using OpenCvSharp;

namespace SamplesWinform
{
  public class CircleFit 
  {
    public void Run()
    {
      //讀取圖片
      var img = Cv2.ImRead("Data/Image/c1.bmp");
      //顯示圖片
      //Cv2.ImShow("Input Image", img);
      
      //轉(zhuǎn)換成灰度圖
      Mat gray = img.CvtColor(ColorConversionCodes.BGR2GRAY);
      
      //閾值二值化操作 閾值參數(shù)可以用一些可視化工具來調(diào)試得到
      Mat ThresholdImg = gray.Threshold(11, 255, ThresholdTypes.Binary);
      Cv2.ImShow("Threshold", ThresholdImg);

      //降噪
      //方法一：高斯變化
      //Mat gaussImg= ThresholdImg.GaussianBlur(new Size(5, 5), 0.8);
      //Cv2.ImShow("GaussianBlur", gaussImg);
      //方法二：中值濾波降噪
      Mat medianImg = ThresholdImg.MedianBlur(5);
      Cv2.ImShow("MedianBlur", medianImg);

      //方法三：膨脹+腐蝕
      ////膨脹處理
      //Mat kernel = new Mat(15, 15, MatType.CV_8UC1);
      //Mat DilateImg = ThresholdImg.Dilate(kernel);
      ////腐蝕處理
      //Mat binary = DilateImg.Erode(kernel);
      ////顯示中間結(jié)果
      //Cv2.ImShow("Dilate & Erode", binary);

      //設(shè)置感興趣的區(qū)域
      int x = 150, y = 100, w = 294, h = 337;
      Rect roi = new Rect(x, y, w, h);
      Mat ROIimg = new Mat(medianImg, roi);
      //Cv2.ImShow("ROI Image", ROIimg);

      //尋找圖像輪廓
      Point[][] contours;
      HierarchyIndex[] hierachy;
      Cv2.FindContours(ROIimg, out contours, out hierachy, RetrievalModes.List, ContourApproximationModes.ApproxTC89KCOS);
      //根據(jù)找到的輪廓點(diǎn)，擬合橢圓
      for (int i = 0; i < contours.Length; i++)
      {
        //擬合函數(shù)必須至少5個點(diǎn)，少于則不擬合
        if (contours[i].Length < 5) continue;
        //橢圓擬合
        var rrt = Cv2.FitEllipse(contours[i]);

        //ROI復(fù)原
        rrt.Center.X += x;
        rrt.Center.Y += y;

        //畫橢圓
        Cv2.Ellipse(img, rrt, new Scalar(0, 0, 255), 2, LineTypes.AntiAlias);
        //畫圓心
        Cv2.Circle(img, (int)(rrt.Center.X), (int)(rrt.Center.Y), 4, new Scalar(255, 0, 0), -1, LineTypes.Link8, 0);
      }
      
      Cv2.ImShow("Fit Circle", img);
    }


   }
}