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Readme.md

Huawei ACL OpenCV+YOLOv3 Sample

0.Enviorment:

Dependence Version
Huawei ACL Framework 1.73.x
OpenCV 4.x

1.Preparing

A.Model preparing

This repo's model base on caffe-yolov3.In this repo,the yolov3 post process is running in NPU unit so you can see there are few code in function YoloPostprocess.The model forward time cost can be less than 12ms.You can reference data/model/README.md to get model transform steps and more infomations.

B.Compile perparing

Before compiling,you should modify the few lines in CMakeLists.txt as follow:

#if you run this program in atlas 800-3000 / atlas 300-3000
#but develop/compile the program in x86 platform, you must install the crossplatform-compiler
#and set it as the target compiler.
#atlas 800-3010 / atlas 300-3010 no needed.
SET(CMAKE_C_COMPILER "aarch64-linux-gnu-gcc-5")
SET(CMAKE_CXX_COMPILER "aarch64-linux-gnu-g++-5")
#set your own opencv install path
set(OpenCV_DIR /home/atlas/opencv_4.4_aarch64/lib/cmake/opencv4)
#set your own acltoolkit install path
set(ACL_PATH /home/atlas/Ascend/ascend-toolkit/20.0.0.RC1/arm64-linux_gcc7.3.0)

2.Compiling

mkdir build & cd build
cmake ..
make

3.Run sample

./ACL_YOLOV3 ./data/model/yolov3.om test.jpg

and you can get result.jpg:

result

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This is a yolov3 sample based on huawei acl framework(version 1.73.x) .Tested in Atlas 800-3000 platform. spread retract
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