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YOLOv5 C++部署示例
本目录下提供infer.cc
快速完成yolov5s模型在SOPHGO BM1684x板子上加速部署的示例。
在部署前,需确认以下两个步骤:
- 软硬件环境满足要求
- 根据开发环境,从头编译FastDeploy仓库
以上步骤请参考SOPHGO部署库编译实现
生成基本目录文件
该例程由以下几个部分组成
.
├── CMakeLists.txt
├── build # 编译文件夹
├── image # 存放图片的文件夹
├── infer.cc
└── model # 存放模型文件的文件夹
编译
编译并拷贝SDK到thirdpartys文件夹
请参考SOPHGO部署库编译仓库编译SDK,编译完成后,将在build目录下生成fastdeploy-0.0.3目录.
拷贝模型文件,以及配置文件至model文件夹
将Paddle模型转换为SOPHGO bmodel模型,转换步骤参考文档
将转换后的SOPHGO bmodel模型文件拷贝至model中
准备测试图片至image文件夹
wget https://gitee.com/paddlepaddle/PaddleDetection/raw/release/2.4/demo/000000014439.jpg
cp 000000014439.jpg ./images
编译example
cd build
cmake .. -DFASTDEPLOY_INSTALL_DIR=${PWD}/fastdeploy-0.0.3
make
运行例程
./infer_demo model images/000000014439.jpg