using OpenCvSharp;
using System;
using System.Drawing;
using System.IO;
using System.Linq;
using System.Drawing.Imaging;
using OpenCvSharp.Extensions;
using System.Collections.Concurrent;
using System.Threading.Tasks;
using System.Diagnostics;
using System.Threading;
//cyf
public class ProcessImg
{
    // 对单个图像进行模板匹配
   
    public static (double score, Rect? coords) MatchTemplate(Mat img, string templatePath)
    {
        // 确保图像和模板文件存在


        // 读取图像和模板
        
        var template = Cv2.ImRead(templatePath, ImreadModes.Color);

        // 创建一个模板匹配的结果矩阵
        var result = new Mat();
        Cv2.MatchTemplate(img, template, result, TemplateMatchModes.CCoeffNormed);

        // 查找最大匹配值
        Cv2.MinMaxLoc(result, out _, out var maxVal, out _, out var maxLoc);

        // 如果找到的最大匹配值大于阈值
        double threshold = 0.3; // 可以根据需要调整阈值
        if (maxVal >= threshold)
        {
            // 计算匹配的坐标     
            var topLeft = maxLoc;
            var rect = new Rect(topLeft.X, topLeft.Y, template.Width, template.Height);

            return (maxVal, rect);
        }

        return (0, null);
    }   

    // 遍历文件夹中的所有图像文件进行模板匹配，并找到最佳得分图像
    public static Double ProcessImagesInFolder(string folderPath, Mat img)
    {
        // 获取所有图像文件
        var imageFiles = Directory.GetFiles(folderPath, "*.*", SearchOption.TopDirectoryOnly)
            .Where(file => file.EndsWith(".jpg", StringComparison.OrdinalIgnoreCase) ||
                           file.EndsWith(".png", StringComparison.OrdinalIgnoreCase) ||
                           file.EndsWith(".bmp", StringComparison.OrdinalIgnoreCase))
            .ToList();

      

        // 确保输出文件夹存在
        

        // 线程数量
        int numThreads = 5;

        // 用于存储每个图像的得分和坐标
        var bestMatch = new ConcurrentBag<(string imagePath, double score, Rect? coords)>();
        DateTime startTime = DateTime.Now;
        Stopwatch sw = new Stopwatch();
        sw.Start();

        Parallel.ForEach(imageFiles, new ParallelOptions { MaxDegreeOfParallelism = numThreads }, picPath =>
        {
            DateTime threadStartTime = DateTime.Now;

            var (score, coords) = MatchTemplate(img, picPath);

            
            
                bestMatch.Add((picPath, score, coords));
            

            DateTime threadEndTime = DateTime.Now;
            TimeSpan threadElapsed = threadEndTime - threadStartTime;
            Console.WriteLine($"线程处理 {picPath} 耗时: {threadElapsed.TotalMilliseconds}ms");
        });

        sw.Stop();
        TimeSpan totalElapsed = sw.Elapsed;
        Console.WriteLine($"处理完成，耗时: {totalElapsed.TotalSeconds}秒");
        // 查找最佳得分
        var best = bestMatch.OrderByDescending(m => m.score).FirstOrDefault();
        return best.score;
        //if (best.coords.HasValue)
        //{
        //    Rect rect = best.coords.Value;
        //    return rect;
        //}

        //else
        //{
        //    return new Rect(0, 0, 0, 0);
        //}
       

    }
    public static Mat BitmapToMat(Bitmap bitmap)
    {
        if (bitmap == null)
        {
            throw new ArgumentException("Bitmap is null");
        }

        // 根据 Bitmap 的宽度、高度和像素格式创建一个与其相对应的 Mat
        Mat mat = new Mat(bitmap.Height, bitmap.Width, MatType.CV_8UC3); // 假设 Bitmap 是 24-bit RGB

        // 锁定 Bitmap 的内存区域以直接访问它的内存
        BitmapData bitmapData = bitmap.LockBits(
            new Rectangle(0, 0, bitmap.Width, bitmap.Height),
            ImageLockMode.ReadOnly,
            bitmap.PixelFormat
        );

        try
        {
            // 使用直接内存拷贝将 Bitmap 的数据拷贝到 Mat
            unsafe
            {
                byte* srcData = (byte*)bitmapData.Scan0;
                byte* dstData = (byte*)mat.DataPointer;

                int stride = bitmapData.Stride;
                int width = bitmap.Width * 3; // 24bpp 3个字节一个像素
                int height = bitmap.Height;

                for (int y = 0; y < height; y++)
                {
                    Buffer.MemoryCopy(srcData + y * stride, dstData + y * mat.Step(), width, width);
                }
            }
        }
        finally
        {
            bitmap.UnlockBits(bitmapData);
        }

        return mat;
    }


}