QT Creator + Opencv + Libtorch +CUDA English

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  1. Download and install QT Creator, configure the environment. Note that the MSVC compiler component is checked during installation. Use MSVC to compile the project. Configure MSVC 2017 x64 in Tools->Options->Build Kits->MSVC 2017 x64, and select the c and c++ compilers as amd64.

  2. If the computer does not have the cdb.exe file (Search by Everything), download and install it. After installation, select Tools->Options->Build Kits->MSVC 2017 x64->Debugger (Debugger) and add cdb.exe.

  3. Download OpenCV and libtorch. Configure the correct path to the project’s .pro file and add it at the end of the .pro file

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    INCLUDEPATH += your path to\opencv-4.5.0-vc14_vc15\opencv\build\include \
    your path to\libtorch17release\include \
    your path to\libtorch17release\include\torch\csrc\api\include

    LIBS += -Lyour path to\opencv-4.5.0-vc14_vc15\opencv\build\x64\vc15\lib -lopencv_world450 \
    -Lyour path to\libtorch17release\lib -lc10 -ltorch -lc10_cuda -lcaffe2_detectron_ops_gpu -lc10d -ltorch_cpu \
    -ltorch_cuda -lgloo -lcaffe2_module_test_dynamic -lasmjit -lcaffe2_nvrtc -lclog -lcpuinfo -ldnnl -lfbgemm -lgloo_cuda \
    -lmkldnn -INCLUDE:?warp_size@cuda@at@@YAHXZ

  4. The project is configured in Release mode, qmake is successfully run, right-click the project to rebuild. Possible errors are:
    Syntax error: identifier “IValue”…
    change the codes in #include \<torch/torch.h> to:

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    #undef slots
    #include <torch/torch.h>
    #define slots Q_SLOTS

if /libtorch/include/ATen/core/ivalue.h and IValue_init.h throw errors, comment the following three lines

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/// \cond DOXYGEN_CANNOT_HANDLE_CONSTRUCTORS_WITH_MACROS_SO_EXCLUDE_THIS_LINE_FROM_DOXYGEN
C10_DEPRECATED_MESSAGE("IValues based on std::vector<T> are potentially slow and deprecated. Please use c10::List<T> instead.")
/// \endcond

  1. The main.cpp for testing：
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    #include "mainwindow.h"
    #include<opencv2/opencv.hpp>
    #include <QApplication>
    #include<iostream>
    #undef slots
    #include<torch/script.h>
    #include<torch/torch.h>
    #define slots Q_SLOTS

    class ConvReluBnImpl : public torch::nn::Module {
    public:
        ConvReluBnImpl(int input_channel=3, int output_channel=64, int kernel_size = 3);
        torch::Tensor forward(torch::Tensor x);
    private:
        // Declare layers
        torch::nn::Conv2d conv{ nullptr };
        torch::nn::BatchNorm2d bn{ nullptr };
    };
    TORCH_MODULE(ConvReluBn);

    ConvReluBnImpl::ConvReluBnImpl(int input_channel, int output_channel, int kernel_size) {
        conv = register_module("conv", torch::nn::Conv2d(torch::nn::Conv2dOptions(input_channel, output_channel, kernel_size).padding(1)));
        bn = register_module("bn", torch::nn::BatchNorm2d(output_channel));

    }

    torch::Tensor ConvReluBnImpl::forward(torch::Tensor x) {
        x = torch::relu(conv->forward(x));
        x = bn(x);
        return x;
    }

    int main(int argc, char *argv[])
    {
        //test torch
        auto device = torch::Device(torch::kCUDA);
        auto model = ConvReluBn(3,4,3);
        model->to(device);
        auto input = torch::zeros({1,3,12,12},torch::kFloat).to(device);
        auto output = model->forward(input);
        std::cout<<output.sizes()<<std::endl;

        //test opencv
        cv::Mat image = cv::imread("C:\\Users\\Administrator\\Pictures\\1.jpg");
        cv::Mat M(200, 200, CV_8UC3, cv::Scalar(0, 0, 255));
        if(!M.data)
            return 0;
        cv::imshow("fff",image);
        cv::imshow("ddd",M);
        cv::waitKey(0);
        cv::destroyAllWindows();
        //test qt
        QApplication a(argc, argv);
        MainWindow w;
        w.show();
        return a.exec();
    }