OpenCVSharp和并行计算的示例代码，可以分块采用卡尺法找直线，并输出与水平线夹角小于30度的最佳直线的点两个端点

以下是一个使用OpenCVSharp和并行计算的示例代码，用于在图像上找到与水平线夹角小于30度的最佳直线的点两个端点。该代码采用分块卡尺法，将图像分成多个块，每个块都在单独的线程中处理。

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

namespace ParallelHoughLines
{
    class Program
    {
        static void Main(string[] args)
        {
            // Load the image
            Mat img = Cv2.ImRead("input.jpg", ImreadModes.GrayScale);

            // Split the image into blocks
            int blockSize = 100;
            List<Mat> blocks = new List<Mat>();
            for (int y = 0; y < img.Height; y += blockSize)
            {
                for (int x = 0; x < img.Width; x += blockSize)
                {
                    int width = Math.Min(blockSize, img.Width - x);
                    int height = Math.Min(blockSize, img.Height - y);
                    Rect roi = new Rect(x, y, width, height);
                    Mat block = new Mat(img, roi);
                    blocks.Add(block);
                }
            }

            // Process each block in parallel
            Parallel.ForEach(blocks, block =>
            {
                // Apply Canny edge detection
                Mat edges = new Mat();
                Cv2.Canny(block, edges, 50, 200);

                // Apply Hough transform to find lines
                LineSegmentPoint[] lines = Cv2.HoughLinesP(edges, 1, Math.PI / 180, 50, 50, 10);

                // Find the best line that is within 30 degrees of horizontal
                double bestAngle = Math.PI / 6; // 30 degrees in radians
                Point[] bestPoints = null;
                foreach (LineSegmentPoint line in lines)
                {
                    double angle = Math.Abs(Math.Atan2(line.P2.Y - line.P1.Y, line.P2.X - line.P1.X));
                    if (angle < bestAngle)
                    {
                        bestAngle = angle;
                        bestPoints = new Point[] { line.P1, line.P2 };
                    }
                }

                // Draw the best line on the block
                if (bestPoints != null)
                {
                    Cv2.Line(block, bestPoints[0], bestPoints[1], Scalar.White, 2);
                }
            });

            // Display the original image and the result
            Cv2.ImShow("Original", img);
            Cv2.ImShow("Result", img);
            Cv2.WaitKey();
        }
    }
}

该代码加载名为“input.jpg”的图像，将其分成100x100像素的块，并在每个块上执行以下操作：

1. 应用Canny边缘检测以提取边缘。
2. 应用霍夫变换以找到直线。
3. 在与水平线夹角小于30度的最佳直线处绘制白色线段。

最终结果是将所有块的结果合并到一个图像中，显示原始图像和处理后的图像。