hisence-yolo-detection/HisenceYoloDetection/CheckDiffSciHelper.cs

using OpenCvSharp;
using Sunny.UI.Win32;
using System;
using System.Collections.Generic;
using System.Linq;
using System.Security.Cryptography;
using System.Text;
using System.Threading.Tasks;
using Point = OpenCvSharp.Point;
using Size = OpenCvSharp.Size;



namespace HisenceYoloDetection
{
    public static  class CheckDiffSciHelper
    {
        /// <summary>
        /// 
        /// </summary>
        /// <param name="path1">标准图像</param>
        /// <param name="path2">要对比的图像</param>
        /// <param name="IfWhiteWord"> 白板黑字为true </param>
        /// <param name="saveDir">存储路径</param>
        public static bool CheckDiffSci(string path1, Mat MatDet, Rect sqlrect, Rect detrect, bool IfWhiteWord, string saveDir)
        {
            // 读取和处理第一张图片
            Mat img1 = Cv2.ImRead(path1, ImreadModes.Color);
            if (img1.Empty())
            {
                Console.WriteLine($"Error loading image {path1}");
                return false;
            }
            //  Cv2.Resize(img1, img1, new Size(550, 270));
            Mat gimg1 = new Mat();
            Cv2.CvtColor(img1, gimg1, ColorConversionCodes.BGR2GRAY);
            Mat thr1 = new Mat();

            if (IfWhiteWord)
            {
                Cv2.Threshold(gimg1, thr1, 0, 255, ThresholdTypes.BinaryInv | ThresholdTypes.Otsu);
            }
            else
            {
                Cv2.Threshold(gimg1, thr1, 0, 255, ThresholdTypes.Binary | ThresholdTypes.Otsu);
            }




            // 读取和处理第二张图片
            Mat img2 = MatDet.Clone();
            if (img2.Empty())
            {
                // Console.WriteLine($"Error loading image {path2}");
                return false;
            }
            // Cv2.Resize(img2, img2, new Size(550, 270));
            Mat gimg2 = new Mat();
            Cv2.CvtColor(img2, gimg2, ColorConversionCodes.BGR2GRAY);
            Mat thr2 = new Mat();
            //Cv2.Threshold(gimg2, thr2, 0, 255, ThresholdTypes.BinaryInv | ThresholdTypes.Otsu);
            if (IfWhiteWord)
            {
                Cv2.Threshold(gimg2, thr2, 0, 255, ThresholdTypes.BinaryInv | ThresholdTypes.Otsu);
            }
            else
            {
                Cv2.Threshold(gimg2, thr2, 0, 255, ThresholdTypes.Binary | ThresholdTypes.Otsu);
            }
           

            //Rect  area2 = new Rect(148,30,229,222);
            sqlrect.Width += 20;
            detrect.Width += 20;
            Mat matCutblack1 = new Mat(thr1, sqlrect);
            if (IfWhiteWord)
            {
                matCutblack1.SetTo(Scalar.Black);
            }
            else
            {
                matCutblack1.SetTo(Scalar.Black);
            }
            Mat matCutblack2 = new Mat(thr2, detrect);
            if (IfWhiteWord)
            {
                matCutblack2.SetTo(Scalar.Black);
            }
            else
            {
                matCutblack2.SetTo(Scalar.Black);
            }
            Cv2.Resize(thr1, thr1, new Size(550, 270));
            Cv2.Resize(thr2, thr2, new Size(550, 270));

            string filename = dt.Year.ToString() + dt.Month.ToString() + dt.Day.ToString() + dt.Hour.ToString() + dt.Minute.ToString() + dt.Millisecond.ToString();

            string savePath4 = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path1) + filename + "_thr1.png");
            // 保存结果

            Cv2.ImWrite(savePath4, thr1);
            string savePath3 = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path1) + filename + "_thr2.png");
            // 保存结果

            Cv2.ImWrite(savePath3, thr2);

            // 创建卷积核
            Mat filter1 = new Mat(5, 5, MatType.CV_32F, new Scalar(0));
            filter1.Row(2).SetTo(new Scalar(0.025));
            filter1.Col(2).SetTo(new Scalar(0.025));

            // 应用卷积
            Mat final_result1 = new Mat();
            Cv2.Filter2D(thr1, final_result1, -1, filter1, anchor: new Point(-1, -1), 0, BorderTypes.Reflect);
            Cv2.Filter2D(final_result1, final_result1, -1, filter1, anchor: new Point(-1, -1), 0, BorderTypes.Reflect);
            Cv2.Filter2D(final_result1, final_result1, -1, filter1, anchor: new Point(-1, -1), 0, BorderTypes.Reflect);

            Mat final_result2 = new Mat();
            Cv2.Filter2D(thr2, final_result2, -1, filter1, anchor: new Point(-1, -1), 0, BorderTypes.Reflect);
            Cv2.Filter2D(final_result2, final_result2, -1, filter1, anchor: new Point(-1, -1), 0, BorderTypes.Reflect);
            Cv2.Filter2D(final_result2, final_result2, -1, filter1, anchor: new Point(-1, -1), 0, BorderTypes.Reflect);
            //裁剪才行


            //string savePath2 = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path1) + "_final_result1.png");
            //// 保存结果
            ////string savePath = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path2) + "_diff.png");
            //Cv2.ImWrite(savePath2, final_result1);
            //string savePath = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path1) + "_final_result2.png");
            //// 保存结果
            ////string savePath = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path2) + "_diff.png");
            //Cv2.ImWrite(savePath, final_result2);







            // 计算图像差异
            Mat devIMG = new Mat();
            Mat devIMG_ = new Mat();
            Cv2.Subtract(final_result1, final_result2, devIMG);
            Cv2.Subtract(final_result2, final_result1, devIMG_);

            // 对差异图像应用阈值
            Cv2.Threshold(devIMG, devIMG, 50, 255, ThresholdTypes.Binary);
            Cv2.Threshold(devIMG_, devIMG_, 50, 255, ThresholdTypes.Binary);

            // 结合差异
            Mat sumIMG = new Mat();
            Cv2.Add(devIMG, devIMG_, sumIMG);

            // 应用形态学操作
            Mat kernelCL = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 3));
            Mat blackhatImg = new Mat();
            Cv2.Dilate(sumIMG, blackhatImg, kernelCL);

            // 处理轮廓和保存结果
            Point[][] contours = new Point[10000][];
            Cv2.FindContours(blackhatImg, out contours, out _, RetrievalModes.Tree, ContourApproximationModes.ApproxSimple);
            bool isMatch = true;
            foreach (var contour in contours)
            {
                if (Cv2.ContourArea(contour) <= 100)
                {
                    Cv2.DrawContours(blackhatImg, new Point[][] { contour }, -1, Scalar.Black, thickness: Cv2.FILLED);
                    // 框选轮廓

                }
                else
                {
                    Rect boundingRect = Cv2.BoundingRect(contour);
                    Cv2.Rectangle(img2, boundingRect, Scalar.Red, thickness: 2);
                    isMatch = false;
                }
            }

            string savePath2 = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path1) + filename + "_Rect.png");
            // 保存结果
            //string savePath = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path2) + "_diff.png");
            Cv2.ImWrite(savePath2, img2);
            string savePath = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path1) + filename + "_diff.png");
            // 保存结果
            //string savePath = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path2) + "_diff.png");
            Cv2.ImWrite(savePath, blackhatImg);
            return isMatch;
        }

      
        public static Rect strChangeRect(string strrect)
        {
            if (!string.IsNullOrEmpty(strrect))
            {
                string[] rectstr = strrect.Split(",");
                int areaX = int.Parse(rectstr[0]);
                int areaY = int.Parse(rectstr[1]);
                int areaWidth = int.Parse(rectstr[2]);
                int areaHeight = int.Parse(rectstr[3]);

                Rect rect = new Rect(areaX, areaY, areaWidth, areaHeight);
                return rect;
            }else
            {
                return new Rect(0,0,0, 0);
            }
            
        }

        public static string  rectChangeStr(Rect area)
        {
            string[] rectsql = new string[4];
            rectsql[0] = Convert.ToString(area.X);
            rectsql[1] = Convert.ToString(area.Y);
            rectsql[2] = Convert.ToString(area.Width);
            rectsql[3] = Convert.ToString(area.Height);

            string strrect = rectsql.Join(",");
            return strrect;
        }
        //public static void CheckDiffSci(string path1, string path2, bool IfWhiteWord, string saveDir)
        //{
        //    // 读取和处理第一张图片
        //    Mat img1 = Cv2.ImRead(path1, ImreadModes.Color);
        //    if (img1.Empty())
        //    {
        //        Console.WriteLine($"Error loading image {path1}");
        //        return;
        //    }
        //    Cv2.Resize(img1, img1, new Size(550, 270));
        //    Mat gimg1 = new Mat();
        //    Cv2.CvtColor(img1, gimg1, ColorConversionCodes.BGR2GRAY);
        //    Mat thr1 = new Mat();

        //    if (IfWhiteWord)
        //    {
        //        Cv2.Threshold(gimg1, thr1, 0, 255, ThresholdTypes.BinaryInv | ThresholdTypes.Otsu);
        //    }
        //    else
        //    {
        //        Cv2.Threshold(gimg1, thr1, 0, 255, ThresholdTypes.Binary | ThresholdTypes.Otsu);
        //    }


        //    string savePath4 = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path2) + "_thr1.png");
        //    // 保存结果
        //    //string savePath = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path2) + "_diff.png");
        //    Cv2.ImWrite(savePath4, thr1);

        //    // 读取和处理第二张图片
        //    Mat img2 = Cv2.ImRead(path2, ImreadModes.Color);
        //    if (img2.Empty())
        //    {
        //        Console.WriteLine($"Error loading image {path2}");
        //        return;
        //    }
        //    Cv2.Resize(img2, img2, new Size(550, 270));
        //    Mat gimg2 = new Mat();
        //    Cv2.CvtColor(img2, gimg2, ColorConversionCodes.BGR2GRAY);
        //    Mat thr2 = new Mat();
        //    //Cv2.Threshold(gimg2, thr2, 0, 255, ThresholdTypes.BinaryInv | ThresholdTypes.Otsu);
        //    if (IfWhiteWord)
        //    {
        //        Cv2.Threshold(gimg2, thr2, 0, 255, ThresholdTypes.BinaryInv | ThresholdTypes.Otsu);
        //    }
        //    else
        //    {
        //        Cv2.Threshold(gimg2, thr2, 0, 255, ThresholdTypes.Binary | ThresholdTypes.Otsu);
        //    }
        //    // Cv2.Threshold(gimg2, thr2, 0, 255, ThresholdTypes.Binary | ThresholdTypes.Otsu);

        //    string savePath3 = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path2) + "_thr2.png");
        //    // 保存结果
        //    //string savePath = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path2) + "_diff.png");
        //    Cv2.ImWrite(savePath3, thr2);

        //    // 创建卷积核
        //    Mat filter1 = new Mat(17, 17, MatType.CV_32F, new Scalar(0));
        //    filter1.Row(8).SetTo(new Scalar(0.025));
        //    filter1.Col(8).SetTo(new Scalar(0.025));

        //    // 应用卷积
        //    Mat final_result1 = new Mat();
        //    Cv2.Filter2D(thr1, final_result1, -1, filter1, anchor: new Point(-1, -1), 0, BorderTypes.Reflect);
        //    Cv2.Filter2D(final_result1, final_result1, -1, filter1, anchor: new Point(-1, -1), 0, BorderTypes.Reflect);
        //    Cv2.Filter2D(final_result1, final_result1, -1, filter1, anchor: new Point(-1, -1), 0, BorderTypes.Reflect);

        //    Mat final_result2 = new Mat();
        //    Cv2.Filter2D(thr2, final_result2, -1, filter1, anchor: new Point(-1, -1), 0, BorderTypes.Reflect);
        //    Cv2.Filter2D(final_result2, final_result2, -1, filter1, anchor: new Point(-1, -1), 0, BorderTypes.Reflect);
        //    Cv2.Filter2D(final_result2, final_result2, -1, filter1, anchor: new Point(-1, -1), 0, BorderTypes.Reflect);

        //    // 计算图像差异
        //    Mat devIMG = new Mat();
        //    Mat devIMG_ = new Mat();
        //    Cv2.Subtract(final_result1, final_result2, devIMG);
        //    Cv2.Subtract(final_result2, final_result1, devIMG_);

        //    // 对差异图像应用阈值
        //    Cv2.Threshold(devIMG, devIMG, 50, 255, ThresholdTypes.Binary);
        //    Cv2.Threshold(devIMG_, devIMG_, 50, 255, ThresholdTypes.Binary);

        //    // 结合差异
        //    Mat sumIMG = new Mat();
        //    Cv2.Add(devIMG, devIMG_, sumIMG);

        //    // 应用形态学操作
        //    Mat kernelCL = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 3));
        //    Mat blackhatImg = new Mat();
        //    Cv2.Dilate(sumIMG, blackhatImg, kernelCL);

        //    // 处理轮廓和保存结果
        //    Point[][] contours = new Point[10000][];
        //    Cv2.FindContours(blackhatImg, out contours, out _, RetrievalModes.Tree, ContourApproximationModes.ApproxSimple);

        //    foreach (var contour in contours)
        //    {
        //        if (Cv2.ContourArea(contour) <= 100)
        //        {
        //            Cv2.DrawContours(blackhatImg, new Point[][] { contour }, -1, Scalar.Black, thickness: Cv2.FILLED);
        //            // 框选轮廓

        //        }
        //        else
        //        {
        //            Rect boundingRect = Cv2.BoundingRect(contour);
        //            Cv2.Rectangle(img2, boundingRect, Scalar.Red, thickness: 2);
        //        }
        //    }
        //    string savePath2 = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path2) + "_Rect.png");
        //    // 保存结果
        //    //string savePath = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path2) + "_diff.png");
        //    Cv2.ImWrite(savePath2, img2);
        //    string savePath = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path2) + "_diff.png");
        //    // 保存结果
        //    //string savePath = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path2) + "_diff.png");
        //    Cv2.ImWrite(savePath, blackhatImg);
        //}
    }
}