OpenCvSharp 编写多线程CircularCaliper找圆心函数 ， 输入图像、找圆扇形区域的最小半径和最大半径、找圆扇形中心点、设定扇形区域起始角度、扇形区域结束角度 先剪出找圆扇形区域图像 输入Caliper个数，宽度、长度、 输入从内到外找圆心、从黑到白找圆 并行计Caliper区域 中心圆可设定请编写函数

以下是一个使用OpenCvSharp编写的多线程CircularCaliper找圆心函数的示例代码：

using System;
using System.Collections.Generic;
using System.Threading.Tasks;
using OpenCvSharp;

public static class CircleDetector
{
    public static Point2f FindCircleCenter(Mat image, float minRadius, float maxRadius, Point2f center, float startAngle, float endAngle, int caliperCount, int caliperWidth, int caliperLength, bool fromInside, bool fromBlackToWhite)
    {
        // Crop the circular region
        Rect roi = new Rect((int)(center.X - maxRadius), (int)(center.Y - maxRadius), (int)(2 * maxRadius), (int)(2 * maxRadius));
        Mat croppedImage = new Mat(image, roi);

        // Preprocess the image
        Mat grayImage = new Mat();
        Cv2.CvtColor(croppedImage, grayImage, ColorConversionCodes.BGR2GRAY);
        Cv2.GaussianBlur(grayImage, grayImage, new Size(7, 7), 0);

        // Compute the step angle
        float stepAngle = (endAngle - startAngle) / (caliperCount - 1);

        // Initialize the result variables
        Point2f bestCenter = new Point2f(center.X, center.Y);
        float bestScore = float.MinValue;

        // Create a list of calipers
        List<Caliper> calipers = new List<Caliper>();
        for (int i = 0; i < caliperCount; i++)
        {
            float angle = startAngle + i * stepAngle;
            calipers.Add(new Caliper(center, angle, caliperWidth, caliperLength, fromInside, fromBlackToWhite));
        }

        // Process the calipers in parallel
        Parallel.ForEach(calipers, caliper =>
        {
            // Compute the score for the current caliper
            float score = caliper.ComputeScore(grayImage, minRadius, maxRadius);

            // Update the result variables if the score is better than the current best score
            lock (bestCenter)
            {
                if (score > bestScore)
                {
                    bestScore = score;
                    bestCenter = caliper.Center;
                }
            }
        });

        // Shift the coordinates of the best center to the original image
        bestCenter.X += roi.X;
        bestCenter.Y += roi.Y;

        return bestCenter;
    }

    private class Caliper
    {
        public Point2f Center { get; private set; }
        public float Angle { get; private set; }
        public int Width { get; private set; }
        public int Length { get; private set; }
        public bool FromInside { get; private set; }
        public bool FromBlackToWhite { get; private set; }

        public Caliper(Point2f center, float angle, int width, int length, bool fromInside, bool fromBlackToWhite)
        {
            Center = center;
            Angle = angle;
            Width = width;
            Length = length;
            FromInside = fromInside;
            FromBlackToWhite = fromBlackToWhite;
        }

        public float ComputeScore(Mat image, float minRadius, float maxRadius)
        {
            float radius = (minRadius + maxRadius) / 2;
            float x = Center.X + radius * (float)Math.Cos(Angle);
            float y = Center.Y + radius * (float)Math.Sin(Angle);
            Point2f point1 = new Point2f(x, y);
            Point2f point2 = new Point2f(x + Length * (float)Math.Cos(Angle + Math.PI / 2), y + Length * (float)Math.Sin(Angle + Math.PI / 2));
            Point2f point3 = new Point2f(x - Length * (float)Math.Cos(Angle), y - Length * (float)Math.Sin(Angle));
            Point2f point4 = new Point2f(x + Length * (float)Math.Cos(Angle - Math.PI / 2), y + Length * (float)Math.Sin(Angle - Math.PI / 2));
            float[] values1 = SampleLine(image, point1, point2, Width);
            float[] values2 = SampleLine(image, point1, point3, Width);
            float[] values3 = SampleLine(image, point1, point4, Width);
            float score = ComputeScore(values1, values2, values3, FromInside, FromBlackToWhite);
            return score;
        }

        private float[] SampleLine(Mat image, Point2f point1, Point2f point2, int width)
        {
            int count = (int)Math.Round(point1.DistanceTo(point2)) / width;
            float[] values = new float[count];
            for (int i = 0; i < count; i++)
            {
                float x = point1.X + (float)i / count * (point2.X - point1.X);
                float y = point1.Y + (float)i / count * (point2.Y - point1.Y);
                values[i] = image.At<float>((int)y, (int)x);
            }
            return values;
        }

        private float ComputeScore(float[] values1, float[] values2, float[] values3, bool fromInside, bool fromBlackToWhite)
        {
            float score = 0;
            if (fromInside)
            {
                for (int i = 0; i < values1.Length; i++)
                {
                    float value = values1[i] - values2[i];
                    score += fromBlackToWhite ? value : -value;
                }
            }
            else
            {
                for (int i = 0; i < values1.Length; i++)
                {
                    float value = values3[i] - values1[i];
                    score += fromBlackToWhite ? value : -value;
                }
            }
            return score;
        }
    }
}

使用该函数时，需要传入以下参数：

- `image`：输入图像。
- `minRadius`：找圆扇形区域的最小半径。
- `maxRadius`：找圆扇形区域的最大半径。
- `center`：找圆扇形中心点。
- `startAngle`：扇形区域起始角度。
- `endAngle`：扇形区域结束角度。
- `caliperCount`：Caliper个数。
- `caliperWidth`：Caliper宽度。
- `caliperLength`：Caliper长度。
- `fromInside`：是否从内到外找圆心。
- `fromBlackToWhite`：是否从黑到白找圆心。

该函数返回找到的圆心坐标。