Enable webcam object detection

src/Yolov5Net.App/Program.cs

@@ -1,38 +1,91 @@
-using System;
+using System;
 using System.Collections.Generic;
 using System.Drawing;
 using Yolov5Net.Scorer;
 using Yolov5Net.Scorer.Models;
+using Yolov5Net.Scorer.Models.Abstract;
+using OpenCvSharp;
 
 namespace Yolov5Net.App
 {
- class Program
+ class webcam_detection
  {
- static void Main(string[] args)
- {
- using var image = Image.FromFile("Assets/test.jpg");
+ VideoCapture video_capture;
 
- using var scorer = new YoloScorer<YoloCocoP5Model>("Assets/Weights/yolov5n.onnx");
+ public void Init()
+ {
+ //Initialise the video capture module
+ video_capture = new VideoCapture(0);
+ video_capture.Set(3, 640); //Set the frame width
+ video_capture.Set(4, 480); //Set the frame height
 
-  List<YoloPrediction> predictions = scorer.Predict(image);
+ }
 
- using var graphics = Graphics.FromImage(image);
+ private Mat GrabFrame()
+ {
+ Mat image = new Mat();
+ //Capture frame by frame
+ video_capture.Read(image);
+ return image;
+ }
 
- foreach (var prediction in predictions) // iterate predictions to draw results
+ public void DetectFeatures()
+ {
+ Mat image;
+ while (true)
  {
- double score = Math.Round(prediction.Score, 2);
+ //Grab the current frame
+ image = GrabFrame();
+
+ // Load model.onnx
+ using var scorer = new YoloScorer<YoloCocoP5Model>("yolov5s.onnx");
+
+ Bitmap image_for_det;
+
+ image_for_det = OpenCvSharp.Extensions.BitmapConverter.ToBitmap(image);
+
+ // Detection
+ List<YoloPrediction> predictions = scorer.Predict(image_for_det);
+
+ foreach (var prediction in predictions) // iterate predictions to draw results
+ {
+ double score = Math.Round(prediction.Score, 2);
+ Console.WriteLine(prediction.Label.Name);
+ Console.WriteLine(score);
 
- graphics.DrawRectangles(new Pen(prediction.Label.Color, 1),
- new[] { prediction.Rectangle });
+ var x1 = prediction.Rectangle.X;
+ var y1 = prediction.Rectangle.Y;
+ var x2 = prediction.Rectangle.X + prediction.Rectangle.Width;
+ var y2 = prediction.Rectangle.Y + prediction.Rectangle.Height;
 
- var (x, y) = (prediction.Rectangle.X - 3, prediction.Rectangle.Y - 23);
+  Cv2.Rectangle(image, new OpenCvSharp.Point(x1, y1), new OpenCvSharp.Point(x2, y2) , color: new Scalar(0,255,0), thickness: 1);
 
- graphics.DrawString($"{prediction.Label.Name} ({score})",
- new Font("Consolas", 16, GraphicsUnit.Pixel), new SolidBrush(prediction.Label.Color),
- new PointF(x, y));
+ Cv2.PutText(image, $"{prediction.Label.Name} ({score})", new OpenCvSharp.Point(x1-3, y1-23), color: new Scalar(0, 255, 0), fontFace: HersheyFonts.HersheySimplex, fontScale: 2);
+
+
+ }
+
+ Cv2.ImShow("frame", image);
+ if (Cv2.WaitKey(1) == (int)ConsoleKey.Enter) // Press Enter to exit
+ break;
  }
 
- image.Save("Assets/result.jpg");
+ }
+
+ public void Release()
+ {
+ video_capture.Release();
+ Cv2.DestroyAllWindows();
+ }
+
+ static void Main(string[] args)
+ {
+ webcam_detection web_det = new webcam_detection();
+ web_det.Init();
+ web_det.DetectFeatures();
+ web_det.Release();
+
  }
  }
+
 }