diff --git a/contrib/Individual/.keep b/contrib/Individual/.keep
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/contrib/Individual/README.md b/contrib/Individual/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..c326b6b2f9f327224c395bc98488e02a37d9eb74
--- /dev/null
+++ b/contrib/Individual/README.md
@@ -0,0 +1,27 @@
+# Individual attribute recognition
+
+## 介绍
+
+行业SDK流程编排，该项目主要实现了从Sample.pipeline中读取pipeline创建推理stream，然后读取一张图片送到stream进行推理，获取推理结构后把结果打印出来，最后销毁stream。
+为了评测，可以从Sample_proto.pipline中读取pipeline创建推理stream，然后读入评测文档，根据评测文档中的数据集路径读入图片，最后将推理结果输出到一个txt文档中，通过对比脚本
+可以得到评测的结果。
+
+## 配置
+
+确保pipeline所需要的yolov4和resnet50模型文件在'../models'中存在，run.sh脚本中LD_LIBRARY_PATH设置了ACL动态库链接路径为/usr/local/Ascend/ascend-toolkit/latest/acllib/lib64，
+如果实际环境中路径不一致，需要替换为实际的目录。
+本项目涵盖人脸识别，人脸关键点提取，人脸对齐，人脸属性识别模型整体的代码。
+main.py以及Sample.pipeline是本项目的核心内容，完成人脸识别，人脸关键点提取，人脸对齐以及人脸属性识别整体的流程。在main.py中修改输入图像的路径即可得到相应的推理结果。
+项目目录下提供了三组可供测试使用的test1,test2,test3。如有需要，可以修改Sample.pipeline完成更丰富的功能。
+项目评测部分主要由在数据集CelebA上完成。该部分由attr_main.py、cal_accuracy.py、Sample_proto.pipeline和groudtruth组成。将数据集文件按照text_full中的路径存放到相应位置，运行脚本文件，可以得到
+一个txt输出，再通过运行cal_accuracy.py完成模型输出与标准值的对比，可以查看到评测结果。
+
+
+## 运行
+
+```python3.7/bash
+运行项目：bash ./run.sh 或者 python3.7 main.py
+运行评测：python3.7 attr_main.py
+python3.7 cal_accuracy.py --gt-file=./test_full.txt --pred-file=./img_result.txt
+```
+如果使用过程中遇到问题，请联系华为技术支持。
\ No newline at end of file
diff --git a/contrib/Individual/attr_main.py b/contrib/Individual/attr_main.py
new file mode 100644
index 0000000000000000000000000000000000000000..59b7782ae975927af4416e24bb5c459fc5f837b9
--- /dev/null
+++ b/contrib/Individual/attr_main.py
@@ -0,0 +1,83 @@
+#!/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 StreamManagerApi.py
+from StreamManagerApi import *
+import os
+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/Sample.pipeline", 'rb') as f:
+        pipelineStr = f.read()
+    ret = streamManagerApi.CreateMultipleStreams(pipelineStr)
+    if ret != 0:
+        print("Failed to create Stream, ret=%s" % str(ret))
+
+    file_handle = open('img_result.txt', 'w')
+    file_handle2 = open('test_full.txt', 'r')
+    while 1:
+        # Construct the input of the stream
+        dataInput = MxDataInput()
+        line = file_handle2.readline()
+        # the length of the path is 34
+        img_path = line[0:34]
+        with open(img_path, 'rb') as f:
+            dataInput.data = f.read()
+     
+        # Inputs data to a specified stream based on streamName.
+        streamName = b'classification+detection'
+        inPluginId = 0
+        uniqueId = streamManagerApi.SendDataWithUniqueId(streamName, inPluginId, dataInput)
+        if uniqueId < 0:
+            print("Failed to send data to stream.")
+
+        # Obtain the inference result by specifying streamName and uniqueId.
+        inferResult = streamManagerApi.GetResultWithUniqueId(streamName, uniqueId, 3000)
+        if inferResult.errorCode != 0:
+            print("GetResultWithUniqueId error. errorCode=%d, errorMsg=%s" % (
+              inferResult.errorCode, inferResult.data.decode()))
+        # save the confidence
+        img_list = []
+        # print the infer result
+        print(inferResult.data.decode())
+        dict_all = inferResult.data.decode()
+        # start of the string
+        begin = 0
+        end = len(dict_all)
+        index = 0
+        # the num of the attribute
+        attr_num = 40
+        # the distence of the 'confidence' and the num is 12
+        next_confidence = 12
+        for i in range(attr_num):
+            # find confidence in dict 
+            loc = dict_all.find('confidence', begin + index, end)
+            # next confidence
+            index = loc + next_confidence
+            img_list.append(int(dict_all[loc + next_confidence]))
+        file_handle.write(img_path + ' ')
+        file_handle.write(str(img_list).replace("[", "").replace("]", "").replace(",", " "))
+        file_handle.write('\n')
+    # destroy streams
+    file_handle.close()
+    streamManagerApi.DestroyAllStreams()
diff --git a/contrib/Individual/cal_accuracy.py b/contrib/Individual/cal_accuracy.py
new file mode 100644
index 0000000000000000000000000000000000000000..e1138a9ae9e401caca99c977606d39774b5e7d25
--- /dev/null
+++ b/contrib/Individual/cal_accuracy.py
@@ -0,0 +1,67 @@
+# 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 numpy as np
+import argparse
+
+
+def get_arguments():
+    parser = argparse.ArgumentParser(description="Attribute Network")
+    parser.add_argument("--gt-file", type=str,
+                        help="ground truth file path.")
+    parser.add_argument("--pred-file", type=str,
+                        help="prediction file path.")
+    parser.add_argument("--path-shift", type=int, default=0,
+                        help="prediction file path.")
+    return parser.parse_args()
+
+
+def cal_attr():
+    args = get_arguments()
+    path_shift = args.path_shift
+    print(args)
+    gt_attr_file = args.gt_file
+    pred_file = args.pred_file
+    attr_num = 40
+    gt_f = open(gt_attr_file, 'r')
+    gt_line = gt_f.readline().strip().split()
+    pred_f = open(pred_file, 'r')
+    #pred_f = open(pred_file, 'r')
+    pred_line = pred_f.readline().strip().split()
+  
+    same_count = np.zeros(attr_num, dtype=np.int32)
+    valid_sum = 0
+    while pred_line:
+        valid_sum += 1
+        for i in range(attr_num):
+            pred_attr = int(pred_line[1 + i])
+            gt_attr = int(gt_line[path_shift + 1 + i])
+            if pred_attr == gt_attr:
+                same_count[i] += 1
+        gt_line = gt_f.readline().strip().split()
+        pred_line = pred_f.readline().strip().split()
+    print(valid_sum)
+    result = np.zeros(attr_num)
+    cur_index = 0
+    for v in same_count:
+        # percentage calculation
+        print(v * 1.0 / valid_sum * 100)
+        result[cur_index] = v * 1.0 / valid_sum * 100
+        cur_index += 1
+    print('mean result', np.mean(result))
+    return result
+
+
+if __name__ == '__main__':
+    cal_attr()
diff --git a/contrib/Individual/main.py b/contrib/Individual/main.py
new file mode 100644
index 0000000000000000000000000000000000000000..f8eb7df06953c65fb90a71dbed85ddb2b74cc738
--- /dev/null
+++ b/contrib/Individual/main.py
@@ -0,0 +1,60 @@
+
+#!/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 StreamManagerApi.py
+from StreamManagerApi import *
+
+if __name__ == '__main__':
+    # init stream manager
+    streamManagerApi = StreamManagerApi()
+    ret = streamManagerApi.InitManager()
+    if ret != 0:
+        print("Failed to init Stream manager, ret=%s" % str(ret))
+
+    # create streams by pipeline config file
+    with open("./pipeline/Sample_proto.pipeline", 'rb') as f:
+        pipelineStr = f.read()
+    ret = streamManagerApi.CreateMultipleStreams(pipelineStr)
+    if ret != 0:
+        print("Failed to create Stream, ret=%s" % str(ret))
+
+    # Construct the input of the stream
+    dataInput = MxDataInput()
+
+    # example
+    with open("./test7.jpg", 'rb') as f:
+        dataInput.data = f.read()
+
+    # Inputs data to a specified stream based on streamName.
+    streamName = b'classification+detection'
+    inPluginId = 0
+    uniqueId = streamManagerApi.SendDataWithUniqueId(streamName, inPluginId, dataInput)
+    if uniqueId < 0:
+        print("Failed to send data to stream.")
+
+    # Obtain the inference result by specifying streamName and uniqueId.
+    inferResult = streamManagerApi.GetResultWithUniqueId(streamName, uniqueId, 3000)
+    if inferResult.errorCode != 0:
+        print("GetResultWithUniqueId error. errorCode=%d, errorMsg=%s" % (
+            inferResult.errorCode, inferResult.data.decode()))
+
+    # print the infer result
+    print(inferResult.data.decode())
+
+    # destroy streams
+    streamManagerApi.DestroyAllStreams()
diff --git a/contrib/Individual/models/.keep b/contrib/Individual/models/.keep
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/contrib/Individual/models/attr.names b/contrib/Individual/models/attr.names
new file mode 100644
index 0000000000000000000000000000000000000000..9a650240e84d102fbbb015d6f17cdcdb5d8d3e4f
--- /dev/null
+++ b/contrib/Individual/models/attr.names
@@ -0,0 +1,82 @@
+#this is  file 
+5_o_Clock_Shadow
+Arched_Eyebrows 
+Attractive 
+Bags_Under_Eyes 
+Bald 
+Bangs 
+Big_Lips 
+Big_Nose 
+Black_Hair 
+Blond_Hair 
+Blurry 
+Brown_Hair 
+Bushy_Eyebrows 
+Chubby 
+Double_Chin 
+Eyeglasses 
+Goatee 
+Gray_Hair 
+Heavy_Makeup 
+High_Cheekbones 
+Male 
+Mouth_Slightly_Open 
+Mustache 
+Narrow_Eyes 
+No_Beard 
+Oval_Face 
+Pale_Skin 
+Pointy_Nose 
+Receding_Hairline 
+Rosy_Cheeks 
+Sideburns 
+Smiling 
+Straight_Hair 
+Wavy_Hair 
+Wearing_Earrings 
+Wearing_Hat 
+Wearing_Lipstick 
+Wearing_Necklace 
+Wearing_Necktie 
+Young
+5_o_Clock_Shadow|no
+Arched_Eyebrows|no
+Attractive|no
+Bags_Under_Eyes|no 
+Bald|no 
+Bangs|no 
+Big_Lips|no 
+Big_Nose|no
+Black_Hair|no 
+Blond_Hair|no 
+Blurry|no 
+Brown_Hair|no 
+Bushy_Eyebrows|no 
+Chubby|no 
+Double_Chin|no 
+Eyeglasses|no 
+Goatee|no
+Gray_Hair|no 
+Heavy_Makeup|no 
+High_Cheekbones|no 
+Male|no
+Mouth_Slightly_Open|no 
+Mustache|no 
+Narrow_Eyes|no 
+No_Beard|no
+Oval_Face|no 
+Pale_Skin|no 
+Pointy_Nose|no 
+Receding_Hairline|no 
+Rosy_Cheeks|no 
+Sideburns|no
+Smiling|no
+Straight_Hair|no 
+Wavy_Hair|no 
+Wearing_Earrings|no 
+Wearing_Hat|no 
+Wearing_Lipstick|no 
+Wearing_Necklace|no 
+Wearing_Necktie|no
+Young|no
+ 
\ No newline at end of file
diff --git a/contrib/Individual/models/coco.names b/contrib/Individual/models/coco.names
new file mode 100644
index 0000000000000000000000000000000000000000..784594cd592c96e549d6363b1e5a5b9aa0e187cc
--- /dev/null
+++ b/contrib/Individual/models/coco.names
@@ -0,0 +1,5 @@
+# This file is originally from https://github.com/pjreddie/darknet/blob/master/data/coco.names
+person
+non motor-vehicle
+motor-vehicle
+face
diff --git a/contrib/Individual/models/face_quality_0605_b1.om b/contrib/Individual/models/face_quality_0605_b1.om
new file mode 100644
index 0000000000000000000000000000000000000000..65f03b1b8d2542b0b822b38d7d7af4f68e65a401
Binary files /dev/null and b/contrib/Individual/models/face_quality_0605_b1.om differ
diff --git a/contrib/Individual/models/libfacelandmarkpostprocessor.so b/contrib/Individual/models/libfacelandmarkpostprocessor.so
new file mode 100644
index 0000000000000000000000000000000000000000..58628a337435fd75483b1514bb664132470d1bdd
Binary files /dev/null and b/contrib/Individual/models/libfacelandmarkpostprocessor.so differ
diff --git a/contrib/Individual/models/libsamplepostprocess.so b/contrib/Individual/models/libsamplepostprocess.so
new file mode 100644
index 0000000000000000000000000000000000000000..76db642fe1be041951d57a6034eb04a0bf630551
Binary files /dev/null and b/contrib/Individual/models/libsamplepostprocess.so differ
diff --git a/contrib/Individual/models/libyolov3postprocess.so b/contrib/Individual/models/libyolov3postprocess.so
new file mode 100644
index 0000000000000000000000000000000000000000..d1b897f46e752b8cc01aa39f4463f2166465a220
Binary files /dev/null and b/contrib/Individual/models/libyolov3postprocess.so differ
diff --git a/contrib/Individual/models/resnet50_aipp_tf.cfg b/contrib/Individual/models/resnet50_aipp_tf.cfg
new file mode 100644
index 0000000000000000000000000000000000000000..5d004f9cbd6c9c2378b866de905162d34ad1a168
--- /dev/null
+++ b/contrib/Individual/models/resnet50_aipp_tf.cfg
@@ -0,0 +1,2 @@
+CLASS_NUM=40
+SOFTMAX=false
\ No newline at end of file
diff --git a/contrib/Individual/models/resnet50_aipp_tf1.cfg b/contrib/Individual/models/resnet50_aipp_tf1.cfg
new file mode 100644
index 0000000000000000000000000000000000000000..fea8d3e2765b2df571753ab7a28a2df593aeffe6
--- /dev/null
+++ b/contrib/Individual/models/resnet50_aipp_tf1.cfg
@@ -0,0 +1,3 @@
+ATTRIBUTE_NUM=40
+ATTRIBUTE_INDEX=0%1%2%3%4%5%6%7%8%9%10%11%12%13%14%15%16%17%18%19%20%21%22%23%24%25%26%27%28%29%30%31%32%33%34%35%36%37%38%39%
+ACTIVATION_FUNCTION=sigmoid
\ No newline at end of file
diff --git a/contrib/Individual/models/yolov4.cfg b/contrib/Individual/models/yolov4.cfg
new file mode 100644
index 0000000000000000000000000000000000000000..231e4566b70e3484203db45960e11a31d68c21a9
--- /dev/null
+++ b/contrib/Individual/models/yolov4.cfg
@@ -0,0 +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
diff --git a/contrib/Individual/pipeline/.keep b/contrib/Individual/pipeline/.keep
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/contrib/Individual/pipeline/Sample.pipeline b/contrib/Individual/pipeline/Sample.pipeline
new file mode 100644
index 0000000000000000000000000000000000000000..2f7b7361c5f91ddbd0f1bbc0640a779a9abd25c0
--- /dev/null
+++ b/contrib/Individual/pipeline/Sample.pipeline
@@ -0,0 +1,58 @@
+{
+    "classification+detection": {
+        "stream_config": {
+            "deviceId": "0"
+        },
+        "mxpi_imagedecoder0": {
+            "factory": "mxpi_imagedecoder",
+            "next": "mxpi_imageresize0"
+       },
+        "mxpi_imageresize0": {
+            "factory": "mxpi_imageresize",
+            "next": "face_attribute",
+            "props": {
+                "dataSource": "mxpi_imagedecoder0",
+                "resizeHeight": "224",
+                "resizeWidth": "224"
+             }
+        },
+            "face_attribute": {
+               "props":{
+                   "dataSource":"mxpi_imageresize0",
+                   "modelPath":"./models/simple.om"
+                },
+               "factory": "mxpi_tensorinfer",
+               "next": "mxpi_classpostprocessor1"
+           },
+           "mxpi_classpostprocessor1": {
+               "props": {
+                "dataSource": "face_attribute",
+                "postProcessConfigPath": "./models/resnet50_aipp_tf.cfg",
+                "labelPath": "./models/attr.names",
+                "postProcessLibPath": "./models/libsamplepostprocess.so"
+            },
+            "factory": "mxpi_classpostprocessor",
+            "next": "mxpi_dataserialize0"
+        },       
+             "mxpi_dataserialize0": {
+            "props": {
+                "outputDataKeys": "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/contrib/Individual/pipeline/Sample_proto.pipeline b/contrib/Individual/pipeline/Sample_proto.pipeline
new file mode 100644
index 0000000000000000000000000000000000000000..b6bb215927c1031b6e29eb147bcb14f11f37288d
--- /dev/null
+++ b/contrib/Individual/pipeline/Sample_proto.pipeline
@@ -0,0 +1,149 @@
+{
+    "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": {
+                "dataSource": "mxpi_imageresize0",
+                "modelPath": "./models/yolov4_detection.om"
+            },
+            "factory": "mxpi_tensorinfer",
+            "next": "mxpi_objectpostprocessor0"
+        },
+        "mxpi_objectpostprocessor0": {
+            "props": {
+                "dataSource": "mxpi_tensorinfer0",
+                "postProcessConfigPath": "./models/yolov4.cfg",
+                "labelPath": "./models/coco.names",
+                "postProcessLibPath": "./models/libyolov3postprocess.so"
+            },
+            "factory": "mxpi_objectpostprocessor",
+            "next": "mxpi_objectdistributor0"
+        },
+        "mxpi_objectdistributor0":{
+            "props":{
+                "classIds":"3,2|1|0",
+                "dataSource":"mxpi_objectpostprocessor0"
+            },
+            "factory":"mxpi_distributor",
+            "next":["mxpi_imagecrop0","fakesink0"]
+        },
+         "fakesink0": {
+             "factory": "fakesink"
+         },
+         "mxpi_imagecrop0": {
+                "props": {
+                    "dataSource": "mxpi_objectdistributor0_0",
+                    "leftExpandRatio":"0.2",
+                    "rightExpandRatio":"0.2",
+                    "upExpandRatio":"0.2",
+                    "downExpandRatio":"0.2",
+                    "resizeHeight":"224",
+                    "resizeWidth":"224"
+               },
+               "factory": "mxpi_imagecrop",
+               "next": "tee0"
+     	    },
+
+         "tee0":{
+               "props":{},
+               "factory":"tee",
+               "next":[
+                   "queue0",
+                   "queue1"
+               ]
+           },
+         "queue0":{
+               "props":{
+                   "max-size-buffers":"50"
+               },
+               "factory":"queue",
+               "next":"mxpi_imageresize1"
+           },
+           "queue1":{
+               "props":{
+                   "max-size-buffers":"50"
+               },
+               "factory":"queue",
+               "next":"mxpi_facealignment0:0"
+           },
+        "mxpi_imageresize1": {
+               "props": {
+                   "resizeHeight":"96",
+                   "resizeWidth":"96",
+                   "dataSource": "mxpi_imagecrop0"
+               },
+               "factory": "mxpi_imageresize",
+               "next": "face_landmark"
+        },
+            "face_landmark": {
+              "props":{
+                   "dataSource":"mxpi_imageresize1",
+                   "modelPath":"./models/face_quality_0605_b1.om",
+                   "postProcessLibPath":"./models/libfacelandmarkpostprocessor.so"
+               },
+               "factory": "mxpi_modelinfer",
+               "next": "mxpi_facealignment0:1"
+           },
+            "mxpi_facealignment0":{
+               "props":{
+                   "status":"1",
+                   "dataSourceImage":"mxpi_imagecrop0",
+                   "dataSourceKeyPoint":"face_landmark",
+                   "afterFaceAlignmentHeight":"224",
+                   "afterFaceAlignmentWidth":"224"
+               },
+               "factory":"mxpi_facealignment",
+               "next": "face_attribute"
+            },
+
+            "face_attribute": {
+               "props":{
+                   "dataSource":"mxpi_facealignment0",
+                   "modelPath":"./models/bgrbgrsimple.om"
+                },
+               "factory": "mxpi_tensorinfer",
+               "next": "mxpi_classpostprocessor1"
+           },
+           "mxpi_classpostprocessor1": {
+               "props": {
+                "dataSource": "face_attribute",
+                "postProcessConfigPath": "./models/resnet50_aipp_tf.cfg",
+                "labelPath": "./models/attr.names",
+                "postProcessLibPath": "./models/libsamplepostprocess.so"
+            },
+            "factory": "mxpi_classpostprocessor",
+            "next": "mxpi_dataserialize0"
+        },
+
+        "mxpi_dataserialize0": {
+            "props": {
+                "outputDataKeys": "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/contrib/Individual/pipeline/Sample_proto1.pipeline b/contrib/Individual/pipeline/Sample_proto1.pipeline
new file mode 100644
index 0000000000000000000000000000000000000000..5d6a804691ebf1fea26cf1a3fd6423aa53ced293
--- /dev/null
+++ b/contrib/Individual/pipeline/Sample_proto1.pipeline
@@ -0,0 +1,139 @@
+{
+    "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": {
+                "dataSource": "mxpi_imageresize0",
+                "modelPath": "./models/yolov4_detection.om"
+            },
+            "factory": "mxpi_tensorinfer",
+            "next": "mxpi_objectpostprocessor0"
+        },
+        "mxpi_objectpostprocessor0": {
+            "props": {
+                "dataSource": "mxpi_tensorinfer0",
+                "postProcessConfigPath": "./models/yolov4.cfg",
+                "labelPath": "./models/coco.names",
+                "postProcessLibPath": "/home/nku_wang6/mxVision/lib/modelpostprocessors/libyolov3postprocess.so"
+            },
+            "factory": "mxpi_objectpostprocessor",
+            "next": "mxpi_imagecrop0"
+        },
+        
+         "mxpi_imagecrop0": {
+                "props": {
+                    "dataSource": "mxpi_objectpostprocessor0",
+                    "leftExpandRatio":"0.2",
+                    "rightExpandRatio":"0.2",
+                    "upExpandRatio":"0.2",
+                    "downExpandRatio":"0.2",
+                    "resizeHeight":"224",
+                    "resizeWidth":"224"
+               },
+               "factory": "mxpi_imagecrop",
+               "next": "tee0"
+     	    },
+
+         "tee0":{
+               "props":{},
+               "factory":"tee",
+               "next":[
+                   "queue0",
+                   "queue1"
+               ]
+           },
+         "queue0":{
+               "props":{
+                   "max-size-buffers":"50"
+               },
+               "factory":"queue",
+               "next":"mxpi_imageresize1"
+           },
+           "queue1":{
+               "props":{
+                   "max-size-buffers":"50"
+               },
+               "factory":"queue",
+               "next":"mxpi_facealignment0:0"
+           },
+        "mxpi_imageresize1": {
+               "props": {
+                   "resizeHeight":"96",
+                   "resizeWidth":"96",
+                   "dataSource": "mxpi_imagecrop0"
+               },
+               "factory": "mxpi_imageresize",
+               "next": "face_landmark"
+        },
+            "face_landmark": {
+              "props":{
+                   "dataSource":"mxpi_imageresize1",
+                   "modelPath":"./models/face_quality_0605_b1.om",
+                   "postProcessLibPath":"/home/nku_wang6/mxVision/lib/libfacelandmarkpostprocessor.so"
+               },
+               "factory": "mxpi_modelinfer",
+               "next": "mxpi_facealignment0:1"
+           },
+            "mxpi_facealignment0":{
+               "props":{
+                   "status":"1",
+                   "dataSourceImage":"mxpi_imagecrop0",
+                   "dataSourceKeyPoint":"face_landmark",
+                   "afterFaceAlignmentHeight":"224",
+                   "afterFaceAlignmentWidth":"224"
+               },
+               "factory":"mxpi_facealignment",
+               "next": "face_attribute"
+            },
+
+            "face_attribute": {
+               "props":{
+                   "dataSource":"mxpi_facealignment0",
+                   "modelPath":"./models/bgrbgrsimple.om"
+                },
+               "factory": "mxpi_tensorinfer",
+               "next": "mxpi_classpostprocessor1"
+           },
+           "mxpi_classpostprocessor1": {
+               "props": {
+                "dataSource": "face_attribute",
+                "postProcessConfigPath": "./models/resnet50_aipp_tf.cfg",
+                "labelPath": "./models/attr.names",
+                "postProcessLibPath": "/home/nku_wang6/mxVision/lib/modelpostprocessors/libsamplepostprocess.so"
+            },
+            "factory": "mxpi_classpostprocessor",
+            "next": "mxpi_dataserialize0"
+        },
+
+        "mxpi_dataserialize0": {
+            "props": {
+                "outputDataKeys": "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/contrib/Individual/run.sh b/contrib/Individual/run.sh
new file mode 100644
index 0000000000000000000000000000000000000000..1d348d753e1de4c04f810c8ca3a70411477efd59
--- /dev/null
+++ b/contrib/Individual/run.sh
@@ -0,0 +1,33 @@
+#!/bin/bash
+
+# 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.
+set -e
+
+CUR_PATH=$(cd "$(dirname "$0")" || { warn "Failed to check path/to/run.sh" ; exit ; } ; pwd)
+
+# Simple log helper functions
+info() { echo -e "\033[1;34m[INFO ][MxStream] $1\033[1;37m" ; }
+warn() { echo >&2 -e "\033[1;31m[WARN ][MxStream] $1\033[1;37m" ; }
+
+export MX_SDK_HOME=${CUR_PATH}/../../..
+export LD_LIBRARY_PATH=${MX_SDK_HOME}/lib:${MX_SDK_HOME}/opensource/lib:${MX_SDK_HOME}/opensource/lib64:/usr/local/Ascend/ascend-toolkit/latest/acllib/lib64:${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:${MX_SDK_HOME}/lib/plugins:/home/nku_wang6/mxVision-2.0.2/samples/mindx_sdk_plugin
+
+#to set PYTHONPATH, import the StreamManagerApi.py
+export PYTHONPATH=$PYTHONPATH:${MX_SDK_HOME}/python
+
+python3.7 main.py
+exit 0
\ No newline at end of file