C# yolov8 OpenVINO+ByteTrack Demo

C# yolov8 OpenVINO+ByteTrack Demo

目录

效果

项目

代码

Form2.cs

YoloV8.cs

ByteTracker.cs

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参考 

效果

项目

​

代码

Form2.cs

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


namespace yolov8_OpenVINO_Demo
{
    public partial class Form2 : Form
    {
        public Form2()
        {
            InitializeComponent();
        }

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

        YoloV8 yoloV8;
        Mat image;

        string image_path = "";
        string model_path;

        string video_path = "";
        string videoFilter = "*.mp4|*.mp4;";
        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)
            {
                Cv2.PutText(result_image, $"{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(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 = "";
            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 == "")
            {
                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;
                }

                _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)
                {
                    Rect rect = new Rect((int)t.RectBox.X, (int)t.RectBox.Y, (int)t.RectBox.Width, (int)t.RectBox.Height);
                    //string txt = $"{t["name"]}-{t.TrackId}:{t.Score: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);
                }

                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)
                {
                    break; // 如果按下ESC，退出循环
                }
            }

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

        }

    }

}
 

  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.Threading;
  8. using System.Windows.Forms;
  9.  
  10.  
  11. namespace yolov8_OpenVINO_Demo
  12. {
  13.     public partial class Form2 : Form
  14.     {
  15.         public Form2()
  16.         {
  17.             InitializeComponent();
  18.         }
  19.  
  20.         string imgFilter = "*.*|*.bmp;*.jpg;*.jpeg;*.tiff;*.tiff;*.png";
  21.  
  22.         YoloV8 yoloV8;
  23.         Mat image;
  24.  
  25.         string image_path = "";
  26.         string model_path;
  27.  
  28.         string video_path = "";
  29.         string videoFilter = "*.mp4|*.mp4;";
  30.         VideoCapture vcapture;
  31.         VideoWriter vwriter;
  32.         bool saveDetVideo = false;
  33.         ByteTracker tracker;
  34.  
  35.         /// <summary>
  36.         /// 单图推理
  37.         /// </summary>
  38.         /// <param name="sender"></param>
  39.         /// <param name="e"></param>
  40.         private void button2_Click(object sender, EventArgs e)
  41.         {
  42.  
  43.             if (image_path == "")
  44.             {
  45.                 return;
  46.             }
  47.  
  48.             button2.Enabled = false;
  49.             pictureBox2.Image = null;
  50.             textBox1.Text = "";
  51.  
  52.             Application.DoEvents();
  53.  
  54.             image = new Mat(image_path);
  55.  
  56.             List<DetectionResult> detResults = yoloV8.Detect(image);
  57.  
  58.             //绘制结果
  59.             Mat result_image = image.Clone();
  60.             foreach (DetectionResult r in detResults)
  61.             {
  62.                 Cv2.PutText(result_image, $"{r.Class}:{r.Confidence:P0}", new OpenCvSharp.Point(r.Rect.TopLeft.X, r.Rect.TopLeft.Y - 10), HersheyFonts.HersheySimplex, 1, Scalar.Red, 2);
  63.                 Cv2.Rectangle(result_image, r.Rect, Scalar.Red, thickness: 2);
  64.             }
  65.  
  66.             if (pictureBox2.Image != null)
  67.             {
  68.                 pictureBox2.Image.Dispose();
  69.             }
  70.             pictureBox2.Image = new Bitmap(result_image.ToMemoryStream());
  71.             textBox1.Text = yoloV8.DetectTime();
  72.  
  73.             button2.Enabled = true;
  74.  
  75.         }
  76.  
  77.         /// <summary>
  78.         /// 窗体加载，初始化
  79.         /// </summary>
  80.         /// <param name="sender"></param>
  81.         /// <param name="e"></param>
  82.         private void Form1_Load(object sender, EventArgs e)
  83.         {
  84.             image_path = "test/dog.jpg";
  85.             pictureBox1.Image = new Bitmap(image_path);
  86.  
  87.             model_path = "model/yolov8n.onnx";
  88.  
  89.             yoloV8 = new YoloV8(model_path, "model/lable.txt");
  90.  
  91.         }
  92.  
  93.         /// <summary>
  94.         /// 选择图片
  95.         /// </summary>
  96.         /// <param name="sender"></param>
  97.         /// <param name="e"></param>
  98.         private void button1_Click_1(object sender, EventArgs e)
  99.         {
  100.             OpenFileDialog ofd = new OpenFileDialog();
  101.             ofd.Filter = imgFilter;
  102.             if (ofd.ShowDialog() != DialogResult.OK) return;
  103.  
  104.             pictureBox1.Image = null;
  105.  
  106.             image_path = ofd.FileName;
  107.             pictureBox1.Image = new Bitmap(image_path);
  108.  
  109.             textBox1.Text = "";
  110.             pictureBox2.Image = null;
  111.         }
  112.  
  113.         /// <summary>
  114.         /// 选择视频
  115.         /// </summary>
  116.         /// <param name="sender"></param>
  117.         /// <param name="e"></param>
  118.         private void button4_Click(object sender, EventArgs e)
  119.         {
  120.             OpenFileDialog ofd = new OpenFileDialog();
  121.             ofd.Filter = videoFilter;
  122.             ofd.InitialDirectory = Application.StartupPath + "\\test";
  123.             if (ofd.ShowDialog() != DialogResult.OK) return;
  124.  
  125.             video_path = ofd.FileName;
  126.  
  127.             textBox1.Text = "";
  128.             pictureBox1.Image = null;
  129.             pictureBox2.Image = null;
  130.  
  131.             button3_Click(null, null);
  132.  
  133.         }
  134.  
  135.         /// <summary>
  136.         /// 视频推理
  137.         /// </summary>
  138.         /// <param name="sender"></param>
  139.         /// <param name="e"></param>
  140.         private void button3_Click(object sender, EventArgs e)
  141.         {
  142.             if (video_path == "")
  143.             {
  144.                 return;
  145.             }
  146.  
  147.             textBox1.Text = "开始检测";
  148.  
  149.             Application.DoEvents();
  150.  
  151.             Thread thread = new Thread(new ThreadStart(VideoDetection));
  152.  
  153.             thread.Start();
  154.             thread.Join();
  155.  
  156.             textBox1.Text = "检测完成！";
  157.         }
  158.  
  159.         void VideoDetection()
  160.         {
  161.             vcapture = new VideoCapture(video_path);
  162.             if (!vcapture.IsOpened())
  163.             {
  164.                 MessageBox.Show("打开视频文件失败");
  165.                 return;
  166.             }
  167.  
  168.             tracker = new ByteTracker((int)vcapture.Fps, 200);
  169.  
  170.             Mat frame = new Mat();
  171.             List<DetectionResult> detResults;
  172.  
  173.             // 获取视频的fps
  174.             double videoFps = vcapture.Get(VideoCaptureProperties.Fps);
  175.             // 计算等待时间（毫秒）
  176.             int delay = (int)(1000 / videoFps);
  177.             Stopwatch _stopwatch = new Stopwatch();
  178.  
  179.             if (checkBox1.Checked)
  180.             {
  181.                 vwriter = new VideoWriter("out.mp4", FourCC.X264, vcapture.Fps, new OpenCvSharp.Size(vcapture.FrameWidth, vcapture.FrameHeight));
  182.                 saveDetVideo = true;
  183.             }
  184.             else
  185.             {
  186.                 saveDetVideo = false;
  187.             }
  188.  
  189.             Cv2.NamedWindow("DetectionResult 按下ESC，退出", WindowFlags.Normal);
  190.             Cv2.ResizeWindow("DetectionResult 按下ESC，退出", vcapture.FrameWidth / 2, vcapture.FrameHeight / 2);
  191.  
  192.             while (vcapture.Read(frame))
  193.             {
  194.                 if (frame.Empty())
  195.                 {
  196.                     MessageBox.Show("读取失败");
  197.                     return;
  198.                 }
  199.  
  200.                 _stopwatch.Restart();
  201.  
  202.                 delay = (int)(1000 / videoFps);
  203.  
  204.                 detResults = yoloV8.Detect(frame);
  205.  
  206.                 //绘制结果
  207.                 //foreach (DetectionResult r in detResults)
  208.                 //{
  209.                 //    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);
  210.                 //    Cv2.Rectangle(frame, r.Rect, Scalar.Red, thickness: 2);
  211.                 //}
  212.  
  213.                 Cv2.PutText(frame, "preprocessTime:" + yoloV8.preprocessTime.ToString("F2") + "ms", new OpenCvSharp.Point(10, 30), HersheyFonts.HersheySimplex, 1, Scalar.Red, 2);
  214.                 Cv2.PutText(frame, "inferTime:" + yoloV8.inferTime.ToString("F2") + "ms", new OpenCvSharp.Point(10, 70), HersheyFonts.HersheySimplex, 1, Scalar.Red, 2);
  215.                 Cv2.PutText(frame, "postprocessTime:" + yoloV8.postprocessTime.ToString("F2") + "ms", new OpenCvSharp.Point(10, 110), HersheyFonts.HersheySimplex, 1, Scalar.Red, 2);
  216.                 Cv2.PutText(frame, "totalTime:" + yoloV8.totalTime.ToString("F2") + "ms", new OpenCvSharp.Point(10, 150), HersheyFonts.HersheySimplex, 1, Scalar.Red, 2);
  217.                 Cv2.PutText(frame, "video fps:" + videoFps.ToString("F2"), new OpenCvSharp.Point(10, 190), HersheyFonts.HersheySimplex, 1, Scalar.Red, 2);
  218.                 Cv2.PutText(frame, "det fps:" + yoloV8.detFps.ToString("F2"), new OpenCvSharp.Point(10, 230), HersheyFonts.HersheySimplex, 1, Scalar.Red, 2);
  219.  
  220.                 List<Track> track = new List<Track>();
  221.                 Track temp;
  222.                 foreach (DetectionResult r in detResults)
  223.                 {
  224.                     RectBox _box = new RectBox(r.Rect.X, r.Rect.Y, r.Rect.Width, r.Rect.Height);
  225.                     temp = new Track(_box, r.Confidence, ("label", r.ClassId), ("name", r.Class));
  226.                     track.Add(temp);
  227.                 }
  228.  
  229.                 var trackOutputs = tracker.Update(track);
  230.  
  231.                 foreach (var t in trackOutputs)
  232.                 {
  233.                     Rect rect = new Rect((int)t.RectBox.X, (int)t.RectBox.Y, (int)t.RectBox.Width, (int)t.RectBox.Height);
  234.                     //string txt = $"{t["name"]}-{t.TrackId}:{t.Score:P0}";
  235.                     string txt = $"{t["name"]}-{t.TrackId}";
  236.                     Cv2.PutText(frame, txt, new OpenCvSharp.Point(rect.TopLeft.X, rect.TopLeft.Y - 10), HersheyFonts.HersheySimplex, 1, Scalar.Red, 2);
  237.                     Cv2.Rectangle(frame, rect, Scalar.Red, thickness: 2);
  238.                 }
  239.  
  240.                 if (saveDetVideo)
  241.                 {
  242.                     vwriter.Write(frame);
  243.                 }
  244.  
  245.                 Cv2.ImShow("DetectionResult 按下ESC，退出", frame);
  246.  
  247.                 // for test
  248.                 // delay = 1;
  249.                 delay = (int)(delay - _stopwatch.ElapsedMilliseconds);
  250.                 if (delay <= 0)
  251.                 {
  252.                     delay = 1;
  253.                 }
  254.                 //Console.WriteLine("delay:" + delay.ToString()) ;
  255.                 if (Cv2.WaitKey(delay) == 27)
  256.                 {
  257.                     break; // 如果按下ESC，退出循环
  258.                 }
  259.             }
  260.  
  261.             Cv2.DestroyAllWindows();
  262.             vcapture.Release();
  263.             if (saveDetVideo)
  264.             {
  265.                 vwriter.Release();
  266.             }
  267.  
  268.         }
  269.  
  270.     }
  271.  
  272. }

YoloV8.cs

  1. using OpenCvSharp;
  2. using OpenCvSharp.Dnn;
  3. using Sdcb.OpenVINO;
  4. using System;
  5. using System.Collections.Generic;
  6. using System.Diagnostics;
  7. using System.IO;
  8. using System.Linq;
  9. using System.Text;
  10.  
  11.  
  12. namespace yolov8_OpenVINO_Demo
  13. {
  14.     public class YoloV8
  15.     {
  16.  
  17.         float[] input_tensor_data;
  18.         float[] outputData;
  19.         List<DetectionResult> detectionResults;
  20.  
  21.         int input_height;
  22.         int input_width;
  23.  
  24.         InferRequest ir;
  25.  
  26.         public string[] class_names;
  27.         int class_num;
  28.         int box_num;
  29.  
  30.         float conf_threshold;
  31.         float nms_threshold;
  32.  
  33.         float ratio_height;
  34.         float ratio_width;
  35.  
  36.         public double preprocessTime;
  37.         public double inferTime;
  38.         public double postprocessTime;
  39.         public double totalTime;
  40.         public double detFps;
  41.  
  42.         public String DetectTime()
  43.         {
  44.             StringBuilder stringBuilder = new StringBuilder();
  45.             stringBuilder.AppendLine($"Preprocess: {preprocessTime:F2}ms");
  46.             stringBuilder.AppendLine($"Infer: {inferTime:F2}ms");
  47.             stringBuilder.AppendLine($"Postprocess: {postprocessTime:F2}ms");
  48.             stringBuilder.AppendLine($"Total: {totalTime:F2}ms");
  49.  
  50.             return stringBuilder.ToString();
  51.         }
  52.  
  53.         public YoloV8(string model_path, string classer_path)
  54.         {
  55.             Model rawModel = OVCore.Shared.ReadModel(model_path);
  56.             PrePostProcessor pp = rawModel.CreatePrePostProcessor();
  57.             PreProcessInputInfo inputInfo = pp.Inputs.Primary;
  58.  
  59.            // inputInfo.TensorInfo.Layout = Sdcb.OpenVINO.Layout.NHWC;
  60.            // inputInfo.ModelInfo.Layout = Sdcb.OpenVINO.Layout.NCHW;
  61.  
  62.             Model m = pp.BuildModel();
  63.             CompiledModel cm = OVCore.Shared.CompileModel(m, "AUTO");
  64.             ir = cm.CreateInferRequest();
  65.  
  66.             class_names = File.ReadAllLines(classer_path, Encoding.UTF8);
  67.             class_num = class_names.Length;
  68.  
  69.             input_height = 640;
  70.             input_width = 640;
  71.  
  72.             box_num = 8400;
  73.  
  74.             conf_threshold = 0.5f;
  75.             nms_threshold = 0.5f;
  76.  
  77.             detectionResults = new List<DetectionResult>();
  78.         }
  79.  
  80.         void Preprocess(Mat image)
  81.         {
  82.             //图片缩放
  83.             int height = image.Rows;
  84.             int width = image.Cols;
  85.             Mat temp_image = image.Clone();
  86.             if (height > input_height || width > input_width)
  87.             {
  88.                 float scale = Math.Min((float)input_height / height, (float)input_width / width);
  89.                 OpenCvSharp.Size new_size = new OpenCvSharp.Size((int)(width * scale), (int)(height * scale));
  90.                 Cv2.Resize(image, temp_image, new_size);
  91.             }
  92.             ratio_height = (float)height / temp_image.Rows;
  93.             ratio_width = (float)width / temp_image.Cols;
  94.             Mat input_img = new Mat();
  95.             Cv2.CopyMakeBorder(temp_image, input_img, 0, input_height - temp_image.Rows, 0, input_width - temp_image.Cols, BorderTypes.Constant, 0);
  96.  
  97.             //归一化
  98.             input_img.ConvertTo(input_img, MatType.CV_32FC3, 1.0 / 255);
  99.  
  100.             input_tensor_data = Common.ExtractMat(input_img);
  101.  
  102.             input_img.Dispose();
  103.             temp_image.Dispose();
  104.         }
  105.  
  106.         void Postprocess(float[] outputData)
  107.         {
  108.             detectionResults.Clear();
  109.  
  110.             float[] data = Common.Transpose(outputData, class_num + 4, box_num);
  111.  
  112.             float[] confidenceInfo = new float[class_num];
  113.             float[] rectData = new float[4];
  114.  
  115.             List<DetectionResult> detResults = new List<DetectionResult>();
  116.  
  117.             for (int i = 0; i < box_num; i++)
  118.             {
  119.                 Array.Copy(data, i * (class_num + 4), rectData, 0, 4);
  120.                 Array.Copy(data, i * (class_num + 4) + 4, confidenceInfo, 0, class_num);
  121.  
  122.                 float score = confidenceInfo.Max(); // 获取最大值
  123.  
  124.                 int maxIndex = Array.IndexOf(confidenceInfo, score); // 获取最大值的位置
  125.  
  126.                 int _centerX = (int)(rectData[0] * ratio_width);
  127.                 int _centerY = (int)(rectData[1] * ratio_height);
  128.                 int _width = (int)(rectData[2] * ratio_width);
  129.                 int _height = (int)(rectData[3] * ratio_height);
  130.  
  131.                 detResults.Add(new DetectionResult(
  132.                    maxIndex,
  133.                    class_names[maxIndex],
  134.                    new Rect(_centerX - _width / 2, _centerY - _height / 2, _width, _height),
  135.                    score));
  136.             }
  137.  
  138.             //NMS
  139.             CvDnn.NMSBoxes(detResults.Select(x => x.Rect), detResults.Select(x => x.Confidence), conf_threshold, nms_threshold, out int[] indices);
  140.             detResults = detResults.Where((x, index) => indices.Contains(index)).ToList();
  141.  
  142.             detectionResults = detResults;
  143.         }
  144.  
  145.         internal List<DetectionResult> Detect(Mat image)
  146.         {
  147.  
  148.             var t1 = Cv2.GetTickCount();
  149.  
  150.             Stopwatch stopwatch = new Stopwatch();
  151.             stopwatch.Start();
  152.  
  153.             Preprocess(image);
  154.  
  155.             preprocessTime = stopwatch.Elapsed.TotalMilliseconds;
  156.             stopwatch.Restart();
  157.  
  158.             using (Tensor input_x = Tensor.FromArray(input_tensor_data, new Shape(1,3, 640, 640)))
  159.             {
  160.                 ir.Inputs[0] = input_x;
  161.             }
  162.  
  163.             ir.Run();
  164.  
  165.             inferTime = stopwatch.Elapsed.TotalMilliseconds;
  166.             stopwatch.Restart();
  167.  
  168.             outputData = ir.Outputs[0].GetData<float>().ToArray();
  169.  
  170.             Postprocess(outputData);
  171.  
  172.             postprocessTime = stopwatch.Elapsed.TotalMilliseconds;
  173.             stopwatch.Stop();
  174.  
  175.             totalTime = preprocessTime + inferTime + postprocessTime;
  176.  
  177.             detFps = (double)stopwatch.Elapsed.TotalSeconds / (double)stopwatch.Elapsed.Ticks;
  178.  
  179.             var t2 = Cv2.GetTickCount();
  180.  
  181.             detFps = 1 / ((t2 - t1) / Cv2.GetTickFrequency());
  182.  
  183.             return detectionResults;
  184.  
  185.         }
  186.  
  187.     }
  188. }

ByteTracker.cs

  1. using System;
  2. using System.Collections.Generic;
  3. using System.Linq;
  4. using System.Text;
  5. using System.Threading.Tasks;
  6.  
  7. namespace ByteTrack
  8. {
  9.     public class ByteTracker
  10.     {
  11.         readonly float _trackThresh;
  12.         readonly float _highThresh;
  13.         readonly float _matchThresh;
  14.         readonly int _maxTimeLost;
  15.  
  16.         int _frameId = 0;
  17.         int _trackIdCount = 0;
  18.  
  19.         readonly List<Track> _trackedTracks = new List<Track>(100);
  20.         readonly List<Track> _lostTracks = new List<Track>(100);
  21.         List<Track> _removedTracks = new List<Track>(100);
  22.  
  23.         public ByteTracker(int frameRate = 30, int trackBuffer = 30, float trackThresh = 0.5f, float highThresh = 0.6f, float matchThresh = 0.8f)
  24.         {
  25.             _trackThresh = trackThresh;
  26.             _highThresh = highThresh;
  27.             _matchThresh = matchThresh;
  28.             _maxTimeLost = (int)(frameRate / 30.0 * trackBuffer);
  29.         }
  30.  
  31.         /// <summary>
  32.         /// 
  33.         /// </summary>
  34.         /// <param name="objects"></param>
  35.         /// <returns></returns>
  36.         public IList<Track> Update(List<Track> tracks)
  37.         {
  38.             #region Step 1: Get detections 
  39.             _frameId++;
  40.  
  41.             // Create new Tracks using the result of object detection
  42.             List<Track> detTracks = new List<Track>();
  43.             List<Track> detLowTracks = new List<Track>();
  44.  
  45.             foreach (var obj in tracks)
  46.             {
  47.                 if (obj.Score >= _trackThresh)
  48.                 {
  49.                     detTracks.Add(obj);
  50.                 }
  51.                 else
  52.                 {
  53.                     detLowTracks.Add(obj);
  54.                 }
  55.             }
  56.  
  57.             // Create lists of existing STrack
  58.             List<Track> activeTracks = new List<Track>();
  59.             List<Track> nonActiveTracks = new List<Track>();
  60.  
  61.             foreach (var trackedTrack in _trackedTracks)
  62.             {
  63.                 if (!trackedTrack.IsActivated)
  64.                 {
  65.                     nonActiveTracks.Add(trackedTrack);
  66.                 }
  67.                 else
  68.                 {
  69.                     activeTracks.Add(trackedTrack);
  70.                 }
  71.             }
  72.  
  73.             var trackPool = activeTracks.Union(_lostTracks).ToArray();
  74.  
  75.             // Predict current pose by KF
  76.             foreach (var track in trackPool)
  77.             {
  78.                 track.Predict();
  79.             }
  80.             #endregion
  81.  
  82.             #region Step 2: First association, with IoU 
  83.             List<Track> currentTrackedTracks = new List<Track>();
  84.             Track[] remainTrackedTracks;
  85.             Track[] remainDetTracks;
  86.             List<Track> refindTracks = new List<Track>();
  87.             {
  88.                 var dists = CalcIouDistance(trackPool, detTracks);
  89.                 LinearAssignment(dists, trackPool.Length, detTracks.Count, _matchThresh,
  90.                     out var matchesIdx,
  91.                     out var unmatchTrackIdx,
  92.                     out var unmatchDetectionIdx);
  93.  
  94.                 foreach (var matchIdx in matchesIdx)
  95.                 {
  96.                     var track = trackPool[matchIdx[0]];
  97.                     var det = detTracks[matchIdx[1]];
  98.                     if (track.State == TrackState.Tracked)
  99.                     {
  100.                         track.Update(det, _frameId);
  101.                         currentTrackedTracks.Add(track);
  102.                     }
  103.                     else
  104.                     {
  105.                         track.ReActivate(det, _frameId);
  106.                         refindTracks.Add(track);
  107.                     }
  108.                 }
  109.  
  110.                 remainDetTracks = unmatchDetectionIdx.Select(unmatchIdx => detTracks[unmatchIdx]).ToArray();
  111.                 remainTrackedTracks = unmatchTrackIdx
  112.                     .Where(unmatchIdx => trackPool[unmatchIdx].State == TrackState.Tracked)
  113.                     .Select(unmatchIdx => trackPool[unmatchIdx])
  114.                     .ToArray();
  115.             }
  116.             #endregion
  117.  
  118.             #region Step 3: Second association, using low score dets 
  119.             List<Track> currentLostTracks = new List<Track>();
  120.             {
  121.                 var dists = CalcIouDistance(remainTrackedTracks, detLowTracks);
  122.                 LinearAssignment(dists, remainTrackedTracks.Length, detLowTracks.Count, 0.5f,
  123.                                  out var matchesIdx,
  124.                                  out var unmatchTrackIdx,
  125.                                  out var unmatchDetectionIdx);
  126.  
  127.                 foreach (var matchIdx in matchesIdx)
  128.                 {
  129.                     var track = remainTrackedTracks[matchIdx[0]];
  130.                     var det = detLowTracks[matchIdx[1]];
  131.                     if (track.State == TrackState.Tracked)
  132.                     {
  133.                         track.Update(det, _frameId);
  134.                         currentTrackedTracks.Add(track);
  135.                     }
  136.                     else
  137.                     {
  138.                         track.ReActivate(det, _frameId);
  139.                         refindTracks.Add(track);
  140.                     }
  141.                 }
  142.  
  143.                 foreach (var unmatchTrack in unmatchTrackIdx)
  144.                 {
  145.                     var track = remainTrackedTracks[unmatchTrack];
  146.                     if (track.State != TrackState.Lost)
  147.                     {
  148.                         track.MarkAsLost();
  149.                         currentLostTracks.Add(track);
  150.                     }
  151.                 }
  152.             }
  153.             #endregion
  154.  
  155.             #region Step 4: Init new tracks 
  156.             List<Track> currentRemovedTracks = new List<Track>();
  157.             {
  158.                 // Deal with unconfirmed tracks, usually tracks with only one beginning frame
  159.                 var dists = CalcIouDistance(nonActiveTracks, remainDetTracks);
  160.                 LinearAssignment(dists, nonActiveTracks.Count, remainDetTracks.Length, 0.7f,
  161.                                  out var matchesIdx,
  162.                                  out var unmatchUnconfirmedIdx,
  163.                                  out var unmatchDetectionIdx);
  164.  
  165.                 foreach (var matchIdx in matchesIdx)
  166.                 {
  167.                     nonActiveTracks[matchIdx[0]].Update(remainDetTracks[matchIdx[1]], _frameId);
  168.                     currentTrackedTracks.Add(nonActiveTracks[matchIdx[0]]);
  169.                 }
  170.  
  171.                 foreach (var unmatchIdx in unmatchUnconfirmedIdx)
  172.                 {
  173.                     var track = nonActiveTracks[unmatchIdx];
  174.                     track.MarkAsRemoved();
  175.                     currentRemovedTracks.Add(track);
  176.                 }
  177.  
  178.                 // Add new stracks
  179.                 foreach (var unmatchIdx in unmatchDetectionIdx)
  180.                 {
  181.                     var track = remainDetTracks[unmatchIdx];
  182.                     if (track.Score < _highThresh)
  183.                         continue;
  184.  
  185.                     _trackIdCount++;
  186.                     track.Activate(_frameId, _trackIdCount);
  187.                     currentTrackedTracks.Add(track);
  188.                 }
  189.             }
  190.             #endregion
  191.  
  192.             #region Step 5: Update state
  193.             foreach (var lostTrack in _lostTracks)
  194.             {
  195.                 if (_frameId - lostTrack.FrameId > _maxTimeLost)
  196.                 {
  197.                     lostTrack.MarkAsRemoved();
  198.                     currentRemovedTracks.Add(lostTrack);
  199.                 }
  200.             }
  201.  
  202.             var trackedTracks = currentTrackedTracks.Union(refindTracks).ToArray();
  203.             var lostTracks = _lostTracks.Except(trackedTracks).Union(currentLostTracks).Except(_removedTracks).ToArray();
  204.             _removedTracks = _removedTracks.Union(currentRemovedTracks).ToList();
  205.             RemoveDuplicateStracks(trackedTracks, lostTracks);
  206.             #endregion
  207.  
  208.             return _trackedTracks.Where(track => track.IsActivated).ToArray();
  209.         }
  210.  
  211.         /// <summary>
  212.         /// 
  213.         /// </summary>
  214.         /// <param name="aTracks"></param>
  215.         /// <param name="bTracks"></param>
  216.         /// <param name="aResults"></param>
  217.         /// <param name="bResults"></param>
  218.         void RemoveDuplicateStracks(IList<Track> aTracks, IList<Track> bTracks)
  219.         {
  220.             _trackedTracks.Clear();
  221.             _lostTracks.Clear();
  222.  
  223.             List<(int, int)> overlappingCombinations;
  224.             var ious = CalcIouDistance(aTracks, bTracks);
  225.  
  226.             if (ious is null)
  227.                 overlappingCombinations = new List<(int, int)>();
  228.             else
  229.             {
  230.                 var rows = ious.GetLength(0);
  231.                 var cols = ious.GetLength(1);
  232.                 overlappingCombinations = new List<(int, int)>(rows * cols / 2);
  233.                 for (var i = 0; i < rows; i++)
  234.                     for (var j = 0; j < cols; j++)
  235.                         if (ious[i, j] < 0.15f)
  236.                             overlappingCombinations.Add((i, j));
  237.             }
  238.  
  239.             var aOverlapping = aTracks.Select(x => false).ToArray();
  240.             var bOverlapping = bTracks.Select(x => false).ToArray();
  241.  
  242.             foreach (var (aIdx, bIdx) in overlappingCombinations)
  243.             {
  244.                 var timep = aTracks[aIdx].FrameId - aTracks[aIdx].StartFrameId;
  245.                 var timeq = bTracks[bIdx].FrameId - bTracks[bIdx].StartFrameId;
  246.                 if (timep > timeq)
  247.                     bOverlapping[bIdx] = true;
  248.                 else
  249.                     aOverlapping[aIdx] = true;
  250.             }
  251.  
  252.             for (var ai = 0; ai < aTracks.Count; ai++)
  253.                 if (!aOverlapping[ai])
  254.                     _trackedTracks.Add(aTracks[ai]);
  255.  
  256.             for (var bi = 0; bi < bTracks.Count; bi++)
  257.                 if (!bOverlapping[bi])
  258.                     _lostTracks.Add(bTracks[bi]);
  259.         }
  260.  
  261.         /// <summary>
  262.         /// 
  263.         /// </summary>
  264.         /// <param name="costMatrix"></param>
  265.         /// <param name="costMatrixSize"></param>
  266.         /// <param name="costMatrixSizeSize"></param>
  267.         /// <param name="thresh"></param>
  268.         /// <param name="matches"></param>
  269.         /// <param name="aUnmatched"></param>
  270.         /// <param name="bUnmatched"></param>
  271.         void LinearAssignment(float[,] costMatrix, int costMatrixSize, int costMatrixSizeSize, float thresh, out IList<int[]> matches, out IList<int> aUnmatched, out IList<int> bUnmatched)
  272.         {
  273.             matches = new List<int[]>();
  274.             if (costMatrix is null)
  275.             {
  276.                 aUnmatched = Enumerable.Range(0, costMatrixSize).ToArray();
  277.                 bUnmatched = Enumerable.Range(0, costMatrixSizeSize).ToArray();
  278.                 return;
  279.             }
  280.  
  281.             bUnmatched = new List<int>();
  282.             aUnmatched = new List<int>();
  283.  
  284.             var (rowsol, colsol) = Lapjv.Exec(costMatrix, true, thresh);
  285.  
  286.             for (var i = 0; i < rowsol.Length; i++)
  287.             {
  288.                 if (rowsol[i] >= 0)
  289.                     matches.Add(new int[] { i, rowsol[i] });
  290.                 else
  291.                     aUnmatched.Add(i);
  292.             }
  293.  
  294.             for (var i = 0; i < colsol.Length; i++)
  295.                 if (colsol[i] < 0)
  296.                     bUnmatched.Add(i);
  297.         }
  298.  
  299.         /// <summary>
  300.         /// 
  301.         /// </summary>
  302.         /// <param name="aRects"></param>
  303.         /// <param name="bRects"></param>
  304.         /// <returns></returns>
  305.         static float[,] CalcIous(IList<RectBox> aRects, IList<RectBox> bRects)
  306.         {
  307.             if (aRects.Count * bRects.Count == 0) return null;
  308.  
  309.             var ious = new float[aRects.Count, bRects.Count];
  310.             for (var bi = 0; bi < bRects.Count; bi++)
  311.                 for (var ai = 0; ai < aRects.Count; ai++)
  312.                     ious[ai, bi] = bRects[bi].CalcIoU(aRects[ai]);
  313.  
  314.             return ious;
  315.         }
  316.  
  317.         /// <summary>
  318.         /// 
  319.         /// </summary>
  320.         /// <param name="aTtracks"></param>
  321.         /// <param name="bTracks"></param>
  322.         /// <returns></returns>
  323.         static float[,] CalcIouDistance(IEnumerable<Track> aTtracks, IEnumerable<Track> bTracks)
  324.         {
  325.             var aRects = aTtracks.Select(x => x.RectBox).ToArray();
  326.             var bRects = bTracks.Select(x => x.RectBox).ToArray();
  327.  
  328.             var ious = CalcIous(aRects, bRects);
  329.             if (ious is null) return null;
  330.  
  331.             var rows = ious.GetLength(0);
  332.             var cols = ious.GetLength(1);
  333.             var matrix = new float[rows, cols];
  334.             for (var i = 0; i < rows; i++)
  335.                 for (var j = 0; j < cols; j++)
  336.                     matrix[i, j] = 1 - ious[i, j];
  337.  
  338.             return matrix;
  339.         }
  340.     }
  341. }

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参考 

https://github.com/devhxj/Yolo8-ByteTrack-CSharp

https://github.com/sdcb/sdcb-openvino-yolov8-det

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