在 Windows 使用 FastDeploy C++ SDK

在 Windows 下使用 FastDeploy C++ SDK 与在 Linux 下使用稍有不同。以下以 PPYOLOE 为例进行演示在CPU/GPU，以及GPU上通过TensorRT加速部署的示例。

在部署前，需确认以下两个步骤

1. 软硬件环境满足要求，参考FastDeploy环境要求
1. 根据开发环境，下载预编译部署库和samples代码，参考FastDeploy预编译库

环境依赖

cmake >= 3.12
Visual Studio 16 2019
cuda >= 11.2 (当WITH_GPU=ON)
cudnn >= 8.0 (当WITH_GPU=ON)
TensorRT >= 8.4 (当ENABLE_TRT_BACKEND=ON)

下载 FastDeploy Windows 10 C++ SDK

可以从以下链接下载编译好的 FastDeploy Windows 10 C++ SDK，SDK中包含了examples代码。

https://bj.bcebos.com/fastdeploy/release/cpp/fastdeploy-win-x64-gpu-0.2.0.zip

准备模型文件和测试图片

可以从以下链接下载模型文件和测试图片，并解压缩

https://bj.bcebos.com/paddlehub/fastdeploy/ppyoloe_crn_l_300e_coco.tgz # (下载后解压缩)
https://gitee.com/paddlepaddle/PaddleDetection/raw/release/2.4/demo/000000014439.jpg

在 Windows 上编译 PPYOLOE

Windows菜单打开x64 Native Tools Command Prompt for VS 2019命令工具，cd到ppyoloe的demo路径

cd fastdeploy-win-x64-gpu-0.2.0\examples\vision\detection\paddledetection\cpp

mkdir build && cd build
cmake .. -G "Visual Studio 16 2019" -A x64 -DFASTDEPLOY_INSTALL_DIR=%cd%\..\..\..\..\..\..\..\fastdeploy-win-x64-gpu-0.2.0 -DCUDA_DIRECTORY="C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v11.2"

然后执行

msbuild infer_demo.sln /m:4 /p:Configuration=Release /p:Platform=x64

配置依赖库路径

方式一：命令行设置环境变量

编译好的exe保存在Release目录下，在运行demo前，需要将模型和测试图片拷贝至该目录。另外，需要在终端指定DLL的搜索路径。请在build目录下执行以下命令。

set FASTDEPLOY_PATH=%cd%\..\..\..\..\..\..\..\fastdeploy-win-x64-gpu-0.2.0
set PATH=%FASTDEPLOY_PATH%\lib;%FASTDEPLOY_PATH%\third_libs\install\onnxruntime\lib;%FASTDEPLOY_PATH%\third_libs\install\opencv-win-x64-3.4.16\build\x64\vc15\bin;%FASTDEPLOY_PATH%\third_libs\install\paddle_inference\paddle\lib;%FASTDEPLOY_PATH%\third_libs\install\paddle_inference\third_party\install\mkldnn\lib;%FASTDEPLOY_PATH%\third_libs\install\paddle_inference\third_party\install\mklml\lib;%FASTDEPLOY_PATH%\third_libs\install\paddle2onnx\lib;%FASTDEPLOY_PATH%\third_libs\install\tensorrt\lib;%FASTDEPLOY_PATH%\third_libs\install\yaml-cpp\lib;%PATH%

注意，需要拷贝onnxruntime.dll到exe所在的目录。

copy /Y %FASTDEPLOY_PATH%\third_libs\install\onnxruntime\lib\onnxruntime* Release\

由于较新的Windows在System32系统目录下自带了onnxruntime.dll，因此就算设置了PATH，系统依然会出现onnxruntime的加载冲突。因此需要先拷贝demo用到的onnxruntime.dll到exe所在的目录。如下

where onnxruntime.dll
C:\Windows\System32\onnxruntime.dll  # windows自带的onnxruntime.dll

方式二：拷贝依赖库到exe的目录下

手动拷贝，或者在build目录下执行以下命令：

set FASTDEPLOY_PATH=%cd%\..\..\..\..\..\..\..\fastdeploy-win-x64-gpu-0.2.0
copy /Y %FASTDEPLOY_PATH%\lib\*.dll Release\
copy /Y %FASTDEPLOY_PATH%\third_libs\install\onnxruntime\lib\*.dll Release\
copy /Y %FASTDEPLOY_PATH%\third_libs\install\opencv-win-x64-3.4.16\build\x64\vc15\bin\*.dll Release\
copy /Y %FASTDEPLOY_PATH%\third_libs\install\paddle_inference\paddle\lib\*.dll Release\
copy /Y %FASTDEPLOY_PATH%\third_libs\install\paddle_inference\third_party\install\mkldnn\lib\*.dll Release\
copy /Y %FASTDEPLOY_PATH%\third_libs\install\paddle_inference\third_party\install\mklml\lib\*.dll Release\
copy /Y %FASTDEPLOY_PATH%\third_libs\install\paddle2onnx\lib\*.dll Release\
copy /Y %FASTDEPLOY_PATH%\third_libs\install\tensorrt\lib\*.dll Release\
copy /Y %FASTDEPLOY_PATH%\third_libs\install\yaml-cpp\lib\*.dll Release\

运行 demo

cd Release
infer_ppyoloe_demo.exe ppyoloe_crn_l_300e_coco 000000014439.jpg 0  # CPU
infer_ppyoloe_demo.exe ppyoloe_crn_l_300e_coco 000000014439.jpg 1  # GPU
infer_ppyoloe_demo.exe ppyoloe_crn_l_300e_coco 000000014439.jpg 2  # GPU + TensorRT

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