSavedPath所指定的文件每次服务启动时会被覆盖重写。
+
+步骤3 运行高速公路火灾识别服务
+
+进入项目根目录，执行如下指令：
+
+      ./main
+火灾检测结果在标准输出中体现；编码视频文件保存在配置文件指定的路径下。
+
+步骤4 停止高速公路火灾识别服务
+停止服务有如下两种方式：
+
+- 视频文件分析完毕后可自动停止服务。
+- 命令行输入Ctrl+C组合键可手动停止服务。
+
+步骤5 查看结果
+
+用户可在标准输出中查看火灾检测结果，在配置项videoSavedPath所指定的文件中查看视频编码结果。
+
+##  5 常见问题
+### 5.1 模型加载失败问题
+问题描述：模型路径正常，但是运行时提示模型加载错误。
+
+解决方案：排查模型路径中是否包含加号等特殊符号。如有，则需要将特殊符号去掉。
+
+### 5.2 模型转换失败问题
+问题描述：模型转换失败，提示模型路径包含非法字符或提示NumPy版本不匹配。
+
+解决方案：1.若提示模型路径包含非法字符，则检查模型路径中是否包含非法字符（如+、-等特殊符号）、修改相关目录名或文件名，从而使得模型路径中不包含非法字符；
+2.若提示NumPy版本不匹配，则检查NumPy版本是否过高，建议安装1.23.5版本的NumPy供模型转换工具调用。
+
diff --git a/contrib/FireDetection/c++/VideoDecoder/VideoDecoder.cpp b/mxVision/mxVision-referenceapps/FireDetection/c++/VideoDecoder/VideoDecoder.cpp
similarity index 97%
rename from contrib/FireDetection/c++/VideoDecoder/VideoDecoder.cpp
rename to mxVision/mxVision-referenceapps/FireDetection/c++/VideoDecoder/VideoDecoder.cpp
index 7e929d5c9430d524a9192be411ee8b980ea96a67..fb24e0fdfe734f4313cfd40997db7227de28f13b 100644
--- a/contrib/FireDetection/c++/VideoDecoder/VideoDecoder.cpp
+++ b/mxVision/mxVision-referenceapps/FireDetection/c++/VideoDecoder/VideoDecoder.cpp
@@ -1,128 +1,128 @@
-/*
- * Copyright(C) 2024. Huawei Technologies Co.,Ltd. All rights reserved.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-#include <sys/time.h>
-#include <iostream>
-#include <sstream>
-#include "MxBase/Log/Log.h"
-#include "./VideoDecoder.h"
-
-using namespace std;
-using namespace MxBase;
-
-namespace ascendVideoDecoder {
-namespace {
-    const double ONE_SCECOND = 1000.;
-}
-
-VideoDecoder::VideoDecoder() {}
-
-VideoDecoder::~VideoDecoder() {}
-
-APP_ERROR VideoDecoder::ParseConfig(const ConfigParser &configParser)
-{
-    std::string itemCfgStr = {};
-    itemCfgStr = std::string("deviceId");
-    APP_ERROR ret = configParser.GetIntValue(itemCfgStr, deviceId_);
-    if (ret != APP_ERR_OK) {
-        LogError << "Get deviceId from config file fail.";
-        return APP_ERR_COMM_FAILURE;
-    }
-    LogDebug << "deviceId=" << deviceId_;
-    return ret;
-}
-
-APP_ERROR VideoDecoder::Init(const ConfigParser &configParser, const uint32_t streamWidthMax,
-                             const uint32_t streamHeightMax)
-                             {
-    LogDebug << "VideoDecoder[" << instanceId_ << "]: Begin to init instance.";
-    APP_ERROR ret = ParseConfig(configParser);
-    if (ret != APP_ERR_OK) {
-        LogError << "VideoDecoder[" << instanceId_ << "]: Fail to parse config params." << GetAppErrCodeInfo(ret) <<
-                 ".";
-        return ret;
-    }
-    // Init the vdec
-    streamWidthMax_ = streamWidthMax;
-    streamHeightMax_ = streamHeightMax;
-    MxBase::VideoDecodeConfig config;
-    MxBase::VideoDecodeCallBack callbackFunc = VideoDecoderCallback;
-    config.callbackFunc = callbackFunc;
-    config.height = streamHeightMax_;
-    config.width = streamWidthMax_;
-    config.inputVideoFormat = videoType_;
-    config.outputImageFormat = MxBase::ImageFormat::YUV_SP_420;
-    try {
-        videoDecoder_ = std::make_shared<MxBase::VideoDecoder>(config, deviceId_, instanceId_);
-    } catch (const std::runtime_error &e) {
-        LogError << "VideoDecoder[" << instanceId_ << "]: mxbs videoDecoder init failed.";
-        return APP_ERR_COMM_FAILURE;
-    }
-
-    LogDebug << "VideoDecoder[" << instanceId_ << "]: VideoDecoder Init OK.";
-    return APP_ERR_OK;
-}
-
-void VideoDecoder::SetInstanceId(int instanceId)
-{
-    instanceId_ = instanceId;
-}
-
-APP_ERROR VideoDecoder::Process(std::shared_ptr<FrameImage> frameImage, std::shared_ptr<BlockingQueue<std::shared_ptr<void>>>& output)
-{
-    LogDebug << "VideoDecoder[" << instanceId_ << "]: VideoDecoder: process start.";
-    gettimeofday(&vdecStartTime, nullptr);
-    APP_ERROR ret = videoDecoder_->Decode(frameImage->image.GetData(), frameImage->image.GetDataSize(),
-                                          frameImage->frameId, output.get());
-    gettimeofday(&vdecEndTime, nullptr);
-    double costMs = (vdecEndTime.tv_sec - vdecStartTime.tv_sec) * ONE_SCECOND +
-            (vdecEndTime.tv_usec - vdecStartTime.tv_usec) / ONE_SCECOND;
-    LogDebug << "VideoDecoder[" << instanceId_ << "]: VideoDecoder: Decode " << costMs << "ms";
-    if (ret != APP_ERR_OK) {
-        LogError << "VideoDecoder[" << instanceId_ << "]: mxbs videoDecode failed, ret=" << ret;
-    }
-    return APP_ERR_OK;
-}
-
-APP_ERROR VideoDecoder::VideoDecoderCallback(MxBase::Image &decodedImage, uint32_t channelId, uint32_t frameId,
-                                             void *userData)
-                                             {
-    LogDebug << "VideoDecoder[" << channelId << "]: VideoDecoderCallback end, frameId:" << frameId;
-    
-    FrameImage frameImage;
-    frameImage.image = decodedImage;
-    frameImage.channelId = channelId;
-    frameImage.frameId = frameId;
-
-    std::shared_ptr<FrameImage> pFrame = std::make_shared<FrameImage>(frameImage);
-
-    BlockingQueue<std::shared_ptr<FrameImage>>* decodedVec = static_cast<BlockingQueue<std::shared_ptr<FrameImage>>*>(userData);
-    if (decodedVec == nullptr) {
-        LogError << "VideoDecoderCallback: decodedVec has been released.";
-        return APP_ERR_DVPP_INVALID_FORMAT;
-    }
-
-    decodedVec->Push(pFrame, true);
-    return APP_ERR_OK;
-}
-
-APP_ERROR VideoDecoder::DeInit(void)
-{
-    LogDebug << "VideoDecoder [" << instanceId_ << "]: Begin to deinit";
-    videoDecoder_.reset();
-    LogDebug << "VideoDecoder [" << instanceId_ << "]: Deinit success.";
-    return APP_ERR_OK;
-}
+/*
+ * Copyright(C) 2024. Huawei Technologies Co.,Ltd. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#include <sys/time.h>
+#include <iostream>
+#include <sstream>
+#include "MxBase/Log/Log.h"
+#include "./VideoDecoder.h"
+
+using namespace std;
+using namespace MxBase;
+
+namespace ascendVideoDecoder {
+namespace {
+    const double ONE_SCECOND = 1000.;
+}
+
+VideoDecoder::VideoDecoder() {}
+
+VideoDecoder::~VideoDecoder() {}
+
+APP_ERROR VideoDecoder::ParseConfig(const ConfigParser &configParser)
+{
+    std::string itemCfgStr = {};
+    itemCfgStr = std::string("deviceId");
+    APP_ERROR ret = configParser.GetIntValue(itemCfgStr, deviceId_);
+    if (ret != APP_ERR_OK) {
+        LogError << "Get deviceId from config file fail.";
+        return APP_ERR_COMM_FAILURE;
+    }
+    LogDebug << "deviceId=" << deviceId_;
+    return ret;
+}
+
+APP_ERROR VideoDecoder::Init(const ConfigParser &configParser, const uint32_t streamWidthMax,
+                             const uint32_t streamHeightMax)
+                             {
+    LogDebug << "VideoDecoder[" << instanceId_ << "]: Begin to init instance.";
+    APP_ERROR ret = ParseConfig(configParser);
+    if (ret != APP_ERR_OK) {
+        LogError << "VideoDecoder[" << instanceId_ << "]: Fail to parse config params." << GetAppErrCodeInfo(ret) <<
+                 ".";
+        return ret;
+    }
+    // Init the vdec
+    streamWidthMax_ = streamWidthMax;
+    streamHeightMax_ = streamHeightMax;
+    MxBase::VideoDecodeConfig config;
+    MxBase::VideoDecodeCallBack callbackFunc = VideoDecoderCallback;
+    config.callbackFunc = callbackFunc;
+    config.height = streamHeightMax_;
+    config.width = streamWidthMax_;
+    config.inputVideoFormat = videoType_;
+    config.outputImageFormat = MxBase::ImageFormat::YUV_SP_420;
+    try {
+        videoDecoder_ = std::make_shared<MxBase::VideoDecoder>(config, deviceId_, instanceId_);
+    } catch (const std::runtime_error &e) {
+        LogError << "VideoDecoder[" << instanceId_ << "]: mxbs videoDecoder init failed.";
+        return APP_ERR_COMM_FAILURE;
+    }
+
+    LogDebug << "VideoDecoder[" << instanceId_ << "]: VideoDecoder Init OK.";
+    return APP_ERR_OK;
+}
+
+void VideoDecoder::SetInstanceId(int instanceId)
+{
+    instanceId_ = instanceId;
+}
+
+APP_ERROR VideoDecoder::Process(std::shared_ptr<FrameImage> frameImage, std::shared_ptr<BlockingQueue<std::shared_ptr<void>>>& output)
+{
+    LogDebug << "VideoDecoder[" << instanceId_ << "]: VideoDecoder: process start.";
+    gettimeofday(&vdecStartTime, nullptr);
+    APP_ERROR ret = videoDecoder_->Decode(frameImage->image.GetData(), frameImage->image.GetDataSize(),
+                                          frameImage->frameId, output.get());
+    gettimeofday(&vdecEndTime, nullptr);
+    double costMs = (vdecEndTime.tv_sec - vdecStartTime.tv_sec) * ONE_SCECOND +
+            (vdecEndTime.tv_usec - vdecStartTime.tv_usec) / ONE_SCECOND;
+    LogDebug << "VideoDecoder[" << instanceId_ << "]: VideoDecoder: Decode " << costMs << "ms";
+    if (ret != APP_ERR_OK) {
+        LogError << "VideoDecoder[" << instanceId_ << "]: mxbs videoDecode failed, ret=" << ret;
+    }
+    return APP_ERR_OK;
+}
+
+APP_ERROR VideoDecoder::VideoDecoderCallback(MxBase::Image &decodedImage, uint32_t channelId, uint32_t frameId,
+                                             void *userData)
+                                             {
+    LogDebug << "VideoDecoder[" << channelId << "]: VideoDecoderCallback end, frameId:" << frameId;
+    
+    FrameImage frameImage;
+    frameImage.image = decodedImage;
+    frameImage.channelId = channelId;
+    frameImage.frameId = frameId;
+
+    std::shared_ptr<FrameImage> pFrame = std::make_shared<FrameImage>(frameImage);
+
+    BlockingQueue<std::shared_ptr<FrameImage>>* decodedVec = static_cast<BlockingQueue<std::shared_ptr<FrameImage>>*>(userData);
+    if (decodedVec == nullptr) {
+        LogError << "VideoDecoderCallback: decodedVec has been released.";
+        return APP_ERR_DVPP_INVALID_FORMAT;
+    }
+
+    decodedVec->Push(pFrame, true);
+    return APP_ERR_OK;
+}
+
+APP_ERROR VideoDecoder::DeInit(void)
+{
+    LogDebug << "VideoDecoder [" << instanceId_ << "]: Begin to deinit";
+    videoDecoder_.reset();
+    LogDebug << "VideoDecoder [" << instanceId_ << "]: Deinit success.";
+    return APP_ERR_OK;
+}
 }
\ No newline at end of file
diff --git a/contrib/FireDetection/c++/VideoDecoder/VideoDecoder.h b/mxVision/mxVision-referenceapps/FireDetection/c++/VideoDecoder/VideoDecoder.h
similarity index 97%
rename from contrib/FireDetection/c++/VideoDecoder/VideoDecoder.h
rename to mxVision/mxVision-referenceapps/FireDetection/c++/VideoDecoder/VideoDecoder.h
index 884dc87029f720828dc595f807af4ffb23c3b979..d3c329aca0d29babbe39aec1a3ae318ed136358a 100644
--- a/contrib/FireDetection/c++/VideoDecoder/VideoDecoder.h
+++ b/mxVision/mxVision-referenceapps/FireDetection/c++/VideoDecoder/VideoDecoder.h
@@ -1,71 +1,71 @@
-/*
- * Copyright(C) 2024. Huawei Technologies Co.,Ltd. All rights reserved.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#ifndef MINDX_SDK_SAMPLE_VIDEODECODER_H
-#define MINDX_SDK_SAMPLE_VIDEODECODER_H
-
-#include <time.h>
-#include <memory>
-#include <stdint.h>
-#include "acl/acl.h"
-#include "MxBase/E2eInfer/VideoDecoder/VideoDecoder.h"
-#include "MxBase/E2eInfer/ImageProcessor/ImageProcessor.h"
-#include "../ConfigParser/ConfigParser.h"
-#include "../BlockingQueue/BlockingQueue.h"
-
-using namespace MxBase;
-
-namespace ascendVideoDecoder {
-struct FrameImage {
-    MxBase::Image image;                 // Video Image Class
-    uint32_t frameId = 0;        // Video Frame Index
-    uint32_t channelId = 0;      // Video Channel Index
-};
-
-class VideoDecoder {
-public:
-    VideoDecoder();
-
-    ~VideoDecoder();
-
-    APP_ERROR Init(const ConfigParser &configParser, const uint32_t streamWidthMax, const uint32_t streamHeightMax);
-
-    APP_ERROR DeInit(void);
-
-    void SetInstanceId(int instanceId);
-
-    APP_ERROR Process(std::shared_ptr<FrameImage> frameImage, std::shared_ptr<BlockingQueue<std::shared_ptr<void>>>& output);
-
-private:
-    APP_ERROR ParseConfig(const ConfigParser &configParser);
-
-    static APP_ERROR VideoDecoderCallback(MxBase::Image &decodedImage, uint32_t channelId, uint32_t frameId,
-                                          void *userData);
-
-private:
-    uint32_t streamWidthMax_ = 1920;
-    uint32_t streamHeightMax_ = 1080;
-    uint32_t skipInterval_ = 3;
-    int32_t deviceId_ = -1;
-    int instanceId_ = -1;
-    std::string videoFormat_ = "H264";
-    struct timeval vdecStartTime = {0};
-    struct timeval vdecEndTime = {0};
-    MxBase::StreamFormat videoType_ = MxBase::StreamFormat::H264_MAIN_LEVEL;
-    std::shared_ptr<MxBase::VideoDecoder> videoDecoder_ = nullptr;
-};
-}
-#endif
+/*
+ * Copyright(C) 2024. Huawei Technologies Co.,Ltd. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef MINDX_SDK_SAMPLE_VIDEODECODER_H
+#define MINDX_SDK_SAMPLE_VIDEODECODER_H
+
+#include <time.h>
+#include <memory>
+#include <stdint.h>
+#include "acl/acl.h"
+#include "MxBase/E2eInfer/VideoDecoder/VideoDecoder.h"
+#include "MxBase/E2eInfer/ImageProcessor/ImageProcessor.h"
+#include "../ConfigParser/ConfigParser.h"
+#include "../BlockingQueue/BlockingQueue.h"
+
+using namespace MxBase;
+
+namespace ascendVideoDecoder {
+struct FrameImage {
+    MxBase::Image image;                 // Video Image Class
+    uint32_t frameId = 0;        // Video Frame Index
+    uint32_t channelId = 0;      // Video Channel Index
+};
+
+class VideoDecoder {
+public:
+    VideoDecoder();
+
+    ~VideoDecoder();
+
+    APP_ERROR Init(const ConfigParser &configParser, const uint32_t streamWidthMax, const uint32_t streamHeightMax);
+
+    APP_ERROR DeInit(void);
+
+    void SetInstanceId(int instanceId);
+
+    APP_ERROR Process(std::shared_ptr<FrameImage> frameImage, std::shared_ptr<BlockingQueue<std::shared_ptr<void>>>& output);
+
+private:
+    APP_ERROR ParseConfig(const ConfigParser &configParser);
+
+    static APP_ERROR VideoDecoderCallback(MxBase::Image &decodedImage, uint32_t channelId, uint32_t frameId,
+                                          void *userData);
+
+private:
+    uint32_t streamWidthMax_ = 1920;
+    uint32_t streamHeightMax_ = 1080;
+    uint32_t skipInterval_ = 3;
+    int32_t deviceId_ = -1;
+    int instanceId_ = -1;
+    std::string videoFormat_ = "H264";
+    struct timeval vdecStartTime = {0};
+    struct timeval vdecEndTime = {0};
+    MxBase::StreamFormat videoType_ = MxBase::StreamFormat::H264_MAIN_LEVEL;
+    std::shared_ptr<MxBase::VideoDecoder> videoDecoder_ = nullptr;
+};
+}
+#endif
diff --git a/contrib/FireDetection/c++/aipp_yolov5.cfg b/mxVision/mxVision-referenceapps/FireDetection/c++/aipp_yolov5.cfg
similarity index 95%
rename from contrib/FireDetection/c++/aipp_yolov5.cfg
rename to mxVision/mxVision-referenceapps/FireDetection/c++/aipp_yolov5.cfg
index be7181c95340192303c76a688362c26b1293f7ad..f5dc2568e0386519eb9581d3017999885c34cdb2 100644
--- a/contrib/FireDetection/c++/aipp_yolov5.cfg
+++ b/mxVision/mxVision-referenceapps/FireDetection/c++/aipp_yolov5.cfg
@@ -1,26 +1,26 @@
-aipp_op { 
-    aipp_mode : static
-    related_input_rank : 0
-    input_format : YUV420SP_U8
-
-    src_image_size_w : 640
-    src_image_size_h : 640
-    crop : false
-    csc_switch : true
-    rbuv_swap_switch : false
-    matrix_r0c0 : 256
-    matrix_r0c1 : 0
-    matrix_r0c2 : 359
-    matrix_r1c0 : 256
-    matrix_r1c1 : -88
-    matrix_r1c2 : -183
-    matrix_r2c0 : 256
-    matrix_r2c1 : 454
-    matrix_r2c2 : 0
-    input_bias_0 : 0
-    input_bias_1 : 128
-    input_bias_2 : 128
-    var_reci_chn_0 : 0.0039216
-    var_reci_chn_1 : 0.0039216
-    var_reci_chn_2 : 0.0039216
+aipp_op { 
+    aipp_mode : static
+    related_input_rank : 0
+    input_format : YUV420SP_U8
+
+    src_image_size_w : 640
+    src_image_size_h : 640
+    crop : false
+    csc_switch : true
+    rbuv_swap_switch : false
+    matrix_r0c0 : 256
+    matrix_r0c1 : 0
+    matrix_r0c2 : 359
+    matrix_r1c0 : 256
+    matrix_r1c1 : -88
+    matrix_r1c2 : -183
+    matrix_r2c0 : 256
+    matrix_r2c1 : 454
+    matrix_r2c2 : 0
+    input_bias_0 : 0
+    input_bias_1 : 128
+    input_bias_2 : 128
+    var_reci_chn_0 : 0.0039216
+    var_reci_chn_1 : 0.0039216
+    var_reci_chn_2 : 0.0039216
 }
\ No newline at end of file
diff --git a/contrib/FireDetection/c++/main.cpp b/mxVision/mxVision-referenceapps/FireDetection/c++/main.cpp
similarity index 100%
rename from contrib/FireDetection/c++/main.cpp
rename to mxVision/mxVision-referenceapps/FireDetection/c++/main.cpp
diff --git a/contrib/FireDetection/c++/setup.config b/mxVision/mxVision-referenceapps/FireDetection/c++/setup.config
similarity index 90%
rename from contrib/FireDetection/c++/setup.config
rename to mxVision/mxVision-referenceapps/FireDetection/c++/setup.config
index 3797a7826566e9b78c25ad9eab66b1902338a245..7f74f58669b8c57a618386f568b5ba3fd180d6c5 100644
--- a/contrib/FireDetection/c++/setup.config
+++ b/mxVision/mxVision-referenceapps/FireDetection/c++/setup.config
@@ -1,21 +1,21 @@
-# configuration for the fire detection task 
-
-
-videoPath = ./fireDetection.264
-
-modelPath = ./firedetection.om
-
-deviceId = 0
-
-skipFrameNumber = 1
-
-videoSavedPath = ./output.h264
-
-width = 1920
-
-height = 1080
-
-
-
-
-
+# configuration for the fire detection task 
+
+
+videoPath = ./fireDetection.264
+
+modelPath = ./firedetection.om
+
+deviceId = 0
+
+skipFrameNumber = 1
+
+videoSavedPath = ./output.h264
+
+width = 1920
+
+height = 1080
+
+
+
+
+
diff --git a/contrib/FireDetection/python/README.md b/mxVision/mxVision-referenceapps/FireDetection/python/README.md
similarity index 97%
rename from contrib/FireDetection/python/README.md
rename to mxVision/mxVision-referenceapps/FireDetection/python/README.md
index 880d0637b2c6af3e97d04ae0e0c914b790dbcbbd..bb60223af6c1a35669d079fcefa87bd3c473c80f 100644
--- a/contrib/FireDetection/python/README.md
+++ b/mxVision/mxVision-referenceapps/FireDetection/python/README.md
@@ -1,106 +1,106 @@
-# 基于mxBase的高速公路车辆火灾识别(Python)
-
-## 1 介绍
-
-### 1.1 简介
-高速公路车辆火灾识别基于mxVision SDK 开发，在 Atlas 300V、Atlas 300V Pro 上进行目标检测。项目主要流程为：通过av模块打开本地视频文件、模拟视频流，然后进行视频解码，解码结果经过模型推理进行火灾和烟雾检测，如果检测到烟雾和火灾则在日志中进行告警。解码后的视频图像会再次编码保存至指定位置。
-
-### 1.2 支持的产品
-支持Atlas 300V和Atlas 300V Pro。
-
-### 1.3 支持的版本
-
-  | MxVision版本  | CANN版本  | Driver/Firmware版本 |
-  | --------- | ------------------ | -------------- | 
-  | 6.0.RC2 | 8.0.RC2   |  24.1.RC2  | 
-  | 6.0.RC3 | 8.0.RC3   |  24.1.RC3  | 
-
-### 1.4 三方依赖
-本项目除了依赖昇腾Driver、Firmware、CANN和mxVision及其要求的配套软件外，还需额外依赖以下python软件：
-
-| 软件名称 | 版本   |
-| -------- | ------ |
-| av | 10.0.0 |
-| numpy | 1.23.5 |
-
-### 1.5 代码目录结构说明
-
-本项目目录如下图所示：
-
-```
-├── frame_analyzer.py  // 视频帧分析
-├── infer_config.json  // 服务配置
-├── aipp_yolov5.cfg
-├── utils.py  
-├── main.py  
-└── README.md
-```
-
-## 2 设置环境变量
-
-在执行后续步骤前，需要设置环境变量：
-
-```bash
-# 执行环境变量脚本使环境变量生效
-. ${ascend-toolkit-path}/set_env.sh
-. ${mxVision-path}/set_env.sh
-# mxVision: mxVision安装路径
-# ascend-toolkit-path: CANN安装路径
-```
-
-## 3 准备模型
-### 步骤1 下载模型相关文件
-根据[链接](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/FireDetection/models.zip)下载并解压得到firedetection.onnx文件。
-
-###  步骤2 转换模型格式
-
-将onnx格式模型转换为om格式模型(--soc_version的参数需根据实际NPU型号设置，Atlas 300V和Atlas 300V Pro设备下该参数为Ascend310P3)。
-
-       atc --model=./firedetection.onnx --framework=5 --output=./firedetection --input_format=NCHW --input_shape="images:1,3,640,640"  --out_nodes="Transpose_217:0;Transpose_233:0;Transpose_249:0"  --enable_small_channel=1 --insert_op_conf=./aipp_yolov5.cfg --soc_version=Ascend310P3 --log=info
-
-##  4 运行
-### 步骤1 设置配置项
- 设置高速公路车辆火灾识别服务配置（修改infer_config.json文件） ，支持的配置项如下所示 ：
-
-|       配置项字段       | 配置项含义           |
-|:-----------------:|-----------------|
-|    video_path     | 用于火灾识别的视频文件路径   |
-|    model_path     | om模型的路径         |
-|     device_id     | 运行服务时使用的NPU设备编号 |
-| skip_frame_number | 指定两次推理的帧间隔数量    |
-| video_saved_path  | 指定编码后视频保存的文件路径  |
-|       width       | 用于火灾识别的视频文件的宽度  |
-|      height       | 用于火灾识别的视频文件的高度  |
-
-
-*device_id需为整数，取值范围为[0, NPU设备个数-1]，`npu-smi info` 命令可以查看NPU设备个数；skip_frame_number需为整数，建议根据实际业务需求设置，推荐设置为3；width和height需为整数，取值范围为[128, 4096]；video_path所指定的视频文件需为H264编码；video_saved_path所指定的文件每次服务启动时会被覆盖重写。
-
-### 步骤2 启动火灾检测服务
-
-      python3 main.py
-### 步骤3 停止高速公路火灾识别服务
-停止服务有如下两种方式：
-
-- 视频文件分析完毕后可自动停止服务。 
-- 命令行输入Ctrl+C组合键可手动停止服务。
-
-###  步骤4 查看结果
-
-用户可在标准输出中查看火灾检测结果，在配置项video_saved_path所指定的文件中查看视频编码结果。
-
-## 5 常见问题
-
-### 5.1 获取视频流问题
-问题描述：获取视频流失败。
-
-  解决方案：检查av库的版本是否为10.0.0。
-### 5.2 模型加载失败问题
-问题描述：模型路径正常，但是运行时提示模型加载错误。
-
-  解决方案：排查模型路径中是否包含加号等特殊符号。如有，则需要将特殊符号去掉。
-  
-### 5.3 模型转换失败问题
-问题描述：模型转换失败，提示模型路径包含非法字符或提示NumPy版本不匹配。
-
-解决方案：1.若提示模型路径包含非法字符，则检查模型路径中是否包含非法字符（如+、-等特殊符号）、修改相关目录名或文件名，从而使得模型路径中不包含非法字符；
+# 基于mxBase的高速公路车辆火灾识别(Python)
+
+## 1 介绍
+
+### 1.1 简介
+高速公路车辆火灾识别基于mxVision SDK 开发，在 Atlas 300V、Atlas 300V Pro 上进行目标检测。项目主要流程为：通过av模块打开本地视频文件、模拟视频流，然后进行视频解码，解码结果经过模型推理进行火灾和烟雾检测，如果检测到烟雾和火灾则在日志中进行告警。解码后的视频图像会再次编码保存至指定位置。
+
+### 1.2 支持的产品
+支持Atlas 300V和Atlas 300V Pro。
+
+### 1.3 支持的版本
+
+  | MxVision版本  | CANN版本  | Driver/Firmware版本 |
+  | --------- | ------------------ | -------------- | 
+  | 6.0.RC2 | 8.0.RC2   |  24.1.RC2  | 
+  | 6.0.RC3 | 8.0.RC3   |  24.1.RC3  | 
+
+### 1.4 三方依赖
+本项目除了依赖昇腾Driver、Firmware、CANN和mxVision及其要求的配套软件外，还需额外依赖以下python软件：
+
+| 软件名称 | 版本   |
+| -------- | ------ |
+| av | 10.0.0 |
+| numpy | 1.23.5 |
+
+### 1.5 代码目录结构说明
+
+本项目目录如下图所示：
+
+```
+├── frame_analyzer.py  // 视频帧分析
+├── infer_config.json  // 服务配置
+├── aipp_yolov5.cfg
+├── utils.py  
+├── main.py  
+└── README.md
+```
+
+## 2 设置环境变量
+
+在执行后续步骤前，需要设置环境变量：
+
+```bash
+# 执行环境变量脚本使环境变量生效
+. ${ascend-toolkit-path}/set_env.sh
+. ${mxVision-path}/set_env.sh
+# mxVision: mxVision安装路径
+# ascend-toolkit-path: CANN安装路径
+```
+
+## 3 准备模型
+### 步骤1 下载模型相关文件
+根据[链接](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/FireDetection/models.zip)下载并解压得到firedetection.onnx文件。
+
+###  步骤2 转换模型格式
+
+将onnx格式模型转换为om格式模型(--soc_version的参数需根据实际NPU型号设置，Atlas 300V和Atlas 300V Pro设备下该参数为Ascend310P3)。
+
+       atc --model=./firedetection.onnx --framework=5 --output=./firedetection --input_format=NCHW --input_shape="images:1,3,640,640"  --out_nodes="Transpose_217:0;Transpose_233:0;Transpose_249:0"  --enable_small_channel=1 --insert_op_conf=./aipp_yolov5.cfg --soc_version=Ascend310P3 --log=info
+
+##  4 运行
+### 步骤1 设置配置项
+ 设置高速公路车辆火灾识别服务配置（修改infer_config.json文件） ，支持的配置项如下所示 ：
+
+|       配置项字段       | 配置项含义           |
+|:-----------------:|-----------------|
+|    video_path     | 用于火灾识别的视频文件路径   |
+|    model_path     | om模型的路径         |
+|     device_id     | 运行服务时使用的NPU设备编号 |
+| skip_frame_number | 指定两次推理的帧间隔数量    |
+| video_saved_path  | 指定编码后视频保存的文件路径  |
+|       width       | 用于火灾识别的视频文件的宽度  |
+|      height       | 用于火灾识别的视频文件的高度  |
+
+
+*device_id需为整数，取值范围为[0, NPU设备个数-1]，`npu-smi info` 命令可以查看NPU设备个数；skip_frame_number需为整数，建议根据实际业务需求设置，推荐设置为3；width和height需为整数，取值范围为[128, 4096]；video_path所指定的视频文件需为H264编码；video_saved_path所指定的文件每次服务启动时会被覆盖重写。
+
+### 步骤2 启动火灾检测服务
+
+      python3 main.py
+### 步骤3 停止高速公路火灾识别服务
+停止服务有如下两种方式：
+
+- 视频文件分析完毕后可自动停止服务。 
+- 命令行输入Ctrl+C组合键可手动停止服务。
+
+###  步骤4 查看结果
+
+用户可在标准输出中查看火灾检测结果，在配置项video_saved_path所指定的文件中查看视频编码结果。
+
+## 5 常见问题
+
+### 5.1 获取视频流问题
+问题描述：获取视频流失败。
+
+  解决方案：检查av库的版本是否为10.0.0。
+### 5.2 模型加载失败问题
+问题描述：模型路径正常，但是运行时提示模型加载错误。
+
+  解决方案：排查模型路径中是否包含加号等特殊符号。如有，则需要将特殊符号去掉。
+  
+### 5.3 模型转换失败问题
+问题描述：模型转换失败，提示模型路径包含非法字符或提示NumPy版本不匹配。
+
+解决方案：1.若提示模型路径包含非法字符，则检查模型路径中是否包含非法字符（如+、-等特殊符号）、修改相关目录名或文件名，从而使得模型路径中不包含非法字符；
 2.若提示NumPy版本不匹配，则检查NumPy版本是否过高，建议安装1.23.5版本的NumPy供模型转换工具调用。
\ No newline at end of file
diff --git a/contrib/FireDetection/python/aipp_yolov5.cfg b/mxVision/mxVision-referenceapps/FireDetection/python/aipp_yolov5.cfg
similarity index 95%
rename from contrib/FireDetection/python/aipp_yolov5.cfg
rename to mxVision/mxVision-referenceapps/FireDetection/python/aipp_yolov5.cfg
index 4990f0d9c63f3a97efa422afb925d4eff484c06f..ad450a5e698982ef36c6de1ef51453ae6e7b66c4 100644
--- a/contrib/FireDetection/python/aipp_yolov5.cfg
+++ b/mxVision/mxVision-referenceapps/FireDetection/python/aipp_yolov5.cfg
@@ -1,26 +1,26 @@
-aipp_op { 
-    aipp_mode : static
-    related_input_rank : 0
-    input_format : YUV420SP_U8
-
-    src_image_size_w : 640
-    src_image_size_h : 640
-    crop : false
-    csc_switch : true
-    rbuv_swap_switch : false
-    matrix_r0c0 : 256
-    matrix_r0c1 : 0
-    matrix_r0c2 : 359
-    matrix_r1c0 : 256
-    matrix_r1c1 : -88
-    matrix_r1c2 : -183
-    matrix_r2c0 : 256
-    matrix_r2c1 : 454
-    matrix_r2c2 : 0
-    input_bias_0 : 0
-    input_bias_1 : 128
-    input_bias_2 : 128
-    var_reci_chn_0 : 0.0039216
-    var_reci_chn_1 : 0.0039216
-    var_reci_chn_2 : 0.0039216
-}
+aipp_op { 
+    aipp_mode : static
+    related_input_rank : 0
+    input_format : YUV420SP_U8
+
+    src_image_size_w : 640
+    src_image_size_h : 640
+    crop : false
+    csc_switch : true
+    rbuv_swap_switch : false
+    matrix_r0c0 : 256
+    matrix_r0c1 : 0
+    matrix_r0c2 : 359
+    matrix_r1c0 : 256
+    matrix_r1c1 : -88
+    matrix_r1c2 : -183
+    matrix_r2c0 : 256
+    matrix_r2c1 : 454
+    matrix_r2c2 : 0
+    input_bias_0 : 0
+    input_bias_1 : 128
+    input_bias_2 : 128
+    var_reci_chn_0 : 0.0039216
+    var_reci_chn_1 : 0.0039216
+    var_reci_chn_2 : 0.0039216
+}
diff --git a/contrib/FireDetection/python/frame_analyzer.py b/mxVision/mxVision-referenceapps/FireDetection/python/frame_analyzer.py
similarity index 97%
rename from contrib/FireDetection/python/frame_analyzer.py
rename to mxVision/mxVision-referenceapps/FireDetection/python/frame_analyzer.py
index e780c9b63763b25289d53fce30751f61e113b943..f0dfa1b338704b2d0b9d3bd91137e82d0f372b1e 100644
--- a/contrib/FireDetection/python/frame_analyzer.py
+++ b/mxVision/mxVision-referenceapps/FireDetection/python/frame_analyzer.py
@@ -1,143 +1,143 @@
-import os
-import numpy as np
-from mindx.sdk import base
-from mindx.sdk.base import Tensor, Model, Size, Rect, log, ImageProcessor, post, Point
-from utils import file_base_check, logger
-
-MODEL_INPUT_HEIGHT = 640
-MODEL_INPUT_WIDTH = 640
-MODEL_SHAPE = Size(MODEL_INPUT_HEIGHT, MODEL_INPUT_WIDTH)
-ANCHORS_SIZE = [[[10, 13], [16, 30], [33, 23]], [[30, 61], [62, 45], [59, 119]], [[116, 90], [156, 198], [373, 326]]]
-NMS_THRESHOLD = 0.6
-INDEX_TO_CLASS = {0: "Fire", 1: "Smoke"}
-
-
-def sigmoid(x):
-    return 1 / (1 + np.exp(-x))
-
-
-def nms(dets, thresh):
-    x1 = dets[:, 0]  # xmin
-    y1 = dets[:, 1]  # ymin
-    x2 = dets[:, 2]  # xmax
-    y2 = dets[:, 3]  # ymax
-    scores = dets[:, 4]  # confidence
-
-    areas = (x2 - x1 + 1) * (y2 - y1 + 1)  # 每个bounding box的面积
-    order = scores.argsort()[::-1]  # 按置信度降序排序
-
-    keep = []  # 用来保存最后留下来的bounding box
-    while order.size > 0:
-        i = order[0]  # 置信度最高的bounding box的index
-        keep.append(i)  # 添加本次置信度最高的bounding box的index
-
-        # 当前bbox和剩下bbox之间的交叉区域
-        xx1 = np.maximum(x1[i], x1[order[1:]])
-        yy1 = np.maximum(y1[i], y1[order[1:]])
-        xx2 = np.minimum(x2[i], x2[order[1:]])
-        yy2 = np.minimum(y2[i], y2[order[1:]])
-
-        # 计算交叉区域的面积
-        w = np.maximum(0.0, xx2 - xx1 + 1)
-        h = np.maximum(0.0, yy2 - yy1 + 1)
-        inter = w * h
-
-        # 交叉区域面积 / (bbox + 某区域面积 - 交叉区域面积)
-        ovr = inter / (areas[i] + areas[order[1:]] - inter)
-
-        # 保留交集小于一定阈值的bounding box
-        inds = np.where(ovr <= thresh)[0]
-        order = order[inds + 1]
-    return keep
-
-
-class FrameAnalyzeModel:
-    def __init__(self, model_path, device_id):
-        file_base_check(os.path.realpath(model_path))
-        self.model = Model(os.path.realpath(model_path), device_id)
-        self.image_processor = ImageProcessor(device_id)
-
-    @staticmethod
-    def __decode_output(output_tensors):
-        output_np_tensors = []
-        for tensor in output_tensors:
-            tensor.to_host()
-            output_np_tensors.append(np.array(tensor))
-        bounding_box_array = []
-        for layer_idx, tensor in enumerate(output_np_tensors):
-            batch, anchor_num, height, width, box_para = tensor.shape
-            for height_idx in range(height):
-                for width_idx in range(width):
-                    for anchor_idx in range(anchor_num):
-                        # Filter unimportant anchor and determine the class of anchor according to the given threshold
-                        objectness = sigmoid(tensor[0, anchor_idx, height_idx, width_idx, 4])
-                        if objectness < 0.1:
-                            continue
-
-                        class_score1 = sigmoid(tensor[0, anchor_idx, height_idx, width_idx, 5]) * objectness
-                        class_score2 = sigmoid(tensor[0, anchor_idx, height_idx, width_idx, 6]) * objectness
-                        if class_score1 < 0.4 and class_score2 < 0.4:
-                            continue
-
-                        temp_score = -1
-                        temp_class_id = -1
-                        if class_score1 < class_score2:
-                            temp_score = class_score2
-                            temp_class_id = 1
-                        else:
-                            temp_score = class_score1
-                            temp_class_id = 0
-
-                        # Convert relative box info into absolute box info according to prior anchors
-                        temp_x = width_idx + sigmoid(tensor[0, anchor_idx, height_idx, width_idx, 0]) * 2 - 0.5
-                        temp_y = height_idx + sigmoid(tensor[0, anchor_idx, height_idx, width_idx, 1]) * 2 - 0.5
-                        temp_width = sigmoid(tensor[0, anchor_idx, height_idx, width_idx, 2]) * \
-                                     sigmoid(tensor[0, anchor_idx, height_idx, width_idx, 2]) * 4 * \
-                                     ANCHORS_SIZE[layer_idx][anchor_idx][0]
-                        temp_height = sigmoid(tensor[0, anchor_idx, height_idx, width_idx, 3]) * \
-                                      sigmoid(tensor[0, anchor_idx, height_idx, width_idx, 3]) * 4 * \
-                                      ANCHORS_SIZE[layer_idx][anchor_idx][1]
-
-                        # Convert (x, y, h, w) format into (x0, y0, x1, y1) format
-                        x0 = max(temp_x / width * MODEL_INPUT_WIDTH - temp_width / 2, 0)
-                        y0 = max(temp_y / height * MODEL_INPUT_HEIGHT - temp_height / 2, 0)
-                        x1 = min(temp_x / width * MODEL_INPUT_WIDTH + temp_width / 2, MODEL_INPUT_WIDTH)
-                        y1 = min(temp_y / width * MODEL_INPUT_HEIGHT + temp_height / 2, MODEL_INPUT_HEIGHT)
-                        bounding_box_array.append([x0, y0, x1, y1, temp_score, temp_class_id])
-        return np.array(bounding_box_array)
-
-    def infer(self, image):
-        height_ratio = image.original_height / MODEL_INPUT_HEIGHT
-        width_ratio = image.original_width / MODEL_INPUT_WIDTH
-        if image.height != MODEL_INPUT_HEIGHT or image.width != MODEL_INPUT_WIDTH:
-            image = self.image_processor.resize(image, MODEL_SHAPE, base.huaweiu_high_order_filter)
-        # model inference
-        image_tensor = [image.to_tensor()]
-        output_tensors = self.model.infer(image_tensor)
-        # decode output results
-        bounding_box_array = self.__decode_output(output_tensors)
-        # conduct non max suppression
-        if bounding_box_array.size != 0:
-            keep_idx = nms(bounding_box_array, NMS_THRESHOLD)
-            # correct bounding box bias due to resize operation
-            bounding_box_array = bounding_box_array[keep_idx, :]
-            bounding_box_array[:, [0, 2]] *= width_ratio
-            bounding_box_array[:, [1, 3]] *= height_ratio
-        return bounding_box_array
-
-
-class FrameAnalyzer:
-    def __init__(self, model_path, device_id):
-        self.frame_analyze_model = FrameAnalyzeModel(model_path, device_id)
-
-    @staticmethod
-    def alarm(analysis_info, frame_id):
-        for bounding_box in analysis_info:
-            left_top_point, right_button_point = (int(bounding_box[0]), int(bounding_box[1])),\
-                                                  (int(bounding_box[2]), int(bounding_box[3]))
-            logger.warning("Frame {} detect {}! Confidence: {:.2f}, x0: {:.2f}, y0: {:.2f}, x1: {:.2f}, y1: {:.2f}"
-                           .format(frame_id, INDEX_TO_CLASS[bounding_box[5]], bounding_box[4], left_top_point[0],
-                                   left_top_point[1], right_button_point[0], right_button_point[1]))
-
-    def analyze(self, image):
-        return self.frame_analyze_model.infer(image)
+import os
+import numpy as np
+from mindx.sdk import base
+from mindx.sdk.base import Tensor, Model, Size, Rect, log, ImageProcessor, post, Point
+from utils import file_base_check, logger
+
+MODEL_INPUT_HEIGHT = 640
+MODEL_INPUT_WIDTH = 640
+MODEL_SHAPE = Size(MODEL_INPUT_HEIGHT, MODEL_INPUT_WIDTH)
+ANCHORS_SIZE = [[[10, 13], [16, 30], [33, 23]], [[30, 61], [62, 45], [59, 119]], [[116, 90], [156, 198], [373, 326]]]
+NMS_THRESHOLD = 0.6
+INDEX_TO_CLASS = {0: "Fire", 1: "Smoke"}
+
+
+def sigmoid(x):
+    return 1 / (1 + np.exp(-x))
+
+
+def nms(dets, thresh):
+    x1 = dets[:, 0]  # xmin
+    y1 = dets[:, 1]  # ymin
+    x2 = dets[:, 2]  # xmax
+    y2 = dets[:, 3]  # ymax
+    scores = dets[:, 4]  # confidence
+
+    areas = (x2 - x1 + 1) * (y2 - y1 + 1)  # 每个bounding box的面积
+    order = scores.argsort()[::-1]  # 按置信度降序排序
+
+    keep = []  # 用来保存最后留下来的bounding box
+    while order.size > 0:
+        i = order[0]  # 置信度最高的bounding box的index
+        keep.append(i)  # 添加本次置信度最高的bounding box的index
+
+        # 当前bbox和剩下bbox之间的交叉区域
+        xx1 = np.maximum(x1[i], x1[order[1:]])
+        yy1 = np.maximum(y1[i], y1[order[1:]])
+        xx2 = np.minimum(x2[i], x2[order[1:]])
+        yy2 = np.minimum(y2[i], y2[order[1:]])
+
+        # 计算交叉区域的面积
+        w = np.maximum(0.0, xx2 - xx1 + 1)
+        h = np.maximum(0.0, yy2 - yy1 + 1)
+        inter = w * h
+
+        # 交叉区域面积 / (bbox + 某区域面积 - 交叉区域面积)
+        ovr = inter / (areas[i] + areas[order[1:]] - inter)
+
+        # 保留交集小于一定阈值的bounding box
+        inds = np.where(ovr <= thresh)[0]
+        order = order[inds + 1]
+    return keep
+
+
+class FrameAnalyzeModel:
+    def __init__(self, model_path, device_id):
+        file_base_check(os.path.realpath(model_path))
+        self.model = Model(os.path.realpath(model_path), device_id)
+        self.image_processor = ImageProcessor(device_id)
+
+    @staticmethod
+    def __decode_output(output_tensors):
+        output_np_tensors = []
+        for tensor in output_tensors:
+            tensor.to_host()
+            output_np_tensors.append(np.array(tensor))
+        bounding_box_array = []
+        for layer_idx, tensor in enumerate(output_np_tensors):
+            batch, anchor_num, height, width, box_para = tensor.shape
+            for height_idx in range(height):
+                for width_idx in range(width):
+                    for anchor_idx in range(anchor_num):
+                        # Filter unimportant anchor and determine the class of anchor according to the given threshold
+                        objectness = sigmoid(tensor[0, anchor_idx, height_idx, width_idx, 4])
+                        if objectness < 0.1:
+                            continue
+
+                        class_score1 = sigmoid(tensor[0, anchor_idx, height_idx, width_idx, 5]) * objectness
+                        class_score2 = sigmoid(tensor[0, anchor_idx, height_idx, width_idx, 6]) * objectness
+                        if class_score1 < 0.4 and class_score2 < 0.4:
+                            continue
+
+                        temp_score = -1
+                        temp_class_id = -1
+                        if class_score1 < class_score2:
+                            temp_score = class_score2
+                            temp_class_id = 1
+                        else:
+                            temp_score = class_score1
+                            temp_class_id = 0
+
+                        # Convert relative box info into absolute box info according to prior anchors
+                        temp_x = width_idx + sigmoid(tensor[0, anchor_idx, height_idx, width_idx, 0]) * 2 - 0.5
+                        temp_y = height_idx + sigmoid(tensor[0, anchor_idx, height_idx, width_idx, 1]) * 2 - 0.5
+                        temp_width = sigmoid(tensor[0, anchor_idx, height_idx, width_idx, 2]) * \
+                                     sigmoid(tensor[0, anchor_idx, height_idx, width_idx, 2]) * 4 * \
+                                     ANCHORS_SIZE[layer_idx][anchor_idx][0]
+                        temp_height = sigmoid(tensor[0, anchor_idx, height_idx, width_idx, 3]) * \
+                                      sigmoid(tensor[0, anchor_idx, height_idx, width_idx, 3]) * 4 * \
+                                      ANCHORS_SIZE[layer_idx][anchor_idx][1]
+
+                        # Convert (x, y, h, w) format into (x0, y0, x1, y1) format
+                        x0 = max(temp_x / width * MODEL_INPUT_WIDTH - temp_width / 2, 0)
+                        y0 = max(temp_y / height * MODEL_INPUT_HEIGHT - temp_height / 2, 0)
+                        x1 = min(temp_x / width * MODEL_INPUT_WIDTH + temp_width / 2, MODEL_INPUT_WIDTH)
+                        y1 = min(temp_y / width * MODEL_INPUT_HEIGHT + temp_height / 2, MODEL_INPUT_HEIGHT)
+                        bounding_box_array.append([x0, y0, x1, y1, temp_score, temp_class_id])
+        return np.array(bounding_box_array)
+
+    def infer(self, image):
+        height_ratio = image.original_height / MODEL_INPUT_HEIGHT
+        width_ratio = image.original_width / MODEL_INPUT_WIDTH
+        if image.height != MODEL_INPUT_HEIGHT or image.width != MODEL_INPUT_WIDTH:
+            image = self.image_processor.resize(image, MODEL_SHAPE, base.huaweiu_high_order_filter)
+        # model inference
+        image_tensor = [image.to_tensor()]
+        output_tensors = self.model.infer(image_tensor)
+        # decode output results
+        bounding_box_array = self.__decode_output(output_tensors)
+        # conduct non max suppression
+        if bounding_box_array.size != 0:
+            keep_idx = nms(bounding_box_array, NMS_THRESHOLD)
+            # correct bounding box bias due to resize operation
+            bounding_box_array = bounding_box_array[keep_idx, :]
+            bounding_box_array[:, [0, 2]] *= width_ratio
+            bounding_box_array[:, [1, 3]] *= height_ratio
+        return bounding_box_array
+
+
+class FrameAnalyzer:
+    def __init__(self, model_path, device_id):
+        self.frame_analyze_model = FrameAnalyzeModel(model_path, device_id)
+
+    @staticmethod
+    def alarm(analysis_info, frame_id):
+        for bounding_box in analysis_info:
+            left_top_point, right_button_point = (int(bounding_box[0]), int(bounding_box[1])),\
+                                                  (int(bounding_box[2]), int(bounding_box[3]))
+            logger.warning("Frame {} detect {}! Confidence: {:.2f}, x0: {:.2f}, y0: {:.2f}, x1: {:.2f}, y1: {:.2f}"
+                           .format(frame_id, INDEX_TO_CLASS[bounding_box[5]], bounding_box[4], left_top_point[0],
+                                   left_top_point[1], right_button_point[0], right_button_point[1]))
+
+    def analyze(self, image):
+        return self.frame_analyze_model.infer(image)
diff --git a/contrib/FireDetection/python/infer_config.json b/mxVision/mxVision-referenceapps/FireDetection/python/infer_config.json
similarity index 95%
rename from contrib/FireDetection/python/infer_config.json
rename to mxVision/mxVision-referenceapps/FireDetection/python/infer_config.json
index 160aea4d4b892b2aaf629646687afa1a58acf107..7279232d9e3f4c7c89e9bc382b0b82a42102841c 100644
--- a/contrib/FireDetection/python/infer_config.json
+++ b/mxVision/mxVision-referenceapps/FireDetection/python/infer_config.json
@@ -1,9 +1,9 @@
-{
-    "video_path": "./fireDetection.264",
-    "model_path": "./firedetection.om",
-    "device_id": 0,
-    "skip_frame_number": 3,
-    "video_saved_path": "./output.h264",
-    "width": 1920,
-    "height": 1080
-}
+{
+    "video_path": "./fireDetection.264",
+    "model_path": "./firedetection.om",
+    "device_id": 0,
+    "skip_frame_number": 3,
+    "video_saved_path": "./output.h264",
+    "width": 1920,
+    "height": 1080
+}
diff --git a/contrib/FireDetection/python/main.py b/mxVision/mxVision-referenceapps/FireDetection/python/main.py
similarity index 97%
rename from contrib/FireDetection/python/main.py
rename to mxVision/mxVision-referenceapps/FireDetection/python/main.py
index c3e712da8643f38dbb4835381b797544589dca6c..6359093578b2422c8612a0cb9266e4ecbb4176c8 100644
--- a/contrib/FireDetection/python/main.py
+++ b/mxVision/mxVision-referenceapps/FireDetection/python/main.py
@@ -1,151 +1,151 @@
-import threading
-import signal
-import time
-import av
-from mindx.sdk import base
-from mindx.sdk.base import VideoDecoder, VideoDecodeConfig,\
-    VdecCallBacker, VideoEncoder, VideoEncodeConfig, VencCallBacker
-from frame_analyzer import FrameAnalyzer
-from utils import infer_config, logger
-
-decoded_data_queue = []
-analyzed_data_queue = []
-decode_finished_flag = False
-SIGNAL_RECEIVED = False
-
-
-class Frame:
-    def __init__(self, image, frame_id):
-        self.image = image
-        self.frame_id = frame_id
-
-
-def stop_handler(signum, frame):
-    global SIGNAL_RECEIVED
-    SIGNAL_RECEIVED = True
-
-
-def vdec_callback_func(decoded_image, channel_id, frame_id):
-    logger.debug('Video decoder output decoded image (channelId:{}, frameId:{}, image.width:{},'
-                 ' image.height:{}, image.format:{})'.format(channel_id, frame_id, decoded_image.width,
-                                                             decoded_image.height, decoded_image.format))
-    # 解码完成的Image类存入列表中
-    decoded_data_queue.append(decoded_image)
-
-
-def vdec_thread_func(vdec_config, vdec_callbacker, device_id, rtsp):
-    global decode_finished_flag
-    global SIGNAL_RECEIVED
-    with av.open(rtsp) as container:
-        count = 0
-        # 初始化VideoDecoder
-        video_decoder = VideoDecoder(vdec_config, vdec_callbacker, device_id, 0)
-        # 校验视频宽高是否符合编码器要求
-        video_stream = next(s for s in container.streams if s.type == 'video')
-        if video_stream.height > infer_config["height"]:
-            logger.error("Video height {} exceeds the configuration height {} in config file. Please adjust config."
-                         .format(video_stream.height, infer_config["height"]))
-            SIGNAL_RECEIVED = True
-            return
-        if video_stream.width > infer_config["width"]:
-            logger.error("Video width {} exceeds the configuration width {} in config file. Please adjust config."
-                         .format(video_stream.width, infer_config["width"]))
-            SIGNAL_RECEIVED = True
-            return
-        # 循环取帧解码
-        for packet in container.demux():
-            if SIGNAL_RECEIVED:
-                break
-            if packet.size == 0:
-                logger.info("Finish to pull rtsp stream.")
-                SIGNAL_RECEIVED = True
-                break
-            logger.debug("send packet:{} ".format(count))
-            video_decoder.decode(packet, count)
-            time.sleep(0.02)
-            count += 1
-        logger.info("There are {} frames in total.".format(count))
-
-
-# 视频编码回调函数
-def venc_callback_func(output, output_datasize, channel_id, frame_id):
-    logger.debug('Video encoder output encoded_stream. (type:{}, outDataSize:{}, channelId:{}, frameId:{})'
-                 .format(type(output), output_datasize, channel_id, frame_id))
-    with open(infer_config["video_saved_path"], 'ab') as file:
-        file.write(output)
-
-
-def venc_thread_func(venc_config, venc_callbacker, device_id):
-    video_encoder = VideoEncoder(venc_config, venc_callbacker, device_id)
-    i = 0
-    global SIGNAL_RECEIVED
-    while not (SIGNAL_RECEIVED and not decoded_data_queue):
-        if not decoded_data_queue:
-            continue
-        frame_image = decoded_data_queue.pop(0)
-        if i % infer_config["skip_frame_number"] == 0:
-            analyzed_data_queue.append(Frame(frame_image, i))
-        video_encoder.encode(frame_image, i)
-        time.sleep(0.02)
-        i += 1
-    logger.info("Venc thread ended.")
-
-
-def analyze_thread_func(model_path, device_id):
-    frame_analyzer = FrameAnalyzer(model_path, device_id)
-    global SIGNAL_RECEIVED
-    while not (SIGNAL_RECEIVED and not analyzed_data_queue):
-        if not analyzed_data_queue:
-            continue
-        frame = analyzed_data_queue.pop(0)
-        results = frame_analyzer.analyze(frame.image)
-        if results.size != 0:
-            frame_analyzer.alarm(results, frame.frame_id)
-    logger.info("Analyze thread ended.")
-
-
-signal.signal(signal.SIGINT, stop_handler)
-if __name__ == '__main__':
-    base.mx_init()
-    vdec_callbacker_instance = VdecCallBacker()
-    vdec_callbacker_instance.registerVdecCallBack(vdec_callback_func)
-    # # 初始化VideoDecodeConfig类并设置参数
-    vdec_conf = VideoDecodeConfig()
-    vdec_conf.inputVideoFormat = base.h264_main_level
-    vdec_conf.outputImageFormat = base.nv12
-    vdec_conf.width = infer_config["width"]
-    vdec_conf.height = infer_config["height"]
-    # 初始化VencCallBacker类并注册回调函数
-    venc_callbacker_instance = VencCallBacker()
-    venc_callbacker_instance.registerVencCallBack(venc_callback_func)
-    # 初始化VideoEncodeConfig
-    venc_conf = VideoEncodeConfig()
-    venc_conf.keyFrameInterval = 50
-    venc_conf.srcRate = 30
-    venc_conf.maxBitRate = 6000
-    venc_conf.ipProp = 30
-
-    # 创建线程，并传递参数
-    vdec = threading.Thread(target=vdec_thread_func, kwargs={'vdec_config': vdec_conf,
-                                                             'vdec_callbacker': vdec_callbacker_instance,
-                                                             "device_id": infer_config["device_id"],
-                                                             "rtsp": infer_config["video_path"]})
-
-    venc = threading.Thread(target=venc_thread_func, kwargs={'venc_config': venc_conf,
-                                                             'venc_callbacker': venc_callbacker_instance,
-                                                             "device_id": infer_config["device_id"]})
-
-    analyze = threading.Thread(target=analyze_thread_func, kwargs={"model_path": infer_config["model_path"],
-                                                                   "device_id": infer_config["device_id"]})
-
-    # 启动线程
-    vdec.start()
-    venc.start()
-    analyze.start()
-
-    # 等待执行完毕
-    vdec.join()
-    venc.join()
-    analyze.join()
-
-    logger.info("Fire detection task ended.")
+import threading
+import signal
+import time
+import av
+from mindx.sdk import base
+from mindx.sdk.base import VideoDecoder, VideoDecodeConfig,\
+    VdecCallBacker, VideoEncoder, VideoEncodeConfig, VencCallBacker
+from frame_analyzer import FrameAnalyzer
+from utils import infer_config, logger
+
+decoded_data_queue = []
+analyzed_data_queue = []
+decode_finished_flag = False
+SIGNAL_RECEIVED = False
+
+
+class Frame:
+    def __init__(self, image, frame_id):
+        self.image = image
+        self.frame_id = frame_id
+
+
+def stop_handler(signum, frame):
+    global SIGNAL_RECEIVED
+    SIGNAL_RECEIVED = True
+
+
+def vdec_callback_func(decoded_image, channel_id, frame_id):
+    logger.debug('Video decoder output decoded image (channelId:{}, frameId:{}, image.width:{},'
+                 ' image.height:{}, image.format:{})'.format(channel_id, frame_id, decoded_image.width,
+                                                             decoded_image.height, decoded_image.format))
+    # 解码完成的Image类存入列表中
+    decoded_data_queue.append(decoded_image)
+
+
+def vdec_thread_func(vdec_config, vdec_callbacker, device_id, rtsp):
+    global decode_finished_flag
+    global SIGNAL_RECEIVED
+    with av.open(rtsp) as container:
+        count = 0
+        # 初始化VideoDecoder
+        video_decoder = VideoDecoder(vdec_config, vdec_callbacker, device_id, 0)
+        # 校验视频宽高是否符合编码器要求
+        video_stream = next(s for s in container.streams if s.type == 'video')
+        if video_stream.height > infer_config["height"]:
+            logger.error("Video height {} exceeds the configuration height {} in config file. Please adjust config."
+                         .format(video_stream.height, infer_config["height"]))
+            SIGNAL_RECEIVED = True
+            return
+        if video_stream.width > infer_config["width"]:
+            logger.error("Video width {} exceeds the configuration width {} in config file. Please adjust config."
+                         .format(video_stream.width, infer_config["width"]))
+            SIGNAL_RECEIVED = True
+            return
+        # 循环取帧解码
+        for packet in container.demux():
+            if SIGNAL_RECEIVED:
+                break
+            if packet.size == 0:
+                logger.info("Finish to pull rtsp stream.")
+                SIGNAL_RECEIVED = True
+                break
+            logger.debug("send packet:{} ".format(count))
+            video_decoder.decode(packet, count)
+            time.sleep(0.02)
+            count += 1
+        logger.info("There are {} frames in total.".format(count))
+
+
+# 视频编码回调函数
+def venc_callback_func(output, output_datasize, channel_id, frame_id):
+    logger.debug('Video encoder output encoded_stream. (type:{}, outDataSize:{}, channelId:{}, frameId:{})'
+                 .format(type(output), output_datasize, channel_id, frame_id))
+    with open(infer_config["video_saved_path"], 'ab') as file:
+        file.write(output)
+
+
+def venc_thread_func(venc_config, venc_callbacker, device_id):
+    video_encoder = VideoEncoder(venc_config, venc_callbacker, device_id)
+    i = 0
+    global SIGNAL_RECEIVED
+    while not (SIGNAL_RECEIVED and not decoded_data_queue):
+        if not decoded_data_queue:
+            continue
+        frame_image = decoded_data_queue.pop(0)
+        if i % infer_config["skip_frame_number"] == 0:
+            analyzed_data_queue.append(Frame(frame_image, i))
+        video_encoder.encode(frame_image, i)
+        time.sleep(0.02)
+        i += 1
+    logger.info("Venc thread ended.")
+
+
+def analyze_thread_func(model_path, device_id):
+    frame_analyzer = FrameAnalyzer(model_path, device_id)
+    global SIGNAL_RECEIVED
+    while not (SIGNAL_RECEIVED and not analyzed_data_queue):
+        if not analyzed_data_queue:
+            continue
+        frame = analyzed_data_queue.pop(0)
+        results = frame_analyzer.analyze(frame.image)
+        if results.size != 0:
+            frame_analyzer.alarm(results, frame.frame_id)
+    logger.info("Analyze thread ended.")
+
+
+signal.signal(signal.SIGINT, stop_handler)
+if __name__ == '__main__':
+    base.mx_init()
+    vdec_callbacker_instance = VdecCallBacker()
+    vdec_callbacker_instance.registerVdecCallBack(vdec_callback_func)
+    # # 初始化VideoDecodeConfig类并设置参数
+    vdec_conf = VideoDecodeConfig()
+    vdec_conf.inputVideoFormat = base.h264_main_level
+    vdec_conf.outputImageFormat = base.nv12
+    vdec_conf.width = infer_config["width"]
+    vdec_conf.height = infer_config["height"]
+    # 初始化VencCallBacker类并注册回调函数
+    venc_callbacker_instance = VencCallBacker()
+    venc_callbacker_instance.registerVencCallBack(venc_callback_func)
+    # 初始化VideoEncodeConfig
+    venc_conf = VideoEncodeConfig()
+    venc_conf.keyFrameInterval = 50
+    venc_conf.srcRate = 30
+    venc_conf.maxBitRate = 6000
+    venc_conf.ipProp = 30
+
+    # 创建线程，并传递参数
+    vdec = threading.Thread(target=vdec_thread_func, kwargs={'vdec_config': vdec_conf,
+                                                             'vdec_callbacker': vdec_callbacker_instance,
+                                                             "device_id": infer_config["device_id"],
+                                                             "rtsp": infer_config["video_path"]})
+
+    venc = threading.Thread(target=venc_thread_func, kwargs={'venc_config': venc_conf,
+                                                             'venc_callbacker': venc_callbacker_instance,
+                                                             "device_id": infer_config["device_id"]})
+
+    analyze = threading.Thread(target=analyze_thread_func, kwargs={"model_path": infer_config["model_path"],
+                                                                   "device_id": infer_config["device_id"]})
+
+    # 启动线程
+    vdec.start()
+    venc.start()
+    analyze.start()
+
+    # 等待执行完毕
+    vdec.join()
+    venc.join()
+    analyze.join()
+
+    logger.info("Fire detection task ended.")
diff --git a/contrib/FireDetection/python/utils.py b/mxVision/mxVision-referenceapps/FireDetection/python/utils.py
similarity index 97%
rename from contrib/FireDetection/python/utils.py
rename to mxVision/mxVision-referenceapps/FireDetection/python/utils.py
index f8f1ff771a44eb3665264b583db8e98d4bc324fc..0165bd1c6d70c62e0bab0f72faa6a28e298beda9 100644
--- a/contrib/FireDetection/python/utils.py
+++ b/mxVision/mxVision-referenceapps/FireDetection/python/utils.py
@@ -1,57 +1,57 @@
-#!/usr/bin/env python3
-# -*- coding: utf-8 -*-
-"""
-Copyright (c) Huawei Technologies Co., Ltd. 2024-2024. All rights reserved.
-Description: Common function for utilization.
-Author: MindX SDK
-Create: 2024
-History: NA
-"""
-import json
-import os
-import logging
-
-
-def file_base_check(path: str) -> None:
-    file_name = os.path.basename(path)
-    if not path or not os.path.isfile(path):
-        raise Exception('The file:{} does not exist!'.format(file_name))
-    if os.path.islink(path):
-        raise Exception('The file:{} is link. invalid file!'.format(file_name))
-    if not os.access(path, mode=os.R_OK):
-        raise Exception('The file:{} is unreadable!'.format(file_name))
-
-
-def read_json_config(json_path: str) -> dict:
-    file_base_check(json_path)
-    try:
-        with open(json_path, "r") as fr:
-            json_data = json.load(fr)
-    except json.decoder.JSONDecodeError as e:
-        raise Exception('json decode error: config file is not a json format file!') from e
-    finally:
-        pass
-    if not isinstance(json_data, dict):
-        raise Exception('json decode error: config file is not a json format file!')
-    return json_data
-
-
-def _init():
-    logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
-    logger_instance = logging.getLogger()
-    file_base_check("./infer_config.json")
-    infer_config_instance = read_json_config("./infer_config.json")
-    file_base_check(infer_config_instance["video_path"])
-    file_base_check(infer_config_instance["model_path"])
-    file_path = infer_config_instance["video_saved_path"]
-    directory = os.path.dirname(file_path)
-    if not os.path.exists(directory):
-        os.makedirs(directory)
-    if os.path.exists(file_path):
-        os.remove(file_path)
-    if infer_config_instance["skip_frame_number"] < 1:
-        raise Exception('skip_frame_number must >= 1.')
-    return logger_instance, infer_config_instance
-
-
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Copyright (c) Huawei Technologies Co., Ltd. 2024-2024. All rights reserved.
+Description: Common function for utilization.
+Author: MindX SDK
+Create: 2024
+History: NA
+"""
+import json
+import os
+import logging
+
+
+def file_base_check(path: str) -> None:
+    file_name = os.path.basename(path)
+    if not path or not os.path.isfile(path):
+        raise Exception('The file:{} does not exist!'.format(file_name))
+    if os.path.islink(path):
+        raise Exception('The file:{} is link. invalid file!'.format(file_name))
+    if not os.access(path, mode=os.R_OK):
+        raise Exception('The file:{} is unreadable!'.format(file_name))
+
+
+def read_json_config(json_path: str) -> dict:
+    file_base_check(json_path)
+    try:
+        with open(json_path, "r") as fr:
+            json_data = json.load(fr)
+    except json.decoder.JSONDecodeError as e:
+        raise Exception('json decode error: config file is not a json format file!') from e
+    finally:
+        pass
+    if not isinstance(json_data, dict):
+        raise Exception('json decode error: config file is not a json format file!')
+    return json_data
+
+
+def _init():
+    logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
+    logger_instance = logging.getLogger()
+    file_base_check("./infer_config.json")
+    infer_config_instance = read_json_config("./infer_config.json")
+    file_base_check(infer_config_instance["video_path"])
+    file_base_check(infer_config_instance["model_path"])
+    file_path = infer_config_instance["video_saved_path"]
+    directory = os.path.dirname(file_path)
+    if not os.path.exists(directory):
+        os.makedirs(directory)
+    if os.path.exists(file_path):
+        os.remove(file_path)
+    if infer_config_instance["skip_frame_number"] < 1:
+        raise Exception('skip_frame_number must >= 1.')
+    return logger_instance, infer_config_instance
+
+
 logger, infer_config = _init()
\ No newline at end of file
diff --git a/mxVision/GeneralTextRecognition/C++/CMakeLists.txt b/mxVision/mxVision-referenceapps/GeneralTextRecognition/C++/CMakeLists.txt
similarity index 100%
rename from mxVision/GeneralTextRecognition/C++/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/GeneralTextRecognition/C++/CMakeLists.txt
diff --git a/mxVision/GeneralTextRecognition/C++/mainMultiThread.cpp b/mxVision/mxVision-referenceapps/GeneralTextRecognition/C++/mainMultiThread.cpp
similarity index 100%
rename from mxVision/GeneralTextRecognition/C++/mainMultiThread.cpp
rename to mxVision/mxVision-referenceapps/GeneralTextRecognition/C++/mainMultiThread.cpp
diff --git a/mxVision/GeneralTextRecognition/C++/run.sh b/mxVision/mxVision-referenceapps/GeneralTextRecognition/C++/run.sh
similarity index 100%
rename from mxVision/GeneralTextRecognition/C++/run.sh
rename to mxVision/mxVision-referenceapps/GeneralTextRecognition/C++/run.sh
diff --git a/mxVision/GeneralTextRecognition/License.md b/mxVision/mxVision-referenceapps/GeneralTextRecognition/License.md
similarity index 100%
rename from mxVision/GeneralTextRecognition/License.md
rename to mxVision/mxVision-referenceapps/GeneralTextRecognition/License.md
diff --git a/mxVision/GeneralTextRecognition/README.md b/mxVision/mxVision-referenceapps/GeneralTextRecognition/README.md
similarity index 100%
rename from mxVision/GeneralTextRecognition/README.md
rename to mxVision/mxVision-referenceapps/GeneralTextRecognition/README.md
diff --git a/mxVision/GeneralTextRecognition/THIRD PARTY OPEN SOURCE SOFTWARE NOTICE.md b/mxVision/mxVision-referenceapps/GeneralTextRecognition/THIRD PARTY OPEN SOURCE SOFTWARE NOTICE.md
similarity index 100%
rename from mxVision/GeneralTextRecognition/THIRD PARTY OPEN SOURCE SOFTWARE NOTICE.md
rename to mxVision/mxVision-referenceapps/GeneralTextRecognition/THIRD PARTY OPEN SOURCE SOFTWARE NOTICE.md
diff --git a/mxVision/GeneralTextRecognition/data/OCR.pipeline b/mxVision/mxVision-referenceapps/GeneralTextRecognition/data/OCR.pipeline
similarity index 100%
rename from mxVision/GeneralTextRecognition/data/OCR.pipeline
rename to mxVision/mxVision-referenceapps/GeneralTextRecognition/data/OCR.pipeline
diff --git a/mxVision/GeneralTextRecognition/data/OCR_multi3.pipeline b/mxVision/mxVision-referenceapps/GeneralTextRecognition/data/OCR_multi3.pipeline
similarity index 100%
rename from mxVision/GeneralTextRecognition/data/OCR_multi3.pipeline
rename to mxVision/mxVision-referenceapps/GeneralTextRecognition/data/OCR_multi3.pipeline
diff --git a/mxVision/GeneralTextRecognition/data/config/cls/cls.cfg b/mxVision/mxVision-referenceapps/GeneralTextRecognition/data/config/cls/cls.cfg
similarity index 100%
rename from mxVision/GeneralTextRecognition/data/config/cls/cls.cfg
rename to mxVision/mxVision-referenceapps/GeneralTextRecognition/data/config/cls/cls.cfg
diff --git a/mxVision/GeneralTextRecognition/data/config/cls/ic15.names b/mxVision/mxVision-referenceapps/GeneralTextRecognition/data/config/cls/ic15.names
similarity index 100%
rename from mxVision/GeneralTextRecognition/data/config/cls/ic15.names
rename to mxVision/mxVision-referenceapps/GeneralTextRecognition/data/config/cls/ic15.names
diff --git a/mxVision/GeneralTextRecognition/data/config/det/det.cfg b/mxVision/mxVision-referenceapps/GeneralTextRecognition/data/config/det/det.cfg
similarity index 100%
rename from mxVision/GeneralTextRecognition/data/config/det/det.cfg
rename to mxVision/mxVision-referenceapps/GeneralTextRecognition/data/config/det/det.cfg
diff --git a/mxVision/GeneralTextRecognition/data/config/rec/rec_cfg.txt b/mxVision/mxVision-referenceapps/GeneralTextRecognition/data/config/rec/rec_cfg.txt
similarity index 100%
rename from mxVision/GeneralTextRecognition/data/config/rec/rec_cfg.txt
rename to mxVision/mxVision-referenceapps/GeneralTextRecognition/data/config/rec/rec_cfg.txt
diff --git a/mxVision/GeneralTextRecognition/data/model/MODEL.md b/mxVision/mxVision-referenceapps/GeneralTextRecognition/data/model/MODEL.md
similarity index 100%
rename from mxVision/GeneralTextRecognition/data/model/MODEL.md
rename to mxVision/mxVision-referenceapps/GeneralTextRecognition/data/model/MODEL.md
diff --git a/mxVision/GeneralTextRecognition/data/model/cls_aipp.cfg b/mxVision/mxVision-referenceapps/GeneralTextRecognition/data/model/cls_aipp.cfg
similarity index 100%
rename from mxVision/GeneralTextRecognition/data/model/cls_aipp.cfg
rename to mxVision/mxVision-referenceapps/GeneralTextRecognition/data/model/cls_aipp.cfg
diff --git a/mxVision/GeneralTextRecognition/data/model/det_aipp.cfg b/mxVision/mxVision-referenceapps/GeneralTextRecognition/data/model/det_aipp.cfg
similarity index 100%
rename from mxVision/GeneralTextRecognition/data/model/det_aipp.cfg
rename to mxVision/mxVision-referenceapps/GeneralTextRecognition/data/model/det_aipp.cfg
diff --git a/mxVision/GeneralTextRecognition/data/model/rec_aipp.cfg b/mxVision/mxVision-referenceapps/GeneralTextRecognition/data/model/rec_aipp.cfg
similarity index 100%
rename from mxVision/GeneralTextRecognition/data/model/rec_aipp.cfg
rename to mxVision/mxVision-referenceapps/GeneralTextRecognition/data/model/rec_aipp.cfg
diff --git a/mxVision/GeneralTextRecognition/main_ocr.py b/mxVision/mxVision-referenceapps/GeneralTextRecognition/main_ocr.py
similarity index 100%
rename from mxVision/GeneralTextRecognition/main_ocr.py
rename to mxVision/mxVision-referenceapps/GeneralTextRecognition/main_ocr.py
diff --git a/mxVision/GeneralTextRecognition/src/Clipper/CMakeLists.txt b/mxVision/mxVision-referenceapps/GeneralTextRecognition/src/Clipper/CMakeLists.txt
similarity index 100%
rename from mxVision/GeneralTextRecognition/src/Clipper/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/GeneralTextRecognition/src/Clipper/CMakeLists.txt
diff --git a/mxVision/GeneralTextRecognition/src/DBPostProcess/CMakeLists.txt b/mxVision/mxVision-referenceapps/GeneralTextRecognition/src/DBPostProcess/CMakeLists.txt
similarity index 100%
rename from mxVision/GeneralTextRecognition/src/DBPostProcess/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/GeneralTextRecognition/src/DBPostProcess/CMakeLists.txt
diff --git a/mxVision/GeneralTextRecognition/src/DBPostProcess/DBPostProcess.cpp b/mxVision/mxVision-referenceapps/GeneralTextRecognition/src/DBPostProcess/DBPostProcess.cpp
similarity index 100%
rename from mxVision/GeneralTextRecognition/src/DBPostProcess/DBPostProcess.cpp
rename to mxVision/mxVision-referenceapps/GeneralTextRecognition/src/DBPostProcess/DBPostProcess.cpp
diff --git a/mxVision/GeneralTextRecognition/src/DBPostProcess/DBPostProcess.h b/mxVision/mxVision-referenceapps/GeneralTextRecognition/src/DBPostProcess/DBPostProcess.h
similarity index 100%
rename from mxVision/GeneralTextRecognition/src/DBPostProcess/DBPostProcess.h
rename to mxVision/mxVision-referenceapps/GeneralTextRecognition/src/DBPostProcess/DBPostProcess.h
diff --git a/mxVision/GeneralTextRecognition/src/README.md b/mxVision/mxVision-referenceapps/GeneralTextRecognition/src/README.md
similarity index 100%
rename from mxVision/GeneralTextRecognition/src/README.md
rename to mxVision/mxVision-referenceapps/GeneralTextRecognition/src/README.md
diff --git a/contrib/GestureKeypointDetection/README.md b/mxVision/mxVision-referenceapps/GestureKeypointDetection/README.md
similarity index 100%
rename from contrib/GestureKeypointDetection/README.md
rename to mxVision/mxVision-referenceapps/GestureKeypointDetection/README.md
diff --git a/contrib/GestureKeypointDetection/detection.pipeline b/mxVision/mxVision-referenceapps/GestureKeypointDetection/detection.pipeline
similarity index 100%
rename from contrib/GestureKeypointDetection/detection.pipeline
rename to mxVision/mxVision-referenceapps/GestureKeypointDetection/detection.pipeline
diff --git a/contrib/GestureKeypointDetection/main.py b/mxVision/mxVision-referenceapps/GestureKeypointDetection/main.py
similarity index 100%
rename from contrib/GestureKeypointDetection/main.py
rename to mxVision/mxVision-referenceapps/GestureKeypointDetection/main.py
diff --git a/contrib/GestureKeypointDetection/model/hand/aipp.cfg b/mxVision/mxVision-referenceapps/GestureKeypointDetection/model/hand/aipp.cfg
similarity index 100%
rename from contrib/GestureKeypointDetection/model/hand/aipp.cfg
rename to mxVision/mxVision-referenceapps/GestureKeypointDetection/model/hand/aipp.cfg
diff --git a/contrib/GestureKeypointDetection/model/hand/coco.names b/mxVision/mxVision-referenceapps/GestureKeypointDetection/model/hand/coco.names
similarity index 100%
rename from contrib/GestureKeypointDetection/model/hand/coco.names
rename to mxVision/mxVision-referenceapps/GestureKeypointDetection/model/hand/coco.names
diff --git a/contrib/GestureKeypointDetection/model/hand/hand.cfg b/mxVision/mxVision-referenceapps/GestureKeypointDetection/model/hand/hand.cfg
similarity index 100%
rename from contrib/GestureKeypointDetection/model/hand/hand.cfg
rename to mxVision/mxVision-referenceapps/GestureKeypointDetection/model/hand/hand.cfg
diff --git a/contrib/GestureKeypointDetection/model/hand/model_conversion.sh b/mxVision/mxVision-referenceapps/GestureKeypointDetection/model/hand/model_conversion.sh
similarity index 100%
rename from contrib/GestureKeypointDetection/model/hand/model_conversion.sh
rename to mxVision/mxVision-referenceapps/GestureKeypointDetection/model/hand/model_conversion.sh
diff --git a/contrib/GestureKeypointDetection/model/keypoint/insert_op.cfg b/mxVision/mxVision-referenceapps/GestureKeypointDetection/model/keypoint/insert_op.cfg
similarity index 100%
rename from contrib/GestureKeypointDetection/model/keypoint/insert_op.cfg
rename to mxVision/mxVision-referenceapps/GestureKeypointDetection/model/keypoint/insert_op.cfg
diff --git a/contrib/GestureKeypointDetection/model/keypoint/model_conversion.sh b/mxVision/mxVision-referenceapps/GestureKeypointDetection/model/keypoint/model_conversion.sh
similarity index 100%
rename from contrib/GestureKeypointDetection/model/keypoint/model_conversion.sh
rename to mxVision/mxVision-referenceapps/GestureKeypointDetection/model/keypoint/model_conversion.sh
diff --git a/contrib/HelmetIdentification/Models/HelmetDetection.pipline b/mxVision/mxVision-referenceapps/HelmetIdentification/Models/HelmetDetection.pipline
similarity index 96%
rename from contrib/HelmetIdentification/Models/HelmetDetection.pipline
rename to mxVision/mxVision-referenceapps/HelmetIdentification/Models/HelmetDetection.pipline
index 285630d410fb1183012925b1de9e79cc707f2b14..91f44913da6c2a40ecf9bd1b97b4223787c2c617 100644
--- a/contrib/HelmetIdentification/Models/HelmetDetection.pipline
+++ b/mxVision/mxVision-referenceapps/HelmetIdentification/Models/HelmetDetection.pipline
@@ -1,147 +1,147 @@
-{
-    "Detection":{
-      "stream_config":{
-        "deviceId":"1"
-       },
-       "mxpi_rtspsrc0":{
-            "factory":"mxpi_rtspsrc",
-            "props":{
-                "rtspUrl":"rtsp://xxx.xxx.xxx.xxx:xxxx/xxx.264",
-                "channelId":"0"
-            },
-            "next":"queuerstp0"
-        },
-        "mxpi_rtspsrc1":{
-            "factory":"mxpi_rtspsrc",
-            "props":{
-                "rtspUrl":"rtsp://xxx.xxx.xxx.xxx:xxxx/xxx.264",
-                "channelId":"1"
-            },
-            "next":"queuerstp1"
-        },
-        "queuerstp0":{
-            "props":{
-                "max-size-buffers":"50"
-            },
-            "factory":"queue",
-            "next":"mxpi_videodecoder0"
-        },
-        "queuerstp1":{
-            "props":{
-                "max-size-buffers":"50"
-            },
-            "factory":"queue",
-            "next":"mxpi_videodecoder1"
-        },
-        "mxpi_videodecoder0":{
-            "factory":"mxpi_videodecoder",
-            "props":{
-                "deviceId":"1",
-                "inputVideoFormat":"H264",
-                "outputImageFormat":"YUV420SP_NV12",
-                "vdecChannelId":"0"
-            },
-            "next":"queue01"
-        },
-        "queue01":{
-            "props":{
-                "max-size-buffers":"500"
-            },
-            "factory":"queue",
-            "next":"mxpi_selectedframe0"
-        },
-        "mxpi_videodecoder1":{
-            "factory":"mxpi_videodecoder",
-            "props":{
-                "deviceId":"1",
-                "inputVideoFormat":"H264",
-                "outputImageFormat":"YUV420SP_NV12",
-                "vdecChannelId":"1"
-            },
-            "next":"queue11"
-        },
-        "queue11":{
-            "props":{
-                "max-size-buffers":"500"
-            },
-            "factory":"queue",
-            "next":"mxpi_selectedframe1"
-        },
-        "mxpi_selectedframe0":{
-            "factory":"mxpi_selectedframe",
-            "next":"mxpi_parallel2serial0:0",
-            "props":{
-                "frameNum":"2"
-            }
-        },
-        "mxpi_selectedframe1":{
-            "factory":"mxpi_selectedframe",
-            "next":"mxpi_parallel2serial0:1",
-            "props":{
-                "frameNum":"2"
-            }
-        },
-        "mxpi_parallel2serial0":{
-            "factory":"mxpi_parallel2serial",
-            "props":{
-                "dataSource":"mxpi_videodecoder0,mxpi_videodecoder1"
-            },
-            "next":"mxpi_imageresize0"
-        },
-        "mxpi_imageresize0":{
-            "props":{
-                "dataSource":"mxpi_parallel2serial0",
-                "resizeType": "Resizer_KeepAspectRatio_Fit",
-                "resizeHeight":"640",
-                "resizeWidth":"640"
-            },
-            "factory":"mxpi_imageresize",
-            "next":"queue0"
-        },
-        "queue0":{
-            "props":{
-                "max-size-buffers":"500"
-            },
-            "factory":"queue",
-            "next":"mxpi_modelinfer0"
-        },
-        "mxpi_modelinfer0":{
-            "props":{
-                "dataSource":"mxpi_imageresize0",
-                "modelPath":"./YOLOv5_s.om",
-                "postProcessConfigPath":"./Helmet_yolov5.cfg",
-                "labelPath":"./imgclass.names",
-                "postProcessLibPath":"./libMpYOLOv5PostProcessor.so"
-            },
-            "factory":"mxpi_modelinfer",
-            "next":"queue1"
-        },
-        "queue1":{
-            "props":{
-                "max-size-buffers":"50"
-            },
-            "factory":"queue",
-            "next":"mxpi_motsimplesort0"
-        },
-        "mxpi_motsimplesort0": {
-                "props": {
-                    "dataSourceDetection": "mxpi_modelinfer0"
-                },
-                "factory": "mxpi_motsimplesort",
-                "next": "mxpi_dataserialize0"
-        },
-        "mxpi_dataserialize0": {
-            "props": {
-                "outputDataKeys": "ReservedFrameInfo,mxpi_modelinfer0"
-            },
-            "factory": "mxpi_dataserialize",
-            "next": "appsink0"
-        },
-        "appsink0": {
-            "props": {
-                "blocksize": "4096000"
-            },
-            "factory": "appsink"
-        }
-    }
-}
+{
+    "Detection":{
+      "stream_config":{
+        "deviceId":"1"
+       },
+       "mxpi_rtspsrc0":{
+            "factory":"mxpi_rtspsrc",
+            "props":{
+                "rtspUrl":"rtsp://xxx.xxx.xxx.xxx:xxxx/xxx.264",
+                "channelId":"0"
+            },
+            "next":"queuerstp0"
+        },
+        "mxpi_rtspsrc1":{
+            "factory":"mxpi_rtspsrc",
+            "props":{
+                "rtspUrl":"rtsp://xxx.xxx.xxx.xxx:xxxx/xxx.264",
+                "channelId":"1"
+            },
+            "next":"queuerstp1"
+        },
+        "queuerstp0":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_videodecoder0"
+        },
+        "queuerstp1":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_videodecoder1"
+        },
+        "mxpi_videodecoder0":{
+            "factory":"mxpi_videodecoder",
+            "props":{
+                "deviceId":"1",
+                "inputVideoFormat":"H264",
+                "outputImageFormat":"YUV420SP_NV12",
+                "vdecChannelId":"0"
+            },
+            "next":"queue01"
+        },
+        "queue01":{
+            "props":{
+                "max-size-buffers":"500"
+            },
+            "factory":"queue",
+            "next":"mxpi_selectedframe0"
+        },
+        "mxpi_videodecoder1":{
+            "factory":"mxpi_videodecoder",
+            "props":{
+                "deviceId":"1",
+                "inputVideoFormat":"H264",
+                "outputImageFormat":"YUV420SP_NV12",
+                "vdecChannelId":"1"
+            },
+            "next":"queue11"
+        },
+        "queue11":{
+            "props":{
+                "max-size-buffers":"500"
+            },
+            "factory":"queue",
+            "next":"mxpi_selectedframe1"
+        },
+        "mxpi_selectedframe0":{
+            "factory":"mxpi_selectedframe",
+            "next":"mxpi_parallel2serial0:0",
+            "props":{
+                "frameNum":"2"
+            }
+        },
+        "mxpi_selectedframe1":{
+            "factory":"mxpi_selectedframe",
+            "next":"mxpi_parallel2serial0:1",
+            "props":{
+                "frameNum":"2"
+            }
+        },
+        "mxpi_parallel2serial0":{
+            "factory":"mxpi_parallel2serial",
+            "props":{
+                "dataSource":"mxpi_videodecoder0,mxpi_videodecoder1"
+            },
+            "next":"mxpi_imageresize0"
+        },
+        "mxpi_imageresize0":{
+            "props":{
+                "dataSource":"mxpi_parallel2serial0",
+                "resizeType": "Resizer_KeepAspectRatio_Fit",
+                "resizeHeight":"640",
+                "resizeWidth":"640"
+            },
+            "factory":"mxpi_imageresize",
+            "next":"queue0"
+        },
+        "queue0":{
+            "props":{
+                "max-size-buffers":"500"
+            },
+            "factory":"queue",
+            "next":"mxpi_modelinfer0"
+        },
+        "mxpi_modelinfer0":{
+            "props":{
+                "dataSource":"mxpi_imageresize0",
+                "modelPath":"./YOLOv5_s.om",
+                "postProcessConfigPath":"./Helmet_yolov5.cfg",
+                "labelPath":"./imgclass.names",
+                "postProcessLibPath":"./libMpYOLOv5PostProcessor.so"
+            },
+            "factory":"mxpi_modelinfer",
+            "next":"queue1"
+        },
+        "queue1":{
+            "props":{
+                "max-size-buffers":"50"
+            },
+            "factory":"queue",
+            "next":"mxpi_motsimplesort0"
+        },
+        "mxpi_motsimplesort0": {
+                "props": {
+                    "dataSourceDetection": "mxpi_modelinfer0"
+                },
+                "factory": "mxpi_motsimplesort",
+                "next": "mxpi_dataserialize0"
+        },
+        "mxpi_dataserialize0": {
+            "props": {
+                "outputDataKeys": "ReservedFrameInfo,mxpi_modelinfer0"
+            },
+            "factory": "mxpi_dataserialize",
+            "next": "appsink0"
+        },
+        "appsink0": {
+            "props": {
+                "blocksize": "4096000"
+            },
+            "factory": "appsink"
+        }
+    }
+}
diff --git a/contrib/HelmetIdentification/Models/Helmet_yolov5.cfg b/mxVision/mxVision-referenceapps/HelmetIdentification/Models/Helmet_yolov5.cfg
similarity index 95%
rename from contrib/HelmetIdentification/Models/Helmet_yolov5.cfg
rename to mxVision/mxVision-referenceapps/HelmetIdentification/Models/Helmet_yolov5.cfg
index 18c08f4fec81169a9c414bc602eff4cd4a383701..1489eda74b234eef5bff5be85ec0690fad4bbf17 100644
--- a/contrib/HelmetIdentification/Models/Helmet_yolov5.cfg
+++ b/mxVision/mxVision-referenceapps/HelmetIdentification/Models/Helmet_yolov5.cfg
@@ -1,10 +1,10 @@
-CLASS_NUM=3
-BIASES_NUM=18
-BIASES=10,13,16,30,33,23,30,61,62,45,59,119,116,90,156,198,373,326
-SCORE_THRESH=0.4
-OBJECTNESS_THRESH=0.3
-IOU_THRESH=0.5
-YOLO_TYPE=3
-ANCHOR_DIM=3
-MODEL_TYPE=1
-RESIZE_FLAG=0
+CLASS_NUM=3
+BIASES_NUM=18
+BIASES=10,13,16,30,33,23,30,61,62,45,59,119,116,90,156,198,373,326
+SCORE_THRESH=0.4
+OBJECTNESS_THRESH=0.3
+IOU_THRESH=0.5
+YOLO_TYPE=3
+ANCHOR_DIM=3
+MODEL_TYPE=1
+RESIZE_FLAG=0
diff --git a/contrib/HelmetIdentification/Models/aipp_YOLOv5.config b/mxVision/mxVision-referenceapps/HelmetIdentification/Models/aipp_YOLOv5.config
similarity index 100%
rename from contrib/HelmetIdentification/Models/aipp_YOLOv5.config
rename to mxVision/mxVision-referenceapps/HelmetIdentification/Models/aipp_YOLOv5.config
diff --git a/contrib/HelmetIdentification/Models/atc-env.sh b/mxVision/mxVision-referenceapps/HelmetIdentification/Models/atc-env.sh
similarity index 100%
rename from contrib/HelmetIdentification/Models/atc-env.sh
rename to mxVision/mxVision-referenceapps/HelmetIdentification/Models/atc-env.sh
diff --git a/contrib/HelmetIdentification/Models/imgclass.names b/mxVision/mxVision-referenceapps/HelmetIdentification/Models/imgclass.names
similarity index 90%
rename from contrib/HelmetIdentification/Models/imgclass.names
rename to mxVision/mxVision-referenceapps/HelmetIdentification/Models/imgclass.names
index a7446756be45822fe5719e37169198958c8ed589..46ddf0e6494212b40956a1687da0725218c2e5a5 100644
--- a/contrib/HelmetIdentification/Models/imgclass.names
+++ b/mxVision/mxVision-referenceapps/HelmetIdentification/Models/imgclass.names
@@ -1,3 +1,3 @@
-person
-head
+person
+head
 helmet
\ No newline at end of file
diff --git a/contrib/HelmetIdentification/Models/main.py b/mxVision/mxVision-referenceapps/HelmetIdentification/Models/main.py
similarity index 97%
rename from contrib/HelmetIdentification/Models/main.py
rename to mxVision/mxVision-referenceapps/HelmetIdentification/Models/main.py
index 41b3e97c6b98e37db05c09f49a024d739c65c103..492b8e78e0aa0b0b53ad707ee0e908145f9d1cda 100644
--- a/contrib/HelmetIdentification/Models/main.py
+++ b/mxVision/mxVision-referenceapps/HelmetIdentification/Models/main.py
@@ -1,81 +1,81 @@
-# Copyright 2021 Huawei Technologies Co., Ltd
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-
-# http://www.apache.org/licenses/LICENSE-2.0
-
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-import time
-import signal
-import cv2
-import numpy as np
-import StreamManagerApi
-import utils
-import MxpiDataType_pb2 as MxpiDataType
-
-
-def my_handler(signum, frame):
-    """
-    :param signum: signum are used to identify the signal
-    :param frame: When the signal occurs, get the status of the process stack
-    func:Change flag of stop_stream
-    """
-    global stop_stream
-    stop_stream = True
-
-
-# exit flag
-stop_stream = False
-# When about to exit, get the exit signal
-signal.signal(signal.SIGINT, my_handler)
-
-# The following belongs to the SDK Process
-# init stream manager
-streamManagerApi = StreamManagerApi.StreamManagerApi()
-ret = streamManagerApi.InitManager()
-if ret != 0:
-    print("Failed to init Stream manager, ret=%s" % str(ret))
-
-# create streams by pipeline config file
-#load  pipline
-with open("HelmetDetection.pipline", 'rb') as f:
-    pipelineStr = f.read()
-ret = streamManagerApi.CreateMultipleStreams(pipelineStr)
-# Print error message
-if ret != 0:
-    print("Failed to create Stream, ret=%s" % str(ret))
-
-# Obtain the inference result by specifying streamName and keyVec
-# The data that needs to be obtained is searched by the plug-in name
-# Stream name
-streamName = b'Detection'
-keyVec0 = StreamManagerApi.StringVector()
-keyVec0.push_back(b"ReservedFrameInfo")
-keyVec0.push_back(b"mxpi_modelinfer0")
-keyVec0.push_back(b"mxpi_motsimplesort0")
-keyVec0.push_back(b"mxpi_videodecoder0")
-keyVec0.push_back(b"mxpi_videodecoder1")
-
-while True:
-    # exit flag
-    if stop_stream:
-        break
-    # Get data through GetProtobuf interface
-    inferResult0 = streamManagerApi.GetResult(streamName, b'appsink0', keyVec0)
-    # Determine whether the output is empty
-    if inferResult0.metadataVec.size() == 0:
-        print('Object detection result of model infer is null!!!')
-        continue
-
-    DictStructure = utils.get_inference_data(inferResult0)
-    # the visualization of the inference result, save the output in the specified folder
-    utils.cv_visualization(DictStructure[0], DictStructure[1], DictStructure[2], DictStructure[3], DictStructure[4])
-
-# Destroy All Streams
-streamManagerApi.DestroyAllStreams()
+# Copyright 2021 Huawei Technologies Co., Ltd
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+
+# http://www.apache.org/licenses/LICENSE-2.0
+
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import time
+import signal
+import cv2
+import numpy as np
+import StreamManagerApi
+import utils
+import MxpiDataType_pb2 as MxpiDataType
+
+
+def my_handler(signum, frame):
+    """
+    :param signum: signum are used to identify the signal
+    :param frame: When the signal occurs, get the status of the process stack
+    func:Change flag of stop_stream
+    """
+    global stop_stream
+    stop_stream = True
+
+
+# exit flag
+stop_stream = False
+# When about to exit, get the exit signal
+signal.signal(signal.SIGINT, my_handler)
+
+# The following belongs to the SDK Process
+# init stream manager
+streamManagerApi = StreamManagerApi.StreamManagerApi()
+ret = streamManagerApi.InitManager()
+if ret != 0:
+    print("Failed to init Stream manager, ret=%s" % str(ret))
+
+# create streams by pipeline config file
+#load  pipline
+with open("HelmetDetection.pipline", 'rb') as f:
+    pipelineStr = f.read()
+ret = streamManagerApi.CreateMultipleStreams(pipelineStr)
+# Print error message
+if ret != 0:
+    print("Failed to create Stream, ret=%s" % str(ret))
+
+# Obtain the inference result by specifying streamName and keyVec
+# The data that needs to be obtained is searched by the plug-in name
+# Stream name
+streamName = b'Detection'
+keyVec0 = StreamManagerApi.StringVector()
+keyVec0.push_back(b"ReservedFrameInfo")
+keyVec0.push_back(b"mxpi_modelinfer0")
+keyVec0.push_back(b"mxpi_motsimplesort0")
+keyVec0.push_back(b"mxpi_videodecoder0")
+keyVec0.push_back(b"mxpi_videodecoder1")
+
+while True:
+    # exit flag
+    if stop_stream:
+        break
+    # Get data through GetProtobuf interface
+    inferResult0 = streamManagerApi.GetResult(streamName, b'appsink0', keyVec0)
+    # Determine whether the output is empty
+    if inferResult0.metadataVec.size() == 0:
+        print('Object detection result of model infer is null!!!')
+        continue
+
+    DictStructure = utils.get_inference_data(inferResult0)
+    # the visualization of the inference result, save the output in the specified folder
+    utils.cv_visualization(DictStructure[0], DictStructure[1], DictStructure[2], DictStructure[3], DictStructure[4])
+
+# Destroy All Streams
+streamManagerApi.DestroyAllStreams()
diff --git a/contrib/HelmetIdentification/Models/utils.py b/mxVision/mxVision-referenceapps/HelmetIdentification/Models/utils.py
similarity index 97%
rename from contrib/HelmetIdentification/Models/utils.py
rename to mxVision/mxVision-referenceapps/HelmetIdentification/Models/utils.py
index 7aaa05f513b15d87280aa40e8727007d18c41e12..11ae9cc49b1047763f054472c2a1bfa15df5a03b 100644
--- a/contrib/HelmetIdentification/Models/utils.py
+++ b/mxVision/mxVision-referenceapps/HelmetIdentification/Models/utils.py
@@ -1,123 +1,123 @@
-# Copyright 2021 Huawei Technologies Co., Ltd
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-
-# http://www.apache.org/licenses/LICENSE-2.0
-
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-import signal
-import cv2
-import numpy as np
-import MxpiDataType_pb2 as MxpiDataType
-
-def cv_visualization(img, infer, shape, frame_id, channel_id):
-    """
-    :param img: Inference image
-    :param infer: Inference result
-    :param shape:Size before image padding
-    :param frame_id:Inference image id
-    :param channel_id:Channel id of the current inference image
-    func: the visualization of the inference result, save the output in the specified folder
-    """
-    img_list2 = []
-    print(shape)
-    # The title of the rectangle
-    title_l = (round(0.0002 * (shape[0] + shape[1])) + 0.35)
-    title_f = max(title_l - 1, 1)
-    # Add the inference results of head to img_list2
-    for bbox0 in infer:
-        if bbox0[5] == 'head':
-            img_list2.append(bbox0)
-    for bbox1 in img_list2:
-        # Determine whether it is helmet
-        bboxes = {'x0': int(bbox1[0]),
-                  'x1': int(bbox1[1]),
-                  'y0': int(bbox1[2]),
-                  'y1': int(bbox1[3]),
-                  'confidence': round(bbox1[4], 4),
-                  'trackid': int(bbox1[6]),
-                  'age': int(bbox1[7])
-                  }
-        print(bboxes)
-        bboxes_list1 = []
-        bboxes_list1.append(int(bboxes['x0']))
-        bboxes_list1.append(int(bboxes['x1']))
-        bboxes_list1.append(int(bboxes['y0']))
-        bboxes_list1.append(int(bboxes['y1']))
-        bboxes_list1 = np.array(bboxes_list1, dtype=np.int32)
-        # Draw rectangle
-        cv2.putText(img, str(bboxes['confidence']), (bboxes_list1[0], bboxes_list1[2]), 0, title_l, [225, 255, 255], thickness=title_f,
-                    lineType=cv2.LINE_AA)
-        # rectangle color [255,255,255]
-        cv2.rectangle(img, (bboxes_list1[0], bboxes_list1[2]), (bboxes_list1[1], bboxes_list1[3]), (0, 0, 255), 2)
-        if bboxes['trackid'] is not None and bboxes['age'] == 1:
-            print("Warning:Not wearing a helmet,InferenceId:{},FrameId:{}".format(bboxes['trackid'], frame_id))
-
-    # Save pictures in two ways
-    if channel_id == 0:
-        oringe_imgfile = './output/one/image' + str(channel_id) + '-' + str(
-            frame_id) + '.jpg'
-        # Warning result save path
-        cv2.imwrite(oringe_imgfile, img)
-    else:
-        # when channel_id equal 1
-        oringe_imgfile = './output/two/image' + str(channel_id) + '-' + str(
-            frame_id) + '.jpg'
-        cv2.imwrite(oringe_imgfile, img)
-
-
-def get_inference_data(inference):
-    """
-    :param inference:output of sdk stream inference
-    :return:img0, img_list1, img0_shape, frame_list0.frameId, frame_list0.channelId
-    """
-
-    # add inferennce data into DATA structure
-    # Frame information structure
-    frame_list0 = MxpiDataType.MxpiFrameInfo()
-    frame_list0.ParseFromString(inference.metadataVec[0].serializedMetadata)
-    # Target object structure
-    object_list = MxpiDataType.MxpiObjectList()
-    object_list.ParseFromString(inference.metadataVec[1].serializedMetadata)
-    # Get target box information
-    objectlist_data = object_list.objectVec
-    # track structure
-    tracklet_list = MxpiDataType.MxpiTrackLetList()
-    tracklet_list.ParseFromString(inference.metadataVec[2].serializedMetadata)
-    # Obtain tracking information
-    tracklet_data = tracklet_list.trackLetVec
-    # image structure
-    vision_list0 = MxpiDataType.MxpiVisionList()
-    vision_list0.ParseFromString(inference.metadataVec[3].serializedMetadata)
-    vision_data0 = vision_list0.visionVec[0].visionData.dataStr
-    # Get picture information
-    vision_info0 = vision_list0.visionVec[0].visionInfo
-
-    # cv2 func YUV to BGR
-    yuv_bytes_nu = 3
-    yuv_bytes_de = 2
-    img_yuv = np.frombuffer(vision_data0, dtype=np.uint8)
-    # reshape
-    img_yuv = img_yuv.reshape(vision_info0.heightAligned * yuv_bytes_nu // yuv_bytes_de, vision_info0.widthAligned)
-    # Color gamut conversion
-    img0 = cv2.cvtColor(img_yuv, cv2.COLOR_YUV2BGR_NV12)
-    # put inference into dict,
-    img_list1 = []
-    for k in range(len(object_list.objectVec)):
-        img_list = [round(objectlist_data[k].x0, 4), round(objectlist_data[k].x1, 4), round(objectlist_data[k].y0, 4),
-                 round(objectlist_data[k].y1, 4),
-                 round(objectlist_data[k].classVec[0].confidence, 4), objectlist_data[k].classVec[0].className,
-                 tracklet_data[k].trackId, tracklet_data[k].age]
-        img_list1.append(img_list)
-
-    # img0_shape is the original image size
-    img0_shape = [vision_info0.heightAligned, vision_info0.widthAligned]
-    # Output the results uniformly through the dictionary
-    dict_structure = [img0, img_list1, img0_shape, frame_list0.frameId, frame_list0.channelId]
-    return dict_structure
+# Copyright 2021 Huawei Technologies Co., Ltd
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+
+# http://www.apache.org/licenses/LICENSE-2.0
+
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import signal
+import cv2
+import numpy as np
+import MxpiDataType_pb2 as MxpiDataType
+
+def cv_visualization(img, infer, shape, frame_id, channel_id):
+    """
+    :param img: Inference image
+    :param infer: Inference result
+    :param shape:Size before image padding
+    :param frame_id:Inference image id
+    :param channel_id:Channel id of the current inference image
+    func: the visualization of the inference result, save the output in the specified folder
+    """
+    img_list2 = []
+    print(shape)
+    # The title of the rectangle
+    title_l = (round(0.0002 * (shape[0] + shape[1])) + 0.35)
+    title_f = max(title_l - 1, 1)
+    # Add the inference results of head to img_list2
+    for bbox0 in infer:
+        if bbox0[5] == 'head':
+            img_list2.append(bbox0)
+    for bbox1 in img_list2:
+        # Determine whether it is helmet
+        bboxes = {'x0': int(bbox1[0]),
+                  'x1': int(bbox1[1]),
+                  'y0': int(bbox1[2]),
+                  'y1': int(bbox1[3]),
+                  'confidence': round(bbox1[4], 4),
+                  'trackid': int(bbox1[6]),
+                  'age': int(bbox1[7])
+                  }
+        print(bboxes)
+        bboxes_list1 = []
+        bboxes_list1.append(int(bboxes['x0']))
+        bboxes_list1.append(int(bboxes['x1']))
+        bboxes_list1.append(int(bboxes['y0']))
+        bboxes_list1.append(int(bboxes['y1']))
+        bboxes_list1 = np.array(bboxes_list1, dtype=np.int32)
+        # Draw rectangle
+        cv2.putText(img, str(bboxes['confidence']), (bboxes_list1[0], bboxes_list1[2]), 0, title_l, [225, 255, 255], thickness=title_f,
+                    lineType=cv2.LINE_AA)
+        # rectangle color [255,255,255]
+        cv2.rectangle(img, (bboxes_list1[0], bboxes_list1[2]), (bboxes_list1[1], bboxes_list1[3]), (0, 0, 255), 2)
+        if bboxes['trackid'] is not None and bboxes['age'] == 1:
+            print("Warning:Not wearing a helmet,InferenceId:{},FrameId:{}".format(bboxes['trackid'], frame_id))
+
+    # Save pictures in two ways
+    if channel_id == 0:
+        oringe_imgfile = './output/one/image' + str(channel_id) + '-' + str(
+            frame_id) + '.jpg'
+        # Warning result save path
+        cv2.imwrite(oringe_imgfile, img)
+    else:
+        # when channel_id equal 1
+        oringe_imgfile = './output/two/image' + str(channel_id) + '-' + str(
+            frame_id) + '.jpg'
+        cv2.imwrite(oringe_imgfile, img)
+
+
+def get_inference_data(inference):
+    """
+    :param inference:output of sdk stream inference
+    :return:img0, img_list1, img0_shape, frame_list0.frameId, frame_list0.channelId
+    """
+
+    # add inferennce data into DATA structure
+    # Frame information structure
+    frame_list0 = MxpiDataType.MxpiFrameInfo()
+    frame_list0.ParseFromString(inference.metadataVec[0].serializedMetadata)
+    # Target object structure
+    object_list = MxpiDataType.MxpiObjectList()
+    object_list.ParseFromString(inference.metadataVec[1].serializedMetadata)
+    # Get target box information
+    objectlist_data = object_list.objectVec
+    # track structure
+    tracklet_list = MxpiDataType.MxpiTrackLetList()
+    tracklet_list.ParseFromString(inference.metadataVec[2].serializedMetadata)
+    # Obtain tracking information
+    tracklet_data = tracklet_list.trackLetVec
+    # image structure
+    vision_list0 = MxpiDataType.MxpiVisionList()
+    vision_list0.ParseFromString(inference.metadataVec[3].serializedMetadata)
+    vision_data0 = vision_list0.visionVec[0].visionData.dataStr
+    # Get picture information
+    vision_info0 = vision_list0.visionVec[0].visionInfo
+
+    # cv2 func YUV to BGR
+    yuv_bytes_nu = 3
+    yuv_bytes_de = 2
+    img_yuv = np.frombuffer(vision_data0, dtype=np.uint8)
+    # reshape
+    img_yuv = img_yuv.reshape(vision_info0.heightAligned * yuv_bytes_nu // yuv_bytes_de, vision_info0.widthAligned)
+    # Color gamut conversion
+    img0 = cv2.cvtColor(img_yuv, cv2.COLOR_YUV2BGR_NV12)
+    # put inference into dict,
+    img_list1 = []
+    for k in range(len(object_list.objectVec)):
+        img_list = [round(objectlist_data[k].x0, 4), round(objectlist_data[k].x1, 4), round(objectlist_data[k].y0, 4),
+                 round(objectlist_data[k].y1, 4),
+                 round(objectlist_data[k].classVec[0].confidence, 4), objectlist_data[k].classVec[0].className,
+                 tracklet_data[k].trackId, tracklet_data[k].age]
+        img_list1.append(img_list)
+
+    # img0_shape is the original image size
+    img0_shape = [vision_info0.heightAligned, vision_info0.widthAligned]
+    # Output the results uniformly through the dictionary
+    dict_structure = [img0, img_list1, img0_shape, frame_list0.frameId, frame_list0.channelId]
+    return dict_structure
diff --git a/contrib/HelmetIdentification/README.md b/mxVision/mxVision-referenceapps/HelmetIdentification/README.md
similarity index 98%
rename from contrib/HelmetIdentification/README.md
rename to mxVision/mxVision-referenceapps/HelmetIdentification/README.md
index 858831d15f942ad33382a35c86c84c561a61afbc..bd8c08fc59ed21635fe1c6a22ccbc0fae826f1d6 100644
--- a/contrib/HelmetIdentification/README.md
+++ b/mxVision/mxVision-referenceapps/HelmetIdentification/README.md
@@ -1,313 +1,313 @@
-# 安全帽识别
-
-## 1 介绍
-### 1.1 简介
-安全帽作为工作中一样重要的安全防护用品，主要保护头部，防高空物体坠落，防物体打击、碰撞。通过识别每个人是否戴上安全帽，可以对没戴安全帽的人做出告警。本项目支持2路视频实时分析，其主要流程为:分两路接收外部调用接口的输入视频路径，将视频输入。通过视频解码将264格式视频解码为YUV格式图片。模型推理使用YOLOv5进行安全帽识别，识别结果经过后处理完成NMS得到识别框。对重复检测出的没戴安全帽的对象进行去重。最后将识别结果输出为两路，并对没佩戴安全帽的情况告警。
-
-技术实现流程图如下：
-
-<img src="https://gitee.com/liu-kai6334/mindxsdk-referenceapps/raw/master/contrib/HelmetIdentification/image/image4.jpg" alt="image4" style="zoom: 80%;" />
-
-### 1.2 支持的产品
-
-本项目基于mxVision SDK进行开发，以Atlas 500 A2为主要的硬件平台。
-
-### 1.3 支持的版本
-
-本样例配套的MxVision版本、CANN版本、Driver/Firmware版本如下所示：
-| MxVision版本  |  CANN版本 | Driver/Firmware版本  |
-|--------------- | ---------------------------------- | ----------|
-| 5.0.0 | 7.0.0 | 23.0.0|
-|6.0.RC2 | 8.0.RC2 | 24.1.RC2| 
-
-MindX SDK安装前准备可参考《用户指南》，[安装教程](https://gitee.com/ascend/mindxsdk-referenceapps/blob/master/docs/quickStart/1-1安装SDK开发套件.md)。
-### 1.4 三方依赖
-环境依赖软件和版本如下表：
-
-| 软件                | 版本         | 说明                          | 获取方式                                                     |
-| ------------------- | ------------ | ----------------------------- | ------------------------------------------------------------ |                    
-| opencv-python       | 4.10.0.54     | 用于识别结果画框              | python3 -m pip install opencv-python|
-| libgl1-mesa-glx |23.0.4-0ubuntu1~22.04.1 |GL库（opencv-python可能会依赖GL）|apt install libgl1-mesa-glx|
-| live555|1.10|实现视频转rstp进行推流|[live555使用教程](https://gitee.com/ascend/mindxsdk-referenceapps/blob/master/docs/参考资料/Live555离线视频转RTSP说明文档.md)|
-|ffmpeg|4.4.4 | 实现mp4格式视频转为264格式视频 |[ffmpeg使用教程](https://gitee.com/ascend/mindxsdk-referenceapps/blob/master/docs/参考资料/pc端ffmpeg安装教程.md)
-
-### 1.5 代码目录结构与说明
-
-本sample工程名称为HelmetIdentification，工程目录如下图所示：
-
-```
-├── Models
-  ├── aipp_YOLOv5.config        # 模型转换配置文件
-  ├──atc-env.sh                 # 模型转换脚本
-  ├──YOLOv5_s.om           #推理模型om文件
-  ├──YOLOv5_s.onnx         #推理模型onnx文件
-  ├──Helmet_yolov5.cfg  #后处理配置文件
-  ├──HelmetDetection.pipline # 安全帽识别推理流程pipline
-  ├──imgclass.names  # 模型所有可识别类
-  ├──main.py         # 推理运行程序
-  ├──utils.py  # 数据处理及可视化脚本
-├── plugins  
-  ├──MxpiSelectedFrame # 跳帧插件
-├── Test  
-  ├──performance_test_main.py # 性能测试脚本  
-  ├──test_select.py # 测试集筛选脚本  
-  ├──parse_voc.py # 测试数据集解析脚本  
-  ├──testmain.py # 测试主程序  
-  ├──map_calculate.py # 精度计算程序
-├── build.sh    
-```
-
-## 2 设置环境变量
-设置CANN及MindX SDK相关的环境变量：
-
-```shell
-. /usr/local/Ascend/ascend-toolkit/set_env.sh   # Ascend-cann-toolkit开发套件包默认安装路径，根据实际安装路径修改
-. ${MX_SDK_HOME}/mxVision/set_env.sh   # ${MX_SDK_HOME}替换为用户的SDK安装路径
-```
-
-## 3.准备模型
-
-**步骤1:** 模型下载
-
- 所用模型如下表所示，模型相关信息可参考[原项目链接](https://github.com/PeterH0323/Smart_Construction)。
-
-| 软件名称                | 版本     | 获取方式                                                     |
-| ----------------------- | -------- | ------------------------------------------------------------ |
-| YOLOv5_s.onnx           | YOLOv5_s | [链接](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/HelmetIdentification/model.zip) |
-
-**步骤2：** onnx文件转换为om文件
-
-将下载后解压出来的onnx模型放到Models路径下，并修改该路径下的atc-env.sh，将其中的`${Home}`改为Models所在路径，运行脚本
-
-
-
-```shell
-sh atc-env.sh
-```
-
-提示 **ATC run success** 说明转换成功。
-
-脚本中包含atc命令:
-
-```shell
---model=${Home}/YOLOv5_s.onnx --framework=5 --output=${Home}/YOLOv5_s  --insert_op_conf=./aipp_YOLOv5.config --input_format=NCHW --log=info --soc_version=Ascend310B1 --input_shape="images:1,3,640,640"
-```
-
-其参数如下表所示
-
-| 参数名           | 参数描述                                                     |
-| ---------------- | :----------------------------------------------------------- |
-| --  framework    | 原始框架类型。当取值为5时，即为ONNX网络模型，仅支持ai.onnx算子域中opset v11版本的算 子。用户也可以将其他opset版本的算子（比如opset v9），通过PyTorch转换成 opset v11版本的onnx算子 |
-| --model          | 原始模型文件路径与文件名                                     |
-| --output         | 如果是开源框架的网络模型，存放转换后的离线模型的路径以及文件名。 |
-| --soc_version    | 模型转换时指定芯片版本。昇腾AI处理器的版本，可从ATC工具安装路径的“/usr/local/Ascend/ascend-toolkit/latest/arm64-linux/atc/data/platform_config”目录下 查看。 ".ini"文件的文件名即为对应的${soc_version} |
-| --insert_op_conf | 插入算子的配置文件路径与文件名， 例如aipp预处理算子。        |
-| --input_shape    | 模型输入数据的 shape。                                       |
-| --out_nodes      | 指定输出节点,如果不指定输出节点（算子名称），则模型的输出默认为最后一层的算子信息，如果 指定，则以指定的为准 |
-
-其中--insert_op_conf参数为aipp预处理算子配置文件路径。该配置文件aipp_YOLOv5.config在输入图像进入模型前进行预处理。该配置文件保存在源码Models目录下。
-
-## 4.编译与运行
-### 4.1 编译mxpi_selectedframe插件
-pipline中mxpi_selectedframe插件完成视频跳帧。对于输入帧率为24fps输入视频进行每三帧抽一帧进行识别。实现8fps的帧率。
-
-将目录切换至./plugins/MxpiSelectedFrame，输入如下命令编译生成mxpi_selectedframe.so：
-
-```shell
-mkdir build
-cd build
-cmake ..
-make -j
-```
-
-编译成功后将产生**libmxpi_selectedframe.so**文件，文件生成位置在build目录下。将其复制至SDK的插件库中(./MindX_SDK/mxVision/lib/plugins)，并修改权限为440。
- 注：[插件编译生成教程](https://gitee.com/ascend/docs-openmind/blob/master/guide/mindx/sdk/tutorials/%E5%8F%82%E8%80%83%E8%B5%84%E6%96%99.md)在《SDK用户手册》深入开发章节。
-
-### 4.2 视频推流
-本项目通过mxpi_rtspsrc拉流输入数据，通过两路GetResult接口输出数据，一路输出带有帧信息的图片数据，一路输出带有帧信息的目标检测框和检测框跟踪信息。推理过程如下：
-
-首先通过[live555](https://gitee.com/ascend/mindxsdk-referenceapps/blob/master/docs/参考资料/Live555离线视频转RTSP说明文档.md)进行推流，进入到live555安装目录下mediaServer路径，上传要推流的视频在本目录下然后推流。 live555只支持特定几种格式文件，不支持MP4。 所以本地文件先要转成live555支持的格式。选择使用[ffmpeg](https://gitee.com/ascend/mindxsdk-referenceapps/blob/master/docs/参考资料/pc端ffmpeg安装教程.md)进行格式转换。
-
-转换命令如下：
-
-```shell
-ffmpeg -i xxx1.mp4 -vcodec h264 -bf 0 -g 25 -r 24 -s 1280*720 -an -f h264 xxx2.264
-```
-
-注：参数如下：
-
-| 参数    | 作用                                                   |
-| ------- | ------------------------------------------------------ |
-| -i      | 表示输入的音视频路径需要转换视频                       |
-| -f      | 强迫采用特定格式输出                                   |
-| -r      | 指定帧率输出                                           |
-| -an     | 关闭音频                                               |
-| -s      | 分辨率控制                                             |
-| -g      | 关键帧间隔控制                                         |
-| -vcodec | 设定视频编解码器，未设定时则使用与输入流相同的编解码器 |
-
-转换完成后上传视频至live555安装目录下mediaServer。输入命令进行推流：
-
-```shell
-./live555MediaServer port-id  //port-id为用户推流的端口号
-```
-
-test.264可替换成任意上传至当前目录的[264格式文件](https://gitee.com/ascend/mindxsdk-referenceapps/blob/master/docs/参考资料/pc端ffmpeg安装教程.md)。
-### 4.3 修改pipline文件
-
-pipline根据1.6节中技术实现流程图编写，**HelmetDetection.pipline**放在源码根目录Models。
-
-1. pipline中mxpi_modelinfer用于加载yolov5安全帽识别模型。该插件包含四个参数，modelPath用于加载om模型文件。labelPath用于加载模型可识别类（imgclass.names）。postProcessLibPath用于加载后处理动态链接库文件，该模块实现NMS等后处理。postProcessConfigPath用于加载后处理所需要的配置文件（Helmet_yolov5.cfg）。本项目使用后处理文件为**libMpYOLOv5PostProcessor.so**（在${MX_SDK}/mxVision/lib下）。该后处理配置文件内容如下：              
-```python
-CLASS_NUM=3
-BIASES_NUM=18
-BIASES=10,13,16,30,33,23,30,61,62,45,59,119,116,90,156,198,373,326
-SCORE_THRESH=0.4
-OBJECTNESS_THRESH=0.3
-IOU_THRESH=0.5
-YOLO_TYPE=3
-ANCHOR_DIM=3
-MODEL_TYPE=1
-RESIZE_FLAG=0
-```
-**pipline中以上四个参数要修改为相应文件所在绝对路径**。
-
-2. 修改pipline中mxpi_rtspsrc的拉流路径
-
-![image2](https://gitee.com/liu-kai6334/mindxsdk-referenceapps/raw/master/contrib/HelmetIdentification/image/image2.jpg)
-
-3. 根据使用的device修改deviceId。
-
-### 4.4 运行推理
-
-编写完pipline文件后即可运行推理流程进行识别，该程序**main.py**放在源码根目录Models。
-
-mian.py通过调用sdk接口创建多个流完成数据接收、处理以及输出，接口调用流程图如下所示：
-
-<img src="https://gitee.com/liu-kai6334/mindxsdk-referenceapps/raw/master/contrib/HelmetIdentification/image/image1.jpg" alt="image1" style="zoom:80%;" />
-
-在Models目录下手动创建output/one,output/two两个文件夹
-
-![image3](https://gitee.com/liu-kai6334/mindxsdk-referenceapps/raw/master/contrib/HelmetIdentification/image/image3.jpg)
-
-切换目录至main.py所在目录下，运行命令：
-
-```shell
-python3.9 main.py
-```
-
-### 4.5 查看结果
-输出结果将原来的两路视频分为两个文件保存，utils.py中的oringe_imgfile用于设置图像输出路径。所有数据放置于output中，one 、two为两路视频输出文件。
-
-输出结果有如下几种情况：
-| 序号 | 输入                           | 输出                                                       |
-| ---- | ------------------------------ | ---------------------------------------------------------- |
-| 1    | 两路只有一路输入               | 只打印有输入一路的输出                                     |
-| 2    | 无输入或输入视频中无可识别对象 | 打印：Object detection  result of model infer is null!!!   |
-| 3    | 输入视频有识别对象             | 打印每次推理的head的帧信息的尺寸与识别结果                       |
-| 4    | 识别对象未佩戴安全帽           | 打印：Warning:Not  wearing a helmet, InferenceId：FrameId: |
-
-## 5. 性能验证
-
-性能测试使用脚本Test/performance_test_main.py，该脚本与main.py大体相同，不同之处是在performance_test_main.py中添加了时间戳测试，测试数据为mxpi_rtspsrc拉取的视频流。两路视频尺寸分别取多组不同尺寸的视频做对比。推理三百帧图片后取平均时间值，平均时间值将在**终端上输出结果**。
-设置如下环境变量：
-
-```shell
-export PYTHONPATH=/usr/local/python3.9.2/bin:${MX_SDK_HOME}/python:{path}
-```
-其中{path}设置为根目录中Models所在路径
-
-运行如下命令得到结果：
-
-```shell
-python3.9 performance_test_main.py
-```
-
-注：1.与运行main.py时相同，运行performance_test_main.py时要先使用live555进行推流。**测试视频**上传至[链接](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/HelmetIdentification/test_video.zip)，该视频为不同尺寸不同帧率的同一视频。如test64036830_158s.264为尺寸640×640，帧率30，时长158s的视频。
-
-2.performance_test_main.py中加载pipline文件应写HelmetDetection.pipline的绝对路径。
-
-
-## 6.精度验证
-
-### 6.1 数据集说明
-
-- 数据集来源:  [Safety-Helmet-Wearing-Dataset](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/HelmetIdentification/data.zip)
-
-- 数据集结构
-
-  ```
-  ├── VOC2028
-    ├── Annotations                 # 图片解释文件，含标签等信息，与JPEGImages中图片一一对应
-    ├── ImageSets                 # 存放txt文件
-    ├── JPEGImages                 # 数据集原图片
-  ```
-
-注：将数据集中的三个文件放置于项目的根目录Test文件下，与**test_select.py**同目录。
-
-### 6.2 测试数据集筛选
-
-依据数据集中ImageSets文件夹中test.txt文件，从原始数据集中筛选出测试数据集，该程序**test_select.py**放在源码根目录Test中，在同目录下创建文件夹TestImages用来存储筛选的数据。在该目录下运行命令：
-```shell
-python3.9 test_select.py
-```
-
-程序运行后在根目录Test中会存放筛选出的测试集图片共1517张。
-
-### 6.3 测试数据集解析
-
-解析测试数据集，在同级目录下生成类别文件**voc.names**、图片信息文件**VOC2028.info**和真实标签文件夹**ground_truth**， 该程序**parse_voc.py**放在源码根目录Test中。
-
-运行命令：
-
-```shell
-python3.9 parse_voc.py 
-```
-
-### 6.4 推理运行
-
-依据编写的pipline业务流，对测试数据集进行推理，输出结果保存在同级目录**detection-test-result**文件夹中，该文件需要手动建立。程序**testmain.py**文件放在源码根目录Test中。
-
-注：输出推理结果文件txt中数据格式为：
-
-```shell
-cls conf x0 y0 x1 y1
-```
-
-其中cls表示识别区域所属类别，conf表示识别置信度，(x0,y0)表示识别区域左上角点的坐标，(x1,y1)表示识别区域右下角点的坐标。  
-
-运行命令：
-
-```shell
-python3.9 testmain.py
-```
-
-注：testmain.py中直接写入了pipline，其中mxpi_modelinfer插件四个参数的配置与HelmetDetection.pipline完全相同。
-
-### 6.5 精度计算
-
-推理完成后，依据图片真实标签和推理结果，计算精度。输出结果保存在同级目录**output**文件夹中，该文件需要手动建立。程序map_calculate.py文件放在源码根目录Test中。
-
-注：测试数据集中图片有两类标签"person"（负样本，未佩戴安全帽）和"hat"（正样本，佩戴安全帽）。模型输出标签有三类"person"、"head"、"helmet"，其中"head"与真实标签"person"对应，"helmet"与真实标签"hat"对应。在**map_calculate.py**文件中做了对应转换处理。  
-
-运行命令：
-
-```shell
-python3.9 map_calculate.py --label_path  ./ground-truth  --npu_txt_path ./detection-test-result/ -na -np
-```
-
-### 6.6查看结果
-终端上打印平均精度mAP，precision、recall和map记录在**output/output.txt**文件中。
-
-## 7 常见问题
-
-### 7.1 图片格式问题
-
-**问题描述：**
-
-E0628 10:14:48.309166 8155  DvppImageDecoder.cpp:152] [mxpi_imagedecoder0] [2006] [DVPP:ecode jpeg or jpg fail]
-
-**解决方案：**
-
-本项目只支持jpg图片输入，如输入其他格式会报如上错误。
-
+# 安全帽识别
+
+## 1 介绍
+### 1.1 简介
+安全帽作为工作中一样重要的安全防护用品，主要保护头部，防高空物体坠落，防物体打击、碰撞。通过识别每个人是否戴上安全帽，可以对没戴安全帽的人做出告警。本项目支持2路视频实时分析，其主要流程为:分两路接收外部调用接口的输入视频路径，将视频输入。通过视频解码将264格式视频解码为YUV格式图片。模型推理使用YOLOv5进行安全帽识别，识别结果经过后处理完成NMS得到识别框。对重复检测出的没戴安全帽的对象进行去重。最后将识别结果输出为两路，并对没佩戴安全帽的情况告警。
+
+技术实现流程图如下：
+
+<img src="https://gitee.com/liu-kai6334/mindxsdk-referenceapps/raw/master/contrib/HelmetIdentification/image/image4.jpg" alt="image4" style="zoom: 80%;" />
+
+### 1.2 支持的产品
+
+本项目基于mxVision SDK进行开发，以Atlas 500 A2为主要的硬件平台。
+
+### 1.3 支持的版本
+
+本样例配套的MxVision版本、CANN版本、Driver/Firmware版本如下所示：
+| MxVision版本  |  CANN版本 | Driver/Firmware版本  |
+|--------------- | ---------------------------------- | ----------|
+| 5.0.0 | 7.0.0 | 23.0.0|
+|6.0.RC2 | 8.0.RC2 | 24.1.RC2| 
+
+MindX SDK安装前准备可参考《用户指南》，[安装教程](https://gitee.com/ascend/mindxsdk-referenceapps/blob/master/docs/quickStart/1-1安装SDK开发套件.md)。
+### 1.4 三方依赖
+环境依赖软件和版本如下表：
+
+| 软件                | 版本         | 说明                          | 获取方式                                                     |
+| ------------------- | ------------ | ----------------------------- | ------------------------------------------------------------ |                    
+| opencv-python       | 4.10.0.54     | 用于识别结果画框              | python3 -m pip install opencv-python|
+| libgl1-mesa-glx |23.0.4-0ubuntu1~22.04.1 |GL库（opencv-python可能会依赖GL）|apt install libgl1-mesa-glx|
+| live555|1.10|实现视频转rstp进行推流|[live555使用教程](https://gitee.com/ascend/mindxsdk-referenceapps/blob/master/docs/参考资料/Live555离线视频转RTSP说明文档.md)|
+|ffmpeg|4.4.4 | 实现mp4格式视频转为264格式视频 |[ffmpeg使用教程](https://gitee.com/ascend/mindxsdk-referenceapps/blob/master/docs/参考资料/pc端ffmpeg安装教程.md)
+
+### 1.5 代码目录结构与说明
+
+本sample工程名称为HelmetIdentification，工程目录如下图所示：
+
+```
+├── Models
+  ├── aipp_YOLOv5.config        # 模型转换配置文件
+  ├──atc-env.sh                 # 模型转换脚本
+  ├──YOLOv5_s.om           #推理模型om文件
+  ├──YOLOv5_s.onnx         #推理模型onnx文件
+  ├──Helmet_yolov5.cfg  #后处理配置文件
+  ├──HelmetDetection.pipline # 安全帽识别推理流程pipline
+  ├──imgclass.names  # 模型所有可识别类
+  ├──main.py         # 推理运行程序
+  ├──utils.py  # 数据处理及可视化脚本
+├── plugins  
+  ├──MxpiSelectedFrame # 跳帧插件
+├── Test  
+  ├──performance_test_main.py # 性能测试脚本  
+  ├──test_select.py # 测试集筛选脚本  
+  ├──parse_voc.py # 测试数据集解析脚本  
+  ├──testmain.py # 测试主程序  
+  ├──map_calculate.py # 精度计算程序
+├── build.sh    
+```
+
+## 2 设置环境变量
+设置CANN及MindX SDK相关的环境变量：
+
+```shell
+. /usr/local/Ascend/ascend-toolkit/set_env.sh   # Ascend-cann-toolkit开发套件包默认安装路径，根据实际安装路径修改
+. ${MX_SDK_HOME}/mxVision/set_env.sh   # ${MX_SDK_HOME}替换为用户的SDK安装路径
+```
+
+## 3.准备模型
+
+**步骤1:** 模型下载
+
+ 所用模型如下表所示，模型相关信息可参考[原项目链接](https://github.com/PeterH0323/Smart_Construction)。
+
+| 软件名称                | 版本     | 获取方式                                                     |
+| ----------------------- | -------- | ------------------------------------------------------------ |
+| YOLOv5_s.onnx           | YOLOv5_s | [链接](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/HelmetIdentification/model.zip) |
+
+**步骤2：** onnx文件转换为om文件
+
+将下载后解压出来的onnx模型放到Models路径下，并修改该路径下的atc-env.sh，将其中的`${Home}`改为Models所在路径，运行脚本
+
+
+
+```shell
+sh atc-env.sh
+```
+
+提示 **ATC run success** 说明转换成功。
+
+脚本中包含atc命令:
+
+```shell
+--model=${Home}/YOLOv5_s.onnx --framework=5 --output=${Home}/YOLOv5_s  --insert_op_conf=./aipp_YOLOv5.config --input_format=NCHW --log=info --soc_version=Ascend310B1 --input_shape="images:1,3,640,640"
+```
+
+其参数如下表所示
+
+| 参数名           | 参数描述                                                     |
+| ---------------- | :----------------------------------------------------------- |
+| --  framework    | 原始框架类型。当取值为5时，即为ONNX网络模型，仅支持ai.onnx算子域中opset v11版本的算 子。用户也可以将其他opset版本的算子（比如opset v9），通过PyTorch转换成 opset v11版本的onnx算子 |
+| --model          | 原始模型文件路径与文件名                                     |
+| --output         | 如果是开源框架的网络模型，存放转换后的离线模型的路径以及文件名。 |
+| --soc_version    | 模型转换时指定芯片版本。昇腾AI处理器的版本，可从ATC工具安装路径的“/usr/local/Ascend/ascend-toolkit/latest/arm64-linux/atc/data/platform_config”目录下 查看。 ".ini"文件的文件名即为对应的${soc_version} |
+| --insert_op_conf | 插入算子的配置文件路径与文件名， 例如aipp预处理算子。        |
+| --input_shape    | 模型输入数据的 shape。                                       |
+| --out_nodes      | 指定输出节点,如果不指定输出节点（算子名称），则模型的输出默认为最后一层的算子信息，如果 指定，则以指定的为准 |
+
+其中--insert_op_conf参数为aipp预处理算子配置文件路径。该配置文件aipp_YOLOv5.config在输入图像进入模型前进行预处理。该配置文件保存在源码Models目录下。
+
+## 4.编译与运行
+### 4.1 编译mxpi_selectedframe插件
+pipline中mxpi_selectedframe插件完成视频跳帧。对于输入帧率为24fps输入视频进行每三帧抽一帧进行识别。实现8fps的帧率。
+
+将目录切换至./plugins/MxpiSelectedFrame，输入如下命令编译生成mxpi_selectedframe.so：
+
+```shell
+mkdir build
+cd build
+cmake ..
+make -j
+```
+
+编译成功后将产生**libmxpi_selectedframe.so**文件，文件生成位置在build目录下。将其复制至SDK的插件库中(./MindX_SDK/mxVision/lib/plugins)，并修改权限为440。
+ 注：[插件编译生成教程](https://gitee.com/ascend/docs-openmind/blob/master/guide/mindx/sdk/tutorials/%E5%8F%82%E8%80%83%E8%B5%84%E6%96%99.md)在《SDK用户手册》深入开发章节。
+
+### 4.2 视频推流
+本项目通过mxpi_rtspsrc拉流输入数据，通过两路GetResult接口输出数据，一路输出带有帧信息的图片数据，一路输出带有帧信息的目标检测框和检测框跟踪信息。推理过程如下：
+
+首先通过[live555](https://gitee.com/ascend/mindxsdk-referenceapps/blob/master/docs/参考资料/Live555离线视频转RTSP说明文档.md)进行推流，进入到live555安装目录下mediaServer路径，上传要推流的视频在本目录下然后推流。 live555只支持特定几种格式文件，不支持MP4。 所以本地文件先要转成live555支持的格式。选择使用[ffmpeg](https://gitee.com/ascend/mindxsdk-referenceapps/blob/master/docs/参考资料/pc端ffmpeg安装教程.md)进行格式转换。
+
+转换命令如下：
+
+```shell
+ffmpeg -i xxx1.mp4 -vcodec h264 -bf 0 -g 25 -r 24 -s 1280*720 -an -f h264 xxx2.264
+```
+
+注：参数如下：
+
+| 参数    | 作用                                                   |
+| ------- | ------------------------------------------------------ |
+| -i      | 表示输入的音视频路径需要转换视频                       |
+| -f      | 强迫采用特定格式输出                                   |
+| -r      | 指定帧率输出                                           |
+| -an     | 关闭音频                                               |
+| -s      | 分辨率控制                                             |
+| -g      | 关键帧间隔控制                                         |
+| -vcodec | 设定视频编解码器，未设定时则使用与输入流相同的编解码器 |
+
+转换完成后上传视频至live555安装目录下mediaServer。输入命令进行推流：
+
+```shell
+./live555MediaServer port-id  //port-id为用户推流的端口号
+```
+
+test.264可替换成任意上传至当前目录的[264格式文件](https://gitee.com/ascend/mindxsdk-referenceapps/blob/master/docs/参考资料/pc端ffmpeg安装教程.md)。
+### 4.3 修改pipline文件
+
+pipline根据1.6节中技术实现流程图编写，**HelmetDetection.pipline**放在源码根目录Models。
+
+1. pipline中mxpi_modelinfer用于加载yolov5安全帽识别模型。该插件包含四个参数，modelPath用于加载om模型文件。labelPath用于加载模型可识别类（imgclass.names）。postProcessLibPath用于加载后处理动态链接库文件，该模块实现NMS等后处理。postProcessConfigPath用于加载后处理所需要的配置文件（Helmet_yolov5.cfg）。本项目使用后处理文件为**libMpYOLOv5PostProcessor.so**（在${MX_SDK}/mxVision/lib下）。该后处理配置文件内容如下：              
+```python
+CLASS_NUM=3
+BIASES_NUM=18
+BIASES=10,13,16,30,33,23,30,61,62,45,59,119,116,90,156,198,373,326
+SCORE_THRESH=0.4
+OBJECTNESS_THRESH=0.3
+IOU_THRESH=0.5
+YOLO_TYPE=3
+ANCHOR_DIM=3
+MODEL_TYPE=1
+RESIZE_FLAG=0
+```
+**pipline中以上四个参数要修改为相应文件所在绝对路径**。
+
+2. 修改pipline中mxpi_rtspsrc的拉流路径
+
+![image2](https://gitee.com/liu-kai6334/mindxsdk-referenceapps/raw/master/contrib/HelmetIdentification/image/image2.jpg)
+
+3. 根据使用的device修改deviceId。
+
+### 4.4 运行推理
+
+编写完pipline文件后即可运行推理流程进行识别，该程序**main.py**放在源码根目录Models。
+
+mian.py通过调用sdk接口创建多个流完成数据接收、处理以及输出，接口调用流程图如下所示：
+
+<img src="https://gitee.com/liu-kai6334/mindxsdk-referenceapps/raw/master/contrib/HelmetIdentification/image/image1.jpg" alt="image1" style="zoom:80%;" />
+
+在Models目录下手动创建output/one,output/two两个文件夹
+
+![image3](https://gitee.com/liu-kai6334/mindxsdk-referenceapps/raw/master/contrib/HelmetIdentification/image/image3.jpg)
+
+切换目录至main.py所在目录下，运行命令：
+
+```shell
+python3.9 main.py
+```
+
+### 4.5 查看结果
+输出结果将原来的两路视频分为两个文件保存，utils.py中的oringe_imgfile用于设置图像输出路径。所有数据放置于output中，one 、two为两路视频输出文件。
+
+输出结果有如下几种情况：
+| 序号 | 输入                           | 输出                                                       |
+| ---- | ------------------------------ | ---------------------------------------------------------- |
+| 1    | 两路只有一路输入               | 只打印有输入一路的输出                                     |
+| 2    | 无输入或输入视频中无可识别对象 | 打印：Object detection  result of model infer is null!!!   |
+| 3    | 输入视频有识别对象             | 打印每次推理的head的帧信息的尺寸与识别结果                       |
+| 4    | 识别对象未佩戴安全帽           | 打印：Warning:Not  wearing a helmet, InferenceId：FrameId: |
+
+## 5. 性能验证
+
+性能测试使用脚本Test/performance_test_main.py，该脚本与main.py大体相同，不同之处是在performance_test_main.py中添加了时间戳测试，测试数据为mxpi_rtspsrc拉取的视频流。两路视频尺寸分别取多组不同尺寸的视频做对比。推理三百帧图片后取平均时间值，平均时间值将在**终端上输出结果**。
+设置如下环境变量：
+
+```shell
+export PYTHONPATH=/usr/local/python3.9.2/bin:${MX_SDK_HOME}/python:{path}
+```
+其中{path}设置为根目录中Models所在路径
+
+运行如下命令得到结果：
+
+```shell
+python3.9 performance_test_main.py
+```
+
+注：1.与运行main.py时相同，运行performance_test_main.py时要先使用live555进行推流。**测试视频**上传至[链接](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/HelmetIdentification/test_video.zip)，该视频为不同尺寸不同帧率的同一视频。如test64036830_158s.264为尺寸640×640，帧率30，时长158s的视频。
+
+2.performance_test_main.py中加载pipline文件应写HelmetDetection.pipline的绝对路径。
+
+
+## 6.精度验证
+
+### 6.1 数据集说明
+
+- 数据集来源:  [Safety-Helmet-Wearing-Dataset](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/HelmetIdentification/data.zip)
+
+- 数据集结构
+
+  ```
+  ├── VOC2028
+    ├── Annotations                 # 图片解释文件，含标签等信息，与JPEGImages中图片一一对应
+    ├── ImageSets                 # 存放txt文件
+    ├── JPEGImages                 # 数据集原图片
+  ```
+
+注：将数据集中的三个文件放置于项目的根目录Test文件下，与**test_select.py**同目录。
+
+### 6.2 测试数据集筛选
+
+依据数据集中ImageSets文件夹中test.txt文件，从原始数据集中筛选出测试数据集，该程序**test_select.py**放在源码根目录Test中，在同目录下创建文件夹TestImages用来存储筛选的数据。在该目录下运行命令：
+```shell
+python3.9 test_select.py
+```
+
+程序运行后在根目录Test中会存放筛选出的测试集图片共1517张。
+
+### 6.3 测试数据集解析
+
+解析测试数据集，在同级目录下生成类别文件**voc.names**、图片信息文件**VOC2028.info**和真实标签文件夹**ground_truth**， 该程序**parse_voc.py**放在源码根目录Test中。
+
+运行命令：
+
+```shell
+python3.9 parse_voc.py 
+```
+
+### 6.4 推理运行
+
+依据编写的pipline业务流，对测试数据集进行推理，输出结果保存在同级目录**detection-test-result**文件夹中，该文件需要手动建立。程序**testmain.py**文件放在源码根目录Test中。
+
+注：输出推理结果文件txt中数据格式为：
+
+```shell
+cls conf x0 y0 x1 y1
+```
+
+其中cls表示识别区域所属类别，conf表示识别置信度，(x0,y0)表示识别区域左上角点的坐标，(x1,y1)表示识别区域右下角点的坐标。  
+
+运行命令：
+
+```shell
+python3.9 testmain.py
+```
+
+注：testmain.py中直接写入了pipline，其中mxpi_modelinfer插件四个参数的配置与HelmetDetection.pipline完全相同。
+
+### 6.5 精度计算
+
+推理完成后，依据图片真实标签和推理结果，计算精度。输出结果保存在同级目录**output**文件夹中，该文件需要手动建立。程序map_calculate.py文件放在源码根目录Test中。
+
+注：测试数据集中图片有两类标签"person"（负样本，未佩戴安全帽）和"hat"（正样本，佩戴安全帽）。模型输出标签有三类"person"、"head"、"helmet"，其中"head"与真实标签"person"对应，"helmet"与真实标签"hat"对应。在**map_calculate.py**文件中做了对应转换处理。  
+
+运行命令：
+
+```shell
+python3.9 map_calculate.py --label_path  ./ground-truth  --npu_txt_path ./detection-test-result/ -na -np
+```
+
+### 6.6查看结果
+终端上打印平均精度mAP，precision、recall和map记录在**output/output.txt**文件中。
+
+## 7 常见问题
+
+### 7.1 图片格式问题
+
+**问题描述：**
+
+E0628 10:14:48.309166 8155  DvppImageDecoder.cpp:152] [mxpi_imagedecoder0] [2006] [DVPP:ecode jpeg or jpg fail]
+
+**解决方案：**
+
+本项目只支持jpg图片输入，如输入其他格式会报如上错误。
+
diff --git a/contrib/HelmetIdentification/Test/map_calculate.py b/mxVision/mxVision-referenceapps/HelmetIdentification/Test/map_calculate.py
similarity index 100%
rename from contrib/HelmetIdentification/Test/map_calculate.py
rename to mxVision/mxVision-referenceapps/HelmetIdentification/Test/map_calculate.py
diff --git a/contrib/HelmetIdentification/Test/parse_voc.py b/mxVision/mxVision-referenceapps/HelmetIdentification/Test/parse_voc.py
similarity index 97%
rename from contrib/HelmetIdentification/Test/parse_voc.py
rename to mxVision/mxVision-referenceapps/HelmetIdentification/Test/parse_voc.py
index 58702776284ade3fca68c6a7fe78c87aff423d53..6ea0605bac365fdde624da75fa5eb90219c4a8ac 100644
--- a/contrib/HelmetIdentification/Test/parse_voc.py
+++ b/mxVision/mxVision-referenceapps/HelmetIdentification/Test/parse_voc.py
@@ -1,94 +1,94 @@
-# Copyright 2021 Huawei Technologies Co., Ltd
-
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-
-# http://www.apache.org/licenses/LICENSE-2.0
-
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-import os
-import argparse
-import xml.etree.ElementTree as ET
-
-CLASSES = ('person', 'hat')
-
-def main(arg):
-    """
-    gain ground-truth
-    """
-    info = open('./VOC2028.info', 'w')
-    cls = open('./voc.names', 'w')
-    for i in CLASSES:
-        cls.write(i)
-        cls.write('\n')
-
-    for idx, jpg_name in enumerate(os.listdir(arg.img_path)):
-        key_name = jpg_name.split('.')[0]
-        xml_name = os.path.join(arg.ann_path, key_name + '.xml')
-        #parse xml
-        tree = ET.parse(xml_name)
-        root = tree.getroot()
-        size = root.find('size')
-        width = size.find('width').text
-        height = size.find('height').text
-        info.write('{} {} {} {}'.format(idx, os.path.join(arg.img_path, jpg_name), width, height))
-        info.write('\n')
-
-        with open('{}/{}'.format(arg.gtp, key_name + '.txt'), 'w') as f:
-            for obj in root.iter('object'):
-                difficult = int(obj.find('difficult').text)
-                cls_name = obj.find('name').text.strip().lower()
-                if cls_name not in CLASSES:
-                    continue
-                xml_box = obj.find('bndbox')
-                xmin = (float(xml_box.find('xmin').text))
-                ymin = (float(xml_box.find('ymin').text))
-                xmax = (float(xml_box.find('xmax').text))
-                ymax = (float(xml_box.find('ymax').text))
-
-                if difficult:
-                    comment = '{} {} {} {} {} {}'.format(cls_name, xmin, ymin, xmax, ymax, 'difficult')
-                else:
-                    comment = '{} {} {} {} {}'.format(cls_name, xmin, ymin, xmax, ymax)
-                f.write(comment)
-                f.write('\n')
- 
-
-def err_msg(msg):
-    """
-    print error message
-    """
-    print('-' * 55)
-    print("The specified '{}' file does not exist".format(msg))
-    print('You can get the correct parameter information from -h')
-    print('-' * 55)
-    exit()
-
-
-def check_args(param):
-    """
-    check input args
-    """
-    if not os.path.exists(param.img_path):
-        err_msg(param.img_path)
-    if not os.path.exists(param.ann_path):
-        err_msg(param.ann_path)
-    if not os.path.exists(param.gtp):
-        os.makedirs(param.gtp)
-    return param
-
-if __name__ == '__main__':
-    parser = argparse.ArgumentParser(description='Parse the VOC2028 dataset label')
-    parser.add_argument("--img_path", default="TestImages", help='The image path')
-    parser.add_argument("--ann_path", default="Annotations", help='Origin xml path')
-    parser.add_argument("--gtp", default="ground-truth/", help='The ground true file path')
-    args = parser.parse_args()
-    args = check_args(args)
-    main(args)
+# Copyright 2021 Huawei Technologies Co., Ltd
+
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+
+# http://www.apache.org/licenses/LICENSE-2.0
+
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import os
+import argparse
+import xml.etree.ElementTree as ET
+
+CLASSES = ('person', 'hat')
+
+def main(arg):
+    """
+    gain ground-truth
+    """
+    info = open('./VOC2028.info', 'w')
+    cls = open('./voc.names', 'w')
+    for i in CLASSES:
+        cls.write(i)
+        cls.write('\n')
+
+    for idx, jpg_name in enumerate(os.listdir(arg.img_path)):
+        key_name = jpg_name.split('.')[0]
+        xml_name = os.path.join(arg.ann_path, key_name + '.xml')
+        #parse xml
+        tree = ET.parse(xml_name)
+        root = tree.getroot()
+        size = root.find('size')
+        width = size.find('width').text
+        height = size.find('height').text
+        info.write('{} {} {} {}'.format(idx, os.path.join(arg.img_path, jpg_name), width, height))
+        info.write('\n')
+
+        with open('{}/{}'.format(arg.gtp, key_name + '.txt'), 'w') as f:
+            for obj in root.iter('object'):
+                difficult = int(obj.find('difficult').text)
+                cls_name = obj.find('name').text.strip().lower()
+                if cls_name not in CLASSES:
+                    continue
+                xml_box = obj.find('bndbox')
+                xmin = (float(xml_box.find('xmin').text))
+                ymin = (float(xml_box.find('ymin').text))
+                xmax = (float(xml_box.find('xmax').text))
+                ymax = (float(xml_box.find('ymax').text))
+
+                if difficult:
+                    comment = '{} {} {} {} {} {}'.format(cls_name, xmin, ymin, xmax, ymax, 'difficult')
+                else:
+                    comment = '{} {} {} {} {}'.format(cls_name, xmin, ymin, xmax, ymax)
+                f.write(comment)
+                f.write('\n')
+ 
+
+def err_msg(msg):
+    """
+    print error message
+    """
+    print('-' * 55)
+    print("The specified '{}' file does not exist".format(msg))
+    print('You can get the correct parameter information from -h')
+    print('-' * 55)
+    exit()
+
+
+def check_args(param):
+    """
+    check input args
+    """
+    if not os.path.exists(param.img_path):
+        err_msg(param.img_path)
+    if not os.path.exists(param.ann_path):
+        err_msg(param.ann_path)
+    if not os.path.exists(param.gtp):
+        os.makedirs(param.gtp)
+    return param
+
+if __name__ == '__main__':
+    parser = argparse.ArgumentParser(description='Parse the VOC2028 dataset label')
+    parser.add_argument("--img_path", default="TestImages", help='The image path')
+    parser.add_argument("--ann_path", default="Annotations", help='Origin xml path')
+    parser.add_argument("--gtp", default="ground-truth/", help='The ground true file path')
+    args = parser.parse_args()
+    args = check_args(args)
+    main(args)
     
\ No newline at end of file
diff --git a/contrib/HelmetIdentification/Test/performance_test_main.py b/mxVision/mxVision-referenceapps/HelmetIdentification/Test/performance_test_main.py
similarity index 96%
rename from contrib/HelmetIdentification/Test/performance_test_main.py
rename to mxVision/mxVision-referenceapps/HelmetIdentification/Test/performance_test_main.py
index 7350d8ddf7483698c02ce441597bcac57483e8a9..61ece7ee2d3616eb53be3e16769411ea4da250af 100644
--- a/contrib/HelmetIdentification/Test/performance_test_main.py
+++ b/mxVision/mxVision-referenceapps/HelmetIdentification/Test/performance_test_main.py
@@ -1,90 +1,90 @@
-# Copyright 2021 Huawei Technologies Co., Ltd
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-
-# http://www.apache.org/licenses/LICENSE-2.0
-
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-import time
-import signal
-import cv2
-import numpy as np
-import StreamManagerApi
-import MxpiDataType_pb2 as MxpiDataType
-import utils
-
-
-def my_handler(signum, frame):
-    """
-    :param signum: signum are used to identify the signal
-    :param frame: When the signal occurs, get the status of the process stack
-    func:Change flag of stop_stream
-    """
-    global stop_stream
-    stop_stream = True
-
-
-# exit flag
-stop_stream = False
-# When about to exit, get the exit signal
-signal.signal(signal.SIGINT, my_handler)
-
-# The following belongs to the SDK Process
-# init stream manager
-streamManagerApi = StreamManagerApi.StreamManagerApi()
-ret = streamManagerApi.InitManager()
-if ret != 0:
-    print("Failed to init Stream manager, ret=%s" % str(ret))
-
-# create streams by pipeline config file
-#load  pipline
-with open("HelmetDetection.pipline", 'rb') as f:
-    pipelineStr = f.read()
-ret = streamManagerApi.CreateMultipleStreams(pipelineStr)
-# Print error message
-if ret != 0:
-    print("Failed to create Stream, ret=%s" % str(ret))
-
-# Obtain the inference result by specifying streamName and keyVec
-# The data that needs to be obtained is searched by the plug-in name
-# Stream name
-streamName = b'Detection'
-keyVec0 = StreamManagerApi.StringVector()
-keyVec0.push_back(b"ReservedFrameInfo")
-keyVec0.push_back(b"mxpi_modelinfer0")
-keyVec0.push_back(b"mxpi_motsimplesort0")
-keyVec0.push_back(b"mxpi_videodecoder0")
-keyVec0.push_back(b"mxpi_videodecoder1")
-
-i = 0
-t_all = 0
-while True:
-    # exit flag
-    if stop_stream:
-        break
-    i += 1
-    if i > 300:
-        break
-    t1 = time.time()
-    inferResult0 = streamManagerApi.GetResult(streamName, b'appsink0', keyVec0)
-    if inferResult0.metadataVec.size() == 0:
-        print('Object detection result of model infer is null!!!')
-        continue
-
-    DictStructure = utils.get_inference_data(inferResult0)
-    # the visualization of the inference result, save the output in the specified folder
-    utils.cv_visualization(DictStructure[0], DictStructure[1], DictStructure[2], DictStructure[3], DictStructure[4])
-    t2 = time.time()
-    t_diff = t2-t1
-    t_all += t_diff
-t_ave = t_all/i
-print("e2e Time:{}".format(t_ave))
-
-# Destroy All Streams
-streamManagerApi.DestroyAllStreams()
+# Copyright 2021 Huawei Technologies Co., Ltd
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+
+# http://www.apache.org/licenses/LICENSE-2.0
+
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import time
+import signal
+import cv2
+import numpy as np
+import StreamManagerApi
+import MxpiDataType_pb2 as MxpiDataType
+import utils
+
+
+def my_handler(signum, frame):
+    """
+    :param signum: signum are used to identify the signal
+    :param frame: When the signal occurs, get the status of the process stack
+    func:Change flag of stop_stream
+    """
+    global stop_stream
+    stop_stream = True
+
+
+# exit flag
+stop_stream = False
+# When about to exit, get the exit signal
+signal.signal(signal.SIGINT, my_handler)
+
+# The following belongs to the SDK Process
+# init stream manager
+streamManagerApi = StreamManagerApi.StreamManagerApi()
+ret = streamManagerApi.InitManager()
+if ret != 0:
+    print("Failed to init Stream manager, ret=%s" % str(ret))
+
+# create streams by pipeline config file
+#load  pipline
+with open("HelmetDetection.pipline", 'rb') as f:
+    pipelineStr = f.read()
+ret = streamManagerApi.CreateMultipleStreams(pipelineStr)
+# Print error message
+if ret != 0:
+    print("Failed to create Stream, ret=%s" % str(ret))
+
+# Obtain the inference result by specifying streamName and keyVec
+# The data that needs to be obtained is searched by the plug-in name
+# Stream name
+streamName = b'Detection'
+keyVec0 = StreamManagerApi.StringVector()
+keyVec0.push_back(b"ReservedFrameInfo")
+keyVec0.push_back(b"mxpi_modelinfer0")
+keyVec0.push_back(b"mxpi_motsimplesort0")
+keyVec0.push_back(b"mxpi_videodecoder0")
+keyVec0.push_back(b"mxpi_videodecoder1")
+
+i = 0
+t_all = 0
+while True:
+    # exit flag
+    if stop_stream:
+        break
+    i += 1
+    if i > 300:
+        break
+    t1 = time.time()
+    inferResult0 = streamManagerApi.GetResult(streamName, b'appsink0', keyVec0)
+    if inferResult0.metadataVec.size() == 0:
+        print('Object detection result of model infer is null!!!')
+        continue
+
+    DictStructure = utils.get_inference_data(inferResult0)
+    # the visualization of the inference result, save the output in the specified folder
+    utils.cv_visualization(DictStructure[0], DictStructure[1], DictStructure[2], DictStructure[3], DictStructure[4])
+    t2 = time.time()
+    t_diff = t2-t1
+    t_all += t_diff
+t_ave = t_all/i
+print("e2e Time:{}".format(t_ave))
+
+# Destroy All Streams
+streamManagerApi.DestroyAllStreams()
diff --git a/contrib/HelmetIdentification/Test/test_select.py b/mxVision/mxVision-referenceapps/HelmetIdentification/Test/test_select.py
similarity index 100%
rename from contrib/HelmetIdentification/Test/test_select.py
rename to mxVision/mxVision-referenceapps/HelmetIdentification/Test/test_select.py
diff --git a/contrib/HelmetIdentification/Test/testmain.py b/mxVision/mxVision-referenceapps/HelmetIdentification/Test/testmain.py
similarity index 97%
rename from contrib/HelmetIdentification/Test/testmain.py
rename to mxVision/mxVision-referenceapps/HelmetIdentification/Test/testmain.py
index df6c1bb34ace98a34b81144274e97f7d0309d4f3..410677ddf66ee2bbc46bb1702ed41d93514eef5d 100644
--- a/contrib/HelmetIdentification/Test/testmain.py
+++ b/mxVision/mxVision-referenceapps/HelmetIdentification/Test/testmain.py
@@ -1,162 +1,162 @@
-# Copyright 2021 Huawei Technologies Co., Ltd
-
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-
-# http://www.apache.org/licenses/LICENSE-2.0
-
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-import json
-import os
-import random
-import cv2
-import numpy as np
-import StreamManagerApi
-import MxpiDataType_pb2 as MxpiDataType
-
-if __name__ == '__main__':
-    # init stream manager
-    streamManagerApi = StreamManagerApi.StreamManagerApi()
-    ret = streamManagerApi.InitManager()
-    if ret != 0:
-        print("Failed to init Stream manager, ret=%s" % str(ret))
-        exit()
-
-    # create streams by pipeline config file
-    pipeline = {
-            "detection": {
-                "stream_config": {
-                    "deviceId": "1"
-                },
-                "appsrc0": {
-                    "props": {
-                        "blocksize": "409600"
-                    },
-                    "factory": "appsrc",
-                    "next": "mxpi_imagedecoder0"
-                },
-                "mxpi_imagedecoder0": {
-                    "factory": "mxpi_imagedecoder",
-                    "next": "mxpi_imageresize0"
-                },
-                "mxpi_imageresize0": {
-                    "factory": "mxpi_imageresize",
-                    "props": {
-                        "dataSource": "mxpi_imagedecoder0",
-                        "resizeType": "Resizer_KeepAspectRatio_Fit",
-                        "resizeHeight": "640",
-                        "resizeWidth": "640"
-                    },
-                    "next": "queue0"
-                },
-                "queue0": {
-                    "props": {
-                        "max-size-buffers": "500"
-                    },
-                    "factory": "queue",
-                    "next": "mxpi_modelinfer0"
-                },
-                "mxpi_modelinfer0": {
-                    "props":{
-                        "dataSource":"mxpi_imageresize0",
-                        "modelPath":"./YOLOv5_s.om",
-                        "postProcessConfigPath":"./Helmet_yolov5.cfg",
-                        "labelPath":"./imgclass.names",
-                        "postProcessLibPath":"./libMpYOLOv5PostProcessor.so"
-                    },
-                    "factory": "mxpi_modelinfer",
-                    "next": "mxpi_dataserialize0"
-                },
-                "mxpi_dataserialize0": {
-                    "props": {
-                        "outputDataKeys": "mxpi_modelinfer0"
-                    },
-                    "factory": "mxpi_dataserialize",
-                    "next": "appsink0"
-                },
-                "appsink0": {
-                    "props": {
-                        "blocksize": "4096000"
-                    },
-                    "factory": "appsink"
-                }
-            }
-    }
-
-    pipelineStr = json.dumps(pipeline).encode()
-    ret = streamManagerApi.CreateMultipleStreams(pipelineStr)
-    if ret != 0:
-        print("Failed to create Stream, ret=%s" % str(ret))
-        exit()
-
-    path = "./TestImages/"
-    for item in os.listdir(path):
-        img_path = os.path.join(path,item)
-        print("file_path:",img_path)
-        img_name = item.split(".")[0]
-        img_txt = "./detection-test-result/" + img_name + ".txt"
-        if os.path.exists(img_txt):
-            os.remove(img_txt)
-        dataInput = StreamManagerApi.MxDataInput()
-        if os.path.exists(img_path) != 1:
-            print("The test image does not exist.")
-
-        with open(img_path, 'rb') as f:
-            dataInput.data = f.read()
-
-
-        # Inputs data to a specified stream based on streamName.
-        streamName = b'detection'
-        ret = streamManagerApi.SendData(streamName, 0, dataInput)
-
-        if ret < 0:
-            print("Failed to send data to stream.")
-
-
-        # Obtain the inference result by specifying streamName and uniqueId.
-        infer_result = streamManagerApi.GetResult(streamName, 0)
-        if infer_result.errorCode != 0:
-            print("GetResult error. errorCode=%d, errorMsg=%s" % (
-                infer_result.errorCode, infer_result.data.decode()))
-
-        # print the infer result
-
-        results = json.loads(infer_result.data.decode())
-        img = cv2.imread(img_path)
-        img_shape = img.shape
-        print(img_shape)
-        bboxes = []
-        key = "MxpiObject"
-        if key not in results.keys():
-            continue
-        for bbox in results['MxpiObject']:
-            bboxes = {'x0': int(bbox['x0']),
-                      'x1': int(bbox['x1']),
-                      'y0': int(bbox['y0']),
-                      'y1': int(bbox['y1']),
-                      'confidence': round(bbox['classVec'][0]['confidence'], 4),
-                      'text': bbox['classVec'][0]['className']}
-            text = "{}{}".format(str(bboxes['confidence']), " ")
-            print(bboxes)
-            L1 = []
-            L1.append(int(bboxes['x0']))
-            L1.append(int(bboxes['x1']))
-            L1.append(int(bboxes['y0']))
-            L1.append(int(bboxes['y1']))
-            L1.append(bboxes['confidence'])
-            L1.append(bboxes['text'])
-            print(L1)
-
-            with open(img_txt,"a+") as f:
-                content = '{} {} {} {} {} {}'.format(L1[5], L1[4], L1[0], L1[2], L1[1], L1[3])
-                f.write(content)
-                f.write('\n')
-
-    # destroy streams
-    streamManagerApi.DestroyAllStreams()
+# Copyright 2021 Huawei Technologies Co., Ltd
+
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+
+# http://www.apache.org/licenses/LICENSE-2.0
+
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import json
+import os
+import random
+import cv2
+import numpy as np
+import StreamManagerApi
+import MxpiDataType_pb2 as MxpiDataType
+
+if __name__ == '__main__':
+    # init stream manager
+    streamManagerApi = StreamManagerApi.StreamManagerApi()
+    ret = streamManagerApi.InitManager()
+    if ret != 0:
+        print("Failed to init Stream manager, ret=%s" % str(ret))
+        exit()
+
+    # create streams by pipeline config file
+    pipeline = {
+            "detection": {
+                "stream_config": {
+                    "deviceId": "1"
+                },
+                "appsrc0": {
+                    "props": {
+                        "blocksize": "409600"
+                    },
+                    "factory": "appsrc",
+                    "next": "mxpi_imagedecoder0"
+                },
+                "mxpi_imagedecoder0": {
+                    "factory": "mxpi_imagedecoder",
+                    "next": "mxpi_imageresize0"
+                },
+                "mxpi_imageresize0": {
+                    "factory": "mxpi_imageresize",
+                    "props": {
+                        "dataSource": "mxpi_imagedecoder0",
+                        "resizeType": "Resizer_KeepAspectRatio_Fit",
+                        "resizeHeight": "640",
+                        "resizeWidth": "640"
+                    },
+                    "next": "queue0"
+                },
+                "queue0": {
+                    "props": {
+                        "max-size-buffers": "500"
+                    },
+                    "factory": "queue",
+                    "next": "mxpi_modelinfer0"
+                },
+                "mxpi_modelinfer0": {
+                    "props":{
+                        "dataSource":"mxpi_imageresize0",
+                        "modelPath":"./YOLOv5_s.om",
+                        "postProcessConfigPath":"./Helmet_yolov5.cfg",
+                        "labelPath":"./imgclass.names",
+                        "postProcessLibPath":"./libMpYOLOv5PostProcessor.so"
+                    },
+                    "factory": "mxpi_modelinfer",
+                    "next": "mxpi_dataserialize0"
+                },
+                "mxpi_dataserialize0": {
+                    "props": {
+                        "outputDataKeys": "mxpi_modelinfer0"
+                    },
+                    "factory": "mxpi_dataserialize",
+                    "next": "appsink0"
+                },
+                "appsink0": {
+                    "props": {
+                        "blocksize": "4096000"
+                    },
+                    "factory": "appsink"
+                }
+            }
+    }
+
+    pipelineStr = json.dumps(pipeline).encode()
+    ret = streamManagerApi.CreateMultipleStreams(pipelineStr)
+    if ret != 0:
+        print("Failed to create Stream, ret=%s" % str(ret))
+        exit()
+
+    path = "./TestImages/"
+    for item in os.listdir(path):
+        img_path = os.path.join(path,item)
+        print("file_path:",img_path)
+        img_name = item.split(".")[0]
+        img_txt = "./detection-test-result/" + img_name + ".txt"
+        if os.path.exists(img_txt):
+            os.remove(img_txt)
+        dataInput = StreamManagerApi.MxDataInput()
+        if os.path.exists(img_path) != 1:
+            print("The test image does not exist.")
+
+        with open(img_path, 'rb') as f:
+            dataInput.data = f.read()
+
+
+        # Inputs data to a specified stream based on streamName.
+        streamName = b'detection'
+        ret = streamManagerApi.SendData(streamName, 0, dataInput)
+
+        if ret < 0:
+            print("Failed to send data to stream.")
+
+
+        # Obtain the inference result by specifying streamName and uniqueId.
+        infer_result = streamManagerApi.GetResult(streamName, 0)
+        if infer_result.errorCode != 0:
+            print("GetResult error. errorCode=%d, errorMsg=%s" % (
+                infer_result.errorCode, infer_result.data.decode()))
+
+        # print the infer result
+
+        results = json.loads(infer_result.data.decode())
+        img = cv2.imread(img_path)
+        img_shape = img.shape
+        print(img_shape)
+        bboxes = []
+        key = "MxpiObject"
+        if key not in results.keys():
+            continue
+        for bbox in results['MxpiObject']:
+            bboxes = {'x0': int(bbox['x0']),
+                      'x1': int(bbox['x1']),
+                      'y0': int(bbox['y0']),
+                      'y1': int(bbox['y1']),
+                      'confidence': round(bbox['classVec'][0]['confidence'], 4),
+                      'text': bbox['classVec'][0]['className']}
+            text = "{}{}".format(str(bboxes['confidence']), " ")
+            print(bboxes)
+            L1 = []
+            L1.append(int(bboxes['x0']))
+            L1.append(int(bboxes['x1']))
+            L1.append(int(bboxes['y0']))
+            L1.append(int(bboxes['y1']))
+            L1.append(bboxes['confidence'])
+            L1.append(bboxes['text'])
+            print(L1)
+
+            with open(img_txt,"a+") as f:
+                content = '{} {} {} {} {} {}'.format(L1[5], L1[4], L1[0], L1[2], L1[1], L1[3])
+                f.write(content)
+                f.write('\n')
+
+    # destroy streams
+    streamManagerApi.DestroyAllStreams()
diff --git a/contrib/HelmetIdentification/build.sh b/mxVision/mxVision-referenceapps/HelmetIdentification/build.sh
similarity index 100%
rename from contrib/HelmetIdentification/build.sh
rename to mxVision/mxVision-referenceapps/HelmetIdentification/build.sh
diff --git a/contrib/HelmetIdentification/image/image1.jpg b/mxVision/mxVision-referenceapps/HelmetIdentification/image/image1.jpg
similarity index 100%
rename from contrib/HelmetIdentification/image/image1.jpg
rename to mxVision/mxVision-referenceapps/HelmetIdentification/image/image1.jpg
diff --git a/contrib/HelmetIdentification/image/image2.jpg b/mxVision/mxVision-referenceapps/HelmetIdentification/image/image2.jpg
similarity index 100%
rename from contrib/HelmetIdentification/image/image2.jpg
rename to mxVision/mxVision-referenceapps/HelmetIdentification/image/image2.jpg
diff --git a/contrib/HelmetIdentification/image/image3.jpg b/mxVision/mxVision-referenceapps/HelmetIdentification/image/image3.jpg
similarity index 100%
rename from contrib/HelmetIdentification/image/image3.jpg
rename to mxVision/mxVision-referenceapps/HelmetIdentification/image/image3.jpg
diff --git a/contrib/HelmetIdentification/image/image4.jpg b/mxVision/mxVision-referenceapps/HelmetIdentification/image/image4.jpg
similarity index 100%
rename from contrib/HelmetIdentification/image/image4.jpg
rename to mxVision/mxVision-referenceapps/HelmetIdentification/image/image4.jpg
diff --git a/contrib/HelmetIdentification/plugins/MxpiSelectedFrame/CMakeLists.txt b/mxVision/mxVision-referenceapps/HelmetIdentification/plugins/MxpiSelectedFrame/CMakeLists.txt
similarity index 100%
rename from contrib/HelmetIdentification/plugins/MxpiSelectedFrame/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/HelmetIdentification/plugins/MxpiSelectedFrame/CMakeLists.txt
diff --git a/contrib/HelmetIdentification/plugins/MxpiSelectedFrame/MxpiSelectedFrame.cpp b/mxVision/mxVision-referenceapps/HelmetIdentification/plugins/MxpiSelectedFrame/MxpiSelectedFrame.cpp
similarity index 100%
rename from contrib/HelmetIdentification/plugins/MxpiSelectedFrame/MxpiSelectedFrame.cpp
rename to mxVision/mxVision-referenceapps/HelmetIdentification/plugins/MxpiSelectedFrame/MxpiSelectedFrame.cpp
diff --git a/contrib/HelmetIdentification/plugins/MxpiSelectedFrame/MxpiSelectedFrame.h b/mxVision/mxVision-referenceapps/HelmetIdentification/plugins/MxpiSelectedFrame/MxpiSelectedFrame.h
similarity index 100%
rename from contrib/HelmetIdentification/plugins/MxpiSelectedFrame/MxpiSelectedFrame.h
rename to mxVision/mxVision-referenceapps/HelmetIdentification/plugins/MxpiSelectedFrame/MxpiSelectedFrame.h
diff --git a/contrib/HelmetIdentification/plugins/MxpiSelectedFrame/build.sh b/mxVision/mxVision-referenceapps/HelmetIdentification/plugins/MxpiSelectedFrame/build.sh
similarity index 100%
rename from contrib/HelmetIdentification/plugins/MxpiSelectedFrame/build.sh
rename to mxVision/mxVision-referenceapps/HelmetIdentification/plugins/MxpiSelectedFrame/build.sh
diff --git a/contrib/IAT/README.md b/mxVision/mxVision-referenceapps/IAT/README.md
similarity index 96%
rename from contrib/IAT/README.md
rename to mxVision/mxVision-referenceapps/IAT/README.md
index efb46e807d3bd2f0d5c0fa7419c67b94d610d55c..b3abff32911670a30d37b16262740f41d86e0ee2 100644
--- a/contrib/IAT/README.md
+++ b/mxVision/mxVision-referenceapps/IAT/README.md
@@ -1,237 +1,237 @@
-# MindX SDK -- RGB图像的夜间增强参考设计
-
-## 1 介绍
-基于 MindX SDK 实现 IAT 模型的推理，在 LOL 数据集上达到 $PSNR\ge$23, $SSIM\ge 0.8$, 并把可视化结果保存到本地，达到预期的功能和精度要求。
-
-### 1.1 支持的产品
-
-支持昇腾310芯片
-
-### 1.2 支持的版本
-
-支持的SDK版本，列出版本号查询方式。
-
-eg：版本号查询方法，在Atlas产品环境下，运行命令：
-
-```
-npu-smi info
-```
-
-版本号为Mind SDK 3.0RC3
-
-### 1.3 软件方案介绍
-
-本方案中，将 PyTorch 版本的低光图像增强模型 [IAT](https://github.com/cuiziteng/illumination-adaptive-transformer)，转化为昇腾的om模型。对于输入的夜间低照度图像，通过调用昇腾om模型进行处理，最终生成经过低光增强后的图像。
-
-
-
-### 1.4 代码目录结构与说明
-
-eg：本sample工程名称为XXX，工程目录如下图所示：
-
-```
-├── images			# README图片文件夹
-├── data		    # 推理图片文件夹
-	├──.keepme  	
-├── models			# 模型文件夹
-	├──.keepme  	
-├── main.py		  	# 推理文件
-├── pth2onnx.py		# 模型转换文件
-└── README.md
-
-```
-
-### 1.5 技术实现流程图
-
-![技术实现流程图](images/技术路线.jpeg)
-
-### 1.6 特性及适用场景
-
-对于夜间图像、低照度图像的增强均使用
-
-
-
-## 2 环境依赖
-
-请列出环境依赖软件和版本。
-
-eg：推荐系统为ubuntu 18.04或centos 7.6，环境依赖软件和版本如下表：
-
-| 软件名称      | 版本             |
-| ------------- | ---------------- |
-| ubuntu        | 18.04.1 LTS      |
-| MindX SDK     | mxVision-3.0.RC3 |
-| Python        | 3.9.2            |
-| CANN          | 5.1.RC2.alpha008 |
-| numpy         | 1.22.3           |
-| opencv-python | 4.5.5            |
-| onnxsim       | 0.4.10           |
-
-在编译运行项目前，需要设置环境变量：
-
-- 环境变量介绍
-
-```
-列出具体执行命令（简化）
-. ${sdk_path}/set_env.sh
-. ${ascend_toolkit_path}/set_env.sh
-```
-
-
-
-## 3 编译与运行
-### 3.1 推理示例代码
-
-**步骤1** （下载原模型代码)
-
-- 下载 PyTorch 版本 [IAT代码](https://github.com/cuiziteng/illumination-adaptive-transformer)
-
-- 根据原模型目录下的README.md文件配置原模型环境，具体代码如下：
-
-  ```
-  $ conda create -n IAT python==3.7.0
-  $ conda activate IAT
-  $ conda install --yes -c pytorch pytorch=1.7.1 torchvision cudatoolkit=11.0
-  $ pip install timm matplotlib IQA_pytorch tqdm
-  ```
-
-
-**步骤2** （配置项目环境）
-
-退出原模型环境，根据第2节环境依赖所述安装相应的项目环境，并设置环境变量。
-
-```
-source ${sdk_path}/set_env.sh
-source ${ascend_toolkit_path}/set_env.sh
-```
-
-**步骤3** （执行编译的步骤）
-
-​    1.pytorch 模型转换 onnx 文件
-
-​	将 `pth2onnx.py` 放到 Illumination-Adaptive_Transformer/IAT_enhance/项目目录下，并切换到原模型环境，运行：
-
-```
-python pth2onnx.py
-```
-
-​    	在该目录下会生成名为IAT_lol.onnx的onnx模型文件 
-
-​    2.简化 onnx 文件	
-
-​	 在上述目录下继续运行:
-
-```
-onnxsim IAT_lol.onnx IAT_lol-sim.onnx
-```
-
-​    	会在路径下生成简化后的IAT_lol-sim.onnx模型文件
-
-​	已经简化好的onnx模型可供参考：[IAT_lol-sim.onnx](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/IAT/IAT_lol-sim.onnx)
-
-​     3.onnx 文件转换 om 文件
-
-​	将环境从原模型环境切换到当前项目环境，然后运行：
-
-```
-atc --framework=5 --model=./IAT_lol-sim.onnx --input_shape="input_1:1,3,400,600" --output=IAT_lol-sim --soc_version=Ascend310
-```
-
-**步骤4** （运行及输出结果）
-
-将要推理的图片放到本项目./data/文件夹下, 并将其改为test.png, 将.om模型放到./models/文件夹下, 命名为iatsim.om。运行:
-
-```
-python main.py
-```
-
-即可在./data/目录下得到推理后的结果.
-
-
-
-## * 4 指标验证
-
-### 4.1 模型规模测试
-
-模型计算量测试需要利用python相关的模型测试工具 fvcore, 在原模型环境中可以使用以下命令进行安装：
-
-```
-pip install fvcore
-```
-
-利用fvcore的相关工具即可测得IAT模型的计算量，测试方法代码如下：
-
-```python
-def evaluate_net():
-    from model.IAT_main import IAT
-    from fvcore.nn import FlopCountAnalysis
-    
-    # 创建IAT网络
-    model = IAT()
-    model = model.cuda()
-    # 创建输入网络的tensor
-    tensor = torch.rand(1, 3, 400, 600).cuda()
-
-    # 分析FLOPs
-    flops = FlopCountAnalysis(model, tensor)
-    print("FLOPs: ", flops.total())
-```
-
-测试结果如下：
-
-![模型计算量](images/模型规模测试.jpeg)
-
-根据[IAT论文](https://github.com/cuiziteng/illumination-adaptive-transformer)所述，该模型参数量约为90K，通过测试得到计算量约为6.019GFLOPs。
-
-
-
-### 4.2 精度测试
-
-**步骤1-3**  与3.1节一致
-
-**步骤4** （获取LOL数据集）
-
-- 下载[LOLv1数据集](https://daooshee.github.io/BMVC2018website/)
-
-- 将数据集解压后将测试集目录(eval15)放到本项目./data/文件夹下,如下图所示:
-
-  ```
-  ├── data		  
-  	├──eval15  	# 精度测试数据集
-  		├──high
-  		├──low
-  ```
-
-**步骤5** （修改主函数并运行）
-
-切换到项目环境下，将main.py中的主函数改为调用test_precision()，运行:
-
-```
-python main.py
-```
-
-即可得到精度测试结果,测试结果如下：
-
-![模型计算量](images/精度测试.jpeg)
-
-
-
-## 5 参考文献
-
-@misc{https://doi.org/10.48550/arxiv.2205.14871,
-  doi = {10.48550/ARXIV.2205.14871},
-
-  url = {https://arxiv.org/abs/2205.14871},
-
-  author = {Cui, Ziteng and Li, Kunchang and Gu, Lin and Su, Shenghan and Gao, Peng and Jiang, Zhengkai and Qiao, Yu and Harada, Tatsuya},
-
-  keywords = {Computer Vision and Pattern Recognition (cs.CV), FOS: Computer and information sciences, FOS: Computer and information sciences},
-
-  title = {You Only Need 90K Parameters to Adapt Light: A Light Weight Transformer for Image Enhancement and Exposure Correction},
-
-  publisher = {arXiv},
-
-  year = {2022},
-
-  copyright = {Creative Commons Attribution 4.0 International}
+# MindX SDK -- RGB图像的夜间增强参考设计
+
+## 1 介绍
+基于 MindX SDK 实现 IAT 模型的推理，在 LOL 数据集上达到 $PSNR\ge$23, $SSIM\ge 0.8$, 并把可视化结果保存到本地，达到预期的功能和精度要求。
+
+### 1.1 支持的产品
+
+支持昇腾310芯片
+
+### 1.2 支持的版本
+
+支持的SDK版本，列出版本号查询方式。
+
+eg：版本号查询方法，在Atlas产品环境下，运行命令：
+
+```
+npu-smi info
+```
+
+版本号为Mind SDK 3.0RC3
+
+### 1.3 软件方案介绍
+
+本方案中，将 PyTorch 版本的低光图像增强模型 [IAT](https://github.com/cuiziteng/illumination-adaptive-transformer)，转化为昇腾的om模型。对于输入的夜间低照度图像，通过调用昇腾om模型进行处理，最终生成经过低光增强后的图像。
+
+
+
+### 1.4 代码目录结构与说明
+
+eg：本sample工程名称为XXX，工程目录如下图所示：
+
+```
+├── images			# README图片文件夹
+├── data		    # 推理图片文件夹
+	├──.keepme  	
+├── models			# 模型文件夹
+	├──.keepme  	
+├── main.py		  	# 推理文件
+├── pth2onnx.py		# 模型转换文件
+└── README.md
+
+```
+
+### 1.5 技术实现流程图
+
+![技术实现流程图](images/技术路线.jpeg)
+
+### 1.6 特性及适用场景
+
+对于夜间图像、低照度图像的增强均使用
+
+
+
+## 2 环境依赖
+
+请列出环境依赖软件和版本。
+
+eg：推荐系统为ubuntu 18.04或centos 7.6，环境依赖软件和版本如下表：
+
+| 软件名称      | 版本             |
+| ------------- | ---------------- |
+| ubuntu        | 18.04.1 LTS      |
+| MindX SDK     | mxVision-3.0.RC3 |
+| Python        | 3.9.2            |
+| CANN          | 5.1.RC2.alpha008 |
+| numpy         | 1.22.3           |
+| opencv-python | 4.5.5            |
+| onnxsim       | 0.4.10           |
+
+在编译运行项目前，需要设置环境变量：
+
+- 环境变量介绍
+
+```
+列出具体执行命令（简化）
+. ${sdk_path}/set_env.sh
+. ${ascend_toolkit_path}/set_env.sh
+```
+
+
+
+## 3 编译与运行
+### 3.1 推理示例代码
+
+**步骤1** （下载原模型代码)
+
+- 下载 PyTorch 版本 [IAT代码](https://github.com/cuiziteng/illumination-adaptive-transformer)
+
+- 根据原模型目录下的README.md文件配置原模型环境，具体代码如下：
+
+  ```
+  $ conda create -n IAT python==3.7.0
+  $ conda activate IAT
+  $ conda install --yes -c pytorch pytorch=1.7.1 torchvision cudatoolkit=11.0
+  $ pip install timm matplotlib IQA_pytorch tqdm
+  ```
+
+
+**步骤2** （配置项目环境）
+
+退出原模型环境，根据第2节环境依赖所述安装相应的项目环境，并设置环境变量。
+
+```
+source ${sdk_path}/set_env.sh
+source ${ascend_toolkit_path}/set_env.sh
+```
+
+**步骤3** （执行编译的步骤）
+
+​    1.pytorch 模型转换 onnx 文件
+
+​	将 `pth2onnx.py` 放到 Illumination-Adaptive_Transformer/IAT_enhance/项目目录下，并切换到原模型环境，运行：
+
+```
+python pth2onnx.py
+```
+
+​    	在该目录下会生成名为IAT_lol.onnx的onnx模型文件 
+
+​    2.简化 onnx 文件	
+
+​	 在上述目录下继续运行:
+
+```
+onnxsim IAT_lol.onnx IAT_lol-sim.onnx
+```
+
+​    	会在路径下生成简化后的IAT_lol-sim.onnx模型文件
+
+​	已经简化好的onnx模型可供参考：[IAT_lol-sim.onnx](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/IAT/IAT_lol-sim.onnx)
+
+​     3.onnx 文件转换 om 文件
+
+​	将环境从原模型环境切换到当前项目环境，然后运行：
+
+```
+atc --framework=5 --model=./IAT_lol-sim.onnx --input_shape="input_1:1,3,400,600" --output=IAT_lol-sim --soc_version=Ascend310
+```
+
+**步骤4** （运行及输出结果）
+
+将要推理的图片放到本项目./data/文件夹下, 并将其改为test.png, 将.om模型放到./models/文件夹下, 命名为iatsim.om。运行:
+
+```
+python main.py
+```
+
+即可在./data/目录下得到推理后的结果.
+
+
+
+## * 4 指标验证
+
+### 4.1 模型规模测试
+
+模型计算量测试需要利用python相关的模型测试工具 fvcore, 在原模型环境中可以使用以下命令进行安装：
+
+```
+pip install fvcore
+```
+
+利用fvcore的相关工具即可测得IAT模型的计算量，测试方法代码如下：
+
+```python
+def evaluate_net():
+    from model.IAT_main import IAT
+    from fvcore.nn import FlopCountAnalysis
+    
+    # 创建IAT网络
+    model = IAT()
+    model = model.cuda()
+    # 创建输入网络的tensor
+    tensor = torch.rand(1, 3, 400, 600).cuda()
+
+    # 分析FLOPs
+    flops = FlopCountAnalysis(model, tensor)
+    print("FLOPs: ", flops.total())
+```
+
+测试结果如下：
+
+![模型计算量](images/模型规模测试.jpeg)
+
+根据[IAT论文](https://github.com/cuiziteng/illumination-adaptive-transformer)所述，该模型参数量约为90K，通过测试得到计算量约为6.019GFLOPs。
+
+
+
+### 4.2 精度测试
+
+**步骤1-3**  与3.1节一致
+
+**步骤4** （获取LOL数据集）
+
+- 下载[LOLv1数据集](https://daooshee.github.io/BMVC2018website/)
+
+- 将数据集解压后将测试集目录(eval15)放到本项目./data/文件夹下,如下图所示:
+
+  ```
+  ├── data		  
+  	├──eval15  	# 精度测试数据集
+  		├──high
+  		├──low
+  ```
+
+**步骤5** （修改主函数并运行）
+
+切换到项目环境下，将main.py中的主函数改为调用test_precision()，运行:
+
+```
+python main.py
+```
+
+即可得到精度测试结果,测试结果如下：
+
+![模型计算量](images/精度测试.jpeg)
+
+
+
+## 5 参考文献
+
+@misc{https://doi.org/10.48550/arxiv.2205.14871,
+  doi = {10.48550/ARXIV.2205.14871},
+
+  url = {https://arxiv.org/abs/2205.14871},
+
+  author = {Cui, Ziteng and Li, Kunchang and Gu, Lin and Su, Shenghan and Gao, Peng and Jiang, Zhengkai and Qiao, Yu and Harada, Tatsuya},
+
+  keywords = {Computer Vision and Pattern Recognition (cs.CV), FOS: Computer and information sciences, FOS: Computer and information sciences},
+
+  title = {You Only Need 90K Parameters to Adapt Light: A Light Weight Transformer for Image Enhancement and Exposure Correction},
+
+  publisher = {arXiv},
+
+  year = {2022},
+
+  copyright = {Creative Commons Attribution 4.0 International}
 }
\ No newline at end of file
diff --git a/contrib/IAT/data/.keepme b/mxVision/mxVision-referenceapps/IAT/data/.keepme
similarity index 100%
rename from contrib/IAT/data/.keepme
rename to mxVision/mxVision-referenceapps/IAT/data/.keepme
diff --git "a/contrib/IAT/images/\346\212\200\346\234\257\350\267\257\347\272\277.jpeg" "b/mxVision/mxVision-referenceapps/IAT/images/\346\212\200\346\234\257\350\267\257\347\272\277.jpeg"
similarity index 100%
rename from "contrib/IAT/images/\346\212\200\346\234\257\350\267\257\347\272\277.jpeg"
rename to "mxVision/mxVision-referenceapps/IAT/images/\346\212\200\346\234\257\350\267\257\347\272\277.jpeg"
diff --git "a/contrib/IAT/images/\346\250\241\345\236\213\350\247\204\346\250\241\346\265\213\350\257\225.jpeg" "b/mxVision/mxVision-referenceapps/IAT/images/\346\250\241\345\236\213\350\247\204\346\250\241\346\265\213\350\257\225.jpeg"
similarity index 100%
rename from "contrib/IAT/images/\346\250\241\345\236\213\350\247\204\346\250\241\346\265\213\350\257\225.jpeg"
rename to "mxVision/mxVision-referenceapps/IAT/images/\346\250\241\345\236\213\350\247\204\346\250\241\346\265\213\350\257\225.jpeg"
diff --git "a/contrib/IAT/images/\347\262\276\345\272\246\346\265\213\350\257\225.jpeg" "b/mxVision/mxVision-referenceapps/IAT/images/\347\262\276\345\272\246\346\265\213\350\257\225.jpeg"
similarity index 100%
rename from "contrib/IAT/images/\347\262\276\345\272\246\346\265\213\350\257\225.jpeg"
rename to "mxVision/mxVision-referenceapps/IAT/images/\347\262\276\345\272\246\346\265\213\350\257\225.jpeg"
diff --git a/contrib/IAT/main.py b/mxVision/mxVision-referenceapps/IAT/main.py
similarity index 100%
rename from contrib/IAT/main.py
rename to mxVision/mxVision-referenceapps/IAT/main.py
diff --git a/contrib/IAT/models/.keepme b/mxVision/mxVision-referenceapps/IAT/models/.keepme
similarity index 100%
rename from contrib/IAT/models/.keepme
rename to mxVision/mxVision-referenceapps/IAT/models/.keepme
diff --git a/contrib/IAT/pth2onnx.py b/mxVision/mxVision-referenceapps/IAT/pth2onnx.py
similarity index 100%
rename from contrib/IAT/pth2onnx.py
rename to mxVision/mxVision-referenceapps/IAT/pth2onnx.py
diff --git a/contrib/Individual/README.md b/mxVision/mxVision-referenceapps/Individual/README.md
similarity index 100%
rename from contrib/Individual/README.md
rename to mxVision/mxVision-referenceapps/Individual/README.md
diff --git a/contrib/Individual/attr_main.py b/mxVision/mxVision-referenceapps/Individual/attr_main.py
similarity index 100%
rename from contrib/Individual/attr_main.py
rename to mxVision/mxVision-referenceapps/Individual/attr_main.py
diff --git a/contrib/Individual/build.sh b/mxVision/mxVision-referenceapps/Individual/build.sh
similarity index 100%
rename from contrib/Individual/build.sh
rename to mxVision/mxVision-referenceapps/Individual/build.sh
diff --git a/contrib/Individual/cal_accuracy.py b/mxVision/mxVision-referenceapps/Individual/cal_accuracy.py
similarity index 100%
rename from contrib/Individual/cal_accuracy.py
rename to mxVision/mxVision-referenceapps/Individual/cal_accuracy.py
diff --git a/contrib/Individual/image/flowchart.png b/mxVision/mxVision-referenceapps/Individual/image/flowchart.png
similarity index 100%
rename from contrib/Individual/image/flowchart.png
rename to mxVision/mxVision-referenceapps/Individual/image/flowchart.png
diff --git a/contrib/Individual/main.py b/mxVision/mxVision-referenceapps/Individual/main.py
similarity index 100%
rename from contrib/Individual/main.py
rename to mxVision/mxVision-referenceapps/Individual/main.py
diff --git a/contrib/Individual/models/attr.names b/mxVision/mxVision-referenceapps/Individual/models/attr.names
similarity index 100%
rename from contrib/Individual/models/attr.names
rename to mxVision/mxVision-referenceapps/Individual/models/attr.names
diff --git a/contrib/Individual/models/coco.names b/mxVision/mxVision-referenceapps/Individual/models/coco.names
similarity index 100%
rename from contrib/Individual/models/coco.names
rename to mxVision/mxVision-referenceapps/Individual/models/coco.names
diff --git a/contrib/Individual/models/insert_op.cfg b/mxVision/mxVision-referenceapps/Individual/models/insert_op.cfg
similarity index 100%
rename from contrib/Individual/models/insert_op.cfg
rename to mxVision/mxVision-referenceapps/Individual/models/insert_op.cfg
diff --git a/contrib/Individual/models/insert_op3.cfg b/mxVision/mxVision-referenceapps/Individual/models/insert_op3.cfg
similarity index 100%
rename from contrib/Individual/models/insert_op3.cfg
rename to mxVision/mxVision-referenceapps/Individual/models/insert_op3.cfg
diff --git a/contrib/Individual/models/resnet50_aipp_tf.cfg b/mxVision/mxVision-referenceapps/Individual/models/resnet50_aipp_tf.cfg
similarity index 100%
rename from contrib/Individual/models/resnet50_aipp_tf.cfg
rename to mxVision/mxVision-referenceapps/Individual/models/resnet50_aipp_tf.cfg
diff --git a/contrib/Individual/models/resnet50_aipp_tf1.cfg b/mxVision/mxVision-referenceapps/Individual/models/resnet50_aipp_tf1.cfg
similarity index 100%
rename from contrib/Individual/models/resnet50_aipp_tf1.cfg
rename to mxVision/mxVision-referenceapps/Individual/models/resnet50_aipp_tf1.cfg
diff --git a/contrib/FatigueDrivingRecognition/model/yolov4.cfg b/mxVision/mxVision-referenceapps/Individual/models/yolov4.cfg
similarity index 94%
rename from contrib/FatigueDrivingRecognition/model/yolov4.cfg
rename to mxVision/mxVision-referenceapps/Individual/models/yolov4.cfg
index 231e4566b70e3484203db45960e11a31d68c21a9..5d4f054021f07e25314172a0a6ed53d744c5abf6 100644
--- a/contrib/FatigueDrivingRecognition/model/yolov4.cfg
+++ b/mxVision/mxVision-referenceapps/Individual/models/yolov4.cfg
@@ -1,10 +1,10 @@
-CLASS_NUM=4
-BIASES_NUM=12
-BIASES=23,27,37,58,81,82,81,82,135,169,344,319
-SCORE_THRESH=0.4
-OBJECTNESS_THRESH=0.8
-IOU_THRESH=0.5
-YOLO_TYPE=2
-ANCHOR_DIM=3
-MODEL_TYPE=0
-RESIZE_FLAG=0
+CLASS_NUM=4
+BIASES_NUM=12
+BIASES=23,27,37,58,81,82,81,82,135,169,344,319
+SCORE_THRESH=0.4
+OBJECTNESS_THRESH=0.8
+IOU_THRESH=0.5
+YOLO_TYPE=2
+ANCHOR_DIM=3
+MODEL_TYPE=0
+RESIZE_FLAG=0
diff --git a/contrib/Individual/pipeline/Attr_part.pipeline b/mxVision/mxVision-referenceapps/Individual/pipeline/Attr_part.pipeline
similarity index 100%
rename from contrib/Individual/pipeline/Attr_part.pipeline
rename to mxVision/mxVision-referenceapps/Individual/pipeline/Attr_part.pipeline
diff --git a/contrib/Individual/pipeline/DectetionAndAttr.pipeline b/mxVision/mxVision-referenceapps/Individual/pipeline/DectetionAndAttr.pipeline
similarity index 100%
rename from contrib/Individual/pipeline/DectetionAndAttr.pipeline
rename to mxVision/mxVision-referenceapps/Individual/pipeline/DectetionAndAttr.pipeline
diff --git a/contrib/Individual/plugins/AttrPostProcess.cpp b/mxVision/mxVision-referenceapps/Individual/plugins/AttrPostProcess.cpp
similarity index 100%
rename from contrib/Individual/plugins/AttrPostProcess.cpp
rename to mxVision/mxVision-referenceapps/Individual/plugins/AttrPostProcess.cpp
diff --git a/contrib/Individual/plugins/AttrPostProcess.h b/mxVision/mxVision-referenceapps/Individual/plugins/AttrPostProcess.h
similarity index 100%
rename from contrib/Individual/plugins/AttrPostProcess.h
rename to mxVision/mxVision-referenceapps/Individual/plugins/AttrPostProcess.h
diff --git a/contrib/Individual/plugins/CMakeLists.txt b/mxVision/mxVision-referenceapps/Individual/plugins/CMakeLists.txt
similarity index 100%
rename from contrib/Individual/plugins/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/Individual/plugins/CMakeLists.txt
diff --git a/contrib/Individual/plugins/build.sh b/mxVision/mxVision-referenceapps/Individual/plugins/build.sh
similarity index 100%
rename from contrib/Individual/plugins/build.sh
rename to mxVision/mxVision-referenceapps/Individual/plugins/build.sh
diff --git a/contrib/Individual/run.sh b/mxVision/mxVision-referenceapps/Individual/run.sh
similarity index 100%
rename from contrib/Individual/run.sh
rename to mxVision/mxVision-referenceapps/Individual/run.sh
diff --git a/contrib/Individual/test_full.txt b/mxVision/mxVision-referenceapps/Individual/test_full.txt
similarity index 100%
rename from contrib/Individual/test_full.txt
rename to mxVision/mxVision-referenceapps/Individual/test_full.txt
diff --git a/mxVision/InferOfflineVideo/regular/CMakeLists.txt b/mxVision/mxVision-referenceapps/InferOfflineVideo/regular/CMakeLists.txt
similarity index 100%
rename from mxVision/InferOfflineVideo/regular/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/InferOfflineVideo/regular/CMakeLists.txt
diff --git a/mxVision/InferOfflineVideo/regular/README.zh.md b/mxVision/mxVision-referenceapps/InferOfflineVideo/regular/README.zh.md
similarity index 100%
rename from mxVision/InferOfflineVideo/regular/README.zh.md
rename to mxVision/mxVision-referenceapps/InferOfflineVideo/regular/README.zh.md
diff --git a/mxVision/InferOfflineVideo/regular/build_x86.sh b/mxVision/mxVision-referenceapps/InferOfflineVideo/regular/build_x86.sh
similarity index 100%
rename from mxVision/InferOfflineVideo/regular/build_x86.sh
rename to mxVision/mxVision-referenceapps/InferOfflineVideo/regular/build_x86.sh
diff --git a/mxVision/InferOfflineVideo/regular/main.cpp b/mxVision/mxVision-referenceapps/InferOfflineVideo/regular/main.cpp
similarity index 100%
rename from mxVision/InferOfflineVideo/regular/main.cpp
rename to mxVision/mxVision-referenceapps/InferOfflineVideo/regular/main.cpp
diff --git a/mxVision/InferOfflineVideo/regular/pipeline/regular.pipeline b/mxVision/mxVision-referenceapps/InferOfflineVideo/regular/pipeline/regular.pipeline
similarity index 100%
rename from mxVision/InferOfflineVideo/regular/pipeline/regular.pipeline
rename to mxVision/mxVision-referenceapps/InferOfflineVideo/regular/pipeline/regular.pipeline
diff --git a/mxVision/InferOfflineVideo/regular/run.sh b/mxVision/mxVision-referenceapps/InferOfflineVideo/regular/run.sh
similarity index 100%
rename from mxVision/InferOfflineVideo/regular/run.sh
rename to mxVision/mxVision-referenceapps/InferOfflineVideo/regular/run.sh
diff --git a/contrib/MMNET/README.md b/mxVision/mxVision-referenceapps/MMNET/README.md
similarity index 96%
rename from contrib/MMNET/README.md
rename to mxVision/mxVision-referenceapps/MMNET/README.md
index 15e0e9264ded441c1f6a27f4dcdd5b64a65c9bb4..de89980e9ca2cbe7d6e9d993025a3549550209f9 100644
--- a/contrib/MMNET/README.md
+++ b/mxVision/mxVision-referenceapps/MMNET/README.md
@@ -1,188 +1,188 @@
-# MMNET人像分割
-
-## 1 介绍
-MMNet致力于解决移动设备上人像抠图的问题，旨在以最小的模型性能降级在移动设备上获得实时推断。MMNet模型基多分支dilated conv以及线性bottleneck模块，性能优于最新模型，并且速度提高了几个数量级。
-
-本开发样例基于MindX SDK实现人像分割的功能，其主要功能是利用MMNET模型对输入图片中的人像进行灰度提取，从而与背景分离开，生成一张人像分割图片。
-
-样例输入：带有人体的jpg图片
-
-样例输出：人像与背景分离的新图片
-
-### 1.1 支持的产品
-
-项目所用的硬件平台：Ascend310
-
-### 1.2 支持的版本
-
-CANN：7.0.RC1
-
-SDK：mxVision 5.0.RC3（可通过cat SDK目录下的 version.info 查看）
-
-### 1.3 代码目录结构与说明
-
-本工程名称为MMNET，工程目录如下图所示：
-
-```
-|-------- test                                // 存放测试图片
-|-------- mask                                // 存放测试图片mask掩膜
-|-------- model
-|           |---- mmnet.aippconf              // aipp配置文件
-|-------- main.py                             // 主程序  
-|-------- pipeline                               
-|           |---- MMNET.pipeline              // pipeline流水线配置文件 
-|-------- evaluate.py                         // 精度测试程序
-|-------- README.md   
-```
-
-### 1.4 场景限制
-
-本项目能够针对人像清晰的图像完成人像分割任务并实现可视化。对于大部分人像图片，在图像清晰且人像在图片中占据较大比例的情况下都可以进行正确识别。但由于MMNET原算法的局限性，在部分情况下识别效果较差，具体如下：
-
-1.人像在图片中比例过小，会出现漏检的情况；
-
-2.对于存在多张人物目标的图片，会无法正确识别并分割；
-
-3.对于环境杂乱颜色过多的图片，分割效果较差，建议使用纯色的背景。
-
-建议使用纯色的背景，且目标在图片中占比较大的图片进行测试。
-
-## 2 环境依赖
-
-| 软件名称  | 版本  |
-| --------- | ----- |
-| MindX SDK | 5.0.CR3 |
-| python    | 3.9.2   |
-| CANN      | 7.0.RC1  |
-| opencv2   |       |
-| numpy     |       |
-
-
-在编译运行项目前，需要设置环境变量：
-
-- 环境变量介绍
-运行以下设置脚本以完成，其中{%Mind_SDK%}请替换为实际SDK安装位置
-
-```
-source {%Mind_SDK%}/mxVision-3.0.RC3/
-```
-
-
-
-## 3 模型转换
-人像分割采用提供的mmnet.pb模型。由于原模型是基于tensorflow的人像分割模型，因此我们需要借助于ATC工具将其转化为对应的om模型。
-
-具体步骤如下：
-**步骤1** 获取模型pb文件
-，下载链接为https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/MMNET/mmnet.pb
-
-**步骤2** 将获取到的mmnet模型pb文件存放至：“项目所在目录/model”
-
-**步骤3** 模型转换
-
-在pb文件所在目录下存放aipp配置文件，文件名为，具体内容如下：
-
-```python
-aipp_op {
-    aipp_mode: static
-    src_image_size_w :256
-    src_image_size_h :256
-    input_format : YUV420SP_U8
-    csc_switch : true
-    rbuv_swap_switch : false
-    matrix_r0c0 : 256
-    matrix_r0c1 : 0
-    matrix_r0c2 : 359
-    matrix_r1c0 : 256
-    matrix_r1c1 : -88
-    matrix_r1c2 : -183
-    matrix_r2c0 : 256
-    matrix_r2c1 : 454
-    matrix_r2c2 : 0
-    input_bias_0 : 0
-    input_bias_1 : 128
-    input_bias_2 : 128
-}
-```
-
-在确保环境变量设置正确后，在pb文件所在目录下执行以下命令：
-
-```
-atc --model=mmnet.pb --framework=3 --output=mmnet --soc_version=Ascend310 --insert_op_conf=mmnet.aippconf --input_shape="input_x:1,256,256,3"
-```
-
-执行完模型转换脚本后，若提示如下信息说明模型转换成功，会在output参数指定的路径下生成mmnet.om模型文件。
-
-```python
-ATC run success  
-```
-
-
-
-## 4 编译运行
-
-接下来进行模型的安装运行，具体步骤如下：
-
-**步骤1** 获取om模型
-
-**步骤2** 修改run.sh中MX_SDK_HOME
-
-
-**步骤3** 配置pipeline
-
-根据所需场景，配置pipeline文件，调整路径参数等。
-
-```python
-"mxpi_tensorinfer0": {
-			"props": {
-				"modelPath": "./model/mmnet.om"
-			},
-			"factory": "mxpi_tensorinfer",
-			"next":"appsink0"
-#修改om文件存放的路径
-```
-
-**步骤4** 存放图片，执行模型进行测试
-
-将测试图片存放至主目录下，修改main.py中的图片存放路径以及人像分割后的存储路径的相关代码：
-【注意】测试图片尽量仅包含一个人物，正脸且周围环境较为简单，同时图片为jpg格式。否则会对人像分割效果有较大影响,造成较大误差。
-
-```
-filepath = "test.jpg"
-filepath_out = "test-out.jpg"
-```
-
-然后执行run.sh文件：
-
-```
-bash run.sh
-```
-
-输出的图片即为样例的人像分割后的图片。
-
-## 5 精度测试
-
-对测试集中的300张图片进行精度测试，具体步骤如下：
-
-**步骤1** 获取测试集的图片,确保测试集的输入图片为jpg格式。
-获取地址为：https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/MMNET/data.zip
-
-**步骤2** 修改evaluate.py中的测试集图片存放路径：
-
-```
-filepath = "./test/"  #测试集图片存放路径
-gt_dir = './mask'   #测试集掩膜mask图片存放路径
-```
-
-**步骤3** 修改run.sh中MX_SDK_HOME和执行文件名称：
-
-```
-python3 evaluate.py
-```
-
-并执行：
-
-```
-bash run.sh
-```
-
+# MMNET人像分割
+
+## 1 介绍
+MMNet致力于解决移动设备上人像抠图的问题，旨在以最小的模型性能降级在移动设备上获得实时推断。MMNet模型基多分支dilated conv以及线性bottleneck模块，性能优于最新模型，并且速度提高了几个数量级。
+
+本开发样例基于MindX SDK实现人像分割的功能，其主要功能是利用MMNET模型对输入图片中的人像进行灰度提取，从而与背景分离开，生成一张人像分割图片。
+
+样例输入：带有人体的jpg图片
+
+样例输出：人像与背景分离的新图片
+
+### 1.1 支持的产品
+
+项目所用的硬件平台：Ascend310
+
+### 1.2 支持的版本
+
+CANN：7.0.RC1
+
+SDK：mxVision 5.0.RC3（可通过cat SDK目录下的 version.info 查看）
+
+### 1.3 代码目录结构与说明
+
+本工程名称为MMNET，工程目录如下图所示：
+
+```
+|-------- test                                // 存放测试图片
+|-------- mask                                // 存放测试图片mask掩膜
+|-------- model
+|           |---- mmnet.aippconf              // aipp配置文件
+|-------- main.py                             // 主程序  
+|-------- pipeline                               
+|           |---- MMNET.pipeline              // pipeline流水线配置文件 
+|-------- evaluate.py                         // 精度测试程序
+|-------- README.md   
+```
+
+### 1.4 场景限制
+
+本项目能够针对人像清晰的图像完成人像分割任务并实现可视化。对于大部分人像图片，在图像清晰且人像在图片中占据较大比例的情况下都可以进行正确识别。但由于MMNET原算法的局限性，在部分情况下识别效果较差，具体如下：
+
+1.人像在图片中比例过小，会出现漏检的情况；
+
+2.对于存在多张人物目标的图片，会无法正确识别并分割；
+
+3.对于环境杂乱颜色过多的图片，分割效果较差，建议使用纯色的背景。
+
+建议使用纯色的背景，且目标在图片中占比较大的图片进行测试。
+
+## 2 环境依赖
+
+| 软件名称  | 版本  |
+| --------- | ----- |
+| MindX SDK | 5.0.CR3 |
+| python    | 3.9.2   |
+| CANN      | 7.0.RC1  |
+| opencv2   |       |
+| numpy     |       |
+
+
+在编译运行项目前，需要设置环境变量：
+
+- 环境变量介绍
+运行以下设置脚本以完成，其中{%Mind_SDK%}请替换为实际SDK安装位置
+
+```
+source {%Mind_SDK%}/mxVision-3.0.RC3/
+```
+
+
+
+## 3 模型转换
+人像分割采用提供的mmnet.pb模型。由于原模型是基于tensorflow的人像分割模型，因此我们需要借助于ATC工具将其转化为对应的om模型。
+
+具体步骤如下：
+**步骤1** 获取模型pb文件
+，下载链接为https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/MMNET/mmnet.pb
+
+**步骤2** 将获取到的mmnet模型pb文件存放至：“项目所在目录/model”
+
+**步骤3** 模型转换
+
+在pb文件所在目录下存放aipp配置文件，文件名为，具体内容如下：
+
+```python
+aipp_op {
+    aipp_mode: static
+    src_image_size_w :256
+    src_image_size_h :256
+    input_format : YUV420SP_U8
+    csc_switch : true
+    rbuv_swap_switch : false
+    matrix_r0c0 : 256
+    matrix_r0c1 : 0
+    matrix_r0c2 : 359
+    matrix_r1c0 : 256
+    matrix_r1c1 : -88
+    matrix_r1c2 : -183
+    matrix_r2c0 : 256
+    matrix_r2c1 : 454
+    matrix_r2c2 : 0
+    input_bias_0 : 0
+    input_bias_1 : 128
+    input_bias_2 : 128
+}
+```
+
+在确保环境变量设置正确后，在pb文件所在目录下执行以下命令：
+
+```
+atc --model=mmnet.pb --framework=3 --output=mmnet --soc_version=Ascend310 --insert_op_conf=mmnet.aippconf --input_shape="input_x:1,256,256,3"
+```
+
+执行完模型转换脚本后，若提示如下信息说明模型转换成功，会在output参数指定的路径下生成mmnet.om模型文件。
+
+```python
+ATC run success  
+```
+
+
+
+## 4 编译运行
+
+接下来进行模型的安装运行，具体步骤如下：
+
+**步骤1** 获取om模型
+
+**步骤2** 修改run.sh中MX_SDK_HOME
+
+
+**步骤3** 配置pipeline
+
+根据所需场景，配置pipeline文件，调整路径参数等。
+
+```python
+"mxpi_tensorinfer0": {
+			"props": {
+				"modelPath": "./model/mmnet.om"
+			},
+			"factory": "mxpi_tensorinfer",
+			"next":"appsink0"
+#修改om文件存放的路径
+```
+
+**步骤4** 存放图片，执行模型进行测试
+
+将测试图片存放至主目录下，修改main.py中的图片存放路径以及人像分割后的存储路径的相关代码：
+【注意】测试图片尽量仅包含一个人物，正脸且周围环境较为简单，同时图片为jpg格式。否则会对人像分割效果有较大影响,造成较大误差。
+
+```
+filepath = "test.jpg"
+filepath_out = "test-out.jpg"
+```
+
+然后执行run.sh文件：
+
+```
+bash run.sh
+```
+
+输出的图片即为样例的人像分割后的图片。
+
+## 5 精度测试
+
+对测试集中的300张图片进行精度测试，具体步骤如下：
+
+**步骤1** 获取测试集的图片,确保测试集的输入图片为jpg格式。
+获取地址为：https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/MMNET/data.zip
+
+**步骤2** 修改evaluate.py中的测试集图片存放路径：
+
+```
+filepath = "./test/"  #测试集图片存放路径
+gt_dir = './mask'   #测试集掩膜mask图片存放路径
+```
+
+**步骤3** 修改run.sh中MX_SDK_HOME和执行文件名称：
+
+```
+python3 evaluate.py
+```
+
+并执行：
+
+```
+bash run.sh
+```
+
diff --git a/contrib/MMNET/evaluate.py b/mxVision/mxVision-referenceapps/MMNET/evaluate.py
similarity index 100%
rename from contrib/MMNET/evaluate.py
rename to mxVision/mxVision-referenceapps/MMNET/evaluate.py
diff --git a/contrib/MMNET/main.py b/mxVision/mxVision-referenceapps/MMNET/main.py
similarity index 100%
rename from contrib/MMNET/main.py
rename to mxVision/mxVision-referenceapps/MMNET/main.py
diff --git a/contrib/MMNET/model/mmnet.aippconf b/mxVision/mxVision-referenceapps/MMNET/model/mmnet.aippconf
similarity index 100%
rename from contrib/MMNET/model/mmnet.aippconf
rename to mxVision/mxVision-referenceapps/MMNET/model/mmnet.aippconf
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similarity index 100%
rename from contrib/MMNET/pipeline/MMNET.pipeline
rename to mxVision/mxVision-referenceapps/MMNET/pipeline/MMNET.pipeline
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rename from contrib/MMNET/run.sh
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rename from contrib/MediaCodeV2/mxbase/MediaCodecV2.h
rename to mxVision/mxVision-referenceapps/MediaCodeV2/mxbase/MediaCodecV2.h
diff --git a/contrib/MediaCodeV2/mxbase/build.sh b/mxVision/mxVision-referenceapps/MediaCodeV2/mxbase/build.sh
similarity index 100%
rename from contrib/MediaCodeV2/mxbase/build.sh
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rename to mxVision/mxVision-referenceapps/MediaCodeV2/out/.keep
diff --git a/contrib/PedestrianAttributeRecognition/dataset/image/.keep b/mxVision/mxVision-referenceapps/MediaCodeV2/test/.keep
similarity index 100%
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rename to mxVision/mxVision-referenceapps/MediaCodeV2/test/.keep
diff --git a/mxVision/MediaCodec/CMakeLists.txt b/mxVision/mxVision-referenceapps/MediaCodec/CMakeLists.txt
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rename from mxVision/MediaCodec/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/MediaCodec/CMakeLists.txt
diff --git a/mxVision/MediaCodec/README.zh.md b/mxVision/mxVision-referenceapps/MediaCodec/README.zh.md
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diff --git a/contrib/ActionRecognition/models/yolov3/.gitkeep b/mxVision/mxVision-referenceapps/MediaCodec/config/.gitkeep
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rename to mxVision/mxVision-referenceapps/MediaCodec/config/setup.config
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similarity index 100%
rename from mxVision/MediaCodec/image.png
rename to mxVision/mxVision-referenceapps/MediaCodec/image.png
diff --git a/mxVision/MediaCodec/main.cpp b/mxVision/mxVision-referenceapps/MediaCodec/main.cpp
similarity index 100%
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rename to mxVision/mxVision-referenceapps/MediaCodec/main.cpp
diff --git a/mxVision/MediaCodec/run.sh b/mxVision/mxVision-referenceapps/MediaCodec/run.sh
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diff --git a/contrib/MeterReader/README.md b/mxVision/mxVision-referenceapps/MeterReader/README.md
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diff --git a/contrib/MeterReader/evaluate/deeplabv3_val/seg_evaluate.py b/mxVision/mxVision-referenceapps/MeterReader/evaluate/deeplabv3_val/seg_evaluate.py
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rename to mxVision/mxVision-referenceapps/MeterReader/evaluate/deeplabv3_val/seg_evaluate.py
diff --git a/contrib/MeterReader/evaluate/yolov5_val/det.py b/mxVision/mxVision-referenceapps/MeterReader/evaluate/yolov5_val/det.py
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rename to mxVision/mxVision-referenceapps/MeterReader/evaluate/yolov5_val/match.py
diff --git a/contrib/MeterReader/evaluate/yolov5_val/yolo2voc.py b/mxVision/mxVision-referenceapps/MeterReader/evaluate/yolov5_val/yolo2voc.py
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diff --git a/contrib/MeterReader/images/README_img/DeepLabv3_pipeline.png b/mxVision/mxVision-referenceapps/MeterReader/images/README_img/DeepLabv3_pipeline.png
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diff --git a/contrib/MeterReader/images/README_img/get_map3.png b/mxVision/mxVision-referenceapps/MeterReader/images/README_img/get_map3.png
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rename to mxVision/mxVision-referenceapps/MeterReader/images/README_img/get_map3.png
diff --git a/contrib/MeterReader/infer/det.py b/mxVision/mxVision-referenceapps/MeterReader/infer/det.py
similarity index 100%
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rename to mxVision/mxVision-referenceapps/MeterReader/infer/det.py
diff --git a/contrib/MeterReader/infer/main.py b/mxVision/mxVision-referenceapps/MeterReader/infer/main.py
similarity index 100%
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rename to mxVision/mxVision-referenceapps/MeterReader/infer/main.py
diff --git a/contrib/MeterReader/infer/seg.py b/mxVision/mxVision-referenceapps/MeterReader/infer/seg.py
similarity index 100%
rename from contrib/MeterReader/infer/seg.py
rename to mxVision/mxVision-referenceapps/MeterReader/infer/seg.py
diff --git a/contrib/MeterReader/models/deeplabv3/seg_aipp.cfg b/mxVision/mxVision-referenceapps/MeterReader/models/deeplabv3/seg_aipp.cfg
similarity index 100%
rename from contrib/MeterReader/models/deeplabv3/seg_aipp.cfg
rename to mxVision/mxVision-referenceapps/MeterReader/models/deeplabv3/seg_aipp.cfg
diff --git a/contrib/MeterReader/models/yolov5/det_aipp.cfg b/mxVision/mxVision-referenceapps/MeterReader/models/yolov5/det_aipp.cfg
similarity index 100%
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rename to mxVision/mxVision-referenceapps/MeterReader/models/yolov5/det_aipp.cfg
diff --git a/contrib/MeterReader/pipeline/deeplabv3/deeplabv3.cfg b/mxVision/mxVision-referenceapps/MeterReader/pipeline/deeplabv3/deeplabv3.cfg
similarity index 100%
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rename to mxVision/mxVision-referenceapps/MeterReader/pipeline/deeplabv3/deeplabv3.cfg
diff --git a/contrib/MeterReader/pipeline/deeplabv3/deeplabv3.names b/mxVision/mxVision-referenceapps/MeterReader/pipeline/deeplabv3/deeplabv3.names
similarity index 100%
rename from contrib/MeterReader/pipeline/deeplabv3/deeplabv3.names
rename to mxVision/mxVision-referenceapps/MeterReader/pipeline/deeplabv3/deeplabv3.names
diff --git a/contrib/MeterReader/pipeline/deeplabv3/seg.pipeline b/mxVision/mxVision-referenceapps/MeterReader/pipeline/deeplabv3/seg.pipeline
similarity index 100%
rename from contrib/MeterReader/pipeline/deeplabv3/seg.pipeline
rename to mxVision/mxVision-referenceapps/MeterReader/pipeline/deeplabv3/seg.pipeline
diff --git a/contrib/MeterReader/pipeline/yolov5/det.pipeline b/mxVision/mxVision-referenceapps/MeterReader/pipeline/yolov5/det.pipeline
similarity index 100%
rename from contrib/MeterReader/pipeline/yolov5/det.pipeline
rename to mxVision/mxVision-referenceapps/MeterReader/pipeline/yolov5/det.pipeline
diff --git a/contrib/MeterReader/plugins/process3/CMakeLists.txt b/mxVision/mxVision-referenceapps/MeterReader/plugins/process3/CMakeLists.txt
similarity index 100%
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rename to mxVision/mxVision-referenceapps/MeterReader/plugins/process3/CMakeLists.txt
diff --git a/contrib/MeterReader/plugins/process3/Myplugin.cpp b/mxVision/mxVision-referenceapps/MeterReader/plugins/process3/Myplugin.cpp
similarity index 100%
rename from contrib/MeterReader/plugins/process3/Myplugin.cpp
rename to mxVision/mxVision-referenceapps/MeterReader/plugins/process3/Myplugin.cpp
diff --git a/contrib/MeterReader/plugins/process3/Myplugin.h b/mxVision/mxVision-referenceapps/MeterReader/plugins/process3/Myplugin.h
similarity index 100%
rename from contrib/MeterReader/plugins/process3/Myplugin.h
rename to mxVision/mxVision-referenceapps/MeterReader/plugins/process3/Myplugin.h
diff --git a/contrib/MeterReader/plugins/process3/build.sh b/mxVision/mxVision-referenceapps/MeterReader/plugins/process3/build.sh
similarity index 100%
rename from contrib/MeterReader/plugins/process3/build.sh
rename to mxVision/mxVision-referenceapps/MeterReader/plugins/process3/build.sh
diff --git a/contrib/MeterReader/plugins/process3/postprocess.cpp b/mxVision/mxVision-referenceapps/MeterReader/plugins/process3/postprocess.cpp
similarity index 100%
rename from contrib/MeterReader/plugins/process3/postprocess.cpp
rename to mxVision/mxVision-referenceapps/MeterReader/plugins/process3/postprocess.cpp
diff --git a/contrib/MeterReader/plugins/process3/postprocess.h b/mxVision/mxVision-referenceapps/MeterReader/plugins/process3/postprocess.h
similarity index 100%
rename from contrib/MeterReader/plugins/process3/postprocess.h
rename to mxVision/mxVision-referenceapps/MeterReader/plugins/process3/postprocess.h
diff --git a/contrib/MonocularDepthEstimation/README.md b/mxVision/mxVision-referenceapps/MonocularDepthEstimation/README.md
similarity index 100%
rename from contrib/MonocularDepthEstimation/README.md
rename to mxVision/mxVision-referenceapps/MonocularDepthEstimation/README.md
diff --git a/contrib/MonocularDepthEstimation/depth_estimation/monocular_depth_estimation.py b/mxVision/mxVision-referenceapps/MonocularDepthEstimation/depth_estimation/monocular_depth_estimation.py
similarity index 100%
rename from contrib/MonocularDepthEstimation/depth_estimation/monocular_depth_estimation.py
rename to mxVision/mxVision-referenceapps/MonocularDepthEstimation/depth_estimation/monocular_depth_estimation.py
diff --git a/contrib/MonocularDepthEstimation/evaluate.py b/mxVision/mxVision-referenceapps/MonocularDepthEstimation/evaluate.py
similarity index 100%
rename from contrib/MonocularDepthEstimation/evaluate.py
rename to mxVision/mxVision-referenceapps/MonocularDepthEstimation/evaluate.py
diff --git a/contrib/MonocularDepthEstimation/main.py b/mxVision/mxVision-referenceapps/MonocularDepthEstimation/main.py
similarity index 100%
rename from contrib/MonocularDepthEstimation/main.py
rename to mxVision/mxVision-referenceapps/MonocularDepthEstimation/main.py
diff --git a/contrib/MonocularDepthEstimation/model/aipp_adabins_640_480.aippconfig b/mxVision/mxVision-referenceapps/MonocularDepthEstimation/model/aipp_adabins_640_480.aippconfig
similarity index 100%
rename from contrib/MonocularDepthEstimation/model/aipp_adabins_640_480.aippconfig
rename to mxVision/mxVision-referenceapps/MonocularDepthEstimation/model/aipp_adabins_640_480.aippconfig
diff --git a/contrib/MonocularDepthEstimation/model/model_conversion.sh b/mxVision/mxVision-referenceapps/MonocularDepthEstimation/model/model_conversion.sh
similarity index 100%
rename from contrib/MonocularDepthEstimation/model/model_conversion.sh
rename to mxVision/mxVision-referenceapps/MonocularDepthEstimation/model/model_conversion.sh
diff --git a/contrib/MonocularDepthEstimation/pipeline/depth_estimation.pipeline b/mxVision/mxVision-referenceapps/MonocularDepthEstimation/pipeline/depth_estimation.pipeline
similarity index 100%
rename from contrib/MonocularDepthEstimation/pipeline/depth_estimation.pipeline
rename to mxVision/mxVision-referenceapps/MonocularDepthEstimation/pipeline/depth_estimation.pipeline
diff --git a/contrib/MonocularDepthEstimation/run.sh b/mxVision/mxVision-referenceapps/MonocularDepthEstimation/run.sh
similarity index 100%
rename from contrib/MonocularDepthEstimation/run.sh
rename to mxVision/mxVision-referenceapps/MonocularDepthEstimation/run.sh
diff --git a/contrib/MonocularDepthEstimation/util/data_process.py b/mxVision/mxVision-referenceapps/MonocularDepthEstimation/util/data_process.py
similarity index 97%
rename from contrib/MonocularDepthEstimation/util/data_process.py
rename to mxVision/mxVision-referenceapps/MonocularDepthEstimation/util/data_process.py
index 698fa25770b4ca00616c8eb7bcef6298b5c1250b..3449f9db16300840397b4d2687c28db8257fcdf1 100644
--- a/contrib/MonocularDepthEstimation/util/data_process.py
+++ b/mxVision/mxVision-referenceapps/MonocularDepthEstimation/util/data_process.py
@@ -1,65 +1,65 @@
-#!/usr/bin/env python
-# -*- encoding: utf-8 -*-
-# Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-# http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-import h5py
-import imageio
-import os
-import numpy as np
-
-if __name__ == '__main__':
-
-    data_file_path = '../test_set/nyu_depth_v2_labeled.mat'
-    output_image_path = '../test_set/image'
-    output_depth_info_path = '../test_set/depth_info'
-
-    # check origin data file
-    path_ready = True
-    if os.path.exists(data_file_path) != 1:
-        path_ready = False
-        print('The {} does not exist, please check first.'.format(data_file_path))
-    if os.path.exists(output_image_path) != 1 or os.path.exists(output_depth_info_path) != 1:
-        path_ready = False
-        print('The {} or {} does not exist, please check first.'.format(output_image_path, output_depth_info_path))
-
-    if not path_ready:
-        print('please ensure input file and output path correct first.')
-        exit(1)
-
-    # load data file
-    data = h5py.File(data_file_path)
-
-    # get image data
-    image = np.array(data['images'])
-    image = np.transpose(image, (0, 2, 3, 1))
-
-    # get depth info data
-    depth = np.array(data['depths'])
-
-    # save image
-    for i in range(image.shape[0]):
-        index = str(i)
-        image_index_path = output_image_path + '/' + index + '.jpg'
-        out_img = image[i, :, :, :]
-        out_img = out_img.transpose(1, 0, 2)
-        imageio.imwrite(image_index_path, out_img)
-
-    # save depth info
-    for i in range(depth.shape[0]):
-        index = str(i)
-        depth_index_path = output_depth_info_path + '/' + index + '.npy'
-        out_depth = depth[i, :, :]
-        out_depth = out_depth.transpose(1, 0)
-        np.save(depth_index_path, out_depth)
+#!/usr/bin/env python
+# -*- encoding: utf-8 -*-
+# Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import h5py
+import imageio
+import os
+import numpy as np
+
+if __name__ == '__main__':
+
+    data_file_path = '../test_set/nyu_depth_v2_labeled.mat'
+    output_image_path = '../test_set/image'
+    output_depth_info_path = '../test_set/depth_info'
+
+    # check origin data file
+    path_ready = True
+    if os.path.exists(data_file_path) != 1:
+        path_ready = False
+        print('The {} does not exist, please check first.'.format(data_file_path))
+    if os.path.exists(output_image_path) != 1 or os.path.exists(output_depth_info_path) != 1:
+        path_ready = False
+        print('The {} or {} does not exist, please check first.'.format(output_image_path, output_depth_info_path))
+
+    if not path_ready:
+        print('please ensure input file and output path correct first.')
+        exit(1)
+
+    # load data file
+    data = h5py.File(data_file_path)
+
+    # get image data
+    image = np.array(data['images'])
+    image = np.transpose(image, (0, 2, 3, 1))
+
+    # get depth info data
+    depth = np.array(data['depths'])
+
+    # save image
+    for i in range(image.shape[0]):
+        index = str(i)
+        image_index_path = output_image_path + '/' + index + '.jpg'
+        out_img = image[i, :, :, :]
+        out_img = out_img.transpose(1, 0, 2)
+        imageio.imwrite(image_index_path, out_img)
+
+    # save depth info
+    for i in range(depth.shape[0]):
+        index = str(i)
+        depth_index_path = output_depth_info_path + '/' + index + '.npy'
+        out_depth = depth[i, :, :]
+        out_depth = out_depth.transpose(1, 0)
+        np.save(depth_index_path, out_depth)
diff --git a/contrib/MonocularDepthEstimation/util/util.py b/mxVision/mxVision-referenceapps/MonocularDepthEstimation/util/util.py
similarity index 100%
rename from contrib/MonocularDepthEstimation/util/util.py
rename to mxVision/mxVision-referenceapps/MonocularDepthEstimation/util/util.py
diff --git a/contrib/MultiChannelVideoDetection/BlockingQueue/BlockingQueue.h b/mxVision/mxVision-referenceapps/MultiChannelVideoDetection/BlockingQueue/BlockingQueue.h
similarity index 100%
rename from contrib/MultiChannelVideoDetection/BlockingQueue/BlockingQueue.h
rename to mxVision/mxVision-referenceapps/MultiChannelVideoDetection/BlockingQueue/BlockingQueue.h
diff --git a/contrib/MultiChannelVideoDetection/CMakeLists.txt b/mxVision/mxVision-referenceapps/MultiChannelVideoDetection/CMakeLists.txt
similarity index 100%
rename from contrib/MultiChannelVideoDetection/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/MultiChannelVideoDetection/CMakeLists.txt
diff --git a/contrib/MultiChannelVideoDetection/ImageResizer/ImageResizer.cpp b/mxVision/mxVision-referenceapps/MultiChannelVideoDetection/ImageResizer/ImageResizer.cpp
similarity index 100%
rename from contrib/MultiChannelVideoDetection/ImageResizer/ImageResizer.cpp
rename to mxVision/mxVision-referenceapps/MultiChannelVideoDetection/ImageResizer/ImageResizer.cpp
diff --git a/contrib/MultiChannelVideoDetection/ImageResizer/ImageResizer.h b/mxVision/mxVision-referenceapps/MultiChannelVideoDetection/ImageResizer/ImageResizer.h
similarity index 100%
rename from contrib/MultiChannelVideoDetection/ImageResizer/ImageResizer.h
rename to mxVision/mxVision-referenceapps/MultiChannelVideoDetection/ImageResizer/ImageResizer.h
diff --git a/contrib/MultiChannelVideoDetection/MultiChannelVideoReasoner/MultiChannelVideoReasoner.cpp b/mxVision/mxVision-referenceapps/MultiChannelVideoDetection/MultiChannelVideoReasoner/MultiChannelVideoReasoner.cpp
similarity index 100%
rename from contrib/MultiChannelVideoDetection/MultiChannelVideoReasoner/MultiChannelVideoReasoner.cpp
rename to mxVision/mxVision-referenceapps/MultiChannelVideoDetection/MultiChannelVideoReasoner/MultiChannelVideoReasoner.cpp
diff --git a/contrib/MultiChannelVideoDetection/MultiChannelVideoReasoner/MultiChannelVideoReasoner.h b/mxVision/mxVision-referenceapps/MultiChannelVideoDetection/MultiChannelVideoReasoner/MultiChannelVideoReasoner.h
similarity index 100%
rename from contrib/MultiChannelVideoDetection/MultiChannelVideoReasoner/MultiChannelVideoReasoner.h
rename to mxVision/mxVision-referenceapps/MultiChannelVideoDetection/MultiChannelVideoReasoner/MultiChannelVideoReasoner.h
diff --git a/contrib/MultiChannelVideoDetection/README.md b/mxVision/mxVision-referenceapps/MultiChannelVideoDetection/README.md
similarity index 100%
rename from contrib/MultiChannelVideoDetection/README.md
rename to mxVision/mxVision-referenceapps/MultiChannelVideoDetection/README.md
diff --git a/contrib/MultiChannelVideoDetection/StreamPuller/StreamPuller.cpp b/mxVision/mxVision-referenceapps/MultiChannelVideoDetection/StreamPuller/StreamPuller.cpp
similarity index 100%
rename from contrib/MultiChannelVideoDetection/StreamPuller/StreamPuller.cpp
rename to mxVision/mxVision-referenceapps/MultiChannelVideoDetection/StreamPuller/StreamPuller.cpp
diff --git a/contrib/MultiChannelVideoDetection/StreamPuller/StreamPuller.h b/mxVision/mxVision-referenceapps/MultiChannelVideoDetection/StreamPuller/StreamPuller.h
similarity index 100%
rename from contrib/MultiChannelVideoDetection/StreamPuller/StreamPuller.h
rename to mxVision/mxVision-referenceapps/MultiChannelVideoDetection/StreamPuller/StreamPuller.h
diff --git a/contrib/MultiChannelVideoDetection/Util/PerformanceMonitor/PerformanceMonitor.cpp b/mxVision/mxVision-referenceapps/MultiChannelVideoDetection/Util/PerformanceMonitor/PerformanceMonitor.cpp
similarity index 100%
rename from contrib/MultiChannelVideoDetection/Util/PerformanceMonitor/PerformanceMonitor.cpp
rename to mxVision/mxVision-referenceapps/MultiChannelVideoDetection/Util/PerformanceMonitor/PerformanceMonitor.cpp
diff --git a/contrib/MultiChannelVideoDetection/Util/PerformanceMonitor/PerformanceMonitor.h b/mxVision/mxVision-referenceapps/MultiChannelVideoDetection/Util/PerformanceMonitor/PerformanceMonitor.h
similarity index 100%
rename from contrib/MultiChannelVideoDetection/Util/PerformanceMonitor/PerformanceMonitor.h
rename to mxVision/mxVision-referenceapps/MultiChannelVideoDetection/Util/PerformanceMonitor/PerformanceMonitor.h
diff --git a/contrib/MultiChannelVideoDetection/Util/Util.cpp b/mxVision/mxVision-referenceapps/MultiChannelVideoDetection/Util/Util.cpp
similarity index 100%
rename from contrib/MultiChannelVideoDetection/Util/Util.cpp
rename to mxVision/mxVision-referenceapps/MultiChannelVideoDetection/Util/Util.cpp
diff --git a/contrib/MultiChannelVideoDetection/Util/Util.h b/mxVision/mxVision-referenceapps/MultiChannelVideoDetection/Util/Util.h
similarity index 100%
rename from contrib/MultiChannelVideoDetection/Util/Util.h
rename to mxVision/mxVision-referenceapps/MultiChannelVideoDetection/Util/Util.h
diff --git a/contrib/MultiChannelVideoDetection/VideoDecoder/VideoDecoder.cpp b/mxVision/mxVision-referenceapps/MultiChannelVideoDetection/VideoDecoder/VideoDecoder.cpp
similarity index 100%
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rename to mxVision/mxVision-referenceapps/MultiChannelVideoDetection/VideoDecoder/VideoDecoder.cpp
diff --git a/contrib/MultiChannelVideoDetection/VideoDecoder/VideoDecoder.h b/mxVision/mxVision-referenceapps/MultiChannelVideoDetection/VideoDecoder/VideoDecoder.h
similarity index 100%
rename from contrib/MultiChannelVideoDetection/VideoDecoder/VideoDecoder.h
rename to mxVision/mxVision-referenceapps/MultiChannelVideoDetection/VideoDecoder/VideoDecoder.h
diff --git a/contrib/MultiChannelVideoDetection/YoloDetector/YoloDetector.cpp b/mxVision/mxVision-referenceapps/MultiChannelVideoDetection/YoloDetector/YoloDetector.cpp
similarity index 100%
rename from contrib/MultiChannelVideoDetection/YoloDetector/YoloDetector.cpp
rename to mxVision/mxVision-referenceapps/MultiChannelVideoDetection/YoloDetector/YoloDetector.cpp
diff --git a/contrib/MultiChannelVideoDetection/YoloDetector/YoloDetector.h b/mxVision/mxVision-referenceapps/MultiChannelVideoDetection/YoloDetector/YoloDetector.h
similarity index 100%
rename from contrib/MultiChannelVideoDetection/YoloDetector/YoloDetector.h
rename to mxVision/mxVision-referenceapps/MultiChannelVideoDetection/YoloDetector/YoloDetector.h
diff --git a/contrib/MultiChannelVideoDetection/build.sh b/mxVision/mxVision-referenceapps/MultiChannelVideoDetection/build.sh
similarity index 100%
rename from contrib/MultiChannelVideoDetection/build.sh
rename to mxVision/mxVision-referenceapps/MultiChannelVideoDetection/build.sh
diff --git a/contrib/MultiChannelVideoDetection/main.cpp b/mxVision/mxVision-referenceapps/MultiChannelVideoDetection/main.cpp
similarity index 100%
rename from contrib/MultiChannelVideoDetection/main.cpp
rename to mxVision/mxVision-referenceapps/MultiChannelVideoDetection/main.cpp
diff --git a/contrib/MultiChannelVideoDetection/model/aipp_yolov3_416_416.aippconfig b/mxVision/mxVision-referenceapps/MultiChannelVideoDetection/model/aipp_yolov3_416_416.aippconfig
similarity index 100%
rename from contrib/MultiChannelVideoDetection/model/aipp_yolov3_416_416.aippconfig
rename to mxVision/mxVision-referenceapps/MultiChannelVideoDetection/model/aipp_yolov3_416_416.aippconfig
diff --git a/contrib/MultiChannelVideoDetection/model/coco.names b/mxVision/mxVision-referenceapps/MultiChannelVideoDetection/model/coco.names
similarity index 100%
rename from contrib/MultiChannelVideoDetection/model/coco.names
rename to mxVision/mxVision-referenceapps/MultiChannelVideoDetection/model/coco.names
diff --git a/contrib/MultiChannelVideoDetection/run.sh b/mxVision/mxVision-referenceapps/MultiChannelVideoDetection/run.sh
similarity index 100%
rename from contrib/MultiChannelVideoDetection/run.sh
rename to mxVision/mxVision-referenceapps/MultiChannelVideoDetection/run.sh
diff --git a/mxVision/MultiThread/C++/CMakeLists.txt b/mxVision/mxVision-referenceapps/MultiThread/C++/CMakeLists.txt
similarity index 100%
rename from mxVision/MultiThread/C++/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/MultiThread/C++/CMakeLists.txt
diff --git a/mxVision/MultiThread/C++/EasyStream.pipeline b/mxVision/mxVision-referenceapps/MultiThread/C++/EasyStream.pipeline
similarity index 100%
rename from mxVision/MultiThread/C++/EasyStream.pipeline
rename to mxVision/mxVision-referenceapps/MultiThread/C++/EasyStream.pipeline
diff --git a/mxVision/MultiThread/C++/EasyStream_protobuf.pipeline b/mxVision/mxVision-referenceapps/MultiThread/C++/EasyStream_protobuf.pipeline
similarity index 100%
rename from mxVision/MultiThread/C++/EasyStream_protobuf.pipeline
rename to mxVision/mxVision-referenceapps/MultiThread/C++/EasyStream_protobuf.pipeline
diff --git a/mxVision/MultiThread/C++/README.zh.md b/mxVision/mxVision-referenceapps/MultiThread/C++/README.zh.md
similarity index 100%
rename from mxVision/MultiThread/C++/README.zh.md
rename to mxVision/mxVision-referenceapps/MultiThread/C++/README.zh.md
diff --git a/mxVision/MultiThread/C++/build.sh b/mxVision/mxVision-referenceapps/MultiThread/C++/build.sh
similarity index 100%
rename from mxVision/MultiThread/C++/build.sh
rename to mxVision/mxVision-referenceapps/MultiThread/C++/build.sh
diff --git a/mxVision/MediaCodec/config/.gitkeep b/mxVision/mxVision-referenceapps/MultiThread/C++/dist/.gitkeep
similarity index 100%
rename from mxVision/MediaCodec/config/.gitkeep
rename to mxVision/mxVision-referenceapps/MultiThread/C++/dist/.gitkeep
diff --git a/mxVision/MultiThread/C++/main.cpp b/mxVision/mxVision-referenceapps/MultiThread/C++/main.cpp
similarity index 100%
rename from mxVision/MultiThread/C++/main.cpp
rename to mxVision/mxVision-referenceapps/MultiThread/C++/main.cpp
diff --git a/mxVision/MultiThread/C++/run.sh b/mxVision/mxVision-referenceapps/MultiThread/C++/run.sh
similarity index 100%
rename from mxVision/MultiThread/C++/run.sh
rename to mxVision/mxVision-referenceapps/MultiThread/C++/run.sh
diff --git a/mxVision/MultiThread/C++/dist/.gitkeep b/mxVision/mxVision-referenceapps/MultiThread/picture/.gitkeep
similarity index 100%
rename from mxVision/MultiThread/C++/dist/.gitkeep
rename to mxVision/mxVision-referenceapps/MultiThread/picture/.gitkeep
diff --git a/mxVision/MultiThread/python/EasyStream.pipeline b/mxVision/mxVision-referenceapps/MultiThread/python/EasyStream.pipeline
similarity index 100%
rename from mxVision/MultiThread/python/EasyStream.pipeline
rename to mxVision/mxVision-referenceapps/MultiThread/python/EasyStream.pipeline
diff --git a/mxVision/MultiThread/python/EasyStream_protobuf.pipeline b/mxVision/mxVision-referenceapps/MultiThread/python/EasyStream_protobuf.pipeline
similarity index 100%
rename from mxVision/MultiThread/python/EasyStream_protobuf.pipeline
rename to mxVision/mxVision-referenceapps/MultiThread/python/EasyStream_protobuf.pipeline
diff --git a/mxVision/MultiThread/python/README.zh.md b/mxVision/mxVision-referenceapps/MultiThread/python/README.zh.md
similarity index 100%
rename from mxVision/MultiThread/python/README.zh.md
rename to mxVision/mxVision-referenceapps/MultiThread/python/README.zh.md
diff --git a/mxVision/MultiThread/python/main.py b/mxVision/mxVision-referenceapps/MultiThread/python/main.py
similarity index 100%
rename from mxVision/MultiThread/python/main.py
rename to mxVision/mxVision-referenceapps/MultiThread/python/main.py
diff --git a/mxVision/MultiThread/python/main_sendprotobuf.py b/mxVision/mxVision-referenceapps/MultiThread/python/main_sendprotobuf.py
similarity index 100%
rename from mxVision/MultiThread/python/main_sendprotobuf.py
rename to mxVision/mxVision-referenceapps/MultiThread/python/main_sendprotobuf.py
diff --git a/mxVision/MultiThread/python/run.sh b/mxVision/mxVision-referenceapps/MultiThread/python/run.sh
similarity index 100%
rename from mxVision/MultiThread/python/run.sh
rename to mxVision/mxVision-referenceapps/MultiThread/python/run.sh
diff --git a/contrib/OCR/pipeline/IDCardRecognition.pipeline b/mxVision/mxVision-referenceapps/OCR/pipeline/IDCardRecognition.pipeline
similarity index 100%
rename from contrib/OCR/pipeline/IDCardRecognition.pipeline
rename to mxVision/mxVision-referenceapps/OCR/pipeline/IDCardRecognition.pipeline
diff --git a/contrib/OCR/pipeline/KeywordDetection.pipeline b/mxVision/mxVision-referenceapps/OCR/pipeline/KeywordDetection.pipeline
similarity index 100%
rename from contrib/OCR/pipeline/KeywordDetection.pipeline
rename to mxVision/mxVision-referenceapps/OCR/pipeline/KeywordDetection.pipeline
diff --git a/contrib/OCR/plugins/TextInfoPlugin/CMakeLists.txt b/mxVision/mxVision-referenceapps/OCR/plugins/TextInfoPlugin/CMakeLists.txt
similarity index 100%
rename from contrib/OCR/plugins/TextInfoPlugin/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/OCR/plugins/TextInfoPlugin/CMakeLists.txt
diff --git a/contrib/OCR/plugins/TextInfoPlugin/TextInfoPlugin.cpp b/mxVision/mxVision-referenceapps/OCR/plugins/TextInfoPlugin/TextInfoPlugin.cpp
similarity index 100%
rename from contrib/OCR/plugins/TextInfoPlugin/TextInfoPlugin.cpp
rename to mxVision/mxVision-referenceapps/OCR/plugins/TextInfoPlugin/TextInfoPlugin.cpp
diff --git a/contrib/OCR/plugins/TextInfoPlugin/TextInfoPlugin.h b/mxVision/mxVision-referenceapps/OCR/plugins/TextInfoPlugin/TextInfoPlugin.h
similarity index 100%
rename from contrib/OCR/plugins/TextInfoPlugin/TextInfoPlugin.h
rename to mxVision/mxVision-referenceapps/OCR/plugins/TextInfoPlugin/TextInfoPlugin.h
diff --git a/contrib/OCR/plugins/TextSimilarityPlugin/CMakeLists.txt b/mxVision/mxVision-referenceapps/OCR/plugins/TextSimilarityPlugin/CMakeLists.txt
similarity index 100%
rename from contrib/OCR/plugins/TextSimilarityPlugin/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/OCR/plugins/TextSimilarityPlugin/CMakeLists.txt
diff --git a/contrib/OCR/plugins/TextSimilarityPlugin/TextSimilarityPlugin.cpp b/mxVision/mxVision-referenceapps/OCR/plugins/TextSimilarityPlugin/TextSimilarityPlugin.cpp
similarity index 97%
rename from contrib/OCR/plugins/TextSimilarityPlugin/TextSimilarityPlugin.cpp
rename to mxVision/mxVision-referenceapps/OCR/plugins/TextSimilarityPlugin/TextSimilarityPlugin.cpp
index 4cf2e3669736058e0e96e8f2db1a7d7413b58a70..db12560a9bd927d9a3c67f2fd8ed2acb77068af3 100644
--- a/contrib/OCR/plugins/TextSimilarityPlugin/TextSimilarityPlugin.cpp
+++ b/mxVision/mxVision-referenceapps/OCR/plugins/TextSimilarityPlugin/TextSimilarityPlugin.cpp
@@ -1,289 +1,289 @@
-/*
- * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
- 
-#include "TextSimilarityPlugin.h"
-#include <iostream>
-#include "MxBase/Log/Log.h"
-#include "MxTools/Proto/MxpiDataType.pb.h"
-#include "MxBase/PostProcessBases/PostProcessDataType.h"
-#include <mutex>
-#include <thread>
-#include <map>
-#include <fstream>
-#include <iostream>
-#include <string>
-#include <vector>
-#include <map>
-#include <regex>
-#include <codecvt>
-#include <algorithm>
-#include <cstdint>
-#include <istream>
-#include <sstream>
-using namespace MxBase;
-using namespace MxTools;
-using namespace MxPlugins;
-using namespace std;
-
-APP_ERROR TextSimilarityPlugin::Init(std::map<std::string, std::shared_ptr<void>> &configParamMap)
-{
-    LogInfo << "Begin to initialize TextInfoPlugin(" << pluginName_ << ").";
-
-    dataSource_ = *std::static_pointer_cast<std::string>(configParamMap["dataSource"]);
-
-    LogInfo << "End to initialize MxpiFairmot(" << pluginName_ << ").";
-    return APP_ERR_OK;
-}
-
-APP_ERROR TextSimilarityPlugin::DeInit()
-{
-    LogInfo << "Begin to deinitialize MxpiFairmot(" << pluginName_ << ").";
-    LogInfo << "End to deinitialize MxpiFairmot(" << pluginName_ << ").";
-    return APP_ERR_OK;
-}
-
-void GetTensors(const std::shared_ptr<MxTools::MxpiTensorPackageList> &tensorPackageList,
-                std::vector<MxBase::TensorBase> &tensors) {
-    for (int i = 0; i < tensorPackageList->tensorpackagevec_size(); ++i) {
-        for (int j = 0; j < tensorPackageList->tensorpackagevec(i).tensorvec_size(); j++) {
-            MxBase::MemoryData memoryData = {};
-            memoryData.deviceId = tensorPackageList->tensorpackagevec(i).tensorvec(j).deviceid();
-            memoryData.type = (MxBase::MemoryData::MemoryType)tensorPackageList->
-                    tensorpackagevec(i).tensorvec(j).memtype();
-            memoryData.size = (uint32_t) tensorPackageList->
-                    tensorpackagevec(i).tensorvec(j).tensordatasize();
-            memoryData.ptrData = (void *) tensorPackageList->
-                    tensorpackagevec(i).tensorvec(j).tensordataptr();
-            std::vector<uint32_t> outputShape = {};
-            for (int k = 0; k < tensorPackageList->
-                    tensorpackagevec(i).tensorvec(j).tensorshape_size(); ++k) {
-                outputShape.push_back((uint32_t) tensorPackageList->
-                        tensorpackagevec(i).tensorvec(j).tensorshape(k));
-            }
-            MxBase::TensorBase tmpTensor(memoryData, true, outputShape,
-                                         (MxBase::TensorDataType)tensorPackageList->
-                                                 tensorpackagevec(i).tensorvec(j).tensordatatype());
-            tensors.push_back(tmpTensor);
-        }
-    }
-}
-
-std::vector<std::shared_ptr<void>> TextSimilarityPlugin::DefineProperties()
-{
-    std::vector<std::shared_ptr<void>> properties;
-    auto datasource = std::make_shared<ElementProperty<string>>(ElementProperty<string> {
-            STRING,
-            "dataSource",
-            "dataSource",
-            "the name of cropped image source",
-            "default", "NULL", "NULL"
-    });
-    properties.push_back(datasource);
-    return properties;
-}
-
-MxpiPortInfo TextSimilarityPlugin::DefineInputPorts()
-{
-    MxpiPortInfo inputPortInfo;
-    std::vector<std::vector<std::string>> value = {{"ANY"}, {"ANY"}, {"ANY"}, {"ANY"}, {"ANY"}, {"ANY"}};
-    GenerateStaticInputPortsInfo(value, inputPortInfo);
-    return inputPortInfo;
-}
-
-MxpiPortInfo TextSimilarityPlugin::DefineOutputPorts()
-{
-    MxpiPortInfo outputPortInfo;
-    std::vector<std::vector<std::string>> value = {{"ANY"}};
-    GenerateStaticOutputPortsInfo(value, outputPortInfo);
-    return outputPortInfo;
-}
-
-namespace {
-    MX_PLUGIN_GENERATE(TextSimilarityPlugin)
-}
-
-void Covert(const std::shared_ptr<MxTools::MxpiTextsInfoList> &textsInfoList,
-            std::vector<MxBase::TextsInfo> &textsInfoVec)
-{
-    for (uint32_t i = 0; i < textsInfoList->textsinfovec_size(); i++) {
-        auto textsInfo = textsInfoList->textsinfovec(i);
-        MxBase::TextsInfo text;
-        for (uint32_t j = 0; j < textsInfo.text_size(); j++) {
-            auto textInfo = textsInfo.text(j);
-            if (textInfo == ""){
-                continue;
-            }
-            text.text.push_back(textInfo);
-        }
-        textsInfoVec.push_back(text);
-    }
-}
-
-APP_ERROR TextSimilarityPlugin::Process(std::vector<MxpiBuffer *> &mxpiBuffer)
-{
-    /*
-     * get the MxpiVisionList and MxpiTrackletList
-     * */
-    LogInfo << "Begin to process MxpiMotSimpleSort(" << elementName_ << ").";
-    // Get MxpiVisionList and MxpiTrackletList from mxpibuffer
-    MxpiBuffer *inputMxpiBuffer0 = mxpiBuffer[0];   // deviceID[0]
-    MxpiMetadataManager mxpiMetadataManager(*inputMxpiBuffer0);
-
-    vector<string> names;
-    std::stringstream ss(dataSource_); // Turn the std::string into a stream.
-    std::string tok;
-
-    while (getline(ss, tok, ','))
-    {
-        names.push_back(tok);
-    }
-
-    // Get the metadata from buffer
-    std::shared_ptr<void> metadata0 = mxpiMetadataManager.GetMetadata(names[0]);
-    std::shared_ptr<MxpiTensorPackageList> srcTensorPackageListSptr0 =
-            std::static_pointer_cast<MxpiTensorPackageList>(metadata0);
-
-    // Get tensorbase
-    std::vector<MxBase::TensorBase> tensors0 = {};
-    GetTensors(srcTensorPackageListSptr0, tensors0);
-
-    auto shape0 = tensors0[0].GetShape();
-    std::vector<std::vector<float> > input1(shape0[1],std::vector<float>(shape0[2]));
-    void *idPtr0 =  tensors0[0].GetBuffer();
-    for(uint32_t i = 0; i < shape0[0]; i++) {
-        for (uint32_t j = 0; j < shape0[1]; j++) {
-            for(int k = 0;k < shape0[2];k++){
-                float x0 = *((float *) idPtr0 + k+j*shape0[2]);
-                input1[j][k] = x0;
-            }
-        }
-    }
-
-    MxpiBuffer *inputMxpiBuffer1 = mxpiBuffer[1];   // deviceID[0]
-    MxpiMetadataManager mxpiMetadataManager1(*inputMxpiBuffer1);
-
-    // Get the metadata from buffer
-    std::shared_ptr<void> metadata1 = mxpiMetadataManager1.GetMetadata(names[1]);
-    std::shared_ptr<MxpiTensorPackageList> srcTensorPackageListSptr1 =
-            std::static_pointer_cast<MxpiTensorPackageList>(metadata1);
-
-    // Get tensorbase
-    std::vector<MxBase::TensorBase> tensors1 = {};
-    GetTensors(srcTensorPackageListSptr1, tensors1);
-    auto shape1 = tensors1[0].GetShape();
-    std::vector<std::vector<float> > input2(shape1[1],std::vector<float>(shape1[2]));
-    void *idPtr1 =  tensors1[0].GetBuffer();
-    for(uint32_t i = 0; i < shape1[0]; i++) {
-        for (uint32_t j = 0; j < shape1[1]; j++) {
-            for(int k = 0;k < shape1[2];k++){
-                float x0 = *((float *) idPtr1 + k+j*shape1[2]);
-                input2[j][k] = x0;
-            }
-        }
-    }
-
-    // Get MxpiVisionList and MxpiTrackletList from mxpibuffer
-    MxpiBuffer *inputMxpiBuffer2 = mxpiBuffer[2];   // deviceID[0]
-    MxpiMetadataManager mxpiMetadataManager2(*inputMxpiBuffer2);
-
-    // Get the metadata from buffer
-    std::shared_ptr<void> metadata2 = mxpiMetadataManager2.GetMetadata(names[2]);
-    std::shared_ptr<MxpiTensorPackageList> srcTensorPackageListSptr2 =
-            std::static_pointer_cast<MxpiTensorPackageList>(metadata2);
-
-    // Get tensorbase
-    std::vector<MxBase::TensorBase> tensors2 = {};
-    GetTensors(srcTensorPackageListSptr2, tensors2);
-    auto shape2 = tensors2[0].GetShape();
-    void *idPtr2 =  tensors2[0].GetBuffer();
-    int  length1 = *(int *) idPtr2;
-
-    // Get MxpiVisionList and MxpiTrackletList from mxpibuffer
-    MxpiBuffer *inputMxpiBuffer3 = mxpiBuffer[3];   // deviceID[0]
-    MxpiMetadataManager mxpiMetadataManager3(*inputMxpiBuffer3);
-
-    // Get the metadata from buffer
-    std::shared_ptr<void> metadata3 = mxpiMetadataManager3.GetMetadata(names[3]);
-    std::shared_ptr<MxpiTensorPackageList> srcTensorPackageListSptr3 =
-            std::static_pointer_cast<MxpiTensorPackageList>(metadata3);
-
-    // Get tensorbase
-    std::vector<MxBase::TensorBase> tensors3 = {};
-    GetTensors(srcTensorPackageListSptr3, tensors3);
-    auto shape3 = tensors3[0].GetShape();
-    void *idPtr3 =  tensors3[0].GetBuffer();
-    int  length2 = *(int *) idPtr3;
-
-    // Get MxpiVisionList and MxpiTrackletList from mxpibuffer
-    MxpiBuffer *inputMxpiBuffer4 = mxpiBuffer[4];   // deviceID[0]
-    MxpiMetadataManager mxpiMetadataManager4(*inputMxpiBuffer4);
-
-    // Get the metadata from buffer
-    std::shared_ptr<void> metadata4 = mxpiMetadataManager4.GetMetadata(names[4]);
-    std::shared_ptr<MxTools::MxpiTextsInfoList> mxpiTextsInfoList4 =
-            std::static_pointer_cast<MxpiTextsInfoList>(metadata4);
-    std::vector<MxBase::TextsInfo> textsInfoVec0 = {};
-    Covert(mxpiTextsInfoList4, textsInfoVec0);
-
-    // Get the metadata from buffer
-    MxpiBuffer *inputMxpiBuffer5 = mxpiBuffer[5];   // deviceID[0]
-    MxpiMetadataManager mxpiMetadataManager5(*inputMxpiBuffer5);
-    std::shared_ptr<void> metadata5 = mxpiMetadataManager5.GetMetadata(names[5]);
-    std::shared_ptr<MxTools::MxpiTextsInfoList> mxpiTextsInfoList5 =
-            std::static_pointer_cast<MxpiTextsInfoList>(metadata5);
-    std::vector<MxBase::TextsInfo> textsInfoVec1 = {};
-    Covert(mxpiTextsInfoList5, textsInfoVec1);
-    bool has_kay = false;
-    float thresh = 0.7;
-    for(int i = 1; i< length1 - 1; i++) {
-        for(int j = 1; j < length2 - 1; j++) {
-            float temp = similarity(input1[i],input2[j]);
-            LogInfo << "text:(" << textsInfoVec0[0].text[i - 1]
-                    << ") keyword:(" << textsInfoVec1[0].text[j - 1] << ") similarity:" << temp;
-            if (temp > thresh) {
-                has_kay = true;
-            }
-        }
-    }
-
-    LogInfo << "has key(bool)?:" << has_kay;
-    // Send the data to downstream plugin
-    SendData(0, *inputMxpiBuffer0);
-    LogInfo << "End to process TextInfoPlugin(" << elementName_ << ").";
-    return APP_ERR_OK;
-}
-
-float TextSimilarityPlugin::scalar_product(vector<float> a, vector<float> b)
-{
-    float product = 0;
-    for (int i = 0; i <= a.size() - 1; i++){
-        product = product + (a[i]) * (b[i]);
-    }
-    return product;
-}
-
-float TextSimilarityPlugin::linalg(vector<float> a) {
-    float res = 0;
-    for (int i = 0; i < a.size(); i++) {
-        res = res + a[i] * a[i];
-    }
-    res = sqrt(res);
-    return res;
-}
-
-float TextSimilarityPlugin::similarity(vector<float>& a, vector<float>& b) {
-    return scalar_product(a, b) / (linalg(a) * linalg(b));
+/*
+ * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+ 
+#include "TextSimilarityPlugin.h"
+#include <iostream>
+#include "MxBase/Log/Log.h"
+#include "MxTools/Proto/MxpiDataType.pb.h"
+#include "MxBase/PostProcessBases/PostProcessDataType.h"
+#include <mutex>
+#include <thread>
+#include <map>
+#include <fstream>
+#include <iostream>
+#include <string>
+#include <vector>
+#include <map>
+#include <regex>
+#include <codecvt>
+#include <algorithm>
+#include <cstdint>
+#include <istream>
+#include <sstream>
+using namespace MxBase;
+using namespace MxTools;
+using namespace MxPlugins;
+using namespace std;
+
+APP_ERROR TextSimilarityPlugin::Init(std::map<std::string, std::shared_ptr<void>> &configParamMap)
+{
+    LogInfo << "Begin to initialize TextInfoPlugin(" << pluginName_ << ").";
+
+    dataSource_ = *std::static_pointer_cast<std::string>(configParamMap["dataSource"]);
+
+    LogInfo << "End to initialize MxpiFairmot(" << pluginName_ << ").";
+    return APP_ERR_OK;
+}
+
+APP_ERROR TextSimilarityPlugin::DeInit()
+{
+    LogInfo << "Begin to deinitialize MxpiFairmot(" << pluginName_ << ").";
+    LogInfo << "End to deinitialize MxpiFairmot(" << pluginName_ << ").";
+    return APP_ERR_OK;
+}
+
+void GetTensors(const std::shared_ptr<MxTools::MxpiTensorPackageList> &tensorPackageList,
+                std::vector<MxBase::TensorBase> &tensors) {
+    for (int i = 0; i < tensorPackageList->tensorpackagevec_size(); ++i) {
+        for (int j = 0; j < tensorPackageList->tensorpackagevec(i).tensorvec_size(); j++) {
+            MxBase::MemoryData memoryData = {};
+            memoryData.deviceId = tensorPackageList->tensorpackagevec(i).tensorvec(j).deviceid();
+            memoryData.type = (MxBase::MemoryData::MemoryType)tensorPackageList->
+                    tensorpackagevec(i).tensorvec(j).memtype();
+            memoryData.size = (uint32_t) tensorPackageList->
+                    tensorpackagevec(i).tensorvec(j).tensordatasize();
+            memoryData.ptrData = (void *) tensorPackageList->
+                    tensorpackagevec(i).tensorvec(j).tensordataptr();
+            std::vector<uint32_t> outputShape = {};
+            for (int k = 0; k < tensorPackageList->
+                    tensorpackagevec(i).tensorvec(j).tensorshape_size(); ++k) {
+                outputShape.push_back((uint32_t) tensorPackageList->
+                        tensorpackagevec(i).tensorvec(j).tensorshape(k));
+            }
+            MxBase::TensorBase tmpTensor(memoryData, true, outputShape,
+                                         (MxBase::TensorDataType)tensorPackageList->
+                                                 tensorpackagevec(i).tensorvec(j).tensordatatype());
+            tensors.push_back(tmpTensor);
+        }
+    }
+}
+
+std::vector<std::shared_ptr<void>> TextSimilarityPlugin::DefineProperties()
+{
+    std::vector<std::shared_ptr<void>> properties;
+    auto datasource = std::make_shared<ElementProperty<string>>(ElementProperty<string> {
+            STRING,
+            "dataSource",
+            "dataSource",
+            "the name of cropped image source",
+            "default", "NULL", "NULL"
+    });
+    properties.push_back(datasource);
+    return properties;
+}
+
+MxpiPortInfo TextSimilarityPlugin::DefineInputPorts()
+{
+    MxpiPortInfo inputPortInfo;
+    std::vector<std::vector<std::string>> value = {{"ANY"}, {"ANY"}, {"ANY"}, {"ANY"}, {"ANY"}, {"ANY"}};
+    GenerateStaticInputPortsInfo(value, inputPortInfo);
+    return inputPortInfo;
+}
+
+MxpiPortInfo TextSimilarityPlugin::DefineOutputPorts()
+{
+    MxpiPortInfo outputPortInfo;
+    std::vector<std::vector<std::string>> value = {{"ANY"}};
+    GenerateStaticOutputPortsInfo(value, outputPortInfo);
+    return outputPortInfo;
+}
+
+namespace {
+    MX_PLUGIN_GENERATE(TextSimilarityPlugin)
+}
+
+void Covert(const std::shared_ptr<MxTools::MxpiTextsInfoList> &textsInfoList,
+            std::vector<MxBase::TextsInfo> &textsInfoVec)
+{
+    for (uint32_t i = 0; i < textsInfoList->textsinfovec_size(); i++) {
+        auto textsInfo = textsInfoList->textsinfovec(i);
+        MxBase::TextsInfo text;
+        for (uint32_t j = 0; j < textsInfo.text_size(); j++) {
+            auto textInfo = textsInfo.text(j);
+            if (textInfo == ""){
+                continue;
+            }
+            text.text.push_back(textInfo);
+        }
+        textsInfoVec.push_back(text);
+    }
+}
+
+APP_ERROR TextSimilarityPlugin::Process(std::vector<MxpiBuffer *> &mxpiBuffer)
+{
+    /*
+     * get the MxpiVisionList and MxpiTrackletList
+     * */
+    LogInfo << "Begin to process MxpiMotSimpleSort(" << elementName_ << ").";
+    // Get MxpiVisionList and MxpiTrackletList from mxpibuffer
+    MxpiBuffer *inputMxpiBuffer0 = mxpiBuffer[0];   // deviceID[0]
+    MxpiMetadataManager mxpiMetadataManager(*inputMxpiBuffer0);
+
+    vector<string> names;
+    std::stringstream ss(dataSource_); // Turn the std::string into a stream.
+    std::string tok;
+
+    while (getline(ss, tok, ','))
+    {
+        names.push_back(tok);
+    }
+
+    // Get the metadata from buffer
+    std::shared_ptr<void> metadata0 = mxpiMetadataManager.GetMetadata(names[0]);
+    std::shared_ptr<MxpiTensorPackageList> srcTensorPackageListSptr0 =
+            std::static_pointer_cast<MxpiTensorPackageList>(metadata0);
+
+    // Get tensorbase
+    std::vector<MxBase::TensorBase> tensors0 = {};
+    GetTensors(srcTensorPackageListSptr0, tensors0);
+
+    auto shape0 = tensors0[0].GetShape();
+    std::vector<std::vector<float> > input1(shape0[1],std::vector<float>(shape0[2]));
+    void *idPtr0 =  tensors0[0].GetBuffer();
+    for(uint32_t i = 0; i < shape0[0]; i++) {
+        for (uint32_t j = 0; j < shape0[1]; j++) {
+            for(int k = 0;k < shape0[2];k++){
+                float x0 = *((float *) idPtr0 + k+j*shape0[2]);
+                input1[j][k] = x0;
+            }
+        }
+    }
+
+    MxpiBuffer *inputMxpiBuffer1 = mxpiBuffer[1];   // deviceID[0]
+    MxpiMetadataManager mxpiMetadataManager1(*inputMxpiBuffer1);
+
+    // Get the metadata from buffer
+    std::shared_ptr<void> metadata1 = mxpiMetadataManager1.GetMetadata(names[1]);
+    std::shared_ptr<MxpiTensorPackageList> srcTensorPackageListSptr1 =
+            std::static_pointer_cast<MxpiTensorPackageList>(metadata1);
+
+    // Get tensorbase
+    std::vector<MxBase::TensorBase> tensors1 = {};
+    GetTensors(srcTensorPackageListSptr1, tensors1);
+    auto shape1 = tensors1[0].GetShape();
+    std::vector<std::vector<float> > input2(shape1[1],std::vector<float>(shape1[2]));
+    void *idPtr1 =  tensors1[0].GetBuffer();
+    for(uint32_t i = 0; i < shape1[0]; i++) {
+        for (uint32_t j = 0; j < shape1[1]; j++) {
+            for(int k = 0;k < shape1[2];k++){
+                float x0 = *((float *) idPtr1 + k+j*shape1[2]);
+                input2[j][k] = x0;
+            }
+        }
+    }
+
+    // Get MxpiVisionList and MxpiTrackletList from mxpibuffer
+    MxpiBuffer *inputMxpiBuffer2 = mxpiBuffer[2];   // deviceID[0]
+    MxpiMetadataManager mxpiMetadataManager2(*inputMxpiBuffer2);
+
+    // Get the metadata from buffer
+    std::shared_ptr<void> metadata2 = mxpiMetadataManager2.GetMetadata(names[2]);
+    std::shared_ptr<MxpiTensorPackageList> srcTensorPackageListSptr2 =
+            std::static_pointer_cast<MxpiTensorPackageList>(metadata2);
+
+    // Get tensorbase
+    std::vector<MxBase::TensorBase> tensors2 = {};
+    GetTensors(srcTensorPackageListSptr2, tensors2);
+    auto shape2 = tensors2[0].GetShape();
+    void *idPtr2 =  tensors2[0].GetBuffer();
+    int  length1 = *(int *) idPtr2;
+
+    // Get MxpiVisionList and MxpiTrackletList from mxpibuffer
+    MxpiBuffer *inputMxpiBuffer3 = mxpiBuffer[3];   // deviceID[0]
+    MxpiMetadataManager mxpiMetadataManager3(*inputMxpiBuffer3);
+
+    // Get the metadata from buffer
+    std::shared_ptr<void> metadata3 = mxpiMetadataManager3.GetMetadata(names[3]);
+    std::shared_ptr<MxpiTensorPackageList> srcTensorPackageListSptr3 =
+            std::static_pointer_cast<MxpiTensorPackageList>(metadata3);
+
+    // Get tensorbase
+    std::vector<MxBase::TensorBase> tensors3 = {};
+    GetTensors(srcTensorPackageListSptr3, tensors3);
+    auto shape3 = tensors3[0].GetShape();
+    void *idPtr3 =  tensors3[0].GetBuffer();
+    int  length2 = *(int *) idPtr3;
+
+    // Get MxpiVisionList and MxpiTrackletList from mxpibuffer
+    MxpiBuffer *inputMxpiBuffer4 = mxpiBuffer[4];   // deviceID[0]
+    MxpiMetadataManager mxpiMetadataManager4(*inputMxpiBuffer4);
+
+    // Get the metadata from buffer
+    std::shared_ptr<void> metadata4 = mxpiMetadataManager4.GetMetadata(names[4]);
+    std::shared_ptr<MxTools::MxpiTextsInfoList> mxpiTextsInfoList4 =
+            std::static_pointer_cast<MxpiTextsInfoList>(metadata4);
+    std::vector<MxBase::TextsInfo> textsInfoVec0 = {};
+    Covert(mxpiTextsInfoList4, textsInfoVec0);
+
+    // Get the metadata from buffer
+    MxpiBuffer *inputMxpiBuffer5 = mxpiBuffer[5];   // deviceID[0]
+    MxpiMetadataManager mxpiMetadataManager5(*inputMxpiBuffer5);
+    std::shared_ptr<void> metadata5 = mxpiMetadataManager5.GetMetadata(names[5]);
+    std::shared_ptr<MxTools::MxpiTextsInfoList> mxpiTextsInfoList5 =
+            std::static_pointer_cast<MxpiTextsInfoList>(metadata5);
+    std::vector<MxBase::TextsInfo> textsInfoVec1 = {};
+    Covert(mxpiTextsInfoList5, textsInfoVec1);
+    bool has_kay = false;
+    float thresh = 0.7;
+    for(int i = 1; i< length1 - 1; i++) {
+        for(int j = 1; j < length2 - 1; j++) {
+            float temp = similarity(input1[i],input2[j]);
+            LogInfo << "text:(" << textsInfoVec0[0].text[i - 1]
+                    << ") keyword:(" << textsInfoVec1[0].text[j - 1] << ") similarity:" << temp;
+            if (temp > thresh) {
+                has_kay = true;
+            }
+        }
+    }
+
+    LogInfo << "has key(bool)?:" << has_kay;
+    // Send the data to downstream plugin
+    SendData(0, *inputMxpiBuffer0);
+    LogInfo << "End to process TextInfoPlugin(" << elementName_ << ").";
+    return APP_ERR_OK;
+}
+
+float TextSimilarityPlugin::scalar_product(vector<float> a, vector<float> b)
+{
+    float product = 0;
+    for (int i = 0; i <= a.size() - 1; i++){
+        product = product + (a[i]) * (b[i]);
+    }
+    return product;
+}
+
+float TextSimilarityPlugin::linalg(vector<float> a) {
+    float res = 0;
+    for (int i = 0; i < a.size(); i++) {
+        res = res + a[i] * a[i];
+    }
+    res = sqrt(res);
+    return res;
+}
+
+float TextSimilarityPlugin::similarity(vector<float>& a, vector<float>& b) {
+    return scalar_product(a, b) / (linalg(a) * linalg(b));
 }
\ No newline at end of file
diff --git a/contrib/OCR/plugins/TextSimilarityPlugin/TextSimilarityPlugin.h b/mxVision/mxVision-referenceapps/OCR/plugins/TextSimilarityPlugin/TextSimilarityPlugin.h
similarity index 100%
rename from contrib/OCR/plugins/TextSimilarityPlugin/TextSimilarityPlugin.h
rename to mxVision/mxVision-referenceapps/OCR/plugins/TextSimilarityPlugin/TextSimilarityPlugin.h
diff --git a/contrib/OpenCVPlugin/OpenCVPlugin/src/OpenCVPlugin/CMakeLists.txt b/mxVision/mxVision-referenceapps/OpenCVPlugin/OpenCVPlugin/src/OpenCVPlugin/CMakeLists.txt
similarity index 97%
rename from contrib/OpenCVPlugin/OpenCVPlugin/src/OpenCVPlugin/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/OpenCVPlugin/OpenCVPlugin/src/OpenCVPlugin/CMakeLists.txt
index 91b8352d0915db9f9f560c5885b6810ab6df2b02..f8f351e95c8adfadc11f51e4aaeb57be10080368 100644
--- a/contrib/OpenCVPlugin/OpenCVPlugin/src/OpenCVPlugin/CMakeLists.txt
+++ b/mxVision/mxVision-referenceapps/OpenCVPlugin/OpenCVPlugin/src/OpenCVPlugin/CMakeLists.txt
@@ -1,36 +1,36 @@
-cmake_minimum_required(VERSION 3.5.2)
-project(OpenCVPlugin)
-
-add_definitions(-D_GLIBCXX_USE_CXX11_ABI=0)
-add_definitions(-Dgoogle=mindxsdk_private)
-set(MX_SDK_HOME "$ENV{MX_SDK_HOME}")
-set(PLUGIN_NAME "mxpi_OpenCVPlugin")
-set(TARGET_LIBRARY ${PLUGIN_NAME})
-set(LIBRARY_OUTPUT_PATH ${PROJECT_SOURCE_DIR}/../../lib/plugins)
-message(${PROJECT_SOURCE_DIR})
-
-
-include_directories(${CMAKE_CURRENT_BINARY_DIR})
-include_directories(${MX_SDK_HOME}/include)
-include_directories(/usr/local/Ascend/ascend-toolkit/latest/runtime/include)
-include_directories(${MX_SDK_HOME}/opensource/include)
-include_directories(${MX_SDK_HOME}/opensource/include/opencv4)
-include_directories(${MX_SDK_HOME}/opensource/include/gstreamer-1.0)
-include_directories(${MX_SDK_HOME}/opensource/include/glib-2.0)
-include_directories(${MX_SDK_HOME}/opensource/lib/glib-2.0/include)
-
-link_directories(${MX_SDK_HOME}/lib)
-link_directories(${MX_SDK_HOME}/opensource/lib)
-
-add_compile_options(-std=c++14 -fPIC -fstack-protector-all -pie -Wno-deprecated-declarations)
-add_compile_options("-DPLUGIN_NAME=${PLUGIN_NAME}")
-
-add_definitions(-DENABLE_DVPP_INTERFACE)
-
-add_library(${TARGET_LIBRARY} SHARED OpenCVPlugin.cpp)
-
-
-target_link_libraries(${TARGET_LIBRARY} glib-2.0 gstreamer-1.0 gobject-2.0 gstbase-1.0 gmodule-2.0 glog opencv_world)
-
-target_link_libraries(${TARGET_LIBRARY} mxpidatatype plugintoolkit mxbase mindxsdk_protobuf)
-target_link_libraries(${TARGET_LIBRARY} -Wl,-z,relro,-z,now,-z,noexecstack -s)
+cmake_minimum_required(VERSION 3.5.2)
+project(OpenCVPlugin)
+
+add_definitions(-D_GLIBCXX_USE_CXX11_ABI=0)
+add_definitions(-Dgoogle=mindxsdk_private)
+set(MX_SDK_HOME "$ENV{MX_SDK_HOME}")
+set(PLUGIN_NAME "mxpi_OpenCVPlugin")
+set(TARGET_LIBRARY ${PLUGIN_NAME})
+set(LIBRARY_OUTPUT_PATH ${PROJECT_SOURCE_DIR}/../../lib/plugins)
+message(${PROJECT_SOURCE_DIR})
+
+
+include_directories(${CMAKE_CURRENT_BINARY_DIR})
+include_directories(${MX_SDK_HOME}/include)
+include_directories(/usr/local/Ascend/ascend-toolkit/latest/runtime/include)
+include_directories(${MX_SDK_HOME}/opensource/include)
+include_directories(${MX_SDK_HOME}/opensource/include/opencv4)
+include_directories(${MX_SDK_HOME}/opensource/include/gstreamer-1.0)
+include_directories(${MX_SDK_HOME}/opensource/include/glib-2.0)
+include_directories(${MX_SDK_HOME}/opensource/lib/glib-2.0/include)
+
+link_directories(${MX_SDK_HOME}/lib)
+link_directories(${MX_SDK_HOME}/opensource/lib)
+
+add_compile_options(-std=c++14 -fPIC -fstack-protector-all -pie -Wno-deprecated-declarations)
+add_compile_options("-DPLUGIN_NAME=${PLUGIN_NAME}")
+
+add_definitions(-DENABLE_DVPP_INTERFACE)
+
+add_library(${TARGET_LIBRARY} SHARED OpenCVPlugin.cpp)
+
+
+target_link_libraries(${TARGET_LIBRARY} glib-2.0 gstreamer-1.0 gobject-2.0 gstbase-1.0 gmodule-2.0 glog opencv_world)
+
+target_link_libraries(${TARGET_LIBRARY} mxpidatatype plugintoolkit mxbase mindxsdk_protobuf)
+target_link_libraries(${TARGET_LIBRARY} -Wl,-z,relro,-z,now,-z,noexecstack -s)
diff --git a/contrib/OpenCVPlugin/OpenCVPlugin/src/OpenCVPlugin/OpenCVPlugin.cpp b/mxVision/mxVision-referenceapps/OpenCVPlugin/OpenCVPlugin/src/OpenCVPlugin/OpenCVPlugin.cpp
similarity index 97%
rename from contrib/OpenCVPlugin/OpenCVPlugin/src/OpenCVPlugin/OpenCVPlugin.cpp
rename to mxVision/mxVision-referenceapps/OpenCVPlugin/OpenCVPlugin/src/OpenCVPlugin/OpenCVPlugin.cpp
index 63c35881010be32c0658704e6627899eefeca7c0..79cdd768b70408c8e2cb6bcd8f9d0eef7023fa94 100644
--- a/contrib/OpenCVPlugin/OpenCVPlugin/src/OpenCVPlugin/OpenCVPlugin.cpp
+++ b/mxVision/mxVision-referenceapps/OpenCVPlugin/OpenCVPlugin/src/OpenCVPlugin/OpenCVPlugin.cpp
@@ -1,437 +1,437 @@
-/*
-* Copyright(C) 2020. Huawei Technologies Co.,Ltd. All rights reserved.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-*     http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-
-#include "OpenCVPlugin.h"
-#include "MxBase/Log/Log.h"
-#include "MxBase/Tensor/TensorBase/TensorBase.h"
-using namespace MxBase;
-using namespace MxPlugins;
-using namespace MxTools;
-using namespace std;
-namespace {
-    const string SAMPLE_KEY = "MxpiVisionList";
-    const int YUV_U = 2;
-    const int YUV_V = 3;
-    const int san = 3;
-    const int er = 2;
-    const int yi = 1;
-    const float yiwu = 1.5;
-}
-
-APP_ERROR MxpiSamplePlugin::Init(std::map<std::string, std::shared_ptr<void>>& configParamMap)
-{
-    LogInfo << "MxpiSamplePlugin::Init start.";
-    APP_ERROR ret = APP_ERR_OK;
-    // Get the property values by key
-    parentName_ = dataSource_;
-    std::shared_ptr<string> descriptionMessageProSptr =
-    std::static_pointer_cast<string>(configParamMap["descriptionMessage"]);
-    height = *std::static_pointer_cast<float>(configParamMap["height"]);
-    width = *std::static_pointer_cast<float>(configParamMap["width"]);
-    fx = *std::static_pointer_cast<double>(configParamMap["fx"]);
-    fy = *std::static_pointer_cast<double>(configParamMap["fy"]);
-    interpolation = *std::static_pointer_cast<int>(configParamMap["interpolation"]); 
-    startRow = *std::static_pointer_cast<double>(configParamMap["startRow"]);
-    endRow = *std::static_pointer_cast<double>(configParamMap["Height"]);
-    startCol = *std::static_pointer_cast<double>(configParamMap["startCol"]);
-    endCol = *std::static_pointer_cast<double>(configParamMap["Width"]);
-    outputDataFormat = *std::static_pointer_cast<string>(configParamMap["outputDataFormat"]);
-    dataType = *std::static_pointer_cast<string>(configParamMap["dataType"]);
-    option = *std::static_pointer_cast<string>(configParamMap["option"]);
-    descriptionMessage_ = *descriptionMessageProSptr.get();
-    return APP_ERR_OK;
-}
-
-APP_ERROR MxpiSamplePlugin::DeInit()
-{
-    LogInfo << "MxpiSamplePlugin::DeInit end.";
-    return APP_ERR_OK;
-}
-
-APP_ERROR MxpiSamplePlugin::SetMxpiErrorInfo(MxpiBuffer& buffer, const std::string pluginName,
-    const MxpiErrorInfo mxpiErrorInfo)
-{
-    APP_ERROR ret = APP_ERR_OK;
-    // Define an object of MxpiMetadataManager
-    MxpiMetadataManager mxpiMetadataManager(buffer);
-    ret = mxpiMetadataManager.AddErrorInfo(pluginName, mxpiErrorInfo);
-    if (ret != APP_ERR_OK) {
-        LogError << "Failed to AddErrorInfo.";
-        return ret;
-    }
-    ret = SendData(0, buffer);
-    return ret;
-}
-
-APP_ERROR MxpiSamplePlugin::openCV(size_t idx, const MxTools::MxpiVision srcMxpiVision,
-                                   MxTools::MxpiVision& dstMxpiVision)
-{
-    LogInfo << "opencv begin";
-    auto& visionInfo = srcMxpiVision.visioninfo();
-    auto& visionData = srcMxpiVision.visiondata();
-    MxBase::MemoryData memorySrc = {};
-    memorySrc.deviceId = visionData.deviceid();
-    memorySrc.type = (MxBase::MemoryData::MemoryType) visionData.memtype();
-    memorySrc.size = visionData.datasize();
-    memorySrc.ptrData = (void*)visionData.dataptr();
-    MxBase::MemoryData memoryDst(visionData.datasize(), MxBase::MemoryData::MEMORY_HOST_NEW);
-    APP_ERROR  res = MxBase::MemoryHelper::MxbsMallocAndCopy(memoryDst, memorySrc);
-    if (res != APP_ERR_OK) {
-        LogError << "Fail to malloc and copy host memory.";
-        return res;
-    }
-    cv::Mat src;
-    cv::Mat imgBgr;
-    Judge(visionData, visionInfo, imgBgr, memorySrc, src, memoryDst);
-    cv::Mat dst;
-    cv::Mat imgYuv;
-    cv::Mat imgRgb;
-    MxBase::MemoryData memoryNewDst(dst.data, MxBase::MemoryData::MEMORY_HOST_NEW);
-    if (option == "resize") {
-	if (memorySrc.type == er) {
-	    cv::resize(imgBgr, dst, cv::Size(width, height), fx, fy, interpolation);
-	}
-	else {
-	    cv::resize(src, dst, cv::Size(width, height), fx, fy, interpolation);
-	}
-    }
-    else {
-      cv::Rect ori(startRow, startCol, endCol, endRow);
-      if (memorySrc.type == san) {
-	dst = src(ori).clone();
-	}
-      else {
-	dst = imgBgr(ori).clone();
-      }
-    }
-    Output(dst, idx, dstMxpiVision);
-    auto ret = APP_ERR_OK;
-    if (ret != APP_ERR_OK) {
-        LogError << "convert mat to mxvision failed!";
-        return ret;
-    }
-    return APP_ERR_OK;
-}
-
-void MxpiSamplePlugin::Judge(auto& visionData, auto& visionInfo, cv::Mat &imgBgr, MxBase::MemoryData memorySrc,
-                             cv::Mat &src, MxBase::MemoryData memoryDst)
-{
-    if (visionData.datatype() == MxTools::MxpiDataType::MXPI_DATA_TYPE_FLOAT32) {
-        imgBgr = cv::Mat(visionInfo.heightaligned(), visionInfo.widthaligned(), CV_32FC3);
-    }
-    else {
-        imgBgr = cv::Mat(visionInfo.heightaligned(), visionInfo.widthaligned(), CV_8UC3);
-    }
-    if (memorySrc.type == san) {
-        if (visionData.datatype() == MxTools::MxpiDataType::MXPI_DATA_TYPE_FLOAT32) {
-            src = cv::Mat(visionInfo.heightaligned(), visionInfo.widthaligned(), CV_32FC3,
-                          memoryDst.ptrData);
-        }
-        else {
-            src = cv::Mat(visionInfo.heightaligned(), visionInfo.widthaligned(), CV_8UC3,
-                          memoryDst.ptrData);
-        }
-    }
-    else {
-        if (visionData.datatype() == MxTools::MxpiDataType::MXPI_DATA_TYPE_FLOAT32) {
-            src = cv::Mat(visionInfo.heightaligned()* YUV_V / YUV_U, visionInfo.widthaligned(), CV_32FC1,
-                          memoryDst.ptrData);
-        }
-        else {
-            src = cv::Mat(visionInfo.heightaligned()* YUV_V / YUV_U, visionInfo.widthaligned(), CV_8UC1,
-                          memoryDst.ptrData);
-        }
-        cv::cvtColor(src, imgBgr, cv::COLOR_YUV2BGR_NV12);
-    }
-}
-
-void MxpiSamplePlugin::Output(cv::Mat dst, size_t idx, MxTools::MxpiVision& dstMxpiVision)
-{
-    cv::Mat imgYuv;
-    cv::Mat imgRgb;
-    if (outputDataFormat == "YUV") {
-        height = dst.rows;
-        width = dst.cols;
-        imgYuv = cv::Mat(height, width, CV_8UC1);
-        dst.convertTo(dst, CV_8UC3);
-        Bgr2Yuv(dst, imgYuv);
-        outputPixelFormat_ = MxBase::MxbasePixelFormat::MXBASE_PIXEL_FORMAT_YUV_SEMIPLANAR_420;
-        auto ret = Mat2MxpiVisionDvpp(idx, imgYuv, dstMxpiVision);
-    }
-    else {
-        if (outputDataFormat == "RGB") {
-        if (dataType == "float32") {
-            imgRgb = cv::Mat(height, width, CV_32FC3);
-            dst.convertTo(imgRgb, CV_32FC3);
-        }
-        else {
-            imgRgb = cv::Mat(height, width, CV_8UC3);
-            dst.convertTo(imgRgb, CV_8UC3);
-        }
-    cv::cvtColor(imgRgb, imgRgb, cv::COLOR_BGR2RGB);
-    outputPixelFormat_ = MxBase::MxbasePixelFormat::MXBASE_PIXEL_FORMAT_RGB_888;
-        auto ret = Mat2MxpiVisionOpencv(idx, imgRgb, dstMxpiVision);
-        }
-        else if (outputDataFormat == "BGR") {
-        if (dataType == "float32") {
-            imgRgb = cv::Mat(height, width, CV_32FC3);
-            dst.convertTo(imgRgb, CV_32FC3);
-        }
-        else {
-            imgRgb = cv::Mat(height, width, CV_8UC3);
-            dst.convertTo(imgRgb, CV_8UC3);
-        }
-        outputPixelFormat_ = MxBase::MxbasePixelFormat::MXBASE_PIXEL_FORMAT_BGR_888;
-            auto ret = Mat2MxpiVisionOpencv(idx, imgRgb, dstMxpiVision);
-        }
-        else {
-        LogError << "outputDataFormat not in RGB,BGR,YUV";
-        }
-    }
-}
-
-APP_ERROR MxpiSamplePlugin::Bgr2Yuv(cv::Mat src, cv::Mat &dst)
-{
-    int w_img = src.cols;
-    int h_img = src.rows;
-    dst = cv::Mat(h_img * yiwu, w_img, CV_8UC1);
-    cv::Mat src_YUV_I420(h_img * yiwu, w_img, CV_8UC1);
-    cvtColor(src, src_YUV_I420, cv::COLOR_BGR2YUV_I420);
-    swapYUV_I420toNV12(src_YUV_I420.data, dst.data, w_img, h_img);
-    return APP_ERR_OK;
-}
-
-void  MxpiSamplePlugin::swapYUV_I420toNV12(unsigned char* i420bytes, unsigned char* nv12bytes, int width, int height)
-{
-    int nLenY = width * height;
-    int nLenU = nLenY / 4;
-
-    memcpy(nv12bytes, i420bytes, width * height);
-
-    for (int i = 0; i < nLenU; i++)
-    {
-        nv12bytes[nLenY + er * i] = i420bytes[nLenY + i];                    // U
-        nv12bytes[nLenY + er * i + 1] = i420bytes[nLenY + nLenU + i];        // V
-    }
-}
-
-APP_ERROR MxpiSamplePlugin::Mat2MxpiVisionDvpp(size_t idx, const cv::Mat& mat, MxTools::MxpiVision& vision)
-{
-    LogInfo << "Mat2MxpiVision begin";
-    auto header = vision.add_headervec();
-    header->set_memberid(idx);
-    header->set_datasource(parentName_);
-
-    auto visionInfo = vision.mutable_visioninfo();
-    visionInfo->set_format(outputPixelFormat_);
-    visionInfo->set_height(mat.rows*YUV_U/YUV_V);
-    visionInfo->set_heightaligned(mat.rows*YUV_U/YUV_V);
-    visionInfo->set_width(mat.cols);
-    visionInfo->set_widthaligned(mat.cols);
-
-    auto visionData = vision.mutable_visiondata();
-    visionData->set_datasize(mat.cols * mat.rows * mat.elemSize());
-    MemoryData memoryDataDst(visionData->datasize(), MemoryData::MEMORY_DVPP, deviceId_);
-    MemoryData memoryDataStr(mat.data, visionData->datasize(), MemoryData::MEMORY_HOST_MALLOC);
-    APP_ERROR  ret = MemoryHelper::MxbsMallocAndCopy(memoryDataDst, memoryDataStr);
-    if (ret != APP_ERR_OK) {
-        LogError << "copy memory error.";
-        return ret;
-    }
-    visionData->set_dataptr((uint64)memoryDataDst.ptrData);
-    visionData->set_deviceid(deviceId_);
-    visionData->set_memtype(MxTools::MXPI_MEMORY_DVPP);
-    if (dataType == "float32") {
-        visionData->set_datatype(MxTools::MxpiDataType::MXPI_DATA_TYPE_FLOAT32);
-    }
-    else if (dataType == "uint8") {
-        visionData->set_datatype(MxTools::MxpiDataType::MXPI_DATA_TYPE_UINT8);
-    }
-    else {
-	LogError << "dataType must in float32,uint8";
-    }
-    LogInfo << "Mat2MxpiVision done";
-    return APP_ERR_OK;
-};
-
-APP_ERROR MxpiSamplePlugin::Mat2MxpiVisionOpencv(size_t idx, const cv::Mat& mat, MxTools::MxpiVision& vision)
-{
-    LogInfo << "Mat2MxpiVision begin";
-    auto header = vision.add_headervec();
-    header->set_memberid(idx);
-    header->set_datasource(parentName_);
-
-    auto visionInfo = vision.mutable_visioninfo();
-    visionInfo->set_format(outputPixelFormat_);
-    visionInfo->set_height(mat.rows);
-    visionInfo->set_heightaligned(mat.rows);
-    visionInfo->set_width(mat.cols);
-    visionInfo->set_widthaligned(mat.cols);
-    auto visionData = vision.mutable_visiondata();
-    visionData->set_datasize(mat.cols * mat.rows * mat.elemSize());
-    MemoryData memoryDataDst(visionData->datasize(), MemoryData::MEMORY_HOST, deviceId_);
-    MemoryData memoryDataStr(mat.data, visionData->datasize(), MemoryData::MEMORY_HOST_MALLOC);
-    APP_ERROR  ret = MemoryHelper::MxbsMallocAndCopy(memoryDataDst, memoryDataStr);
-    if (ret != APP_ERR_OK) {
-        LogError << "copy memory error.";
-        return ret;
-    }
-    visionData->set_dataptr((uint64)memoryDataDst.ptrData);
-    visionData->set_deviceid(deviceId_);
-    visionData->set_memtype(MxTools::MXPI_MEMORY_HOST);
-    if (dataType == "float32") {
-	visionData->set_datatype(MxTools::MxpiDataType::MXPI_DATA_TYPE_FLOAT32);
-    }
-    else if (dataType == "uint8") {
-	visionData->set_datatype(MxTools::MxpiDataType::MXPI_DATA_TYPE_UINT8);
-    }
-    else {
-        LogError << "dataType must in float32,uint8";
-    }
-    LogInfo << "Mat2MxpiVision done";
-    return APP_ERR_OK;
-};
-
-APP_ERROR MxpiSamplePlugin::GenerateVisionList(const MxpiVisionList srcMxpiVisionList,
-                                               MxpiVisionList& dstMxpiVisionList)
-{
-    for (int i = 0; i< srcMxpiVisionList.visionvec_size();i++) {
-        auto srcMxpiVision = srcMxpiVisionList.visionvec(i);
-        MxTools::MxpiVision dstVision;
-        APP_ERROR ret = openCV(i, srcMxpiVision, dstVision);
-        if (ret != APP_ERR_OK) {
-            LogWarn << "element("<< elementName_<<") normailze failed";
-        }
-        dstMxpiVisionList.add_visionvec()->CopyFrom(dstVision);
-    }
-    if (dstMxpiVisionList.visionvec_size() == 0) {
-        LogError <<  "element("<< elementName_<<") dst vision vec size is 0!";
-        return APP_ERR_COMM_FAILURE;
-    }
-    LogInfo << "Generate done";
-    return APP_ERR_OK;
-}
-
-APP_ERROR MxpiSamplePlugin::Process(std::vector<MxpiBuffer*>& mxpiBuffer)
-{
-    LogInfo << "MxpiSamplePlugin::Process start";
-    MxpiBuffer* buffer = mxpiBuffer[0];
-    MxpiMetadataManager mxpiMetadataManager(*buffer);
-    MxpiErrorInfo mxpiErrorInfo;
-    ErrorInfo_.str("");
-    auto errorInfoPtr = mxpiMetadataManager.GetErrorInfo();
-    if (errorInfoPtr != nullptr) {
-        ErrorInfo_ << GetError(APP_ERR_COMM_FAILURE, pluginName_) << "MxpiSamplePlugin process is not implemented";
-        mxpiErrorInfo.ret = APP_ERR_COMM_FAILURE;
-        mxpiErrorInfo.errorInfo = ErrorInfo_.str();
-        SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
-        LogError << "MxpiSamplePlugin process is not implemented";
-        return APP_ERR_COMM_FAILURE;
-    }
-    // Get the data from buffer
-    shared_ptr<void> metadata = mxpiMetadataManager.GetMetadata(parentName_);
-    if (metadata == nullptr) {
-        SendData(0, *buffer);
-        return APP_ERR_METADATA_IS_NULL; // self define the error code
-    }
-    // check the proto struct name
-    google::protobuf::Message* msg = (google::protobuf::Message*)metadata.get();
-    const google::protobuf::Descriptor* desc = msg->GetDescriptor();
-    if (desc->name() != SAMPLE_KEY) {
-        ErrorInfo_ << GetError(APP_ERR_PROTOBUF_NAME_MISMATCH, pluginName_)
-        << "Proto struct name is not MxpiVisionList, failed with:" << desc->name();
-        mxpiErrorInfo.ret = APP_ERR_PROTOBUF_NAME_MISMATCH;
-        mxpiErrorInfo.errorInfo = ErrorInfo_.str();
-        SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
-        return APP_ERR_PROTOBUF_NAME_MISMATCH; // self define the error code
-    }
-    // Generate sample output
-    shared_ptr<MxpiVisionList> srcMxpiVisionListSptr = static_pointer_cast<MxpiVisionList>(metadata);
-    shared_ptr<MxpiVisionList> dstMxpiVisionListptr = make_shared<MxpiVisionList>();
-    LogInfo << "generate";
-    APP_ERROR ret = GenerateVisionList(*srcMxpiVisionListSptr, *dstMxpiVisionListptr);
-    if (ret != APP_ERR_OK) {
-        LogError << GetError(ret, pluginName_) << "MxpiSamplePlugin gets inference information failed.";
-        mxpiErrorInfo.ret = ret;
-        mxpiErrorInfo.errorInfo = ErrorInfo_.str();
-        SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
-        return ret;
-    }
-    // Add Generated data to metedata
-    ret = mxpiMetadataManager.AddProtoMetadata(pluginName_, static_pointer_cast<void>(dstMxpiVisionListptr));
-    if (ret != APP_ERR_OK) {
-        ErrorInfo_ << GetError(ret, pluginName_) << "MxpiSamplePlugin add metadata failed.";
-        mxpiErrorInfo.ret = ret;
-        mxpiErrorInfo.errorInfo = ErrorInfo_.str();
-        SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
-        return ret;
-    }
-    // Send the data to downstream plugin
-    SendData(0, *buffer);
-    LogInfo << "MxpiSamplePlugin::Process end";
-    return APP_ERR_OK;
-}
-
-std::vector<std::shared_ptr<void>> MxpiSamplePlugin::DefineProperties()
-{
-    // Define an A to store properties
-    std::vector<std::shared_ptr<void>> properties;
-    // Set the type and related information of the properties, and the key is the name
-    auto descriptionMessageProSptr = std::make_shared<ElementProperty<string>>(ElementProperty<string> {
-        STRING, "descriptionMessage", "message", "Description mesasge of plugin", "This is MxpiSamplePlugin", "NULL", "NULL"});
-    auto startRow = std::make_shared<ElementProperty<double>>(ElementProperty<double> {
-	DOUBLE, "startRow", "startRow", "the start_row of crop image", 1, 0.0, 8192.0});
-    auto startCol = std::make_shared<ElementProperty<double>>(ElementProperty<double> {
-	DOUBLE, "startCol", "startCol", "the start_col of crop  image", 1, 0.0, 8192.0});
-    auto Height = std::make_shared<ElementProperty<double>>(ElementProperty<double> {
-	DOUBLE, "Height", "Height", "the Height of crop image", 256, 1.0, 8192.0});
-    auto Width = std::make_shared<ElementProperty<double>>(ElementProperty<double> {
-	DOUBLE, "Width", "Width", "the Width of crop image", 256, 1.0, 8192.0});
-    auto height = std::make_shared<ElementProperty<float>>(ElementProperty<float> {
-        FLOAT, "height", "height", "the height of image", 256, 1, 8192});
-    auto width = std::make_shared<ElementProperty<float>>(ElementProperty<float> {
-        FLOAT, "width", "width", "the width of image", 256, 1, 8192});
-    auto fx = std::make_shared<ElementProperty<double>>(ElementProperty<double> {
-        DOUBLE, "fx", "fx", "the fx ratio  of image", 0, 0, 1});
-    auto fy = std::make_shared<ElementProperty<double>>(ElementProperty<double> {
-        DOUBLE, "fy", "fy", "the fy ratio  of image", 0, 0, 1});
-    auto outputDataFormat = std::make_shared<ElementProperty<string>>(ElementProperty<string> {
-        STRING, "outputDataFormat", "outputDataFormat", "the format of the output  RGB or BGR or YUV", "YUV", "NULL", "NULL"});
-    auto dataType = std::make_shared<ElementProperty<string>>(ElementProperty<string> {
-        STRING, "dataType", "dataType", "the dataType  float32 or uint8 ", "uint8", "NULL", "NULL"});
-    auto interpolation = std::make_shared<ElementProperty<int>>(ElementProperty<int> {
-        INT, "interpolation", "interpolation", "the interpolation  of image", 1, 0, 4});
-    auto option = std::make_shared<ElementProperty<string>>(ElementProperty<string> {
-		            STRING, "option", "option", "OPTION of plugin", "resize", "NULL", "NULL"});
-    properties.push_back(descriptionMessageProSptr);
-    properties.push_back(startRow);
-    properties.push_back(startCol);
-    properties.push_back(Height);
-    properties.push_back(Width);
-    properties.push_back(height);
-    properties.push_back(width);
-    properties.push_back(fx);
-    properties.push_back(fy);
-    properties.push_back(outputDataFormat);
-    properties.push_back(dataType);
-    properties.push_back(option);
-    properties.push_back(interpolation);
-
-    return properties;
-}
-
-// Register the Sample plugin through macro
-MX_PLUGIN_GENERATE(MxpiSamplePlugin)
+/*
+* Copyright(C) 2020. Huawei Technologies Co.,Ltd. All rights reserved.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*     http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "OpenCVPlugin.h"
+#include "MxBase/Log/Log.h"
+#include "MxBase/Tensor/TensorBase/TensorBase.h"
+using namespace MxBase;
+using namespace MxPlugins;
+using namespace MxTools;
+using namespace std;
+namespace {
+    const string SAMPLE_KEY = "MxpiVisionList";
+    const int YUV_U = 2;
+    const int YUV_V = 3;
+    const int san = 3;
+    const int er = 2;
+    const int yi = 1;
+    const float yiwu = 1.5;
+}
+
+APP_ERROR MxpiSamplePlugin::Init(std::map<std::string, std::shared_ptr<void>>& configParamMap)
+{
+    LogInfo << "MxpiSamplePlugin::Init start.";
+    APP_ERROR ret = APP_ERR_OK;
+    // Get the property values by key
+    parentName_ = dataSource_;
+    std::shared_ptr<string> descriptionMessageProSptr =
+    std::static_pointer_cast<string>(configParamMap["descriptionMessage"]);
+    height = *std::static_pointer_cast<float>(configParamMap["height"]);
+    width = *std::static_pointer_cast<float>(configParamMap["width"]);
+    fx = *std::static_pointer_cast<double>(configParamMap["fx"]);
+    fy = *std::static_pointer_cast<double>(configParamMap["fy"]);
+    interpolation = *std::static_pointer_cast<int>(configParamMap["interpolation"]); 
+    startRow = *std::static_pointer_cast<double>(configParamMap["startRow"]);
+    endRow = *std::static_pointer_cast<double>(configParamMap["Height"]);
+    startCol = *std::static_pointer_cast<double>(configParamMap["startCol"]);
+    endCol = *std::static_pointer_cast<double>(configParamMap["Width"]);
+    outputDataFormat = *std::static_pointer_cast<string>(configParamMap["outputDataFormat"]);
+    dataType = *std::static_pointer_cast<string>(configParamMap["dataType"]);
+    option = *std::static_pointer_cast<string>(configParamMap["option"]);
+    descriptionMessage_ = *descriptionMessageProSptr.get();
+    return APP_ERR_OK;
+}
+
+APP_ERROR MxpiSamplePlugin::DeInit()
+{
+    LogInfo << "MxpiSamplePlugin::DeInit end.";
+    return APP_ERR_OK;
+}
+
+APP_ERROR MxpiSamplePlugin::SetMxpiErrorInfo(MxpiBuffer& buffer, const std::string pluginName,
+    const MxpiErrorInfo mxpiErrorInfo)
+{
+    APP_ERROR ret = APP_ERR_OK;
+    // Define an object of MxpiMetadataManager
+    MxpiMetadataManager mxpiMetadataManager(buffer);
+    ret = mxpiMetadataManager.AddErrorInfo(pluginName, mxpiErrorInfo);
+    if (ret != APP_ERR_OK) {
+        LogError << "Failed to AddErrorInfo.";
+        return ret;
+    }
+    ret = SendData(0, buffer);
+    return ret;
+}
+
+APP_ERROR MxpiSamplePlugin::openCV(size_t idx, const MxTools::MxpiVision srcMxpiVision,
+                                   MxTools::MxpiVision& dstMxpiVision)
+{
+    LogInfo << "opencv begin";
+    auto& visionInfo = srcMxpiVision.visioninfo();
+    auto& visionData = srcMxpiVision.visiondata();
+    MxBase::MemoryData memorySrc = {};
+    memorySrc.deviceId = visionData.deviceid();
+    memorySrc.type = (MxBase::MemoryData::MemoryType) visionData.memtype();
+    memorySrc.size = visionData.datasize();
+    memorySrc.ptrData = (void*)visionData.dataptr();
+    MxBase::MemoryData memoryDst(visionData.datasize(), MxBase::MemoryData::MEMORY_HOST_NEW);
+    APP_ERROR  res = MxBase::MemoryHelper::MxbsMallocAndCopy(memoryDst, memorySrc);
+    if (res != APP_ERR_OK) {
+        LogError << "Fail to malloc and copy host memory.";
+        return res;
+    }
+    cv::Mat src;
+    cv::Mat imgBgr;
+    Judge(visionData, visionInfo, imgBgr, memorySrc, src, memoryDst);
+    cv::Mat dst;
+    cv::Mat imgYuv;
+    cv::Mat imgRgb;
+    MxBase::MemoryData memoryNewDst(dst.data, MxBase::MemoryData::MEMORY_HOST_NEW);
+    if (option == "resize") {
+	if (memorySrc.type == er) {
+	    cv::resize(imgBgr, dst, cv::Size(width, height), fx, fy, interpolation);
+	}
+	else {
+	    cv::resize(src, dst, cv::Size(width, height), fx, fy, interpolation);
+	}
+    }
+    else {
+      cv::Rect ori(startRow, startCol, endCol, endRow);
+      if (memorySrc.type == san) {
+	dst = src(ori).clone();
+	}
+      else {
+	dst = imgBgr(ori).clone();
+      }
+    }
+    Output(dst, idx, dstMxpiVision);
+    auto ret = APP_ERR_OK;
+    if (ret != APP_ERR_OK) {
+        LogError << "convert mat to mxvision failed!";
+        return ret;
+    }
+    return APP_ERR_OK;
+}
+
+void MxpiSamplePlugin::Judge(auto& visionData, auto& visionInfo, cv::Mat &imgBgr, MxBase::MemoryData memorySrc,
+                             cv::Mat &src, MxBase::MemoryData memoryDst)
+{
+    if (visionData.datatype() == MxTools::MxpiDataType::MXPI_DATA_TYPE_FLOAT32) {
+        imgBgr = cv::Mat(visionInfo.heightaligned(), visionInfo.widthaligned(), CV_32FC3);
+    }
+    else {
+        imgBgr = cv::Mat(visionInfo.heightaligned(), visionInfo.widthaligned(), CV_8UC3);
+    }
+    if (memorySrc.type == san) {
+        if (visionData.datatype() == MxTools::MxpiDataType::MXPI_DATA_TYPE_FLOAT32) {
+            src = cv::Mat(visionInfo.heightaligned(), visionInfo.widthaligned(), CV_32FC3,
+                          memoryDst.ptrData);
+        }
+        else {
+            src = cv::Mat(visionInfo.heightaligned(), visionInfo.widthaligned(), CV_8UC3,
+                          memoryDst.ptrData);
+        }
+    }
+    else {
+        if (visionData.datatype() == MxTools::MxpiDataType::MXPI_DATA_TYPE_FLOAT32) {
+            src = cv::Mat(visionInfo.heightaligned()* YUV_V / YUV_U, visionInfo.widthaligned(), CV_32FC1,
+                          memoryDst.ptrData);
+        }
+        else {
+            src = cv::Mat(visionInfo.heightaligned()* YUV_V / YUV_U, visionInfo.widthaligned(), CV_8UC1,
+                          memoryDst.ptrData);
+        }
+        cv::cvtColor(src, imgBgr, cv::COLOR_YUV2BGR_NV12);
+    }
+}
+
+void MxpiSamplePlugin::Output(cv::Mat dst, size_t idx, MxTools::MxpiVision& dstMxpiVision)
+{
+    cv::Mat imgYuv;
+    cv::Mat imgRgb;
+    if (outputDataFormat == "YUV") {
+        height = dst.rows;
+        width = dst.cols;
+        imgYuv = cv::Mat(height, width, CV_8UC1);
+        dst.convertTo(dst, CV_8UC3);
+        Bgr2Yuv(dst, imgYuv);
+        outputPixelFormat_ = MxBase::MxbasePixelFormat::MXBASE_PIXEL_FORMAT_YUV_SEMIPLANAR_420;
+        auto ret = Mat2MxpiVisionDvpp(idx, imgYuv, dstMxpiVision);
+    }
+    else {
+        if (outputDataFormat == "RGB") {
+        if (dataType == "float32") {
+            imgRgb = cv::Mat(height, width, CV_32FC3);
+            dst.convertTo(imgRgb, CV_32FC3);
+        }
+        else {
+            imgRgb = cv::Mat(height, width, CV_8UC3);
+            dst.convertTo(imgRgb, CV_8UC3);
+        }
+    cv::cvtColor(imgRgb, imgRgb, cv::COLOR_BGR2RGB);
+    outputPixelFormat_ = MxBase::MxbasePixelFormat::MXBASE_PIXEL_FORMAT_RGB_888;
+        auto ret = Mat2MxpiVisionOpencv(idx, imgRgb, dstMxpiVision);
+        }
+        else if (outputDataFormat == "BGR") {
+        if (dataType == "float32") {
+            imgRgb = cv::Mat(height, width, CV_32FC3);
+            dst.convertTo(imgRgb, CV_32FC3);
+        }
+        else {
+            imgRgb = cv::Mat(height, width, CV_8UC3);
+            dst.convertTo(imgRgb, CV_8UC3);
+        }
+        outputPixelFormat_ = MxBase::MxbasePixelFormat::MXBASE_PIXEL_FORMAT_BGR_888;
+            auto ret = Mat2MxpiVisionOpencv(idx, imgRgb, dstMxpiVision);
+        }
+        else {
+        LogError << "outputDataFormat not in RGB,BGR,YUV";
+        }
+    }
+}
+
+APP_ERROR MxpiSamplePlugin::Bgr2Yuv(cv::Mat src, cv::Mat &dst)
+{
+    int w_img = src.cols;
+    int h_img = src.rows;
+    dst = cv::Mat(h_img * yiwu, w_img, CV_8UC1);
+    cv::Mat src_YUV_I420(h_img * yiwu, w_img, CV_8UC1);
+    cvtColor(src, src_YUV_I420, cv::COLOR_BGR2YUV_I420);
+    swapYUV_I420toNV12(src_YUV_I420.data, dst.data, w_img, h_img);
+    return APP_ERR_OK;
+}
+
+void  MxpiSamplePlugin::swapYUV_I420toNV12(unsigned char* i420bytes, unsigned char* nv12bytes, int width, int height)
+{
+    int nLenY = width * height;
+    int nLenU = nLenY / 4;
+
+    memcpy(nv12bytes, i420bytes, width * height);
+
+    for (int i = 0; i < nLenU; i++)
+    {
+        nv12bytes[nLenY + er * i] = i420bytes[nLenY + i];                    // U
+        nv12bytes[nLenY + er * i + 1] = i420bytes[nLenY + nLenU + i];        // V
+    }
+}
+
+APP_ERROR MxpiSamplePlugin::Mat2MxpiVisionDvpp(size_t idx, const cv::Mat& mat, MxTools::MxpiVision& vision)
+{
+    LogInfo << "Mat2MxpiVision begin";
+    auto header = vision.add_headervec();
+    header->set_memberid(idx);
+    header->set_datasource(parentName_);
+
+    auto visionInfo = vision.mutable_visioninfo();
+    visionInfo->set_format(outputPixelFormat_);
+    visionInfo->set_height(mat.rows*YUV_U/YUV_V);
+    visionInfo->set_heightaligned(mat.rows*YUV_U/YUV_V);
+    visionInfo->set_width(mat.cols);
+    visionInfo->set_widthaligned(mat.cols);
+
+    auto visionData = vision.mutable_visiondata();
+    visionData->set_datasize(mat.cols * mat.rows * mat.elemSize());
+    MemoryData memoryDataDst(visionData->datasize(), MemoryData::MEMORY_DVPP, deviceId_);
+    MemoryData memoryDataStr(mat.data, visionData->datasize(), MemoryData::MEMORY_HOST_MALLOC);
+    APP_ERROR  ret = MemoryHelper::MxbsMallocAndCopy(memoryDataDst, memoryDataStr);
+    if (ret != APP_ERR_OK) {
+        LogError << "copy memory error.";
+        return ret;
+    }
+    visionData->set_dataptr((uint64)memoryDataDst.ptrData);
+    visionData->set_deviceid(deviceId_);
+    visionData->set_memtype(MxTools::MXPI_MEMORY_DVPP);
+    if (dataType == "float32") {
+        visionData->set_datatype(MxTools::MxpiDataType::MXPI_DATA_TYPE_FLOAT32);
+    }
+    else if (dataType == "uint8") {
+        visionData->set_datatype(MxTools::MxpiDataType::MXPI_DATA_TYPE_UINT8);
+    }
+    else {
+	LogError << "dataType must in float32,uint8";
+    }
+    LogInfo << "Mat2MxpiVision done";
+    return APP_ERR_OK;
+};
+
+APP_ERROR MxpiSamplePlugin::Mat2MxpiVisionOpencv(size_t idx, const cv::Mat& mat, MxTools::MxpiVision& vision)
+{
+    LogInfo << "Mat2MxpiVision begin";
+    auto header = vision.add_headervec();
+    header->set_memberid(idx);
+    header->set_datasource(parentName_);
+
+    auto visionInfo = vision.mutable_visioninfo();
+    visionInfo->set_format(outputPixelFormat_);
+    visionInfo->set_height(mat.rows);
+    visionInfo->set_heightaligned(mat.rows);
+    visionInfo->set_width(mat.cols);
+    visionInfo->set_widthaligned(mat.cols);
+    auto visionData = vision.mutable_visiondata();
+    visionData->set_datasize(mat.cols * mat.rows * mat.elemSize());
+    MemoryData memoryDataDst(visionData->datasize(), MemoryData::MEMORY_HOST, deviceId_);
+    MemoryData memoryDataStr(mat.data, visionData->datasize(), MemoryData::MEMORY_HOST_MALLOC);
+    APP_ERROR  ret = MemoryHelper::MxbsMallocAndCopy(memoryDataDst, memoryDataStr);
+    if (ret != APP_ERR_OK) {
+        LogError << "copy memory error.";
+        return ret;
+    }
+    visionData->set_dataptr((uint64)memoryDataDst.ptrData);
+    visionData->set_deviceid(deviceId_);
+    visionData->set_memtype(MxTools::MXPI_MEMORY_HOST);
+    if (dataType == "float32") {
+	visionData->set_datatype(MxTools::MxpiDataType::MXPI_DATA_TYPE_FLOAT32);
+    }
+    else if (dataType == "uint8") {
+	visionData->set_datatype(MxTools::MxpiDataType::MXPI_DATA_TYPE_UINT8);
+    }
+    else {
+        LogError << "dataType must in float32,uint8";
+    }
+    LogInfo << "Mat2MxpiVision done";
+    return APP_ERR_OK;
+};
+
+APP_ERROR MxpiSamplePlugin::GenerateVisionList(const MxpiVisionList srcMxpiVisionList,
+                                               MxpiVisionList& dstMxpiVisionList)
+{
+    for (int i = 0; i< srcMxpiVisionList.visionvec_size();i++) {
+        auto srcMxpiVision = srcMxpiVisionList.visionvec(i);
+        MxTools::MxpiVision dstVision;
+        APP_ERROR ret = openCV(i, srcMxpiVision, dstVision);
+        if (ret != APP_ERR_OK) {
+            LogWarn << "element("<< elementName_<<") normailze failed";
+        }
+        dstMxpiVisionList.add_visionvec()->CopyFrom(dstVision);
+    }
+    if (dstMxpiVisionList.visionvec_size() == 0) {
+        LogError <<  "element("<< elementName_<<") dst vision vec size is 0!";
+        return APP_ERR_COMM_FAILURE;
+    }
+    LogInfo << "Generate done";
+    return APP_ERR_OK;
+}
+
+APP_ERROR MxpiSamplePlugin::Process(std::vector<MxpiBuffer*>& mxpiBuffer)
+{
+    LogInfo << "MxpiSamplePlugin::Process start";
+    MxpiBuffer* buffer = mxpiBuffer[0];
+    MxpiMetadataManager mxpiMetadataManager(*buffer);
+    MxpiErrorInfo mxpiErrorInfo;
+    ErrorInfo_.str("");
+    auto errorInfoPtr = mxpiMetadataManager.GetErrorInfo();
+    if (errorInfoPtr != nullptr) {
+        ErrorInfo_ << GetError(APP_ERR_COMM_FAILURE, pluginName_) << "MxpiSamplePlugin process is not implemented";
+        mxpiErrorInfo.ret = APP_ERR_COMM_FAILURE;
+        mxpiErrorInfo.errorInfo = ErrorInfo_.str();
+        SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
+        LogError << "MxpiSamplePlugin process is not implemented";
+        return APP_ERR_COMM_FAILURE;
+    }
+    // Get the data from buffer
+    shared_ptr<void> metadata = mxpiMetadataManager.GetMetadata(parentName_);
+    if (metadata == nullptr) {
+        SendData(0, *buffer);
+        return APP_ERR_METADATA_IS_NULL; // self define the error code
+    }
+    // check the proto struct name
+    google::protobuf::Message* msg = (google::protobuf::Message*)metadata.get();
+    const google::protobuf::Descriptor* desc = msg->GetDescriptor();
+    if (desc->name() != SAMPLE_KEY) {
+        ErrorInfo_ << GetError(APP_ERR_PROTOBUF_NAME_MISMATCH, pluginName_)
+        << "Proto struct name is not MxpiVisionList, failed with:" << desc->name();
+        mxpiErrorInfo.ret = APP_ERR_PROTOBUF_NAME_MISMATCH;
+        mxpiErrorInfo.errorInfo = ErrorInfo_.str();
+        SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
+        return APP_ERR_PROTOBUF_NAME_MISMATCH; // self define the error code
+    }
+    // Generate sample output
+    shared_ptr<MxpiVisionList> srcMxpiVisionListSptr = static_pointer_cast<MxpiVisionList>(metadata);
+    shared_ptr<MxpiVisionList> dstMxpiVisionListptr = make_shared<MxpiVisionList>();
+    LogInfo << "generate";
+    APP_ERROR ret = GenerateVisionList(*srcMxpiVisionListSptr, *dstMxpiVisionListptr);
+    if (ret != APP_ERR_OK) {
+        LogError << GetError(ret, pluginName_) << "MxpiSamplePlugin gets inference information failed.";
+        mxpiErrorInfo.ret = ret;
+        mxpiErrorInfo.errorInfo = ErrorInfo_.str();
+        SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
+        return ret;
+    }
+    // Add Generated data to metedata
+    ret = mxpiMetadataManager.AddProtoMetadata(pluginName_, static_pointer_cast<void>(dstMxpiVisionListptr));
+    if (ret != APP_ERR_OK) {
+        ErrorInfo_ << GetError(ret, pluginName_) << "MxpiSamplePlugin add metadata failed.";
+        mxpiErrorInfo.ret = ret;
+        mxpiErrorInfo.errorInfo = ErrorInfo_.str();
+        SetMxpiErrorInfo(*buffer, pluginName_, mxpiErrorInfo);
+        return ret;
+    }
+    // Send the data to downstream plugin
+    SendData(0, *buffer);
+    LogInfo << "MxpiSamplePlugin::Process end";
+    return APP_ERR_OK;
+}
+
+std::vector<std::shared_ptr<void>> MxpiSamplePlugin::DefineProperties()
+{
+    // Define an A to store properties
+    std::vector<std::shared_ptr<void>> properties;
+    // Set the type and related information of the properties, and the key is the name
+    auto descriptionMessageProSptr = std::make_shared<ElementProperty<string>>(ElementProperty<string> {
+        STRING, "descriptionMessage", "message", "Description mesasge of plugin", "This is MxpiSamplePlugin", "NULL", "NULL"});
+    auto startRow = std::make_shared<ElementProperty<double>>(ElementProperty<double> {
+	DOUBLE, "startRow", "startRow", "the start_row of crop image", 1, 0.0, 8192.0});
+    auto startCol = std::make_shared<ElementProperty<double>>(ElementProperty<double> {
+	DOUBLE, "startCol", "startCol", "the start_col of crop  image", 1, 0.0, 8192.0});
+    auto Height = std::make_shared<ElementProperty<double>>(ElementProperty<double> {
+	DOUBLE, "Height", "Height", "the Height of crop image", 256, 1.0, 8192.0});
+    auto Width = std::make_shared<ElementProperty<double>>(ElementProperty<double> {
+	DOUBLE, "Width", "Width", "the Width of crop image", 256, 1.0, 8192.0});
+    auto height = std::make_shared<ElementProperty<float>>(ElementProperty<float> {
+        FLOAT, "height", "height", "the height of image", 256, 1, 8192});
+    auto width = std::make_shared<ElementProperty<float>>(ElementProperty<float> {
+        FLOAT, "width", "width", "the width of image", 256, 1, 8192});
+    auto fx = std::make_shared<ElementProperty<double>>(ElementProperty<double> {
+        DOUBLE, "fx", "fx", "the fx ratio  of image", 0, 0, 1});
+    auto fy = std::make_shared<ElementProperty<double>>(ElementProperty<double> {
+        DOUBLE, "fy", "fy", "the fy ratio  of image", 0, 0, 1});
+    auto outputDataFormat = std::make_shared<ElementProperty<string>>(ElementProperty<string> {
+        STRING, "outputDataFormat", "outputDataFormat", "the format of the output  RGB or BGR or YUV", "YUV", "NULL", "NULL"});
+    auto dataType = std::make_shared<ElementProperty<string>>(ElementProperty<string> {
+        STRING, "dataType", "dataType", "the dataType  float32 or uint8 ", "uint8", "NULL", "NULL"});
+    auto interpolation = std::make_shared<ElementProperty<int>>(ElementProperty<int> {
+        INT, "interpolation", "interpolation", "the interpolation  of image", 1, 0, 4});
+    auto option = std::make_shared<ElementProperty<string>>(ElementProperty<string> {
+		            STRING, "option", "option", "OPTION of plugin", "resize", "NULL", "NULL"});
+    properties.push_back(descriptionMessageProSptr);
+    properties.push_back(startRow);
+    properties.push_back(startCol);
+    properties.push_back(Height);
+    properties.push_back(Width);
+    properties.push_back(height);
+    properties.push_back(width);
+    properties.push_back(fx);
+    properties.push_back(fy);
+    properties.push_back(outputDataFormat);
+    properties.push_back(dataType);
+    properties.push_back(option);
+    properties.push_back(interpolation);
+
+    return properties;
+}
+
+// Register the Sample plugin through macro
+MX_PLUGIN_GENERATE(MxpiSamplePlugin)
diff --git a/contrib/OpenCVPlugin/OpenCVPlugin/src/OpenCVPlugin/OpenCVPlugin.h b/mxVision/mxVision-referenceapps/OpenCVPlugin/OpenCVPlugin/src/OpenCVPlugin/OpenCVPlugin.h
similarity index 97%
rename from contrib/OpenCVPlugin/OpenCVPlugin/src/OpenCVPlugin/OpenCVPlugin.h
rename to mxVision/mxVision-referenceapps/OpenCVPlugin/OpenCVPlugin/src/OpenCVPlugin/OpenCVPlugin.h
index 576e61bcb9ee963d9eb872fe497a8311b304218e..437b3b95b8571bed4b7d1c40cd6d7ee36e014ff0 100644
--- a/contrib/OpenCVPlugin/OpenCVPlugin/src/OpenCVPlugin/OpenCVPlugin.h
+++ b/mxVision/mxVision-referenceapps/OpenCVPlugin/OpenCVPlugin/src/OpenCVPlugin/OpenCVPlugin.h
@@ -1,99 +1,99 @@
-/*
-* Copyright(C) 2020. Huawei Technologies Co.,Ltd. All rights reserved.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-*     http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-
-#ifndef SDKMEMORY_MXPISAMPLEPLUGIN_H
-#define SDKMEMORY_MXPISAMPLEPLUGIN_H
-#include "opencv2/opencv.hpp"
-#include "MxTools/PluginToolkit/base/MxPluginGenerator.h"
-#include "MxTools/PluginToolkit/base/MxPluginBase.h"
-#include "MxTools/PluginToolkit/metadata/MxpiMetadataManager.h"
-#include "MxTools/Proto/MxpiDataType.pb.h"
-#include "MxBase/ErrorCode/ErrorCode.h"
-#include "MxBase/DvppWrapper/DvppWrapper.h"
-
-/**
-* @api
-* @brief Definition of MxpiSamplePlugin class.
-*/
-namespace MxPlugins {
-class MxpiSamplePlugin : public MxTools::MxPluginBase {
-public:
-    /**
-     * @api
-     * @brief Initialize configure parameter.
-     * @param configParamMap
-     * @return APP_ERROR
-     */
-    APP_ERROR Init(std::map<std::string, std::shared_ptr<void>>& configParamMap) override;
-    /**
-     * @api
-     * @brief DeInitialize configure parameter.
-     * @return APP_ERROR
-     */
-    APP_ERROR DeInit() override;
-    /**
-     * @api
-     * @brief Process the data of MxpiBuffer.
-     * @param mxpiBuffer
-     * @return APP_ERROR
-     */
-    APP_ERROR Process(std::vector<MxTools::MxpiBuffer*>& mxpiBuffer) override;
-    /**
-     * @api
-     * @brief Definition the parameter of configure properties.
-     * @return std::vector<std::shared_ptr<void>>
-     */
-    static std::vector<std::shared_ptr<void>> DefineProperties();
-    /**
-     * @api
-     * @brief Get the number of class id and confidence from model inference.
-     * @param key
-     * @param buffer
-     * @return APP_ERROR
-     */
-    APP_ERROR GenerateVisionList(const MxTools::MxpiVisionList srcMxpiVisionListptr,
-                                 MxTools::MxpiVisionList& dstMxpiVisionListptr);
-    APP_ERROR openCV(size_t idx, const MxTools::MxpiVision srcMxpiVision,
-        		    MxTools::MxpiVision& dstMxpiVision);
-    APP_ERROR Bgr2Yuv(cv::Mat src, cv::Mat &dst);
-    APP_ERROR Mat2MxpiVisionOpencv(size_t idx, const cv::Mat& mat, MxTools::MxpiVision& vision);
-    APP_ERROR Mat2MxpiVisionDvpp(size_t idx, const cv::Mat& mat, MxTools::MxpiVision& vision);
-    void swapYUV_I420toNV12(unsigned char* i420bytes, unsigned char* nv12bytes, int width, int height);
-    void Judge(auto& visionData, auto& visionInfo, cv::Mat &imgBgr, MxBase::MemoryData memorySrc,
-                                      cv::Mat &src, MxBase::MemoryData memoryDst);
-    void Output(cv::Mat dst, size_t idx, MxTools::MxpiVision& dstMxpiVision);
-private:
-    APP_ERROR SetMxpiErrorInfo(MxTools::MxpiBuffer& buffer, const std::string pluginName,
-    const MxTools::MxpiErrorInfo mxpiErrorInfo);
-    std::string parentName_;
-    std::string descriptionMessage_;
-    double startRow;
-    double startCol;
-    double endRow;
-    double endCol;
-    float height;
-    float width;
-    double fx;
-    double fy;
-    std::string outputDataFormat;
-    std::string dataType;
-    std::string option;
-    int interpolation;
-    std::ostringstream ErrorInfo_;
-    MxBase::MxbasePixelFormat outputPixelFormat_;
-    };
-}
-#endif
+/*
+* Copyright(C) 2020. Huawei Technologies Co.,Ltd. All rights reserved.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*     http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#ifndef SDKMEMORY_MXPISAMPLEPLUGIN_H
+#define SDKMEMORY_MXPISAMPLEPLUGIN_H
+#include "opencv2/opencv.hpp"
+#include "MxTools/PluginToolkit/base/MxPluginGenerator.h"
+#include "MxTools/PluginToolkit/base/MxPluginBase.h"
+#include "MxTools/PluginToolkit/metadata/MxpiMetadataManager.h"
+#include "MxTools/Proto/MxpiDataType.pb.h"
+#include "MxBase/ErrorCode/ErrorCode.h"
+#include "MxBase/DvppWrapper/DvppWrapper.h"
+
+/**
+* @api
+* @brief Definition of MxpiSamplePlugin class.
+*/
+namespace MxPlugins {
+class MxpiSamplePlugin : public MxTools::MxPluginBase {
+public:
+    /**
+     * @api
+     * @brief Initialize configure parameter.
+     * @param configParamMap
+     * @return APP_ERROR
+     */
+    APP_ERROR Init(std::map<std::string, std::shared_ptr<void>>& configParamMap) override;
+    /**
+     * @api
+     * @brief DeInitialize configure parameter.
+     * @return APP_ERROR
+     */
+    APP_ERROR DeInit() override;
+    /**
+     * @api
+     * @brief Process the data of MxpiBuffer.
+     * @param mxpiBuffer
+     * @return APP_ERROR
+     */
+    APP_ERROR Process(std::vector<MxTools::MxpiBuffer*>& mxpiBuffer) override;
+    /**
+     * @api
+     * @brief Definition the parameter of configure properties.
+     * @return std::vector<std::shared_ptr<void>>
+     */
+    static std::vector<std::shared_ptr<void>> DefineProperties();
+    /**
+     * @api
+     * @brief Get the number of class id and confidence from model inference.
+     * @param key
+     * @param buffer
+     * @return APP_ERROR
+     */
+    APP_ERROR GenerateVisionList(const MxTools::MxpiVisionList srcMxpiVisionListptr,
+                                 MxTools::MxpiVisionList& dstMxpiVisionListptr);
+    APP_ERROR openCV(size_t idx, const MxTools::MxpiVision srcMxpiVision,
+        		    MxTools::MxpiVision& dstMxpiVision);
+    APP_ERROR Bgr2Yuv(cv::Mat src, cv::Mat &dst);
+    APP_ERROR Mat2MxpiVisionOpencv(size_t idx, const cv::Mat& mat, MxTools::MxpiVision& vision);
+    APP_ERROR Mat2MxpiVisionDvpp(size_t idx, const cv::Mat& mat, MxTools::MxpiVision& vision);
+    void swapYUV_I420toNV12(unsigned char* i420bytes, unsigned char* nv12bytes, int width, int height);
+    void Judge(auto& visionData, auto& visionInfo, cv::Mat &imgBgr, MxBase::MemoryData memorySrc,
+                                      cv::Mat &src, MxBase::MemoryData memoryDst);
+    void Output(cv::Mat dst, size_t idx, MxTools::MxpiVision& dstMxpiVision);
+private:
+    APP_ERROR SetMxpiErrorInfo(MxTools::MxpiBuffer& buffer, const std::string pluginName,
+    const MxTools::MxpiErrorInfo mxpiErrorInfo);
+    std::string parentName_;
+    std::string descriptionMessage_;
+    double startRow;
+    double startCol;
+    double endRow;
+    double endCol;
+    float height;
+    float width;
+    double fx;
+    double fy;
+    std::string outputDataFormat;
+    std::string dataType;
+    std::string option;
+    int interpolation;
+    std::ostringstream ErrorInfo_;
+    MxBase::MxbasePixelFormat outputPixelFormat_;
+    };
+}
+#endif
diff --git a/contrib/OpenCVPlugin/README.md b/mxVision/mxVision-referenceapps/OpenCVPlugin/README.md
similarity index 97%
rename from contrib/OpenCVPlugin/README.md
rename to mxVision/mxVision-referenceapps/OpenCVPlugin/README.md
index ec45cc3894d8da456618587f32bab03bb61526a0..8528374d8b26b9a4a5f2204a522f04e1ba900d52 100644
--- a/contrib/OpenCVPlugin/README.md
+++ b/mxVision/mxVision-referenceapps/OpenCVPlugin/README.md
@@ -1,202 +1,202 @@
-
-
-# OpenCV 插件
-
-## 1. 介绍
-
-本代码仓插件实现了opencv的抠图和缩放功能。   
-抠图：
-支持根据目标检测的（x,y）坐标和（width,height）宽高进行图像裁剪（抠图）。   
-缩放：
-对解码后的YUV格式以及BGR格式的图像进行指定宽高的缩放。
-
-### 1.1 支持的产品
-
-本项目以昇腾Atlas310卡为主要的硬件平台。
-
-
-### 1.2 支持的版本
-
-支持的SDK版本为 2.0.4, CANN 版本为 5.0.4。
-
-
-### 1.3 软件方案介绍 
-
-本项目包含两个功能，即抠图与缩放。
-
-#### 1.3.1 抠图
-
-整体业务流程为：待检测图片通过 appsrc 插件输入，然后使用图像解码插件 mxpi_imagedecoder 对图片进行解码，再通过图像抠图插件 OpenCVPlugin进行将图片抠图（其前后可接其他插件）。最后通过输出插件 appsink 获取结果，并在外部进行可视化，将结果标记到原图上，本系统的各模块及功能描述如表1所示：
-
-表1 系统方案各模块功能描述：
-
-| 序号 | 子系统     | 功能描述              |
-| ---- | ---------- | --------------------- |
-| 1    | 图片输入   | 获取 jpg 格式输入图片 |
-| 2    | 图片解码   | 解码图片              |
-| 3    | 其他插件   | 其他插件的功能        |
-| 4    | 抠图       | 对输入图片进行抠图    |
-| 5    | 其他插件   | 其他插件的功能        |
-| 6    | 结果输出   | 获取检测结果          |
-| 7    | 结果可视化 | 将结果保存            |
-
-
-#### 1.3.2 缩放
-
-整体业务流程为：待检测图片信息经预处理后通过 appsrc 插件输入，然后使用图像解码插件 mxpi_imagedecoder 对图片进行解码，再通过图像缩放插件 OpenCVPlugin进行对图片进行缩放（其前后可接其他插件）。最后通过输出插件 appsink 获取检测结果，并在外部进行可视化，将结果标记到原图上，本系统的各模块及功能描述如表2所示：
-
-表2 系统方案各模块功能描述：
-
-| 序号 | 子系统     | 功能描述              |
-| ---- | ---------- | --------------------- |
-| 1    | 图片输入   | 获取 jpg 格式输入图片 |
-| 2    | 图片解码   | 解码图片              |
-| 3    | 其他插件   | 其他插件的功能        |
-| 4    | 缩放       | 对输入图片进行缩放    |
-| 5    | 其他插件   | 其他插件的功能        |
-| 6    | 结果输出   | 获取检测结果          |
-| 7    | 结果可视化 | 将结果保存            |
-
-### 1.4 代码目录结构与说明
-
-本工程名称为OpenCVPlugin，工程目录如下所示：
-
-```
-.
-├── image
-│   ├── pipeline.jpg
-├── OpenCVPlugin
-│   ├──lib （编译后生成）
-│   ├──src
-│   │   ├──OpenCVPlugin
-│   │       ├── CMakeLists.txt
-│   │       ├── OpenCVPlugin.cpp
-│   │       └── OpenCVPlugin.h
-├── python
-│   ├── main.py
-│   └── test.pipeline
-├── build.sh
-└── README.md
-
-```
-
-### 1.5 技术实现流程图
-
-OpenCVPlugin 插件流程图。
-
-<center>
-    <img src="./images/pipeline.jpg">
-    <br>
-</center>
-
-
-### 1.6 适用场景
-
-输入：metadata（数据类型“MxpiVisionList”）   
-输出：metadata（数据类型“MxpiVisionList”）
-
-静态输入：{"image/yuv","image/rgb"}   
-静态输出：{"image/rgb"}
-
-## 2 环境依赖
-
-推荐系统为ubuntu 18.04，环境依赖软件和版本如下表：
-
-| 软件名称 | 版本  |
-| -------- | ----- |
-| cmake    | 3.5+  |
-| mxVision | 2.0.4 |
-| python   | 3.9.2 |
-
-确保环境中正确安装mxVision SDK。
-
-在编译运行项目前，需要设置环境变量：
-
-MindX SDK 环境变量:
-
-```
-. ${SDK-path}/set_env.sh
-```
-
-CANN 环境变量：
-
-```
-. ${ascend-toolkit-path}/set_env.sh
-```
-
-- 环境变量介绍
-
-```
-SDK-path: SDK mxVision 安装路径
-ascend-toolkit-path: CANN 安装路径
-```
-
-## 3 属性介绍
-
-### 3.1 抠图功能的pipeline属性
-
-| 序号 | 属性             | 描述                                                 | 是否为必选项 | 是否可修改 |
-| ---- | ---------------- | ----------------------------------------------------- | ------------ | ---------- |
-| 1    | option           | 插件功能选择，此处使用"crop"                          | 是           | 是         |
-| 2    | startRow         | 抠图选定区域的开始纵坐标， 默认为"0"，取值为0~原图高  | 否           | 是         |
-| 3    | startCol         | 抠图选定区域的开始横坐标， 默认为"0" ，取值为0~原图宽   | 否           | 是         |
-| 4    | Height           | 抠图选定区域的高，默认为"256"  ，取值为1~原图高，且必须为2的倍数 | 否           | 是         |
-| 5    | Width            | 抠图选定区域的宽，默认为"256" ，取值为1~原图宽，且必须为16的倍数  | 否           | 是         |
-| 6    | outputDataFormat | 插件输出的数据格式，可选值为"RGB" "BGR" "YUV"        | 是           | 是         |
-| 7    | dataType         | 插件输出的数据类型，可选值为"uint8"和"float32"，默认为“uint8”        | 否           | 是         |
-   
-注：如果抠图的尺寸大于原图尺寸，插件会补边，出现绿色边框。
-
-### 3.2 缩放功能的pipeline属性
-
-| 序号 | 属性             | 描述                                                 | 是否为必选项 | 是否可修改 |
-| ---- | ---------------- | ---------------------------------------------------- | ------------ | ---------- |
-| 1    | option           | 插件功能选择，此处使用"resize"                       | 是           | 是         |
-| 2    | height           | 缩放后的高度， 默认为"256"，取值为1~8192，必须为2的倍数             | 否           | 是         |
-| 3    | width            | 缩放后的宽度， 默认为"256"，取值为1~8192，必须为16的倍数 | 否           | 是         |
-| 4    | fx               | width方向缩放比例，默认为"0"，取值为0~1       | 否           | 是         |
-| 5    | fy               | height方向缩放比例，默认为"0"，取值为0~1       | 否           | 是         |
-| 6    | interpolation    | 图片插值方式，默认为"1"，取值为0~4                   | 否           | 是         |
-| 7    | outputDataFormat | 插件输出的数据格式，可选值为"RGB" "BGR" "YUV"       | 是           | 是         |
-| 8    | dataType         | 插件输出的数据类型，可选值为"uint8"和"float32"，默认为“uint8”       | 否           | 是         |
-
-注：fx和fy参数在height与width参数被赋值时失效，如有需要，可自行更改插件代码中resize部分。
-
-插值方式的取值具体描述：   
-
-| interpolation选项 | 插值方式                   | int值 |
-| ----------------- | -------------------------- | ----- |
-| INTER_NEAREST     | 最近邻插值                 | 0     |
-| INTER_LINEAR      | 双线性插值（默认）         | 1     |
-| INTER_CUBIC       | 基于4*4像素领域的3次插值法 | 2     |
-| INTER_AREA        | 使用像素区域关系进行重采样 | 3     |
-| INTER_LANCZOS4    | 8x8像素邻域的Lanczos插值   | 4     |
-
-## 4. 编译与运行
-
-**步骤1** **修改CMakeLists.txt文件** 
-
-第**15**行 将“/usr/local/Ascend/ascend-toolkit/latest/runtime/include”替换为实际include路径。
-
-**步骤2** **编译**  
-
-进入到主路径：
-
-```
-bash build.sh
-```
-
-**步骤3** **运行**
-
-在main.py所在目录上传图片命名为"person.jpg"，可通过修改pipeline文件选择相应的功能。
-
-```
-python3 main.py
-```
-
-注：插件输出宽高分别需要16、2对齐。   
-插件使用YUV格式输出时，将main.py 87、89、91行保持注释;94、95行注释打开。    同时将下游插件的"cvProcessor"属性删除。     
-插件使用RGB格式输出时，将main.py 87、89行注释打开;91、94、95行保持注释。     
-插件使用BGR格式输出时，将main.py 87、91行注释打开;89、94、95行保持注释。     
-插件输出为float32格式时，打开85行，注释86行。   
+
+
+# OpenCV 插件
+
+## 1. 介绍
+
+本代码仓插件实现了opencv的抠图和缩放功能。   
+抠图：
+支持根据目标检测的（x,y）坐标和（width,height）宽高进行图像裁剪（抠图）。   
+缩放：
+对解码后的YUV格式以及BGR格式的图像进行指定宽高的缩放。
+
+### 1.1 支持的产品
+
+本项目以昇腾Atlas310卡为主要的硬件平台。
+
+
+### 1.2 支持的版本
+
+支持的SDK版本为 2.0.4, CANN 版本为 5.0.4。
+
+
+### 1.3 软件方案介绍 
+
+本项目包含两个功能，即抠图与缩放。
+
+#### 1.3.1 抠图
+
+整体业务流程为：待检测图片通过 appsrc 插件输入，然后使用图像解码插件 mxpi_imagedecoder 对图片进行解码，再通过图像抠图插件 OpenCVPlugin进行将图片抠图（其前后可接其他插件）。最后通过输出插件 appsink 获取结果，并在外部进行可视化，将结果标记到原图上，本系统的各模块及功能描述如表1所示：
+
+表1 系统方案各模块功能描述：
+
+| 序号 | 子系统     | 功能描述              |
+| ---- | ---------- | --------------------- |
+| 1    | 图片输入   | 获取 jpg 格式输入图片 |
+| 2    | 图片解码   | 解码图片              |
+| 3    | 其他插件   | 其他插件的功能        |
+| 4    | 抠图       | 对输入图片进行抠图    |
+| 5    | 其他插件   | 其他插件的功能        |
+| 6    | 结果输出   | 获取检测结果          |
+| 7    | 结果可视化 | 将结果保存            |
+
+
+#### 1.3.2 缩放
+
+整体业务流程为：待检测图片信息经预处理后通过 appsrc 插件输入，然后使用图像解码插件 mxpi_imagedecoder 对图片进行解码，再通过图像缩放插件 OpenCVPlugin进行对图片进行缩放（其前后可接其他插件）。最后通过输出插件 appsink 获取检测结果，并在外部进行可视化，将结果标记到原图上，本系统的各模块及功能描述如表2所示：
+
+表2 系统方案各模块功能描述：
+
+| 序号 | 子系统     | 功能描述              |
+| ---- | ---------- | --------------------- |
+| 1    | 图片输入   | 获取 jpg 格式输入图片 |
+| 2    | 图片解码   | 解码图片              |
+| 3    | 其他插件   | 其他插件的功能        |
+| 4    | 缩放       | 对输入图片进行缩放    |
+| 5    | 其他插件   | 其他插件的功能        |
+| 6    | 结果输出   | 获取检测结果          |
+| 7    | 结果可视化 | 将结果保存            |
+
+### 1.4 代码目录结构与说明
+
+本工程名称为OpenCVPlugin，工程目录如下所示：
+
+```
+.
+├── image
+│   ├── pipeline.jpg
+├── OpenCVPlugin
+│   ├──lib （编译后生成）
+│   ├──src
+│   │   ├──OpenCVPlugin
+│   │       ├── CMakeLists.txt
+│   │       ├── OpenCVPlugin.cpp
+│   │       └── OpenCVPlugin.h
+├── python
+│   ├── main.py
+│   └── test.pipeline
+├── build.sh
+└── README.md
+
+```
+
+### 1.5 技术实现流程图
+
+OpenCVPlugin 插件流程图。
+
+<center>
+    <img src="./images/pipeline.jpg">
+    <br>
+</center>
+
+
+### 1.6 适用场景
+
+输入：metadata（数据类型“MxpiVisionList”）   
+输出：metadata（数据类型“MxpiVisionList”）
+
+静态输入：{"image/yuv","image/rgb"}   
+静态输出：{"image/rgb"}
+
+## 2 环境依赖
+
+推荐系统为ubuntu 18.04，环境依赖软件和版本如下表：
+
+| 软件名称 | 版本  |
+| -------- | ----- |
+| cmake    | 3.5+  |
+| mxVision | 2.0.4 |
+| python   | 3.9.2 |
+
+确保环境中正确安装mxVision SDK。
+
+在编译运行项目前，需要设置环境变量：
+
+MindX SDK 环境变量:
+
+```
+. ${SDK-path}/set_env.sh
+```
+
+CANN 环境变量：
+
+```
+. ${ascend-toolkit-path}/set_env.sh
+```
+
+- 环境变量介绍
+
+```
+SDK-path: SDK mxVision 安装路径
+ascend-toolkit-path: CANN 安装路径
+```
+
+## 3 属性介绍
+
+### 3.1 抠图功能的pipeline属性
+
+| 序号 | 属性             | 描述                                                 | 是否为必选项 | 是否可修改 |
+| ---- | ---------------- | ----------------------------------------------------- | ------------ | ---------- |
+| 1    | option           | 插件功能选择，此处使用"crop"                          | 是           | 是         |
+| 2    | startRow         | 抠图选定区域的开始纵坐标， 默认为"0"，取值为0~原图高  | 否           | 是         |
+| 3    | startCol         | 抠图选定区域的开始横坐标， 默认为"0" ，取值为0~原图宽   | 否           | 是         |
+| 4    | Height           | 抠图选定区域的高，默认为"256"  ，取值为1~原图高，且必须为2的倍数 | 否           | 是         |
+| 5    | Width            | 抠图选定区域的宽，默认为"256" ，取值为1~原图宽，且必须为16的倍数  | 否           | 是         |
+| 6    | outputDataFormat | 插件输出的数据格式，可选值为"RGB" "BGR" "YUV"        | 是           | 是         |
+| 7    | dataType         | 插件输出的数据类型，可选值为"uint8"和"float32"，默认为“uint8”        | 否           | 是         |
+   
+注：如果抠图的尺寸大于原图尺寸，插件会补边，出现绿色边框。
+
+### 3.2 缩放功能的pipeline属性
+
+| 序号 | 属性             | 描述                                                 | 是否为必选项 | 是否可修改 |
+| ---- | ---------------- | ---------------------------------------------------- | ------------ | ---------- |
+| 1    | option           | 插件功能选择，此处使用"resize"                       | 是           | 是         |
+| 2    | height           | 缩放后的高度， 默认为"256"，取值为1~8192，必须为2的倍数             | 否           | 是         |
+| 3    | width            | 缩放后的宽度， 默认为"256"，取值为1~8192，必须为16的倍数 | 否           | 是         |
+| 4    | fx               | width方向缩放比例，默认为"0"，取值为0~1       | 否           | 是         |
+| 5    | fy               | height方向缩放比例，默认为"0"，取值为0~1       | 否           | 是         |
+| 6    | interpolation    | 图片插值方式，默认为"1"，取值为0~4                   | 否           | 是         |
+| 7    | outputDataFormat | 插件输出的数据格式，可选值为"RGB" "BGR" "YUV"       | 是           | 是         |
+| 8    | dataType         | 插件输出的数据类型，可选值为"uint8"和"float32"，默认为“uint8”       | 否           | 是         |
+
+注：fx和fy参数在height与width参数被赋值时失效，如有需要，可自行更改插件代码中resize部分。
+
+插值方式的取值具体描述：   
+
+| interpolation选项 | 插值方式                   | int值 |
+| ----------------- | -------------------------- | ----- |
+| INTER_NEAREST     | 最近邻插值                 | 0     |
+| INTER_LINEAR      | 双线性插值（默认）         | 1     |
+| INTER_CUBIC       | 基于4*4像素领域的3次插值法 | 2     |
+| INTER_AREA        | 使用像素区域关系进行重采样 | 3     |
+| INTER_LANCZOS4    | 8x8像素邻域的Lanczos插值   | 4     |
+
+## 4. 编译与运行
+
+**步骤1** **修改CMakeLists.txt文件** 
+
+第**15**行 将“/usr/local/Ascend/ascend-toolkit/latest/runtime/include”替换为实际include路径。
+
+**步骤2** **编译**  
+
+进入到主路径：
+
+```
+bash build.sh
+```
+
+**步骤3** **运行**
+
+在main.py所在目录上传图片命名为"person.jpg"，可通过修改pipeline文件选择相应的功能。
+
+```
+python3 main.py
+```
+
+注：插件输出宽高分别需要16、2对齐。   
+插件使用YUV格式输出时，将main.py 87、89、91行保持注释;94、95行注释打开。    同时将下游插件的"cvProcessor"属性删除。     
+插件使用RGB格式输出时，将main.py 87、89行注释打开;91、94、95行保持注释。     
+插件使用BGR格式输出时，将main.py 87、91行注释打开;89、94、95行保持注释。     
+插件输出为float32格式时，打开85行，注释86行。   
 插件输出为uint8时，打开86行，注释85行。 
\ No newline at end of file
diff --git a/contrib/OpenCVPlugin/build.sh b/mxVision/mxVision-referenceapps/OpenCVPlugin/build.sh
similarity index 100%
rename from contrib/OpenCVPlugin/build.sh
rename to mxVision/mxVision-referenceapps/OpenCVPlugin/build.sh
diff --git a/contrib/OpenCVPlugin/images/pipeline.jpg b/mxVision/mxVision-referenceapps/OpenCVPlugin/images/pipeline.jpg
similarity index 100%
rename from contrib/OpenCVPlugin/images/pipeline.jpg
rename to mxVision/mxVision-referenceapps/OpenCVPlugin/images/pipeline.jpg
diff --git a/contrib/OpenCVPlugin/python/main.py b/mxVision/mxVision-referenceapps/OpenCVPlugin/python/main.py
similarity index 100%
rename from contrib/OpenCVPlugin/python/main.py
rename to mxVision/mxVision-referenceapps/OpenCVPlugin/python/main.py
diff --git a/contrib/OpenCVPlugin/python/test.pipeline b/mxVision/mxVision-referenceapps/OpenCVPlugin/python/test.pipeline
similarity index 100%
rename from contrib/OpenCVPlugin/python/test.pipeline
rename to mxVision/mxVision-referenceapps/OpenCVPlugin/python/test.pipeline
diff --git a/contrib/OpenposeKeypointDetection/README.md b/mxVision/mxVision-referenceapps/OpenposeKeypointDetection/README.md
similarity index 98%
rename from contrib/OpenposeKeypointDetection/README.md
rename to mxVision/mxVision-referenceapps/OpenposeKeypointDetection/README.md
index f8dc89fc73dd1da11952319ca6941ba8d86635db..21b42cd6f8298b1de254192fbebc692839c3ea15 100644
--- a/contrib/OpenposeKeypointDetection/README.md
+++ b/mxVision/mxVision-referenceapps/OpenposeKeypointDetection/README.md
@@ -1,249 +1,249 @@
-# 人体关键点检测
-## 1. 介绍
-### 1.1 简介
-人体关键点检测插件基于 MindXSDK 开发，在昇腾芯片上进行人体关键点和骨架检测，将检测结果可视化并保存。输入一幅图像，可以检测得到图像中所有行人的关键点并连接成人体骨架。
-人体关键点检测是指在输入图像上对指定的 18 类人体骨骼关键点位置进行检测，包括包括鼻子、左眼、右眼、左耳、右耳、左肩、右肩、左肘、右肘、左手腕、右手腕、左髋、右髋、左膝、右膝、左踝、右踝。然后将关键点正确配对组成相应的人体骨架，展示人体姿态，共 19 类人体骨架，如左肩和左肘两个关键点连接组成左上臂，右膝和右踝两个关键点连接组成右小腿等。
-本方案采取OpenPose模型，将待检测图片输入模型进行推理，推理得到包含人体关键点信息和关键点之间关联度信息的两个特征图，首先从关键点特征图中提取得到所有候选人体关键点，然后结合关联度信息特征图将不同的关键点组合连接成为人体骨架，再将所有人体骨架连接组成不同的人体，最后将关键点和骨架信息标注在输入图像上，描绘人体姿态。本方案可以对遮挡人体、小人体、密集分布人体等进行检测，还适用于不同姿态（蹲坐、俯卧等）、不同方向（正面、侧面、背面等）以及模糊人体关键点检测等多种复杂场景。
-
-本样例业务流程为：待检测图片通过 appsrc 插件输入，然后使用图像解码插件mxpi_imagedecoder对图片进行解码，再通过图像缩放插件mxpi_imageresize将图像缩放至满足检测模型要求的输入图像大小要求，缩放后的图像输入模型推理插件mxpi_tensorinfer得到检测结果，本项目开发的 OpenPose 人体关键点检测插件处理推理结果，从中提取关键点，确定关键点和关键点之间的连接关系，输出关键点连接形成的人体，最后通过序列化插件mxpi_dataserialize 和输出插件 appsink 获取人体关键点检测插件输出结果，并在外部进行人体姿态可视化描绘。本系统的各模块及功能描述如表1所示：
-
-表1 系统方案各模块功能描述：
-
-| 序号 | 子系统 | 功能描述     |
-| ---- | ------ | ------------ |
-| 1    | 图片输入    | 获取 jpg 格式输入图片 |
-| 2    | 图片解码    | 解码图片 |
-| 3    | 图片缩放    | 将输入图片放缩到模型指定输入的尺寸大小 |
-| 4    | 模型推理    | 对输入张量进行推理 |
-| 5    | 人体关键点检测    | 从模型推理结果检测人体关键点，并连接成人体骨架 |
-| 6    | 序列化    | 将检测结果组装成json字符串 |
-| 7    | 结果输出    | 将序列化结果输出|
-| 8    | 结果可视化    | 将检测得到的关键点和人体骨架标注在输入图片上|
-
-人体关键点检测插件的输入是模型推理插件输出的特征图，对于 OpenPose 模型，输出两个特征图，分别是关键点特征图 K 和关联度特征图 P，其中 K 的形状大小为 19 × w × h，P 的形状大小为 38 × w × h（w, h 表示特征图宽、高）， K中每个通道的二维特征图上每个位置的值表示该类关键点在该位置的置信度，共计 18 类关键点，关键点特征图的最后一个通道即第 19 个通道为背景点类。P 中每两个通道组成的三维特征图上的每个位置的值表示对应类别关键点在该位置处的向量坐标（x, y），通过计算两个不同类关键点组成的连接置信度将关键点连接成骨架，关键点之间组成的骨架共 19 类。
-
-关键点插件从输出特征图检测得到人体关键点和骨架的整体流程为：
-1. **将推理输出特征图缩放至原图尺寸大小。** 先将 K 和 P 放大 8 倍，因为 OpenPose 模型推理过程中会将输入缩小 8 倍得到特征图，然后去除 mxpi_imageresize 插件在缩放原图到指定尺寸时在图片右侧和下方添加的补边值，最后将特征图缩放到原图的尺寸大小。
-2. **从关键点特征图检测得到每一类的候选关键点。** 首先将置信度小于一定阈值 T 的点的置信度设为 0，这些位置不会成为候选关键点；如果该点的置信度值大于其上、下、左、右四个相邻点的置信度值，则该点是该类关键点的一个候选关键点；对于每个候选关键点，去除其周围与其欧式距离小于一定阈值 TD 的其他候选关键点。上述过程如图1 所示。
-
-
-<center>
-    图1. 候选关键点选择示意图  </div>
-    <br>
-    <img src="./images/KeypointNms.jpg">
-    <br>
-    <div style="color:orange;
-    display: inline-block;
-    color: #999;
-    padding: 2px;">
-</center>
-
-
-3. **结合关联度特征图 P 将候选关键点配对形成候选骨架。** 对于每个骨架（kp1, kp2), 得到 kp1 的所有候选关键点集 S1={kp1_0, kp1_1, ……} 和 kp2 的所有候选关键点集 S2={kp2_0, kp2_1, ……}，将 S1 中的每个点 kp1_i和 S2 中的每个点 kp2_j 组合，计算每个点对是该骨架的置信度。计算方式为：在 kp1_i 和 kp2_j 两点连成的线段上等间距的生成 10 个点，每两个相邻点确定一个子段，通过这些子段计算该骨架的置信度并筛选得到候选骨架, 最后去除冲突的候选骨架，即两个骨架有相同的端点时，保留置信度高的骨架。
-
-4. **将候选骨架组成人体。** 将有相同端点的骨架依次连接，最终组成一个或多个人体。
-
-### 1.2 支持的产品
-
-本项目基于mxVision SDK进行开发，以Atlas 500 A2为主要的硬件平台。
-
-
-### 1.3 支持的版本
-
-本样例配套的MxVision版本、CANN版本、Driver/Firmware版本如下所示：
-| MxVision版本  |  CANN版本 | Driver/Firmware版本  |
-|--------------- | ---------------------------------- | ----------|
-| 5.0.0 | 7.0.0 | 23.0.0|
-|6.0.RC2 | 8.0.RC2 | 24.1.RC2| 
-
-
-### 1.4 三方依赖
-环境依赖软件和版本如下表：
-
-| 软件                | 版本         | 说明                          | 获取方式                                                     |
-| ------------------- | ------------ | ----------------------------- | ------------------------------------------------------------ |                    
-| pycocotools       | 2.0.8     | python COCO 评测工具            | pip3 install pycocotools|
-
-
-### 1.5 代码目录结构说明
-
-本工程名称为 OpenposeKeypointDetection，工程目录如下所示：
-```
-.
-├── build.sh
-├── images   # readme中使用的图片
-│   ├── EvaluateInfo.png
-│   ├── KeypointNms.jpg
-│   ├── PathError.png
-│   └── PipelineError.png
-├── plugins  # 后处理插件源码
-│   ├── build.sh
-│   ├── CMakeLists.txt
-│   ├── MxpiOpenposePostProcess.cpp
-│   └── MxpiOpenposePostProcess.h
-├── proto    # 后处理插件protobuf定义
-│   ├── build.sh
-│   ├── CMakeLists.txt
-│   └── mxpiOpenposeProto.proto
-├── python
-│   ├── evaluate.py   # 精度验证脚本
-│   ├── main.py       # 推理脚本
-│   ├── models        # 模型文件
-│   │   ├── insert_op.cfg       # 模型转换配置文件
-│   │   └── model_conversion.sh # 模型转换脚本
-│   └── pipeline      # 
-│       └── Openpose.pipeline   # pipline文件
-└── README.md
-```
-
-## 2 设置环境变量
-设置CANN及MindX SDK相关的环境变量。
-
-```shell
-. /usr/local/Ascend/ascend-toolkit/set_env.sh   # Ascend-cann-toolkit开发套件包默认安装路径，根据实际安装路径修改
-. ${MX_SDK_HOME}/mxVision/set_env.sh   # ${MX_SDK_HOME}替换为用户的SDK安装路径
-```
-
-
-## 3. 准备模型
-
-本项目中适用的模型是 OpenPose 模型，[原模型项目代码](https://github.com/Daniil-Osokin/lightweight-human-pose-estimation.pytorch)。此处提供pytorch 模型和onnx 模型[下载链接](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/OpenposeKeypointDetection/model.zip) 。然后使用模型转换工具 ATC 将 onnx 模型转换为 om 模型，模型转换工具相关介绍[参考链接](https://www.hiascend.com/document/detail/zh/canncommercial/80RC2/devaids/auxiliarydevtool/atlasatc_16_0001.html) 。
-
-转换om模型步骤如下：
-
-**步骤1**  从上述模型下载链接中下载onnx模型，将解压出来的simplified_560_openpose_pytorch.onnx放至 ``python/models`` 文件夹下。
-
-**步骤2**  进入 ``python/models`` 文件夹下执行命令：
-```
-bash model_convertion.sh
-```
-执行该命令后会在当前文件夹下生成项目需要的模型文件 openpose_pytorch_560.om。执行后终端输出为：
-```
-ATC start working now, please wait for a moment.
-ATC run success, welcome to the next use.
-```
-表示命令执行成功。
-
-## 4. 编译与运行
-
-### 4.1 编译后处理插件
-
-在项目根目录下执行命令：
-```
-bash build.sh
-chmod 440 plugins/build/libmxpi_openposepostprocess.so
-cp plugins/build/libmxpi_openposepostprocess.so ${SDK_INSTALL_PATH}/mxVision/lib/plugins/ # ${SDK_INSTALL_PATH}替换为用户的SDK安装路径
-```
-注意需要将生成的so权限改为440。
-
-### 4.2 运行
-将一张包含人体的图片放在项目目录python下，与main.py同目录，命名为 test.jpg。在该图片上进行检测，执行命令：
-```
-cd python
-python3 main.py
-```
-### 4.3 查看结果
-
-命令执行成功后在当前目录下生成检测结果文件 test_detect_result.jpg，查看结果文件验证检测结果。
-
-## 5. 精度验证
-### 5.1 获取数据集
-执行下述命令下载 COCO keypoint VAL 2017 数据集与标注文件：
-```
-wget http://images.cocodataset.org/zips/val2017.zip
-wget http://images.cocodataset.org/annotations/annotations_trainval2017.zip
-```
-在 ``python`` 目录下创建 ``dataset`` 目录，将数据集压缩文件解压至 ``python/dataset`` 目录下确保下载完数据集和标注文件后的 python 目录结构为：
-```
-.
-├── dataset
-│   ├── annotations
-│   │   ├── person_keypoints_val2017.json
-│   │   └── ...
-│   └── val2017
-│       ├── 000000581615.jpg
-│       ├── 000000581781.jpg
-│       └── ...
-├── evaluate.py
-├── main.py
-├── models
-│   ├── convert_to_onnx.py
-│   ├── insert_op.cfg
-│   └── model_conversion.sh
-└── pipeline
-    └── Openpose.pipeline
-```
-### 5.2 执行验证
-```
-cd python
-python3 evaluate.py
-```
-
-### 5.3 查看结果
-命令执行结束后输出 COCO 格式的评测结果，并生成 val2017_keypoint_detect_result.json 检测结果文件。输出结果如下图所示：
-<center>
-    图2. 模型精度测试输出结果 </div>
-    <img src="./images/EvaluateInfo.png">
-    <br>
-    <div style="color:orange;
-    display: inline-block;
-    color: #999;
-    padding: 2px;">
-</center>
-其中圈出来的部分为模型在 COCO VAL 2017 数据集上，IOU 阈值为 0.50:0.05:0.95 时的精度值。
-
-## 6 常见问题
-
-
-### 6.1 模型参数配置问题
-
-**问题描述：**
-
-``python/pipeline/Openpose.pipeline`` 中模型输入尺寸相关参数需要和使用的 om 模型相对应，否则会报如下类型的错：
-
-<center>
-    图3. 模型输入尺寸和 pipeline 中参数设置不匹配报错 </div>
-    <img src="./images/PipelineError.png">
-    <br>
-    <div style="color:orange;
-    display: inline-block;
-    color: #999;
-    padding: 2px;">
-</center>
-
-**解决方案：**
-
-确保 ``python/pipeline/Openpose.pipeline`` 中 mxpi_imageresize0 插件的 resizeWidth 和 resizeHeight 属性值是转换模型过程中设置的模型输入尺寸值；mxpi_openposepostprocess0 插件中的 inputWidth 和 inputHeight 属性值是转换模型过程中设置的模型输入尺寸值。
-
-
-### 6.2 评测过程中的文件路径问题
-
-**问题描述：**
-
-精度评测过程中，将 COCO VAL 2017 数据集文件夹和标注文件夹放在正确位置，否则执行评测程序时找不到文件，报如下类型的错：
-
-<center>
-    图4. 文件路径报错 </div>
-    <img src="./images/PathError.png">
-    <br>
-    <div style="color:orange;
-    display: inline-block;
-    color: #999;
-    padding: 2px;">
-</center>
-
-
-**解决方案：**
-
-
-下载完数据集和标注文件后，确保 ``python/dataset`` 目录结构为：
-```
-.
-├── annotations
-│   ├── person_keypoints_val2017.json
-│   └── ...
-└── val2017
-    ├── 000000581615.jpg
-    ├── 000000581781.jpg
-    └── other-images
+# 人体关键点检测
+## 1. 介绍
+### 1.1 简介
+人体关键点检测插件基于 MindXSDK 开发，在昇腾芯片上进行人体关键点和骨架检测，将检测结果可视化并保存。输入一幅图像，可以检测得到图像中所有行人的关键点并连接成人体骨架。
+人体关键点检测是指在输入图像上对指定的 18 类人体骨骼关键点位置进行检测，包括包括鼻子、左眼、右眼、左耳、右耳、左肩、右肩、左肘、右肘、左手腕、右手腕、左髋、右髋、左膝、右膝、左踝、右踝。然后将关键点正确配对组成相应的人体骨架，展示人体姿态，共 19 类人体骨架，如左肩和左肘两个关键点连接组成左上臂，右膝和右踝两个关键点连接组成右小腿等。
+本方案采取OpenPose模型，将待检测图片输入模型进行推理，推理得到包含人体关键点信息和关键点之间关联度信息的两个特征图，首先从关键点特征图中提取得到所有候选人体关键点，然后结合关联度信息特征图将不同的关键点组合连接成为人体骨架，再将所有人体骨架连接组成不同的人体，最后将关键点和骨架信息标注在输入图像上，描绘人体姿态。本方案可以对遮挡人体、小人体、密集分布人体等进行检测，还适用于不同姿态（蹲坐、俯卧等）、不同方向（正面、侧面、背面等）以及模糊人体关键点检测等多种复杂场景。
+
+本样例业务流程为：待检测图片通过 appsrc 插件输入，然后使用图像解码插件mxpi_imagedecoder对图片进行解码，再通过图像缩放插件mxpi_imageresize将图像缩放至满足检测模型要求的输入图像大小要求，缩放后的图像输入模型推理插件mxpi_tensorinfer得到检测结果，本项目开发的 OpenPose 人体关键点检测插件处理推理结果，从中提取关键点，确定关键点和关键点之间的连接关系，输出关键点连接形成的人体，最后通过序列化插件mxpi_dataserialize 和输出插件 appsink 获取人体关键点检测插件输出结果，并在外部进行人体姿态可视化描绘。本系统的各模块及功能描述如表1所示：
+
+表1 系统方案各模块功能描述：
+
+| 序号 | 子系统 | 功能描述     |
+| ---- | ------ | ------------ |
+| 1    | 图片输入    | 获取 jpg 格式输入图片 |
+| 2    | 图片解码    | 解码图片 |
+| 3    | 图片缩放    | 将输入图片放缩到模型指定输入的尺寸大小 |
+| 4    | 模型推理    | 对输入张量进行推理 |
+| 5    | 人体关键点检测    | 从模型推理结果检测人体关键点，并连接成人体骨架 |
+| 6    | 序列化    | 将检测结果组装成json字符串 |
+| 7    | 结果输出    | 将序列化结果输出|
+| 8    | 结果可视化    | 将检测得到的关键点和人体骨架标注在输入图片上|
+
+人体关键点检测插件的输入是模型推理插件输出的特征图，对于 OpenPose 模型，输出两个特征图，分别是关键点特征图 K 和关联度特征图 P，其中 K 的形状大小为 19 × w × h，P 的形状大小为 38 × w × h（w, h 表示特征图宽、高）， K中每个通道的二维特征图上每个位置的值表示该类关键点在该位置的置信度，共计 18 类关键点，关键点特征图的最后一个通道即第 19 个通道为背景点类。P 中每两个通道组成的三维特征图上的每个位置的值表示对应类别关键点在该位置处的向量坐标（x, y），通过计算两个不同类关键点组成的连接置信度将关键点连接成骨架，关键点之间组成的骨架共 19 类。
+
+关键点插件从输出特征图检测得到人体关键点和骨架的整体流程为：
+1. **将推理输出特征图缩放至原图尺寸大小。** 先将 K 和 P 放大 8 倍，因为 OpenPose 模型推理过程中会将输入缩小 8 倍得到特征图，然后去除 mxpi_imageresize 插件在缩放原图到指定尺寸时在图片右侧和下方添加的补边值，最后将特征图缩放到原图的尺寸大小。
+2. **从关键点特征图检测得到每一类的候选关键点。** 首先将置信度小于一定阈值 T 的点的置信度设为 0，这些位置不会成为候选关键点；如果该点的置信度值大于其上、下、左、右四个相邻点的置信度值，则该点是该类关键点的一个候选关键点；对于每个候选关键点，去除其周围与其欧式距离小于一定阈值 TD 的其他候选关键点。上述过程如图1 所示。
+
+
+<center>
+    图1. 候选关键点选择示意图  </div>
+    <br>
+    <img src="./images/KeypointNms.jpg">
+    <br>
+    <div style="color:orange;
+    display: inline-block;
+    color: #999;
+    padding: 2px;">
+</center>
+
+
+3. **结合关联度特征图 P 将候选关键点配对形成候选骨架。** 对于每个骨架（kp1, kp2), 得到 kp1 的所有候选关键点集 S1={kp1_0, kp1_1, ……} 和 kp2 的所有候选关键点集 S2={kp2_0, kp2_1, ……}，将 S1 中的每个点 kp1_i和 S2 中的每个点 kp2_j 组合，计算每个点对是该骨架的置信度。计算方式为：在 kp1_i 和 kp2_j 两点连成的线段上等间距的生成 10 个点，每两个相邻点确定一个子段，通过这些子段计算该骨架的置信度并筛选得到候选骨架, 最后去除冲突的候选骨架，即两个骨架有相同的端点时，保留置信度高的骨架。
+
+4. **将候选骨架组成人体。** 将有相同端点的骨架依次连接，最终组成一个或多个人体。
+
+### 1.2 支持的产品
+
+本项目基于mxVision SDK进行开发，以Atlas 500 A2为主要的硬件平台。
+
+
+### 1.3 支持的版本
+
+本样例配套的MxVision版本、CANN版本、Driver/Firmware版本如下所示：
+| MxVision版本  |  CANN版本 | Driver/Firmware版本  |
+|--------------- | ---------------------------------- | ----------|
+| 5.0.0 | 7.0.0 | 23.0.0|
+|6.0.RC2 | 8.0.RC2 | 24.1.RC2| 
+
+
+### 1.4 三方依赖
+环境依赖软件和版本如下表：
+
+| 软件                | 版本         | 说明                          | 获取方式                                                     |
+| ------------------- | ------------ | ----------------------------- | ------------------------------------------------------------ |                    
+| pycocotools       | 2.0.8     | python COCO 评测工具            | pip3 install pycocotools|
+
+
+### 1.5 代码目录结构说明
+
+本工程名称为 OpenposeKeypointDetection，工程目录如下所示：
+```
+.
+├── build.sh
+├── images   # readme中使用的图片
+│   ├── EvaluateInfo.png
+│   ├── KeypointNms.jpg
+│   ├── PathError.png
+│   └── PipelineError.png
+├── plugins  # 后处理插件源码
+│   ├── build.sh
+│   ├── CMakeLists.txt
+│   ├── MxpiOpenposePostProcess.cpp
+│   └── MxpiOpenposePostProcess.h
+├── proto    # 后处理插件protobuf定义
+│   ├── build.sh
+│   ├── CMakeLists.txt
+│   └── mxpiOpenposeProto.proto
+├── python
+│   ├── evaluate.py   # 精度验证脚本
+│   ├── main.py       # 推理脚本
+│   ├── models        # 模型文件
+│   │   ├── insert_op.cfg       # 模型转换配置文件
+│   │   └── model_conversion.sh # 模型转换脚本
+│   └── pipeline      # 
+│       └── Openpose.pipeline   # pipline文件
+└── README.md
+```
+
+## 2 设置环境变量
+设置CANN及MindX SDK相关的环境变量。
+
+```shell
+. /usr/local/Ascend/ascend-toolkit/set_env.sh   # Ascend-cann-toolkit开发套件包默认安装路径，根据实际安装路径修改
+. ${MX_SDK_HOME}/mxVision/set_env.sh   # ${MX_SDK_HOME}替换为用户的SDK安装路径
+```
+
+
+## 3. 准备模型
+
+本项目中适用的模型是 OpenPose 模型，[原模型项目代码](https://github.com/Daniil-Osokin/lightweight-human-pose-estimation.pytorch)。此处提供pytorch 模型和onnx 模型[下载链接](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/OpenposeKeypointDetection/model.zip) 。然后使用模型转换工具 ATC 将 onnx 模型转换为 om 模型，模型转换工具相关介绍[参考链接](https://www.hiascend.com/document/detail/zh/canncommercial/80RC2/devaids/auxiliarydevtool/atlasatc_16_0001.html) 。
+
+转换om模型步骤如下：
+
+**步骤1**  从上述模型下载链接中下载onnx模型，将解压出来的simplified_560_openpose_pytorch.onnx放至 ``python/models`` 文件夹下。
+
+**步骤2**  进入 ``python/models`` 文件夹下执行命令：
+```
+bash model_convertion.sh
+```
+执行该命令后会在当前文件夹下生成项目需要的模型文件 openpose_pytorch_560.om。执行后终端输出为：
+```
+ATC start working now, please wait for a moment.
+ATC run success, welcome to the next use.
+```
+表示命令执行成功。
+
+## 4. 编译与运行
+
+### 4.1 编译后处理插件
+
+在项目根目录下执行命令：
+```
+bash build.sh
+chmod 440 plugins/build/libmxpi_openposepostprocess.so
+cp plugins/build/libmxpi_openposepostprocess.so ${SDK_INSTALL_PATH}/mxVision/lib/plugins/ # ${SDK_INSTALL_PATH}替换为用户的SDK安装路径
+```
+注意需要将生成的so权限改为440。
+
+### 4.2 运行
+将一张包含人体的图片放在项目目录python下，与main.py同目录，命名为 test.jpg。在该图片上进行检测，执行命令：
+```
+cd python
+python3 main.py
+```
+### 4.3 查看结果
+
+命令执行成功后在当前目录下生成检测结果文件 test_detect_result.jpg，查看结果文件验证检测结果。
+
+## 5. 精度验证
+### 5.1 获取数据集
+执行下述命令下载 COCO keypoint VAL 2017 数据集与标注文件：
+```
+wget http://images.cocodataset.org/zips/val2017.zip
+wget http://images.cocodataset.org/annotations/annotations_trainval2017.zip
+```
+在 ``python`` 目录下创建 ``dataset`` 目录，将数据集压缩文件解压至 ``python/dataset`` 目录下确保下载完数据集和标注文件后的 python 目录结构为：
+```
+.
+├── dataset
+│   ├── annotations
+│   │   ├── person_keypoints_val2017.json
+│   │   └── ...
+│   └── val2017
+│       ├── 000000581615.jpg
+│       ├── 000000581781.jpg
+│       └── ...
+├── evaluate.py
+├── main.py
+├── models
+│   ├── convert_to_onnx.py
+│   ├── insert_op.cfg
+│   └── model_conversion.sh
+└── pipeline
+    └── Openpose.pipeline
+```
+### 5.2 执行验证
+```
+cd python
+python3 evaluate.py
+```
+
+### 5.3 查看结果
+命令执行结束后输出 COCO 格式的评测结果，并生成 val2017_keypoint_detect_result.json 检测结果文件。输出结果如下图所示：
+<center>
+    图2. 模型精度测试输出结果 </div>
+    <img src="./images/EvaluateInfo.png">
+    <br>
+    <div style="color:orange;
+    display: inline-block;
+    color: #999;
+    padding: 2px;">
+</center>
+其中圈出来的部分为模型在 COCO VAL 2017 数据集上，IOU 阈值为 0.50:0.05:0.95 时的精度值。
+
+## 6 常见问题
+
+
+### 6.1 模型参数配置问题
+
+**问题描述：**
+
+``python/pipeline/Openpose.pipeline`` 中模型输入尺寸相关参数需要和使用的 om 模型相对应，否则会报如下类型的错：
+
+<center>
+    图3. 模型输入尺寸和 pipeline 中参数设置不匹配报错 </div>
+    <img src="./images/PipelineError.png">
+    <br>
+    <div style="color:orange;
+    display: inline-block;
+    color: #999;
+    padding: 2px;">
+</center>
+
+**解决方案：**
+
+确保 ``python/pipeline/Openpose.pipeline`` 中 mxpi_imageresize0 插件的 resizeWidth 和 resizeHeight 属性值是转换模型过程中设置的模型输入尺寸值；mxpi_openposepostprocess0 插件中的 inputWidth 和 inputHeight 属性值是转换模型过程中设置的模型输入尺寸值。
+
+
+### 6.2 评测过程中的文件路径问题
+
+**问题描述：**
+
+精度评测过程中，将 COCO VAL 2017 数据集文件夹和标注文件夹放在正确位置，否则执行评测程序时找不到文件，报如下类型的错：
+
+<center>
+    图4. 文件路径报错 </div>
+    <img src="./images/PathError.png">
+    <br>
+    <div style="color:orange;
+    display: inline-block;
+    color: #999;
+    padding: 2px;">
+</center>
+
+
+**解决方案：**
+
+
+下载完数据集和标注文件后，确保 ``python/dataset`` 目录结构为：
+```
+.
+├── annotations
+│   ├── person_keypoints_val2017.json
+│   └── ...
+└── val2017
+    ├── 000000581615.jpg
+    ├── 000000581781.jpg
+    └── other-images
 ```
\ No newline at end of file
diff --git a/contrib/OpenposeKeypointDetection/build.sh b/mxVision/mxVision-referenceapps/OpenposeKeypointDetection/build.sh
similarity index 100%
rename from contrib/OpenposeKeypointDetection/build.sh
rename to mxVision/mxVision-referenceapps/OpenposeKeypointDetection/build.sh
diff --git a/contrib/OpenposeKeypointDetection/images/EvaluateInfo.png b/mxVision/mxVision-referenceapps/OpenposeKeypointDetection/images/EvaluateInfo.png
similarity index 100%
rename from contrib/OpenposeKeypointDetection/images/EvaluateInfo.png
rename to mxVision/mxVision-referenceapps/OpenposeKeypointDetection/images/EvaluateInfo.png
diff --git a/contrib/OpenposeKeypointDetection/images/KeypointNms.jpg b/mxVision/mxVision-referenceapps/OpenposeKeypointDetection/images/KeypointNms.jpg
similarity index 100%
rename from contrib/OpenposeKeypointDetection/images/KeypointNms.jpg
rename to mxVision/mxVision-referenceapps/OpenposeKeypointDetection/images/KeypointNms.jpg
diff --git a/contrib/OpenposeKeypointDetection/images/PathError.png b/mxVision/mxVision-referenceapps/OpenposeKeypointDetection/images/PathError.png
similarity index 100%
rename from contrib/OpenposeKeypointDetection/images/PathError.png
rename to mxVision/mxVision-referenceapps/OpenposeKeypointDetection/images/PathError.png
diff --git a/contrib/OpenposeKeypointDetection/images/PipelineError.png b/mxVision/mxVision-referenceapps/OpenposeKeypointDetection/images/PipelineError.png
similarity index 100%
rename from contrib/OpenposeKeypointDetection/images/PipelineError.png
rename to mxVision/mxVision-referenceapps/OpenposeKeypointDetection/images/PipelineError.png
diff --git a/contrib/OpenposeKeypointDetection/plugins/CMakeLists.txt b/mxVision/mxVision-referenceapps/OpenposeKeypointDetection/plugins/CMakeLists.txt
similarity index 98%
rename from contrib/OpenposeKeypointDetection/plugins/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/OpenposeKeypointDetection/plugins/CMakeLists.txt
index 8f7799dfe1ddff5ac3602ed3f3681615bc710ba4..0b4a2a84193c83258e13d58b7b3cbcc4aeccc383 100644
--- a/contrib/OpenposeKeypointDetection/plugins/CMakeLists.txt
+++ b/mxVision/mxVision-referenceapps/OpenposeKeypointDetection/plugins/CMakeLists.txt
@@ -1,26 +1,26 @@
-cmake_minimum_required(VERSION 3.5.2)
-project(OpenposePlugin)
-add_definitions(-D_GLIBCXX_USE_CXX11_ABI=0 -Dgoogle=mindxsdk_private)
-
-set(PLUGIN_NAME "mxpi_openposepostprocess")
-set(TARGET_LIBRARY ${PLUGIN_NAME})
-set(MX_SDK_HOME "$ENV{MX_SDK_HOME}")
-
-include_directories(${CMAKE_CURRENT_BINARY_DIR})
-include_directories(${MX_SDK_HOME}/include)
-include_directories(${MX_SDK_HOME}/opensource/include)
-include_directories(${MX_SDK_HOME}/opensource/include/gstreamer-1.0)
-include_directories(${MX_SDK_HOME}/opensource/include/glib-2.0)
-include_directories(${MX_SDK_HOME}/opensource/lib/glib-2.0/include)
-include_directories(${MX_SDK_HOME}/opensource/include/opencv4)
-include_directories(${PROJECT_SOURCE_DIR}/../proto)
-link_directories(${MX_SDK_HOME}/lib)
-link_directories(${MX_SDK_HOME}/opensource/lib)
-link_directories(${PROJECT_SOURCE_DIR}/../proto/lib)
-
-add_compile_options(-std=c++11 -fPIC -fstack-protector-all -pie -Wno-deprecated-declarations)
-add_compile_options("-DPLUGIN_NAME=${PLUGIN_NAME}")
-add_definitions(-DENABLE_DVPP_INTERFACE)
-add_library(${TARGET_LIBRARY} SHARED MxpiOpenposePostProcess.cpp)
-target_link_libraries(${TARGET_LIBRARY} glib-2.0 gstreamer-1.0 gobject-2.0 gstbase-1.0 gmodule-2.0 glog)
+cmake_minimum_required(VERSION 3.5.2)
+project(OpenposePlugin)
+add_definitions(-D_GLIBCXX_USE_CXX11_ABI=0 -Dgoogle=mindxsdk_private)
+
+set(PLUGIN_NAME "mxpi_openposepostprocess")
+set(TARGET_LIBRARY ${PLUGIN_NAME})
+set(MX_SDK_HOME "$ENV{MX_SDK_HOME}")
+
+include_directories(${CMAKE_CURRENT_BINARY_DIR})
+include_directories(${MX_SDK_HOME}/include)
+include_directories(${MX_SDK_HOME}/opensource/include)
+include_directories(${MX_SDK_HOME}/opensource/include/gstreamer-1.0)
+include_directories(${MX_SDK_HOME}/opensource/include/glib-2.0)
+include_directories(${MX_SDK_HOME}/opensource/lib/glib-2.0/include)
+include_directories(${MX_SDK_HOME}/opensource/include/opencv4)
+include_directories(${PROJECT_SOURCE_DIR}/../proto)
+link_directories(${MX_SDK_HOME}/lib)
+link_directories(${MX_SDK_HOME}/opensource/lib)
+link_directories(${PROJECT_SOURCE_DIR}/../proto/lib)
+
+add_compile_options(-std=c++11 -fPIC -fstack-protector-all -pie -Wno-deprecated-declarations)
+add_compile_options("-DPLUGIN_NAME=${PLUGIN_NAME}")
+add_definitions(-DENABLE_DVPP_INTERFACE)
+add_library(${TARGET_LIBRARY} SHARED MxpiOpenposePostProcess.cpp)
+target_link_libraries(${TARGET_LIBRARY} glib-2.0 gstreamer-1.0 gobject-2.0 gstbase-1.0 gmodule-2.0 glog)
 target_link_libraries(${TARGET_LIBRARY} mxpidatatype plugintoolkit mxbase mindxsdk_protobuf mxpiopenposeproto)
\ No newline at end of file
diff --git a/contrib/OpenposeKeypointDetection/plugins/MxpiOpenposePostProcess.cpp b/mxVision/mxVision-referenceapps/OpenposeKeypointDetection/plugins/MxpiOpenposePostProcess.cpp
similarity index 100%
rename from contrib/OpenposeKeypointDetection/plugins/MxpiOpenposePostProcess.cpp
rename to mxVision/mxVision-referenceapps/OpenposeKeypointDetection/plugins/MxpiOpenposePostProcess.cpp
diff --git a/contrib/OpenposeKeypointDetection/plugins/MxpiOpenposePostProcess.h b/mxVision/mxVision-referenceapps/OpenposeKeypointDetection/plugins/MxpiOpenposePostProcess.h
similarity index 100%
rename from contrib/OpenposeKeypointDetection/plugins/MxpiOpenposePostProcess.h
rename to mxVision/mxVision-referenceapps/OpenposeKeypointDetection/plugins/MxpiOpenposePostProcess.h
diff --git a/contrib/OpenposeKeypointDetection/plugins/build.sh b/mxVision/mxVision-referenceapps/OpenposeKeypointDetection/plugins/build.sh
similarity index 100%
rename from contrib/OpenposeKeypointDetection/plugins/build.sh
rename to mxVision/mxVision-referenceapps/OpenposeKeypointDetection/plugins/build.sh
diff --git a/contrib/OpenposeKeypointDetection/proto/CMakeLists.txt b/mxVision/mxVision-referenceapps/OpenposeKeypointDetection/proto/CMakeLists.txt
similarity index 97%
rename from contrib/OpenposeKeypointDetection/proto/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/OpenposeKeypointDetection/proto/CMakeLists.txt
index f8de00df2738c11015e11a946a1c2fc8e35acf08..1134431f9cc663ec22df388be0684e54b3828c35 100644
--- a/contrib/OpenposeKeypointDetection/proto/CMakeLists.txt
+++ b/mxVision/mxVision-referenceapps/OpenposeKeypointDetection/proto/CMakeLists.txt
@@ -1,46 +1,46 @@
-cmake_minimum_required(VERSION 3.5.1)
-project(ProtoFile)
-
-set(TARGET_LIBRARY mxpiopenposeproto)
-
-# Compile options
-add_definitions(-D_GLIBCXX_USE_CXX11_ABI=0)
-add_definitions(-Dgoogle=mindxsdk_private)
-add_compile_options(-std=c++11 -fPIC -fstack-protector-all -pie -Wno-deprecated-declarations)
-
-set(MX_SDK_HOME "$ENV{MX_SDK_HOME}")
-
-if (EXISTS ${MX_SDK_HOME})
-    set(PROTOBUF_FOUND TRUE)
-    set(PROTOBUF_PROTOC_EXECUTABLE ${MX_SDK_HOME}/opensource/bin/protoc)
-    set(PROTOBUF_INCLUDE_DIRS ${MX_SDK_HOME}/opensource/include)
-    include_directories(${PROTOBUF_INCLUDE_DIRS})
-    link_directories(${MX_SDK_HOME}/opensource/lib)
-
-endif ()
-if (PROTOBUF_FOUND)
-    message(STATUS "protobuf library found")
-
-else()
-    message(FATAL_ERROR "protobuf library is needed but cant be found")
-endif ()
-
-LIST(APPEND PROTO_FLAGS -I${PROJECT_SOURCE_DIR})
-
-EXECUTE_PROCESS(
-        COMMAND ${PROTOBUF_PROTOC_EXECUTABLE} ${PROTO_FLAGS} --cpp_out=${PROJECT_SOURCE_DIR} ${PROJECT_SOURCE_DIR}/mxpiOpenposeProto.proto
-        COMMAND ${PROTOBUF_PROTOC_EXECUTABLE} ${PROTO_FLAGS} --python_out=${PROJECT_SOURCE_DIR} ${PROJECT_SOURCE_DIR}/mxpiOpenposeProto.proto
-        WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}
-)
-
-file(GLOB_RECURSE SOURCE_FILES ${PROJECT_SOURCE_DIR}/*.cc)
-add_library(${TARGET_LIBRARY} SHARED ${SOURCE_FILES})
-target_link_libraries(${TARGET_LIBRARY} mindxsdk_protobuf)
-#target_link_libraries(${TARGET_LIBRARY} -Wl,-z,relro,-z,now,-z,noexecstack -s)
-
-if (ENABLE_TEST)
-    target_link_libraries(${TARGET_LIBRARY} gcov)
-endif ()
-
-set(LIBRARY_OUTPUT_PATH ${PROJECT_SOURCE_DIR}/lib)
-install(TARGETS ${TARGET_LIBRARY} LIBRARY DESTINATION ${PROJECT_SOURCE_DIR}/lib)
+cmake_minimum_required(VERSION 3.5.1)
+project(ProtoFile)
+
+set(TARGET_LIBRARY mxpiopenposeproto)
+
+# Compile options
+add_definitions(-D_GLIBCXX_USE_CXX11_ABI=0)
+add_definitions(-Dgoogle=mindxsdk_private)
+add_compile_options(-std=c++11 -fPIC -fstack-protector-all -pie -Wno-deprecated-declarations)
+
+set(MX_SDK_HOME "$ENV{MX_SDK_HOME}")
+
+if (EXISTS ${MX_SDK_HOME})
+    set(PROTOBUF_FOUND TRUE)
+    set(PROTOBUF_PROTOC_EXECUTABLE ${MX_SDK_HOME}/opensource/bin/protoc)
+    set(PROTOBUF_INCLUDE_DIRS ${MX_SDK_HOME}/opensource/include)
+    include_directories(${PROTOBUF_INCLUDE_DIRS})
+    link_directories(${MX_SDK_HOME}/opensource/lib)
+
+endif ()
+if (PROTOBUF_FOUND)
+    message(STATUS "protobuf library found")
+
+else()
+    message(FATAL_ERROR "protobuf library is needed but cant be found")
+endif ()
+
+LIST(APPEND PROTO_FLAGS -I${PROJECT_SOURCE_DIR})
+
+EXECUTE_PROCESS(
+        COMMAND ${PROTOBUF_PROTOC_EXECUTABLE} ${PROTO_FLAGS} --cpp_out=${PROJECT_SOURCE_DIR} ${PROJECT_SOURCE_DIR}/mxpiOpenposeProto.proto
+        COMMAND ${PROTOBUF_PROTOC_EXECUTABLE} ${PROTO_FLAGS} --python_out=${PROJECT_SOURCE_DIR} ${PROJECT_SOURCE_DIR}/mxpiOpenposeProto.proto
+        WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}
+)
+
+file(GLOB_RECURSE SOURCE_FILES ${PROJECT_SOURCE_DIR}/*.cc)
+add_library(${TARGET_LIBRARY} SHARED ${SOURCE_FILES})
+target_link_libraries(${TARGET_LIBRARY} mindxsdk_protobuf)
+#target_link_libraries(${TARGET_LIBRARY} -Wl,-z,relro,-z,now,-z,noexecstack -s)
+
+if (ENABLE_TEST)
+    target_link_libraries(${TARGET_LIBRARY} gcov)
+endif ()
+
+set(LIBRARY_OUTPUT_PATH ${PROJECT_SOURCE_DIR}/lib)
+install(TARGETS ${TARGET_LIBRARY} LIBRARY DESTINATION ${PROJECT_SOURCE_DIR}/lib)
diff --git a/contrib/OpenposeKeypointDetection/proto/build.sh b/mxVision/mxVision-referenceapps/OpenposeKeypointDetection/proto/build.sh
similarity index 100%
rename from contrib/OpenposeKeypointDetection/proto/build.sh
rename to mxVision/mxVision-referenceapps/OpenposeKeypointDetection/proto/build.sh
diff --git a/contrib/OpenposeKeypointDetection/proto/mxpiOpenposeProto.proto b/mxVision/mxVision-referenceapps/OpenposeKeypointDetection/proto/mxpiOpenposeProto.proto
similarity index 94%
rename from contrib/OpenposeKeypointDetection/proto/mxpiOpenposeProto.proto
rename to mxVision/mxVision-referenceapps/OpenposeKeypointDetection/proto/mxpiOpenposeProto.proto
index 4f3b4d88e6ae3e5ef537b1b54a8466ba726e3b06..4132596421e3a4ecb151fd52f0cf51d9c63d2917 100644
--- a/contrib/OpenposeKeypointDetection/proto/mxpiOpenposeProto.proto
+++ b/mxVision/mxVision-referenceapps/OpenposeKeypointDetection/proto/mxpiOpenposeProto.proto
@@ -1,33 +1,33 @@
-syntax = "proto3";
-package mxpiopenposeproto;
-message MxpiMetaHeader
-{
-string parentName = 1;
-int32 memberId = 2;
-string dataSource = 3;
-}
-
-message MxpiSkeletonInfo
-{
-int32 cocoSkeletonIndex1 = 1;
-int32 cocoSkeletonIndex2 = 2;
-float x0 = 3;
-float y0 = 4;
-float point1Score = 5;
-float x1 = 6;
-float y1 = 7;
-float point2Score = 8;
-float skeletonScore = 9;
-}
-
-message MxpiPersonInfo
-{
-repeated MxpiMetaHeader headerVec = 1;
-repeated MxpiSkeletonInfo skeletonInfoVec = 2;
-float score = 3;
-}
-
-message MxpiPersonList
-{
-repeated MxpiPersonInfo personInfoVec = 1;
+syntax = "proto3";
+package mxpiopenposeproto;
+message MxpiMetaHeader
+{
+string parentName = 1;
+int32 memberId = 2;
+string dataSource = 3;
+}
+
+message MxpiSkeletonInfo
+{
+int32 cocoSkeletonIndex1 = 1;
+int32 cocoSkeletonIndex2 = 2;
+float x0 = 3;
+float y0 = 4;
+float point1Score = 5;
+float x1 = 6;
+float y1 = 7;
+float point2Score = 8;
+float skeletonScore = 9;
+}
+
+message MxpiPersonInfo
+{
+repeated MxpiMetaHeader headerVec = 1;
+repeated MxpiSkeletonInfo skeletonInfoVec = 2;
+float score = 3;
+}
+
+message MxpiPersonList
+{
+repeated MxpiPersonInfo personInfoVec = 1;
 }
\ No newline at end of file
diff --git a/contrib/OpenposeKeypointDetection/python/evaluate.py b/mxVision/mxVision-referenceapps/OpenposeKeypointDetection/python/evaluate.py
similarity index 100%
rename from contrib/OpenposeKeypointDetection/python/evaluate.py
rename to mxVision/mxVision-referenceapps/OpenposeKeypointDetection/python/evaluate.py
diff --git a/contrib/OpenposeKeypointDetection/python/main.py b/mxVision/mxVision-referenceapps/OpenposeKeypointDetection/python/main.py
similarity index 100%
rename from contrib/OpenposeKeypointDetection/python/main.py
rename to mxVision/mxVision-referenceapps/OpenposeKeypointDetection/python/main.py
diff --git a/contrib/OpenposeKeypointDetection/python/models/insert_op.cfg b/mxVision/mxVision-referenceapps/OpenposeKeypointDetection/python/models/insert_op.cfg
similarity index 100%
rename from contrib/OpenposeKeypointDetection/python/models/insert_op.cfg
rename to mxVision/mxVision-referenceapps/OpenposeKeypointDetection/python/models/insert_op.cfg
diff --git a/contrib/OpenposeKeypointDetection/python/models/model_conversion.sh b/mxVision/mxVision-referenceapps/OpenposeKeypointDetection/python/models/model_conversion.sh
similarity index 100%
rename from contrib/OpenposeKeypointDetection/python/models/model_conversion.sh
rename to mxVision/mxVision-referenceapps/OpenposeKeypointDetection/python/models/model_conversion.sh
diff --git a/contrib/OpenposeKeypointDetection/python/pipeline/Openpose.pipeline b/mxVision/mxVision-referenceapps/OpenposeKeypointDetection/python/pipeline/Openpose.pipeline
similarity index 100%
rename from contrib/OpenposeKeypointDetection/python/pipeline/Openpose.pipeline
rename to mxVision/mxVision-referenceapps/OpenposeKeypointDetection/python/pipeline/Openpose.pipeline
diff --git a/mxVision/OpticalCharacterRecognition/README.md b/mxVision/mxVision-referenceapps/OpticalCharacterRecognition/README.md
similarity index 100%
rename from mxVision/OpticalCharacterRecognition/README.md
rename to mxVision/mxVision-referenceapps/OpticalCharacterRecognition/README.md
diff --git a/mxVision/OpticalCharacterRecognition/src/AscendBase/Base/ArgumentParser/ArgumentParser.cpp b/mxVision/mxVision-referenceapps/OpticalCharacterRecognition/src/AscendBase/Base/ArgumentParser/ArgumentParser.cpp
similarity index 100%
rename from mxVision/OpticalCharacterRecognition/src/AscendBase/Base/ArgumentParser/ArgumentParser.cpp
rename to mxVision/mxVision-referenceapps/OpticalCharacterRecognition/src/AscendBase/Base/ArgumentParser/ArgumentParser.cpp
diff --git a/mxVision/OpticalCharacterRecognition/src/AscendBase/Base/ArgumentParser/ArgumentParser.h b/mxVision/mxVision-referenceapps/OpticalCharacterRecognition/src/AscendBase/Base/ArgumentParser/ArgumentParser.h
similarity index 100%
rename from mxVision/OpticalCharacterRecognition/src/AscendBase/Base/ArgumentParser/ArgumentParser.h
rename to mxVision/mxVision-referenceapps/OpticalCharacterRecognition/src/AscendBase/Base/ArgumentParser/ArgumentParser.h
diff --git a/mxVision/OpticalCharacterRecognition/src/AscendBase/Base/BlockingQueue/BlockingQueue.h b/mxVision/mxVision-referenceapps/OpticalCharacterRecognition/src/AscendBase/Base/BlockingQueue/BlockingQueue.h
similarity index 100%
rename from mxVision/OpticalCharacterRecognition/src/AscendBase/Base/BlockingQueue/BlockingQueue.h
rename to mxVision/mxVision-referenceapps/OpticalCharacterRecognition/src/AscendBase/Base/BlockingQueue/BlockingQueue.h
diff --git a/mxVision/OpticalCharacterRecognition/src/AscendBase/Base/ConfigParser/ConfigParser.cpp b/mxVision/mxVision-referenceapps/OpticalCharacterRecognition/src/AscendBase/Base/ConfigParser/ConfigParser.cpp
similarity index 100%
rename from mxVision/OpticalCharacterRecognition/src/AscendBase/Base/ConfigParser/ConfigParser.cpp
rename to mxVision/mxVision-referenceapps/OpticalCharacterRecognition/src/AscendBase/Base/ConfigParser/ConfigParser.cpp
diff --git a/mxVision/OpticalCharacterRecognition/src/AscendBase/Base/ConfigParser/ConfigParser.h b/mxVision/mxVision-referenceapps/OpticalCharacterRecognition/src/AscendBase/Base/ConfigParser/ConfigParser.h
similarity index 100%
rename from mxVision/OpticalCharacterRecognition/src/AscendBase/Base/ConfigParser/ConfigParser.h
rename to mxVision/mxVision-referenceapps/OpticalCharacterRecognition/src/AscendBase/Base/ConfigParser/ConfigParser.h
diff --git a/mxVision/OpticalCharacterRecognition/src/AscendBase/Base/Framework/ModuleManagers/ModuleBase.cpp b/mxVision/mxVision-referenceapps/OpticalCharacterRecognition/src/AscendBase/Base/Framework/ModuleManagers/ModuleBase.cpp
similarity index 100%
rename from mxVision/OpticalCharacterRecognition/src/AscendBase/Base/Framework/ModuleManagers/ModuleBase.cpp
rename to mxVision/mxVision-referenceapps/OpticalCharacterRecognition/src/AscendBase/Base/Framework/ModuleManagers/ModuleBase.cpp
diff --git a/mxVision/OpticalCharacterRecognition/src/AscendBase/Base/Framework/ModuleManagers/ModuleBase.h b/mxVision/mxVision-referenceapps/OpticalCharacterRecognition/src/AscendBase/Base/Framework/ModuleManagers/ModuleBase.h
similarity index 100%
rename from mxVision/OpticalCharacterRecognition/src/AscendBase/Base/Framework/ModuleManagers/ModuleBase.h
rename to mxVision/mxVision-referenceapps/OpticalCharacterRecognition/src/AscendBase/Base/Framework/ModuleManagers/ModuleBase.h
diff --git a/mxVision/OpticalCharacterRecognition/src/AscendBase/Base/Framework/ModuleManagers/ModuleFactory.h b/mxVision/mxVision-referenceapps/OpticalCharacterRecognition/src/AscendBase/Base/Framework/ModuleManagers/ModuleFactory.h
similarity index 100%
rename from mxVision/OpticalCharacterRecognition/src/AscendBase/Base/Framework/ModuleManagers/ModuleFactory.h
rename to mxVision/mxVision-referenceapps/OpticalCharacterRecognition/src/AscendBase/Base/Framework/ModuleManagers/ModuleFactory.h
diff --git a/mxVision/OpticalCharacterRecognition/src/AscendBase/Base/Framework/ModuleManagers/ModuleManager.cpp b/mxVision/mxVision-referenceapps/OpticalCharacterRecognition/src/AscendBase/Base/Framework/ModuleManagers/ModuleManager.cpp
similarity index 100%
rename from mxVision/OpticalCharacterRecognition/src/AscendBase/Base/Framework/ModuleManagers/ModuleManager.cpp
rename to mxVision/mxVision-referenceapps/OpticalCharacterRecognition/src/AscendBase/Base/Framework/ModuleManagers/ModuleManager.cpp
diff --git a/mxVision/OpticalCharacterRecognition/src/AscendBase/Base/Framework/ModuleManagers/ModuleManager.h b/mxVision/mxVision-referenceapps/OpticalCharacterRecognition/src/AscendBase/Base/Framework/ModuleManagers/ModuleManager.h
similarity index 100%
rename from mxVision/OpticalCharacterRecognition/src/AscendBase/Base/Framework/ModuleManagers/ModuleManager.h
rename to mxVision/mxVision-referenceapps/OpticalCharacterRecognition/src/AscendBase/Base/Framework/ModuleManagers/ModuleManager.h
diff --git a/mxVision/OpticalCharacterRecognition/src/AscendBase/Base/Framework/ModuleProcessors/CharacterRecognitionPost/CharacterRecognitionPost.cpp b/mxVision/mxVision-referenceapps/OpticalCharacterRecognition/src/AscendBase/Base/Framework/ModuleProcessors/CharacterRecognitionPost/CharacterRecognitionPost.cpp
similarity index 100%
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rename to mxVision/mxVision-referenceapps/PPYOLOEPlusDetection/plugin/CMakeLists.txt
diff --git a/mxVision/PPYOLOEPlusDetection/plugin/PPYoloePostProcess.cpp b/mxVision/mxVision-referenceapps/PPYOLOEPlusDetection/plugin/PPYoloePostProcess.cpp
similarity index 100%
rename from mxVision/PPYOLOEPlusDetection/plugin/PPYoloePostProcess.cpp
rename to mxVision/mxVision-referenceapps/PPYOLOEPlusDetection/plugin/PPYoloePostProcess.cpp
diff --git a/mxVision/PPYOLOEPlusDetection/plugin/PPYoloePostProcess.h b/mxVision/mxVision-referenceapps/PPYOLOEPlusDetection/plugin/PPYoloePostProcess.h
similarity index 100%
rename from mxVision/PPYOLOEPlusDetection/plugin/PPYoloePostProcess.h
rename to mxVision/mxVision-referenceapps/PPYOLOEPlusDetection/plugin/PPYoloePostProcess.h
diff --git a/mxVision/PPYOLOEPlusDetection/run.sh b/mxVision/mxVision-referenceapps/PPYOLOEPlusDetection/run.sh
similarity index 100%
rename from mxVision/PPYOLOEPlusDetection/run.sh
rename to mxVision/mxVision-referenceapps/PPYOLOEPlusDetection/run.sh
diff --git a/contrib/PassengerflowEstimation/README.md b/mxVision/mxVision-referenceapps/PassengerflowEstimation/README.md
similarity index 98%
rename from contrib/PassengerflowEstimation/README.md
rename to mxVision/mxVision-referenceapps/PassengerflowEstimation/README.md
index fa84cd2d57ac0cf1434a79326096c197ceaba119..94d09bf5a85de671e6798e8a525bb889baf03be8 100644
--- a/contrib/PassengerflowEstimation/README.md
+++ b/mxVision/mxVision-referenceapps/PassengerflowEstimation/README.md
@@ -1,252 +1,252 @@
-# passengerflowestimation客流量检测
-
-## 1介绍
-
-passengerflowestimation基于MindXSDK开发，在昇腾芯片上进行客流量统计，将最后统计得到的客流量结果在终端内显示。输入一段视频，最后可以得出在某一时间内的客流量。
-
-### 1.1支持的产品
-
-本产品以昇腾310（推理）卡为硬件平台。
-
-### 1.2支持的版本
-
-该项目支持的SDK版本为2.0.4，CANN版本为5.0.4。
-
-### 1.3软件方案介绍
-
-基于MindX SDK的passengerflowestimation客流量检测业务流程为：待检测视频存放在live555服务器上经过mxpi_rtspsrc拉流插件输入，然后使用视频解码插件mxpi_videodecoder进行视频解码。用tee串流插件对解码的视频流进行分发。随后用mxpi_imageresize插件将图像方所至满足检测模型要求的输入图像大小要求，放缩后的图像输入模型推理插件mxpi_tensorinfer进行处理。将经过模型推理插件处理后的数据流输入到mxpi_objectpostprocessor之中，对目标检测模型推理的输出张量进行后处理。处理完毕后，再输入mxpi_selectobject插件中对类名为人的目标框进行筛选，紧接着输入到mxpi_motsimplesortV2插件中实现多目标路径记录功能。本项目开发的mxpi_passengerflowestimation插件将统计识别到的人的数目并输出到终端(此处统计的人数是是通过规定直线人流量)。最后通过mxpi_videoencoder将输入的视频标记出被识别出的人后输出。
-
-表1.1系统方案各子系统功能描述：
-
-| 序号 | 子系统         | 功能描述                                                     |
-| ---- | -------------- | ------------------------------------------------------------ |
-| 1    | 视频输入流     | 接收外部调用接口的输入视频路径，对视频进行拉流，并将拉去的裸流存储到缓冲区（buffer）中，并发送到下游插件。 |
-| 2    | 视频解码       | 用于视频解码，当前只支持H264格式。                           |
-| 3    | 数据分发       | 对单个输入数据进行2次分发。                                  |
-| 4    | 数据缓存       | 输出时为后续处理过程创建一个线程，用于将输入数据与输出数据解耦，并创建缓存队列，存储尚未输入到下流插件的数据。 |
-| 5    | 图像处理       | 对解码后的YUV格式的图像进行放缩。                            |
-| 6    | 模型推理插件   | 目标分类或检测。                                             |
-| 7    | 模型后处理插件 | 对模型输出的张量进行后处理。                                 |
-| 8    | 目标筛选插件   | 对需要进行统计的目标进行筛选。                               |
-| 9    | 统计客流量插件 | 对视频中筛选出来的目标进行数量统计。                         |
-| 10   | 目标框转绘插件 | 将流中传进的数据转换可用于OSD插件绘图所使用的MxpiOsdinstancesList数据类型。 |
-| 11   | OSD可视化插件  | 实现对视频流的每一帧图像进行绘制。                           |
-| 12   | 视频编码插件   | 用于将OSD可视化插件输出的图片进行视频编码，输出视频。        |
-
-### 1.4代码目录结构与说明
-
-本项目名为passengerflowestimation客流量检测，项目目录如下所示：
-
-```
-├── models
-│   ├── aipp_Passengerflowdetection.config            # 模型转换aipp配置文件
-│   ├── passengerflowestimation.onnx      # onnx模型
-│   └── yolov4.om               # om模型
-├── pipeline
-│   └── passengerflowestimation.pipeline        # pipeline文件
-├── plugins
-│   ├── mxpi_passengerflowestimate     # passengerflowestimation后处理插件
-│   │   ├── CMakeLists.txt        
-│   │   ├── PassengerFlowEstimation.cpp  
-│   │   ├── PassengerFlowEstimation.h
-│   │   └── build.sh
-│   └── mxpi_selectobject  # 筛选目标插件
-│       ├── CMakeLists.txt
-│       ├── mxpi_selectobject.cpp
-│       ├── mxpi_selectobject.h
-│       └── build.sh
-├── CMakeLists.txt
-├── build.sh
-├── main.cpp
-```
-
-### 1.5技术实现流程图
-
-本项目实现对输入视频的人流量进行统计，流程图如下：
-
-![img](https://gitee.com/distancemay/mindxsdk-referenceapps/raw/master/contrib/PassengerflowEstimation/images/image1.png)
-
-
-
-## 2环境依赖
-
-推荐系统为ubuntu  18.04,环境以来软件和版本如下：
-
-| 软件名称            | 版本  | 说明                          | 获取方式                                                  |
-| ------------------- | ----- | ----------------------------- | --------------------------------------------------------- |
-| MindX SDK           | 2.0.4 | mxVision软件包                | [链接](https://www.hiascend.com/software/Mindx-sdk)       |
-| ubuntu              | 18.04 | 操作系统                      | 请上ubuntu官网获取                                        |
-| Ascend-CANN-toolkit | 5.0.4 | Ascend-cann-toolkit开发套件包 | [链接](https://www.hiascend.com/software/cann/commercial) |
-
-在项目编译运行时候，需要设置环境变量：
-
-```
-. /usr/local/Ascend/ascend-toolkit/set_env.sh
-. ${SDK安装路径}/mxVision/set_env.sh
-```
-
-注：其中SDK安装路径${MX_SDK_HOME}替换为用户的SDK安装路径。并且本项目用到了mxpi_opencvosd插件，使用mxpi_opencvosd插件前，需要使用osd相关的模型文件，请执行MindX SDK开发套件包安装目录下operators/opencvosd/generate_osd_om.sh脚本生成所需模型文件（在generate_osd_om.sh所在文件夹下执行`bash generate_osd_om.sh `，若这条命令执行失败，则将passengerflowestimation目录下的.om文件移动到generate_osd_om.sh所在的文件夹目录下MindXSDK安装路径/mxVision/operators/opencvosd下）。{install_path}替换为开发套件包所在路径。**（注：开头两行为每次一重新开启终端执行程序就需要输入，此外的其他为转换模型需要，若已经转换模型成功，则不需要输入这些）**
-
-
-
-## 3 软件依赖
-
-推理中涉及到第三方软件依赖如下表所示。
-
-| 软件名称 | 版本       | 说明                           | 使用教程                                                     |
-| -------- | ---------- | ------------------------------ | ------------------------------------------------------------ |
-| live555  | 1.09       | 实现视频转rstp进行推流         | [链接](https://gitee.com/ascend/docs-openmind/blob/master/guide/mindx/sdk/one_stop_navigation.md) |
-| ffmpeg   | 2021-07-21 | 实现mp4格式视频转为264格式视频 | [链接](https://gitee.com/ascend/docs-openmind/blob/master/guide/mindx/sdk/one_stop_navigation.md) |
-
-
-
-## 4 模型转换
-
-本项目中使用的模型是yolov4模型，onnx模型可以直接[下载](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/PassengerflowEstimation/ATC%20Yolov4%28FP16%29%20from%20Pytorch.zip)。下载后使用模型转换工具ATC将onnx模型转换为om模型，模型转换工具相关介绍参考链接：https://gitee.com/ascend/docs-openmind/blob/master/guide/mindx/sdk/tutorials/%E5%8F%82%E8%80%83%E8%B5%84%E6%96%99.md
-
-模型转换步骤如下：
-
-1. 从链接处下载onnx模型至`passengerflowestimation/models`文件夹下，将模型修改名称为`passengerflowestimation.onnx`。
-2. 进入`passengerflowestimation/models`文件夹下面执行命令**（注：提前设置好环境变量）**：
-
-```
-atc --model=${模型路径}/passengerflowestimation.onnx --framework=5 --output=${输出.om模型路径}/yolov4 --input_format=NCHW --output_type=FP32 --soc_version=Ascend310 --input_shape="input:1,3,608,608" --log=info --insert_op_conf=${aipp文件路径}/aipp_Passengerflowdetection.config 
-```
-
-执行该命令后会在指定输出.om模型路径生成项目指定模型文件`passengerflowestimation.om`。若模型转换成功则输出：
-
-```
-ATC start working now, please wait for a moment.
-ATC run success, welcome to the next use.
-```
-
-模型转换的aipp文件配置如下：
-
-```
-aipp_op{
-    aipp_mode:static
-    input_format : YUV420SP_U8
-
-    src_image_size_w : 608
-    src_image_size_h : 608
-
-    crop: false
-    load_start_pos_h : 0
-    load_start_pos_w : 0
-    crop_size_w : 608
-    crop_size_h: 608
-
-    csc_switch : true
-    rbuv_swap_switch : true
-    
-    
-    min_chn_0 : 0
-    min_chn_1 : 0
-    min_chn_2 : 0
-    var_reci_chn_0: 0.003921568627451
-    var_reci_chn_1: 0.003921568627451
-    var_reci_chn_2: 0.003921568627451
-
-    
-    matrix_r0c0: 256
-    matrix_r0c1: 0
-    matrix_r0c2: 359
-    matrix_r1c0: 256
-    matrix_r1c1: -88
-    matrix_r1c2: -183
-    matrix_r2c0: 256
-    matrix_r2c1: 454
-    matrix_r2c2: 0
-    input_bias_0: 0
-    input_bias_1: 128
-    input_bias_2: 128}
-```
-
-## 5准备
-
-按照第3小结**软件依赖**安装live555和ffmpeg，按照 [Live555离线视频转RTSP说明文档](https://gitee.com/ascend/docs-openmind/blob/master/guide/mindx/sdk/one_stop_navigation.md)将mp4视频转换为h264格式。并将生成的264格式的视频上传到`live/mediaServer`目录下，然后修改`passengerflowestimation/pipeline`目录下的`passengerflowestimation.pipeline`文件中mxpi_rtspsrc0的内容。
-
-```
-"mxpi_rtspsrc0": {
-            "factory": "mxpi_rtspsrc",
-            "props": {
-                "rtspUrl":"rtsp://xxx.xxx.xxx.xxx:xxxx/xxx.264",      // 修改为自己所使用的的服务器和文件名
-                "channelId": "0"
-            },
-            "next": "mxpi_videodecoder0"
-        },
-```
-
-在mxpi_objectpostprocessor0插件中，修改postProcessLibPath中的路径为自己libyolov3postprocess.so文件路径。
-## 6编译与运行
-
-### 步骤1
-
-按照第二小节环境依赖中的步骤设置环境变量。
-
-### 步骤2
-
-按照第四小节模型转换中的步骤获取om模型文件，放置在`passengerflowestimation/models`目录下。
-
-### 步骤3 修改
-
-对于mxpi_passengerflowestimate插件的使用说明：
-
-在pipeline中，mxpi_passengerflowestimate插件如下：
-
-```
-"mxpi_passengerflowestimation0": {
-                "props": {
-                    "dataSource": "mxpi_selectobject0",
-                    "motSource": "motV2",
-                    "x0":"736",
-                    "y0":"191",
-                    "x1":"1870",
-                    "y1":"191"
-                },
-                "factory": "mxpi_passengerflowestimation",
-                "next": "mxpi_object2osdinstances0"
-            },
-```
-
-这里点$(x_0,y_0)$与$(x_1,y_1)$确定了一条线段，这个插件统计经过该线段的客流量。修改mxpi_objectpostprocessor0插件中的postProcessLibPath为自己当前的libyolov3postprocess.so路径。
-
-### 步骤4 编译
-
-进入passengerflowestimation目录，在passengerflowestimation目录下执行命令：
-
-```
-bash build.sh
-```
-
-命令执行成功之后会在passengerflowestimation/plugins/mxpi_passengerflowestimation和passengerflowestimation/plugins/mxpi_selectobject目录下分别生成build文件夹。将build文件夹下生成的.so下载后上传到${SDK安装路径}/mxVision/lib/plugins目录下。在生成build文件夹后，进入到build目录下执行如下指令：
-
-```
-chmod 640 libmxpi_passengerflowestimation.so
-chmod 640 libmxpi_selectobject.so
-```
-
-
-
-### 步骤5 运行：
-
-在passengerflowestimation目录下运行：
-
-```
-python3 main.py
-```
-
-最后生成的结果将会在passengerflowestimation文件夹目录下result.h264文件里面。
-
-
-
-## 7性能测试
-
-测试帧率： 本样例的测试脚本main.py测试拉流25帧视频时输出的帧率，通过计算帧数和整个计算过程所需时间的比值，统计整个过程中平均帧率。
-测试视频的帧率为25，分辨率1920*1080，因为拉流开始会导致丢帧，而测试脚本是通过计算帧数和整个处理过程所需的时间的比值获得的平均帧率，所以测试视频的帧数过少会引起性能测试值偏低，FRAMENUM需要设为较大值(不小于源测试视频的帧数)。
-经过计算平均fps值，得到平均fps为24.9（如下图所示），考虑到一开始拉流丢帧造成的损失，满足性能测试要求。 
-![img](https://gitee.com/distancemay/mindxsdk-referenceapps/raw/master/contrib/PassengerflowEstimation/images/image5.png)
-
-## 8适用场景
-本项目适用于俯视角度较大，并且人流量不是非常密集的视频中人流量统计。若人流非常密集，由于yolov4模型识别人体不准确，故无法准确统计客流量。并且在视频中的画线要尽量水平。待检测的视频最好如下所示：
+# passengerflowestimation客流量检测
+
+## 1介绍
+
+passengerflowestimation基于MindXSDK开发，在昇腾芯片上进行客流量统计，将最后统计得到的客流量结果在终端内显示。输入一段视频，最后可以得出在某一时间内的客流量。
+
+### 1.1支持的产品
+
+本产品以昇腾310（推理）卡为硬件平台。
+
+### 1.2支持的版本
+
+该项目支持的SDK版本为2.0.4，CANN版本为5.0.4。
+
+### 1.3软件方案介绍
+
+基于MindX SDK的passengerflowestimation客流量检测业务流程为：待检测视频存放在live555服务器上经过mxpi_rtspsrc拉流插件输入，然后使用视频解码插件mxpi_videodecoder进行视频解码。用tee串流插件对解码的视频流进行分发。随后用mxpi_imageresize插件将图像方所至满足检测模型要求的输入图像大小要求，放缩后的图像输入模型推理插件mxpi_tensorinfer进行处理。将经过模型推理插件处理后的数据流输入到mxpi_objectpostprocessor之中，对目标检测模型推理的输出张量进行后处理。处理完毕后，再输入mxpi_selectobject插件中对类名为人的目标框进行筛选，紧接着输入到mxpi_motsimplesortV2插件中实现多目标路径记录功能。本项目开发的mxpi_passengerflowestimation插件将统计识别到的人的数目并输出到终端(此处统计的人数是是通过规定直线人流量)。最后通过mxpi_videoencoder将输入的视频标记出被识别出的人后输出。
+
+表1.1系统方案各子系统功能描述：
+
+| 序号 | 子系统         | 功能描述                                                     |
+| ---- | -------------- | ------------------------------------------------------------ |
+| 1    | 视频输入流     | 接收外部调用接口的输入视频路径，对视频进行拉流，并将拉去的裸流存储到缓冲区（buffer）中，并发送到下游插件。 |
+| 2    | 视频解码       | 用于视频解码，当前只支持H264格式。                           |
+| 3    | 数据分发       | 对单个输入数据进行2次分发。                                  |
+| 4    | 数据缓存       | 输出时为后续处理过程创建一个线程，用于将输入数据与输出数据解耦，并创建缓存队列，存储尚未输入到下流插件的数据。 |
+| 5    | 图像处理       | 对解码后的YUV格式的图像进行放缩。                            |
+| 6    | 模型推理插件   | 目标分类或检测。                                             |
+| 7    | 模型后处理插件 | 对模型输出的张量进行后处理。                                 |
+| 8    | 目标筛选插件   | 对需要进行统计的目标进行筛选。                               |
+| 9    | 统计客流量插件 | 对视频中筛选出来的目标进行数量统计。                         |
+| 10   | 目标框转绘插件 | 将流中传进的数据转换可用于OSD插件绘图所使用的MxpiOsdinstancesList数据类型。 |
+| 11   | OSD可视化插件  | 实现对视频流的每一帧图像进行绘制。                           |
+| 12   | 视频编码插件   | 用于将OSD可视化插件输出的图片进行视频编码，输出视频。        |
+
+### 1.4代码目录结构与说明
+
+本项目名为passengerflowestimation客流量检测，项目目录如下所示：
+
+```
+├── models
+│   ├── aipp_Passengerflowdetection.config            # 模型转换aipp配置文件
+│   ├── passengerflowestimation.onnx      # onnx模型
+│   └── yolov4.om               # om模型
+├── pipeline
+│   └── passengerflowestimation.pipeline        # pipeline文件
+├── plugins
+│   ├── mxpi_passengerflowestimate     # passengerflowestimation后处理插件
+│   │   ├── CMakeLists.txt        
+│   │   ├── PassengerFlowEstimation.cpp  
+│   │   ├── PassengerFlowEstimation.h
+│   │   └── build.sh
+│   └── mxpi_selectobject  # 筛选目标插件
+│       ├── CMakeLists.txt
+│       ├── mxpi_selectobject.cpp
+│       ├── mxpi_selectobject.h
+│       └── build.sh
+├── CMakeLists.txt
+├── build.sh
+├── main.cpp
+```
+
+### 1.5技术实现流程图
+
+本项目实现对输入视频的人流量进行统计，流程图如下：
+
+![img](https://gitee.com/distancemay/mindxsdk-referenceapps/raw/master/contrib/PassengerflowEstimation/images/image1.png)
+
+
+
+## 2环境依赖
+
+推荐系统为ubuntu  18.04,环境以来软件和版本如下：
+
+| 软件名称            | 版本  | 说明                          | 获取方式                                                  |
+| ------------------- | ----- | ----------------------------- | --------------------------------------------------------- |
+| MindX SDK           | 2.0.4 | mxVision软件包                | [链接](https://www.hiascend.com/software/Mindx-sdk)       |
+| ubuntu              | 18.04 | 操作系统                      | 请上ubuntu官网获取                                        |
+| Ascend-CANN-toolkit | 5.0.4 | Ascend-cann-toolkit开发套件包 | [链接](https://www.hiascend.com/software/cann/commercial) |
+
+在项目编译运行时候，需要设置环境变量：
+
+```
+. /usr/local/Ascend/ascend-toolkit/set_env.sh
+. ${SDK安装路径}/mxVision/set_env.sh
+```
+
+注：其中SDK安装路径${MX_SDK_HOME}替换为用户的SDK安装路径。并且本项目用到了mxpi_opencvosd插件，使用mxpi_opencvosd插件前，需要使用osd相关的模型文件，请执行MindX SDK开发套件包安装目录下operators/opencvosd/generate_osd_om.sh脚本生成所需模型文件（在generate_osd_om.sh所在文件夹下执行`bash generate_osd_om.sh `，若这条命令执行失败，则将passengerflowestimation目录下的.om文件移动到generate_osd_om.sh所在的文件夹目录下MindXSDK安装路径/mxVision/operators/opencvosd下）。{install_path}替换为开发套件包所在路径。**（注：开头两行为每次一重新开启终端执行程序就需要输入，此外的其他为转换模型需要，若已经转换模型成功，则不需要输入这些）**
+
+
+
+## 3 软件依赖
+
+推理中涉及到第三方软件依赖如下表所示。
+
+| 软件名称 | 版本       | 说明                           | 使用教程                                                     |
+| -------- | ---------- | ------------------------------ | ------------------------------------------------------------ |
+| live555  | 1.09       | 实现视频转rstp进行推流         | [链接](https://gitee.com/ascend/docs-openmind/blob/master/guide/mindx/sdk/one_stop_navigation.md) |
+| ffmpeg   | 2021-07-21 | 实现mp4格式视频转为264格式视频 | [链接](https://gitee.com/ascend/docs-openmind/blob/master/guide/mindx/sdk/one_stop_navigation.md) |
+
+
+
+## 4 模型转换
+
+本项目中使用的模型是yolov4模型，onnx模型可以直接[下载](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/PassengerflowEstimation/ATC%20Yolov4%28FP16%29%20from%20Pytorch.zip)。下载后使用模型转换工具ATC将onnx模型转换为om模型，模型转换工具相关介绍参考链接：https://gitee.com/ascend/docs-openmind/blob/master/guide/mindx/sdk/tutorials/%E5%8F%82%E8%80%83%E8%B5%84%E6%96%99.md
+
+模型转换步骤如下：
+
+1. 从链接处下载onnx模型至`passengerflowestimation/models`文件夹下，将模型修改名称为`passengerflowestimation.onnx`。
+2. 进入`passengerflowestimation/models`文件夹下面执行命令**（注：提前设置好环境变量）**：
+
+```
+atc --model=${模型路径}/passengerflowestimation.onnx --framework=5 --output=${输出.om模型路径}/yolov4 --input_format=NCHW --output_type=FP32 --soc_version=Ascend310 --input_shape="input:1,3,608,608" --log=info --insert_op_conf=${aipp文件路径}/aipp_Passengerflowdetection.config 
+```
+
+执行该命令后会在指定输出.om模型路径生成项目指定模型文件`passengerflowestimation.om`。若模型转换成功则输出：
+
+```
+ATC start working now, please wait for a moment.
+ATC run success, welcome to the next use.
+```
+
+模型转换的aipp文件配置如下：
+
+```
+aipp_op{
+    aipp_mode:static
+    input_format : YUV420SP_U8
+
+    src_image_size_w : 608
+    src_image_size_h : 608
+
+    crop: false
+    load_start_pos_h : 0
+    load_start_pos_w : 0
+    crop_size_w : 608
+    crop_size_h: 608
+
+    csc_switch : true
+    rbuv_swap_switch : true
+    
+    
+    min_chn_0 : 0
+    min_chn_1 : 0
+    min_chn_2 : 0
+    var_reci_chn_0: 0.003921568627451
+    var_reci_chn_1: 0.003921568627451
+    var_reci_chn_2: 0.003921568627451
+
+    
+    matrix_r0c0: 256
+    matrix_r0c1: 0
+    matrix_r0c2: 359
+    matrix_r1c0: 256
+    matrix_r1c1: -88
+    matrix_r1c2: -183
+    matrix_r2c0: 256
+    matrix_r2c1: 454
+    matrix_r2c2: 0
+    input_bias_0: 0
+    input_bias_1: 128
+    input_bias_2: 128}
+```
+
+## 5准备
+
+按照第3小结**软件依赖**安装live555和ffmpeg，按照 [Live555离线视频转RTSP说明文档](https://gitee.com/ascend/docs-openmind/blob/master/guide/mindx/sdk/one_stop_navigation.md)将mp4视频转换为h264格式。并将生成的264格式的视频上传到`live/mediaServer`目录下，然后修改`passengerflowestimation/pipeline`目录下的`passengerflowestimation.pipeline`文件中mxpi_rtspsrc0的内容。
+
+```
+"mxpi_rtspsrc0": {
+            "factory": "mxpi_rtspsrc",
+            "props": {
+                "rtspUrl":"rtsp://xxx.xxx.xxx.xxx:xxxx/xxx.264",      // 修改为自己所使用的的服务器和文件名
+                "channelId": "0"
+            },
+            "next": "mxpi_videodecoder0"
+        },
+```
+
+在mxpi_objectpostprocessor0插件中，修改postProcessLibPath中的路径为自己libyolov3postprocess.so文件路径。
+## 6编译与运行
+
+### 步骤1
+
+按照第二小节环境依赖中的步骤设置环境变量。
+
+### 步骤2
+
+按照第四小节模型转换中的步骤获取om模型文件，放置在`passengerflowestimation/models`目录下。
+
+### 步骤3 修改
+
+对于mxpi_passengerflowestimate插件的使用说明：
+
+在pipeline中，mxpi_passengerflowestimate插件如下：
+
+```
+"mxpi_passengerflowestimation0": {
+                "props": {
+                    "dataSource": "mxpi_selectobject0",
+                    "motSource": "motV2",
+                    "x0":"736",
+                    "y0":"191",
+                    "x1":"1870",
+                    "y1":"191"
+                },
+                "factory": "mxpi_passengerflowestimation",
+                "next": "mxpi_object2osdinstances0"
+            },
+```
+
+这里点$(x_0,y_0)$与$(x_1,y_1)$确定了一条线段，这个插件统计经过该线段的客流量。修改mxpi_objectpostprocessor0插件中的postProcessLibPath为自己当前的libyolov3postprocess.so路径。
+
+### 步骤4 编译
+
+进入passengerflowestimation目录，在passengerflowestimation目录下执行命令：
+
+```
+bash build.sh
+```
+
+命令执行成功之后会在passengerflowestimation/plugins/mxpi_passengerflowestimation和passengerflowestimation/plugins/mxpi_selectobject目录下分别生成build文件夹。将build文件夹下生成的.so下载后上传到${SDK安装路径}/mxVision/lib/plugins目录下。在生成build文件夹后，进入到build目录下执行如下指令：
+
+```
+chmod 640 libmxpi_passengerflowestimation.so
+chmod 640 libmxpi_selectobject.so
+```
+
+
+
+### 步骤5 运行：
+
+在passengerflowestimation目录下运行：
+
+```
+python3 main.py
+```
+
+最后生成的结果将会在passengerflowestimation文件夹目录下result.h264文件里面。
+
+
+
+## 7性能测试
+
+测试帧率： 本样例的测试脚本main.py测试拉流25帧视频时输出的帧率，通过计算帧数和整个计算过程所需时间的比值，统计整个过程中平均帧率。
+测试视频的帧率为25，分辨率1920*1080，因为拉流开始会导致丢帧，而测试脚本是通过计算帧数和整个处理过程所需的时间的比值获得的平均帧率，所以测试视频的帧数过少会引起性能测试值偏低，FRAMENUM需要设为较大值(不小于源测试视频的帧数)。
+经过计算平均fps值，得到平均fps为24.9（如下图所示），考虑到一开始拉流丢帧造成的损失，满足性能测试要求。 
+![img](https://gitee.com/distancemay/mindxsdk-referenceapps/raw/master/contrib/PassengerflowEstimation/images/image5.png)
+
+## 8适用场景
+本项目适用于俯视角度较大，并且人流量不是非常密集的视频中人流量统计。若人流非常密集，由于yolov4模型识别人体不准确，故无法准确统计客流量。并且在视频中的画线要尽量水平。待检测的视频最好如下所示：
 ![img](https://gitee.com/distancemay/mindxsdk-referenceapps/raw/master/contrib/PassengerflowEstimation/images/image4.png)
\ No newline at end of file
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rename to mxVision/mxVision-referenceapps/PatchCoreAnomalyDetection_mindspore/README.md
diff --git a/contrib/PatchCoreAnomalyDetection_mindspore/config.yaml b/mxVision/mxVision-referenceapps/PatchCoreAnomalyDetection_mindspore/config.yaml
similarity index 100%
rename from contrib/PatchCoreAnomalyDetection_mindspore/config.yaml
rename to mxVision/mxVision-referenceapps/PatchCoreAnomalyDetection_mindspore/config.yaml
diff --git a/contrib/PatchCoreAnomalyDetection_mindspore/images/grid.png b/mxVision/mxVision-referenceapps/PatchCoreAnomalyDetection_mindspore/images/grid.png
similarity index 100%
rename from contrib/PatchCoreAnomalyDetection_mindspore/images/grid.png
rename to mxVision/mxVision-referenceapps/PatchCoreAnomalyDetection_mindspore/images/grid.png
diff --git a/contrib/PatchCoreAnomalyDetection_mindspore/images/pill.png b/mxVision/mxVision-referenceapps/PatchCoreAnomalyDetection_mindspore/images/pill.png
similarity index 100%
rename from contrib/PatchCoreAnomalyDetection_mindspore/images/pill.png
rename to mxVision/mxVision-referenceapps/PatchCoreAnomalyDetection_mindspore/images/pill.png
diff --git a/contrib/PatchCoreAnomalyDetection_mindspore/models.py b/mxVision/mxVision-referenceapps/PatchCoreAnomalyDetection_mindspore/models.py
similarity index 100%
rename from contrib/PatchCoreAnomalyDetection_mindspore/models.py
rename to mxVision/mxVision-referenceapps/PatchCoreAnomalyDetection_mindspore/models.py
diff --git a/contrib/PatchCoreAnomalyDetection_mindspore/mvtec.py b/mxVision/mxVision-referenceapps/PatchCoreAnomalyDetection_mindspore/mvtec.py
similarity index 100%
rename from contrib/PatchCoreAnomalyDetection_mindspore/mvtec.py
rename to mxVision/mxVision-referenceapps/PatchCoreAnomalyDetection_mindspore/mvtec.py
diff --git a/contrib/PatchCoreAnomalyDetection_mindspore/network.py b/mxVision/mxVision-referenceapps/PatchCoreAnomalyDetection_mindspore/network.py
similarity index 100%
rename from contrib/PatchCoreAnomalyDetection_mindspore/network.py
rename to mxVision/mxVision-referenceapps/PatchCoreAnomalyDetection_mindspore/network.py
diff --git a/contrib/PatchCoreAnomalyDetection_mindspore/pthtockpt.py b/mxVision/mxVision-referenceapps/PatchCoreAnomalyDetection_mindspore/pthtockpt.py
similarity index 100%
rename from contrib/PatchCoreAnomalyDetection_mindspore/pthtockpt.py
rename to mxVision/mxVision-referenceapps/PatchCoreAnomalyDetection_mindspore/pthtockpt.py
diff --git a/contrib/PatchCoreAnomalyDetection_mindspore/tools.py b/mxVision/mxVision-referenceapps/PatchCoreAnomalyDetection_mindspore/tools.py
similarity index 100%
rename from contrib/PatchCoreAnomalyDetection_mindspore/tools.py
rename to mxVision/mxVision-referenceapps/PatchCoreAnomalyDetection_mindspore/tools.py
diff --git a/contrib/PatchCoreAnomalyDetection_mindspore/train.py b/mxVision/mxVision-referenceapps/PatchCoreAnomalyDetection_mindspore/train.py
similarity index 100%
rename from contrib/PatchCoreAnomalyDetection_mindspore/train.py
rename to mxVision/mxVision-referenceapps/PatchCoreAnomalyDetection_mindspore/train.py
diff --git a/contrib/PatchCoreAnomalyDetection_mindspore/train_all.py b/mxVision/mxVision-referenceapps/PatchCoreAnomalyDetection_mindspore/train_all.py
similarity index 100%
rename from contrib/PatchCoreAnomalyDetection_mindspore/train_all.py
rename to mxVision/mxVision-referenceapps/PatchCoreAnomalyDetection_mindspore/train_all.py
diff --git a/contrib/PedestrianAttributeRecognition/License b/mxVision/mxVision-referenceapps/PedestrianAttributeRecognition/License
similarity index 100%
rename from contrib/PedestrianAttributeRecognition/License
rename to mxVision/mxVision-referenceapps/PedestrianAttributeRecognition/License
diff --git a/contrib/PedestrianAttributeRecognition/README.md b/mxVision/mxVision-referenceapps/PedestrianAttributeRecognition/README.md
similarity index 97%
rename from contrib/PedestrianAttributeRecognition/README.md
rename to mxVision/mxVision-referenceapps/PedestrianAttributeRecognition/README.md
index 6d6527ac1a6ce00ab07de077b68d864d1cd327c0..8e87bcd7304beb733595ee9f9e737299214e3d55 100644
--- a/contrib/PedestrianAttributeRecognition/README.md
+++ b/mxVision/mxVision-referenceapps/PedestrianAttributeRecognition/README.md
@@ -1,231 +1,231 @@
-# MindX SDK-行人属性检测
-
-## 1 介绍
-本开发样例是基于MindX SDK开发的端到端的Python应用实例，可在昇腾芯片上进行行人属性识别，并把可视化结果保存到本地。开发端到端行人属性识别，实现对检测图片中行人的定位与属性识别，并达到精度要求。该Sample的主要处理流程为：数据输入>预处理>行人检测>抠图缩放>行人属性识别>结果可视化
-
-### 1.1 支持的产品
-
-支持昇腾310芯片推理。
-
-### 1.2 支持的版本
-
-支持的SDK版本为2.0.4.b011。 
-
-MindX SDK安装前准备可参考《用户指南》，[安装教程](https://gitee.com/ascend/mindxsdk-referenceapps/blob/master/docs/quickStart/1-1安装SDK开发套件.md)
-
-### 1.3 软件方案介绍
-
-基于MindX SDK的行人属性识别业务流程：待检测图片通过appsrc插件输入，然后使用图像解码插件mxpi_imagedecoder对图片进行解码，再通过图像缩放插件mxpi_imageresize将图像缩放至满足行人检测模型(yolov3)要求的输入图像大小要求，缩放后的图像输入模型推理插件mxpi_tensorinfer中进行推理，随后将数据送入后处理插件mxpi_objectpostprocessor中进行处理，将得到的结果经过分发插件mxpi_distributor输出，随后将数据输出到裁剪插件mxpi_imagecrop中，根据上游推理插件推理出的结果进行裁剪出行人，并将裁剪后的图像输入到Deepmar的模型推理插件中，进行行人属性推理，最后将行人属性推理插件经序列化插件mxpi_dataserialize输出，即得到属性的预测结果，并将结果进行标签化，即为该图片的属性推理结果。
-
-表1.1 系统方案各子系统功能描述：
-
-| 序号 | 子系统             | 功能描述                                                     |
-| ---- | ------------------ | ------------------------------------------------------------ |
-| 1    | 图片输入           | 获取jpg格式的输入图片                                        |
-| 2    | 图片解码           | 解码图片                                                     |
-| 3    | 图片缩放           | 将输入图片缩放到模型指定输入的尺寸大小                       |
-| 4    | 行人检测           | 将输入的张量送入Yolov3模型推理插件中进行推理，得到行人检测框 |
-| 5    | Yolov3模型后处理   | 对Yolov3推理插件的输出结果进行处理                           |
-| 6    | Yolov3检测结果分发 | 对检测到的person类进行分发                                   |
-| 7    | 图像裁剪           | 对Yolov3检测出的行人进行裁剪                                 |
-| 8    | 行人属性检测       | 将裁剪后的图像数据送入Deepmar推理插件中进行属性推理          |
-| 9    | 结果序列化         | 将35个属性推理结果序列化输出                                 |
-
-### 1.4 代码目录结构与说明
-
-本sample工程名称为yolov3_deepmar，工程目录如下图所示：
-```
-.
-├── dataset
-│   ├── image
-│   ├── test_image
-│   ├── image_jpg
-│   ├── PETA.mat
-│   ├── png2jpg.py
-│   ├── transform_peta.py
-│   ├── peta_dataset.pkl
-│   └── peta_partition.pkl
-├── model
-│   ├── deepmar
-│       ├── deepmar_bs1_aipp_1.om
-│       ├── deepmar_bs1_unaipp.om
-│       ├── aipp_deepmar.config
-│       ├── Deepmar_bs1.onnx
-│   ├── yolov3
-│       ├── coco.names
-│       ├── yolov3_tf_bs1_fp16.cfg
-│       ├── yolov3_tf_bs_fp16.om
-│       ├── yolov3_tf.pb
-│       ├── aipp_yolov3_416_416.aippconfig
-├── pipeline
-│   ├── test.pipeline
-│   ├── test_only_deepmar.pipeline
-├── evaluate.py
-├── evaluate_for_deepmar.py
-├── License
-├── simgei.ttf
-├── main.py
-├── README.md
-└── run.sh
-```
-
-
-
-## 2 环境依赖
-
-推荐系统为ubantu 18.04，环境依赖软件和版本如下表：
-
-| 软件名称    | 版本   |
-| ----------- | ------ |
-| python      | 3.9.2  |
-| mxVision    | 2.0.4  |
-| pillow      | 8.0.1  |
-| pickle5     | 0.0.11 |
-
-确保环境中正确安装mxVision SDK。
-
-模型转换所需ATC工具环境搭建参考链接：https://gitee.com/ascend/docs-openmind/blob/master/guide/mindx/sdk/tutorials/%E5%8F%82%E8%80%83%E8%B5%84%E6%96%99.md
-
-在编译运行项目前，需要设置环境变量：
-
-- 环境变量介绍
-将${SDK安装路径}替换为自己的SDK安装路径; 
-```python
-export MX_SDK_HOME=${SDK安装路径}/mxVision
-export install_path=/usr/local/Ascend/ascend-toolkit/latest
-export PATH=/usr/local/python3.9.2/bin:${install_path}/atc/ccec_compiler/bin:${install_path}/atc/bin:$PATH
-export PYTHONPATH=${install_path}/atc/python/site-packages:${install_path}/atc/python/site-packages/auto_tune.egg/auto_tune:${install_path}/atc/python/site-packages/schedule_search.egg:$PYTHONPATH
-export LD_LIBRARY_PATH=${install_path}/atc/lib64:$LD_LIBRARY_PATH
-export ASCEND_OPP_PATH=${install_path}/opp
-```
-
-## 3 模型转换
-
-本项目中用到的模型有：yolov3，deeomar两个模型。模型下载链接为：[链接](https://mindx.sdk.obs.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/PedestrianAttributeRecognition/model.zip)
-
-获取yolov3_tf.pb文件，将yolov3的pb文件下载到本地，并将其放在“/model/yolov3”路径下，在终端移至该路径下，执行下面命令：。
-
-```python
-atc --model=./yolov3_tf.pb --framework=3 --output=./yolov3_tf_bs1_fp16 --soc_version=Ascend310 --insert_op_conf=./aipp_yolov3_416_416.aippconfig --input_shape="input/input_data:1,416,416,3" --out_nodes="conv_lbbox/BiasAdd:0;conv_mbbox/BiasAdd:0;conv_sbbox/BiasAdd:0"
-```
-更多的atc模型转换信息可以参考此链接样例：https://gitee.com/ascend/docs-openmind/blob/master/guide/mindx/sdk/tutorials/%E5%8F%82%E8%80%83%E8%B5%84%E6%96%99.md
-
-deepmar模型，对于无aipp设置的离线模型的转换，只需将atc转换时的 --insert_op_conf参数删除即可。
-
-对于deepmar离线模型的aipp的设置，如下:
-
-```python
-aipp_op{
-    aipp_mode:static
-    input_format : YUV420SP_U8
-
-    src_image_size_w : 224
-    src_image_size_h : 224
-
-    crop: false
-    load_start_pos_h : 0
-    load_start_pos_w : 0
-    crop_size_w : 224
-    crop_size_h: 224
-
-    csc_switch : true
-    rbuv_swap_switch : false
-
-    mean_chn_0 : 123
-    mean_chn_1 : 116
-    mean_chn_2 : 103
-    min_chn_0 : 0.675
-    min_chn_1 : 0.28
-    min_chn_2 : 0.53
-    var_reci_chn_0: 0.0171
-    var_reci_chn_1: 0.0175
-    var_reci_chn_2: 0.0174
-
-    matrix_r0c0: 256
-    matrix_r0c1: 0
-    matrix_r0c2: 359
-    matrix_r1c0: 256
-    matrix_r1c1: -88
-    matrix_r1c2: -183
-    matrix_r2c0: 256
-    matrix_r2c1: 454
-    matrix_r2c2: 0
-    input_bias_0: 16
-    input_bias_1: 128
-    input_bias_2: 128}
-```
-下载好deepmar之后，将Deepmar_bs1.onnx文件拷贝到本样例的“model/deepmar”路径下，并在终端中移至该路径下，执行下面命令进行将onnx模型转om模型：
-
-```python
-atc --model=./Deepmar_bs1.onnx --framework=5 --output=./deepmar_bs1_aipp_1 --input_format=NCHW --input_shape="actual_input_1:1,3,224,224" --enable_small_channel=1 --log=error --soc_version=Ascend310  --insert_op_conf=aipp_deepmar.config
-```
-对于无aipp设置的离线模型，可执行下面命令得到：
-
-```python
-atc --model=./Deepmar_bs1.onnx --framework=5 --output=./deepmar_bs1_unaipp --input_format=NCHW --input_shape="actual_input_1:1,3,224,224" --enable_small_channel=1 --log=error --soc_version=Ascend310
-```
-
-
-
-
-## 4 编译与运行
-
-**步骤1** 参照第3章节中的模型转换步骤，将yolov3的离线模型转换成功
-
-**步骤2** 参照第3章节中的模型转换步骤，将deepmar的离线模型转换成功
-
-**步骤3** 将需要进行推理的行人图片放入/dataset/test_image文件夹下，并修改main.py脚本中第91行中的“img_path"为需要推理的图片路径，将test.pipeline中的后处理so文件修改为SDK安装路径。
-
-**步骤4** 执行命令：python main.py,得到final_result.jpg可视化结果
-
-
-
-## 5 精度测试
-
-下载开源数据集Peta，[下载地址](https://mindx.sdk.obs.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/PedestrianAttributeRecognition/data.zip)，
-
-（1）将下载好的文件夹中”./dataset/peta/images/*.png“中的images文件夹放入样例代码中的dataset/image文件夹下；将PETA.mat文件放在样例代码的dataset文件夹下。
-
-（2）将Peta数据集中的png格式图片转为jpg格式图片
-
-​	修改png2img.py脚本中的“filePath”为Peta数据集中的png格式图片的路径，并运行下面命令：
-
-```python
-python png2jpg.py
-```
-
-（3）拆分数据集
-
-修改transform_peta.py脚本中的petaPath为PETA.mat文件的路径，添加save_file参数的文件保存路径以及traintest_split_file的参数路径，即将"样例工程路径"修改为自己的代码运行路径并运行下面命令：
-
-```python
-python dataset/transform_peta.py 
-```
-
-（4）精度测试
-
-修改下面代码：
-
-```python
-    for idx in partition['test'][0]:
-        image.append(dataset['test_image'][idx])
-        label_tmp = np.array(dataset['att'][idx])[dataset['selected_attribute']].tolist()
-        label.append(label_tmp)
-```
-
-依次修改上面代码中"partition\['test'][0]"为"partition\['test'][0]"、"partition\['test'][1]"、"partition\['test'][2]"、"partition\['test'][3]"、"partition\['test'][4]"
-
-并运行下面命令：
-
-```python
-python evaluate_for_deepmar.py
-```
-
-可得到五组测试结果，并将五组测试结果求平均，可得到最终的peta测试集的平均属性识别准确率。
-
-## 6 常见问题
-
-测试样例的像素大小要做在32\*32～8192\*8192之间(其中不包含32*32的像素，图片像素大小必须大于32\*32)，且里边的行人对象像素的高度需在[6,4096]之间，宽度需在[32,4096]之间。
-
-## 7 适用场景
-本样例适用于常见行人所处场景，如街道、红路灯路口、商场等，对于所推理的图片中的行人对象要求尽可能的完整、清晰、无遮挡、无重叠等。
+# MindX SDK-行人属性检测
+
+## 1 介绍
+本开发样例是基于MindX SDK开发的端到端的Python应用实例，可在昇腾芯片上进行行人属性识别，并把可视化结果保存到本地。开发端到端行人属性识别，实现对检测图片中行人的定位与属性识别，并达到精度要求。该Sample的主要处理流程为：数据输入>预处理>行人检测>抠图缩放>行人属性识别>结果可视化
+
+### 1.1 支持的产品
+
+支持昇腾310芯片推理。
+
+### 1.2 支持的版本
+
+支持的SDK版本为2.0.4.b011。 
+
+MindX SDK安装前准备可参考《用户指南》，[安装教程](https://gitee.com/ascend/mindxsdk-referenceapps/blob/master/docs/quickStart/1-1安装SDK开发套件.md)
+
+### 1.3 软件方案介绍
+
+基于MindX SDK的行人属性识别业务流程：待检测图片通过appsrc插件输入，然后使用图像解码插件mxpi_imagedecoder对图片进行解码，再通过图像缩放插件mxpi_imageresize将图像缩放至满足行人检测模型(yolov3)要求的输入图像大小要求，缩放后的图像输入模型推理插件mxpi_tensorinfer中进行推理，随后将数据送入后处理插件mxpi_objectpostprocessor中进行处理，将得到的结果经过分发插件mxpi_distributor输出，随后将数据输出到裁剪插件mxpi_imagecrop中，根据上游推理插件推理出的结果进行裁剪出行人，并将裁剪后的图像输入到Deepmar的模型推理插件中，进行行人属性推理，最后将行人属性推理插件经序列化插件mxpi_dataserialize输出，即得到属性的预测结果，并将结果进行标签化，即为该图片的属性推理结果。
+
+表1.1 系统方案各子系统功能描述：
+
+| 序号 | 子系统             | 功能描述                                                     |
+| ---- | ------------------ | ------------------------------------------------------------ |
+| 1    | 图片输入           | 获取jpg格式的输入图片                                        |
+| 2    | 图片解码           | 解码图片                                                     |
+| 3    | 图片缩放           | 将输入图片缩放到模型指定输入的尺寸大小                       |
+| 4    | 行人检测           | 将输入的张量送入Yolov3模型推理插件中进行推理，得到行人检测框 |
+| 5    | Yolov3模型后处理   | 对Yolov3推理插件的输出结果进行处理                           |
+| 6    | Yolov3检测结果分发 | 对检测到的person类进行分发                                   |
+| 7    | 图像裁剪           | 对Yolov3检测出的行人进行裁剪                                 |
+| 8    | 行人属性检测       | 将裁剪后的图像数据送入Deepmar推理插件中进行属性推理          |
+| 9    | 结果序列化         | 将35个属性推理结果序列化输出                                 |
+
+### 1.4 代码目录结构与说明
+
+本sample工程名称为yolov3_deepmar，工程目录如下图所示：
+```
+.
+├── dataset
+│   ├── image
+│   ├── test_image
+│   ├── image_jpg
+│   ├── PETA.mat
+│   ├── png2jpg.py
+│   ├── transform_peta.py
+│   ├── peta_dataset.pkl
+│   └── peta_partition.pkl
+├── model
+│   ├── deepmar
+│       ├── deepmar_bs1_aipp_1.om
+│       ├── deepmar_bs1_unaipp.om
+│       ├── aipp_deepmar.config
+│       ├── Deepmar_bs1.onnx
+│   ├── yolov3
+│       ├── coco.names
+│       ├── yolov3_tf_bs1_fp16.cfg
+│       ├── yolov3_tf_bs_fp16.om
+│       ├── yolov3_tf.pb
+│       ├── aipp_yolov3_416_416.aippconfig
+├── pipeline
+│   ├── test.pipeline
+│   ├── test_only_deepmar.pipeline
+├── evaluate.py
+├── evaluate_for_deepmar.py
+├── License
+├── simgei.ttf
+├── main.py
+├── README.md
+└── run.sh
+```
+
+
+
+## 2 环境依赖
+
+推荐系统为ubantu 18.04，环境依赖软件和版本如下表：
+
+| 软件名称    | 版本   |
+| ----------- | ------ |
+| python      | 3.9.2  |
+| mxVision    | 2.0.4  |
+| pillow      | 8.0.1  |
+| pickle5     | 0.0.11 |
+
+确保环境中正确安装mxVision SDK。
+
+模型转换所需ATC工具环境搭建参考链接：https://gitee.com/ascend/docs-openmind/blob/master/guide/mindx/sdk/tutorials/%E5%8F%82%E8%80%83%E8%B5%84%E6%96%99.md
+
+在编译运行项目前，需要设置环境变量：
+
+- 环境变量介绍
+将${SDK安装路径}替换为自己的SDK安装路径; 
+```python
+export MX_SDK_HOME=${SDK安装路径}/mxVision
+export install_path=/usr/local/Ascend/ascend-toolkit/latest
+export PATH=/usr/local/python3.9.2/bin:${install_path}/atc/ccec_compiler/bin:${install_path}/atc/bin:$PATH
+export PYTHONPATH=${install_path}/atc/python/site-packages:${install_path}/atc/python/site-packages/auto_tune.egg/auto_tune:${install_path}/atc/python/site-packages/schedule_search.egg:$PYTHONPATH
+export LD_LIBRARY_PATH=${install_path}/atc/lib64:$LD_LIBRARY_PATH
+export ASCEND_OPP_PATH=${install_path}/opp
+```
+
+## 3 模型转换
+
+本项目中用到的模型有：yolov3，deeomar两个模型。模型下载链接为：[链接](https://mindx.sdk.obs.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/PedestrianAttributeRecognition/model.zip)
+
+获取yolov3_tf.pb文件，将yolov3的pb文件下载到本地，并将其放在“/model/yolov3”路径下，在终端移至该路径下，执行下面命令：。
+
+```python
+atc --model=./yolov3_tf.pb --framework=3 --output=./yolov3_tf_bs1_fp16 --soc_version=Ascend310 --insert_op_conf=./aipp_yolov3_416_416.aippconfig --input_shape="input/input_data:1,416,416,3" --out_nodes="conv_lbbox/BiasAdd:0;conv_mbbox/BiasAdd:0;conv_sbbox/BiasAdd:0"
+```
+更多的atc模型转换信息可以参考此链接样例：https://gitee.com/ascend/docs-openmind/blob/master/guide/mindx/sdk/tutorials/%E5%8F%82%E8%80%83%E8%B5%84%E6%96%99.md
+
+deepmar模型，对于无aipp设置的离线模型的转换，只需将atc转换时的 --insert_op_conf参数删除即可。
+
+对于deepmar离线模型的aipp的设置，如下:
+
+```python
+aipp_op{
+    aipp_mode:static
+    input_format : YUV420SP_U8
+
+    src_image_size_w : 224
+    src_image_size_h : 224
+
+    crop: false
+    load_start_pos_h : 0
+    load_start_pos_w : 0
+    crop_size_w : 224
+    crop_size_h: 224
+
+    csc_switch : true
+    rbuv_swap_switch : false
+
+    mean_chn_0 : 123
+    mean_chn_1 : 116
+    mean_chn_2 : 103
+    min_chn_0 : 0.675
+    min_chn_1 : 0.28
+    min_chn_2 : 0.53
+    var_reci_chn_0: 0.0171
+    var_reci_chn_1: 0.0175
+    var_reci_chn_2: 0.0174
+
+    matrix_r0c0: 256
+    matrix_r0c1: 0
+    matrix_r0c2: 359
+    matrix_r1c0: 256
+    matrix_r1c1: -88
+    matrix_r1c2: -183
+    matrix_r2c0: 256
+    matrix_r2c1: 454
+    matrix_r2c2: 0
+    input_bias_0: 16
+    input_bias_1: 128
+    input_bias_2: 128}
+```
+下载好deepmar之后，将Deepmar_bs1.onnx文件拷贝到本样例的“model/deepmar”路径下，并在终端中移至该路径下，执行下面命令进行将onnx模型转om模型：
+
+```python
+atc --model=./Deepmar_bs1.onnx --framework=5 --output=./deepmar_bs1_aipp_1 --input_format=NCHW --input_shape="actual_input_1:1,3,224,224" --enable_small_channel=1 --log=error --soc_version=Ascend310  --insert_op_conf=aipp_deepmar.config
+```
+对于无aipp设置的离线模型，可执行下面命令得到：
+
+```python
+atc --model=./Deepmar_bs1.onnx --framework=5 --output=./deepmar_bs1_unaipp --input_format=NCHW --input_shape="actual_input_1:1,3,224,224" --enable_small_channel=1 --log=error --soc_version=Ascend310
+```
+
+
+
+
+## 4 编译与运行
+
+**步骤1** 参照第3章节中的模型转换步骤，将yolov3的离线模型转换成功
+
+**步骤2** 参照第3章节中的模型转换步骤，将deepmar的离线模型转换成功
+
+**步骤3** 将需要进行推理的行人图片放入/dataset/test_image文件夹下，并修改main.py脚本中第91行中的“img_path"为需要推理的图片路径，将test.pipeline中的后处理so文件修改为SDK安装路径。
+
+**步骤4** 执行命令：python main.py,得到final_result.jpg可视化结果
+
+
+
+## 5 精度测试
+
+下载开源数据集Peta，[下载地址](https://mindx.sdk.obs.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/PedestrianAttributeRecognition/data.zip)，
+
+（1）将下载好的文件夹中”./dataset/peta/images/*.png“中的images文件夹放入样例代码中的dataset/image文件夹下；将PETA.mat文件放在样例代码的dataset文件夹下。
+
+（2）将Peta数据集中的png格式图片转为jpg格式图片
+
+​	修改png2img.py脚本中的“filePath”为Peta数据集中的png格式图片的路径，并运行下面命令：
+
+```python
+python png2jpg.py
+```
+
+（3）拆分数据集
+
+修改transform_peta.py脚本中的petaPath为PETA.mat文件的路径，添加save_file参数的文件保存路径以及traintest_split_file的参数路径，即将"样例工程路径"修改为自己的代码运行路径并运行下面命令：
+
+```python
+python dataset/transform_peta.py 
+```
+
+（4）精度测试
+
+修改下面代码：
+
+```python
+    for idx in partition['test'][0]:
+        image.append(dataset['test_image'][idx])
+        label_tmp = np.array(dataset['att'][idx])[dataset['selected_attribute']].tolist()
+        label.append(label_tmp)
+```
+
+依次修改上面代码中"partition\['test'][0]"为"partition\['test'][0]"、"partition\['test'][1]"、"partition\['test'][2]"、"partition\['test'][3]"、"partition\['test'][4]"
+
+并运行下面命令：
+
+```python
+python evaluate_for_deepmar.py
+```
+
+可得到五组测试结果，并将五组测试结果求平均，可得到最终的peta测试集的平均属性识别准确率。
+
+## 6 常见问题
+
+测试样例的像素大小要做在32\*32～8192\*8192之间(其中不包含32*32的像素，图片像素大小必须大于32\*32)，且里边的行人对象像素的高度需在[6,4096]之间，宽度需在[32,4096]之间。
+
+## 7 适用场景
+本样例适用于常见行人所处场景，如街道、红路灯路口、商场等，对于所推理的图片中的行人对象要求尽可能的完整、清晰、无遮挡、无重叠等。
diff --git a/contrib/PedestrianAttributeRecognition/dataset/image_jpg/.keep b/mxVision/mxVision-referenceapps/PedestrianAttributeRecognition/dataset/image/.keep
similarity index 100%
rename from contrib/PedestrianAttributeRecognition/dataset/image_jpg/.keep
rename to mxVision/mxVision-referenceapps/PedestrianAttributeRecognition/dataset/image/.keep
diff --git a/contrib/PedestrianAttributeRecognition/dataset/test_image/.keep b/mxVision/mxVision-referenceapps/PedestrianAttributeRecognition/dataset/image_jpg/.keep
similarity index 100%
rename from contrib/PedestrianAttributeRecognition/dataset/test_image/.keep
rename to mxVision/mxVision-referenceapps/PedestrianAttributeRecognition/dataset/image_jpg/.keep
diff --git a/contrib/PedestrianAttributeRecognition/dataset/png2jpg.py b/mxVision/mxVision-referenceapps/PedestrianAttributeRecognition/dataset/png2jpg.py
similarity index 100%
rename from contrib/PedestrianAttributeRecognition/dataset/png2jpg.py
rename to mxVision/mxVision-referenceapps/PedestrianAttributeRecognition/dataset/png2jpg.py
diff --git a/contrib/PedestrianAttributeRecognition/model/deepmar/.keep b/mxVision/mxVision-referenceapps/PedestrianAttributeRecognition/dataset/test_image/.keep
similarity index 100%
rename from contrib/PedestrianAttributeRecognition/model/deepmar/.keep
rename to mxVision/mxVision-referenceapps/PedestrianAttributeRecognition/dataset/test_image/.keep
diff --git a/contrib/PedestrianAttributeRecognition/dataset/transform_peta.py b/mxVision/mxVision-referenceapps/PedestrianAttributeRecognition/dataset/transform_peta.py
similarity index 100%
rename from contrib/PedestrianAttributeRecognition/dataset/transform_peta.py
rename to mxVision/mxVision-referenceapps/PedestrianAttributeRecognition/dataset/transform_peta.py
diff --git a/contrib/PedestrianAttributeRecognition/evaluate.py b/mxVision/mxVision-referenceapps/PedestrianAttributeRecognition/evaluate.py
similarity index 100%
rename from contrib/PedestrianAttributeRecognition/evaluate.py
rename to mxVision/mxVision-referenceapps/PedestrianAttributeRecognition/evaluate.py
diff --git a/contrib/PedestrianAttributeRecognition/evaluate_for_deepmar.py b/mxVision/mxVision-referenceapps/PedestrianAttributeRecognition/evaluate_for_deepmar.py
similarity index 100%
rename from contrib/PedestrianAttributeRecognition/evaluate_for_deepmar.py
rename to mxVision/mxVision-referenceapps/PedestrianAttributeRecognition/evaluate_for_deepmar.py
diff --git a/contrib/PedestrianAttributeRecognition/main.py b/mxVision/mxVision-referenceapps/PedestrianAttributeRecognition/main.py
similarity index 100%
rename from contrib/PedestrianAttributeRecognition/main.py
rename to mxVision/mxVision-referenceapps/PedestrianAttributeRecognition/main.py
diff --git a/contrib/PedestrianAttributeRecognition/model/yolov3/.keep b/mxVision/mxVision-referenceapps/PedestrianAttributeRecognition/model/deepmar/.keep
similarity index 100%
rename from contrib/PedestrianAttributeRecognition/model/yolov3/.keep
rename to mxVision/mxVision-referenceapps/PedestrianAttributeRecognition/model/deepmar/.keep
diff --git a/contrib/PedestrianAttributeRecognition/model/deepmar/aipp_deepmar.config b/mxVision/mxVision-referenceapps/PedestrianAttributeRecognition/model/deepmar/aipp_deepmar.config
similarity index 100%
rename from contrib/PedestrianAttributeRecognition/model/deepmar/aipp_deepmar.config
rename to mxVision/mxVision-referenceapps/PedestrianAttributeRecognition/model/deepmar/aipp_deepmar.config
diff --git a/contrib/PersonCount/model/.keep b/mxVision/mxVision-referenceapps/PedestrianAttributeRecognition/model/yolov3/.keep
similarity index 100%
rename from contrib/PersonCount/model/.keep
rename to mxVision/mxVision-referenceapps/PedestrianAttributeRecognition/model/yolov3/.keep
diff --git a/contrib/PedestrianAttributeRecognition/model/yolov3/aipp_yolov3_416_416.aippconfig b/mxVision/mxVision-referenceapps/PedestrianAttributeRecognition/model/yolov3/aipp_yolov3_416_416.aippconfig
similarity index 100%
rename from contrib/PedestrianAttributeRecognition/model/yolov3/aipp_yolov3_416_416.aippconfig
rename to mxVision/mxVision-referenceapps/PedestrianAttributeRecognition/model/yolov3/aipp_yolov3_416_416.aippconfig
diff --git a/contrib/PedestrianAttributeRecognition/model/yolov3/coco.names b/mxVision/mxVision-referenceapps/PedestrianAttributeRecognition/model/yolov3/coco.names
similarity index 89%
rename from contrib/PedestrianAttributeRecognition/model/yolov3/coco.names
rename to mxVision/mxVision-referenceapps/PedestrianAttributeRecognition/model/yolov3/coco.names
index e71d1d9ac150203b2374308a93865c1049aa7946..fff3c0e9afd5025f350302156234e8254aad2a8b 100644
--- a/contrib/PedestrianAttributeRecognition/model/yolov3/coco.names
+++ b/mxVision/mxVision-referenceapps/PedestrianAttributeRecognition/model/yolov3/coco.names
@@ -1,82 +1,82 @@
-# This file is originally from https://github.com/pjreddie/darknet/blob/master/data/coco.names
-persopn
-bicycle
-car
-motorbike
-aeroplane
-bus
-train
-truck
-boat
-traffic light
-fire hydrant
-stop sign
-parking meter
-bench
-bird
-cat
-dog
-horse
-sheep
-cow
-elephant
-bear
-zebra
-giraffe
-backpack
-umbrella
-handbag
-tie
-suitcase
-frisbee
-skis
-snowboard
-sports ball
-kite
-baseball bat
-baseball glove
-skateboard
-surfboard
-tennis racket
-bottle
-wine glass
-cup
-fork
-knife
-spoon
-bowl
-banana
-apple
-sandwich
-orange
-broccoli
-carrot
-hot dog
-pizza
-donut
-cake
-chair
-sofa
-pottedplant
-bed
-diningtable
-toilet
-tvmonitor
-laptop
-mouse
-remote
-keyboard
-cell phone
-microwave
-oven
-toaster
-sink
-refrigerator
-book
-clock
-vase
-scissors
-teddy bear
-hair drier
-toothbrush
-
+# This file is originally from https://github.com/pjreddie/darknet/blob/master/data/coco.names
+persopn
+bicycle
+car
+motorbike
+aeroplane
+bus
+train
+truck
+boat
+traffic light
+fire hydrant
+stop sign
+parking meter
+bench
+bird
+cat
+dog
+horse
+sheep
+cow
+elephant
+bear
+zebra
+giraffe
+backpack
+umbrella
+handbag
+tie
+suitcase
+frisbee
+skis
+snowboard
+sports ball
+kite
+baseball bat
+baseball glove
+skateboard
+surfboard
+tennis racket
+bottle
+wine glass
+cup
+fork
+knife
+spoon
+bowl
+banana
+apple
+sandwich
+orange
+broccoli
+carrot
+hot dog
+pizza
+donut
+cake
+chair
+sofa
+pottedplant
+bed
+diningtable
+toilet
+tvmonitor
+laptop
+mouse
+remote
+keyboard
+cell phone
+microwave
+oven
+toaster
+sink
+refrigerator
+book
+clock
+vase
+scissors
+teddy bear
+hair drier
+toothbrush
+
diff --git a/contrib/PedestrianAttributeRecognition/model/yolov3/yolov3_tf_bs1_fp16.cfg b/mxVision/mxVision-referenceapps/PedestrianAttributeRecognition/model/yolov3/yolov3_tf_bs1_fp16.cfg
similarity index 100%
rename from contrib/PedestrianAttributeRecognition/model/yolov3/yolov3_tf_bs1_fp16.cfg
rename to mxVision/mxVision-referenceapps/PedestrianAttributeRecognition/model/yolov3/yolov3_tf_bs1_fp16.cfg
diff --git a/contrib/PedestrianAttributeRecognition/pipeline/test.pipeline b/mxVision/mxVision-referenceapps/PedestrianAttributeRecognition/pipeline/test.pipeline
similarity index 100%
rename from contrib/PedestrianAttributeRecognition/pipeline/test.pipeline
rename to mxVision/mxVision-referenceapps/PedestrianAttributeRecognition/pipeline/test.pipeline
diff --git a/contrib/PedestrianAttributeRecognition/pipeline/test_only_deepmar.pipeline b/mxVision/mxVision-referenceapps/PedestrianAttributeRecognition/pipeline/test_only_deepmar.pipeline
similarity index 100%
rename from contrib/PedestrianAttributeRecognition/pipeline/test_only_deepmar.pipeline
rename to mxVision/mxVision-referenceapps/PedestrianAttributeRecognition/pipeline/test_only_deepmar.pipeline
diff --git a/contrib/PedestrianAttributeRecognition/run.sh b/mxVision/mxVision-referenceapps/PedestrianAttributeRecognition/run.sh
similarity index 100%
rename from contrib/PedestrianAttributeRecognition/run.sh
rename to mxVision/mxVision-referenceapps/PedestrianAttributeRecognition/run.sh
diff --git a/contrib/PersonCount/Plugin1/CMakeLists.txt b/mxVision/mxVision-referenceapps/PersonCount/Plugin1/CMakeLists.txt
similarity index 100%
rename from contrib/PersonCount/Plugin1/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/PersonCount/Plugin1/CMakeLists.txt
diff --git a/contrib/PersonCount/Plugin1/CountPersonPostProcessor.cpp b/mxVision/mxVision-referenceapps/PersonCount/Plugin1/CountPersonPostProcessor.cpp
similarity index 100%
rename from contrib/PersonCount/Plugin1/CountPersonPostProcessor.cpp
rename to mxVision/mxVision-referenceapps/PersonCount/Plugin1/CountPersonPostProcessor.cpp
diff --git a/contrib/PersonCount/Plugin1/CountPersonPostProcessor.h b/mxVision/mxVision-referenceapps/PersonCount/Plugin1/CountPersonPostProcessor.h
similarity index 100%
rename from contrib/PersonCount/Plugin1/CountPersonPostProcessor.h
rename to mxVision/mxVision-referenceapps/PersonCount/Plugin1/CountPersonPostProcessor.h
diff --git a/contrib/PersonCount/README.md b/mxVision/mxVision-referenceapps/PersonCount/README.md
similarity index 98%
rename from contrib/PersonCount/README.md
rename to mxVision/mxVision-referenceapps/PersonCount/README.md
index ccf1f49cf560c393315f78d066b5459e046fa2f4..cd1baf60ea25cb0d6928d52e3bc15d3e81e5e59f 100644
--- a/contrib/PersonCount/README.md
+++ b/mxVision/mxVision-referenceapps/PersonCount/README.md
@@ -1,175 +1,175 @@
-人群密度计数
-
-## 1 介绍
-（项目的概述，包含的功能）
-（项目的主要流程）
-项目的概述：基于MindX SDK，在昇腾平台上，开发端到端人群计数-人群密度估计，输入一幅人群图像，输出图像当中人的计数（估计）的结果。  
-  
-项目的主要流程：  
-（1）输入类型是图片数据（jpg图片序列）,本项目使用的数据集图片来源是https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/PersonCount/data.zip   
-（2）通过调用MindX SDK提供的图像解码接口mxpi_imagedecoder，解码后获取图像数据。  
-（3）然后进行图像尺寸大小变换，调用MindX SDK提供的图像尺寸大小变换接口mxpi_imageresize插件，检测模式的输入图像大小要求高800，宽1408。  
-（4）将尺寸变换后的图像数据输入人群计数模型进行推理,推理使用的caffemodel模型和om模型来源是https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/PersonCount/model.zip     
-（5）模型后处理，调用MindX SDK提供的模型推理插件mxpi_modelinfer，后处理配置文件存放的地址是"models/insert_op.cfg"。然后调用MindX SDK提供的插件mxpi_dataserialize，将stream结果组装成json字符串输出。  
-（6）模型输出经过后处理后，得到人群密度估计图和人群计数估计值。  
-场景限制：  
-  输入的图像应为人群图像，图像中含有多个人，能取得较好的推理效果。  
-### 1.1 支持的产品
-
-可列出项目所用的硬件平台、支持的硬件平台、访问方式等  
-人群计数项目使用的硬件平台为华为海思Ascend310。其中，om模型适配海思Ascend310硬件平台，模型的推理过程也由硬件平台Ascend310完成。  
-  
-### 1.2 支持的版本  
-  
-支持的SDK版本：20.2.0  
-  
-
-### 1.3 软件方案介绍
-
-请先总体介绍项目的方案架构。如果项目设计方案中涉及子系统，请详细描述各子系统功能。如果设计了不同的功能模块，则请详细描述各模块功能。
-项目的方案架构：  
-
-我们将人群计数任务划分为多个子任务，并针对每个子任务设计相应的子系统来实现相应的功能。  
-表1.1 系统方案各子系统功能描述：  
-
-| 序号 | 子系统 | 功能描述     |  
-| ---- | ------ | ------------ |  
-| 1    | 模型转换    | 利用昇腾SDK提供的ATC转换工具将caffemodel转换成om模型|  
-| 2    | 后处理插件 | 获取推理结果，并计算人数，图片数据归一化，ObjectInfo中的mask用来存归一化后的图片数据，ObjectInfo中的classId用来存估计的人数 |  
-
-### 1.4 代码目录结构与说明
-
-本工程名称为 [南开大学]人群密度统计，工程目录如下图所示：  
-│  build.sh  //用于生成后处理共享库的编译命令使用sh build.sh完成编译  
-│  main.py   //对待检测图片进行人群计数的主体程序，包含读入图片数据、模型推理、写热度图等功能特性  
-│  run.sh    //人群计数的运行脚本，运行main.py文件  
-├─accuracy and performance //存放精度与性能测试的代码   
-│  └─test.py  //精度与性能测试的代码   
-│
-├─config     //配置文件夹  
-│  |--insert_op.cfg //生成om模型的config文件  
-│  └─person.names  //label文件  
-│      
-├─img  //存放readme使用到的png图片  
-│  |--tech_arch.png  //1.5节使用的技术实现流程图  
-|  └─err1.png       //章节6使用到的错误报告截图  
-│        
-├─model //转换后的om模型  
-│  └─count_person_8.caffe.om  
-│  
-├─model transformation script
-│  |--insert_op.cfg  //模型转换需要的配置文件
-│  └─ model_conversion.sh //模型转换脚本
-│ 
-├─pipeline //本项目使用的前端是python开发，用到的pipeline配置嵌入到main.py，所以该文件夹为空  
-├─Plugin1  //编译后处理插件所需的源文件，生成的共享库文件存放于build文件夹  
-│  |--CMakeLists.txt  
-│  |--CountPersonPostProcessor.cpp  
-└─ └─ CountPersonPostProcessor.h  
-
-### 1.5 技术实现流程图
-
-（可放入流程图片）  
-![Image text](https://gitee.com/superman418/mindxsdk-referenceapps/raw/master/contrib/PersonCount/img/tech_arch.png)
-
-## 2 环境依赖
-
-请列出环境依赖软件和版本。
-
-推荐系统为ubantu 18.04。
-
-| 软件名称 | 版本   |
-| -------- | ------ |
-| MindX SDK mxManufacture    |    5.0.0    |
-| ascend-toolkit             |    7.0.0    |
-
-在编译运行项目前，需要设置环境变量：
-执行 
-```
-. ${MX_SDK_HOME}/set_env.sh
-```
-${MX_SDK_HOME}为mxVision SDK安装路径。
-
-或者手动导入环境变量
-```
-MX_SDK_HOME="~/mxVision"  
-LD_LIBRARY_PATH=\\${MX_SDK_HOME}/lib:\\${MX_SDK_HOME}/opensource/lib:\\${MX_SDK_HOME}/opensource/lib64:/usr/local/Ascend/ascend-toolkit/latest/acllib/lib64:/usr/local/Ascend/driver/lib64:/usr/local/Ascend/ascend-toolkit:\\${LD_LIBRARY_PATH}  
-PYTHONPATH=\\${MX_SDK_HOME}/python:\\${PYTHONPATH}  
-
-install_path=/usr/local/Ascend/ascend-toolkit/latest
-PATH=/usr/local/python3.9.2/bin:\\${install_path}/atc/ccec_compiler/bin:\\${install_path}/atc/bin:\\$PATH  
-PYTHONPATH=\\${install_path}/atc/python/site-packages:\\${install_path}/atc/python/site-packages/auto_tune.egg/auto_tune:\\${install_path}/atc/python/site-packages/schedule_search.egg  
-LD_LIBRARY_PATH=\\${install_path}/atc/lib64:\\$LD_LIBRARY_PATH  
-ASCEND_OPP_PATH=\\${install_path}/opp
-```  
-
-- 环境变量介绍  
-MX_SDK_HOME指明MindX SDK mxVision的根安装路径，用于包含MindX SDK提供的所有库和头文件。  
-LD_LIBRARY_PATH提供了MindX SDK已开发的插件和相关的库信息。  
-install_path指明ascend-toolkit的安装路径。  
-PATH变量中添加了python的执行路径和atc转换工具的执行路径。  
-LD_LIBRARY_PATH添加了ascend-toolkit和MindX SDK提供的库目录路径。  
-ASCEND_OPP_PATH指明atc转换工具需要的目录。  
-
-具体执行命令
-```
-export MX_SDK_HOME="~/mxVision"  
-export LD_LIBRARY_PATH=\\${MX_SDK_HOME}/lib:\\${MX_SDK_HOME}/opensource/lib:\\${MX_SDK_HOME}/opensource/lib64:/usr/local/Ascend/ascend-toolkit/latest/acllib/lib64:/usr/local/Ascend/driver/lib64:/usr/local/Ascend/ascend-toolkit:\\${LD_LIBRARY_PATH}  
-
-export install_path=/usr/local/Ascend/ascend-toolkit/latest  
-export PATH=/usr/local/python3.9.2/bin:\\${install_path}/atc/ccec_compiler/bin:\\${install_path}/atc/bin:\\$PATH  
-export PYTHONPATH=\\${install_path}/atc/python/site-packages:\\${install_path}/atc/python/site-packages/auto_tune.egg/auto_tune:\\${install_path}/atc/python/site-packages/schedule_search.egg  
-export LD_LIBRARY_PATH=\\${install_path}/atc/lib64:\\$LD_LIBRARY_PATH  
-export ASCEND_OPP_PATH=\\${install_path}/opp    
-```
-
-## 依赖安装
-
-安装MindX SDK mxVision：
-```
-chmod u+x Ascend-mindxsdk-mxVision_XXX.run
-./Ascend-mindxsdk-mxVision_XXX.run
-```
-ascend-toolkit:
-从/usr/local/Ascend/ascend-toolkit/latest/路径获取
-
-## 编译与运行
-（描述项目安装运行的全部步骤，，如果不涉及个人路径，请直接列出具体执行命令）
-
-示例步骤如下：
-**步骤1** （修改相应文件）修改Plugin1目录下的CMakeLists.txt中PROJECT_SOURCE_DIR变量，该变量指向MindX SDK mxVision的根安装路径。修改main.py中的DATASET_PATH变量，该变量指向待检测的图片路径。修改main.py中gt_path变量，改变了指向待检测图片的groundtruth.此外，如果想要得到pipeline中各个插件的具体运行时间，
-可以修改mxVisionSDK的sdk.conf文件，使得enable_ps变量为true.
-
-**步骤2** （设置环境变量）按照第二章节设置环境变量所需的具体执行指令执行即可。
-
-**步骤3** （执行编译的步骤）首先通过运行build.sh脚本文件生成后处理使用的共享库如sh build.sh，修改构建后的共享库libcountpersonpostprocess.so权限为440。然后使用模型转换命令将caffe模型转化为om模型待使用，具体命令为atc --input_shape="blob1:8,3,800,1408" --weight="model/count_person.caffe.caffemodel" --input_format=NCHW --output="model/count_person_8.caffe" --soc_version=Ascend310 --insert_op_conf=model/insert_op.cfg --framework=0 --model="model/count_person.caffe.prototxt"。此外，我们已经在文件夹model transformation script提供了模型转换脚本将脚本文件复制到主目录即可运行.
-
-**步骤4** （运行及输出结果）直接运行run.sh即可，生成的热度图保存在当前目录的heat_map文件夹下（需要手动创建heat_map目录），并且每张热度图的命名以原图片名称为前缀以heatmap为后缀。此外，我们还在文件夹accuracy and performance code提供了精度与性能测试代码，将test.py和test.sh拷贝到主目录中然后执行sh test.sh即可运行精度与性能测试代码。
-
-
-
-
-## 5 软件依赖说明
-
-如果涉及第三方软件依赖，请详细列出。
-
-| 依赖软件 | 版本  | 说明                     |
-| -------- | ----- | ------------------------ |
-| cmake     | 3.10.2 | 用于编译并生成后处理插件 |
-| python    | 3.9.2     |  用于编译用户程序如main.py   |
-
-
-
-## 6 常见问题
-
-请按照问题重要程度，详细列出可能要到的问题，和解决方法。
-
-### 6.1 batch问题
-
-**问题描述：**
-在使用batch机制时，模型需要的数据维度和输入到流中的数据维度不匹配。该问题造成的主要原因是因为老版的MindX_SDK不提供自动组batch功能。程序中使用多次senddata函数，每次send一张图片到流中，并假设tensorinfer插件能够自动组batch然后进行batch模型的推理。
-截图或报错信息：
-![err information](https://gitee.com/superman418/mindxsdk-referenceapps/raw/master/contrib/PersonCount/img/err1.png)
-**解决方案：**
-
+人群密度计数
+
+## 1 介绍
+（项目的概述，包含的功能）
+（项目的主要流程）
+项目的概述：基于MindX SDK，在昇腾平台上，开发端到端人群计数-人群密度估计，输入一幅人群图像，输出图像当中人的计数（估计）的结果。  
+  
+项目的主要流程：  
+（1）输入类型是图片数据（jpg图片序列）,本项目使用的数据集图片来源是https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/PersonCount/data.zip   
+（2）通过调用MindX SDK提供的图像解码接口mxpi_imagedecoder，解码后获取图像数据。  
+（3）然后进行图像尺寸大小变换，调用MindX SDK提供的图像尺寸大小变换接口mxpi_imageresize插件，检测模式的输入图像大小要求高800，宽1408。  
+（4）将尺寸变换后的图像数据输入人群计数模型进行推理,推理使用的caffemodel模型和om模型来源是https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/PersonCount/model.zip     
+（5）模型后处理，调用MindX SDK提供的模型推理插件mxpi_modelinfer，后处理配置文件存放的地址是"models/insert_op.cfg"。然后调用MindX SDK提供的插件mxpi_dataserialize，将stream结果组装成json字符串输出。  
+（6）模型输出经过后处理后，得到人群密度估计图和人群计数估计值。  
+场景限制：  
+  输入的图像应为人群图像，图像中含有多个人，能取得较好的推理效果。  
+### 1.1 支持的产品
+
+可列出项目所用的硬件平台、支持的硬件平台、访问方式等  
+人群计数项目使用的硬件平台为华为海思Ascend310。其中，om模型适配海思Ascend310硬件平台，模型的推理过程也由硬件平台Ascend310完成。  
+  
+### 1.2 支持的版本  
+  
+支持的SDK版本：20.2.0  
+  
+
+### 1.3 软件方案介绍
+
+请先总体介绍项目的方案架构。如果项目设计方案中涉及子系统，请详细描述各子系统功能。如果设计了不同的功能模块，则请详细描述各模块功能。
+项目的方案架构：  
+
+我们将人群计数任务划分为多个子任务，并针对每个子任务设计相应的子系统来实现相应的功能。  
+表1.1 系统方案各子系统功能描述：  
+
+| 序号 | 子系统 | 功能描述     |  
+| ---- | ------ | ------------ |  
+| 1    | 模型转换    | 利用昇腾SDK提供的ATC转换工具将caffemodel转换成om模型|  
+| 2    | 后处理插件 | 获取推理结果，并计算人数，图片数据归一化，ObjectInfo中的mask用来存归一化后的图片数据，ObjectInfo中的classId用来存估计的人数 |  
+
+### 1.4 代码目录结构与说明
+
+本工程名称为 [南开大学]人群密度统计，工程目录如下图所示：  
+│  build.sh  //用于生成后处理共享库的编译命令使用sh build.sh完成编译  
+│  main.py   //对待检测图片进行人群计数的主体程序，包含读入图片数据、模型推理、写热度图等功能特性  
+│  run.sh    //人群计数的运行脚本，运行main.py文件  
+├─accuracy and performance //存放精度与性能测试的代码   
+│  └─test.py  //精度与性能测试的代码   
+│
+├─config     //配置文件夹  
+│  |--insert_op.cfg //生成om模型的config文件  
+│  └─person.names  //label文件  
+│      
+├─img  //存放readme使用到的png图片  
+│  |--tech_arch.png  //1.5节使用的技术实现流程图  
+|  └─err1.png       //章节6使用到的错误报告截图  
+│        
+├─model //转换后的om模型  
+│  └─count_person_8.caffe.om  
+│  
+├─model transformation script
+│  |--insert_op.cfg  //模型转换需要的配置文件
+│  └─ model_conversion.sh //模型转换脚本
+│ 
+├─pipeline //本项目使用的前端是python开发，用到的pipeline配置嵌入到main.py，所以该文件夹为空  
+├─Plugin1  //编译后处理插件所需的源文件，生成的共享库文件存放于build文件夹  
+│  |--CMakeLists.txt  
+│  |--CountPersonPostProcessor.cpp  
+└─ └─ CountPersonPostProcessor.h  
+
+### 1.5 技术实现流程图
+
+（可放入流程图片）  
+![Image text](https://gitee.com/superman418/mindxsdk-referenceapps/raw/master/contrib/PersonCount/img/tech_arch.png)
+
+## 2 环境依赖
+
+请列出环境依赖软件和版本。
+
+推荐系统为ubantu 18.04。
+
+| 软件名称 | 版本   |
+| -------- | ------ |
+| MindX SDK mxManufacture    |    5.0.0    |
+| ascend-toolkit             |    7.0.0    |
+
+在编译运行项目前，需要设置环境变量：
+执行 
+```
+. ${MX_SDK_HOME}/set_env.sh
+```
+${MX_SDK_HOME}为mxVision SDK安装路径。
+
+或者手动导入环境变量
+```
+MX_SDK_HOME="~/mxVision"  
+LD_LIBRARY_PATH=\\${MX_SDK_HOME}/lib:\\${MX_SDK_HOME}/opensource/lib:\\${MX_SDK_HOME}/opensource/lib64:/usr/local/Ascend/ascend-toolkit/latest/acllib/lib64:/usr/local/Ascend/driver/lib64:/usr/local/Ascend/ascend-toolkit:\\${LD_LIBRARY_PATH}  
+PYTHONPATH=\\${MX_SDK_HOME}/python:\\${PYTHONPATH}  
+
+install_path=/usr/local/Ascend/ascend-toolkit/latest
+PATH=/usr/local/python3.9.2/bin:\\${install_path}/atc/ccec_compiler/bin:\\${install_path}/atc/bin:\\$PATH  
+PYTHONPATH=\\${install_path}/atc/python/site-packages:\\${install_path}/atc/python/site-packages/auto_tune.egg/auto_tune:\\${install_path}/atc/python/site-packages/schedule_search.egg  
+LD_LIBRARY_PATH=\\${install_path}/atc/lib64:\\$LD_LIBRARY_PATH  
+ASCEND_OPP_PATH=\\${install_path}/opp
+```  
+
+- 环境变量介绍  
+MX_SDK_HOME指明MindX SDK mxVision的根安装路径，用于包含MindX SDK提供的所有库和头文件。  
+LD_LIBRARY_PATH提供了MindX SDK已开发的插件和相关的库信息。  
+install_path指明ascend-toolkit的安装路径。  
+PATH变量中添加了python的执行路径和atc转换工具的执行路径。  
+LD_LIBRARY_PATH添加了ascend-toolkit和MindX SDK提供的库目录路径。  
+ASCEND_OPP_PATH指明atc转换工具需要的目录。  
+
+具体执行命令
+```
+export MX_SDK_HOME="~/mxVision"  
+export LD_LIBRARY_PATH=\\${MX_SDK_HOME}/lib:\\${MX_SDK_HOME}/opensource/lib:\\${MX_SDK_HOME}/opensource/lib64:/usr/local/Ascend/ascend-toolkit/latest/acllib/lib64:/usr/local/Ascend/driver/lib64:/usr/local/Ascend/ascend-toolkit:\\${LD_LIBRARY_PATH}  
+
+export install_path=/usr/local/Ascend/ascend-toolkit/latest  
+export PATH=/usr/local/python3.9.2/bin:\\${install_path}/atc/ccec_compiler/bin:\\${install_path}/atc/bin:\\$PATH  
+export PYTHONPATH=\\${install_path}/atc/python/site-packages:\\${install_path}/atc/python/site-packages/auto_tune.egg/auto_tune:\\${install_path}/atc/python/site-packages/schedule_search.egg  
+export LD_LIBRARY_PATH=\\${install_path}/atc/lib64:\\$LD_LIBRARY_PATH  
+export ASCEND_OPP_PATH=\\${install_path}/opp    
+```
+
+## 依赖安装
+
+安装MindX SDK mxVision：
+```
+chmod u+x Ascend-mindxsdk-mxVision_XXX.run
+./Ascend-mindxsdk-mxVision_XXX.run
+```
+ascend-toolkit:
+从/usr/local/Ascend/ascend-toolkit/latest/路径获取
+
+## 编译与运行
+（描述项目安装运行的全部步骤，，如果不涉及个人路径，请直接列出具体执行命令）
+
+示例步骤如下：
+**步骤1** （修改相应文件）修改Plugin1目录下的CMakeLists.txt中PROJECT_SOURCE_DIR变量，该变量指向MindX SDK mxVision的根安装路径。修改main.py中的DATASET_PATH变量，该变量指向待检测的图片路径。修改main.py中gt_path变量，改变了指向待检测图片的groundtruth.此外，如果想要得到pipeline中各个插件的具体运行时间，
+可以修改mxVisionSDK的sdk.conf文件，使得enable_ps变量为true.
+
+**步骤2** （设置环境变量）按照第二章节设置环境变量所需的具体执行指令执行即可。
+
+**步骤3** （执行编译的步骤）首先通过运行build.sh脚本文件生成后处理使用的共享库如sh build.sh，修改构建后的共享库libcountpersonpostprocess.so权限为440。然后使用模型转换命令将caffe模型转化为om模型待使用，具体命令为atc --input_shape="blob1:8,3,800,1408" --weight="model/count_person.caffe.caffemodel" --input_format=NCHW --output="model/count_person_8.caffe" --soc_version=Ascend310 --insert_op_conf=model/insert_op.cfg --framework=0 --model="model/count_person.caffe.prototxt"。此外，我们已经在文件夹model transformation script提供了模型转换脚本将脚本文件复制到主目录即可运行.
+
+**步骤4** （运行及输出结果）直接运行run.sh即可，生成的热度图保存在当前目录的heat_map文件夹下（需要手动创建heat_map目录），并且每张热度图的命名以原图片名称为前缀以heatmap为后缀。此外，我们还在文件夹accuracy and performance code提供了精度与性能测试代码，将test.py和test.sh拷贝到主目录中然后执行sh test.sh即可运行精度与性能测试代码。
+
+
+
+
+## 5 软件依赖说明
+
+如果涉及第三方软件依赖，请详细列出。
+
+| 依赖软件 | 版本  | 说明                     |
+| -------- | ----- | ------------------------ |
+| cmake     | 3.10.2 | 用于编译并生成后处理插件 |
+| python    | 3.9.2     |  用于编译用户程序如main.py   |
+
+
+
+## 6 常见问题
+
+请按照问题重要程度，详细列出可能要到的问题，和解决方法。
+
+### 6.1 batch问题
+
+**问题描述：**
+在使用batch机制时，模型需要的数据维度和输入到流中的数据维度不匹配。该问题造成的主要原因是因为老版的MindX_SDK不提供自动组batch功能。程序中使用多次senddata函数，每次send一张图片到流中，并假设tensorinfer插件能够自动组batch然后进行batch模型的推理。
+截图或报错信息：
+![err information](https://gitee.com/superman418/mindxsdk-referenceapps/raw/master/contrib/PersonCount/img/err1.png)
+**解决方案：**
+
 新版Ascend-mindxsdk-mxvision_2.0.4_linux-aarch64中的tensorinfer插件能够自动组batch然后进行batch模型的推理，可以解决该问题。
\ No newline at end of file
diff --git a/contrib/PersonCount/accuracy and performance code/test.py b/mxVision/mxVision-referenceapps/PersonCount/accuracy and performance code/test.py
similarity index 97%
rename from contrib/PersonCount/accuracy and performance code/test.py
rename to mxVision/mxVision-referenceapps/PersonCount/accuracy and performance code/test.py
index b82dd67ec4a253c72a28c12fe426a5a58851cc5e..16e5d1d1580faa11cbdaa00930f2cf6d4a42bc4a 100644
--- a/contrib/PersonCount/accuracy and performance code/test.py	
+++ b/mxVision/mxVision-referenceapps/PersonCount/accuracy and performance code/test.py	
@@ -1,176 +1,176 @@
-#!/usr/bin/env python
-# coding=utf-8
-
-"""
-Copyright(C) Huawei Technologies Co.,Ltd. 2012-2021 All rights reserved.
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
-    http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License.
-"""
-
-import json
-import os
-import cv2
-import scipy.io as sio
-import numpy as np
-import math
-from StreamManagerApi import StreamManagerApi, MxDataInput, StringVector
-import MxpiDataType_pb2 as MxpiDataType
-import time
-
-if __name__ == '__main__':
-    # create streams
-    streamManagerApi = StreamManagerApi()
-    ret = streamManagerApi.InitManager()
-    if ret != 0:
-        print("Failed to init Stream manager, ret=%s" % str(ret))
-        exit()
-    #pipeline config include several types of plugins.
-    #input plugin
-    #multi-media picture preprocess plugin
-    #tensorinfer plugin
-    #postprocess plugin
-    #output plugin
-    pipeline = {
-        "detection": {
-            "stream_config": {
-                "deviceId": "0"
-            },
-            "appsrc0": {
-                "props": {
-                    "blocksize": "409600"
-                },
-                "factory": "appsrc",
-                "next": "mxpi_imagedecoder0"
-            },
-            "mxpi_imagedecoder0": {
-                "factory": "mxpi_imagedecoder",
-                "next": "mxpi_imageresize0"
-            },
-            "mxpi_imageresize0": {
-                "props": {
-                  "resizeHeight":"800",
-                  "resizeWidth":"1408",
-                  "dataSource":"mxpi_imagedecoder0"
-                },
-                "factory": "mxpi_imageresize",
-                "next": "mxpi_tensorinfer0"
-            },
-            "mxpi_tensorinfer0": {
-                "props": {
-                    "dataSource":"mxpi_imageresize0",
-                    "modelPath": "model/count_person_8.caffe.om",
-                    "waitingTime":"500",
-                },
-                "factory": "mxpi_tensorinfer",
-                "next": "mxpi_objectpostprocessor0"
-            },
-            "mxpi_objectpostprocessor0": {
-                "props": {
-                        "dataSource": "mxpi_tensorinfer0",
-                        "funcLanguage":"c++",
-                        "postProcessConfigPath": "config/insert_op.cfg",
-                        "labelPath": "config/person.names",
-                        "postProcessLibPath": "Plugin1/build/libcountpersonpostprocess.so",
-                },
-                "factory": "mxpi_objectpostprocessor",
-                "next": "appsink0"
-            },
-            "appsink0": {
-                "props": {
-                    "blocksize": "40960000"
-                },
-                "factory": "appsink"
-            }
-        }
-    }
-    #transfer pipeline string into json format
-    pipelineStr = json.dumps(pipeline).encode()
-    ret = streamManagerApi.CreateMultipleStreams(pipelineStr)
-    if ret != 0:
-        print("Failed to create Stream, ret=%s" % str(ret))
-        exit()
-    # Construct the input of the stream
-    dataInput = MxDataInput()
-    #dataset path needs to fixde as specific path
-    Dataset_Path = '../tools/python_count/ShanghaiTech/part_B_images/'
-    namelist = os.listdir(Dataset_Path)
-    person_num_list=[]
-    gt_list=[]
-    #start time
-    time_start=time.time()
-    uniqueIds=[]
-    streamName = b'detection'
-    #the shape of output image and output heat map
-    image_H=800
-    image_W=1408
-    #the pixel position of the person number text embedded in the heat map
-    position=300
-    #infer all the picture in target Dataset_Path directory
-    for i in range(1, len(namelist) + 1):
-        with open(Dataset_Path + 'IMG_' + str(i) + '.jpg', 'rb') as f:
-            data = f.read()
-        inPluginId = i
-        dataInput.data = data
-        # Inputs data to a specified stream based on streamName.
-        # continuous datasend is used to support batch mechanism
-        uniqueId = streamManagerApi.SendData(streamName, 0, dataInput)
-        if uniqueId < 0:
-            print("Failed to send data to stream.")
-            exit()
-        uniqueIds.append(uniqueId)
-    key = b"mxpi_objectpostprocessor0"
-    keyVec = StringVector()
-    keyVec.push_back(key)
-    for i in range(1, len(namelist)+1):
-        # Obtain the inference result by specifying streamName and uniqueId.
-        infer_result = streamManagerApi.GetProtobuf(streamName, 0, keyVec)
-        objectList = MxpiDataType.MxpiObjectList()
-        objectList.ParseFromString(infer_result[0].messageBuf)
-        results = objectList.objectVec[0]
-        #the persor num is stored in classId attribution.
-        person_num=results.classVec[0].classId
-        person_num_list.append(person_num)
-        #output heatmap is stored in mask attribution.
-        data=results.imageMask.dataStr
-        data=np.frombuffer(data, dtype=np.uint8)
-        #the data is reshape as origin image size
-        data=data.reshape((image_H, image_W))
-        image=cv2.applyColorMap(data, cv2.COLORMAP_JET)
-        #person num txt is embedded into heatmap.
-        text="Count: " + str(person_num)
-        RGB=(0, 0, 255)
-        cv2.putText(image, text, (position, position), cv2.FONT_HERSHEY_SIMPLEX, 4, RGB, 4)
-        cv2.imwrite("./heat_map/" + str(i) + "_heatmap.jpg", image)
-    #end time
-    time_end = time.time()
-    print("total image number:", len(namelist))
-    print('time cost', time_end - time_start, 's')
-    for i in range(1, len(namelist)+1):
-        #load ground truth information
-        #gt_num represents the person number of ground truth.
-        #the ground truth needs to be fixed as specific path.
-        gt_path="../tools/python_count/ShanghaiTech/part_B_test/GT_IMG_" + str(i) + ".mat"
-        data1=sio.loadmat(gt_path)
-        gt_num=int(data1['image_info'][0][0][0][0][1][0][0])
-        gt_list.append(gt_num)
-    MAE = 0
-    MSE = 0
-    #computing mse of prediction value and ground truth
-    for i in range(len(namelist)):
-        MAE += abs(person_num_list[i] - gt_list[i])
-        MSE += (person_num_list[i] - gt_list[i]) ** 2
-    MAE /= len(namelist)
-    MSE = (MSE / len(namelist)) ** 0.5
-    print("MAE:", MAE, "\tMSE:", MSE)
-    # destroy streams
-    streamManagerApi.DestroyAllStreams()
+#!/usr/bin/env python
+# coding=utf-8
+
+"""
+Copyright(C) Huawei Technologies Co.,Ltd. 2012-2021 All rights reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+"""
+
+import json
+import os
+import cv2
+import scipy.io as sio
+import numpy as np
+import math
+from StreamManagerApi import StreamManagerApi, MxDataInput, StringVector
+import MxpiDataType_pb2 as MxpiDataType
+import time
+
+if __name__ == '__main__':
+    # create streams
+    streamManagerApi = StreamManagerApi()
+    ret = streamManagerApi.InitManager()
+    if ret != 0:
+        print("Failed to init Stream manager, ret=%s" % str(ret))
+        exit()
+    #pipeline config include several types of plugins.
+    #input plugin
+    #multi-media picture preprocess plugin
+    #tensorinfer plugin
+    #postprocess plugin
+    #output plugin
+    pipeline = {
+        "detection": {
+            "stream_config": {
+                "deviceId": "0"
+            },
+            "appsrc0": {
+                "props": {
+                    "blocksize": "409600"
+                },
+                "factory": "appsrc",
+                "next": "mxpi_imagedecoder0"
+            },
+            "mxpi_imagedecoder0": {
+                "factory": "mxpi_imagedecoder",
+                "next": "mxpi_imageresize0"
+            },
+            "mxpi_imageresize0": {
+                "props": {
+                  "resizeHeight":"800",
+                  "resizeWidth":"1408",
+                  "dataSource":"mxpi_imagedecoder0"
+                },
+                "factory": "mxpi_imageresize",
+                "next": "mxpi_tensorinfer0"
+            },
+            "mxpi_tensorinfer0": {
+                "props": {
+                    "dataSource":"mxpi_imageresize0",
+                    "modelPath": "model/count_person_8.caffe.om",
+                    "waitingTime":"500",
+                },
+                "factory": "mxpi_tensorinfer",
+                "next": "mxpi_objectpostprocessor0"
+            },
+            "mxpi_objectpostprocessor0": {
+                "props": {
+                        "dataSource": "mxpi_tensorinfer0",
+                        "funcLanguage":"c++",
+                        "postProcessConfigPath": "config/insert_op.cfg",
+                        "labelPath": "config/person.names",
+                        "postProcessLibPath": "Plugin1/build/libcountpersonpostprocess.so",
+                },
+                "factory": "mxpi_objectpostprocessor",
+                "next": "appsink0"
+            },
+            "appsink0": {
+                "props": {
+                    "blocksize": "40960000"
+                },
+                "factory": "appsink"
+            }
+        }
+    }
+    #transfer pipeline string into json format
+    pipelineStr = json.dumps(pipeline).encode()
+    ret = streamManagerApi.CreateMultipleStreams(pipelineStr)
+    if ret != 0:
+        print("Failed to create Stream, ret=%s" % str(ret))
+        exit()
+    # Construct the input of the stream
+    dataInput = MxDataInput()
+    #dataset path needs to fixde as specific path
+    Dataset_Path = '../tools/python_count/ShanghaiTech/part_B_images/'
+    namelist = os.listdir(Dataset_Path)
+    person_num_list=[]
+    gt_list=[]
+    #start time
+    time_start=time.time()
+    uniqueIds=[]
+    streamName = b'detection'
+    #the shape of output image and output heat map
+    image_H=800
+    image_W=1408
+    #the pixel position of the person number text embedded in the heat map
+    position=300
+    #infer all the picture in target Dataset_Path directory
+    for i in range(1, len(namelist) + 1):
+        with open(Dataset_Path + 'IMG_' + str(i) + '.jpg', 'rb') as f:
+            data = f.read()
+        inPluginId = i
+        dataInput.data = data
+        # Inputs data to a specified stream based on streamName.
+        # continuous datasend is used to support batch mechanism
+        uniqueId = streamManagerApi.SendData(streamName, 0, dataInput)
+        if uniqueId < 0:
+            print("Failed to send data to stream.")
+            exit()
+        uniqueIds.append(uniqueId)
+    key = b"mxpi_objectpostprocessor0"
+    keyVec = StringVector()
+    keyVec.push_back(key)
+    for i in range(1, len(namelist)+1):
+        # Obtain the inference result by specifying streamName and uniqueId.
+        infer_result = streamManagerApi.GetProtobuf(streamName, 0, keyVec)
+        objectList = MxpiDataType.MxpiObjectList()
+        objectList.ParseFromString(infer_result[0].messageBuf)
+        results = objectList.objectVec[0]
+        #the persor num is stored in classId attribution.
+        person_num=results.classVec[0].classId
+        person_num_list.append(person_num)
+        #output heatmap is stored in mask attribution.
+        data=results.imageMask.dataStr
+        data=np.frombuffer(data, dtype=np.uint8)
+        #the data is reshape as origin image size
+        data=data.reshape((image_H, image_W))
+        image=cv2.applyColorMap(data, cv2.COLORMAP_JET)
+        #person num txt is embedded into heatmap.
+        text="Count: " + str(person_num)
+        RGB=(0, 0, 255)
+        cv2.putText(image, text, (position, position), cv2.FONT_HERSHEY_SIMPLEX, 4, RGB, 4)
+        cv2.imwrite("./heat_map/" + str(i) + "_heatmap.jpg", image)
+    #end time
+    time_end = time.time()
+    print("total image number:", len(namelist))
+    print('time cost', time_end - time_start, 's')
+    for i in range(1, len(namelist)+1):
+        #load ground truth information
+        #gt_num represents the person number of ground truth.
+        #the ground truth needs to be fixed as specific path.
+        gt_path="../tools/python_count/ShanghaiTech/part_B_test/GT_IMG_" + str(i) + ".mat"
+        data1=sio.loadmat(gt_path)
+        gt_num=int(data1['image_info'][0][0][0][0][1][0][0])
+        gt_list.append(gt_num)
+    MAE = 0
+    MSE = 0
+    #computing mse of prediction value and ground truth
+    for i in range(len(namelist)):
+        MAE += abs(person_num_list[i] - gt_list[i])
+        MSE += (person_num_list[i] - gt_list[i]) ** 2
+    MAE /= len(namelist)
+    MSE = (MSE / len(namelist)) ** 0.5
+    print("MAE:", MAE, "\tMSE:", MSE)
+    # destroy streams
+    streamManagerApi.DestroyAllStreams()
diff --git a/contrib/PersonCount/accuracy and performance code/test.sh b/mxVision/mxVision-referenceapps/PersonCount/accuracy and performance code/test.sh
similarity index 100%
rename from contrib/PersonCount/accuracy and performance code/test.sh
rename to mxVision/mxVision-referenceapps/PersonCount/accuracy and performance code/test.sh
diff --git a/contrib/PersonCount/build.sh b/mxVision/mxVision-referenceapps/PersonCount/build.sh
similarity index 100%
rename from contrib/PersonCount/build.sh
rename to mxVision/mxVision-referenceapps/PersonCount/build.sh
diff --git a/contrib/PersonCount/config/insert_op.cfg b/mxVision/mxVision-referenceapps/PersonCount/config/insert_op.cfg
similarity index 100%
rename from contrib/PersonCount/config/insert_op.cfg
rename to mxVision/mxVision-referenceapps/PersonCount/config/insert_op.cfg
diff --git a/contrib/PersonCount/config/person.names b/mxVision/mxVision-referenceapps/PersonCount/config/person.names
similarity index 100%
rename from contrib/PersonCount/config/person.names
rename to mxVision/mxVision-referenceapps/PersonCount/config/person.names
diff --git a/contrib/PersonCount/img/err1.png b/mxVision/mxVision-referenceapps/PersonCount/img/err1.png
similarity index 100%
rename from contrib/PersonCount/img/err1.png
rename to mxVision/mxVision-referenceapps/PersonCount/img/err1.png
diff --git a/contrib/PersonCount/img/tech_arch.png b/mxVision/mxVision-referenceapps/PersonCount/img/tech_arch.png
similarity index 100%
rename from contrib/PersonCount/img/tech_arch.png
rename to mxVision/mxVision-referenceapps/PersonCount/img/tech_arch.png
diff --git a/contrib/PersonCount/main.py b/mxVision/mxVision-referenceapps/PersonCount/main.py
similarity index 100%
rename from contrib/PersonCount/main.py
rename to mxVision/mxVision-referenceapps/PersonCount/main.py
diff --git a/contrib/PersonCount/model transformation script/insert_op.cfg b/mxVision/mxVision-referenceapps/PersonCount/model transformation script/insert_op.cfg
similarity index 100%
rename from contrib/PersonCount/model transformation script/insert_op.cfg
rename to mxVision/mxVision-referenceapps/PersonCount/model transformation script/insert_op.cfg
diff --git a/contrib/PersonCount/model transformation script/model_conversion.sh b/mxVision/mxVision-referenceapps/PersonCount/model transformation script/model_conversion.sh
similarity index 100%
rename from contrib/PersonCount/model transformation script/model_conversion.sh
rename to mxVision/mxVision-referenceapps/PersonCount/model transformation script/model_conversion.sh
diff --git a/contrib/ReIDv2/data/.keep b/mxVision/mxVision-referenceapps/PersonCount/model/.keep
similarity index 100%
rename from contrib/ReIDv2/data/.keep
rename to mxVision/mxVision-referenceapps/PersonCount/model/.keep
diff --git a/contrib/PersonCount/pipeline/test.pipeline b/mxVision/mxVision-referenceapps/PersonCount/pipeline/test.pipeline
similarity index 100%
rename from contrib/PersonCount/pipeline/test.pipeline
rename to mxVision/mxVision-referenceapps/PersonCount/pipeline/test.pipeline
diff --git a/contrib/PersonCount/run.sh b/mxVision/mxVision-referenceapps/PersonCount/run.sh
similarity index 100%
rename from contrib/PersonCount/run.sh
rename to mxVision/mxVision-referenceapps/PersonCount/run.sh
diff --git a/contrib/PicoDet/PicodetPostProcess/CMakeLists.txt b/mxVision/mxVision-referenceapps/PicoDet/PicodetPostProcess/CMakeLists.txt
similarity index 100%
rename from contrib/PicoDet/PicodetPostProcess/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/PicoDet/PicodetPostProcess/CMakeLists.txt
diff --git a/contrib/PicoDet/PicodetPostProcess/PicodetPostProcess.cpp b/mxVision/mxVision-referenceapps/PicoDet/PicodetPostProcess/PicodetPostProcess.cpp
similarity index 100%
rename from contrib/PicoDet/PicodetPostProcess/PicodetPostProcess.cpp
rename to mxVision/mxVision-referenceapps/PicoDet/PicodetPostProcess/PicodetPostProcess.cpp
diff --git a/contrib/PicoDet/PicodetPostProcess/PicodetPostProcess.h b/mxVision/mxVision-referenceapps/PicoDet/PicodetPostProcess/PicodetPostProcess.h
similarity index 100%
rename from contrib/PicoDet/PicodetPostProcess/PicodetPostProcess.h
rename to mxVision/mxVision-referenceapps/PicoDet/PicodetPostProcess/PicodetPostProcess.h
diff --git a/contrib/PicoDet/PicodetPostProcess/build.sh b/mxVision/mxVision-referenceapps/PicoDet/PicodetPostProcess/build.sh
similarity index 100%
rename from contrib/PicoDet/PicodetPostProcess/build.sh
rename to mxVision/mxVision-referenceapps/PicoDet/PicodetPostProcess/build.sh
diff --git a/contrib/PicoDet/README.md b/mxVision/mxVision-referenceapps/PicoDet/README.md
similarity index 100%
rename from contrib/PicoDet/README.md
rename to mxVision/mxVision-referenceapps/PicoDet/README.md
diff --git a/contrib/PicoDet/build.sh b/mxVision/mxVision-referenceapps/PicoDet/build.sh
similarity index 100%
rename from contrib/PicoDet/build.sh
rename to mxVision/mxVision-referenceapps/PicoDet/build.sh
diff --git a/contrib/PicoDet/colorlist.txt b/mxVision/mxVision-referenceapps/PicoDet/colorlist.txt
similarity index 100%
rename from contrib/PicoDet/colorlist.txt
rename to mxVision/mxVision-referenceapps/PicoDet/colorlist.txt
diff --git a/contrib/PicoDet/evaluate.py b/mxVision/mxVision-referenceapps/PicoDet/evaluate.py
similarity index 100%
rename from contrib/PicoDet/evaluate.py
rename to mxVision/mxVision-referenceapps/PicoDet/evaluate.py
diff --git "a/contrib/PicoDet/images/sdk\346\265\201\347\250\213\345\233\276.png" "b/mxVision/mxVision-referenceapps/PicoDet/images/sdk\346\265\201\347\250\213\345\233\276.png"
similarity index 100%
rename from "contrib/PicoDet/images/sdk\346\265\201\347\250\213\345\233\276.png"
rename to "mxVision/mxVision-referenceapps/PicoDet/images/sdk\346\265\201\347\250\213\345\233\276.png"
diff --git "a/contrib/PicoDet/images/\347\262\276\345\272\246\347\273\223\346\236\234.png" "b/mxVision/mxVision-referenceapps/PicoDet/images/\347\262\276\345\272\246\347\273\223\346\236\234.png"
similarity index 100%
rename from "contrib/PicoDet/images/\347\262\276\345\272\246\347\273\223\346\236\234.png"
rename to "mxVision/mxVision-referenceapps/PicoDet/images/\347\262\276\345\272\246\347\273\223\346\236\234.png"
diff --git a/contrib/PicoDet/main.py b/mxVision/mxVision-referenceapps/PicoDet/main.py
similarity index 100%
rename from contrib/PicoDet/main.py
rename to mxVision/mxVision-referenceapps/PicoDet/main.py
diff --git a/contrib/PicoDet/models/picodet.aippconfig b/mxVision/mxVision-referenceapps/PicoDet/models/picodet.aippconfig
similarity index 100%
rename from contrib/PicoDet/models/picodet.aippconfig
rename to mxVision/mxVision-referenceapps/PicoDet/models/picodet.aippconfig
diff --git a/contrib/PicoDet/models/picodet.cfg b/mxVision/mxVision-referenceapps/PicoDet/models/picodet.cfg
similarity index 100%
rename from contrib/PicoDet/models/picodet.cfg
rename to mxVision/mxVision-referenceapps/PicoDet/models/picodet.cfg
diff --git a/contrib/PicoDet/picodet.pipeline b/mxVision/mxVision-referenceapps/PicoDet/picodet.pipeline
similarity index 100%
rename from contrib/PicoDet/picodet.pipeline
rename to mxVision/mxVision-referenceapps/PicoDet/picodet.pipeline
diff --git a/contrib/PixelLink/README.md b/mxVision/mxVision-referenceapps/PixelLink/README.md
similarity index 98%
rename from contrib/PixelLink/README.md
rename to mxVision/mxVision-referenceapps/PixelLink/README.md
index 8ff9cb7dd66e6b25ef1c2ce623051e683a801401..7903519a749f540fc207b050e20545be54a93a1b 100644
--- a/contrib/PixelLink/README.md
+++ b/mxVision/mxVision-referenceapps/PixelLink/README.md
@@ -1,179 +1,179 @@
-# Pixellink文本检测
-
-## 1 介绍
-  本开发样例完成图像文本检测功能，供用户参考。本系统基于mxVision SDK进行开发，以昇腾Atlas310卡为主要的硬件平台，开发端到端准确识别图像文本的位置信息，最后能够实现可视化，将识别到的文本位置用线条框选出来。
-  本项目试用场景为：包含字母/数字文本区域的场景图像，对于非数据集的场景下，识别要求文字区域尽可能清晰，区域大小能够占图像尺寸的5%及以上最佳，最大不得超过图片的50%左右。图像中文本区域要不存在遮挡、具有较为稀疏的密集度、文本要求为数字或者英文，文本区域的文本字体最好是规范的单个字体。由于原模型的训练场景原因，本样例无法保证对其他类型文本识别的精度，例如屏幕截图等。若文本区域存在遮挡、文本区域过于密集等可能存在无法检测出结果的问题。对于输入图像，图像要求为3通道的的RGB图像。输入其他格式的图像将无法完成检测功能。图像大小为720x1280x3最佳。图像中全部的文字区域不清晰、大小不支持识别、或者不存在英文或数字的文字区域时，识别可能会出现无文本区域的问题，最后可视化即为原图。本项目在运行代码后，会根据测试图像生成一个txt文件，其中包含文字区域位置的点坐标，每一个文字区域由四个坐标点组成。最后会根据txt文件中的每一组坐标点在图像上绘制出文本区域的四边形框。其中，四边形线条框不一定为规则矩形。
-
-
-### 1.1 支持的产品
-
-本项目以昇腾Atlas310卡为主要的硬件平台。
-
-### 1.2 支持的版本
-
-支持的SDK版本，列出版本号查询方式。
-
-支持的SDK版本为2.0.4。
-
-版本号查询方法，在Atlas产品环境下，运行命令：npu-smi info进行查看。
-
-
-### 1.3 软件方案介绍
-
-  本系统设计了不同的功能模块。主要流程为：图片传入流中，将图像放缩至特定尺寸，再利用基于tensorflow的pixellink文本检测模型检测文本区域，生成两个tensor值，将这两个tensor的值分别进行softmax处理，然后经过后处理完成掩码生成，像素点的并查集构建以及文本框轮廓的获取等。各模块功能描述如表1.1所示：
-
-表1.1 系统方案中各模块功能：
-| 序号 | 子系统    | 功能描述                                                                   |
-|----|--------|------------------------------------------------------------------------|
-| 1  | 图像输入   | 调用MindX SDK的appsrc插件对视频数据进行拉流                                          |
-| 2  | 图像放缩   | 调用MindX SDK的mxpi_imageresize                                           |
-| 3  | 文本区域检测  | 通过文本区域检测模型，获取图像中的文本位置、以及像素点关联等数据                                           |
-| 4  | 结果输出   | 输出文本位置以及像素点关联等信息    |
-| 5  | 后处理   | 根据输出结果进行后处理，将结果写入到txt文件中    |
-| 6  | 可视化   | 将txt文件中的文本区域坐标连线绘制到图像中    |
-
-
-### 1.4 代码目录结构与说明
-
-本工程名称为PixelLink，工程目录如下图所示：
-
-```
-.
-├── model
-│   └── convert.cfg  // 模型转化文件
-├── pipeline
-│   └── Pixel.pipeline
-├── get_version.py
-├── main.py
-├── README.md
-├── process.py
-├── process2.py
-└── main_get_groundtruth.py
-```
-
-
-### 1.5 技术实现流程图
-
-![Pixellink文本检测流程图](https://images.gitee.com/uploads/images/2021/1029/112024_3a19c293_9366121.png "屏幕截图.png")
-
-
-
-## 2 环境依赖
-
-推荐系统为ubuntu 18.04，环境依赖软件和版本如下表：
-
-| 软件名称  | 版本   |
-| -------- | ------ |
-| cmake    | 3.5+   |
-| mxVision | 2.0.4  |
-| python   | 3.9.2  |
-| CANN     | 5.0.4  |
-| Polygon3 | 3.0.9.1|
-
-
-注意：在运行评测代码时，可能出现没有Polygon包的报错，可以pip install Polygon3导入。
-
-在编译运行项目前，需要设置环境变量：
-
-模型转换所需ATC工具环境搭建参考链接：https://gitee.com/ascend/docs-openmind/blob/master/guide/mindx/sdk/tutorials/%E5%8F%82%E8%80%83%E8%B5%84%E6%96%99.md
-
-
-在编译运行项目前，需要设置环境变量：
-
-步骤1：安装mxVision SDK。 
-步骤2：配置mxVision SDK环境变量、lib库环境变量以及python环境变量。
-
-```
-export MX_SDK_HOME=${安装路径}/mxVision
-export LD_LIBRARY_PATH="${MX_SDK_HOME}/lib:${MX_SDK_HOME}/opensource/lib:${LD_LIBRARY_PATH}"
-export PYTHONPATH="${MX_SDK_HOME}/python:${PYTHONPATH}"
-export GST_PLUGIN_SCANNER="${MX_SDK_HOME}/opensource/libexec/gstreamer-1.0/gst-plugin-scanner"
-export GST_PLUGIN_PATH="${MX_SDK_HOME}/opensource/lib/gstreamer-1.0:${MX_SDK_HOME}/lib/plugins"
-```
-
-- 环境变量介绍
-- MX_SDK_HOME为SDK安装路径
-- LD_LIBRARY_PATH为lib库路径
-- PYTHONPATH为python环境路径
-
-
-## 3 模型转换
-本项目中用到的模型有：基于tensorflow转化出的pb形式的pixelLink模型。
-
-pb模型提供在链接：https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/PixelLink/pixellink_tf.pb;
-
-转换离线模型参考昇腾Gitee：https://gitee.com/ascend/docs-openmind/blob/master/guide/mindx/sdk/tutorials/%E5%8F%82%E8%80%83%E8%B5%84%E6%96%99.md
-
-首先需要配置ATC环境，下载pb模型，放到相应的路径后，修改模型转换的cfg配置文件，配置文件已经上传至项目目录model下。使用命令
-
-```
-atc --model=pixellink_tf.pb --framework=3 --output=pixellink --output_type=FP32 --soc_version=Ascend310 --input_shape="Placeholder:1,768,1280,3"
---insert_op_conf=convert.cfg --log=info
-```
-转化项目模型。
-
-
-注意：转化时，可根据需要修改输出的模型名称。注意模型以及转化所需文件的路径，防止atc命令找不到相关文件。
-
-
-## 4 编译与运行
-**步骤1**
-下载项目文件，以及icdar2015数据集，其中项目文件链接在模型转换部分已经给出。数据集链接：https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/PixelLink/data.zip
-
-zip文件中数据集为ch4_test_image，gt.zip是评测代码需要的groundtruth。评测代码可以在官网：https://rrc.cvc.uab.es/?ch=4&com=downloads进行下载，注意在官网中需要先进行登录。然后选择Incidental Scene Text,再选择My Methods,从offline evaluation部分进行下载（下载Evaluation Scripts）。由于需要注册和下载会给用户带来不便，所以提供了链接https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/PixelLink/data.zip 下载评测代码。
-
-
-
-**步骤2**
-  在安装mxVision SDK后，配置SDK安装路径、lib路径以及python路径，这些路径需要根据用户实际情况配置，例如SDK安装路径需要与用户本身安装路径一致，不一致将导致环境错误。同理，lib路径与python路径，都需要与实际情况一致。将下载的模型文件以及其他配置文件放到项目路径中，与pipeline内路径对应。修改pipeline内路径与模型文件一致。需要按照代码中的路径去创建文件路径，也可以根据实际需要修改代码中的路径变量。
-  
-
-**步骤3** 
-与main.py同路径下创建ch4_test_images文件夹，将数据集解压后放到该文件夹内，可以从中取出一张图像，命名为test.jpg，并放到与main.py同路径下。
-
-**步骤4**
-运行推理代码：
-
-```
-python3 main.py
-```
-输出结果：可以直接得到这张测试图像的推理结果，该结果会存到一个txt文件中，并在同目录下可视化test.jpg的检测结果。可视化结果命名为my_test.jpg。
-
-运行评测代码：
-
-  将解压后的icdar2015数据集中的测试集部分解压到ch4_test_images文件夹中。ch4_test_images与main_get_groundtruth.py同目录，人工在main_get_groundtruth.py同目录下创建test文件夹，运行main_get_groundtruth.py，会生成数据集中每张图像的检测结果，检测结果会存放到./test/image_txt/目标路径下。需要人工将结果压缩为zip文件，命名为om_result.zip（可以根据需要命名为其他名称，但是后续运行评测代码时需要名称对应），压缩后将zip文件和groundtruth的zip文件（gt.zip）放到script.py路径下，gt.zip是原模型的groundtruth，用以作为评测的基准。该zip文件可以在链接：https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/PixelLink/data.zip 获取。
-  评测代码在步骤1中已经完成下载，需要将里面的gt.zip以及script.py和rrc_evaluation_funcs_1_1.py放到与main.py同目录下。最后，运行script.py，得到评测结果。运行评测代码文件路径要求如下图所示：
-
-```
-.
-├── model
-│   └── convert.cfg  // 模型转化文件
-├── pipeline
-│   └── Pixel.pipeline
-├── get_version.py
-├── main.py
-├── README.md
-├── main_get_groundtruth.py
-├── rrc_evaluation_funcs_1_1.py
-├── ch4_test_images
-│   ├── img_1.jpg
-│   ├── img_2.jpg
-│   └── ......(other images)
-├── gt.zip
-├── om_result.zip（人工运行main_get_groundtruth.py后生成的txt文件压缩为zip，命名为om_result.zip）
-├── test
-│   └── image_txt（存放main_get_groundtruth.py对测试集上的运行结果）
-│          ├── res_img_1.txt
-│          ├── res_img_1.txt
-│          └── ......(other txts)
-└── script.py
-```
-
-
-
-```
-python3 main_get_groundtruth.py
-python3 script.py -g=./gt.zip -s=./om_result.zip
-```
-输出结果：首先得到本模型在ICDAR2015测试集上的推理结果，结果生成在./test/image_txt/下。再通过运行脚本代码可以得到原模型输出结果与本模型的结果的对比，最后得到本模型的平均指标。
-
+# Pixellink文本检测
+
+## 1 介绍
+  本开发样例完成图像文本检测功能，供用户参考。本系统基于mxVision SDK进行开发，以昇腾Atlas310卡为主要的硬件平台，开发端到端准确识别图像文本的位置信息，最后能够实现可视化，将识别到的文本位置用线条框选出来。
+  本项目试用场景为：包含字母/数字文本区域的场景图像，对于非数据集的场景下，识别要求文字区域尽可能清晰，区域大小能够占图像尺寸的5%及以上最佳，最大不得超过图片的50%左右。图像中文本区域要不存在遮挡、具有较为稀疏的密集度、文本要求为数字或者英文，文本区域的文本字体最好是规范的单个字体。由于原模型的训练场景原因，本样例无法保证对其他类型文本识别的精度，例如屏幕截图等。若文本区域存在遮挡、文本区域过于密集等可能存在无法检测出结果的问题。对于输入图像，图像要求为3通道的的RGB图像。输入其他格式的图像将无法完成检测功能。图像大小为720x1280x3最佳。图像中全部的文字区域不清晰、大小不支持识别、或者不存在英文或数字的文字区域时，识别可能会出现无文本区域的问题，最后可视化即为原图。本项目在运行代码后，会根据测试图像生成一个txt文件，其中包含文字区域位置的点坐标，每一个文字区域由四个坐标点组成。最后会根据txt文件中的每一组坐标点在图像上绘制出文本区域的四边形框。其中，四边形线条框不一定为规则矩形。
+
+
+### 1.1 支持的产品
+
+本项目以昇腾Atlas310卡为主要的硬件平台。
+
+### 1.2 支持的版本
+
+支持的SDK版本，列出版本号查询方式。
+
+支持的SDK版本为2.0.4。
+
+版本号查询方法，在Atlas产品环境下，运行命令：npu-smi info进行查看。
+
+
+### 1.3 软件方案介绍
+
+  本系统设计了不同的功能模块。主要流程为：图片传入流中，将图像放缩至特定尺寸，再利用基于tensorflow的pixellink文本检测模型检测文本区域，生成两个tensor值，将这两个tensor的值分别进行softmax处理，然后经过后处理完成掩码生成，像素点的并查集构建以及文本框轮廓的获取等。各模块功能描述如表1.1所示：
+
+表1.1 系统方案中各模块功能：
+| 序号 | 子系统    | 功能描述                                                                   |
+|----|--------|------------------------------------------------------------------------|
+| 1  | 图像输入   | 调用MindX SDK的appsrc插件对视频数据进行拉流                                          |
+| 2  | 图像放缩   | 调用MindX SDK的mxpi_imageresize                                           |
+| 3  | 文本区域检测  | 通过文本区域检测模型，获取图像中的文本位置、以及像素点关联等数据                                           |
+| 4  | 结果输出   | 输出文本位置以及像素点关联等信息    |
+| 5  | 后处理   | 根据输出结果进行后处理，将结果写入到txt文件中    |
+| 6  | 可视化   | 将txt文件中的文本区域坐标连线绘制到图像中    |
+
+
+### 1.4 代码目录结构与说明
+
+本工程名称为PixelLink，工程目录如下图所示：
+
+```
+.
+├── model
+│   └── convert.cfg  // 模型转化文件
+├── pipeline
+│   └── Pixel.pipeline
+├── get_version.py
+├── main.py
+├── README.md
+├── process.py
+├── process2.py
+└── main_get_groundtruth.py
+```
+
+
+### 1.5 技术实现流程图
+
+![Pixellink文本检测流程图](https://images.gitee.com/uploads/images/2021/1029/112024_3a19c293_9366121.png "屏幕截图.png")
+
+
+
+## 2 环境依赖
+
+推荐系统为ubuntu 18.04，环境依赖软件和版本如下表：
+
+| 软件名称  | 版本   |
+| -------- | ------ |
+| cmake    | 3.5+   |
+| mxVision | 2.0.4  |
+| python   | 3.9.2  |
+| CANN     | 5.0.4  |
+| Polygon3 | 3.0.9.1|
+
+
+注意：在运行评测代码时，可能出现没有Polygon包的报错，可以pip install Polygon3导入。
+
+在编译运行项目前，需要设置环境变量：
+
+模型转换所需ATC工具环境搭建参考链接：https://gitee.com/ascend/docs-openmind/blob/master/guide/mindx/sdk/tutorials/%E5%8F%82%E8%80%83%E8%B5%84%E6%96%99.md
+
+
+在编译运行项目前，需要设置环境变量：
+
+步骤1：安装mxVision SDK。 
+步骤2：配置mxVision SDK环境变量、lib库环境变量以及python环境变量。
+
+```
+export MX_SDK_HOME=${安装路径}/mxVision
+export LD_LIBRARY_PATH="${MX_SDK_HOME}/lib:${MX_SDK_HOME}/opensource/lib:${LD_LIBRARY_PATH}"
+export PYTHONPATH="${MX_SDK_HOME}/python:${PYTHONPATH}"
+export GST_PLUGIN_SCANNER="${MX_SDK_HOME}/opensource/libexec/gstreamer-1.0/gst-plugin-scanner"
+export GST_PLUGIN_PATH="${MX_SDK_HOME}/opensource/lib/gstreamer-1.0:${MX_SDK_HOME}/lib/plugins"
+```
+
+- 环境变量介绍
+- MX_SDK_HOME为SDK安装路径
+- LD_LIBRARY_PATH为lib库路径
+- PYTHONPATH为python环境路径
+
+
+## 3 模型转换
+本项目中用到的模型有：基于tensorflow转化出的pb形式的pixelLink模型。
+
+pb模型提供在链接：https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/PixelLink/pixellink_tf.pb;
+
+转换离线模型参考昇腾Gitee：https://gitee.com/ascend/docs-openmind/blob/master/guide/mindx/sdk/tutorials/%E5%8F%82%E8%80%83%E8%B5%84%E6%96%99.md
+
+首先需要配置ATC环境，下载pb模型，放到相应的路径后，修改模型转换的cfg配置文件，配置文件已经上传至项目目录model下。使用命令
+
+```
+atc --model=pixellink_tf.pb --framework=3 --output=pixellink --output_type=FP32 --soc_version=Ascend310 --input_shape="Placeholder:1,768,1280,3"
+--insert_op_conf=convert.cfg --log=info
+```
+转化项目模型。
+
+
+注意：转化时，可根据需要修改输出的模型名称。注意模型以及转化所需文件的路径，防止atc命令找不到相关文件。
+
+
+## 4 编译与运行
+**步骤1**
+下载项目文件，以及icdar2015数据集，其中项目文件链接在模型转换部分已经给出。数据集链接：https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/PixelLink/data.zip
+
+zip文件中数据集为ch4_test_image，gt.zip是评测代码需要的groundtruth。评测代码可以在官网：https://rrc.cvc.uab.es/?ch=4&com=downloads进行下载，注意在官网中需要先进行登录。然后选择Incidental Scene Text,再选择My Methods,从offline evaluation部分进行下载（下载Evaluation Scripts）。由于需要注册和下载会给用户带来不便，所以提供了链接https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/PixelLink/data.zip 下载评测代码。
+
+
+
+**步骤2**
+  在安装mxVision SDK后，配置SDK安装路径、lib路径以及python路径，这些路径需要根据用户实际情况配置，例如SDK安装路径需要与用户本身安装路径一致，不一致将导致环境错误。同理，lib路径与python路径，都需要与实际情况一致。将下载的模型文件以及其他配置文件放到项目路径中，与pipeline内路径对应。修改pipeline内路径与模型文件一致。需要按照代码中的路径去创建文件路径，也可以根据实际需要修改代码中的路径变量。
+  
+
+**步骤3** 
+与main.py同路径下创建ch4_test_images文件夹，将数据集解压后放到该文件夹内，可以从中取出一张图像，命名为test.jpg，并放到与main.py同路径下。
+
+**步骤4**
+运行推理代码：
+
+```
+python3 main.py
+```
+输出结果：可以直接得到这张测试图像的推理结果，该结果会存到一个txt文件中，并在同目录下可视化test.jpg的检测结果。可视化结果命名为my_test.jpg。
+
+运行评测代码：
+
+  将解压后的icdar2015数据集中的测试集部分解压到ch4_test_images文件夹中。ch4_test_images与main_get_groundtruth.py同目录，人工在main_get_groundtruth.py同目录下创建test文件夹，运行main_get_groundtruth.py，会生成数据集中每张图像的检测结果，检测结果会存放到./test/image_txt/目标路径下。需要人工将结果压缩为zip文件，命名为om_result.zip（可以根据需要命名为其他名称，但是后续运行评测代码时需要名称对应），压缩后将zip文件和groundtruth的zip文件（gt.zip）放到script.py路径下，gt.zip是原模型的groundtruth，用以作为评测的基准。该zip文件可以在链接：https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/PixelLink/data.zip 获取。
+  评测代码在步骤1中已经完成下载，需要将里面的gt.zip以及script.py和rrc_evaluation_funcs_1_1.py放到与main.py同目录下。最后，运行script.py，得到评测结果。运行评测代码文件路径要求如下图所示：
+
+```
+.
+├── model
+│   └── convert.cfg  // 模型转化文件
+├── pipeline
+│   └── Pixel.pipeline
+├── get_version.py
+├── main.py
+├── README.md
+├── main_get_groundtruth.py
+├── rrc_evaluation_funcs_1_1.py
+├── ch4_test_images
+│   ├── img_1.jpg
+│   ├── img_2.jpg
+│   └── ......(other images)
+├── gt.zip
+├── om_result.zip（人工运行main_get_groundtruth.py后生成的txt文件压缩为zip，命名为om_result.zip）
+├── test
+│   └── image_txt（存放main_get_groundtruth.py对测试集上的运行结果）
+│          ├── res_img_1.txt
+│          ├── res_img_1.txt
+│          └── ......(other txts)
+└── script.py
+```
+
+
+
+```
+python3 main_get_groundtruth.py
+python3 script.py -g=./gt.zip -s=./om_result.zip
+```
+输出结果：首先得到本模型在ICDAR2015测试集上的推理结果，结果生成在./test/image_txt/下。再通过运行脚本代码可以得到原模型输出结果与本模型的结果的对比，最后得到本模型的平均指标。
+
diff --git a/contrib/PixelLink/get_version.py b/mxVision/mxVision-referenceapps/PixelLink/get_version.py
similarity index 100%
rename from contrib/PixelLink/get_version.py
rename to mxVision/mxVision-referenceapps/PixelLink/get_version.py
diff --git a/contrib/PixelLink/main.py b/mxVision/mxVision-referenceapps/PixelLink/main.py
similarity index 100%
rename from contrib/PixelLink/main.py
rename to mxVision/mxVision-referenceapps/PixelLink/main.py
diff --git a/contrib/PixelLink/main_get_groundtruth.py b/mxVision/mxVision-referenceapps/PixelLink/main_get_groundtruth.py
similarity index 100%
rename from contrib/PixelLink/main_get_groundtruth.py
rename to mxVision/mxVision-referenceapps/PixelLink/main_get_groundtruth.py
diff --git a/contrib/PixelLink/model/convert.cfg b/mxVision/mxVision-referenceapps/PixelLink/model/convert.cfg
similarity index 100%
rename from contrib/PixelLink/model/convert.cfg
rename to mxVision/mxVision-referenceapps/PixelLink/model/convert.cfg
diff --git a/contrib/PixelLink/pipeline/Pixel.pipeline b/mxVision/mxVision-referenceapps/PixelLink/pipeline/Pixel.pipeline
similarity index 100%
rename from contrib/PixelLink/pipeline/Pixel.pipeline
rename to mxVision/mxVision-referenceapps/PixelLink/pipeline/Pixel.pipeline
diff --git a/contrib/PixelLink/process.py b/mxVision/mxVision-referenceapps/PixelLink/process.py
similarity index 100%
rename from contrib/PixelLink/process.py
rename to mxVision/mxVision-referenceapps/PixelLink/process.py
diff --git a/contrib/PixelLink/process2.py b/mxVision/mxVision-referenceapps/PixelLink/process2.py
similarity index 100%
rename from contrib/PixelLink/process2.py
rename to mxVision/mxVision-referenceapps/PixelLink/process2.py
diff --git a/contrib/PortraitSegmentation/README.md b/mxVision/mxVision-referenceapps/PortraitSegmentation/README.md
similarity index 97%
rename from contrib/PortraitSegmentation/README.md
rename to mxVision/mxVision-referenceapps/PortraitSegmentation/README.md
index dd371eb56ea8708a2141b8fb16eeb0276a3f55c3..7cb27522420ad9771a0f749032fcd0d9a46310dc 100644
--- a/contrib/PortraitSegmentation/README.md
+++ b/mxVision/mxVision-referenceapps/PortraitSegmentation/README.md
@@ -1,92 +1,92 @@
-# MindXSDK 人像分割与背景替换
-
-## 1 介绍
-
-### 1.1 简介
-本开发样例基于MindX SDK实现了端到端的人像分割与背景替换（Portrait Segmentation and Background Replacement, PSBR）。PSBR的主要功能是使用Portrait模型对输入图片中的人像进行分割，然后与背景图像融合，实现背景替换。输入为带有简单背景的单人jpg图片和一张没有人像的背景jpg图片，输出为人像背景替换后的jpg图片。
-
-### 1.2 支持的产品
-Atlas 300I pro、Atlas 300V pro
-
-### 1.3 支持的版本
-本样例配套的MxVision版本、CANN版本、Driver/Firmware版本如下所示：
-| MxVision版本  | CANN版本  | Driver/Firmware版本  |
-| --------- | ------------------ | -------------- | 
-| 6.0.RC3 | 8.0.RC3   |  24.1.RC3  | 
-
-### 1.4 三方依赖
-| 软件名称 | 版本     |
-| -------- |--------|
-| opencv_python   | 3.4.0 |
-
-### 1.5 代码目录结构说明
-本工程名称为PortraitSegmentation，工程目录如下图所示：
-```
-├── models
-|   ├──  portrait.pb                 // 人像分割pb模型
-|   ├──  insert_op.cfg               // 模型转换配置文件
-|   └──  portrait.om                 // 人像分割om模型
-├── pipline
-|   └──  segment.pipeline            // 人像分割模型pipeline配置文件
-├── main.py                             
-└── README.md   
-```
-
-### 1.6 相关约束
-为了达到良好的背景替换效果，输入的人像jpg图片构图应尽可能简单，仅包含单个人像及其相应的背景，其中人像应与其他物体有一定的间隔并显示出完整的轮廓。
-
-## 2 设置环境变量
-```
-. /usr/local/Ascend/ascend-toolkit/set_env.sh #CANN默认安装路径，根据实际安装路径修改
-. ${SDK_INSTALL_PATH}/mxVision/set_env.sh #根据实际SDK安装路径修改
-```
-
-## 3 准备模型
-**步骤1**：  下载Portrait原始模型：[下载地址](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/PortraitSegmentation/model.zip)，并将获取到的Portrait模型pb文件存放至本案例代码的PortraitSegmentation/models 目录下。
-
-**步骤2**：  进入PortraitSegmentation/models目录执行以下命令。
-```
-atc --model=portrait.pb  --input_shape="Inputs/x_input:1,224,224,3"  --framework=3  --output=portrait --insert_op_conf=insert_op.cfg --soc_version=Ascend310P3
-```
-
-**步骤3**： 执行命令后，终端提示如下信息说明模型转换成功，会在output参数指定的路径下生成portrait.om模型文件。  
-```
-ATC run success, welcome to the next use.
-```
-
-## 4 运行
-**步骤1**：配置pipeline
-根据所需场景，修改segment.pipeline文件第32行：
-```
-#配置mxpi_tensorinfer插件的模型加载路径： modelPath
-"mxpi_tensorinfer0": {
-    "props": {
-        "dataSource": "mxpi_imageresize0",
-        "modelPath": "models/portrait.om"
-    },
-    "factory": "mxpi_tensorinfer",
-    "next": "appsink0"
-},
-```
-
-**步骤2**：准备输入图片
-在工程根目录下新建data文件夹：
-```
-mkdir data
-```
-在data文件夹下存放对应jpg格式的人像和背景测试图片，并分别命名为background.jpg以及portrait.jpg。
-
-**步骤3**：新建result文件夹
-在工程根目录下新建result文件夹：
-```
-mkdir result
-```
-用于存放结果图片。
-
-**步骤4**：在工程根目录下执行
-```
-python3 main.py data/background.jpg data/portrait.jpg
-```
-
-**步骤5**：查看结果
+# MindXSDK 人像分割与背景替换
+
+## 1 介绍
+
+### 1.1 简介
+本开发样例基于MindX SDK实现了端到端的人像分割与背景替换（Portrait Segmentation and Background Replacement, PSBR）。PSBR的主要功能是使用Portrait模型对输入图片中的人像进行分割，然后与背景图像融合，实现背景替换。输入为带有简单背景的单人jpg图片和一张没有人像的背景jpg图片，输出为人像背景替换后的jpg图片。
+
+### 1.2 支持的产品
+Atlas 300I pro、Atlas 300V pro
+
+### 1.3 支持的版本
+本样例配套的MxVision版本、CANN版本、Driver/Firmware版本如下所示：
+| MxVision版本  | CANN版本  | Driver/Firmware版本  |
+| --------- | ------------------ | -------------- | 
+| 6.0.RC3 | 8.0.RC3   |  24.1.RC3  | 
+
+### 1.4 三方依赖
+| 软件名称 | 版本     |
+| -------- |--------|
+| opencv_python   | 3.4.0 |
+
+### 1.5 代码目录结构说明
+本工程名称为PortraitSegmentation，工程目录如下图所示：
+```
+├── models
+|   ├──  portrait.pb                 // 人像分割pb模型
+|   ├──  insert_op.cfg               // 模型转换配置文件
+|   └──  portrait.om                 // 人像分割om模型
+├── pipline
+|   └──  segment.pipeline            // 人像分割模型pipeline配置文件
+├── main.py                             
+└── README.md   
+```
+
+### 1.6 相关约束
+为了达到良好的背景替换效果，输入的人像jpg图片构图应尽可能简单，仅包含单个人像及其相应的背景，其中人像应与其他物体有一定的间隔并显示出完整的轮廓。
+
+## 2 设置环境变量
+```
+. /usr/local/Ascend/ascend-toolkit/set_env.sh #CANN默认安装路径，根据实际安装路径修改
+. ${SDK_INSTALL_PATH}/mxVision/set_env.sh #根据实际SDK安装路径修改
+```
+
+## 3 准备模型
+**步骤1**：  下载Portrait原始模型：[下载地址](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/PortraitSegmentation/model.zip)，并将获取到的Portrait模型pb文件存放至本案例代码的PortraitSegmentation/models 目录下。
+
+**步骤2**：  进入PortraitSegmentation/models目录执行以下命令。
+```
+atc --model=portrait.pb  --input_shape="Inputs/x_input:1,224,224,3"  --framework=3  --output=portrait --insert_op_conf=insert_op.cfg --soc_version=Ascend310P3
+```
+
+**步骤3**： 执行命令后，终端提示如下信息说明模型转换成功，会在output参数指定的路径下生成portrait.om模型文件。  
+```
+ATC run success, welcome to the next use.
+```
+
+## 4 运行
+**步骤1**：配置pipeline
+根据所需场景，修改segment.pipeline文件第32行：
+```
+#配置mxpi_tensorinfer插件的模型加载路径： modelPath
+"mxpi_tensorinfer0": {
+    "props": {
+        "dataSource": "mxpi_imageresize0",
+        "modelPath": "models/portrait.om"
+    },
+    "factory": "mxpi_tensorinfer",
+    "next": "appsink0"
+},
+```
+
+**步骤2**：准备输入图片
+在工程根目录下新建data文件夹：
+```
+mkdir data
+```
+在data文件夹下存放对应jpg格式的人像和背景测试图片，并分别命名为background.jpg以及portrait.jpg。
+
+**步骤3**：新建result文件夹
+在工程根目录下新建result文件夹：
+```
+mkdir result
+```
+用于存放结果图片。
+
+**步骤4**：在工程根目录下执行
+```
+python3 main.py data/background.jpg data/portrait.jpg
+```
+
+**步骤5**：查看结果
 在result目录中查看背景替换结果图片。
\ No newline at end of file
diff --git a/contrib/PortraitSegmentation/main.py b/mxVision/mxVision-referenceapps/PortraitSegmentation/main.py
similarity index 97%
rename from contrib/PortraitSegmentation/main.py
rename to mxVision/mxVision-referenceapps/PortraitSegmentation/main.py
index 25ccac3ef08cff949aca1205d5dc30afb0f2d2f6..e07c3b80fef155f8b9c8b0b062f79c60f76e9263 100644
--- a/contrib/PortraitSegmentation/main.py
+++ b/mxVision/mxVision-referenceapps/PortraitSegmentation/main.py
@@ -1,162 +1,162 @@
-#!/usr/bin/env python
-#-*-coding:utf-8-*-
-
-"""
-Portrait Segmentation and Background Replacement
-"""
-
-# Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-# http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-
-import sys
-import os
-import io
-import cv2
-import numpy as np
-from PIL import Image
-import MxpiDataType_pb2 as MxpiDataType
-from StreamManagerApi import StreamManagerApi, MxDataInput, StringVector
-
-STREAM_NAME = b'segmentation'
-IN_PLUGIN_ID = 0
-
-COLOR_DEPTH = 255
-
-MODEL_OUTPUT_WIDTH = 224
-MODEL_OUTPUT_HEIGHT = 224
-MODEL_OUTPUT_DIMENSION = 2
-
-BACKGROUND_IMAGE_PATH = sys.argv[1]
-PORTRAIT_IMAGE_PATH = sys.argv[2]
-
-DEFAULT_THRESHOLD = 1
-EXPECTED_PARAMETERS = 4
-
-REPEAT_AXIS = 3
-REPEAT_TIMES = 2
-
-MIN_IMAGE_SIZE = 32
-MAX_IMAGE_SIZE = 8192
-
-if __name__ == '__main__':
-    #  check input image
-    input_path = [BACKGROUND_IMAGE_PATH, PORTRAIT_IMAGE_PATH]
-    input_image_data = []
-    for i in input_path:
-        # check input image
-        input_valid = False
-        if os.path.exists(i) != 1:
-            error_message = 'The {} does not exist'.format(i)
-            print(error_message)
-        else:
-            try:
-                image = Image.open(i)
-                if image.format != 'JPEG':
-                    print('input image only support jpg, curr format is {}'.format(image.format))
-                elif image.width < MIN_IMAGE_SIZE or image.width > MAX_IMAGE_SIZE:
-                    print('input image width must in range [32, 8192], curr is {}'.format(image.width))
-                elif image.height < MIN_IMAGE_SIZE or image.height > MAX_IMAGE_SIZE:
-                    print('input image height must in range [32, 8192], curr is {}'.format(image.height))
-                else:
-                    input_valid = True
-                    # read input image bytes
-                    image_bytes = io.BytesIO()
-                    image.save(image_bytes, format='JPEG')
-                    input_image_data.append(image_bytes.getvalue())
-            except IOError:
-                print('an IOError occurred while opening {}, maybe your input is not a picture'.format(i))
-        if not input_valid:
-            print('The input image {} is invalid.'.format(i))
-            exit()
-            
-    # initialize the stream manager
-    stream_manager = StreamManagerApi()
-    stream_state = stream_manager.InitManager()
-    if stream_state != 0:
-        print("Failed to init Stream manager, ret=%s" % str(stream_state))
-        exit()
-
-    # create streams by the pipeline config
-    with open("pipeline/segment.pipeline", 'rb') as f:
-        pipeline = f.read().replace(b'\r', b'').replace(b'\n', b'')
-    pipeline_string = pipeline
-
-    stream_state = stream_manager.CreateMultipleStreams(pipeline_string)
-    if stream_state != 0:
-        print("Failed to create Stream, ret=%s" % str(stream_state))
-        exit()
-
-    # prepare the input of the stream #begin
-
-    # check the background img
-    data_input = MxDataInput()
-    data_input.data = input_image_data[1]
-    # prepare the input of the stream #end
-
-    # send the prepared data to the stream
-    unique_id = stream_manager.SendData(STREAM_NAME, IN_PLUGIN_ID, data_input)
-
-    if unique_id < 0:
-        print("Failed to send data to stream.")
-        exit()
-
-    # construct the resulted streamStateurned by the stream
-    plugin_names = [b"mxpi_tensorinfer0"]
-    name_vector = StringVector()
-    for name in plugin_names:
-        name_vector.push_back(name)
-    # get inference result
-    infer_result = stream_manager.GetProtobuf(STREAM_NAME, 0, name_vector)
-
-    # check whether the inferred results is valid or not
-    if len(infer_result) == 0:
-        error_message = 'unable to get effective infer results, please check the stream log for details'
-        print(error_message)
-        exit()
-    if infer_result[0].errorCode != 0:
-        error_message = "GetProtobuf error. errorCode=%d, errorMessage=%s" % (
-        infer_result[0].errorCode, infer_result[0].messageName)
-        print(error_message)
-        exit()
-
-    # change output tensors into numpy array based on the model's output shape.
-    tensor_package = MxpiDataType.MxpiTensorPackageList()
-    tensor_package.ParseFromString(infer_result[0].messageBuf)
-
-    # converting the byte data into little-endian 32 bit float array ('<f4')
-    output_tensor = np.frombuffer(tensor_package.tensorPackageVec[0].tensorVec[0].dataStr, dtype='<f4')
-    mask = np.clip((output_tensor * COLOR_DEPTH), 0, COLOR_DEPTH)
-    mask = mask.reshape(MODEL_OUTPUT_WIDTH, MODEL_OUTPUT_HEIGHT, MODEL_OUTPUT_DIMENSION)
-    mask = mask[:, :, 0]
-
-    # a threshold t to determine how precise the segmentation strategy will be, a lower of value of t will only
-    # remains pixels that are more likely to be a portrait. The default setting of t is 1, which remains all the pixels
-    # that are classified as the portrait by the PortraitNet model.
-    threshold = float(sys.argv[3] if len(sys.argv) == EXPECTED_PARAMETERS else DEFAULT_THRESHOLD)
-    mask[mask >= (threshold * COLOR_DEPTH)] = 255
-
-    # read the background and portrait image
-    background = cv2.imread(sys.argv[1])
-    portrait = cv2.imread(sys.argv[2])
-    height, width = portrait.shape[:2]
-    # resize the background image based on the size of portrait image
-    background = cv2.resize(background, (width, height))
-    # replace the background in portrait image with the new background
-    mask = mask / COLOR_DEPTH
-    mask_resize = cv2.resize(mask, (width, height))
-    mask_expansion = np.repeat(mask_resize[..., np.newaxis], REPEAT_AXIS, REPEAT_TIMES)
-    result = np.uint8(background * mask_expansion + portrait * (1 - mask_expansion))
-    # save the new image in current catalog
-    cv2.imwrite('result/result1.jpg', result)
+#!/usr/bin/env python
+#-*-coding:utf-8-*-
+
+"""
+Portrait Segmentation and Background Replacement
+"""
+
+# Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+
+import sys
+import os
+import io
+import cv2
+import numpy as np
+from PIL import Image
+import MxpiDataType_pb2 as MxpiDataType
+from StreamManagerApi import StreamManagerApi, MxDataInput, StringVector
+
+STREAM_NAME = b'segmentation'
+IN_PLUGIN_ID = 0
+
+COLOR_DEPTH = 255
+
+MODEL_OUTPUT_WIDTH = 224
+MODEL_OUTPUT_HEIGHT = 224
+MODEL_OUTPUT_DIMENSION = 2
+
+BACKGROUND_IMAGE_PATH = sys.argv[1]
+PORTRAIT_IMAGE_PATH = sys.argv[2]
+
+DEFAULT_THRESHOLD = 1
+EXPECTED_PARAMETERS = 4
+
+REPEAT_AXIS = 3
+REPEAT_TIMES = 2
+
+MIN_IMAGE_SIZE = 32
+MAX_IMAGE_SIZE = 8192
+
+if __name__ == '__main__':
+    #  check input image
+    input_path = [BACKGROUND_IMAGE_PATH, PORTRAIT_IMAGE_PATH]
+    input_image_data = []
+    for i in input_path:
+        # check input image
+        input_valid = False
+        if os.path.exists(i) != 1:
+            error_message = 'The {} does not exist'.format(i)
+            print(error_message)
+        else:
+            try:
+                image = Image.open(i)
+                if image.format != 'JPEG':
+                    print('input image only support jpg, curr format is {}'.format(image.format))
+                elif image.width < MIN_IMAGE_SIZE or image.width > MAX_IMAGE_SIZE:
+                    print('input image width must in range [32, 8192], curr is {}'.format(image.width))
+                elif image.height < MIN_IMAGE_SIZE or image.height > MAX_IMAGE_SIZE:
+                    print('input image height must in range [32, 8192], curr is {}'.format(image.height))
+                else:
+                    input_valid = True
+                    # read input image bytes
+                    image_bytes = io.BytesIO()
+                    image.save(image_bytes, format='JPEG')
+                    input_image_data.append(image_bytes.getvalue())
+            except IOError:
+                print('an IOError occurred while opening {}, maybe your input is not a picture'.format(i))
+        if not input_valid:
+            print('The input image {} is invalid.'.format(i))
+            exit()
+            
+    # initialize the stream manager
+    stream_manager = StreamManagerApi()
+    stream_state = stream_manager.InitManager()
+    if stream_state != 0:
+        print("Failed to init Stream manager, ret=%s" % str(stream_state))
+        exit()
+
+    # create streams by the pipeline config
+    with open("pipeline/segment.pipeline", 'rb') as f:
+        pipeline = f.read().replace(b'\r', b'').replace(b'\n', b'')
+    pipeline_string = pipeline
+
+    stream_state = stream_manager.CreateMultipleStreams(pipeline_string)
+    if stream_state != 0:
+        print("Failed to create Stream, ret=%s" % str(stream_state))
+        exit()
+
+    # prepare the input of the stream #begin
+
+    # check the background img
+    data_input = MxDataInput()
+    data_input.data = input_image_data[1]
+    # prepare the input of the stream #end
+
+    # send the prepared data to the stream
+    unique_id = stream_manager.SendData(STREAM_NAME, IN_PLUGIN_ID, data_input)
+
+    if unique_id < 0:
+        print("Failed to send data to stream.")
+        exit()
+
+    # construct the resulted streamStateurned by the stream
+    plugin_names = [b"mxpi_tensorinfer0"]
+    name_vector = StringVector()
+    for name in plugin_names:
+        name_vector.push_back(name)
+    # get inference result
+    infer_result = stream_manager.GetProtobuf(STREAM_NAME, 0, name_vector)
+
+    # check whether the inferred results is valid or not
+    if len(infer_result) == 0:
+        error_message = 'unable to get effective infer results, please check the stream log for details'
+        print(error_message)
+        exit()
+    if infer_result[0].errorCode != 0:
+        error_message = "GetProtobuf error. errorCode=%d, errorMessage=%s" % (
+        infer_result[0].errorCode, infer_result[0].messageName)
+        print(error_message)
+        exit()
+
+    # change output tensors into numpy array based on the model's output shape.
+    tensor_package = MxpiDataType.MxpiTensorPackageList()
+    tensor_package.ParseFromString(infer_result[0].messageBuf)
+
+    # converting the byte data into little-endian 32 bit float array ('<f4')
+    output_tensor = np.frombuffer(tensor_package.tensorPackageVec[0].tensorVec[0].dataStr, dtype='<f4')
+    mask = np.clip((output_tensor * COLOR_DEPTH), 0, COLOR_DEPTH)
+    mask = mask.reshape(MODEL_OUTPUT_WIDTH, MODEL_OUTPUT_HEIGHT, MODEL_OUTPUT_DIMENSION)
+    mask = mask[:, :, 0]
+
+    # a threshold t to determine how precise the segmentation strategy will be, a lower of value of t will only
+    # remains pixels that are more likely to be a portrait. The default setting of t is 1, which remains all the pixels
+    # that are classified as the portrait by the PortraitNet model.
+    threshold = float(sys.argv[3] if len(sys.argv) == EXPECTED_PARAMETERS else DEFAULT_THRESHOLD)
+    mask[mask >= (threshold * COLOR_DEPTH)] = 255
+
+    # read the background and portrait image
+    background = cv2.imread(sys.argv[1])
+    portrait = cv2.imread(sys.argv[2])
+    height, width = portrait.shape[:2]
+    # resize the background image based on the size of portrait image
+    background = cv2.resize(background, (width, height))
+    # replace the background in portrait image with the new background
+    mask = mask / COLOR_DEPTH
+    mask_resize = cv2.resize(mask, (width, height))
+    mask_expansion = np.repeat(mask_resize[..., np.newaxis], REPEAT_AXIS, REPEAT_TIMES)
+    result = np.uint8(background * mask_expansion + portrait * (1 - mask_expansion))
+    # save the new image in current catalog
+    cv2.imwrite('result/result1.jpg', result)
diff --git a/contrib/PortraitSegmentation/models/insert_op.cfg b/mxVision/mxVision-referenceapps/PortraitSegmentation/models/insert_op.cfg
similarity index 94%
rename from contrib/PortraitSegmentation/models/insert_op.cfg
rename to mxVision/mxVision-referenceapps/PortraitSegmentation/models/insert_op.cfg
index 640e5831cf9a539ffd8669ad9701ce866838f76f..dacc19eb1843c3b1032a29a3ac79e0277f82f94b 100644
--- a/contrib/PortraitSegmentation/models/insert_op.cfg
+++ b/mxVision/mxVision-referenceapps/PortraitSegmentation/models/insert_op.cfg
@@ -1,31 +1,31 @@
-aipp_op { 
-related_input_rank : 0
-src_image_size_w : 224
-src_image_size_h : 224
-crop : false
-input_format : YUV420SP_U8
-aipp_mode: static
-csc_switch : true
-rbuv_swap_switch : false
-matrix_r0c0 : 298
-matrix_r0c1 : 0
-matrix_r0c2 : 409
-matrix_r1c0 : 298
-matrix_r1c1 : -100
-matrix_r1c2 : -208
-matrix_r2c0 : 298
-matrix_r2c1 : 516
-matrix_r2c2 : 0
-input_bias_0 : 16
-input_bias_1 : 128
-input_bias_2 : 128
-mean_chn_0 : 104
-mean_chn_1 : 117
-mean_chn_2 : 123
-min_chn_0 : 0.0
-min_chn_1 : 0.0
-min_chn_2 : 0.0
-var_reci_chn_0 : 0.017
-var_reci_chn_1 : 0.017
-var_reci_chn_2 : 0.017
-}
+aipp_op { 
+related_input_rank : 0
+src_image_size_w : 224
+src_image_size_h : 224
+crop : false
+input_format : YUV420SP_U8
+aipp_mode: static
+csc_switch : true
+rbuv_swap_switch : false
+matrix_r0c0 : 298
+matrix_r0c1 : 0
+matrix_r0c2 : 409
+matrix_r1c0 : 298
+matrix_r1c1 : -100
+matrix_r1c2 : -208
+matrix_r2c0 : 298
+matrix_r2c1 : 516
+matrix_r2c2 : 0
+input_bias_0 : 16
+input_bias_1 : 128
+input_bias_2 : 128
+mean_chn_0 : 104
+mean_chn_1 : 117
+mean_chn_2 : 123
+min_chn_0 : 0.0
+min_chn_1 : 0.0
+min_chn_2 : 0.0
+var_reci_chn_0 : 0.017
+var_reci_chn_1 : 0.017
+var_reci_chn_2 : 0.017
+}
diff --git a/contrib/PortraitSegmentation/pipeline/segment.pipeline b/mxVision/mxVision-referenceapps/PortraitSegmentation/pipeline/segment.pipeline
similarity index 96%
rename from contrib/PortraitSegmentation/pipeline/segment.pipeline
rename to mxVision/mxVision-referenceapps/PortraitSegmentation/pipeline/segment.pipeline
index b7fcaa5f573f176c854a4191cd431bd20443ac39..23fabbf57f9d7a3e24aaf77f1b739fd4839852b2 100644
--- a/contrib/PortraitSegmentation/pipeline/segment.pipeline
+++ b/mxVision/mxVision-referenceapps/PortraitSegmentation/pipeline/segment.pipeline
@@ -1,44 +1,44 @@
-{
-    "segmentation": {
-        "stream_config": {
-            "deviceId": "0"
-        },
-        "appsrc0": {
-            "props": {
-                "blocksize": "409600"
-            },
-            "factory": "appsrc",
-            "next": "mxpi_imagedecoder0"
-        },
-        "mxpi_imagedecoder0": {
-            "props": {
-                "deviceId": "0"
-            },
-            "factory": "mxpi_imagedecoder",
-            "next": "mxpi_imageresize0"
-        },
-        "mxpi_imageresize0": {
-            "props": {
-                "dataSource": "mxpi_imagedecoder0",
-                "resizeHeight": "224",
-                "resizeWidth": "224"
-            },
-            "factory": "mxpi_imageresize",
-            "next": "mxpi_tensorinfer0"
-        },
-        "mxpi_tensorinfer0": {
-            "props": {
-                "dataSource": "mxpi_imageresize0",
-                "modelPath": "models/portrait.om"
-            },
-            "factory": "mxpi_tensorinfer",
-            "next": "appsink0"
-        },
-        "appsink0": {
-            "props": {
-                "blocksize": "4096000"
-            },
-            "factory": "appsink"
-        }
-    }
+{
+    "segmentation": {
+        "stream_config": {
+            "deviceId": "0"
+        },
+        "appsrc0": {
+            "props": {
+                "blocksize": "409600"
+            },
+            "factory": "appsrc",
+            "next": "mxpi_imagedecoder0"
+        },
+        "mxpi_imagedecoder0": {
+            "props": {
+                "deviceId": "0"
+            },
+            "factory": "mxpi_imagedecoder",
+            "next": "mxpi_imageresize0"
+        },
+        "mxpi_imageresize0": {
+            "props": {
+                "dataSource": "mxpi_imagedecoder0",
+                "resizeHeight": "224",
+                "resizeWidth": "224"
+            },
+            "factory": "mxpi_imageresize",
+            "next": "mxpi_tensorinfer0"
+        },
+        "mxpi_tensorinfer0": {
+            "props": {
+                "dataSource": "mxpi_imageresize0",
+                "modelPath": "models/portrait.om"
+            },
+            "factory": "mxpi_tensorinfer",
+            "next": "appsink0"
+        },
+        "appsink0": {
+            "props": {
+                "blocksize": "4096000"
+            },
+            "factory": "appsink"
+        }
+    }
 }
\ No newline at end of file
diff --git a/contrib/PoseEstNet/README.md b/mxVision/mxVision-referenceapps/PoseEstNet/README.md
similarity index 100%
rename from contrib/PoseEstNet/README.md
rename to mxVision/mxVision-referenceapps/PoseEstNet/README.md
diff --git a/contrib/PoseEstNet/eval.py b/mxVision/mxVision-referenceapps/PoseEstNet/eval.py
similarity index 100%
rename from contrib/PoseEstNet/eval.py
rename to mxVision/mxVision-referenceapps/PoseEstNet/eval.py
diff --git a/contrib/PoseEstNet/image/output_eval.png b/mxVision/mxVision-referenceapps/PoseEstNet/image/output_eval.png
similarity index 100%
rename from contrib/PoseEstNet/image/output_eval.png
rename to mxVision/mxVision-referenceapps/PoseEstNet/image/output_eval.png
diff --git a/contrib/PoseEstNet/image/plugin_tree.png b/mxVision/mxVision-referenceapps/PoseEstNet/image/plugin_tree.png
similarity index 100%
rename from contrib/PoseEstNet/image/plugin_tree.png
rename to mxVision/mxVision-referenceapps/PoseEstNet/image/plugin_tree.png
diff --git a/contrib/PoseEstNet/image/project_tree.png b/mxVision/mxVision-referenceapps/PoseEstNet/image/project_tree.png
similarity index 100%
rename from contrib/PoseEstNet/image/project_tree.png
rename to mxVision/mxVision-referenceapps/PoseEstNet/image/project_tree.png
diff --git a/contrib/PoseEstNet/main.py b/mxVision/mxVision-referenceapps/PoseEstNet/main.py
similarity index 100%
rename from contrib/PoseEstNet/main.py
rename to mxVision/mxVision-referenceapps/PoseEstNet/main.py
diff --git a/contrib/PoseEstNet/models/aipp_hrnet_256_256.aippconfig b/mxVision/mxVision-referenceapps/PoseEstNet/models/aipp_hrnet_256_256.aippconfig
similarity index 100%
rename from contrib/PoseEstNet/models/aipp_hrnet_256_256.aippconfig
rename to mxVision/mxVision-referenceapps/PoseEstNet/models/aipp_hrnet_256_256.aippconfig
diff --git a/contrib/PoseEstNet/models/aipp_nv12.cfg b/mxVision/mxVision-referenceapps/PoseEstNet/models/aipp_nv12.cfg
similarity index 100%
rename from contrib/PoseEstNet/models/aipp_nv12.cfg
rename to mxVision/mxVision-referenceapps/PoseEstNet/models/aipp_nv12.cfg
diff --git a/contrib/PoseEstNet/models/coco.names b/mxVision/mxVision-referenceapps/PoseEstNet/models/coco.names
similarity index 100%
rename from contrib/PoseEstNet/models/coco.names
rename to mxVision/mxVision-referenceapps/PoseEstNet/models/coco.names
diff --git a/contrib/PoseEstNet/models/yolov3.cfg b/mxVision/mxVision-referenceapps/PoseEstNet/models/yolov3.cfg
similarity index 100%
rename from contrib/PoseEstNet/models/yolov3.cfg
rename to mxVision/mxVision-referenceapps/PoseEstNet/models/yolov3.cfg
diff --git a/contrib/PoseEstNet/pipeline/PoseEstNet.pipeline b/mxVision/mxVision-referenceapps/PoseEstNet/pipeline/PoseEstNet.pipeline
similarity index 100%
rename from contrib/PoseEstNet/pipeline/PoseEstNet.pipeline
rename to mxVision/mxVision-referenceapps/PoseEstNet/pipeline/PoseEstNet.pipeline
diff --git a/contrib/PoseEstNet/pipeline/eval_PoseEstNet.pipeline b/mxVision/mxVision-referenceapps/PoseEstNet/pipeline/eval_PoseEstNet.pipeline
similarity index 100%
rename from contrib/PoseEstNet/pipeline/eval_PoseEstNet.pipeline
rename to mxVision/mxVision-referenceapps/PoseEstNet/pipeline/eval_PoseEstNet.pipeline
diff --git a/contrib/PoseEstNet/plugins/build.sh b/mxVision/mxVision-referenceapps/PoseEstNet/plugins/build.sh
similarity index 100%
rename from contrib/PoseEstNet/plugins/build.sh
rename to mxVision/mxVision-referenceapps/PoseEstNet/plugins/build.sh
diff --git a/contrib/PoseEstNet/plugins/postprocess/CMakeLists.txt b/mxVision/mxVision-referenceapps/PoseEstNet/plugins/postprocess/CMakeLists.txt
similarity index 100%
rename from contrib/PoseEstNet/plugins/postprocess/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/PoseEstNet/plugins/postprocess/CMakeLists.txt
diff --git a/contrib/PoseEstNet/plugins/postprocess/MxpiPNetPostprocess.cpp b/mxVision/mxVision-referenceapps/PoseEstNet/plugins/postprocess/MxpiPNetPostprocess.cpp
similarity index 100%
rename from contrib/PoseEstNet/plugins/postprocess/MxpiPNetPostprocess.cpp
rename to mxVision/mxVision-referenceapps/PoseEstNet/plugins/postprocess/MxpiPNetPostprocess.cpp
diff --git a/contrib/PoseEstNet/plugins/postprocess/MxpiPNetPostprocess.h b/mxVision/mxVision-referenceapps/PoseEstNet/plugins/postprocess/MxpiPNetPostprocess.h
similarity index 100%
rename from contrib/PoseEstNet/plugins/postprocess/MxpiPNetPostprocess.h
rename to mxVision/mxVision-referenceapps/PoseEstNet/plugins/postprocess/MxpiPNetPostprocess.h
diff --git a/contrib/PoseEstNet/plugins/postprocess/build.sh b/mxVision/mxVision-referenceapps/PoseEstNet/plugins/postprocess/build.sh
similarity index 100%
rename from contrib/PoseEstNet/plugins/postprocess/build.sh
rename to mxVision/mxVision-referenceapps/PoseEstNet/plugins/postprocess/build.sh
diff --git a/contrib/PoseEstNet/plugins/preprocess/CMakeLists.txt b/mxVision/mxVision-referenceapps/PoseEstNet/plugins/preprocess/CMakeLists.txt
similarity index 100%
rename from contrib/PoseEstNet/plugins/preprocess/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/PoseEstNet/plugins/preprocess/CMakeLists.txt
diff --git a/contrib/PoseEstNet/plugins/preprocess/MxpiPNetPreprocess.cpp b/mxVision/mxVision-referenceapps/PoseEstNet/plugins/preprocess/MxpiPNetPreprocess.cpp
similarity index 100%
rename from contrib/PoseEstNet/plugins/preprocess/MxpiPNetPreprocess.cpp
rename to mxVision/mxVision-referenceapps/PoseEstNet/plugins/preprocess/MxpiPNetPreprocess.cpp
diff --git a/contrib/PoseEstNet/plugins/preprocess/MxpiPNetPreprocess.h b/mxVision/mxVision-referenceapps/PoseEstNet/plugins/preprocess/MxpiPNetPreprocess.h
similarity index 100%
rename from contrib/PoseEstNet/plugins/preprocess/MxpiPNetPreprocess.h
rename to mxVision/mxVision-referenceapps/PoseEstNet/plugins/preprocess/MxpiPNetPreprocess.h
diff --git a/contrib/PoseEstNet/plugins/preprocess/build.sh b/mxVision/mxVision-referenceapps/PoseEstNet/plugins/preprocess/build.sh
similarity index 100%
rename from contrib/PoseEstNet/plugins/preprocess/build.sh
rename to mxVision/mxVision-referenceapps/PoseEstNet/plugins/preprocess/build.sh
diff --git a/contrib/PraNetSegmentation/README.md b/mxVision/mxVision-referenceapps/PraNetSegmentation/README.md
similarity index 100%
rename from contrib/PraNetSegmentation/README.md
rename to mxVision/mxVision-referenceapps/PraNetSegmentation/README.md
diff --git a/contrib/PraNetSegmentation/main.py b/mxVision/mxVision-referenceapps/PraNetSegmentation/main.py
similarity index 100%
rename from contrib/PraNetSegmentation/main.py
rename to mxVision/mxVision-referenceapps/PraNetSegmentation/main.py
diff --git a/contrib/PraNetSegmentation/model/onnx2om.sh b/mxVision/mxVision-referenceapps/PraNetSegmentation/model/onnx2om.sh
similarity index 100%
rename from contrib/PraNetSegmentation/model/onnx2om.sh
rename to mxVision/mxVision-referenceapps/PraNetSegmentation/model/onnx2om.sh
diff --git a/contrib/PraNetSegmentation/model/pranet.aippconfig b/mxVision/mxVision-referenceapps/PraNetSegmentation/model/pranet.aippconfig
similarity index 100%
rename from contrib/PraNetSegmentation/model/pranet.aippconfig
rename to mxVision/mxVision-referenceapps/PraNetSegmentation/model/pranet.aippconfig
diff --git a/contrib/PraNetSegmentation/pipeline/pranet_pipeline.json b/mxVision/mxVision-referenceapps/PraNetSegmentation/pipeline/pranet_pipeline.json
similarity index 100%
rename from contrib/PraNetSegmentation/pipeline/pranet_pipeline.json
rename to mxVision/mxVision-referenceapps/PraNetSegmentation/pipeline/pranet_pipeline.json
diff --git a/contrib/PraNetSegmentation/plugin/postprocess/CMakeLists.txt b/mxVision/mxVision-referenceapps/PraNetSegmentation/plugin/postprocess/CMakeLists.txt
similarity index 100%
rename from contrib/PraNetSegmentation/plugin/postprocess/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/PraNetSegmentation/plugin/postprocess/CMakeLists.txt
diff --git a/contrib/PraNetSegmentation/plugin/postprocess/Postprocess.cpp b/mxVision/mxVision-referenceapps/PraNetSegmentation/plugin/postprocess/Postprocess.cpp
similarity index 100%
rename from contrib/PraNetSegmentation/plugin/postprocess/Postprocess.cpp
rename to mxVision/mxVision-referenceapps/PraNetSegmentation/plugin/postprocess/Postprocess.cpp
diff --git a/contrib/PraNetSegmentation/plugin/postprocess/Postprocess.h b/mxVision/mxVision-referenceapps/PraNetSegmentation/plugin/postprocess/Postprocess.h
similarity index 100%
rename from contrib/PraNetSegmentation/plugin/postprocess/Postprocess.h
rename to mxVision/mxVision-referenceapps/PraNetSegmentation/plugin/postprocess/Postprocess.h
diff --git a/contrib/PraNetSegmentation/plugin/postprocess/build.sh b/mxVision/mxVision-referenceapps/PraNetSegmentation/plugin/postprocess/build.sh
similarity index 100%
rename from contrib/PraNetSegmentation/plugin/postprocess/build.sh
rename to mxVision/mxVision-referenceapps/PraNetSegmentation/plugin/postprocess/build.sh
diff --git a/contrib/PraNetSegmentation/test_metric.py b/mxVision/mxVision-referenceapps/PraNetSegmentation/test_metric.py
similarity index 100%
rename from contrib/PraNetSegmentation/test_metric.py
rename to mxVision/mxVision-referenceapps/PraNetSegmentation/test_metric.py
diff --git a/mxVision/PutText/PutText/CMakeLists.txt b/mxVision/mxVision-referenceapps/PutText/PutText/CMakeLists.txt
similarity index 100%
rename from mxVision/PutText/PutText/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/PutText/PutText/CMakeLists.txt
diff --git a/mxVision/PutText/PutText/CaptionGenManager.cpp b/mxVision/mxVision-referenceapps/PutText/PutText/CaptionGenManager.cpp
similarity index 100%
rename from mxVision/PutText/PutText/CaptionGenManager.cpp
rename to mxVision/mxVision-referenceapps/PutText/PutText/CaptionGenManager.cpp
diff --git a/mxVision/PutText/PutText/CaptionGenManager.h b/mxVision/mxVision-referenceapps/PutText/PutText/CaptionGenManager.h
similarity index 100%
rename from mxVision/PutText/PutText/CaptionGenManager.h
rename to mxVision/mxVision-referenceapps/PutText/PutText/CaptionGenManager.h
diff --git a/mxVision/PutText/PutText/CaptionGeneration.cpp b/mxVision/mxVision-referenceapps/PutText/PutText/CaptionGeneration.cpp
similarity index 100%
rename from mxVision/PutText/PutText/CaptionGeneration.cpp
rename to mxVision/mxVision-referenceapps/PutText/PutText/CaptionGeneration.cpp
diff --git a/mxVision/PutText/PutText/CaptionGeneration.h b/mxVision/mxVision-referenceapps/PutText/PutText/CaptionGeneration.h
similarity index 100%
rename from mxVision/PutText/PutText/CaptionGeneration.h
rename to mxVision/mxVision-referenceapps/PutText/PutText/CaptionGeneration.h
diff --git a/mxVision/PutText/PutText/CaptionImpl.cpp b/mxVision/mxVision-referenceapps/PutText/PutText/CaptionImpl.cpp
similarity index 100%
rename from mxVision/PutText/PutText/CaptionImpl.cpp
rename to mxVision/mxVision-referenceapps/PutText/PutText/CaptionImpl.cpp
diff --git a/mxVision/PutText/PutText/CaptionImpl.h b/mxVision/mxVision-referenceapps/PutText/PutText/CaptionImpl.h
similarity index 100%
rename from mxVision/PutText/PutText/CaptionImpl.h
rename to mxVision/mxVision-referenceapps/PutText/PutText/CaptionImpl.h
diff --git a/mxVision/PutText/PutText/CaptionPool.cpp b/mxVision/mxVision-referenceapps/PutText/PutText/CaptionPool.cpp
similarity index 97%
rename from mxVision/PutText/PutText/CaptionPool.cpp
rename to mxVision/mxVision-referenceapps/PutText/PutText/CaptionPool.cpp
index 73cc35fff3980d441e75e6b0d782f735ff1a2703..c27f750e28f237f042454ea7e03af6a248601970 100644
--- a/mxVision/PutText/PutText/CaptionPool.cpp
+++ b/mxVision/mxVision-referenceapps/PutText/PutText/CaptionPool.cpp
@@ -1,75 +1,75 @@
-/*
- * Copyright(C) 2024. Huawei Technologies Co.,Ltd. All rights reserved.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-#include "CaptionPool.h"
-
-CaptionPool::CaptionPool(size_t max_size) {
-    text2Lenghth_ = std::make_shared<LimitedSizeMap<std::string, int>>(max_size);
-    text2CaptionMap_ = std::make_shared<LimitedSizeMap<std::string, MxBase::Tensor>>(max_size);
-    text2MaskMap_ = std::make_shared<LimitedSizeMap<std::string, MxBase::Tensor>>(max_size);
-}
-
-APP_ERROR CaptionPool::putCaptionAndMask(std::string text1, std::string text2, MxBase::Tensor caption,
-                                         MxBase::Tensor mask) {
-    std::string textMark = text1 + "_" + text2;
-    if(text2MaskMap_ != nullptr && text2CaptionMap_ != nullptr) {
-        text2CaptionMap_->put(textMark, caption);
-        text2MaskMap_->put(textMark, mask);
-        return APP_ERR_OK;
-    }
-    return APP_ERR_COMM_FAILURE;
-}
-
-APP_ERROR CaptionPool::getCaptionAndMask(std::string text1, std::string text2, MxBase::Tensor& caption,
-                                         MxBase::Tensor& mask) {
-    std::string textMark = text1 + "_" + text2;
-    if (text2MaskMap_ != nullptr && text2CaptionMap_ != nullptr &&
-        text2CaptionMap_->get(textMark, caption) && text2MaskMap_->get(textMark, mask)) {
-        return APP_ERR_OK;
-    }
-    return APP_ERR_COMM_FAILURE;
-}
-
-bool CaptionPool::isCaptionExist(std::string text1, std::string text2) {
-    std::string textMark = text1 + "_" + text2;
-    if (text2MaskMap_ != nullptr && text2CaptionMap_ != nullptr &&
-        text2MaskMap_->isExist(textMark) && text2CaptionMap_->isExist(textMark)) {
-        return true;
-    }
-    return false;
-}
-
-APP_ERROR CaptionPool::putCaptionLength(std::string text, int length) {
-    if (text2Lenghth_ != nullptr) {
-        text2Lenghth_->put(text, length);
-        return APP_ERR_OK;
-    }
-    return APP_ERR_COMM_FAILURE;
-}
-
-
-APP_ERROR CaptionPool::getCaptionLength(std::string text, int& length) {
-    if (text2Lenghth_ != nullptr && text2Lenghth_->get(text, length)) {
-        return APP_ERR_OK;
-    }
-    return APP_ERR_COMM_FAILURE;
-}
-
-bool CaptionPool::isCaptionLengthExist(std::string text) {
-    if (text2Lenghth_ != nullptr && text2Lenghth_->isExist(text)) {
-        return true;
-    }
-    return false;
+/*
+ * Copyright(C) 2024. Huawei Technologies Co.,Ltd. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#include "CaptionPool.h"
+
+CaptionPool::CaptionPool(size_t max_size) {
+    text2Lenghth_ = std::make_shared<LimitedSizeMap<std::string, int>>(max_size);
+    text2CaptionMap_ = std::make_shared<LimitedSizeMap<std::string, MxBase::Tensor>>(max_size);
+    text2MaskMap_ = std::make_shared<LimitedSizeMap<std::string, MxBase::Tensor>>(max_size);
+}
+
+APP_ERROR CaptionPool::putCaptionAndMask(std::string text1, std::string text2, MxBase::Tensor caption,
+                                         MxBase::Tensor mask) {
+    std::string textMark = text1 + "_" + text2;
+    if(text2MaskMap_ != nullptr && text2CaptionMap_ != nullptr) {
+        text2CaptionMap_->put(textMark, caption);
+        text2MaskMap_->put(textMark, mask);
+        return APP_ERR_OK;
+    }
+    return APP_ERR_COMM_FAILURE;
+}
+
+APP_ERROR CaptionPool::getCaptionAndMask(std::string text1, std::string text2, MxBase::Tensor& caption,
+                                         MxBase::Tensor& mask) {
+    std::string textMark = text1 + "_" + text2;
+    if (text2MaskMap_ != nullptr && text2CaptionMap_ != nullptr &&
+        text2CaptionMap_->get(textMark, caption) && text2MaskMap_->get(textMark, mask)) {
+        return APP_ERR_OK;
+    }
+    return APP_ERR_COMM_FAILURE;
+}
+
+bool CaptionPool::isCaptionExist(std::string text1, std::string text2) {
+    std::string textMark = text1 + "_" + text2;
+    if (text2MaskMap_ != nullptr && text2CaptionMap_ != nullptr &&
+        text2MaskMap_->isExist(textMark) && text2CaptionMap_->isExist(textMark)) {
+        return true;
+    }
+    return false;
+}
+
+APP_ERROR CaptionPool::putCaptionLength(std::string text, int length) {
+    if (text2Lenghth_ != nullptr) {
+        text2Lenghth_->put(text, length);
+        return APP_ERR_OK;
+    }
+    return APP_ERR_COMM_FAILURE;
+}
+
+
+APP_ERROR CaptionPool::getCaptionLength(std::string text, int& length) {
+    if (text2Lenghth_ != nullptr && text2Lenghth_->get(text, length)) {
+        return APP_ERR_OK;
+    }
+    return APP_ERR_COMM_FAILURE;
+}
+
+bool CaptionPool::isCaptionLengthExist(std::string text) {
+    if (text2Lenghth_ != nullptr && text2Lenghth_->isExist(text)) {
+        return true;
+    }
+    return false;
 }
\ No newline at end of file
diff --git a/mxVision/PutText/PutText/CaptionPool.h b/mxVision/mxVision-referenceapps/PutText/PutText/CaptionPool.h
similarity index 96%
rename from mxVision/PutText/PutText/CaptionPool.h
rename to mxVision/mxVision-referenceapps/PutText/PutText/CaptionPool.h
index 71ad232d63289e94bcf462a35380e15bc9d24817..80ceb1bb471457aa49675818c794db4f4b933b72 100644
--- a/mxVision/PutText/PutText/CaptionPool.h
+++ b/mxVision/mxVision-referenceapps/PutText/PutText/CaptionPool.h
@@ -1,91 +1,91 @@
-/*
- * Copyright(C) 2024. Huawei Technologies Co.,Ltd. All rights reserved.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-#ifndef CAPTIONPOOL_H
-#define CAPTIONPOOL_H
-
-#include <iostream>
-#include <list>
-#include <unordered_map>
-#include "MxBase/MxBase.h"
-
-const int CAPTION_POOL_DEFAULT_SIZE = 10;
-
-template <typename K, typename V>
-class LimitedSizeMap {
-public:
-    explicit LimitedSizeMap(size_t max_size) {
-        max_size_ = max_size;
-    }
-
-    void put(const K& key, const V& value) {
-        if (map.find(key) == map.end()) {
-            if (order.size() >= max_size_) {
-                K oldest = order.front();
-                order.pop_front();
-                map.erase(oldest);
-            }
-            order.push_back(key);
-        } else {
-            order.remove(key);
-            order.push_back(key);
-        }
-        map[key] = value;
-    }
-
-    bool get(const K& key, V& value) {
-        if (map.find(key) != map.end()) {
-            value = map[key];
-            return true;
-        }
-        return false;
-    }
-
-    bool isExist(const K& key) {
-        if (map.find(key) != map.end()) {
-            return true;
-        }
-        return false;
-    }
-
-private:
-    size_t max_size_;
-    std::list<K> order;
-    std::unordered_map<K, V> map;
-};
-
-class CaptionPool {
-public:
-    explicit CaptionPool(size_t max_size = CAPTION_POOL_DEFAULT_SIZE);
-
-    APP_ERROR putCaptionAndMask(std::string text1, std::string text2, MxBase::Tensor caption, MxBase::Tensor mask);
-
-    APP_ERROR getCaptionAndMask(std::string text1, std::string text2, MxBase::Tensor& caption, MxBase::Tensor& mask);
-
-    bool isCaptionExist(std::string text1, std::string text2);
-
-    APP_ERROR putCaptionLength(std::string text, int length);
-
-    APP_ERROR getCaptionLength(std::string text, int& length);
-
-    bool isCaptionLengthExist(std::string text);
-
-private:
-    std::shared_ptr<LimitedSizeMap<std::string, MxBase::Tensor>> text2CaptionMap_;
-    std::shared_ptr<LimitedSizeMap<std::string, MxBase::Tensor>> text2MaskMap_;
-    std::shared_ptr<LimitedSizeMap<std::string, int>> text2Lenghth_;
-};
-
+/*
+ * Copyright(C) 2024. Huawei Technologies Co.,Ltd. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#ifndef CAPTIONPOOL_H
+#define CAPTIONPOOL_H
+
+#include <iostream>
+#include <list>
+#include <unordered_map>
+#include "MxBase/MxBase.h"
+
+const int CAPTION_POOL_DEFAULT_SIZE = 10;
+
+template <typename K, typename V>
+class LimitedSizeMap {
+public:
+    explicit LimitedSizeMap(size_t max_size) {
+        max_size_ = max_size;
+    }
+
+    void put(const K& key, const V& value) {
+        if (map.find(key) == map.end()) {
+            if (order.size() >= max_size_) {
+                K oldest = order.front();
+                order.pop_front();
+                map.erase(oldest);
+            }
+            order.push_back(key);
+        } else {
+            order.remove(key);
+            order.push_back(key);
+        }
+        map[key] = value;
+    }
+
+    bool get(const K& key, V& value) {
+        if (map.find(key) != map.end()) {
+            value = map[key];
+            return true;
+        }
+        return false;
+    }
+
+    bool isExist(const K& key) {
+        if (map.find(key) != map.end()) {
+            return true;
+        }
+        return false;
+    }
+
+private:
+    size_t max_size_;
+    std::list<K> order;
+    std::unordered_map<K, V> map;
+};
+
+class CaptionPool {
+public:
+    explicit CaptionPool(size_t max_size = CAPTION_POOL_DEFAULT_SIZE);
+
+    APP_ERROR putCaptionAndMask(std::string text1, std::string text2, MxBase::Tensor caption, MxBase::Tensor mask);
+
+    APP_ERROR getCaptionAndMask(std::string text1, std::string text2, MxBase::Tensor& caption, MxBase::Tensor& mask);
+
+    bool isCaptionExist(std::string text1, std::string text2);
+
+    APP_ERROR putCaptionLength(std::string text, int length);
+
+    APP_ERROR getCaptionLength(std::string text, int& length);
+
+    bool isCaptionLengthExist(std::string text);
+
+private:
+    std::shared_ptr<LimitedSizeMap<std::string, MxBase::Tensor>> text2CaptionMap_;
+    std::shared_ptr<LimitedSizeMap<std::string, MxBase::Tensor>> text2MaskMap_;
+    std::shared_ptr<LimitedSizeMap<std::string, int>> text2Lenghth_;
+};
+
 #endif 
\ No newline at end of file
diff --git a/mxVision/PutText/PutText/main.cpp b/mxVision/mxVision-referenceapps/PutText/PutText/main.cpp
similarity index 100%
rename from mxVision/PutText/PutText/main.cpp
rename to mxVision/mxVision-referenceapps/PutText/PutText/main.cpp
diff --git a/mxVision/PutText/PutText/readme.md b/mxVision/mxVision-referenceapps/PutText/PutText/readme.md
similarity index 100%
rename from mxVision/PutText/PutText/readme.md
rename to mxVision/mxVision-referenceapps/PutText/PutText/readme.md
diff --git a/mxVision/PutText/VocabGeneration/gen_font_textures.py b/mxVision/mxVision-referenceapps/PutText/VocabGeneration/gen_font_textures.py
similarity index 100%
rename from mxVision/PutText/VocabGeneration/gen_font_textures.py
rename to mxVision/mxVision-referenceapps/PutText/VocabGeneration/gen_font_textures.py
diff --git a/mxVision/PutText/VocabGeneration/readme.md b/mxVision/mxVision-referenceapps/PutText/VocabGeneration/readme.md
similarity index 100%
rename from mxVision/PutText/VocabGeneration/readme.md
rename to mxVision/mxVision-referenceapps/PutText/VocabGeneration/readme.md
diff --git a/mxVision/PutText/VocabGeneration/requirement.txt b/mxVision/mxVision-referenceapps/PutText/VocabGeneration/requirement.txt
similarity index 100%
rename from mxVision/PutText/VocabGeneration/requirement.txt
rename to mxVision/mxVision-referenceapps/PutText/VocabGeneration/requirement.txt
diff --git a/mxVision/PutText/VocabGeneration/vocab.txt b/mxVision/mxVision-referenceapps/PutText/VocabGeneration/vocab.txt
similarity index 100%
rename from mxVision/PutText/VocabGeneration/vocab.txt
rename to mxVision/mxVision-referenceapps/PutText/VocabGeneration/vocab.txt
diff --git a/contrib/RTM3DTargetDetection/README.md b/mxVision/mxVision-referenceapps/RTM3DTargetDetection/README.md
similarity index 100%
rename from contrib/RTM3DTargetDetection/README.md
rename to mxVision/mxVision-referenceapps/RTM3DTargetDetection/README.md
diff --git a/contrib/RTM3DTargetDetection/build.sh b/mxVision/mxVision-referenceapps/RTM3DTargetDetection/build.sh
similarity index 100%
rename from contrib/RTM3DTargetDetection/build.sh
rename to mxVision/mxVision-referenceapps/RTM3DTargetDetection/build.sh
diff --git a/contrib/RTM3DTargetDetection/draw_box.py b/mxVision/mxVision-referenceapps/RTM3DTargetDetection/draw_box.py
similarity index 100%
rename from contrib/RTM3DTargetDetection/draw_box.py
rename to mxVision/mxVision-referenceapps/RTM3DTargetDetection/draw_box.py
diff --git "a/contrib/RTM3DTargetDetection/images/3D\347\233\256\346\240\207pipeline\346\265\201\347\250\213\345\233\276.png" "b/mxVision/mxVision-referenceapps/RTM3DTargetDetection/images/3D\347\233\256\346\240\207pipeline\346\265\201\347\250\213\345\233\276.png"
similarity index 100%
rename from "contrib/RTM3DTargetDetection/images/3D\347\233\256\346\240\207pipeline\346\265\201\347\250\213\345\233\276.png"
rename to "mxVision/mxVision-referenceapps/RTM3DTargetDetection/images/3D\347\233\256\346\240\207pipeline\346\265\201\347\250\213\345\233\276.png"
diff --git "a/contrib/RTM3DTargetDetection/images/3D\347\233\256\346\240\207\346\243\200\346\265\213\346\265\201\347\250\213\345\233\276.png" "b/mxVision/mxVision-referenceapps/RTM3DTargetDetection/images/3D\347\233\256\346\240\207\346\243\200\346\265\213\346\265\201\347\250\213\345\233\276.png"
similarity index 100%
rename from "contrib/RTM3DTargetDetection/images/3D\347\233\256\346\240\207\346\243\200\346\265\213\346\265\201\347\250\213\345\233\276.png"
rename to "mxVision/mxVision-referenceapps/RTM3DTargetDetection/images/3D\347\233\256\346\240\207\346\243\200\346\265\213\346\265\201\347\250\213\345\233\276.png"
diff --git a/contrib/RTM3DTargetDetection/main.py b/mxVision/mxVision-referenceapps/RTM3DTargetDetection/main.py
similarity index 100%
rename from contrib/RTM3DTargetDetection/main.py
rename to mxVision/mxVision-referenceapps/RTM3DTargetDetection/main.py
diff --git a/contrib/RTM3DTargetDetection/models/coco.names b/mxVision/mxVision-referenceapps/RTM3DTargetDetection/models/coco.names
similarity index 100%
rename from contrib/RTM3DTargetDetection/models/coco.names
rename to mxVision/mxVision-referenceapps/RTM3DTargetDetection/models/coco.names
diff --git a/contrib/RTM3DTargetDetection/models/dla34.aippconfig b/mxVision/mxVision-referenceapps/RTM3DTargetDetection/models/dla34.aippconfig
similarity index 100%
rename from contrib/RTM3DTargetDetection/models/dla34.aippconfig
rename to mxVision/mxVision-referenceapps/RTM3DTargetDetection/models/dla34.aippconfig
diff --git a/contrib/RTM3DTargetDetection/models/rtm3d.cfg b/mxVision/mxVision-referenceapps/RTM3DTargetDetection/models/rtm3d.cfg
similarity index 100%
rename from contrib/RTM3DTargetDetection/models/rtm3d.cfg
rename to mxVision/mxVision-referenceapps/RTM3DTargetDetection/models/rtm3d.cfg
diff --git a/contrib/RTM3DTargetDetection/pipeline/rtm3d.pipeline b/mxVision/mxVision-referenceapps/RTM3DTargetDetection/pipeline/rtm3d.pipeline
similarity index 100%
rename from contrib/RTM3DTargetDetection/pipeline/rtm3d.pipeline
rename to mxVision/mxVision-referenceapps/RTM3DTargetDetection/pipeline/rtm3d.pipeline
diff --git a/contrib/RTM3DTargetDetection/plugins/RTM3DPostProcess/CMakeLists.txt b/mxVision/mxVision-referenceapps/RTM3DTargetDetection/plugins/RTM3DPostProcess/CMakeLists.txt
similarity index 100%
rename from contrib/RTM3DTargetDetection/plugins/RTM3DPostProcess/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/RTM3DTargetDetection/plugins/RTM3DPostProcess/CMakeLists.txt
diff --git a/contrib/RTM3DTargetDetection/plugins/RTM3DPostProcess/RTM3DPostProcess.cpp b/mxVision/mxVision-referenceapps/RTM3DTargetDetection/plugins/RTM3DPostProcess/RTM3DPostProcess.cpp
similarity index 100%
rename from contrib/RTM3DTargetDetection/plugins/RTM3DPostProcess/RTM3DPostProcess.cpp
rename to mxVision/mxVision-referenceapps/RTM3DTargetDetection/plugins/RTM3DPostProcess/RTM3DPostProcess.cpp
diff --git a/contrib/RTM3DTargetDetection/plugins/RTM3DPostProcess/RTM3DPostProcess.h b/mxVision/mxVision-referenceapps/RTM3DTargetDetection/plugins/RTM3DPostProcess/RTM3DPostProcess.h
similarity index 100%
rename from contrib/RTM3DTargetDetection/plugins/RTM3DPostProcess/RTM3DPostProcess.h
rename to mxVision/mxVision-referenceapps/RTM3DTargetDetection/plugins/RTM3DPostProcess/RTM3DPostProcess.h
diff --git a/contrib/RTM3DTargetDetection/plugins/RTM3DPostProcess/build.sh b/mxVision/mxVision-referenceapps/RTM3DTargetDetection/plugins/RTM3DPostProcess/build.sh
similarity index 100%
rename from contrib/RTM3DTargetDetection/plugins/RTM3DPostProcess/build.sh
rename to mxVision/mxVision-referenceapps/RTM3DTargetDetection/plugins/RTM3DPostProcess/build.sh
diff --git a/contrib/RTM3DTargetDetection/plugins/build.sh b/mxVision/mxVision-referenceapps/RTM3DTargetDetection/plugins/build.sh
similarity index 100%
rename from contrib/RTM3DTargetDetection/plugins/build.sh
rename to mxVision/mxVision-referenceapps/RTM3DTargetDetection/plugins/build.sh
diff --git a/contrib/RTMHumanKeypointsDetection/.gitignore b/mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/.gitignore
similarity index 100%
rename from contrib/RTMHumanKeypointsDetection/.gitignore
rename to mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/.gitignore
diff --git a/contrib/RTMHumanKeypointsDetection/CMakeLists.txt b/mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/CMakeLists.txt
similarity index 100%
rename from contrib/RTMHumanKeypointsDetection/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/CMakeLists.txt
diff --git a/contrib/RTMHumanKeypointsDetection/README.md b/mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/README.md
similarity index 97%
rename from contrib/RTMHumanKeypointsDetection/README.md
rename to mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/README.md
index 6ed27603613f5f7c19f4ebc31cdd03e8523fefb5..f8aa560b257695cd533155496cf523eeef8cb8ca 100644
--- a/contrib/RTMHumanKeypointsDetection/README.md
+++ b/mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/README.md
@@ -1,248 +1,248 @@
-# 实时人体关键点检测
-
-## 1 介绍
-
-### 1.1 简介
-人体关键点检测是指在输入图像上对指定的 18 类人体骨骼关键点位置进行检测，然后将关键点正确配对组成相应的人体骨架，展示人体姿态。本项目基于MindX SDK，在昇腾平台上，实现了对RTSP视频流进行人体关键点检测并连接成人体骨架，最后将检测结果可视化并保存。
-本系统技术流程图如下所示：
-
-![pipeline](image/pipeline.png)
-
-本系统设计了不同的功能模块。主要流程为：视频拉流传入业务流中，然后通过解码插件对视频进行解码，再对解码出来的YUV图像进行尺寸调整，然后利用OpenPose模型进行人体关键点检测，然后我们自己编写的后处理插件会把人体关键点信息传递给绘图插件，绘图完毕后进行视频编码，最后把结果输出。各模块功能描述如下表所示：
-
-
-| 序号 | 子系统     | 功能描述                                                     |
-| :--- | :--------- | :----------------------------------------------------------- |
-| 1    | 视频拉流   | 调用MindX SDK的 **mxpi_rtspsrc**接收外部调用接口的输入视频路径，对视频进行拉流 |
-| 2    | 视频解码   | 调用MindX SDK的**mxpi_videodecoder**                         |
-| 3    | 图像缩放   | 调用**mxpi_imageresize**对解码后的YUV格式的图像进行指定宽高的缩放 |
-| 4    | 检测推理   | 使用已经训练好的OpenPose模型，检测出图像中的车辆信息。插件：**mxpi_tensorinfer** |
-| 5    | 模型后处理 | 使用自己编译的**mxpi_rtmopenposepostprocess**插件的后处理库libmxpi_rtmopenposepostprocess.so，进行人体关键点检测的后处理 |
-| 6    | 绘图       | 调用OSD基础功能在YUV图片上绘制直线。插件：**mxpi_opencvosd** |
-| 7    | 视频编码   | 调用MindX SDK的**mxpi_videoencoder**进行视频编码             |
-| 8    | 输出       | 调用MindX SDK的**appsink**进行业务流结果的输出               |
-
-
-
-使用测试视频应当人物清晰、光线充足、无环境背景干扰，而且人物在画面中占据范围不应太小、人物姿态不应过于扭曲、人物不应完全侧对镜头、背景不应太复杂；视频切勿有遮挡，不清晰等情况。
-### 1.2 支持的产品
-
-x86_64 Atlas 300I（型号3010）和arm Atlas 300I（型号3000）。
-
-### 1.3 支持的版本
-
-本样例配套的MxVision版本、CANN版本、Driver/Firmware版本如下所示：
-
-| MxVision版本  | CANN版本  | Driver/Firmware版本  |
-| --------- | ------------------ | -------------- | 
-| 5.0.0 | 7.0.0   |  23.0.0  |
-
-### 1.4 三方依赖
-本项目除了依赖昇腾Driver、Firmware、CANN和mxVision及其要求的配套软件外，还需额外依赖以下软件：
-
-| 软件名称 | 版本   |
-| -------- | ----- |
-| live555  | 1.09 |
-
-*精度验证需要额外的依赖，详见第5节（精度验证）。
-### 1.5 代码目录结构说明
-
-本工程名称为RTMHumanKeypointsDetection，工程目录如下图所示：
-
-```
-├── build.sh  # 编译
-├── CMakeLists.txt
-├── eval  # 用于精度验证
-│   ├── eval.py
-│   ├── pipeline
-│   │   └── rtmOpenposeEval.pipeline
-│   ├── plugin
-│   │   ├── build.sh
-│   │   ├── CMakeLists.txt
-│   │   ├── MxpiRTMOpenposePostProcessEval.cpp
-│   │   └── MxpiRTMOpenposePostProcessEval.h
-│   └── proto
-│       ├── build.sh
-│       ├── CMakeLists.txt
-│       └── MxpiRTMOpenposeProtoEval.proto
-├── image
-│   └── pipeline.png
-├── main.cpp
-├── models
-│   └── insert_op.cfg
-├── pipeline
-│   └── rtmOpenpose.pipeline
-├── plugins  # 实时人体关键点检测后处理库
-│   ├── build.sh
-│   ├── CMakeLists.txt
-│   ├── MxpiRTMOpenposePostProcess.cpp
-│   └── MxpiRTMOpenposePostProcess.h
-├── README.md
-└── run.sh   # 运行
-```
-
-
-## 2 设置环境变量
-
-在执行后续步骤前，需要设置环境变量：
-
-```bash
-# 执行环境变量脚本使环境变量生效
-. ${ascend-toolkit-path}/set_env.sh
-. ${mxVision-path}/set_env.sh
-# mxVision: mxVision安装路径
-# ascend-toolkit-path: CANN安装路径
-```
-## 3 准备模型
-
-本项目需要使用的模型包括用于人体姿态估计的模型和用于画图的osd模型，需要执行以下步骤得到：
-
-步骤1 下载模型相关文件
-根据[链接](https://gitee.com/link?target=https%3A%2F%2Fmindx.sdk.obs.cn-north-4.myhuaweicloud.com%2Fmindxsdk-referenceapps%2520%2Fcontrib%2FRTMHumanKeypointsDetection%2Fhuman-pose-estimation512.onnx)下载得到human-pose-estimation512.onnx文件。
-
-步骤2 转换模型格式
-
-将onnx模型拷贝至"${RTMHumanKeypointsDetection代码包目录}/models/"目录下，并在拷贝目标目录下执行以下命令将onnx模型转换成om模型：
-
-       atc --model=./human-pose-estimation512.onnx --framework=5 --output=openpose_pytorch_512 --soc_version=Ascend310 --input_shape="data:1, 3, 512, 512" --input_format=NCHW --insert_op_conf=./insert_op.cfg
-
-步骤3 生成osd模型文件
-
-本项目需要使用 `mxpi_opencvosd` 插件，使用前需要生成所需的模型文件。执行MindX SDK开发套件包安装目录下 `operators/opencvosd/generate_osd_om.sh` 脚本生成所需模型文件。
-
-## 4 编译与运行
-步骤1 创建rtsp视频流
-
-使用live555创建rtsp视频流，live555的使用方法可以参考[链接](https://gitee.com/ascend/docs-openmind/blob/master/guide/mindx/sdk/tutorials/reference_material/Live555%E7%A6%BB%E7%BA%BF%E8%A7%86%E9%A2%91%E8%BD%ACRTSP%E8%AF%B4%E6%98%8E%E6%96%87%E6%A1%A3.md)。
-
-步骤2 配置pipeline文件中的rtsp视频流地址、模型文件路径和视频的宽高
-
-打开`RTMHumanKeypointsDetection/pipeline`目录下的rtmOpenpose.pipeline文件。根据步骤1创建的rtsp视频流地址，设置mxpi_rtspsrc0的rtspUrl值，如下所示：
-
-```
-        "mxpi_rtspsrc0": {
-            "factory": "mxpi_rtspsrc",
-            "props": {
-                "rtspUrl":"rtsp://xxx.xxx.xxx.xxx:xxxx/xxx.264",      // 修改为自己所使用的的服务器和文件名
-                "channelId": "0"
-            },
-            "next": "mxpi_videodecoder0"
-        },
-```
-
-
-根据om模型的文件路径，设置mxpi_tensorinfer0的modelPath值，如下所示：
-
-```
-        "mxpi_tensorinfer0":{
-            "next":"mxpi_rtmopenposepostprocess0",
-            "factory":"mxpi_tensorinfer",
-            "props":{
-                "dataSource": "mxpi_imageresize0",
-                "modelPath":"./models/openpose_pytorch_512.om"	//检查om模型文件名是否正确
-            }
-        },
-```
-
-根据rtsp视频流中视频的实际高和宽，设置mxpi_videoencoder0的imageHeight和imageWidth值，如下所示：
-
-```
-        "mxpi_videoencoder0":{
-            "props": {
-                "inputFormat": "YUV420SP_NV12",
-                "outputFormat": "H264",
-                "fps": "1",
-                "iFrameInterval": "50",
-                "imageHeight": "720",		#rtsp视频流中视频的实际高
-                "imageWidth": "1280"		#rtsp视频流中视频的实际宽
-            },
-```
-
-步骤3 编译插件
-
-在`plugins/`目录里面执行命令：
-
-```bash
-bash build.sh
-```
-
-
-步骤4 编译和运行主程序
-
-回到项目主目录下执行命令：
-
-```bash
-bash run.sh
-```
-
-步骤5 停止服务
-
-命令行输入Ctrl+C组合键可停止服务。
-
-步骤6 查看结果
-
-命令执行成功后会在控制台输出检测的帧率，并在当前目录下生成结果视频文件`out.h264`。
-
-## 5 精度验证
-步骤1 安装 python COCO 评测工具
-执行命令：
-```
-pip3 install pycocotools
-```
-步骤2 下载 COCO VAL 2017 数据集
-下载 COCO VAL 2017 数据集，下载链接：https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/OpenposeKeypointDetection/data.zip
-在 ``eval`` 目录下创建 ``dataset`` 目录，将数据集压缩文件解压至 ``eval/dataset`` 目录下。确保下载完数据集和标注文件后的 eval 目录结构为：
-```
-.
-├── dataset
-│   ├── annotations
-│   │   └── person_keypoints_val2017.json
-│   └── val2017
-│       ├── 000000581615.jpg
-│       ├── 000000581781.jpg
-│       └── other-images
-└── eval.py
-
-```
-步骤3 编译proto
-在 eval/proto/ 目录中执行命令：
-```
-bash build.sh
-```
-
-步骤4 编译用于精度测试的后处理插件
-在 eval/plugins/ 目录中执行命令：
-```
-bash build.sh
-```
-
-步骤5 执行命令：
-在 eval/ 目录中执行命令：
-```
-python3 eval.py
-```
-
-## 6 常见问题
-
-### 6.1 检测输出帧率过低问题
-
-问题描述：控制台输出检测的帧率低于25fps（如下10fps），如下所示：
-
-```bash
-I20220727 09:21:02.990229 32360 MxpiVideoEncoder.cpp:324] Plugin(mxpi_videoencoder0) fps (10).
-```
-
-解决方案： 确保输入的视频帧率高于25fps。
-
-### 6.2 视频编码参数配置错误问题
-
-问题描述：运行过程中报错如下：
-
-```bash
-E20220728 17:05:59.947093 19710 DvppWrapper.cpp:573] input width(888) is not same as venc input format(1280)
-E20220728 17:05:59.947126 19710 MxpiVideoEncoder.cpp:310] [mxpi_videoencoder0][2010][DVPP: encode H264 or H265 fail] Encode fail.
-```
-
-`pipeline/rtmOpenpose.pipeline`中视频编码插件分辨率参数指定错误。手动指定imageHeight 和 imageWidth 属性，需要和rtsp视频流中视频的分配率相同。
-
-解决方案：确保`pipeline/rtmOpenpose.pipeline`中 mxpi_videoencoder0 插件中的 imageHeight 和 imageWidth 为rtsp视频流中视频的实际高和宽。
+# 实时人体关键点检测
+
+## 1 介绍
+
+### 1.1 简介
+人体关键点检测是指在输入图像上对指定的 18 类人体骨骼关键点位置进行检测，然后将关键点正确配对组成相应的人体骨架，展示人体姿态。本项目基于MindX SDK，在昇腾平台上，实现了对RTSP视频流进行人体关键点检测并连接成人体骨架，最后将检测结果可视化并保存。
+本系统技术流程图如下所示：
+
+![pipeline](image/pipeline.png)
+
+本系统设计了不同的功能模块。主要流程为：视频拉流传入业务流中，然后通过解码插件对视频进行解码，再对解码出来的YUV图像进行尺寸调整，然后利用OpenPose模型进行人体关键点检测，然后我们自己编写的后处理插件会把人体关键点信息传递给绘图插件，绘图完毕后进行视频编码，最后把结果输出。各模块功能描述如下表所示：
+
+
+| 序号 | 子系统     | 功能描述                                                     |
+| :--- | :--------- | :----------------------------------------------------------- |
+| 1    | 视频拉流   | 调用MindX SDK的 **mxpi_rtspsrc**接收外部调用接口的输入视频路径，对视频进行拉流 |
+| 2    | 视频解码   | 调用MindX SDK的**mxpi_videodecoder**                         |
+| 3    | 图像缩放   | 调用**mxpi_imageresize**对解码后的YUV格式的图像进行指定宽高的缩放 |
+| 4    | 检测推理   | 使用已经训练好的OpenPose模型，检测出图像中的车辆信息。插件：**mxpi_tensorinfer** |
+| 5    | 模型后处理 | 使用自己编译的**mxpi_rtmopenposepostprocess**插件的后处理库libmxpi_rtmopenposepostprocess.so，进行人体关键点检测的后处理 |
+| 6    | 绘图       | 调用OSD基础功能在YUV图片上绘制直线。插件：**mxpi_opencvosd** |
+| 7    | 视频编码   | 调用MindX SDK的**mxpi_videoencoder**进行视频编码             |
+| 8    | 输出       | 调用MindX SDK的**appsink**进行业务流结果的输出               |
+
+
+
+使用测试视频应当人物清晰、光线充足、无环境背景干扰，而且人物在画面中占据范围不应太小、人物姿态不应过于扭曲、人物不应完全侧对镜头、背景不应太复杂；视频切勿有遮挡，不清晰等情况。
+### 1.2 支持的产品
+
+x86_64 Atlas 300I（型号3010）和arm Atlas 300I（型号3000）。
+
+### 1.3 支持的版本
+
+本样例配套的MxVision版本、CANN版本、Driver/Firmware版本如下所示：
+
+| MxVision版本  | CANN版本  | Driver/Firmware版本  |
+| --------- | ------------------ | -------------- | 
+| 5.0.0 | 7.0.0   |  23.0.0  |
+
+### 1.4 三方依赖
+本项目除了依赖昇腾Driver、Firmware、CANN和mxVision及其要求的配套软件外，还需额外依赖以下软件：
+
+| 软件名称 | 版本   |
+| -------- | ----- |
+| live555  | 1.09 |
+
+*精度验证需要额外的依赖，详见第5节（精度验证）。
+### 1.5 代码目录结构说明
+
+本工程名称为RTMHumanKeypointsDetection，工程目录如下图所示：
+
+```
+├── build.sh  # 编译
+├── CMakeLists.txt
+├── eval  # 用于精度验证
+│   ├── eval.py
+│   ├── pipeline
+│   │   └── rtmOpenposeEval.pipeline
+│   ├── plugin
+│   │   ├── build.sh
+│   │   ├── CMakeLists.txt
+│   │   ├── MxpiRTMOpenposePostProcessEval.cpp
+│   │   └── MxpiRTMOpenposePostProcessEval.h
+│   └── proto
+│       ├── build.sh
+│       ├── CMakeLists.txt
+│       └── MxpiRTMOpenposeProtoEval.proto
+├── image
+│   └── pipeline.png
+├── main.cpp
+├── models
+│   └── insert_op.cfg
+├── pipeline
+│   └── rtmOpenpose.pipeline
+├── plugins  # 实时人体关键点检测后处理库
+│   ├── build.sh
+│   ├── CMakeLists.txt
+│   ├── MxpiRTMOpenposePostProcess.cpp
+│   └── MxpiRTMOpenposePostProcess.h
+├── README.md
+└── run.sh   # 运行
+```
+
+
+## 2 设置环境变量
+
+在执行后续步骤前，需要设置环境变量：
+
+```bash
+# 执行环境变量脚本使环境变量生效
+. ${ascend-toolkit-path}/set_env.sh
+. ${mxVision-path}/set_env.sh
+# mxVision: mxVision安装路径
+# ascend-toolkit-path: CANN安装路径
+```
+## 3 准备模型
+
+本项目需要使用的模型包括用于人体姿态估计的模型和用于画图的osd模型，需要执行以下步骤得到：
+
+步骤1 下载模型相关文件
+根据[链接](https://gitee.com/link?target=https%3A%2F%2Fmindx.sdk.obs.cn-north-4.myhuaweicloud.com%2Fmindxsdk-referenceapps%2520%2Fcontrib%2FRTMHumanKeypointsDetection%2Fhuman-pose-estimation512.onnx)下载得到human-pose-estimation512.onnx文件。
+
+步骤2 转换模型格式
+
+将onnx模型拷贝至"${RTMHumanKeypointsDetection代码包目录}/models/"目录下，并在拷贝目标目录下执行以下命令将onnx模型转换成om模型：
+
+       atc --model=./human-pose-estimation512.onnx --framework=5 --output=openpose_pytorch_512 --soc_version=Ascend310 --input_shape="data:1, 3, 512, 512" --input_format=NCHW --insert_op_conf=./insert_op.cfg
+
+步骤3 生成osd模型文件
+
+本项目需要使用 `mxpi_opencvosd` 插件，使用前需要生成所需的模型文件。执行MindX SDK开发套件包安装目录下 `operators/opencvosd/generate_osd_om.sh` 脚本生成所需模型文件。
+
+## 4 编译与运行
+步骤1 创建rtsp视频流
+
+使用live555创建rtsp视频流，live555的使用方法可以参考[链接](https://gitee.com/ascend/docs-openmind/blob/master/guide/mindx/sdk/tutorials/reference_material/Live555%E7%A6%BB%E7%BA%BF%E8%A7%86%E9%A2%91%E8%BD%ACRTSP%E8%AF%B4%E6%98%8E%E6%96%87%E6%A1%A3.md)。
+
+步骤2 配置pipeline文件中的rtsp视频流地址、模型文件路径和视频的宽高
+
+打开`RTMHumanKeypointsDetection/pipeline`目录下的rtmOpenpose.pipeline文件。根据步骤1创建的rtsp视频流地址，设置mxpi_rtspsrc0的rtspUrl值，如下所示：
+
+```
+        "mxpi_rtspsrc0": {
+            "factory": "mxpi_rtspsrc",
+            "props": {
+                "rtspUrl":"rtsp://xxx.xxx.xxx.xxx:xxxx/xxx.264",      // 修改为自己所使用的的服务器和文件名
+                "channelId": "0"
+            },
+            "next": "mxpi_videodecoder0"
+        },
+```
+
+
+根据om模型的文件路径，设置mxpi_tensorinfer0的modelPath值，如下所示：
+
+```
+        "mxpi_tensorinfer0":{
+            "next":"mxpi_rtmopenposepostprocess0",
+            "factory":"mxpi_tensorinfer",
+            "props":{
+                "dataSource": "mxpi_imageresize0",
+                "modelPath":"./models/openpose_pytorch_512.om"	//检查om模型文件名是否正确
+            }
+        },
+```
+
+根据rtsp视频流中视频的实际高和宽，设置mxpi_videoencoder0的imageHeight和imageWidth值，如下所示：
+
+```
+        "mxpi_videoencoder0":{
+            "props": {
+                "inputFormat": "YUV420SP_NV12",
+                "outputFormat": "H264",
+                "fps": "1",
+                "iFrameInterval": "50",
+                "imageHeight": "720",		#rtsp视频流中视频的实际高
+                "imageWidth": "1280"		#rtsp视频流中视频的实际宽
+            },
+```
+
+步骤3 编译插件
+
+在`plugins/`目录里面执行命令：
+
+```bash
+bash build.sh
+```
+
+
+步骤4 编译和运行主程序
+
+回到项目主目录下执行命令：
+
+```bash
+bash run.sh
+```
+
+步骤5 停止服务
+
+命令行输入Ctrl+C组合键可停止服务。
+
+步骤6 查看结果
+
+命令执行成功后会在控制台输出检测的帧率，并在当前目录下生成结果视频文件`out.h264`。
+
+## 5 精度验证
+步骤1 安装 python COCO 评测工具
+执行命令：
+```
+pip3 install pycocotools
+```
+步骤2 下载 COCO VAL 2017 数据集
+下载 COCO VAL 2017 数据集，下载链接：https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/OpenposeKeypointDetection/data.zip
+在 ``eval`` 目录下创建 ``dataset`` 目录，将数据集压缩文件解压至 ``eval/dataset`` 目录下。确保下载完数据集和标注文件后的 eval 目录结构为：
+```
+.
+├── dataset
+│   ├── annotations
+│   │   └── person_keypoints_val2017.json
+│   └── val2017
+│       ├── 000000581615.jpg
+│       ├── 000000581781.jpg
+│       └── other-images
+└── eval.py
+
+```
+步骤3 编译proto
+在 eval/proto/ 目录中执行命令：
+```
+bash build.sh
+```
+
+步骤4 编译用于精度测试的后处理插件
+在 eval/plugins/ 目录中执行命令：
+```
+bash build.sh
+```
+
+步骤5 执行命令：
+在 eval/ 目录中执行命令：
+```
+python3 eval.py
+```
+
+## 6 常见问题
+
+### 6.1 检测输出帧率过低问题
+
+问题描述：控制台输出检测的帧率低于25fps（如下10fps），如下所示：
+
+```bash
+I20220727 09:21:02.990229 32360 MxpiVideoEncoder.cpp:324] Plugin(mxpi_videoencoder0) fps (10).
+```
+
+解决方案： 确保输入的视频帧率高于25fps。
+
+### 6.2 视频编码参数配置错误问题
+
+问题描述：运行过程中报错如下：
+
+```bash
+E20220728 17:05:59.947093 19710 DvppWrapper.cpp:573] input width(888) is not same as venc input format(1280)
+E20220728 17:05:59.947126 19710 MxpiVideoEncoder.cpp:310] [mxpi_videoencoder0][2010][DVPP: encode H264 or H265 fail] Encode fail.
+```
+
+`pipeline/rtmOpenpose.pipeline`中视频编码插件分辨率参数指定错误。手动指定imageHeight 和 imageWidth 属性，需要和rtsp视频流中视频的分配率相同。
+
+解决方案：确保`pipeline/rtmOpenpose.pipeline`中 mxpi_videoencoder0 插件中的 imageHeight 和 imageWidth 为rtsp视频流中视频的实际高和宽。
diff --git a/contrib/RTMHumanKeypointsDetection/build.sh b/mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/build.sh
similarity index 100%
rename from contrib/RTMHumanKeypointsDetection/build.sh
rename to mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/build.sh
diff --git a/contrib/RTMHumanKeypointsDetection/eval/eval.py b/mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/eval/eval.py
similarity index 100%
rename from contrib/RTMHumanKeypointsDetection/eval/eval.py
rename to mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/eval/eval.py
diff --git a/contrib/RTMHumanKeypointsDetection/eval/pipeline/rtmOpenposeEval.pipeline b/mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/eval/pipeline/rtmOpenposeEval.pipeline
similarity index 100%
rename from contrib/RTMHumanKeypointsDetection/eval/pipeline/rtmOpenposeEval.pipeline
rename to mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/eval/pipeline/rtmOpenposeEval.pipeline
diff --git a/contrib/RTMHumanKeypointsDetection/eval/plugin/CMakeLists.txt b/mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/eval/plugin/CMakeLists.txt
similarity index 100%
rename from contrib/RTMHumanKeypointsDetection/eval/plugin/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/eval/plugin/CMakeLists.txt
diff --git a/contrib/RTMHumanKeypointsDetection/eval/plugin/MxpiRTMOpenposePostProcessEval.cpp b/mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/eval/plugin/MxpiRTMOpenposePostProcessEval.cpp
similarity index 100%
rename from contrib/RTMHumanKeypointsDetection/eval/plugin/MxpiRTMOpenposePostProcessEval.cpp
rename to mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/eval/plugin/MxpiRTMOpenposePostProcessEval.cpp
diff --git a/contrib/RTMHumanKeypointsDetection/eval/plugin/MxpiRTMOpenposePostProcessEval.h b/mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/eval/plugin/MxpiRTMOpenposePostProcessEval.h
similarity index 100%
rename from contrib/RTMHumanKeypointsDetection/eval/plugin/MxpiRTMOpenposePostProcessEval.h
rename to mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/eval/plugin/MxpiRTMOpenposePostProcessEval.h
diff --git a/contrib/RTMHumanKeypointsDetection/eval/plugin/build.sh b/mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/eval/plugin/build.sh
similarity index 100%
rename from contrib/RTMHumanKeypointsDetection/eval/plugin/build.sh
rename to mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/eval/plugin/build.sh
diff --git a/contrib/RTMHumanKeypointsDetection/eval/proto/CMakeLists.txt b/mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/eval/proto/CMakeLists.txt
similarity index 97%
rename from contrib/RTMHumanKeypointsDetection/eval/proto/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/eval/proto/CMakeLists.txt
index aa96dff7cc335c32ad81149811b994f0f6b354f7..b288cfa4c6e91fa1a4a25620de36832272697066 100644
--- a/contrib/RTMHumanKeypointsDetection/eval/proto/CMakeLists.txt
+++ b/mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/eval/proto/CMakeLists.txt
@@ -1,46 +1,46 @@
-cmake_minimum_required(VERSION 3.5.1)
-project(ProtoFile)
-
-set(TARGET_LIBRARY MxpiRTMOpenposeProtoEval)
-
-# Compile options
-add_definitions(-D_GLIBCXX_USE_CXX11_ABI=0)
-add_definitions(-Dgoogle=mindxsdk_private)
-add_compile_options(-std=c++11 -fPIC -fstack-protector-all -pie -Wno-deprecated-declarations)
-
-set(MX_SDK_HOME "$ENV{MX_SDK_HOME}")
-
-if (EXISTS ${MX_SDK_HOME})
-    set(PROTOBUF_FOUND TRUE)
-    set(PROTOBUF_PROTOC_EXECUTABLE ${MX_SDK_HOME}/opensource/bin/protoc)
-    set(PROTOBUF_INCLUDE_DIRS ${MX_SDK_HOME}/opensource/include)
-    include_directories(${PROTOBUF_INCLUDE_DIRS})
-    link_directories(${MX_SDK_HOME}/opensource/lib)
-
-endif ()
-if (PROTOBUF_FOUND)
-    message(STATUS "protobuf library found")
-
-else()
-    message(FATAL_ERROR "protobuf library is needed but cant be found")
-endif ()
-
-LIST(APPEND PROTO_FLAGS -I${PROJECT_SOURCE_DIR})
-
-EXECUTE_PROCESS(
-        COMMAND ${PROTOBUF_PROTOC_EXECUTABLE} ${PROTO_FLAGS} --cpp_out=${PROJECT_SOURCE_DIR} ${PROJECT_SOURCE_DIR}/MxpiRTMOpenposeProtoEval.proto
-        COMMAND ${PROTOBUF_PROTOC_EXECUTABLE} ${PROTO_FLAGS} --python_out=${PROJECT_SOURCE_DIR} ${PROJECT_SOURCE_DIR}/MxpiRTMOpenposeProtoEval.proto
-        WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}
-)
-
-file(GLOB_RECURSE SOURCE_FILES ${PROJECT_SOURCE_DIR}/*.cc)
-add_library(${TARGET_LIBRARY} SHARED ${SOURCE_FILES})
-target_link_libraries(${TARGET_LIBRARY} mindxsdk_protobuf)
-#target_link_libraries(${TARGET_LIBRARY} -Wl,-z,relro,-z,now,-z,noexecstack -s)
-
-if (ENABLE_TEST)
-    target_link_libraries(${TARGET_LIBRARY} gcov)
-endif ()
-
-set(LIBRARY_OUTPUT_PATH ${PROJECT_SOURCE_DIR}/lib)
-install(TARGETS ${TARGET_LIBRARY} LIBRARY DESTINATION ${PROJECT_SOURCE_DIR}/lib)
+cmake_minimum_required(VERSION 3.5.1)
+project(ProtoFile)
+
+set(TARGET_LIBRARY MxpiRTMOpenposeProtoEval)
+
+# Compile options
+add_definitions(-D_GLIBCXX_USE_CXX11_ABI=0)
+add_definitions(-Dgoogle=mindxsdk_private)
+add_compile_options(-std=c++11 -fPIC -fstack-protector-all -pie -Wno-deprecated-declarations)
+
+set(MX_SDK_HOME "$ENV{MX_SDK_HOME}")
+
+if (EXISTS ${MX_SDK_HOME})
+    set(PROTOBUF_FOUND TRUE)
+    set(PROTOBUF_PROTOC_EXECUTABLE ${MX_SDK_HOME}/opensource/bin/protoc)
+    set(PROTOBUF_INCLUDE_DIRS ${MX_SDK_HOME}/opensource/include)
+    include_directories(${PROTOBUF_INCLUDE_DIRS})
+    link_directories(${MX_SDK_HOME}/opensource/lib)
+
+endif ()
+if (PROTOBUF_FOUND)
+    message(STATUS "protobuf library found")
+
+else()
+    message(FATAL_ERROR "protobuf library is needed but cant be found")
+endif ()
+
+LIST(APPEND PROTO_FLAGS -I${PROJECT_SOURCE_DIR})
+
+EXECUTE_PROCESS(
+        COMMAND ${PROTOBUF_PROTOC_EXECUTABLE} ${PROTO_FLAGS} --cpp_out=${PROJECT_SOURCE_DIR} ${PROJECT_SOURCE_DIR}/MxpiRTMOpenposeProtoEval.proto
+        COMMAND ${PROTOBUF_PROTOC_EXECUTABLE} ${PROTO_FLAGS} --python_out=${PROJECT_SOURCE_DIR} ${PROJECT_SOURCE_DIR}/MxpiRTMOpenposeProtoEval.proto
+        WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}
+)
+
+file(GLOB_RECURSE SOURCE_FILES ${PROJECT_SOURCE_DIR}/*.cc)
+add_library(${TARGET_LIBRARY} SHARED ${SOURCE_FILES})
+target_link_libraries(${TARGET_LIBRARY} mindxsdk_protobuf)
+#target_link_libraries(${TARGET_LIBRARY} -Wl,-z,relro,-z,now,-z,noexecstack -s)
+
+if (ENABLE_TEST)
+    target_link_libraries(${TARGET_LIBRARY} gcov)
+endif ()
+
+set(LIBRARY_OUTPUT_PATH ${PROJECT_SOURCE_DIR}/lib)
+install(TARGETS ${TARGET_LIBRARY} LIBRARY DESTINATION ${PROJECT_SOURCE_DIR}/lib)
diff --git a/contrib/RTMHumanKeypointsDetection/eval/proto/MxpiRTMOpenposeProtoEval.proto b/mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/eval/proto/MxpiRTMOpenposeProtoEval.proto
similarity index 94%
rename from contrib/RTMHumanKeypointsDetection/eval/proto/MxpiRTMOpenposeProtoEval.proto
rename to mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/eval/proto/MxpiRTMOpenposeProtoEval.proto
index 1a3df4d4a41956ee909f1392f6b1da32683e0c0a..5d1843e59cbd54230b6c32b8b5ad39ede763cf1a 100644
--- a/contrib/RTMHumanKeypointsDetection/eval/proto/MxpiRTMOpenposeProtoEval.proto
+++ b/mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/eval/proto/MxpiRTMOpenposeProtoEval.proto
@@ -1,33 +1,33 @@
-syntax = "proto3";
-package MxpiRTMOpenposeProtoEval;
-message MxpiMetaHeader
-{
-string parentName = 1;
-int32 memberId = 2;
-string dataSource = 3;
-}
-
-message MxpiSkeletonInfo
-{
-int32 cocoSkeletonIndex1 = 1;
-int32 cocoSkeletonIndex2 = 2;
-float x0 = 3;
-float y0 = 4;
-float point1Score = 5;
-float x1 = 6;
-float y1 = 7;
-float point2Score = 8;
-float skeletonScore = 9;
-}
-
-message MxpiPersonInfo
-{
-repeated MxpiMetaHeader headerVec = 1;
-repeated MxpiSkeletonInfo skeletonInfoVec = 2;
-float score = 3;
-}
-
-message MxpiPersonList
-{
-repeated MxpiPersonInfo personInfoVec = 1;
+syntax = "proto3";
+package MxpiRTMOpenposeProtoEval;
+message MxpiMetaHeader
+{
+string parentName = 1;
+int32 memberId = 2;
+string dataSource = 3;
+}
+
+message MxpiSkeletonInfo
+{
+int32 cocoSkeletonIndex1 = 1;
+int32 cocoSkeletonIndex2 = 2;
+float x0 = 3;
+float y0 = 4;
+float point1Score = 5;
+float x1 = 6;
+float y1 = 7;
+float point2Score = 8;
+float skeletonScore = 9;
+}
+
+message MxpiPersonInfo
+{
+repeated MxpiMetaHeader headerVec = 1;
+repeated MxpiSkeletonInfo skeletonInfoVec = 2;
+float score = 3;
+}
+
+message MxpiPersonList
+{
+repeated MxpiPersonInfo personInfoVec = 1;
 }
\ No newline at end of file
diff --git a/contrib/RTMHumanKeypointsDetection/eval/proto/build.sh b/mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/eval/proto/build.sh
similarity index 100%
rename from contrib/RTMHumanKeypointsDetection/eval/proto/build.sh
rename to mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/eval/proto/build.sh
diff --git a/contrib/RTMHumanKeypointsDetection/image/pipeline.png b/mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/image/pipeline.png
similarity index 100%
rename from contrib/RTMHumanKeypointsDetection/image/pipeline.png
rename to mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/image/pipeline.png
diff --git a/contrib/RTMHumanKeypointsDetection/main.cpp b/mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/main.cpp
similarity index 100%
rename from contrib/RTMHumanKeypointsDetection/main.cpp
rename to mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/main.cpp
diff --git a/contrib/RTMHumanKeypointsDetection/models/insert_op.cfg b/mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/models/insert_op.cfg
similarity index 95%
rename from contrib/RTMHumanKeypointsDetection/models/insert_op.cfg
rename to mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/models/insert_op.cfg
index 47625ae1b40a1b9e16600832240f0e4a0e381ae3..4299125e2d1818e55ef909440040a582b04453e9 100644
--- a/contrib/RTMHumanKeypointsDetection/models/insert_op.cfg
+++ b/mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/models/insert_op.cfg
@@ -1,31 +1,31 @@
-aipp_op {
-    related_input_rank: 0
-    src_image_size_w: 512
-    src_image_size_h: 512
-    crop: false
-    input_format: YUV420SP_U8
-    aipp_mode: static
-    csc_switch: true
-    rbuv_swap_switch: false
-    matrix_r0c0: 256
-    matrix_r0c1: 454
-    matrix_r0c2: 0
-    matrix_r1c0: 256
-    matrix_r1c1: -88
-    matrix_r1c2: -183
-    matrix_r2c0: 256
-    matrix_r2c1: 0
-    matrix_r2c2: 359
-    input_bias_0: 0
-    input_bias_1: 128
-    input_bias_2: 128
-    mean_chn_0: 128
-    mean_chn_1: 128
-    mean_chn_2: 128
-    min_chn_0: 0.0
-    min_chn_1: 0.0
-    min_chn_2: 0.0
-    var_reci_chn_0: 0.00390625
-    var_reci_chn_1: 0.00390625
-    var_reci_chn_2: 0.00390625
+aipp_op {
+    related_input_rank: 0
+    src_image_size_w: 512
+    src_image_size_h: 512
+    crop: false
+    input_format: YUV420SP_U8
+    aipp_mode: static
+    csc_switch: true
+    rbuv_swap_switch: false
+    matrix_r0c0: 256
+    matrix_r0c1: 454
+    matrix_r0c2: 0
+    matrix_r1c0: 256
+    matrix_r1c1: -88
+    matrix_r1c2: -183
+    matrix_r2c0: 256
+    matrix_r2c1: 0
+    matrix_r2c2: 359
+    input_bias_0: 0
+    input_bias_1: 128
+    input_bias_2: 128
+    mean_chn_0: 128
+    mean_chn_1: 128
+    mean_chn_2: 128
+    min_chn_0: 0.0
+    min_chn_1: 0.0
+    min_chn_2: 0.0
+    var_reci_chn_0: 0.00390625
+    var_reci_chn_1: 0.00390625
+    var_reci_chn_2: 0.00390625
 }
\ No newline at end of file
diff --git a/contrib/RTMHumanKeypointsDetection/pipeline/rtmOpenpose.pipeline b/mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/pipeline/rtmOpenpose.pipeline
similarity index 96%
rename from contrib/RTMHumanKeypointsDetection/pipeline/rtmOpenpose.pipeline
rename to mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/pipeline/rtmOpenpose.pipeline
index fde17604a59be2399c60f03b48fb32f4e475df46..75df06f2854afc2898161fe08cac15e9ae68100f 100644
--- a/contrib/RTMHumanKeypointsDetection/pipeline/rtmOpenpose.pipeline
+++ b/mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/pipeline/rtmOpenpose.pipeline
@@ -1,131 +1,131 @@
-{
-    "Video+Openpose":{
-        "stream_config":{
-            "deviceId":"0"
-        },
-        "mxpi_rtspsrc0":{
-            "next":"queue0",
-            "factory":"mxpi_rtspsrc",
-            "props":{
-                "rtspUrl":"rtsp://XXX.XXX.XXX.XXX/test1.264",
-                "channelId":"0"
-            }
-        },
-        "queue0":{
-            "next":"mxpi_videodecoder0",
-            "factory":"queue",
-            "props":{
-                "max-size-buffers":"200"
-            }
-        },
-        "mxpi_videodecoder0":{
-            "next":"tee0",
-            "factory":"mxpi_videodecoder",
-            "props":{
-                "outputImageFormat":"YUV420SP_NV12",
-                "inputVideoFormat":"H264",
-                "vdecChannelId":"0"
-            }
-        },
-        "tee0":{
-            "factory": "tee",
-            "next":[
-                "queue1",
-                "queue2"
-            ]
-        },
-        "queue2":{
-            "next": "mxpi_opencvosd0:0",
-            "factory": "queue",
-            "props":{
-                "max-size-buffers": "200"
-            }
-        },
-        "queue1":{
-            "next":"mxpi_imageresize0",
-            "factory":"queue",
-            "props":{
-                "max-size-buffers":"200"
-            }
-        },
-        "mxpi_imageresize0":{
-            "next":"queue3",
-            "factory":"mxpi_imageresize",
-            "props":{
-                "interpolation":"1",
-                "resizeWidth":"512",
-                "resizeHeight":"512",
-                "dataSource":"mxpi_videodecoder0",
-                "resizeType":"Resizer_KeepAspectRatio_Fit"
-            }
-        },
-        "queue3":{
-            "next":"mxpi_tensorinfer0",
-            "factory":"queue",
-            "props":{
-                "max-size-buffers":"200"
-            }
-        },
-        "mxpi_tensorinfer0":{
-            "next":"mxpi_rtmopenposepostprocess0",
-            "factory":"mxpi_tensorinfer",
-            "props":{
-                "dataSource": "mxpi_imageresize0",
-                "modelPath":"./models/openpose_pytorch_512.om"
-            }
-        },
-        "mxpi_rtmopenposepostprocess0":{
-            "next":"queue4",
-            "factory":"mxpi_rtmopenposepostprocess",
-            "props":{
-                "imageSource":"mxpi_videodecoder0",
-                "inputHeight":"512",
-                "dataSource":"mxpi_tensorinfer0",
-                "inputWidth":"512"
-            }
-        },
-        "queue4":{
-            "next":"mxpi_opencvosd0:1",
-            "factory":"queue",
-            "props":{
-                "max-size-buffers":"200"
-            }
-        },
-        "mxpi_opencvosd0":{
-            "factory": "mxpi_opencvosd",
-            "next": "queue5"
-        },
-        "queue5":{
-            "props":{
-                "max-size-buffers": "200"
-            },
-            "factory": "queue",
-            "next": "mxpi_videoencoder0"
-        },
-        "mxpi_videoencoder0":{
-            "props": {
-                "inputFormat": "YUV420SP_NV12",
-                "outputFormat": "H264",
-                "fps": "1",
-                "iFrameInterval": "50",
-                "imageHeight": "720",
-                "imageWidth": "1280"
-            },
-            "factory": "mxpi_videoencoder",
-            "next": "queue6"
-        },
-        "queue6": {
-            "props": {
-                "max-size-buffers": "200"
-            },
-            "factory": "queue",
-            "next": "appsink0"
-        },
-        "appsink0":{
-            "factory":"appsink",
-            "props":{
-                "blocksize":"4056000"
-            }
-        }
-    }
-}
+{
+    "Video+Openpose":{
+        "stream_config":{
+            "deviceId":"0"
+        },
+        "mxpi_rtspsrc0":{
+            "next":"queue0",
+            "factory":"mxpi_rtspsrc",
+            "props":{
+                "rtspUrl":"rtsp://XXX.XXX.XXX.XXX/test1.264",
+                "channelId":"0"
+            }
+        },
+        "queue0":{
+            "next":"mxpi_videodecoder0",
+            "factory":"queue",
+            "props":{
+                "max-size-buffers":"200"
+            }
+        },
+        "mxpi_videodecoder0":{
+            "next":"tee0",
+            "factory":"mxpi_videodecoder",
+            "props":{
+                "outputImageFormat":"YUV420SP_NV12",
+                "inputVideoFormat":"H264",
+                "vdecChannelId":"0"
+            }
+        },
+        "tee0":{
+            "factory": "tee",
+            "next":[
+                "queue1",
+                "queue2"
+            ]
+        },
+        "queue2":{
+            "next": "mxpi_opencvosd0:0",
+            "factory": "queue",
+            "props":{
+                "max-size-buffers": "200"
+            }
+        },
+        "queue1":{
+            "next":"mxpi_imageresize0",
+            "factory":"queue",
+            "props":{
+                "max-size-buffers":"200"
+            }
+        },
+        "mxpi_imageresize0":{
+            "next":"queue3",
+            "factory":"mxpi_imageresize",
+            "props":{
+                "interpolation":"1",
+                "resizeWidth":"512",
+                "resizeHeight":"512",
+                "dataSource":"mxpi_videodecoder0",
+                "resizeType":"Resizer_KeepAspectRatio_Fit"
+            }
+        },
+        "queue3":{
+            "next":"mxpi_tensorinfer0",
+            "factory":"queue",
+            "props":{
+                "max-size-buffers":"200"
+            }
+        },
+        "mxpi_tensorinfer0":{
+            "next":"mxpi_rtmopenposepostprocess0",
+            "factory":"mxpi_tensorinfer",
+            "props":{
+                "dataSource": "mxpi_imageresize0",
+                "modelPath":"./models/openpose_pytorch_512.om"
+            }
+        },
+        "mxpi_rtmopenposepostprocess0":{
+            "next":"queue4",
+            "factory":"mxpi_rtmopenposepostprocess",
+            "props":{
+                "imageSource":"mxpi_videodecoder0",
+                "inputHeight":"512",
+                "dataSource":"mxpi_tensorinfer0",
+                "inputWidth":"512"
+            }
+        },
+        "queue4":{
+            "next":"mxpi_opencvosd0:1",
+            "factory":"queue",
+            "props":{
+                "max-size-buffers":"200"
+            }
+        },
+        "mxpi_opencvosd0":{
+            "factory": "mxpi_opencvosd",
+            "next": "queue5"
+        },
+        "queue5":{
+            "props":{
+                "max-size-buffers": "200"
+            },
+            "factory": "queue",
+            "next": "mxpi_videoencoder0"
+        },
+        "mxpi_videoencoder0":{
+            "props": {
+                "inputFormat": "YUV420SP_NV12",
+                "outputFormat": "H264",
+                "fps": "1",
+                "iFrameInterval": "50",
+                "imageHeight": "720",
+                "imageWidth": "1280"
+            },
+            "factory": "mxpi_videoencoder",
+            "next": "queue6"
+        },
+        "queue6": {
+            "props": {
+                "max-size-buffers": "200"
+            },
+            "factory": "queue",
+            "next": "appsink0"
+        },
+        "appsink0":{
+            "factory":"appsink",
+            "props":{
+                "blocksize":"4056000"
+            }
+        }
+    }
+}
diff --git a/contrib/RTMHumanKeypointsDetection/plugins/CMakeLists.txt b/mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/plugins/CMakeLists.txt
similarity index 100%
rename from contrib/RTMHumanKeypointsDetection/plugins/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/plugins/CMakeLists.txt
diff --git a/contrib/RTMHumanKeypointsDetection/plugins/MxpiRTMOpenposePostProcess.cpp b/mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/plugins/MxpiRTMOpenposePostProcess.cpp
similarity index 100%
rename from contrib/RTMHumanKeypointsDetection/plugins/MxpiRTMOpenposePostProcess.cpp
rename to mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/plugins/MxpiRTMOpenposePostProcess.cpp
diff --git a/contrib/RTMHumanKeypointsDetection/plugins/MxpiRTMOpenposePostProcess.h b/mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/plugins/MxpiRTMOpenposePostProcess.h
similarity index 100%
rename from contrib/RTMHumanKeypointsDetection/plugins/MxpiRTMOpenposePostProcess.h
rename to mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/plugins/MxpiRTMOpenposePostProcess.h
diff --git a/contrib/RTMHumanKeypointsDetection/plugins/build.sh b/mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/plugins/build.sh
similarity index 100%
rename from contrib/RTMHumanKeypointsDetection/plugins/build.sh
rename to mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/plugins/build.sh
diff --git a/contrib/RTMHumanKeypointsDetection/run.sh b/mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/run.sh
similarity index 100%
rename from contrib/RTMHumanKeypointsDetection/run.sh
rename to mxVision/mxVision-referenceapps/RTMHumanKeypointsDetection/run.sh
diff --git a/contrib/ReID/README.md b/mxVision/mxVision-referenceapps/ReID/README.md
similarity index 100%
rename from contrib/ReID/README.md
rename to mxVision/mxVision-referenceapps/ReID/README.md
diff --git a/contrib/ReID/main.py b/mxVision/mxVision-referenceapps/ReID/main.py
similarity index 100%
rename from contrib/ReID/main.py
rename to mxVision/mxVision-referenceapps/ReID/main.py
diff --git a/contrib/ReID/makeYourOwnDataset.py b/mxVision/mxVision-referenceapps/ReID/makeYourOwnDataset.py
similarity index 100%
rename from contrib/ReID/makeYourOwnDataset.py
rename to mxVision/mxVision-referenceapps/ReID/makeYourOwnDataset.py
diff --git a/contrib/ReID/models/ReID_onnx2om.cfg b/mxVision/mxVision-referenceapps/ReID/models/ReID_onnx2om.cfg
similarity index 100%
rename from contrib/ReID/models/ReID_onnx2om.cfg
rename to mxVision/mxVision-referenceapps/ReID/models/ReID_onnx2om.cfg
diff --git a/contrib/ReID/models/coco.names b/mxVision/mxVision-referenceapps/ReID/models/coco.names
similarity index 100%
rename from contrib/ReID/models/coco.names
rename to mxVision/mxVision-referenceapps/ReID/models/coco.names
diff --git a/contrib/ReID/models/yolov3.cfg b/mxVision/mxVision-referenceapps/ReID/models/yolov3.cfg
similarity index 100%
rename from contrib/ReID/models/yolov3.cfg
rename to mxVision/mxVision-referenceapps/ReID/models/yolov3.cfg
diff --git a/contrib/ReID/pipeline/ReID.pipeline b/mxVision/mxVision-referenceapps/ReID/pipeline/ReID.pipeline
similarity index 100%
rename from contrib/ReID/pipeline/ReID.pipeline
rename to mxVision/mxVision-referenceapps/ReID/pipeline/ReID.pipeline
diff --git a/contrib/ReIDv2/README.md b/mxVision/mxVision-referenceapps/ReIDv2/README.md
similarity index 100%
rename from contrib/ReIDv2/README.md
rename to mxVision/mxVision-referenceapps/ReIDv2/README.md
diff --git a/contrib/ReIDv2/result/.keep b/mxVision/mxVision-referenceapps/ReIDv2/data/.keep
similarity index 100%
rename from contrib/ReIDv2/result/.keep
rename to mxVision/mxVision-referenceapps/ReIDv2/data/.keep
diff --git a/contrib/ReIDv2/image/V1_running_time.jpg b/mxVision/mxVision-referenceapps/ReIDv2/image/V1_running_time.jpg
similarity index 100%
rename from contrib/ReIDv2/image/V1_running_time.jpg
rename to mxVision/mxVision-referenceapps/ReIDv2/image/V1_running_time.jpg
diff --git a/contrib/ReIDv2/image/V2_running_time.jpg b/mxVision/mxVision-referenceapps/ReIDv2/image/V2_running_time.jpg
similarity index 100%
rename from contrib/ReIDv2/image/V2_running_time.jpg
rename to mxVision/mxVision-referenceapps/ReIDv2/image/V2_running_time.jpg
diff --git a/contrib/ReIDv2/image/flow_chart.jpg b/mxVision/mxVision-referenceapps/ReIDv2/image/flow_chart.jpg
similarity index 100%
rename from contrib/ReIDv2/image/flow_chart.jpg
rename to mxVision/mxVision-referenceapps/ReIDv2/image/flow_chart.jpg
diff --git a/contrib/ReIDv2/image/flow_chart_v2.jpg b/mxVision/mxVision-referenceapps/ReIDv2/image/flow_chart_v2.jpg
similarity index 100%
rename from contrib/ReIDv2/image/flow_chart_v2.jpg
rename to mxVision/mxVision-referenceapps/ReIDv2/image/flow_chart_v2.jpg
diff --git a/contrib/ReIDv2/image/result_v1.jpg b/mxVision/mxVision-referenceapps/ReIDv2/image/result_v1.jpg
similarity index 100%
rename from contrib/ReIDv2/image/result_v1.jpg
rename to mxVision/mxVision-referenceapps/ReIDv2/image/result_v1.jpg
diff --git a/contrib/ReIDv2/image/result_v2.jpg b/mxVision/mxVision-referenceapps/ReIDv2/image/result_v2.jpg
similarity index 100%
rename from contrib/ReIDv2/image/result_v2.jpg
rename to mxVision/mxVision-referenceapps/ReIDv2/image/result_v2.jpg
diff --git a/contrib/ReIDv2/img.png b/mxVision/mxVision-referenceapps/ReIDv2/img.png
similarity index 100%
rename from contrib/ReIDv2/img.png
rename to mxVision/mxVision-referenceapps/ReIDv2/img.png
diff --git a/contrib/ReIDv2/mainv2.py b/mxVision/mxVision-referenceapps/ReIDv2/mainv2.py
similarity index 100%
rename from contrib/ReIDv2/mainv2.py
rename to mxVision/mxVision-referenceapps/ReIDv2/mainv2.py
diff --git a/contrib/ReIDv2/models/ReID_onnx2om.cfg b/mxVision/mxVision-referenceapps/ReIDv2/models/ReID_onnx2om.cfg
similarity index 100%
rename from contrib/ReIDv2/models/ReID_onnx2om.cfg
rename to mxVision/mxVision-referenceapps/ReIDv2/models/ReID_onnx2om.cfg
diff --git a/contrib/ReIDv2/models/coco.names b/mxVision/mxVision-referenceapps/ReIDv2/models/coco.names
similarity index 100%
rename from contrib/ReIDv2/models/coco.names
rename to mxVision/mxVision-referenceapps/ReIDv2/models/coco.names
diff --git a/contrib/ReIDv2/models/yolov3.cfg b/mxVision/mxVision-referenceapps/ReIDv2/models/yolov3.cfg
similarity index 100%
rename from contrib/ReIDv2/models/yolov3.cfg
rename to mxVision/mxVision-referenceapps/ReIDv2/models/yolov3.cfg
diff --git a/contrib/SuperResolution/image/.keep b/mxVision/mxVision-referenceapps/ReIDv2/result/.keep
similarity index 100%
rename from contrib/SuperResolution/image/.keep
rename to mxVision/mxVision-referenceapps/ReIDv2/result/.keep
diff --git a/contrib/RemoteSensingSegmentation/README.md b/mxVision/mxVision-referenceapps/RemoteSensingSegmentation/README.md
similarity index 100%
rename from contrib/RemoteSensingSegmentation/README.md
rename to mxVision/mxVision-referenceapps/RemoteSensingSegmentation/README.md
diff --git a/contrib/RemoteSensingSegmentation/config/configure.cfg b/mxVision/mxVision-referenceapps/RemoteSensingSegmentation/config/configure.cfg
similarity index 100%
rename from contrib/RemoteSensingSegmentation/config/configure.cfg
rename to mxVision/mxVision-referenceapps/RemoteSensingSegmentation/config/configure.cfg
diff --git a/contrib/RemoteSensingSegmentation/main.py b/mxVision/mxVision-referenceapps/RemoteSensingSegmentation/main.py
similarity index 100%
rename from contrib/RemoteSensingSegmentation/main.py
rename to mxVision/mxVision-referenceapps/RemoteSensingSegmentation/main.py
diff --git a/contrib/RemoteSensingSegmentation/pipeline/segmentation.pipeline b/mxVision/mxVision-referenceapps/RemoteSensingSegmentation/pipeline/segmentation.pipeline
similarity index 100%
rename from contrib/RemoteSensingSegmentation/pipeline/segmentation.pipeline
rename to mxVision/mxVision-referenceapps/RemoteSensingSegmentation/pipeline/segmentation.pipeline
diff --git a/contrib/RemoteSensingSegmentation/util/model_conversion.sh b/mxVision/mxVision-referenceapps/RemoteSensingSegmentation/util/model_conversion.sh
similarity index 100%
rename from contrib/RemoteSensingSegmentation/util/model_conversion.sh
rename to mxVision/mxVision-referenceapps/RemoteSensingSegmentation/util/model_conversion.sh
diff --git a/contrib/RemoteSensingSegmentation/util/transform_model_util.py b/mxVision/mxVision-referenceapps/RemoteSensingSegmentation/util/transform_model_util.py
similarity index 100%
rename from contrib/RemoteSensingSegmentation/util/transform_model_util.py
rename to mxVision/mxVision-referenceapps/RemoteSensingSegmentation/util/transform_model_util.py
diff --git a/contrib/RemoteSensingSegmentation/util/visual_utils.py b/mxVision/mxVision-referenceapps/RemoteSensingSegmentation/util/visual_utils.py
similarity index 100%
rename from contrib/RemoteSensingSegmentation/util/visual_utils.py
rename to mxVision/mxVision-referenceapps/RemoteSensingSegmentation/util/visual_utils.py
diff --git a/contrib/Retinaface/README.md b/mxVision/mxVision-referenceapps/Retinaface/README.md
similarity index 96%
rename from contrib/Retinaface/README.md
rename to mxVision/mxVision-referenceapps/Retinaface/README.md
index 28a7c5d0c886bcad9d7b30c089f5d9f4175dd56f..4a481ff0f451df4fa5b18b08d74c030c4666c7bd 100644
--- a/contrib/Retinaface/README.md
+++ b/mxVision/mxVision-referenceapps/Retinaface/README.md
@@ -1,347 +1,347 @@
-## Retinaface目标检测
-
-## 1介绍
-
-Retinaface基于MindX_SDK开发，在昇腾芯片上进行目标检测，并实现可视化呈现。输入单张图片，对其进行推理，输出推理结果。
-
-### 1.1 支持的产品
-
-本产品以昇腾310（推理）卡为硬件平台。
-
-### 1.2 支持的版本
-
-该项目支持的SDK版本为2.0.4，CANN版本为5.0.4。
-
-### 1.3 软件方案介绍
-
-表1.1 系统方案各子系统功能描述：
-
-| 序号 | 子系统         | 功能描述                                                     |
-| ---- | -------------- | ------------------------------------------------------------ |
-| 1    | 图片输入       | 接收外部调用接口的输入视频路径，对视频进行拉流，并将拉去的裸流存储到缓冲区（buffer）中，并发送到下游插件。 |
-| 2    | 模型推理插件   | 目标检测。                                                   |
-| 3    | 模型后处理插件 | 对模型输出的张量进行后处理，得到物体类型数据。               |
-
-
-
-### 1.4 代码目录结构与说明
-
-本项目名为Retinaface目标检测，项目目录如下所示：
-
-````
-.
-├── build.sh
-├── run.sh
-├── config
-│   └── aipp.cfg
-│   ├── face_Retina.cfg
-├── images
-├── main.py
-├── test.py
-├── utils.py
-├── model
-│   └── run.sh
-├── plugin
-│   └── build.sh
-│   ├── CMakeLists.txt
-│   ├── TotalYunetPostProcess.cpp
-│   └── TotalYunetPostProcess.h
-├── README.md
-````
-
-
-
-### 1.5 技术实现流程图
-
-![流程图](images/process.png)
-
-
-
-### 1.6 特性及适用场景
-
-本项目根据widerface数据集训练得到，适用于目标检测，并且将目标位置与五官位置标出。
-
-本项目在绝大多数情况下准确，但是存在以下检测异常的情况：
-
-1.正常检测中，由于模型本身的限制，会出现部分物体检测不到/检测错误；
-
-2.图片中无检测目标时，会出现可视化异常，输出结果无图片信息；
-
-3.对于图片中一些侧脸和与目标相似的动物脸的情况，模型可能会出现漏检测或者误检测；
-
-
-
-## 2 环境依赖
-
-推荐系统为ubuntu  18.04,环境软件和版本如下：
-
-| 软件名称            | 版本  | 说明                          | 获取方式                                                  |
-| ------------------- | ----- | ----------------------------- | :-------------------------------------------------------- |
-| MindX SDK           | 2.0.4 | mxVision软件包                | [链接](https://www.hiascend.com/software/Mindx-sdk)       |
-| ubuntu              | 18.04 | 操作系统                      | 请上ubuntu官网获取                                        |
-| Ascend-CANN-toolkit | 5.0.4 | Ascend-cann-toolkit开发套件包 | [链接](https://www.hiascend.com/software/cann/commercial) |
-
-
-
-在编译运行项目前，需要设置环境变量：
-
-MindSDK 环境变量：
-
-```
-. ${SDK-path}/set_env.sh
-```
-
-CANN 环境变量：
-
-```
-. ${ascend-toolkit-path}/set_env.sh
-```
-
-- 环境变量介绍
-
-```
-SDK-path: mxVision SDK * 安装路径
-ascend-toolkit-path: CANN 安装路径。
-```
-
-## 3 软件依赖说明
-
-* Cpython
-    
-    可通过pip指令直接安装：
-    ```
-    pip3 install cpython
-    ```
-
-* Ipython
-
-    可通过pip指令直接安装：
-    ```
-    pip3 install ipython
-    ```
-
-## 4.推理文件准备
-进入项目根目录，执行以下命令，创建所需文件夹：
-```
-mkdir include
-mkdir -p evaluate/widerface_txt/
-```
-下载本模型论文官方源码，可通过git clone下载：
-```
-git clone https://github.com/biubug6/Pytorch_Retinaface.git
-```
-或者直接下载[论文代码仓库](https://github.com/biubug6/Pytorch_Retinaface)中的zip代码包解压。
-
-1、准备include目录中的文件
-
-* 将Pytorch_Retinaface项目中的
-    * Pytorch_Retinaface/layers/functions/prior_box.py
-    * Pytorch_Retinaface/utils/box_utils.py
-    * Pytorch_Retinaface/utils/nms/py_cpu_nms.py
-    
-    放入本项目include文件夹下。
-
-2、准备evaluate目录中的文件
-* 将Pytorch_Retinaface项目中的
-    * Pytorch_Retinaface/widerface_evaluate
-
-    文件夹放入本项目evaluate文件夹下。
-
-3、编译测试依赖代码
-进入evaluate/widerface_evaluate路径下：
-```
-    python3 setup.py build_ext --inplace
-```
-
-4、准备模型及标签文件
-在ModelZoo社区[下载](https://www.hiascend.com/zh/software/modelzoo/models/detail/1/7270b02a457d4c4ab262277a646517f9)“ATC Retinaface(FP16) from Pytorch.zip”模型代码包并上传至服务器解压。
-* 将模型代码包中的"retinaface.onnx"模型拷贝至项目根目录的"model"目录下
-* 将模型代码包中的"Retinaface/data/widerface/val/wider_val.txt"标签文件拷贝至"evaluate"目录下；
-
-## 4 模型转化
-
-下载后解包，得到`Retinaface.onnx`，使用模型转换工具ATC将onnx模型转换为om模型，模型转换工具相关介绍参考[链接](https://gitee.com/ascend/docs-openmind/blob/master/guide/mindx/sdk/tutorials/%E5%8F%82%E8%80%83%E8%B5%84%E6%96%99.md)
-
-模型转换步骤如下：
-
-1、`cd`到`model`文件夹，运行
-
-````
-bash run.sh
-````
-
-2、执行该命令后会在指定输出.om模型路径生成项目指定模型文件newRetinaface.om。若模型转换成功则输出：
-
-```
-ATC start working now, please wait for a moment.
-ATC run success, welcome to the next use.
-```
-
-aipp文件配置如下：
-
-```
-aipp_op {
-aipp_mode: static
-
-input_format :RGB888_U8
-src_image_size_w :1000
-src_image_size_h :1000
-
-mean_chn_0 :104
-mean_chn_1 :117
-mean_chn_2 :123
-
-var_reci_chn_0 :1
-var_reci_chn_1 :1
-var_reci_chn_2 :1
-}
-
-```
-
-## 5 编译运行
-
-`main.py`：用来生成单张图片推理的可视化结果，以提供推理模型的应用实例。
-
-1、在项目根目录下，cd到plugin目录，并执行以下命令进行编译：
-
-```
-mkdir build
-cd build
-cmake ..
-make -j
-make install
-```
-
-将build文件夹下`libtotalyunetpostprocess.so`修改权限为`640`
-并且复制到MindSDK安装路径的`lib/modelpostprocessors`目录。
-
-
-2、查看项目根目录下的config/aipp.cfg权限是否为640，若不是请修改。
-
-
-
-3、准备好测试图片`test.jpg`，放置在项目根目录。
-
-4、运行`main.py`程序
-
-确认并修改“main.py”中下列所示的代码：
-```
-pipeline = {
-        "Retinaface": {
-            "stream_config": {
-                "deviceId": "0"   # 运行NPU卡ID
-            },
-            "appsrc0": {
-                "props": {
-                    "blocksize": "409600"
-                },
-                "factory": "appsrc",
-                "next": "mxpi_tensorinfer0"
-            },
-            "mxpi_tensorinfer0": {
-                "props": {
-                    "singleBatchInfer": "1",
-                    "dataSource": "appsrc0",
-                    "modelPath": "./model/newRetinaface.om" # 推理所需模型
-                },
-                "factory": "mxpi_tensorinfer",
-                "next": "mxpi_objectpostprocessor0"
-            },
-            "mxpi_objectpostprocessor0": {
-            "props": {
-                "dataSource": "mxpi_tensorinfer0",
-                "postProcessConfigPath": "./config/face_Retina.cfg", # 推理所需的配置文件
-                "postProcessLibPath": "libtotalyunetpostprocess.so"
-            },
-            "factory": "mxpi_objectpostprocessor",
-            "next": "appsink0"
-            },
-            "appsink0": {
-                "props": {
-                    "blocksize": "409600"
-                },
-                "factory": "appsink"
-            }
-        }
-    }
-```
-在代码根目录下，执行以下命令进行推理：
-```
-bash run.sh
-```
-最后会得到`result.jpg`即为输出结果
-
-
-
-## 6 精度验证
-
-本模型使用widerface数据集进行精度评估。
-
-1.[下载](https://share.weiyun.com/5ot9Qv1)数据集放到Retinaface目录下
-
-2.打开test.py文件,在开头修改路径参数：
-* RNDB修改为widerface验证集的位置。
-* RNDY修改为保存结果txt文件的文件夹位置。 
-如例：
-    ```
-    RNDB = "./widerface/val/images/"
-    RNDY = "./evaluate/widerface_txt"
-    ```
-
-3.确认并修改“test.py”中下列所示的代码：
-```
-pipeline = {
-    "Retinaface": {
-        "stream_config": {
-            "deviceId": "0" # 运行NPU卡ID
-        },
-        "appsrc0": {
-            "props": {
-                "blocksize": "409600"
-            },
-            "factory": "appsrc",
-            "next": "mxpi_tensorinfer0"
-        },
-        "mxpi_tensorinfer0": {
-            "props": {
-                "singleBatchInfer": "1",
-                "dataSource": "appsrc0",
-                "modelPath": "./model/newRetinaface.om" # 推理所需模型
-            },
-            "factory": "mxpi_tensorinfer",
-            "next": "appsink0"
-        },
-        "appsink0": {
-            "props": {
-                "blocksize": "409600"
-            },
-            "factory": "appsink"
-        }
-    }
-}
-```
-在Retinaface目录运行
-```
-python3 test.py
-```
-该程序会逐一推理widerface官方验证集之中的样本，并将结果保存在RNDY文件当中。
-
-4、进入`evaluate/widerface_evaluate`目录下，运行`python3 evaluation.py -p <your prediction dir> -g <groud truth dir>`, 其中：
-
-* `<your prediction dir>`即RNDY是模型推理的结果。
-
-* `<groud truth dir>`是widerface_evaluate中的groun_truth文件夹。
-
-比如：
-```
-python3 evaluation.py -p ../widerface_txt/ -g ground_truth/
-```
-最终得到的精度如下图所示：
-
-![模型推理结果](images/result.png)
-
-原模型精度如下图所示：
-
-![源模型推理结果](images/origin.png)
-
+## Retinaface目标检测
+
+## 1介绍
+
+Retinaface基于MindX_SDK开发，在昇腾芯片上进行目标检测，并实现可视化呈现。输入单张图片，对其进行推理，输出推理结果。
+
+### 1.1 支持的产品
+
+本产品以昇腾310（推理）卡为硬件平台。
+
+### 1.2 支持的版本
+
+该项目支持的SDK版本为2.0.4，CANN版本为5.0.4。
+
+### 1.3 软件方案介绍
+
+表1.1 系统方案各子系统功能描述：
+
+| 序号 | 子系统         | 功能描述                                                     |
+| ---- | -------------- | ------------------------------------------------------------ |
+| 1    | 图片输入       | 接收外部调用接口的输入视频路径，对视频进行拉流，并将拉去的裸流存储到缓冲区（buffer）中，并发送到下游插件。 |
+| 2    | 模型推理插件   | 目标检测。                                                   |
+| 3    | 模型后处理插件 | 对模型输出的张量进行后处理，得到物体类型数据。               |
+
+
+
+### 1.4 代码目录结构与说明
+
+本项目名为Retinaface目标检测，项目目录如下所示：
+
+````
+.
+├── build.sh
+├── run.sh
+├── config
+│   └── aipp.cfg
+│   ├── face_Retina.cfg
+├── images
+├── main.py
+├── test.py
+├── utils.py
+├── model
+│   └── run.sh
+├── plugin
+│   └── build.sh
+│   ├── CMakeLists.txt
+│   ├── TotalYunetPostProcess.cpp
+│   └── TotalYunetPostProcess.h
+├── README.md
+````
+
+
+
+### 1.5 技术实现流程图
+
+![流程图](images/process.png)
+
+
+
+### 1.6 特性及适用场景
+
+本项目根据widerface数据集训练得到，适用于目标检测，并且将目标位置与五官位置标出。
+
+本项目在绝大多数情况下准确，但是存在以下检测异常的情况：
+
+1.正常检测中，由于模型本身的限制，会出现部分物体检测不到/检测错误；
+
+2.图片中无检测目标时，会出现可视化异常，输出结果无图片信息；
+
+3.对于图片中一些侧脸和与目标相似的动物脸的情况，模型可能会出现漏检测或者误检测；
+
+
+
+## 2 环境依赖
+
+推荐系统为ubuntu  18.04,环境软件和版本如下：
+
+| 软件名称            | 版本  | 说明                          | 获取方式                                                  |
+| ------------------- | ----- | ----------------------------- | :-------------------------------------------------------- |
+| MindX SDK           | 2.0.4 | mxVision软件包                | [链接](https://www.hiascend.com/software/Mindx-sdk)       |
+| ubuntu              | 18.04 | 操作系统                      | 请上ubuntu官网获取                                        |
+| Ascend-CANN-toolkit | 5.0.4 | Ascend-cann-toolkit开发套件包 | [链接](https://www.hiascend.com/software/cann/commercial) |
+
+
+
+在编译运行项目前，需要设置环境变量：
+
+MindSDK 环境变量：
+
+```
+. ${SDK-path}/set_env.sh
+```
+
+CANN 环境变量：
+
+```
+. ${ascend-toolkit-path}/set_env.sh
+```
+
+- 环境变量介绍
+
+```
+SDK-path: mxVision SDK * 安装路径
+ascend-toolkit-path: CANN 安装路径。
+```
+
+## 3 软件依赖说明
+
+* Cpython
+    
+    可通过pip指令直接安装：
+    ```
+    pip3 install cpython
+    ```
+
+* Ipython
+
+    可通过pip指令直接安装：
+    ```
+    pip3 install ipython
+    ```
+
+## 4.推理文件准备
+进入项目根目录，执行以下命令，创建所需文件夹：
+```
+mkdir include
+mkdir -p evaluate/widerface_txt/
+```
+下载本模型论文官方源码，可通过git clone下载：
+```
+git clone https://github.com/biubug6/Pytorch_Retinaface.git
+```
+或者直接下载[论文代码仓库](https://github.com/biubug6/Pytorch_Retinaface)中的zip代码包解压。
+
+1、准备include目录中的文件
+
+* 将Pytorch_Retinaface项目中的
+    * Pytorch_Retinaface/layers/functions/prior_box.py
+    * Pytorch_Retinaface/utils/box_utils.py
+    * Pytorch_Retinaface/utils/nms/py_cpu_nms.py
+    
+    放入本项目include文件夹下。
+
+2、准备evaluate目录中的文件
+* 将Pytorch_Retinaface项目中的
+    * Pytorch_Retinaface/widerface_evaluate
+
+    文件夹放入本项目evaluate文件夹下。
+
+3、编译测试依赖代码
+进入evaluate/widerface_evaluate路径下：
+```
+    python3 setup.py build_ext --inplace
+```
+
+4、准备模型及标签文件
+在ModelZoo社区[下载](https://www.hiascend.com/zh/software/modelzoo/models/detail/1/7270b02a457d4c4ab262277a646517f9)“ATC Retinaface(FP16) from Pytorch.zip”模型代码包并上传至服务器解压。
+* 将模型代码包中的"retinaface.onnx"模型拷贝至项目根目录的"model"目录下
+* 将模型代码包中的"Retinaface/data/widerface/val/wider_val.txt"标签文件拷贝至"evaluate"目录下；
+
+## 4 模型转化
+
+下载后解包，得到`Retinaface.onnx`，使用模型转换工具ATC将onnx模型转换为om模型，模型转换工具相关介绍参考[链接](https://gitee.com/ascend/docs-openmind/blob/master/guide/mindx/sdk/tutorials/%E5%8F%82%E8%80%83%E8%B5%84%E6%96%99.md)
+
+模型转换步骤如下：
+
+1、`cd`到`model`文件夹，运行
+
+````
+bash run.sh
+````
+
+2、执行该命令后会在指定输出.om模型路径生成项目指定模型文件newRetinaface.om。若模型转换成功则输出：
+
+```
+ATC start working now, please wait for a moment.
+ATC run success, welcome to the next use.
+```
+
+aipp文件配置如下：
+
+```
+aipp_op {
+aipp_mode: static
+
+input_format :RGB888_U8
+src_image_size_w :1000
+src_image_size_h :1000
+
+mean_chn_0 :104
+mean_chn_1 :117
+mean_chn_2 :123
+
+var_reci_chn_0 :1
+var_reci_chn_1 :1
+var_reci_chn_2 :1
+}
+
+```
+
+## 5 编译运行
+
+`main.py`：用来生成单张图片推理的可视化结果，以提供推理模型的应用实例。
+
+1、在项目根目录下，cd到plugin目录，并执行以下命令进行编译：
+
+```
+mkdir build
+cd build
+cmake ..
+make -j
+make install
+```
+
+将build文件夹下`libtotalyunetpostprocess.so`修改权限为`640`
+并且复制到MindSDK安装路径的`lib/modelpostprocessors`目录。
+
+
+2、查看项目根目录下的config/aipp.cfg权限是否为640，若不是请修改。
+
+
+
+3、准备好测试图片`test.jpg`，放置在项目根目录。
+
+4、运行`main.py`程序
+
+确认并修改“main.py”中下列所示的代码：
+```
+pipeline = {
+        "Retinaface": {
+            "stream_config": {
+                "deviceId": "0"   # 运行NPU卡ID
+            },
+            "appsrc0": {
+                "props": {
+                    "blocksize": "409600"
+                },
+                "factory": "appsrc",
+                "next": "mxpi_tensorinfer0"
+            },
+            "mxpi_tensorinfer0": {
+                "props": {
+                    "singleBatchInfer": "1",
+                    "dataSource": "appsrc0",
+                    "modelPath": "./model/newRetinaface.om" # 推理所需模型
+                },
+                "factory": "mxpi_tensorinfer",
+                "next": "mxpi_objectpostprocessor0"
+            },
+            "mxpi_objectpostprocessor0": {
+            "props": {
+                "dataSource": "mxpi_tensorinfer0",
+                "postProcessConfigPath": "./config/face_Retina.cfg", # 推理所需的配置文件
+                "postProcessLibPath": "libtotalyunetpostprocess.so"
+            },
+            "factory": "mxpi_objectpostprocessor",
+            "next": "appsink0"
+            },
+            "appsink0": {
+                "props": {
+                    "blocksize": "409600"
+                },
+                "factory": "appsink"
+            }
+        }
+    }
+```
+在代码根目录下，执行以下命令进行推理：
+```
+bash run.sh
+```
+最后会得到`result.jpg`即为输出结果
+
+
+
+## 6 精度验证
+
+本模型使用widerface数据集进行精度评估。
+
+1.[下载](https://share.weiyun.com/5ot9Qv1)数据集放到Retinaface目录下
+
+2.打开test.py文件,在开头修改路径参数：
+* RNDB修改为widerface验证集的位置。
+* RNDY修改为保存结果txt文件的文件夹位置。 
+如例：
+    ```
+    RNDB = "./widerface/val/images/"
+    RNDY = "./evaluate/widerface_txt"
+    ```
+
+3.确认并修改“test.py”中下列所示的代码：
+```
+pipeline = {
+    "Retinaface": {
+        "stream_config": {
+            "deviceId": "0" # 运行NPU卡ID
+        },
+        "appsrc0": {
+            "props": {
+                "blocksize": "409600"
+            },
+            "factory": "appsrc",
+            "next": "mxpi_tensorinfer0"
+        },
+        "mxpi_tensorinfer0": {
+            "props": {
+                "singleBatchInfer": "1",
+                "dataSource": "appsrc0",
+                "modelPath": "./model/newRetinaface.om" # 推理所需模型
+            },
+            "factory": "mxpi_tensorinfer",
+            "next": "appsink0"
+        },
+        "appsink0": {
+            "props": {
+                "blocksize": "409600"
+            },
+            "factory": "appsink"
+        }
+    }
+}
+```
+在Retinaface目录运行
+```
+python3 test.py
+```
+该程序会逐一推理widerface官方验证集之中的样本，并将结果保存在RNDY文件当中。
+
+4、进入`evaluate/widerface_evaluate`目录下，运行`python3 evaluation.py -p <your prediction dir> -g <groud truth dir>`, 其中：
+
+* `<your prediction dir>`即RNDY是模型推理的结果。
+
+* `<groud truth dir>`是widerface_evaluate中的groun_truth文件夹。
+
+比如：
+```
+python3 evaluation.py -p ../widerface_txt/ -g ground_truth/
+```
+最终得到的精度如下图所示：
+
+![模型推理结果](images/result.png)
+
+原模型精度如下图所示：
+
+![源模型推理结果](images/origin.png)
+
 符合精度偏差要求，精度达标。
\ No newline at end of file
diff --git a/contrib/Retinaface/build.sh b/mxVision/mxVision-referenceapps/Retinaface/build.sh
similarity index 100%
rename from contrib/Retinaface/build.sh
rename to mxVision/mxVision-referenceapps/Retinaface/build.sh
diff --git a/contrib/Retinaface/config/aipp.cfg b/mxVision/mxVision-referenceapps/Retinaface/config/aipp.cfg
similarity index 100%
rename from contrib/Retinaface/config/aipp.cfg
rename to mxVision/mxVision-referenceapps/Retinaface/config/aipp.cfg
diff --git a/contrib/yunet/config/face_yunet.cfg b/mxVision/mxVision-referenceapps/Retinaface/config/face_Retina.cfg
similarity index 100%
rename from contrib/yunet/config/face_yunet.cfg
rename to mxVision/mxVision-referenceapps/Retinaface/config/face_Retina.cfg
diff --git a/contrib/Retinaface/images/origin.png b/mxVision/mxVision-referenceapps/Retinaface/images/origin.png
similarity index 100%
rename from contrib/Retinaface/images/origin.png
rename to mxVision/mxVision-referenceapps/Retinaface/images/origin.png
diff --git a/contrib/Retinaface/images/process.png b/mxVision/mxVision-referenceapps/Retinaface/images/process.png
similarity index 100%
rename from contrib/Retinaface/images/process.png
rename to mxVision/mxVision-referenceapps/Retinaface/images/process.png
diff --git a/contrib/Retinaface/images/result.png b/mxVision/mxVision-referenceapps/Retinaface/images/result.png
similarity index 100%
rename from contrib/Retinaface/images/result.png
rename to mxVision/mxVision-referenceapps/Retinaface/images/result.png
diff --git a/contrib/Retinaface/main.py b/mxVision/mxVision-referenceapps/Retinaface/main.py
similarity index 96%
rename from contrib/Retinaface/main.py
rename to mxVision/mxVision-referenceapps/Retinaface/main.py
index 6739038f201901579aacd6095b5bdafb4bba5247..db73d0ad234b2358e0b9dfedd817a74091bf71cd 100644
--- a/contrib/Retinaface/main.py
+++ b/mxVision/mxVision-referenceapps/Retinaface/main.py
@@ -1,148 +1,148 @@
-#!/usr/bin/env python
-# coding=utf-8
-
-"""
-Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
-http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License.
-"""
-
-import shutil
-import json
-import argparse
-import os
-import tqdm
-import numpy as np
-import cv2
-import MxpiDataType_pb2 as MxpiDataType
-from PIL import Image
-from utils import preprocess_for_main
-from StreamManagerApi import StreamManagerApi, MxDataInput, StringVector
-from StreamManagerApi import StreamManagerApi, MxProtobufIn, InProtobufVector, StringVector
-
-if __name__ == '__main__':
-    streamManagerApi = StreamManagerApi()
-    ret = streamManagerApi.InitManager()
-    if ret != 0:
-        print("Failed to init Stream manager, ret=%s" % str(ret))
-        exit()
-
-    pipeline = {
-        "Retinaface": {
-            "stream_config": {
-                "deviceId": "0"
-            },
-            "appsrc0": {
-                "props": {
-                    "blocksize": "409600"
-                },
-                "factory": "appsrc",
-                "next": "mxpi_tensorinfer0"
-            },
-            "mxpi_tensorinfer0": {
-                "props": {
-                    "singleBatchInfer": "1",
-                    "dataSource": "appsrc0",
-                    "modelPath": "./model/newRetinaface.om"
-                },
-                "factory": "mxpi_tensorinfer",
-                "next": "mxpi_objectpostprocessor0"
-            },
-            "mxpi_objectpostprocessor0": {
-            "props": {
-                "dataSource": "mxpi_tensorinfer0",
-                "postProcessConfigPath": "./config/face_Retina.cfg",
-                "postProcessLibPath": "libtotalyunetpostprocess.so"
-            },
-            "factory": "mxpi_objectpostprocessor",
-            "next": "appsink0"
-            },
-            "appsink0": {
-                "props": {
-                    "blocksize": "409600"
-                },
-                "factory": "appsink"
-            }
-        }
-    }
-    pipelineStr = json.dumps(pipeline).encode()
-    ret = streamManagerApi.CreateMultipleStreams(pipelineStr)
-    if ret != 0:
-        print("Failed to create Stream, ret=%s" % str(ret))
-        exit()
-
-    IMAGE = "./test.jpg"
-    
-    if not os.path.exists(IMAGE):
-        print("Test image does not exsit!")
-        exit()
-    
-    tensor_data , return_img = preprocess_for_main(IMAGE)
-    tensor = tensor_data[None, :]
-
-    STREAMNAME = b"Retinaface"
-    INPLUGINID = 0
-    visionList = MxpiDataType.MxpiVisionList()
-    visionVec = visionList.visionVec.add()
-    visionInfo = visionVec.visionInfo
-
-    visionInfo.width = 1000
-    visionInfo.height = 1000
-    visionInfo.widthAligned = 1000
-    visionInfo.heightAligned = 1000
-    visionData = visionVec.visionData
-    visionData.dataStr = tensor.tobytes()
-    visionData.deviceId = 0
-    visionData.memType = 0
-    visionData.dataSize = len(tensor)
-    
-    KEY_VALUE = b"appsrc0"
-    protobufVec = InProtobufVector()
-    
-    protobuf = MxProtobufIn()
-    protobuf.key = KEY_VALUE
-    protobuf.type = b"MxTools.MxpiVisionList"
-    protobuf.protobuf = visionList.SerializeToString()
-    protobufVec.push_back(protobuf)
- 
-    uniqueId = streamManagerApi.SendProtobuf(STREAMNAME, INPLUGINID, protobufVec)
-
-    keys = [b'mxpi_objectpostprocessor0']
-    keyVec = StringVector()
-    for key in keys:
-        keyVec.push_back(key)
-    infer_result = streamManagerApi.GetProtobuf(STREAMNAME, 0, keyVec)
-    if infer_result.size() == 0:
-        print("infer_result is null")
-        exit()
-
-    if infer_result[0].errorCode != 0:
-        print("GetProtobuf error. errorCode=%d" % (infer_result[0].errorCode))
-        exit()
-    objectList = MxpiDataType.MxpiObjectList()
-    objectList.ParseFromString(infer_result[0].messageBuf)
-
-    img = cv2.imread('./test.jpg')
-    result = objectList.objectVec
-    resize , left, top, right, bottom = return_img
-    for x in result:
-        new_x0 = max(int((x.x0-left)/resize), 0)
-        new_x1 = max(int((x.x1-left)/resize), 0)
-        new_y0 = max(int((x.y0-top)/resize), 0)
-        new_y1 = max(int((x.y1-top)/resize), 0)
-
-        confidence = x.classVec[0].confidence
-        cv2.rectangle(img, (new_x0, new_y0), (new_x1, new_y1), (255, 0, 0), 2)
-
-    cv2.imwrite("./result.jpg", img)
-    streamManagerApi.DestroyAllStreams()
+#!/usr/bin/env python
+# coding=utf-8
+
+"""
+Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+"""
+
+import shutil
+import json
+import argparse
+import os
+import tqdm
+import numpy as np
+import cv2
+import MxpiDataType_pb2 as MxpiDataType
+from PIL import Image
+from utils import preprocess_for_main
+from StreamManagerApi import StreamManagerApi, MxDataInput, StringVector
+from StreamManagerApi import StreamManagerApi, MxProtobufIn, InProtobufVector, StringVector
+
+if __name__ == '__main__':
+    streamManagerApi = StreamManagerApi()
+    ret = streamManagerApi.InitManager()
+    if ret != 0:
+        print("Failed to init Stream manager, ret=%s" % str(ret))
+        exit()
+
+    pipeline = {
+        "Retinaface": {
+            "stream_config": {
+                "deviceId": "0"
+            },
+            "appsrc0": {
+                "props": {
+                    "blocksize": "409600"
+                },
+                "factory": "appsrc",
+                "next": "mxpi_tensorinfer0"
+            },
+            "mxpi_tensorinfer0": {
+                "props": {
+                    "singleBatchInfer": "1",
+                    "dataSource": "appsrc0",
+                    "modelPath": "./model/newRetinaface.om"
+                },
+                "factory": "mxpi_tensorinfer",
+                "next": "mxpi_objectpostprocessor0"
+            },
+            "mxpi_objectpostprocessor0": {
+            "props": {
+                "dataSource": "mxpi_tensorinfer0",
+                "postProcessConfigPath": "./config/face_Retina.cfg",
+                "postProcessLibPath": "libtotalyunetpostprocess.so"
+            },
+            "factory": "mxpi_objectpostprocessor",
+            "next": "appsink0"
+            },
+            "appsink0": {
+                "props": {
+                    "blocksize": "409600"
+                },
+                "factory": "appsink"
+            }
+        }
+    }
+    pipelineStr = json.dumps(pipeline).encode()
+    ret = streamManagerApi.CreateMultipleStreams(pipelineStr)
+    if ret != 0:
+        print("Failed to create Stream, ret=%s" % str(ret))
+        exit()
+
+    IMAGE = "./test.jpg"
+    
+    if not os.path.exists(IMAGE):
+        print("Test image does not exsit!")
+        exit()
+    
+    tensor_data , return_img = preprocess_for_main(IMAGE)
+    tensor = tensor_data[None, :]
+
+    STREAMNAME = b"Retinaface"
+    INPLUGINID = 0
+    visionList = MxpiDataType.MxpiVisionList()
+    visionVec = visionList.visionVec.add()
+    visionInfo = visionVec.visionInfo
+
+    visionInfo.width = 1000
+    visionInfo.height = 1000
+    visionInfo.widthAligned = 1000
+    visionInfo.heightAligned = 1000
+    visionData = visionVec.visionData
+    visionData.dataStr = tensor.tobytes()
+    visionData.deviceId = 0
+    visionData.memType = 0
+    visionData.dataSize = len(tensor)
+    
+    KEY_VALUE = b"appsrc0"
+    protobufVec = InProtobufVector()
+    
+    protobuf = MxProtobufIn()
+    protobuf.key = KEY_VALUE
+    protobuf.type = b"MxTools.MxpiVisionList"
+    protobuf.protobuf = visionList.SerializeToString()
+    protobufVec.push_back(protobuf)
+ 
+    uniqueId = streamManagerApi.SendProtobuf(STREAMNAME, INPLUGINID, protobufVec)
+
+    keys = [b'mxpi_objectpostprocessor0']
+    keyVec = StringVector()
+    for key in keys:
+        keyVec.push_back(key)
+    infer_result = streamManagerApi.GetProtobuf(STREAMNAME, 0, keyVec)
+    if infer_result.size() == 0:
+        print("infer_result is null")
+        exit()
+
+    if infer_result[0].errorCode != 0:
+        print("GetProtobuf error. errorCode=%d" % (infer_result[0].errorCode))
+        exit()
+    objectList = MxpiDataType.MxpiObjectList()
+    objectList.ParseFromString(infer_result[0].messageBuf)
+
+    img = cv2.imread('./test.jpg')
+    result = objectList.objectVec
+    resize , left, top, right, bottom = return_img
+    for x in result:
+        new_x0 = max(int((x.x0-left)/resize), 0)
+        new_x1 = max(int((x.x1-left)/resize), 0)
+        new_y0 = max(int((x.y0-top)/resize), 0)
+        new_y1 = max(int((x.y1-top)/resize), 0)
+
+        confidence = x.classVec[0].confidence
+        cv2.rectangle(img, (new_x0, new_y0), (new_x1, new_y1), (255, 0, 0), 2)
+
+    cv2.imwrite("./result.jpg", img)
+    streamManagerApi.DestroyAllStreams()
diff --git a/contrib/Retinaface/model/run.sh b/mxVision/mxVision-referenceapps/Retinaface/model/run.sh
similarity index 100%
rename from contrib/Retinaface/model/run.sh
rename to mxVision/mxVision-referenceapps/Retinaface/model/run.sh
diff --git a/contrib/Retinaface/plugin/CMakeLists.txt b/mxVision/mxVision-referenceapps/Retinaface/plugin/CMakeLists.txt
similarity index 100%
rename from contrib/Retinaface/plugin/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/Retinaface/plugin/CMakeLists.txt
diff --git a/contrib/Retinaface/plugin/TotalYunetPostProcess.cpp b/mxVision/mxVision-referenceapps/Retinaface/plugin/TotalYunetPostProcess.cpp
similarity index 100%
rename from contrib/Retinaface/plugin/TotalYunetPostProcess.cpp
rename to mxVision/mxVision-referenceapps/Retinaface/plugin/TotalYunetPostProcess.cpp
diff --git a/contrib/Retinaface/plugin/TotalYunetPostProcess.h b/mxVision/mxVision-referenceapps/Retinaface/plugin/TotalYunetPostProcess.h
similarity index 100%
rename from contrib/Retinaface/plugin/TotalYunetPostProcess.h
rename to mxVision/mxVision-referenceapps/Retinaface/plugin/TotalYunetPostProcess.h
diff --git a/contrib/Retinaface/plugin/build.sh b/mxVision/mxVision-referenceapps/Retinaface/plugin/build.sh
similarity index 100%
rename from contrib/Retinaface/plugin/build.sh
rename to mxVision/mxVision-referenceapps/Retinaface/plugin/build.sh
diff --git a/contrib/Retinaface/run.sh b/mxVision/mxVision-referenceapps/Retinaface/run.sh
similarity index 100%
rename from contrib/Retinaface/run.sh
rename to mxVision/mxVision-referenceapps/Retinaface/run.sh
diff --git a/contrib/Retinaface/test.py b/mxVision/mxVision-referenceapps/Retinaface/test.py
similarity index 100%
rename from contrib/Retinaface/test.py
rename to mxVision/mxVision-referenceapps/Retinaface/test.py
diff --git a/contrib/Retinaface/utils.py b/mxVision/mxVision-referenceapps/Retinaface/utils.py
similarity index 100%
rename from contrib/Retinaface/utils.py
rename to mxVision/mxVision-referenceapps/Retinaface/utils.py
diff --git a/contrib/RoadSegmentation/README.md b/mxVision/mxVision-referenceapps/RoadSegmentation/README.md
similarity index 100%
rename from contrib/RoadSegmentation/README.md
rename to mxVision/mxVision-referenceapps/RoadSegmentation/README.md
diff --git a/contrib/RoadSegmentation/build.sh b/mxVision/mxVision-referenceapps/RoadSegmentation/build.sh
similarity index 100%
rename from contrib/RoadSegmentation/build.sh
rename to mxVision/mxVision-referenceapps/RoadSegmentation/build.sh
diff --git a/contrib/RoadSegmentation/config/aipp_road_segmentation.config b/mxVision/mxVision-referenceapps/RoadSegmentation/config/aipp_road_segmentation.config
similarity index 100%
rename from contrib/RoadSegmentation/config/aipp_road_segmentation.config
rename to mxVision/mxVision-referenceapps/RoadSegmentation/config/aipp_road_segmentation.config
diff --git a/contrib/RoadSegmentation/image/SDK_process.png b/mxVision/mxVision-referenceapps/RoadSegmentation/image/SDK_process.png
similarity index 100%
rename from contrib/RoadSegmentation/image/SDK_process.png
rename to mxVision/mxVision-referenceapps/RoadSegmentation/image/SDK_process.png
diff --git a/contrib/RoadSegmentation/image/imagedecoder_error.png b/mxVision/mxVision-referenceapps/RoadSegmentation/image/imagedecoder_error.png
similarity index 100%
rename from contrib/RoadSegmentation/image/imagedecoder_error.png
rename to mxVision/mxVision-referenceapps/RoadSegmentation/image/imagedecoder_error.png
diff --git a/contrib/RoadSegmentation/main.py b/mxVision/mxVision-referenceapps/RoadSegmentation/main.py
similarity index 100%
rename from contrib/RoadSegmentation/main.py
rename to mxVision/mxVision-referenceapps/RoadSegmentation/main.py
diff --git a/contrib/RoadSegmentation/model/pt2onnx.py b/mxVision/mxVision-referenceapps/RoadSegmentation/model/pt2onnx.py
similarity index 100%
rename from contrib/RoadSegmentation/model/pt2onnx.py
rename to mxVision/mxVision-referenceapps/RoadSegmentation/model/pt2onnx.py
diff --git a/contrib/RoadSegmentation/pipeline/road.pipeline b/mxVision/mxVision-referenceapps/RoadSegmentation/pipeline/road.pipeline
similarity index 100%
rename from contrib/RoadSegmentation/pipeline/road.pipeline
rename to mxVision/mxVision-referenceapps/RoadSegmentation/pipeline/road.pipeline
diff --git a/contrib/RoadSegmentation/plugin/RoadSegPostProcess/CMakeLists.txt b/mxVision/mxVision-referenceapps/RoadSegmentation/plugin/RoadSegPostProcess/CMakeLists.txt
similarity index 100%
rename from contrib/RoadSegmentation/plugin/RoadSegPostProcess/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/RoadSegmentation/plugin/RoadSegPostProcess/CMakeLists.txt
diff --git a/contrib/RoadSegmentation/plugin/RoadSegPostProcess/MxpiRoadSegPostProcess.cpp b/mxVision/mxVision-referenceapps/RoadSegmentation/plugin/RoadSegPostProcess/MxpiRoadSegPostProcess.cpp
similarity index 100%
rename from contrib/RoadSegmentation/plugin/RoadSegPostProcess/MxpiRoadSegPostProcess.cpp
rename to mxVision/mxVision-referenceapps/RoadSegmentation/plugin/RoadSegPostProcess/MxpiRoadSegPostProcess.cpp
diff --git a/contrib/RoadSegmentation/plugin/RoadSegPostProcess/MxpiRoadSegPostProcess.h b/mxVision/mxVision-referenceapps/RoadSegmentation/plugin/RoadSegPostProcess/MxpiRoadSegPostProcess.h
similarity index 100%
rename from contrib/RoadSegmentation/plugin/RoadSegPostProcess/MxpiRoadSegPostProcess.h
rename to mxVision/mxVision-referenceapps/RoadSegmentation/plugin/RoadSegPostProcess/MxpiRoadSegPostProcess.h
diff --git a/contrib/RoadSegmentation/plugin/RoadSegPostProcess/build.sh b/mxVision/mxVision-referenceapps/RoadSegmentation/plugin/RoadSegPostProcess/build.sh
similarity index 100%
rename from contrib/RoadSegmentation/plugin/RoadSegPostProcess/build.sh
rename to mxVision/mxVision-referenceapps/RoadSegmentation/plugin/RoadSegPostProcess/build.sh
diff --git a/mxVision/RtspServer/README.zh.md b/mxVision/mxVision-referenceapps/RtspServer/README.zh.md
similarity index 100%
rename from mxVision/RtspServer/README.zh.md
rename to mxVision/mxVision-referenceapps/RtspServer/README.zh.md
diff --git a/contrib/SOLOV2/README.md b/mxVision/mxVision-referenceapps/SOLOV2/README.md
similarity index 100%
rename from contrib/SOLOV2/README.md
rename to mxVision/mxVision-referenceapps/SOLOV2/README.md
diff --git a/contrib/SOLOV2/build.sh b/mxVision/mxVision-referenceapps/SOLOV2/build.sh
similarity index 100%
rename from contrib/SOLOV2/build.sh
rename to mxVision/mxVision-referenceapps/SOLOV2/build.sh
diff --git a/contrib/SOLOV2/images/eval_result.png b/mxVision/mxVision-referenceapps/SOLOV2/images/eval_result.png
similarity index 100%
rename from contrib/SOLOV2/images/eval_result.png
rename to mxVision/mxVision-referenceapps/SOLOV2/images/eval_result.png
diff --git a/contrib/SOLOV2/images/pipeline.png b/mxVision/mxVision-referenceapps/SOLOV2/images/pipeline.png
similarity index 100%
rename from contrib/SOLOV2/images/pipeline.png
rename to mxVision/mxVision-referenceapps/SOLOV2/images/pipeline.png
diff --git a/contrib/SOLOV2/postprocess/CMakeLists.txt b/mxVision/mxVision-referenceapps/SOLOV2/postprocess/CMakeLists.txt
similarity index 100%
rename from contrib/SOLOV2/postprocess/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/SOLOV2/postprocess/CMakeLists.txt
diff --git a/contrib/SOLOV2/postprocess/Solov2PostProcess.cpp b/mxVision/mxVision-referenceapps/SOLOV2/postprocess/Solov2PostProcess.cpp
similarity index 100%
rename from contrib/SOLOV2/postprocess/Solov2PostProcess.cpp
rename to mxVision/mxVision-referenceapps/SOLOV2/postprocess/Solov2PostProcess.cpp
diff --git a/contrib/SOLOV2/postprocess/Solov2PostProcess.h b/mxVision/mxVision-referenceapps/SOLOV2/postprocess/Solov2PostProcess.h
similarity index 100%
rename from contrib/SOLOV2/postprocess/Solov2PostProcess.h
rename to mxVision/mxVision-referenceapps/SOLOV2/postprocess/Solov2PostProcess.h
diff --git a/contrib/SOLOV2/postprocess/build.sh b/mxVision/mxVision-referenceapps/SOLOV2/postprocess/build.sh
similarity index 100%
rename from contrib/SOLOV2/postprocess/build.sh
rename to mxVision/mxVision-referenceapps/SOLOV2/postprocess/build.sh
diff --git a/contrib/SOLOV2/python/Main/main_eval.py b/mxVision/mxVision-referenceapps/SOLOV2/python/Main/main_eval.py
similarity index 100%
rename from contrib/SOLOV2/python/Main/main_eval.py
rename to mxVision/mxVision-referenceapps/SOLOV2/python/Main/main_eval.py
diff --git a/contrib/SOLOV2/python/Main/main_visualize.py b/mxVision/mxVision-referenceapps/SOLOV2/python/Main/main_visualize.py
similarity index 100%
rename from contrib/SOLOV2/python/Main/main_visualize.py
rename to mxVision/mxVision-referenceapps/SOLOV2/python/Main/main_visualize.py
diff --git a/contrib/SOLOV2/python/models/aipp_config/aipp_opencv.cfg b/mxVision/mxVision-referenceapps/SOLOV2/python/models/aipp_config/aipp_opencv.cfg
similarity index 100%
rename from contrib/SOLOV2/python/models/aipp_config/aipp_opencv.cfg
rename to mxVision/mxVision-referenceapps/SOLOV2/python/models/aipp_config/aipp_opencv.cfg
diff --git a/contrib/SOLOV2/python/models/solov2.cfg b/mxVision/mxVision-referenceapps/SOLOV2/python/models/solov2.cfg
similarity index 100%
rename from contrib/SOLOV2/python/models/solov2.cfg
rename to mxVision/mxVision-referenceapps/SOLOV2/python/models/solov2.cfg
diff --git a/contrib/SOLOV2/python/pipeline/solov2.pipeline b/mxVision/mxVision-referenceapps/SOLOV2/python/pipeline/solov2.pipeline
similarity index 100%
rename from contrib/SOLOV2/python/pipeline/solov2.pipeline
rename to mxVision/mxVision-referenceapps/SOLOV2/python/pipeline/solov2.pipeline
diff --git a/contrib/STGCN/README.md b/mxVision/mxVision-referenceapps/STGCN/README.md
similarity index 100%
rename from contrib/STGCN/README.md
rename to mxVision/mxVision-referenceapps/STGCN/README.md
diff --git a/contrib/STGCN/convert_om.sh b/mxVision/mxVision-referenceapps/STGCN/convert_om.sh
similarity index 100%
rename from contrib/STGCN/convert_om.sh
rename to mxVision/mxVision-referenceapps/STGCN/convert_om.sh
diff --git a/contrib/STGCN/main.py b/mxVision/mxVision-referenceapps/STGCN/main.py
similarity index 100%
rename from contrib/STGCN/main.py
rename to mxVision/mxVision-referenceapps/STGCN/main.py
diff --git a/contrib/STGCN/pipeline/stgcn.pipeline b/mxVision/mxVision-referenceapps/STGCN/pipeline/stgcn.pipeline
similarity index 100%
rename from contrib/STGCN/pipeline/stgcn.pipeline
rename to mxVision/mxVision-referenceapps/STGCN/pipeline/stgcn.pipeline
diff --git a/contrib/STGCN/predict.py b/mxVision/mxVision-referenceapps/STGCN/predict.py
similarity index 100%
rename from contrib/STGCN/predict.py
rename to mxVision/mxVision-referenceapps/STGCN/predict.py
diff --git a/contrib/STGCN/train_need/export_onnx.py b/mxVision/mxVision-referenceapps/STGCN/train_need/export_onnx.py
similarity index 100%
rename from contrib/STGCN/train_need/export_onnx.py
rename to mxVision/mxVision-referenceapps/STGCN/train_need/export_onnx.py
diff --git a/contrib/SentimentAnalysis/README.md b/mxVision/mxVision-referenceapps/SentimentAnalysis/README.md
similarity index 100%
rename from contrib/SentimentAnalysis/README.md
rename to mxVision/mxVision-referenceapps/SentimentAnalysis/README.md
diff --git a/contrib/SentimentAnalysis/build.sh b/mxVision/mxVision-referenceapps/SentimentAnalysis/build.sh
similarity index 100%
rename from contrib/SentimentAnalysis/build.sh
rename to mxVision/mxVision-referenceapps/SentimentAnalysis/build.sh
diff --git a/contrib/SentimentAnalysis/mxBase/CMakeLists.txt b/mxVision/mxVision-referenceapps/SentimentAnalysis/mxBase/CMakeLists.txt
similarity index 100%
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rename to mxVision/mxVision-referenceapps/SentimentAnalysis/mxBase/CMakeLists.txt
diff --git a/contrib/SentimentAnalysis/mxBase/SentimentAnalysis/SentimentAnalysis.cpp b/mxVision/mxVision-referenceapps/SentimentAnalysis/mxBase/SentimentAnalysis/SentimentAnalysis.cpp
similarity index 100%
rename from contrib/SentimentAnalysis/mxBase/SentimentAnalysis/SentimentAnalysis.cpp
rename to mxVision/mxVision-referenceapps/SentimentAnalysis/mxBase/SentimentAnalysis/SentimentAnalysis.cpp
diff --git a/contrib/SentimentAnalysis/mxBase/SentimentAnalysis/SentimentAnalysis.h b/mxVision/mxVision-referenceapps/SentimentAnalysis/mxBase/SentimentAnalysis/SentimentAnalysis.h
similarity index 100%
rename from contrib/SentimentAnalysis/mxBase/SentimentAnalysis/SentimentAnalysis.h
rename to mxVision/mxVision-referenceapps/SentimentAnalysis/mxBase/SentimentAnalysis/SentimentAnalysis.h
diff --git a/contrib/SentimentAnalysis/mxBase/build.sh b/mxVision/mxVision-referenceapps/SentimentAnalysis/mxBase/build.sh
similarity index 100%
rename from contrib/SentimentAnalysis/mxBase/build.sh
rename to mxVision/mxVision-referenceapps/SentimentAnalysis/mxBase/build.sh
diff --git a/contrib/SentimentAnalysis/mxBase/data/vocab.txt b/mxVision/mxVision-referenceapps/SentimentAnalysis/mxBase/data/vocab.txt
similarity index 100%
rename from contrib/SentimentAnalysis/mxBase/data/vocab.txt
rename to mxVision/mxVision-referenceapps/SentimentAnalysis/mxBase/data/vocab.txt
diff --git a/contrib/SentimentAnalysis/mxBase/main.cpp b/mxVision/mxVision-referenceapps/SentimentAnalysis/mxBase/main.cpp
similarity index 100%
rename from contrib/SentimentAnalysis/mxBase/main.cpp
rename to mxVision/mxVision-referenceapps/SentimentAnalysis/mxBase/main.cpp
diff --git a/contrib/SentimentAnalysis/mxBase/model/sentiment_analysis_label.names b/mxVision/mxVision-referenceapps/SentimentAnalysis/mxBase/model/sentiment_analysis_label.names
similarity index 100%
rename from contrib/SentimentAnalysis/mxBase/model/sentiment_analysis_label.names
rename to mxVision/mxVision-referenceapps/SentimentAnalysis/mxBase/model/sentiment_analysis_label.names
diff --git a/contrib/SentimentAnalysis/mxBase/out/prediction_label.txt b/mxVision/mxVision-referenceapps/SentimentAnalysis/mxBase/out/prediction_label.txt
similarity index 100%
rename from contrib/SentimentAnalysis/mxBase/out/prediction_label.txt
rename to mxVision/mxVision-referenceapps/SentimentAnalysis/mxBase/out/prediction_label.txt
diff --git a/contrib/SentimentAnalysis/mxBase/test/Test.cpp b/mxVision/mxVision-referenceapps/SentimentAnalysis/mxBase/test/Test.cpp
similarity index 100%
rename from contrib/SentimentAnalysis/mxBase/test/Test.cpp
rename to mxVision/mxVision-referenceapps/SentimentAnalysis/mxBase/test/Test.cpp
diff --git a/contrib/SentimentAnalysis/mxBase/test/Test.h b/mxVision/mxVision-referenceapps/SentimentAnalysis/mxBase/test/Test.h
similarity index 100%
rename from contrib/SentimentAnalysis/mxBase/test/Test.h
rename to mxVision/mxVision-referenceapps/SentimentAnalysis/mxBase/test/Test.h
diff --git a/contrib/SentimentAnalysis/sdk/build.sh b/mxVision/mxVision-referenceapps/SentimentAnalysis/sdk/build.sh
similarity index 100%
rename from contrib/SentimentAnalysis/sdk/build.sh
rename to mxVision/mxVision-referenceapps/SentimentAnalysis/sdk/build.sh
diff --git a/contrib/SentimentAnalysis/sdk/config/sentiment_analysis_aipp_tf.cfg b/mxVision/mxVision-referenceapps/SentimentAnalysis/sdk/config/sentiment_analysis_aipp_tf.cfg
similarity index 100%
rename from contrib/SentimentAnalysis/sdk/config/sentiment_analysis_aipp_tf.cfg
rename to mxVision/mxVision-referenceapps/SentimentAnalysis/sdk/config/sentiment_analysis_aipp_tf.cfg
diff --git a/contrib/SentimentAnalysis/sdk/config/sentiment_analysis_label.names b/mxVision/mxVision-referenceapps/SentimentAnalysis/sdk/config/sentiment_analysis_label.names
similarity index 100%
rename from contrib/SentimentAnalysis/sdk/config/sentiment_analysis_label.names
rename to mxVision/mxVision-referenceapps/SentimentAnalysis/sdk/config/sentiment_analysis_label.names
diff --git a/contrib/SentimentAnalysis/sdk/data/vocab.txt b/mxVision/mxVision-referenceapps/SentimentAnalysis/sdk/data/vocab.txt
similarity index 100%
rename from contrib/SentimentAnalysis/sdk/data/vocab.txt
rename to mxVision/mxVision-referenceapps/SentimentAnalysis/sdk/data/vocab.txt
diff --git a/contrib/SentimentAnalysis/sdk/flowChart.jpg b/mxVision/mxVision-referenceapps/SentimentAnalysis/sdk/flowChart.jpg
similarity index 100%
rename from contrib/SentimentAnalysis/sdk/flowChart.jpg
rename to mxVision/mxVision-referenceapps/SentimentAnalysis/sdk/flowChart.jpg
diff --git a/contrib/SentimentAnalysis/sdk/main.py b/mxVision/mxVision-referenceapps/SentimentAnalysis/sdk/main.py
similarity index 100%
rename from contrib/SentimentAnalysis/sdk/main.py
rename to mxVision/mxVision-referenceapps/SentimentAnalysis/sdk/main.py
diff --git a/contrib/SentimentAnalysis/sdk/model/model_conversion.sh b/mxVision/mxVision-referenceapps/SentimentAnalysis/sdk/model/model_conversion.sh
similarity index 100%
rename from contrib/SentimentAnalysis/sdk/model/model_conversion.sh
rename to mxVision/mxVision-referenceapps/SentimentAnalysis/sdk/model/model_conversion.sh
diff --git a/contrib/SentimentAnalysis/sdk/out/prediction_label.txt b/mxVision/mxVision-referenceapps/SentimentAnalysis/sdk/out/prediction_label.txt
similarity index 100%
rename from contrib/SentimentAnalysis/sdk/out/prediction_label.txt
rename to mxVision/mxVision-referenceapps/SentimentAnalysis/sdk/out/prediction_label.txt
diff --git a/contrib/SentimentAnalysis/sdk/pipeline/sentiment_analysis.pipeline b/mxVision/mxVision-referenceapps/SentimentAnalysis/sdk/pipeline/sentiment_analysis.pipeline
similarity index 100%
rename from contrib/SentimentAnalysis/sdk/pipeline/sentiment_analysis.pipeline
rename to mxVision/mxVision-referenceapps/SentimentAnalysis/sdk/pipeline/sentiment_analysis.pipeline
diff --git a/contrib/SentimentAnalysis/sdk/run.sh b/mxVision/mxVision-referenceapps/SentimentAnalysis/sdk/run.sh
similarity index 100%
rename from contrib/SentimentAnalysis/sdk/run.sh
rename to mxVision/mxVision-referenceapps/SentimentAnalysis/sdk/run.sh
diff --git a/contrib/SentimentAnalysis/sdk/test/test.py b/mxVision/mxVision-referenceapps/SentimentAnalysis/sdk/test/test.py
similarity index 100%
rename from contrib/SentimentAnalysis/sdk/test/test.py
rename to mxVision/mxVision-referenceapps/SentimentAnalysis/sdk/test/test.py
diff --git a/contrib/SentimentAnalysis/sdk/test/test.sh b/mxVision/mxVision-referenceapps/SentimentAnalysis/sdk/test/test.sh
similarity index 100%
rename from contrib/SentimentAnalysis/sdk/test/test.sh
rename to mxVision/mxVision-referenceapps/SentimentAnalysis/sdk/test/test.sh
diff --git a/contrib/SentimentAnalysis/sdk/tokenizer.py b/mxVision/mxVision-referenceapps/SentimentAnalysis/sdk/tokenizer.py
similarity index 100%
rename from contrib/SentimentAnalysis/sdk/tokenizer.py
rename to mxVision/mxVision-referenceapps/SentimentAnalysis/sdk/tokenizer.py
diff --git a/contrib/StyleTransfer/README.md b/mxVision/mxVision-referenceapps/StyleTransfer/README.md
similarity index 96%
rename from contrib/StyleTransfer/README.md
rename to mxVision/mxVision-referenceapps/StyleTransfer/README.md
index c353072d14507fc8369ba502ad159dbc0153bd82..039b51f1852bd07fed090056f81fa3af5af47475 100644
--- a/contrib/StyleTransfer/README.md
+++ b/mxVision/mxVision-referenceapps/StyleTransfer/README.md
@@ -1,207 +1,207 @@
-# Mind SDK 风格转换参考设计（从航拍图到卫星图的转换）
-
-## 介绍
-
-本文中风格转换中的航拍图到卫星图转换。它通过一种无监督的少样本的学习方式，能够实现风格转换。
-
-论文原文：https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix
-
-测试集下载地址：https://people.eecs.berkeley.edu/~taesung_park/CycleGAN/datasets/maps.zip
-
-初始模型、推理模型及转换脚本下载：https://www.hiascend.com/zh/software/modelzoo/detail/1/3ba3b04fd4964d9b81974381b73f491d
-
-### 项目实现流程及适用场景
-
-![avatar](./README_img/pic.png)
-
-
-项目的主要流程：
-（1）输入类型是图片数据（jpg图片序列）
-（2）通过调用MindX SDK提供的图像解码接口mxpi_imagedecoder，解码后获取图像数据。
-（3）然后进行图像尺寸大小变换，调用MindX SDK提供的图像尺寸大小变换接口mxpi_imageresize插件，输入图像大小要求高256，宽256。
-（4）模型后处理，调用MindX SDK提供的模型推理插件mxpi_modelinfer。然后调用MindX SDK提供的appsink将结果取出。
-（5）模型输出经过后处理后，得到图片数组并写入图片。
-场景限制：
-输入的图像应为卫星航拍图，在清晰度较好的情况下，能取得较好的推理效果。
-
-### 支持的产品以及环境依赖
-
-支持 Atlas 200dk开发者套件、Ascend 310推理芯片。
-
-```
-|   软件名称    |    版本     |
-| :-----------: | :---------: |
-|    ubuntu     |  18.04.5 LTS |
-|   MindX SDK   |    5.0.RC3    |
-|    Python     |    3.9.2    |
-|     CANN      |    7.0.RC1    |
-|     numpy     |   1.22.3    |
-| opencv-python |    4.5.5    |
-```
-
-版本号查询方法，在Atlas产品环境下，运行命令：
-
-```
-npu-smi info
-
-```
-运行后会在终端输出：
-```
-+------------------------------------------------------------------------------+
-| npu-smi 21.0.3.1                     Version: 21.0.3.1                       |
-+-------------------+-----------------+----------------------------------------+
-| NPU     Name      | Health          | Power(W)          Temp(C)              |
-| Chip    Device    | Bus-Id          | AICore(%)         Memory-Usage(MB)     |
-+===================+=================+========================================+
-| 0       310       | OK              | 12.8              58                   |
-| 0       0         | NA              | 0                 5324 / 8192          |
-+===================+=================+========================================+
-```
-
-### 软件方案介绍
-
-```
-| 序号 | 子系统  | 功能描述 |
-| 1   | 图像输入 | 调用MindX SDK的appsrc输入图片|
-| 2   | 图像解码 | 调用MindX SDK的mxpi_imagedecoder对图像解码|
-| 3   | 图像放缩 | 调用MindX SDK的mxpi_imageresize，放缩到256*256大小 |
-| 4   | 图像推理 | 调用MindX SDK的mxpi_tensorinfer推理图像|
-| 5   | 结果输出 | 输出图片信息|
-```
-
-### 代码目录结构与说明
-
-本参考设计工程名称为StyleTransfer，工程目录如下图所示： 
-
-```
-StyleTransfer
-.
-├── README.md
-├── README_img      
-│   └── pic.png  //README流程图
-├── models       
-│   └── aipp_CycleGAN_pth.config  //aipp配置文件  
-├── pipeline
-│   └── styletransfer.pipeline
-└── src
-    └── main.py
-```
-
-### python第三方库
-
-```
-numpy == 1.16.6
-
-Pillow == 8.2.0
-
-opencv-python == 4.5.2
-
-sympy == 1.4
-
-decorator == 4.4.2
-
-requests == 2.22.0
-
-tqdm == 4.61.0
-
-PyYAML == 5.4.1
-```
-
-### 开发准备
-
-> 模型转换
-
-**步骤1** 将pth模型转换为onnx模型
-
-首先在ModelZoo下载CycleGAN模型。
-
-下载地址：https://www.hiascend.com/zh/software/modelzoo/detail/1/3ba3b04fd4964d9b81974381b73f491d
-
-模型获取解压后，将CycleGAN文件夹下的所有文件及文件夹全部都放在StyleTransfer/models文件夹中
-
-**步骤2** 设置环境变量
-
-运行MindXSDK与ascend-toolkit下的set_env.sh设置环境变量
-MindXSDK：${MX_SDK_HOME}/set_env.sh
-
-ascend-toolkit：/usr/local/Ascend/ascend-toolkit/set_env.sh
-```
-bash set_env.sh 
-
-```
-
-**步骤3** 将原始pth模型转化为onnx模型
-
-进入/models目录
-
-```
-python3  CycleGAN_onnx_export.py  --model_ga_path=latest_net_G_A.pth  --model_gb_path=latest_net_G_B.pth  --onnx_path=./onnxmodel/  --model_ga_onnx_name=model_Ga.onnx  --model_gb_onnx_name=model_Gb.onnx
-```
-生成的onnx模型在./onnxmodel/文件夹下
-
-**步骤4** 配置AIPP
-
-```
-aipp_op{
-    aipp_mode:static
-    input_format : YUV420SP_U8
-    csc_switch : true
-    rbuv_swap_switch : true
-    src_image_size_w : 256
-    src_image_size_h : 256
-    min_chn_0 : 127.5
-    min_chn_1 : 127.5
-    min_chn_2 : 127.5
-    var_reci_chn_0: 0.007843137254901
-    var_reci_chn_1: 0.007843137254901
-    var_reci_chn_2: 0.007843137254901
-    matrix_r0c0: 256
-    matrix_r0c1: 0
-    matrix_r0c2: 359
-    matrix_r1c0: 256
-    matrix_r1c1: -88
-    matrix_r1c2: -183
-    matrix_r2c0: 256
-    matrix_r2c1: 454
-    matrix_r2c2: 0
-    input_bias_0: 0
-    input_bias_1: 128
-    input_bias_2: 128
-}
-```
-保存在/models下的aipp_CycleGAN_pth.config文件中。
-
-**步骤5** 将onnx模型转换为om模型
-
-仍然在/models目录中操作
-```
-atc --framework=5   --model=./onnxmodel/model_Ga.onnx  --output=sat2map   --input_format=NCHW   --input_shape="img_sat_maps:1,3,256,256" --out_nodes="maps"  --log=debug --soc_version=Ascend310 --insert_op_conf=aipp_CycleGAN_pth.config
-```
-
-转换完成后存放在/models中。
-
-**步骤6** 下载测试集
-
-在文章介绍中下载maps测试集，然后将测试集中testA文件夹复制到/StyleTransfer目录下
-
-更改测试图片可以通过更改main.py脚本的IMG_PATH变量。默认的测试图片是/StyleTransfer/testA/sat.jpg
-
-**步骤7** 运行程序
-
-```
-python3 main.py
-```
-
-###  运行结果
-
-生成的地图存放在result目录中。
-
-如果没有需要在StyleTransfer文件夹中手动创建
-
-```
-mkdir result
-```
-查看生成图片
-```
-ls ../result/map.jpg 
+# Mind SDK 风格转换参考设计（从航拍图到卫星图的转换）
+
+## 介绍
+
+本文中风格转换中的航拍图到卫星图转换。它通过一种无监督的少样本的学习方式，能够实现风格转换。
+
+论文原文：https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix
+
+测试集下载地址：https://people.eecs.berkeley.edu/~taesung_park/CycleGAN/datasets/maps.zip
+
+初始模型、推理模型及转换脚本下载：https://www.hiascend.com/zh/software/modelzoo/detail/1/3ba3b04fd4964d9b81974381b73f491d
+
+### 项目实现流程及适用场景
+
+![avatar](./README_img/pic.png)
+
+
+项目的主要流程：
+（1）输入类型是图片数据（jpg图片序列）
+（2）通过调用MindX SDK提供的图像解码接口mxpi_imagedecoder，解码后获取图像数据。
+（3）然后进行图像尺寸大小变换，调用MindX SDK提供的图像尺寸大小变换接口mxpi_imageresize插件，输入图像大小要求高256，宽256。
+（4）模型后处理，调用MindX SDK提供的模型推理插件mxpi_modelinfer。然后调用MindX SDK提供的appsink将结果取出。
+（5）模型输出经过后处理后，得到图片数组并写入图片。
+场景限制：
+输入的图像应为卫星航拍图，在清晰度较好的情况下，能取得较好的推理效果。
+
+### 支持的产品以及环境依赖
+
+支持 Atlas 200dk开发者套件、Ascend 310推理芯片。
+
+```
+|   软件名称    |    版本     |
+| :-----------: | :---------: |
+|    ubuntu     |  18.04.5 LTS |
+|   MindX SDK   |    5.0.RC3    |
+|    Python     |    3.9.2    |
+|     CANN      |    7.0.RC1    |
+|     numpy     |   1.22.3    |
+| opencv-python |    4.5.5    |
+```
+
+版本号查询方法，在Atlas产品环境下，运行命令：
+
+```
+npu-smi info
+
+```
+运行后会在终端输出：
+```
++------------------------------------------------------------------------------+
+| npu-smi 21.0.3.1                     Version: 21.0.3.1                       |
++-------------------+-----------------+----------------------------------------+
+| NPU     Name      | Health          | Power(W)          Temp(C)              |
+| Chip    Device    | Bus-Id          | AICore(%)         Memory-Usage(MB)     |
++===================+=================+========================================+
+| 0       310       | OK              | 12.8              58                   |
+| 0       0         | NA              | 0                 5324 / 8192          |
++===================+=================+========================================+
+```
+
+### 软件方案介绍
+
+```
+| 序号 | 子系统  | 功能描述 |
+| 1   | 图像输入 | 调用MindX SDK的appsrc输入图片|
+| 2   | 图像解码 | 调用MindX SDK的mxpi_imagedecoder对图像解码|
+| 3   | 图像放缩 | 调用MindX SDK的mxpi_imageresize，放缩到256*256大小 |
+| 4   | 图像推理 | 调用MindX SDK的mxpi_tensorinfer推理图像|
+| 5   | 结果输出 | 输出图片信息|
+```
+
+### 代码目录结构与说明
+
+本参考设计工程名称为StyleTransfer，工程目录如下图所示： 
+
+```
+StyleTransfer
+.
+├── README.md
+├── README_img      
+│   └── pic.png  //README流程图
+├── models       
+│   └── aipp_CycleGAN_pth.config  //aipp配置文件  
+├── pipeline
+│   └── styletransfer.pipeline
+└── src
+    └── main.py
+```
+
+### python第三方库
+
+```
+numpy == 1.16.6
+
+Pillow == 8.2.0
+
+opencv-python == 4.5.2
+
+sympy == 1.4
+
+decorator == 4.4.2
+
+requests == 2.22.0
+
+tqdm == 4.61.0
+
+PyYAML == 5.4.1
+```
+
+### 开发准备
+
+> 模型转换
+
+**步骤1** 将pth模型转换为onnx模型
+
+首先在ModelZoo下载CycleGAN模型。
+
+下载地址：https://www.hiascend.com/zh/software/modelzoo/detail/1/3ba3b04fd4964d9b81974381b73f491d
+
+模型获取解压后，将CycleGAN文件夹下的所有文件及文件夹全部都放在StyleTransfer/models文件夹中
+
+**步骤2** 设置环境变量
+
+运行MindXSDK与ascend-toolkit下的set_env.sh设置环境变量
+MindXSDK：${MX_SDK_HOME}/set_env.sh
+
+ascend-toolkit：/usr/local/Ascend/ascend-toolkit/set_env.sh
+```
+bash set_env.sh 
+
+```
+
+**步骤3** 将原始pth模型转化为onnx模型
+
+进入/models目录
+
+```
+python3  CycleGAN_onnx_export.py  --model_ga_path=latest_net_G_A.pth  --model_gb_path=latest_net_G_B.pth  --onnx_path=./onnxmodel/  --model_ga_onnx_name=model_Ga.onnx  --model_gb_onnx_name=model_Gb.onnx
+```
+生成的onnx模型在./onnxmodel/文件夹下
+
+**步骤4** 配置AIPP
+
+```
+aipp_op{
+    aipp_mode:static
+    input_format : YUV420SP_U8
+    csc_switch : true
+    rbuv_swap_switch : true
+    src_image_size_w : 256
+    src_image_size_h : 256
+    min_chn_0 : 127.5
+    min_chn_1 : 127.5
+    min_chn_2 : 127.5
+    var_reci_chn_0: 0.007843137254901
+    var_reci_chn_1: 0.007843137254901
+    var_reci_chn_2: 0.007843137254901
+    matrix_r0c0: 256
+    matrix_r0c1: 0
+    matrix_r0c2: 359
+    matrix_r1c0: 256
+    matrix_r1c1: -88
+    matrix_r1c2: -183
+    matrix_r2c0: 256
+    matrix_r2c1: 454
+    matrix_r2c2: 0
+    input_bias_0: 0
+    input_bias_1: 128
+    input_bias_2: 128
+}
+```
+保存在/models下的aipp_CycleGAN_pth.config文件中。
+
+**步骤5** 将onnx模型转换为om模型
+
+仍然在/models目录中操作
+```
+atc --framework=5   --model=./onnxmodel/model_Ga.onnx  --output=sat2map   --input_format=NCHW   --input_shape="img_sat_maps:1,3,256,256" --out_nodes="maps"  --log=debug --soc_version=Ascend310 --insert_op_conf=aipp_CycleGAN_pth.config
+```
+
+转换完成后存放在/models中。
+
+**步骤6** 下载测试集
+
+在文章介绍中下载maps测试集，然后将测试集中testA文件夹复制到/StyleTransfer目录下
+
+更改测试图片可以通过更改main.py脚本的IMG_PATH变量。默认的测试图片是/StyleTransfer/testA/sat.jpg
+
+**步骤7** 运行程序
+
+```
+python3 main.py
+```
+
+###  运行结果
+
+生成的地图存放在result目录中。
+
+如果没有需要在StyleTransfer文件夹中手动创建
+
+```
+mkdir result
+```
+查看生成图片
+```
+ls ../result/map.jpg 
 ```
\ No newline at end of file
diff --git a/contrib/StyleTransfer/README_img/pic.png b/mxVision/mxVision-referenceapps/StyleTransfer/README_img/pic.png
similarity index 100%
rename from contrib/StyleTransfer/README_img/pic.png
rename to mxVision/mxVision-referenceapps/StyleTransfer/README_img/pic.png
diff --git a/contrib/StyleTransfer/models/aipp_CycleGAN_pth.config b/mxVision/mxVision-referenceapps/StyleTransfer/models/aipp_CycleGAN_pth.config
similarity index 100%
rename from contrib/StyleTransfer/models/aipp_CycleGAN_pth.config
rename to mxVision/mxVision-referenceapps/StyleTransfer/models/aipp_CycleGAN_pth.config
diff --git a/contrib/StyleTransfer/pipeline/styletransfer.pipeline b/mxVision/mxVision-referenceapps/StyleTransfer/pipeline/styletransfer.pipeline
similarity index 96%
rename from contrib/StyleTransfer/pipeline/styletransfer.pipeline
rename to mxVision/mxVision-referenceapps/StyleTransfer/pipeline/styletransfer.pipeline
index 0a0021907741b68c338dcaa67ac34043bc247c14..3ffd8517c615cf8f9afaf359642e3f233601e7a1 100644
--- a/contrib/StyleTransfer/pipeline/styletransfer.pipeline
+++ b/mxVision/mxVision-referenceapps/StyleTransfer/pipeline/styletransfer.pipeline
@@ -1,44 +1,44 @@
-{
-    "styletransfer": {
-        "stream_config": {
-            "deviceId": "0"
-        },
-        "appsrc0": {
-            "props": {
-                "blocksize": "409600"
-            },
-            "factory": "appsrc",
-            "next": "mxpi_imagedecoder0"
-        },
-        "mxpi_imagedecoder0": {
-            "props": {
-                "deviceId": "0"
-            },
-            "factory": "mxpi_imagedecoder",
-            "next": "mxpi_imageresize0"
-        },
-        "mxpi_imageresize0": {
-            "props": {
-                "dataSource": "mxpi_imagedecoder0",
-                "resizeHeight": "256",
-                "resizeWidth": "256"
-            },
-            "factory": "mxpi_imageresize",
-            "next": "mxpi_tensorinfer0"
-        },
-        "mxpi_tensorinfer0": {
-            "props": {
-                "dataSource": "mxpi_imageresize0",
-                "modelPath": "../models/sat2map.om"
-            },
-            "factory": "mxpi_tensorinfer",
-            "next": "appsink0"
-        },
-        "appsink0": {
-            "props": {
-                "blocksize": "4096000"
-            },
-            "factory": "appsink"
-        }
-    }
-}
+{
+    "styletransfer": {
+        "stream_config": {
+            "deviceId": "0"
+        },
+        "appsrc0": {
+            "props": {
+                "blocksize": "409600"
+            },
+            "factory": "appsrc",
+            "next": "mxpi_imagedecoder0"
+        },
+        "mxpi_imagedecoder0": {
+            "props": {
+                "deviceId": "0"
+            },
+            "factory": "mxpi_imagedecoder",
+            "next": "mxpi_imageresize0"
+        },
+        "mxpi_imageresize0": {
+            "props": {
+                "dataSource": "mxpi_imagedecoder0",
+                "resizeHeight": "256",
+                "resizeWidth": "256"
+            },
+            "factory": "mxpi_imageresize",
+            "next": "mxpi_tensorinfer0"
+        },
+        "mxpi_tensorinfer0": {
+            "props": {
+                "dataSource": "mxpi_imageresize0",
+                "modelPath": "../models/sat2map.om"
+            },
+            "factory": "mxpi_tensorinfer",
+            "next": "appsink0"
+        },
+        "appsink0": {
+            "props": {
+                "blocksize": "4096000"
+            },
+            "factory": "appsink"
+        }
+    }
+}
diff --git a/contrib/StyleTransfer/src/main.py b/mxVision/mxVision-referenceapps/StyleTransfer/src/main.py
similarity index 96%
rename from contrib/StyleTransfer/src/main.py
rename to mxVision/mxVision-referenceapps/StyleTransfer/src/main.py
index 2f2522cc54f4080e80f0103213e084dafa9dbe97..1dda733cd7e3f07e0c2cc14d20fba8a06cd22951 100644
--- a/contrib/StyleTransfer/src/main.py
+++ b/mxVision/mxVision-referenceapps/StyleTransfer/src/main.py
@@ -1,104 +1,104 @@
-#!/usr/bin/env python
-#-*-coding:utf-8-*-
-
-# Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-# http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-
-import sys
-import os
-import io
-import cv2
-from cv2 import COLOR_RGB2BGR
-import numpy as np
-import MxpiDataType_pb2 as MxpiDataType
-from StreamManagerApi import StreamManagerApi, MxDataInput, StringVector
-
-MODEL_WIDTH = 256
-MODEL_HEIGHT = 256
-
-RGB_TUNNEL_NUMBER = 3
-NORMALIZE_MAX = 255.0
-
-if __name__ == '__main__':
-    #  check input image
-    IMG_PATH = "../testA/sat.jpg"
-    PIPELINE = "../pipeline/styletransfer.pipeline"
-
-    # initialize the stream manager
-    stream_manager = StreamManagerApi()
-    stream_state = stream_manager.InitManager()
-
-    # check pipeline
-    if os.path.exists(PIPELINE) != 1:
-        print("The pipeline does not exist.")
-        exit()
-    # create streams by the pipeline config
-    with open(PIPELINE, 'rb') as f:
-        pipeline = f.read().replace(b'\r', b'').replace(b'\n', b'')
-    pipeline_string = pipeline
-    stream_state = stream_manager.CreateMultipleStreams(pipeline_string)
-    if stream_state != 0:
-        print("Failed to create Stream, ret=%s" % str(stream_state))
-        exit()
-
-    # prepare the input of the stream #begin
-    STREAM_NAME = b"styletransfer"
-    PLUGIN_ID = 0
-    dataInput = MxDataInput()
-
-    if os.path.exists(IMG_PATH) != 1:
-        print("The test image does not exist.")
-        exit()
-
-    with open(IMG_PATH, 'rb') as f:
-        dataInput.data = f.read()
-    ret = stream_manager.SendData(STREAM_NAME, PLUGIN_ID, dataInput)
-
-    if ret < 0:
-        print("Failed to send data to stream")
-        exit()
-
-    keys = [b"mxpi_tensorinfer0"]
-    keyVec = StringVector()
-    for key in keys:
-        keyVec.push_back(key)
-
-    # Get the result from the stream
-    infer = stream_manager.GetResult(STREAM_NAME, b'appsink0', keyVec)
-    if infer.metadataVec[0].errorCode != 0:
-        print("GetResult error. errorCode=%d ,errorMsg=%s" % (
-            infer.metadataVec[0].errorCode, infer.metadataVec[0].errorMsg))
-        exit()
-
-    tensorList = MxpiDataType.MxpiTensorPackageList()
-    tensorList.ParseFromString(infer.metadataVec[0].serializedMetadata)
-    output_res_DANet = np.frombuffer(tensorList.tensorPackageVec[0].tensorVec[0].dataStr, dtype=np.float32)
-
-    # Reshape and transpose
-    result = output_res_DANet.reshape(RGB_TUNNEL_NUMBER, MODEL_WIDTH, MODEL_WIDTH)
-    result = result.transpose(1, 2, 0)
-
-    # Reverse Normalize
-    result = result * NORMALIZE_MAX
-    result = cv2.cvtColor(result, COLOR_RGB2BGR)
-    result = cv2.resize(result, (MODEL_WIDTH, MODEL_HEIGHT))
-    print("___________infer_finish_____________")
-
-    cv2.imwrite('../result/map.jpg', result)
-
-    stream_manager.DestroyAllStreams()
-
-
-
+#!/usr/bin/env python
+#-*-coding:utf-8-*-
+
+# Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+
+import sys
+import os
+import io
+import cv2
+from cv2 import COLOR_RGB2BGR
+import numpy as np
+import MxpiDataType_pb2 as MxpiDataType
+from StreamManagerApi import StreamManagerApi, MxDataInput, StringVector
+
+MODEL_WIDTH = 256
+MODEL_HEIGHT = 256
+
+RGB_TUNNEL_NUMBER = 3
+NORMALIZE_MAX = 255.0
+
+if __name__ == '__main__':
+    #  check input image
+    IMG_PATH = "../testA/sat.jpg"
+    PIPELINE = "../pipeline/styletransfer.pipeline"
+
+    # initialize the stream manager
+    stream_manager = StreamManagerApi()
+    stream_state = stream_manager.InitManager()
+
+    # check pipeline
+    if os.path.exists(PIPELINE) != 1:
+        print("The pipeline does not exist.")
+        exit()
+    # create streams by the pipeline config
+    with open(PIPELINE, 'rb') as f:
+        pipeline = f.read().replace(b'\r', b'').replace(b'\n', b'')
+    pipeline_string = pipeline
+    stream_state = stream_manager.CreateMultipleStreams(pipeline_string)
+    if stream_state != 0:
+        print("Failed to create Stream, ret=%s" % str(stream_state))
+        exit()
+
+    # prepare the input of the stream #begin
+    STREAM_NAME = b"styletransfer"
+    PLUGIN_ID = 0
+    dataInput = MxDataInput()
+
+    if os.path.exists(IMG_PATH) != 1:
+        print("The test image does not exist.")
+        exit()
+
+    with open(IMG_PATH, 'rb') as f:
+        dataInput.data = f.read()
+    ret = stream_manager.SendData(STREAM_NAME, PLUGIN_ID, dataInput)
+
+    if ret < 0:
+        print("Failed to send data to stream")
+        exit()
+
+    keys = [b"mxpi_tensorinfer0"]
+    keyVec = StringVector()
+    for key in keys:
+        keyVec.push_back(key)
+
+    # Get the result from the stream
+    infer = stream_manager.GetResult(STREAM_NAME, b'appsink0', keyVec)
+    if infer.metadataVec[0].errorCode != 0:
+        print("GetResult error. errorCode=%d ,errorMsg=%s" % (
+            infer.metadataVec[0].errorCode, infer.metadataVec[0].errorMsg))
+        exit()
+
+    tensorList = MxpiDataType.MxpiTensorPackageList()
+    tensorList.ParseFromString(infer.metadataVec[0].serializedMetadata)
+    output_res_DANet = np.frombuffer(tensorList.tensorPackageVec[0].tensorVec[0].dataStr, dtype=np.float32)
+
+    # Reshape and transpose
+    result = output_res_DANet.reshape(RGB_TUNNEL_NUMBER, MODEL_WIDTH, MODEL_WIDTH)
+    result = result.transpose(1, 2, 0)
+
+    # Reverse Normalize
+    result = result * NORMALIZE_MAX
+    result = cv2.cvtColor(result, COLOR_RGB2BGR)
+    result = cv2.resize(result, (MODEL_WIDTH, MODEL_HEIGHT))
+    print("___________infer_finish_____________")
+
+    cv2.imwrite('../result/map.jpg', result)
+
+    stream_manager.DestroyAllStreams()
+
+
+
diff --git a/contrib/SuperResolution/README.md b/mxVision/mxVision-referenceapps/SuperResolution/README.md
similarity index 100%
rename from contrib/SuperResolution/README.md
rename to mxVision/mxVision-referenceapps/SuperResolution/README.md
diff --git a/contrib/SuperResolution/evaluate.py b/mxVision/mxVision-referenceapps/SuperResolution/evaluate.py
similarity index 100%
rename from contrib/SuperResolution/evaluate.py
rename to mxVision/mxVision-referenceapps/SuperResolution/evaluate.py
diff --git a/contrib/SuperResolution/font/SourceHanSansCN-Normal-2.otf b/mxVision/mxVision-referenceapps/SuperResolution/font/SourceHanSansCN-Normal-2.otf
similarity index 100%
rename from contrib/SuperResolution/font/SourceHanSansCN-Normal-2.otf
rename to mxVision/mxVision-referenceapps/SuperResolution/font/SourceHanSansCN-Normal-2.otf
diff --git a/contrib/SuperResolution/result/.keep b/mxVision/mxVision-referenceapps/SuperResolution/image/.keep
similarity index 100%
rename from contrib/SuperResolution/result/.keep
rename to mxVision/mxVision-referenceapps/SuperResolution/image/.keep
diff --git a/contrib/SuperResolution/main.py b/mxVision/mxVision-referenceapps/SuperResolution/main.py
similarity index 100%
rename from contrib/SuperResolution/main.py
rename to mxVision/mxVision-referenceapps/SuperResolution/main.py
diff --git a/contrib/SuperResolution/model/YUV420SP_U8_GRAY.cfg b/mxVision/mxVision-referenceapps/SuperResolution/model/YUV420SP_U8_GRAY.cfg
similarity index 100%
rename from contrib/SuperResolution/model/YUV420SP_U8_GRAY.cfg
rename to mxVision/mxVision-referenceapps/SuperResolution/model/YUV420SP_U8_GRAY.cfg
diff --git a/contrib/SuperResolution/testSet/91-images-jpg/.keep b/mxVision/mxVision-referenceapps/SuperResolution/result/.keep
similarity index 100%
rename from contrib/SuperResolution/testSet/91-images-jpg/.keep
rename to mxVision/mxVision-referenceapps/SuperResolution/result/.keep
diff --git a/contrib/SuperResolution/testSet/91-images/.keep b/mxVision/mxVision-referenceapps/SuperResolution/testSet/91-images-jpg/.keep
similarity index 100%
rename from contrib/SuperResolution/testSet/91-images/.keep
rename to mxVision/mxVision-referenceapps/SuperResolution/testSet/91-images-jpg/.keep
diff --git a/contrib/VehicleCounting/data/.keep b/mxVision/mxVision-referenceapps/SuperResolution/testSet/91-images/.keep
similarity index 100%
rename from contrib/VehicleCounting/data/.keep
rename to mxVision/mxVision-referenceapps/SuperResolution/testSet/91-images/.keep
diff --git a/contrib/SuperResolution/testSet/bmp2jpg.py b/mxVision/mxVision-referenceapps/SuperResolution/testSet/bmp2jpg.py
similarity index 100%
rename from contrib/SuperResolution/testSet/bmp2jpg.py
rename to mxVision/mxVision-referenceapps/SuperResolution/testSet/bmp2jpg.py
diff --git a/contrib/SuperResolution/utils.py b/mxVision/mxVision-referenceapps/SuperResolution/utils.py
similarity index 100%
rename from contrib/SuperResolution/utils.py
rename to mxVision/mxVision-referenceapps/SuperResolution/utils.py
diff --git a/contrib/SuperRetina/README.md b/mxVision/mxVision-referenceapps/SuperRetina/README.md
similarity index 97%
rename from contrib/SuperRetina/README.md
rename to mxVision/mxVision-referenceapps/SuperRetina/README.md
index d1703f5923d4dd6ef35d8d4d463bd6fc142fd249..ccc9176091d6fc99f291a47d031353c94cea43d8 100644
--- a/contrib/SuperRetina/README.md
+++ b/mxVision/mxVision-referenceapps/SuperRetina/README.md
@@ -1,131 +1,131 @@
-# 基于深度学习的图像配准
-
-## 1 介绍
-
-### 1.1 简介
-
-基于深度学习的图像配准基于 MindXSDK 开发，在晟腾芯片上进行图像配准。输入两幅图片，可以匹配两幅图像中的特征点。
-图像配准的业务流程为：将输入的两幅图片进行归一化等预处理操作后，输入到模型中进行推理，对输出的关键点，进行极大值抑制去除相近的关键点，再进一步去除靠近边界的关键点，最后利用knn聚类算法得到可能性最大的关键点。本系统的各模块及功能描述如下：
-
-| 序号 | 子系统   | 功能描述                   |
-| ---- | -------- | -------------------------- |
-| 1    | 图像输入 | 读取图像                   |
-| 2    | 预处理   | 对图像进行预处理           |
-| 3    | 模型推理 | 对输入进行推理并输出结果   |
-| 4    | 后处理   | 从模型推理结果中解出关键点 |
-
-
-### 1.2 支持的产品
-本项目以昇腾Atlas 500 A2为主要的硬件平台。
-
-### 1.3 支持的版本
-本样例配套的MxVision版本、CANN版本、Driver/Firmware版本如下所示：
-| MxVision版本  | CANN版本  | Driver/Firmware版本  |
-| --------- | ------------------ | -------------- |
-| 5.0.0 | 7.0.0   |  23.0.0  |
-| 6.0.RC2 | 8.0.RC2   |  24.1.RC2  |
-
-### 1.4 三方依赖
-
-| 软件名称    | 版本    | 
-|---------|-------| 
-| numpy   | 1.23.0 |
-| scipy   | 1.13.1 |
-| pytorch | 1.7.0 |
-| tqdm    | 4.64.1 |
-
-
-### 1.5 代码目录结构说明
-```txt
-.
-│  README.mdn
-│  onnx2om.sh
-│
-└─python
-    │  main.py
-    │  requirements.txt
-    │  predictor.py
-    │  resize.py
-    │
-    ├─config
-    │  test.yaml
-```
-
-
-## 2 设置环境变量
-```bash
-export PYTHONPATH=${MX_SDK_HOME}/python/:$PYTHONPATH
-export install_path=${install_path}
-. ${install_path}/set_env.sh
-. ${MX_SDK_HOME}/set_env.sh
-```
-
-注：
-**${MX_SDK_HOME}** 替换为用户自己的MindX_SDK安装路径（例如："/home/xxx/MindX_SDK/mxVision"）；
-
-**${install_path}** 替换为CANN开发套件包所在路径（例如：/usr/local/Ascend/ascend-toolkit/latest）。
-
-
-## 3 准备模型
-
-模型转换使用的是ATC工具，具体使用教程可参考[《ATC工具使用指南》](https://www.hiascend.com/document/detail/zh/CANNCommunityEdition/80RC2alpha003/devaids/auxiliarydevtool/atlasatc_16_0001.html)。
-
-**步骤1** 获取.onnx模型
-本文提供已完成转换的onnx模型供开发者使用：https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/SuperRetina/models.zip
-
-**步骤2** **onnx转om** 将步骤2中转换获得的onnx模型存放至**服务器端**的SuperRetina/目录下，执行如下命令：
-```bash
-bash onnx2om.sh ./SuperRetina.onnx ./SuperRetina
-```
-
-
-## 4 运行
-
-**步骤1**  在./python目录下创建./samples文件夹，下载需要配准的图像上传到文件夹中。（注意：图像宽高需根据模型调整，若不对本文提供的模型做改变，需限制为768*768）。
-
-**步骤2**  按照第 2 小节 环境依赖 中的步骤设置环境变量。
-
-**步骤3**  按照第 3 小节 模型转换 中的步骤获得 om 模型文件,在./python目录下创建./model文件夹，将om文件移动到model文件夹中。
-
-**步骤4**  在./python目录下运行predictor.py，首先按需求修改路径：
-
-```bash
-    f1 = './data/samples/query.jpg'   # image path
-    f2 = './data/samples/refer.jpg'   # image path
-    merged = align_image_pair(f1, f2, model, show=True)
-```
-
-执行如下命令：
-
-```bash
-python predictor.py
-```
-输出两幅图像，分别命名为match_result.jpg和result.jpg。
-
-
-
-## 5 精度验证
-
-**步骤1**  在./python目录下创建./data文件夹，下载[FIRE数据集]( https://projects.ics.forth.gr/cvrl/fire/FIRE.7z)，解压后将./FIRE文件夹，放到./data文件夹。
-
-**步骤2**  在./python目录下执行resize脚本，将数据集图片缩放到模型的输入的大小，同时也对groudTruth做了缩放。缩放后的图片位于./data/FIRE/Images/resized文件夹下。
-
-**步骤3**  按照第 2 小节 环境依赖 中的步骤设置环境变量。
-
-**步骤4**  按照第 3 小节 模型转换 中的步骤获得 om 模型文件,在./python目录下创建./model文件夹,将om文件移动到model文件夹中。
-
-**步骤5**  在./python目录下运行main.py函数，执行如下命令：
-
-```bash
-python main.py 
-```
-
-结果输出到终端，结果如下所示：
-
-```bash
-100%|██████████| 133/133 [1:37:18<00:00, 43.90s/it]
-----------------------------------------
-Failed:0.00%, Inaccurate:0.00%, Acceptable:100.00%
-----------------------------------------
-S: 0.999, P: 0.894, A: 0.960, mAUC: 0.951
+# 基于深度学习的图像配准
+
+## 1 介绍
+
+### 1.1 简介
+
+基于深度学习的图像配准基于 MindXSDK 开发，在晟腾芯片上进行图像配准。输入两幅图片，可以匹配两幅图像中的特征点。
+图像配准的业务流程为：将输入的两幅图片进行归一化等预处理操作后，输入到模型中进行推理，对输出的关键点，进行极大值抑制去除相近的关键点，再进一步去除靠近边界的关键点，最后利用knn聚类算法得到可能性最大的关键点。本系统的各模块及功能描述如下：
+
+| 序号 | 子系统   | 功能描述                   |
+| ---- | -------- | -------------------------- |
+| 1    | 图像输入 | 读取图像                   |
+| 2    | 预处理   | 对图像进行预处理           |
+| 3    | 模型推理 | 对输入进行推理并输出结果   |
+| 4    | 后处理   | 从模型推理结果中解出关键点 |
+
+
+### 1.2 支持的产品
+本项目以昇腾Atlas 500 A2为主要的硬件平台。
+
+### 1.3 支持的版本
+本样例配套的MxVision版本、CANN版本、Driver/Firmware版本如下所示：
+| MxVision版本  | CANN版本  | Driver/Firmware版本  |
+| --------- | ------------------ | -------------- |
+| 5.0.0 | 7.0.0   |  23.0.0  |
+| 6.0.RC2 | 8.0.RC2   |  24.1.RC2  |
+
+### 1.4 三方依赖
+
+| 软件名称    | 版本    | 
+|---------|-------| 
+| numpy   | 1.23.0 |
+| scipy   | 1.13.1 |
+| pytorch | 1.7.0 |
+| tqdm    | 4.64.1 |
+
+
+### 1.5 代码目录结构说明
+```txt
+.
+│  README.mdn
+│  onnx2om.sh
+│
+└─python
+    │  main.py
+    │  requirements.txt
+    │  predictor.py
+    │  resize.py
+    │
+    ├─config
+    │  test.yaml
+```
+
+
+## 2 设置环境变量
+```bash
+export PYTHONPATH=${MX_SDK_HOME}/python/:$PYTHONPATH
+export install_path=${install_path}
+. ${install_path}/set_env.sh
+. ${MX_SDK_HOME}/set_env.sh
+```
+
+注：
+**${MX_SDK_HOME}** 替换为用户自己的MindX_SDK安装路径（例如："/home/xxx/MindX_SDK/mxVision"）；
+
+**${install_path}** 替换为CANN开发套件包所在路径（例如：/usr/local/Ascend/ascend-toolkit/latest）。
+
+
+## 3 准备模型
+
+模型转换使用的是ATC工具，具体使用教程可参考[《ATC工具使用指南》](https://www.hiascend.com/document/detail/zh/CANNCommunityEdition/80RC2alpha003/devaids/auxiliarydevtool/atlasatc_16_0001.html)。
+
+**步骤1** 获取.onnx模型
+本文提供已完成转换的onnx模型供开发者使用：https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/SuperRetina/models.zip
+
+**步骤2** **onnx转om** 将步骤2中转换获得的onnx模型存放至**服务器端**的SuperRetina/目录下，执行如下命令：
+```bash
+bash onnx2om.sh ./SuperRetina.onnx ./SuperRetina
+```
+
+
+## 4 运行
+
+**步骤1**  在./python目录下创建./samples文件夹，下载需要配准的图像上传到文件夹中。（注意：图像宽高需根据模型调整，若不对本文提供的模型做改变，需限制为768*768）。
+
+**步骤2**  按照第 2 小节 环境依赖 中的步骤设置环境变量。
+
+**步骤3**  按照第 3 小节 模型转换 中的步骤获得 om 模型文件,在./python目录下创建./model文件夹，将om文件移动到model文件夹中。
+
+**步骤4**  在./python目录下运行predictor.py，首先按需求修改路径：
+
+```bash
+    f1 = './data/samples/query.jpg'   # image path
+    f2 = './data/samples/refer.jpg'   # image path
+    merged = align_image_pair(f1, f2, model, show=True)
+```
+
+执行如下命令：
+
+```bash
+python predictor.py
+```
+输出两幅图像，分别命名为match_result.jpg和result.jpg。
+
+
+
+## 5 精度验证
+
+**步骤1**  在./python目录下创建./data文件夹，下载[FIRE数据集]( https://projects.ics.forth.gr/cvrl/fire/FIRE.7z)，解压后将./FIRE文件夹，放到./data文件夹。
+
+**步骤2**  在./python目录下执行resize脚本，将数据集图片缩放到模型的输入的大小，同时也对groudTruth做了缩放。缩放后的图片位于./data/FIRE/Images/resized文件夹下。
+
+**步骤3**  按照第 2 小节 环境依赖 中的步骤设置环境变量。
+
+**步骤4**  按照第 3 小节 模型转换 中的步骤获得 om 模型文件,在./python目录下创建./model文件夹,将om文件移动到model文件夹中。
+
+**步骤5**  在./python目录下运行main.py函数，执行如下命令：
+
+```bash
+python main.py 
+```
+
+结果输出到终端，结果如下所示：
+
+```bash
+100%|██████████| 133/133 [1:37:18<00:00, 43.90s/it]
+----------------------------------------
+Failed:0.00%, Inaccurate:0.00%, Acceptable:100.00%
+----------------------------------------
+S: 0.999, P: 0.894, A: 0.960, mAUC: 0.951
 ```
\ No newline at end of file
diff --git a/contrib/SuperRetina/images/pipeline.png b/mxVision/mxVision-referenceapps/SuperRetina/images/pipeline.png
similarity index 100%
rename from contrib/SuperRetina/images/pipeline.png
rename to mxVision/mxVision-referenceapps/SuperRetina/images/pipeline.png
diff --git a/contrib/SuperRetina/onnx2om.sh b/mxVision/mxVision-referenceapps/SuperRetina/onnx2om.sh
similarity index 100%
rename from contrib/SuperRetina/onnx2om.sh
rename to mxVision/mxVision-referenceapps/SuperRetina/onnx2om.sh
diff --git a/contrib/SuperRetina/python/config/test.yaml b/mxVision/mxVision-referenceapps/SuperRetina/python/config/test.yaml
similarity index 100%
rename from contrib/SuperRetina/python/config/test.yaml
rename to mxVision/mxVision-referenceapps/SuperRetina/python/config/test.yaml
diff --git a/contrib/SuperRetina/python/main.py b/mxVision/mxVision-referenceapps/SuperRetina/python/main.py
similarity index 97%
rename from contrib/SuperRetina/python/main.py
rename to mxVision/mxVision-referenceapps/SuperRetina/python/main.py
index f24a586b547e7e00cec7827d9782292fbaf84e40..8136a756e62371c6af2e1c9111c8f0a2849bc6f0 100644
--- a/contrib/SuperRetina/python/main.py
+++ b/mxVision/mxVision-referenceapps/SuperRetina/python/main.py
@@ -1,468 +1,468 @@
-#!/usr/bin/env python
-# coding=utf-8
-
-"""
-Copyright(C) Huawei Technologies Co.,Ltd. 2022 All rights reserved.
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
-    http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License.
-"""
-
-from ast import mod
-import os
-import time
-import numpy as np
-from tqdm import tqdm
-from numpy.lib.stride_tricks import as_strided
-import yaml
-from PIL import Image
-
-import cv2
-
-
-import mindx.sdk as sdk
-
-CONFIG_PATH = './config/test.yaml' # config path
-if os.path.exists(CONFIG_PATH):
-    with open(CONFIG_PATH) as f:
-        config = yaml.safe_load(f)
-else:
-    raise FileNotFoundError("Config File doesn't Exist")
-
-model_image_width = config['PREDICT']['model_image_width']
-model_image_height = config['PREDICT']['model_image_height']
-nms_thresh = config['PREDICT']['nms_thresh']
-nms_size = config['PREDICT']['nms_size']
-knn_thresh = config['PREDICT']['knn_thresh']
-use_matching_trick = config['PREDICT']['use_matching_trick']
-
-
-def pre_processing(data):
-    """ Enhance retinal images """
-    train_imgs = datasets_normalized(data)
-    train_imgs = clahe_equalized(train_imgs)
-    train_imgs = adjust_gamma(train_imgs, 1.2)
-
-    train_imgs = train_imgs / 255.
-
-    return train_imgs.astype(np.float32)
-
-
-def datasets_normalized(images):
-    images_std = np.std(images)
-    images_mean = np.mean(images)
-    images_normalized = (images - images_mean) / (images_std + 1e-6)
-    minv = np.min(images_normalized)
-    images_normalized = ((images_normalized - minv) /
-                         (np.max(images_normalized) - minv)) * 255
-
-    return images_normalized
-
-
-def clahe_equalized(images):
-    clahe = cv2.createCLAHE(clipLimit=2.0, tileGridSize=(8, 8))
-    images_equalized = np.empty(images.shape)
-    images_equalized[:, :] = clahe.apply(np.array(images[:, :],
-                                                  dtype=np.uint8))
-
-    return images_equalized
-
-
-def adjust_gamma(images, gamma=1.0):
-    inv_gamma = 1.0 / gamma
-    table = np.array([((i / 255.0) ** inv_gamma) * 255
-                      for i in np.arange(0, 256)]).astype("uint8")
-    new_images = np.empty(images.shape)
-    new_images[:, :] = cv2.LUT(np.array(images[:, :],
-                                        dtype=np.uint8), table)
-
-    return new_images
-
-
-def transform(image):
-    img = Image.fromarray(image)
-    img = img.resize((768, 768), resample=Image.BILINEAR) # input image size must be 768x768
-    img = np.array(img)
-    img = np.expand_dims(img, axis=0)
-    img = img.astype(np.float64) / 255.0
-    return img
-
-
-def image_read(read_query_path, read_refer_path, query_is_image=False):
-    if query_is_image:
-        read_query_image = read_query_path
-    else:
-        read_query_image = cv2.imread(read_query_path, cv2.IMREAD_COLOR)
-        read_query_image = read_query_image[:, :, 1]
-        read_query_image = pre_processing(read_query_image)
-    read_refer_image = cv2.imread(read_refer_path, cv2.IMREAD_COLOR)
-
-    assert read_query_image.shape[:2] == read_refer_image.shape[:2]
-    read_image_height, read_image_width = read_query_image.shape[:2]
-
-    read_refer_image = read_refer_image[:, :, 1]
-    read_refer_image = pre_processing(read_refer_image)
-
-    read_query_image = (read_query_image * 255).astype(np.uint8)
-    read_refer_image = (read_refer_image * 255).astype(np.uint8)
-
-    return [read_query_image, read_refer_image, read_image_height, read_image_width]
-
-
-def cal_auc(s_error, p_error, a_error):
-    assert (len(s_error) == 71)  # Easy pairs
-    assert (len(p_error) == 48)  # Hard pairs. Note file control_points_P37_1_2.txt is ignored
-    assert (len(a_error) == 14)  # Moderate pairs
-
-    s_error = np.array(s_error)
-    p_error = np.array(p_error)
-    a_error = np.array(a_error)
-
-    limit = 25
-    gs_error = np.zeros(limit + 1)
-    gp_error = np.zeros(limit + 1)
-    ga_error = np.zeros(limit + 1)
-
-    accum_s = 0
-    accum_p = 0
-    accum_a = 0
-
-    for i in range(1, limit + 1):
-        gs_error[i] = np.sum(s_error < i) * 100 / len(s_error)
-        gp_error[i] = np.sum(p_error < i) * 100 / len(p_error)
-        ga_error[i] = np.sum(a_error < i) * 100 / len(a_error)
-
-        accum_s = accum_s + gs_error[i]
-        accum_p = accum_p + gp_error[i]
-        accum_a = accum_a + ga_error[i]
-
-    auc_s = accum_s / (limit * 100)
-    auc_p = accum_p / (limit * 100)
-    auc_a = accum_a / (limit * 100)
-    mauc = (auc_s + auc_p + auc_a) / 3.0
-    return {'s': auc_s, 'p': auc_p, 'a': auc_a, 'mAUC': mauc}
-
-
-def pool2d(maxpool_input, kernel_size, stride, padding=0):
-    maxpool_input = np.pad(maxpool_input, padding, mode='constant')
-    # Window view of A
-    output_shape = ((maxpool_input.shape[0] - kernel_size) // stride + 1,
-                    (maxpool_input.shape[1] - kernel_size) // stride + 1)
-    
-    shape_w = (output_shape[0], output_shape[1], kernel_size, kernel_size)
-    strides_w = (stride*maxpool_input.strides[0], stride*maxpool_input.strides[1],
-    maxpool_input.strides[0], maxpool_input.strides[1])
-    
-    a_w = np.lib.stride_tricks.as_strided(maxpool_input, shape_w, strides_w)
-
-    return a_w.max(axis=(2, 3))
-
-
-def max_pooling(x, kernel_size, stride, padding):
-    x1 = x.copy()
-    a = x[0, 0, :, :]
-    b = x[1, 0, :, :]
-    x1[0, 0, :, :] = pool2d(a, kernel_size, stride, padding)
-    x1[1, 0, :, :] = pool2d(b, kernel_size, stride, padding)
-    
-    return x1
-
-
-def simple_nms(scores, nms_radius: int):
-    """ Fast Non-maximum suppression to remove nearby geo_points """
-    assert (nms_radius >= 0)
-
-    def max_pool(x):
-        return max_pooling(
-            x, kernel_size=nms_radius * 2 + 1, stride=1,
-            padding=nms_radius)
-
-    zeros = np.zeros_like(scores)
-    max_mask = scores == max_pool(scores)
-    for _ in range(2):
-        supp_mask = max_pool(max_mask.astype(np.float32)) > 0
-        supp_scores = np.where(supp_mask, zeros, scores)
-        new_max_mask = supp_scores == max_pool(supp_scores)
-        max_mask = max_mask | (new_max_mask & (~supp_mask))
-    return np.where(max_mask, scores, zeros)
-
-
-def grid_sample(sample_input, grid):
-    n_grid, c_grid, h_in, w_in = sample_input.shape
-    n_grid, h_out, w_out, _ = grid.shape
-    output = np.random.random((n_grid, c_grid, h_out, w_out))
-    for i in range(n_grid):
-        for j in range(c_grid):
-            for k in range(h_out):
-                for l in range(w_out):
-                    x, y = grid[i][k][l][0], grid[i][k][l][1]
-                    param = [0.0, 0.0]
-                    param[0] = (w_in - 1) * (x + 1) / 2
-                    param[1] = (h_in - 1) * (y + 1) / 2
-                    x1 = int(param[0] + 1)
-                    x0 = x1 - 1
-                    y1 = int(param[1] + 1)
-                    y0 = y1 - 1
-                    param[0] = abs(param[0] - x0)
-                    param[1] = abs(param[1] - y0)
-                    left_top_value, left_bottom_value, right_top_value, right_bottom_value = 0, 0, 0, 0
-                    if 0 <= x0 < w_in and 0 <= y0 < h_in:
-                        left_top_value = sample_input[i][j][y0][x0]
-                    if 0 <= x1 < w_in and 0 <= y0 < h_in:
-                        right_top_value = sample_input[i][j][y0][x1]
-                    if 0 <= x0 < w_in and 0 <= y1 < h_in:
-                        left_bottom_value = sample_input[i][j][y1][x0]
-                    if 0 <= x1 < w_in and 0 <= y1 < h_in:
-                        right_bottom_value = sample_input[i][j][y1][x1]
-                    left_top = left_top_value * (1 - param[0]) * (1 - param[1])
-                    left_bottom = left_bottom_value * (1 - param[0]) * param[1]
-                    right_top = right_top_value * param[0] * (1 - param[1])
-                    right_bottom = right_bottom_value * param[0] * param[1]
-                    result = left_bottom + left_top + right_bottom + right_top
-                    output[i][j][k][l] = result
-    return output
-
-
-def normalize(x, p, dim):
-    """
-    Implement a function that normalizes each row of the matrix x (to have unit length).
-    
-    Argument:
-    x -- A numpy matrix of shape (n, m)
-    
-    Returns:
-    x -- The normalized (by row) numpy matrix. You are allowed to modify x.
-    """
-    x_norm = np.linalg.norm(x, ord=p, axis = dim, keepdims = True)
-    x = np.divide(x, x_norm + 1e-6)
- 
-    return x
-
-
-def cal_homography(query_path, refer_path, comp_model, query_is_image=False):
-    goodmatch, cv_kpts_query, cv_kpts_refer, raw_query_image, raw_refer_image, comp_image_height, comp_image_width = \
-    match(query_path, refer_path, comp_model, query_is_image=query_is_image)
-    h_m = None
-    comp_inliers_num_rate = 0
-
-    if len(goodmatch) >= 4:
-        src_pts = [cv_kpts_query[m.queryIdx].pt for m in goodmatch]
-        src_pts = np.float32(src_pts).reshape(-1, 1, 2)
-        dst_pts = [cv_kpts_refer[m.trainIdx].pt for m in goodmatch]
-        dst_pts = np.float32(dst_pts).reshape(-1, 1, 2)
-
-        h_m, mask = cv2.findHomography(src_pts, dst_pts, cv2.LMEDS)
-
-        goodmatch = np.array(goodmatch)[mask.ravel() == 1]
-        comp_inliers_num_rate = mask.sum() / len(mask.ravel())
-    return [h_m, comp_inliers_num_rate, raw_query_image, raw_refer_image, comp_image_height, comp_image_width]
-
-
-def sample_keypoint_desc(keypoints, descriptors, s: int = 8):
-    """ Interpolate descriptors at keypoint locations """
-    b_s, c_s, h_s, w_s = descriptors.shape
-    keypoints = keypoints.copy().astype(np.float32)
-
-    keypoints /= np.array([w_s * s - 1, h_s * s - 1]).astype(np.float32)[None]
-    keypoints = keypoints * 2 - 1  # normalize to (-1, 1)
-
-    descriptors = grid_sample(
-        descriptors, keypoints.reshape(b_s, 1, -1, 2))
-
-    descriptors = normalize(
-        descriptors.reshape(b_s, c_s, -1), p=2, dim=1)
-    return descriptors
-
-
-def remove_borders(keypoints, scores, border: int, height: int, width: int):
-    """ Removes keypoints too close to the border """
-    mask_h = (keypoints[:, 0] >= border) & (keypoints[:, 0] < (height - border))
-    mask_w = (keypoints[:, 1] >= border) & (keypoints[:, 1] < (width - border))
-    mask = mask_h & mask_w
-    return keypoints[mask], scores[mask]
-
-
-def evaluate(query_path, refer_path, infer_model, query_is_image=False):
-    raw_tensor_query , raw_tensor_refer, eval_image_height, eval_image_width =\
-    image_read(query_path, refer_path, query_is_image=query_is_image)
-    tensor_query = transform(raw_tensor_query)
-    tensor_refer = transform(raw_tensor_refer)
-    inputs  = np.concatenate((np.expand_dims(tensor_query, axis=0), np.expand_dims(tensor_refer, axis=0)), axis=0)
-    inputs = inputs.astype(np.float32)
-    inputs_tensor = sdk.Tensor(inputs)
-    inputs_tensor.to_device(0)
-    inputs_tensor_list = [inputs_tensor]
-    outputs = infer_model.infer(inputs_tensor_list)
-    outputs[0].to_host()
-    outputs[1].to_host()
-    infer_data_detector = outputs[0]
-    infer_data_descriptor = outputs[1]
-    infer_data_detector = np.array(infer_data_detector)
-    infer_data_descriptor = np.array(infer_data_descriptor)
-
-    # get the infer result
-    detector_pred = np.reshape(infer_data_detector, (2, 1, 768, 768))
-    descriptor_pred = np.reshape(infer_data_descriptor, (2, 256, 94, 94))
-
-    scores = simple_nms(detector_pred, nms_radius=nms_size)
-    _, _, h_detector, w_detector = detector_pred.shape
-    scores = scores.reshape(-1, h_detector, w_detector)
-
-    keypoints = [np.transpose(np.nonzero(s > nms_thresh)) for s in scores]
-
-    scores = [s[tuple(np.array(k).T.tolist())] for s, k in zip(scores, keypoints)]
-
-    # Discard keypoints near the image borders
-    keypoints, scores = list(zip(*[
-        remove_borders(np.array(k), np.array(s), 4, h_detector, w_detector)
-        for k, s in zip(keypoints, scores)]))
-
-    keypoints = [np.flip(k, [1]).astype(np.float32) for k in keypoints]
-
-    descriptors = [sample_keypoint_desc(k[None], d[None], 8)[0]
-                    for k, d in zip(keypoints, descriptor_pred)]
-    keypoints = [k for k in keypoints]
-    return [keypoints, descriptors, raw_tensor_query, raw_tensor_refer, eval_image_height, eval_image_width]
-
-
-def match(query_path, refer_path, match_model, query_is_image=False):
-    keypoints, descriptors, raw_query_image, raw_refer_image, match_image_height, match_image_width =\
-    evaluate(query_path, refer_path, match_model, query_is_image=query_is_image)
-    query_keypoints, refer_keypoints = keypoints[0], keypoints[1]
-    query_desc, refer_desc = descriptors[0].T.astype(np.float32), descriptors[1].T.astype(np.float32)
-
-    # mapping keypoints to scaled keypoints
-    cv_kpts_query = [cv2.KeyPoint(int(i[0] / model_image_width * match_image_width),
-                                    int(i[1] / model_image_height * match_image_height), 30)
-                        for i in query_keypoints]
-    cv_kpts_refer = [cv2.KeyPoint(int(i[0] / model_image_width * match_image_width),
-                                    int(i[1] / model_image_height * match_image_height), 30)
-                        for i in refer_keypoints]
-
-    good_match = []
-    status = []
-    matches = []
-    knn_matcher = cv2.BFMatcher(cv2.NORM_L2)
-    try:
-        matches = knn_matcher.knnMatch(query_desc, refer_desc, k=2)
-        for m, n in matches:
-            if m.distance < knn_thresh * n.distance:
-                good_match.append(m)
-                status.append(True)
-            else:
-                status.append(False)
-    except Exception:
-        pass
-    return [good_match, cv_kpts_query, cv_kpts_refer, raw_query_image,
-    raw_refer_image, match_image_height, match_image_width]
-
-
-if __name__ == '__main__':
-    # init stream manager
-    FILEPATH = "./model/SuperRetina.om"       # om path
-    DEVICEID = 0                             # device id
-    model = sdk.model(FILEPATH, DEVICEID)
-
-    # set stream name and device
-    STREAM_NAME = b'superretina'
-    IN_PLUGIN_ID = 0
-    DATA_PATH = './data/'
-
-    TESTSET = 'FIRE'
-
-    if not os.path.isdir(DATA_PATH):
-        print("data path don't exit.")
-        exit()
-
-    ground_dir = os.path.join(DATA_PATH, TESTSET, 'Ground Truth/resized')
-    image_dir = os.path.join(DATA_PATH, TESTSET, 'Images/resized')
-    OUT_PATH = '../result'
-    matches_pair = [x for x in os.listdir(ground_dir) if x.endswith('.txt')
-                and not x.endswith('P37_1_2.txt')]
-
-    PAIRFAILED = 0
-    PAIRINACCURATE = 0
-    IMMAE = 0
-    IMMEE = 0
-
-    matches_pair.sort()
-    BIGNUMBER = 1e6
-    good_number = []
-    IMAGENUMBER = 0
-    # category: S, P, A, corresponding to Easy, Hard, Mod in paper
-    auc = dict([(category, []) for category in ['S', 'P', 'A']])
-
-    for read_file in tqdm(matches_pair):
-        ground_file = os.path.join(ground_dir, read_file)
-        name = read_file.replace('.txt', '')
-
-        category = name.split('_')[2][0]
-
-        name_rf = name.split('_')[2] + '_' + name.split('_')[3]
-        name_qr = name.split('_')[2] + '_' + name.split('_')[4]
-
-        query_im = os.path.join(image_dir, name_qr)
-        refer_im = os.path.join(image_dir, name_rf)
-        query_im = query_im + '.jpg'
-        refer_im = refer_im + '.jpg'
-        H_m1, inliers_number, query_image, _, image_height, image_width =\
-            cal_homography(query_im, refer_im, model)
-        HM2 = None
-        if use_matching_trick:
-            if H_m1 is not None:
-                h, w = image_height, image_width
-                query_align_one = cv2.warpPerspective(query_image, H_m1, (h, w), borderMode=cv2.BORDER_CONSTANT,
-                                                borderValue=(0))
-                query_align_one = query_align_one.astype(float)
-                query_align_one /= 255.
-                HM2, inliers_number, _, _, image_height, image_width =\
-                cal_homography(query_align_one, refer_im, model, query_is_image=True)
-
-        good_number.append(inliers_number)
-        IMAGENUMBER += 1
-
-        if inliers_number < 1e-6:
-            PAIRFAILED += 1
-            AVGDIST = BIGNUMBER
-        else:
-            ground_points = np.loadtxt(ground_file)
-            origin = np.zeros([len(ground_points), 2])
-            destination = np.zeros([len(ground_points), 2])
-            origin[:, 0] = ground_points[:, 2]
-            origin[:, 1] = ground_points[:, 3]
-            destination[:, 0] = ground_points[:, 0]
-            destination[:, 1] = ground_points[:, 1]
-            destination_pred = cv2.perspectiveTransform(origin.reshape(-1, 1, 2), H_m1)
-            if HM2 is not None:
-                destination_pred = cv2.perspectiveTransform(destination_pred.reshape(-1, 1, 2), HM2)
-
-            destination_pred = destination_pred.squeeze()
-
-            difference = (destination - destination_pred) ** 2
-            difference = np.sqrt(difference[:, 0] + difference[:, 1])
-            AVGDIST = difference.mean()
-            
-            IMMAE = difference.max()
-            IMMEE = np.median(difference)
-            if IMMAE > 50 or IMMEE > 20:
-                PAIRINACCURATE += 1
-        auc[category].append(AVGDIST)
-    
-    print('----------------------------------------------------------')
-    print(f"fail:{'%.2f' % (100*PAIRFAILED/IMAGENUMBER)}%, inaccurate:{'%.2f' % (100*PAIRINACCURATE/IMAGENUMBER)}%, "
-        f"acceptable:{'%.2f' % (100*(IMAGENUMBER-PAIRINACCURATE-PAIRFAILED)/IMAGENUMBER)}%")
-
-    print('----------------------------------------------------------')
-
-    auc = cal_auc(auc['S'], auc['P'], auc['A'])
-    print('S: %.3f, P: %.3f, A: %.3f, mAUC: %.3f' % (auc.get('s'), auc.get('p'), auc.get('a'), auc.get('mAUC')))
+#!/usr/bin/env python
+# coding=utf-8
+
+"""
+Copyright(C) Huawei Technologies Co.,Ltd. 2022 All rights reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+"""
+
+from ast import mod
+import os
+import time
+import numpy as np
+from tqdm import tqdm
+from numpy.lib.stride_tricks import as_strided
+import yaml
+from PIL import Image
+
+import cv2
+
+
+import mindx.sdk as sdk
+
+CONFIG_PATH = './config/test.yaml' # config path
+if os.path.exists(CONFIG_PATH):
+    with open(CONFIG_PATH) as f:
+        config = yaml.safe_load(f)
+else:
+    raise FileNotFoundError("Config File doesn't Exist")
+
+model_image_width = config['PREDICT']['model_image_width']
+model_image_height = config['PREDICT']['model_image_height']
+nms_thresh = config['PREDICT']['nms_thresh']
+nms_size = config['PREDICT']['nms_size']
+knn_thresh = config['PREDICT']['knn_thresh']
+use_matching_trick = config['PREDICT']['use_matching_trick']
+
+
+def pre_processing(data):
+    """ Enhance retinal images """
+    train_imgs = datasets_normalized(data)
+    train_imgs = clahe_equalized(train_imgs)
+    train_imgs = adjust_gamma(train_imgs, 1.2)
+
+    train_imgs = train_imgs / 255.
+
+    return train_imgs.astype(np.float32)
+
+
+def datasets_normalized(images):
+    images_std = np.std(images)
+    images_mean = np.mean(images)
+    images_normalized = (images - images_mean) / (images_std + 1e-6)
+    minv = np.min(images_normalized)
+    images_normalized = ((images_normalized - minv) /
+                         (np.max(images_normalized) - minv)) * 255
+
+    return images_normalized
+
+
+def clahe_equalized(images):
+    clahe = cv2.createCLAHE(clipLimit=2.0, tileGridSize=(8, 8))
+    images_equalized = np.empty(images.shape)
+    images_equalized[:, :] = clahe.apply(np.array(images[:, :],
+                                                  dtype=np.uint8))
+
+    return images_equalized
+
+
+def adjust_gamma(images, gamma=1.0):
+    inv_gamma = 1.0 / gamma
+    table = np.array([((i / 255.0) ** inv_gamma) * 255
+                      for i in np.arange(0, 256)]).astype("uint8")
+    new_images = np.empty(images.shape)
+    new_images[:, :] = cv2.LUT(np.array(images[:, :],
+                                        dtype=np.uint8), table)
+
+    return new_images
+
+
+def transform(image):
+    img = Image.fromarray(image)
+    img = img.resize((768, 768), resample=Image.BILINEAR) # input image size must be 768x768
+    img = np.array(img)
+    img = np.expand_dims(img, axis=0)
+    img = img.astype(np.float64) / 255.0
+    return img
+
+
+def image_read(read_query_path, read_refer_path, query_is_image=False):
+    if query_is_image:
+        read_query_image = read_query_path
+    else:
+        read_query_image = cv2.imread(read_query_path, cv2.IMREAD_COLOR)
+        read_query_image = read_query_image[:, :, 1]
+        read_query_image = pre_processing(read_query_image)
+    read_refer_image = cv2.imread(read_refer_path, cv2.IMREAD_COLOR)
+
+    assert read_query_image.shape[:2] == read_refer_image.shape[:2]
+    read_image_height, read_image_width = read_query_image.shape[:2]
+
+    read_refer_image = read_refer_image[:, :, 1]
+    read_refer_image = pre_processing(read_refer_image)
+
+    read_query_image = (read_query_image * 255).astype(np.uint8)
+    read_refer_image = (read_refer_image * 255).astype(np.uint8)
+
+    return [read_query_image, read_refer_image, read_image_height, read_image_width]
+
+
+def cal_auc(s_error, p_error, a_error):
+    assert (len(s_error) == 71)  # Easy pairs
+    assert (len(p_error) == 48)  # Hard pairs. Note file control_points_P37_1_2.txt is ignored
+    assert (len(a_error) == 14)  # Moderate pairs
+
+    s_error = np.array(s_error)
+    p_error = np.array(p_error)
+    a_error = np.array(a_error)
+
+    limit = 25
+    gs_error = np.zeros(limit + 1)
+    gp_error = np.zeros(limit + 1)
+    ga_error = np.zeros(limit + 1)
+
+    accum_s = 0
+    accum_p = 0
+    accum_a = 0
+
+    for i in range(1, limit + 1):
+        gs_error[i] = np.sum(s_error < i) * 100 / len(s_error)
+        gp_error[i] = np.sum(p_error < i) * 100 / len(p_error)
+        ga_error[i] = np.sum(a_error < i) * 100 / len(a_error)
+
+        accum_s = accum_s + gs_error[i]
+        accum_p = accum_p + gp_error[i]
+        accum_a = accum_a + ga_error[i]
+
+    auc_s = accum_s / (limit * 100)
+    auc_p = accum_p / (limit * 100)
+    auc_a = accum_a / (limit * 100)
+    mauc = (auc_s + auc_p + auc_a) / 3.0
+    return {'s': auc_s, 'p': auc_p, 'a': auc_a, 'mAUC': mauc}
+
+
+def pool2d(maxpool_input, kernel_size, stride, padding=0):
+    maxpool_input = np.pad(maxpool_input, padding, mode='constant')
+    # Window view of A
+    output_shape = ((maxpool_input.shape[0] - kernel_size) // stride + 1,
+                    (maxpool_input.shape[1] - kernel_size) // stride + 1)
+    
+    shape_w = (output_shape[0], output_shape[1], kernel_size, kernel_size)
+    strides_w = (stride*maxpool_input.strides[0], stride*maxpool_input.strides[1],
+    maxpool_input.strides[0], maxpool_input.strides[1])
+    
+    a_w = np.lib.stride_tricks.as_strided(maxpool_input, shape_w, strides_w)
+
+    return a_w.max(axis=(2, 3))
+
+
+def max_pooling(x, kernel_size, stride, padding):
+    x1 = x.copy()
+    a = x[0, 0, :, :]
+    b = x[1, 0, :, :]
+    x1[0, 0, :, :] = pool2d(a, kernel_size, stride, padding)
+    x1[1, 0, :, :] = pool2d(b, kernel_size, stride, padding)
+    
+    return x1
+
+
+def simple_nms(scores, nms_radius: int):
+    """ Fast Non-maximum suppression to remove nearby geo_points """
+    assert (nms_radius >= 0)
+
+    def max_pool(x):
+        return max_pooling(
+            x, kernel_size=nms_radius * 2 + 1, stride=1,
+            padding=nms_radius)
+
+    zeros = np.zeros_like(scores)
+    max_mask = scores == max_pool(scores)
+    for _ in range(2):
+        supp_mask = max_pool(max_mask.astype(np.float32)) > 0
+        supp_scores = np.where(supp_mask, zeros, scores)
+        new_max_mask = supp_scores == max_pool(supp_scores)
+        max_mask = max_mask | (new_max_mask & (~supp_mask))
+    return np.where(max_mask, scores, zeros)
+
+
+def grid_sample(sample_input, grid):
+    n_grid, c_grid, h_in, w_in = sample_input.shape
+    n_grid, h_out, w_out, _ = grid.shape
+    output = np.random.random((n_grid, c_grid, h_out, w_out))
+    for i in range(n_grid):
+        for j in range(c_grid):
+            for k in range(h_out):
+                for l in range(w_out):
+                    x, y = grid[i][k][l][0], grid[i][k][l][1]
+                    param = [0.0, 0.0]
+                    param[0] = (w_in - 1) * (x + 1) / 2
+                    param[1] = (h_in - 1) * (y + 1) / 2
+                    x1 = int(param[0] + 1)
+                    x0 = x1 - 1
+                    y1 = int(param[1] + 1)
+                    y0 = y1 - 1
+                    param[0] = abs(param[0] - x0)
+                    param[1] = abs(param[1] - y0)
+                    left_top_value, left_bottom_value, right_top_value, right_bottom_value = 0, 0, 0, 0
+                    if 0 <= x0 < w_in and 0 <= y0 < h_in:
+                        left_top_value = sample_input[i][j][y0][x0]
+                    if 0 <= x1 < w_in and 0 <= y0 < h_in:
+                        right_top_value = sample_input[i][j][y0][x1]
+                    if 0 <= x0 < w_in and 0 <= y1 < h_in:
+                        left_bottom_value = sample_input[i][j][y1][x0]
+                    if 0 <= x1 < w_in and 0 <= y1 < h_in:
+                        right_bottom_value = sample_input[i][j][y1][x1]
+                    left_top = left_top_value * (1 - param[0]) * (1 - param[1])
+                    left_bottom = left_bottom_value * (1 - param[0]) * param[1]
+                    right_top = right_top_value * param[0] * (1 - param[1])
+                    right_bottom = right_bottom_value * param[0] * param[1]
+                    result = left_bottom + left_top + right_bottom + right_top
+                    output[i][j][k][l] = result
+    return output
+
+
+def normalize(x, p, dim):
+    """
+    Implement a function that normalizes each row of the matrix x (to have unit length).
+    
+    Argument:
+    x -- A numpy matrix of shape (n, m)
+    
+    Returns:
+    x -- The normalized (by row) numpy matrix. You are allowed to modify x.
+    """
+    x_norm = np.linalg.norm(x, ord=p, axis = dim, keepdims = True)
+    x = np.divide(x, x_norm + 1e-6)
+ 
+    return x
+
+
+def cal_homography(query_path, refer_path, comp_model, query_is_image=False):
+    goodmatch, cv_kpts_query, cv_kpts_refer, raw_query_image, raw_refer_image, comp_image_height, comp_image_width = \
+    match(query_path, refer_path, comp_model, query_is_image=query_is_image)
+    h_m = None
+    comp_inliers_num_rate = 0
+
+    if len(goodmatch) >= 4:
+        src_pts = [cv_kpts_query[m.queryIdx].pt for m in goodmatch]
+        src_pts = np.float32(src_pts).reshape(-1, 1, 2)
+        dst_pts = [cv_kpts_refer[m.trainIdx].pt for m in goodmatch]
+        dst_pts = np.float32(dst_pts).reshape(-1, 1, 2)
+
+        h_m, mask = cv2.findHomography(src_pts, dst_pts, cv2.LMEDS)
+
+        goodmatch = np.array(goodmatch)[mask.ravel() == 1]
+        comp_inliers_num_rate = mask.sum() / len(mask.ravel())
+    return [h_m, comp_inliers_num_rate, raw_query_image, raw_refer_image, comp_image_height, comp_image_width]
+
+
+def sample_keypoint_desc(keypoints, descriptors, s: int = 8):
+    """ Interpolate descriptors at keypoint locations """
+    b_s, c_s, h_s, w_s = descriptors.shape
+    keypoints = keypoints.copy().astype(np.float32)
+
+    keypoints /= np.array([w_s * s - 1, h_s * s - 1]).astype(np.float32)[None]
+    keypoints = keypoints * 2 - 1  # normalize to (-1, 1)
+
+    descriptors = grid_sample(
+        descriptors, keypoints.reshape(b_s, 1, -1, 2))
+
+    descriptors = normalize(
+        descriptors.reshape(b_s, c_s, -1), p=2, dim=1)
+    return descriptors
+
+
+def remove_borders(keypoints, scores, border: int, height: int, width: int):
+    """ Removes keypoints too close to the border """
+    mask_h = (keypoints[:, 0] >= border) & (keypoints[:, 0] < (height - border))
+    mask_w = (keypoints[:, 1] >= border) & (keypoints[:, 1] < (width - border))
+    mask = mask_h & mask_w
+    return keypoints[mask], scores[mask]
+
+
+def evaluate(query_path, refer_path, infer_model, query_is_image=False):
+    raw_tensor_query , raw_tensor_refer, eval_image_height, eval_image_width =\
+    image_read(query_path, refer_path, query_is_image=query_is_image)
+    tensor_query = transform(raw_tensor_query)
+    tensor_refer = transform(raw_tensor_refer)
+    inputs  = np.concatenate((np.expand_dims(tensor_query, axis=0), np.expand_dims(tensor_refer, axis=0)), axis=0)
+    inputs = inputs.astype(np.float32)
+    inputs_tensor = sdk.Tensor(inputs)
+    inputs_tensor.to_device(0)
+    inputs_tensor_list = [inputs_tensor]
+    outputs = infer_model.infer(inputs_tensor_list)
+    outputs[0].to_host()
+    outputs[1].to_host()
+    infer_data_detector = outputs[0]
+    infer_data_descriptor = outputs[1]
+    infer_data_detector = np.array(infer_data_detector)
+    infer_data_descriptor = np.array(infer_data_descriptor)
+
+    # get the infer result
+    detector_pred = np.reshape(infer_data_detector, (2, 1, 768, 768))
+    descriptor_pred = np.reshape(infer_data_descriptor, (2, 256, 94, 94))
+
+    scores = simple_nms(detector_pred, nms_radius=nms_size)
+    _, _, h_detector, w_detector = detector_pred.shape
+    scores = scores.reshape(-1, h_detector, w_detector)
+
+    keypoints = [np.transpose(np.nonzero(s > nms_thresh)) for s in scores]
+
+    scores = [s[tuple(np.array(k).T.tolist())] for s, k in zip(scores, keypoints)]
+
+    # Discard keypoints near the image borders
+    keypoints, scores = list(zip(*[
+        remove_borders(np.array(k), np.array(s), 4, h_detector, w_detector)
+        for k, s in zip(keypoints, scores)]))
+
+    keypoints = [np.flip(k, [1]).astype(np.float32) for k in keypoints]
+
+    descriptors = [sample_keypoint_desc(k[None], d[None], 8)[0]
+                    for k, d in zip(keypoints, descriptor_pred)]
+    keypoints = [k for k in keypoints]
+    return [keypoints, descriptors, raw_tensor_query, raw_tensor_refer, eval_image_height, eval_image_width]
+
+
+def match(query_path, refer_path, match_model, query_is_image=False):
+    keypoints, descriptors, raw_query_image, raw_refer_image, match_image_height, match_image_width =\
+    evaluate(query_path, refer_path, match_model, query_is_image=query_is_image)
+    query_keypoints, refer_keypoints = keypoints[0], keypoints[1]
+    query_desc, refer_desc = descriptors[0].T.astype(np.float32), descriptors[1].T.astype(np.float32)
+
+    # mapping keypoints to scaled keypoints
+    cv_kpts_query = [cv2.KeyPoint(int(i[0] / model_image_width * match_image_width),
+                                    int(i[1] / model_image_height * match_image_height), 30)
+                        for i in query_keypoints]
+    cv_kpts_refer = [cv2.KeyPoint(int(i[0] / model_image_width * match_image_width),
+                                    int(i[1] / model_image_height * match_image_height), 30)
+                        for i in refer_keypoints]
+
+    good_match = []
+    status = []
+    matches = []
+    knn_matcher = cv2.BFMatcher(cv2.NORM_L2)
+    try:
+        matches = knn_matcher.knnMatch(query_desc, refer_desc, k=2)
+        for m, n in matches:
+            if m.distance < knn_thresh * n.distance:
+                good_match.append(m)
+                status.append(True)
+            else:
+                status.append(False)
+    except Exception:
+        pass
+    return [good_match, cv_kpts_query, cv_kpts_refer, raw_query_image,
+    raw_refer_image, match_image_height, match_image_width]
+
+
+if __name__ == '__main__':
+    # init stream manager
+    FILEPATH = "./model/SuperRetina.om"       # om path
+    DEVICEID = 0                             # device id
+    model = sdk.model(FILEPATH, DEVICEID)
+
+    # set stream name and device
+    STREAM_NAME = b'superretina'
+    IN_PLUGIN_ID = 0
+    DATA_PATH = './data/'
+
+    TESTSET = 'FIRE'
+
+    if not os.path.isdir(DATA_PATH):
+        print("data path don't exit.")
+        exit()
+
+    ground_dir = os.path.join(DATA_PATH, TESTSET, 'Ground Truth/resized')
+    image_dir = os.path.join(DATA_PATH, TESTSET, 'Images/resized')
+    OUT_PATH = '../result'
+    matches_pair = [x for x in os.listdir(ground_dir) if x.endswith('.txt')
+                and not x.endswith('P37_1_2.txt')]
+
+    PAIRFAILED = 0
+    PAIRINACCURATE = 0
+    IMMAE = 0
+    IMMEE = 0
+
+    matches_pair.sort()
+    BIGNUMBER = 1e6
+    good_number = []
+    IMAGENUMBER = 0
+    # category: S, P, A, corresponding to Easy, Hard, Mod in paper
+    auc = dict([(category, []) for category in ['S', 'P', 'A']])
+
+    for read_file in tqdm(matches_pair):
+        ground_file = os.path.join(ground_dir, read_file)
+        name = read_file.replace('.txt', '')
+
+        category = name.split('_')[2][0]
+
+        name_rf = name.split('_')[2] + '_' + name.split('_')[3]
+        name_qr = name.split('_')[2] + '_' + name.split('_')[4]
+
+        query_im = os.path.join(image_dir, name_qr)
+        refer_im = os.path.join(image_dir, name_rf)
+        query_im = query_im + '.jpg'
+        refer_im = refer_im + '.jpg'
+        H_m1, inliers_number, query_image, _, image_height, image_width =\
+            cal_homography(query_im, refer_im, model)
+        HM2 = None
+        if use_matching_trick:
+            if H_m1 is not None:
+                h, w = image_height, image_width
+                query_align_one = cv2.warpPerspective(query_image, H_m1, (h, w), borderMode=cv2.BORDER_CONSTANT,
+                                                borderValue=(0))
+                query_align_one = query_align_one.astype(float)
+                query_align_one /= 255.
+                HM2, inliers_number, _, _, image_height, image_width =\
+                cal_homography(query_align_one, refer_im, model, query_is_image=True)
+
+        good_number.append(inliers_number)
+        IMAGENUMBER += 1
+
+        if inliers_number < 1e-6:
+            PAIRFAILED += 1
+            AVGDIST = BIGNUMBER
+        else:
+            ground_points = np.loadtxt(ground_file)
+            origin = np.zeros([len(ground_points), 2])
+            destination = np.zeros([len(ground_points), 2])
+            origin[:, 0] = ground_points[:, 2]
+            origin[:, 1] = ground_points[:, 3]
+            destination[:, 0] = ground_points[:, 0]
+            destination[:, 1] = ground_points[:, 1]
+            destination_pred = cv2.perspectiveTransform(origin.reshape(-1, 1, 2), H_m1)
+            if HM2 is not None:
+                destination_pred = cv2.perspectiveTransform(destination_pred.reshape(-1, 1, 2), HM2)
+
+            destination_pred = destination_pred.squeeze()
+
+            difference = (destination - destination_pred) ** 2
+            difference = np.sqrt(difference[:, 0] + difference[:, 1])
+            AVGDIST = difference.mean()
+            
+            IMMAE = difference.max()
+            IMMEE = np.median(difference)
+            if IMMAE > 50 or IMMEE > 20:
+                PAIRINACCURATE += 1
+        auc[category].append(AVGDIST)
+    
+    print('----------------------------------------------------------')
+    print(f"fail:{'%.2f' % (100*PAIRFAILED/IMAGENUMBER)}%, inaccurate:{'%.2f' % (100*PAIRINACCURATE/IMAGENUMBER)}%, "
+        f"acceptable:{'%.2f' % (100*(IMAGENUMBER-PAIRINACCURATE-PAIRFAILED)/IMAGENUMBER)}%")
+
+    print('----------------------------------------------------------')
+
+    auc = cal_auc(auc['S'], auc['P'], auc['A'])
+    print('S: %.3f, P: %.3f, A: %.3f, mAUC: %.3f' % (auc.get('s'), auc.get('p'), auc.get('a'), auc.get('mAUC')))
    
\ No newline at end of file
diff --git a/contrib/SuperRetina/python/predictor.py b/mxVision/mxVision-referenceapps/SuperRetina/python/predictor.py
similarity index 97%
rename from contrib/SuperRetina/python/predictor.py
rename to mxVision/mxVision-referenceapps/SuperRetina/python/predictor.py
index da72c114d65073740d06e5357c5dcd0b788406b7..76b0013b620abfff52580c19c060d3124aab3129 100644
--- a/contrib/SuperRetina/python/predictor.py
+++ b/mxVision/mxVision-referenceapps/SuperRetina/python/predictor.py
@@ -1,433 +1,433 @@
-#!/usr/bin/env python
-# coding=utf-8
-
-"""
-Copyright(C) Huawei Technologies Co.,Ltd. 2022 All rights reserved.
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
-    http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License.
-"""
-
-from ast import mod
-import os
-import time
-import numpy as np
-from tqdm import tqdm
-import matplotlib.pyplot as plt
-from numpy.lib.stride_tricks import as_strided
-import yaml
-from PIL import Image
-
-import cv2
-
-
-import mindx.sdk as sdk
-
-CONFIG_PATH = './config/test.yaml' # config path
-if os.path.exists(CONFIG_PATH):
-    with open(CONFIG_PATH) as f:
-        config = yaml.safe_load(f)
-else:
-    raise FileNotFoundError("Config File doesn't Exist")
-
-model_image_width = config['PREDICT']['model_image_width']
-model_image_height = config['PREDICT']['model_image_height']
-nms_thresh = config['PREDICT']['nms_thresh']
-nms_size = config['PREDICT']['nms_size']
-knn_thresh = config['PREDICT']['knn_thresh']
-use_matching_trick = config['PREDICT']['use_matching_trick']
-
-
-def pre_processing(data):
-    """ Enhance retinal images """
-    train_imgs = datasets_normalized(data)
-    train_imgs = clahe_equalized(train_imgs)
-    train_imgs = adjust_gamma(train_imgs, 1.2)
-
-    train_imgs = train_imgs / 255.
-
-    return train_imgs.astype(np.float32)
-
-
-def datasets_normalized(images):
-    images_std = np.std(images)
-    images_mean = np.mean(images)
-    images_normalized = (images - images_mean) / (images_std + 1e-6)
-    minv = np.min(images_normalized)
-    images_normalized = ((images_normalized - minv) /
-                         (np.max(images_normalized) - minv)) * 255
-
-    return images_normalized
-
-
-def clahe_equalized(images):
-    clahe = cv2.createCLAHE(clipLimit=2.0, tileGridSize=(8, 8))
-    images_equalized = np.empty(images.shape)
-    images_equalized[:, :] = clahe.apply(np.array(images[:, :],
-                                                  dtype=np.uint8))
-
-    return images_equalized
-
-
-def adjust_gamma(images, gamma=1.0):
-    inv_gamma = 1.0 / gamma
-    table = np.array([((i / 255.0) ** inv_gamma) * 255
-                      for i in np.arange(0, 256)]).astype("uint8") # Zoom pixels from 0-255 to 0-1
-    new_images = np.empty(images.shape)
-    new_images[:, :] = cv2.LUT(np.array(images[:, :],
-                                        dtype=np.uint8), table)
-
-    return new_images
-
-
-def transform(image_trans):
-    img = Image.fromarray(image_trans)
-    img = img.resize((768, 768), resample=Image.BILINEAR)
-    img = np.array(img)
-    img = np.expand_dims(img, axis=0)
-    img = img.astype(np.float64) / 255.0
-    return img
-
-
-def image_read(read_query_path, read_refer_path, query_is_image=False):
-    if query_is_image:
-        read_query_image = read_query_path
-    else:
-        read_query_image = cv2.imread(read_query_path, cv2.IMREAD_COLOR)
-        read_query_image = read_query_image[:, :, 1]
-        read_query_image = pre_processing(read_query_image)
-    read_refer_image = cv2.imread(read_refer_path, cv2.IMREAD_COLOR)
-
-    assert read_query_image.shape[:2] == read_refer_image.shape[:2]
-    read_image_height, read_image_width = read_query_image.shape[:2]
-
-    read_refer_image = read_refer_image[:, :, 1]
-    read_refer_image = pre_processing(read_refer_image)
-
-    read_query_image = (read_query_image * 255).astype(np.uint8)
-    read_refer_image = (read_refer_image * 255).astype(np.uint8)
-
-    return [read_query_image, read_refer_image, read_image_height, read_image_width]
-
-
-def pool2d(maxpool_input, kernel_size, stride, padding=0):
-    maxpool_input = np.pad(maxpool_input, padding, mode='constant')
-    # Window view of A
-    output_shape = ((maxpool_input.shape[0] - kernel_size) // stride + 1,
-                    (maxpool_input.shape[1] - kernel_size) // stride + 1)
-    
-    shape_w = (output_shape[0], output_shape[1], kernel_size, kernel_size)
-    strides_w = (stride*maxpool_input.strides[0], stride*maxpool_input.strides[1],
-    maxpool_input.strides[0], maxpool_input.strides[1])
-    
-    a_w = np.lib.stride_tricks.as_strided(maxpool_input, shape_w, strides_w)
-
-    return a_w.max(axis=(2, 3))
-
-
-def max_pooling(x, kernel_size, stride, padding):
-    x1 = x.copy()
-    a = x[0, 0, :, :]
-    b = x[1, 0, :, :]
-    x1[0, 0, :, :] = pool2d(a, kernel_size, stride, padding)
-    x1[1, 0, :, :] = pool2d(b, kernel_size, stride, padding)
-    
-    return x1
-
-
-def cal_homography(query_path, refer_path, comp_model, query_is_image=False, comp_show=False):
-    rightmatch, kpts_query, kpts_refer, raw_query_image, raw_refer_image, comp_image_height, comp_image_width = \
-    match(query_path, refer_path, comp_model, query_is_image=query_is_image, match_show=comp_show)
-    h_m = None
-    cal_inliers_number = 0
-
-    if len(rightmatch) >= 4:
-        src = [kpts_query[m.queryIdx].pt for m in rightmatch]
-        src = np.float32(src).reshape(-1, 1, 2)
-        dst = [kpts_refer[m.trainIdx].pt for m in rightmatch]
-        dst = np.float32(dst).reshape(-1, 1, 2)
-
-        h_m, mask = cv2.findHomography(src, dst, cv2.LMEDS)
-
-        rightmatch = np.array(rightmatch)[mask.ravel() == 1]
-        cal_inliers_number = mask.sum() / len(mask.ravel())
-    return [h_m, cal_inliers_number, raw_query_image, raw_refer_image, comp_image_height, comp_image_width]
-
-
-def plot_matches(image_alpha, image_beta, kpsa, kpsb, matches, status):
-    (alphah, alphaw) = image_alpha.shape[:2]
-    (betah, betaw) = image_beta.shape[:2]
-    plot_image = np.zeros((max(alphah, betah), alphaw + betaw, 3), dtype="uint8")
-    if len(image_alpha.shape) == 2:
-        image_alpha = cv2.cvtColor(image_alpha, cv2.COLOR_GRAY2RGB)
-        image_beta = cv2.cvtColor(image_beta, cv2.COLOR_GRAY2RGB)
-
-    plot_image[0:alphah, 0:alphaw] = image_alpha
-    plot_image[0:betah, alphaw:] = image_beta
-
-    for (matched, _), s in zip(matches, status):
-        trainidx, queryidx = matched.trainIdx, matched.queryIdx
-        if s == 1:
-
-            pt_alpha = (int(kpsa[queryidx].pt[0]), int(kpsa[queryidx].pt[1]))
-            pt_beta = (int(kpsb[trainidx].pt[0]) + alphaw, int(kpsb[trainidx].pt[1]))
-            cv2.line(plot_image, pt_alpha, pt_beta, (0, 255, 0), 2)
-
-    return plot_image
-
-
-def simple_nms(scores, nms_radius: int):
-    """ Fast Non-maximum suppression to remove nearby geo_points """
-    assert (nms_radius >= 0)
-
-    def max_pool(x):
-        return max_pooling(
-            x, kernel_size=nms_radius * 2 + 1, stride=1,
-            padding=nms_radius)
-
-    zeros = np.zeros_like(scores)
-    max_mask = scores == max_pool(scores)
-    for _ in range(2):
-        supp_mask = max_pool(max_mask.astype(np.float32)) > 0
-        supp_scores = np.where(supp_mask, zeros, scores)
-        new_max_mask = supp_scores == max_pool(supp_scores)
-        max_mask = max_mask | (new_max_mask & (~supp_mask))
-    return np.where(max_mask, scores, zeros)
-
-
-def plot_result(query_image, refer_image, cv_kpts_query, cv_kpts_refer, matches, status):
-    query_np = np.array([kp.pt for kp in cv_kpts_query])
-    refer_np = np.array([kp.pt for kp in cv_kpts_refer])
-    refer_np[:, 0] += query_image.shape[1]
-    matched_image = plot_matches(query_image, refer_image, cv_kpts_query, cv_kpts_refer, matches, status)
-    plt.figure(dpi=300)
-    plt.scatter(query_np[:, 0], query_np[:, 1], s=1, c='r')
-    plt.scatter(refer_np[:, 0], refer_np[:, 1], s=1, c='r')
-    plt.axis('off')
-    plt.title('match results, #right match: {}'.format(status.sum()))
-    plt.imshow(cv2.cvtColor(matched_image, cv2.COLOR_BGR2RGB))
-    plt.savefig("./match_result.jpg")
-    plt.close()
-    return 0
-
-
-def grid_sample(sample_input, grid):
-    n_grid, c_grid, h_in, w_in = sample_input.shape
-    n_grid, h_out, w_out, _ = grid.shape
-    output = np.random.random((n_grid, c_grid, h_out, w_out))
-    for i in range(n_grid):
-        for j in range(c_grid):
-            for k in range(h_out):
-                for l in range(w_out):
-                    x, y = grid[i][k][l][0], grid[i][k][l][1]
-                    param = [0.0, 0.0]
-                    param[0] = (w_in - 1) * (x + 1) / 2
-                    param[1] = (h_in - 1) * (y + 1) / 2
-                    x1 = int(param[0] + 1)
-                    x0 = x1 - 1
-                    y1 = int(param[1] + 1)
-                    y0 = y1 - 1
-                    param[0] = abs(param[0] - x0)
-                    param[1] = abs(param[1] - y0)
-                    left_top_value, left_bottom_value, right_top_value, right_bottom_value = 0, 0, 0, 0
-                    if 0 <= x0 < w_in and 0 <= y0 < h_in:
-                        left_top_value = sample_input[i][j][y0][x0]
-                    if 0 <= x1 < w_in and 0 <= y0 < h_in:
-                        right_top_value = sample_input[i][j][y0][x1]
-                    if 0 <= x0 < w_in and 0 <= y1 < h_in:
-                        left_bottom_value = sample_input[i][j][y1][x0]
-                    if 0 <= x1 < w_in and 0 <= y1 < h_in:
-                        right_bottom_value = sample_input[i][j][y1][x1]
-                    left_top = left_top_value * (1 - param[0]) * (1 - param[1])
-                    left_bottom = left_bottom_value * (1 - param[0]) * param[1]
-                    right_top = right_top_value * param[0] * (1 - param[1])
-                    right_bottom = right_bottom_value * param[0] * param[1]
-                    result = left_bottom + left_top + right_bottom + right_top
-                    output[i][j][k][l] = result
-    return output
-
-
-def normalize(x, p, dim):
-    """
-    Implement a function that normalizes each row of the matrix x (to have unit length).
-    
-    Argument:
-    x -- A numpy matrix of shape (n, m)
-    
-    Returns:
-    x -- The normalized (by row) numpy matrix. You are allowed to modify x.
-    """
-    x_norm = np.linalg.norm(x, ord=p, axis = dim, keepdims = True)
-    x = np.divide(x, x_norm + 1e-6)
- 
-    return x
-
-
-def sample_keypoint_desc(keypoints, descriptors, s: int = 8):
-    """ Interpolate descriptors at keypoint locations """
-    b_s, c_s, h_s, w_s = descriptors.shape
-    keypoints = keypoints.copy().astype(np.float32)
-
-    keypoints /= np.array([w_s * s - 1, h_s * s - 1]).astype(np.float32)[None]
-    keypoints = keypoints * 2 - 1  # normalize to (-1, 1)
-
-    descriptors = grid_sample(
-        descriptors, keypoints.reshape(b_s, 1, -1, 2))
-
-    descriptors = normalize(
-        descriptors.reshape(b_s, c_s, -1), p=2, dim=1)
-    return descriptors
-
-
-def align_pair(query_path, refer_path, align_model, show=False):
-    h_m, _, raw_query_image, raw_refer_image, align_image_height, align_image_width =\
-        cal_homography(query_path, refer_path, align_model, comp_show=show)
-
-    if h_m is not None:
-        height, width = align_image_height, align_image_width
-        align_query = cv2.warpPerspective(raw_query_image, h_m, (height, width), borderMode=cv2.BORDER_CONSTANT,
-                                            borderValue=(0))
-
-        point_merged = np.zeros((height, width, 3), dtype=np.uint8)
-
-        if len(align_query.shape) == 3:
-            align_query = cv2.cvtColor(align_query, cv2.COLOR_BGR2GRAY)
-        if len(raw_refer_image.shape) == 3:
-            gray_refer = cv2.cvtColor(raw_refer_image, cv2.COLOR_BGR2GRAY)
-        else:
-            gray_refer = raw_refer_image
-        point_merged[:, :, 0] = align_query
-        point_merged[:, :, 1] = gray_refer
-
-        if show:
-            plt.figure(dpi=200)
-            plt.imshow(point_merged)
-            plt.axis('off')
-            plt.savefig("./result.jpg")
-            plt.close()
-        return point_merged
-
-    print("Matched Failed!")
-    return 0
-
-
-def remove_borders(keypoints, scores, border: int, height: int, width: int):
-    """ Removes keypoints too close to the border """
-    mask_h = (keypoints[:, 0] >= border) & (keypoints[:, 0] < (height - border))
-    mask_w = (keypoints[:, 1] >= border) & (keypoints[:, 1] < (width - border))
-    mask = mask_h & mask_w
-    return keypoints[mask], scores[mask]
-
-
-def evaluate(query_path, refer_path, infer_model, query_is_image=False):
-    raw_tensor_query , raw_tensor_refer, eval_image_height, eval_image_width =\
-    image_read(query_path, refer_path, query_is_image=query_is_image)
-    tensor_query = transform(raw_tensor_query)
-    tensor_refer = transform(raw_tensor_refer)
-    inputs  = np.concatenate((np.expand_dims(tensor_query, axis=0), np.expand_dims(tensor_refer, axis=0)), axis=0)
-    inputs = inputs.astype(np.float32)
-    inputs_tensor = sdk.Tensor(inputs)
-    inputs_tensor.to_device(0)
-    inputs_tensor_list = [inputs_tensor]
-    outputs = infer_model.infer(inputs_tensor_list)
-    outputs[0].to_host()
-    outputs[1].to_host()
-    infer_data_detector = outputs[0]
-    infer_data_descriptor = outputs[1]
-    infer_data_detector = np.array(infer_data_detector)
-    infer_data_descriptor = np.array(infer_data_descriptor)
-
-    # get the infer result
-    detector_pred = np.reshape(infer_data_detector, (2, 1, 768, 768)) # Size of model input is 2x1x768x768
-    descriptor_pred = np.reshape(infer_data_descriptor,
-    (2, 256, 94, 94)) # Size of another input to the model is 2x256x94x94
-
-    scores = simple_nms(detector_pred, nms_radius=nms_size)
-    _, _, h_detector, w_detector = detector_pred.shape
-    scores = scores.reshape(-1, h_detector, w_detector)
-
-    keypoints = [np.transpose(np.nonzero(s > nms_thresh)) for s in scores]
-
-    scores = [s[tuple(np.array(k).T.tolist())] for s, k in zip(scores, keypoints)]
-
-    # Discard keypoints near the image borders
-    keypoints, scores = list(zip(*[
-        remove_borders(np.array(k), np.array(s), 4, h_detector, w_detector)
-        for k, s in zip(keypoints, scores)]))
-
-    keypoints = [np.flip(k, [1]).astype(np.float32) for k in keypoints]
-
-    descriptors = [sample_keypoint_desc(k[None], d[None], 8)[0]
-                    for k, d in zip(keypoints, descriptor_pred)]
-    keypoints = [k for k in keypoints]
-    return [keypoints, descriptors, raw_tensor_query, raw_tensor_refer, eval_image_height, eval_image_width]
-
-
-def match(query_path, refer_path, match_model, query_is_image=False, match_show=False):
-    keypoints, descriptors, raw_query_image, raw_refer_image, match_image_height, match_image_width =\
-    evaluate(query_path, refer_path, match_model, query_is_image=query_is_image)
-    query_keypoints, refer_keypoints = keypoints[0], keypoints[1]
-    query_desc, refer_desc = descriptors[0].T.astype(np.float32), descriptors[1].T.astype(np.float32)
-
-    # mapping keypoints to scaled keypoints
-    cv_kpts_query = [cv2.KeyPoint(int(i[0] / model_image_width * match_image_width),
-                                    int(i[1] / model_image_height * match_image_height), 30)
-                        for i in query_keypoints]
-    cv_kpts_refer = [cv2.KeyPoint(int(i[0] / model_image_width * match_image_width),
-                                    int(i[1] / model_image_height * match_image_height), 30)
-                        for i in refer_keypoints]
-
-    right_match = []
-    condition = []
-    matching = []
-    knn_matcher = cv2.BFMatcher(cv2.NORM_L2)
-    try:
-        matching = knn_matcher.knnMatch(query_desc, refer_desc, k=2)
-        for m, n in matching:
-            if m.distance < knn_thresh * n.distance:
-                right_match.append(m)
-                condition.append(True)
-            else:
-                condition.append(False)
-    except Exception:
-        pass
-    if match_show:
-        plot_result(raw_query_image, raw_refer_image, cv_kpts_query,
-        cv_kpts_refer, matching, np.array(condition))
-    return [right_match, cv_kpts_query, cv_kpts_refer, raw_query_image,
-    raw_refer_image, match_image_height, match_image_width]
-
-
-if __name__ == '__main__':
-    # init stream manager
-    FILEPATH = "./model/SuperRetina.om"       # om path
-    DEVICEID = 0                             # device id
-    model = sdk.model(FILEPATH, DEVICEID)
-
-    F1 = './data/samples/query.jpg'
-    F2 = './data/samples/refer.jpg'
-
-    if not os.path.exists(F1) and os.path.exists(F2):
-        print("F1 or F2 File doesn't Exist")
-        exit()
-
-    try:
-        image = Image.open(F1)
-        image = Image.open(F2)
-        image.verify()
-        image.close()
-    except Exception as exc:
-        print(exc)
-        print("F1 or F2 incorrect format")
-        exit()
-    
-    align_merged = align_pair(F1, F2, model, show=True)
+#!/usr/bin/env python
+# coding=utf-8
+
+"""
+Copyright(C) Huawei Technologies Co.,Ltd. 2022 All rights reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+"""
+
+from ast import mod
+import os
+import time
+import numpy as np
+from tqdm import tqdm
+import matplotlib.pyplot as plt
+from numpy.lib.stride_tricks import as_strided
+import yaml
+from PIL import Image
+
+import cv2
+
+
+import mindx.sdk as sdk
+
+CONFIG_PATH = './config/test.yaml' # config path
+if os.path.exists(CONFIG_PATH):
+    with open(CONFIG_PATH) as f:
+        config = yaml.safe_load(f)
+else:
+    raise FileNotFoundError("Config File doesn't Exist")
+
+model_image_width = config['PREDICT']['model_image_width']
+model_image_height = config['PREDICT']['model_image_height']
+nms_thresh = config['PREDICT']['nms_thresh']
+nms_size = config['PREDICT']['nms_size']
+knn_thresh = config['PREDICT']['knn_thresh']
+use_matching_trick = config['PREDICT']['use_matching_trick']
+
+
+def pre_processing(data):
+    """ Enhance retinal images """
+    train_imgs = datasets_normalized(data)
+    train_imgs = clahe_equalized(train_imgs)
+    train_imgs = adjust_gamma(train_imgs, 1.2)
+
+    train_imgs = train_imgs / 255.
+
+    return train_imgs.astype(np.float32)
+
+
+def datasets_normalized(images):
+    images_std = np.std(images)
+    images_mean = np.mean(images)
+    images_normalized = (images - images_mean) / (images_std + 1e-6)
+    minv = np.min(images_normalized)
+    images_normalized = ((images_normalized - minv) /
+                         (np.max(images_normalized) - minv)) * 255
+
+    return images_normalized
+
+
+def clahe_equalized(images):
+    clahe = cv2.createCLAHE(clipLimit=2.0, tileGridSize=(8, 8))
+    images_equalized = np.empty(images.shape)
+    images_equalized[:, :] = clahe.apply(np.array(images[:, :],
+                                                  dtype=np.uint8))
+
+    return images_equalized
+
+
+def adjust_gamma(images, gamma=1.0):
+    inv_gamma = 1.0 / gamma
+    table = np.array([((i / 255.0) ** inv_gamma) * 255
+                      for i in np.arange(0, 256)]).astype("uint8") # Zoom pixels from 0-255 to 0-1
+    new_images = np.empty(images.shape)
+    new_images[:, :] = cv2.LUT(np.array(images[:, :],
+                                        dtype=np.uint8), table)
+
+    return new_images
+
+
+def transform(image_trans):
+    img = Image.fromarray(image_trans)
+    img = img.resize((768, 768), resample=Image.BILINEAR)
+    img = np.array(img)
+    img = np.expand_dims(img, axis=0)
+    img = img.astype(np.float64) / 255.0
+    return img
+
+
+def image_read(read_query_path, read_refer_path, query_is_image=False):
+    if query_is_image:
+        read_query_image = read_query_path
+    else:
+        read_query_image = cv2.imread(read_query_path, cv2.IMREAD_COLOR)
+        read_query_image = read_query_image[:, :, 1]
+        read_query_image = pre_processing(read_query_image)
+    read_refer_image = cv2.imread(read_refer_path, cv2.IMREAD_COLOR)
+
+    assert read_query_image.shape[:2] == read_refer_image.shape[:2]
+    read_image_height, read_image_width = read_query_image.shape[:2]
+
+    read_refer_image = read_refer_image[:, :, 1]
+    read_refer_image = pre_processing(read_refer_image)
+
+    read_query_image = (read_query_image * 255).astype(np.uint8)
+    read_refer_image = (read_refer_image * 255).astype(np.uint8)
+
+    return [read_query_image, read_refer_image, read_image_height, read_image_width]
+
+
+def pool2d(maxpool_input, kernel_size, stride, padding=0):
+    maxpool_input = np.pad(maxpool_input, padding, mode='constant')
+    # Window view of A
+    output_shape = ((maxpool_input.shape[0] - kernel_size) // stride + 1,
+                    (maxpool_input.shape[1] - kernel_size) // stride + 1)
+    
+    shape_w = (output_shape[0], output_shape[1], kernel_size, kernel_size)
+    strides_w = (stride*maxpool_input.strides[0], stride*maxpool_input.strides[1],
+    maxpool_input.strides[0], maxpool_input.strides[1])
+    
+    a_w = np.lib.stride_tricks.as_strided(maxpool_input, shape_w, strides_w)
+
+    return a_w.max(axis=(2, 3))
+
+
+def max_pooling(x, kernel_size, stride, padding):
+    x1 = x.copy()
+    a = x[0, 0, :, :]
+    b = x[1, 0, :, :]
+    x1[0, 0, :, :] = pool2d(a, kernel_size, stride, padding)
+    x1[1, 0, :, :] = pool2d(b, kernel_size, stride, padding)
+    
+    return x1
+
+
+def cal_homography(query_path, refer_path, comp_model, query_is_image=False, comp_show=False):
+    rightmatch, kpts_query, kpts_refer, raw_query_image, raw_refer_image, comp_image_height, comp_image_width = \
+    match(query_path, refer_path, comp_model, query_is_image=query_is_image, match_show=comp_show)
+    h_m = None
+    cal_inliers_number = 0
+
+    if len(rightmatch) >= 4:
+        src = [kpts_query[m.queryIdx].pt for m in rightmatch]
+        src = np.float32(src).reshape(-1, 1, 2)
+        dst = [kpts_refer[m.trainIdx].pt for m in rightmatch]
+        dst = np.float32(dst).reshape(-1, 1, 2)
+
+        h_m, mask = cv2.findHomography(src, dst, cv2.LMEDS)
+
+        rightmatch = np.array(rightmatch)[mask.ravel() == 1]
+        cal_inliers_number = mask.sum() / len(mask.ravel())
+    return [h_m, cal_inliers_number, raw_query_image, raw_refer_image, comp_image_height, comp_image_width]
+
+
+def plot_matches(image_alpha, image_beta, kpsa, kpsb, matches, status):
+    (alphah, alphaw) = image_alpha.shape[:2]
+    (betah, betaw) = image_beta.shape[:2]
+    plot_image = np.zeros((max(alphah, betah), alphaw + betaw, 3), dtype="uint8")
+    if len(image_alpha.shape) == 2:
+        image_alpha = cv2.cvtColor(image_alpha, cv2.COLOR_GRAY2RGB)
+        image_beta = cv2.cvtColor(image_beta, cv2.COLOR_GRAY2RGB)
+
+    plot_image[0:alphah, 0:alphaw] = image_alpha
+    plot_image[0:betah, alphaw:] = image_beta
+
+    for (matched, _), s in zip(matches, status):
+        trainidx, queryidx = matched.trainIdx, matched.queryIdx
+        if s == 1:
+
+            pt_alpha = (int(kpsa[queryidx].pt[0]), int(kpsa[queryidx].pt[1]))
+            pt_beta = (int(kpsb[trainidx].pt[0]) + alphaw, int(kpsb[trainidx].pt[1]))
+            cv2.line(plot_image, pt_alpha, pt_beta, (0, 255, 0), 2)
+
+    return plot_image
+
+
+def simple_nms(scores, nms_radius: int):
+    """ Fast Non-maximum suppression to remove nearby geo_points """
+    assert (nms_radius >= 0)
+
+    def max_pool(x):
+        return max_pooling(
+            x, kernel_size=nms_radius * 2 + 1, stride=1,
+            padding=nms_radius)
+
+    zeros = np.zeros_like(scores)
+    max_mask = scores == max_pool(scores)
+    for _ in range(2):
+        supp_mask = max_pool(max_mask.astype(np.float32)) > 0
+        supp_scores = np.where(supp_mask, zeros, scores)
+        new_max_mask = supp_scores == max_pool(supp_scores)
+        max_mask = max_mask | (new_max_mask & (~supp_mask))
+    return np.where(max_mask, scores, zeros)
+
+
+def plot_result(query_image, refer_image, cv_kpts_query, cv_kpts_refer, matches, status):
+    query_np = np.array([kp.pt for kp in cv_kpts_query])
+    refer_np = np.array([kp.pt for kp in cv_kpts_refer])
+    refer_np[:, 0] += query_image.shape[1]
+    matched_image = plot_matches(query_image, refer_image, cv_kpts_query, cv_kpts_refer, matches, status)
+    plt.figure(dpi=300)
+    plt.scatter(query_np[:, 0], query_np[:, 1], s=1, c='r')
+    plt.scatter(refer_np[:, 0], refer_np[:, 1], s=1, c='r')
+    plt.axis('off')
+    plt.title('match results, #right match: {}'.format(status.sum()))
+    plt.imshow(cv2.cvtColor(matched_image, cv2.COLOR_BGR2RGB))
+    plt.savefig("./match_result.jpg")
+    plt.close()
+    return 0
+
+
+def grid_sample(sample_input, grid):
+    n_grid, c_grid, h_in, w_in = sample_input.shape
+    n_grid, h_out, w_out, _ = grid.shape
+    output = np.random.random((n_grid, c_grid, h_out, w_out))
+    for i in range(n_grid):
+        for j in range(c_grid):
+            for k in range(h_out):
+                for l in range(w_out):
+                    x, y = grid[i][k][l][0], grid[i][k][l][1]
+                    param = [0.0, 0.0]
+                    param[0] = (w_in - 1) * (x + 1) / 2
+                    param[1] = (h_in - 1) * (y + 1) / 2
+                    x1 = int(param[0] + 1)
+                    x0 = x1 - 1
+                    y1 = int(param[1] + 1)
+                    y0 = y1 - 1
+                    param[0] = abs(param[0] - x0)
+                    param[1] = abs(param[1] - y0)
+                    left_top_value, left_bottom_value, right_top_value, right_bottom_value = 0, 0, 0, 0
+                    if 0 <= x0 < w_in and 0 <= y0 < h_in:
+                        left_top_value = sample_input[i][j][y0][x0]
+                    if 0 <= x1 < w_in and 0 <= y0 < h_in:
+                        right_top_value = sample_input[i][j][y0][x1]
+                    if 0 <= x0 < w_in and 0 <= y1 < h_in:
+                        left_bottom_value = sample_input[i][j][y1][x0]
+                    if 0 <= x1 < w_in and 0 <= y1 < h_in:
+                        right_bottom_value = sample_input[i][j][y1][x1]
+                    left_top = left_top_value * (1 - param[0]) * (1 - param[1])
+                    left_bottom = left_bottom_value * (1 - param[0]) * param[1]
+                    right_top = right_top_value * param[0] * (1 - param[1])
+                    right_bottom = right_bottom_value * param[0] * param[1]
+                    result = left_bottom + left_top + right_bottom + right_top
+                    output[i][j][k][l] = result
+    return output
+
+
+def normalize(x, p, dim):
+    """
+    Implement a function that normalizes each row of the matrix x (to have unit length).
+    
+    Argument:
+    x -- A numpy matrix of shape (n, m)
+    
+    Returns:
+    x -- The normalized (by row) numpy matrix. You are allowed to modify x.
+    """
+    x_norm = np.linalg.norm(x, ord=p, axis = dim, keepdims = True)
+    x = np.divide(x, x_norm + 1e-6)
+ 
+    return x
+
+
+def sample_keypoint_desc(keypoints, descriptors, s: int = 8):
+    """ Interpolate descriptors at keypoint locations """
+    b_s, c_s, h_s, w_s = descriptors.shape
+    keypoints = keypoints.copy().astype(np.float32)
+
+    keypoints /= np.array([w_s * s - 1, h_s * s - 1]).astype(np.float32)[None]
+    keypoints = keypoints * 2 - 1  # normalize to (-1, 1)
+
+    descriptors = grid_sample(
+        descriptors, keypoints.reshape(b_s, 1, -1, 2))
+
+    descriptors = normalize(
+        descriptors.reshape(b_s, c_s, -1), p=2, dim=1)
+    return descriptors
+
+
+def align_pair(query_path, refer_path, align_model, show=False):
+    h_m, _, raw_query_image, raw_refer_image, align_image_height, align_image_width =\
+        cal_homography(query_path, refer_path, align_model, comp_show=show)
+
+    if h_m is not None:
+        height, width = align_image_height, align_image_width
+        align_query = cv2.warpPerspective(raw_query_image, h_m, (height, width), borderMode=cv2.BORDER_CONSTANT,
+                                            borderValue=(0))
+
+        point_merged = np.zeros((height, width, 3), dtype=np.uint8)
+
+        if len(align_query.shape) == 3:
+            align_query = cv2.cvtColor(align_query, cv2.COLOR_BGR2GRAY)
+        if len(raw_refer_image.shape) == 3:
+            gray_refer = cv2.cvtColor(raw_refer_image, cv2.COLOR_BGR2GRAY)
+        else:
+            gray_refer = raw_refer_image
+        point_merged[:, :, 0] = align_query
+        point_merged[:, :, 1] = gray_refer
+
+        if show:
+            plt.figure(dpi=200)
+            plt.imshow(point_merged)
+            plt.axis('off')
+            plt.savefig("./result.jpg")
+            plt.close()
+        return point_merged
+
+    print("Matched Failed!")
+    return 0
+
+
+def remove_borders(keypoints, scores, border: int, height: int, width: int):
+    """ Removes keypoints too close to the border """
+    mask_h = (keypoints[:, 0] >= border) & (keypoints[:, 0] < (height - border))
+    mask_w = (keypoints[:, 1] >= border) & (keypoints[:, 1] < (width - border))
+    mask = mask_h & mask_w
+    return keypoints[mask], scores[mask]
+
+
+def evaluate(query_path, refer_path, infer_model, query_is_image=False):
+    raw_tensor_query , raw_tensor_refer, eval_image_height, eval_image_width =\
+    image_read(query_path, refer_path, query_is_image=query_is_image)
+    tensor_query = transform(raw_tensor_query)
+    tensor_refer = transform(raw_tensor_refer)
+    inputs  = np.concatenate((np.expand_dims(tensor_query, axis=0), np.expand_dims(tensor_refer, axis=0)), axis=0)
+    inputs = inputs.astype(np.float32)
+    inputs_tensor = sdk.Tensor(inputs)
+    inputs_tensor.to_device(0)
+    inputs_tensor_list = [inputs_tensor]
+    outputs = infer_model.infer(inputs_tensor_list)
+    outputs[0].to_host()
+    outputs[1].to_host()
+    infer_data_detector = outputs[0]
+    infer_data_descriptor = outputs[1]
+    infer_data_detector = np.array(infer_data_detector)
+    infer_data_descriptor = np.array(infer_data_descriptor)
+
+    # get the infer result
+    detector_pred = np.reshape(infer_data_detector, (2, 1, 768, 768)) # Size of model input is 2x1x768x768
+    descriptor_pred = np.reshape(infer_data_descriptor,
+    (2, 256, 94, 94)) # Size of another input to the model is 2x256x94x94
+
+    scores = simple_nms(detector_pred, nms_radius=nms_size)
+    _, _, h_detector, w_detector = detector_pred.shape
+    scores = scores.reshape(-1, h_detector, w_detector)
+
+    keypoints = [np.transpose(np.nonzero(s > nms_thresh)) for s in scores]
+
+    scores = [s[tuple(np.array(k).T.tolist())] for s, k in zip(scores, keypoints)]
+
+    # Discard keypoints near the image borders
+    keypoints, scores = list(zip(*[
+        remove_borders(np.array(k), np.array(s), 4, h_detector, w_detector)
+        for k, s in zip(keypoints, scores)]))
+
+    keypoints = [np.flip(k, [1]).astype(np.float32) for k in keypoints]
+
+    descriptors = [sample_keypoint_desc(k[None], d[None], 8)[0]
+                    for k, d in zip(keypoints, descriptor_pred)]
+    keypoints = [k for k in keypoints]
+    return [keypoints, descriptors, raw_tensor_query, raw_tensor_refer, eval_image_height, eval_image_width]
+
+
+def match(query_path, refer_path, match_model, query_is_image=False, match_show=False):
+    keypoints, descriptors, raw_query_image, raw_refer_image, match_image_height, match_image_width =\
+    evaluate(query_path, refer_path, match_model, query_is_image=query_is_image)
+    query_keypoints, refer_keypoints = keypoints[0], keypoints[1]
+    query_desc, refer_desc = descriptors[0].T.astype(np.float32), descriptors[1].T.astype(np.float32)
+
+    # mapping keypoints to scaled keypoints
+    cv_kpts_query = [cv2.KeyPoint(int(i[0] / model_image_width * match_image_width),
+                                    int(i[1] / model_image_height * match_image_height), 30)
+                        for i in query_keypoints]
+    cv_kpts_refer = [cv2.KeyPoint(int(i[0] / model_image_width * match_image_width),
+                                    int(i[1] / model_image_height * match_image_height), 30)
+                        for i in refer_keypoints]
+
+    right_match = []
+    condition = []
+    matching = []
+    knn_matcher = cv2.BFMatcher(cv2.NORM_L2)
+    try:
+        matching = knn_matcher.knnMatch(query_desc, refer_desc, k=2)
+        for m, n in matching:
+            if m.distance < knn_thresh * n.distance:
+                right_match.append(m)
+                condition.append(True)
+            else:
+                condition.append(False)
+    except Exception:
+        pass
+    if match_show:
+        plot_result(raw_query_image, raw_refer_image, cv_kpts_query,
+        cv_kpts_refer, matching, np.array(condition))
+    return [right_match, cv_kpts_query, cv_kpts_refer, raw_query_image,
+    raw_refer_image, match_image_height, match_image_width]
+
+
+if __name__ == '__main__':
+    # init stream manager
+    FILEPATH = "./model/SuperRetina.om"       # om path
+    DEVICEID = 0                             # device id
+    model = sdk.model(FILEPATH, DEVICEID)
+
+    F1 = './data/samples/query.jpg'
+    F2 = './data/samples/refer.jpg'
+
+    if not os.path.exists(F1) and os.path.exists(F2):
+        print("F1 or F2 File doesn't Exist")
+        exit()
+
+    try:
+        image = Image.open(F1)
+        image = Image.open(F2)
+        image.verify()
+        image.close()
+    except Exception as exc:
+        print(exc)
+        print("F1 or F2 incorrect format")
+        exit()
+    
+    align_merged = align_pair(F1, F2, model, show=True)
diff --git a/contrib/SuperRetina/python/requirements.txt b/mxVision/mxVision-referenceapps/SuperRetina/python/requirements.txt
similarity index 100%
rename from contrib/SuperRetina/python/requirements.txt
rename to mxVision/mxVision-referenceapps/SuperRetina/python/requirements.txt
diff --git a/contrib/SuperRetina/python/resize.py b/mxVision/mxVision-referenceapps/SuperRetina/python/resize.py
similarity index 100%
rename from contrib/SuperRetina/python/resize.py
rename to mxVision/mxVision-referenceapps/SuperRetina/python/resize.py
diff --git a/contrib/TSM/README.md b/mxVision/mxVision-referenceapps/TSM/README.md
similarity index 96%
rename from contrib/TSM/README.md
rename to mxVision/mxVision-referenceapps/TSM/README.md
index 7356a5817e95e3b71e646b78bad726b9b8c5f77f..7917b3b2737879b8906315fdb67ca741a23a2c85 100644
--- a/contrib/TSM/README.md
+++ b/mxVision/mxVision-referenceapps/TSM/README.md
@@ -1,341 +1,341 @@
-# TSM视频分类参考设计
-
-## 1 介绍
-使用TSM模型，基于Kinetics-400数据集，在MindX SDK环境下实现视频分类功能。将测试视频传入脚本进行前处理，模型推理，后处理等功能，最终得到模型推理的精度和性能。
-
-### 1.1 支持的产品
-
-以昇腾Atlas310卡为主要的硬件平台
-
-### 1.2 支持的版本
-
-CANN：7.0.RC1
-
-SDK：mxVision 5.0.RC3（可通过cat SDK目录下的 version.info 查看）
-
-### 1.3 软件方案介绍
-
-项目主要由离线精度测试文件，在线功能测试文件，离线单视频推理性能测试文件，模型文件，测试数据集预处理文件组成。
-
-### 1.4 代码目录结构与说明
-
-```text
-├── TSM
-    ├── README.md                        // 所有模型相关说明
-    ├── model
-        ├── onnx2om.sh                   // 转om模型脚本
-        ├── onnx2om1.sh                  // 在线模型转om模型脚本
-    ├── label
-        ├── kinetics_val.csv             // label文件
-    ├── download_data
-        ├── k400_extractor.sh            // 解压数据集脚本
-    ├── offline.png                      // 离线推理技术实现流程
-    ├── online.png                       // 在线推理技术实现流程
-    ├── online_infer.py                  // 在线推理精度脚本
-    ├── offline_infer.py                 // 离线推理精度脚本
-    ├── speed.py                         // 离线单视频推理NPU性能脚本
-    ├── speed_gpu.py                     // 离线单视频推理GPU性能脚本
-```
-
-### 1.5技术实现流程
-
-离线推理流程：
-
-![离线推理流程](./offline.png)
-
-在线推理流程：
-
-![离线推理流程](./online.png)
-
-### 1.6特性及适用场景
-
-离线模型：
-
-本案例中的 TSM 模型适用于Kinetics数据集中的400类视频分类，并可以返回测试集视频的精度值及单视频识别的种类、性能。
-
-在以下两种情况视频分类情况不太好：1. 视频长度过短（小于3s）。 2. 视频帧率过低。
-
-在线模型：
-
-本案例中的在线模型适用于26中手势识别，并可以返回识别手势的名称。
-
-## 2 环境依赖
-
-推荐系统为ubuntu 18.04，环境依赖软件和版本如下表
-
-| 软件名称     | 版本     |
-|----------|--------|
-| cmake    | 3.5+   |
-| mxVision | 5.0.RC3 |
-| Python   | 3.9    |
-| torch    | 1.10.0 |
-| ffmpeg   | 4.2.1  |
-
-- 环境变量搭建
-
-在运行项目前，需要设置环境变量：
-
-MindSDK 环境变量：
-
-```Shell
-. ${SDK-path}/set_env.sh
-```
-
-CANN 环境变量：
-
-```Shell
-. ${ascend-toolkit-path}/set_env.sh
-```
-
-环境变量介绍
-
-SDK-path: mxVision SDK 安装路径
-
-ascend-toolkit-path: CANN 安装路径。
-
-下载[ffmpeg](https://github.com/FFmpeg/FFmpeg/archive/n4.2.1.tar.gz)，解压进入并执行以下命令安装：
-
-```Shell
-./configure --prefix=/usr/local/ffmpeg --enable-shared
-make -j
-make install
-```
-
-安装完毕后导入环境变量
-
-```Shell
-export PATH=/usr/local/ffmpeg/bin:$PATH
-export LD_LIBRARY_PATH=/usr/local/ffmpeg/lib:$LD_LIBRARY_PATH
-```
-
-## 3  离线推理
-
-**步骤1** Kinetics-400数据集下载
-
-参考[Kinetics-400 数据准备](https://github.com/PaddlePaddle/PaddleVideo/blob/develop/docs/zh-CN/dataset/k400.md#%E4%B8%8B%E8%BD%BDvideo%E6%95%B0%E6%8D%AE)中的脚本下载操作，在代码根目录的"download_data"目录下准备"download.sh"数据集下载脚本和"val_link.list"验证集链接列表文件。
-
-```text
-├── TSM
-    ├── download_data
-        ├── download.sh                  // 下载数据集脚本
-        ├── k400_extractor.sh            // 解压数据集脚本
-        ├── val_link.list    
-```
-
-进入代码根目录的"download_data"目录下，执行以下命令下载数据集压缩包val_part1.tar、val_part2.tar、val_part3.tar：
-
-```Shell
-bash download.sh val_link.list
-```
-
-然后执行以下命令解压数据集到代码根目录下：
-
-```Shell
-bash k400_extractor.sh
-```
-
-数据集结构如下：
-
-```text
-├── TSM
-    ├── data
-        ├── abseiling
-        ├── air_drumming
-        ├── ...
-        ├── zumba
-```
-
-**步骤2** 数据集预处理
-
-1、视频抽帧
-
-在代码根目录执行以下命令创建所需目录：
-
-```Shell
-mkdir tools
-mkdir ops
-```
-
-下载[“temporal-shift-module-master.zip”](https://github.com/mit-han-lab/temporal-shift-module/tree/master)代码包并上传服务器解压，将代码包中"tools"目录下的"vid2img_kinetics.py"、"gen_label_kinetics.py"、"kinetics_label_map.txt"三个文件拷贝至参考设计代码根目录的“tools”目录下。
-
-```text
-├── TSM
-    ├── tools 
-        ├── gen_label_kinetics.py        // label生成脚本
-        ├── vid2img_kinetics.py          // 视频抽帧脚本
-        ├── kinetics_label_map.txt
-```
-
-将代码包中"ops"目录下的"basic_ops.py"、"dataset.py"、"dataset_config.py"、"models.py"、"temporal_shift.py"、"transforms.py"六个文件拷贝至参考设计代码根目录的“ops”目录下。
-
-```text
-    ├── ops
-        ├── basic_ops.py
-        ├── dataset.py                   // 数据集构建脚本
-        ├── dataset_config.py            // 数据集配置脚本
-        ├── models.py                    // 模型搭建脚本 
-        ├── temporal_shift.py
-        ├── transforms.py
-```
-
-修改“tools”目录下的 vid2img_kinetics.py 内容，将77、78行注释。
-
-```text
-
-77行 #class_name = 'test'
-78行 #class_process(dir_path, dst_dir_path, class_name)
-
-``` 
-
-在参考设计代码根目录下，执行以下命令对数据集视频进行抽帧并生成图片：
-
-```shell
-mkdir dataset
-cd ./tools
-python3 vid2img_kinetics.py [video_path] [image_path]
-e.g.
-python3 vid2img_kinetics.py ../data ../dataset/
-```
-
-修改“tools”目录下gen_label_kinetics.py 内容。
-
-```text
-
-# 11行 dataset_path = '../dataset'           # 放视频抽帧后的图片路径
-# 12行 label_path = '../label'               # 存放label路径
-# 25行 files_input = ['kinetics_val.csv']
-# 26行 files_output = ['val_videofolder.txt']
-# 37行 folders.append(items[1])
-# 57行 output.append('%s %d %d'%(os.path.join('../dataset/',os.path.join(categories_list[i], curFolder)), len(dir_files), curIDX))
-
-``` 
-
-在“tools”目录下，执行以下命令生成标签文件：
-
-```shell
-python3 gen_label_kinetics.py
-```
-
-**步骤3** 模型转换
-
-下载[离线模型](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/TSM/offline_models.zip) TSM.onnx, 将下载好的模型放在“${TSM代码根目录}/model”目录下。
-
-将模型转换为om模型，在“model”目录下，执行以下命令生成om模型
-
-```shell
-bash onnx2om.sh
-```
-
-**步骤4** 精度测试
-
-修改${TSM代码根目录}/ops/dataset_config.py 脚本中参数root_data、filename_imglist_train和filename_imglist_val，若仅进行离线精度测试则可忽略filename_imglist_train设置。
-
-```shell
-import os
-
-ROOT_DATASET = './labels/'    # 标签文件所在路径
-
-...
-
-def return_kinetics(modality):
-    filename_categories = 400
-    if modality == 'RGB':
-        root_data = ROOT_DATASET                                # 训练集根目录
-        filename_imglist_train = 'train_videofolder.txt'        # 训练数据集标签
-        filename_imglist_val = 'val_videofolder.txt'            # 测试数据集标签
-        prefix = 'img_{:05d}.jpg'
-    else:
-        raise NotImplementedError('no such modality:' + modality)
-    return filename_categories, filename_imglist_train, filename_imglist_val, root_data, prefix
-```
-
-在参考设计代码根目录下，运行精度测试脚本
-
-```shell
-python3 offline_infer.py kinetics
-```
-
-原模型精度值为71.1%，实测精度值为71.01%，符合精度偏差范围，精度达标。
-
-**步骤5** 性能测试
-
-将用来测试的单视频放在参考设计代码根目录下，如视频“test_speed.mp4”，运行性能测试脚本
-
-修改speed_gpu.py与speed.py参数，'./test_speed.mp4'为测试视频，测试视频类别需在Kinetics-400数据集的400个种类内且视频长度至少为3s。
-
-```python
-def main():
-    cmd = 'ffmpeg  -i \"{}\" -threads 1 -vf scale=-1:331 -q:v 0 \"{}/img_%05d.jpg\"'.format('./test_speed.mp4', './image')
-    subprocess.call(cmd, shell=True,
-                    stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
-    files = os.listdir(r"./image/")
-```
-
-GPU性能(Tesla_V100S_PCIE_32GB)
-
-在参考设计代码根目录下，运行GPU性能测试脚本
-
-```shell
-python3 speed_gpu.py kinetics --test_segments=8 --test_crops=1 --batch_size=1
-```
-
-注：speed_gpu.py脚本需在GPU环境上运行，NPU环境无法运行。
-
-得到单视频纯推理性能为0.08sec/video
-
-SDK性能
-
-在参考设计代码根目录下，运行SDK性能测试脚本
-
-```shell
-python3 speed.py
-```
-
-注：speed.py脚本需在NPU环境上运行。
-
-得到单视频纯推理性能为0.189sec/video
-
-## 4 在线推理
-
-**步骤1** 安装[视频流工具](https://gitee.com/ascend/docs-openmind/blob/master/guide/mindx/sdk/tutorials/reference_material/Live555%E7%A6%BB%E7%BA%BF%E8%A7%86%E9%A2%91%E8%BD%ACRTSP%E8%AF%B4%E6%98%8E%E6%96%87%E6%A1%A3.md)
-
-**步骤2** 生成视频流
-
-根据提示当前只支持部分视频格式，并不支持.mp4后缀的文件，但可以通过ffmpeg转换生成[ffmpeg安装教程](https://gitee.com/ascend/docs-openmind/blob/master/guide/mindx/sdk/tutorials/reference_material/pc%E7%AB%AFffmpeg%E5%AE%89%E8%A3%85%E6%95%99%E7%A8%8B.md)，如下所示为MP4转换为h.264命令：
-
-使用ffmpeg工具将带有手势的“jester.mp4”的mp4格式视频转换生成为“jester.264”的264格式视频：
-
-```shell
-ffmpeg -i jester.mp4 -vcodec h264 -bf 0 -g 25 -r 10 -s 1280*720 -an -f h264 jester.264
-
-//-bf B帧数目控制，-g 关键帧间隔控制，-s 分辨率控制 -an关闭音频， -r 指定帧率
-```
-
-使用live555生成视频流。
-
-**步骤3** 模型转换
-
-下载[在线模型](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/TSM/online_models.zip) jester.onnx
-
-将下载好的模型放在参考设计代码根目录的“model”目录下。
-
-将模型转换为om模型，在“model”目录下，运行脚本生成om模型
-
-```shell
-bash onnx2om1.sh
-```
-
-**步骤4** 程序测试
-
-```shell
-python3 online_infer.py
-```
-
-修改参数，'ip:port/jester.264'为测试视频流，其中ip为起流的机器ip地址，port为起流的机器端口地址，jester.264为测试视频jester.mp4通过ffmpeg转换后的视频。
-
-```python
-def video2img():
-    cmd = 'ffmpeg  -i \"{}\" -threads 1 -vf scale=-1:331 -q:v 0 \"{}/img_%05d.jpg\"'.format('rtsp://ip:port/jester.264', './image')
-    subprocess.call(cmd, shell=True,
-                    stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
-```
+# TSM视频分类参考设计
+
+## 1 介绍
+使用TSM模型，基于Kinetics-400数据集，在MindX SDK环境下实现视频分类功能。将测试视频传入脚本进行前处理，模型推理，后处理等功能，最终得到模型推理的精度和性能。
+
+### 1.1 支持的产品
+
+以昇腾Atlas310卡为主要的硬件平台
+
+### 1.2 支持的版本
+
+CANN：7.0.RC1
+
+SDK：mxVision 5.0.RC3（可通过cat SDK目录下的 version.info 查看）
+
+### 1.3 软件方案介绍
+
+项目主要由离线精度测试文件，在线功能测试文件，离线单视频推理性能测试文件，模型文件，测试数据集预处理文件组成。
+
+### 1.4 代码目录结构与说明
+
+```text
+├── TSM
+    ├── README.md                        // 所有模型相关说明
+    ├── model
+        ├── onnx2om.sh                   // 转om模型脚本
+        ├── onnx2om1.sh                  // 在线模型转om模型脚本
+    ├── label
+        ├── kinetics_val.csv             // label文件
+    ├── download_data
+        ├── k400_extractor.sh            // 解压数据集脚本
+    ├── offline.png                      // 离线推理技术实现流程
+    ├── online.png                       // 在线推理技术实现流程
+    ├── online_infer.py                  // 在线推理精度脚本
+    ├── offline_infer.py                 // 离线推理精度脚本
+    ├── speed.py                         // 离线单视频推理NPU性能脚本
+    ├── speed_gpu.py                     // 离线单视频推理GPU性能脚本
+```
+
+### 1.5技术实现流程
+
+离线推理流程：
+
+![离线推理流程](./offline.png)
+
+在线推理流程：
+
+![离线推理流程](./online.png)
+
+### 1.6特性及适用场景
+
+离线模型：
+
+本案例中的 TSM 模型适用于Kinetics数据集中的400类视频分类，并可以返回测试集视频的精度值及单视频识别的种类、性能。
+
+在以下两种情况视频分类情况不太好：1. 视频长度过短（小于3s）。 2. 视频帧率过低。
+
+在线模型：
+
+本案例中的在线模型适用于26中手势识别，并可以返回识别手势的名称。
+
+## 2 环境依赖
+
+推荐系统为ubuntu 18.04，环境依赖软件和版本如下表
+
+| 软件名称     | 版本     |
+|----------|--------|
+| cmake    | 3.5+   |
+| mxVision | 5.0.RC3 |
+| Python   | 3.9    |
+| torch    | 1.10.0 |
+| ffmpeg   | 4.2.1  |
+
+- 环境变量搭建
+
+在运行项目前，需要设置环境变量：
+
+MindSDK 环境变量：
+
+```Shell
+. ${SDK-path}/set_env.sh
+```
+
+CANN 环境变量：
+
+```Shell
+. ${ascend-toolkit-path}/set_env.sh
+```
+
+环境变量介绍
+
+SDK-path: mxVision SDK 安装路径
+
+ascend-toolkit-path: CANN 安装路径。
+
+下载[ffmpeg](https://github.com/FFmpeg/FFmpeg/archive/n4.2.1.tar.gz)，解压进入并执行以下命令安装：
+
+```Shell
+./configure --prefix=/usr/local/ffmpeg --enable-shared
+make -j
+make install
+```
+
+安装完毕后导入环境变量
+
+```Shell
+export PATH=/usr/local/ffmpeg/bin:$PATH
+export LD_LIBRARY_PATH=/usr/local/ffmpeg/lib:$LD_LIBRARY_PATH
+```
+
+## 3  离线推理
+
+**步骤1** Kinetics-400数据集下载
+
+参考[Kinetics-400 数据准备](https://github.com/PaddlePaddle/PaddleVideo/blob/develop/docs/zh-CN/dataset/k400.md#%E4%B8%8B%E8%BD%BDvideo%E6%95%B0%E6%8D%AE)中的脚本下载操作，在代码根目录的"download_data"目录下准备"download.sh"数据集下载脚本和"val_link.list"验证集链接列表文件。
+
+```text
+├── TSM
+    ├── download_data
+        ├── download.sh                  // 下载数据集脚本
+        ├── k400_extractor.sh            // 解压数据集脚本
+        ├── val_link.list    
+```
+
+进入代码根目录的"download_data"目录下，执行以下命令下载数据集压缩包val_part1.tar、val_part2.tar、val_part3.tar：
+
+```Shell
+bash download.sh val_link.list
+```
+
+然后执行以下命令解压数据集到代码根目录下：
+
+```Shell
+bash k400_extractor.sh
+```
+
+数据集结构如下：
+
+```text
+├── TSM
+    ├── data
+        ├── abseiling
+        ├── air_drumming
+        ├── ...
+        ├── zumba
+```
+
+**步骤2** 数据集预处理
+
+1、视频抽帧
+
+在代码根目录执行以下命令创建所需目录：
+
+```Shell
+mkdir tools
+mkdir ops
+```
+
+下载[“temporal-shift-module-master.zip”](https://github.com/mit-han-lab/temporal-shift-module/tree/master)代码包并上传服务器解压，将代码包中"tools"目录下的"vid2img_kinetics.py"、"gen_label_kinetics.py"、"kinetics_label_map.txt"三个文件拷贝至参考设计代码根目录的“tools”目录下。
+
+```text
+├── TSM
+    ├── tools 
+        ├── gen_label_kinetics.py        // label生成脚本
+        ├── vid2img_kinetics.py          // 视频抽帧脚本
+        ├── kinetics_label_map.txt
+```
+
+将代码包中"ops"目录下的"basic_ops.py"、"dataset.py"、"dataset_config.py"、"models.py"、"temporal_shift.py"、"transforms.py"六个文件拷贝至参考设计代码根目录的“ops”目录下。
+
+```text
+    ├── ops
+        ├── basic_ops.py
+        ├── dataset.py                   // 数据集构建脚本
+        ├── dataset_config.py            // 数据集配置脚本
+        ├── models.py                    // 模型搭建脚本 
+        ├── temporal_shift.py
+        ├── transforms.py
+```
+
+修改“tools”目录下的 vid2img_kinetics.py 内容，将77、78行注释。
+
+```text
+
+77行 #class_name = 'test'
+78行 #class_process(dir_path, dst_dir_path, class_name)
+
+``` 
+
+在参考设计代码根目录下，执行以下命令对数据集视频进行抽帧并生成图片：
+
+```shell
+mkdir dataset
+cd ./tools
+python3 vid2img_kinetics.py [video_path] [image_path]
+e.g.
+python3 vid2img_kinetics.py ../data ../dataset/
+```
+
+修改“tools”目录下gen_label_kinetics.py 内容。
+
+```text
+
+# 11行 dataset_path = '../dataset'           # 放视频抽帧后的图片路径
+# 12行 label_path = '../label'               # 存放label路径
+# 25行 files_input = ['kinetics_val.csv']
+# 26行 files_output = ['val_videofolder.txt']
+# 37行 folders.append(items[1])
+# 57行 output.append('%s %d %d'%(os.path.join('../dataset/',os.path.join(categories_list[i], curFolder)), len(dir_files), curIDX))
+
+``` 
+
+在“tools”目录下，执行以下命令生成标签文件：
+
+```shell
+python3 gen_label_kinetics.py
+```
+
+**步骤3** 模型转换
+
+下载[离线模型](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/TSM/offline_models.zip) TSM.onnx, 将下载好的模型放在“${TSM代码根目录}/model”目录下。
+
+将模型转换为om模型，在“model”目录下，执行以下命令生成om模型
+
+```shell
+bash onnx2om.sh
+```
+
+**步骤4** 精度测试
+
+修改${TSM代码根目录}/ops/dataset_config.py 脚本中参数root_data、filename_imglist_train和filename_imglist_val，若仅进行离线精度测试则可忽略filename_imglist_train设置。
+
+```shell
+import os
+
+ROOT_DATASET = './labels/'    # 标签文件所在路径
+
+...
+
+def return_kinetics(modality):
+    filename_categories = 400
+    if modality == 'RGB':
+        root_data = ROOT_DATASET                                # 训练集根目录
+        filename_imglist_train = 'train_videofolder.txt'        # 训练数据集标签
+        filename_imglist_val = 'val_videofolder.txt'            # 测试数据集标签
+        prefix = 'img_{:05d}.jpg'
+    else:
+        raise NotImplementedError('no such modality:' + modality)
+    return filename_categories, filename_imglist_train, filename_imglist_val, root_data, prefix
+```
+
+在参考设计代码根目录下，运行精度测试脚本
+
+```shell
+python3 offline_infer.py kinetics
+```
+
+原模型精度值为71.1%，实测精度值为71.01%，符合精度偏差范围，精度达标。
+
+**步骤5** 性能测试
+
+将用来测试的单视频放在参考设计代码根目录下，如视频“test_speed.mp4”，运行性能测试脚本
+
+修改speed_gpu.py与speed.py参数，'./test_speed.mp4'为测试视频，测试视频类别需在Kinetics-400数据集的400个种类内且视频长度至少为3s。
+
+```python
+def main():
+    cmd = 'ffmpeg  -i \"{}\" -threads 1 -vf scale=-1:331 -q:v 0 \"{}/img_%05d.jpg\"'.format('./test_speed.mp4', './image')
+    subprocess.call(cmd, shell=True,
+                    stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
+    files = os.listdir(r"./image/")
+```
+
+GPU性能(Tesla_V100S_PCIE_32GB)
+
+在参考设计代码根目录下，运行GPU性能测试脚本
+
+```shell
+python3 speed_gpu.py kinetics --test_segments=8 --test_crops=1 --batch_size=1
+```
+
+注：speed_gpu.py脚本需在GPU环境上运行，NPU环境无法运行。
+
+得到单视频纯推理性能为0.08sec/video
+
+SDK性能
+
+在参考设计代码根目录下，运行SDK性能测试脚本
+
+```shell
+python3 speed.py
+```
+
+注：speed.py脚本需在NPU环境上运行。
+
+得到单视频纯推理性能为0.189sec/video
+
+## 4 在线推理
+
+**步骤1** 安装[视频流工具](https://gitee.com/ascend/docs-openmind/blob/master/guide/mindx/sdk/tutorials/reference_material/Live555%E7%A6%BB%E7%BA%BF%E8%A7%86%E9%A2%91%E8%BD%ACRTSP%E8%AF%B4%E6%98%8E%E6%96%87%E6%A1%A3.md)
+
+**步骤2** 生成视频流
+
+根据提示当前只支持部分视频格式，并不支持.mp4后缀的文件，但可以通过ffmpeg转换生成[ffmpeg安装教程](https://gitee.com/ascend/docs-openmind/blob/master/guide/mindx/sdk/tutorials/reference_material/pc%E7%AB%AFffmpeg%E5%AE%89%E8%A3%85%E6%95%99%E7%A8%8B.md)，如下所示为MP4转换为h.264命令：
+
+使用ffmpeg工具将带有手势的“jester.mp4”的mp4格式视频转换生成为“jester.264”的264格式视频：
+
+```shell
+ffmpeg -i jester.mp4 -vcodec h264 -bf 0 -g 25 -r 10 -s 1280*720 -an -f h264 jester.264
+
+//-bf B帧数目控制，-g 关键帧间隔控制，-s 分辨率控制 -an关闭音频， -r 指定帧率
+```
+
+使用live555生成视频流。
+
+**步骤3** 模型转换
+
+下载[在线模型](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/TSM/online_models.zip) jester.onnx
+
+将下载好的模型放在参考设计代码根目录的“model”目录下。
+
+将模型转换为om模型，在“model”目录下，运行脚本生成om模型
+
+```shell
+bash onnx2om1.sh
+```
+
+**步骤4** 程序测试
+
+```shell
+python3 online_infer.py
+```
+
+修改参数，'ip:port/jester.264'为测试视频流，其中ip为起流的机器ip地址，port为起流的机器端口地址，jester.264为测试视频jester.mp4通过ffmpeg转换后的视频。
+
+```python
+def video2img():
+    cmd = 'ffmpeg  -i \"{}\" -threads 1 -vf scale=-1:331 -q:v 0 \"{}/img_%05d.jpg\"'.format('rtsp://ip:port/jester.264', './image')
+    subprocess.call(cmd, shell=True,
+                    stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
+```
diff --git a/contrib/TSM/download_data/k400_extractor.sh b/mxVision/mxVision-referenceapps/TSM/download_data/k400_extractor.sh
similarity index 100%
rename from contrib/TSM/download_data/k400_extractor.sh
rename to mxVision/mxVision-referenceapps/TSM/download_data/k400_extractor.sh
diff --git a/contrib/TSM/label/kinetics_val.csv b/mxVision/mxVision-referenceapps/TSM/label/kinetics_val.csv
similarity index 100%
rename from contrib/TSM/label/kinetics_val.csv
rename to mxVision/mxVision-referenceapps/TSM/label/kinetics_val.csv
diff --git a/contrib/TSM/model/onnx2om.sh b/mxVision/mxVision-referenceapps/TSM/model/onnx2om.sh
similarity index 100%
rename from contrib/TSM/model/onnx2om.sh
rename to mxVision/mxVision-referenceapps/TSM/model/onnx2om.sh
diff --git a/contrib/TSM/model/onnx2om1.sh b/mxVision/mxVision-referenceapps/TSM/model/onnx2om1.sh
similarity index 100%
rename from contrib/TSM/model/onnx2om1.sh
rename to mxVision/mxVision-referenceapps/TSM/model/onnx2om1.sh
diff --git a/contrib/TSM/offline.png b/mxVision/mxVision-referenceapps/TSM/offline.png
similarity index 100%
rename from contrib/TSM/offline.png
rename to mxVision/mxVision-referenceapps/TSM/offline.png
diff --git a/contrib/TSM/offline_infer.py b/mxVision/mxVision-referenceapps/TSM/offline_infer.py
similarity index 97%
rename from contrib/TSM/offline_infer.py
rename to mxVision/mxVision-referenceapps/TSM/offline_infer.py
index 0fb02ef43f2ac000b7ec5de3bc308399bd60c816..72a223dcc58564007061373969d3d488e4e37814 100644
--- a/contrib/TSM/offline_infer.py
+++ b/mxVision/mxVision-referenceapps/TSM/offline_infer.py
@@ -1,136 +1,136 @@
-# Copyright(C) 2022. Huawei Technologies Co.,Ltd. All rights reserved.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-# http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-import torch.nn.parallel
-import numpy as np
-from ops.dataset import TSNDataSet
-import torchvision
-from ops.transforms import GroupScale
-from ops.transforms import GroupCenterCrop
-from ops.transforms import Stack
-from ops.transforms import ToTorchFormatTensor
-from ops.transforms import GroupNormalize
-from ops import dataset_config
-import mindx.sdk as sdk
-
-WEIGHT = 'TSM_kinetics_RGB_resnet50_shift8_blockres_avg_segment8_e50.pth'
-weights = WEIGHT.split(',')
-coeff = [1] * len(weights)
-test_file = [None] * len(weights)
-modalities = []
-data_list = []
-TOTAL = None
-
-
-def process(video, segment, mol):
-    with torch.no_grad():
-        j, datas, labels = video
-        batch_size = labels.numel()
-        data1 = datas.view(-1, 3, datas.size(2), datas.size(3))
-        data1 = data1.view(batch_size, segment, 3, data1.size(2), data1.size(3))
-        filepath = "./model/TSM.om"
-        device_id = 0                          
-        m = sdk.model(filepath, device_id)
-        t = sdk.Tensor(np.array(data1))
-        t.to_device(0)
-        rsts = m.infer(t)
-        rsts[0].to_host()
-        rsts = rsts[0]
-        rsts = np.array(rsts)
-        rsts = rsts.reshape(batch_size, 1, -1).mean(1)
-        rsts = torch.Tensor(rsts)
-        rsts = rsts.data.cpu().numpy().copy()
-        rsts = rsts.reshape(batch_size, classes)
-        return j, rsts, labels
-
-for test in test_file:
-    MODALITY = 'RGB'
-    modalities.append(MODALITY)
-    classes, train_list, val_list, path, prefix = dataset_config.return_dataset('kinetics', MODALITY)
-    
-    dataset = torch.utils.data.DataLoader(
-            TSNDataSet(path, val_list, num_segments=8, new_length=1, modality='RGB',
-                       image_tmpl='img_{:05d}.jpg', test_mode=True, remove_missing = 1,
-                       transform=torchvision.transforms.Compose([
-                           torchvision.transforms.Compose([GroupScale(256), GroupCenterCrop(224), ]),
-                           Stack(roll=('resnet50' in ['BNInception', 'InceptionV3'])),
-                           ToTorchFormatTensor(div=('resnet50' not in ['BNInception', 'InceptionV3'])),
-                           GroupNormalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]),
-                       ]), dense_sample=False, twice_sample=False), batch_size=1, shuffle=False, num_workers=8, 
-                       pin_memory=True, )
-    data_gen = enumerate(dataset)
-    TOTAL = len(dataset.dataset)
-    data_list.append(data_gen)
- 
-
-class Meter(object):
-    def __init__(self):
-        self.reset()
-        self.val = None
-        self.avg = None
-
-    def reset(self):
-        self.val = 0
-        self.avg = 0
-        self.sum = 0
-        self.count = 0
-
-    def update(self, val, n=1):
-        self.val = val
-        self.sum += val * n
-        self.count += n
-        self.avg = self.sum / self.count
-
-
-def acc(outputs, target, topk=(1,)):
-    max1 = max(topk)
-    batch = target.size(0)
-    _, pred = outputs.topk(max1, 1, True, True)
-    pred = pred.t()
-    correct = pred.eq(target.view(1, -1).expand_as(pred))
-    res = []
-    for k in topk:
-        correct1 = correct[:k].view(-1).float().sum(0)
-        res.append(correct1.mul_(100.0 / batch))
-    return res
-
-output = []
-top1 = Meter()
-top5 = Meter()
-
-for i, data_label in enumerate(zip(*data_list)):
-    with torch.no_grad():
-        if i >= TOTAL:
-            break
-        this_rst = []
-        THIS_LABEL = None
-        for (_, (data, label)), modality in zip(data_label, modalities):
-            rst = process((i, data, label), 8, modality)
-            this_rst.append(rst[1])
-            THIS_LABEL = label
-        assert len(this_rst) == len(coeff)
-        for i_coeff, this_rsts in enumerate(this_rst):
-            this_rsts *= coeff[i_coeff]
-        predict = sum(this_rst) / len(this_rst)
-
-        for p, g in zip(predict, THIS_LABEL.cpu().numpy()):
-            output.append([p[None, ...], g])
-        prec1, prec5 = acc(torch.from_numpy(predict), THIS_LABEL, topk=(1, 5))
-        top1.update(prec1.item(), THIS_LABEL.numel())
-        top5.update(prec5.item(), THIS_LABEL.numel())
-        print('video {} finished, finish {}/{}, Prec@1 {:.3f} Prec@5 {:.3f}'.format(i, i, TOTAL,
-                                                                                    top1.avg, top5.avg))
-
-print('-----finished------')
+# Copyright(C) 2022. Huawei Technologies Co.,Ltd. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import torch.nn.parallel
+import numpy as np
+from ops.dataset import TSNDataSet
+import torchvision
+from ops.transforms import GroupScale
+from ops.transforms import GroupCenterCrop
+from ops.transforms import Stack
+from ops.transforms import ToTorchFormatTensor
+from ops.transforms import GroupNormalize
+from ops import dataset_config
+import mindx.sdk as sdk
+
+WEIGHT = 'TSM_kinetics_RGB_resnet50_shift8_blockres_avg_segment8_e50.pth'
+weights = WEIGHT.split(',')
+coeff = [1] * len(weights)
+test_file = [None] * len(weights)
+modalities = []
+data_list = []
+TOTAL = None
+
+
+def process(video, segment, mol):
+    with torch.no_grad():
+        j, datas, labels = video
+        batch_size = labels.numel()
+        data1 = datas.view(-1, 3, datas.size(2), datas.size(3))
+        data1 = data1.view(batch_size, segment, 3, data1.size(2), data1.size(3))
+        filepath = "./model/TSM.om"
+        device_id = 0                          
+        m = sdk.model(filepath, device_id)
+        t = sdk.Tensor(np.array(data1))
+        t.to_device(0)
+        rsts = m.infer(t)
+        rsts[0].to_host()
+        rsts = rsts[0]
+        rsts = np.array(rsts)
+        rsts = rsts.reshape(batch_size, 1, -1).mean(1)
+        rsts = torch.Tensor(rsts)
+        rsts = rsts.data.cpu().numpy().copy()
+        rsts = rsts.reshape(batch_size, classes)
+        return j, rsts, labels
+
+for test in test_file:
+    MODALITY = 'RGB'
+    modalities.append(MODALITY)
+    classes, train_list, val_list, path, prefix = dataset_config.return_dataset('kinetics', MODALITY)
+    
+    dataset = torch.utils.data.DataLoader(
+            TSNDataSet(path, val_list, num_segments=8, new_length=1, modality='RGB',
+                       image_tmpl='img_{:05d}.jpg', test_mode=True, remove_missing = 1,
+                       transform=torchvision.transforms.Compose([
+                           torchvision.transforms.Compose([GroupScale(256), GroupCenterCrop(224), ]),
+                           Stack(roll=('resnet50' in ['BNInception', 'InceptionV3'])),
+                           ToTorchFormatTensor(div=('resnet50' not in ['BNInception', 'InceptionV3'])),
+                           GroupNormalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]),
+                       ]), dense_sample=False, twice_sample=False), batch_size=1, shuffle=False, num_workers=8, 
+                       pin_memory=True, )
+    data_gen = enumerate(dataset)
+    TOTAL = len(dataset.dataset)
+    data_list.append(data_gen)
+ 
+
+class Meter(object):
+    def __init__(self):
+        self.reset()
+        self.val = None
+        self.avg = None
+
+    def reset(self):
+        self.val = 0
+        self.avg = 0
+        self.sum = 0
+        self.count = 0
+
+    def update(self, val, n=1):
+        self.val = val
+        self.sum += val * n
+        self.count += n
+        self.avg = self.sum / self.count
+
+
+def acc(outputs, target, topk=(1,)):
+    max1 = max(topk)
+    batch = target.size(0)
+    _, pred = outputs.topk(max1, 1, True, True)
+    pred = pred.t()
+    correct = pred.eq(target.view(1, -1).expand_as(pred))
+    res = []
+    for k in topk:
+        correct1 = correct[:k].view(-1).float().sum(0)
+        res.append(correct1.mul_(100.0 / batch))
+    return res
+
+output = []
+top1 = Meter()
+top5 = Meter()
+
+for i, data_label in enumerate(zip(*data_list)):
+    with torch.no_grad():
+        if i >= TOTAL:
+            break
+        this_rst = []
+        THIS_LABEL = None
+        for (_, (data, label)), modality in zip(data_label, modalities):
+            rst = process((i, data, label), 8, modality)
+            this_rst.append(rst[1])
+            THIS_LABEL = label
+        assert len(this_rst) == len(coeff)
+        for i_coeff, this_rsts in enumerate(this_rst):
+            this_rsts *= coeff[i_coeff]
+        predict = sum(this_rst) / len(this_rst)
+
+        for p, g in zip(predict, THIS_LABEL.cpu().numpy()):
+            output.append([p[None, ...], g])
+        prec1, prec5 = acc(torch.from_numpy(predict), THIS_LABEL, topk=(1, 5))
+        top1.update(prec1.item(), THIS_LABEL.numel())
+        top5.update(prec5.item(), THIS_LABEL.numel())
+        print('video {} finished, finish {}/{}, Prec@1 {:.3f} Prec@5 {:.3f}'.format(i, i, TOTAL,
+                                                                                    top1.avg, top5.avg))
+
+print('-----finished------')
 print('Finall Prec@1 {:.02f}% Prec@5 {:.02f}%'.format(top1.avg, top5.avg))
\ No newline at end of file
diff --git a/contrib/TSM/online.png b/mxVision/mxVision-referenceapps/TSM/online.png
similarity index 100%
rename from contrib/TSM/online.png
rename to mxVision/mxVision-referenceapps/TSM/online.png
diff --git a/contrib/TSM/online_infer.py b/mxVision/mxVision-referenceapps/TSM/online_infer.py
similarity index 97%
rename from contrib/TSM/online_infer.py
rename to mxVision/mxVision-referenceapps/TSM/online_infer.py
index 1a666251c0f70da3be86bcc23321ba5ea4212189..1243b52a4f2ab3b5b580758405c09b3fcc2dc110 100644
--- a/contrib/TSM/online_infer.py
+++ b/mxVision/mxVision-referenceapps/TSM/online_infer.py
@@ -1,178 +1,178 @@
-# Copyright(C) 2022. Huawei Technologies Co.,Ltd. All rights reserved.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-# http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-import os
-import time
-import subprocess
-import threading
-import shutil
-import inspect
-import ctypes
-from multiprocessing import Manager
-from multiprocessing import Process
-import numpy as np
-from PIL import Image, ImageOps
-import mindx.sdk as sdk
-
-REFINE_OUTPUT = True
-FILE_PATH = "./model/jester.om"
-DEVICE_ID = 0
-
-if not os.path.exists('./image'):
-    os.makedirs('./image')
-else:
-    shutil.rmtree('./image')
-    os.makedirs('./image')   
-    
-catigories = ["Doing other things", "Drumming Fingers", "No gesture", "Pulling Hand In", 
-              "Pulling Two Fingers In", "Pushing Hand Away", "Pushing Two Fingers Away", 
-              "Rolling Hand Backward", "Rolling Hand Forward", "Shaking Hand", "Sliding Two Fingers Down", 
-              "Sliding Two Fingers Left", "Sliding Two Fingers Right", "Sliding Two Fingers Up", 
-              "Stop Sign", "Swiping Down", "Swiping Left", "Swiping Right", "Swiping Up", 
-              "Thumb Down", "Thumb Up", "Turning Hand Clockwise", "Turning Hand Counterclockwise", 
-              "Zooming In With Full Hand", "Zooming In With Two Fingers", "Zooming Out With Full Hand", 
-              "Zooming Out With Two Fingers"]
-
-IMGS = []
-
-
-def video2img():
-    cmd = 'ffmpeg  -i \"{}\" -threads 1 -vf scale=-1:331 -q:v 0 \"{}/img_%05d.jpg\"'.format(
-          'rtsp://ip:port/jester.264', './image')
-    subprocess.call(cmd, shell=True,
-                    stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
-
-
-def process_output(idx_, history):
-    if not REFINE_OUTPUT:
-        return idx_, history
-
-    max_hist_len = 20
-
-    if idx_ in [7, 8, 21, 22, 3]:
-        idx_ = history[-1]
-    if idx_ == 0:
-        idx_ = 2
-    if idx_ != history[-1]:
-        if not (history[-1] == history[-2]): 
-            idx_ = history[-1]
-
-    history.append(idx_)
-    history = history[-max_hist_len:]
-
-    return history[-1], history
-
-
-def readimg():
-    global IMGS
-    while True:
-        for filename in os.listdir(r"./image"):
-            if filename not in IMGS:
-                IMGS.append(filename)
-
-
-def crop_image(re_img, new_height, new_width):
-    re_img = Image.fromarray(np.uint8(re_img))
-    width, height = re_img.size
-    left = (width - new_width)/2
-    top = (height - new_height)/2
-    right = (width + new_width)/2
-    bottom = (height + new_height)/2
-    crop_im = re_img.crop((left, top, right, bottom))
-    crop_im = np.asarray(crop_im)
-    return crop_im
-
-
-def stop_thread(thread):
-    _async_raise(thread.ident, SystemExit)
-
-
-def _async_raise(tid, exctype):
-    tid = ctypes.c_long(tid)
-    if not inspect.isclass(exctype):
-        exctype = type(exctype)
-    res = ctypes.pythonapi.PyThreadState_SetAsyncExc(tid, ctypes.py_object(exctype))
-    if res == 0:
-        raise ValueError("invalid thread id")
-    elif res != 1:
-        ctypes.pythonapi.PyThreadState_SetAsyncExc(tid, None)
-        raise SystemError("PyThreadState_SetAsyncExc failed")
-
-
-def main():
-    index = 0
-    time.sleep(10)
-    buffer = [
-        sdk.Tensor(np.zeros([1, 3, 56, 56], dtype=np.float32)),
-        sdk.Tensor(np.zeros([1, 4, 28, 28], dtype=np.float32)),
-        sdk.Tensor(np.zeros([1, 4, 28, 28], dtype=np.float32)),
-        sdk.Tensor(np.zeros([1, 8, 14, 14], dtype=np.float32)),
-        sdk.Tensor(np.zeros([1, 8, 14, 14], dtype=np.float32)),
-        sdk.Tensor(np.zeros([1, 8, 14, 14], dtype=np.float32)),
-        sdk.Tensor(np.zeros([1, 12, 14, 14], dtype=np.float32)),
-        sdk.Tensor(np.zeros([1, 12, 14, 14], dtype=np.float32)),
-        sdk.Tensor(np.zeros([1, 20, 7, 7], dtype=np.float32)),
-        sdk.Tensor(np.zeros([1, 20, 7, 7], dtype=np.float32))]
-    for t in buffer:
-        t.to_device(DEVICE_ID)
-    md = sdk.model(FILE_PATH, DEVICE_ID) 
-    i_frame = -2
-    history = [2]
-    history_logit = []
-    history_timing = []
-    while True:
-        try: 
-            i_frame += 2
-            time.sleep(0.2)
-            filename = IMGS[i_frame]
-            img = Image.open("./image/" + filename).convert('RGB')
-            if img.width > img.height:
-                frame_pil = img.resize((round(256 * img.width / img.height), 256))
-            else:
-                frame_pil = img.resize((256, round(256 * img.height / img.width)))
-            image = crop_image(frame_pil, 224, 224).transpose(2, 0, 1)
-            img_tran = [0, 0, 0]
-            for i in range(3):
-                img_tran[0] = (image[0] / 255-0.485) / 0.229
-                img_tran[1] = (image[1] / 255-0.456) / 0.224
-                img_tran[2] = (image[2] / 255-0.406) / 0.225
-            img_tran = np.array(img_tran).astype(np.float32)
-            img_tran = sdk.Tensor(img_tran)
-            img_tran.to_device(DEVICE_ID)
-            inputs = [img_tran, ] + buffer
-            outputs = md.infer(inputs)
-            buffer = outputs[1:]
-            outputs[0].to_host()
-            out = outputs[0]
-            feat = np.array(out)
-            idx_ = np.argmax(feat, axis=1)[0]
-            history_logit.append(feat)
-            history_logit = history_logit[-12:]
-            avg_logit = sum(history_logit)
-            idx_ = np.argmax(avg_logit, axis=1)[0]
-            idx, history = process_output(idx_, history)
-
-            print(f"{index} {catigories[idx]}")
-            index += 1
-        except KeyboardInterrupt:
-            print("stop")
-            stop_thread(s1)
-            stop_thread(s2)
-            break
-s1 = threading.Thread(target=video2img)
-s2 = threading.Thread(target=readimg)
-if __name__ == '__main__':
-    s1.start()
-    s2.start()
+# Copyright(C) 2022. Huawei Technologies Co.,Ltd. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import os
+import time
+import subprocess
+import threading
+import shutil
+import inspect
+import ctypes
+from multiprocessing import Manager
+from multiprocessing import Process
+import numpy as np
+from PIL import Image, ImageOps
+import mindx.sdk as sdk
+
+REFINE_OUTPUT = True
+FILE_PATH = "./model/jester.om"
+DEVICE_ID = 0
+
+if not os.path.exists('./image'):
+    os.makedirs('./image')
+else:
+    shutil.rmtree('./image')
+    os.makedirs('./image')   
+    
+catigories = ["Doing other things", "Drumming Fingers", "No gesture", "Pulling Hand In", 
+              "Pulling Two Fingers In", "Pushing Hand Away", "Pushing Two Fingers Away", 
+              "Rolling Hand Backward", "Rolling Hand Forward", "Shaking Hand", "Sliding Two Fingers Down", 
+              "Sliding Two Fingers Left", "Sliding Two Fingers Right", "Sliding Two Fingers Up", 
+              "Stop Sign", "Swiping Down", "Swiping Left", "Swiping Right", "Swiping Up", 
+              "Thumb Down", "Thumb Up", "Turning Hand Clockwise", "Turning Hand Counterclockwise", 
+              "Zooming In With Full Hand", "Zooming In With Two Fingers", "Zooming Out With Full Hand", 
+              "Zooming Out With Two Fingers"]
+
+IMGS = []
+
+
+def video2img():
+    cmd = 'ffmpeg  -i \"{}\" -threads 1 -vf scale=-1:331 -q:v 0 \"{}/img_%05d.jpg\"'.format(
+          'rtsp://ip:port/jester.264', './image')
+    subprocess.call(cmd, shell=True,
+                    stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
+
+
+def process_output(idx_, history):
+    if not REFINE_OUTPUT:
+        return idx_, history
+
+    max_hist_len = 20
+
+    if idx_ in [7, 8, 21, 22, 3]:
+        idx_ = history[-1]
+    if idx_ == 0:
+        idx_ = 2
+    if idx_ != history[-1]:
+        if not (history[-1] == history[-2]): 
+            idx_ = history[-1]
+
+    history.append(idx_)
+    history = history[-max_hist_len:]
+
+    return history[-1], history
+
+
+def readimg():
+    global IMGS
+    while True:
+        for filename in os.listdir(r"./image"):
+            if filename not in IMGS:
+                IMGS.append(filename)
+
+
+def crop_image(re_img, new_height, new_width):
+    re_img = Image.fromarray(np.uint8(re_img))
+    width, height = re_img.size
+    left = (width - new_width)/2
+    top = (height - new_height)/2
+    right = (width + new_width)/2
+    bottom = (height + new_height)/2
+    crop_im = re_img.crop((left, top, right, bottom))
+    crop_im = np.asarray(crop_im)
+    return crop_im
+
+
+def stop_thread(thread):
+    _async_raise(thread.ident, SystemExit)
+
+
+def _async_raise(tid, exctype):
+    tid = ctypes.c_long(tid)
+    if not inspect.isclass(exctype):
+        exctype = type(exctype)
+    res = ctypes.pythonapi.PyThreadState_SetAsyncExc(tid, ctypes.py_object(exctype))
+    if res == 0:
+        raise ValueError("invalid thread id")
+    elif res != 1:
+        ctypes.pythonapi.PyThreadState_SetAsyncExc(tid, None)
+        raise SystemError("PyThreadState_SetAsyncExc failed")
+
+
+def main():
+    index = 0
+    time.sleep(10)
+    buffer = [
+        sdk.Tensor(np.zeros([1, 3, 56, 56], dtype=np.float32)),
+        sdk.Tensor(np.zeros([1, 4, 28, 28], dtype=np.float32)),
+        sdk.Tensor(np.zeros([1, 4, 28, 28], dtype=np.float32)),
+        sdk.Tensor(np.zeros([1, 8, 14, 14], dtype=np.float32)),
+        sdk.Tensor(np.zeros([1, 8, 14, 14], dtype=np.float32)),
+        sdk.Tensor(np.zeros([1, 8, 14, 14], dtype=np.float32)),
+        sdk.Tensor(np.zeros([1, 12, 14, 14], dtype=np.float32)),
+        sdk.Tensor(np.zeros([1, 12, 14, 14], dtype=np.float32)),
+        sdk.Tensor(np.zeros([1, 20, 7, 7], dtype=np.float32)),
+        sdk.Tensor(np.zeros([1, 20, 7, 7], dtype=np.float32))]
+    for t in buffer:
+        t.to_device(DEVICE_ID)
+    md = sdk.model(FILE_PATH, DEVICE_ID) 
+    i_frame = -2
+    history = [2]
+    history_logit = []
+    history_timing = []
+    while True:
+        try: 
+            i_frame += 2
+            time.sleep(0.2)
+            filename = IMGS[i_frame]
+            img = Image.open("./image/" + filename).convert('RGB')
+            if img.width > img.height:
+                frame_pil = img.resize((round(256 * img.width / img.height), 256))
+            else:
+                frame_pil = img.resize((256, round(256 * img.height / img.width)))
+            image = crop_image(frame_pil, 224, 224).transpose(2, 0, 1)
+            img_tran = [0, 0, 0]
+            for i in range(3):
+                img_tran[0] = (image[0] / 255-0.485) / 0.229
+                img_tran[1] = (image[1] / 255-0.456) / 0.224
+                img_tran[2] = (image[2] / 255-0.406) / 0.225
+            img_tran = np.array(img_tran).astype(np.float32)
+            img_tran = sdk.Tensor(img_tran)
+            img_tran.to_device(DEVICE_ID)
+            inputs = [img_tran, ] + buffer
+            outputs = md.infer(inputs)
+            buffer = outputs[1:]
+            outputs[0].to_host()
+            out = outputs[0]
+            feat = np.array(out)
+            idx_ = np.argmax(feat, axis=1)[0]
+            history_logit.append(feat)
+            history_logit = history_logit[-12:]
+            avg_logit = sum(history_logit)
+            idx_ = np.argmax(avg_logit, axis=1)[0]
+            idx, history = process_output(idx_, history)
+
+            print(f"{index} {catigories[idx]}")
+            index += 1
+        except KeyboardInterrupt:
+            print("stop")
+            stop_thread(s1)
+            stop_thread(s2)
+            break
+s1 = threading.Thread(target=video2img)
+s2 = threading.Thread(target=readimg)
+if __name__ == '__main__':
+    s1.start()
+    s2.start()
     main()
\ No newline at end of file
diff --git a/contrib/TSM/speed.py b/mxVision/mxVision-referenceapps/TSM/speed.py
similarity index 98%
rename from contrib/TSM/speed.py
rename to mxVision/mxVision-referenceapps/TSM/speed.py
index 7ffb89cf24af09278a1f59cb6ceefbf1cf390e5b..3f178564dd389ec1cf72b8a1a93568de6c7791da 100644
--- a/contrib/TSM/speed.py
+++ b/mxVision/mxVision-referenceapps/TSM/speed.py
@@ -1,167 +1,167 @@
-# Copyright(C) 2022. Huawei Technologies Co.,Ltd. All rights reserved.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-# http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-import os
-import time
-import subprocess
-import shutil
-from PIL import Image
-import mindx.sdk as sdk
-import numpy as np
-
-FILE_PATH = "./model/TSM.om"
-DEVICE_ID = 0 
-cls_text = ['abseiling', 'air drumming', 'answering questions', 'applauding', 'applying cream', 
-            'archery', 'arm wrestling', 'arranging flowers', 'assembling computer', 'auctioning', 
-            'baby waking up', 'baking cookies', 'balloon blowing', 'bandaging', 'barbequing', 
-            'bartending', 'beatboxing', 'bee keeping', 'belly dancing', 'bench pressing', 'bending back',
-            'bending metal', 'biking through snow', 'blasting sand', 'blowing glass', 'blowing leaves',
-            'blowing nose', 'blowing out candles', 'bobsledding', 'bookbinding', 'bouncing on trampoline', 
-            'bowling', 'braiding hair', 'breading or breadcrumbing', 'breakdancing', 'brush painting',
-            'brushing hair', 'brushing teeth', 'building cabinet', 'building shed', 'bungee jumping', 
-            'busking', 'canoeing or kayaking', 'capoeira', 'carrying baby', 'cartwheeling', 
-            'carving pumpkin', 'catching fish', 'catching or throwing baseball', 'catching or throwing frisbee', 
-            'catching or throwing softball', 'celebrating', 'changing oil', 'changing wheel', 'checking tires', 
-            'cheerleading', 'chopping wood', 'clapping', 'clay pottery making', 'clean and jerk', 'cleaning floor', 
-            'cleaning gutters', 'cleaning pool', 'cleaning shoes', 'cleaning toilet', 'cleaning windows', 
-            'climbing a rope', 'climbing ladder', 'climbing tree', 'contact juggling', 'cooking chicken', 
-            'cooking egg', 'cooking on campfire', 'cooking sausages', 'counting money', 'country line dancing', 
-            'cracking neck', 'crawling baby', 'crossing river', 'crying', 'curling hair', 'cutting nails', 
-            'cutting pineapple', 'cutting watermelon', 'dancing ballet', 'dancing charleston', 'dancing gangnam style', 
-            'dancing macarena', 'deadlifting', 'decorating the christmas tree', 'digging', 'dining', 
-            'disc golfing', 'diving cliff', 'dodgeball', 'doing aerobics', 'doing laundry', 'doing nails', 
-            'drawing', 'dribbling basketball', 'drinking', 'drinking beer', 'drinking shots', 'driving car', 
-            'driving tractor', 'drop kicking', 'drumming fingers', 'dunking basketball', 'dying hair', 
-            'eating burger', 'eating cake', 'eating carrots', 'eating chips', 'eating doughnuts', 'eating hotdog', 
-            'eating ice cream', 'eating spaghetti', 'eating watermelon', 'egg hunting', 'exercising arm', 
-            'exercising with an exercise ball', 'extinguishing fire', 'faceplanting', 'feeding birds', 'feeding fish', 
-            'feeding goats', 'filling eyebrows', 'finger snapping', 'fixing hair', 'flipping pancake', 'flying kite', 
-            'folding clothes', 'folding napkins', 'folding paper', 'front raises', 'frying vegetables', 
-            'garbage collecting', 'gargling', 'getting a haircut', 'getting a tattoo', 'giving or receiving award', 
-            'golf chipping', 'golf driving', 'golf putting', 'grinding meat', 'grooming dog', 'grooming horse',
-            'gymnastics tumbling', 'hammer throw', 'headbanging', 'headbutting', 'high jump', 'high kick', 
-            'hitting baseball', 'hockey stop', 'holding snake', 'hopscotch', 'hoverboarding', 'hugging', 
-            'hula hooping', 'hurdling', 'hurling (sport)', 'ice climbing', 'ice fishing', 'ice skating', 
-            'ironing', 'javelin throw', 'jetskiing', 'jogging', 'juggling balls', 'juggling fire', 
-            'juggling soccer ball', 'jumping into pool', 'jumpstyle dancing', 'kicking field goal', 
-            'kicking soccer ball', 'kissing', 'kitesurfing', 'knitting', 'krumping', 'laughing', 
-            'laying bricks', 'long jump', 'lunge', 'making a cake', 'making a sandwich', 'making bed', 
-            'making jewelry', 'making pizza', 'making snowman', 'making sushi', 
-            'making tea', 'marching', 'massaging back', 'massaging feet', 'massaging legs', 
-            "massaging person's head", 'milking cow', 'mopping floor', 'motorcycling', 'moving furniture', 
-            'mowing lawn', 'news anchoring', 'opening bottle', 'opening present', 'paragliding', 'parasailing', 
-            'parkour', 'passing American football (in game)', 'passing American football (not in game)', 
-            'peeling apples', 'peeling potatoes', 'petting animal (not cat)', 'petting cat', 'picking fruit', 
-            'planting trees', 'plastering', 'playing accordion', 'playing badminton', 'playing bagpipes', 
-            'playing basketball', 'playing bass guitar', 'playing cards', 'playing cello', 'playing chess', 
-            'playing clarinet', 'playing controller', 'playing cricket', 'playing cymbals', 'playing didgeridoo', 
-            'playing drums', 'playing flute', 'playing guitar', 'playing harmonica', 'playing harp', 
-            'playing ice hockey', 'playing keyboard', 'playing kickball', 'playing monopoly', 'playing organ', 
-            'playing paintball', 'playing piano', 'playing poker', 'playing recorder', 'playing saxophone', 
-            'playing squash or racquetball', 'playing tennis', 'playing trombone', 'playing trumpet', 
-            'playing ukulele', 'playing violin', 'playing volleyball', 'playing xylophone', 'pole vault', 
-            'presenting weather forecast', 'pull ups', 'pumping fist', 'pumping gas', 'punching bag', 
-            'punching person (boxing)', 'push up', 'pushing car', 'pushing cart', 'pushing wheelchair', 
-            'reading book', 'reading newspaper', 'recording music', 'riding a bike', 'riding camel', 
-            'riding elephant', 'riding mechanical bull', 'riding mountain bike', 'riding mule', 
-            'riding or walking with horse', 'riding scooter', 'riding unicycle', 'ripping paper', 'robot dancing', 
-            'rock climbing', 'rock scissors paper', 'roller skating', 'running on treadmill', 'sailing', 
-            'salsa dancing', 'sanding floor', 'scrambling eggs', 'scuba diving', 'setting table', 'shaking hands', 
-            'shaking head', 'sharpening knives', 'sharpening pencil', 'shaving head', 'shaving legs', 
-            'shearing sheep', 'shining shoes', 'shooting basketball', 'shooting goal (soccer)', 'shot put', 
-            'shoveling snow', 'shredding paper', 'shuffling cards', 'side kick', 'sign language interpreting', 
-            'singing', 'situp', 'skateboarding', 'ski jumping', 'skiing (not slalom or crosscountry)', 
-            'skiing crosscountry', 'skiing slalom', 'skipping rope', 'skydiving', 'slacklining', 'slapping', 
-            'sled dog racing', 'smoking', 'smoking hookah', 'snatch weight lifting', 'sneezing', 'sniffing', 
-            'snorkeling', 'snowboarding', 'snowkiting', 'snowmobiling', 'somersaulting', 'spinning poi', 
-            'spray painting', 'spraying', 'springboard diving', 'squat', 'sticking tongue out', 'stomping grapes', 
-            'stretching arm', 'stretching leg', 'strumming guitar', 'surfing crowd', 'surfing water', 
-            'sweeping floor', 'swimming backstroke', 'swimming breast stroke', 'swimming butterfly stroke', 
-            'swing dancing', 'swinging legs', 'swinging on something', 'sword fighting', 'tai chi', 
-            'taking a shower', 'tango dancing', 'tap dancing', 'tapping guitar', 'tapping pen', 'tasting beer', 
-            'tasting food', 'testifying', 'texting', 'throwing axe', 'throwing ball', 'throwing discus', 
-            'tickling', 'tobogganing', 'tossing coin', 'tossing salad', 'training dog', 'trapezing', 
-            'trimming or shaving beard', 'trimming trees', 'triple jump', 'tying bow tie', 'tying knot (not on a tie)', 
-            'tying tie', 'unboxing', 'unloading truck', 'using computer', 'using remote controller (not gaming)', 
-            'using segway', 'vault', 'waiting in line', 'walking the dog', 'washing dishes', 'washing feet',
-            'washing hair', 'washing hands', 'water skiing', 'water sliding', 'watering plants', 'waxing back', 
-            'waxing chest', 'waxing eyebrows', 'waxing legs', 'weaving basket', 'welding', 'whistling', 'windsurfing', 
-            'wrapping present', 'wrestling', 'writing', 'yawning', 'yoga', 'zumba', 'None']
-
-if not os.path.exists('./image'):
-    os.makedirs('./image')
-else:
-    shutil.rmtree('./image')
-    os.makedirs('./image')    
-
-
-def crop_image(re_img, new_height, new_width):
-    re_img = Image.fromarray(np.uint8(re_img))
-    width, height = re_img.size
-    left = (width - new_width)/2
-    top = (height - new_height)/2
-    right = (width + new_width)/2
-    bottom = (height + new_height)/2
-    crop_im = re_img.crop((left, top, right, bottom))
-    crop_im = np.asarray(crop_im)
-    return crop_im
-
-
-def main():
-    cmd = 'ffmpeg  -i \"{}\" -threads 1 -vf scale=-1:331 -q:v 0 \"{}/img_%05d.jpg\"'.format('./test.mp4', './image')
-    subprocess.call(cmd, shell=True,
-                    stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
-    files = os.listdir(r"./image/")
-    files.sort(key=lambda x:int(x.split('img_')[1].split('.jpg')[0]))
-    tick = len(files) / float(8)
-    offsets = np.array([int(tick / 2.0 + tick * x) for x in range(8)])
-    pil_img_list = list()
-    i = 0
-    s = 400 
-    if len(files) != 0:
-        for i in range(8):
-            filename = files[int(offsets[i])]
-            img = Image.open("./image/" + filename).convert('RGB')
-        
-            if img.width > img.height:
-                frame_pil = img.resize((round(256 * img.width / img.height), 256))
-            else:
-                frame_pil = img.resize((256, round(256 * img.height / img.width)))
-            image = crop_image(frame_pil, 224, 224).transpose(2, 0, 1)
-            imgs = [0, 0, 0]
-            imgs[0] = (image[0] / 255-0.485) / 0.229
-            imgs[1] = (image[1] / 255-0.456) / 0.224
-            imgs[2] = (image[2] / 255-0.406) / 0.225
-            pil_img_list.extend([imgs])
-        this_rst_list = []
-        md = sdk.model(FILE_PATH, DEVICE_ID)
-        inputs = np.array(pil_img_list).astype(np.float32)
-        t = sdk.Tensor(inputs)
-        t.to_device(0)
-        start_time = time.time()
-        out = md.infer(t)
-        cnt_time = time.time() - start_time
-        out[0].to_host()
-        out = out[0]
-        out = np.array(out)
-        this_rst_list.append(out)
-        output_index = int(np.argmax(out))
-        s = output_index
-        print(cls_text[s])
-        print('average {:.3f} sec/video'.format(float(cnt_time)))
-    else:
-        print("This video is not exist!!")
-
-if __name__ == '__main__':
-    main()
+# Copyright(C) 2022. Huawei Technologies Co.,Ltd. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import os
+import time
+import subprocess
+import shutil
+from PIL import Image
+import mindx.sdk as sdk
+import numpy as np
+
+FILE_PATH = "./model/TSM.om"
+DEVICE_ID = 0 
+cls_text = ['abseiling', 'air drumming', 'answering questions', 'applauding', 'applying cream', 
+            'archery', 'arm wrestling', 'arranging flowers', 'assembling computer', 'auctioning', 
+            'baby waking up', 'baking cookies', 'balloon blowing', 'bandaging', 'barbequing', 
+            'bartending', 'beatboxing', 'bee keeping', 'belly dancing', 'bench pressing', 'bending back',
+            'bending metal', 'biking through snow', 'blasting sand', 'blowing glass', 'blowing leaves',
+            'blowing nose', 'blowing out candles', 'bobsledding', 'bookbinding', 'bouncing on trampoline', 
+            'bowling', 'braiding hair', 'breading or breadcrumbing', 'breakdancing', 'brush painting',
+            'brushing hair', 'brushing teeth', 'building cabinet', 'building shed', 'bungee jumping', 
+            'busking', 'canoeing or kayaking', 'capoeira', 'carrying baby', 'cartwheeling', 
+            'carving pumpkin', 'catching fish', 'catching or throwing baseball', 'catching or throwing frisbee', 
+            'catching or throwing softball', 'celebrating', 'changing oil', 'changing wheel', 'checking tires', 
+            'cheerleading', 'chopping wood', 'clapping', 'clay pottery making', 'clean and jerk', 'cleaning floor', 
+            'cleaning gutters', 'cleaning pool', 'cleaning shoes', 'cleaning toilet', 'cleaning windows', 
+            'climbing a rope', 'climbing ladder', 'climbing tree', 'contact juggling', 'cooking chicken', 
+            'cooking egg', 'cooking on campfire', 'cooking sausages', 'counting money', 'country line dancing', 
+            'cracking neck', 'crawling baby', 'crossing river', 'crying', 'curling hair', 'cutting nails', 
+            'cutting pineapple', 'cutting watermelon', 'dancing ballet', 'dancing charleston', 'dancing gangnam style', 
+            'dancing macarena', 'deadlifting', 'decorating the christmas tree', 'digging', 'dining', 
+            'disc golfing', 'diving cliff', 'dodgeball', 'doing aerobics', 'doing laundry', 'doing nails', 
+            'drawing', 'dribbling basketball', 'drinking', 'drinking beer', 'drinking shots', 'driving car', 
+            'driving tractor', 'drop kicking', 'drumming fingers', 'dunking basketball', 'dying hair', 
+            'eating burger', 'eating cake', 'eating carrots', 'eating chips', 'eating doughnuts', 'eating hotdog', 
+            'eating ice cream', 'eating spaghetti', 'eating watermelon', 'egg hunting', 'exercising arm', 
+            'exercising with an exercise ball', 'extinguishing fire', 'faceplanting', 'feeding birds', 'feeding fish', 
+            'feeding goats', 'filling eyebrows', 'finger snapping', 'fixing hair', 'flipping pancake', 'flying kite', 
+            'folding clothes', 'folding napkins', 'folding paper', 'front raises', 'frying vegetables', 
+            'garbage collecting', 'gargling', 'getting a haircut', 'getting a tattoo', 'giving or receiving award', 
+            'golf chipping', 'golf driving', 'golf putting', 'grinding meat', 'grooming dog', 'grooming horse',
+            'gymnastics tumbling', 'hammer throw', 'headbanging', 'headbutting', 'high jump', 'high kick', 
+            'hitting baseball', 'hockey stop', 'holding snake', 'hopscotch', 'hoverboarding', 'hugging', 
+            'hula hooping', 'hurdling', 'hurling (sport)', 'ice climbing', 'ice fishing', 'ice skating', 
+            'ironing', 'javelin throw', 'jetskiing', 'jogging', 'juggling balls', 'juggling fire', 
+            'juggling soccer ball', 'jumping into pool', 'jumpstyle dancing', 'kicking field goal', 
+            'kicking soccer ball', 'kissing', 'kitesurfing', 'knitting', 'krumping', 'laughing', 
+            'laying bricks', 'long jump', 'lunge', 'making a cake', 'making a sandwich', 'making bed', 
+            'making jewelry', 'making pizza', 'making snowman', 'making sushi', 
+            'making tea', 'marching', 'massaging back', 'massaging feet', 'massaging legs', 
+            "massaging person's head", 'milking cow', 'mopping floor', 'motorcycling', 'moving furniture', 
+            'mowing lawn', 'news anchoring', 'opening bottle', 'opening present', 'paragliding', 'parasailing', 
+            'parkour', 'passing American football (in game)', 'passing American football (not in game)', 
+            'peeling apples', 'peeling potatoes', 'petting animal (not cat)', 'petting cat', 'picking fruit', 
+            'planting trees', 'plastering', 'playing accordion', 'playing badminton', 'playing bagpipes', 
+            'playing basketball', 'playing bass guitar', 'playing cards', 'playing cello', 'playing chess', 
+            'playing clarinet', 'playing controller', 'playing cricket', 'playing cymbals', 'playing didgeridoo', 
+            'playing drums', 'playing flute', 'playing guitar', 'playing harmonica', 'playing harp', 
+            'playing ice hockey', 'playing keyboard', 'playing kickball', 'playing monopoly', 'playing organ', 
+            'playing paintball', 'playing piano', 'playing poker', 'playing recorder', 'playing saxophone', 
+            'playing squash or racquetball', 'playing tennis', 'playing trombone', 'playing trumpet', 
+            'playing ukulele', 'playing violin', 'playing volleyball', 'playing xylophone', 'pole vault', 
+            'presenting weather forecast', 'pull ups', 'pumping fist', 'pumping gas', 'punching bag', 
+            'punching person (boxing)', 'push up', 'pushing car', 'pushing cart', 'pushing wheelchair', 
+            'reading book', 'reading newspaper', 'recording music', 'riding a bike', 'riding camel', 
+            'riding elephant', 'riding mechanical bull', 'riding mountain bike', 'riding mule', 
+            'riding or walking with horse', 'riding scooter', 'riding unicycle', 'ripping paper', 'robot dancing', 
+            'rock climbing', 'rock scissors paper', 'roller skating', 'running on treadmill', 'sailing', 
+            'salsa dancing', 'sanding floor', 'scrambling eggs', 'scuba diving', 'setting table', 'shaking hands', 
+            'shaking head', 'sharpening knives', 'sharpening pencil', 'shaving head', 'shaving legs', 
+            'shearing sheep', 'shining shoes', 'shooting basketball', 'shooting goal (soccer)', 'shot put', 
+            'shoveling snow', 'shredding paper', 'shuffling cards', 'side kick', 'sign language interpreting', 
+            'singing', 'situp', 'skateboarding', 'ski jumping', 'skiing (not slalom or crosscountry)', 
+            'skiing crosscountry', 'skiing slalom', 'skipping rope', 'skydiving', 'slacklining', 'slapping', 
+            'sled dog racing', 'smoking', 'smoking hookah', 'snatch weight lifting', 'sneezing', 'sniffing', 
+            'snorkeling', 'snowboarding', 'snowkiting', 'snowmobiling', 'somersaulting', 'spinning poi', 
+            'spray painting', 'spraying', 'springboard diving', 'squat', 'sticking tongue out', 'stomping grapes', 
+            'stretching arm', 'stretching leg', 'strumming guitar', 'surfing crowd', 'surfing water', 
+            'sweeping floor', 'swimming backstroke', 'swimming breast stroke', 'swimming butterfly stroke', 
+            'swing dancing', 'swinging legs', 'swinging on something', 'sword fighting', 'tai chi', 
+            'taking a shower', 'tango dancing', 'tap dancing', 'tapping guitar', 'tapping pen', 'tasting beer', 
+            'tasting food', 'testifying', 'texting', 'throwing axe', 'throwing ball', 'throwing discus', 
+            'tickling', 'tobogganing', 'tossing coin', 'tossing salad', 'training dog', 'trapezing', 
+            'trimming or shaving beard', 'trimming trees', 'triple jump', 'tying bow tie', 'tying knot (not on a tie)', 
+            'tying tie', 'unboxing', 'unloading truck', 'using computer', 'using remote controller (not gaming)', 
+            'using segway', 'vault', 'waiting in line', 'walking the dog', 'washing dishes', 'washing feet',
+            'washing hair', 'washing hands', 'water skiing', 'water sliding', 'watering plants', 'waxing back', 
+            'waxing chest', 'waxing eyebrows', 'waxing legs', 'weaving basket', 'welding', 'whistling', 'windsurfing', 
+            'wrapping present', 'wrestling', 'writing', 'yawning', 'yoga', 'zumba', 'None']
+
+if not os.path.exists('./image'):
+    os.makedirs('./image')
+else:
+    shutil.rmtree('./image')
+    os.makedirs('./image')    
+
+
+def crop_image(re_img, new_height, new_width):
+    re_img = Image.fromarray(np.uint8(re_img))
+    width, height = re_img.size
+    left = (width - new_width)/2
+    top = (height - new_height)/2
+    right = (width + new_width)/2
+    bottom = (height + new_height)/2
+    crop_im = re_img.crop((left, top, right, bottom))
+    crop_im = np.asarray(crop_im)
+    return crop_im
+
+
+def main():
+    cmd = 'ffmpeg  -i \"{}\" -threads 1 -vf scale=-1:331 -q:v 0 \"{}/img_%05d.jpg\"'.format('./test.mp4', './image')
+    subprocess.call(cmd, shell=True,
+                    stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
+    files = os.listdir(r"./image/")
+    files.sort(key=lambda x:int(x.split('img_')[1].split('.jpg')[0]))
+    tick = len(files) / float(8)
+    offsets = np.array([int(tick / 2.0 + tick * x) for x in range(8)])
+    pil_img_list = list()
+    i = 0
+    s = 400 
+    if len(files) != 0:
+        for i in range(8):
+            filename = files[int(offsets[i])]
+            img = Image.open("./image/" + filename).convert('RGB')
+        
+            if img.width > img.height:
+                frame_pil = img.resize((round(256 * img.width / img.height), 256))
+            else:
+                frame_pil = img.resize((256, round(256 * img.height / img.width)))
+            image = crop_image(frame_pil, 224, 224).transpose(2, 0, 1)
+            imgs = [0, 0, 0]
+            imgs[0] = (image[0] / 255-0.485) / 0.229
+            imgs[1] = (image[1] / 255-0.456) / 0.224
+            imgs[2] = (image[2] / 255-0.406) / 0.225
+            pil_img_list.extend([imgs])
+        this_rst_list = []
+        md = sdk.model(FILE_PATH, DEVICE_ID)
+        inputs = np.array(pil_img_list).astype(np.float32)
+        t = sdk.Tensor(inputs)
+        t.to_device(0)
+        start_time = time.time()
+        out = md.infer(t)
+        cnt_time = time.time() - start_time
+        out[0].to_host()
+        out = out[0]
+        out = np.array(out)
+        this_rst_list.append(out)
+        output_index = int(np.argmax(out))
+        s = output_index
+        print(cls_text[s])
+        print('average {:.3f} sec/video'.format(float(cnt_time)))
+    else:
+        print("This video is not exist!!")
+
+if __name__ == '__main__':
+    main()
diff --git a/contrib/TSM/speed_gpu.py b/mxVision/mxVision-referenceapps/TSM/speed_gpu.py
similarity index 100%
rename from contrib/TSM/speed_gpu.py
rename to mxVision/mxVision-referenceapps/TSM/speed_gpu.py
diff --git a/contrib/TextSnake/README.md b/mxVision/mxVision-referenceapps/TextSnake/README.md
similarity index 100%
rename from contrib/TextSnake/README.md
rename to mxVision/mxVision-referenceapps/TextSnake/README.md
diff --git a/contrib/TextSnake/evaluate.py b/mxVision/mxVision-referenceapps/TextSnake/evaluate.py
similarity index 100%
rename from contrib/TextSnake/evaluate.py
rename to mxVision/mxVision-referenceapps/TextSnake/evaluate.py
diff --git a/contrib/TextSnake/main.py b/mxVision/mxVision-referenceapps/TextSnake/main.py
similarity index 100%
rename from contrib/TextSnake/main.py
rename to mxVision/mxVision-referenceapps/TextSnake/main.py
diff --git a/contrib/TextSnake/t.pipeline b/mxVision/mxVision-referenceapps/TextSnake/t.pipeline
similarity index 100%
rename from contrib/TextSnake/t.pipeline
rename to mxVision/mxVision-referenceapps/TextSnake/t.pipeline
diff --git "a/contrib/TextSnake/\347\262\276\345\272\2461.png" "b/mxVision/mxVision-referenceapps/TextSnake/\347\262\276\345\272\2461.png"
similarity index 100%
rename from "contrib/TextSnake/\347\262\276\345\272\2461.png"
rename to "mxVision/mxVision-referenceapps/TextSnake/\347\262\276\345\272\2461.png"
diff --git "a/contrib/TextSnake/\347\262\276\345\272\2462.png" "b/mxVision/mxVision-referenceapps/TextSnake/\347\262\276\345\272\2462.png"
similarity index 100%
rename from "contrib/TextSnake/\347\262\276\345\272\2462.png"
rename to "mxVision/mxVision-referenceapps/TextSnake/\347\262\276\345\272\2462.png"
diff --git a/mxVision/TrustedAudit/README.md b/mxVision/mxVision-referenceapps/TrustedAudit/README.md
similarity index 100%
rename from mxVision/TrustedAudit/README.md
rename to mxVision/mxVision-referenceapps/TrustedAudit/README.md
diff --git a/mxVision/TrustedAudit/build.sh b/mxVision/mxVision-referenceapps/TrustedAudit/build.sh
similarity index 100%
rename from mxVision/TrustedAudit/build.sh
rename to mxVision/mxVision-referenceapps/TrustedAudit/build.sh
diff --git a/mxVision/TrustedAudit/docker/Dockerfile_es b/mxVision/mxVision-referenceapps/TrustedAudit/docker/Dockerfile_es
similarity index 100%
rename from mxVision/TrustedAudit/docker/Dockerfile_es
rename to mxVision/mxVision-referenceapps/TrustedAudit/docker/Dockerfile_es
diff --git a/mxVision/TrustedAudit/docker/Dockerfile_opengauss b/mxVision/mxVision-referenceapps/TrustedAudit/docker/Dockerfile_opengauss
similarity index 100%
rename from mxVision/TrustedAudit/docker/Dockerfile_opengauss
rename to mxVision/mxVision-referenceapps/TrustedAudit/docker/Dockerfile_opengauss
diff --git a/mxVision/TrustedAudit/docker/Dockerfile_python b/mxVision/mxVision-referenceapps/TrustedAudit/docker/Dockerfile_python
similarity index 100%
rename from mxVision/TrustedAudit/docker/Dockerfile_python
rename to mxVision/mxVision-referenceapps/TrustedAudit/docker/Dockerfile_python
diff --git a/mxVision/TrustedAudit/docker/docker_run.sh b/mxVision/mxVision-referenceapps/TrustedAudit/docker/docker_run.sh
similarity index 100%
rename from mxVision/TrustedAudit/docker/docker_run.sh
rename to mxVision/mxVision-referenceapps/TrustedAudit/docker/docker_run.sh
diff --git a/mxVision/TrustedAudit/plugin/CMakeLists.txt b/mxVision/mxVision-referenceapps/TrustedAudit/plugin/CMakeLists.txt
similarity index 100%
rename from mxVision/TrustedAudit/plugin/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/TrustedAudit/plugin/CMakeLists.txt
diff --git a/mxVision/TrustedAudit/plugin/MxpiTrustedAuditPlugin.cpp b/mxVision/mxVision-referenceapps/TrustedAudit/plugin/MxpiTrustedAuditPlugin.cpp
similarity index 100%
rename from mxVision/TrustedAudit/plugin/MxpiTrustedAuditPlugin.cpp
rename to mxVision/mxVision-referenceapps/TrustedAudit/plugin/MxpiTrustedAuditPlugin.cpp
diff --git a/mxVision/TrustedAudit/plugin/MxpiTrustedAuditPlugin.h b/mxVision/mxVision-referenceapps/TrustedAudit/plugin/MxpiTrustedAuditPlugin.h
similarity index 100%
rename from mxVision/TrustedAudit/plugin/MxpiTrustedAuditPlugin.h
rename to mxVision/mxVision-referenceapps/TrustedAudit/plugin/MxpiTrustedAuditPlugin.h
diff --git a/mxVision/TrustedAudit/plugin/build.sh b/mxVision/mxVision-referenceapps/TrustedAudit/plugin/build.sh
similarity index 100%
rename from mxVision/TrustedAudit/plugin/build.sh
rename to mxVision/mxVision-referenceapps/TrustedAudit/plugin/build.sh
diff --git a/mxVision/TrustedAudit/trusted_audit/TrustedAudit.pipeline b/mxVision/mxVision-referenceapps/TrustedAudit/trusted_audit/TrustedAudit.pipeline
similarity index 100%
rename from mxVision/TrustedAudit/trusted_audit/TrustedAudit.pipeline
rename to mxVision/mxVision-referenceapps/TrustedAudit/trusted_audit/TrustedAudit.pipeline
diff --git a/mxVision/TrustedAudit/trusted_audit/main_trusted_audit.py b/mxVision/mxVision-referenceapps/TrustedAudit/trusted_audit/main_trusted_audit.py
similarity index 100%
rename from mxVision/TrustedAudit/trusted_audit/main_trusted_audit.py
rename to mxVision/mxVision-referenceapps/TrustedAudit/trusted_audit/main_trusted_audit.py
diff --git a/mxVision/TrustedAudit/trusted_audit/mindx/kill_watcher.py b/mxVision/mxVision-referenceapps/TrustedAudit/trusted_audit/mindx/kill_watcher.py
similarity index 100%
rename from mxVision/TrustedAudit/trusted_audit/mindx/kill_watcher.py
rename to mxVision/mxVision-referenceapps/TrustedAudit/trusted_audit/mindx/kill_watcher.py
diff --git a/mxVision/TrustedAudit/trusted_audit/mindx/mindx_watcher_and_sender.py b/mxVision/mxVision-referenceapps/TrustedAudit/trusted_audit/mindx/mindx_watcher_and_sender.py
similarity index 100%
rename from mxVision/TrustedAudit/trusted_audit/mindx/mindx_watcher_and_sender.py
rename to mxVision/mxVision-referenceapps/TrustedAudit/trusted_audit/mindx/mindx_watcher_and_sender.py
diff --git a/mxVision/TrustedAudit/trusted_audit/src/database_init.py b/mxVision/mxVision-referenceapps/TrustedAudit/trusted_audit/src/database_init.py
similarity index 100%
rename from mxVision/TrustedAudit/trusted_audit/src/database_init.py
rename to mxVision/mxVision-referenceapps/TrustedAudit/trusted_audit/src/database_init.py
diff --git a/mxVision/TrustedAudit/trusted_audit/src/es_database_operate.py b/mxVision/mxVision-referenceapps/TrustedAudit/trusted_audit/src/es_database_operate.py
similarity index 100%
rename from mxVision/TrustedAudit/trusted_audit/src/es_database_operate.py
rename to mxVision/mxVision-referenceapps/TrustedAudit/trusted_audit/src/es_database_operate.py
diff --git a/mxVision/TrustedAudit/trusted_audit/src/full_audit.py b/mxVision/mxVision-referenceapps/TrustedAudit/trusted_audit/src/full_audit.py
similarity index 100%
rename from mxVision/TrustedAudit/trusted_audit/src/full_audit.py
rename to mxVision/mxVision-referenceapps/TrustedAudit/trusted_audit/src/full_audit.py
diff --git a/mxVision/TrustedAudit/trusted_audit/src/full_search.py b/mxVision/mxVision-referenceapps/TrustedAudit/trusted_audit/src/full_search.py
similarity index 100%
rename from mxVision/TrustedAudit/trusted_audit/src/full_search.py
rename to mxVision/mxVision-referenceapps/TrustedAudit/trusted_audit/src/full_search.py
diff --git a/mxVision/TrustedAudit/trusted_audit/src/gauss_database_operate.py b/mxVision/mxVision-referenceapps/TrustedAudit/trusted_audit/src/gauss_database_operate.py
similarity index 100%
rename from mxVision/TrustedAudit/trusted_audit/src/gauss_database_operate.py
rename to mxVision/mxVision-referenceapps/TrustedAudit/trusted_audit/src/gauss_database_operate.py
diff --git a/mxVision/TrustedAudit/trusted_audit/src/merkle.py b/mxVision/mxVision-referenceapps/TrustedAudit/trusted_audit/src/merkle.py
similarity index 100%
rename from mxVision/TrustedAudit/trusted_audit/src/merkle.py
rename to mxVision/mxVision-referenceapps/TrustedAudit/trusted_audit/src/merkle.py
diff --git a/mxVision/TrustedAudit/trusted_audit/src/server_config.py b/mxVision/mxVision-referenceapps/TrustedAudit/trusted_audit/src/server_config.py
similarity index 100%
rename from mxVision/TrustedAudit/trusted_audit/src/server_config.py
rename to mxVision/mxVision-referenceapps/TrustedAudit/trusted_audit/src/server_config.py
diff --git a/mxVision/TrustedAudit/trusted_audit/src/test_a.py b/mxVision/mxVision-referenceapps/TrustedAudit/trusted_audit/src/test_a.py
similarity index 100%
rename from mxVision/TrustedAudit/trusted_audit/src/test_a.py
rename to mxVision/mxVision-referenceapps/TrustedAudit/trusted_audit/src/test_a.py
diff --git a/mxVision/TrustedAudit/trusted_audit/src/test_b.py b/mxVision/mxVision-referenceapps/TrustedAudit/trusted_audit/src/test_b.py
similarity index 100%
rename from mxVision/TrustedAudit/trusted_audit/src/test_b.py
rename to mxVision/mxVision-referenceapps/TrustedAudit/trusted_audit/src/test_b.py
diff --git a/mxVision/TrustedAudit/trusted_audit/src/test_c.py b/mxVision/mxVision-referenceapps/TrustedAudit/trusted_audit/src/test_c.py
similarity index 100%
rename from mxVision/TrustedAudit/trusted_audit/src/test_c.py
rename to mxVision/mxVision-referenceapps/TrustedAudit/trusted_audit/src/test_c.py
diff --git a/mxVision/TrustedAudit/trusted_audit/src/test_d.py b/mxVision/mxVision-referenceapps/TrustedAudit/trusted_audit/src/test_d.py
similarity index 100%
rename from mxVision/TrustedAudit/trusted_audit/src/test_d.py
rename to mxVision/mxVision-referenceapps/TrustedAudit/trusted_audit/src/test_d.py
diff --git a/mxVision/TrustedAudit/trusted_audit/src/tranlog_audit_serv.py b/mxVision/mxVision-referenceapps/TrustedAudit/trusted_audit/src/tranlog_audit_serv.py
similarity index 100%
rename from mxVision/TrustedAudit/trusted_audit/src/tranlog_audit_serv.py
rename to mxVision/mxVision-referenceapps/TrustedAudit/trusted_audit/src/tranlog_audit_serv.py
diff --git a/mxVision/TrustedAudit/trusted_audit/src/user_audit.py b/mxVision/mxVision-referenceapps/TrustedAudit/trusted_audit/src/user_audit.py
similarity index 100%
rename from mxVision/TrustedAudit/trusted_audit/src/user_audit.py
rename to mxVision/mxVision-referenceapps/TrustedAudit/trusted_audit/src/user_audit.py
diff --git a/mxVision/TrustedAudit/trusted_audit/src/user_search.py b/mxVision/mxVision-referenceapps/TrustedAudit/trusted_audit/src/user_search.py
similarity index 100%
rename from mxVision/TrustedAudit/trusted_audit/src/user_search.py
rename to mxVision/mxVision-referenceapps/TrustedAudit/trusted_audit/src/user_search.py
diff --git a/contrib/VCOD_SLTNet/README.md b/mxVision/mxVision-referenceapps/VCOD_SLTNet/README.md
similarity index 100%
rename from contrib/VCOD_SLTNet/README.md
rename to mxVision/mxVision-referenceapps/VCOD_SLTNet/README.md
diff --git a/contrib/VCOD_SLTNet/flowchart.jpeg b/mxVision/mxVision-referenceapps/VCOD_SLTNet/flowchart.jpeg
similarity index 100%
rename from contrib/VCOD_SLTNet/flowchart.jpeg
rename to mxVision/mxVision-referenceapps/VCOD_SLTNet/flowchart.jpeg
diff --git a/contrib/VCOD_SLTNet/inference.py b/mxVision/mxVision-referenceapps/VCOD_SLTNet/inference.py
similarity index 100%
rename from contrib/VCOD_SLTNet/inference.py
rename to mxVision/mxVision-referenceapps/VCOD_SLTNet/inference.py
diff --git a/contrib/VCOD_SLTNet/torch2onnx.py b/mxVision/mxVision-referenceapps/VCOD_SLTNet/torch2onnx.py
similarity index 100%
rename from contrib/VCOD_SLTNet/torch2onnx.py
rename to mxVision/mxVision-referenceapps/VCOD_SLTNet/torch2onnx.py
diff --git a/contrib/VehicleCounting/BlockingQueue/BlockingQueue.h b/mxVision/mxVision-referenceapps/VehicleCounting/BlockingQueue/BlockingQueue.h
similarity index 100%
rename from contrib/VehicleCounting/BlockingQueue/BlockingQueue.h
rename to mxVision/mxVision-referenceapps/VehicleCounting/BlockingQueue/BlockingQueue.h
diff --git a/contrib/VehicleCounting/CMakeLists.txt b/mxVision/mxVision-referenceapps/VehicleCounting/CMakeLists.txt
similarity index 100%
rename from contrib/VehicleCounting/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/VehicleCounting/CMakeLists.txt
diff --git a/contrib/VehicleCounting/README.md b/mxVision/mxVision-referenceapps/VehicleCounting/README.md
similarity index 100%
rename from contrib/VehicleCounting/README.md
rename to mxVision/mxVision-referenceapps/VehicleCounting/README.md
diff --git a/contrib/VehicleCounting/ReadConfig/GetConfig.cpp b/mxVision/mxVision-referenceapps/VehicleCounting/ReadConfig/GetConfig.cpp
similarity index 96%
rename from contrib/VehicleCounting/ReadConfig/GetConfig.cpp
rename to mxVision/mxVision-referenceapps/VehicleCounting/ReadConfig/GetConfig.cpp
index de00dd46d5975513443ee9b286fb8873638add72..ac70675049d7db382d93401001128780ffc045e8 100644
--- a/contrib/VehicleCounting/ReadConfig/GetConfig.cpp
+++ b/mxVision/mxVision-referenceapps/VehicleCounting/ReadConfig/GetConfig.cpp
@@ -1,147 +1,147 @@
-#include "GetConfig.h"
-#include <fstream>
-#include <iostream>
-#include <sstream>
-#include <vector>
-using namespace std;
-
-vector<string> v={"video_width","video_height","frame_rate","is_singlelane","lane_num","line_s_x",
-                  "line_s_y","line_e_x","line_e_y","is_vertical","point_x","point_y","point1_x",
-                  "point1_y","point2_x","point2_y","det_threshold","nms_iouthreshold"};
-vector<string> v1={"is_singlelane","lane_num","is_vertical"};
-bool isnum(string s)
-{
-    stringstream sin(s);
-    double t;
-    char p;
-    if(!(sin >> t)){
-        return false;
-    }
-    if(sin >> p){
-        return false;
-    }
-    else{
-        return true;
-    }
-}
-
-bool IsSpace(char c)
-{
-    if (' ' == c || '\t' == c){
-        return true;
-    }
-    return false;
-}
- 
-bool IsCommentChar(char c)
-{
-    if (c == COMMENT_CHAR){
-        return true;
-    }else{
-        return false;
-    }
-}
- 
-void Trim(string & str)
-{
-    if (str.empty()) {
-        return;
-    }
-    uint32_t i;
-    int start_pos, end_pos;
-    for (i = 0; i < str.size(); ++i) {
-        if (!IsSpace(str[i])) {
-            break;
-        }
-    }
-    if (i == str.size()) { // 全部是空白字符串
-        str = "";
-        return;
-    }
-    start_pos = i;
-    for (i = str.size() - 1; i >= 0; --i) {
-        if (!IsSpace(str[i])) {
-            break;
-        }
-    }
-    end_pos = i;
-    str = str.substr(start_pos, end_pos - start_pos + 1);
-}
- 
-bool AnalyseLine(const string & line, string & key, string & value)
-{
-    if (line.empty()){
-        return false;
-    }
-    int start_pos = 0, end_pos = line.size() - 1, pos;
-    if ((pos = line.find(COMMENT_CHAR)) != -1) {
-        if (0 == pos) {  // 行的第一个字符就是注释字符
-            return false;
-        }
-        end_pos = pos - 1;
-    }
-    string new_line = line.substr(start_pos, start_pos + 1 - end_pos);  // 预处理，删除注释部分
- 
-    if ((pos = new_line.find(':')) == -1){
-        return false;  // 没有:号
-    }
-
-    key = new_line.substr(0, pos);
-    value = new_line.substr(pos + 1, end_pos + 1- (pos + 1));
- 
-    Trim(key);
-    if (key.empty()) {
-        return false;
-    }
-    Trim(value);
-    return true;
-}
- 
-// 读取数据
-bool ReadConfig(const string & filename, map<string, string> & m)
-{
-    m.clear();
-    ifstream infile(filename.c_str());
-    if (!infile) {
-        cout << "file open error!" << endl;
-        return false;
-    }
-    string line, key, value;
-    bool is_null = true;
-    while (getline(infile, line)) {
-        if (AnalyseLine(line, key, value)) {
-            is_null = false;
-            // 判断参数是否不为空
-            if(value.empty()){
-                cout << "parameter "<<key<<" is empty!" << endl;
-                return false;
-            }
-            // 判断value是否为合法数字
-            if(!isnum(value)){
-                cout << "parameter "<<key<<" is illegal!" << endl;
-                return false;
-            }
-            m[key] = value;
-        }
-    }
-    if(is_null){
-        cout << "config file is null!" << endl;
-        return false;
-    }
-    // 判断is_singlelane,lane_num,is_vertical取值的合法性
-    for(uint32_t i=0;i<v1.size();i++){
-        if(stoi(m[v1[i]])!=0&&stoi(m[v1[i]])!=1){
-            cout << "parameter "<<v1[i]<<" value is illegal!" << endl;
-            return false;
-        }
-    }
-    // 判断是否读取到每个参数
-    for(uint32_t i=0;i<v.size();i++){
-        if(m.find(v[i])==m.end()){
-            cout << "parameter "<<v[i]<<" do not exist!" << endl;
-            return false;
-        }
-    }
-    infile.close();
-    return true;
-}
+#include "GetConfig.h"
+#include <fstream>
+#include <iostream>
+#include <sstream>
+#include <vector>
+using namespace std;
+
+vector<string> v={"video_width","video_height","frame_rate","is_singlelane","lane_num","line_s_x",
+                  "line_s_y","line_e_x","line_e_y","is_vertical","point_x","point_y","point1_x",
+                  "point1_y","point2_x","point2_y","det_threshold","nms_iouthreshold"};
+vector<string> v1={"is_singlelane","lane_num","is_vertical"};
+bool isnum(string s)
+{
+    stringstream sin(s);
+    double t;
+    char p;
+    if(!(sin >> t)){
+        return false;
+    }
+    if(sin >> p){
+        return false;
+    }
+    else{
+        return true;
+    }
+}
+
+bool IsSpace(char c)
+{
+    if (' ' == c || '\t' == c){
+        return true;
+    }
+    return false;
+}
+ 
+bool IsCommentChar(char c)
+{
+    if (c == COMMENT_CHAR){
+        return true;
+    }else{
+        return false;
+    }
+}
+ 
+void Trim(string & str)
+{
+    if (str.empty()) {
+        return;
+    }
+    uint32_t i;
+    int start_pos, end_pos;
+    for (i = 0; i < str.size(); ++i) {
+        if (!IsSpace(str[i])) {
+            break;
+        }
+    }
+    if (i == str.size()) { // 全部是空白字符串
+        str = "";
+        return;
+    }
+    start_pos = i;
+    for (i = str.size() - 1; i >= 0; --i) {
+        if (!IsSpace(str[i])) {
+            break;
+        }
+    }
+    end_pos = i;
+    str = str.substr(start_pos, end_pos - start_pos + 1);
+}
+ 
+bool AnalyseLine(const string & line, string & key, string & value)
+{
+    if (line.empty()){
+        return false;
+    }
+    int start_pos = 0, end_pos = line.size() - 1, pos;
+    if ((pos = line.find(COMMENT_CHAR)) != -1) {
+        if (0 == pos) {  // 行的第一个字符就是注释字符
+            return false;
+        }
+        end_pos = pos - 1;
+    }
+    string new_line = line.substr(start_pos, start_pos + 1 - end_pos);  // 预处理，删除注释部分
+ 
+    if ((pos = new_line.find(':')) == -1){
+        return false;  // 没有:号
+    }
+
+    key = new_line.substr(0, pos);
+    value = new_line.substr(pos + 1, end_pos + 1- (pos + 1));
+ 
+    Trim(key);
+    if (key.empty()) {
+        return false;
+    }
+    Trim(value);
+    return true;
+}
+ 
+// 读取数据
+bool ReadConfig(const string & filename, map<string, string> & m)
+{
+    m.clear();
+    ifstream infile(filename.c_str());
+    if (!infile) {
+        cout << "file open error!" << endl;
+        return false;
+    }
+    string line, key, value;
+    bool is_null = true;
+    while (getline(infile, line)) {
+        if (AnalyseLine(line, key, value)) {
+            is_null = false;
+            // 判断参数是否不为空
+            if(value.empty()){
+                cout << "parameter "<<key<<" is empty!" << endl;
+                return false;
+            }
+            // 判断value是否为合法数字
+            if(!isnum(value)){
+                cout << "parameter "<<key<<" is illegal!" << endl;
+                return false;
+            }
+            m[key] = value;
+        }
+    }
+    if(is_null){
+        cout << "config file is null!" << endl;
+        return false;
+    }
+    // 判断is_singlelane,lane_num,is_vertical取值的合法性
+    for(uint32_t i=0;i<v1.size();i++){
+        if(stoi(m[v1[i]])!=0&&stoi(m[v1[i]])!=1){
+            cout << "parameter "<<v1[i]<<" value is illegal!" << endl;
+            return false;
+        }
+    }
+    // 判断是否读取到每个参数
+    for(uint32_t i=0;i<v.size();i++){
+        if(m.find(v[i])==m.end()){
+            cout << "parameter "<<v[i]<<" do not exist!" << endl;
+            return false;
+        }
+    }
+    infile.close();
+    return true;
+}
diff --git a/contrib/VehicleCounting/ReadConfig/GetConfig.h b/mxVision/mxVision-referenceapps/VehicleCounting/ReadConfig/GetConfig.h
similarity index 95%
rename from contrib/VehicleCounting/ReadConfig/GetConfig.h
rename to mxVision/mxVision-referenceapps/VehicleCounting/ReadConfig/GetConfig.h
index aae11f3be6b75ea75690766af9ee9f457f667192..d76506772cf0f8edac09e9510e3bd66d86486a14 100644
--- a/contrib/VehicleCounting/ReadConfig/GetConfig.h
+++ b/mxVision/mxVision-referenceapps/VehicleCounting/ReadConfig/GetConfig.h
@@ -1,13 +1,13 @@
-//
-// Created by 16663 on 2021/11/24.
-//
-
-#ifndef STREAM_PULL_SAMPLE_GETCONFIG_H
-#define STREAM_PULL_SAMPLE_GETCONFIG_H
-#define COMMENT_CHAR '#'
-#include <string>
-#include <map>
-
-bool ReadConfig(const std::string & filename, std::map<std::string, std::string> & m);
-
-#endif // STREAM_PULL_SAMPLE_GETCONFIG_H
+//
+// Created by 16663 on 2021/11/24.
+//
+
+#ifndef STREAM_PULL_SAMPLE_GETCONFIG_H
+#define STREAM_PULL_SAMPLE_GETCONFIG_H
+#define COMMENT_CHAR '#'
+#include <string>
+#include <map>
+
+bool ReadConfig(const std::string & filename, std::map<std::string, std::string> & m);
+
+#endif // STREAM_PULL_SAMPLE_GETCONFIG_H
diff --git a/contrib/VehicleCounting/VideoProcess/DataType.h b/mxVision/mxVision-referenceapps/VehicleCounting/VideoProcess/DataType.h
similarity index 96%
rename from contrib/VehicleCounting/VideoProcess/DataType.h
rename to mxVision/mxVision-referenceapps/VehicleCounting/VideoProcess/DataType.h
index 153f96ea29510b272cf732faadec360e1709a45f..24cfc634a4a3644406f94e70e0e9eb9cca364407 100644
--- a/contrib/VehicleCounting/VideoProcess/DataType.h
+++ b/mxVision/mxVision-referenceapps/VehicleCounting/VideoProcess/DataType.h
@@ -1,94 +1,94 @@
-/*
- * Copyright(C) 2020. Huawei Technologies Co.,Ltd. All rights reserved.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#ifndef STREAM_PULL_SAMPLE_DATATYPE_H
-#define STREAM_PULL_SAMPLE_DATATYPE_H
-
-#include <memory>
-#include <cstdint>
-#include <vector>
-#include <fstream>
-#include <iostream>
-#include <map>
-#include "opencv2/highgui.hpp"
-#include "opencv2/imgcodecs.hpp"
-#include "opencv2/imgproc.hpp"
-
-namespace ascendVehicleTracking {
-#define DVPP_ALIGN_UP(x, align) ((((x) + ((align)-1)) / (align)) * (align))
-
-    const int MODULE_QUEUE_SIZE = 1000;
-
-    enum FrameMode {
-        FRAME_MODE_SEARCH = 0,
-        FRAME_MODE_REG
-    };
-
-    struct DataBuffer {
-        std::shared_ptr<uint8_t> deviceData;
-        std::shared_ptr<uint8_t> hostData;
-        uint32_t dataSize; // buffer size
-        DataBuffer() : deviceData(nullptr), hostData(nullptr), dataSize(0) {}
-    };
-
-    struct DetectInfo {
-        int32_t classId;
-        float confidence;
-        float minx; // x value of left-top point
-        float miny; // y value of left-top point
-        float height;
-        float width;
-    };
-
-    enum TraceFlag {
-        NEW_VEHICLE = 0,
-        TRACkED_VEHICLE,
-        LOST_VEHICLE
-    };
-
-    struct TraceInfo {
-        int32_t id;
-        TraceFlag flag;
-        int32_t survivalTime; // How long is it been since the first time, unit: detection period
-        int32_t detectedTime; // How long is the vehicle detected, unit: detection period
-        std::chrono::time_point<std::chrono::high_resolution_clock> createTime;
-    };
-
-    struct TrackLet {
-        TraceInfo info;
-        // reserved:  kalman status parameter
-        int32_t lostTime;                     // undetected time for tracked vehicle
-        std::vector<DataBuffer> shortFeature; // nearest 10 frame
-    };
-
-    struct VehicleQuality {
-        float score;
-    };
-
-    struct Coordinate2D {
-        uint32_t x;
-        uint32_t y;
-    };
-
-} // namespace ascendVehicleTracking
-
-struct AttrT {
-    AttrT(std::string name, std::string value) : name(std::move(name)), value(std::move(value)) {}
-    std::string name = {};
-    std::string value = {};
-};
-
-#endif // STREAM_PULL_SAMPLE_DATATYPE_H
+/*
+ * Copyright(C) 2020. Huawei Technologies Co.,Ltd. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef STREAM_PULL_SAMPLE_DATATYPE_H
+#define STREAM_PULL_SAMPLE_DATATYPE_H
+
+#include <memory>
+#include <cstdint>
+#include <vector>
+#include <fstream>
+#include <iostream>
+#include <map>
+#include "opencv2/highgui.hpp"
+#include "opencv2/imgcodecs.hpp"
+#include "opencv2/imgproc.hpp"
+
+namespace ascendVehicleTracking {
+#define DVPP_ALIGN_UP(x, align) ((((x) + ((align)-1)) / (align)) * (align))
+
+    const int MODULE_QUEUE_SIZE = 1000;
+
+    enum FrameMode {
+        FRAME_MODE_SEARCH = 0,
+        FRAME_MODE_REG
+    };
+
+    struct DataBuffer {
+        std::shared_ptr<uint8_t> deviceData;
+        std::shared_ptr<uint8_t> hostData;
+        uint32_t dataSize; // buffer size
+        DataBuffer() : deviceData(nullptr), hostData(nullptr), dataSize(0) {}
+    };
+
+    struct DetectInfo {
+        int32_t classId;
+        float confidence;
+        float minx; // x value of left-top point
+        float miny; // y value of left-top point
+        float height;
+        float width;
+    };
+
+    enum TraceFlag {
+        NEW_VEHICLE = 0,
+        TRACkED_VEHICLE,
+        LOST_VEHICLE
+    };
+
+    struct TraceInfo {
+        int32_t id;
+        TraceFlag flag;
+        int32_t survivalTime; // How long is it been since the first time, unit: detection period
+        int32_t detectedTime; // How long is the vehicle detected, unit: detection period
+        std::chrono::time_point<std::chrono::high_resolution_clock> createTime;
+    };
+
+    struct TrackLet {
+        TraceInfo info;
+        // reserved:  kalman status parameter
+        int32_t lostTime;                     // undetected time for tracked vehicle
+        std::vector<DataBuffer> shortFeature; // nearest 10 frame
+    };
+
+    struct VehicleQuality {
+        float score;
+    };
+
+    struct Coordinate2D {
+        uint32_t x;
+        uint32_t y;
+    };
+
+} // namespace ascendVehicleTracking
+
+struct AttrT {
+    AttrT(std::string name, std::string value) : name(std::move(name)), value(std::move(value)) {}
+    std::string name = {};
+    std::string value = {};
+};
+
+#endif // STREAM_PULL_SAMPLE_DATATYPE_H
diff --git a/contrib/VehicleCounting/VideoProcess/Hungarian.cpp b/mxVision/mxVision-referenceapps/VehicleCounting/VideoProcess/Hungarian.cpp
similarity index 97%
rename from contrib/VehicleCounting/VideoProcess/Hungarian.cpp
rename to mxVision/mxVision-referenceapps/VehicleCounting/VideoProcess/Hungarian.cpp
index 90cfe183d5f6dd406a4f717c787fcbbe1d16b209..3d27037372120a118b73f635fd7a210f9773f693 100644
--- a/contrib/VehicleCounting/VideoProcess/Hungarian.cpp
+++ b/mxVision/mxVision-referenceapps/VehicleCounting/VideoProcess/Hungarian.cpp
@@ -1,165 +1,165 @@
-/*
- * Copyright(C) 2020. Huawei Technologies Co.,Ltd. All rights reserved.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#include "Hungarian.h"
-#include <cstring>
-#include <sys/time.h>
-#include "MxBase/Log/Log.h"
-
-namespace {
-    const int INF = 0x3f3f3f3f;
-    const int VISITED = 1;
-    const int HUNGARIAN_CONTENT = 7;
-    const int X_MATCH_OFFSET = 0;
-    const int Y_MATCH_OFFSET = 1;
-    const int X_VALUE_OFFSET = 2;
-    const int Y_VALUE_OFFSET = 3;
-    const int SLACK_OFFSET = 4;
-    const int X_VISIT_OFFSET = 5;
-    const int Y_VISIT_OFFSET = 6;
-}
-
-APP_ERROR HungarianHandleInit(HungarianHandle &handle, int row, int cols)
-{
-    handle.max = (row > cols) ? row : cols;
-    auto adjMat = std::shared_ptr<int>();
-    adjMat.reset(new int[handle.max * handle.max], std::default_delete<int[]>());
-    if (adjMat == nullptr) {
-        LogFatal << "HungarianHandleInit new failed";
-        return APP_ERR_ACL_FAILURE;
-    }
-
-    handle.adjMat = adjMat;
-
-    void* ptr[HUNGARIAN_CONTENT] = {nullptr};
-    for (int i = 0; i < HUNGARIAN_CONTENT; ++i) {
-        ptr[i] = malloc(handle.max * sizeof(int));
-        if (ptr[i] == nullptr) {
-            LogFatal << "HungarianHandleInit Malloc failed";
-            return APP_ERR_ACL_FAILURE;
-        }
-    }
-
-    handle.xMatch.reset((int *)ptr[X_MATCH_OFFSET], free);
-    handle.yMatch.reset((int *)ptr[Y_MATCH_OFFSET], free);
-    handle.xValue.reset((int *)ptr[X_VALUE_OFFSET], free);
-    handle.yValue.reset((int *)ptr[Y_VALUE_OFFSET], free);
-    handle.slack.reset((int *)ptr[SLACK_OFFSET], free);
-    handle.xVisit.reset((int *)ptr[X_VISIT_OFFSET], free);
-    handle.yVisit.reset((int *)ptr[Y_VISIT_OFFSET], free);
-    return APP_ERR_OK;
-}
-
-static void HungarianInit(HungarianHandle &handle, const std::vector<std::vector<int>> &cost, int rows, int cols)
-{
-    int i, j, value;
-    if (rows > cols) {
-        handle.transpose = true;
-        handle.cols = rows;
-        handle.rows = cols;
-        handle.resX = handle.yMatch.get();
-        handle.resY = handle.xMatch.get();
-    } else {
-        handle.transpose = false;
-        handle.rows = rows;
-        handle.cols = cols;
-        handle.resX = handle.xMatch.get();
-        handle.resY = handle.yMatch.get();
-    }
-
-    for (i = 0; i < handle.rows; ++i) {
-        handle.xValue.get()[i] = 0;
-        handle.xMatch.get()[i] = -1;
-        for (j = 0; j < handle.cols; ++j) {
-            if (handle.transpose) {
-                value = cost[j][i];
-            } else {
-                value = cost[i][j];
-            }
-            handle.adjMat.get()[i * handle.cols + j] = value;
-            if (handle.xValue.get()[i] < value) {
-                handle.xValue.get()[i] = value;
-            }
-        }
-    }
-
-    for (i = 0; i < handle.cols; ++i) {
-        handle.yValue.get()[i] = 0;
-        handle.yMatch.get()[i] = -1;
-    }
-}
-
-static bool Match(HungarianHandle &handle, int id)
-{
-    int j, delta;
-    handle.xVisit.get()[id] = VISITED;
-    for (j = 0; j < handle.cols; ++j) {
-        if (handle.yVisit.get()[j] == VISITED) {
-            continue;
-        }
-        delta = handle.xValue.get()[id] + handle.yValue.get()[j] - handle.adjMat.get()[id * handle.cols + j];
-        if (delta == 0) {
-            handle.yVisit.get()[j] = VISITED;
-            if (handle.yMatch.get()[j] == -1 || Match(handle, handle.yMatch.get()[j])) {
-                handle.yMatch.get()[j] = id;
-                handle.xMatch.get()[id] = j;
-                return true;
-            }
-        } else if (delta < handle.slack.get()[j]) {
-            handle.slack.get()[j] = delta;
-        }
-    }
-    return false;
-}
-
-int HungarianSolve(HungarianHandle &handle, const std::vector<std::vector<int>> &cost, int rows, int cols)
-{
-    HungarianInit(handle, cost, rows, cols);
-    int i, j, delta;
-    for (i = 0; i < handle.rows; ++i) {
-        while (true) {
-            std::fill(handle.xVisit.get(), handle.xVisit.get() + handle.rows, 0);
-            std::fill(handle.yVisit.get(), handle.yVisit.get() + handle.cols, 0);
-            for (j = 0; j < handle.cols; ++j) {
-                handle.slack.get()[j] = INF;
-            }
-            if (Match(handle, i)) {
-                break;
-            }
-            delta = INF;
-            for (j = 0; j < handle.cols; ++j) {
-                if (handle.yVisit.get()[j] != VISITED && delta > handle.slack.get()[j]) {
-                    delta = handle.slack.get()[j];
-                }
-            }
-            if (delta == INF) {
-                LogDebug << "Hungarian solve is invalid!";
-                return -1;
-            }
-            for (j = 0; j < handle.rows; ++j) {
-                if (handle.xVisit.get()[j] == VISITED) {
-                    handle.xValue.get()[j] -= delta;
-                }
-            }
-            for (j = 0; j < handle.cols; ++j) {
-                if (handle.yVisit.get()[j] == VISITED) {
-                    handle.yValue.get()[j] += delta;
-                }
-            }
-        }
-    }
-    return handle.rows;
-}
+/*
+ * Copyright(C) 2020. Huawei Technologies Co.,Ltd. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "Hungarian.h"
+#include <cstring>
+#include <sys/time.h>
+#include "MxBase/Log/Log.h"
+
+namespace {
+    const int INF = 0x3f3f3f3f;
+    const int VISITED = 1;
+    const int HUNGARIAN_CONTENT = 7;
+    const int X_MATCH_OFFSET = 0;
+    const int Y_MATCH_OFFSET = 1;
+    const int X_VALUE_OFFSET = 2;
+    const int Y_VALUE_OFFSET = 3;
+    const int SLACK_OFFSET = 4;
+    const int X_VISIT_OFFSET = 5;
+    const int Y_VISIT_OFFSET = 6;
+}
+
+APP_ERROR HungarianHandleInit(HungarianHandle &handle, int row, int cols)
+{
+    handle.max = (row > cols) ? row : cols;
+    auto adjMat = std::shared_ptr<int>();
+    adjMat.reset(new int[handle.max * handle.max], std::default_delete<int[]>());
+    if (adjMat == nullptr) {
+        LogFatal << "HungarianHandleInit new failed";
+        return APP_ERR_ACL_FAILURE;
+    }
+
+    handle.adjMat = adjMat;
+
+    void* ptr[HUNGARIAN_CONTENT] = {nullptr};
+    for (int i = 0; i < HUNGARIAN_CONTENT; ++i) {
+        ptr[i] = malloc(handle.max * sizeof(int));
+        if (ptr[i] == nullptr) {
+            LogFatal << "HungarianHandleInit Malloc failed";
+            return APP_ERR_ACL_FAILURE;
+        }
+    }
+
+    handle.xMatch.reset((int *)ptr[X_MATCH_OFFSET], free);
+    handle.yMatch.reset((int *)ptr[Y_MATCH_OFFSET], free);
+    handle.xValue.reset((int *)ptr[X_VALUE_OFFSET], free);
+    handle.yValue.reset((int *)ptr[Y_VALUE_OFFSET], free);
+    handle.slack.reset((int *)ptr[SLACK_OFFSET], free);
+    handle.xVisit.reset((int *)ptr[X_VISIT_OFFSET], free);
+    handle.yVisit.reset((int *)ptr[Y_VISIT_OFFSET], free);
+    return APP_ERR_OK;
+}
+
+static void HungarianInit(HungarianHandle &handle, const std::vector<std::vector<int>> &cost, int rows, int cols)
+{
+    int i, j, value;
+    if (rows > cols) {
+        handle.transpose = true;
+        handle.cols = rows;
+        handle.rows = cols;
+        handle.resX = handle.yMatch.get();
+        handle.resY = handle.xMatch.get();
+    } else {
+        handle.transpose = false;
+        handle.rows = rows;
+        handle.cols = cols;
+        handle.resX = handle.xMatch.get();
+        handle.resY = handle.yMatch.get();
+    }
+
+    for (i = 0; i < handle.rows; ++i) {
+        handle.xValue.get()[i] = 0;
+        handle.xMatch.get()[i] = -1;
+        for (j = 0; j < handle.cols; ++j) {
+            if (handle.transpose) {
+                value = cost[j][i];
+            } else {
+                value = cost[i][j];
+            }
+            handle.adjMat.get()[i * handle.cols + j] = value;
+            if (handle.xValue.get()[i] < value) {
+                handle.xValue.get()[i] = value;
+            }
+        }
+    }
+
+    for (i = 0; i < handle.cols; ++i) {
+        handle.yValue.get()[i] = 0;
+        handle.yMatch.get()[i] = -1;
+    }
+}
+
+static bool Match(HungarianHandle &handle, int id)
+{
+    int j, delta;
+    handle.xVisit.get()[id] = VISITED;
+    for (j = 0; j < handle.cols; ++j) {
+        if (handle.yVisit.get()[j] == VISITED) {
+            continue;
+        }
+        delta = handle.xValue.get()[id] + handle.yValue.get()[j] - handle.adjMat.get()[id * handle.cols + j];
+        if (delta == 0) {
+            handle.yVisit.get()[j] = VISITED;
+            if (handle.yMatch.get()[j] == -1 || Match(handle, handle.yMatch.get()[j])) {
+                handle.yMatch.get()[j] = id;
+                handle.xMatch.get()[id] = j;
+                return true;
+            }
+        } else if (delta < handle.slack.get()[j]) {
+            handle.slack.get()[j] = delta;
+        }
+    }
+    return false;
+}
+
+int HungarianSolve(HungarianHandle &handle, const std::vector<std::vector<int>> &cost, int rows, int cols)
+{
+    HungarianInit(handle, cost, rows, cols);
+    int i, j, delta;
+    for (i = 0; i < handle.rows; ++i) {
+        while (true) {
+            std::fill(handle.xVisit.get(), handle.xVisit.get() + handle.rows, 0);
+            std::fill(handle.yVisit.get(), handle.yVisit.get() + handle.cols, 0);
+            for (j = 0; j < handle.cols; ++j) {
+                handle.slack.get()[j] = INF;
+            }
+            if (Match(handle, i)) {
+                break;
+            }
+            delta = INF;
+            for (j = 0; j < handle.cols; ++j) {
+                if (handle.yVisit.get()[j] != VISITED && delta > handle.slack.get()[j]) {
+                    delta = handle.slack.get()[j];
+                }
+            }
+            if (delta == INF) {
+                LogDebug << "Hungarian solve is invalid!";
+                return -1;
+            }
+            for (j = 0; j < handle.rows; ++j) {
+                if (handle.xVisit.get()[j] == VISITED) {
+                    handle.xValue.get()[j] -= delta;
+                }
+            }
+            for (j = 0; j < handle.cols; ++j) {
+                if (handle.yVisit.get()[j] == VISITED) {
+                    handle.yValue.get()[j] += delta;
+                }
+            }
+        }
+    }
+    return handle.rows;
+}
diff --git a/contrib/VehicleCounting/VideoProcess/Hungarian.h b/mxVision/mxVision-referenceapps/VehicleCounting/VideoProcess/Hungarian.h
similarity index 96%
rename from contrib/VehicleCounting/VideoProcess/Hungarian.h
rename to mxVision/mxVision-referenceapps/VehicleCounting/VideoProcess/Hungarian.h
index 1b782f8c8ef9c8c7a8338c0c5b446dece2585509..36e2605171e7c269ff2c7ace144abc0211bb2377 100644
--- a/contrib/VehicleCounting/VideoProcess/Hungarian.h
+++ b/mxVision/mxVision-referenceapps/VehicleCounting/VideoProcess/Hungarian.h
@@ -1,46 +1,46 @@
-/*
- * Copyright(C) 2020. Huawei Technologies Co.,Ltd. All rights reserved.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#ifndef STREAM_PULL_SAMPLE_HUNGARIAN_H
-#define STREAM_PULL_SAMPLE_HUNGARIAN_H
-
-#include <vector>
-#include <memory>
-#include "DataType.h"
-#include "MxBase/PostProcessBases/PostProcessDataType.h"
-#include "MxBase/ErrorCode/ErrorCodes.h"
-
-struct HungarianHandle {
-    int rows;
-    int cols;
-    int max;
-    int *resX;
-    int *resY;
-    bool transpose;
-    std::shared_ptr<int> adjMat;
-    std::shared_ptr<int> xMatch;
-    std::shared_ptr<int> yMatch;
-    std::shared_ptr<int> xValue;
-    std::shared_ptr<int> yValue;
-    std::shared_ptr<int> slack;
-    std::shared_ptr<int> xVisit;
-    std::shared_ptr<int> yVisit;
-};
-
-APP_ERROR HungarianHandleInit(HungarianHandle &handle, int row, int cols);
-int HungarianSolve(HungarianHandle &handle, const std::vector<std::vector<int>> &cost, int rows, int cols);
-
-#endif // STREAM_PULL_SAMPLE_HUNGARIAN_H
+/*
+ * Copyright(C) 2020. Huawei Technologies Co.,Ltd. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef STREAM_PULL_SAMPLE_HUNGARIAN_H
+#define STREAM_PULL_SAMPLE_HUNGARIAN_H
+
+#include <vector>
+#include <memory>
+#include "DataType.h"
+#include "MxBase/PostProcessBases/PostProcessDataType.h"
+#include "MxBase/ErrorCode/ErrorCodes.h"
+
+struct HungarianHandle {
+    int rows;
+    int cols;
+    int max;
+    int *resX;
+    int *resY;
+    bool transpose;
+    std::shared_ptr<int> adjMat;
+    std::shared_ptr<int> xMatch;
+    std::shared_ptr<int> yMatch;
+    std::shared_ptr<int> xValue;
+    std::shared_ptr<int> yValue;
+    std::shared_ptr<int> slack;
+    std::shared_ptr<int> xVisit;
+    std::shared_ptr<int> yVisit;
+};
+
+APP_ERROR HungarianHandleInit(HungarianHandle &handle, int row, int cols);
+int HungarianSolve(HungarianHandle &handle, const std::vector<std::vector<int>> &cost, int rows, int cols);
+
+#endif // STREAM_PULL_SAMPLE_HUNGARIAN_H
diff --git a/contrib/VehicleCounting/VideoProcess/KalmanTracker.cpp b/mxVision/mxVision-referenceapps/VehicleCounting/VideoProcess/KalmanTracker.cpp
similarity index 97%
rename from contrib/VehicleCounting/VideoProcess/KalmanTracker.cpp
rename to mxVision/mxVision-referenceapps/VehicleCounting/VideoProcess/KalmanTracker.cpp
index 29ad7e376a6d940a868a4449bd7a8daa5a3f9015..8b6e3eb353b5449070305af445a4b9a600c18b29 100644
--- a/contrib/VehicleCounting/VideoProcess/KalmanTracker.cpp
+++ b/mxVision/mxVision-referenceapps/VehicleCounting/VideoProcess/KalmanTracker.cpp
@@ -1,138 +1,138 @@
-/*
- * Copyright(C) 2020. Huawei Technologies Co.,Ltd. All rights reserved.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#include "KalmanTracker.h"
-namespace ascendVehicleTracking {
-    namespace {
-        const int OFFSET = 2;
-        const int MULTIPLE = 2;
-    }
-
-    /*
-     * The SORT algorithm uses a linear constant velocity model,which assumes 7
-     * states, including
-     * x coordinate of bounding box center
-     * y coordinate of bounding box center
-     * area of bounding box
-     * aspect ratio of w to h
-     * velocity of x
-     * velocity of y
-     * variation rate of area
-     *
-     * The aspect ratio is considered to be unchanged, so there is no additive item
-     * for aspect ratio in the transitionMatrix
-     *
-     *
-     * Kalman filter equation step by step
-     * (1)  X(k|k-1)=AX(k-1|k-1)+BU(k)
-     * X(k|k-1) is the predicted state(statePre),X(k-1|k-1) is the k-1 statePost,A
-     * is transitionMatrix, B is controlMatrix, U(k) is control state, in SORT U(k) is 0.
-     *
-     * (2)  P(k|k-1)=AP(k-1|k-1)A'+Q
-     * P(k|k-1) is the predicted errorCovPre, P(k-1|k-1) is the k-1 errorCovPost,
-     * Q is processNoiseCov
-     *
-     * (3)  Kg(k)=P(k|k-1)H'/(HP(k|k-1))H'+R
-     * Kg(k) is the kalman gain, the ratio of estimate variance in total variance,
-     * H is the measurementMatrix,R is the measurementNoiseCov
-     *
-     * (4)  X(k|k)=X(k|k-1)+Kg(k)(Z(k)-HX(k|k-1))
-     * X(k|k) is the k statePost, Z(k) is the measurement of K, in SORT Z(k) is
-     * the detection result of k
-     *
-     * (5)  P(k|k)=(1-Kg(k)H)P(k|k-1)
-     * P(k|k) is the errorCovPost
-     */
-    void KalmanTracker::CvKalmanInit(MxBase::ObjectInfo initRect)
-    {
-        const int stateDim = 7;
-        const int measureDim = 4;
-        cvkalmanfilter_ = cv::KalmanFilter(stateDim, measureDim, 0); // zero control
-        measurement_ = cv::Mat::zeros(measureDim, 1, CV_32F);        // 4 measurements, Z(k), according to detection results
-        // A, will not be updated
-        cvkalmanfilter_.transitionMatrix = (cv::Mat_<float>(stateDim, stateDim) << 1, 0, 0, 0, 1, 0, 0, 0, 1,
-         0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 
-         0, 0, 0, 0, 0, 1);
-        cvkalmanfilter_.measurementMatrix =(cv::Mat_<float>(measureDim, stateDim) << 1, 0, 0, 0, 0, 0, 0, 0, 1, 
-        0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0 );
-        cv::setIdentity(cvkalmanfilter_.measurementMatrix);                          // H, will not be updated
-        cv::setIdentity(cvkalmanfilter_.processNoiseCov, cv::Scalar::all(1e-2));     // Q, will not be updated
-        cv::setIdentity(cvkalmanfilter_.measurementNoiseCov, cv::Scalar::all(1e-1)); // R, will bot be updated
-        cv::setIdentity(cvkalmanfilter_.errorCovPost, cv::Scalar::all(1));           // P(k-1|k-1), will be updated
-
-        // initialize state vector with bounding box in
-        // [center_x,center_y,area,ratio]
-        // style, the velocity is 0
-        // X(k-1|k-1)
-        cvkalmanfilter_.statePost.at<float>(0, 0) = initRect.x0 + (initRect.x1 - initRect.x0) / MULTIPLE;
-        cvkalmanfilter_.statePost.at<float>(1, 0) = initRect.y0 + (initRect.y1 - initRect.y0) / MULTIPLE;
-        cvkalmanfilter_.statePost.at<float>(OFFSET, 0) = (initRect.x1 - initRect.x0) * (initRect.y1 - initRect.y0);
-        cvkalmanfilter_.statePost.at<float>(OFFSET + 1, 0) = (initRect.x1 - initRect.x0) / (initRect.y1 - initRect.y0);
-    }
-
-    // Predict the bounding box.
-    MxBase::ObjectInfo KalmanTracker::Predict()
-    {
-        // predict
-        // return X(k|k-1)=AX(k-1|k-1), and update
-        // P(k|k-1) <- AP(k-1|k-1)A'+Q
-        MxBase::ObjectInfo detectInfo = {};
-        cv::Mat predictState = cvkalmanfilter_.predict();
-        float *pData = (float *)(predictState.data);
-        float w = sqrt((*(pData + OFFSET)) * (*(pData + OFFSET + 1)));
-        if (w < DBL_EPSILON) {
-            detectInfo.x0 = 0;
-            detectInfo.y0 = 0;
-            detectInfo.x1 = 0;
-            detectInfo.y1 = 0;
-            detectInfo.classId = 0;
-            return detectInfo;
-        }
-        if(w == 0){
-            return MxBase::ObjectInfo{};
-        }
-        float h = (*(pData + OFFSET)) / w;
-        float x = (*pData) - w / MULTIPLE;
-        float y = (*(pData + 1)) - h / MULTIPLE;
-        if (x < 0 && (*pData) > 0) {
-            x = 0;
-        }
-        if (y < 0 && (*(pData + 1)) > 0) {
-            y = 0;
-        }
-        detectInfo.x0 = x;
-        detectInfo.y0 = y;
-        detectInfo.x1 = x+w;
-        detectInfo.y1 = y+h;
-        return detectInfo;
-    }
-
-    // Update the state using observed bounding box
-    void KalmanTracker::Update(MxBase::ObjectInfo stateMat)
-    {
-        // measurement_, update Z(k)
-        float *pData = (float *)(measurement_.data);
-        *pData = stateMat.x0 + (stateMat.x1-stateMat.x0) / MULTIPLE;
-        *(pData + 1) = stateMat.y0 + (stateMat.y1-stateMat.y0) / MULTIPLE;
-        *(pData + OFFSET) = (stateMat.x1-stateMat.x0) * (stateMat.y1-stateMat.y0);
-        *(pData + OFFSET + 1) = (stateMat.x1-stateMat.x0) / (stateMat.y1-stateMat.y0);
-        // update, do the following steps:
-        // Kg(k): P(k|k-1)H'/(HP(k|k-1))H'+R
-        // X(k|k): X(k|k-1)+Kg(k)(Z(k)-HX(k|k-1))
-        // P(k|k): (1-Kg(k)H)P(k|k-1)
-        cvkalmanfilter_.correct(measurement_);
-    }
-} // namespace
+/*
+ * Copyright(C) 2020. Huawei Technologies Co.,Ltd. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "KalmanTracker.h"
+namespace ascendVehicleTracking {
+    namespace {
+        const int OFFSET = 2;
+        const int MULTIPLE = 2;
+    }
+
+    /*
+     * The SORT algorithm uses a linear constant velocity model,which assumes 7
+     * states, including
+     * x coordinate of bounding box center
+     * y coordinate of bounding box center
+     * area of bounding box
+     * aspect ratio of w to h
+     * velocity of x
+     * velocity of y
+     * variation rate of area
+     *
+     * The aspect ratio is considered to be unchanged, so there is no additive item
+     * for aspect ratio in the transitionMatrix
+     *
+     *
+     * Kalman filter equation step by step
+     * (1)  X(k|k-1)=AX(k-1|k-1)+BU(k)
+     * X(k|k-1) is the predicted state(statePre),X(k-1|k-1) is the k-1 statePost,A
+     * is transitionMatrix, B is controlMatrix, U(k) is control state, in SORT U(k) is 0.
+     *
+     * (2)  P(k|k-1)=AP(k-1|k-1)A'+Q
+     * P(k|k-1) is the predicted errorCovPre, P(k-1|k-1) is the k-1 errorCovPost,
+     * Q is processNoiseCov
+     *
+     * (3)  Kg(k)=P(k|k-1)H'/(HP(k|k-1))H'+R
+     * Kg(k) is the kalman gain, the ratio of estimate variance in total variance,
+     * H is the measurementMatrix,R is the measurementNoiseCov
+     *
+     * (4)  X(k|k)=X(k|k-1)+Kg(k)(Z(k)-HX(k|k-1))
+     * X(k|k) is the k statePost, Z(k) is the measurement of K, in SORT Z(k) is
+     * the detection result of k
+     *
+     * (5)  P(k|k)=(1-Kg(k)H)P(k|k-1)
+     * P(k|k) is the errorCovPost
+     */
+    void KalmanTracker::CvKalmanInit(MxBase::ObjectInfo initRect)
+    {
+        const int stateDim = 7;
+        const int measureDim = 4;
+        cvkalmanfilter_ = cv::KalmanFilter(stateDim, measureDim, 0); // zero control
+        measurement_ = cv::Mat::zeros(measureDim, 1, CV_32F);        // 4 measurements, Z(k), according to detection results
+        // A, will not be updated
+        cvkalmanfilter_.transitionMatrix = (cv::Mat_<float>(stateDim, stateDim) << 1, 0, 0, 0, 1, 0, 0, 0, 1,
+         0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 
+         0, 0, 0, 0, 0, 1);
+        cvkalmanfilter_.measurementMatrix =(cv::Mat_<float>(measureDim, stateDim) << 1, 0, 0, 0, 0, 0, 0, 0, 1, 
+        0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0 );
+        cv::setIdentity(cvkalmanfilter_.measurementMatrix);                          // H, will not be updated
+        cv::setIdentity(cvkalmanfilter_.processNoiseCov, cv::Scalar::all(1e-2));     // Q, will not be updated
+        cv::setIdentity(cvkalmanfilter_.measurementNoiseCov, cv::Scalar::all(1e-1)); // R, will bot be updated
+        cv::setIdentity(cvkalmanfilter_.errorCovPost, cv::Scalar::all(1));           // P(k-1|k-1), will be updated
+
+        // initialize state vector with bounding box in
+        // [center_x,center_y,area,ratio]
+        // style, the velocity is 0
+        // X(k-1|k-1)
+        cvkalmanfilter_.statePost.at<float>(0, 0) = initRect.x0 + (initRect.x1 - initRect.x0) / MULTIPLE;
+        cvkalmanfilter_.statePost.at<float>(1, 0) = initRect.y0 + (initRect.y1 - initRect.y0) / MULTIPLE;
+        cvkalmanfilter_.statePost.at<float>(OFFSET, 0) = (initRect.x1 - initRect.x0) * (initRect.y1 - initRect.y0);
+        cvkalmanfilter_.statePost.at<float>(OFFSET + 1, 0) = (initRect.x1 - initRect.x0) / (initRect.y1 - initRect.y0);
+    }
+
+    // Predict the bounding box.
+    MxBase::ObjectInfo KalmanTracker::Predict()
+    {
+        // predict
+        // return X(k|k-1)=AX(k-1|k-1), and update
+        // P(k|k-1) <- AP(k-1|k-1)A'+Q
+        MxBase::ObjectInfo detectInfo = {};
+        cv::Mat predictState = cvkalmanfilter_.predict();
+        float *pData = (float *)(predictState.data);
+        float w = sqrt((*(pData + OFFSET)) * (*(pData + OFFSET + 1)));
+        if (w < DBL_EPSILON) {
+            detectInfo.x0 = 0;
+            detectInfo.y0 = 0;
+            detectInfo.x1 = 0;
+            detectInfo.y1 = 0;
+            detectInfo.classId = 0;
+            return detectInfo;
+        }
+        if(w == 0){
+            return MxBase::ObjectInfo{};
+        }
+        float h = (*(pData + OFFSET)) / w;
+        float x = (*pData) - w / MULTIPLE;
+        float y = (*(pData + 1)) - h / MULTIPLE;
+        if (x < 0 && (*pData) > 0) {
+            x = 0;
+        }
+        if (y < 0 && (*(pData + 1)) > 0) {
+            y = 0;
+        }
+        detectInfo.x0 = x;
+        detectInfo.y0 = y;
+        detectInfo.x1 = x+w;
+        detectInfo.y1 = y+h;
+        return detectInfo;
+    }
+
+    // Update the state using observed bounding box
+    void KalmanTracker::Update(MxBase::ObjectInfo stateMat)
+    {
+        // measurement_, update Z(k)
+        float *pData = (float *)(measurement_.data);
+        *pData = stateMat.x0 + (stateMat.x1-stateMat.x0) / MULTIPLE;
+        *(pData + 1) = stateMat.y0 + (stateMat.y1-stateMat.y0) / MULTIPLE;
+        *(pData + OFFSET) = (stateMat.x1-stateMat.x0) * (stateMat.y1-stateMat.y0);
+        *(pData + OFFSET + 1) = (stateMat.x1-stateMat.x0) / (stateMat.y1-stateMat.y0);
+        // update, do the following steps:
+        // Kg(k): P(k|k-1)H'/(HP(k|k-1))H'+R
+        // X(k|k): X(k|k-1)+Kg(k)(Z(k)-HX(k|k-1))
+        // P(k|k): (1-Kg(k)H)P(k|k-1)
+        cvkalmanfilter_.correct(measurement_);
+    }
+} // namespace
diff --git a/contrib/VehicleCounting/VideoProcess/KalmanTracker.h b/mxVision/mxVision-referenceapps/VehicleCounting/VideoProcess/KalmanTracker.h
similarity index 97%
rename from contrib/VehicleCounting/VideoProcess/KalmanTracker.h
rename to mxVision/mxVision-referenceapps/VehicleCounting/VideoProcess/KalmanTracker.h
index 402abcecc92d91fa92ab4a8c5d06502578abdf35..b6579f85263b28f6a8753c2cdfbc19fa5fc12df5 100644
--- a/contrib/VehicleCounting/VideoProcess/KalmanTracker.h
+++ b/mxVision/mxVision-referenceapps/VehicleCounting/VideoProcess/KalmanTracker.h
@@ -1,39 +1,39 @@
-/*
- * Copyright(C) 2020. Huawei Technologies Co.,Ltd. All rights reserved.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#ifndef STREAM_PULL_SAMPLE_KALMANTRACKER_H
-#define STREAM_PULL_SAMPLE_KALMANTRACKER_H
-
-#include "opencv2/highgui/highgui.hpp"
-#include "opencv2/video/tracking.hpp"
-#include "DataType.h"
-#include "MxBase/PostProcessBases/PostProcessDataType.h"
-
-namespace ascendVehicleTracking {
-class KalmanTracker {
-public:
-    KalmanTracker() {}
-    ~KalmanTracker() {}
-    void CvKalmanInit(MxBase::ObjectInfo initRect);
-    MxBase::ObjectInfo Predict();
-    void Update(MxBase::ObjectInfo stateMat);
-private:
-    cv::KalmanFilter cvkalmanfilter_ = {};
-    cv::Mat measurement_ = {};
-};
-} // namesapce ascendVehicleTracking
-
-#endif // STREAM_PULL_SAMPLE_KALMANTRACKER_H
+/*
+ * Copyright(C) 2020. Huawei Technologies Co.,Ltd. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef STREAM_PULL_SAMPLE_KALMANTRACKER_H
+#define STREAM_PULL_SAMPLE_KALMANTRACKER_H
+
+#include "opencv2/highgui/highgui.hpp"
+#include "opencv2/video/tracking.hpp"
+#include "DataType.h"
+#include "MxBase/PostProcessBases/PostProcessDataType.h"
+
+namespace ascendVehicleTracking {
+class KalmanTracker {
+public:
+    KalmanTracker() {}
+    ~KalmanTracker() {}
+    void CvKalmanInit(MxBase::ObjectInfo initRect);
+    MxBase::ObjectInfo Predict();
+    void Update(MxBase::ObjectInfo stateMat);
+private:
+    cv::KalmanFilter cvkalmanfilter_ = {};
+    cv::Mat measurement_ = {};
+};
+} // namesapce ascendVehicleTracking
+
+#endif // STREAM_PULL_SAMPLE_KALMANTRACKER_H
diff --git a/contrib/VehicleCounting/VideoProcess/MOTConnection.cpp b/mxVision/mxVision-referenceapps/VehicleCounting/VideoProcess/MOTConnection.cpp
similarity index 100%
rename from contrib/VehicleCounting/VideoProcess/MOTConnection.cpp
rename to mxVision/mxVision-referenceapps/VehicleCounting/VideoProcess/MOTConnection.cpp
diff --git a/contrib/VehicleCounting/VideoProcess/MOTConnection.h b/mxVision/mxVision-referenceapps/VehicleCounting/VideoProcess/MOTConnection.h
similarity index 97%
rename from contrib/VehicleCounting/VideoProcess/MOTConnection.h
rename to mxVision/mxVision-referenceapps/VehicleCounting/VideoProcess/MOTConnection.h
index cc0a401dc5b622eaf307c352cecc360732e3033f..63948ab7189392243273e527a9cb4c953000d5fa 100644
--- a/contrib/VehicleCounting/VideoProcess/MOTConnection.h
+++ b/mxVision/mxVision-referenceapps/VehicleCounting/VideoProcess/MOTConnection.h
@@ -1,78 +1,78 @@
-/*
- * Copyright(C) 2020. Huawei Technologies Co.,Ltd. All rights reserved.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#ifndef STREAM_PULL_SAMPLE_MOTCONNECTION_H
-#define STREAM_PULL_SAMPLE_MOTCONNECTION_H
-
-#include <thread>
-#include <list>
-#include <utility>
-#include "KalmanTracker.h"
-#include "Hungarian.h"
-#include "DataType.h"
-#include "MxBase/ErrorCode/ErrorCodes.h"
-#include "MxBase/DvppWrapper/DvppWrapper.h"
-#include "MxBase/MemoryHelper/MemoryHelper.h"
-#include "MxBase/DeviceManager/DeviceManager.h"
-#include "MxBase/Tensor/TensorBase/TensorBase.h"
-#include "MxBase/PostProcessBases/PostProcessDataType.h"
-#include "ObjectPostProcessors/Yolov3PostProcess.h"
-
-namespace ascendVehicleTracking {
-struct TraceLet {
-    TraceInfo info = {};
-    int32_t lostAge = 0;
-    KalmanTracker kalman;
-    std::list<std::pair<DataBuffer, float>> shortFeatureQueue;
-    MxBase::ObjectInfo detectInfo = {};
-};
-
-class MOTConnection {
-public:
-    APP_ERROR ProcessSort(std::vector<std::vector<MxBase::ObjectInfo>> &objInfos);
-    APP_ERROR GettrackResult(std::vector<MxBase::ObjectInfo> &objInfos_);
-
-private:
-    double trackThreshold_ = 0.3;
-    double kIOU_ = 1.0;
-    int32_t method_ = 1;
-    int32_t lostThreshold_ = 3;
-    uint32_t maxNumberFeature_ = 0;
-    int32_t generatedId_ = 0;
-    std::vector<TraceLet> traceList_ = {};
-
-private:
-
-    void FilterLowThreshold(const HungarianHandle &hungarianHandleObj, const std::vector<std::vector<int>> &disMatrix,
-                                std::vector<cv::Point> &matchedTracedDetected, std::vector<bool> &detectVehicleFlagVec);
-
-    void UpdateUnmatchedTraceLet(const std::vector<std::vector<MxBase::ObjectInfo>> &objInfos);
-
-    void UpdateMatchedTraceLet(const std::vector<cv::Point> &matchedTracedDetected,
-                                   std::vector<std::vector<MxBase::ObjectInfo>> &objInfos);
-
-    void AddNewDetectedVehicle(std::vector<MxBase::ObjectInfo> &unmatchedVehicleObjectQueue);
-
-    void UpdateTraceLetAndFrame(const std::vector<cv::Point> &matchedTracedDetected,
-                                std::vector<std::vector<MxBase::ObjectInfo>> &objInfos, std::vector<MxBase::ObjectInfo> &unmatchedVehicleObjectQueue);
-
-    void TrackObjectPredict();
-    void TrackObjectUpdate(const std::vector<std::vector<MxBase::ObjectInfo>> &objInfos,
-                           std::vector<cv::Point> &matchedTracedDetected, std::vector<MxBase::ObjectInfo> &unmatchedVehicleObjectQueue);
-};
-} // namespace ascendVehicleTracking
-
-#endif // STREAM_PULL_SAMPLE_MOTCONNECTION_H
+/*
+ * Copyright(C) 2020. Huawei Technologies Co.,Ltd. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef STREAM_PULL_SAMPLE_MOTCONNECTION_H
+#define STREAM_PULL_SAMPLE_MOTCONNECTION_H
+
+#include <thread>
+#include <list>
+#include <utility>
+#include "KalmanTracker.h"
+#include "Hungarian.h"
+#include "DataType.h"
+#include "MxBase/ErrorCode/ErrorCodes.h"
+#include "MxBase/DvppWrapper/DvppWrapper.h"
+#include "MxBase/MemoryHelper/MemoryHelper.h"
+#include "MxBase/DeviceManager/DeviceManager.h"
+#include "MxBase/Tensor/TensorBase/TensorBase.h"
+#include "MxBase/PostProcessBases/PostProcessDataType.h"
+#include "ObjectPostProcessors/Yolov3PostProcess.h"
+
+namespace ascendVehicleTracking {
+struct TraceLet {
+    TraceInfo info = {};
+    int32_t lostAge = 0;
+    KalmanTracker kalman;
+    std::list<std::pair<DataBuffer, float>> shortFeatureQueue;
+    MxBase::ObjectInfo detectInfo = {};
+};
+
+class MOTConnection {
+public:
+    APP_ERROR ProcessSort(std::vector<std::vector<MxBase::ObjectInfo>> &objInfos);
+    APP_ERROR GettrackResult(std::vector<MxBase::ObjectInfo> &objInfos_);
+
+private:
+    double trackThreshold_ = 0.3;
+    double kIOU_ = 1.0;
+    int32_t method_ = 1;
+    int32_t lostThreshold_ = 3;
+    uint32_t maxNumberFeature_ = 0;
+    int32_t generatedId_ = 0;
+    std::vector<TraceLet> traceList_ = {};
+
+private:
+
+    void FilterLowThreshold(const HungarianHandle &hungarianHandleObj, const std::vector<std::vector<int>> &disMatrix,
+                                std::vector<cv::Point> &matchedTracedDetected, std::vector<bool> &detectVehicleFlagVec);
+
+    void UpdateUnmatchedTraceLet(const std::vector<std::vector<MxBase::ObjectInfo>> &objInfos);
+
+    void UpdateMatchedTraceLet(const std::vector<cv::Point> &matchedTracedDetected,
+                                   std::vector<std::vector<MxBase::ObjectInfo>> &objInfos);
+
+    void AddNewDetectedVehicle(std::vector<MxBase::ObjectInfo> &unmatchedVehicleObjectQueue);
+
+    void UpdateTraceLetAndFrame(const std::vector<cv::Point> &matchedTracedDetected,
+                                std::vector<std::vector<MxBase::ObjectInfo>> &objInfos, std::vector<MxBase::ObjectInfo> &unmatchedVehicleObjectQueue);
+
+    void TrackObjectPredict();
+    void TrackObjectUpdate(const std::vector<std::vector<MxBase::ObjectInfo>> &objInfos,
+                           std::vector<cv::Point> &matchedTracedDetected, std::vector<MxBase::ObjectInfo> &unmatchedVehicleObjectQueue);
+};
+} // namespace ascendVehicleTracking
+
+#endif // STREAM_PULL_SAMPLE_MOTCONNECTION_H
diff --git a/contrib/VehicleCounting/VideoProcess/VideoProcess.cpp b/mxVision/mxVision-referenceapps/VehicleCounting/VideoProcess/VideoProcess.cpp
similarity index 100%
rename from contrib/VehicleCounting/VideoProcess/VideoProcess.cpp
rename to mxVision/mxVision-referenceapps/VehicleCounting/VideoProcess/VideoProcess.cpp
diff --git a/contrib/VehicleCounting/VideoProcess/VideoProcess.h b/mxVision/mxVision-referenceapps/VehicleCounting/VideoProcess/VideoProcess.h
similarity index 100%
rename from contrib/VehicleCounting/VideoProcess/VideoProcess.h
rename to mxVision/mxVision-referenceapps/VehicleCounting/VideoProcess/VideoProcess.h
diff --git a/contrib/VehicleCounting/Yolov4Detection/Yolov4Detection.cpp b/mxVision/mxVision-referenceapps/VehicleCounting/Yolov4Detection/Yolov4Detection.cpp
similarity index 100%
rename from contrib/VehicleCounting/Yolov4Detection/Yolov4Detection.cpp
rename to mxVision/mxVision-referenceapps/VehicleCounting/Yolov4Detection/Yolov4Detection.cpp
diff --git a/contrib/VehicleCounting/Yolov4Detection/Yolov4Detection.h b/mxVision/mxVision-referenceapps/VehicleCounting/Yolov4Detection/Yolov4Detection.h
similarity index 100%
rename from contrib/VehicleCounting/Yolov4Detection/Yolov4Detection.h
rename to mxVision/mxVision-referenceapps/VehicleCounting/Yolov4Detection/Yolov4Detection.h
diff --git a/contrib/VehicleCounting/result/.keep b/mxVision/mxVision-referenceapps/VehicleCounting/data/.keep
similarity index 100%
rename from contrib/VehicleCounting/result/.keep
rename to mxVision/mxVision-referenceapps/VehicleCounting/data/.keep
diff --git a/contrib/VehicleCounting/img/process.JPG b/mxVision/mxVision-referenceapps/VehicleCounting/img/process.JPG
similarity index 100%
rename from contrib/VehicleCounting/img/process.JPG
rename to mxVision/mxVision-referenceapps/VehicleCounting/img/process.JPG
diff --git a/contrib/VehicleCounting/main.cpp b/mxVision/mxVision-referenceapps/VehicleCounting/main.cpp
similarity index 100%
rename from contrib/VehicleCounting/main.cpp
rename to mxVision/mxVision-referenceapps/VehicleCounting/main.cpp
diff --git a/contrib/VehicleCounting/model/aipp_yolov3_416_416.config b/mxVision/mxVision-referenceapps/VehicleCounting/model/aipp_yolov3_416_416.config
similarity index 100%
rename from contrib/VehicleCounting/model/aipp_yolov3_416_416.config
rename to mxVision/mxVision-referenceapps/VehicleCounting/model/aipp_yolov3_416_416.config
diff --git a/contrib/VehicleCounting/model/aipp_yolov4_608_608.config b/mxVision/mxVision-referenceapps/VehicleCounting/model/aipp_yolov4_608_608.config
similarity index 100%
rename from contrib/VehicleCounting/model/aipp_yolov4_608_608.config
rename to mxVision/mxVision-referenceapps/VehicleCounting/model/aipp_yolov4_608_608.config
diff --git a/contrib/VehicleCounting/model/coco.names b/mxVision/mxVision-referenceapps/VehicleCounting/model/coco.names
similarity index 100%
rename from contrib/VehicleCounting/model/coco.names
rename to mxVision/mxVision-referenceapps/VehicleCounting/model/coco.names
diff --git a/contrib/VehicleCounting/params.config b/mxVision/mxVision-referenceapps/VehicleCounting/params.config
similarity index 100%
rename from contrib/VehicleCounting/params.config
rename to mxVision/mxVision-referenceapps/VehicleCounting/params.config
diff --git a/contrib/VehicleCounting/result1/.keep b/mxVision/mxVision-referenceapps/VehicleCounting/result/.keep
similarity index 100%
rename from contrib/VehicleCounting/result1/.keep
rename to mxVision/mxVision-referenceapps/VehicleCounting/result/.keep
diff --git a/contrib/VehicleRetrogradeRecognition/.keep b/mxVision/mxVision-referenceapps/VehicleCounting/result1/.keep
similarity index 100%
rename from contrib/VehicleRetrogradeRecognition/.keep
rename to mxVision/mxVision-referenceapps/VehicleCounting/result1/.keep
diff --git a/contrib/VehicleIdentification/README.md b/mxVision/mxVision-referenceapps/VehicleIdentification/README.md
similarity index 100%
rename from contrib/VehicleIdentification/README.md
rename to mxVision/mxVision-referenceapps/VehicleIdentification/README.md
diff --git a/contrib/VehicleIdentification/build.sh b/mxVision/mxVision-referenceapps/VehicleIdentification/build.sh
similarity index 100%
rename from contrib/VehicleIdentification/build.sh
rename to mxVision/mxVision-referenceapps/VehicleIdentification/build.sh
diff --git a/contrib/VehicleIdentification/img/pipeline.png b/mxVision/mxVision-referenceapps/VehicleIdentification/img/pipeline.png
similarity index 100%
rename from contrib/VehicleIdentification/img/pipeline.png
rename to mxVision/mxVision-referenceapps/VehicleIdentification/img/pipeline.png
diff --git a/contrib/VehicleIdentification/img/process.png b/mxVision/mxVision-referenceapps/VehicleIdentification/img/process.png
similarity index 100%
rename from contrib/VehicleIdentification/img/process.png
rename to mxVision/mxVision-referenceapps/VehicleIdentification/img/process.png
diff --git a/contrib/VehicleIdentification/main.py b/mxVision/mxVision-referenceapps/VehicleIdentification/main.py
similarity index 100%
rename from contrib/VehicleIdentification/main.py
rename to mxVision/mxVision-referenceapps/VehicleIdentification/main.py
diff --git a/contrib/VehicleIdentification/models/googlenet/car.names b/mxVision/mxVision-referenceapps/VehicleIdentification/models/googlenet/car.names
similarity index 100%
rename from contrib/VehicleIdentification/models/googlenet/car.names
rename to mxVision/mxVision-referenceapps/VehicleIdentification/models/googlenet/car.names
diff --git a/contrib/VehicleIdentification/models/googlenet/insert_op.cfg b/mxVision/mxVision-referenceapps/VehicleIdentification/models/googlenet/insert_op.cfg
similarity index 100%
rename from contrib/VehicleIdentification/models/googlenet/insert_op.cfg
rename to mxVision/mxVision-referenceapps/VehicleIdentification/models/googlenet/insert_op.cfg
diff --git a/contrib/VehicleIdentification/models/googlenet/updatemodel.py b/mxVision/mxVision-referenceapps/VehicleIdentification/models/googlenet/updatemodel.py
similarity index 100%
rename from contrib/VehicleIdentification/models/googlenet/updatemodel.py
rename to mxVision/mxVision-referenceapps/VehicleIdentification/models/googlenet/updatemodel.py
diff --git a/contrib/VehicleIdentification/models/googlenet/vehiclepostprocess.cfg b/mxVision/mxVision-referenceapps/VehicleIdentification/models/googlenet/vehiclepostprocess.cfg
similarity index 100%
rename from contrib/VehicleIdentification/models/googlenet/vehiclepostprocess.cfg
rename to mxVision/mxVision-referenceapps/VehicleIdentification/models/googlenet/vehiclepostprocess.cfg
diff --git a/contrib/VehicleIdentification/models/yolo/aipp_yolov3_416_416.aippconfig b/mxVision/mxVision-referenceapps/VehicleIdentification/models/yolo/aipp_yolov3_416_416.aippconfig
similarity index 100%
rename from contrib/VehicleIdentification/models/yolo/aipp_yolov3_416_416.aippconfig
rename to mxVision/mxVision-referenceapps/VehicleIdentification/models/yolo/aipp_yolov3_416_416.aippconfig
diff --git a/mxVision/AsyncInfer/model/yolov3/coco.names b/mxVision/mxVision-referenceapps/VehicleIdentification/models/yolo/coco.names
similarity index 100%
rename from mxVision/AsyncInfer/model/yolov3/coco.names
rename to mxVision/mxVision-referenceapps/VehicleIdentification/models/yolo/coco.names
diff --git a/contrib/VehicleIdentification/models/yolo/yolov3_tf_bs1_fp16.cfg b/mxVision/mxVision-referenceapps/VehicleIdentification/models/yolo/yolov3_tf_bs1_fp16.cfg
similarity index 100%
rename from contrib/VehicleIdentification/models/yolo/yolov3_tf_bs1_fp16.cfg
rename to mxVision/mxVision-referenceapps/VehicleIdentification/models/yolo/yolov3_tf_bs1_fp16.cfg
diff --git a/contrib/VehicleIdentification/pipeline/identification.pipeline b/mxVision/mxVision-referenceapps/VehicleIdentification/pipeline/identification.pipeline
similarity index 100%
rename from contrib/VehicleIdentification/pipeline/identification.pipeline
rename to mxVision/mxVision-referenceapps/VehicleIdentification/pipeline/identification.pipeline
diff --git a/contrib/VehicleIdentification/vehiclePostProcess/CMakeLists.txt b/mxVision/mxVision-referenceapps/VehicleIdentification/vehiclePostProcess/CMakeLists.txt
similarity index 100%
rename from contrib/VehicleIdentification/vehiclePostProcess/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/VehicleIdentification/vehiclePostProcess/CMakeLists.txt
diff --git a/contrib/VehicleIdentification/vehiclePostProcess/VehiclePostProcess.cpp b/mxVision/mxVision-referenceapps/VehicleIdentification/vehiclePostProcess/VehiclePostProcess.cpp
similarity index 100%
rename from contrib/VehicleIdentification/vehiclePostProcess/VehiclePostProcess.cpp
rename to mxVision/mxVision-referenceapps/VehicleIdentification/vehiclePostProcess/VehiclePostProcess.cpp
diff --git a/contrib/VehicleIdentification/vehiclePostProcess/VehiclePostProcess.h b/mxVision/mxVision-referenceapps/VehicleIdentification/vehiclePostProcess/VehiclePostProcess.h
similarity index 100%
rename from contrib/VehicleIdentification/vehiclePostProcess/VehiclePostProcess.h
rename to mxVision/mxVision-referenceapps/VehicleIdentification/vehiclePostProcess/VehiclePostProcess.h
diff --git a/contrib/VehicleIdentification/vehiclePostProcess/build.sh b/mxVision/mxVision-referenceapps/VehicleIdentification/vehiclePostProcess/build.sh
similarity index 100%
rename from contrib/VehicleIdentification/vehiclePostProcess/build.sh
rename to mxVision/mxVision-referenceapps/VehicleIdentification/vehiclePostProcess/build.sh
diff --git a/contrib/VideoGestureRecognition/.keep b/mxVision/mxVision-referenceapps/VehicleRetrogradeRecognition/.keep
similarity index 100%
rename from contrib/VideoGestureRecognition/.keep
rename to mxVision/mxVision-referenceapps/VehicleRetrogradeRecognition/.keep
diff --git a/contrib/VehicleRetrogradeRecognition/CMakeLists.txt b/mxVision/mxVision-referenceapps/VehicleRetrogradeRecognition/CMakeLists.txt
similarity index 96%
rename from contrib/VehicleRetrogradeRecognition/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/VehicleRetrogradeRecognition/CMakeLists.txt
index 3d62f649598eac6c6c6b8f60fc3f69d2e22ea999..245702106f2d0bf7878f6a0d324fcad80e9d905d 100644
--- a/contrib/VehicleRetrogradeRecognition/CMakeLists.txt
+++ b/mxVision/mxVision-referenceapps/VehicleRetrogradeRecognition/CMakeLists.txt
@@ -1,49 +1,49 @@
-# Copyright (c) Huawei Technologies Co., Ltd. 2019-2021. All rights reserved.
-
-# CMake lowest version requirement
-cmake_minimum_required(VERSION 3.5.0)
-
-# project information
-project(VehicleRetrogradeRecognition)   
-
-set(MX_SDK_HOME "$ENV{MX_SDK_HOME}")   
-
-if (NOT DEFINED ENV{MX_SDK_HOME})      
-    string(REGEX REPLACE "(.*)/(.*)/(.*)/(.*)" "\\1" MX_SDK_HOME  ${CMAKE_CURRENT_SOURCE_DIR})
-    message(STATUS "set default MX_SDK_HOME: ${MX_SDK_HOME}")
-else ()
-    message(STATUS "env MX_SDK_HOME: ${MX_SDK_HOME}")
-endif()
-
-# Compile options
-add_definitions(-D_GLIBCXX_USE_CXX11_ABI=0)  
-add_definitions(-Dgoogle=mindxsdk_private)      
-add_compile_options(-std=c++11 -fPIC -fstack-protector-all -Wall)   
-
-set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR})       
-set(CMAKE_CXX_FLAGS_DEBUG "-g")                                      
-set(CMAKE_EXE_LINKER_FLAGS "${CMAKE_EXE_LINKER_FLAGS} -Wl,-z,relro,-z,now,-z,noexecstack -pie")
-
-# Header path  
-include_directories(
-    ${MX_SDK_HOME}/include/     
-    ${MX_SDK_HOME}/opensource/include/
-)
-
-# add host lib path   
-link_directories(
-    ${MX_SDK_HOME}/lib/
-    ${MX_SDK_HOME}/opensource/lib/
-    ${MX_SDK_HOME}/opensource/lib64/
-)
-link_libraries(pthread)
-add_executable(main main.cpp)
-
-target_link_libraries(main glog mxbase plugintoolkit mxpidatatype streammanager mindxsdk_protobuf)
-
-install(TARGETS main DESTINATION ${CMAKE_RUNTIME_OUTPUT_DIRECTORY})
-
-
-
-
-
+# Copyright (c) Huawei Technologies Co., Ltd. 2019-2021. All rights reserved.
+
+# CMake lowest version requirement
+cmake_minimum_required(VERSION 3.5.0)
+
+# project information
+project(VehicleRetrogradeRecognition)   
+
+set(MX_SDK_HOME "$ENV{MX_SDK_HOME}")   
+
+if (NOT DEFINED ENV{MX_SDK_HOME})      
+    string(REGEX REPLACE "(.*)/(.*)/(.*)/(.*)" "\\1" MX_SDK_HOME  ${CMAKE_CURRENT_SOURCE_DIR})
+    message(STATUS "set default MX_SDK_HOME: ${MX_SDK_HOME}")
+else ()
+    message(STATUS "env MX_SDK_HOME: ${MX_SDK_HOME}")
+endif()
+
+# Compile options
+add_definitions(-D_GLIBCXX_USE_CXX11_ABI=0)  
+add_definitions(-Dgoogle=mindxsdk_private)      
+add_compile_options(-std=c++11 -fPIC -fstack-protector-all -Wall)   
+
+set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR})       
+set(CMAKE_CXX_FLAGS_DEBUG "-g")                                      
+set(CMAKE_EXE_LINKER_FLAGS "${CMAKE_EXE_LINKER_FLAGS} -Wl,-z,relro,-z,now,-z,noexecstack -pie")
+
+# Header path  
+include_directories(
+    ${MX_SDK_HOME}/include/     
+    ${MX_SDK_HOME}/opensource/include/
+)
+
+# add host lib path   
+link_directories(
+    ${MX_SDK_HOME}/lib/
+    ${MX_SDK_HOME}/opensource/lib/
+    ${MX_SDK_HOME}/opensource/lib64/
+)
+link_libraries(pthread)
+add_executable(main main.cpp)
+
+target_link_libraries(main glog mxbase plugintoolkit mxpidatatype streammanager mindxsdk_protobuf)
+
+install(TARGETS main DESTINATION ${CMAKE_RUNTIME_OUTPUT_DIRECTORY})
+
+
+
+
+
diff --git a/contrib/VehicleRetrogradeRecognition/README.md b/mxVision/mxVision-referenceapps/VehicleRetrogradeRecognition/README.md
similarity index 98%
rename from contrib/VehicleRetrogradeRecognition/README.md
rename to mxVision/mxVision-referenceapps/VehicleRetrogradeRecognition/README.md
index c6a57cd4ccffa8f562d13adb5e310b36438f3c59..a07987aa79a4114d6e3c4f51a0ba1d80221db1b5 100644
--- a/contrib/VehicleRetrogradeRecognition/README.md
+++ b/mxVision/mxVision-referenceapps/VehicleRetrogradeRecognition/README.md
@@ -1,262 +1,262 @@
-# VehicleRetrogradeRecognition交通逆行识别
-
-## 1 介绍
-
-VehicleRetrogradeRecognition交通逆行识别后处理插件基于MindXSDK开发，在晟腾芯片上进行目标检测和跟踪，可以对逆行车辆进行画框和编号，将检测结果可视化并保存。项目主要流程为：通过live555服务器进行拉流输入视频，然后进行视频解码将264格式的视频解码为YUV格式的图片，图片缩放后经过模型推理进行逆行车辆识别，识别结果经过VehicleRetrogradeRecognition后处理后得到识别框，对识别框进行跟踪和车辆行驶方向判断，用编号覆盖原有的类别信息，再将逆行车辆的识别框和类别信息分别转绘到图片上，最后将图片编码成视频进行输出。 
-
-### 1.1 支持的产品
-
-昇腾310(推理)
-
-### 1.2 支持的版本
-
-本样例配套的CANN版本为[7.0.rc1](https://www.hiascend.com/software/cann/commercial)。支持的SDK版本为[5.0.rc3](https://www.hiascend.com/software/Mindx-sdk)。
-
-MindX SDK安装前准备可参考《用户指南》，[安装教程](https://gitee.com/ascend/mindxsdk-referenceapps/blob/master/docs/quickStart/1-1安装SDK开发套件.md)
-
-### 1.3 软件方案介绍
-
-基于MindX SDK的VehicleRetrogradeRecognition车辆逆行识别业务流程为：待检测视频存放在live555服务器上经mxpi_rtspsrc拉流插件输入，然后使用视频解码插件mxpi_videodecoder将视频解码成图片，再通过图像缩放插件mxpi_imageresize将图像缩放至满足检测模型要求的输入图像大小要求，缩放后的图像输入模型推理插件mxpi_tensorinfer得到检测结果，检测结果通过后处理插件objectpostprocessor处理，再通过mxpi_distributor插件筛选出汽车和卡车的检测结果，再接入跟踪插件mxpi_motsimplesortV2中识别框进行目标跟踪，得到目标的跟踪编号，本项目开发的MxpiTrackRetrogradeCar后处理插件识别出逆行的车辆目标，得到识别框，使用mxpi_object2osdinstances和mxpi_opencvosd分别将识别框和类名（存储跟踪编号）绘制到原图片，再通过mxpi_videoencoder将图片合成视频。
-
-表1.1 系统方案各子系统功能描述：
-
-| 序号 | 子系统               | 功能描述                                                     |
-| ---- | -------------------- | :----------------------------------------------------------- |
-| 1    | 视频输入             | 接收外部调用接口的输入视频路径，对视频进行拉流，并将拉取的裸流存储到缓冲区（buffer）中，并发送到下游插件。 |
-| 2    | 视频解码             | 用于视频解码，当前只支持H264/H265格式。                      |
-| 3    | 数据分发             | 对单个输入数据分发多次。                                     |
-| 4    | 数据缓存             | 输出时为后续处理过程另创建一个线程，用于将输入数据与输出数据解耦，并创建缓存队列，存储尚未输出到下流插件的数据。 |
-| 5    | 图像处理             | 对解码后的YUV格式的图像进行指定宽高的缩放，暂时只支持YUV格式 的图像。 |
-| 6    | 模型推理插件         | 目标分类或检测，目前只支持单tensor输入（图像数据）的推理模型。 |
-| 7    | 模型后处理插件       | 实现对模型推理输出的tensor解析，获取目标检测框以及对应的识别标签，传输到筛选模块。 |
-| 8    | 筛选插件             | 筛选出识别的车辆。                 |
-| 9    | 跟踪插件             | 实现多目标（包括机非人、目标）路径记录功能。                 |
-| 10   | 交通逆行识别插件      | 识别出道路中逆行的车辆，再将数据传入数据流中。 |
-| 11   | 目标框转绘插件       | 将流中传进的MxpiObjectList数据类型转换可用于OSD插件绘图所使用的的 MxpiOsdInstancesList数据类型。 |
-| 12   | OSD可视化插件        | 主要实现对每帧图像标注跟踪结果。                             |
-| 13   | 视频编码插件         | 用于将OSD可视化插件输出的图片进行视频编码，输出视频。        |
-
-### 1.4 代码目录结构与说明
-
-本工程名称为VehicleRetrogradeRecognition，工程目录如下图所示：
-
-```
-├── models
-│   ├── aipp_yolov4_576_576.config            # 模型转换aipp配置文件
-│   ├── coco.names
-│   ├── fusion_result.json
-│   └── yolov4_bs.om               # om模型
-├── pipeline
-│   └── VehicleRetrogradeRecognition.pipeline        # pipeline文件
-├── plugins
-│   └── MxpiTrackRetrogradeCar     # MxpiTrackRetrogradeCar后处理插件
-│       ├── CMakeLists.txt        
-│       ├── MxpiTrackRetrogradeCar.cpp  
-│       ├── MxpiTrackRetrogradeCar.h
-│       └── build.sh
-├── CMakeLists.txt
-├── build.sh
-├── main.cpp
-└── run.sh
-```
-
-
-
-### 1.5 技术实现流程图
-
-![](image/image1.jpg)
-
-
-
-## 2 环境依赖
-
-推荐系统为ubantu 18.04，环境依赖软件和版本如下表：
-
-| 软件名称            | 版本        | 说明                          | 获取方式                                                     |
-| ------------------- | ----------- | ----------------------------- | ------------------------------------------------------------ |
-| MindX SDK           | 5.0.rc3       | mxVision软件包                | [链接](https://www.hiascend.com/software/Mindx-sdk) |
-| ubuntu              | 18.04.1 LTS | 操作系统                      | Ubuntu官网获取                                               |
-| Ascend-CANN-toolkit | 7.0.rc1       | Ascend-cann-toolkit开发套件包 | [链接](https://www.hiascend.com/software/cann/commercial)    |
-
-在编译运行项目前，需要设置环境变量：
-
-```
-export MX_SDK_HOME=${SDK安装路径}/mxVision
-export install_path=/usr/local/Ascend/ascend-toolkit/latest
-export PATH=/usr/local/python3.9.2/bin:${install_path}/atc/ccec_compiler/bin:${install_path}/atc/bin:$PATH
-export ASCEND_OPP_PATH=${install_path}/opp
-export ASCEND_AICPU_PATH=${install_path}
-export LD_LIBRARY_PATH=${install_path}/atc/lib64:${MX_SDK_HOME}/lib:${MX_SDK_HOME}/opensource/lib:$LD_LIBRARY_PATH
-export GST_PLUGIN_SCANNER=${MX_SDK_HOME}/opensource/libexec/gstreamer-1.0/gst-plugin-scanner
-export GST_PLUGIN_PATH=${MX_SDK_HOME}/opensource/lib/gstreamer-1.0:${MX_SDK_HOME}/lib/plugins
-```
-
-注：其中SDK安装路径${MX_SDK_HOME}替换为用户的SDK安装路径;install_path替换为开发套件包所在路径。LD_LIBRARY_PATH用以加载开发套件包中lib库。
-
-
-
-## 3 软件依赖
-
-推理中涉及到第三方软件依赖如下表所示。
-
-| 依赖软件 | 版本       | 说明                           | 使用教程                                                     |
-| -------- | ---------- | ------------------------------ | ------------------------------------------------------------ |
-| live555  | 1.09       | 实现视频转rstp进行推流         | [链接](https://gitee.com/ascend/docs-openmind/blob/master/guide/mindx/sdk/one_stop_navigation.md) |
-| ffmpeg   | 2021-07-21 | 实现mp4格式视频转为264格式视频 | [链接](https://gitee.com/ascend/docs-openmind/blob/master/guide/mindx/sdk/one_stop_navigation.md) |
-
-
-
-## 4 模型转换
-
-**步骤1** 模型获取
-在ModelZoo上下载[YOLOv4模型](https://www.hiascend.com/zh/software/modelzoo/detail/1/abb7e641964c459398173248aa5353bc)
-
-**步骤2** 模型存放
-将获取到的YOLOv4模型onnx文件存放至："样例项目所在目录/models/"。
-
-**步骤3** 模型转换
-在onnx文件所在目录下执行一下命令
-
-```
-# 设置环境变量（请确认install_path路径是否正确）
-# Set environment PATH (Please confirm that the install_path is correct).
-
-export install_path=/usr/local/Ascend/ascend-toolkit/latest
-export PATH=/usr/local/python3.9.2/bin:${install_path}/atc/ccec_compiler/bin:${install_path}/atc/bin:$PATH
-export PYTHONPATH=${install_path}/atc/python/site-packages:${install_path}/atc/python/site-packages/auto_tune.egg/auto_tune:${install_path}/atc/python/site-packages/schedule_search.egg
-export LD_LIBRARY_PATH=${install_path}/atc/lib64:$LD_LIBRARY_PATH
-export ASCEND_OPP_PATH=${install_path}/opp
-
-# 执行，转换YOLOv4模型
-# Execute, transform YOLOv4 model.
-
-YOLOv4:
-atc --model=./yolov4_dynamic_bs.onnx --framework=5 --output=yolov4_bs --input_format=NCHW --soc_version=Ascend310 --insert_op_conf=./aipp_yolov4_576_576.config --input_shape="input:1,3,576,576" --out_nodes="Conv_434:0;Conv_418:0;Conv_402:0"
-```
-
-执行完模型转换脚本后，会生成相应的.om模型文件。我们也提供了原模型以及已经转换好的YOLOv4 om模型：[链接](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/VehicleRetrogradeRecognition/models.zip)
-
-模型转换使用了ATC工具，如需更多信息请参考:
-
- https://gitee.com/ascend/docs-openmind/blob/master/guide/mindx/sdk/tutorials/%E5%8F%82%E8%80%83%E8%B5%84%E6%96%99.md
-
-
-## 5 准备
-
-**步骤1** 通过pc端ffmpeg软件将输入视频格式转换为.264格式，如下所示为MP4转换为h.264命令：
-```
-ffmpeg -i test.mp4 -vcodec h264 -bf 0 -g 25 -s 1280*720 -an -f h264 test.264
-
-//-bf B帧数目控制，-g 关键帧间隔控制，-s 分辨率控制 -an关闭音频， -r 指定帧率
-```
-
-**步骤2** 按照第3小结**软件依赖**安装live555和ffmpeg，按照步骤1或者 [Live555离线视频转RTSP说明文档](https://gitee.com/ascend/docs-openmind/blob/master/guide/mindx/sdk/one_stop_navigation.md)将mp4视频转换为h264格式。并将生成的264格式的视频上传到`live/mediaServer`目录下，然后修改`VehicleRetrogradeRecognition/pipeline`目录下的VehicleRetrogradeRecognition.pipeline文件中mxpi_rtspsrc0的内容。
-
-```
-        "mxpi_rtspsrc0": {
-            "factory": "mxpi_rtspsrc",
-            "props": {
-                "rtspUrl":"rtsp://xxx.xxx.xxx.xxx:xxxx/xxx.264",      // 修改为自己所使用的的服务器和文件名
-                "channelId": "0"
-            },
-            "next": "mxpi_videodecoder0"
-        },
-```
-
-**步骤3** 根据视频划分道路的分界线，取分界线两端点的坐标，写在mxpi_trackretrogradecar插件中，其中isVertical为0时代表道路是竖直或倾斜的，isVertical为1时则代表道路是基本水平的。
-
-```
-        "mxpi_trackretrogradecar0": {
-                    "props": {
-                            "dataSource": "mxpi_distributor0_0",
-                            "motSource": "mxpi_motsimplesortV20",
-                            "x1": "550",
-                            "y1": "0",
-                            "x2": "0",
-                            "y2": "423",
-                            "isVertical": "0"
-                    },
-                    "factory": "mxpi_trackretrogradecar",
-                    "next": "queue4"
-                },
-```
-
-
-## 使用场景概括
-
-### 适用条件
-
-适用于较为笔直的公路，且只有两个方向的来车。
-
-### 限制条件
-
-尺寸条件：单个车辆的宽高像素不得超过500
-
-光照条件：光线较为良好，如果光线不足，必须有车辆的完整轮廓
-
-视频条件：视频拍摄需固定，不能发生抖动或者移动的情况
-
-## 参数调节
-
-| 参数名称 |参数介绍| 修改方法   | 默认值   |
-| -------------- | --------------------------------------------- | --------------------------------------------------------------------- | -------- |
-|trackThreshold      |路径记录对象属于同一目标概率阈值，大于该阈值认为是同一对象|在pipeline文件中，修改mxpi_motsimplesortV2插件中的trackThreshold的大小即可| 0.5 |
-|lostThreshold|路径记录目标丢失帧数阈值，帧数大于该阈值认为行程目标已丢失 |在pipeline文件中，修改mxpi_motsimplesortV2插件中的lostThreshold的大小即可|3|
-|IOU_THRESH       |两个框的IOU阈值，超过阈值即认为同一个框,用于nms算法|在models/yolov4.cfg文件中，修改IOU_THRESH的大小即可|0.6|
-|SCORE_THRESH     |是否为框的阈值，大于阈值即认为是框|在models/yolov4.cfg文件中，修改SCORE_THRESH的大小即可|0.6|
-|OBJECTNESS_THRESH     |是否为目标的阈值，大于阈值即认为是目标|在models/yolov4.cfg文件中，修改OBJECTNESS_THRESH的大小即可|0.7|
-
-
-## 6 编译与运行
-
-**步骤1** 按照第2小节 **环境依赖** 中的步骤设置环境变量。
-
-**步骤2** 按照第4小节 **模型转换** 中的步骤获得 om 模型文件，放置在 `VehicleRetrogradeRecognition/models` 目录下。
-
-**步骤3** 修改`VehicleRetrogradeRecognition/plugins/MxpiTrackRetrogradeCar`文件夹下的CMakeLists.txt文件。将其中的"$ENV{MX_SDK_HOME}"修改成自己的SDK目录。
-
-**步骤4** 编译。进入 `VehicleRetrogradeRecognition` 目录，在 `VehicleRetrogradeRecognition` 目录下执行命令：
-
-```
-bash build.sh
-```
-
-命令执行成功后会在`VehicleRetrogradeRecognition/plugins/MxpiTrackRetrogradeCar`目录下生成build文件夹。将`VehicleRetrogradeRecognition/plugins/MxpiTrackRetrogradeCar/build`目录下生成的的libmxpi_trackretrogradecar.so下载后上传到`${SDK安装路径}/mxVision/lib/plugins`目录下，然后将权限设置为0640。
-
-**步骤5** 运行。回到VehicleRetrogradeRecognition目录下，在VehicleRetrogradeRecognition目录下执行命令：
-
-```
-bash run.sh
-```
-
-命令执行成功后会在当前目录下生成检测结果视频文件out.h264,然后执行命令：
-
-```
-ffmpeg -f h264 -i out.h264 -vcodec copy out.mp4
-```
-
-命令执行成功后会得到检测结果视频文件的mp4格式。
-
-## 7 性能测试
-
-**测试帧率：**
-
-使用`VehicleRetrogradeRecognition/test`目录下的main.cpp替换`VehicleRetrogradeRecognition`目录下的main.cpp，然后按照第6小结编译与运行中的步骤进行编译运行，服务器会输出运行到该帧的平均帧率。
-
-![](image/image2.jpg)
-
-本样例统计出每秒处理的帧数，输入为25帧率的视频，单路推理，理应每秒处理25 * 1 = 25帧，如统计每秒的帧率达到25则性能达标。经测试，本样例满足1920*1080分辨率下25帧率的推理。
-
-## 8 常见问题
-
-8.1 视频编码参数配置错误
-
-**问题描述：**
-
-`VehicleRetrogradeRecognition/pipeline/VehicleRetrogradeRecognition.pipeline`中视频编码分辨率需手动指定imageHeight 和 imageWidth 属性，需要和视频输入分配率相同，否则会包如下类型的错：
-
-![](image/image3.jpg)
-
-**解决方案：**
-
-确保`VehicleRetrogradeRecognition/pipeline/VehicleRetrogradeRecognition.pipeline`中 mxpi_videoencoder0 插件的 imageHeight 和 imageWidth 属性值是输入264视频的高和宽。
+# VehicleRetrogradeRecognition交通逆行识别
+
+## 1 介绍
+
+VehicleRetrogradeRecognition交通逆行识别后处理插件基于MindXSDK开发，在晟腾芯片上进行目标检测和跟踪，可以对逆行车辆进行画框和编号，将检测结果可视化并保存。项目主要流程为：通过live555服务器进行拉流输入视频，然后进行视频解码将264格式的视频解码为YUV格式的图片，图片缩放后经过模型推理进行逆行车辆识别，识别结果经过VehicleRetrogradeRecognition后处理后得到识别框，对识别框进行跟踪和车辆行驶方向判断，用编号覆盖原有的类别信息，再将逆行车辆的识别框和类别信息分别转绘到图片上，最后将图片编码成视频进行输出。 
+
+### 1.1 支持的产品
+
+昇腾310(推理)
+
+### 1.2 支持的版本
+
+本样例配套的CANN版本为[7.0.rc1](https://www.hiascend.com/software/cann/commercial)。支持的SDK版本为[5.0.rc3](https://www.hiascend.com/software/Mindx-sdk)。
+
+MindX SDK安装前准备可参考《用户指南》，[安装教程](https://gitee.com/ascend/mindxsdk-referenceapps/blob/master/docs/quickStart/1-1安装SDK开发套件.md)
+
+### 1.3 软件方案介绍
+
+基于MindX SDK的VehicleRetrogradeRecognition车辆逆行识别业务流程为：待检测视频存放在live555服务器上经mxpi_rtspsrc拉流插件输入，然后使用视频解码插件mxpi_videodecoder将视频解码成图片，再通过图像缩放插件mxpi_imageresize将图像缩放至满足检测模型要求的输入图像大小要求，缩放后的图像输入模型推理插件mxpi_tensorinfer得到检测结果，检测结果通过后处理插件objectpostprocessor处理，再通过mxpi_distributor插件筛选出汽车和卡车的检测结果，再接入跟踪插件mxpi_motsimplesortV2中识别框进行目标跟踪，得到目标的跟踪编号，本项目开发的MxpiTrackRetrogradeCar后处理插件识别出逆行的车辆目标，得到识别框，使用mxpi_object2osdinstances和mxpi_opencvosd分别将识别框和类名（存储跟踪编号）绘制到原图片，再通过mxpi_videoencoder将图片合成视频。
+
+表1.1 系统方案各子系统功能描述：
+
+| 序号 | 子系统               | 功能描述                                                     |
+| ---- | -------------------- | :----------------------------------------------------------- |
+| 1    | 视频输入             | 接收外部调用接口的输入视频路径，对视频进行拉流，并将拉取的裸流存储到缓冲区（buffer）中，并发送到下游插件。 |
+| 2    | 视频解码             | 用于视频解码，当前只支持H264/H265格式。                      |
+| 3    | 数据分发             | 对单个输入数据分发多次。                                     |
+| 4    | 数据缓存             | 输出时为后续处理过程另创建一个线程，用于将输入数据与输出数据解耦，并创建缓存队列，存储尚未输出到下流插件的数据。 |
+| 5    | 图像处理             | 对解码后的YUV格式的图像进行指定宽高的缩放，暂时只支持YUV格式 的图像。 |
+| 6    | 模型推理插件         | 目标分类或检测，目前只支持单tensor输入（图像数据）的推理模型。 |
+| 7    | 模型后处理插件       | 实现对模型推理输出的tensor解析，获取目标检测框以及对应的识别标签，传输到筛选模块。 |
+| 8    | 筛选插件             | 筛选出识别的车辆。                 |
+| 9    | 跟踪插件             | 实现多目标（包括机非人、目标）路径记录功能。                 |
+| 10   | 交通逆行识别插件      | 识别出道路中逆行的车辆，再将数据传入数据流中。 |
+| 11   | 目标框转绘插件       | 将流中传进的MxpiObjectList数据类型转换可用于OSD插件绘图所使用的的 MxpiOsdInstancesList数据类型。 |
+| 12   | OSD可视化插件        | 主要实现对每帧图像标注跟踪结果。                             |
+| 13   | 视频编码插件         | 用于将OSD可视化插件输出的图片进行视频编码，输出视频。        |
+
+### 1.4 代码目录结构与说明
+
+本工程名称为VehicleRetrogradeRecognition，工程目录如下图所示：
+
+```
+├── models
+│   ├── aipp_yolov4_576_576.config            # 模型转换aipp配置文件
+│   ├── coco.names
+│   ├── fusion_result.json
+│   └── yolov4_bs.om               # om模型
+├── pipeline
+│   └── VehicleRetrogradeRecognition.pipeline        # pipeline文件
+├── plugins
+│   └── MxpiTrackRetrogradeCar     # MxpiTrackRetrogradeCar后处理插件
+│       ├── CMakeLists.txt        
+│       ├── MxpiTrackRetrogradeCar.cpp  
+│       ├── MxpiTrackRetrogradeCar.h
+│       └── build.sh
+├── CMakeLists.txt
+├── build.sh
+├── main.cpp
+└── run.sh
+```
+
+
+
+### 1.5 技术实现流程图
+
+![](image/image1.jpg)
+
+
+
+## 2 环境依赖
+
+推荐系统为ubantu 18.04，环境依赖软件和版本如下表：
+
+| 软件名称            | 版本        | 说明                          | 获取方式                                                     |
+| ------------------- | ----------- | ----------------------------- | ------------------------------------------------------------ |
+| MindX SDK           | 5.0.rc3       | mxVision软件包                | [链接](https://www.hiascend.com/software/Mindx-sdk) |
+| ubuntu              | 18.04.1 LTS | 操作系统                      | Ubuntu官网获取                                               |
+| Ascend-CANN-toolkit | 7.0.rc1       | Ascend-cann-toolkit开发套件包 | [链接](https://www.hiascend.com/software/cann/commercial)    |
+
+在编译运行项目前，需要设置环境变量：
+
+```
+export MX_SDK_HOME=${SDK安装路径}/mxVision
+export install_path=/usr/local/Ascend/ascend-toolkit/latest
+export PATH=/usr/local/python3.9.2/bin:${install_path}/atc/ccec_compiler/bin:${install_path}/atc/bin:$PATH
+export ASCEND_OPP_PATH=${install_path}/opp
+export ASCEND_AICPU_PATH=${install_path}
+export LD_LIBRARY_PATH=${install_path}/atc/lib64:${MX_SDK_HOME}/lib:${MX_SDK_HOME}/opensource/lib:$LD_LIBRARY_PATH
+export GST_PLUGIN_SCANNER=${MX_SDK_HOME}/opensource/libexec/gstreamer-1.0/gst-plugin-scanner
+export GST_PLUGIN_PATH=${MX_SDK_HOME}/opensource/lib/gstreamer-1.0:${MX_SDK_HOME}/lib/plugins
+```
+
+注：其中SDK安装路径${MX_SDK_HOME}替换为用户的SDK安装路径;install_path替换为开发套件包所在路径。LD_LIBRARY_PATH用以加载开发套件包中lib库。
+
+
+
+## 3 软件依赖
+
+推理中涉及到第三方软件依赖如下表所示。
+
+| 依赖软件 | 版本       | 说明                           | 使用教程                                                     |
+| -------- | ---------- | ------------------------------ | ------------------------------------------------------------ |
+| live555  | 1.09       | 实现视频转rstp进行推流         | [链接](https://gitee.com/ascend/docs-openmind/blob/master/guide/mindx/sdk/one_stop_navigation.md) |
+| ffmpeg   | 2021-07-21 | 实现mp4格式视频转为264格式视频 | [链接](https://gitee.com/ascend/docs-openmind/blob/master/guide/mindx/sdk/one_stop_navigation.md) |
+
+
+
+## 4 模型转换
+
+**步骤1** 模型获取
+在ModelZoo上下载[YOLOv4模型](https://www.hiascend.com/zh/software/modelzoo/detail/1/abb7e641964c459398173248aa5353bc)
+
+**步骤2** 模型存放
+将获取到的YOLOv4模型onnx文件存放至："样例项目所在目录/models/"。
+
+**步骤3** 模型转换
+在onnx文件所在目录下执行一下命令
+
+```
+# 设置环境变量（请确认install_path路径是否正确）
+# Set environment PATH (Please confirm that the install_path is correct).
+
+export install_path=/usr/local/Ascend/ascend-toolkit/latest
+export PATH=/usr/local/python3.9.2/bin:${install_path}/atc/ccec_compiler/bin:${install_path}/atc/bin:$PATH
+export PYTHONPATH=${install_path}/atc/python/site-packages:${install_path}/atc/python/site-packages/auto_tune.egg/auto_tune:${install_path}/atc/python/site-packages/schedule_search.egg
+export LD_LIBRARY_PATH=${install_path}/atc/lib64:$LD_LIBRARY_PATH
+export ASCEND_OPP_PATH=${install_path}/opp
+
+# 执行，转换YOLOv4模型
+# Execute, transform YOLOv4 model.
+
+YOLOv4:
+atc --model=./yolov4_dynamic_bs.onnx --framework=5 --output=yolov4_bs --input_format=NCHW --soc_version=Ascend310 --insert_op_conf=./aipp_yolov4_576_576.config --input_shape="input:1,3,576,576" --out_nodes="Conv_434:0;Conv_418:0;Conv_402:0"
+```
+
+执行完模型转换脚本后，会生成相应的.om模型文件。我们也提供了原模型以及已经转换好的YOLOv4 om模型：[链接](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/VehicleRetrogradeRecognition/models.zip)
+
+模型转换使用了ATC工具，如需更多信息请参考:
+
+ https://gitee.com/ascend/docs-openmind/blob/master/guide/mindx/sdk/tutorials/%E5%8F%82%E8%80%83%E8%B5%84%E6%96%99.md
+
+
+## 5 准备
+
+**步骤1** 通过pc端ffmpeg软件将输入视频格式转换为.264格式，如下所示为MP4转换为h.264命令：
+```
+ffmpeg -i test.mp4 -vcodec h264 -bf 0 -g 25 -s 1280*720 -an -f h264 test.264
+
+//-bf B帧数目控制，-g 关键帧间隔控制，-s 分辨率控制 -an关闭音频， -r 指定帧率
+```
+
+**步骤2** 按照第3小结**软件依赖**安装live555和ffmpeg，按照步骤1或者 [Live555离线视频转RTSP说明文档](https://gitee.com/ascend/docs-openmind/blob/master/guide/mindx/sdk/one_stop_navigation.md)将mp4视频转换为h264格式。并将生成的264格式的视频上传到`live/mediaServer`目录下，然后修改`VehicleRetrogradeRecognition/pipeline`目录下的VehicleRetrogradeRecognition.pipeline文件中mxpi_rtspsrc0的内容。
+
+```
+        "mxpi_rtspsrc0": {
+            "factory": "mxpi_rtspsrc",
+            "props": {
+                "rtspUrl":"rtsp://xxx.xxx.xxx.xxx:xxxx/xxx.264",      // 修改为自己所使用的的服务器和文件名
+                "channelId": "0"
+            },
+            "next": "mxpi_videodecoder0"
+        },
+```
+
+**步骤3** 根据视频划分道路的分界线，取分界线两端点的坐标，写在mxpi_trackretrogradecar插件中，其中isVertical为0时代表道路是竖直或倾斜的，isVertical为1时则代表道路是基本水平的。
+
+```
+        "mxpi_trackretrogradecar0": {
+                    "props": {
+                            "dataSource": "mxpi_distributor0_0",
+                            "motSource": "mxpi_motsimplesortV20",
+                            "x1": "550",
+                            "y1": "0",
+                            "x2": "0",
+                            "y2": "423",
+                            "isVertical": "0"
+                    },
+                    "factory": "mxpi_trackretrogradecar",
+                    "next": "queue4"
+                },
+```
+
+
+## 使用场景概括
+
+### 适用条件
+
+适用于较为笔直的公路，且只有两个方向的来车。
+
+### 限制条件
+
+尺寸条件：单个车辆的宽高像素不得超过500
+
+光照条件：光线较为良好，如果光线不足，必须有车辆的完整轮廓
+
+视频条件：视频拍摄需固定，不能发生抖动或者移动的情况
+
+## 参数调节
+
+| 参数名称 |参数介绍| 修改方法   | 默认值   |
+| -------------- | --------------------------------------------- | --------------------------------------------------------------------- | -------- |
+|trackThreshold      |路径记录对象属于同一目标概率阈值，大于该阈值认为是同一对象|在pipeline文件中，修改mxpi_motsimplesortV2插件中的trackThreshold的大小即可| 0.5 |
+|lostThreshold|路径记录目标丢失帧数阈值，帧数大于该阈值认为行程目标已丢失 |在pipeline文件中，修改mxpi_motsimplesortV2插件中的lostThreshold的大小即可|3|
+|IOU_THRESH       |两个框的IOU阈值，超过阈值即认为同一个框,用于nms算法|在models/yolov4.cfg文件中，修改IOU_THRESH的大小即可|0.6|
+|SCORE_THRESH     |是否为框的阈值，大于阈值即认为是框|在models/yolov4.cfg文件中，修改SCORE_THRESH的大小即可|0.6|
+|OBJECTNESS_THRESH     |是否为目标的阈值，大于阈值即认为是目标|在models/yolov4.cfg文件中，修改OBJECTNESS_THRESH的大小即可|0.7|
+
+
+## 6 编译与运行
+
+**步骤1** 按照第2小节 **环境依赖** 中的步骤设置环境变量。
+
+**步骤2** 按照第4小节 **模型转换** 中的步骤获得 om 模型文件，放置在 `VehicleRetrogradeRecognition/models` 目录下。
+
+**步骤3** 修改`VehicleRetrogradeRecognition/plugins/MxpiTrackRetrogradeCar`文件夹下的CMakeLists.txt文件。将其中的"$ENV{MX_SDK_HOME}"修改成自己的SDK目录。
+
+**步骤4** 编译。进入 `VehicleRetrogradeRecognition` 目录，在 `VehicleRetrogradeRecognition` 目录下执行命令：
+
+```
+bash build.sh
+```
+
+命令执行成功后会在`VehicleRetrogradeRecognition/plugins/MxpiTrackRetrogradeCar`目录下生成build文件夹。将`VehicleRetrogradeRecognition/plugins/MxpiTrackRetrogradeCar/build`目录下生成的的libmxpi_trackretrogradecar.so下载后上传到`${SDK安装路径}/mxVision/lib/plugins`目录下，然后将权限设置为0640。
+
+**步骤5** 运行。回到VehicleRetrogradeRecognition目录下，在VehicleRetrogradeRecognition目录下执行命令：
+
+```
+bash run.sh
+```
+
+命令执行成功后会在当前目录下生成检测结果视频文件out.h264,然后执行命令：
+
+```
+ffmpeg -f h264 -i out.h264 -vcodec copy out.mp4
+```
+
+命令执行成功后会得到检测结果视频文件的mp4格式。
+
+## 7 性能测试
+
+**测试帧率：**
+
+使用`VehicleRetrogradeRecognition/test`目录下的main.cpp替换`VehicleRetrogradeRecognition`目录下的main.cpp，然后按照第6小结编译与运行中的步骤进行编译运行，服务器会输出运行到该帧的平均帧率。
+
+![](image/image2.jpg)
+
+本样例统计出每秒处理的帧数，输入为25帧率的视频，单路推理，理应每秒处理25 * 1 = 25帧，如统计每秒的帧率达到25则性能达标。经测试，本样例满足1920*1080分辨率下25帧率的推理。
+
+## 8 常见问题
+
+8.1 视频编码参数配置错误
+
+**问题描述：**
+
+`VehicleRetrogradeRecognition/pipeline/VehicleRetrogradeRecognition.pipeline`中视频编码分辨率需手动指定imageHeight 和 imageWidth 属性，需要和视频输入分配率相同，否则会包如下类型的错：
+
+![](image/image3.jpg)
+
+**解决方案：**
+
+确保`VehicleRetrogradeRecognition/pipeline/VehicleRetrogradeRecognition.pipeline`中 mxpi_videoencoder0 插件的 imageHeight 和 imageWidth 属性值是输入264视频的高和宽。
diff --git a/contrib/VehicleRetrogradeRecognition/build.sh b/mxVision/mxVision-referenceapps/VehicleRetrogradeRecognition/build.sh
similarity index 100%
rename from contrib/VehicleRetrogradeRecognition/build.sh
rename to mxVision/mxVision-referenceapps/VehicleRetrogradeRecognition/build.sh
diff --git a/contrib/VehicleRetrogradeRecognition/image/image1.jpg b/mxVision/mxVision-referenceapps/VehicleRetrogradeRecognition/image/image1.jpg
similarity index 100%
rename from contrib/VehicleRetrogradeRecognition/image/image1.jpg
rename to mxVision/mxVision-referenceapps/VehicleRetrogradeRecognition/image/image1.jpg
diff --git a/contrib/VehicleRetrogradeRecognition/image/image2.jpg b/mxVision/mxVision-referenceapps/VehicleRetrogradeRecognition/image/image2.jpg
similarity index 100%
rename from contrib/VehicleRetrogradeRecognition/image/image2.jpg
rename to mxVision/mxVision-referenceapps/VehicleRetrogradeRecognition/image/image2.jpg
diff --git a/contrib/VehicleRetrogradeRecognition/image/image3.jpg b/mxVision/mxVision-referenceapps/VehicleRetrogradeRecognition/image/image3.jpg
similarity index 100%
rename from contrib/VehicleRetrogradeRecognition/image/image3.jpg
rename to mxVision/mxVision-referenceapps/VehicleRetrogradeRecognition/image/image3.jpg
diff --git a/contrib/VehicleRetrogradeRecognition/main.cpp b/mxVision/mxVision-referenceapps/VehicleRetrogradeRecognition/main.cpp
similarity index 100%
rename from contrib/VehicleRetrogradeRecognition/main.cpp
rename to mxVision/mxVision-referenceapps/VehicleRetrogradeRecognition/main.cpp
diff --git a/contrib/VehicleRetrogradeRecognition/models/aipp_yolov4_576_576.config b/mxVision/mxVision-referenceapps/VehicleRetrogradeRecognition/models/aipp_yolov4_576_576.config
similarity index 100%
rename from contrib/VehicleRetrogradeRecognition/models/aipp_yolov4_576_576.config
rename to mxVision/mxVision-referenceapps/VehicleRetrogradeRecognition/models/aipp_yolov4_576_576.config
diff --git a/contrib/VehicleRetrogradeRecognition/models/coco.names b/mxVision/mxVision-referenceapps/VehicleRetrogradeRecognition/models/coco.names
similarity index 100%
rename from contrib/VehicleRetrogradeRecognition/models/coco.names
rename to mxVision/mxVision-referenceapps/VehicleRetrogradeRecognition/models/coco.names
diff --git a/contrib/VehicleRetrogradeRecognition/models/fusion_result.json b/mxVision/mxVision-referenceapps/VehicleRetrogradeRecognition/models/fusion_result.json
similarity index 100%
rename from contrib/VehicleRetrogradeRecognition/models/fusion_result.json
rename to mxVision/mxVision-referenceapps/VehicleRetrogradeRecognition/models/fusion_result.json
diff --git a/contrib/VehicleRetrogradeRecognition/models/yolov4.cfg b/mxVision/mxVision-referenceapps/VehicleRetrogradeRecognition/models/yolov4.cfg
similarity index 95%
rename from contrib/VehicleRetrogradeRecognition/models/yolov4.cfg
rename to mxVision/mxVision-referenceapps/VehicleRetrogradeRecognition/models/yolov4.cfg
index 63b35d71a93928490a4ae14fc1367ea4f7f39afd..e333039562b6e738e8068cb3fa779972984e4ef5 100644
--- a/contrib/VehicleRetrogradeRecognition/models/yolov4.cfg
+++ b/mxVision/mxVision-referenceapps/VehicleRetrogradeRecognition/models/yolov4.cfg
@@ -1,12 +1,12 @@
-CLASS_NUM=80
-BIASES_NUM=18
-BIASES=10,13,16,30,33,23,30,61,62,45,59,119,116,90,156,198,373,326
-SCORE_THRESH=0.6
-OBJECTNESS_THRESH=0.7
-IOU_THRESH=0.6
-YOLO_TYPE=3
-ANCHOR_DIM=3
-MODEL_TYPE=1
-RESIZE_FLAG=0
-YOLO_VERSION=4
+CLASS_NUM=80
+BIASES_NUM=18
+BIASES=10,13,16,30,33,23,30,61,62,45,59,119,116,90,156,198,373,326
+SCORE_THRESH=0.6
+OBJECTNESS_THRESH=0.7
+IOU_THRESH=0.6
+YOLO_TYPE=3
+ANCHOR_DIM=3
+MODEL_TYPE=1
+RESIZE_FLAG=0
+YOLO_VERSION=4
 FRAMEWORK=PYTORCH
\ No newline at end of file
diff --git a/contrib/VehicleRetrogradeRecognition/pipeline/VehicleRetrogradeRecognition.pipeline b/mxVision/mxVision-referenceapps/VehicleRetrogradeRecognition/pipeline/VehicleRetrogradeRecognition.pipeline
similarity index 96%
rename from contrib/VehicleRetrogradeRecognition/pipeline/VehicleRetrogradeRecognition.pipeline
rename to mxVision/mxVision-referenceapps/VehicleRetrogradeRecognition/pipeline/VehicleRetrogradeRecognition.pipeline
index 52115131ff3beb5e6402b1cedd2bd6d445e9d094..43821a71f3e33070acd534afd82dbe5908b2b9af 100644
--- a/contrib/VehicleRetrogradeRecognition/pipeline/VehicleRetrogradeRecognition.pipeline
+++ b/mxVision/mxVision-referenceapps/VehicleRetrogradeRecognition/pipeline/VehicleRetrogradeRecognition.pipeline
@@ -1,179 +1,179 @@
-{
-    "encoder": {
-        "stream_config": {
-            "deviceId": "0"
-        },
-        "mxpi_rtspsrc0": {
-            "factory": "mxpi_rtspsrc",
-            "props": {
-                "rtspUrl":"rtsp://xxx.xxx.xxx.xxx:xxxx/test.264",
-                "channelId": "0"
-            },
-            "next": "queue0"
-        },
-        "queue0": {
-            "props": {
-                "max-size-buffers": "200"
-            },
-            "factory": "queue",
-            "next": "mxpi_videodecoder0"
-        },
-        "mxpi_videodecoder0": {
-            "factory": "mxpi_videodecoder",
-            "props": {
-                "inputVideoFormat": "H264",
-                "outputImageFormat": "YUV420SP_NV12",
-                "vdecChannelId": "0"
-            },
-            "next": "tee0"
-        },
-        "tee0": {
-            "factory": "tee",
-            "next": [
-                "queue1",
-                "queue2"
-            ]
-        },
-        "queue1": {
-            "props": {
-                "max-size-buffers": "200"
-            },
-            "factory": "queue",
-            "next": "mxpi_imageresize0"
-        },
-        "queue2": {
-            "props": {
-                "max-size-buffers": "200"
-            },
-            "factory": "queue",
-            "next": "mxpi_opencvosd0:0"
-        },
-        "mxpi_imageresize0": {
-            "props": {
-                "resizeHeight": "576",
-                "resizeWidth": "576",
-                "resizeType": "Resizer_KeepAspectRatio_Fit"
-            },
-            "factory": "mxpi_imageresize",
-            "next": "queue3"
-        },
-        "queue3": {
-            "props": {
-                "max-size-buffers": "200"
-            },
-            "factory": "queue",
-            "next": "mxpi_tensorinfer0"
-        },
-        "mxpi_tensorinfer0": {
-            "props": {
-                "dataSource": "mxpi_imageresize0",
-                "modelPath": "./models/yolov4_bs.om"
-            },
-            "factory": "mxpi_tensorinfer",
-            "next": "mxpi_objectpostprocessor0"
-        },
-        "mxpi_objectpostprocessor0": {
-            "props": {
-                "dataSource": "mxpi_tensorinfer0",
-                "funcLanguage":"c++",
-                "postProcessConfigPath": "./models/yolov4.cfg",
-                "labelPath": "./models/coco.names",
-                "postProcessLibPath": "libyolov3postprocess.so"
-            },
-            "factory": "mxpi_objectpostprocessor",
-            "next": "mxpi_distributor0"
-        },
-        "mxpi_distributor0": {
-            "props": {
-                "dataSource": "mxpi_objectpostprocessor0",
-                "classIds": "2|7"
-            },
-            "factory": "mxpi_distributor",
-            "next": "mxpi_motsimplesortV20"
-        },
-        "mxpi_motsimplesortV20": {
-            "props": {
-                "dataSourceDetection": "mxpi_distributor0_0",
-                "trackThreshold": "0.5",
-                "lostThreshold": "3"
-            },
-            "factory": "mxpi_motsimplesortV2",
-            "next": "mxpi_trackretrogradecar0"
-        },
-        "mxpi_trackretrogradecar0": {
-            "props": {
-                    "dataSource": "mxpi_distributor0_0",
-                    "motSource": "mxpi_motsimplesortV20",
-                    "x1": "550",
-                    "y1": "0",
-                    "x2": "0",
-                    "y2": "423",
-                    "isVertical": "0"
-            },
-            "factory": "mxpi_trackretrogradecar",
-            "next": "queue4"
-        },
-        "queue4": {
-            "props": {
-                "max-size-buffers": "200"
-            },
-            "factory": "queue",
-            "next": "mxpi_object2osdinstances0"
-        },
-        "mxpi_object2osdinstances0": {
-            "props": {
-                "dataSource": "mxpi_trackretrogradecar0",
-                "colorMap": "255,100,100|100,255,100|100,100,255|255,128,0",
-                "fontFace": "1",
-                "fontScale": "1",
-                "fontThickness": "1",
-                "fontLineType": "8",
-                "rectThickness": "3",
-                "rectLineType": "8"
-            },
-            "factory": "mxpi_object2osdinstances",
-            "next": "queue5"
-        },
-        "queue5": {
-            "props": {
-                "max-size-buffers": "200"
-            },
-            "factory": "queue",
-            "next": "mxpi_opencvosd0:1"
-        },
-        "mxpi_opencvosd0": {
-            "factory": "mxpi_opencvosd",
-            "next": "queue6"
-        },
-        "queue6": {
-            "props": {
-                "max-size-buffers": "200"
-            },
-            "factory": "queue",
-            "next": "mxpi_videoencoder0"
-        },
-        "mxpi_videoencoder0": {
-            "props": {
-                "inputFormat": "YUV420SP_NV12",
-                "outputFormat": "H264",
-                "fps": "1",
-                "iFrameInterval": "50",
-                "imageWidth":"1280",
-                "imageHeight":"720"
-            },
-            "factory": "mxpi_videoencoder",
-            "next": "queue7"
-        },
-        "queue7": {
-            "props": {
-                "max-size-buffers": "200"
-            },
-            "factory": "queue",
-            "next": "appsink0"
-        },
-        "appsink0": {
-            "factory": "appsink",
-            "former": "mxpi_videoencoder0"
-        }
-    }
-}
+{
+    "encoder": {
+        "stream_config": {
+            "deviceId": "0"
+        },
+        "mxpi_rtspsrc0": {
+            "factory": "mxpi_rtspsrc",
+            "props": {
+                "rtspUrl":"rtsp://xxx.xxx.xxx.xxx:xxxx/test.264",
+                "channelId": "0"
+            },
+            "next": "queue0"
+        },
+        "queue0": {
+            "props": {
+                "max-size-buffers": "200"
+            },
+            "factory": "queue",
+            "next": "mxpi_videodecoder0"
+        },
+        "mxpi_videodecoder0": {
+            "factory": "mxpi_videodecoder",
+            "props": {
+                "inputVideoFormat": "H264",
+                "outputImageFormat": "YUV420SP_NV12",
+                "vdecChannelId": "0"
+            },
+            "next": "tee0"
+        },
+        "tee0": {
+            "factory": "tee",
+            "next": [
+                "queue1",
+                "queue2"
+            ]
+        },
+        "queue1": {
+            "props": {
+                "max-size-buffers": "200"
+            },
+            "factory": "queue",
+            "next": "mxpi_imageresize0"
+        },
+        "queue2": {
+            "props": {
+                "max-size-buffers": "200"
+            },
+            "factory": "queue",
+            "next": "mxpi_opencvosd0:0"
+        },
+        "mxpi_imageresize0": {
+            "props": {
+                "resizeHeight": "576",
+                "resizeWidth": "576",
+                "resizeType": "Resizer_KeepAspectRatio_Fit"
+            },
+            "factory": "mxpi_imageresize",
+            "next": "queue3"
+        },
+        "queue3": {
+            "props": {
+                "max-size-buffers": "200"
+            },
+            "factory": "queue",
+            "next": "mxpi_tensorinfer0"
+        },
+        "mxpi_tensorinfer0": {
+            "props": {
+                "dataSource": "mxpi_imageresize0",
+                "modelPath": "./models/yolov4_bs.om"
+            },
+            "factory": "mxpi_tensorinfer",
+            "next": "mxpi_objectpostprocessor0"
+        },
+        "mxpi_objectpostprocessor0": {
+            "props": {
+                "dataSource": "mxpi_tensorinfer0",
+                "funcLanguage":"c++",
+                "postProcessConfigPath": "./models/yolov4.cfg",
+                "labelPath": "./models/coco.names",
+                "postProcessLibPath": "libyolov3postprocess.so"
+            },
+            "factory": "mxpi_objectpostprocessor",
+            "next": "mxpi_distributor0"
+        },
+        "mxpi_distributor0": {
+            "props": {
+                "dataSource": "mxpi_objectpostprocessor0",
+                "classIds": "2|7"
+            },
+            "factory": "mxpi_distributor",
+            "next": "mxpi_motsimplesortV20"
+        },
+        "mxpi_motsimplesortV20": {
+            "props": {
+                "dataSourceDetection": "mxpi_distributor0_0",
+                "trackThreshold": "0.5",
+                "lostThreshold": "3"
+            },
+            "factory": "mxpi_motsimplesortV2",
+            "next": "mxpi_trackretrogradecar0"
+        },
+        "mxpi_trackretrogradecar0": {
+            "props": {
+                    "dataSource": "mxpi_distributor0_0",
+                    "motSource": "mxpi_motsimplesortV20",
+                    "x1": "550",
+                    "y1": "0",
+                    "x2": "0",
+                    "y2": "423",
+                    "isVertical": "0"
+            },
+            "factory": "mxpi_trackretrogradecar",
+            "next": "queue4"
+        },
+        "queue4": {
+            "props": {
+                "max-size-buffers": "200"
+            },
+            "factory": "queue",
+            "next": "mxpi_object2osdinstances0"
+        },
+        "mxpi_object2osdinstances0": {
+            "props": {
+                "dataSource": "mxpi_trackretrogradecar0",
+                "colorMap": "255,100,100|100,255,100|100,100,255|255,128,0",
+                "fontFace": "1",
+                "fontScale": "1",
+                "fontThickness": "1",
+                "fontLineType": "8",
+                "rectThickness": "3",
+                "rectLineType": "8"
+            },
+            "factory": "mxpi_object2osdinstances",
+            "next": "queue5"
+        },
+        "queue5": {
+            "props": {
+                "max-size-buffers": "200"
+            },
+            "factory": "queue",
+            "next": "mxpi_opencvosd0:1"
+        },
+        "mxpi_opencvosd0": {
+            "factory": "mxpi_opencvosd",
+            "next": "queue6"
+        },
+        "queue6": {
+            "props": {
+                "max-size-buffers": "200"
+            },
+            "factory": "queue",
+            "next": "mxpi_videoencoder0"
+        },
+        "mxpi_videoencoder0": {
+            "props": {
+                "inputFormat": "YUV420SP_NV12",
+                "outputFormat": "H264",
+                "fps": "1",
+                "iFrameInterval": "50",
+                "imageWidth":"1280",
+                "imageHeight":"720"
+            },
+            "factory": "mxpi_videoencoder",
+            "next": "queue7"
+        },
+        "queue7": {
+            "props": {
+                "max-size-buffers": "200"
+            },
+            "factory": "queue",
+            "next": "appsink0"
+        },
+        "appsink0": {
+            "factory": "appsink",
+            "former": "mxpi_videoencoder0"
+        }
+    }
+}
diff --git a/contrib/VehicleRetrogradeRecognition/plugins/MxpiTrackRetrogradeCar/CMakeLists.txt b/mxVision/mxVision-referenceapps/VehicleRetrogradeRecognition/plugins/MxpiTrackRetrogradeCar/CMakeLists.txt
similarity index 100%
rename from contrib/VehicleRetrogradeRecognition/plugins/MxpiTrackRetrogradeCar/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/VehicleRetrogradeRecognition/plugins/MxpiTrackRetrogradeCar/CMakeLists.txt
diff --git a/contrib/VehicleRetrogradeRecognition/plugins/MxpiTrackRetrogradeCar/MxpiTrackRetrogradeCar.cpp b/mxVision/mxVision-referenceapps/VehicleRetrogradeRecognition/plugins/MxpiTrackRetrogradeCar/MxpiTrackRetrogradeCar.cpp
similarity index 100%
rename from contrib/VehicleRetrogradeRecognition/plugins/MxpiTrackRetrogradeCar/MxpiTrackRetrogradeCar.cpp
rename to mxVision/mxVision-referenceapps/VehicleRetrogradeRecognition/plugins/MxpiTrackRetrogradeCar/MxpiTrackRetrogradeCar.cpp
diff --git a/contrib/VehicleRetrogradeRecognition/plugins/MxpiTrackRetrogradeCar/MxpiTrackRetrogradeCar.h b/mxVision/mxVision-referenceapps/VehicleRetrogradeRecognition/plugins/MxpiTrackRetrogradeCar/MxpiTrackRetrogradeCar.h
similarity index 100%
rename from contrib/VehicleRetrogradeRecognition/plugins/MxpiTrackRetrogradeCar/MxpiTrackRetrogradeCar.h
rename to mxVision/mxVision-referenceapps/VehicleRetrogradeRecognition/plugins/MxpiTrackRetrogradeCar/MxpiTrackRetrogradeCar.h
diff --git a/contrib/VehicleRetrogradeRecognition/plugins/MxpiTrackRetrogradeCar/build.sh b/mxVision/mxVision-referenceapps/VehicleRetrogradeRecognition/plugins/MxpiTrackRetrogradeCar/build.sh
similarity index 100%
rename from contrib/VehicleRetrogradeRecognition/plugins/MxpiTrackRetrogradeCar/build.sh
rename to mxVision/mxVision-referenceapps/VehicleRetrogradeRecognition/plugins/MxpiTrackRetrogradeCar/build.sh
diff --git a/contrib/VehicleRetrogradeRecognition/run.sh b/mxVision/mxVision-referenceapps/VehicleRetrogradeRecognition/run.sh
similarity index 100%
rename from contrib/VehicleRetrogradeRecognition/run.sh
rename to mxVision/mxVision-referenceapps/VehicleRetrogradeRecognition/run.sh
diff --git a/contrib/VehicleRetrogradeRecognition/test/main.cpp b/mxVision/mxVision-referenceapps/VehicleRetrogradeRecognition/test/main.cpp
similarity index 100%
rename from contrib/VehicleRetrogradeRecognition/test/main.cpp
rename to mxVision/mxVision-referenceapps/VehicleRetrogradeRecognition/test/main.cpp
diff --git a/contrib/VideoGestureRecognition/BlockingQueue/.keep b/mxVision/mxVision-referenceapps/VideoGestureRecognition/.keep
similarity index 100%
rename from contrib/VideoGestureRecognition/BlockingQueue/.keep
rename to mxVision/mxVision-referenceapps/VideoGestureRecognition/.keep
diff --git a/contrib/VideoGestureRecognition/FrameSkippingSampling/.keep b/mxVision/mxVision-referenceapps/VideoGestureRecognition/BlockingQueue/.keep
similarity index 100%
rename from contrib/VideoGestureRecognition/FrameSkippingSampling/.keep
rename to mxVision/mxVision-referenceapps/VideoGestureRecognition/BlockingQueue/.keep
diff --git a/contrib/VideoGestureRecognition/BlockingQueue/BlockingQueue.h b/mxVision/mxVision-referenceapps/VideoGestureRecognition/BlockingQueue/BlockingQueue.h
similarity index 95%
rename from contrib/VideoGestureRecognition/BlockingQueue/BlockingQueue.h
rename to mxVision/mxVision-referenceapps/VideoGestureRecognition/BlockingQueue/BlockingQueue.h
index 770fcac504d04b9add969d3f374baa69c1eaea1d..c94c13413145b8cf35db219bbb56d1404e7529c7 100644
--- a/contrib/VideoGestureRecognition/BlockingQueue/BlockingQueue.h
+++ b/mxVision/mxVision-referenceapps/VideoGestureRecognition/BlockingQueue/BlockingQueue.h
@@ -1,208 +1,208 @@
-/*
- * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-#ifndef VIDEOGESTUREREASONER_BLOCKINGQUEUE_H
-#define VIDEOGESTUREREASONER_BLOCKINGQUEUE_H
-
-#include <condition_variable>
-#include <list>
-#include <mutex>
-#include <cstdint>
-#include "MxBase/ErrorCode/ErrorCode.h"
-
-template <typename T> class BlockingQueue {
-public:
-    explicit BlockingQueue(uint32_t maxSize = DEFAULT_MAX_QUEUE_SIZE) : maxSize(maxSize), isStopped(false) {}
-    ~BlockingQueue() = default;
-
-    APP_ERROR Pop(T& item)
-    {
-        std::unique_lock<std::mutex> lock(mutex);
-
-        while (queue_.empty() && !isStopped) {
-            emptyCond.wait(lock);
-        }
-
-        if (isStopped) {
-            return APP_ERR_QUEUE_STOPED;
-        }
-
-        if (queue_.empty()) {
-            return APP_ERR_QUEUE_EMPTY;
-        } else {
-            item = queue_.front();
-            queue_.pop_front();
-        }
-
-        fullCond.notify_one();
-
-        return APP_ERR_OK;
-    }
-
-    APP_ERROR Pop(T& item, uint32_t timeOutMs)
-    {
-        std::unique_lock<std::mutex> lock(mutex);
-        auto realTime = std::chrono::milliseconds(timeOutMs);
-
-        while (queue_.empty() && !isStopped) {
-            emptyCond.wait_for(lock, realTime);
-        }
-
-        if (isStopped) {
-            return APP_ERR_QUEUE_STOPED;
-        }
-
-        if (queue_.empty()) {
-            return APP_ERR_QUEUE_EMPTY;
-        } else {
-            item = queue_.front();
-            queue_.pop_front();
-        }
-
-        fullCond.notify_one();
-
-        return APP_ERR_OK;
-    }
-
-    APP_ERROR Push(const T& item, bool isWait = false)
-    {
-        std::unique_lock<std::mutex> lock(mutex);
-
-        while (queue_.size() >= maxSize && isWait && !isStopped) {
-            fullCond.wait(lock);
-        }
-
-        if (isStopped) {
-            return APP_ERR_QUEUE_STOPED;
-        }
-
-        if (queue_.size() >= maxSize) {
-            return APP_ERR_QUEUE_FULL;
-        }
-        queue_.push_back(item);
-
-        emptyCond.notify_one();
-
-        return APP_ERR_OK;
-    }
-
-    APP_ERROR Push_Front(const T &item, bool isWait = false)
-    {
-        std::unique_lock<std::mutex> lock(mutex);
-
-        while (queue_.size() >= maxSize && isWait && !isStopped) {
-            fullCond.wait(lock);
-        }
-
-        if (isStopped) {
-            return APP_ERR_QUEUE_STOPED;
-        }
-
-        if (queue_.size() >= maxSize) {
-            return APP_ERR_QUEUE_FULL;
-        }
-
-        queue_.push_front(item);
-
-        emptyCond.notify_one();
-
-        return APP_ERR_OK;
-    }
-
-    void Stop()
-    {
-        {
-            std::unique_lock<std::mutex> lock(mutex);
-            isStopped = true;
-        }
-
-        fullCond.notify_all();
-        emptyCond.notify_all();
-    }
-
-    void Restart()
-    {
-        {
-            std::unique_lock<std::mutex> lock(mutex);
-            isStopped = false;
-        }
-    }
-
-// if the queue is stopped ,need call this function to release the unprocessed items
-    std::list<T> GetRemainItems()
-    {
-        std::unique_lock<std::mutex> lock(mutex);
-
-        if (!isStopped) {
-            return std::list<T>();
-        }
-
-        return queue_;
-    }
-
-    APP_ERROR GetBackItem(T &item)
-    {
-        if (isStopped) {
-            return APP_ERR_QUEUE_STOPED;
-        }
-
-        if (queue_.empty()) {
-            return APP_ERR_QUEUE_EMPTY;
-        }
-
-        item = queue_.back();
-        return APP_ERR_OK;
-    }
-
-    APP_ERROR IsEmpty()
-    {
-        return queue_.empty();
-    }
-
-    APP_ERROR IsFull()
-    {
-        std::unique_lock<std::mutex> lock(mutex);
-        return queue_.size() >= maxSize;
-    }
-
-    int GetSize() const
-    {
-        return queue_.size();
-    }
-
-    std::mutex *GetLock()
-    {
-        return &mutex;
-    }
-
-    void Clear()
-    {
-        std::unique_lock<std::mutex> lock(mutex);
-        queue_.clear();
-    }
-
-private:
-    std::list<T> queue_;
-    std::mutex mutex;
-    std::condition_variable emptyCond;
-    std::condition_variable fullCond;
-    uint32_t maxSize;
-
-    bool isStopped;
-
-private:
-    static const int DEFAULT_MAX_QUEUE_SIZE = 256;
-};
-#endif // MULTICHANNELVIDEODETECTION_BLOCKINGQUEUE_H
+/*
+ * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#ifndef VIDEOGESTUREREASONER_BLOCKINGQUEUE_H
+#define VIDEOGESTUREREASONER_BLOCKINGQUEUE_H
+
+#include <condition_variable>
+#include <list>
+#include <mutex>
+#include <cstdint>
+#include "MxBase/ErrorCode/ErrorCode.h"
+
+template <typename T> class BlockingQueue {
+public:
+    explicit BlockingQueue(uint32_t maxSize = DEFAULT_MAX_QUEUE_SIZE) : maxSize(maxSize), isStopped(false) {}
+    ~BlockingQueue() = default;
+
+    APP_ERROR Pop(T& item)
+    {
+        std::unique_lock<std::mutex> lock(mutex);
+
+        while (queue_.empty() && !isStopped) {
+            emptyCond.wait(lock);
+        }
+
+        if (isStopped) {
+            return APP_ERR_QUEUE_STOPED;
+        }
+
+        if (queue_.empty()) {
+            return APP_ERR_QUEUE_EMPTY;
+        } else {
+            item = queue_.front();
+            queue_.pop_front();
+        }
+
+        fullCond.notify_one();
+
+        return APP_ERR_OK;
+    }
+
+    APP_ERROR Pop(T& item, uint32_t timeOutMs)
+    {
+        std::unique_lock<std::mutex> lock(mutex);
+        auto realTime = std::chrono::milliseconds(timeOutMs);
+
+        while (queue_.empty() && !isStopped) {
+            emptyCond.wait_for(lock, realTime);
+        }
+
+        if (isStopped) {
+            return APP_ERR_QUEUE_STOPED;
+        }
+
+        if (queue_.empty()) {
+            return APP_ERR_QUEUE_EMPTY;
+        } else {
+            item = queue_.front();
+            queue_.pop_front();
+        }
+
+        fullCond.notify_one();
+
+        return APP_ERR_OK;
+    }
+
+    APP_ERROR Push(const T& item, bool isWait = false)
+    {
+        std::unique_lock<std::mutex> lock(mutex);
+
+        while (queue_.size() >= maxSize && isWait && !isStopped) {
+            fullCond.wait(lock);
+        }
+
+        if (isStopped) {
+            return APP_ERR_QUEUE_STOPED;
+        }
+
+        if (queue_.size() >= maxSize) {
+            return APP_ERR_QUEUE_FULL;
+        }
+        queue_.push_back(item);
+
+        emptyCond.notify_one();
+
+        return APP_ERR_OK;
+    }
+
+    APP_ERROR Push_Front(const T &item, bool isWait = false)
+    {
+        std::unique_lock<std::mutex> lock(mutex);
+
+        while (queue_.size() >= maxSize && isWait && !isStopped) {
+            fullCond.wait(lock);
+        }
+
+        if (isStopped) {
+            return APP_ERR_QUEUE_STOPED;
+        }
+
+        if (queue_.size() >= maxSize) {
+            return APP_ERR_QUEUE_FULL;
+        }
+
+        queue_.push_front(item);
+
+        emptyCond.notify_one();
+
+        return APP_ERR_OK;
+    }
+
+    void Stop()
+    {
+        {
+            std::unique_lock<std::mutex> lock(mutex);
+            isStopped = true;
+        }
+
+        fullCond.notify_all();
+        emptyCond.notify_all();
+    }
+
+    void Restart()
+    {
+        {
+            std::unique_lock<std::mutex> lock(mutex);
+            isStopped = false;
+        }
+    }
+
+// if the queue is stopped ,need call this function to release the unprocessed items
+    std::list<T> GetRemainItems()
+    {
+        std::unique_lock<std::mutex> lock(mutex);
+
+        if (!isStopped) {
+            return std::list<T>();
+        }
+
+        return queue_;
+    }
+
+    APP_ERROR GetBackItem(T &item)
+    {
+        if (isStopped) {
+            return APP_ERR_QUEUE_STOPED;
+        }
+
+        if (queue_.empty()) {
+            return APP_ERR_QUEUE_EMPTY;
+        }
+
+        item = queue_.back();
+        return APP_ERR_OK;
+    }
+
+    APP_ERROR IsEmpty()
+    {
+        return queue_.empty();
+    }
+
+    APP_ERROR IsFull()
+    {
+        std::unique_lock<std::mutex> lock(mutex);
+        return queue_.size() >= maxSize;
+    }
+
+    int GetSize() const
+    {
+        return queue_.size();
+    }
+
+    std::mutex *GetLock()
+    {
+        return &mutex;
+    }
+
+    void Clear()
+    {
+        std::unique_lock<std::mutex> lock(mutex);
+        queue_.clear();
+    }
+
+private:
+    std::list<T> queue_;
+    std::mutex mutex;
+    std::condition_variable emptyCond;
+    std::condition_variable fullCond;
+    uint32_t maxSize;
+
+    bool isStopped;
+
+private:
+    static const int DEFAULT_MAX_QUEUE_SIZE = 256;
+};
+#endif // MULTICHANNELVIDEODETECTION_BLOCKINGQUEUE_H
diff --git a/contrib/VideoGestureRecognition/CMakeLists.txt b/mxVision/mxVision-referenceapps/VideoGestureRecognition/CMakeLists.txt
similarity index 96%
rename from contrib/VideoGestureRecognition/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/VideoGestureRecognition/CMakeLists.txt
index e7d77ac720157395cfffd5851ad5d8af4ede2ef9..76a25181eaa1a2f25bc1c562a285e9867745cba6 100644
--- a/contrib/VideoGestureRecognition/CMakeLists.txt
+++ b/mxVision/mxVision-referenceapps/VideoGestureRecognition/CMakeLists.txt
@@ -1,52 +1,52 @@
-cmake_minimum_required(VERSION 3.10)
-project(MultiChannelVideoDetection)
-
-add_compile_options(-fPIC -fstack-protector-all -g -Wl,-z,relro,-z,now,-z -pie -Wall)
-add_definitions(-D_GLIBCXX_USE_CXX11_ABI=0 -Dgoogle=mindxsdk_private)
-
-set(CMAKE_RUNTIME_OUTPUT_DIRECTORY "${CMAKE_CURRENT_SOURCE_DIR}/")
-set(OUTPUT_NAME "videoGestureRecognition")
-
-set(MX_SDK_HOME "$ENV{MX_SDK_HOME}")
-set(FFMPEG_PATH {ffmpeg实际安装路径})
-
-include_directories(
-        ${CMAKE_CURRENT_SOURCE_DIR}
-        ${MX_SDK_HOME}/include
-        ${MX_SDK_HOME}/opensource/include
-        ${MX_SDK_HOME}/opensource/include/opencv4
-        ${MX_SDK_HOME}/include/MxBase/postprocess/include
-        ${FFMPEG_PATH}/include
-)
-
-link_directories(
-        ${MX_SDK_HOME}/lib
-        ${MX_SDK_HOME}/opensource/lib
-        ${MX_SDK_HOME}/lib/modelpostprocessors
-        ${FFMPEG_PATH}/lib
-)
-
-add_executable(${OUTPUT_NAME} main.cpp
-        Util/Util.cpp
-        StreamPuller/StreamPuller.cpp
-        VideoDecoder/VideoDecoder.cpp
-        ImageResizer/ImageResizer.cpp
-        ResnetDetector/ResnetDetector.cpp
-        VideoGestureReasoner/VideoGestureReasoner.cpp
-        FrameSkippingSampling/FrameSkippingSampling.cpp
-        VideoGestureReasoner/VideoGestureReasoner.cpp)
-target_link_libraries(${OUTPUT_NAME}
-        avcodec
-        avdevice
-        avfilter
-        avformat
-        avcodec
-        avutil
-        swscale
-        swresample
-        glog
-        mxbase
-        opencv_world
-        pthread m
-        resnet50postprocess
+cmake_minimum_required(VERSION 3.10)
+project(MultiChannelVideoDetection)
+
+add_compile_options(-fPIC -fstack-protector-all -g -Wl,-z,relro,-z,now,-z -pie -Wall)
+add_definitions(-D_GLIBCXX_USE_CXX11_ABI=0 -Dgoogle=mindxsdk_private)
+
+set(CMAKE_RUNTIME_OUTPUT_DIRECTORY "${CMAKE_CURRENT_SOURCE_DIR}/")
+set(OUTPUT_NAME "videoGestureRecognition")
+
+set(MX_SDK_HOME "$ENV{MX_SDK_HOME}")
+set(FFMPEG_PATH {ffmpeg实际安装路径})
+
+include_directories(
+        ${CMAKE_CURRENT_SOURCE_DIR}
+        ${MX_SDK_HOME}/include
+        ${MX_SDK_HOME}/opensource/include
+        ${MX_SDK_HOME}/opensource/include/opencv4
+        ${MX_SDK_HOME}/include/MxBase/postprocess/include
+        ${FFMPEG_PATH}/include
+)
+
+link_directories(
+        ${MX_SDK_HOME}/lib
+        ${MX_SDK_HOME}/opensource/lib
+        ${MX_SDK_HOME}/lib/modelpostprocessors
+        ${FFMPEG_PATH}/lib
+)
+
+add_executable(${OUTPUT_NAME} main.cpp
+        Util/Util.cpp
+        StreamPuller/StreamPuller.cpp
+        VideoDecoder/VideoDecoder.cpp
+        ImageResizer/ImageResizer.cpp
+        ResnetDetector/ResnetDetector.cpp
+        VideoGestureReasoner/VideoGestureReasoner.cpp
+        FrameSkippingSampling/FrameSkippingSampling.cpp
+        VideoGestureReasoner/VideoGestureReasoner.cpp)
+target_link_libraries(${OUTPUT_NAME}
+        avcodec
+        avdevice
+        avfilter
+        avformat
+        avcodec
+        avutil
+        swscale
+        swresample
+        glog
+        mxbase
+        opencv_world
+        pthread m
+        resnet50postprocess
         )
\ No newline at end of file
diff --git a/contrib/VideoGestureRecognition/ImageResizer/.keep b/mxVision/mxVision-referenceapps/VideoGestureRecognition/FrameSkippingSampling/.keep
similarity index 100%
rename from contrib/VideoGestureRecognition/ImageResizer/.keep
rename to mxVision/mxVision-referenceapps/VideoGestureRecognition/FrameSkippingSampling/.keep
diff --git a/contrib/VideoGestureRecognition/FrameSkippingSampling/FrameSkippingSampling.cpp b/mxVision/mxVision-referenceapps/VideoGestureRecognition/FrameSkippingSampling/FrameSkippingSampling.cpp
similarity index 97%
rename from contrib/VideoGestureRecognition/FrameSkippingSampling/FrameSkippingSampling.cpp
rename to mxVision/mxVision-referenceapps/VideoGestureRecognition/FrameSkippingSampling/FrameSkippingSampling.cpp
index 899ec7ce2e31ef540c2fa49f4ee25a1f217ab188..6dd8c2652e32c34eb9b82c210ec8685ec3f1a9a5 100644
--- a/contrib/VideoGestureRecognition/FrameSkippingSampling/FrameSkippingSampling.cpp
+++ b/mxVision/mxVision-referenceapps/VideoGestureRecognition/FrameSkippingSampling/FrameSkippingSampling.cpp
@@ -1,62 +1,62 @@
-/*
- * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#include "FrameSkippingSampling.h"
-#include "MxBase/Log/Log.h"
-
-namespace AscendFrameSkippingSampling {
-    uint32_t FrameSkippingSampling::g_samplingCounter = 0;
-
-    APP_ERROR FrameSkippingSampling::Init(uint32_t maxSamplingInterval,
-                                          uint32_t samplingInterval,
-                                          uint32_t deviceId)
-    {
-        LogDebug << "FrameSkippingSampling" << ": FrameSkippingSampling init start.";
-
-        stopFlag = false;
-        this->maxSamplingInterval = maxSamplingInterval;
-        this->samplingInterval = samplingInterval;
-        this->deviceId = deviceId;
-
-        LogDebug << "FrameSkippingSampling" << ": FrameSkippingSampling init success.";
-        return APP_ERR_OK;
-    }
-
-    APP_ERROR FrameSkippingSampling::DeInit()
-    {
-        LogDebug << "FrameSkippingSampling" << ": FrameSkippingSampling deinit start.";
-
-        stopFlag = true;
-        samplingInterval = 1;
-
-        LogDebug << "FrameSkippingSampling" << ": FrameSkippingSampling deinit success.";
-        return APP_ERR_OK;
-    }
-
-    APP_ERROR FrameSkippingSampling::Process()
-    {
-        stopFlag = false;
-        if (samplingInterval > maxSamplingInterval) {
-            LogError << "sample interval exceeding the upper limit";
-            return APP_ERR_COMM_FAILURE;
-        }
-        if (g_samplingCounter % samplingInterval == 0) {
-            stopFlag = true;
-        }
-        g_samplingCounter += 1;
-        return APP_ERR_OK;
-    }
-}
+/*
+ * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "FrameSkippingSampling.h"
+#include "MxBase/Log/Log.h"
+
+namespace AscendFrameSkippingSampling {
+    uint32_t FrameSkippingSampling::g_samplingCounter = 0;
+
+    APP_ERROR FrameSkippingSampling::Init(uint32_t maxSamplingInterval,
+                                          uint32_t samplingInterval,
+                                          uint32_t deviceId)
+    {
+        LogDebug << "FrameSkippingSampling" << ": FrameSkippingSampling init start.";
+
+        stopFlag = false;
+        this->maxSamplingInterval = maxSamplingInterval;
+        this->samplingInterval = samplingInterval;
+        this->deviceId = deviceId;
+
+        LogDebug << "FrameSkippingSampling" << ": FrameSkippingSampling init success.";
+        return APP_ERR_OK;
+    }
+
+    APP_ERROR FrameSkippingSampling::DeInit()
+    {
+        LogDebug << "FrameSkippingSampling" << ": FrameSkippingSampling deinit start.";
+
+        stopFlag = true;
+        samplingInterval = 1;
+
+        LogDebug << "FrameSkippingSampling" << ": FrameSkippingSampling deinit success.";
+        return APP_ERR_OK;
+    }
+
+    APP_ERROR FrameSkippingSampling::Process()
+    {
+        stopFlag = false;
+        if (samplingInterval > maxSamplingInterval) {
+            LogError << "sample interval exceeding the upper limit";
+            return APP_ERR_COMM_FAILURE;
+        }
+        if (g_samplingCounter % samplingInterval == 0) {
+            stopFlag = true;
+        }
+        g_samplingCounter += 1;
+        return APP_ERR_OK;
+    }
+}
diff --git a/contrib/VideoGestureRecognition/FrameSkippingSampling/FrameSkippingSampling.h b/mxVision/mxVision-referenceapps/VideoGestureRecognition/FrameSkippingSampling/FrameSkippingSampling.h
similarity index 96%
rename from contrib/VideoGestureRecognition/FrameSkippingSampling/FrameSkippingSampling.h
rename to mxVision/mxVision-referenceapps/VideoGestureRecognition/FrameSkippingSampling/FrameSkippingSampling.h
index 3b45fb6673017cd9c22be582dc37b9adbbc4092a..853d38d79179c92ff8a294e0ef7f6644017430a7 100644
--- a/contrib/VideoGestureRecognition/FrameSkippingSampling/FrameSkippingSampling.h
+++ b/mxVision/mxVision-referenceapps/VideoGestureRecognition/FrameSkippingSampling/FrameSkippingSampling.h
@@ -1,48 +1,48 @@
-/*
- * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#ifndef VIDEOGESTUREREASONER_FRAMESKIPPINGSAMPLING_H
-#define VIDEOGESTUREREASONER_FRAMESKIPPINGSAMPLING_H
-
-#include "MxBase/ErrorCode/ErrorCode.h"
-
-namespace AscendFrameSkippingSampling {
-    class FrameSkippingSampling {
-    public:
-        FrameSkippingSampling() = default;
-
-        ~FrameSkippingSampling() = default;
-
-        APP_ERROR Init(uint32_t maxSamplingInterval, uint32_t samplingInterval, uint32_t deviceId);
-
-        APP_ERROR DeInit();
-
-        APP_ERROR Process();
-
-    public:
-        bool stopFlag;
-
-    private:
-        static uint32_t g_samplingCounter;
-        // device id
-        uint32_t deviceId = 0;
-        // Sampling interval
-        uint32_t samplingInterval = 0;
-        // max Sampling interval
-        uint32_t maxSamplingInterval = 0;
-    };
-} // end AscendFrameSkippingSampling
-#endif // MULTICHANNELVIDEODETECTION_FRAMESKIPPINGSAMPLING_H
+/*
+ * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef VIDEOGESTUREREASONER_FRAMESKIPPINGSAMPLING_H
+#define VIDEOGESTUREREASONER_FRAMESKIPPINGSAMPLING_H
+
+#include "MxBase/ErrorCode/ErrorCode.h"
+
+namespace AscendFrameSkippingSampling {
+    class FrameSkippingSampling {
+    public:
+        FrameSkippingSampling() = default;
+
+        ~FrameSkippingSampling() = default;
+
+        APP_ERROR Init(uint32_t maxSamplingInterval, uint32_t samplingInterval, uint32_t deviceId);
+
+        APP_ERROR DeInit();
+
+        APP_ERROR Process();
+
+    public:
+        bool stopFlag;
+
+    private:
+        static uint32_t g_samplingCounter;
+        // device id
+        uint32_t deviceId = 0;
+        // Sampling interval
+        uint32_t samplingInterval = 0;
+        // max Sampling interval
+        uint32_t maxSamplingInterval = 0;
+    };
+} // end AscendFrameSkippingSampling
+#endif // MULTICHANNELVIDEODETECTION_FRAMESKIPPINGSAMPLING_H
diff --git a/contrib/VideoGestureRecognition/ResnetDetector/.keep b/mxVision/mxVision-referenceapps/VideoGestureRecognition/ImageResizer/.keep
similarity index 100%
rename from contrib/VideoGestureRecognition/ResnetDetector/.keep
rename to mxVision/mxVision-referenceapps/VideoGestureRecognition/ImageResizer/.keep
diff --git a/contrib/VideoGestureRecognition/ImageResizer/ImageResizer.cpp b/mxVision/mxVision-referenceapps/VideoGestureRecognition/ImageResizer/ImageResizer.cpp
similarity index 97%
rename from contrib/VideoGestureRecognition/ImageResizer/ImageResizer.cpp
rename to mxVision/mxVision-referenceapps/VideoGestureRecognition/ImageResizer/ImageResizer.cpp
index b7b6f0d5bb31bea464b6ceaa3b74d87b41d52454..74ffd0cf9e18d92f7c03f2bd8810d54d5e196bf6 100644
--- a/contrib/VideoGestureRecognition/ImageResizer/ImageResizer.cpp
+++ b/mxVision/mxVision-referenceapps/VideoGestureRecognition/ImageResizer/ImageResizer.cpp
@@ -1,99 +1,99 @@
-/*
- * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#include "ImageResizer.h"
-#include "MxBase/Log/Log.h"
-
-namespace AscendImageResizer {
-APP_ERROR ImageResizer::Init(uint32_t deviceId)
-{
-    LogDebug << "ImageResizer init start.";
-    this->deviceId = deviceId;
-
-    // init DvppWrapper
-    vDvppWrapper = std::make_shared<MxBase::DvppWrapper>();
-    APP_ERROR ret = vDvppWrapper->Init();
-    if (ret != APP_ERR_OK) {
-        LogError << "DvppWrapper init failed, ret = " << ret << ".";
-        return ret;
-    }
-
-    stopFlag = false;
-    LogDebug << "ImageResizer init successful.";
-    return  APP_ERR_OK;
-}
-
-APP_ERROR ImageResizer::DeInit()
-{
-    LogDebug << "ImageResizer deinit start.";
-
-    APP_ERROR ret = vDvppWrapper->DeInit();
-    if (ret != APP_ERR_OK) {
-        LogError << "DvppWrapper deinit failed.";
-        return ret;
-    }
-
-    stopFlag = true;
-
-    LogDebug << "ImageResizer deinit successful.";
-    return APP_ERR_OK;
-}
-
-APP_ERROR ImageResizer::Resize(MxBase::DvppDataInfo &inputImageInfo,
-                               const uint32_t &resizeWidth, const uint32_t &resizeHeight,
-                               MxBase::DvppDataInfo &outputImageInfo)
-{
-    // check image
-    if (inputImageInfo.data == nullptr || inputImageInfo.dataSize <= 0 ||
-        inputImageInfo.width <= 0 || inputImageInfo.height <= 0) {
-        LogError << "Invalid image.";
-        return APP_ERR_COMM_INVALID_PARAM;
-    }
-
-    MxBase::ResizeConfig resizeConfig = {};
-    resizeConfig.width = resizeWidth;
-    resizeConfig.height = resizeHeight;
-
-    APP_ERROR ret = vDvppWrapper->VpcResize(inputImageInfo, outputImageInfo, resizeConfig);
-    if (ret != APP_ERR_OK) {
-        LogError << GetError(ret) << "VpcResize failed.";
-        return ret;
-    }
-
-    return APP_ERR_OK;
-}
-
-APP_ERROR ImageResizer::ResizeFromMemory(MxBase::MemoryData &imageInfo, const ImageResizerParma &imageInitParma,
-                                         MxBase::DvppDataInfo &outputImageInfo)
-{
-    // check image
-    if (imageInfo.ptrData == nullptr || imageInfo.size <= 0) {
-        LogError << "Invalid image.";
-        return APP_ERR_COMM_INVALID_PARAM;
-    }
-
-    MxBase::DvppDataInfo input = {};
-    input.width = imageInitParma.originWidth;
-    input.height = imageInitParma.originHeight;
-    input.widthStride = imageInitParma.originWidth;
-    input.heightStride = imageInitParma.originHeight;
-    input.dataSize = imageInfo.size;
-    input.data = (uint8_t*)imageInfo.ptrData;
-    input.frameId = imageInfo.deviceId;
-
-    return Resize(input, imageInitParma.resizeWidth, imageInitParma.resizeHeight, outputImageInfo);
-}
-} // end AscendImageResizer
+/*
+ * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "ImageResizer.h"
+#include "MxBase/Log/Log.h"
+
+namespace AscendImageResizer {
+APP_ERROR ImageResizer::Init(uint32_t deviceId)
+{
+    LogDebug << "ImageResizer init start.";
+    this->deviceId = deviceId;
+
+    // init DvppWrapper
+    vDvppWrapper = std::make_shared<MxBase::DvppWrapper>();
+    APP_ERROR ret = vDvppWrapper->Init();
+    if (ret != APP_ERR_OK) {
+        LogError << "DvppWrapper init failed, ret = " << ret << ".";
+        return ret;
+    }
+
+    stopFlag = false;
+    LogDebug << "ImageResizer init successful.";
+    return  APP_ERR_OK;
+}
+
+APP_ERROR ImageResizer::DeInit()
+{
+    LogDebug << "ImageResizer deinit start.";
+
+    APP_ERROR ret = vDvppWrapper->DeInit();
+    if (ret != APP_ERR_OK) {
+        LogError << "DvppWrapper deinit failed.";
+        return ret;
+    }
+
+    stopFlag = true;
+
+    LogDebug << "ImageResizer deinit successful.";
+    return APP_ERR_OK;
+}
+
+APP_ERROR ImageResizer::Resize(MxBase::DvppDataInfo &inputImageInfo,
+                               const uint32_t &resizeWidth, const uint32_t &resizeHeight,
+                               MxBase::DvppDataInfo &outputImageInfo)
+{
+    // check image
+    if (inputImageInfo.data == nullptr || inputImageInfo.dataSize <= 0 ||
+        inputImageInfo.width <= 0 || inputImageInfo.height <= 0) {
+        LogError << "Invalid image.";
+        return APP_ERR_COMM_INVALID_PARAM;
+    }
+
+    MxBase::ResizeConfig resizeConfig = {};
+    resizeConfig.width = resizeWidth;
+    resizeConfig.height = resizeHeight;
+
+    APP_ERROR ret = vDvppWrapper->VpcResize(inputImageInfo, outputImageInfo, resizeConfig);
+    if (ret != APP_ERR_OK) {
+        LogError << GetError(ret) << "VpcResize failed.";
+        return ret;
+    }
+
+    return APP_ERR_OK;
+}
+
+APP_ERROR ImageResizer::ResizeFromMemory(MxBase::MemoryData &imageInfo, const ImageResizerParma &imageInitParma,
+                                         MxBase::DvppDataInfo &outputImageInfo)
+{
+    // check image
+    if (imageInfo.ptrData == nullptr || imageInfo.size <= 0) {
+        LogError << "Invalid image.";
+        return APP_ERR_COMM_INVALID_PARAM;
+    }
+
+    MxBase::DvppDataInfo input = {};
+    input.width = imageInitParma.originWidth;
+    input.height = imageInitParma.originHeight;
+    input.widthStride = imageInitParma.originWidth;
+    input.heightStride = imageInitParma.originHeight;
+    input.dataSize = imageInfo.size;
+    input.data = (uint8_t*)imageInfo.ptrData;
+    input.frameId = imageInfo.deviceId;
+
+    return Resize(input, imageInitParma.resizeWidth, imageInitParma.resizeHeight, outputImageInfo);
+}
+} // end AscendImageResizer
diff --git a/contrib/VideoGestureRecognition/ImageResizer/ImageResizer.h b/mxVision/mxVision-referenceapps/VideoGestureRecognition/ImageResizer/ImageResizer.h
similarity index 97%
rename from contrib/VideoGestureRecognition/ImageResizer/ImageResizer.h
rename to mxVision/mxVision-referenceapps/VideoGestureRecognition/ImageResizer/ImageResizer.h
index 4769c865373ae7868d998f34b1c1ae4f25675a14..0defb1854ecfd31dfd9328639689793944e92f4b 100644
--- a/contrib/VideoGestureRecognition/ImageResizer/ImageResizer.h
+++ b/mxVision/mxVision-referenceapps/VideoGestureRecognition/ImageResizer/ImageResizer.h
@@ -1,57 +1,57 @@
-/*
- * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#ifndef VIDEOGESTUREREASONER_IMAGERESIZER_H
-#define VIDEOGESTUREREASONER_IMAGERESIZER_H
-
-#include "MxBase/ErrorCode/ErrorCode.h"
-#include "MxBase/DvppWrapper/DvppWrapper.h"
-#include "MxBase/MemoryHelper/MemoryHelper.h"
-#include "../BlockingQueue/BlockingQueue.h"
-
-namespace AscendImageResizer {
-    struct ImageResizerParma{
-        uint32_t originWidth = 0;
-        uint32_t originHeight = 0;
-        uint32_t resizeWidth = 0;
-        uint32_t resizeHeight = 0;
-    };
-class ImageResizer {
-public:
-    ImageResizer() = default;
-    ~ImageResizer() = default;
-
-    APP_ERROR Init(uint32_t deviceId);
-    APP_ERROR DeInit();
-    APP_ERROR Resize(MxBase::DvppDataInfo &inputImageInfo,
-                     const uint32_t &resizeWidth, const uint32_t &resizeHeight,
-                     MxBase::DvppDataInfo &outputImageInfo);
-    APP_ERROR ResizeFromMemory(MxBase::MemoryData &imageInfo, const ImageResizerParma &imageInitParma,
-                     MxBase::DvppDataInfo &outputImageInfo);
-
-public:
-    // running flag
-    bool stopFlag = false;
-
-private:
-    // image processor
-    std::shared_ptr<MxBase::DvppWrapper> vDvppWrapper;
-
-    // device id
-    uint32_t deviceId = 0;
-};
-} // end AscendImageResizer
-#endif // MULTICHANNELVIDEODETECTION_IMAGERESIZER_H
+/*
+ * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef VIDEOGESTUREREASONER_IMAGERESIZER_H
+#define VIDEOGESTUREREASONER_IMAGERESIZER_H
+
+#include "MxBase/ErrorCode/ErrorCode.h"
+#include "MxBase/DvppWrapper/DvppWrapper.h"
+#include "MxBase/MemoryHelper/MemoryHelper.h"
+#include "../BlockingQueue/BlockingQueue.h"
+
+namespace AscendImageResizer {
+    struct ImageResizerParma{
+        uint32_t originWidth = 0;
+        uint32_t originHeight = 0;
+        uint32_t resizeWidth = 0;
+        uint32_t resizeHeight = 0;
+    };
+class ImageResizer {
+public:
+    ImageResizer() = default;
+    ~ImageResizer() = default;
+
+    APP_ERROR Init(uint32_t deviceId);
+    APP_ERROR DeInit();
+    APP_ERROR Resize(MxBase::DvppDataInfo &inputImageInfo,
+                     const uint32_t &resizeWidth, const uint32_t &resizeHeight,
+                     MxBase::DvppDataInfo &outputImageInfo);
+    APP_ERROR ResizeFromMemory(MxBase::MemoryData &imageInfo, const ImageResizerParma &imageInitParma,
+                     MxBase::DvppDataInfo &outputImageInfo);
+
+public:
+    // running flag
+    bool stopFlag = false;
+
+private:
+    // image processor
+    std::shared_ptr<MxBase::DvppWrapper> vDvppWrapper;
+
+    // device id
+    uint32_t deviceId = 0;
+};
+} // end AscendImageResizer
+#endif // MULTICHANNELVIDEODETECTION_IMAGERESIZER_H
diff --git a/contrib/VideoGestureRecognition/README.md b/mxVision/mxVision-referenceapps/VideoGestureRecognition/README.md
similarity index 97%
rename from contrib/VideoGestureRecognition/README.md
rename to mxVision/mxVision-referenceapps/VideoGestureRecognition/README.md
index ccf965049e9417a48278a17a3272827916e35079..cf4ff70946c603314c129b0d3cb52b30468ea208 100644
--- a/contrib/VideoGestureRecognition/README.md
+++ b/mxVision/mxVision-referenceapps/VideoGestureRecognition/README.md
@@ -1,205 +1,205 @@
-# 基于MxBase的视频手势识别运行
-
-## 介绍
-
-手势识别是指对视频中出现的手势进行分类，实现对本地（H264）进行手势识别并分类，生成可视化结果。
-使用测试视频中的手势尺寸大致应为视频大小的二分之一，同时应当符合国际标准，背景要单一，手势要清晰，光线充足；视频切勿有遮挡，不清晰等情况。
-
-### 目录结构
-```
-.
-|-------- BlockingQueue
-|           |---- BlockingQueue.h                   // 阻塞队列 (视频帧缓存容器)
-|-------- ImageResizer
-|           |---- ImageResizer.cpp                  // 图片缩放.cpp
-|           |---- ImageResizer.h                    // 图片缩放.h
-|-------- FrameSkippingSampling
-|           |---- FrameSkippingSampling.cpp         // 跳帧采样.cpp
-|           |---- FrameSkippingSampling.h           // 跳帧采样.h
-|-------- model
-|           |---- resnet18.cfg                      // Resnet18 模型转换配置文件
-|           |---- resnet18.names                    // Resnet18 标签文件
-|-------- VideoGestureReasoner
-|           |---- VideoGestureReasoner.cpp          // 视频手势推理业务逻辑封装.cpp
-|           |---- VideoGestureReasoner.h            // 视频手势推理业务逻辑封装.h
-|-------- result                                    // 推理结果存放处（图片的形式）
-|-------- StreamPuller
-|           |---- StreamPuller.cpp                  // 视频拉流.cpp
-|           |---- StreamPuller.h                    // 视频拉流.h
-|-------- Util
-|           |---- Util.cpp                          // 工具类.cpp
-|           |---- Util.h                            // 工具类.h
-|-------- VideoDecoder
-|           |---- VideoDecoder.cpp                  // 视频解码.cpp
-|           |---- VideoDecoder.h                    // 视频解码.h
-|-------- ResnetDetector
-|           |---- ResnetDetector.cpp                  // Resnet识别.cpp
-|           |---- ResnetDetector.h                    // Resnet识别.h
-|-------- data
-|-------- build.sh                                  // 样例编译脚本
-|-------- CMakeLists.txt                            // CMake配置
-|-------- main.cpp                                  // 视频手势识别测试样例
-|-------- README.md                                 // ReadMe
-|-------- run.sh                                    // 样例运行脚本
-
-```
-
-### 依赖
-| 依赖软件      | 版本   | 下载地址                                                     | 说明                                         |
-| ------------- | ------ | ------------------------------------------------------------ | -------------------------------------------- |
-| ffmpeg        | 4.2.1  | [Link](https://github.com/FFmpeg/FFmpeg/archive/n4.2.1.tar.gz) | 视频转码解码组件                             |
-
-**注意：**
-
-第三方库默认全部安装到/usr/local/下面，全部安装完成后，请设置环境变量
-```bash
-export PATH=/usr/local/ffmpeg/bin:$PATH
-export LD_LIBRARY_PATH=/usr/local/ffmpeg/lib:$LD_LIBRARY_PATH
-```
-
-#### FFmpeg
-
-下载完，按以下命令进行解压和编译
-
-```bash
-tar -xzvf n4.2.1.tar.gz
-cd FFmpeg-n4.2.1
-./configure --prefix=/usr/local/ffmpeg --enable-shared
-make -j
-make install
-```
-
-### 准备工作
-
-> 模型转换
-
-**步骤1** 下载Resnet18模型权重和网络以及cfg文件。[下载地址](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/VideoGestureRecognition/model.zip)
-
-**步骤2** 将获取到的文件存放至："样例项目所在目录/model/"
-
-**步骤3** 模型转换
-
-在模型权重和网络文件所在目录下执行以下命令
-
-```
-# 设置环境变量（请确认install_path路径是否正确）
-# Set environment PATH (Please confirm that the install_path is correct).
-
-export install_path=/usr/local/Ascend/ascend-toolkit/latest
-export PATH=/usr/local/python3.9.2/bin:${install_path}/atc/ccec_compiler/bin:${install_path}/atc/bin:$PATH
-export PYTHONPATH=${install_path}/atc/python/site-packages:${install_path}/atc/python/site-packages/auto_tune.egg/auto_tune:${install_path}/atc/python/site-packages/schedule_search.egg
-export LD_LIBRARY_PATH=${install_path}/atc/lib64:$LD_LIBRARY_PATH
-export ASCEND_OPP_PATH=${install_path}/opp
-
-# 执行，转换Resnet18模型
-# Execute, transform Resnet18 model.
-
-atc --model=./resnet18_gesture.prototxt --weight=./resnet18_gesture.caffemodel --framework=0 --output=gesture_yuv --soc_version=Ascend310 --insert_op_conf=./insert_op.cfg --input_shape="data:1,3,224,224" --input_format=NCHW
-```
-
-执行完模型转换脚本后，会生成相应的.om模型文件。 执行完模型转换脚本后，会生成相应的.om模型文件。
-
-模型转换使用了ATC工具，如需更多信息请参考:
-
- https://gitee.com/ascend/docs-openmind/blob/master/guide/mindx/sdk/tutorials/%E5%8F%82%E8%80%83%E8%B5%84%E6%96%99.md
-
-> 相关参数修改
-
-main.cpp中配置rtsp流源地址(需要自行准备可用的视频流，视频流格式为H264)。
-同样地测试视频也可下载（[链接](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/VideoGestureRecognition/data.zip)）。
-
-提示：使用测试视频中的手势尺寸大致应为视频大小的二分之一，同时应当符合国际标准，背景要单一，手势要清晰，光线充足；视频切勿有遮挡，不清晰等情况。
-
-[Live555拉流教程](../../docs/参考资料/Live555离线视频转RTSP说明文档.md)
-```c++ rtspList.emplace_back("#{本地或rtsp流地址}"); ```
-
-[配置ResnetDetector插件的模型加载路径modelPath]
-```c++ reasonerConfig.resnetModelPath = "${Resnet18.om模型路径}"```
-
-配置ResnetDetector插件的模型加载路径labelPath
-```c++ reasonerConfig.resnetLabelPath = "${resnet18.names路径}";```
-
-其他可配置项DECODE_FRAME_QUEUE_LENGTH DECODE_FRAME_WAIT_TIME SAMPLING_INTERVAL MAX_SAMPLING_INTERVAL
-```c++ DECODE_FRAME_QUEUE_LENGTH = 100; DECODE_FRAME_WAIT_TIME = 10; SAMPLING_INTERVAL = 24; MAX_SAMPLING_INTERVAL = 100;```
-
-
-### 配置环境变量
-
-```
-# 执行如下命令，打开.bashrc文件
-cd $HOME
-vi .bashrc
-# 在.bashrc文件中添加以下环境变量
-MX_SDK_HOME=${SDK安装路径}
-FFMPEG_PATH=${FFMPEG安装路径}
-
-LD_LIBRARY_PATH=${MX_SDK_HOME}/lib:${MX_SDK_HOME}/opensource/lib:${MX_SDK_HOME}/opensource/lib64:${FFMPEG_PATH}/lib:/usr/local/Ascend/ascend-toolkit/latest/acllib/lib64:/usr/local/Ascend/driver/lib64/
-
-GST_PLUGIN_SCANNER=${MX_SDK_HOME}/opensource/libexec/gstreamer-1.0/gst-plugin-scanner
-
-GST_PLUGIN_PATH=${MX_SDK_HOME}/opensource/lib/gstreamer-1.0:${MX_SDK_HOME}/lib/plugins
-
-# 保存退出.bashrc文件
-# 执行如下命令使环境变量生效
-source ~/.bashrc
-
-#查看环境变量
-env
-```
-
-### 配置SDK路径
-
-配置CMakeLists.txt文件中的`MX_SDK_HOME`与`FFMPEG_PATH`环境变量
-
-```
-set(MX_SDK_HOME ${SDK安装路径}/mxVision)
-set(FFMPEG_PATH {ffmpeg实际安装路径})
-
-```
-
-
-### 编译项目文件
-
-手动编译请参照 ①，脚本编译请参照 ②
-
->  ① 新建立build目录，进入build执行cmake ..（..代表包含CMakeLists.txt的源文件父目录），在build目录下生成了编译需要的Makefile和中间文件。执行make构建工程，构建成功后就会生成可执行文件。
-
-```
-mkdir build
-
-cd build
-
-cmake ..
-
-make
-
-Scanning dependencies of target sample
-[ 11%] Building CXX object CMakeFiles/sample.dir/main.cpp.o
-[ 22%] Building CXX object CMakeFiles/sample.dir/StreamPuller/StreamPuller.cpp.o
-[ 33%] Building CXX object CMakeFiles/sample.dir/VideoDecoder/VideoDecoder.cpp.o
-[ 44%] Building CXX object CMakeFiles/sample.dir/ImageResizer/ImageResizer.cpp.o
-[ 66%] Building CXX object CMakeFiles/sample.dir/ResnetDetector/ResnetDetector.cpp.o
-[ 77%] Building CXX object CMakeFiles/sample.dir/MultiChannelVideoReasoner/MultiChannelVideoReasoner.cpp.o
-[ 88%] Building CXX object CMakeFiles/sample.dir/FrameSkippingSampling/FrameSkippingSampling.cpp.o
-[100%] Linking CXX executable ../sample
-[100%] Built target sample
-# sample就是CMakeLists文件中指定生成的可执行文件。
-```
-
->  ② 运行项目根目录下的`build.sh`
-```bash
-chmod +x build.sh
-bash build.sh
-```
-### 执行脚本
-
-执行`run.sh`脚本前请先确认可执行文件`sample`已生成。
-
-```
-chmod +x run.sh
-bash run.sh
-```
-
-### 查看结果
-
+# 基于MxBase的视频手势识别运行
+
+## 介绍
+
+手势识别是指对视频中出现的手势进行分类，实现对本地（H264）进行手势识别并分类，生成可视化结果。
+使用测试视频中的手势尺寸大致应为视频大小的二分之一，同时应当符合国际标准，背景要单一，手势要清晰，光线充足；视频切勿有遮挡，不清晰等情况。
+
+### 目录结构
+```
+.
+|-------- BlockingQueue
+|           |---- BlockingQueue.h                   // 阻塞队列 (视频帧缓存容器)
+|-------- ImageResizer
+|           |---- ImageResizer.cpp                  // 图片缩放.cpp
+|           |---- ImageResizer.h                    // 图片缩放.h
+|-------- FrameSkippingSampling
+|           |---- FrameSkippingSampling.cpp         // 跳帧采样.cpp
+|           |---- FrameSkippingSampling.h           // 跳帧采样.h
+|-------- model
+|           |---- resnet18.cfg                      // Resnet18 模型转换配置文件
+|           |---- resnet18.names                    // Resnet18 标签文件
+|-------- VideoGestureReasoner
+|           |---- VideoGestureReasoner.cpp          // 视频手势推理业务逻辑封装.cpp
+|           |---- VideoGestureReasoner.h            // 视频手势推理业务逻辑封装.h
+|-------- result                                    // 推理结果存放处（图片的形式）
+|-------- StreamPuller
+|           |---- StreamPuller.cpp                  // 视频拉流.cpp
+|           |---- StreamPuller.h                    // 视频拉流.h
+|-------- Util
+|           |---- Util.cpp                          // 工具类.cpp
+|           |---- Util.h                            // 工具类.h
+|-------- VideoDecoder
+|           |---- VideoDecoder.cpp                  // 视频解码.cpp
+|           |---- VideoDecoder.h                    // 视频解码.h
+|-------- ResnetDetector
+|           |---- ResnetDetector.cpp                  // Resnet识别.cpp
+|           |---- ResnetDetector.h                    // Resnet识别.h
+|-------- data
+|-------- build.sh                                  // 样例编译脚本
+|-------- CMakeLists.txt                            // CMake配置
+|-------- main.cpp                                  // 视频手势识别测试样例
+|-------- README.md                                 // ReadMe
+|-------- run.sh                                    // 样例运行脚本
+
+```
+
+### 依赖
+| 依赖软件      | 版本   | 下载地址                                                     | 说明                                         |
+| ------------- | ------ | ------------------------------------------------------------ | -------------------------------------------- |
+| ffmpeg        | 4.2.1  | [Link](https://github.com/FFmpeg/FFmpeg/archive/n4.2.1.tar.gz) | 视频转码解码组件                             |
+
+**注意：**
+
+第三方库默认全部安装到/usr/local/下面，全部安装完成后，请设置环境变量
+```bash
+export PATH=/usr/local/ffmpeg/bin:$PATH
+export LD_LIBRARY_PATH=/usr/local/ffmpeg/lib:$LD_LIBRARY_PATH
+```
+
+#### FFmpeg
+
+下载完，按以下命令进行解压和编译
+
+```bash
+tar -xzvf n4.2.1.tar.gz
+cd FFmpeg-n4.2.1
+./configure --prefix=/usr/local/ffmpeg --enable-shared
+make -j
+make install
+```
+
+### 准备工作
+
+> 模型转换
+
+**步骤1** 下载Resnet18模型权重和网络以及cfg文件。[下载地址](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/VideoGestureRecognition/model.zip)
+
+**步骤2** 将获取到的文件存放至："样例项目所在目录/model/"
+
+**步骤3** 模型转换
+
+在模型权重和网络文件所在目录下执行以下命令
+
+```
+# 设置环境变量（请确认install_path路径是否正确）
+# Set environment PATH (Please confirm that the install_path is correct).
+
+export install_path=/usr/local/Ascend/ascend-toolkit/latest
+export PATH=/usr/local/python3.9.2/bin:${install_path}/atc/ccec_compiler/bin:${install_path}/atc/bin:$PATH
+export PYTHONPATH=${install_path}/atc/python/site-packages:${install_path}/atc/python/site-packages/auto_tune.egg/auto_tune:${install_path}/atc/python/site-packages/schedule_search.egg
+export LD_LIBRARY_PATH=${install_path}/atc/lib64:$LD_LIBRARY_PATH
+export ASCEND_OPP_PATH=${install_path}/opp
+
+# 执行，转换Resnet18模型
+# Execute, transform Resnet18 model.
+
+atc --model=./resnet18_gesture.prototxt --weight=./resnet18_gesture.caffemodel --framework=0 --output=gesture_yuv --soc_version=Ascend310 --insert_op_conf=./insert_op.cfg --input_shape="data:1,3,224,224" --input_format=NCHW
+```
+
+执行完模型转换脚本后，会生成相应的.om模型文件。 执行完模型转换脚本后，会生成相应的.om模型文件。
+
+模型转换使用了ATC工具，如需更多信息请参考:
+
+ https://gitee.com/ascend/docs-openmind/blob/master/guide/mindx/sdk/tutorials/%E5%8F%82%E8%80%83%E8%B5%84%E6%96%99.md
+
+> 相关参数修改
+
+main.cpp中配置rtsp流源地址(需要自行准备可用的视频流，视频流格式为H264)。
+同样地测试视频也可下载（[链接](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/VideoGestureRecognition/data.zip)）。
+
+提示：使用测试视频中的手势尺寸大致应为视频大小的二分之一，同时应当符合国际标准，背景要单一，手势要清晰，光线充足；视频切勿有遮挡，不清晰等情况。
+
+[Live555拉流教程](../../docs/参考资料/Live555离线视频转RTSP说明文档.md)
+```c++ rtspList.emplace_back("#{本地或rtsp流地址}"); ```
+
+[配置ResnetDetector插件的模型加载路径modelPath]
+```c++ reasonerConfig.resnetModelPath = "${Resnet18.om模型路径}"```
+
+配置ResnetDetector插件的模型加载路径labelPath
+```c++ reasonerConfig.resnetLabelPath = "${resnet18.names路径}";```
+
+其他可配置项DECODE_FRAME_QUEUE_LENGTH DECODE_FRAME_WAIT_TIME SAMPLING_INTERVAL MAX_SAMPLING_INTERVAL
+```c++ DECODE_FRAME_QUEUE_LENGTH = 100; DECODE_FRAME_WAIT_TIME = 10; SAMPLING_INTERVAL = 24; MAX_SAMPLING_INTERVAL = 100;```
+
+
+### 配置环境变量
+
+```
+# 执行如下命令，打开.bashrc文件
+cd $HOME
+vi .bashrc
+# 在.bashrc文件中添加以下环境变量
+MX_SDK_HOME=${SDK安装路径}
+FFMPEG_PATH=${FFMPEG安装路径}
+
+LD_LIBRARY_PATH=${MX_SDK_HOME}/lib:${MX_SDK_HOME}/opensource/lib:${MX_SDK_HOME}/opensource/lib64:${FFMPEG_PATH}/lib:/usr/local/Ascend/ascend-toolkit/latest/acllib/lib64:/usr/local/Ascend/driver/lib64/
+
+GST_PLUGIN_SCANNER=${MX_SDK_HOME}/opensource/libexec/gstreamer-1.0/gst-plugin-scanner
+
+GST_PLUGIN_PATH=${MX_SDK_HOME}/opensource/lib/gstreamer-1.0:${MX_SDK_HOME}/lib/plugins
+
+# 保存退出.bashrc文件
+# 执行如下命令使环境变量生效
+source ~/.bashrc
+
+#查看环境变量
+env
+```
+
+### 配置SDK路径
+
+配置CMakeLists.txt文件中的`MX_SDK_HOME`与`FFMPEG_PATH`环境变量
+
+```
+set(MX_SDK_HOME ${SDK安装路径}/mxVision)
+set(FFMPEG_PATH {ffmpeg实际安装路径})
+
+```
+
+
+### 编译项目文件
+
+手动编译请参照 ①，脚本编译请参照 ②
+
+>  ① 新建立build目录，进入build执行cmake ..（..代表包含CMakeLists.txt的源文件父目录），在build目录下生成了编译需要的Makefile和中间文件。执行make构建工程，构建成功后就会生成可执行文件。
+
+```
+mkdir build
+
+cd build
+
+cmake ..
+
+make
+
+Scanning dependencies of target sample
+[ 11%] Building CXX object CMakeFiles/sample.dir/main.cpp.o
+[ 22%] Building CXX object CMakeFiles/sample.dir/StreamPuller/StreamPuller.cpp.o
+[ 33%] Building CXX object CMakeFiles/sample.dir/VideoDecoder/VideoDecoder.cpp.o
+[ 44%] Building CXX object CMakeFiles/sample.dir/ImageResizer/ImageResizer.cpp.o
+[ 66%] Building CXX object CMakeFiles/sample.dir/ResnetDetector/ResnetDetector.cpp.o
+[ 77%] Building CXX object CMakeFiles/sample.dir/MultiChannelVideoReasoner/MultiChannelVideoReasoner.cpp.o
+[ 88%] Building CXX object CMakeFiles/sample.dir/FrameSkippingSampling/FrameSkippingSampling.cpp.o
+[100%] Linking CXX executable ../sample
+[100%] Built target sample
+# sample就是CMakeLists文件中指定生成的可执行文件。
+```
+
+>  ② 运行项目根目录下的`build.sh`
+```bash
+chmod +x build.sh
+bash build.sh
+```
+### 执行脚本
+
+执行`run.sh`脚本前请先确认可执行文件`sample`已生成。
+
+```
+chmod +x run.sh
+bash run.sh
+```
+
+### 查看结果
+
 执行`run.sh`完毕后，如果配置了检测结果写文件，sample会将手势识别结果，以jpg格式的图片保存在工程目录下`result`中。
\ No newline at end of file
diff --git a/contrib/VideoGestureRecognition/StreamPuller/.keep b/mxVision/mxVision-referenceapps/VideoGestureRecognition/ResnetDetector/.keep
similarity index 100%
rename from contrib/VideoGestureRecognition/StreamPuller/.keep
rename to mxVision/mxVision-referenceapps/VideoGestureRecognition/ResnetDetector/.keep
diff --git a/contrib/VideoGestureRecognition/ResnetDetector/ResnetDetector.cpp b/mxVision/mxVision-referenceapps/VideoGestureRecognition/ResnetDetector/ResnetDetector.cpp
similarity index 97%
rename from contrib/VideoGestureRecognition/ResnetDetector/ResnetDetector.cpp
rename to mxVision/mxVision-referenceapps/VideoGestureRecognition/ResnetDetector/ResnetDetector.cpp
index 4d88bf4709ec2f322a16fcd55293c6dd9f25ba8b..cd34274b87d825a064ad69693a76e94940c7d769 100644
--- a/contrib/VideoGestureRecognition/ResnetDetector/ResnetDetector.cpp
+++ b/mxVision/mxVision-referenceapps/VideoGestureRecognition/ResnetDetector/ResnetDetector.cpp
@@ -1,313 +1,313 @@
-/*
- * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#include "ResnetDetector.h"
-#include "MxBase/Tensor/TensorContext/TensorContext.h"
-#include <fstream>
-
-namespace AscendResnetDetector {
-namespace {
-    const uint32_t YUV_BYTE_NU = 3;
-    const uint32_t YUV_BYTE_DE = 2;
-    const uint32_t VPC_H_ALIGN = 2;
-}
-
-APP_ERROR ResnetDetector::Init(const ResnetInitParam &initParam)
-{
-    LogDebug << "ResnetDetector init start.";
-    this->deviceId = initParam.deviceId;
-
-    // set tensor context
-    APP_ERROR ret = MxBase::TensorContext::GetInstance()->SetContext(initParam.deviceId);
-    if (ret != APP_ERR_OK) {
-        LogError << "Set tensor context failed, ret = " << ret << ".";
-        return ret;
-    }
-
-    // Init Resnet model
-    ret = InitModel(initParam);
-    if (ret != APP_ERR_OK) {
-        LogError << "init model failed.";
-        return ret;
-    }
-
-    // Init model post process
-    ret = InitPostProcess(initParam);
-    if (ret != APP_ERR_OK) {
-        LogError << "init model post process failed.";
-        return ret;
-    }
-
-    // Load labels map
-    ret = LoadLabels(initParam.labelPath, labelMap);
-    if (ret != APP_ERR_OK) {
-        LogError << "Failed to load labels, ret=" << ret << ".";
-        return ret;
-    }
-
-    LogDebug << "ResnetDetector init successful.";
-    return APP_ERR_OK;
-}
-
-APP_ERROR ResnetDetector::DeInit()
-{
-    LogDebug << "ResnetDetector deinit start.";
-
-    APP_ERROR ret = model->DeInit();
-    if (ret != APP_ERR_OK) {
-        LogError << "deinit model failed";
-        return ret;
-    }
-
-    ret = postProcess->DeInit();
-    if (ret != APP_ERR_OK) {
-        LogError << "deinit model postprocess failed.";
-        return ret;
-    }
-
-    LogDebug << "ResnetDetector deinit successful.";
-    return APP_ERR_OK;
-}
-
-APP_ERROR ResnetDetector::Process()
-{
-    return APP_ERR_OK;
-}
-
-APP_ERROR ResnetDetector::Detect(const MxBase::DvppDataInfo &imageInfo,
-                                 std::vector<std::vector<MxBase::ClassInfo>> &objInfos,
-                                 const uint32_t &imageOriginWidth,
-                                 const uint32_t &imageOriginHeight)
-{
-    // transform image data to tensor
-    MxBase::TensorBase tensor;
-    APP_ERROR ret = TransformImageToTensor(imageInfo, tensor);
-    if (ret != APP_ERR_OK) {
-        LogError << "Transform image to tensor failed, ret = " << ret << ".";
-        return ret;
-    }
-
-    std::vector<MxBase::TensorBase> inputs = {};
-    std::vector<MxBase::TensorBase> outputs = {};
-    inputs.push_back(tensor);
-
-    LogInfo << "input tensor" << tensor.GetDesc();
-
-    // model infer
-    ret = Inference(inputs, outputs);
-    if (ret != APP_ERR_OK) {
-        LogError << "Model infer failed, ret = " << ret << ".";
-        return ret;
-    }
-
-    // model post process
-    ret = PostProcess(outputs, imageOriginWidth, imageOriginHeight, objInfos);
-    if (ret != APP_ERR_OK) {
-        LogError << "Model post process failed, ret = " << ret << ".";
-        return ret;
-    }
-
-    return APP_ERR_OK;
-}
-
-/// ========== private Method ========== ///
-
-APP_ERROR ResnetDetector::InitModel(const ResnetInitParam &initParam)
-{
-    LogDebug << "ResnetDetector init model start.";
-    model = std::make_shared<MxBase::ModelInferenceProcessor>();
-    LogInfo << "model path: " << initParam.modelPath;
-
-    APP_ERROR ret = model->Init(initParam.modelPath, modelDesc);
-    if (ret != APP_ERR_OK) {
-        LogError << "ModelInferenceProcessor init failed, ret=" << ret << ".";
-        return ret;
-    }
-
-    LogDebug << "ResnetDetector init model successfully.";
-    return APP_ERR_OK;
-}
-
-APP_ERROR ResnetDetector::InitPostProcess(const ResnetInitParam &initParam)
-{
-    LogDebug << "ResnetDetector init postprocess start.";
-    std::map<std::string, std::shared_ptr<void>> config;
-    LoadPostProcessConfig(initParam, config);
-
-    postProcess = std::make_shared<MxBase::Resnet50PostProcess>();
-    APP_ERROR ret = postProcess->Init(config);
-    if (ret != APP_ERR_OK) {
-        LogError << "ModelPostProcess init failed, ret=" << ret << ".";
-        return ret;
-    }
-
-    LogDebug << "ResnetDetector init postprocess successfully.";
-    return APP_ERR_OK;
-}
-
-APP_ERROR ResnetDetector::TransformImageToTensor(const MxBase::DvppDataInfo &imageInfo,
-                                                 MxBase::TensorBase &tensor) const
-{
-    MxBase::MemoryData memoryData((void*)imageInfo.data,
-                                  imageInfo.dataSize,
-                                  MxBase::MemoryData::MEMORY_DVPP,
-                                  deviceId);
-
-    if (imageInfo.heightStride % VPC_H_ALIGN != 0) {
-        LogError << "Output data height(" << imageInfo.heightStride << ") can't be divided by " << VPC_H_ALIGN << ".";
-        MxBase::MemoryHelper::MxbsFree(memoryData);
-        return APP_ERR_COMM_INVALID_PARAM;
-    }
-    std::vector<uint32_t> shape = {imageInfo.heightStride * YUV_BYTE_DE, imageInfo.widthStride * YUV_BYTE_DE};
-
-    tensor = MxBase::TensorBase(memoryData, false, shape, MxBase::TENSOR_DTYPE_UINT8);
-
-    return APP_ERR_OK;
-}
-
-APP_ERROR ResnetDetector::Inference(const std::vector<MxBase::TensorBase> &inputs,
-                                    std::vector<MxBase::TensorBase> &outputs)
-{
-    APP_ERROR ret;
-
-    // check input
-    if (inputs.empty() || inputs[0].GetBuffer() == nullptr) {
-        LogError << "input is null";
-        return APP_ERR_FAILURE;
-    }
-
-    auto dtypes = model->GetOutputDataType();
-    for (size_t i = 0; i < modelDesc.outputTensors.size(); ++i) {
-        std::vector<uint32_t> shape = {};
-        for (size_t j = 0; j < modelDesc.outputTensors[i].tensorDims.size(); ++j) {
-            shape.push_back((uint32_t)modelDesc.outputTensors[i].tensorDims[j]);
-        }
-
-        MxBase::TensorBase tensor(shape, dtypes[i], MxBase::MemoryData::MemoryType::MEMORY_DVPP, deviceId);
-        ret = MxBase::TensorBase::TensorBaseMalloc(tensor);
-        if (ret != APP_ERR_OK) {
-            LogError << "TensorBaseMalloc failed, ret = " << ret << ".";
-            return ret;
-        }
-
-        outputs.push_back(tensor);
-    }
-
-    LogInfo << outputs[0].GetDesc();
-
-    MxBase::DynamicInfo dynamicInfo = {};
-    dynamicInfo.dynamicType = MxBase::DynamicType::STATIC_BATCH;
-
-    // model infer
-    auto startTime = std::chrono::high_resolution_clock::now();
-    ret = model->ModelInference(inputs, outputs, dynamicInfo);
-    auto endTime = std::chrono::high_resolution_clock::now();
-    double costMs = std::chrono::duration<double, std::milli>(endTime - startTime).count();
-    LogInfo << "model inference time: " << costMs;
-
-    if (ret != APP_ERR_OK) {
-        LogError << "ModelInference failed, ret=" << ret << ".";
-        return ret;
-    }
-
-    return APP_ERR_OK;
-}
-
-APP_ERROR ResnetDetector::PostProcess(const std::vector<MxBase::TensorBase> &modelOutputs,
-                                      const uint32_t &width,
-                                      const uint32_t &height,
-                                      std::vector<std::vector<MxBase::ClassInfo>> &objInfos)
-{
-    MxBase::ResizedImageInfo imageInfo = {};
-    imageInfo.widthOriginal = width;
-    imageInfo.heightOriginal = height;
-    imageInfo.widthResize = netWidth;
-    imageInfo.heightResize = netHeight;
-    imageInfo.resizeType = MxBase::RESIZER_STRETCHING;
-    std::vector<MxBase::ResizedImageInfo> imageInfoVec = {};
-    imageInfoVec.push_back(imageInfo);
-
-    APP_ERROR ret = postProcess->Process(modelOutputs, objInfos);
-    if (ret != APP_ERR_OK) {
-        LogError << "PostProcess failed, ret=" << ret << ".";
-        return ret;
-    }
-
-    return APP_ERR_OK;
-}
-
-APP_ERROR ResnetDetector::LoadLabels(const std::string &labelPath, std::map<int, std::string> &labelMap)
-{
-    LogInfo << "load model labels start.";
-
-    std::ifstream infile;
-    // open label file
-    infile.open(labelPath, std::ios_base::in);
-    std::string s;
-    // check label file validity
-    if (infile.fail()) {
-        LogError << "Failed to open label file: " << labelPath << ".";
-        return APP_ERR_COMM_OPEN_FAIL;
-    }
-
-    labelMap.clear();
-    // construct label map
-    int count = 0;
-    while (std::getline(infile, s)) {
-        if (s.compare(0, 0, "#") == 0 || s.compare(1, 1, "#") == 0) {
-            continue;
-        }
-        size_t eraseIndex = s.find_last_not_of("\r\n\t");
-        if (eraseIndex != std::string::npos) {
-            s.erase(eraseIndex + 1, s.size() - eraseIndex);
-        }
-        labelMap.insert(std::pair<int, std::string>(count, s));
-        count++;
-    }
-
-    infile.close();
-    LogInfo << "load model labels successfully.";
-    return APP_ERR_OK;
-}
-
-APP_ERROR ResnetDetector::LoadPostProcessConfig(const ResnetInitParam &initParam,
-                                                std::map<std::string, std::shared_ptr<void>> &config)
-{
-    LogInfo << "load postprocess config start.";
-
-    MxBase::ConfigData configData;
-    const std::string checkTensor = initParam.checkTensor ? "true" : "false";
-
-    configData.SetJsonValue("CLASS_NUM", std::to_string(initParam.classNum));
-    configData.SetJsonValue("BIASES_NUM", std::to_string(initParam.biasesNum));
-    configData.SetJsonValue("BIASES", initParam.biases);
-    configData.SetJsonValue("OBJECTNESS_THRESH", initParam.objectnessThresh);
-    configData.SetJsonValue("IOU_THRESH", initParam.iouThresh);
-    configData.SetJsonValue("SCORE_THRESH", initParam.scoreThresh);
-    configData.SetJsonValue("Resnet_TYPE", std::to_string(initParam.resnetType));
-    configData.SetJsonValue("MODEL_TYPE", std::to_string(initParam.modelType));
-    configData.SetJsonValue("INPUT_TYPE", std::to_string(initParam.inputType));
-    configData.SetJsonValue("ANCHOR_DIM", std::to_string(initParam.anchorDim));
-    configData.SetJsonValue("CHECK_MODEL", checkTensor);
-
-    auto jsonStr = configData.GetCfgJson().serialize();
-    config["postProcessConfigContent"] = std::make_shared<std::string>(jsonStr);
-    config["labelPath"] = std::make_shared<std::string>(initParam.labelPath);
-
-    LogInfo << "load postprocess config successfully.";
-    return APP_ERR_OK;
-}
-} // end AscendResnetDetector
+/*
+ * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "ResnetDetector.h"
+#include "MxBase/Tensor/TensorContext/TensorContext.h"
+#include <fstream>
+
+namespace AscendResnetDetector {
+namespace {
+    const uint32_t YUV_BYTE_NU = 3;
+    const uint32_t YUV_BYTE_DE = 2;
+    const uint32_t VPC_H_ALIGN = 2;
+}
+
+APP_ERROR ResnetDetector::Init(const ResnetInitParam &initParam)
+{
+    LogDebug << "ResnetDetector init start.";
+    this->deviceId = initParam.deviceId;
+
+    // set tensor context
+    APP_ERROR ret = MxBase::TensorContext::GetInstance()->SetContext(initParam.deviceId);
+    if (ret != APP_ERR_OK) {
+        LogError << "Set tensor context failed, ret = " << ret << ".";
+        return ret;
+    }
+
+    // Init Resnet model
+    ret = InitModel(initParam);
+    if (ret != APP_ERR_OK) {
+        LogError << "init model failed.";
+        return ret;
+    }
+
+    // Init model post process
+    ret = InitPostProcess(initParam);
+    if (ret != APP_ERR_OK) {
+        LogError << "init model post process failed.";
+        return ret;
+    }
+
+    // Load labels map
+    ret = LoadLabels(initParam.labelPath, labelMap);
+    if (ret != APP_ERR_OK) {
+        LogError << "Failed to load labels, ret=" << ret << ".";
+        return ret;
+    }
+
+    LogDebug << "ResnetDetector init successful.";
+    return APP_ERR_OK;
+}
+
+APP_ERROR ResnetDetector::DeInit()
+{
+    LogDebug << "ResnetDetector deinit start.";
+
+    APP_ERROR ret = model->DeInit();
+    if (ret != APP_ERR_OK) {
+        LogError << "deinit model failed";
+        return ret;
+    }
+
+    ret = postProcess->DeInit();
+    if (ret != APP_ERR_OK) {
+        LogError << "deinit model postprocess failed.";
+        return ret;
+    }
+
+    LogDebug << "ResnetDetector deinit successful.";
+    return APP_ERR_OK;
+}
+
+APP_ERROR ResnetDetector::Process()
+{
+    return APP_ERR_OK;
+}
+
+APP_ERROR ResnetDetector::Detect(const MxBase::DvppDataInfo &imageInfo,
+                                 std::vector<std::vector<MxBase::ClassInfo>> &objInfos,
+                                 const uint32_t &imageOriginWidth,
+                                 const uint32_t &imageOriginHeight)
+{
+    // transform image data to tensor
+    MxBase::TensorBase tensor;
+    APP_ERROR ret = TransformImageToTensor(imageInfo, tensor);
+    if (ret != APP_ERR_OK) {
+        LogError << "Transform image to tensor failed, ret = " << ret << ".";
+        return ret;
+    }
+
+    std::vector<MxBase::TensorBase> inputs = {};
+    std::vector<MxBase::TensorBase> outputs = {};
+    inputs.push_back(tensor);
+
+    LogInfo << "input tensor" << tensor.GetDesc();
+
+    // model infer
+    ret = Inference(inputs, outputs);
+    if (ret != APP_ERR_OK) {
+        LogError << "Model infer failed, ret = " << ret << ".";
+        return ret;
+    }
+
+    // model post process
+    ret = PostProcess(outputs, imageOriginWidth, imageOriginHeight, objInfos);
+    if (ret != APP_ERR_OK) {
+        LogError << "Model post process failed, ret = " << ret << ".";
+        return ret;
+    }
+
+    return APP_ERR_OK;
+}
+
+/// ========== private Method ========== ///
+
+APP_ERROR ResnetDetector::InitModel(const ResnetInitParam &initParam)
+{
+    LogDebug << "ResnetDetector init model start.";
+    model = std::make_shared<MxBase::ModelInferenceProcessor>();
+    LogInfo << "model path: " << initParam.modelPath;
+
+    APP_ERROR ret = model->Init(initParam.modelPath, modelDesc);
+    if (ret != APP_ERR_OK) {
+        LogError << "ModelInferenceProcessor init failed, ret=" << ret << ".";
+        return ret;
+    }
+
+    LogDebug << "ResnetDetector init model successfully.";
+    return APP_ERR_OK;
+}
+
+APP_ERROR ResnetDetector::InitPostProcess(const ResnetInitParam &initParam)
+{
+    LogDebug << "ResnetDetector init postprocess start.";
+    std::map<std::string, std::shared_ptr<void>> config;
+    LoadPostProcessConfig(initParam, config);
+
+    postProcess = std::make_shared<MxBase::Resnet50PostProcess>();
+    APP_ERROR ret = postProcess->Init(config);
+    if (ret != APP_ERR_OK) {
+        LogError << "ModelPostProcess init failed, ret=" << ret << ".";
+        return ret;
+    }
+
+    LogDebug << "ResnetDetector init postprocess successfully.";
+    return APP_ERR_OK;
+}
+
+APP_ERROR ResnetDetector::TransformImageToTensor(const MxBase::DvppDataInfo &imageInfo,
+                                                 MxBase::TensorBase &tensor) const
+{
+    MxBase::MemoryData memoryData((void*)imageInfo.data,
+                                  imageInfo.dataSize,
+                                  MxBase::MemoryData::MEMORY_DVPP,
+                                  deviceId);
+
+    if (imageInfo.heightStride % VPC_H_ALIGN != 0) {
+        LogError << "Output data height(" << imageInfo.heightStride << ") can't be divided by " << VPC_H_ALIGN << ".";
+        MxBase::MemoryHelper::MxbsFree(memoryData);
+        return APP_ERR_COMM_INVALID_PARAM;
+    }
+    std::vector<uint32_t> shape = {imageInfo.heightStride * YUV_BYTE_DE, imageInfo.widthStride * YUV_BYTE_DE};
+
+    tensor = MxBase::TensorBase(memoryData, false, shape, MxBase::TENSOR_DTYPE_UINT8);
+
+    return APP_ERR_OK;
+}
+
+APP_ERROR ResnetDetector::Inference(const std::vector<MxBase::TensorBase> &inputs,
+                                    std::vector<MxBase::TensorBase> &outputs)
+{
+    APP_ERROR ret;
+
+    // check input
+    if (inputs.empty() || inputs[0].GetBuffer() == nullptr) {
+        LogError << "input is null";
+        return APP_ERR_FAILURE;
+    }
+
+    auto dtypes = model->GetOutputDataType();
+    for (size_t i = 0; i < modelDesc.outputTensors.size(); ++i) {
+        std::vector<uint32_t> shape = {};
+        for (size_t j = 0; j < modelDesc.outputTensors[i].tensorDims.size(); ++j) {
+            shape.push_back((uint32_t)modelDesc.outputTensors[i].tensorDims[j]);
+        }
+
+        MxBase::TensorBase tensor(shape, dtypes[i], MxBase::MemoryData::MemoryType::MEMORY_DVPP, deviceId);
+        ret = MxBase::TensorBase::TensorBaseMalloc(tensor);
+        if (ret != APP_ERR_OK) {
+            LogError << "TensorBaseMalloc failed, ret = " << ret << ".";
+            return ret;
+        }
+
+        outputs.push_back(tensor);
+    }
+
+    LogInfo << outputs[0].GetDesc();
+
+    MxBase::DynamicInfo dynamicInfo = {};
+    dynamicInfo.dynamicType = MxBase::DynamicType::STATIC_BATCH;
+
+    // model infer
+    auto startTime = std::chrono::high_resolution_clock::now();
+    ret = model->ModelInference(inputs, outputs, dynamicInfo);
+    auto endTime = std::chrono::high_resolution_clock::now();
+    double costMs = std::chrono::duration<double, std::milli>(endTime - startTime).count();
+    LogInfo << "model inference time: " << costMs;
+
+    if (ret != APP_ERR_OK) {
+        LogError << "ModelInference failed, ret=" << ret << ".";
+        return ret;
+    }
+
+    return APP_ERR_OK;
+}
+
+APP_ERROR ResnetDetector::PostProcess(const std::vector<MxBase::TensorBase> &modelOutputs,
+                                      const uint32_t &width,
+                                      const uint32_t &height,
+                                      std::vector<std::vector<MxBase::ClassInfo>> &objInfos)
+{
+    MxBase::ResizedImageInfo imageInfo = {};
+    imageInfo.widthOriginal = width;
+    imageInfo.heightOriginal = height;
+    imageInfo.widthResize = netWidth;
+    imageInfo.heightResize = netHeight;
+    imageInfo.resizeType = MxBase::RESIZER_STRETCHING;
+    std::vector<MxBase::ResizedImageInfo> imageInfoVec = {};
+    imageInfoVec.push_back(imageInfo);
+
+    APP_ERROR ret = postProcess->Process(modelOutputs, objInfos);
+    if (ret != APP_ERR_OK) {
+        LogError << "PostProcess failed, ret=" << ret << ".";
+        return ret;
+    }
+
+    return APP_ERR_OK;
+}
+
+APP_ERROR ResnetDetector::LoadLabels(const std::string &labelPath, std::map<int, std::string> &labelMap)
+{
+    LogInfo << "load model labels start.";
+
+    std::ifstream infile;
+    // open label file
+    infile.open(labelPath, std::ios_base::in);
+    std::string s;
+    // check label file validity
+    if (infile.fail()) {
+        LogError << "Failed to open label file: " << labelPath << ".";
+        return APP_ERR_COMM_OPEN_FAIL;
+    }
+
+    labelMap.clear();
+    // construct label map
+    int count = 0;
+    while (std::getline(infile, s)) {
+        if (s.compare(0, 0, "#") == 0 || s.compare(1, 1, "#") == 0) {
+            continue;
+        }
+        size_t eraseIndex = s.find_last_not_of("\r\n\t");
+        if (eraseIndex != std::string::npos) {
+            s.erase(eraseIndex + 1, s.size() - eraseIndex);
+        }
+        labelMap.insert(std::pair<int, std::string>(count, s));
+        count++;
+    }
+
+    infile.close();
+    LogInfo << "load model labels successfully.";
+    return APP_ERR_OK;
+}
+
+APP_ERROR ResnetDetector::LoadPostProcessConfig(const ResnetInitParam &initParam,
+                                                std::map<std::string, std::shared_ptr<void>> &config)
+{
+    LogInfo << "load postprocess config start.";
+
+    MxBase::ConfigData configData;
+    const std::string checkTensor = initParam.checkTensor ? "true" : "false";
+
+    configData.SetJsonValue("CLASS_NUM", std::to_string(initParam.classNum));
+    configData.SetJsonValue("BIASES_NUM", std::to_string(initParam.biasesNum));
+    configData.SetJsonValue("BIASES", initParam.biases);
+    configData.SetJsonValue("OBJECTNESS_THRESH", initParam.objectnessThresh);
+    configData.SetJsonValue("IOU_THRESH", initParam.iouThresh);
+    configData.SetJsonValue("SCORE_THRESH", initParam.scoreThresh);
+    configData.SetJsonValue("Resnet_TYPE", std::to_string(initParam.resnetType));
+    configData.SetJsonValue("MODEL_TYPE", std::to_string(initParam.modelType));
+    configData.SetJsonValue("INPUT_TYPE", std::to_string(initParam.inputType));
+    configData.SetJsonValue("ANCHOR_DIM", std::to_string(initParam.anchorDim));
+    configData.SetJsonValue("CHECK_MODEL", checkTensor);
+
+    auto jsonStr = configData.GetCfgJson().serialize();
+    config["postProcessConfigContent"] = std::make_shared<std::string>(jsonStr);
+    config["labelPath"] = std::make_shared<std::string>(initParam.labelPath);
+
+    LogInfo << "load postprocess config successfully.";
+    return APP_ERR_OK;
+}
+} // end AscendResnetDetector
diff --git a/contrib/VideoGestureRecognition/ResnetDetector/ResnetDetector.h b/mxVision/mxVision-referenceapps/VideoGestureRecognition/ResnetDetector/ResnetDetector.h
similarity index 97%
rename from contrib/VideoGestureRecognition/ResnetDetector/ResnetDetector.h
rename to mxVision/mxVision-referenceapps/VideoGestureRecognition/ResnetDetector/ResnetDetector.h
index 5fcb147c9b34f2f70d931e5e9c5bf741f2cb2f86..655df7616d06d5ee91bc0a18a1245e17d5438b26 100644
--- a/contrib/VideoGestureRecognition/ResnetDetector/ResnetDetector.h
+++ b/mxVision/mxVision-referenceapps/VideoGestureRecognition/ResnetDetector/ResnetDetector.h
@@ -1,94 +1,94 @@
-/*
- * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#ifndef VIDEOGESTURERECOGNITION_RESNET_DETECTOR_H
-#define VIDEOGESTURERECOGNITION_RESNET_DETECTOR_H
-
-#include "MxBase/ErrorCode/ErrorCode.h"
-#include "MxBase/DvppWrapper/DvppWrapper.h"
-#include "MxBase/ModelInfer/ModelInferenceProcessor.h"
-#include "ClassPostProcessors/Resnet50PostProcess.h"
-#include "../BlockingQueue/BlockingQueue.h"
-
-namespace AscendResnetDetector {
-struct ResnetInitParam {
-    uint32_t deviceId = 0;
-    std::string labelPath;
-    bool checkTensor = true;
-    std::string modelPath;
-    uint32_t classNum = 0;
-    uint32_t biasesNum = 0;
-    std::string biases;
-    std::string objectnessThresh;
-    std::string iouThresh;
-    std::string scoreThresh;
-    uint32_t resnetType = 0;
-    uint32_t modelType = 0;
-    uint32_t inputType = 0;
-    uint32_t anchorDim = 0;
-};
-
-class ResnetDetector {
-public:
-    ResnetDetector() = default;
-    ~ResnetDetector() = default;
-
-    APP_ERROR Init(const ResnetInitParam & initParam);
-    APP_ERROR DeInit();
-    APP_ERROR Process();
-
-    APP_ERROR Detect(const MxBase::DvppDataInfo &imageInfo,
-                     std::vector<std::vector<MxBase::ClassInfo>> &objInfos,
-                     const uint32_t &imageOriginWidth,
-                     const uint32_t &imageOriginHeight);
-
-public:
-    // running flag
-    bool stopFlag = true;
-
-protected:
-    static APP_ERROR LoadLabels(const std::string &labelPath, std::map<int, std::string> &labelMap);
-    static APP_ERROR LoadPostProcessConfig(const ResnetInitParam &initParam,
-                                           std::map<std::string,
-                                           std::shared_ptr<void>> &config);
-
-private:
-    APP_ERROR InitModel(const ResnetInitParam &initParam);
-    APP_ERROR InitPostProcess(const ResnetInitParam &initParam);
-    APP_ERROR TransformImageToTensor(const MxBase::DvppDataInfo &imageInfo, MxBase::TensorBase &tensor) const;
-    APP_ERROR Inference(const std::vector<MxBase::TensorBase> &inputs, std::vector<MxBase::TensorBase> &outputs);
-    APP_ERROR PostProcess(const std::vector<MxBase::TensorBase> &modelOutputs,
-                          const uint32_t &width,
-                          const uint32_t &height,
-                          std::vector<std::vector<MxBase::ClassInfo>> &objInfos);
-
-private:
-    // model
-    std::shared_ptr<MxBase::ModelInferenceProcessor> model;
-    // infer result post process
-    std::shared_ptr<MxBase::Resnet50PostProcess> postProcess;
-    MxBase::ModelDesc modelDesc = {};
-    std::map<int, std::string> labelMap = {};
-
-    // device id
-    uint32_t deviceId = 1;
-    // network width
-    uint32_t const netWidth = 256;
-    // network height
-    uint32_t const netHeight = 224;
-};
-} // end AscendResnetDetector
-#endif // VIDEOGESTURERECOGNITION_RESNET_DETECTOR_H
+/*
+ * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef VIDEOGESTURERECOGNITION_RESNET_DETECTOR_H
+#define VIDEOGESTURERECOGNITION_RESNET_DETECTOR_H
+
+#include "MxBase/ErrorCode/ErrorCode.h"
+#include "MxBase/DvppWrapper/DvppWrapper.h"
+#include "MxBase/ModelInfer/ModelInferenceProcessor.h"
+#include "ClassPostProcessors/Resnet50PostProcess.h"
+#include "../BlockingQueue/BlockingQueue.h"
+
+namespace AscendResnetDetector {
+struct ResnetInitParam {
+    uint32_t deviceId = 0;
+    std::string labelPath;
+    bool checkTensor = true;
+    std::string modelPath;
+    uint32_t classNum = 0;
+    uint32_t biasesNum = 0;
+    std::string biases;
+    std::string objectnessThresh;
+    std::string iouThresh;
+    std::string scoreThresh;
+    uint32_t resnetType = 0;
+    uint32_t modelType = 0;
+    uint32_t inputType = 0;
+    uint32_t anchorDim = 0;
+};
+
+class ResnetDetector {
+public:
+    ResnetDetector() = default;
+    ~ResnetDetector() = default;
+
+    APP_ERROR Init(const ResnetInitParam & initParam);
+    APP_ERROR DeInit();
+    APP_ERROR Process();
+
+    APP_ERROR Detect(const MxBase::DvppDataInfo &imageInfo,
+                     std::vector<std::vector<MxBase::ClassInfo>> &objInfos,
+                     const uint32_t &imageOriginWidth,
+                     const uint32_t &imageOriginHeight);
+
+public:
+    // running flag
+    bool stopFlag = true;
+
+protected:
+    static APP_ERROR LoadLabels(const std::string &labelPath, std::map<int, std::string> &labelMap);
+    static APP_ERROR LoadPostProcessConfig(const ResnetInitParam &initParam,
+                                           std::map<std::string,
+                                           std::shared_ptr<void>> &config);
+
+private:
+    APP_ERROR InitModel(const ResnetInitParam &initParam);
+    APP_ERROR InitPostProcess(const ResnetInitParam &initParam);
+    APP_ERROR TransformImageToTensor(const MxBase::DvppDataInfo &imageInfo, MxBase::TensorBase &tensor) const;
+    APP_ERROR Inference(const std::vector<MxBase::TensorBase> &inputs, std::vector<MxBase::TensorBase> &outputs);
+    APP_ERROR PostProcess(const std::vector<MxBase::TensorBase> &modelOutputs,
+                          const uint32_t &width,
+                          const uint32_t &height,
+                          std::vector<std::vector<MxBase::ClassInfo>> &objInfos);
+
+private:
+    // model
+    std::shared_ptr<MxBase::ModelInferenceProcessor> model;
+    // infer result post process
+    std::shared_ptr<MxBase::Resnet50PostProcess> postProcess;
+    MxBase::ModelDesc modelDesc = {};
+    std::map<int, std::string> labelMap = {};
+
+    // device id
+    uint32_t deviceId = 1;
+    // network width
+    uint32_t const netWidth = 256;
+    // network height
+    uint32_t const netHeight = 224;
+};
+} // end AscendResnetDetector
+#endif // VIDEOGESTURERECOGNITION_RESNET_DETECTOR_H
diff --git a/contrib/VideoGestureRecognition/Util/.keep b/mxVision/mxVision-referenceapps/VideoGestureRecognition/StreamPuller/.keep
similarity index 100%
rename from contrib/VideoGestureRecognition/Util/.keep
rename to mxVision/mxVision-referenceapps/VideoGestureRecognition/StreamPuller/.keep
diff --git a/contrib/VideoGestureRecognition/StreamPuller/StreamPuller.cpp b/mxVision/mxVision-referenceapps/VideoGestureRecognition/StreamPuller/StreamPuller.cpp
similarity index 96%
rename from contrib/VideoGestureRecognition/StreamPuller/StreamPuller.cpp
rename to mxVision/mxVision-referenceapps/VideoGestureRecognition/StreamPuller/StreamPuller.cpp
index 74560b6dd32dd8a37346c1770a83ea6e5df7b2a8..df8e81c5cd9b869e34ca67c5279b24641767b33e 100644
--- a/contrib/VideoGestureRecognition/StreamPuller/StreamPuller.cpp
+++ b/mxVision/mxVision-referenceapps/VideoGestureRecognition/StreamPuller/StreamPuller.cpp
@@ -1,253 +1,253 @@
-/*
- * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#include "StreamPuller.h"
-#include <thread>
-#include "MxBase/Log/Log.h"
-
-namespace AscendStreamPuller {
-namespace {
-    const uint32_t LOW_THRESHOLD = 0;
-    const uint32_t MAX_THRESHOLD = 4096;
-}
-
-APP_ERROR StreamPuller::Init(const std::string &rtspUrl, uint32_t deviceId)
-{
-    LogDebug << "StreamPuller" << ": StreamPuller init start.";
-
-    this->deviceId = deviceId;
-    this->streamName = rtspUrl;
-    this->frameInfo.source = rtspUrl;
-
-    stopFlag = false;
-
-    APP_ERROR ret = TryToStartStream();
-    if (ret != APP_ERR_OK) {
-        LogError << "start stream failed";
-        return ret;
-    }
-
-    LogDebug << "StreamPuller" << ": StreamPuller init success.";
-    return APP_ERR_OK;
-}
-
-APP_ERROR StreamPuller::DeInit()
-{
-    LogDebug << "StreamPuller" << ": StreamPuller deinit start.";
-    AVFormatContext *pAvFormatContext = formatContext.get();
-    avformat_close_input(&pAvFormatContext);
-
-    stopFlag = true;
-    formatContext = nullptr;
-    LogDebug << "StreamPuller" << ": StreamPuller deinit success.";
-    return APP_ERR_OK;
-}
-
-APP_ERROR StreamPuller::Process()
-{
-    PullStreamDataLoop();
-    return APP_ERR_OK;
-}
-
-MxBase::MemoryData StreamPuller::GetNextFrame()
-{
-    AVPacket packet;
-
-    av_init_packet(&packet);
-    while (true) {
-        if (stopFlag || formatContext == nullptr) {
-            LogDebug << "StreamPuller stopped or deinit, pull video stream exit";
-            break;
-        }
-
-        APP_ERROR ret = av_read_frame(formatContext.get(), &packet);
-        if (ret != APP_ERR_OK) {
-            if (ret == AVERROR_EOF) {
-                LogDebug << "StreamPuller channel StreamPuller is EOF, over!";
-                stopFlag = true;
-                break;
-            }
-
-            LogError << "StreamPuller channel Read frame failed, continue!";
-            std::this_thread::sleep_for(std::chrono::microseconds(1));
-            continue;
-        } else if (packet.stream_index != frameInfo.videoStream) {
-            LogDebug << "packet is not video stream. continue";
-            av_packet_unref(&packet);
-            std::this_thread::sleep_for(std::chrono::microseconds(1));
-            continue;
-        }
-
-        if (packet.size <= 0) {
-            LogError << "Invalid packet.size: " << packet.size;
-            continue;
-        }
-
-        // deep copy packet data
-        auto packetData = new uint8_t[(size_t)packet.size + 1];
-        memcpy(packetData, packet.data, (size_t)packet.size);
-
-        // put video frame into queue
-        MxBase::MemoryData streamData((void *)packetData, (size_t)packet.size,
-                                      MxBase::MemoryData::MEMORY_HOST_NEW, deviceId);
-
-        av_packet_unref(&packet);
-        return streamData;
-    }
-
-    av_packet_unref(&packet);
-
-    return {nullptr, 0, MxBase::MemoryData::MEMORY_HOST_NEW, deviceId};
-}
-
-VideoFrameInfo StreamPuller::GetFrameInfo() const
-{
-    return frameInfo;
-}
-
-/// ========== Private Method ========== ///
-APP_ERROR StreamPuller::TryToStartStream()
-{
-    uint32_t failureNum = 0;
-    while (failureNum < maxReTryOpenStream) {
-        APP_ERROR ret = StartStream();
-        if (ret == APP_ERR_OK) {
-            LogDebug << "StreamPuller start stream success.";
-            ret = GetStreamInfo();
-            if (ret != APP_ERR_OK) {
-                LogError << "StreamPuller get stream info error";
-                return ret;
-            }
-            return APP_ERR_OK;
-        }
-        LogError << "StreamPuller start stream failed, retry: " << ++failureNum;
-    }
-
-    stopFlag = true;
-    return APP_ERR_COMM_INIT_FAIL;
-}
-
-APP_ERROR StreamPuller::StartStream()
-{
-    // init network
-    avformat_network_init();
-
-    // specify an empty deleter to avoid double free
-    auto deleter = [] (AVFormatContext *avFormatContext) {
-    };
-
-    // malloc avformat context
-    AVFormatContext *pAvformatContext = avformat_alloc_context();
-    formatContext = std::shared_ptr<AVFormatContext>(pAvformatContext, deleter);
-    if (formatContext == nullptr) {
-        LogError << "formatContext is null.";
-        return APP_ERR_COMM_INVALID_POINTER;
-    }
-
-    APP_ERROR ret = CreateFormatContext();
-    if (ret != APP_ERR_OK) {
-        LogError << "Couldn't create format context" << " ret = " << ret;
-        return ret;
-    }
-
-    // for debug dump
-    av_dump_format(formatContext.get(), 0, streamName.c_str(), 0);
-    return APP_ERR_OK;
-}
-
-APP_ERROR StreamPuller::CreateFormatContext()
-{
-    // create message for stream pull
-    AVDictionary *options = nullptr;
-    av_dict_set(&options, "rtsp_transport", "tcp", 0);
-    av_dict_set(&options, "stimeout", "3000000", 0);
-
-    AVFormatContext *pAvformatContext = formatContext.get();
-    APP_ERROR ret = avformat_open_input(&pAvformatContext, streamName.c_str(), nullptr, &options);
-    if (options != nullptr) {
-        av_dict_free(&options);
-    }
-
-    if (ret != APP_ERR_OK) {
-        LogError << "Couldn't open input stream " << streamName.c_str() <<  " ret = " << ret;
-        return APP_ERR_STREAM_NOT_EXIST;
-    }
-
-    ret = avformat_find_stream_info(formatContext.get(), nullptr);
-    if (ret != APP_ERR_OK) {
-        LogError << "Couldn't find stream information" << " ret = " << ret;
-        return APP_ERR_STREAM_NOT_EXIST;
-    }
-
-    return APP_ERR_OK;
-}
-
-APP_ERROR StreamPuller::GetStreamInfo()
-{
-    frameInfo.videoStream = -1;
-
-    if (formatContext != nullptr) {
-        for (uint32_t i = 0; i < formatContext->nb_streams; i++) {
-            AVStream *inStream = formatContext->streams[i];
-            if (inStream->codecpar->codec_type == AVMEDIA_TYPE_VIDEO) {
-                frameInfo.videoStream = i;
-                frameInfo.width = inStream->codecpar->width;
-                frameInfo.height = inStream->codecpar->height;
-                break;
-            }
-        }
-        if (frameInfo.videoStream == -1) {
-            LogError << "Didn't find a video stream!";
-            return APP_ERR_COMM_FAILURE;
-        }
-
-        AVCodecID codecId = formatContext->streams[frameInfo.videoStream]->codecpar->codec_id;
-        if (codecId == AV_CODEC_ID_H264) {
-            frameInfo.format = MxBase::MXBASE_STREAM_FORMAT_H264_MAIN_LEVEL;
-        } else if (codecId == AV_CODEC_ID_H265) {
-            frameInfo.format = MxBase::MXBASE_STREAM_FORMAT_H265_MAIN_LEVEL;
-        } else {
-            LogError << "\033[0;31mError unsupported format \033[0m" << codecId;
-            return APP_ERR_COMM_FAILURE;
-        }
-    }
-
-    // check video frame size
-    if (frameInfo.width < LOW_THRESHOLD || frameInfo.height < LOW_THRESHOLD ||
-        frameInfo.width > MAX_THRESHOLD || frameInfo.height > MAX_THRESHOLD) {
-        LogError << "Size of frame is not supported in DVPP Video Decode!";
-        return APP_ERR_COMM_FAILURE;
-    }
-
-    return APP_ERR_OK;
-}
-
-void StreamPuller::PullStreamDataLoop()
-{
-    while (true) {
-        if (stopFlag || formatContext == nullptr) {
-            LogDebug << "StreamPuller stopped or deinit, pull video stream exit";
-            break;
-        }
-        MxBase::MemoryData videoFrame = GetNextFrame();
-        if (videoFrame.size == 0 || videoFrame.ptrData == nullptr) {
-            LogDebug << "empty video frame, not need! continue!";
-            continue;
-        }
-        // todo send stream data to Device
-    }
-}
+/*
+ * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "StreamPuller.h"
+#include <thread>
+#include "MxBase/Log/Log.h"
+
+namespace AscendStreamPuller {
+namespace {
+    const uint32_t LOW_THRESHOLD = 0;
+    const uint32_t MAX_THRESHOLD = 4096;
+}
+
+APP_ERROR StreamPuller::Init(const std::string &rtspUrl, uint32_t deviceId)
+{
+    LogDebug << "StreamPuller" << ": StreamPuller init start.";
+
+    this->deviceId = deviceId;
+    this->streamName = rtspUrl;
+    this->frameInfo.source = rtspUrl;
+
+    stopFlag = false;
+
+    APP_ERROR ret = TryToStartStream();
+    if (ret != APP_ERR_OK) {
+        LogError << "start stream failed";
+        return ret;
+    }
+
+    LogDebug << "StreamPuller" << ": StreamPuller init success.";
+    return APP_ERR_OK;
+}
+
+APP_ERROR StreamPuller::DeInit()
+{
+    LogDebug << "StreamPuller" << ": StreamPuller deinit start.";
+    AVFormatContext *pAvFormatContext = formatContext.get();
+    avformat_close_input(&pAvFormatContext);
+
+    stopFlag = true;
+    formatContext = nullptr;
+    LogDebug << "StreamPuller" << ": StreamPuller deinit success.";
+    return APP_ERR_OK;
+}
+
+APP_ERROR StreamPuller::Process()
+{
+    PullStreamDataLoop();
+    return APP_ERR_OK;
+}
+
+MxBase::MemoryData StreamPuller::GetNextFrame()
+{
+    AVPacket packet;
+
+    av_init_packet(&packet);
+    while (true) {
+        if (stopFlag || formatContext == nullptr) {
+            LogDebug << "StreamPuller stopped or deinit, pull video stream exit";
+            break;
+        }
+
+        APP_ERROR ret = av_read_frame(formatContext.get(), &packet);
+        if (ret != APP_ERR_OK) {
+            if (ret == AVERROR_EOF) {
+                LogDebug << "StreamPuller channel StreamPuller is EOF, over!";
+                stopFlag = true;
+                break;
+            }
+
+            LogError << "StreamPuller channel Read frame failed, continue!";
+            std::this_thread::sleep_for(std::chrono::microseconds(1));
+            continue;
+        } else if (packet.stream_index != frameInfo.videoStream) {
+            LogDebug << "packet is not video stream. continue";
+            av_packet_unref(&packet);
+            std::this_thread::sleep_for(std::chrono::microseconds(1));
+            continue;
+        }
+
+        if (packet.size <= 0) {
+            LogError << "Invalid packet.size: " << packet.size;
+            continue;
+        }
+
+        // deep copy packet data
+        auto packetData = new uint8_t[(size_t)packet.size + 1];
+        memcpy(packetData, packet.data, (size_t)packet.size);
+
+        // put video frame into queue
+        MxBase::MemoryData streamData((void *)packetData, (size_t)packet.size,
+                                      MxBase::MemoryData::MEMORY_HOST_NEW, deviceId);
+
+        av_packet_unref(&packet);
+        return streamData;
+    }
+
+    av_packet_unref(&packet);
+
+    return {nullptr, 0, MxBase::MemoryData::MEMORY_HOST_NEW, deviceId};
+}
+
+VideoFrameInfo StreamPuller::GetFrameInfo() const
+{
+    return frameInfo;
+}
+
+/// ========== Private Method ========== ///
+APP_ERROR StreamPuller::TryToStartStream()
+{
+    uint32_t failureNum = 0;
+    while (failureNum < maxReTryOpenStream) {
+        APP_ERROR ret = StartStream();
+        if (ret == APP_ERR_OK) {
+            LogDebug << "StreamPuller start stream success.";
+            ret = GetStreamInfo();
+            if (ret != APP_ERR_OK) {
+                LogError << "StreamPuller get stream info error";
+                return ret;
+            }
+            return APP_ERR_OK;
+        }
+        LogError << "StreamPuller start stream failed, retry: " << ++failureNum;
+    }
+
+    stopFlag = true;
+    return APP_ERR_COMM_INIT_FAIL;
+}
+
+APP_ERROR StreamPuller::StartStream()
+{
+    // init network
+    avformat_network_init();
+
+    // specify an empty deleter to avoid double free
+    auto deleter = [] (AVFormatContext *avFormatContext) {
+    };
+
+    // malloc avformat context
+    AVFormatContext *pAvformatContext = avformat_alloc_context();
+    formatContext = std::shared_ptr<AVFormatContext>(pAvformatContext, deleter);
+    if (formatContext == nullptr) {
+        LogError << "formatContext is null.";
+        return APP_ERR_COMM_INVALID_POINTER;
+    }
+
+    APP_ERROR ret = CreateFormatContext();
+    if (ret != APP_ERR_OK) {
+        LogError << "Couldn't create format context" << " ret = " << ret;
+        return ret;
+    }
+
+    // for debug dump
+    av_dump_format(formatContext.get(), 0, streamName.c_str(), 0);
+    return APP_ERR_OK;
+}
+
+APP_ERROR StreamPuller::CreateFormatContext()
+{
+    // create message for stream pull
+    AVDictionary *options = nullptr;
+    av_dict_set(&options, "rtsp_transport", "tcp", 0);
+    av_dict_set(&options, "stimeout", "3000000", 0);
+
+    AVFormatContext *pAvformatContext = formatContext.get();
+    APP_ERROR ret = avformat_open_input(&pAvformatContext, streamName.c_str(), nullptr, &options);
+    if (options != nullptr) {
+        av_dict_free(&options);
+    }
+
+    if (ret != APP_ERR_OK) {
+        LogError << "Couldn't open input stream " << streamName.c_str() <<  " ret = " << ret;
+        return APP_ERR_STREAM_NOT_EXIST;
+    }
+
+    ret = avformat_find_stream_info(formatContext.get(), nullptr);
+    if (ret != APP_ERR_OK) {
+        LogError << "Couldn't find stream information" << " ret = " << ret;
+        return APP_ERR_STREAM_NOT_EXIST;
+    }
+
+    return APP_ERR_OK;
+}
+
+APP_ERROR StreamPuller::GetStreamInfo()
+{
+    frameInfo.videoStream = -1;
+
+    if (formatContext != nullptr) {
+        for (uint32_t i = 0; i < formatContext->nb_streams; i++) {
+            AVStream *inStream = formatContext->streams[i];
+            if (inStream->codecpar->codec_type == AVMEDIA_TYPE_VIDEO) {
+                frameInfo.videoStream = i;
+                frameInfo.width = inStream->codecpar->width;
+                frameInfo.height = inStream->codecpar->height;
+                break;
+            }
+        }
+        if (frameInfo.videoStream == -1) {
+            LogError << "Didn't find a video stream!";
+            return APP_ERR_COMM_FAILURE;
+        }
+
+        AVCodecID codecId = formatContext->streams[frameInfo.videoStream]->codecpar->codec_id;
+        if (codecId == AV_CODEC_ID_H264) {
+            frameInfo.format = MxBase::MXBASE_STREAM_FORMAT_H264_MAIN_LEVEL;
+        } else if (codecId == AV_CODEC_ID_H265) {
+            frameInfo.format = MxBase::MXBASE_STREAM_FORMAT_H265_MAIN_LEVEL;
+        } else {
+            LogError << "\033[0;31mError unsupported format \033[0m" << codecId;
+            return APP_ERR_COMM_FAILURE;
+        }
+    }
+
+    // check video frame size
+    if (frameInfo.width < LOW_THRESHOLD || frameInfo.height < LOW_THRESHOLD ||
+        frameInfo.width > MAX_THRESHOLD || frameInfo.height > MAX_THRESHOLD) {
+        LogError << "Size of frame is not supported in DVPP Video Decode!";
+        return APP_ERR_COMM_FAILURE;
+    }
+
+    return APP_ERR_OK;
+}
+
+void StreamPuller::PullStreamDataLoop()
+{
+    while (true) {
+        if (stopFlag || formatContext == nullptr) {
+            LogDebug << "StreamPuller stopped or deinit, pull video stream exit";
+            break;
+        }
+        MxBase::MemoryData videoFrame = GetNextFrame();
+        if (videoFrame.size == 0 || videoFrame.ptrData == nullptr) {
+            LogDebug << "empty video frame, not need! continue!";
+            continue;
+        }
+        // todo send stream data to Device
+    }
+}
 } // end AscendStreamPuller
\ No newline at end of file
diff --git a/contrib/VideoGestureRecognition/StreamPuller/StreamPuller.h b/mxVision/mxVision-referenceapps/VideoGestureRecognition/StreamPuller/StreamPuller.h
similarity index 96%
rename from contrib/VideoGestureRecognition/StreamPuller/StreamPuller.h
rename to mxVision/mxVision-referenceapps/VideoGestureRecognition/StreamPuller/StreamPuller.h
index d5780ef5d103ea5b7863ae874663daf1442d1081..38268fa6240bb77ca42b8c8644413c27da08e3d7 100644
--- a/contrib/VideoGestureRecognition/StreamPuller/StreamPuller.h
+++ b/mxVision/mxVision-referenceapps/VideoGestureRecognition/StreamPuller/StreamPuller.h
@@ -1,77 +1,77 @@
-/*
- * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#ifndef VIDEOGESTUREREASONER_STREAMPULLER_H
-#define VIDEOGESTUREREASONER_STREAMPULLER_H
-
-#include <MxBase/DvppWrapper/DvppWrapper.h>
-#include "MxBase/MemoryHelper/MemoryHelper.h"
-#include "MxBase/ErrorCode/ErrorCode.h"
-#include "../BlockingQueue/BlockingQueue.h"
-
-extern "C" {
-#include "libavformat/avformat.h"
-}
-
-namespace AscendStreamPuller {
-struct VideoFrameInfo {
-    uint32_t width = 0;
-    uint32_t height = 0;
-    // video stream channel id
-    int32_t videoStream = 0;
-    // video format
-    MxBase::MxbaseStreamFormat format;
-    // video source
-    std::string source;
-};
-
-class StreamPuller {
-public:
-    StreamPuller() = default;
-    ~StreamPuller() = default;
-    APP_ERROR Init(const std::string &rtspUrl, uint32_t deviceId);
-    APP_ERROR DeInit();
-    APP_ERROR Process();
-    MxBase::MemoryData GetNextFrame();
-
-    VideoFrameInfo GetFrameInfo() const;
-
-public:
-    // running flag
-    bool stopFlag = true;
-
-private:
-    APP_ERROR TryToStartStream();
-    APP_ERROR StartStream();
-    APP_ERROR CreateFormatContext();
-    APP_ERROR GetStreamInfo();
-    void PullStreamDataLoop();
-
-private:
-    // rtsp stream source
-    std::string streamName = {};
-    // device id
-    uint32_t deviceId;
-    // max retry times
-    uint32_t maxReTryOpenStream = 1;
-    // video frame property
-    VideoFrameInfo frameInfo = {};
-    // ffmpeg class member
-    std::shared_ptr<AVFormatContext> formatContext;
-};
-} // end AscendStreamPuller
-
+/*
+ * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef VIDEOGESTUREREASONER_STREAMPULLER_H
+#define VIDEOGESTUREREASONER_STREAMPULLER_H
+
+#include <MxBase/DvppWrapper/DvppWrapper.h>
+#include "MxBase/MemoryHelper/MemoryHelper.h"
+#include "MxBase/ErrorCode/ErrorCode.h"
+#include "../BlockingQueue/BlockingQueue.h"
+
+extern "C" {
+#include "libavformat/avformat.h"
+}
+
+namespace AscendStreamPuller {
+struct VideoFrameInfo {
+    uint32_t width = 0;
+    uint32_t height = 0;
+    // video stream channel id
+    int32_t videoStream = 0;
+    // video format
+    MxBase::MxbaseStreamFormat format;
+    // video source
+    std::string source;
+};
+
+class StreamPuller {
+public:
+    StreamPuller() = default;
+    ~StreamPuller() = default;
+    APP_ERROR Init(const std::string &rtspUrl, uint32_t deviceId);
+    APP_ERROR DeInit();
+    APP_ERROR Process();
+    MxBase::MemoryData GetNextFrame();
+
+    VideoFrameInfo GetFrameInfo() const;
+
+public:
+    // running flag
+    bool stopFlag = true;
+
+private:
+    APP_ERROR TryToStartStream();
+    APP_ERROR StartStream();
+    APP_ERROR CreateFormatContext();
+    APP_ERROR GetStreamInfo();
+    void PullStreamDataLoop();
+
+private:
+    // rtsp stream source
+    std::string streamName = {};
+    // device id
+    uint32_t deviceId;
+    // max retry times
+    uint32_t maxReTryOpenStream = 1;
+    // video frame property
+    VideoFrameInfo frameInfo = {};
+    // ffmpeg class member
+    std::shared_ptr<AVFormatContext> formatContext;
+};
+} // end AscendStreamPuller
+
 #endif // VIDEOGESTUREREASONER_STREAMPULLER_H
\ No newline at end of file
diff --git a/contrib/VideoGestureRecognition/VideoDecoder/.keep b/mxVision/mxVision-referenceapps/VideoGestureRecognition/Util/.keep
similarity index 100%
rename from contrib/VideoGestureRecognition/VideoDecoder/.keep
rename to mxVision/mxVision-referenceapps/VideoGestureRecognition/Util/.keep
diff --git a/contrib/VideoGestureRecognition/Util/Util.cpp b/mxVision/mxVision-referenceapps/VideoGestureRecognition/Util/Util.cpp
similarity index 100%
rename from contrib/VideoGestureRecognition/Util/Util.cpp
rename to mxVision/mxVision-referenceapps/VideoGestureRecognition/Util/Util.cpp
diff --git a/contrib/VideoGestureRecognition/Util/Util.h b/mxVision/mxVision-referenceapps/VideoGestureRecognition/Util/Util.h
similarity index 97%
rename from contrib/VideoGestureRecognition/Util/Util.h
rename to mxVision/mxVision-referenceapps/VideoGestureRecognition/Util/Util.h
index be0c009f73f7eb4ad5eec9d0615e929f8c659f85..ee116608a216e804025f121d3a4f04e90b0bb238 100644
--- a/contrib/VideoGestureRecognition/Util/Util.h
+++ b/mxVision/mxVision-referenceapps/VideoGestureRecognition/Util/Util.h
@@ -1,66 +1,66 @@
-/*
- * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#ifndef MULTICHANNELVIDEODETECTION_UTIL_H
-#define MULTICHANNELVIDEODETECTION_UTIL_H
-
-#include <dirent.h>
-#include <cstdlib>
-#include "MxBase/Log/Log.h"
-#include "MxBase/DvppWrapper/DvppWrapper.h"
-#include "opencv2/opencv.hpp"
-#include "../StreamPuller/StreamPuller.h"
-#include "../VideoDecoder/VideoDecoder.h"
-#include "../BlockingQueue/BlockingQueue.h"
-#include "../ResnetDetector/ResnetDetector.h"
-
-class Util {
-public:
-    Util() = default;
-    ~Util() = default;
-
-    static void InitVideoDecoderParam(AscendVideoDecoder::DecoderInitParam &initParam,
-                                      const uint32_t deviceId, const uint32_t channelId,
-                                      const AscendStreamPuller::VideoFrameInfo &videoFrameInfo);
-
-    static void InitResnetParam(AscendResnetDetector::ResnetInitParam &initParam,
-                                const uint32_t deviceId, const std::string &labelPath,
-                                const std::string &modelPath);
-
-    static bool IsExistDataInQueueMap(const std::map<int,
-                                       std::shared_ptr<BlockingQueue<std::shared_ptr<void>>>> &decodeFrameQueueMap);
-
-    static APP_ERROR SaveResult(std::shared_ptr<MxBase::MemoryData> resultInfo, const uint32_t frameId,
-                                const std::vector<std::vector<MxBase::ClassInfo>>& objInfos,
-                                const uint32_t videoWidth, const uint32_t videoHeight,
-                                const int rtspIndex);
-
-private:
-    // class num
-    static const uint32_t CLASS_LABEL_NUM = 21;
-    // biases num
-    static const uint32_t BIASES_LABEL_NUM = 18;
-    // resnet type
-    static const uint32_t RESNET_TYPE = 3;
-    // anchor dim
-    static const uint32_t ANCHOR_DIM = 3;
-    // yuv type
-    static const uint32_t YUV_BYTE_NU = 3;
-    static const uint32_t YUV_BYTE_DE = 2;
-    static const uint32_t POINT_TYPE = 2;
-};
-
-#endif // MULTICHANNELVIDEODETECTION_UTIL_H
+/*
+ * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef MULTICHANNELVIDEODETECTION_UTIL_H
+#define MULTICHANNELVIDEODETECTION_UTIL_H
+
+#include <dirent.h>
+#include <cstdlib>
+#include "MxBase/Log/Log.h"
+#include "MxBase/DvppWrapper/DvppWrapper.h"
+#include "opencv2/opencv.hpp"
+#include "../StreamPuller/StreamPuller.h"
+#include "../VideoDecoder/VideoDecoder.h"
+#include "../BlockingQueue/BlockingQueue.h"
+#include "../ResnetDetector/ResnetDetector.h"
+
+class Util {
+public:
+    Util() = default;
+    ~Util() = default;
+
+    static void InitVideoDecoderParam(AscendVideoDecoder::DecoderInitParam &initParam,
+                                      const uint32_t deviceId, const uint32_t channelId,
+                                      const AscendStreamPuller::VideoFrameInfo &videoFrameInfo);
+
+    static void InitResnetParam(AscendResnetDetector::ResnetInitParam &initParam,
+                                const uint32_t deviceId, const std::string &labelPath,
+                                const std::string &modelPath);
+
+    static bool IsExistDataInQueueMap(const std::map<int,
+                                       std::shared_ptr<BlockingQueue<std::shared_ptr<void>>>> &decodeFrameQueueMap);
+
+    static APP_ERROR SaveResult(std::shared_ptr<MxBase::MemoryData> resultInfo, const uint32_t frameId,
+                                const std::vector<std::vector<MxBase::ClassInfo>>& objInfos,
+                                const uint32_t videoWidth, const uint32_t videoHeight,
+                                const int rtspIndex);
+
+private:
+    // class num
+    static const uint32_t CLASS_LABEL_NUM = 21;
+    // biases num
+    static const uint32_t BIASES_LABEL_NUM = 18;
+    // resnet type
+    static const uint32_t RESNET_TYPE = 3;
+    // anchor dim
+    static const uint32_t ANCHOR_DIM = 3;
+    // yuv type
+    static const uint32_t YUV_BYTE_NU = 3;
+    static const uint32_t YUV_BYTE_DE = 2;
+    static const uint32_t POINT_TYPE = 2;
+};
+
+#endif // MULTICHANNELVIDEODETECTION_UTIL_H
diff --git a/contrib/VideoGestureRecognition/VideoGestureReasoner/.keep b/mxVision/mxVision-referenceapps/VideoGestureRecognition/VideoDecoder/.keep
similarity index 100%
rename from contrib/VideoGestureRecognition/VideoGestureReasoner/.keep
rename to mxVision/mxVision-referenceapps/VideoGestureRecognition/VideoDecoder/.keep
diff --git a/contrib/VideoGestureRecognition/VideoDecoder/VideoDecoder.cpp b/mxVision/mxVision-referenceapps/VideoGestureRecognition/VideoDecoder/VideoDecoder.cpp
similarity index 96%
rename from contrib/VideoGestureRecognition/VideoDecoder/VideoDecoder.cpp
rename to mxVision/mxVision-referenceapps/VideoGestureRecognition/VideoDecoder/VideoDecoder.cpp
index 51ed37bafddd360c479b00107f8e8152b81aad24..243b787c5f804c694f8e64f705e6d71ef8884d62 100644
--- a/contrib/VideoGestureRecognition/VideoDecoder/VideoDecoder.cpp
+++ b/mxVision/mxVision-referenceapps/VideoGestureRecognition/VideoDecoder/VideoDecoder.cpp
@@ -1,155 +1,155 @@
-/*
- * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#include "VideoDecoder.h"
-#include "MxBase/Log/Log.h"
-
-namespace AscendVideoDecoder {
-namespace {
-}
-
-APP_ERROR VideoDecoder::Init(const DecoderInitParam &initParam)
-{
-    LogDebug << "VideoDecoder init start.";
-
-    this->channelId = initParam.channelId;
-    this->deviceId = initParam.deviceId;
-    this->frameWidth = initParam.inputVideoWidth;
-    this->frameHeight = initParam.inputVideoHeight;
-
-    APP_ERROR ret = InitDvppWrapper(initParam);
-    if (ret != APP_ERR_OK) {
-        LogError << "Init DvppWrapper failed.";
-        return ret;
-    }
-
-    stopFlag = false;
-    LogDebug << "VideoDecoder init successful.";
-    return APP_ERR_OK;
-}
-
-APP_ERROR VideoDecoder::DeInit()
-{
-    LogDebug << "VideoDecoder deinit start.";
-
-    APP_ERROR ret = vDvppWrapper->DeInitVdec();
-    if (ret != APP_ERR_OK) {
-        LogError << "Failed to deinit dvppWrapper";
-        return ret;
-    }
-
-    stopFlag = true;
-    LogDebug << "VideoDecoder deinit successful.";
-    return APP_ERR_OK;
-}
-
-APP_ERROR VideoDecoder::Process()
-{
-    return APP_ERR_OK;
-}
-
-APP_ERROR VideoDecoder::Decode(MxBase::MemoryData &streamData,
-                               const uint32_t &width,
-                               const uint32_t &height, void *userData)
-{
-    MxBase::MemoryData dvppMemory((size_t)streamData.size, MxBase::MemoryData::MEMORY_DVPP, this->channelId);
-    APP_ERROR ret = MxBase::MemoryHelper::MxbsMallocAndCopy(dvppMemory, streamData);
-    if (ret != APP_ERR_OK) {
-        LogError << "Failed to MxbsMallocAndCopy";
-        return ret;
-    }
-    MxBase::DvppDataInfo inputDataInfo;
-    inputDataInfo.dataSize = dvppMemory.size;
-    inputDataInfo.data = (uint8_t *)dvppMemory.ptrData;
-    inputDataInfo.height = height;
-    inputDataInfo.width = width;
-    inputDataInfo.channelId = this->channelId;
-    inputDataInfo.frameId = frameId;
-
-    ret = vDvppWrapper->DvppVdec(inputDataInfo, userData);
-    if (ret != APP_ERR_OK) {
-        LogError << "DvppVdec Failed";
-        MxBase::MemoryHelper::MxbsFree(dvppMemory);
-        return ret;
-    }
-
-    frameId++;
-    return APP_ERR_OK;
-}
-
-/// ========== private Method ========== ///
-
-APP_ERROR VideoDecoder::InitDvppWrapper(const DecoderInitParam &initParam)
-{
-    // init decode config
-    MxBase::VdecConfig vdecConfig;
-    vdecConfig.inputVideoFormat = initParam.inputVideoFormat;
-    vdecConfig.outputImageFormat = initParam.outputImageFormat;
-    vdecConfig.deviceId = initParam.deviceId;
-    vdecConfig.channelId = initParam.channelId;
-    vdecConfig.callbackFunc = VideoDecodeCallback;
-    vdecConfig.outMode = 1;
-
-    vDvppWrapper = std::make_shared<MxBase::DvppWrapper>();
-    if (vDvppWrapper == nullptr) {
-        LogError << "Failed to create DvppWrapper";
-        return APP_ERR_COMM_INIT_FAIL;
-    }
-
-    APP_ERROR ret = vDvppWrapper->InitVdec(vdecConfig);
-    if (ret != APP_ERR_OK) {
-        LogError << "Failed to init DvppWrapper";
-        return ret;
-    }
-
-    return APP_ERR_OK;
-}
-
-APP_ERROR VideoDecoder::VideoDecodeCallback(std::shared_ptr<void> buffer,
-                                            MxBase::DvppDataInfo &inputDataInfo, void *userData)
-{
-    LogDebug << "decode frame " << inputDataInfo.frameId << " complete";
-
-    auto deleter = [] (MxBase::MemoryData *memoryData) {
-        if (memoryData == nullptr) {
-            LogError << "MxbsFree failed";
-            return;
-        }
-
-        APP_ERROR ret = MxBase::MemoryHelper::MxbsFree(*memoryData);
-        delete memoryData;
-        if (ret != APP_ERR_OK) {
-            LogError << GetError(ret) << " MxbsFree failed";
-            return;
-        }
-    };
-
-    auto output = std::shared_ptr<MxBase::MemoryData>(
-            new MxBase::MemoryData(buffer.get(), (size_t)inputDataInfo.dataSize,
-                                   MxBase::MemoryData::MEMORY_DVPP,
-                                   inputDataInfo.frameId), deleter);
-
-    if (userData == nullptr) {
-        LogInfo << "userData is null";
-        return APP_ERR_COMM_INVALID_POINTER;
-    }
-
-    // put decoded frame into decoded frame queue
-    auto *decodeFrameQueue = (BlockingQueue<std::shared_ptr<void>>*)userData;
-    decodeFrameQueue->Push(output);
-    return APP_ERR_OK;
-}
+/*
+ * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "VideoDecoder.h"
+#include "MxBase/Log/Log.h"
+
+namespace AscendVideoDecoder {
+namespace {
+}
+
+APP_ERROR VideoDecoder::Init(const DecoderInitParam &initParam)
+{
+    LogDebug << "VideoDecoder init start.";
+
+    this->channelId = initParam.channelId;
+    this->deviceId = initParam.deviceId;
+    this->frameWidth = initParam.inputVideoWidth;
+    this->frameHeight = initParam.inputVideoHeight;
+
+    APP_ERROR ret = InitDvppWrapper(initParam);
+    if (ret != APP_ERR_OK) {
+        LogError << "Init DvppWrapper failed.";
+        return ret;
+    }
+
+    stopFlag = false;
+    LogDebug << "VideoDecoder init successful.";
+    return APP_ERR_OK;
+}
+
+APP_ERROR VideoDecoder::DeInit()
+{
+    LogDebug << "VideoDecoder deinit start.";
+
+    APP_ERROR ret = vDvppWrapper->DeInitVdec();
+    if (ret != APP_ERR_OK) {
+        LogError << "Failed to deinit dvppWrapper";
+        return ret;
+    }
+
+    stopFlag = true;
+    LogDebug << "VideoDecoder deinit successful.";
+    return APP_ERR_OK;
+}
+
+APP_ERROR VideoDecoder::Process()
+{
+    return APP_ERR_OK;
+}
+
+APP_ERROR VideoDecoder::Decode(MxBase::MemoryData &streamData,
+                               const uint32_t &width,
+                               const uint32_t &height, void *userData)
+{
+    MxBase::MemoryData dvppMemory((size_t)streamData.size, MxBase::MemoryData::MEMORY_DVPP, this->channelId);
+    APP_ERROR ret = MxBase::MemoryHelper::MxbsMallocAndCopy(dvppMemory, streamData);
+    if (ret != APP_ERR_OK) {
+        LogError << "Failed to MxbsMallocAndCopy";
+        return ret;
+    }
+    MxBase::DvppDataInfo inputDataInfo;
+    inputDataInfo.dataSize = dvppMemory.size;
+    inputDataInfo.data = (uint8_t *)dvppMemory.ptrData;
+    inputDataInfo.height = height;
+    inputDataInfo.width = width;
+    inputDataInfo.channelId = this->channelId;
+    inputDataInfo.frameId = frameId;
+
+    ret = vDvppWrapper->DvppVdec(inputDataInfo, userData);
+    if (ret != APP_ERR_OK) {
+        LogError << "DvppVdec Failed";
+        MxBase::MemoryHelper::MxbsFree(dvppMemory);
+        return ret;
+    }
+
+    frameId++;
+    return APP_ERR_OK;
+}
+
+/// ========== private Method ========== ///
+
+APP_ERROR VideoDecoder::InitDvppWrapper(const DecoderInitParam &initParam)
+{
+    // init decode config
+    MxBase::VdecConfig vdecConfig;
+    vdecConfig.inputVideoFormat = initParam.inputVideoFormat;
+    vdecConfig.outputImageFormat = initParam.outputImageFormat;
+    vdecConfig.deviceId = initParam.deviceId;
+    vdecConfig.channelId = initParam.channelId;
+    vdecConfig.callbackFunc = VideoDecodeCallback;
+    vdecConfig.outMode = 1;
+
+    vDvppWrapper = std::make_shared<MxBase::DvppWrapper>();
+    if (vDvppWrapper == nullptr) {
+        LogError << "Failed to create DvppWrapper";
+        return APP_ERR_COMM_INIT_FAIL;
+    }
+
+    APP_ERROR ret = vDvppWrapper->InitVdec(vdecConfig);
+    if (ret != APP_ERR_OK) {
+        LogError << "Failed to init DvppWrapper";
+        return ret;
+    }
+
+    return APP_ERR_OK;
+}
+
+APP_ERROR VideoDecoder::VideoDecodeCallback(std::shared_ptr<void> buffer,
+                                            MxBase::DvppDataInfo &inputDataInfo, void *userData)
+{
+    LogDebug << "decode frame " << inputDataInfo.frameId << " complete";
+
+    auto deleter = [] (MxBase::MemoryData *memoryData) {
+        if (memoryData == nullptr) {
+            LogError << "MxbsFree failed";
+            return;
+        }
+
+        APP_ERROR ret = MxBase::MemoryHelper::MxbsFree(*memoryData);
+        delete memoryData;
+        if (ret != APP_ERR_OK) {
+            LogError << GetError(ret) << " MxbsFree failed";
+            return;
+        }
+    };
+
+    auto output = std::shared_ptr<MxBase::MemoryData>(
+            new MxBase::MemoryData(buffer.get(), (size_t)inputDataInfo.dataSize,
+                                   MxBase::MemoryData::MEMORY_DVPP,
+                                   inputDataInfo.frameId), deleter);
+
+    if (userData == nullptr) {
+        LogInfo << "userData is null";
+        return APP_ERR_COMM_INVALID_POINTER;
+    }
+
+    // put decoded frame into decoded frame queue
+    auto *decodeFrameQueue = (BlockingQueue<std::shared_ptr<void>>*)userData;
+    decodeFrameQueue->Push(output);
+    return APP_ERR_OK;
+}
 } // end AscendVideoDecoder
\ No newline at end of file
diff --git a/contrib/VideoGestureRecognition/VideoDecoder/VideoDecoder.h b/mxVision/mxVision-referenceapps/VideoGestureRecognition/VideoDecoder/VideoDecoder.h
similarity index 96%
rename from contrib/VideoGestureRecognition/VideoDecoder/VideoDecoder.h
rename to mxVision/mxVision-referenceapps/VideoGestureRecognition/VideoDecoder/VideoDecoder.h
index a986a7d8fbc4a382db0dbb0ebf6e85b4fc5fd6ee..26b6074affd1d138f0185aa5b1cfc4a87633da5c 100644
--- a/contrib/VideoGestureRecognition/VideoDecoder/VideoDecoder.h
+++ b/mxVision/mxVision-referenceapps/VideoGestureRecognition/VideoDecoder/VideoDecoder.h
@@ -1,74 +1,74 @@
-/*
- * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#ifndef VIDEOGESTUREREASONER_VIDEODECODER_H
-#define VIDEOGESTUREREASONER_VIDEODECODER_H
-
-#include "MxBase/ErrorCode/ErrorCode.h"
-#include "MxBase/DvppWrapper/DvppWrapper.h"
-#include "MxBase/MemoryHelper/MemoryHelper.h"
-#include "../BlockingQueue/BlockingQueue.h"
-
-namespace AscendVideoDecoder {
-struct DecoderInitParam {
-    uint32_t deviceId = 0;
-    uint32_t channelId = 0;
-    uint32_t inputVideoWidth = 0;
-    uint32_t inputVideoHeight = 0;
-    MxBase::MxbaseStreamFormat inputVideoFormat;
-    MxBase::MxbasePixelFormat outputImageFormat;
-};
-
-class VideoDecoder {
-public:
-    VideoDecoder() = default;
-    ~VideoDecoder() = default;
-
-    APP_ERROR Init(const DecoderInitParam &initParam);
-    APP_ERROR DeInit();
-    APP_ERROR Process();
-    APP_ERROR Decode(MxBase::MemoryData &streamData,
-                     const uint32_t &width,
-                     const uint32_t &height, void *userData);
-
-public:
-    // running flag
-    bool stopFlag = true;
-
-private:
-    APP_ERROR InitDvppWrapper(const DecoderInitParam &initParam);
-    static APP_ERROR VideoDecodeCallback(std::shared_ptr<void> buffer,
-                                         MxBase::DvppDataInfo &inputDataInfo, void *userData);
-
-private:
-    // channel id
-    uint32_t channelId = 0;
-    // device id
-    uint32_t deviceId = 0;
-
-    // curr video frame id
-    uint32_t frameId = 0;
-    // video width
-    uint32_t frameWidth = 0;
-    // video height
-    uint32_t frameHeight = 0;
-
-    // video decoder (MX SDK)
-    std::shared_ptr<MxBase::DvppWrapper> vDvppWrapper;
-};
-} // end AscendVideoDecoder
-
-#endif // VIDEOGESTUREREASONER_VIDEODECODER_H
+/*
+ * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef VIDEOGESTUREREASONER_VIDEODECODER_H
+#define VIDEOGESTUREREASONER_VIDEODECODER_H
+
+#include "MxBase/ErrorCode/ErrorCode.h"
+#include "MxBase/DvppWrapper/DvppWrapper.h"
+#include "MxBase/MemoryHelper/MemoryHelper.h"
+#include "../BlockingQueue/BlockingQueue.h"
+
+namespace AscendVideoDecoder {
+struct DecoderInitParam {
+    uint32_t deviceId = 0;
+    uint32_t channelId = 0;
+    uint32_t inputVideoWidth = 0;
+    uint32_t inputVideoHeight = 0;
+    MxBase::MxbaseStreamFormat inputVideoFormat;
+    MxBase::MxbasePixelFormat outputImageFormat;
+};
+
+class VideoDecoder {
+public:
+    VideoDecoder() = default;
+    ~VideoDecoder() = default;
+
+    APP_ERROR Init(const DecoderInitParam &initParam);
+    APP_ERROR DeInit();
+    APP_ERROR Process();
+    APP_ERROR Decode(MxBase::MemoryData &streamData,
+                     const uint32_t &width,
+                     const uint32_t &height, void *userData);
+
+public:
+    // running flag
+    bool stopFlag = true;
+
+private:
+    APP_ERROR InitDvppWrapper(const DecoderInitParam &initParam);
+    static APP_ERROR VideoDecodeCallback(std::shared_ptr<void> buffer,
+                                         MxBase::DvppDataInfo &inputDataInfo, void *userData);
+
+private:
+    // channel id
+    uint32_t channelId = 0;
+    // device id
+    uint32_t deviceId = 0;
+
+    // curr video frame id
+    uint32_t frameId = 0;
+    // video width
+    uint32_t frameWidth = 0;
+    // video height
+    uint32_t frameHeight = 0;
+
+    // video decoder (MX SDK)
+    std::shared_ptr<MxBase::DvppWrapper> vDvppWrapper;
+};
+} // end AscendVideoDecoder
+
+#endif // VIDEOGESTUREREASONER_VIDEODECODER_H
diff --git a/contrib/VideoGestureRecognition/model/.keep b/mxVision/mxVision-referenceapps/VideoGestureRecognition/VideoGestureReasoner/.keep
similarity index 100%
rename from contrib/VideoGestureRecognition/model/.keep
rename to mxVision/mxVision-referenceapps/VideoGestureRecognition/VideoGestureReasoner/.keep
diff --git a/contrib/VideoGestureRecognition/VideoGestureReasoner/VideoGestureReasoner.cpp b/mxVision/mxVision-referenceapps/VideoGestureRecognition/VideoGestureReasoner/VideoGestureReasoner.cpp
similarity index 97%
rename from contrib/VideoGestureRecognition/VideoGestureReasoner/VideoGestureReasoner.cpp
rename to mxVision/mxVision-referenceapps/VideoGestureRecognition/VideoGestureReasoner/VideoGestureReasoner.cpp
index 04e1e3a95461f122b5ef51d95ad303b547118a9d..c2d220b49562ceb2ae9b11d19344f82129749934 100644
--- a/contrib/VideoGestureRecognition/VideoGestureReasoner/VideoGestureReasoner.cpp
+++ b/mxVision/mxVision-referenceapps/VideoGestureRecognition/VideoGestureReasoner/VideoGestureReasoner.cpp
@@ -1,432 +1,432 @@
-/*
- * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#include "VideoGestureReasoner.h"
-#include "../Util/Util.h"
-#include "MxBase/DeviceManager/DeviceManager.h"
-
-// init static variable
-bool VideoGestureReasoner::g_forceStop = false;
-
-APP_ERROR VideoGestureReasoner::Init(const ReasonerConfig &initConfig)
-{
-    LogDebug << "Init VideoGestureReasoner start.";
-    APP_ERROR ret;
-
-    ret = CreateStreamPullerAndVideoDecoder(initConfig);
-    if (ret != APP_ERR_OK) {
-        LogError << "CreateStreamPullerAndVideoDecoder failed.";
-        return ret;
-    }
-
-    ret = CreateFrameSkippingSampling(initConfig);
-    if (ret != APP_ERR_OK) {
-        LogError << "CreateFrameSkippingSampling failed.";
-        return ret;
-    }
-
-    ret = CreateImageResizer(initConfig);
-    if (ret != APP_ERR_OK) {
-        LogError << "CreateImageResizer failed.";
-        return ret;
-    }
-
-    ret = CreateResnetDetector(initConfig);
-    if (ret != APP_ERR_OK) {
-        LogError << "CreateResnetDetector failed.";
-        return ret;
-    }
-
-    this->deviceId = initConfig.deviceId;
-    this->resnetModelWidth = initConfig.resnetModelWidth;
-    this->resnetModelHeight = initConfig.resnetModelHeight;
-    this->popDecodeFrameWaitTime = initConfig.popDecodeFrameWaitTime;
-    this->maxDecodeFrameQueueLength = initConfig.maxDecodeFrameQueueLength;
-
-    this->stopFlag = false;
-    return APP_ERR_OK;
-}
-
-void VideoGestureReasoner::Process()
-{
-    std::vector<std::thread> videoProcessThreads;
-
-    auto decodeFrameQueue = std::make_shared<BlockingQueue<std::shared_ptr<void>>>(maxDecodeFrameQueueLength);
-    std::thread getDecodeVideoFrame(GetDecodeVideoFrame,
-                                    streamPullers[0],
-                                    videoDecoders[0],
-                                    decodeFrameQueue, this);
-
-    // save
-    videoProcessThreads.push_back(std::move(getDecodeVideoFrame));
-    decodeFrameQueueMap.insert(std::pair<int,
-                               std::shared_ptr<BlockingQueue<std::shared_ptr<void>>>>(0, decodeFrameQueue));
-
-    std::thread getDetectionResult(GetDetectionResult,
-                                   resnetModelWidth,
-                                   resnetModelHeight,
-                                   popDecodeFrameWaitTime, this);
-    videoProcessThreads.push_back(std::move(getDetectionResult));
-
-    while (!stopFlag) {
-        bool allVideoDataPulledAndDecoded = true;
-
-        if (streamPullers[0]->stopFlag) {
-            if (!videoDecoders[0]->stopFlag) {
-                LogDebug << "video frame decoded and no fresh data, quit video decoder. ";
-                videoDecoders[0]->stopFlag = true;
-            }
-        } else {
-            allVideoDataPulledAndDecoded = false;
-        }
-
-        bool allVideoDataProcessed = !Util::IsExistDataInQueueMap(decodeFrameQueueMap);
-        if (allVideoDataPulledAndDecoded && allVideoDataProcessed) {
-            LogDebug << "all decoded frame detected and no fresh data, quit image resizer and resnet detector";
-            imageResizer->stopFlag = true;
-            resnetDetector->stopFlag = true;
-        }
-
-        if (allVideoDataPulledAndDecoded && imageResizer->stopFlag && resnetDetector->stopFlag) {
-            LogDebug << "Both of stream puller, video decoder, image resizer and resnet detector quit, main quit";
-            stopFlag = true;
-        }
-
-        // force stop case
-        if (VideoGestureReasoner::g_forceStop) {
-            LogInfo << "Force stop VideoGestureReasoner.";
-            stopFlag = true;
-        }
-        std::this_thread::sleep_for(std::chrono::microseconds(delayTime));
-    }
-
-    // threads join
-    for (auto & videoProcessThread : videoProcessThreads) {
-        videoProcessThread.join();
-    }
-}
-
-APP_ERROR VideoGestureReasoner::DeInit()
-{
-    APP_ERROR ret;
-
-    ret = DestroyStreamPullerAndVideoDecoder();
-    if (ret != APP_ERR_OK) {
-        LogError << "DestroyStreamPullerAndVideoDecoder failed.";
-        return ret;
-    }
-
-    ret = DestroyFrameSkippingSampling();
-    if (ret != APP_ERR_OK) {
-        LogError << "DestroyFrameSkippingSampling failed.";
-        return ret;
-    }
-
-    ret = DestroyImageResizer();
-    if (ret != APP_ERR_OK) {
-        LogError << "DestroyImageResizer failed.";
-        return ret;
-    }
-
-    ret = DestroyResnetDetector();
-    if (ret != APP_ERR_OK) {
-        LogError << "DestroyresnetDetector failed.";
-        return ret;
-    }
-
-    ClearData();
-
-    this->stopFlag = true;
-    return APP_ERR_OK;
-}
-
-/// ========== static Method ========== ///
-void VideoGestureReasoner::GetDecodeVideoFrame(const std::shared_ptr<AscendStreamPuller::StreamPuller> &streamPuller,
-                                               const std::shared_ptr<AscendVideoDecoder::VideoDecoder> &videoDecoder,
-                                               const std::shared_ptr<BlockingQueue
-                                                       <std::shared_ptr<void>>> &decodeFrameQueue,
-                                               const VideoGestureReasoner *videoGestureReasoner)
-{
-    // set device
-    MxBase::DeviceContext device;
-    device.devId = videoGestureReasoner->deviceId;
-    APP_ERROR ret = MxBase::DeviceManager::GetInstance()->SetDevice(device);
-    if (ret != APP_ERR_OK) {
-        LogError << "SetDevice failed";
-        return;
-    }
-
-    while (true) {
-        if (videoGestureReasoner->stopFlag) {
-            LogDebug << "stop video stream pull and video frame decode";
-            streamPuller->stopFlag = true;
-            videoDecoder->stopFlag = true;
-            break;
-        }
-
-        if (streamPuller->stopFlag) {
-            LogDebug << "no video frame to pull and all pulled video frame decoded. quit!";
-            break;
-        }
-
-        // video stream pull
-        auto videoFrameData = streamPuller->GetNextFrame();
-        if (videoFrameData.size == 0) {
-            LogDebug << "empty video frame, not need decode, continue!";
-            continue;
-        }
-        videoDecoder->Decode(videoFrameData,
-                             streamPuller->GetFrameInfo().width,
-                             streamPuller->GetFrameInfo().height,
-                             decodeFrameQueue.get());
-    }
-}
-
-void VideoGestureReasoner::GetDetectionResult(const uint32_t &modelWidth,
-                                              const uint32_t &modelHeight,
-                                              const uint32_t &popDecodeFrameWaitTime,
-                                              const VideoGestureReasoner *videoGestureReasoner)
-{
-    // set device
-    MxBase::DeviceContext device;
-    device.devId = videoGestureReasoner->deviceId;
-    APP_ERROR ret = MxBase::DeviceManager::GetInstance()->SetDevice(device);
-    if (ret != APP_ERR_OK) {
-        LogError << "SetDevice failed";
-        return;
-    }
-
-    auto imageResizer = videoGestureReasoner->imageResizer;
-    auto resnetDetector = videoGestureReasoner->resnetDetector;
-    auto decodeFrameQueueMap = videoGestureReasoner->decodeFrameQueueMap;
-    auto videoFrameInfos = videoGestureReasoner->videoFrameInfos;
-    auto frameSkippingSampling = videoGestureReasoner->frameSkippingSampling;
-    while (true) {
-        if (videoGestureReasoner->stopFlag) {
-            LogDebug << "stop image resize and resnet detect";
-            imageResizer->stopFlag = true;
-            resnetDetector->stopFlag = true;
-            break;
-        }
-
-        if (imageResizer->stopFlag && resnetDetector->stopFlag) {
-            LogDebug << "no image need to resize and all image detected. quit!";
-            break;
-        }
-
-        if (!Util::IsExistDataInQueueMap(decodeFrameQueueMap)) {
-            continue;
-        }
-
-        std::_Rb_tree_const_iterator<std::pair<const int, std::shared_ptr<BlockingQueue<std::shared_ptr<void>>>>> iter;
-        for (iter = decodeFrameQueueMap.begin(); iter != decodeFrameQueueMap.end(); iter++) {
-            auto rtspIndex = iter->first;
-            auto decodeFrameQueue = iter->second;
-            if (decodeFrameQueue->IsEmpty()) {
-                continue;
-            }
-
-            ret = frameSkippingSampling->Process();
-            if (ret != APP_ERR_OK) {
-                LogError << "FrameSkippingSampling failed";
-                continue;
-            }
-
-            // get decode frame data
-            std::shared_ptr<void> data = nullptr;
-            ret = decodeFrameQueue->Pop(data, popDecodeFrameWaitTime);
-            if (ret != APP_ERR_OK) {
-                LogError << "Pop failed";
-                continue;
-            }
-            auto decodeFrame = std::make_shared<MxBase::MemoryData>();
-            decodeFrame = std::static_pointer_cast<MxBase::MemoryData>(data);
-
-            if (frameSkippingSampling->stopFlag) {
-                APP_ERROR ret = MxBase::DeviceManager::GetInstance()->SetDevice(device);
-                LogError << "resize frame and iter :";
-                // resize frame
-                MxBase::DvppDataInfo resizeFrame = {};
-                AscendImageResizer::ImageResizerParma imageInitParma;
-                imageInitParma.originHeight = videoFrameInfos[rtspIndex].height;
-                imageInitParma.originWidth = videoFrameInfos[rtspIndex].width;
-                imageInitParma.resizeHeight = modelHeight;
-                imageInitParma.resizeWidth = modelWidth;
-
-                ret = imageResizer->ResizeFromMemory(*decodeFrame, imageInitParma, resizeFrame);
-                if (ret != APP_ERR_OK) {
-                    LogError << "Resize image failed, ret = " << ret << " " << GetError(ret);
-                    continue;
-                }
-
-                // resnet detect
-                std::vector<std::vector<MxBase::ClassInfo>> objInfos;
-                ret = resnetDetector->Detect(resizeFrame, objInfos,
-                                             videoFrameInfos[rtspIndex].width,
-                                             videoFrameInfos[rtspIndex].height);
-                if (ret != APP_ERR_OK) {
-                    LogError << "Resnet detect image failed, ret = " << ret << " " << GetError(ret) << ".";
-                    continue;
-                }
-
-                // save detect result
-                ret = Util::SaveResult(decodeFrame, resizeFrame.frameId, objInfos,
-                                       videoFrameInfos[rtspIndex].width, videoFrameInfos[rtspIndex].height, rtspIndex);
-                if (ret != APP_ERR_OK) {
-                    LogError << "Save result failed, ret=" << ret << ".";
-                    return;
-                }
-            }
-        }
-    }
-}
-
-/// ========== private Method ========== ///
-APP_ERROR VideoGestureReasoner::CreateStreamPullerAndVideoDecoder(const ReasonerConfig &config)
-{
-    auto rtspList = config.rtspList;
-
-    APP_ERROR ret;
-    AscendStreamPuller::VideoFrameInfo videoFrameInfo;
-    AscendVideoDecoder::DecoderInitParam decoderInitParam = {};
-
-    auto streamPuller = std::make_shared<AscendStreamPuller::StreamPuller>();
-    auto videoDecoder = std::make_shared<AscendVideoDecoder::VideoDecoder>();
-
-    ret = streamPuller->Init(rtspList[0], config.deviceId);
-    if (ret != APP_ERR_OK) {
-        LogError << "Init " << " StreamPuller failed, stream name: " << rtspList[0];
-        return ret;
-    }
-    videoFrameInfo = streamPuller->GetFrameInfo();
-
-    Util::InitVideoDecoderParam(decoderInitParam, config.deviceId, config.baseVideoChannelId, videoFrameInfo);
-    ret = videoDecoder->Init(decoderInitParam);
-    if (ret != APP_ERR_OK) {
-        LogError << "Init " << " VideoDecoder failed";
-        return ret;
-    }
-
-    // save
-    streamPullers.push_back(streamPuller);
-    videoDecoders.push_back(videoDecoder);
-    videoFrameInfos.push_back(videoFrameInfo);
-
-    return APP_ERR_OK;
-}
-
-APP_ERROR VideoGestureReasoner::CreateFrameSkippingSampling(const ReasonerConfig &config)
-{
-    APP_ERROR ret;
-    frameSkippingSampling = std::make_shared<AscendFrameSkippingSampling::FrameSkippingSampling>();
-    ret = frameSkippingSampling->Init(config.maxSamplingInterval, config.samplingInterval, config.deviceId);
-    if (ret != APP_ERR_OK) {
-        LogError << "Init SamplingInterval failed";
-        return ret;
-    }
-    return APP_ERR_OK;
-}
-
-APP_ERROR VideoGestureReasoner::CreateImageResizer(const ReasonerConfig &config)
-{
-    imageResizer = std::make_shared<AscendImageResizer::ImageResizer>();
-
-    APP_ERROR ret = imageResizer->Init(config.deviceId);
-    if (ret != APP_ERR_OK) {
-        LogError << "Init image resizer failed";
-        return ret;
-    }
-    return APP_ERR_OK;
-}
-
-APP_ERROR VideoGestureReasoner::CreateResnetDetector(const ReasonerConfig &config)
-{
-    resnetDetector = std::make_shared<AscendResnetDetector::ResnetDetector>();
-
-    AscendResnetDetector::ResnetInitParam resnetInitParam;
-    Util::InitResnetParam(resnetInitParam, config.deviceId, config.resnetLabelPath, config.resnetModelPath);
-    APP_ERROR ret = resnetDetector->Init(resnetInitParam);
-    if (ret != APP_ERR_OK) {
-        LogError << "Init resnet detector failed.";
-        return ret;
-    }
-    return APP_ERR_OK;
-}
-
-APP_ERROR VideoGestureReasoner::DestroyStreamPullerAndVideoDecoder()
-{
-    APP_ERROR ret;
-    // deinit video decoder
-    ret = videoDecoders[0]->DeInit();
-    if (ret != APP_ERR_OK) {
-        LogError << "Deinit " << " VideoDecoder failed";
-        return ret;
-    }
-
-    // deinit stream puller
-    ret = streamPullers[0]->DeInit();
-    if (ret != APP_ERR_OK) {
-        LogError << "Deinit "  << " StreamPuller failed.";
-        return ret;
-    }
-
-    return APP_ERR_OK;
-}
-
-APP_ERROR VideoGestureReasoner::DestroyFrameSkippingSampling()
-{
-    APP_ERROR ret = frameSkippingSampling->DeInit();
-    if (ret != APP_ERR_OK) {
-        LogError << "FrameSkippingSampling DeInit failed.";
-        return ret;
-    }
-    return APP_ERR_OK;
-}
-
-APP_ERROR VideoGestureReasoner::DestroyImageResizer()
-{
-    APP_ERROR ret = imageResizer->DeInit();
-    if (ret != APP_ERR_OK) {
-        LogError << "ImageResizer DeInit failed.";
-        return ret;
-    }
-    return APP_ERR_OK;
-}
-
-APP_ERROR VideoGestureReasoner::DestroyResnetDetector()
-{
-    APP_ERROR ret = resnetDetector->DeInit();
-    if (ret != APP_ERR_OK) {
-        LogError << "ResnetDetector DeInit failed.";
-        return ret;
-    }
-    return APP_ERR_OK;
-}
-
-void VideoGestureReasoner::ClearData()
-{
-    // stop and clear queue
-    std::_Rb_tree_const_iterator<std::pair<const int, std::shared_ptr<BlockingQueue<std::shared_ptr<void>>>>> iter;
-    for (iter = decodeFrameQueueMap.begin(); iter != decodeFrameQueueMap.end(); iter++) {
-        iter->second->Stop();
-        iter->second->Clear();
-    }
-    decodeFrameQueueMap.clear();
-    videoFrameInfos.clear();
-    videoDecoders.clear();
-    streamPullers.clear();
-}
-
+/*
+ * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "VideoGestureReasoner.h"
+#include "../Util/Util.h"
+#include "MxBase/DeviceManager/DeviceManager.h"
+
+// init static variable
+bool VideoGestureReasoner::g_forceStop = false;
+
+APP_ERROR VideoGestureReasoner::Init(const ReasonerConfig &initConfig)
+{
+    LogDebug << "Init VideoGestureReasoner start.";
+    APP_ERROR ret;
+
+    ret = CreateStreamPullerAndVideoDecoder(initConfig);
+    if (ret != APP_ERR_OK) {
+        LogError << "CreateStreamPullerAndVideoDecoder failed.";
+        return ret;
+    }
+
+    ret = CreateFrameSkippingSampling(initConfig);
+    if (ret != APP_ERR_OK) {
+        LogError << "CreateFrameSkippingSampling failed.";
+        return ret;
+    }
+
+    ret = CreateImageResizer(initConfig);
+    if (ret != APP_ERR_OK) {
+        LogError << "CreateImageResizer failed.";
+        return ret;
+    }
+
+    ret = CreateResnetDetector(initConfig);
+    if (ret != APP_ERR_OK) {
+        LogError << "CreateResnetDetector failed.";
+        return ret;
+    }
+
+    this->deviceId = initConfig.deviceId;
+    this->resnetModelWidth = initConfig.resnetModelWidth;
+    this->resnetModelHeight = initConfig.resnetModelHeight;
+    this->popDecodeFrameWaitTime = initConfig.popDecodeFrameWaitTime;
+    this->maxDecodeFrameQueueLength = initConfig.maxDecodeFrameQueueLength;
+
+    this->stopFlag = false;
+    return APP_ERR_OK;
+}
+
+void VideoGestureReasoner::Process()
+{
+    std::vector<std::thread> videoProcessThreads;
+
+    auto decodeFrameQueue = std::make_shared<BlockingQueue<std::shared_ptr<void>>>(maxDecodeFrameQueueLength);
+    std::thread getDecodeVideoFrame(GetDecodeVideoFrame,
+                                    streamPullers[0],
+                                    videoDecoders[0],
+                                    decodeFrameQueue, this);
+
+    // save
+    videoProcessThreads.push_back(std::move(getDecodeVideoFrame));
+    decodeFrameQueueMap.insert(std::pair<int,
+                               std::shared_ptr<BlockingQueue<std::shared_ptr<void>>>>(0, decodeFrameQueue));
+
+    std::thread getDetectionResult(GetDetectionResult,
+                                   resnetModelWidth,
+                                   resnetModelHeight,
+                                   popDecodeFrameWaitTime, this);
+    videoProcessThreads.push_back(std::move(getDetectionResult));
+
+    while (!stopFlag) {
+        bool allVideoDataPulledAndDecoded = true;
+
+        if (streamPullers[0]->stopFlag) {
+            if (!videoDecoders[0]->stopFlag) {
+                LogDebug << "video frame decoded and no fresh data, quit video decoder. ";
+                videoDecoders[0]->stopFlag = true;
+            }
+        } else {
+            allVideoDataPulledAndDecoded = false;
+        }
+
+        bool allVideoDataProcessed = !Util::IsExistDataInQueueMap(decodeFrameQueueMap);
+        if (allVideoDataPulledAndDecoded && allVideoDataProcessed) {
+            LogDebug << "all decoded frame detected and no fresh data, quit image resizer and resnet detector";
+            imageResizer->stopFlag = true;
+            resnetDetector->stopFlag = true;
+        }
+
+        if (allVideoDataPulledAndDecoded && imageResizer->stopFlag && resnetDetector->stopFlag) {
+            LogDebug << "Both of stream puller, video decoder, image resizer and resnet detector quit, main quit";
+            stopFlag = true;
+        }
+
+        // force stop case
+        if (VideoGestureReasoner::g_forceStop) {
+            LogInfo << "Force stop VideoGestureReasoner.";
+            stopFlag = true;
+        }
+        std::this_thread::sleep_for(std::chrono::microseconds(delayTime));
+    }
+
+    // threads join
+    for (auto & videoProcessThread : videoProcessThreads) {
+        videoProcessThread.join();
+    }
+}
+
+APP_ERROR VideoGestureReasoner::DeInit()
+{
+    APP_ERROR ret;
+
+    ret = DestroyStreamPullerAndVideoDecoder();
+    if (ret != APP_ERR_OK) {
+        LogError << "DestroyStreamPullerAndVideoDecoder failed.";
+        return ret;
+    }
+
+    ret = DestroyFrameSkippingSampling();
+    if (ret != APP_ERR_OK) {
+        LogError << "DestroyFrameSkippingSampling failed.";
+        return ret;
+    }
+
+    ret = DestroyImageResizer();
+    if (ret != APP_ERR_OK) {
+        LogError << "DestroyImageResizer failed.";
+        return ret;
+    }
+
+    ret = DestroyResnetDetector();
+    if (ret != APP_ERR_OK) {
+        LogError << "DestroyresnetDetector failed.";
+        return ret;
+    }
+
+    ClearData();
+
+    this->stopFlag = true;
+    return APP_ERR_OK;
+}
+
+/// ========== static Method ========== ///
+void VideoGestureReasoner::GetDecodeVideoFrame(const std::shared_ptr<AscendStreamPuller::StreamPuller> &streamPuller,
+                                               const std::shared_ptr<AscendVideoDecoder::VideoDecoder> &videoDecoder,
+                                               const std::shared_ptr<BlockingQueue
+                                                       <std::shared_ptr<void>>> &decodeFrameQueue,
+                                               const VideoGestureReasoner *videoGestureReasoner)
+{
+    // set device
+    MxBase::DeviceContext device;
+    device.devId = videoGestureReasoner->deviceId;
+    APP_ERROR ret = MxBase::DeviceManager::GetInstance()->SetDevice(device);
+    if (ret != APP_ERR_OK) {
+        LogError << "SetDevice failed";
+        return;
+    }
+
+    while (true) {
+        if (videoGestureReasoner->stopFlag) {
+            LogDebug << "stop video stream pull and video frame decode";
+            streamPuller->stopFlag = true;
+            videoDecoder->stopFlag = true;
+            break;
+        }
+
+        if (streamPuller->stopFlag) {
+            LogDebug << "no video frame to pull and all pulled video frame decoded. quit!";
+            break;
+        }
+
+        // video stream pull
+        auto videoFrameData = streamPuller->GetNextFrame();
+        if (videoFrameData.size == 0) {
+            LogDebug << "empty video frame, not need decode, continue!";
+            continue;
+        }
+        videoDecoder->Decode(videoFrameData,
+                             streamPuller->GetFrameInfo().width,
+                             streamPuller->GetFrameInfo().height,
+                             decodeFrameQueue.get());
+    }
+}
+
+void VideoGestureReasoner::GetDetectionResult(const uint32_t &modelWidth,
+                                              const uint32_t &modelHeight,
+                                              const uint32_t &popDecodeFrameWaitTime,
+                                              const VideoGestureReasoner *videoGestureReasoner)
+{
+    // set device
+    MxBase::DeviceContext device;
+    device.devId = videoGestureReasoner->deviceId;
+    APP_ERROR ret = MxBase::DeviceManager::GetInstance()->SetDevice(device);
+    if (ret != APP_ERR_OK) {
+        LogError << "SetDevice failed";
+        return;
+    }
+
+    auto imageResizer = videoGestureReasoner->imageResizer;
+    auto resnetDetector = videoGestureReasoner->resnetDetector;
+    auto decodeFrameQueueMap = videoGestureReasoner->decodeFrameQueueMap;
+    auto videoFrameInfos = videoGestureReasoner->videoFrameInfos;
+    auto frameSkippingSampling = videoGestureReasoner->frameSkippingSampling;
+    while (true) {
+        if (videoGestureReasoner->stopFlag) {
+            LogDebug << "stop image resize and resnet detect";
+            imageResizer->stopFlag = true;
+            resnetDetector->stopFlag = true;
+            break;
+        }
+
+        if (imageResizer->stopFlag && resnetDetector->stopFlag) {
+            LogDebug << "no image need to resize and all image detected. quit!";
+            break;
+        }
+
+        if (!Util::IsExistDataInQueueMap(decodeFrameQueueMap)) {
+            continue;
+        }
+
+        std::_Rb_tree_const_iterator<std::pair<const int, std::shared_ptr<BlockingQueue<std::shared_ptr<void>>>>> iter;
+        for (iter = decodeFrameQueueMap.begin(); iter != decodeFrameQueueMap.end(); iter++) {
+            auto rtspIndex = iter->first;
+            auto decodeFrameQueue = iter->second;
+            if (decodeFrameQueue->IsEmpty()) {
+                continue;
+            }
+
+            ret = frameSkippingSampling->Process();
+            if (ret != APP_ERR_OK) {
+                LogError << "FrameSkippingSampling failed";
+                continue;
+            }
+
+            // get decode frame data
+            std::shared_ptr<void> data = nullptr;
+            ret = decodeFrameQueue->Pop(data, popDecodeFrameWaitTime);
+            if (ret != APP_ERR_OK) {
+                LogError << "Pop failed";
+                continue;
+            }
+            auto decodeFrame = std::make_shared<MxBase::MemoryData>();
+            decodeFrame = std::static_pointer_cast<MxBase::MemoryData>(data);
+
+            if (frameSkippingSampling->stopFlag) {
+                APP_ERROR ret = MxBase::DeviceManager::GetInstance()->SetDevice(device);
+                LogError << "resize frame and iter :";
+                // resize frame
+                MxBase::DvppDataInfo resizeFrame = {};
+                AscendImageResizer::ImageResizerParma imageInitParma;
+                imageInitParma.originHeight = videoFrameInfos[rtspIndex].height;
+                imageInitParma.originWidth = videoFrameInfos[rtspIndex].width;
+                imageInitParma.resizeHeight = modelHeight;
+                imageInitParma.resizeWidth = modelWidth;
+
+                ret = imageResizer->ResizeFromMemory(*decodeFrame, imageInitParma, resizeFrame);
+                if (ret != APP_ERR_OK) {
+                    LogError << "Resize image failed, ret = " << ret << " " << GetError(ret);
+                    continue;
+                }
+
+                // resnet detect
+                std::vector<std::vector<MxBase::ClassInfo>> objInfos;
+                ret = resnetDetector->Detect(resizeFrame, objInfos,
+                                             videoFrameInfos[rtspIndex].width,
+                                             videoFrameInfos[rtspIndex].height);
+                if (ret != APP_ERR_OK) {
+                    LogError << "Resnet detect image failed, ret = " << ret << " " << GetError(ret) << ".";
+                    continue;
+                }
+
+                // save detect result
+                ret = Util::SaveResult(decodeFrame, resizeFrame.frameId, objInfos,
+                                       videoFrameInfos[rtspIndex].width, videoFrameInfos[rtspIndex].height, rtspIndex);
+                if (ret != APP_ERR_OK) {
+                    LogError << "Save result failed, ret=" << ret << ".";
+                    return;
+                }
+            }
+        }
+    }
+}
+
+/// ========== private Method ========== ///
+APP_ERROR VideoGestureReasoner::CreateStreamPullerAndVideoDecoder(const ReasonerConfig &config)
+{
+    auto rtspList = config.rtspList;
+
+    APP_ERROR ret;
+    AscendStreamPuller::VideoFrameInfo videoFrameInfo;
+    AscendVideoDecoder::DecoderInitParam decoderInitParam = {};
+
+    auto streamPuller = std::make_shared<AscendStreamPuller::StreamPuller>();
+    auto videoDecoder = std::make_shared<AscendVideoDecoder::VideoDecoder>();
+
+    ret = streamPuller->Init(rtspList[0], config.deviceId);
+    if (ret != APP_ERR_OK) {
+        LogError << "Init " << " StreamPuller failed, stream name: " << rtspList[0];
+        return ret;
+    }
+    videoFrameInfo = streamPuller->GetFrameInfo();
+
+    Util::InitVideoDecoderParam(decoderInitParam, config.deviceId, config.baseVideoChannelId, videoFrameInfo);
+    ret = videoDecoder->Init(decoderInitParam);
+    if (ret != APP_ERR_OK) {
+        LogError << "Init " << " VideoDecoder failed";
+        return ret;
+    }
+
+    // save
+    streamPullers.push_back(streamPuller);
+    videoDecoders.push_back(videoDecoder);
+    videoFrameInfos.push_back(videoFrameInfo);
+
+    return APP_ERR_OK;
+}
+
+APP_ERROR VideoGestureReasoner::CreateFrameSkippingSampling(const ReasonerConfig &config)
+{
+    APP_ERROR ret;
+    frameSkippingSampling = std::make_shared<AscendFrameSkippingSampling::FrameSkippingSampling>();
+    ret = frameSkippingSampling->Init(config.maxSamplingInterval, config.samplingInterval, config.deviceId);
+    if (ret != APP_ERR_OK) {
+        LogError << "Init SamplingInterval failed";
+        return ret;
+    }
+    return APP_ERR_OK;
+}
+
+APP_ERROR VideoGestureReasoner::CreateImageResizer(const ReasonerConfig &config)
+{
+    imageResizer = std::make_shared<AscendImageResizer::ImageResizer>();
+
+    APP_ERROR ret = imageResizer->Init(config.deviceId);
+    if (ret != APP_ERR_OK) {
+        LogError << "Init image resizer failed";
+        return ret;
+    }
+    return APP_ERR_OK;
+}
+
+APP_ERROR VideoGestureReasoner::CreateResnetDetector(const ReasonerConfig &config)
+{
+    resnetDetector = std::make_shared<AscendResnetDetector::ResnetDetector>();
+
+    AscendResnetDetector::ResnetInitParam resnetInitParam;
+    Util::InitResnetParam(resnetInitParam, config.deviceId, config.resnetLabelPath, config.resnetModelPath);
+    APP_ERROR ret = resnetDetector->Init(resnetInitParam);
+    if (ret != APP_ERR_OK) {
+        LogError << "Init resnet detector failed.";
+        return ret;
+    }
+    return APP_ERR_OK;
+}
+
+APP_ERROR VideoGestureReasoner::DestroyStreamPullerAndVideoDecoder()
+{
+    APP_ERROR ret;
+    // deinit video decoder
+    ret = videoDecoders[0]->DeInit();
+    if (ret != APP_ERR_OK) {
+        LogError << "Deinit " << " VideoDecoder failed";
+        return ret;
+    }
+
+    // deinit stream puller
+    ret = streamPullers[0]->DeInit();
+    if (ret != APP_ERR_OK) {
+        LogError << "Deinit "  << " StreamPuller failed.";
+        return ret;
+    }
+
+    return APP_ERR_OK;
+}
+
+APP_ERROR VideoGestureReasoner::DestroyFrameSkippingSampling()
+{
+    APP_ERROR ret = frameSkippingSampling->DeInit();
+    if (ret != APP_ERR_OK) {
+        LogError << "FrameSkippingSampling DeInit failed.";
+        return ret;
+    }
+    return APP_ERR_OK;
+}
+
+APP_ERROR VideoGestureReasoner::DestroyImageResizer()
+{
+    APP_ERROR ret = imageResizer->DeInit();
+    if (ret != APP_ERR_OK) {
+        LogError << "ImageResizer DeInit failed.";
+        return ret;
+    }
+    return APP_ERR_OK;
+}
+
+APP_ERROR VideoGestureReasoner::DestroyResnetDetector()
+{
+    APP_ERROR ret = resnetDetector->DeInit();
+    if (ret != APP_ERR_OK) {
+        LogError << "ResnetDetector DeInit failed.";
+        return ret;
+    }
+    return APP_ERR_OK;
+}
+
+void VideoGestureReasoner::ClearData()
+{
+    // stop and clear queue
+    std::_Rb_tree_const_iterator<std::pair<const int, std::shared_ptr<BlockingQueue<std::shared_ptr<void>>>>> iter;
+    for (iter = decodeFrameQueueMap.begin(); iter != decodeFrameQueueMap.end(); iter++) {
+        iter->second->Stop();
+        iter->second->Clear();
+    }
+    decodeFrameQueueMap.clear();
+    videoFrameInfos.clear();
+    videoDecoders.clear();
+    streamPullers.clear();
+}
+
diff --git a/contrib/VideoGestureRecognition/VideoGestureReasoner/VideoGestureReasoner.h b/mxVision/mxVision-referenceapps/VideoGestureRecognition/VideoGestureReasoner/VideoGestureReasoner.h
similarity index 97%
rename from contrib/VideoGestureRecognition/VideoGestureReasoner/VideoGestureReasoner.h
rename to mxVision/mxVision-referenceapps/VideoGestureRecognition/VideoGestureReasoner/VideoGestureReasoner.h
index 73efb6679deaa9bcb29353d766266370e600792b..3cf56b0f19415e11b76689923bff0122466fbdba 100644
--- a/contrib/VideoGestureRecognition/VideoGestureReasoner/VideoGestureReasoner.h
+++ b/mxVision/mxVision-referenceapps/VideoGestureRecognition/VideoGestureReasoner/VideoGestureReasoner.h
@@ -1,98 +1,98 @@
-/*
- * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#ifndef VIDEOGESTUREREASONER_VIDEOGESTUREREASONER_H
-#define VIDEOGESTUREREASONER_VIDEOGESTUREREASONER_H
-
-#include <thread>
-#include "../FrameSkippingSampling/FrameSkippingSampling.h"
-#include "../StreamPuller/StreamPuller.h"
-#include "../VideoDecoder/VideoDecoder.h"
-#include "../ImageResizer/ImageResizer.h"
-#include "../ResnetDetector/ResnetDetector.h"
-
-struct ReasonerConfig {
-    uint32_t deviceId = 0;
-    uint32_t baseVideoChannelId = 0;
-    std::vector<std::string> rtspList;
-    std::string resnetModelPath;
-    std::string resnetLabelPath;
-    uint32_t resnetModelWidth = 0;
-    uint32_t resnetModelHeight = 0;
-    uint32_t maxDecodeFrameQueueLength = 0;
-    uint32_t popDecodeFrameWaitTime = 0;
-    uint32_t samplingInterval = 0;
-    uint32_t maxSamplingInterval = 0;
-};
-
-class VideoGestureReasoner {
-public:
-    VideoGestureReasoner() = default;
-    ~VideoGestureReasoner() = default;
-
-    APP_ERROR Init(const ReasonerConfig &initConfig);
-    APP_ERROR DeInit();
-    void Process();
-
-public:
-    static bool g_forceStop;
-
-private:
-    static void GetDecodeVideoFrame(const std::shared_ptr<AscendStreamPuller::StreamPuller> &streamPuller,
-                                    const std::shared_ptr<AscendVideoDecoder::VideoDecoder> &videoDecoder,
-                                    const std::shared_ptr<BlockingQueue<std::shared_ptr<void>>> &decodeFrameQueue,
-                                    const VideoGestureReasoner *videoGestureReasoner);
-    static void GetDetectionResult(const uint32_t &modelWidth,
-                                   const uint32_t &modelHeight,
-                                   const uint32_t &popDecodeFrameWaitTime,
-                                   const VideoGestureReasoner *videoGestureReasoner);
-
-private:
-    APP_ERROR CreateStreamPullerAndVideoDecoder(const ReasonerConfig &config);
-    APP_ERROR CreateFrameSkippingSampling(const ReasonerConfig &config);
-    APP_ERROR CreateImageResizer(const ReasonerConfig &config);
-    APP_ERROR CreateResnetDetector(const ReasonerConfig &config);
-
-    APP_ERROR DestroyStreamPullerAndVideoDecoder();
-    APP_ERROR DestroyFrameSkippingSampling();
-    APP_ERROR DestroyImageResizer();
-    APP_ERROR DestroyResnetDetector();
-
-    void ClearData();
-
-private:
-    uint32_t deviceId = 0;
-    bool stopFlag = true;
-    const uint32_t delayTime = 1000;
-
-    uint32_t resnetModelWidth = 0;
-    uint32_t resnetModelHeight = 0;
-    uint32_t popDecodeFrameWaitTime = 0;
-    uint32_t maxDecodeFrameQueueLength = 0;
-
-private:
-    std::vector<AscendStreamPuller::VideoFrameInfo> videoFrameInfos;
-    std::vector<std::shared_ptr<AscendStreamPuller::StreamPuller>> streamPullers;
-    std::vector<std::shared_ptr<AscendVideoDecoder::VideoDecoder>> videoDecoders;
-
-    std::shared_ptr<AscendImageResizer::ImageResizer> imageResizer;
-    std::shared_ptr<AscendResnetDetector::ResnetDetector> resnetDetector;
-    std::shared_ptr<AscendFrameSkippingSampling::FrameSkippingSampling> frameSkippingSampling;
-
-    std::map<int, std::shared_ptr<BlockingQueue<std::shared_ptr<void>>>> decodeFrameQueueMap;
-};
-
-#endif // VIDEOGESTUREREASONER_VIDEOGESTUREREASONER_H
+/*
+ * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef VIDEOGESTUREREASONER_VIDEOGESTUREREASONER_H
+#define VIDEOGESTUREREASONER_VIDEOGESTUREREASONER_H
+
+#include <thread>
+#include "../FrameSkippingSampling/FrameSkippingSampling.h"
+#include "../StreamPuller/StreamPuller.h"
+#include "../VideoDecoder/VideoDecoder.h"
+#include "../ImageResizer/ImageResizer.h"
+#include "../ResnetDetector/ResnetDetector.h"
+
+struct ReasonerConfig {
+    uint32_t deviceId = 0;
+    uint32_t baseVideoChannelId = 0;
+    std::vector<std::string> rtspList;
+    std::string resnetModelPath;
+    std::string resnetLabelPath;
+    uint32_t resnetModelWidth = 0;
+    uint32_t resnetModelHeight = 0;
+    uint32_t maxDecodeFrameQueueLength = 0;
+    uint32_t popDecodeFrameWaitTime = 0;
+    uint32_t samplingInterval = 0;
+    uint32_t maxSamplingInterval = 0;
+};
+
+class VideoGestureReasoner {
+public:
+    VideoGestureReasoner() = default;
+    ~VideoGestureReasoner() = default;
+
+    APP_ERROR Init(const ReasonerConfig &initConfig);
+    APP_ERROR DeInit();
+    void Process();
+
+public:
+    static bool g_forceStop;
+
+private:
+    static void GetDecodeVideoFrame(const std::shared_ptr<AscendStreamPuller::StreamPuller> &streamPuller,
+                                    const std::shared_ptr<AscendVideoDecoder::VideoDecoder> &videoDecoder,
+                                    const std::shared_ptr<BlockingQueue<std::shared_ptr<void>>> &decodeFrameQueue,
+                                    const VideoGestureReasoner *videoGestureReasoner);
+    static void GetDetectionResult(const uint32_t &modelWidth,
+                                   const uint32_t &modelHeight,
+                                   const uint32_t &popDecodeFrameWaitTime,
+                                   const VideoGestureReasoner *videoGestureReasoner);
+
+private:
+    APP_ERROR CreateStreamPullerAndVideoDecoder(const ReasonerConfig &config);
+    APP_ERROR CreateFrameSkippingSampling(const ReasonerConfig &config);
+    APP_ERROR CreateImageResizer(const ReasonerConfig &config);
+    APP_ERROR CreateResnetDetector(const ReasonerConfig &config);
+
+    APP_ERROR DestroyStreamPullerAndVideoDecoder();
+    APP_ERROR DestroyFrameSkippingSampling();
+    APP_ERROR DestroyImageResizer();
+    APP_ERROR DestroyResnetDetector();
+
+    void ClearData();
+
+private:
+    uint32_t deviceId = 0;
+    bool stopFlag = true;
+    const uint32_t delayTime = 1000;
+
+    uint32_t resnetModelWidth = 0;
+    uint32_t resnetModelHeight = 0;
+    uint32_t popDecodeFrameWaitTime = 0;
+    uint32_t maxDecodeFrameQueueLength = 0;
+
+private:
+    std::vector<AscendStreamPuller::VideoFrameInfo> videoFrameInfos;
+    std::vector<std::shared_ptr<AscendStreamPuller::StreamPuller>> streamPullers;
+    std::vector<std::shared_ptr<AscendVideoDecoder::VideoDecoder>> videoDecoders;
+
+    std::shared_ptr<AscendImageResizer::ImageResizer> imageResizer;
+    std::shared_ptr<AscendResnetDetector::ResnetDetector> resnetDetector;
+    std::shared_ptr<AscendFrameSkippingSampling::FrameSkippingSampling> frameSkippingSampling;
+
+    std::map<int, std::shared_ptr<BlockingQueue<std::shared_ptr<void>>>> decodeFrameQueueMap;
+};
+
+#endif // VIDEOGESTUREREASONER_VIDEOGESTUREREASONER_H
diff --git a/contrib/VideoGestureRecognition/build.sh b/mxVision/mxVision-referenceapps/VideoGestureRecognition/build.sh
similarity index 100%
rename from contrib/VideoGestureRecognition/build.sh
rename to mxVision/mxVision-referenceapps/VideoGestureRecognition/build.sh
diff --git a/contrib/VideoGestureRecognition/main.cpp b/mxVision/mxVision-referenceapps/VideoGestureRecognition/main.cpp
similarity index 96%
rename from contrib/VideoGestureRecognition/main.cpp
rename to mxVision/mxVision-referenceapps/VideoGestureRecognition/main.cpp
index 9c7e1b7207dcea01af053d2ec15758296da1f913..cf3c43636084324a580029ba68105c25ab9bae13 100644
--- a/contrib/VideoGestureRecognition/main.cpp
+++ b/mxVision/mxVision-referenceapps/VideoGestureRecognition/main.cpp
@@ -1,158 +1,158 @@
-/*
- * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#include "MxBase/ErrorCode/ErrorCode.h"
-#include "MxBase/Log/Log.h"
-#include "MxBase/DeviceManager/DeviceManager.h"
-#include "VideoGestureReasoner/VideoGestureReasoner.h"
-#include <csignal>
-
-namespace {
-    // device id
-    const uint32_t DEVICE_ID = 0;
-    // channel id
-    const uint32_t BASE_CHANNEL_ID = 0;
-    // model input width
-    const uint32_t MODEL_WIDTH = 256;
-    // model input height
-    const uint32_t MODEL_HEIGHT = 224;
-    // sampling interval
-    const uint32_t SAMPLING_INTERVAL = 24;
-    // maximum sampling interval
-    const uint32_t MAX_SAMPLING_INTERVAL = 100;
-    // decoding waiting time
-    const uint32_t DECODE_FRAME_WAIT_TIME = 10;
-    // maximum decoding queue length
-    const uint32_t DECODE_FRAME_QUEUE_LENGTH = 100;
-}
-
-static void SigHandler(int signal)
-{
-    if (signal == SIGINT) {
-        VideoGestureReasoner::g_forceStop = true;
-        LogInfo << "Force quit VideoGestureReasoner.";
-    }
-}
-static APP_ERROR Process(std::vector<std::string> &rtspList)
-{
-    auto videoGestureReasoner = std::make_shared<VideoGestureReasoner>();
-    ReasonerConfig reasonerConfig;
-    reasonerConfig.deviceId = DEVICE_ID;
-    reasonerConfig.baseVideoChannelId = BASE_CHANNEL_ID;
-    reasonerConfig.rtspList = rtspList;
-    reasonerConfig.resnetModelPath = "${gesture_yuv.om模型路径}";
-    reasonerConfig.resnetLabelPath = "${resnet18.names路径}";
-    reasonerConfig.resnetModelWidth = MODEL_WIDTH;
-    reasonerConfig.resnetModelHeight = MODEL_HEIGHT;
-    reasonerConfig.maxDecodeFrameQueueLength = DECODE_FRAME_QUEUE_LENGTH;
-    reasonerConfig.popDecodeFrameWaitTime = DECODE_FRAME_WAIT_TIME;
-    reasonerConfig.samplingInterval = SAMPLING_INTERVAL;
-    reasonerConfig.maxSamplingInterval = MAX_SAMPLING_INTERVAL;
-
-    // init
-    APP_ERROR ret = videoGestureReasoner->Init(reasonerConfig);
-    if (ret != APP_ERR_OK) {
-        LogError << "Init multi channel video infer failed.";
-        return ret;
-    }
-
-    // run
-    videoGestureReasoner->Process();
-
-    // destroy reasoner
-    ret = videoGestureReasoner->DeInit();
-    if (ret != APP_ERR_OK) {
-        LogError << "Deinit multi channel video infer failed.";
-        return ret;
-    }
-
-    // destroy devices
-    ret = MxBase::DeviceManager::GetInstance()->DestroyDevices();
-    if (ret != APP_ERR_OK) {
-        LogError << "DestroyDevices failed";
-        return ret;
-    }
-    return APP_ERR_OK;
-}
-
-static void LoadVideoSource(int argc, const std::vector<std::string> &argv, std::vector<std::string> &rtspList)
-{
-    if (argc <= 1) {
-        LogWarn
-                << "Please enter at least one video stream address, such as './videoGestureRecognition xxx/xxx/xx.264'.";
-        LogWarn << "Not config rtsp video stream address, use code setting.";
-
-        rtspList.emplace_back("#{rtsp流地址}");
-    } else {
-        for (int i = 1; i < argc; i++) {
-            LogInfo << "rtsp video stream " << i << " " << argv[i];
-            rtspList.emplace_back(argv[i]);
-        }
-    }
-}
-
-int main(int argc, char *argv[])
-{
-    // rtsp video string
-    std::vector<std::string> rtspList = {};
-
-    // load arguments
-    std::string rtspPrefix = "rtsp";
-    for (int i = 0; i < argc; i++) {
-        if (strcmp(argv[i], rtspPrefix.c_str()) == 0) {
-            auto rtspIndex = strtok(argv[i], "=");
-            auto rtspStream = strtok(NULL, "=");
-
-            LogInfo << rtspIndex << " = " << rtspStream;
-            rtspList.emplace_back(rtspStream);
-        }
-    }
-    std::vector<std::string> arguments = {};
-    for (int i = 0; i < argc; i++) {
-        arguments.emplace_back(argv[i]);
-    }
-    LoadVideoSource(argc, arguments, rtspList);
-
-    /// === resource init === ///
-    // init devices
-    APP_ERROR ret = MxBase::DeviceManager::GetInstance()->InitDevices();
-    if (ret != APP_ERR_OK) {
-        LogError << "InitDevices failed";
-        return ret;
-    }
-
-    // set devices
-    MxBase::DeviceContext device;
-    device.devId = DEVICE_ID;
-    ret = MxBase::DeviceManager::GetInstance()->SetDevice(device);
-    if (ret != APP_ERR_OK) {
-        LogError << "SetDevice failed";
-        return ret;
-    }
-
-    if (signal(SIGINT, SigHandler) == SIG_ERR) {
-        LogError << "can not catch SIGINT";
-        return APP_ERR_COMM_FAILURE;
-    }
-
-    // inference start
-    ret = Process(rtspList);
-    if (ret != APP_ERR_OK) {
-        LogError << "inference start failed";
-        return ret;
-    }
-    return 0;
+/*
+ * Copyright(C) 2021. Huawei Technologies Co.,Ltd. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "MxBase/ErrorCode/ErrorCode.h"
+#include "MxBase/Log/Log.h"
+#include "MxBase/DeviceManager/DeviceManager.h"
+#include "VideoGestureReasoner/VideoGestureReasoner.h"
+#include <csignal>
+
+namespace {
+    // device id
+    const uint32_t DEVICE_ID = 0;
+    // channel id
+    const uint32_t BASE_CHANNEL_ID = 0;
+    // model input width
+    const uint32_t MODEL_WIDTH = 256;
+    // model input height
+    const uint32_t MODEL_HEIGHT = 224;
+    // sampling interval
+    const uint32_t SAMPLING_INTERVAL = 24;
+    // maximum sampling interval
+    const uint32_t MAX_SAMPLING_INTERVAL = 100;
+    // decoding waiting time
+    const uint32_t DECODE_FRAME_WAIT_TIME = 10;
+    // maximum decoding queue length
+    const uint32_t DECODE_FRAME_QUEUE_LENGTH = 100;
+}
+
+static void SigHandler(int signal)
+{
+    if (signal == SIGINT) {
+        VideoGestureReasoner::g_forceStop = true;
+        LogInfo << "Force quit VideoGestureReasoner.";
+    }
+}
+static APP_ERROR Process(std::vector<std::string> &rtspList)
+{
+    auto videoGestureReasoner = std::make_shared<VideoGestureReasoner>();
+    ReasonerConfig reasonerConfig;
+    reasonerConfig.deviceId = DEVICE_ID;
+    reasonerConfig.baseVideoChannelId = BASE_CHANNEL_ID;
+    reasonerConfig.rtspList = rtspList;
+    reasonerConfig.resnetModelPath = "${gesture_yuv.om模型路径}";
+    reasonerConfig.resnetLabelPath = "${resnet18.names路径}";
+    reasonerConfig.resnetModelWidth = MODEL_WIDTH;
+    reasonerConfig.resnetModelHeight = MODEL_HEIGHT;
+    reasonerConfig.maxDecodeFrameQueueLength = DECODE_FRAME_QUEUE_LENGTH;
+    reasonerConfig.popDecodeFrameWaitTime = DECODE_FRAME_WAIT_TIME;
+    reasonerConfig.samplingInterval = SAMPLING_INTERVAL;
+    reasonerConfig.maxSamplingInterval = MAX_SAMPLING_INTERVAL;
+
+    // init
+    APP_ERROR ret = videoGestureReasoner->Init(reasonerConfig);
+    if (ret != APP_ERR_OK) {
+        LogError << "Init multi channel video infer failed.";
+        return ret;
+    }
+
+    // run
+    videoGestureReasoner->Process();
+
+    // destroy reasoner
+    ret = videoGestureReasoner->DeInit();
+    if (ret != APP_ERR_OK) {
+        LogError << "Deinit multi channel video infer failed.";
+        return ret;
+    }
+
+    // destroy devices
+    ret = MxBase::DeviceManager::GetInstance()->DestroyDevices();
+    if (ret != APP_ERR_OK) {
+        LogError << "DestroyDevices failed";
+        return ret;
+    }
+    return APP_ERR_OK;
+}
+
+static void LoadVideoSource(int argc, const std::vector<std::string> &argv, std::vector<std::string> &rtspList)
+{
+    if (argc <= 1) {
+        LogWarn
+                << "Please enter at least one video stream address, such as './videoGestureRecognition xxx/xxx/xx.264'.";
+        LogWarn << "Not config rtsp video stream address, use code setting.";
+
+        rtspList.emplace_back("#{rtsp流地址}");
+    } else {
+        for (int i = 1; i < argc; i++) {
+            LogInfo << "rtsp video stream " << i << " " << argv[i];
+            rtspList.emplace_back(argv[i]);
+        }
+    }
+}
+
+int main(int argc, char *argv[])
+{
+    // rtsp video string
+    std::vector<std::string> rtspList = {};
+
+    // load arguments
+    std::string rtspPrefix = "rtsp";
+    for (int i = 0; i < argc; i++) {
+        if (strcmp(argv[i], rtspPrefix.c_str()) == 0) {
+            auto rtspIndex = strtok(argv[i], "=");
+            auto rtspStream = strtok(NULL, "=");
+
+            LogInfo << rtspIndex << " = " << rtspStream;
+            rtspList.emplace_back(rtspStream);
+        }
+    }
+    std::vector<std::string> arguments = {};
+    for (int i = 0; i < argc; i++) {
+        arguments.emplace_back(argv[i]);
+    }
+    LoadVideoSource(argc, arguments, rtspList);
+
+    /// === resource init === ///
+    // init devices
+    APP_ERROR ret = MxBase::DeviceManager::GetInstance()->InitDevices();
+    if (ret != APP_ERR_OK) {
+        LogError << "InitDevices failed";
+        return ret;
+    }
+
+    // set devices
+    MxBase::DeviceContext device;
+    device.devId = DEVICE_ID;
+    ret = MxBase::DeviceManager::GetInstance()->SetDevice(device);
+    if (ret != APP_ERR_OK) {
+        LogError << "SetDevice failed";
+        return ret;
+    }
+
+    if (signal(SIGINT, SigHandler) == SIG_ERR) {
+        LogError << "can not catch SIGINT";
+        return APP_ERR_COMM_FAILURE;
+    }
+
+    // inference start
+    ret = Process(rtspList);
+    if (ret != APP_ERR_OK) {
+        LogError << "inference start failed";
+        return ret;
+    }
+    return 0;
 }
\ No newline at end of file
diff --git a/contrib/ai_paint/model/.keep b/mxVision/mxVision-referenceapps/VideoGestureRecognition/model/.keep
similarity index 100%
rename from contrib/ai_paint/model/.keep
rename to mxVision/mxVision-referenceapps/VideoGestureRecognition/model/.keep
diff --git a/contrib/VideoGestureRecognition/model/resnet18.cfg b/mxVision/mxVision-referenceapps/VideoGestureRecognition/model/resnet18.cfg
similarity index 100%
rename from contrib/VideoGestureRecognition/model/resnet18.cfg
rename to mxVision/mxVision-referenceapps/VideoGestureRecognition/model/resnet18.cfg
diff --git a/contrib/VideoGestureRecognition/model/resnet18.names b/mxVision/mxVision-referenceapps/VideoGestureRecognition/model/resnet18.names
similarity index 84%
rename from contrib/VideoGestureRecognition/model/resnet18.names
rename to mxVision/mxVision-referenceapps/VideoGestureRecognition/model/resnet18.names
index 9395f7008ebad7694b1646253c896936ca1506ac..fec04289464353f363c3e64b5d487c51bd5df46d 100644
--- a/contrib/VideoGestureRecognition/model/resnet18.names
+++ b/mxVision/mxVision-referenceapps/VideoGestureRecognition/model/resnet18.names
@@ -1,21 +1,21 @@
-0
-1
-2
-3
-4
-5
-6
-7
-8
-9
-left
-ok
-right
-rock
-finger heart
-praise
-prayer
-stop
-Give the middle finger
-bow
+0
+1
+2
+3
+4
+5
+6
+7
+8
+9
+left
+ok
+right
+rock
+finger heart
+praise
+prayer
+stop
+Give the middle finger
+bow
 No gesture
\ No newline at end of file
diff --git a/contrib/VideoGestureRecognition/run.sh b/mxVision/mxVision-referenceapps/VideoGestureRecognition/run.sh
similarity index 100%
rename from contrib/VideoGestureRecognition/run.sh
rename to mxVision/mxVision-referenceapps/VideoGestureRecognition/run.sh
diff --git a/contrib/YOLOX/README.md b/mxVision/mxVision-referenceapps/YOLOX/README.md
similarity index 100%
rename from contrib/YOLOX/README.md
rename to mxVision/mxVision-referenceapps/YOLOX/README.md
diff --git a/contrib/YOLOX/build.sh b/mxVision/mxVision-referenceapps/YOLOX/build.sh
similarity index 100%
rename from contrib/YOLOX/build.sh
rename to mxVision/mxVision-referenceapps/YOLOX/build.sh
diff --git a/contrib/YOLOX/images/MindXSDKValueError.png b/mxVision/mxVision-referenceapps/YOLOX/images/MindXSDKValueError.png
similarity index 100%
rename from contrib/YOLOX/images/MindXSDKValueError.png
rename to mxVision/mxVision-referenceapps/YOLOX/images/MindXSDKValueError.png
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rename to mxVision/mxVision-referenceapps/YOLOX/images/permissionerror.png
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rename from mxVision/YOLOv7Detection/plugin/Yolov7PostProcess.h
rename to mxVision/mxVision-referenceapps/YOLOv7Detection/plugin/Yolov7PostProcess.h
diff --git a/mxVision/YOLOv7Detection/run.sh b/mxVision/mxVision-referenceapps/YOLOv7Detection/run.sh
similarity index 100%
rename from mxVision/YOLOv7Detection/run.sh
rename to mxVision/mxVision-referenceapps/YOLOv7Detection/run.sh
diff --git a/mxVision/YoloV3Infer/CMakeLists.txt b/mxVision/mxVision-referenceapps/YoloV3Infer/CMakeLists.txt
similarity index 100%
rename from mxVision/YoloV3Infer/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/YoloV3Infer/CMakeLists.txt
diff --git a/mxVision/YoloV3Infer/README.md b/mxVision/mxVision-referenceapps/YoloV3Infer/README.md
similarity index 100%
rename from mxVision/YoloV3Infer/README.md
rename to mxVision/mxVision-referenceapps/YoloV3Infer/README.md
diff --git a/mxVision/YoloV3Infer/main.cpp b/mxVision/mxVision-referenceapps/YoloV3Infer/main.cpp
similarity index 100%
rename from mxVision/YoloV3Infer/main.cpp
rename to mxVision/mxVision-referenceapps/YoloV3Infer/main.cpp
diff --git a/mxVision/YoloV3Infer/model/aipp_yolov3_416_416.aippconfig b/mxVision/mxVision-referenceapps/YoloV3Infer/model/aipp_yolov3_416_416.aippconfig
similarity index 100%
rename from mxVision/YoloV3Infer/model/aipp_yolov3_416_416.aippconfig
rename to mxVision/mxVision-referenceapps/YoloV3Infer/model/aipp_yolov3_416_416.aippconfig
diff --git a/mxVision/YoloV3Infer/model/yolov3.names b/mxVision/mxVision-referenceapps/YoloV3Infer/model/yolov3.names
similarity index 100%
rename from mxVision/YoloV3Infer/model/yolov3.names
rename to mxVision/mxVision-referenceapps/YoloV3Infer/model/yolov3.names
diff --git a/mxVision/YoloV3Infer/model/yolov3_tf_bs1_fp16.cfg b/mxVision/mxVision-referenceapps/YoloV3Infer/model/yolov3_tf_bs1_fp16.cfg
similarity index 100%
rename from mxVision/YoloV3Infer/model/yolov3_tf_bs1_fp16.cfg
rename to mxVision/mxVision-referenceapps/YoloV3Infer/model/yolov3_tf_bs1_fp16.cfg
diff --git a/mxVision/YoloV3Infer/run.sh b/mxVision/mxVision-referenceapps/YoloV3Infer/run.sh
similarity index 100%
rename from mxVision/YoloV3Infer/run.sh
rename to mxVision/mxVision-referenceapps/YoloV3Infer/run.sh
diff --git a/contrib/ai_paint/README.md b/mxVision/mxVision-referenceapps/ai_paint/README.md
similarity index 100%
rename from contrib/ai_paint/README.md
rename to mxVision/mxVision-referenceapps/ai_paint/README.md
diff --git a/contrib/human_segmentation/.keep b/mxVision/mxVision-referenceapps/ai_paint/model/.keep
similarity index 100%
rename from contrib/human_segmentation/.keep
rename to mxVision/mxVision-referenceapps/ai_paint/model/.keep
diff --git a/contrib/ai_paint/pipeline/ai_paint.pipeline b/mxVision/mxVision-referenceapps/ai_paint/pipeline/ai_paint.pipeline
similarity index 100%
rename from contrib/ai_paint/pipeline/ai_paint.pipeline
rename to mxVision/mxVision-referenceapps/ai_paint/pipeline/ai_paint.pipeline
diff --git a/contrib/ai_paint/python/main.py b/mxVision/mxVision-referenceapps/ai_paint/python/main.py
similarity index 100%
rename from contrib/ai_paint/python/main.py
rename to mxVision/mxVision-referenceapps/ai_paint/python/main.py
diff --git a/contrib/ai_paint/python/net_config.ini b/mxVision/mxVision-referenceapps/ai_paint/python/net_config.ini
similarity index 100%
rename from contrib/ai_paint/python/net_config.ini
rename to mxVision/mxVision-referenceapps/ai_paint/python/net_config.ini
diff --git a/contrib/biggan/ACCURACY.png b/mxVision/mxVision-referenceapps/biggan/ACCURACY.png
similarity index 100%
rename from contrib/biggan/ACCURACY.png
rename to mxVision/mxVision-referenceapps/biggan/ACCURACY.png
diff --git a/contrib/biggan/RESULT.jpg b/mxVision/mxVision-referenceapps/biggan/RESULT.jpg
similarity index 100%
rename from contrib/biggan/RESULT.jpg
rename to mxVision/mxVision-referenceapps/biggan/RESULT.jpg
diff --git a/contrib/biggan/Readme.md b/mxVision/mxVision-referenceapps/biggan/Readme.md
similarity index 100%
rename from contrib/biggan/Readme.md
rename to mxVision/mxVision-referenceapps/biggan/Readme.md
diff --git a/contrib/biggan/SDK.jpg b/mxVision/mxVision-referenceapps/biggan/SDK.jpg
similarity index 100%
rename from contrib/biggan/SDK.jpg
rename to mxVision/mxVision-referenceapps/biggan/SDK.jpg
diff --git a/contrib/biggan/python/biggan.pipeline b/mxVision/mxVision-referenceapps/biggan/python/biggan.pipeline
similarity index 100%
rename from contrib/biggan/python/biggan.pipeline
rename to mxVision/mxVision-referenceapps/biggan/python/biggan.pipeline
diff --git a/contrib/biggan/python/main.py b/mxVision/mxVision-referenceapps/biggan/python/main.py
similarity index 100%
rename from contrib/biggan/python/main.py
rename to mxVision/mxVision-referenceapps/biggan/python/main.py
diff --git a/contrib/facemaskdetection/README.md b/mxVision/mxVision-referenceapps/facemaskdetection/README.md
similarity index 97%
rename from contrib/facemaskdetection/README.md
rename to mxVision/mxVision-referenceapps/facemaskdetection/README.md
index cbfd8ae4797f56097de6b0cd448a68bf7044a68f..895c551d4165df8536d822faae11c0a5f60d7a35 100644
--- a/contrib/facemaskdetection/README.md
+++ b/mxVision/mxVision-referenceapps/facemaskdetection/README.md
@@ -1,104 +1,104 @@
-# 口罩识别参考设计
-
-## 1 介绍
-
-### 1.1 简介
-
-识别图片中的人是否佩戴口罩。图片数据经过 抽帧、解码后，送给口罩检测模型推理。
-
-### 1.2 支持的产品
-
-本项目支持昇腾Atlas 300I pro、 Atlas 300V pro
-
-### 1.3 支持的版本
-本样例配套的MxVision版本、CANN版本、Driver/Firmware版本如下所示：
-
-| MxVision版本  | CANN版本  | Driver/Firmware版本  |
-| --------- | ------------------ | -------------- |
-| 6.0.RC3   | 8.0.RC3   |  24.1.RC3  |
-
-### 1.4 三方依赖
-
-第三方依赖软件和版本如下表。请确认环境已安装pip3后，使用pip3 install 安装以下依赖。
-
-|软件名称    | 版本        |
-|-----------|-----------|
-| numpy     | 1.24.0    |
-| opencv-python   | 4.9.0.80 |
-
-### 1.5 代码目录结构说明
-
-本sample工程名称为口罩识别参考设计，工程目录如下图所示：
-
-```
-.
-|—— image
-│   └── image1.png		  # 技术实现流程图
-├── README.md                     # 模型转换配置文件
-├── anchor_decode.py              # 计算bbox(参考第4章运行获取源码)
-├── anchor_generator.py           # 生成先验框（参考第4章运行获取源码）
-├── image.py			  # 图片识别主程序
-├── main.pipeline		  # 口罩识别推理流程pipline
-├── models			  # 推理模型文件夹
-│   └── face_mask.aippconfig	  # 转模型前处理配置文件
-└── nms.py			  # nms计算程序
-```
-
-
-
-### 1.5 技术实现流程图
-
-
-
-<img src="./image/image1.png" alt="image2" width="200" height="500" />
-
-## 2 设置环境变量
-
-```bash
-#设置CANN环境变量，ascend-toolkit-path为cann安装路径
-. ${ascend-toolkit-path}/set_env.sh
-
-#设置MindX SDK 环境变量，SDK-path为mxVision SDK 安装路径
-. ${SDK-path}/set_env.sh
-```
-
-## 3 准备模型
-
-**步骤1:** 获取face_mask_detection的原始模型(face_mask_detection.pb)
-
-[GitHub](https://github.com/AIZOOTech/FaceMaskDetection/blob/master/models/face_mask_detection.pb)
-
-**步骤2:** 将获取到的模型pb文件存放至项目所在目录下的models目录
-
-
-**步骤3:** 进入models目录执行om模型转换
-
-使用ATC将.pb文件转成为.om文件
-```
-cd models/
-atc --model=./face_mask_detection.pb --framework=3 --output=./aipp --output_type=FP32 --soc_version=Ascend310P3 --input_shape="data_1:1,260,260,3" --input_format=NHWC --insert_op_conf=./face_mask.aippconfig
-```
-其中--insert_op_conf参数为aipp预处理算子配置文件路径。该配置文件face_mask.aippconfig在输入图像进入模型前进行预处理。该配置文件保存在源码models目录下。
-
-执行完模型转换后，若提示如下信息说明模型转换成功，可以在该路径下找到名为aipp.om模型文件。
-
-```
-ATC run success, welcome to the next use.
-``` 
-## 4 运行
-
-**步骤1:** 下载后处理代码
-
-在链接[GitHub](https://github.com/AIZOOTech/FaceMaskDetection/tree/master/utils)下载开源代码中utils文件夹内的3个py文件(anchor_decode.py,anchor_generator.py, nms.py)并放置于项目根目录即可，最终的目录结构参见 [1.5 代码目录结构与说明]
-
-**步骤2:** 根据使用的设备id，修改源码根目录下**main.pipeline**中所有的deviceId：
-```
-"deviceId": "0"                # 根据实际使用的设备id修改
-```
-**步骤3:** 准备测试图片，放在源码根目录下，运行推理：
-```
-python3.9 image.py mask.jpg
-```
-**步骤4:** 查看结果
-
+# 口罩识别参考设计
+
+## 1 介绍
+
+### 1.1 简介
+
+识别图片中的人是否佩戴口罩。图片数据经过 抽帧、解码后，送给口罩检测模型推理。
+
+### 1.2 支持的产品
+
+本项目支持昇腾Atlas 300I pro、 Atlas 300V pro
+
+### 1.3 支持的版本
+本样例配套的MxVision版本、CANN版本、Driver/Firmware版本如下所示：
+
+| MxVision版本  | CANN版本  | Driver/Firmware版本  |
+| --------- | ------------------ | -------------- |
+| 6.0.RC3   | 8.0.RC3   |  24.1.RC3  |
+
+### 1.4 三方依赖
+
+第三方依赖软件和版本如下表。请确认环境已安装pip3后，使用pip3 install 安装以下依赖。
+
+|软件名称    | 版本        |
+|-----------|-----------|
+| numpy     | 1.24.0    |
+| opencv-python   | 4.9.0.80 |
+
+### 1.5 代码目录结构说明
+
+本sample工程名称为口罩识别参考设计，工程目录如下图所示：
+
+```
+.
+|—— image
+│   └── image1.png		  # 技术实现流程图
+├── README.md                     # 模型转换配置文件
+├── anchor_decode.py              # 计算bbox(参考第4章运行获取源码)
+├── anchor_generator.py           # 生成先验框（参考第4章运行获取源码）
+├── image.py			  # 图片识别主程序
+├── main.pipeline		  # 口罩识别推理流程pipline
+├── models			  # 推理模型文件夹
+│   └── face_mask.aippconfig	  # 转模型前处理配置文件
+└── nms.py			  # nms计算程序
+```
+
+
+
+### 1.5 技术实现流程图
+
+
+
+<img src="./image/image1.png" alt="image2" width="200" height="500" />
+
+## 2 设置环境变量
+
+```bash
+#设置CANN环境变量，ascend-toolkit-path为cann安装路径
+. ${ascend-toolkit-path}/set_env.sh
+
+#设置MindX SDK 环境变量，SDK-path为mxVision SDK 安装路径
+. ${SDK-path}/set_env.sh
+```
+
+## 3 准备模型
+
+**步骤1:** 获取face_mask_detection的原始模型(face_mask_detection.pb)
+
+[GitHub](https://github.com/AIZOOTech/FaceMaskDetection/blob/master/models/face_mask_detection.pb)
+
+**步骤2:** 将获取到的模型pb文件存放至项目所在目录下的models目录
+
+
+**步骤3:** 进入models目录执行om模型转换
+
+使用ATC将.pb文件转成为.om文件
+```
+cd models/
+atc --model=./face_mask_detection.pb --framework=3 --output=./aipp --output_type=FP32 --soc_version=Ascend310P3 --input_shape="data_1:1,260,260,3" --input_format=NHWC --insert_op_conf=./face_mask.aippconfig
+```
+其中--insert_op_conf参数为aipp预处理算子配置文件路径。该配置文件face_mask.aippconfig在输入图像进入模型前进行预处理。该配置文件保存在源码models目录下。
+
+执行完模型转换后，若提示如下信息说明模型转换成功，可以在该路径下找到名为aipp.om模型文件。
+
+```
+ATC run success, welcome to the next use.
+``` 
+## 4 运行
+
+**步骤1:** 下载后处理代码
+
+在链接[GitHub](https://github.com/AIZOOTech/FaceMaskDetection/tree/master/utils)下载开源代码中utils文件夹内的3个py文件(anchor_decode.py,anchor_generator.py, nms.py)并放置于项目根目录即可，最终的目录结构参见 [1.5 代码目录结构与说明]
+
+**步骤2:** 根据使用的设备id，修改源码根目录下**main.pipeline**中所有的deviceId：
+```
+"deviceId": "0"                # 根据实际使用的设备id修改
+```
+**步骤3:** 准备测试图片，放在源码根目录下，运行推理：
+```
+python3.9 image.py mask.jpg
+```
+**步骤4:** 查看结果
+
 输出结果对原图像的目标以及口罩进行识别画框并将结果保存至根目录下**my_result.jpg**
\ No newline at end of file
diff --git a/contrib/facemaskdetection/image.py b/mxVision/mxVision-referenceapps/facemaskdetection/image.py
similarity index 100%
rename from contrib/facemaskdetection/image.py
rename to mxVision/mxVision-referenceapps/facemaskdetection/image.py
diff --git a/contrib/facemaskdetection/image/image1.png b/mxVision/mxVision-referenceapps/facemaskdetection/image/image1.png
similarity index 100%
rename from contrib/facemaskdetection/image/image1.png
rename to mxVision/mxVision-referenceapps/facemaskdetection/image/image1.png
diff --git a/contrib/facemaskdetection/main.pipeline b/mxVision/mxVision-referenceapps/facemaskdetection/main.pipeline
similarity index 100%
rename from contrib/facemaskdetection/main.pipeline
rename to mxVision/mxVision-referenceapps/facemaskdetection/main.pipeline
diff --git a/contrib/facemaskdetection/models/face_mask.aippconfig b/mxVision/mxVision-referenceapps/facemaskdetection/models/face_mask.aippconfig
similarity index 100%
rename from contrib/facemaskdetection/models/face_mask.aippconfig
rename to mxVision/mxVision-referenceapps/facemaskdetection/models/face_mask.aippconfig
diff --git a/contrib/faceswap/Img4md/img.png b/mxVision/mxVision-referenceapps/faceswap/Img4md/img.png
similarity index 100%
rename from contrib/faceswap/Img4md/img.png
rename to mxVision/mxVision-referenceapps/faceswap/Img4md/img.png
diff --git a/contrib/faceswap/README.md b/mxVision/mxVision-referenceapps/faceswap/README.md
similarity index 100%
rename from contrib/faceswap/README.md
rename to mxVision/mxVision-referenceapps/faceswap/README.md
diff --git a/contrib/faceswap/faceswap_main.py b/mxVision/mxVision-referenceapps/faceswap/faceswap_main.py
similarity index 100%
rename from contrib/faceswap/faceswap_main.py
rename to mxVision/mxVision-referenceapps/faceswap/faceswap_main.py
diff --git a/contrib/faceswap/faceswap_post.py b/mxVision/mxVision-referenceapps/faceswap/faceswap_post.py
similarity index 100%
rename from contrib/faceswap/faceswap_post.py
rename to mxVision/mxVision-referenceapps/faceswap/faceswap_post.py
diff --git a/contrib/faceswap/model/V3ONNX.cfg b/mxVision/mxVision-referenceapps/faceswap/model/V3ONNX.cfg
similarity index 100%
rename from contrib/faceswap/model/V3ONNX.cfg
rename to mxVision/mxVision-referenceapps/faceswap/model/V3ONNX.cfg
diff --git a/contrib/FatigueDrivingRecognition/model/coco.names b/mxVision/mxVision-referenceapps/faceswap/model/coco.names
similarity index 97%
rename from contrib/FatigueDrivingRecognition/model/coco.names
rename to mxVision/mxVision-referenceapps/faceswap/model/coco.names
index 6e80a9a1e7954cd1ae38f063fb3d1aa4f77249db..5c3b17966bb24c8e33ca187bac7565e4a68ea897 100644
--- a/contrib/FatigueDrivingRecognition/model/coco.names
+++ b/mxVision/mxVision-referenceapps/faceswap/model/coco.names
@@ -1,5 +1,5 @@
-# This file is originally from https://github.com/pjreddie/darknet/blob/master/data/coco.names
-person
-non motor-vehicle
-motor-vehicle
+# This file is originally from https://github.com/pjreddie/darknet/blob/master/data/coco.names
+person
+non motor-vehicle
+motor-vehicle
 face
\ No newline at end of file
diff --git a/contrib/Individual/models/yolov4.cfg b/mxVision/mxVision-referenceapps/faceswap/model/yolov4.cfg
similarity index 94%
rename from contrib/Individual/models/yolov4.cfg
rename to mxVision/mxVision-referenceapps/faceswap/model/yolov4.cfg
index 231e4566b70e3484203db45960e11a31d68c21a9..5d4f054021f07e25314172a0a6ed53d744c5abf6 100644
--- a/contrib/Individual/models/yolov4.cfg
+++ b/mxVision/mxVision-referenceapps/faceswap/model/yolov4.cfg
@@ -1,10 +1,10 @@
-CLASS_NUM=4
-BIASES_NUM=12
-BIASES=23,27,37,58,81,82,81,82,135,169,344,319
-SCORE_THRESH=0.4
-OBJECTNESS_THRESH=0.8
-IOU_THRESH=0.5
-YOLO_TYPE=2
-ANCHOR_DIM=3
-MODEL_TYPE=0
-RESIZE_FLAG=0
+CLASS_NUM=4
+BIASES_NUM=12
+BIASES=23,27,37,58,81,82,81,82,135,169,344,319
+SCORE_THRESH=0.4
+OBJECTNESS_THRESH=0.8
+IOU_THRESH=0.5
+YOLO_TYPE=2
+ANCHOR_DIM=3
+MODEL_TYPE=0
+RESIZE_FLAG=0
diff --git a/contrib/faceswap/pipeline/faceswap.pipeline b/mxVision/mxVision-referenceapps/faceswap/pipeline/faceswap.pipeline
similarity index 100%
rename from contrib/faceswap/pipeline/faceswap.pipeline
rename to mxVision/mxVision-referenceapps/faceswap/pipeline/faceswap.pipeline
diff --git a/contrib/human_segmentation/.gitignore b/mxVision/mxVision-referenceapps/human_segmentation/.gitignore
similarity index 100%
rename from contrib/human_segmentation/.gitignore
rename to mxVision/mxVision-referenceapps/human_segmentation/.gitignore
diff --git a/contrib/human_segmentation/build/.keep b/mxVision/mxVision-referenceapps/human_segmentation/.keep
similarity index 100%
rename from contrib/human_segmentation/build/.keep
rename to mxVision/mxVision-referenceapps/human_segmentation/.keep
diff --git a/contrib/human_segmentation/CMakeLists.txt b/mxVision/mxVision-referenceapps/human_segmentation/CMakeLists.txt
similarity index 100%
rename from contrib/human_segmentation/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/human_segmentation/CMakeLists.txt
diff --git a/contrib/human_segmentation/README.md b/mxVision/mxVision-referenceapps/human_segmentation/README.md
similarity index 100%
rename from contrib/human_segmentation/README.md
rename to mxVision/mxVision-referenceapps/human_segmentation/README.md
diff --git a/contrib/human_segmentation/build.sh b/mxVision/mxVision-referenceapps/human_segmentation/build.sh
similarity index 100%
rename from contrib/human_segmentation/build.sh
rename to mxVision/mxVision-referenceapps/human_segmentation/build.sh
diff --git a/contrib/human_segmentation/data/.keep b/mxVision/mxVision-referenceapps/human_segmentation/build/.keep
similarity index 100%
rename from contrib/human_segmentation/data/.keep
rename to mxVision/mxVision-referenceapps/human_segmentation/build/.keep
diff --git a/contrib/human_segmentation/model/.keep b/mxVision/mxVision-referenceapps/human_segmentation/data/.keep
similarity index 100%
rename from contrib/human_segmentation/model/.keep
rename to mxVision/mxVision-referenceapps/human_segmentation/data/.keep
diff --git a/contrib/human_segmentation/main.cpp b/mxVision/mxVision-referenceapps/human_segmentation/main.cpp
similarity index 100%
rename from contrib/human_segmentation/main.cpp
rename to mxVision/mxVision-referenceapps/human_segmentation/main.cpp
diff --git a/contrib/human_segmentation/result/.keep b/mxVision/mxVision-referenceapps/human_segmentation/model/.keep
similarity index 100%
rename from contrib/human_segmentation/result/.keep
rename to mxVision/mxVision-referenceapps/human_segmentation/model/.keep
diff --git "a/docs/MindX SDK\345\270\270\350\247\201\351\227\256\351\242\230FAQ/img/.keep" b/mxVision/mxVision-referenceapps/human_segmentation/result/.keep
similarity index 100%
rename from "docs/MindX SDK\345\270\270\350\247\201\351\227\256\351\242\230FAQ/img/.keep"
rename to mxVision/mxVision-referenceapps/human_segmentation/result/.keep
diff --git a/contrib/human_segmentation/run.sh b/mxVision/mxVision-referenceapps/human_segmentation/run.sh
similarity index 100%
rename from contrib/human_segmentation/run.sh
rename to mxVision/mxVision-referenceapps/human_segmentation/run.sh
diff --git a/contrib/human_segmentation/test.pipeline b/mxVision/mxVision-referenceapps/human_segmentation/test.pipeline
similarity index 100%
rename from contrib/human_segmentation/test.pipeline
rename to mxVision/mxVision-referenceapps/human_segmentation/test.pipeline
diff --git a/contrib/msame/README.md b/mxVision/mxVision-referenceapps/msame/README.md
similarity index 96%
rename from contrib/msame/README.md
rename to mxVision/mxVision-referenceapps/msame/README.md
index 6698a4f564755cd251b42104d4bbee19bb19553c..1a31235821266ca4381a2af0b9165ebfa2228657 100644
--- a/contrib/msame/README.md
+++ b/mxVision/mxVision-referenceapps/msame/README.md
@@ -1,128 +1,128 @@
-# 模型推理工具
-
-## 1 介绍
-基于MindX SDK实现开发模型推理工具，用于测试om模型推理，本例为msame的python版本实现。   
-[msame-C++工具链接](https://gitee.com/ascend/tools/tree/master/msame)
-
-### 1.1 支持的产品   
-本项目以昇腾Atlas300I卡为主要的硬件平台。   
-
-### 1.2 支持的版本   
-| 软件名称  | 版本           |
-| --------- | -------------- |
-| python    | 3.9.2          |
-| MindX SDK | 3.0.0.alpha    |
-| CANN      | 6.0.1.alpha001 |
-
-### 1.3 适用场景   
-
-使用于单输入或多输入模型推理   
-
-
-### 1.4 代码目录结构与说明
-
-```
-.
-├── img
-│   ├── error1.jpg                            // msame-C++推理结果
-│   │── error2.jpg                            // 本例(msame-python)推理结果
-│   │── error3.jpg                            // 输入不一致报错截图
-│   │── process.jpg                           // 流程图
-├── set_env.sh                                // 需要设置的环境变量
-├── msame.py                                  // 模型推理工具代码
-├── README.md                                 // ReadMe
-```
-
-
-
-
-### 1.5 技术实现流程图
-
-![image-20220401173124980](./img/process.png)
-
-
-
-
-
-## 2 环境依赖
-
-软件依赖说明：
-
-| 依赖软件 | 版本   | 说明                   |
-| -------- | ------ | ---------------------- |
-| numpy    | 1.21.2 | 将数据保存为二进制文件 |
-
-在编译运行项目前，需要设置环境变量：
-
-```
-. /usr/local/Ascend/ascend-toolkit/set_env.sh #toolkit默认安装路径，根据实际安装路径修改
-. ${SDK_INSTALL_PATH}/mxVision/set_env.sh
-```
-
-## 3 依赖安装
-
-```
-pip install numpy == 1.21.2
-```
-
-## 4 准备工作
-
-注：多输入样例在输入时，多个输入用  ,  隔开。
-
-##  5 编译与运行
-示例步骤如下：   
-**步骤1** 设置环境变量
-
-**步骤2**  运行
-
-```
-python3.9 msame.py --model xxx --input xxx --output xxx  --loop xxx --outfmt xxx
-```
-在输出路径下成功输出预期的“.txt”或“.bin”则运行成功，否则报错。   
-参数说明：
-```
---input   
-功能说明：模型的输入路径 参数值：bin或npy文件路径与文件名 示例：--input dog.npy
---output   
-功能说明：模型的输出路径 参数值：bin或txt文件路径 示例：--output .
---model   
-功能说明：om模型的路径 参数值：模型路径与模型名称 示例：--model yolov3.om
---outfmt    
-功能说明：模型的输出格式 参数值：TXT 或 BIN 示例：--outfmt TXT
---loop   
-功能说明：执行推理的次数 默认为1 参数值：正整数 示例：--loop 2
---device   
-功能说明：执行代码的设备编号 参数值：自然数 示例：--device 1 
-```
-单输入模型：   
-以yolov3模型npy文件输入作为示例参考：
-
-```
-python3.9 msame.py  --model yolov3_tf_bs1_fp16.om --input dog.npy --output test --outfmt TXT
-```
-执行成功后，在test目录下生成yolov3_tf_bs1_fp16_0.txt，yolov3_tf_bs1_fp16_1.txt， yolov3_tf_bs1_fp16_2.txt   
-输出文件的个数与模型的输出有关。   
-
-多输入模型：   
-
-以pointcnn模型bin文件输入作为示例参考：    
-
-```
-python3.9 msame.py --model pointcnn_bs64.om --output test --outfmt BIN --input pointcnn.bin,pointcnn.bin
-```
-
-执行成功后，在test目录下生成pointcnn_bs64_0.bin     
-
-## 6 常见问题
-### 6.1 存储为txt格式时可能会出现第六位开始的误差，可以忽略此问题。  
- 执行msame-C++输出结果：   
-![image-20220401173124980](./img/error1.png)
- 执行本例（msame-python）输出结果：   
-![image-20220401173124980](./img/error2.png)
-### 6.2 模型需要的输入与提供的数据不一致   
-![image-20220401173124980](./img/error3.png)
-问题描述：   
-模型需要的输入shape与提供的数据shape不一致。   
-解决方案：   
-可在msame.py中自行输出m.input_shape查看模型需要的输入shape，m.input_dtype查看数据的shape。   
-自行编写脚本查看bin或npy文件的shape和dtype，与模型的shape和dtype对齐。
+# 模型推理工具
+
+## 1 介绍
+基于MindX SDK实现开发模型推理工具，用于测试om模型推理，本例为msame的python版本实现。   
+[msame-C++工具链接](https://gitee.com/ascend/tools/tree/master/msame)
+
+### 1.1 支持的产品   
+本项目以昇腾Atlas300I卡为主要的硬件平台。   
+
+### 1.2 支持的版本   
+| 软件名称  | 版本           |
+| --------- | -------------- |
+| python    | 3.9.2          |
+| MindX SDK | 3.0.0.alpha    |
+| CANN      | 6.0.1.alpha001 |
+
+### 1.3 适用场景   
+
+使用于单输入或多输入模型推理   
+
+
+### 1.4 代码目录结构与说明
+
+```
+.
+├── img
+│   ├── error1.jpg                            // msame-C++推理结果
+│   │── error2.jpg                            // 本例(msame-python)推理结果
+│   │── error3.jpg                            // 输入不一致报错截图
+│   │── process.jpg                           // 流程图
+├── set_env.sh                                // 需要设置的环境变量
+├── msame.py                                  // 模型推理工具代码
+├── README.md                                 // ReadMe
+```
+
+
+
+
+### 1.5 技术实现流程图
+
+![image-20220401173124980](./img/process.png)
+
+
+
+
+
+## 2 环境依赖
+
+软件依赖说明：
+
+| 依赖软件 | 版本   | 说明                   |
+| -------- | ------ | ---------------------- |
+| numpy    | 1.21.2 | 将数据保存为二进制文件 |
+
+在编译运行项目前，需要设置环境变量：
+
+```
+. /usr/local/Ascend/ascend-toolkit/set_env.sh #toolkit默认安装路径，根据实际安装路径修改
+. ${SDK_INSTALL_PATH}/mxVision/set_env.sh
+```
+
+## 3 依赖安装
+
+```
+pip install numpy == 1.21.2
+```
+
+## 4 准备工作
+
+注：多输入样例在输入时，多个输入用  ,  隔开。
+
+##  5 编译与运行
+示例步骤如下：   
+**步骤1** 设置环境变量
+
+**步骤2**  运行
+
+```
+python3.9 msame.py --model xxx --input xxx --output xxx  --loop xxx --outfmt xxx
+```
+在输出路径下成功输出预期的“.txt”或“.bin”则运行成功，否则报错。   
+参数说明：
+```
+--input   
+功能说明：模型的输入路径 参数值：bin或npy文件路径与文件名 示例：--input dog.npy
+--output   
+功能说明：模型的输出路径 参数值：bin或txt文件路径 示例：--output .
+--model   
+功能说明：om模型的路径 参数值：模型路径与模型名称 示例：--model yolov3.om
+--outfmt    
+功能说明：模型的输出格式 参数值：TXT 或 BIN 示例：--outfmt TXT
+--loop   
+功能说明：执行推理的次数 默认为1 参数值：正整数 示例：--loop 2
+--device   
+功能说明：执行代码的设备编号 参数值：自然数 示例：--device 1 
+```
+单输入模型：   
+以yolov3模型npy文件输入作为示例参考：
+
+```
+python3.9 msame.py  --model yolov3_tf_bs1_fp16.om --input dog.npy --output test --outfmt TXT
+```
+执行成功后，在test目录下生成yolov3_tf_bs1_fp16_0.txt，yolov3_tf_bs1_fp16_1.txt， yolov3_tf_bs1_fp16_2.txt   
+输出文件的个数与模型的输出有关。   
+
+多输入模型：   
+
+以pointcnn模型bin文件输入作为示例参考：    
+
+```
+python3.9 msame.py --model pointcnn_bs64.om --output test --outfmt BIN --input pointcnn.bin,pointcnn.bin
+```
+
+执行成功后，在test目录下生成pointcnn_bs64_0.bin     
+
+## 6 常见问题
+### 6.1 存储为txt格式时可能会出现第六位开始的误差，可以忽略此问题。  
+ 执行msame-C++输出结果：   
+![image-20220401173124980](./img/error1.png)
+ 执行本例（msame-python）输出结果：   
+![image-20220401173124980](./img/error2.png)
+### 6.2 模型需要的输入与提供的数据不一致   
+![image-20220401173124980](./img/error3.png)
+问题描述：   
+模型需要的输入shape与提供的数据shape不一致。   
+解决方案：   
+可在msame.py中自行输出m.input_shape查看模型需要的输入shape，m.input_dtype查看数据的shape。   
+自行编写脚本查看bin或npy文件的shape和dtype，与模型的shape和dtype对齐。
diff --git a/contrib/msame/img/error1.png b/mxVision/mxVision-referenceapps/msame/img/error1.png
similarity index 100%
rename from contrib/msame/img/error1.png
rename to mxVision/mxVision-referenceapps/msame/img/error1.png
diff --git a/contrib/msame/img/error2.png b/mxVision/mxVision-referenceapps/msame/img/error2.png
similarity index 100%
rename from contrib/msame/img/error2.png
rename to mxVision/mxVision-referenceapps/msame/img/error2.png
diff --git a/contrib/msame/img/error3.png b/mxVision/mxVision-referenceapps/msame/img/error3.png
similarity index 100%
rename from contrib/msame/img/error3.png
rename to mxVision/mxVision-referenceapps/msame/img/error3.png
diff --git a/contrib/msame/img/process.png b/mxVision/mxVision-referenceapps/msame/img/process.png
similarity index 100%
rename from contrib/msame/img/process.png
rename to mxVision/mxVision-referenceapps/msame/img/process.png
diff --git a/contrib/msame/msame.py b/mxVision/mxVision-referenceapps/msame/msame.py
similarity index 100%
rename from contrib/msame/msame.py
rename to mxVision/mxVision-referenceapps/msame/msame.py
diff --git a/contrib/mxBase_wheatDetection/CMakeLists.txt b/mxVision/mxVision-referenceapps/mxBase_wheatDetection/CMakeLists.txt
similarity index 100%
rename from contrib/mxBase_wheatDetection/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/mxBase_wheatDetection/CMakeLists.txt
diff --git a/contrib/mxBase_wheatDetection/README.md b/mxVision/mxVision-referenceapps/mxBase_wheatDetection/README.md
similarity index 100%
rename from contrib/mxBase_wheatDetection/README.md
rename to mxVision/mxVision-referenceapps/mxBase_wheatDetection/README.md
diff --git a/contrib/mxBase_wheatDetection/build.sh b/mxVision/mxVision-referenceapps/mxBase_wheatDetection/build.sh
similarity index 100%
rename from contrib/mxBase_wheatDetection/build.sh
rename to mxVision/mxVision-referenceapps/mxBase_wheatDetection/build.sh
diff --git a/contrib/mxBase_wheatDetection/image-2021092301.jpg b/mxVision/mxVision-referenceapps/mxBase_wheatDetection/image-2021092301.jpg
similarity index 100%
rename from contrib/mxBase_wheatDetection/image-2021092301.jpg
rename to mxVision/mxVision-referenceapps/mxBase_wheatDetection/image-2021092301.jpg
diff --git a/contrib/mxBase_wheatDetection/main.cpp b/mxVision/mxVision-referenceapps/mxBase_wheatDetection/main.cpp
similarity index 100%
rename from contrib/mxBase_wheatDetection/main.cpp
rename to mxVision/mxVision-referenceapps/mxBase_wheatDetection/main.cpp
diff --git a/contrib/mxBase_wheatDetection/model/aipp.aippconfig b/mxVision/mxVision-referenceapps/mxBase_wheatDetection/model/aipp.aippconfig
similarity index 100%
rename from contrib/mxBase_wheatDetection/model/aipp.aippconfig
rename to mxVision/mxVision-referenceapps/mxBase_wheatDetection/model/aipp.aippconfig
diff --git a/contrib/mxBase_wheatDetection/model/coco.names b/mxVision/mxVision-referenceapps/mxBase_wheatDetection/model/coco.names
similarity index 100%
rename from contrib/mxBase_wheatDetection/model/coco.names
rename to mxVision/mxVision-referenceapps/mxBase_wheatDetection/model/coco.names
diff --git a/contrib/mxBase_wheatDetection/yolov5Detection/Yolov5Detection.cpp b/mxVision/mxVision-referenceapps/mxBase_wheatDetection/yolov5Detection/Yolov5Detection.cpp
similarity index 100%
rename from contrib/mxBase_wheatDetection/yolov5Detection/Yolov5Detection.cpp
rename to mxVision/mxVision-referenceapps/mxBase_wheatDetection/yolov5Detection/Yolov5Detection.cpp
diff --git a/contrib/mxBase_wheatDetection/yolov5Detection/Yolov5Detection.h b/mxVision/mxVision-referenceapps/mxBase_wheatDetection/yolov5Detection/Yolov5Detection.h
similarity index 100%
rename from contrib/mxBase_wheatDetection/yolov5Detection/Yolov5Detection.h
rename to mxVision/mxVision-referenceapps/mxBase_wheatDetection/yolov5Detection/Yolov5Detection.h
diff --git a/contrib/mxBase_wheatDetection/yolov5PostProcess/Yolov5PostProcess.cpp b/mxVision/mxVision-referenceapps/mxBase_wheatDetection/yolov5PostProcess/Yolov5PostProcess.cpp
similarity index 100%
rename from contrib/mxBase_wheatDetection/yolov5PostProcess/Yolov5PostProcess.cpp
rename to mxVision/mxVision-referenceapps/mxBase_wheatDetection/yolov5PostProcess/Yolov5PostProcess.cpp
diff --git a/contrib/mxBase_wheatDetection/yolov5PostProcess/Yolov5PostProcess.h b/mxVision/mxVision-referenceapps/mxBase_wheatDetection/yolov5PostProcess/Yolov5PostProcess.h
similarity index 100%
rename from contrib/mxBase_wheatDetection/yolov5PostProcess/Yolov5PostProcess.h
rename to mxVision/mxVision-referenceapps/mxBase_wheatDetection/yolov5PostProcess/Yolov5PostProcess.h
diff --git a/contrib/yunet/README.md b/mxVision/mxVision-referenceapps/yunet/README.md
similarity index 97%
rename from contrib/yunet/README.md
rename to mxVision/mxVision-referenceapps/yunet/README.md
index 216cfe9678ddd3c87a408d7c0dab4ee1437a9cc1..4d01eb3d932682204f2b77b319b54d80e4247e97 100644
--- a/contrib/yunet/README.md
+++ b/mxVision/mxVision-referenceapps/yunet/README.md
@@ -1,283 +1,283 @@
-## yunet实时人脸检测
-
-## 1介绍
-
-yunet基于MindXSDK开发，在昇腾芯片上进行人脸检测，并实现可视化呈现。输入3路视频，对其进行推理，输出推理结果。
-
-### 1.1 支持的产品
-
-本产品以昇腾310（推理）卡为硬件平台。
-
-### 1.2 支持的版本
-
-CANN：7.0.0
-
-SDK：mxVision 5.0.0（可通过cat SDK目录下的 version.info 查看）
-
-### 1.3 软件方案介绍
-
-表1.1 系统方案各子系统功能描述：
-
-| 序号 | 子系统         | 功能描述                                                     |
-| ---- | -------------- | ------------------------------------------------------------ |
-| 1    | 视频输入流     | 接收外部调用接口的输入视频路径，对视频进行拉流，并将拉去的裸流存储到缓冲区（buffer）中，并发送到下游插件。 |
-| 2    | 视频解码       | 用于视频解码，当前只支持H264格式。                           |
-| 3    | 数据分发       | 对单个输入数据进行2次分发。                                  |
-| 4    | 数据缓存       | 输出时为后续处理过程创建一个线程，用于将输入数据与输出数据解耦，并创建缓存队列，存储尚未输入到下流插件的数据。 |
-| 5    | 图像处理       | 对解码后的YUV格式的图像进行放缩。                            |
-| 6    | 模型推理插件   | 目标检测。                                                   |
-| 7    | 模型后处理插件 | 对模型输出的张量进行后处理，得到物体类型数据。               |
-| 8    | 目标框转绘插件 | 物体类型转化为OSD实例                                        |
-| 9    | OSD可视化插件  | 实现对视频流的每一帧图像进行绘制。                           |
-| 10   | 视频编码插件   | 用于将OSD可视化插件输出的图片进行视频编码，输出视频。        |
-
-
-
-### 1.4 代码目录结构与说明
-
-本项目名为yunet实时人脸检测，项目目录如下所示：
-
-````
-├── build.sh
-├── config
-│   ├── face_yunet.cfg      # yunet配置文件
-│   └── Yunet.aippconfig    # 模型转换aipp配置文件
-├── kpmain.py	# 关键点信息输出代码
-├── main.py		# 单路视频输出代码
-├── test.py		# 三路后处理性能测试代码
-├── models
-│   └── Yunet.onnx 
-├── pipeline
-│   ├── InferTest.pipeline	# 三路后处理性能测试pipeline
-│   ├── PluginTest.pipeline	# 原方案插件性能测试pipeline
-│   ├── KPYunet.pipeline	# 关键点信息输出pipeline
-│   └── Yunet.pipeline   	# 单路视频输出pipeline
-├── plugin
-│   ├── build.sh
-│   ├── CMakeLists.txt
-│   ├── YunetPostProcess.cpp	# 人脸检测框后处理代码
-│   └── YunetPostProcess.h
-├── plugin2
-│   ├── build.sh
-│   ├── CMakeLists.txt
-│   ├── KPYunetPostProcess.cpp	# 人脸关键点后处理代码
-│   ├── KPYunetPostProcess.h
-├── plugin3
-│   ├── build.sh
-│   ├── CMakeLists.txt
-│   ├── TotalYunetPostProcess.cpp	# 人脸检测框与关键点后处理代码（以供可视化）
-│   └── TotalYunetPostProcess.h
-├── README.md
-└── run.sh
-````
-
-
-
-### 1.5 技术实现流程图
-
-![process](images/process.png)
-
-### 1.6 特性及适用场景
-
-本项目适用于单人及多人正脸视频。对于人脸侧面视频，可以将人脸位置正确标出，但关键点信息标注准确率较低。本项目可以适用于仰卧人脸，但不适用于侧卧人脸。
-
-特别地，在无人脸的情况下，我们在视频左上角设置了红色提示点。当左上角像素出现红色时，说明此场景没有检测出人脸。（下面给出该特殊点检测框的数据信息）
-
-````
-"MxpiObject":[{"classVec":[{"classId":3,"className":"","confidence":0,"headerVec":[]}],"x0":0,"x1":0,"y0":0,"y1":0}]
-````
-另外，本项目要求输入视频为1920*1080 25fps视频，不支持25帧率以上视频。
-
-
-
-
-## 2 环境依赖
-
-推荐系统为ubuntu  18.04,环境软件和版本如下：
-
-| 软件名称            | 版本    | 说明                          | 获取方式                                                  |
-| ------------------- |-------| ----------------------------- | :-------------------------------------------------------- |
-| MindX SDK           | 5.0.0 | mxVision软件包                | [链接](https://www.hiascend.com/software/Mindx-sdk)       |
-| ubuntu              | 18.04 | 操作系统                      | 请上ubuntu官网获取                                        |
-| Ascend-CANN-toolkit | 7.0.0 | Ascend-cann-toolkit开发套件包 | [链接](https://www.hiascend.com/software/cann/commercial) |
-
-
-
-在编译运行项目前，需要设置环境变量：
-
-MindXSDK 环境变量：
-
-```
-. ${SDK-path}/set_env.sh
-```
-
-CANN 环境变量：
-
-```
-. ${ascend-toolkit-path}/set_env.sh
-```
-
-- 环境变量介绍
-
-```
-SDK-path: mxVision SDK 安装路径
-ascend-toolkit-path: CANN 安装路径。
-```
-
-
-
-
-## 3 软件依赖说明
-
-
-
-| 软件名称 | 版本  | 说明                           | 使用教程                                                     |
-| -------- | ----- | ------------------------------ | ------------------------------------------------------------ |
-| live555  | 1.09  | 实现视频转rstp进行推流         | [链接](https://gitee.com/ascend/mindxsdk-referenceapps/blob/master/docs/%E5%8F%82%E8%80%83%E8%B5%84%E6%96%99/Live555%E7%A6%BB%E7%BA%BF%E8%A7%86%E9%A2%91%E8%BD%ACRTSP%E8%AF%B4%E6%98%8E%E6%96%87%E6%A1%A3.md) |
-| ffmpeg   | 4.2.1 | 实现mp4格式视频转为264格式视频 | [链接](https://gitee.com/ascend/mindxsdk-referenceapps/blob/master/docs/%E5%8F%82%E8%80%83%E8%B5%84%E6%96%99/pc%E7%AB%AFffmpeg%E5%AE%89%E8%A3%85%E6%95%99%E7%A8%8B.md#https://ffmpeg.org/download.html) |
-
-
-设置视频源，此处用rtsp拉流，将视频源转化为.264格式。
-
-````
-ffmpeg -i xxx.mp4 -vcodec h264 -bf 0 -g 25 -r 25 -s 1920*1080 -an -f h264 xxx.264
-````
-
-将转化后的.264视频用live555产生rtsp拉流。
-
-由于本项目是支持端对端3路推理，故设置3个视频源，请使用者自行将pipeline中的对应位置修改为自己所使用的的服务器和文件名。
-
-
-
-## 4 模型转化
-
-本项目中使用的模型是yunet模型，onnx模型可以直接[下载](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/yunet/yunet.onnx)。下载后使用模型转换工具ATC将onnx模型转换为om模型，模型转换工具相关介绍参考[链接](https://gitee.com/ascend/docs-openmind/blob/master/guide/mindx/sdk/tutorials/%E5%8F%82%E8%80%83%E8%B5%84%E6%96%99.md)
-
-模型转换步骤如下：
-
-按照2环境依赖设置环境变量
-
-`cd`到`models`文件夹，运行
-
-````
-atc --framework=5 --model=yunet.onnx --output=yunet --input_format=NCHW --input_shape="input:1,3,120,160" --log=debug --soc_version=Ascend310 --insert_op_conf=../config/Yunet.aippconfig
-````
-
-执行该命令后会在指定输出.om模型路径生成项目指定模型文件`yunet.om`。若模型转换成功则输出：
-
-```
-ATC start working now, please wait for a moment.
-ATC run success, welcome to the next use.
-```
-
-aipp文件配置如下：
-
-```
-aipp_op {
-    related_input_rank : 0
-    src_image_size_w : 160
-    src_image_size_h : 120
-    crop : false
-    aipp_mode: static
-    input_format : YUV420SP_U8
-    csc_switch : true
-    rbuv_swap_switch : false
-    matrix_r0c0 : 256
-    matrix_r0c1 : 454
-    matrix_r0c2 : 0
-    matrix_r1c0 : 256
-    matrix_r1c1 : -88
-    matrix_r1c2 : -183
-    matrix_r2c0 : 256
-    matrix_r2c1 : 0
-    matrix_r2c2 : 359
-    input_bias_0 : 0
-    input_bias_1 : 128
-    input_bias_2 : 128
-    mean_chn_0 : 0
-    mean_chn_1 : 0
-    mean_chn_2 : 0
-    min_chn_0 : 0.0
-    min_chn_1 : 0.0
-    min_chn_2 : 0.0
-    var_reci_chn_0 : 1.0
-    var_reci_chn_1 : 1.0
-    var_reci_chn_2 : 1.0
-}
-```
-
-
-
-## 5 编译运行
-
-`main.py`：用来生成端对端单路推理的可视化视频，以提供单路推理结果可视化的应用样例
-
-`kpmain.py`：用来生成单路关键点后处理的数据结果（用来确保关键点类型后处理的实现成功，关键点效果看main.py的可视化结果）
-
-（`kpmain.py`在此项目中不是必须的，当前没有keypoint类型osd支持下，仅给出单路pipeline输出数据信息供参考）
-
-`test.py`：用来输出端对端三路推理的后处理结果，以检测三路推理性能是否达标
-
-需要注意的是，本项目后处理插件支持三路视频推理的后处理，但由于mxVision-2.0.4暂不支持三路后处理输出，所以此处采取单路视频可视化和三路推理性能检测两部分，分别提供可视化应用与性能检测的功能。
-
-1.编译后处理插件
-
-`cd`到`plugin`目录，`mkdir`新建文件夹`build`
-
-`cd`到`build`，运行
-
-````
-cmake ..
-make -j
-make install
-````
-
-将生成的模型后处理so拷贝至MindXSDK安装路径的`lib/modelpostprocessors`目录。如果权限问题，`cd`到MindXSDK安装路径的`lib/modelpostprocessors`目录，将`libyunetpostprocess.so`的权限更改为`640`。
-
-对于`plugin2`、`plugin3`目录也同样处理。
-
-2.`config/face_yunet.cfg` 确认权限`640`。
-
-3.运行`main.py`程序
-
-`cd`到根目录，运行
-
-````
-bash run.sh
-````
-
-最后会得到`result.264`即为输出结果
-
-
-
-## 6 性能检测
-修改`run.sh`中
-````
-python3 main.py
-````
-改为
-````
-python3 test.py
-````
-运行
-````
-bash run.sh
-````
-测试插件`libtotalyunetpostprocess.so`的性能：
-
-![fps](images/fps2.png)
-
-因为性能检测结果实时输出，使用者在`test.py`运行过程中可以实时查看检测结果，并且在需要时，可以在输出帧率后立刻按CTRL+C停止，以查看帧率。
-性能检测结果如上。本项目三路推理的3秒平均帧率在74.0-75.0之间，满足端对端三路25fps的需求。
-
-
-
-
-## 7 常见问题
-
-若视频解码器负荷过高则会出现以下问题：
-![error1](images/error1.png)
-![error2](images/error2.png)
-
-导致此问题的可能原因为：视频帧率过高、视频尺寸过大或解码器正在同时解码过多其他视频
+## yunet实时人脸检测
+
+## 1介绍
+
+yunet基于MindXSDK开发，在昇腾芯片上进行人脸检测，并实现可视化呈现。输入3路视频，对其进行推理，输出推理结果。
+
+### 1.1 支持的产品
+
+本产品以昇腾310（推理）卡为硬件平台。
+
+### 1.2 支持的版本
+
+CANN：7.0.0
+
+SDK：mxVision 5.0.0（可通过cat SDK目录下的 version.info 查看）
+
+### 1.3 软件方案介绍
+
+表1.1 系统方案各子系统功能描述：
+
+| 序号 | 子系统         | 功能描述                                                     |
+| ---- | -------------- | ------------------------------------------------------------ |
+| 1    | 视频输入流     | 接收外部调用接口的输入视频路径，对视频进行拉流，并将拉去的裸流存储到缓冲区（buffer）中，并发送到下游插件。 |
+| 2    | 视频解码       | 用于视频解码，当前只支持H264格式。                           |
+| 3    | 数据分发       | 对单个输入数据进行2次分发。                                  |
+| 4    | 数据缓存       | 输出时为后续处理过程创建一个线程，用于将输入数据与输出数据解耦，并创建缓存队列，存储尚未输入到下流插件的数据。 |
+| 5    | 图像处理       | 对解码后的YUV格式的图像进行放缩。                            |
+| 6    | 模型推理插件   | 目标检测。                                                   |
+| 7    | 模型后处理插件 | 对模型输出的张量进行后处理，得到物体类型数据。               |
+| 8    | 目标框转绘插件 | 物体类型转化为OSD实例                                        |
+| 9    | OSD可视化插件  | 实现对视频流的每一帧图像进行绘制。                           |
+| 10   | 视频编码插件   | 用于将OSD可视化插件输出的图片进行视频编码，输出视频。        |
+
+
+
+### 1.4 代码目录结构与说明
+
+本项目名为yunet实时人脸检测，项目目录如下所示：
+
+````
+├── build.sh
+├── config
+│   ├── face_yunet.cfg      # yunet配置文件
+│   └── Yunet.aippconfig    # 模型转换aipp配置文件
+├── kpmain.py	# 关键点信息输出代码
+├── main.py		# 单路视频输出代码
+├── test.py		# 三路后处理性能测试代码
+├── models
+│   └── Yunet.onnx 
+├── pipeline
+│   ├── InferTest.pipeline	# 三路后处理性能测试pipeline
+│   ├── PluginTest.pipeline	# 原方案插件性能测试pipeline
+│   ├── KPYunet.pipeline	# 关键点信息输出pipeline
+│   └── Yunet.pipeline   	# 单路视频输出pipeline
+├── plugin
+│   ├── build.sh
+│   ├── CMakeLists.txt
+│   ├── YunetPostProcess.cpp	# 人脸检测框后处理代码
+│   └── YunetPostProcess.h
+├── plugin2
+│   ├── build.sh
+│   ├── CMakeLists.txt
+│   ├── KPYunetPostProcess.cpp	# 人脸关键点后处理代码
+│   ├── KPYunetPostProcess.h
+├── plugin3
+│   ├── build.sh
+│   ├── CMakeLists.txt
+│   ├── TotalYunetPostProcess.cpp	# 人脸检测框与关键点后处理代码（以供可视化）
+│   └── TotalYunetPostProcess.h
+├── README.md
+└── run.sh
+````
+
+
+
+### 1.5 技术实现流程图
+
+![process](images/process.png)
+
+### 1.6 特性及适用场景
+
+本项目适用于单人及多人正脸视频。对于人脸侧面视频，可以将人脸位置正确标出，但关键点信息标注准确率较低。本项目可以适用于仰卧人脸，但不适用于侧卧人脸。
+
+特别地，在无人脸的情况下，我们在视频左上角设置了红色提示点。当左上角像素出现红色时，说明此场景没有检测出人脸。（下面给出该特殊点检测框的数据信息）
+
+````
+"MxpiObject":[{"classVec":[{"classId":3,"className":"","confidence":0,"headerVec":[]}],"x0":0,"x1":0,"y0":0,"y1":0}]
+````
+另外，本项目要求输入视频为1920*1080 25fps视频，不支持25帧率以上视频。
+
+
+
+
+## 2 环境依赖
+
+推荐系统为ubuntu  18.04,环境软件和版本如下：
+
+| 软件名称            | 版本    | 说明                          | 获取方式                                                  |
+| ------------------- |-------| ----------------------------- | :-------------------------------------------------------- |
+| MindX SDK           | 5.0.0 | mxVision软件包                | [链接](https://www.hiascend.com/software/Mindx-sdk)       |
+| ubuntu              | 18.04 | 操作系统                      | 请上ubuntu官网获取                                        |
+| Ascend-CANN-toolkit | 7.0.0 | Ascend-cann-toolkit开发套件包 | [链接](https://www.hiascend.com/software/cann/commercial) |
+
+
+
+在编译运行项目前，需要设置环境变量：
+
+MindXSDK 环境变量：
+
+```
+. ${SDK-path}/set_env.sh
+```
+
+CANN 环境变量：
+
+```
+. ${ascend-toolkit-path}/set_env.sh
+```
+
+- 环境变量介绍
+
+```
+SDK-path: mxVision SDK 安装路径
+ascend-toolkit-path: CANN 安装路径。
+```
+
+
+
+
+## 3 软件依赖说明
+
+
+
+| 软件名称 | 版本  | 说明                           | 使用教程                                                     |
+| -------- | ----- | ------------------------------ | ------------------------------------------------------------ |
+| live555  | 1.09  | 实现视频转rstp进行推流         | [链接](https://gitee.com/ascend/mindxsdk-referenceapps/blob/master/docs/%E5%8F%82%E8%80%83%E8%B5%84%E6%96%99/Live555%E7%A6%BB%E7%BA%BF%E8%A7%86%E9%A2%91%E8%BD%ACRTSP%E8%AF%B4%E6%98%8E%E6%96%87%E6%A1%A3.md) |
+| ffmpeg   | 4.2.1 | 实现mp4格式视频转为264格式视频 | [链接](https://gitee.com/ascend/mindxsdk-referenceapps/blob/master/docs/%E5%8F%82%E8%80%83%E8%B5%84%E6%96%99/pc%E7%AB%AFffmpeg%E5%AE%89%E8%A3%85%E6%95%99%E7%A8%8B.md#https://ffmpeg.org/download.html) |
+
+
+设置视频源，此处用rtsp拉流，将视频源转化为.264格式。
+
+````
+ffmpeg -i xxx.mp4 -vcodec h264 -bf 0 -g 25 -r 25 -s 1920*1080 -an -f h264 xxx.264
+````
+
+将转化后的.264视频用live555产生rtsp拉流。
+
+由于本项目是支持端对端3路推理，故设置3个视频源，请使用者自行将pipeline中的对应位置修改为自己所使用的的服务器和文件名。
+
+
+
+## 4 模型转化
+
+本项目中使用的模型是yunet模型，onnx模型可以直接[下载](https://mindx.sdk.obs.cn-north-4.myhuaweicloud.com/mindxsdk-referenceapps%20/contrib/yunet/yunet.onnx)。下载后使用模型转换工具ATC将onnx模型转换为om模型，模型转换工具相关介绍参考[链接](https://gitee.com/ascend/docs-openmind/blob/master/guide/mindx/sdk/tutorials/%E5%8F%82%E8%80%83%E8%B5%84%E6%96%99.md)
+
+模型转换步骤如下：
+
+按照2环境依赖设置环境变量
+
+`cd`到`models`文件夹，运行
+
+````
+atc --framework=5 --model=yunet.onnx --output=yunet --input_format=NCHW --input_shape="input:1,3,120,160" --log=debug --soc_version=Ascend310 --insert_op_conf=../config/Yunet.aippconfig
+````
+
+执行该命令后会在指定输出.om模型路径生成项目指定模型文件`yunet.om`。若模型转换成功则输出：
+
+```
+ATC start working now, please wait for a moment.
+ATC run success, welcome to the next use.
+```
+
+aipp文件配置如下：
+
+```
+aipp_op {
+    related_input_rank : 0
+    src_image_size_w : 160
+    src_image_size_h : 120
+    crop : false
+    aipp_mode: static
+    input_format : YUV420SP_U8
+    csc_switch : true
+    rbuv_swap_switch : false
+    matrix_r0c0 : 256
+    matrix_r0c1 : 454
+    matrix_r0c2 : 0
+    matrix_r1c0 : 256
+    matrix_r1c1 : -88
+    matrix_r1c2 : -183
+    matrix_r2c0 : 256
+    matrix_r2c1 : 0
+    matrix_r2c2 : 359
+    input_bias_0 : 0
+    input_bias_1 : 128
+    input_bias_2 : 128
+    mean_chn_0 : 0
+    mean_chn_1 : 0
+    mean_chn_2 : 0
+    min_chn_0 : 0.0
+    min_chn_1 : 0.0
+    min_chn_2 : 0.0
+    var_reci_chn_0 : 1.0
+    var_reci_chn_1 : 1.0
+    var_reci_chn_2 : 1.0
+}
+```
+
+
+
+## 5 编译运行
+
+`main.py`：用来生成端对端单路推理的可视化视频，以提供单路推理结果可视化的应用样例
+
+`kpmain.py`：用来生成单路关键点后处理的数据结果（用来确保关键点类型后处理的实现成功，关键点效果看main.py的可视化结果）
+
+（`kpmain.py`在此项目中不是必须的，当前没有keypoint类型osd支持下，仅给出单路pipeline输出数据信息供参考）
+
+`test.py`：用来输出端对端三路推理的后处理结果，以检测三路推理性能是否达标
+
+需要注意的是，本项目后处理插件支持三路视频推理的后处理，但由于mxVision-2.0.4暂不支持三路后处理输出，所以此处采取单路视频可视化和三路推理性能检测两部分，分别提供可视化应用与性能检测的功能。
+
+1.编译后处理插件
+
+`cd`到`plugin`目录，`mkdir`新建文件夹`build`
+
+`cd`到`build`，运行
+
+````
+cmake ..
+make -j
+make install
+````
+
+将生成的模型后处理so拷贝至MindXSDK安装路径的`lib/modelpostprocessors`目录。如果权限问题，`cd`到MindXSDK安装路径的`lib/modelpostprocessors`目录，将`libyunetpostprocess.so`的权限更改为`640`。
+
+对于`plugin2`、`plugin3`目录也同样处理。
+
+2.`config/face_yunet.cfg` 确认权限`640`。
+
+3.运行`main.py`程序
+
+`cd`到根目录，运行
+
+````
+bash run.sh
+````
+
+最后会得到`result.264`即为输出结果
+
+
+
+## 6 性能检测
+修改`run.sh`中
+````
+python3 main.py
+````
+改为
+````
+python3 test.py
+````
+运行
+````
+bash run.sh
+````
+测试插件`libtotalyunetpostprocess.so`的性能：
+
+![fps](images/fps2.png)
+
+因为性能检测结果实时输出，使用者在`test.py`运行过程中可以实时查看检测结果，并且在需要时，可以在输出帧率后立刻按CTRL+C停止，以查看帧率。
+性能检测结果如上。本项目三路推理的3秒平均帧率在74.0-75.0之间，满足端对端三路25fps的需求。
+
+
+
+
+## 7 常见问题
+
+若视频解码器负荷过高则会出现以下问题：
+![error1](images/error1.png)
+![error2](images/error2.png)
+
+导致此问题的可能原因为：视频帧率过高、视频尺寸过大或解码器正在同时解码过多其他视频
 解决方案：确保三路视频都为1920*1080 25fps并且减少其它任务的运行
\ No newline at end of file
diff --git a/contrib/yunet/build.sh b/mxVision/mxVision-referenceapps/yunet/build.sh
similarity index 100%
rename from contrib/yunet/build.sh
rename to mxVision/mxVision-referenceapps/yunet/build.sh
diff --git a/contrib/yunet/config/Yunet.aippconfig b/mxVision/mxVision-referenceapps/yunet/config/Yunet.aippconfig
similarity index 100%
rename from contrib/yunet/config/Yunet.aippconfig
rename to mxVision/mxVision-referenceapps/yunet/config/Yunet.aippconfig
diff --git a/contrib/Retinaface/config/face_Retina.cfg b/mxVision/mxVision-referenceapps/yunet/config/face_yunet.cfg
similarity index 91%
rename from contrib/Retinaface/config/face_Retina.cfg
rename to mxVision/mxVision-referenceapps/yunet/config/face_yunet.cfg
index 30e9ff3c25931b11dbabf613f210b923bfdbd1f9..6b008934a4ad6eb25f38b551ebfef39ef31cf31d 100644
--- a/contrib/Retinaface/config/face_Retina.cfg
+++ b/mxVision/mxVision-referenceapps/yunet/config/face_yunet.cfg
@@ -1,4 +1,4 @@
-CLASS_NUM=1
-SCORE_THRESH=0.8
-IOU_THRESH=0.9
-
+CLASS_NUM=1
+SCORE_THRESH=0.8
+IOU_THRESH=0.9
+
diff --git a/contrib/yunet/images/error1.png b/mxVision/mxVision-referenceapps/yunet/images/error1.png
similarity index 100%
rename from contrib/yunet/images/error1.png
rename to mxVision/mxVision-referenceapps/yunet/images/error1.png
diff --git a/contrib/yunet/images/error2.png b/mxVision/mxVision-referenceapps/yunet/images/error2.png
similarity index 100%
rename from contrib/yunet/images/error2.png
rename to mxVision/mxVision-referenceapps/yunet/images/error2.png
diff --git a/contrib/yunet/images/fps.png b/mxVision/mxVision-referenceapps/yunet/images/fps.png
similarity index 100%
rename from contrib/yunet/images/fps.png
rename to mxVision/mxVision-referenceapps/yunet/images/fps.png
diff --git a/contrib/yunet/images/fps1.png b/mxVision/mxVision-referenceapps/yunet/images/fps1.png
similarity index 100%
rename from contrib/yunet/images/fps1.png
rename to mxVision/mxVision-referenceapps/yunet/images/fps1.png
diff --git a/contrib/yunet/images/fps2.png b/mxVision/mxVision-referenceapps/yunet/images/fps2.png
similarity index 100%
rename from contrib/yunet/images/fps2.png
rename to mxVision/mxVision-referenceapps/yunet/images/fps2.png
diff --git a/contrib/yunet/images/problem.png b/mxVision/mxVision-referenceapps/yunet/images/problem.png
similarity index 100%
rename from contrib/yunet/images/problem.png
rename to mxVision/mxVision-referenceapps/yunet/images/problem.png
diff --git a/contrib/yunet/images/process.png b/mxVision/mxVision-referenceapps/yunet/images/process.png
similarity index 100%
rename from contrib/yunet/images/process.png
rename to mxVision/mxVision-referenceapps/yunet/images/process.png
diff --git a/contrib/yunet/images/process1.png b/mxVision/mxVision-referenceapps/yunet/images/process1.png
similarity index 100%
rename from contrib/yunet/images/process1.png
rename to mxVision/mxVision-referenceapps/yunet/images/process1.png
diff --git a/contrib/yunet/kpmain.py b/mxVision/mxVision-referenceapps/yunet/kpmain.py
similarity index 100%
rename from contrib/yunet/kpmain.py
rename to mxVision/mxVision-referenceapps/yunet/kpmain.py
diff --git a/contrib/yunet/main.py b/mxVision/mxVision-referenceapps/yunet/main.py
similarity index 100%
rename from contrib/yunet/main.py
rename to mxVision/mxVision-referenceapps/yunet/main.py
diff --git a/contrib/yunet/pipeline/InferTest.pipeline b/mxVision/mxVision-referenceapps/yunet/pipeline/InferTest.pipeline
similarity index 100%
rename from contrib/yunet/pipeline/InferTest.pipeline
rename to mxVision/mxVision-referenceapps/yunet/pipeline/InferTest.pipeline
diff --git a/contrib/yunet/pipeline/KPYunet.pipeline b/mxVision/mxVision-referenceapps/yunet/pipeline/KPYunet.pipeline
similarity index 100%
rename from contrib/yunet/pipeline/KPYunet.pipeline
rename to mxVision/mxVision-referenceapps/yunet/pipeline/KPYunet.pipeline
diff --git a/contrib/yunet/pipeline/PluginTest.pipeline b/mxVision/mxVision-referenceapps/yunet/pipeline/PluginTest.pipeline
similarity index 100%
rename from contrib/yunet/pipeline/PluginTest.pipeline
rename to mxVision/mxVision-referenceapps/yunet/pipeline/PluginTest.pipeline
diff --git a/contrib/yunet/pipeline/Yunet.pipeline b/mxVision/mxVision-referenceapps/yunet/pipeline/Yunet.pipeline
similarity index 100%
rename from contrib/yunet/pipeline/Yunet.pipeline
rename to mxVision/mxVision-referenceapps/yunet/pipeline/Yunet.pipeline
diff --git a/contrib/yunet/plugin/CMakeLists.txt b/mxVision/mxVision-referenceapps/yunet/plugin/CMakeLists.txt
similarity index 100%
rename from contrib/yunet/plugin/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/yunet/plugin/CMakeLists.txt
diff --git a/contrib/yunet/plugin/YunetPostProcess.cpp b/mxVision/mxVision-referenceapps/yunet/plugin/YunetPostProcess.cpp
similarity index 100%
rename from contrib/yunet/plugin/YunetPostProcess.cpp
rename to mxVision/mxVision-referenceapps/yunet/plugin/YunetPostProcess.cpp
diff --git a/contrib/yunet/plugin/YunetPostProcess.h b/mxVision/mxVision-referenceapps/yunet/plugin/YunetPostProcess.h
similarity index 100%
rename from contrib/yunet/plugin/YunetPostProcess.h
rename to mxVision/mxVision-referenceapps/yunet/plugin/YunetPostProcess.h
diff --git a/contrib/yunet/plugin/build.sh b/mxVision/mxVision-referenceapps/yunet/plugin/build.sh
similarity index 100%
rename from contrib/yunet/plugin/build.sh
rename to mxVision/mxVision-referenceapps/yunet/plugin/build.sh
diff --git a/contrib/yunet/plugin2/CMakeLists.txt b/mxVision/mxVision-referenceapps/yunet/plugin2/CMakeLists.txt
similarity index 100%
rename from contrib/yunet/plugin2/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/yunet/plugin2/CMakeLists.txt
diff --git a/contrib/yunet/plugin2/KPYunetPostProcess.cpp b/mxVision/mxVision-referenceapps/yunet/plugin2/KPYunetPostProcess.cpp
similarity index 100%
rename from contrib/yunet/plugin2/KPYunetPostProcess.cpp
rename to mxVision/mxVision-referenceapps/yunet/plugin2/KPYunetPostProcess.cpp
diff --git a/contrib/yunet/plugin2/KPYunetPostProcess.h b/mxVision/mxVision-referenceapps/yunet/plugin2/KPYunetPostProcess.h
similarity index 100%
rename from contrib/yunet/plugin2/KPYunetPostProcess.h
rename to mxVision/mxVision-referenceapps/yunet/plugin2/KPYunetPostProcess.h
diff --git a/contrib/yunet/plugin2/build.sh b/mxVision/mxVision-referenceapps/yunet/plugin2/build.sh
similarity index 100%
rename from contrib/yunet/plugin2/build.sh
rename to mxVision/mxVision-referenceapps/yunet/plugin2/build.sh
diff --git a/contrib/yunet/plugin3/CMakeLists.txt b/mxVision/mxVision-referenceapps/yunet/plugin3/CMakeLists.txt
similarity index 100%
rename from contrib/yunet/plugin3/CMakeLists.txt
rename to mxVision/mxVision-referenceapps/yunet/plugin3/CMakeLists.txt
diff --git a/contrib/yunet/plugin3/TotalYunetPostProcess.cpp b/mxVision/mxVision-referenceapps/yunet/plugin3/TotalYunetPostProcess.cpp
similarity index 100%
rename from contrib/yunet/plugin3/TotalYunetPostProcess.cpp
rename to mxVision/mxVision-referenceapps/yunet/plugin3/TotalYunetPostProcess.cpp
diff --git a/contrib/yunet/plugin3/TotalYunetPostProcess.h b/mxVision/mxVision-referenceapps/yunet/plugin3/TotalYunetPostProcess.h
similarity index 100%
rename from contrib/yunet/plugin3/TotalYunetPostProcess.h
rename to mxVision/mxVision-referenceapps/yunet/plugin3/TotalYunetPostProcess.h
diff --git a/contrib/yunet/plugin3/build.sh b/mxVision/mxVision-referenceapps/yunet/plugin3/build.sh
similarity index 100%
rename from contrib/yunet/plugin3/build.sh
rename to mxVision/mxVision-referenceapps/yunet/plugin3/build.sh
diff --git a/contrib/yunet/run.sh b/mxVision/mxVision-referenceapps/yunet/run.sh
similarity index 100%
rename from contrib/yunet/run.sh
rename to mxVision/mxVision-referenceapps/yunet/run.sh
diff --git a/contrib/yunet/test.py b/mxVision/mxVision-referenceapps/yunet/test.py
similarity index 100%
rename from contrib/yunet/test.py
rename to mxVision/mxVision-referenceapps/yunet/test.py
diff --git a/tutorials/.keep b/mxVision/mxVision-tutorials/.keep
similarity index 100%
rename from tutorials/.keep
rename to mxVision/mxVision-tutorials/.keep
diff --git a/tutorials/DvppWrapperSample/CMakeLists.txt b/mxVision/mxVision-tutorials/DvppWrapperSample/CMakeLists.txt
similarity index 100%
rename from tutorials/DvppWrapperSample/CMakeLists.txt
rename to mxVision/mxVision-tutorials/DvppWrapperSample/CMakeLists.txt
diff --git a/tutorials/DvppWrapperSample/README.md b/mxVision/mxVision-tutorials/DvppWrapperSample/README.md
similarity index 100%
rename from tutorials/DvppWrapperSample/README.md
rename to mxVision/mxVision-tutorials/DvppWrapperSample/README.md
diff --git a/tutorials/DvppWrapperSample/main.cpp b/mxVision/mxVision-tutorials/DvppWrapperSample/main.cpp
similarity index 100%
rename from tutorials/DvppWrapperSample/main.cpp
rename to mxVision/mxVision-tutorials/DvppWrapperSample/main.cpp
diff --git a/tutorials/ImageDetectionSample/C++/CMakeLists.txt b/mxVision/mxVision-tutorials/ImageDetectionSample/C++/CMakeLists.txt
similarity index 100%
rename from tutorials/ImageDetectionSample/C++/CMakeLists.txt
rename to mxVision/mxVision-tutorials/ImageDetectionSample/C++/CMakeLists.txt
diff --git a/tutorials/ImageDetectionSample/C++/README.md b/mxVision/mxVision-tutorials/ImageDetectionSample/C++/README.md
similarity index 100%
rename from tutorials/ImageDetectionSample/C++/README.md
rename to mxVision/mxVision-tutorials/ImageDetectionSample/C++/README.md
diff --git a/tutorials/ImageDetectionSample/C++/main.cpp b/mxVision/mxVision-tutorials/ImageDetectionSample/C++/main.cpp
similarity index 100%
rename from tutorials/ImageDetectionSample/C++/main.cpp
rename to mxVision/mxVision-tutorials/ImageDetectionSample/C++/main.cpp
diff --git a/tutorials/ImageDetectionSample/C++/model/aipp_yolov3_416_416.aippconfig b/mxVision/mxVision-tutorials/ImageDetectionSample/C++/model/aipp_yolov3_416_416.aippconfig
similarity index 100%
rename from tutorials/ImageDetectionSample/C++/model/aipp_yolov3_416_416.aippconfig
rename to mxVision/mxVision-tutorials/ImageDetectionSample/C++/model/aipp_yolov3_416_416.aippconfig
diff --git a/tutorials/ImageDetectionSample/C++/model/yolov3_tf_bs1_fp16.cfg b/mxVision/mxVision-tutorials/ImageDetectionSample/C++/model/yolov3_tf_bs1_fp16.cfg
similarity index 100%
rename from tutorials/ImageDetectionSample/C++/model/yolov3_tf_bs1_fp16.cfg
rename to mxVision/mxVision-tutorials/ImageDetectionSample/C++/model/yolov3_tf_bs1_fp16.cfg
diff --git a/tutorials/ImageDetectionSample/C++/run.sh b/mxVision/mxVision-tutorials/ImageDetectionSample/C++/run.sh
similarity index 100%
rename from tutorials/ImageDetectionSample/C++/run.sh
rename to mxVision/mxVision-tutorials/ImageDetectionSample/C++/run.sh
diff --git a/tutorials/ImageDetectionSample/C++/test.pipeline b/mxVision/mxVision-tutorials/ImageDetectionSample/C++/test.pipeline
similarity index 100%
rename from tutorials/ImageDetectionSample/C++/test.pipeline
rename to mxVision/mxVision-tutorials/ImageDetectionSample/C++/test.pipeline
diff --git a/tutorials/ImageDetectionSample/python/README.md b/mxVision/mxVision-tutorials/ImageDetectionSample/python/README.md
similarity index 100%
rename from tutorials/ImageDetectionSample/python/README.md
rename to mxVision/mxVision-tutorials/ImageDetectionSample/python/README.md
diff --git a/tutorials/ImageDetectionSample/python/main.py b/mxVision/mxVision-tutorials/ImageDetectionSample/python/main.py
similarity index 100%
rename from tutorials/ImageDetectionSample/python/main.py
rename to mxVision/mxVision-tutorials/ImageDetectionSample/python/main.py
diff --git a/tutorials/ImageDetectionSample/python/models/aipp_yolov3_416_416.aippconfig b/mxVision/mxVision-tutorials/ImageDetectionSample/python/models/aipp_yolov3_416_416.aippconfig
similarity index 100%
rename from tutorials/ImageDetectionSample/python/models/aipp_yolov3_416_416.aippconfig
rename to mxVision/mxVision-tutorials/ImageDetectionSample/python/models/aipp_yolov3_416_416.aippconfig
diff --git a/tutorials/ImageDetectionSample/python/models/model_conversion.sh b/mxVision/mxVision-tutorials/ImageDetectionSample/python/models/model_conversion.sh
similarity index 100%
rename from tutorials/ImageDetectionSample/python/models/model_conversion.sh
rename to mxVision/mxVision-tutorials/ImageDetectionSample/python/models/model_conversion.sh
diff --git a/tutorials/ImageDetectionSample/python/models/yolov3_tf_bs1_fp16.cfg b/mxVision/mxVision-tutorials/ImageDetectionSample/python/models/yolov3_tf_bs1_fp16.cfg
similarity index 100%
rename from tutorials/ImageDetectionSample/python/models/yolov3_tf_bs1_fp16.cfg
rename to mxVision/mxVision-tutorials/ImageDetectionSample/python/models/yolov3_tf_bs1_fp16.cfg
diff --git a/tutorials/OsdSample/C++/CMakeLists.txt b/mxVision/mxVision-tutorials/OsdSample/C++/CMakeLists.txt
similarity index 100%
rename from tutorials/OsdSample/C++/CMakeLists.txt
rename to mxVision/mxVision-tutorials/OsdSample/C++/CMakeLists.txt
diff --git a/tutorials/OsdSample/C++/main.cpp b/mxVision/mxVision-tutorials/OsdSample/C++/main.cpp
similarity index 100%
rename from tutorials/OsdSample/C++/main.cpp
rename to mxVision/mxVision-tutorials/OsdSample/C++/main.cpp
diff --git a/tutorials/OsdSample/C++/run.sh b/mxVision/mxVision-tutorials/OsdSample/C++/run.sh
similarity index 100%
rename from tutorials/OsdSample/C++/run.sh
rename to mxVision/mxVision-tutorials/OsdSample/C++/run.sh
diff --git a/tutorials/OsdSample/README.md b/mxVision/mxVision-tutorials/OsdSample/README.md
similarity index 100%
rename from tutorials/OsdSample/README.md
rename to mxVision/mxVision-tutorials/OsdSample/README.md
diff --git a/tutorials/OsdSample/data/.keep b/mxVision/mxVision-tutorials/OsdSample/data/.keep
similarity index 100%
rename from tutorials/OsdSample/data/.keep
rename to mxVision/mxVision-tutorials/OsdSample/data/.keep
diff --git a/tutorials/OsdSample/json/ExternalOsdInstances.json b/mxVision/mxVision-tutorials/OsdSample/json/ExternalOsdInstances.json
similarity index 100%
rename from tutorials/OsdSample/json/ExternalOsdInstances.json
rename to mxVision/mxVision-tutorials/OsdSample/json/ExternalOsdInstances.json
diff --git a/tutorials/OsdSample/pipeline/SampleOsd.pipeline b/mxVision/mxVision-tutorials/OsdSample/pipeline/SampleOsd.pipeline
similarity index 96%
rename from tutorials/OsdSample/pipeline/SampleOsd.pipeline
rename to mxVision/mxVision-tutorials/OsdSample/pipeline/SampleOsd.pipeline
index 9757602fb35b1d93f3fcf95e3699c27eb8728448..ba41502a49679dcf9eac3436d3d00d4bd35f522b 100644
--- a/tutorials/OsdSample/pipeline/SampleOsd.pipeline
+++ b/mxVision/mxVision-tutorials/OsdSample/pipeline/SampleOsd.pipeline
@@ -1,55 +1,55 @@
-{
-    "encoder":{
-        "stream_config":{
-            "deviceId":"0"
-        },
-        "appsrc0":{
-            "props":{
-                "blocksize":"40960000"
-            },
-            "factory":"appsrc",
-            "next":"mxpi_imagedecoder0"
-        },
-        "mxpi_imagedecoder0":{
-            "factory":"mxpi_imagedecoder",
-            "next":"mxpi_imageresize0"
-        },
-        "mxpi_imageresize0":{
-            "props":{
-                "resizeHeight":"512",
-                "resizeWidth":"512"
-            },
-            "factory":"mxpi_imageresize",
-            "next":"mxpi_opencvosd0:0"
-        },
-        "appsrc1":{
-            "props":{
-                "blocksize":"40960000"
-            },
-            "factory":"appsrc",
-            "next":"mxpi_osdinstancemerger0"
-        },
-        "mxpi_osdinstancemerger0":{
-            "props":{
-                "dataSourceList":"appsrc1"
-            },
-            "factory":"mxpi_osdinstancemerger",
-            "next":"mxpi_opencvosd0:1"
-        },
-        "mxpi_opencvosd0":{
-            "factory":"mxpi_opencvosd",
-            "next":"mxpi_imageencoder0"
-        },
-        "mxpi_imageencoder0":{
-            "factory":"mxpi_imageencoder",
-            "next":"appsink0"
-        },
-        "appsink0":{
-            "props":{
-                "blocksize":"40960000",
-                "location":"./testout.jpg"
-            },
-            "factory":"filesink"
-        }
-    }
+{
+    "encoder":{
+        "stream_config":{
+            "deviceId":"0"
+        },
+        "appsrc0":{
+            "props":{
+                "blocksize":"40960000"
+            },
+            "factory":"appsrc",
+            "next":"mxpi_imagedecoder0"
+        },
+        "mxpi_imagedecoder0":{
+            "factory":"mxpi_imagedecoder",
+            "next":"mxpi_imageresize0"
+        },
+        "mxpi_imageresize0":{
+            "props":{
+                "resizeHeight":"512",
+                "resizeWidth":"512"
+            },
+            "factory":"mxpi_imageresize",
+            "next":"mxpi_opencvosd0:0"
+        },
+        "appsrc1":{
+            "props":{
+                "blocksize":"40960000"
+            },
+            "factory":"appsrc",
+            "next":"mxpi_osdinstancemerger0"
+        },
+        "mxpi_osdinstancemerger0":{
+            "props":{
+                "dataSourceList":"appsrc1"
+            },
+            "factory":"mxpi_osdinstancemerger",
+            "next":"mxpi_opencvosd0:1"
+        },
+        "mxpi_opencvosd0":{
+            "factory":"mxpi_opencvosd",
+            "next":"mxpi_imageencoder0"
+        },
+        "mxpi_imageencoder0":{
+            "factory":"mxpi_imageencoder",
+            "next":"appsink0"
+        },
+        "appsink0":{
+            "props":{
+                "blocksize":"40960000",
+                "location":"./testout.jpg"
+            },
+            "factory":"filesink"
+        }
+    }
 }
\ No newline at end of file
diff --git a/tutorials/OsdSample/python/main.py b/mxVision/mxVision-tutorials/OsdSample/python/main.py
similarity index 97%
rename from tutorials/OsdSample/python/main.py
rename to mxVision/mxVision-tutorials/OsdSample/python/main.py
index acc0b5416b25c0baaea5effb44df1465c3b3658a..7aa5c7f6e600a779c169416fe3d017e6786acc05 100644
--- a/tutorials/OsdSample/python/main.py
+++ b/mxVision/mxVision-tutorials/OsdSample/python/main.py
@@ -1,78 +1,78 @@
-#!/usr/bin/env python
-# coding=utf-8
-
-"""
-Copyright 2020 Huawei Technologies Co., Ltd
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
-http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License.
-"""
-
-import json
-import time
-from StreamManagerApi import StreamManagerApi, \
-    MxDataInput, MxProtobufIn, InProtobufVector
-import MxpiOSDType_pb2 as MxpiOSDType
-from google.protobuf.json_format import *
-
-if __name__ == '__main__':
-    # init stream manager
-    stream_manager_api = StreamManagerApi()
-    ret = stream_manager_api.InitManager()
-    if ret != 0:
-        print("Failed to init Stream manager, ret=%s" % str(ret))
-        exit()
-
-    # create streams by pipeline config file
-    with open("../pipeline/SampleOsd.pipeline", 'rb') as f:
-        pipeline_str = f.read()
-    ret = stream_manager_api.CreateMultipleStreams(pipeline_str)
-    if ret != 0:
-        print("Failed to create Stream, ret=%s" % str(ret))
-        exit()
-
-    # Construct the input of the stream
-    data_input = MxDataInput()
-    with open("../data/test.jpg", 'rb') as f:
-        data_input.data = f.read()
-
-    # Send image.
-    stream_name = b'encoder'
-    in_plugin_id = 0
-    ret = stream_manager_api.SendData(stream_name, in_plugin_id, data_input)
-    if ret < 0:
-        print("Failed to send data to stream.")
-        exit()
-
-    # Send osd instances protobuf.
-    with open("../json/ExternalOsdInstances.json", "r") as f:
-        message_json = json.load(f)
-    print(message_json)
-    in_plugin_id = 1
-    osd_instances_list = MxpiOSDType.MxpiOsdInstancesList()
-    osd_instances_list = ParseDict(message_json, osd_instances_list)
-
-    protobuf_vec = InProtobufVector()
-    protobuf = MxProtobufIn()
-    protobuf.key = b'appsrc1'
-    protobuf.type = b'MxTools.MxpiOsdInstancesList'
-    protobuf.protobuf = osd_instances_list.SerializeToString()
-    protobuf_vec.push_back(protobuf)
-    ret = stream_manager_api.SendProtobuf(stream_name, in_plugin_id, protobuf_vec)
-    if ret < 0:
-        print("Failed to send protobuf to stream.")
-        exit()
-
-    time.sleep(2)
-
-    # destroy streams
+#!/usr/bin/env python
+# coding=utf-8
+
+"""
+Copyright 2020 Huawei Technologies Co., Ltd
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+"""
+
+import json
+import time
+from StreamManagerApi import StreamManagerApi, \
+    MxDataInput, MxProtobufIn, InProtobufVector
+import MxpiOSDType_pb2 as MxpiOSDType
+from google.protobuf.json_format import *
+
+if __name__ == '__main__':
+    # init stream manager
+    stream_manager_api = StreamManagerApi()
+    ret = stream_manager_api.InitManager()
+    if ret != 0:
+        print("Failed to init Stream manager, ret=%s" % str(ret))
+        exit()
+
+    # create streams by pipeline config file
+    with open("../pipeline/SampleOsd.pipeline", 'rb') as f:
+        pipeline_str = f.read()
+    ret = stream_manager_api.CreateMultipleStreams(pipeline_str)
+    if ret != 0:
+        print("Failed to create Stream, ret=%s" % str(ret))
+        exit()
+
+    # Construct the input of the stream
+    data_input = MxDataInput()
+    with open("../data/test.jpg", 'rb') as f:
+        data_input.data = f.read()
+
+    # Send image.
+    stream_name = b'encoder'
+    in_plugin_id = 0
+    ret = stream_manager_api.SendData(stream_name, in_plugin_id, data_input)
+    if ret < 0:
+        print("Failed to send data to stream.")
+        exit()
+
+    # Send osd instances protobuf.
+    with open("../json/ExternalOsdInstances.json", "r") as f:
+        message_json = json.load(f)
+    print(message_json)
+    in_plugin_id = 1
+    osd_instances_list = MxpiOSDType.MxpiOsdInstancesList()
+    osd_instances_list = ParseDict(message_json, osd_instances_list)
+
+    protobuf_vec = InProtobufVector()
+    protobuf = MxProtobufIn()
+    protobuf.key = b'appsrc1'
+    protobuf.type = b'MxTools.MxpiOsdInstancesList'
+    protobuf.protobuf = osd_instances_list.SerializeToString()
+    protobuf_vec.push_back(protobuf)
+    ret = stream_manager_api.SendProtobuf(stream_name, in_plugin_id, protobuf_vec)
+    if ret < 0:
+        print("Failed to send protobuf to stream.")
+        exit()
+
+    time.sleep(2)
+
+    # destroy streams
     stream_manager_api.DestroyAllStreams()
\ No newline at end of file
diff --git a/tutorials/PipelineInputOutputSample/C++/CMakeLists.txt b/mxVision/mxVision-tutorials/PipelineInputOutputSample/C++/CMakeLists.txt
similarity index 100%
rename from tutorials/PipelineInputOutputSample/C++/CMakeLists.txt
rename to mxVision/mxVision-tutorials/PipelineInputOutputSample/C++/CMakeLists.txt
diff --git a/tutorials/PipelineInputOutputSample/C++/README.md b/mxVision/mxVision-tutorials/PipelineInputOutputSample/C++/README.md
similarity index 100%
rename from tutorials/PipelineInputOutputSample/C++/README.md
rename to mxVision/mxVision-tutorials/PipelineInputOutputSample/C++/README.md
diff --git a/tutorials/PipelineInputOutputSample/C++/main.cpp b/mxVision/mxVision-tutorials/PipelineInputOutputSample/C++/main.cpp
similarity index 100%
rename from tutorials/PipelineInputOutputSample/C++/main.cpp
rename to mxVision/mxVision-tutorials/PipelineInputOutputSample/C++/main.cpp
diff --git a/tutorials/PipelineInputOutputSample/C++/test.pipeline b/mxVision/mxVision-tutorials/PipelineInputOutputSample/C++/test.pipeline
similarity index 100%
rename from tutorials/PipelineInputOutputSample/C++/test.pipeline
rename to mxVision/mxVision-tutorials/PipelineInputOutputSample/C++/test.pipeline
diff --git a/tutorials/PipelineInputOutputSample/python/README.md b/mxVision/mxVision-tutorials/PipelineInputOutputSample/python/README.md
similarity index 100%
rename from tutorials/PipelineInputOutputSample/python/README.md
rename to mxVision/mxVision-tutorials/PipelineInputOutputSample/python/README.md
diff --git a/tutorials/PipelineInputOutputSample/python/main.py b/mxVision/mxVision-tutorials/PipelineInputOutputSample/python/main.py
similarity index 100%
rename from tutorials/PipelineInputOutputSample/python/main.py
rename to mxVision/mxVision-tutorials/PipelineInputOutputSample/python/main.py
diff --git a/tutorials/SamplePostProcess/CMakeLists.txt b/mxVision/mxVision-tutorials/SamplePostProcess/CMakeLists.txt
similarity index 100%
rename from tutorials/SamplePostProcess/CMakeLists.txt
rename to mxVision/mxVision-tutorials/SamplePostProcess/CMakeLists.txt
diff --git a/tutorials/SamplePostProcess/README.md b/mxVision/mxVision-tutorials/SamplePostProcess/README.md
similarity index 96%
rename from tutorials/SamplePostProcess/README.md
rename to mxVision/mxVision-tutorials/SamplePostProcess/README.md
index 599a63db11da992f0221643c8a9dc1596bb76afd..abd4a54c67c4c10a5037f7d10d0eb3183d471a69 100644
--- a/tutorials/SamplePostProcess/README.md
+++ b/mxVision/mxVision-tutorials/SamplePostProcess/README.md
@@ -1,41 +1,41 @@
-# SDK后处理开发教程
-
-## 1 介绍
-
-### 1.1 简介
-本应用基于SDK提供的后处理框架，实现自定义resnet50后处理类和yolov3后处理类，并编译生成得到对应so文件。
-
-### 1.2 支持的产品
-x86_64 Atlas 300I（型号3010）和arm Atlas 300I（型号3000）。
-
-### 1.3 支持的版本
-
-本样例配套的MxVision版本、CANN版本、Driver/Firmware版本如下所示：
-
-| MxVision版本  | CANN版本  | Driver/Firmware版本  |
-| --------- | ------------------ | -------------- | 
-| 5.0.0 | 7.0.0   |  23.0.0  |
-
-
-## 2 设置环境变量
-
-在执行后续步骤前，需要设置环境变量：
-
-```bash
-# 执行环境变量脚本使环境变量生效
-. ${ascend-toolkit-path}/set_env.sh
-. ${mxVision-path}/set_env.sh
-# mxVision: mxVision安装路径
-# ascend-toolkit-path: CANN安装路径
-```
-
-##  3 编译
-步骤1 编译
-
-1. 在项目根目录创建cmakeDir目录并进入该目录。
-2. 执行cmake.. && make编译项目。
-
-步骤2 查看结果
-
-编译得到的so保存在项目根目录的lib目录下。其中，libsamplepostprocess.so用于resnet50的后处理；libyolov3postprocess.so用于yolov3的后处理。
-
+# SDK后处理开发教程
+
+## 1 介绍
+
+### 1.1 简介
+本应用基于SDK提供的后处理框架，实现自定义resnet50后处理类和yolov3后处理类，并编译生成得到对应so文件。
+
+### 1.2 支持的产品
+x86_64 Atlas 300I（型号3010）和arm Atlas 300I（型号3000）。
+
+### 1.3 支持的版本
+
+本样例配套的MxVision版本、CANN版本、Driver/Firmware版本如下所示：
+
+| MxVision版本  | CANN版本  | Driver/Firmware版本  |
+| --------- | ------------------ | -------------- | 
+| 5.0.0 | 7.0.0   |  23.0.0  |
+
+
+## 2 设置环境变量
+
+在执行后续步骤前，需要设置环境变量：
+
+```bash
+# 执行环境变量脚本使环境变量生效
+. ${ascend-toolkit-path}/set_env.sh
+. ${mxVision-path}/set_env.sh
+# mxVision: mxVision安装路径
+# ascend-toolkit-path: CANN安装路径
+```
+
+##  3 编译
+步骤1 编译
+
+1. 在项目根目录创建cmakeDir目录并进入该目录。
+2. 执行cmake.. && make编译项目。
+
+步骤2 查看结果
+
+编译得到的so保存在项目根目录的lib目录下。其中，libsamplepostprocess.so用于resnet50的后处理；libyolov3postprocess.so用于yolov3的后处理。
+
diff --git a/tutorials/SamplePostProcess/Sample_new.pipeline b/mxVision/mxVision-tutorials/SamplePostProcess/Sample_new.pipeline
similarity index 97%
rename from tutorials/SamplePostProcess/Sample_new.pipeline
rename to mxVision/mxVision-tutorials/SamplePostProcess/Sample_new.pipeline
index ee61337ac6ed9fd1ba544ace09d2486d068548b2..bb3312c289330e1dc62565504d13cb0e4d4271fc 100644
--- a/tutorials/SamplePostProcess/Sample_new.pipeline
+++ b/mxVision/mxVision-tutorials/SamplePostProcess/Sample_new.pipeline
@@ -1,77 +1,77 @@
-{
-    "classification+detection": {
-        "stream_config": {
-            "deviceId": "0"
-        },
-        "mxpi_imagedecoder0": {
-            "factory": "mxpi_imagedecoder",
-            "next": "mxpi_imageresize0"
-        },
-        "mxpi_imageresize0": {
-            "factory": "mxpi_imageresize",
-            "next": "mxpi_tensorinfer0"
-        },
-        "mxpi_tensorinfer0": {
-            "props": {
-                "modelPath": "../models/yolov3/yolov3_tf_bs1_fp16.om"
-            },
-            "factory": "mxpi_tensorinfer",
-            "next": "mxpi_objectpostprocessor0"
-        },
-        "mxpi_objectpostprocessor0": {
-            "props": {
-                "dataSource": "mxpi_tensorinfer0",
-                "postProcessConfigPath": "../models/yolov3/yolov3_tf_bs1_fp16.cfg",
-                "labelPath": "../models/yolov3/coco.names",
-                "postProcessLibPath": "../../lib/libyolov3postprocess.so"
-            },
-            "factory": "mxpi_objectpostprocessor",
-            "next": "mxpi_imagecrop0"
-        },
-        "mxpi_imagecrop0": {
-            "factory": "mxpi_imagecrop",
-            "next": "mxpi_imageresize1"
-        },
-        "mxpi_imageresize1": {
-            "factory": "mxpi_imageresize",
-            "next": "mxpi_tensorinfer1"
-        },
-        "mxpi_tensorinfer1": {
-            "props": {
-                "modelPath": "../models/resnet50/resnet50_aipp_tf.om"
-            },
-            "factory": "mxpi_tensorinfer",
-            "next": "mxpi_classpostprocessor1"
-        },
-        "mxpi_classpostprocessor1": {
-            "props": {
-                "dataSource": "mxpi_tensorinfer1",
-                "postProcessConfigPath": "../models/resnet50/resnet50_aipp_tf.cfg",
-                "labelPath": "../models/resnet50/imagenet1000_clsidx_to_labels.names",
-                "postProcessLibPath": "../../lib/libsamplepostprocess.so"
-            },
-            "factory": "mxpi_classpostprocessor",
-            "next": "mxpi_dataserialize0"
-        },
-        "mxpi_dataserialize0": {
-            "props": {
-                "outputDataKeys": "mxpi_objectpostprocessor0,mxpi_classpostprocessor1"
-            },
-            "factory": "mxpi_dataserialize",
-            "next": "appsink0"
-        },
-        "appsrc0": {
-            "props": {
-                "blocksize": "409600"
-            },
-            "factory": "appsrc",
-            "next": "mxpi_imagedecoder0"
-        },
-        "appsink0": {
-            "props": {
-                "blocksize": "4096000"
-            },
-            "factory": "appsink"
-        }
-    }
-}
+{
+    "classification+detection": {
+        "stream_config": {
+            "deviceId": "0"
+        },
+        "mxpi_imagedecoder0": {
+            "factory": "mxpi_imagedecoder",
+            "next": "mxpi_imageresize0"
+        },
+        "mxpi_imageresize0": {
+            "factory": "mxpi_imageresize",
+            "next": "mxpi_tensorinfer0"
+        },
+        "mxpi_tensorinfer0": {
+            "props": {
+                "modelPath": "../models/yolov3/yolov3_tf_bs1_fp16.om"
+            },
+            "factory": "mxpi_tensorinfer",
+            "next": "mxpi_objectpostprocessor0"
+        },
+        "mxpi_objectpostprocessor0": {
+            "props": {
+                "dataSource": "mxpi_tensorinfer0",
+                "postProcessConfigPath": "../models/yolov3/yolov3_tf_bs1_fp16.cfg",
+                "labelPath": "../models/yolov3/coco.names",
+                "postProcessLibPath": "../../lib/libyolov3postprocess.so"
+            },
+            "factory": "mxpi_objectpostprocessor",
+            "next": "mxpi_imagecrop0"
+        },
+        "mxpi_imagecrop0": {
+            "factory": "mxpi_imagecrop",
+            "next": "mxpi_imageresize1"
+        },
+        "mxpi_imageresize1": {
+            "factory": "mxpi_imageresize",
+            "next": "mxpi_tensorinfer1"
+        },
+        "mxpi_tensorinfer1": {
+            "props": {
+                "modelPath": "../models/resnet50/resnet50_aipp_tf.om"
+            },
+            "factory": "mxpi_tensorinfer",
+            "next": "mxpi_classpostprocessor1"
+        },
+        "mxpi_classpostprocessor1": {
+            "props": {
+                "dataSource": "mxpi_tensorinfer1",
+                "postProcessConfigPath": "../models/resnet50/resnet50_aipp_tf.cfg",
+                "labelPath": "../models/resnet50/imagenet1000_clsidx_to_labels.names",
+                "postProcessLibPath": "../../lib/libsamplepostprocess.so"
+            },
+            "factory": "mxpi_classpostprocessor",
+            "next": "mxpi_dataserialize0"
+        },
+        "mxpi_dataserialize0": {
+            "props": {
+                "outputDataKeys": "mxpi_objectpostprocessor0,mxpi_classpostprocessor1"
+            },
+            "factory": "mxpi_dataserialize",
+            "next": "appsink0"
+        },
+        "appsrc0": {
+            "props": {
+                "blocksize": "409600"
+            },
+            "factory": "appsrc",
+            "next": "mxpi_imagedecoder0"
+        },
+        "appsink0": {
+            "props": {
+                "blocksize": "4096000"
+            },
+            "factory": "appsink"
+        }
+    }
+}
diff --git a/tutorials/SamplePostProcess/src/samplepostprocess/CMakeLists.txt b/mxVision/mxVision-tutorials/SamplePostProcess/src/samplepostprocess/CMakeLists.txt
similarity index 100%
rename from tutorials/SamplePostProcess/src/samplepostprocess/CMakeLists.txt
rename to mxVision/mxVision-tutorials/SamplePostProcess/src/samplepostprocess/CMakeLists.txt
diff --git a/tutorials/SamplePostProcess/src/samplepostprocess/SamplePostProcess.cpp b/mxVision/mxVision-tutorials/SamplePostProcess/src/samplepostprocess/SamplePostProcess.cpp
similarity index 100%
rename from tutorials/SamplePostProcess/src/samplepostprocess/SamplePostProcess.cpp
rename to mxVision/mxVision-tutorials/SamplePostProcess/src/samplepostprocess/SamplePostProcess.cpp
diff --git a/tutorials/SamplePostProcess/src/samplepostprocess/SamplePostProcess.h b/mxVision/mxVision-tutorials/SamplePostProcess/src/samplepostprocess/SamplePostProcess.h
similarity index 100%
rename from tutorials/SamplePostProcess/src/samplepostprocess/SamplePostProcess.h
rename to mxVision/mxVision-tutorials/SamplePostProcess/src/samplepostprocess/SamplePostProcess.h
diff --git a/tutorials/SamplePostProcess/src/yolov3/CMakeLists.txt b/mxVision/mxVision-tutorials/SamplePostProcess/src/yolov3/CMakeLists.txt
similarity index 100%
rename from tutorials/SamplePostProcess/src/yolov3/CMakeLists.txt
rename to mxVision/mxVision-tutorials/SamplePostProcess/src/yolov3/CMakeLists.txt
diff --git a/tutorials/SamplePostProcess/src/yolov3/Yolov3PostProcess.cpp b/mxVision/mxVision-tutorials/SamplePostProcess/src/yolov3/Yolov3PostProcess.cpp
similarity index 100%
rename from tutorials/SamplePostProcess/src/yolov3/Yolov3PostProcess.cpp
rename to mxVision/mxVision-tutorials/SamplePostProcess/src/yolov3/Yolov3PostProcess.cpp
diff --git a/tutorials/SamplePostProcess/src/yolov3/Yolov3PostProcess.h b/mxVision/mxVision-tutorials/SamplePostProcess/src/yolov3/Yolov3PostProcess.h
similarity index 100%
rename from tutorials/SamplePostProcess/src/yolov3/Yolov3PostProcess.h
rename to mxVision/mxVision-tutorials/SamplePostProcess/src/yolov3/Yolov3PostProcess.h
diff --git a/tutorials/mindx_sdk_plugin/CMakeLists.txt b/mxVision/mxVision-tutorials/mindx_sdk_plugin/CMakeLists.txt
similarity index 100%
rename from tutorials/mindx_sdk_plugin/CMakeLists.txt
rename to mxVision/mxVision-tutorials/mindx_sdk_plugin/CMakeLists.txt
diff --git a/tutorials/mindx_sdk_plugin/README.md b/mxVision/mxVision-tutorials/mindx_sdk_plugin/README.md
similarity index 96%
rename from tutorials/mindx_sdk_plugin/README.md
rename to mxVision/mxVision-tutorials/mindx_sdk_plugin/README.md
index 3d62946bd8700592383e15f33304613af5586c90..dd07bd5d170f265ac9fcc4533ec64579af47f398 100644
--- a/tutorials/mindx_sdk_plugin/README.md
+++ b/mxVision/mxVision-tutorials/mindx_sdk_plugin/README.md
@@ -1,59 +1,59 @@
-# SDK插件开发样例
-
-## 1 介绍
-
-### 1.1 简介
-
-SDK插件开发样例基于c++代码，生成SDK插件，以用于自定义插件后处理开发。
-
-### 1.2 支持的产品
-
-Atlas 300I pro、Atlas 300V pro
-
-### 1.3 支持的版本
-
-| MxVision版本 | CANN版本  | Driver/Firmware版本 |
-|------------|---------|-------------------|
-| 6.0.RC2    | 8.0.RC2 | 24.1.RC2          |
-| 6.0.RC3    | 8.0.RC3 | 24.1.RC3          |
-
-### 1.4 代码目录结构说明
-
-```
-├── mindx_sdk_plugin
-|   ├── src
-|   │   ├── mxpi_sampleplugin
-|   |   |   ├── MxpiSamplePlugin.cpp
-|   |   |   ├── MxpiSamplePlugin.h
-|   |   |   └── CMakeLists.txt
-|   └── CMakeLists.txt
-```
-
-## 2 设置环境变量
-
-```
-# MindX SDK环境变量:
-.${SDK-path}/set_env.sh
-
-# CANN环境变量:
-.${ascend-toolkit-path}/set_env.sh
-
-# 环境变量介绍
-SDK-path:SDK mxVision安装路径
-ascend-toolkit-path:CANN安装路径
-```
-将主目录下的`CMakeLists.txt`文件中第七行`set(MX_SDK_HOME "/usr/local/Ascend/mindx_sdk/mxVision/")`中`/usr/local/Ascend/mindx_sdk/mxVision/`内容替换为上述SDK安装路径。
-
-## 3 编译与运行
-
-**步骤1：** 在项目根目录下创建build文件夹，使用cmake命令进行编译，生成插件*.so文件：
-
-```
-# 创建build目录
-mkdir build
-cd build
-# cmake编译
-cmake ..
-make
-```
-**步骤2：** 查看结果：执行成功后会在`主目录/lib/plugins/`下生成插件*.so文件。
+# SDK插件开发样例
+
+## 1 介绍
+
+### 1.1 简介
+
+SDK插件开发样例基于c++代码，生成SDK插件，以用于自定义插件后处理开发。
+
+### 1.2 支持的产品
+
+Atlas 300I pro、Atlas 300V pro
+
+### 1.3 支持的版本
+
+| MxVision版本 | CANN版本  | Driver/Firmware版本 |
+|------------|---------|-------------------|
+| 6.0.RC2    | 8.0.RC2 | 24.1.RC2          |
+| 6.0.RC3    | 8.0.RC3 | 24.1.RC3          |
+
+### 1.4 代码目录结构说明
+
+```
+├── mindx_sdk_plugin
+|   ├── src
+|   │   ├── mxpi_sampleplugin
+|   |   |   ├── MxpiSamplePlugin.cpp
+|   |   |   ├── MxpiSamplePlugin.h
+|   |   |   └── CMakeLists.txt
+|   └── CMakeLists.txt
+```
+
+## 2 设置环境变量
+
+```
+# MindX SDK环境变量:
+.${SDK-path}/set_env.sh
+
+# CANN环境变量:
+.${ascend-toolkit-path}/set_env.sh
+
+# 环境变量介绍
+SDK-path:SDK mxVision安装路径
+ascend-toolkit-path:CANN安装路径
+```
+将主目录下的`CMakeLists.txt`文件中第七行`set(MX_SDK_HOME "/usr/local/Ascend/mindx_sdk/mxVision/")`中`/usr/local/Ascend/mindx_sdk/mxVision/`内容替换为上述SDK安装路径。
+
+## 3 编译与运行
+
+**步骤1：** 在项目根目录下创建build文件夹，使用cmake命令进行编译，生成插件*.so文件：
+
+```
+# 创建build目录
+mkdir build
+cd build
+# cmake编译
+cmake ..
+make
+```
+**步骤2：** 查看结果：执行成功后会在`主目录/lib/plugins/`下生成插件*.so文件。
diff --git a/tutorials/mindx_sdk_plugin/src/mxpi_sampleplugin/CMakeLists.txt b/mxVision/mxVision-tutorials/mindx_sdk_plugin/src/mxpi_sampleplugin/CMakeLists.txt
similarity index 100%
rename from tutorials/mindx_sdk_plugin/src/mxpi_sampleplugin/CMakeLists.txt
rename to mxVision/mxVision-tutorials/mindx_sdk_plugin/src/mxpi_sampleplugin/CMakeLists.txt
diff --git a/tutorials/mindx_sdk_plugin/src/mxpi_sampleplugin/MxpiSamplePlugin.cpp b/mxVision/mxVision-tutorials/mindx_sdk_plugin/src/mxpi_sampleplugin/MxpiSamplePlugin.cpp
similarity index 100%
rename from tutorials/mindx_sdk_plugin/src/mxpi_sampleplugin/MxpiSamplePlugin.cpp
rename to mxVision/mxVision-tutorials/mindx_sdk_plugin/src/mxpi_sampleplugin/MxpiSamplePlugin.cpp
diff --git a/tutorials/mindx_sdk_plugin/src/mxpi_sampleplugin/MxpiSamplePlugin.h b/mxVision/mxVision-tutorials/mindx_sdk_plugin/src/mxpi_sampleplugin/MxpiSamplePlugin.h
similarity index 100%
rename from tutorials/mindx_sdk_plugin/src/mxpi_sampleplugin/MxpiSamplePlugin.h
rename to mxVision/mxVision-tutorials/mindx_sdk_plugin/src/mxpi_sampleplugin/MxpiSamplePlugin.h
diff --git a/tutorials/mxBaseSample/CMakeLists.txt b/mxVision/mxVision-tutorials/mxBaseSample/CMakeLists.txt
similarity index 100%
rename from tutorials/mxBaseSample/CMakeLists.txt
rename to mxVision/mxVision-tutorials/mxBaseSample/CMakeLists.txt
diff --git a/tutorials/mxBaseSample/README.md b/mxVision/mxVision-tutorials/mxBaseSample/README.md
similarity index 100%
rename from tutorials/mxBaseSample/README.md
rename to mxVision/mxVision-tutorials/mxBaseSample/README.md
diff --git a/tutorials/mxBaseSample/build.sh b/mxVision/mxVision-tutorials/mxBaseSample/build.sh
similarity index 100%
rename from tutorials/mxBaseSample/build.sh
rename to mxVision/mxVision-tutorials/mxBaseSample/build.sh
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