使用 C++ 编写支持多模型调用的动态连接库，将 yolov5的ONNX 模型加载进来，并编译生成dll与注释供其他程序使用

首先，要使用 C++ 编写支持多模型调用的动态连接库，需要使用一些库，比如 OpenCV 和 ONNX Runtime。以下是一个基本的示例代码：

#include <iostream>
#include <vector>
#include <opencv2/opencv.hpp>
#include <onnxruntime_cxx_api.h>

class YOLOv5Detector {
public:
    YOLOv5Detector(const std::string& model_path) {
        // Initialize ONNX Runtime
        Ort::Env env(ORT_LOGGING_LEVEL_WARNING, "test");
        Ort::SessionOptions session_options;
        session_options.SetIntraOpNumThreads(1);
        session_options.SetGraphOptimizationLevel(GraphOptimizationLevel::ORT_ENABLE_BASIC);
        session_ = std::make_unique<Ort::Session>(env, model_path, session_options);

        // Get model input and output information
        auto input_info = session_.get()->GetInputTypeInfo(0);
        auto output_info = session_.get()->GetOutputTypeInfo(0);
        input_name_ = input_info.GetOnnxName();
        output_name_ = output_info.GetOnnxName();
        input_dims_ = input_info.GetTensorTypeAndShapeInfo().GetShape();
        output_dims_ = output_info.GetTensorTypeAndShapeInfo().GetShape();
    }

    std::vector<cv::Rect> detect(const cv::Mat& image) {
        // Preprocess image
        cv::Mat resized_image;
        cv::resize(image, resized_image, cv::Size(input_dims_[3], input_dims_[2]));
        cv::Mat float_image;
        resized_image.convertTo(float_image, CV_32FC3, 1.0 / 255.0);
        std::vector<float> input_data(float_image.ptr<float>(), float_image.ptr<float>() + float_image.total() * float_image.channels());

        // Initialize input and output tensors
        Ort::MemoryInfo memory_info = Ort::MemoryInfo::CreateCpu(OrtDeviceAllocator, OrtMemTypeCPU);
        std::vector<int64_t> input_shape = {1, 3, input_dims_[2], input_dims_[3]};
        std::vector<int64_t> output_shape = {1, static_cast<int64_t>(output_dims_[1]), static_cast<int64_t>(output_dims_[2]), static_cast<int64_t>(output_dims_[3])};
        Ort::Value input_tensor = Ort::Value::CreateTensor<float>(memory_info, input_data.data(), input_data.size(), input_shape.data(), input_shape.size());
        Ort::Value output_tensor = Ort::Value::CreateTensor<float>(memory_info, nullptr, output_shape.data(), output_shape.size());

        // Run inference
        std::vector<const char*> input_names = {input_name_.c_str()};
        std::vector<const char*> output_names = {output_name_.c_str()};
        session_.get()->Run(Ort::RunOptions{nullptr}, input_names.data(), &input_tensor, 1, output_names.data(), 1, &output_tensor);

        // Postprocess output
        const float* output_data = output_tensor.GetTensorMutableData<float>();
        std::vector<cv::Rect> detected_rects;
        for (int i = 0; i < output_dims_[1]; i++) {
            float score = output_data[5 * i + 4];
            if (score >= 0.5) {
                float x_center = output_data[5 * i];
                float y_center = output_data[5 * i + 1];
                float width = output_data[5 * i + 2];
                float height = output_data[5 * i + 3];
                int x_left = static_cast<int>((x_center - width / 2) * image.cols);
                int y_top = static_cast<int>((y_center - height / 2) * image.rows);
                int rect_width = static_cast<int>(width * image.cols);
                int rect_height = static_cast<int>(height * image.rows);
                detected_rects.emplace_back(x_left, y_top, rect_width, rect_height);
            }
        }

        return detected_rects;
    }

private:
    std::unique_ptr<Ort::Session> session_;
    std::string input_name_;
    std::string output_name_;
    std::vector<int64_t> input_dims_;
    std::vector<int64_t> output_dims_;
};

此代码创建了一个名为 `YOLOv5Detector` 的类，该类使用 ONNX Runtime 加载 YOLOv5 模型，并在给定图像上运行检测。检测结果是矩形的列表，表示在图像中检测到的对象。

要将此类编译为 DLL，您需要使用 Visual Studio 或其他支持 Windows DLL 编译的 IDE。以下是一个示例项目文件：

<?xml version="1.0" encoding="utf-8"?>
<Project DefaultTargets="Build" ToolsVersion="15.0" xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
  <ItemGroup Label="ProjectConfigurations">
    <ProjectConfiguration Include="Debug|Win32">
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      <Platform>Win32</Platform>
    </ProjectConfiguration>
    <ProjectConfiguration Include="Release|Win32">
      <Configuration>Release</Configuration>
      <Platform>Win32</Platform>
    </ProjectConfiguration>
  </ItemGroup>
  <PropertyGroup Label="Globals">
    <VCProjectVersion>16.0</VCProjectVersion>
    <ProjectGuid>{GUID}</ProjectGuid>
    <Keyword>Win32Proj</Keyword>
    <RootNamespace>YOLOv5Detector</RootNamespace>
    <WindowsTargetPlatformVersion>10.0.19041.0</WindowsTargetPlatformVersion>
  </PropertyGroup>
  <Import Project="$(VCTargetsPath)\Microsoft.Cpp.Default.props" />
  <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'" Label="Configuration">
    <ConfigurationType>DynamicLibrary</ConfigurationType>
    <UseDebugLibraries>true</UseDebugLibraries>
    <PlatformToolset>v142</PlatformToolset>
    <CharacterSet>Unicode</CharacterSet>
    <CLRSupport>true</CLRSupport>
    <WholeProgramOptimization>false</WholeProgramOptimization>
    <UseOfMfc>false</UseOfMfc>
  </PropertyGroup>
  <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|Win32'" Label="Configuration">
    <ConfigurationType>DynamicLibrary</ConfigurationType>
    <UseDebugLibraries>false</UseDebugLibraries>
    <PlatformToolset>v142</PlatformToolset>
    <CharacterSet>Unicode</CharacterSet>
    <CLRSupport>true</CLRSupport>
    <WholeProgramOptimization>false</WholeProgramOptimization>
    <UseOfMfc>false</UseOfMfc>
  </PropertyGroup>
  <Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
  <ImportGroup Label="ExtensionSettings">
  </ImportGroup>
  <ImportGroup Label="Shared">
  </ImportGroup>
  <ImportGroup Label="PropertySheets" Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'">
    <Import Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" />
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  <ImportGroup Label="PropertySheets" Condition="'$(Configuration)|$(Platform)'=='Release|Win32'">
    <Import Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" />
  </ImportGroup>
  <PropertyGroup Label="UserMacros" />
  <ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'">
    <ClCompile>
      <Optimization>Disabled</Optimization>
      <AdditionalIncludeDirectories>$(OPENCV_DIR)\include;$(ONNXRUNTIME_DIR)\include;</AdditionalIncludeDirectories>
      <PreprocessorDefinitions>_DEBUG;_CRT_SECURE_NO_WARNINGS;WIN32;_WINDOWS;%(PreprocessorDefinitions)</PreprocessorDefinitions>
      <MinimalRebuild>false</MinimalRebuild>
      <BasicRuntimeChecks>EnableFastChecks</BasicRuntimeChecks>
      <RuntimeLibrary>MultiThreadedDebugDLL</RuntimeLibrary>
      <PrecompiledHeader>Create</PrecompiledHeader>
      <PrecompiledHeaderFile>pch.h</PrecompiledHeaderFile>
      <PrecompiledHeaderOutputFile>$(IntDir)\$(TargetName).pch</PrecompiledHeaderOutputFile>
      <WarningLevel>Level3</WarningLevel>
      <DebugInformationFormat>ProgramDatabase</DebugInformationFormat>
      <CompileAs>Default</CompileAs>
      <InlineFunctionExpansion>AnySuitable</InlineFunctionExpansion>
      <EnableEnhancedInstructionSet>AdvancedVectorExtensions2</EnableEnhancedInstructionSet>
      <TreatWarningAsError>true</TreatWarningAsError>
      <LanguageStandard>c++17</LanguageStandard>
    </ClCompile>
    <Link>
      <AdditionalDependencies>onnxruntime.lib;opencv_world450d.lib;%(AdditionalDependencies)</AdditionalDependencies>
      <AdditionalLibraryDirectories>$(OPENCV_DIR)\x64\vc15\lib;$(ONNXRUNTIME_DIR)\lib;%(AdditionalLibraryDirectories)</AdditionalLibraryDirectories>
      <GenerateDebugInformation>true</GenerateDebugInformation>
      <SubSystem>Windows</SubSystem>
      <TargetMachine>MachineX64</TargetMachine>
    </Link>
  </ItemDefinitionGroup>
  <ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Release|Win32'">
    <ClCompile>
      <Optimization>MaxSpeed</Optimization>
      <FunctionLevelLinking>true</FunctionLevelLinking>
      <IntrinsicFunctions>true</IntrinsicFunctions>
      <PreprocessorDefinitions>NDEBUG;_CRT_SECURE_NO_WARNINGS;WIN32;_WINDOWS;%(PreprocessorDefinitions)</PreprocessorDefinitions>
      <MinimalRebuild>false</MinimalRebuild>
      <RuntimeLibrary>MultiThreadedDLL</RuntimeLibrary>
      <PrecompiledHeader>Create</PrecompiledHeader>
      <PrecompiledHeaderFile>pch.h</PrecompiledHeaderFile>
      <PrecompiledHeaderOutputFile>$(IntDir)\$(TargetName).pch</PrecompiledHeaderOutputFile>
      <WarningLevel>Level3</WarningLevel>
      <DebugInformationFormat>ProgramDatabase</DebugInformationFormat>
      <CompileAs>Default</CompileAs>
      <InlineFunctionExpansion>AnySuitable</InlineFunctionExpansion>
      <EnableEnhancedInstructionSet>AdvancedVectorExtensions2</EnableEnhancedInstructionSet>
      <TreatWarningAsError>true</TreatWarningAsError>
      <LanguageStandard>c++17</LanguageStandard>
    </ClCompile>
    <Link>
      <AdditionalDependencies>onnxruntime.lib;opencv_world450.lib;%(AdditionalDependencies)</AdditionalDependencies>
      <AdditionalLibraryDirectories>$(OPENCV_DIR)\x64\vc15\lib;$(ONNXRUNTIME_DIR)\lib;%(AdditionalLibraryDirectories)</AdditionalLibraryDirectories>
      <GenerateDebugInformation>true</GenerateDebugInformation>
      <SubSystem>Windows</SubSystem>
      <TargetMachine>MachineX64</TargetMachine>
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  </ItemDefinitionGroup>
  <ItemGroup>
    <ClCompile Include="detector.cpp" />
    <ClCompile Include="pch.cpp">
      <PrecompiledHeader Condition=" '$(Configuration)|$(Platform)'=='Debug|Win32' ">Create</PrecompiledHeader>
      <PrecompiledHeader Condition=" '$(Configuration)|$(Platform)'=='Release|Win32' ">Create</PrecompiledHeader>
    </ClCompile>
    <ClInclude Include="detector.h" />
    <ClInclude Include="pch.h" />
  </ItemGroup>
  <Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
  <ImportGroup Label="ExtensionTargets">
  </ImportGroup>
</Project>

将此项目文件保存为 `YOLOv5Detector.vcxproj`，然后使用 Visual Studio 打开该文件并构建解决方案。这将生成一个名为 `YOLOv5Detector.dll` 的 DLL 文件。您可以在其他 C++ 程序中使用此 DLL 文件，并调用 `YOLOv5Detector` 类来运行目标检测算法。