FastDeploy C++ GPU本地编译（Windows）

由于官方已经编译好的opencv版本较旧，所以本地编译。

除了指定opencv路径以外（不指定会自动下载，版本较旧），其他所有按官方步骤进行

FastDeploy/build_on_win_with_gui.md at release/1.0.5 · PaddlePaddle/FastDeploy (github.com)

 如果想openvino、onnxruntime也用自己指定的版本，已经尝试过在CMake GUI中指定路径但没有编译生成（可能是cmake有问题，如果您编译成功，欢迎留言分享）。可以尝试如下方法：

可以先不指定路径，CMake GUI上Configure、Generate、OpenProject，然后VS自动打开后，ALL_BUILD处鼠标右键——生成，等待……等待……编译完成。

“自己指定的build路径\third_libs\install”路径里会出现openvino、onnxruntime的文件夹，将自己下载的版本对应文件替换进去，再次编译。

下载地址：Releases · microsoft/onnxruntime (github.com)

Releases · openvinotoolkit/openvino (github.com)

---------------------------------------------------------------------- 进入正题 --------------------------------------------------------------------

下载并配置编译环境，参考我的博客 深度学习 - 随笔分类 - 夕西行 - 博客园 (cnblogs.com)

版本：

• TensorRT-8.5.3.1.Windows10.x86_64.cuda-11.8.cudnn8.6
• cuda_11.8.0_522.06_windows
• cudnn-windows-x86_64-8.6.0.163_cuda11-archive
• zlib x64
• OpenCV 4.7.0

1、下载源码 Releases · PaddlePaddle/FastDeploy (github.com)

选择最新的release

2、CMake GUI编译Release版本（官方只提供了Release版）

 点击Configure，选择vs2019，x64，确定后进行如下设置：

只编译Release版本：

• 

勾选：

• ENABLE_ORT_BACKEND
• ENABLE_PADDLE_BACKEND
• ENABLE_TRT_BACKEND
• ENABLE_OPENVINO_BACKEND
• ENABLE_VISION
• ENABLE_TEXT

选择路径：

• opencv路径，

• 设置最终编译完毕后的库路径（手动新建），
• 设置cuda，
• 设置tensorrt，
• 勾选GPU，

3、以上设置完毕后，点击Configure，多次点击不出现红色提示后，点击Generate，Open Project。

VS自动打开后，ALL_BUILD处鼠标右键——生成，等待……等待……编译完成。

等待编译完毕后，INSTALL处鼠标右键——生成，库就出现在之前设置的路径里了。

在库文件夹中新建bin，双击 fastdeploy_init.bat，将所有的dll放入bin中。

bin添加到系统环境变量。

【实战】

vs新建infer控制台程序

#include "fastdeploy/vision.h"

int main() {
    namespace vision = fastdeploy::vision;
    auto model = vision::detection::PPYOLOE("ppyoloe_crn_l_300e_coco/model.pdmodel",
        "ppyoloe_crn_l_300e_coco/model.pdiparams",
        "ppyoloe_crn_l_300e_coco/infer_cfg.yml");
    auto im = cv::imread("000000014439.jpg");

    vision::DetectionResult res;
    model.Predict(im, &res);

    auto vis_im = vision::VisDetection(im, res, 0.5);
    cv::imwrite("vis_image.jpg", vis_im);
    return 0;
}

【CPU的配置文件props】

<?xml version="1.0" encoding="utf-8"?>
<Project ToolsVersion="4.0" xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
    <ImportGroup Label="PropertySheets" />
    <PropertyGroup Label="UserMacros" />
    <PropertyGroup />
    <ItemDefinitionGroup>
        <ClCompile>
            <AdditionalIncludeDirectories>C:\opencv\build\include;C:\opencv\build\include\opencv2;%(AdditionalIncludeDirectories)</AdditionalIncludeDirectories>
            <AdditionalIncludeDirectories>C:\fastdeploy-win-x64-cpu-1.0.5\include;%(AdditionalIncludeDirectories)</AdditionalIncludeDirectories>
        </ClCompile>
        <Link>
            <AdditionalLibraryDirectories>C:\opencv\build\x64\vc16\lib;%(AdditionalLibraryDirectories)</AdditionalLibraryDirectories>
            <AdditionalDependencies>opencv_world470.lib;%(AdditionalDependencies)</AdditionalDependencies>
            <AdditionalLibraryDirectories>C:\fastdeploy-win-x64-cpu-1.0.5\lib;%(AdditionalLibraryDirectories)</AdditionalLibraryDirectories>
            <AdditionalDependencies>fastdeploy.lib;%(AdditionalDependencies)</AdditionalDependencies>
        </Link>
    </ItemDefinitionGroup>
</Project>

【GPU的配置文件props】

<?xml version="1.0" encoding="utf-8"?>
<Project ToolsVersion="4.0" xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
    <ImportGroup Label="PropertySheets" />
    <PropertyGroup Label="UserMacros" />
    <PropertyGroup />
    <ItemDefinitionGroup>
        <ClCompile>
            <AdditionalIncludeDirectories>C:\opencv\build\include;C:\opencv\build\include\opencv2;%(AdditionalIncludeDirectories)</AdditionalIncludeDirectories>
            <AdditionalIncludeDirectories>C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8\include;%(AdditionalIncludeDirectories)</AdditionalIncludeDirectories>
            <AdditionalIncludeDirectories>C:\fastdeploy-win-x64-gpu-1.0.5\include;%(AdditionalIncludeDirectories)</AdditionalIncludeDirectories>
        </ClCompile>
        <Link>
            <AdditionalLibraryDirectories>C:\opencv\build\x64\vc16\lib;%(AdditionalLibraryDirectories)</AdditionalLibraryDirectories>
            <AdditionalDependencies>opencv_world470.lib;%(AdditionalDependencies)</AdditionalDependencies>
            <AdditionalLibraryDirectories>C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8\lib\x64;%(AdditionalLibraryDirectories)</AdditionalLibraryDirectories>
            <AdditionalDependencies>cublasLt.lib;cuda.lib;cudadevrt.lib;cudart.lib;cudart_static.lib;cudnn.lib;cudnn_adv_infer.lib;cudnn_adv_infer64_8.lib;cudnn_adv_train.lib;cudnn_adv_train64_8.lib;cudnn_cnn_infer.lib;cudnn_cnn_infer64_8.lib;cudnn_cnn_train.lib;cudnn_cnn_train64_8.lib;cudnn_ops_infer.lib;cudnn_ops_infer64_8.lib;cudnn_ops_train.lib;cudnn_ops_train64_8.lib;cudnn64_8.lib;cufft.lib;cufftw.lib;cufilt.lib;curand.lib;cusolver.lib;cusolverMg.lib;cusparse.lib;nppc.lib;nppial.lib;nppicc.lib;nppidei.lib;nppif.lib;nppig.lib;nppim.lib;nppist.lib;nppisu.lib;nppitc.lib;npps.lib;nvblas.lib;nvjpeg.lib;nvml.lib;nvptxcompiler_static.lib;nvrtc.lib;nvrtc_static.lib;nvrtc-builtins_static.lib;OpenCL.lib;%(AdditionalDependencies)</AdditionalDependencies>
            <AdditionalLibraryDirectories>C:\fastdeploy-win-x64-gpu-1.0.5\lib;%(AdditionalLibraryDirectories)</AdditionalLibraryDirectories>
            <AdditionalDependencies>fastdeploy.lib;%(AdditionalDependencies)</AdditionalDependencies>
        </Link>
        <CudaCompile>
              <CodeGeneration>compute_61,sm_61</CodeGeneration>
              <TargetMachinePlatform>64</TargetMachinePlatform>
        </CudaCompile>
    </ItemDefinitionGroup>
</Project>

 

有的电脑运行时会出现如下错误：

原因是编译得到的 yaml-cpp.dll，即使已经添加到系统环境变量，exe依然识别不到它。所以将它放到 C:\Windows\System32 或者 放到exe所在目录。

有的电脑程序无法运行：

可能是C盘有多余的其他版本的dll，如C:\Windows\SysWOW64\或者System32中onnxruntime.dll，删除之。

【模型转换】

onnx格式的模型可以使用官方转换工具，转为paddle。GitHub - PaddlePaddle/X2Paddle: Deep learning model converter for PaddlePaddle. (『飞桨』深度学习模型转换工具)

官方提供的工具 FastDeploy/README.md at develop · PaddlePaddle/FastDeploy · GitHub