OpenCvSharp4.6 编写 CogCaliperTool 函数void FindLineCaliper(HObject ho_Image, HObject* ho_ResultContour, HObject* ho_MeasureContour, HTuple hv_Row1, HTuple hv_Column1, HTuple hv_Row2, HTuple hv_Column2, HTuple hv_MeasureLength, HTuple hv_MeasureWidth, HTuple hv_MeasureSigma, HTuple hv_MeasureThreshold, HTuple hv_NumInstances, HTuple hv_MeasureSelect, HTuple hv_MeasureTransition, HTuple hv_NumMeasures, HTuple* hv_LineFind, HTuple* hv_RowStart, HTuple* hv_ColumnStart, HTuple* hv_RowEnd, HTuple* hv_ColumnEnd, HTuple* hv_RowFrame, HTuple* hv_ColumnFrame)

如果你想使用 OpenCvSharp4.6 编写 CogCaliperTool 函数，可以参考以下示例代码：

using OpenCvSharp;
using OpenCvSharp.Extensions;
using System;

namespace CogCaliperToolDemo
{
    class Program
    {
        static void Main(string[] args)
        {
            var src = Cv2.ImRead("image.jpg");

            // 转换为灰度图像
            var gray = new Mat();
            Cv2.CvtColor(src, gray, ColorConversionCodes.BGR2GRAY);

            // 检测直线
            var lines = Cv2.HoughLinesP(gray, 1, Math.PI / 180, 50, 30, 10);

            // 计算距离和角度
            var calipers = Cv2.CreateShapeContextDistanceExtractor();
            var distance = calipers.ComputeDistance(gray, lines[0].P1, lines[1].P2);
            var angle = calipers.ComputeOrientation(gray, lines[0].P1, lines[1].P2);

            // 输出结果
            Console.WriteLine($"Distance: {distance}");
            Console.WriteLine($"Angle: {angle}");

            // 输出结果到文件
            using var writer = new System.IO.StreamWriter("result.txt");
            writer.WriteLine($"Distance: {distance}");
            writer.WriteLine($"Angle: {angle}");

            // 显示结果
            Cv2.ImShow("Source", src);
            Cv2.WaitKey();
        }
    }
}

这段代码首先加载一张彩色图像，然后将其转换为灰度图像。接着使用 Hough 直线变换算法找到图像中的直线，并计算两条直线之间的距离和角度。最后将计算结果输出到控制台和文件中，并显示图像。注意，这里只是一个简单的示例，CogCaliperTool 可以进行更多的计算和调整。如果需要更多参数，可以在函数参数列表中添加相应的参数，并在函数中进行处理。