using OpenCvSharp;
using System;
using System.Collections.Generic;
using System.Drawing;
using System.Drawing.Imaging;
using System.IO;
using System.Linq;
using System.Text;
using System.Threading.Tasks;

namespace OpenCvSharpTest
{
    public static class ReadCodeTest
    {
        public static string Read10CodeTest1(Bitmap Bitmapimage)
        {
            bool IsShuZhi = false;

            //读取图片
            //Mat image = Cv2.ImRead("D:\\work\\WindowsFormsTest\\TestImage\\20250609165353.jpg");

            Mat image =  BitmapToMat(Bitmapimage);
            Mat gray = new Mat();

            //灰度化预处理
            Cv2.CvtColor(image, gray, ColorConversionCodes.BGR2GRAY);
            Cv2.ImShow("gray", ResizeMat(gray));

            //二值化
            Mat binary = new Mat();
            Cv2.Threshold(gray, binary, 100, 255, ThresholdTypes.Binary);
            //Cv2.ImShow("binary", ResizeMat(binary));

            //计算梯度
            Mat gradX = new Mat();
            if (IsShuZhi)
            {
                Cv2.Sobel(binary, gradX, MatType.CV_32F, 1, 0, 1, 1, 0, BorderTypes.Default);
            }
            else
            {
                Cv2.Sobel(binary, gradX, MatType.CV_32F, 0, 1, 1, 1, 0, BorderTypes.Default);
            }
            //Cv2.ImShow("gradX", ResizeMat(gradX));

            //计算绝对值
            Mat absGradX = new Mat();
            Cv2.ConvertScaleAbs(gradX, absGradX, 1, 0);
            //Cv2.ImShow("absGradX", ResizeMat(absGradX));

            //闭运算
            Mat kernelX = new Mat();
            if (IsShuZhi)
            {
                kernelX = Cv2.GetStructuringElement(MorphShapes.Rect, new OpenCvSharp.Size(80, 5));
            }
            else
            {
                kernelX = Cv2.GetStructuringElement(MorphShapes.Rect, new OpenCvSharp.Size(5, 40));
            }
            Mat closed = new Mat();
            Cv2.MorphologyEx(absGradX, closed, MorphTypes.Close, kernelX);
            Cv2.ImShow("closedimg", ResizeMat(closed));

            //查找轮廓
            OpenCvSharp.Point[][] contours;
            HierarchyIndex[] hierarchy;
            Cv2.FindContours(closed, out contours, out hierarchy, RetrievalModes.Tree, ContourApproximationModes.ApproxSimple);

            List<BlobInfo> filteredBlobs = new List<BlobInfo>();
            int minPixelCount = 1000;
            int maxPixelCount = 6000000;
            double minRectangularity = 0.6; // 最小矩形度


            foreach (OpenCvSharp.Point[] contour in contours)
            {
                double area = Cv2.ContourArea(contour);
                if (area >= minPixelCount && area <= maxPixelCount)
                {// 计算矩形度
                    double rectangularity = CalculateRectangularity(contour);

                    // 矩形度筛选
                    if (rectangularity >= minRectangularity)
                    {
                        // 获取轮廓的边界矩形
                        Rect boundingRect = Cv2.BoundingRect(contour);

                        BlobInfo blobInfo = new BlobInfo
                        {
                            Contour = contour,
                            Area = area,
                            Rectangularity = rectangularity,
                            BoundingRect = boundingRect,
                            Center = new OpenCvSharp.Point(boundingRect.X + boundingRect.Width / 2,
                                             boundingRect.Y + boundingRect.Height / 2)
                        };

                        filteredBlobs.Add(blobInfo);

                        Console.WriteLine($"轮廓 - 面积: {area:F0} 像素, 矩形度: {rectangularity:F2}");
                    }
                }
            }

            // 在原图上绘制筛选后的轮廓
            //Mat outputImage = new Mat();
            //foreach (var blobInfo in filteredBlobs)
            //{
            //    Cv2.DrawContours(image, new[] { blobInfo.Contour }, -1, Scalar.Green, 5);
            //}

            //Cv2.ImShow("Output Image", ReadCodeTest.ResizeMat(image));


            //if (contours.Count() == 0)
            //    return "";

            ////筛选矩形并找到最大面积
            //var maxContour = contours.OrderByDescending(c => Cv2.ContourArea(c)).First();
            if (filteredBlobs.Count() == 0)
            {
                Cv2.WaitKey(0);
                return "";
            }
            OpenCvSharp.Rect ShowboundingRect = Cv2.BoundingRect(filteredBlobs.First().Contour);
            //Cv2.Rectangle(image, boundingRect, Scalar.Red, 2);

            OpenCvSharp.Rect roi = new OpenCvSharp.Rect(ShowboundingRect.X + (ShowboundingRect.Width / 4), ShowboundingRect.Y - 25, ShowboundingRect.Width / 2, ShowboundingRect.Height + 50);
            Mat roiMat = binary.SubMat(roi).Clone();
            Cv2.ImShow("roi", ResizeMat(roiMat));

            Mat binary2 = new Mat();
            // 使用THRESH_BINARY_INV反转黑白，黑色物体变为白色区域
            Cv2.Threshold(roiMat, binary2, 128, 255, ThresholdTypes.BinaryInv);

            OpenCvSharp.Point[][] contours1;
            HierarchyIndex[] hierarchy1;
            Cv2.FindContours(binary2, out contours1, out hierarchy1,
                           RetrievalModes.External, ContourApproximationModes.ApproxSimple);

            Console.WriteLine(contours1.Count().ToString());
            var widths = contours1.OrderBy(c => Cv2.BoundingRect(c).Y).Select(c => Cv2.BoundingRect(c).Height).ToArray();

            double ave = widths.Average();
            var CodeResult = widths.Select(w => w > ave ? 1 : 0).ToArray();
            Console.WriteLine(string.Join("", CodeResult));


            //// 显示结果
            //Cv2.ImShow("Result", ResizeMat(image));
            Cv2.WaitKey(0);

            ////显示结果
            //Cv2.DestroyAllWindows();
            image.Dispose();

            return string.Join("", CodeResult);
            //return "";
        }

        public static void FindOcrCode()
        {
            Mat image1 = Cv2.ImRead("D:\\work\\WindowsFormsTest\\TestImage\\wechat_2025-09-03_112903_716.png");
            Mat image2 = Cv2.ImRead("D:\\work\\WindowsFormsTest\\TestImage\\wechat_2025-09-03_112903_716_1.png");
            // 查找轮廓
            OpenCvSharp.Point[][] contours1;
            OpenCvSharp.Point[][] contours2;
            Cv2.FindContours(image1, out contours1, out _, RetrievalModes.External, ContourApproximationModes.ApproxSimple);
            Cv2.FindContours(image2, out contours2, out _, RetrievalModes.External, ContourApproximationModes.ApproxSimple);

            // 轮廓匹配
            double similarity = Cv2.MatchShapes(contours1[0], contours2[0], ShapeMatchModes.I1);

            // 相似度值越小表示轮廓越相似
            if (similarity < 0.1)
            {
                Console.WriteLine("轮廓非常相似");
            }
        }

        public static Mat ResizeMat(Mat mat)
        {
            Mat resizedImage = new Mat();
            double maxSize = 800;
            double scale = Math.Min(maxSize / mat.Width, maxSize / mat.Height);
            OpenCvSharp.Size scaledSize = new OpenCvSharp.Size(mat.Width * scale, mat.Height * scale);
            Cv2.Resize(mat, resizedImage, scaledSize);
            return resizedImage;
        }

        /// <summary>
        /// 将Bitmap转换为Mat(输出为彩色图)
        /// 转换后的图像可以增加彩色框
        /// </summary>
        /// <param name="bitmap">源Bitmap</param>
        /// <returns>对应的Mat对象</returns>
        static Mat BitmapToMat(Bitmap bitmap)
        {
            using (var ms = new MemoryStream())
            {
                bitmap.Save(ms, ImageFormat.Bmp);
                ms.Position = 0;
                return Mat.FromStream(ms, ImreadModes.Color);
            }
        }

        /// <summary>
        /// 计算轮廓的矩形度
        /// 矩形度 = 轮廓面积 / 最小外接矩形面积
        /// </summary>
        /// <param name="contour">轮廓点集</param>
        /// <returns>矩形度值 (0-1)</returns>
        static double CalculateRectangularity(OpenCvSharp.Point[] contour)
        {
            // 计算轮廓面积
            double contourArea = Cv2.ContourArea(contour);

            // 获取最小外接矩形
            RotatedRect minAreaRect = Cv2.MinAreaRect(contour);

            // 计算最小外接矩形面积
            double rectArea = minAreaRect.Size.Width * minAreaRect.Size.Height;

            // 避免除零错误
            if (rectArea <= 0)
                return 0;

            // 计算矩形度
            double rectangularity = contourArea / rectArea;

            // 确保值在合理范围内
            return Math.Max(0, Math.Min(1, rectangularity));
        }
    }
}