linux C++ onnxruntime yolov8 视频检测Demo

linux C++ onnxruntime yolov8 视频检测Demo

目录

项目目录

效果

​编辑CMakeLists.txt

代码 

下载

项目目录

效果

./yolov8_demo --help

./yolov8_demo -c=2 -p=true

./yolov8_demo -c=1 -s=true

CMakeLists.txt

  1. # cmake needs this line
  2. cmake_minimum_required(VERSION 3.0)
  3.  
  4. # Define project name
  5. project(yolov8_demo)
  6.  
  7. # Release模式下的编译指令
  8. # SET(CMAKE_BUILD_TYPE "Release")
  9. # set(CMAKE_C_FLAGS_RELEASE "${CMAKE_C_FLAGS_RELEASE} -s")
  10. # set(CMAKE_CXX_FLAGS_RELEASE "${CMAKE_CXX_FLAGS_RELEASE} -std=c++17 -pthread -Wall -Wl")
  11.  
  12. # Debug模式下的编译指令
  13. SET(CMAKE_BUILD_TYPE "Debug")
  14. set(CMAKE_C_FLAGS_RELEASE "${CMAKE_C_FLAGS_DEBUG}")
  15. set(CMAKE_CXX_FLAGS_DEBUG "${CMAKE_CXX_FLAGS_DEBUG} -std=c++17 -pthread") 
  16.  
  17. set(OpenCV_LIBS opencv_videoio opencv_imgcodecs opencv_imgproc opencv_core opencv_dnn opencv_highgui)
  18.  
  19. include_directories(
  20.     /usr/local/include/opencv4
  21.     ${PROJECT_SOURCE_DIR}/include
  22.     ${PROJECT_SOURCE_DIR}/include/onnxruntime
  23. )
  24.  
  25. link_directories(
  26.     ${PROJECT_SOURCE_DIR}/lib/onnxruntime   # 第三方动态库文件
  27.     /usr/local/lib/
  28. )
  29.  
  30. #递归指定源码的路径
  31. file(GLOB_RECURSE SRCS ${PROJECT_SOURCE_DIR}/src/*.cpp)
  32.  
  33. # Declare the executable target built from your sources
  34. add_executable(yolov8_demo ${SRCS})
  35.  
  36. # Link your application with OpenCV libraries
  37. target_link_libraries(yolov8_demo 
  38. -lonnxruntime
  39. ${OpenCV_LIBS}
  40. )

代码 

main.cpp

#include <opencv2/core.hpp>

#include

#include

#include

#include

#include

#include

int VideoDet(int index, bool showDet, bool useGPU, bool printPerStepInfo)

{

    size_t threadId = static_cast(syscall(SYS_gettid));

    // std::cout << "index:" << index << " thread id: " << threadId << std::endl;

    cv::VideoCapture capture("./test/test_car_person_1080P.mp4");

    // 检查视频是否成功打开

    if (!capture.isOpened())

    {

        std::cout << "无法读取视频文件" << std::endl;

        return -1;

    }

    int frameCount = capture.get(cv::CAP_PROP_FRAME_COUNT); // 获取视频帧数

    double fps = capture.get(cv::CAP_PROP_FPS);             // 获取帧率

    int delay = int(1000 / fps);                            // 根据帧率计算帧间间隔时间

    // delay=1;

    std::string model_path = "./models/yolov8n.onnx";

    std::string lable_path = "./models/lable.txt";

    int GPUCount = 2;

    int device_id = 0;

    if (index >= GPUCount)

    {

        device_id = index % GPUCount;

    }

    else

    {

        device_id = index;

    }

    // device_id=0;

    YoloV8 yoloV8(model_path, lable_path, useGPU, device_id);

    yoloV8.index = index;

    yoloV8.threadId = threadId;

    yoloV8.videoFps = fps;

    yoloV8.frameCount = frameCount;

    // std::cout << "device_id:" << yoloV8.device_id << std::endl;

    // vector detectionResult;

    // Mat frame=cv::imread("../test/dog.jpg");

    // yoloV8.Detect(frame, detectionResult);

    // std::cout << "detectionResult size:" << detectionResult.size() << std::endl;

    string winname = "detectionResult-" + std::to_string(index);

    while (true)

    {

        double start = (double)cv::getTickCount();

        delay = int(1000 / fps);

        Mat frame;

        bool success = capture.read(frame); // 读取一帧数据

        // 检查是否成功读取帧

        if (!success)

        {

            std::cout << "index:" << index << ",读取完毕" << std::endl;

            yoloV8.PrintAvgCostTime();

            break;

        }

        vector detectionResult;

        yoloV8.Detect(frame, detectionResult);

        // std::cout <<"index:"<

        yoloV8.detectionResultSize = detectionResult.size();

        if (printPerStepInfo)

        {

            yoloV8.PrintCostTime();

            yoloV8.PrintAvgCostTime();

        }

        if (showDet)

        {

            yoloV8.Draw(frame, detectionResult);

            imshow(winname, frame);

            double costTime = ((double)getTickCount() - start) / getTickFrequency();

            delay = delay - costTime;

            if (delay <= 0)

            {

                delay = 1;

            }

            if (waitKey(delay) == 27) // 通过按下ESC键退出循环

            {

                break;

            }

        }

    }

    capture.release(); // 释放视频对象

    if (showDet)

    {

        cv::destroyWindow(winname);

    }

    return 0;

}

int main(int argc, char *const argv[])

{

    int threadCount = 1;

    bool showDet = false;

    bool useGPU = false;

    bool printPerStepInfo = true;

    const char *keys ="{h help                || print this message}"

        "{c threadCount         | 1     | run thread number}"

        "{s showDet             | false | show detection result}"

        "{g useGPU              | false | use GPU}"

        "{p printPerStepInfo    | false | print per Step Info}";

    cv::CommandLineParser parser(argc, argv, keys);

    if(parser.has("help"))

    {

        parser.about("YoloV8 demo v1.0.0");

        parser.printMessage();

        return 0;

    }

    threadCount=parser.get("threadCount");

    showDet=parser.get("showDet");

    useGPU=parser.get("useGPU");

    printPerStepInfo=parser.get("printPerStepInfo");

    std::cout << std::boolalpha;

    std::cout << "threadCount:" << threadCount << ",showDet:" << showDet<< ",useGPU:" << useGPU << ",printPerStepInfo:" << printPerStepInfo << std::endl;

    for (size_t i = 0; i < threadCount; i++)

    {

        std::thread thread(VideoDet, i, showDet, useGPU, printPerStepInfo);

        thread.detach();

    }

    while (true)

    {

        sleep(100);

    }

    return 0;

}

  1. #include <opencv2/core.hpp>
  2. #include <opencv2/highgui.hpp>
  3. #include <iostream>
  4. #include <YoloV8.hpp>
  5. #include <unistd.h>
  6. #include <sys/syscall.h>
  7. #include <thread>
  8.  
  9. int VideoDet(int index, bool showDet, bool useGPU, bool printPerStepInfo)
  10. {
  11.     size_t threadId = static_cast<size_t>(syscall(SYS_gettid));
  12.     // std::cout << "index:" << index << " thread id: " << threadId << std::endl;
  13.  
  14.     cv::VideoCapture capture("./test/test_car_person_1080P.mp4");
  15.  
  16.     // 检查视频是否成功打开
  17.     if (!capture.isOpened())
  18.     {
  19.         std::cout << "无法读取视频文件" << std::endl;
  20.         return -1;
  21.     }
  22.  
  23.     int frameCount = capture.get(cv::CAP_PROP_FRAME_COUNT); // 获取视频帧数
  24.     double fps = capture.get(cv::CAP_PROP_FPS);             // 获取帧率
  25.     int delay = int(1000 / fps);                            // 根据帧率计算帧间间隔时间
  26.     // delay=1;
  27.  
  28.     std::string model_path = "./models/yolov8n.onnx";
  29.     std::string lable_path = "./models/lable.txt";
  30.  
  31.     int GPUCount = 2;
  32.     int device_id = 0;
  33.     if (index >= GPUCount)
  34.     {
  35.         device_id = index % GPUCount;
  36.     }
  37.     else
  38.     {
  39.         device_id = index;
  40.     }
  41.  
  42.     // device_id=0;
  43.  
  44.     YoloV8 yoloV8(model_path, lable_path, useGPU, device_id);
  45.  
  46.     yoloV8.index = index;
  47.     yoloV8.threadId = threadId;
  48.     yoloV8.videoFps = fps;
  49.     yoloV8.frameCount = frameCount;
  50.  
  51.     // std::cout << "device_id:" << yoloV8.device_id << std::endl;
  52.  
  53.     // vector<DetectionResult> detectionResult;
  54.     // Mat frame=cv::imread("../test/dog.jpg");
  55.     // yoloV8.Detect(frame, detectionResult);
  56.     // std::cout << "detectionResult size:" << detectionResult.size() << std::endl;
  57.  
  58.     string winname = "detectionResult-" + std::to_string(index);
  59.  
  60.     while (true)
  61.     {
  62.  
  63.         double start = (double)cv::getTickCount();
  64.         delay = int(1000 / fps);
  65.  
  66.         Mat frame;
  67.         bool success = capture.read(frame); // 读取一帧数据
  68.  
  69.         // 检查是否成功读取帧
  70.         if (!success)
  71.         {
  72.             std::cout << "index:" << index << ",读取完毕" << std::endl;
  73.             yoloV8.PrintAvgCostTime();
  74.             break;
  75.         }
  76.  
  77.         vector<DetectionResult> detectionResult;
  78.  
  79.         yoloV8.Detect(frame, detectionResult);
  80.  
  81.         // std::cout <<"index:"<<index<< " thread id: " << threadId << " detectionResult size: " << detectionResult.size() << std::endl;
  82.         yoloV8.detectionResultSize = detectionResult.size();
  83.  
  84.         if (printPerStepInfo)
  85.         {
  86.             yoloV8.PrintCostTime();
  87.             yoloV8.PrintAvgCostTime();
  88.         }
  89.  
  90.         if (showDet)
  91.         {
  92.             yoloV8.Draw(frame, detectionResult);
  93.  
  94.             imshow(winname, frame);
  95.  
  96.             double costTime = ((double)getTickCount() - start) / getTickFrequency();
  97.             delay = delay - costTime;
  98.             if (delay <= 0)
  99.             {
  100.                 delay = 1;
  101.             }
  102.  
  103.             if (waitKey(delay) == 27) // 通过按下ESC键退出循环
  104.             {
  105.                 break;
  106.             }
  107.         }
  108.     }
  109.  
  110.     capture.release(); // 释放视频对象
  111.  
  112.     if (showDet)
  113.     {
  114.         cv::destroyWindow(winname);
  115.     }
  116.  
  117.     return 0;
  118. }
  119.  
  120. int main(int argc, char *const argv[])
  121. {
  122.     int threadCount = 1;
  123.     bool showDet = false;
  124.     bool useGPU = false;
  125.     bool printPerStepInfo = true;
  126.  
  127.     const char *keys ="{h help                || print this message}"
  128.         "{c threadCount         | 1     | run thread number}"
  129.         "{s showDet             | false | show detection result}"
  130.         "{g useGPU              | false | use GPU}"
  131.         "{p printPerStepInfo    | false | print per Step Info}";
  132.  
  133.     cv::CommandLineParser parser(argc, argv, keys);
  134.  
  135.     if(parser.has("help"))
  136.     {
  137.         parser.about("YoloV8 demo v1.0.0");
  138.         parser.printMessage();
  139.         return 0;
  140.     }
  141.  
  142.     threadCount=parser.get<int>("threadCount");
  143.     showDet=parser.get<bool>("showDet");
  144.     useGPU=parser.get<bool>("useGPU");
  145.     printPerStepInfo=parser.get<bool>("printPerStepInfo");
  146.  
  147.     std::cout << std::boolalpha;
  148.     std::cout << "threadCount:" << threadCount << ",showDet:" << showDet<< ",useGPU:" << useGPU << ",printPerStepInfo:" << printPerStepInfo << std::endl;
  149.  
  150.     for (size_t i = 0; i < threadCount; i++)
  151.     {
  152.         std::thread thread(VideoDet, i, showDet, useGPU, printPerStepInfo);
  153.         thread.detach();
  154.     }
  155.  
  156.     while (true)
  157.     {
  158.         sleep(100);
  159.     }
  160.  
  161.     return 0;
  162. }

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