C# YoloV8 模型效果验证工具(OnnxRuntime+ByteTrack推理)

C# YoloV8 模型效果验证工具(OnnxRuntime+ByteTrack推理)

目录

效果

项目

代码

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效果

模型效果验证工具

项目

代码

using ByteTrack;
using OpenCvSharp;
using System;
using System.Collections.Generic;
using System.Diagnostics;
using System.Drawing;
using System.Drawing.Imaging;
using System.Threading;
using System.Threading.Tasks;
using System.Windows.Forms;


namespace C__yolov8_OnnxRuntime_ByteTrack_Demo
{
    public partial class Form2 : Form
    {
        public Form2()
        {
            InitializeComponent();
        }

        string imgFilter = "图片|*.bmp;*.jpg;*.jpeg;*.tiff;*.tiff;*.png";

        YoloV8 yoloV8;
        Mat image;

        string image_path = "";
        string model_path;

        string video_path = "";
        string videoFilter = "视频|*.mp4;*.avi;*.dav";
        VideoCapture vcapture;
        VideoWriter vwriter;
        bool saveDetVideo = false;
        ByteTracker tracker;

        ///


        /// 单图推理
        ///
        ///
        ///
        private void button2_Click(object sender, EventArgs e)
        {

            if (image_path == "")
            {
                return;
            }

            button2.Enabled = false;
            pictureBox2.Image = null;
            textBox1.Text = "";

            Application.DoEvents();

            image = new Mat(image_path);

            List detResults = yoloV8.Detect(image);

            //绘制结果
            Mat result_image = image.Clone();
            foreach (DetectionResult r in detResults)
            {
                string info = $"{r.Class}:{r.Confidence:P0}";
                //绘制
                Cv2.PutText(result_image, info, new OpenCvSharp.Point(r.Rect.TopLeft.X, r.Rect.TopLeft.Y - 10), HersheyFonts.HersheySimplex, 1, Scalar.Red, 2);
                Cv2.Rectangle(result_image, r.Rect, Scalar.Red, thickness: 2);

            }

            if (pictureBox2.Image != null)
            {
                pictureBox2.Image.Dispose();
            }
            pictureBox2.Image = new Bitmap(result_image.ToMemoryStream());
            textBox1.Text = yoloV8.DetectTime();

            button2.Enabled = true;

        }

        ///


        /// 窗体加载，初始化
        ///
        ///
        ///
        private void Form1_Load(object sender, EventArgs e)
        {
            image_path = "test/dog.jpg";
            pictureBox1.Image = new Bitmap(image_path);

            model_path = "model/yolov8n.onnx";

            yoloV8 = new YoloV8(model_path, "model/lable.txt");
        }

        ///


        /// 选择图片
        ///
        ///
        ///
        private void button1_Click_1(object sender, EventArgs e)
        {
            OpenFileDialog ofd = new OpenFileDialog();
            ofd.Filter = imgFilter;
            if (ofd.ShowDialog() != DialogResult.OK) return;

            pictureBox1.Image = null;

            image_path = ofd.FileName;
            pictureBox1.Image = new Bitmap(image_path);

            textBox1.Text = "";
            pictureBox2.Image = null;
        }

        ///


        /// 选择视频
        ///
        ///
        ///
        private void button4_Click(object sender, EventArgs e)
        {
            OpenFileDialog ofd = new OpenFileDialog();
            ofd.Filter = videoFilter;
            ofd.InitialDirectory = Application.StartupPath + "\\test";
            if (ofd.ShowDialog() != DialogResult.OK) return;

            video_path = ofd.FileName;

            textBox1.Text = video_path;
            //pictureBox1.Image = null;
            //pictureBox2.Image = null;

            //button3_Click(null, null);

        }

        ///


        /// 视频推理
        ///
        ///
        ///
        private void button3_Click(object sender, EventArgs e)
        {
            if (video_path == "")
            {
                MessageBox.Show("请先选择视频！");
                return;
            }

            textBox1.Text = "开始检测";

            Application.DoEvents();

            Thread thread = new Thread(new ThreadStart(VideoDetection));

            thread.Start();
            thread.Join();

            textBox1.Text = "检测完成！";
        }

        void VideoDetection()
        {
            vcapture = new VideoCapture(video_path);
            if (!vcapture.IsOpened())
            {
                MessageBox.Show("打开视频文件失败");
                return;
            }

            tracker = new ByteTracker((int)vcapture.Fps, 200);

            Mat frame = new Mat();
            List detResults;

            // 获取视频的fps
            double videoFps = vcapture.Get(VideoCaptureProperties.Fps);
            // 计算等待时间（毫秒）
            int delay = (int)(1000 / videoFps);
            Stopwatch _stopwatch = new Stopwatch();

            if (checkBox1.Checked)
            {
                vwriter = new VideoWriter("out.mp4", FourCC.X264, vcapture.Fps, new OpenCvSharp.Size(vcapture.FrameWidth, vcapture.FrameHeight));
                saveDetVideo = true;
            }
            else
            {
                saveDetVideo = false;
            }

            Cv2.NamedWindow("DetectionResult 按下ESC，退出", WindowFlags.Normal);
            Cv2.ResizeWindow("DetectionResult 按下ESC，退出", vcapture.FrameWidth / 2, vcapture.FrameHeight / 2);

            while (vcapture.Read(frame))
            {
                if (frame.Empty())
                {
                    MessageBox.Show("读取失败");
                    return;
                }
                Mat mat_temp = frame.Clone();
                _stopwatch.Restart();

                delay = (int)(1000 / videoFps);

                detResults = yoloV8.Detect(frame);

                //绘制结果
                //foreach (DetectionResult r in detResults)
                //{
                //    Cv2.PutText(frame, $"{r.Class}:{r.Confidence:P0}", new OpenCvSharp.Point(r.Rect.TopLeft.X, r.Rect.TopLeft.Y - 10), HersheyFonts.HersheySimplex, 1, Scalar.Red, 2);
                //    Cv2.Rectangle(frame, r.Rect, Scalar.Red, thickness: 2);
                //}

                Cv2.PutText(frame, "preprocessTime:" + yoloV8.preprocessTime.ToString("F2") + "ms", new OpenCvSharp.Point(10, 30), HersheyFonts.HersheySimplex, 1, Scalar.Red, 2);
                Cv2.PutText(frame, "inferTime:" + yoloV8.inferTime.ToString("F2") + "ms", new OpenCvSharp.Point(10, 70), HersheyFonts.HersheySimplex, 1, Scalar.Red, 2);
                Cv2.PutText(frame, "postprocessTime:" + yoloV8.postprocessTime.ToString("F2") + "ms", new OpenCvSharp.Point(10, 110), HersheyFonts.HersheySimplex, 1, Scalar.Red, 2);
                Cv2.PutText(frame, "totalTime:" + yoloV8.totalTime.ToString("F2") + "ms", new OpenCvSharp.Point(10, 150), HersheyFonts.HersheySimplex, 1, Scalar.Red, 2);
                Cv2.PutText(frame, "video fps:" + videoFps.ToString("F2"), new OpenCvSharp.Point(10, 190), HersheyFonts.HersheySimplex, 1, Scalar.Red, 2);
                Cv2.PutText(frame, "det fps:" + yoloV8.detFps.ToString("F2"), new OpenCvSharp.Point(10, 230), HersheyFonts.HersheySimplex, 1, Scalar.Red, 2);

                List track = new List();
                Track temp;
                foreach (DetectionResult r in detResults)
                {
                    RectBox _box = new RectBox(r.Rect.X, r.Rect.Y, r.Rect.Width, r.Rect.Height);
                    temp = new Track(_box, r.Confidence, ("label", r.ClassId), ("name", r.Class));
                    track.Add(temp);
                }

                var trackOutputs = tracker.Update(track);

                foreach (var t in trackOutputs)
                {
                    int x = (int)t.RectBox.X;
                    int y = (int)t.RectBox.Y;
                    int width = (int)t.RectBox.Width;
                    int height = (int)t.RectBox.Height;

                    if (x < 0)
                    {
                        x = 0;
                    }

                    if (y < 0)
                    {
                        y = 0;
                    }

                    if (x + width > mat_temp.Width)
                    {
                        width = mat_temp.Width - x;
                    }

                    if (y + height > mat_temp.Height)
                    {
                        height = mat_temp.Height - y;
                    }

                    Rect rect = new Rect(x, y, width, height);

                    string txt = $"{t["name"]}-{t.TrackId}:{t.Score:P0}";
                    
                    //if (t["name"].ToString() != "Plate" && t["name"].ToString() != "Person")
                    //{
                    //    Mat mat_car = new Mat(mat_temp, rect);
                    //    KeyValuePair cls = yoloV8_Cls.Detect(mat_car);
                    //    mat_car.Dispose();
                    //    txt += $" {cls.Key}:{cls.Value:P0}";
                    //}

                    //string txt = $"{t["name"]}-{t.TrackId}";
                    Cv2.PutText(frame, txt, new OpenCvSharp.Point(rect.TopLeft.X, rect.TopLeft.Y - 10), HersheyFonts.HersheySimplex, 1, Scalar.Red, 2);
                    Cv2.Rectangle(frame, rect, Scalar.Red, thickness: 2);
                }
                mat_temp.Dispose();


                if (saveDetVideo)
                {
                    vwriter.Write(frame);
                }

                Cv2.ImShow("DetectionResult 按下ESC，退出", frame);

                // for test
                // delay = 1;
                delay = (int)(delay - _stopwatch.ElapsedMilliseconds);
                if (delay <= 0)
                {
                    delay = 1;
                }
                //Console.WriteLine("delay:" + delay.ToString()) ;
                if (Cv2.WaitKey(delay) == 27 || Cv2.GetWindowProperty("DetectionResult 按下ESC，退出", WindowPropertyFlags.Visible) < 1.0)
                {
                    Cv2.DestroyAllWindows();
                    vcapture.Release();
                    break;
                }
            }

            Cv2.DestroyAllWindows();
            vcapture.Release();
            if (saveDetVideo)
            {
                vwriter.Release();
            }

        }

        string model_path1 = "";
        string model_path2 = "";
        string onnxFilter = "onnx模型|*.onnx;";

        private void button5_Click(object sender, EventArgs e)
        {
            if (video_path == "")
            {
                MessageBox.Show("请先选择视频！");
                return;
            }

            if (model_path1 == "")
            {
                MessageBox.Show("选择模型1");
                OpenFileDialog ofd = new OpenFileDialog();
                ofd.Filter = onnxFilter;
                ofd.InitialDirectory = Application.StartupPath + "\\model";
                if (ofd.ShowDialog() != DialogResult.OK) return;
                model_path1 = ofd.FileName;
            }

            if (model_path2 == "")
            {
                MessageBox.Show("选择模型2");
                OpenFileDialog ofd1 = new OpenFileDialog();
                ofd1.Filter = onnxFilter;
                ofd1.InitialDirectory = Application.StartupPath + "\\model";
                if (ofd1.ShowDialog() != DialogResult.OK) return;
                model_path2 = ofd1.FileName;
            }

            textBox1.Text = "开始检测";
            Application.DoEvents();

            Task task = new Task(() =>
            {
                VideoCapture vcapture = new VideoCapture(video_path);
                if (!vcapture.IsOpened())
                {
                    MessageBox.Show("打开视频文件失败");
                    return;
                }

                YoloV8_Compare yoloV8 = new YoloV8_Compare(model_path1, model_path2, "model/lable.txt");

                Mat frame = new Mat();

                // 获取视频的fps
                double videoFps = vcapture.Get(VideoCaptureProperties.Fps);
                // 计算等待时间（毫秒）
                int delay = (int)(1000 / videoFps);
                Stopwatch _stopwatch = new Stopwatch();

                Cv2.NamedWindow("DetectionResult 按下ESC，退出", WindowFlags.Normal);
                Cv2.ResizeWindow("DetectionResult 按下ESC，退出", vcapture.FrameWidth, vcapture.FrameHeight / 2);

                while (vcapture.Read(frame))
                {
                    if (frame.Empty())
                    {
                        MessageBox.Show("读取失败");
                        return;
                    }

                    _stopwatch.Restart();

                    delay = (int)(1000 / videoFps);

                    Mat result = yoloV8.Detect(frame, videoFps.ToString("F2"));

                    Cv2.ImShow("DetectionResult 按下ESC，退出", result);

                    // for test
                    // delay = 1;
                    delay = (int)(delay - _stopwatch.ElapsedMilliseconds);
                    if (delay <= 0)
                    {
                        delay = 1;
                    }
                    //Console.WriteLine("delay:" + delay.ToString()) ;
                    // 如果按下ESC或点击关闭，退出循环
                    if (Cv2.WaitKey(delay) == 27 || Cv2.GetWindowProperty("DetectionResult 按下ESC，退出", WindowPropertyFlags.Visible) < 1.0)
                    {
                        Cv2.DestroyAllWindows();
                        vcapture.Release();
                        break;
                    }
                }

                textBox1.Invoke(new Action(() =>
                {
                    textBox1.Text = "检测结束！";

                }));

            });
            task.Start();

        }

        //保存
        SaveFileDialog sdf = new SaveFileDialog();
        private void button6_Click(object sender, EventArgs e)
        {
            if (pictureBox2.Image == null)
            {
                return;
            }
            Bitmap output = new Bitmap(pictureBox2.Image);
            sdf.Title = "保存";
            sdf.Filter = "Images (*.jpg)|*.jpg|Images (*.png)|*.png|Images (*.bmp)|*.bmp";
            if (sdf.ShowDialog() == DialogResult.OK)
            {
                switch (sdf.FilterIndex)
                {
                    case 1:
                        {
                            output.Save(sdf.FileName, ImageFormat.Jpeg);
                            break;
                        }
                    case 2:
                        {
                            output.Save(sdf.FileName, ImageFormat.Png);
                            break;
                        }
                    case 3:
                        {
                            output.Save(sdf.FileName, ImageFormat.Bmp);
                            break;
                        }
                }
                MessageBox.Show("保存成功，位置：" + sdf.FileName);
            }

        }

        ///


        /// 选择模型
        ///
        ///
        ///
        private void button7_Click(object sender, EventArgs e)
        {
            OpenFileDialog ofd = new OpenFileDialog();
            ofd.Filter = onnxFilter;
            ofd.InitialDirectory = Application.StartupPath + "\\model";
            if (ofd.ShowDialog() != DialogResult.OK) return;
            model_path = ofd.FileName;
            yoloV8 = new YoloV8(model_path, "model/lable.txt");

        }
    }

}

  1. using ByteTrack;
  2. using OpenCvSharp;
  3. using System;
  4. using System.Collections.Generic;
  5. using System.Diagnostics;
  6. using System.Drawing;
  7. using System.Drawing.Imaging;
  8. using System.Threading;
  9. using System.Threading.Tasks;
  10. using System.Windows.Forms;
  11.  
  12.  
  13. namespace C__yolov8_OnnxRuntime_ByteTrack_Demo
  14. {
  15.     public partial class Form2 : Form
  16.     {
  17.         public Form2()
  18.         {
  19.             InitializeComponent();
  20.         }
  21.  
  22.         string imgFilter = "图片|*.bmp;*.jpg;*.jpeg;*.tiff;*.tiff;*.png";
  23.  
  24.         YoloV8 yoloV8;
  25.         Mat image;
  26.  
  27.         string image_path = "";
  28.         string model_path;
  29.  
  30.         string video_path = "";
  31.         string videoFilter = "视频|*.mp4;*.avi;*.dav";
  32.         VideoCapture vcapture;
  33.         VideoWriter vwriter;
  34.         bool saveDetVideo = false;
  35.         ByteTracker tracker;
  36.  
  37.         /// <summary>
  38.         /// 单图推理
  39.         /// </summary>
  40.         /// <param name="sender"></param>
  41.         /// <param name="e"></param>
  42.         private void button2_Click(object sender, EventArgs e)
  43.         {
  44.  
  45.             if (image_path == "")
  46.             {
  47.                 return;
  48.             }
  49.  
  50.             button2.Enabled = false;
  51.             pictureBox2.Image = null;
  52.             textBox1.Text = "";
  53.  
  54.             Application.DoEvents();
  55.  
  56.             image = new Mat(image_path);
  57.  
  58.             List<DetectionResult> detResults = yoloV8.Detect(image);
  59.  
  60.             //绘制结果
  61.             Mat result_image = image.Clone();
  62.             foreach (DetectionResult r in detResults)
  63.             {
  64.                 string info = $"{r.Class}:{r.Confidence:P0}";
  65.                 //绘制
  66.                 Cv2.PutText(result_image, info, new OpenCvSharp.Point(r.Rect.TopLeft.X, r.Rect.TopLeft.Y - 10), HersheyFonts.HersheySimplex, 1, Scalar.Red, 2);
  67.                 Cv2.Rectangle(result_image, r.Rect, Scalar.Red, thickness: 2);
  68.  
  69.             }
  70.  
  71.             if (pictureBox2.Image != null)
  72.             {
  73.                 pictureBox2.Image.Dispose();
  74.             }
  75.             pictureBox2.Image = new Bitmap(result_image.ToMemoryStream());
  76.             textBox1.Text = yoloV8.DetectTime();
  77.  
  78.             button2.Enabled = true;
  79.  
  80.         }
  81.  
  82.         /// <summary>
  83.         /// 窗体加载，初始化
  84.         /// </summary>
  85.         /// <param name="sender"></param>
  86.         /// <param name="e"></param>
  87.         private void Form1_Load(object sender, EventArgs e)
  88.         {
  89.             image_path = "test/dog.jpg";
  90.             pictureBox1.Image = new Bitmap(image_path);
  91.  
  92.             model_path = "model/yolov8n.onnx";
  93.  
  94.             yoloV8 = new YoloV8(model_path, "model/lable.txt");
  95.         }
  96.  
  97.         /// <summary>
  98.         /// 选择图片
  99.         /// </summary>
  100.         /// <param name="sender"></param>
  101.         /// <param name="e"></param>
  102.         private void button1_Click_1(object sender, EventArgs e)
  103.         {
  104.             OpenFileDialog ofd = new OpenFileDialog();
  105.             ofd.Filter = imgFilter;
  106.             if (ofd.ShowDialog() != DialogResult.OK) return;
  107.  
  108.             pictureBox1.Image = null;
  109.  
  110.             image_path = ofd.FileName;
  111.             pictureBox1.Image = new Bitmap(image_path);
  112.  
  113.             textBox1.Text = "";
  114.             pictureBox2.Image = null;
  115.         }
  116.  
  117.         /// <summary>
  118.         /// 选择视频
  119.         /// </summary>
  120.         /// <param name="sender"></param>
  121.         /// <param name="e"></param>
  122.         private void button4_Click(object sender, EventArgs e)
  123.         {
  124.             OpenFileDialog ofd = new OpenFileDialog();
  125.             ofd.Filter = videoFilter;
  126.             ofd.InitialDirectory = Application.StartupPath + "\\test";
  127.             if (ofd.ShowDialog() != DialogResult.OK) return;
  128.  
  129.             video_path = ofd.FileName;
  130.  
  131.             textBox1.Text = video_path;
  132.             //pictureBox1.Image = null;
  133.             //pictureBox2.Image = null;
  134.  
  135.             //button3_Click(null, null);
  136.  
  137.         }
  138.  
  139.         /// <summary>
  140.         /// 视频推理
  141.         /// </summary>
  142.         /// <param name="sender"></param>
  143.         /// <param name="e"></param>
  144.         private void button3_Click(object sender, EventArgs e)
  145.         {
  146.             if (video_path == "")
  147.             {
  148.                 MessageBox.Show("请先选择视频！");
  149.                 return;
  150.             }
  151.  
  152.             textBox1.Text = "开始检测";
  153.  
  154.             Application.DoEvents();
  155.  
  156.             Thread thread = new Thread(new ThreadStart(VideoDetection));
  157.  
  158.             thread.Start();
  159.             thread.Join();
  160.  
  161.             textBox1.Text = "检测完成！";
  162.         }
  163.  
  164.         void VideoDetection()
  165.         {
  166.             vcapture = new VideoCapture(video_path);
  167.             if (!vcapture.IsOpened())
  168.             {
  169.                 MessageBox.Show("打开视频文件失败");
  170.                 return;
  171.             }
  172.  
  173.             tracker = new ByteTracker((int)vcapture.Fps, 200);
  174.  
  175.             Mat frame = new Mat();
  176.             List<DetectionResult> detResults;
  177.  
  178.             // 获取视频的fps
  179.             double videoFps = vcapture.Get(VideoCaptureProperties.Fps);
  180.             // 计算等待时间（毫秒）
  181.             int delay = (int)(1000 / videoFps);
  182.             Stopwatch _stopwatch = new Stopwatch();
  183.  
  184.             if (checkBox1.Checked)
  185.             {
  186.                 vwriter = new VideoWriter("out.mp4", FourCC.X264, vcapture.Fps, new OpenCvSharp.Size(vcapture.FrameWidth, vcapture.FrameHeight));
  187.                 saveDetVideo = true;
  188.             }
  189.             else
  190.             {
  191.                 saveDetVideo = false;
  192.             }
  193.  
  194.             Cv2.NamedWindow("DetectionResult 按下ESC，退出", WindowFlags.Normal);
  195.             Cv2.ResizeWindow("DetectionResult 按下ESC，退出", vcapture.FrameWidth / 2, vcapture.FrameHeight / 2);
  196.  
  197.             while (vcapture.Read(frame))
  198.             {
  199.                 if (frame.Empty())
  200.                 {
  201.                     MessageBox.Show("读取失败");
  202.                     return;
  203.                 }
  204.                 Mat mat_temp = frame.Clone();
  205.                 _stopwatch.Restart();
  206.  
  207.                 delay = (int)(1000 / videoFps);
  208.  
  209.                 detResults = yoloV8.Detect(frame);
  210.  
  211.                 //绘制结果
  212.                 //foreach (DetectionResult r in detResults)
  213.                 //{
  214.                 //    Cv2.PutText(frame, $"{r.Class}:{r.Confidence:P0}", new OpenCvSharp.Point(r.Rect.TopLeft.X, r.Rect.TopLeft.Y - 10), HersheyFonts.HersheySimplex, 1, Scalar.Red, 2);
  215.                 //    Cv2.Rectangle(frame, r.Rect, Scalar.Red, thickness: 2);
  216.                 //}
  217.  
  218.                 Cv2.PutText(frame, "preprocessTime:" + yoloV8.preprocessTime.ToString("F2") + "ms", new OpenCvSharp.Point(10, 30), HersheyFonts.HersheySimplex, 1, Scalar.Red, 2);
  219.                 Cv2.PutText(frame, "inferTime:" + yoloV8.inferTime.ToString("F2") + "ms", new OpenCvSharp.Point(10, 70), HersheyFonts.HersheySimplex, 1, Scalar.Red, 2);
  220.                 Cv2.PutText(frame, "postprocessTime:" + yoloV8.postprocessTime.ToString("F2") + "ms", new OpenCvSharp.Point(10, 110), HersheyFonts.HersheySimplex, 1, Scalar.Red, 2);
  221.                 Cv2.PutText(frame, "totalTime:" + yoloV8.totalTime.ToString("F2") + "ms", new OpenCvSharp.Point(10, 150), HersheyFonts.HersheySimplex, 1, Scalar.Red, 2);
  222.                 Cv2.PutText(frame, "video fps:" + videoFps.ToString("F2"), new OpenCvSharp.Point(10, 190), HersheyFonts.HersheySimplex, 1, Scalar.Red, 2);
  223.                 Cv2.PutText(frame, "det fps:" + yoloV8.detFps.ToString("F2"), new OpenCvSharp.Point(10, 230), HersheyFonts.HersheySimplex, 1, Scalar.Red, 2);
  224.  
  225.                 List<Track> track = new List<Track>();
  226.                 Track temp;
  227.                 foreach (DetectionResult r in detResults)
  228.                 {
  229.                     RectBox _box = new RectBox(r.Rect.X, r.Rect.Y, r.Rect.Width, r.Rect.Height);
  230.                     temp = new Track(_box, r.Confidence, ("label", r.ClassId), ("name", r.Class));
  231.                     track.Add(temp);
  232.                 }
  233.  
  234.                 var trackOutputs = tracker.Update(track);
  235.  
  236.                 foreach (var t in trackOutputs)
  237.                 {
  238.                     int x = (int)t.RectBox.X;
  239.                     int y = (int)t.RectBox.Y;
  240.                     int width = (int)t.RectBox.Width;
  241.                     int height = (int)t.RectBox.Height;
  242.  
  243.                     if (x < 0)
  244.                     {
  245.                         x = 0;
  246.                     }
  247.  
  248.                     if (y < 0)
  249.                     {
  250.                         y = 0;
  251.                     }
  252.  
  253.                     if (x + width > mat_temp.Width)
  254.                     {
  255.                         width = mat_temp.Width - x;
  256.                     }
  257.  
  258.                     if (y + height > mat_temp.Height)
  259.                     {
  260.                         height = mat_temp.Height - y;
  261.                     }
  262.  
  263.                     Rect rect = new Rect(x, y, width, height);
  264.  
  265.                     string txt = $"{t["name"]}-{t.TrackId}:{t.Score:P0}";
  266.                     
  267.                     //if (t["name"].ToString() != "Plate" && t["name"].ToString() != "Person")
  268.                     //{
  269.                     //    Mat mat_car = new Mat(mat_temp, rect);
  270.                     //    KeyValuePair<string, float> cls = yoloV8_Cls.Detect(mat_car);
  271.                     //    mat_car.Dispose();
  272.                     //    txt += $" {cls.Key}:{cls.Value:P0}";
  273.                     //}
  274.  
  275.                     //string txt = $"{t["name"]}-{t.TrackId}";
  276.                     Cv2.PutText(frame, txt, new OpenCvSharp.Point(rect.TopLeft.X, rect.TopLeft.Y - 10), HersheyFonts.HersheySimplex, 1, Scalar.Red, 2);
  277.                     Cv2.Rectangle(frame, rect, Scalar.Red, thickness: 2);
  278.                 }
  279.                 mat_temp.Dispose();
  280.  
  281.  
  282.                 if (saveDetVideo)
  283.                 {
  284.                     vwriter.Write(frame);
  285.                 }
  286.  
  287.                 Cv2.ImShow("DetectionResult 按下ESC，退出", frame);
  288.  
  289.                 // for test
  290.                 // delay = 1;
  291.                 delay = (int)(delay - _stopwatch.ElapsedMilliseconds);
  292.                 if (delay <= 0)
  293.                 {
  294.                     delay = 1;
  295.                 }
  296.                 //Console.WriteLine("delay:" + delay.ToString()) ;
  297.                 if (Cv2.WaitKey(delay) == 27 || Cv2.GetWindowProperty("DetectionResult 按下ESC，退出", WindowPropertyFlags.Visible) < 1.0)
  298.                 {
  299.                     Cv2.DestroyAllWindows();
  300.                     vcapture.Release();
  301.                     break;
  302.                 }
  303.             }
  304.  
  305.             Cv2.DestroyAllWindows();
  306.             vcapture.Release();
  307.             if (saveDetVideo)
  308.             {
  309.                 vwriter.Release();
  310.             }
  311.  
  312.         }
  313.  
  314.         string model_path1 = "";
  315.         string model_path2 = "";
  316.         string onnxFilter = "onnx模型|*.onnx;";
  317.  
  318.         private void button5_Click(object sender, EventArgs e)
  319.         {
  320.             if (video_path == "")
  321.             {
  322.                 MessageBox.Show("请先选择视频！");
  323.                 return;
  324.             }
  325.  
  326.             if (model_path1 == "")
  327.             {
  328.                 MessageBox.Show("选择模型1");
  329.                 OpenFileDialog ofd = new OpenFileDialog();
  330.                 ofd.Filter = onnxFilter;
  331.                 ofd.InitialDirectory = Application.StartupPath + "\\model";
  332.                 if (ofd.ShowDialog() != DialogResult.OK) return;
  333.                 model_path1 = ofd.FileName;
  334.             }
  335.  
  336.             if (model_path2 == "")
  337.             {
  338.                 MessageBox.Show("选择模型2");
  339.                 OpenFileDialog ofd1 = new OpenFileDialog();
  340.                 ofd1.Filter = onnxFilter;
  341.                 ofd1.InitialDirectory = Application.StartupPath + "\\model";
  342.                 if (ofd1.ShowDialog() != DialogResult.OK) return;
  343.                 model_path2 = ofd1.FileName;
  344.             }
  345.  
  346.             textBox1.Text = "开始检测";
  347.             Application.DoEvents();
  348.  
  349.             Task task = new Task(() =>
  350.             {
  351.                 VideoCapture vcapture = new VideoCapture(video_path);
  352.                 if (!vcapture.IsOpened())
  353.                 {
  354.                     MessageBox.Show("打开视频文件失败");
  355.                     return;
  356.                 }
  357.  
  358.                 YoloV8_Compare yoloV8 = new YoloV8_Compare(model_path1, model_path2, "model/lable.txt");
  359.  
  360.                 Mat frame = new Mat();
  361.  
  362.                 // 获取视频的fps
  363.                 double videoFps = vcapture.Get(VideoCaptureProperties.Fps);
  364.                 // 计算等待时间（毫秒）
  365.                 int delay = (int)(1000 / videoFps);
  366.                 Stopwatch _stopwatch = new Stopwatch();
  367.  
  368.                 Cv2.NamedWindow("DetectionResult 按下ESC，退出", WindowFlags.Normal);
  369.                 Cv2.ResizeWindow("DetectionResult 按下ESC，退出", vcapture.FrameWidth, vcapture.FrameHeight / 2);
  370.  
  371.                 while (vcapture.Read(frame))
  372.                 {
  373.                     if (frame.Empty())
  374.                     {
  375.                         MessageBox.Show("读取失败");
  376.                         return;
  377.                     }
  378.  
  379.                     _stopwatch.Restart();
  380.  
  381.                     delay = (int)(1000 / videoFps);
  382.  
  383.                     Mat result = yoloV8.Detect(frame, videoFps.ToString("F2"));
  384.  
  385.                     Cv2.ImShow("DetectionResult 按下ESC，退出", result);
  386.  
  387.                     // for test
  388.                     // delay = 1;
  389.                     delay = (int)(delay - _stopwatch.ElapsedMilliseconds);
  390.                     if (delay <= 0)
  391.                     {
  392.                         delay = 1;
  393.                     }
  394.                     //Console.WriteLine("delay:" + delay.ToString()) ;
  395.                     // 如果按下ESC或点击关闭，退出循环
  396.                     if (Cv2.WaitKey(delay) == 27 || Cv2.GetWindowProperty("DetectionResult 按下ESC，退出", WindowPropertyFlags.Visible) < 1.0)
  397.                     {
  398.                         Cv2.DestroyAllWindows();
  399.                         vcapture.Release();
  400.                         break;
  401.                     }
  402.                 }
  403.  
  404.                 textBox1.Invoke(new Action(() =>
  405.                 {
  406.                     textBox1.Text = "检测结束！";
  407.  
  408.                 }));
  409.  
  410.             });
  411.             task.Start();
  412.  
  413.         }
  414.  
  415.         //保存
  416.         SaveFileDialog sdf = new SaveFileDialog();
  417.         private void button6_Click(object sender, EventArgs e)
  418.         {
  419.             if (pictureBox2.Image == null)
  420.             {
  421.                 return;
  422.             }
  423.             Bitmap output = new Bitmap(pictureBox2.Image);
  424.             sdf.Title = "保存";
  425.             sdf.Filter = "Images (*.jpg)|*.jpg|Images (*.png)|*.png|Images (*.bmp)|*.bmp";
  426.             if (sdf.ShowDialog() == DialogResult.OK)
  427.             {
  428.                 switch (sdf.FilterIndex)
  429.                 {
  430.                     case 1:
  431.                         {
  432.                             output.Save(sdf.FileName, ImageFormat.Jpeg);
  433.                             break;
  434.                         }
  435.                     case 2:
  436.                         {
  437.                             output.Save(sdf.FileName, ImageFormat.Png);
  438.                             break;
  439.                         }
  440.                     case 3:
  441.                         {
  442.                             output.Save(sdf.FileName, ImageFormat.Bmp);
  443.                             break;
  444.                         }
  445.                 }
  446.                 MessageBox.Show("保存成功，位置：" + sdf.FileName);
  447.             }
  448.  
  449.         }
  450.  
  451.         /// <summary>
  452.         /// 选择模型
  453.         /// </summary>
  454.         /// <param name="sender"></param>
  455.         /// <param name="e"></param>
  456.         private void button7_Click(object sender, EventArgs e)
  457.         {
  458.             OpenFileDialog ofd = new OpenFileDialog();
  459.             ofd.Filter = onnxFilter;
  460.             ofd.InitialDirectory = Application.StartupPath + "\\model";
  461.             if (ofd.ShowDialog() != DialogResult.OK) return;
  462.             model_path = ofd.FileName;
  463.             yoloV8 = new YoloV8(model_path, "model/lable.txt");
  464.  
  465.         }
  466.     }
  467.  
  468. }

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