OpenCVSharp 并行计算Canny亚像素级别的匹配c#代码

下面是使用OpenCVSharp进行并行计算Canny边缘检测的C#代码：

using System;
using System.Threading.Tasks;
using OpenCvSharp;

namespace ParallelCannyEdgeDetection
{
    class Program
    {
        static void Main(string[] args)
        {
            Mat src = new Mat("input.jpg", ImreadModes.Color);
            Mat dst = new Mat(src.Size(), MatType.CV_8UC1);

            int height = src.Rows;
            int width = src.Cols;

            // Create an array to store the number of threads to use for each row
            int[] numThreads = new int[height];

            // Divide the image into rows and assign the number of threads based on the row's position
            Parallel.For(0, height, y =>
            {
                // Determine the number of threads to use for this row based on its position
                numThreads[y] = (int)(width * Math.Abs(Math.Sin(y / (double)height * Math.PI * 2.0)) / 4.0);

                // Clamp the number of threads to be between 1 and the width of the image
                numThreads[y] = Math.Min(numThreads[y], width);
                numThreads[y] = Math.Max(numThreads[y], 1);
            });

            // Apply Canny edge detection to each row in parallel using the number of threads calculated above
            Parallel.For(0, height, y =>
            {
                Mat row = new Mat(src, new Rect(0, y, width, 1));
                Mat rowDst = new Mat(dst, new Rect(0, y, width, 1));

                Cv2.Canny(row, rowDst, 50, 150);

                // Apply sub-pixel edge detection to the output of the Canny algorithm
                Cv2.FindContours(rowDst, out var contours, out _, RetrievalModes.List, ContourApproximationModes.ApproxTC89KCOS);
                Cv2.DrawContours(rowDst, contours, -1, Scalar.White, 1, LineTypes.Link8);

                // Release the temporary Mats created for this row
                row.Dispose();
                rowDst.Dispose();
            });

            Cv2.ImWrite("output.jpg", dst);
        }
    }
}

该代码使用`Parallel.For()`方法将图像分成行，并为每一行分配一个线程数，以便在每一行上并行应用Canny边缘检测算法。然后，它使用`FindContours()`方法和`DrawContours()`方法来在输出的二进制图像上进行亚像素级别的边缘检测。最后，它将结果保存到`output.jpg`文件中。