1

HisenceYoloDetection/CheckDiffSciHelper.cs

@@ -1,20 +1,70 @@
 using OpenCvSharp;
+using OpenCvSharp.Flann;
+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 static System.Net.Mime.MediaTypeNames;
 using Point = OpenCvSharp.Point;
 using Size = OpenCvSharp.Size;
-
-
+using System;
+using OpenCvSharp;
+using OpenCvSharp.Features2D;
+using OpenCvSharp.Flann;
+using System.Drawing;
 
 namespace HisenceYoloDetection
 {
     public static class CheckDiffSciHelper
     {
 
+
+        public static Mat ProcessImage(Mat image, Rect fillRect)
+        {
+            // 获取图像尺寸
+            int width = image.Width;
+            int height = image.Height;
+
+            // 定义左下角 30x30 矩形框
+            int rectSize = 30;
+            int rectX = 0;
+            int rectY = height - rectSize; // 确保是左下角
+
+            // 检查左下角矩形框是否在图像范围内
+            if (rectY < 0 || rectX < 0 || rectSize > width || rectSize > height)
+            {
+                Console.WriteLine("图像尺寸不足以获取指定区域");
+                return image;
+            }
+
+            // 定义感兴趣区域 (ROI) 并计算其平均颜色
+            Rect roi = new Rect(rectX, rectY, rectSize, rectSize);
+            Mat roiMat = new Mat(image, roi);
+            Scalar meanColor = Cv2.Mean(roiMat);
+
+            // 创建 Scalar 类型的颜色填充
+            Scalar fillColor = new Scalar(meanColor.Val0, meanColor.Val1, meanColor.Val2);
+
+            // 修改 fillRect 的 Y 和 Height 属性以覆盖整个图像的高度
+            fillRect.Y = 0;             // 起始位置为顶部
+            fillRect.Height = height;   // 高度覆盖整个图像
+
+            // 检查填充矩形是否在图像范围内
+            if (fillRect.X < 0 || fillRect.X + fillRect.Width > width)
+            {
+                Console.WriteLine("填充区域超出图像范围");
+                return image;
+            }
+
+            // 使用 OpenCV 的 rectangle 函数进行填充
+            Cv2.Rectangle(image, fillRect.TopLeft, fillRect.BottomRight, fillColor, Cv2.FILLED);
+
+            return image;
+        }
+
         /// <summary>
         /// 
         /// </summary>
@@ -22,9 +72,9 @@ namespace HisenceYoloDetection
         /// <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)
+        public static bool CheckDiffSci(string path1, Mat MatDet, ref Mat ResultMat,Rect sqlrect, Rect detrect, bool IfWhiteWord, string saveDir,string SN)
         {
-            // 读取和处理第一张图片
+            // 读取和处理第一张图片。。
             Mat img1 = Cv2.ImRead(path1, ImreadModes.Color);
             if (img1.Empty())
             {
@@ -32,11 +82,12 @@ namespace HisenceYoloDetection
                 return false;
             }
             //  Cv2.Resize(img1, img1, new Size(550, 270));
+            img1 = ProcessImage(img1, sqlrect);
             Mat gimg1 = new Mat();
             Cv2.CvtColor(img1, gimg1, ColorConversionCodes.BGR2GRAY);
             Mat thr1 = new Mat();
 
-           if(IfWhiteWord)
+            if (IfWhiteWord)
             {
                 Cv2.Threshold(gimg1, thr1, 0, 255, ThresholdTypes.BinaryInv | ThresholdTypes.Otsu);
             }
@@ -50,12 +101,16 @@ namespace HisenceYoloDetection
 
             // 读取和处理第二张图片
             Mat img2 = MatDet.Clone();
+            ResultMat= MatDet.Clone();
             if (img2.Empty())
             {
                 // Console.WriteLine($"Error loading image {path2}");
                 return false;
             }
             // Cv2.Resize(img2, img2, new Size(550, 270));
+            img2 = ProcessImage(img2, detrect);
+            Rect bottomleftRect= new Rect(0,img1.Height-30,30,30);
+            Scalar avgColor1 = Cv2.Mean(new Mat(img1,bottomleftRect));
             Mat gimg2 = new Mat();
             Cv2.CvtColor(img2, gimg2, ColorConversionCodes.BGR2GRAY);
             Mat thr2 = new Mat();
@@ -68,14 +123,15 @@ namespace HisenceYoloDetection
             {
                 Cv2.Threshold(gimg2, thr2, 0, 255, ThresholdTypes.Binary | ThresholdTypes.Otsu);
             }
-            // Cv2.Threshold(gimg2, thr2, 0, 255, ThresholdTypes.Binary | ThresholdTypes.Otsu);
-
 
 
             //Rect  area2 = new Rect(148,30,229,222);
             sqlrect.Width += 20;
+            sqlrect.Height+= 100;
             detrect.Width += 20;
+            detrect.Height+=100;
             Mat matCutblack1 = new Mat(thr1, sqlrect);
+
             if (IfWhiteWord)
             {
                 matCutblack1.SetTo(Scalar.Black);
@@ -95,17 +151,17 @@ namespace HisenceYoloDetection
             }
             Cv2.Resize(thr1, thr1, new Size(550, 270));
             Cv2.Resize(thr2, thr2, new Size(550, 270));
-            DateTime dt= DateTime.Now;
-           string filename= dt.Year.ToString() + dt.Month.ToString() + dt.Day.ToString() + dt.Hour.ToString() + dt.Minute.ToString() + dt.Millisecond.ToString();
+            DateTime dt = DateTime.Now;
+            string filename = SN;
 
-            string savePath4 = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path1) + filename+"_thr1.png");
+           // 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");
+            //Cv2.ImWrite(savePath4, thr1);
+            //string savePath3 = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path1) + filename + "_thr2.png");
             // 保存结果
 
-            Cv2.ImWrite(savePath3, thr2);
+            //Cv2.ImWrite(savePath3, thr2);
 
             // 创建卷积核
             Mat filter1 = new Mat(15, 15, MatType.CV_32F, new Scalar(0));
@@ -125,6 +181,255 @@ namespace HisenceYoloDetection
             //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_);
+            //string savePathd = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path1) + filename + "devIMG.png");
+            //// 保存结果
+
+            //Cv2.ImWrite(savePathd, devIMG);
+            //string savePathd1 = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path1) + filename + "devIMG_.png");
+            //// 保存结果
+
+            //Cv2.ImWrite(savePathd1, devIMG_);
+            // 对差异图像应用阈值
+            Cv2.Threshold(devIMG, devIMG, 20, 255, ThresholdTypes.Binary);
+            Cv2.Threshold(devIMG_, devIMG_, 20, 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) <= 500)
+                {
+                    Cv2.DrawContours(blackhatImg, new Point[][] { contour }, -1, Scalar.Black, thickness: Cv2.FILLED);
+                    // 框选轮廓
+                    //string savePath2 = Path.Combine("D:\\Hisence\\Test\\2\\ok", 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("D:\\Hisence\\Test\\2\\ok", Path.GetFileNameWithoutExtension(path1) + filename + "_diff.png");
+                    // 保存结果
+                    //string savePath = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path2) + "_diff.png");
+                   // Cv2.ImWrite(savePath, blackhatImg);
+                }
+                else
+                {
+                    Rect boundingRect = Cv2.BoundingRect(contour);
+                     Cv2.Resize(img2, img2, new Size(550, 270));
+                    Cv2.Rectangle(img2, boundingRect, Scalar.Red, thickness: 2);
+                    isMatch = false;
+                    string savePath2 = Path.Combine("D:\\Hisence\\Test\\2\\ng",filename + "_Rect.png");
+                    // 保存结果
+                    //string savePath = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path2) + "_diff.png");
+                    Cv2.ImWrite(savePath2, img2);
+                    CheckDiffSciHelper1.ResizeImage(savePath2, savePath2, 640, 480, 75);
+
+                    ResultMat = img2.Clone();
+                   string savePath = Path.Combine("D:\\Hisence\\Test\\2\\ng", Path.GetFileNameWithoutExtension(path1) + filename + "_diff.png");
+                    // 保存结果
+                    //string savePath = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path2) + "_diff.png");
+                    Cv2.ImWrite(savePath, blackhatImg);
+                }
+            }
+
+            // 新增的白色面积占比判断
+            double whiteArea1 = Cv2.CountNonZero(thr1);
+            double whiteArea2 = Cv2.CountNonZero(thr2);
+            double ratio1 = whiteArea1 / (thr1.Rows * thr1.Cols);
+            double ratio2 = whiteArea2 / (thr2.Rows * thr2.Cols);
+
+            if (Math.Abs(ratio1 - ratio2) >= 0.90)
+            {
+                isMatch = true;
+            }
+
+            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 class CheckDiffSciHelper1
+        {
+            /// <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,string SN)
+            {
+                // 读取和处理第一张图片
+                Mat img1 = Cv2.ImRead(path1, ImreadModes.Color);
+
+                if (img1.Empty())
+                {
+                    Console.WriteLine($"Error loading image {path1}");
+                    return false;
+                }
+                //  Cv2.Resize(img1, img1, new Size(550, 270));
+                img1 = RemoveBorders(img1);
+                Mat gimg1 = new Mat();
+                Cv2.CvtColor(img1, gimg1, ColorConversionCodes.BGR2GRAY);
+                Mat thr1 = new Mat();
+
+                if (IfWhiteWord)
+                {
+                    Cv2.Threshold(gimg1, thr1, 0, 255, ThresholdTypes.BinaryInv | ThresholdTypes.Otsu);
+                }
+                else
+                {
+                    Cv2.Threshold(gimg1, thr1, 0, 255, ThresholdTypes.Binary | ThresholdTypes.Otsu);
+                }
+
+
+
+
+                // 读取和处理第二张图片
+                Mat img2 = MatDet.Clone();
+                if (img2.Empty())
+                {
+                    // Console.WriteLine($"Error loading image {path2}");
+                    return false;
+                }
+                // Cv2.Resize(img2, img2, new Size(550, 270));
+                img2 = RemoveBorders(img2);
+                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;
+                sqlrect.Height += 20;
+                detrect.Width += 20;
+                detrect.Height += 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(845, 498));
+                Cv2.Resize(thr2, thr2, new Size(845, 498));
+                DateTime dt = DateTime.Now;
+                string filename = SN;
+
+                //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(15, 15, MatType.CV_32F, new Scalar(0));
+                filter1.Row(7).SetTo(new Scalar(0.025));
+                filter1.Col(7).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);
+
+                //Cv2.Filter2D(final_result1, final_result1, -1, filter2, 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);
+
+                //Cv2.Filter2D(final_result2, final_result2, -1, filter2, 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");
@@ -145,15 +450,25 @@ namespace HisenceYoloDetection
                 Mat devIMG_ = new Mat();
                 Cv2.Subtract(final_result1, final_result2, devIMG);
                 Cv2.Subtract(final_result2, final_result1, devIMG_);
+                //string savePathd = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path1) + filename + "devIMG.png");
+                // 保存结果
 
+               // Cv2.ImWrite(savePathd, devIMG);
+                //string savePathd1 = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path1) + filename + "devIMG_.png");
+                // 保存结果
+
+                //Cv2.ImWrite(savePathd1, 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);
+                Cv2.Threshold(devIMG, devIMG, 8, 255, ThresholdTypes.Binary);
+                Cv2.Threshold(devIMG_, devIMG_, 8, 255, ThresholdTypes.Binary);
 
                 // 结合差异
                 Mat sumIMG = new Mat();
                 Cv2.Add(devIMG, devIMG_, sumIMG);
+                //string savePaths = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path1) + filename + "sumIMG.png");
+                // 保存结果
 
+                //Cv2.ImWrite(savePaths, sumIMG);
                 // 应用形态学操作
                 Mat kernelCL = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 3));
                 Mat blackhatImg = new Mat();
@@ -165,7 +480,7 @@ namespace HisenceYoloDetection
                 bool isMatch = true;
                 foreach (var contour in contours)
                 {
-                if (Cv2.ContourArea(contour) <= 100)
+                    if (Cv2.ContourArea(contour) <= 500)
                     {
                         Cv2.DrawContours(blackhatImg, new Point[][] { contour }, -1, Scalar.Black, thickness: Cv2.FILLED);
                         // 框选轮廓
@@ -175,168 +490,142 @@ namespace HisenceYoloDetection
                     {
                         Rect boundingRect = Cv2.BoundingRect(contour);
                         Cv2.Rectangle(img2, boundingRect, Scalar.Red, thickness: 2);
-                    isMatch= false;
+                        isMatch = false;
                     }
                 }
 
-            string savePath2 = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path1) + filename+"_Rect.png");
+                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");
+                //ResizeImage(savePath2, savePath2, 640, 480, 75);
+                //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);
+                //Cv2.ImWrite(savePath, blackhatImg);
                 return isMatch;
             }
 
-        public static Rect strChangeRect(string strrect)
+           public static void ResizeImage(string inputPath, string outputPath, int newWidth, int newHeight, int quality)
             {
-            if (!string.IsNullOrEmpty(strrect))
+                // 加载原始图像
+                using (Mat originalImage = Cv2.ImRead(inputPath))
                 {
-                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]);
+                    // 创建一个Mat对象用于存储缩放后的图像
+                    using (Mat resizedImage = new Mat())
+                    {
+                        // 缩放图像
+                        Cv2.Resize(originalImage, resizedImage, new OpenCvSharp.Size(newWidth, newHeight));
 
-                Rect rect = new Rect(areaX, areaY, areaWidth, areaHeight);
-                return rect;
-            }else
-            {
-                return new Rect(0,0,0, 0);
+                        // 保存图像为JPEG格式，并设置压缩质量
+                        SaveJpeg(outputPath, resizedImage, quality);
+                        Console.WriteLine($"Image saved to {outputPath}");
+                    }
+                }
             }
 
-        }
-
-        public static string  rectChangeStr(Rect area)
+            static void SaveJpeg(string path, Mat image, int quality)
             {
-            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);
+                // 设置JPEG编码参数
+                var encodeParams = new[] { new ImageEncodingParam(ImwriteFlags.JpegQuality, quality) };
 
-            string strrect = rectsql.Join(",");
-            return strrect;
+                // 保存图像
+                Cv2.ImWrite(path, image, encodeParams);
             }
-        //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();
+            static Mat RemoveBorders(Mat image)
+            {
+                // 将图像转换为灰度图
+                Mat grayImage = new Mat();
+                Cv2.CvtColor(image, grayImage, ColorConversionCodes.BGR2GRAY);
 
-        //    if (IfWhiteWord)
-        //    {
-        //        Cv2.Threshold(gimg1, thr1, 0, 255, ThresholdTypes.BinaryInv | ThresholdTypes.Otsu);
-        //    }
-        //    else
-        //    {
-        //        Cv2.Threshold(gimg1, thr1, 0, 255, ThresholdTypes.Binary | ThresholdTypes.Otsu);
-        //    }
+                // 使用自适应二值化将图像变为黑白图
+                Mat binaryImage = new Mat();
+                Cv2.AdaptiveThreshold(grayImage, binaryImage, 255, AdaptiveThresholdTypes.MeanC, ThresholdTypes.Binary, 11, 2);
 
+                // 反转颜色
+                Mat invertedBinaryImage = new Mat();
+                Cv2.BitwiseNot(binaryImage, invertedBinaryImage);
 
-        //    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);
+                // 查找轮廓
+                Point[][] contours;
+                HierarchyIndex[] hierarchy;
+                Cv2.FindContours(invertedBinaryImage, out contours, out hierarchy, RetrievalModes.External, ContourApproximationModes.ApproxSimple);
 
-        //    // 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);
-        //}
+                // 找到包含最大面积的轮廓
+                double maxArea = 0;
+                Point[] maxContour = null;
+                foreach (var contour in contours)
+                {
+                    double area = Cv2.ContourArea(contour);
+                    if (area > maxArea)
+                    {
+                        maxArea = area;
+                        maxContour = contour;
                     }
-}
+                }
+
+                if (maxContour == null)
+                {
+                    Console.WriteLine("未找到有效轮廓！");
+                    return image;
+                }
+
+                // 找到平行四边形的四个顶点
+                Point[] approx = Cv2.ApproxPolyDP(maxContour, Cv2.ArcLength(maxContour, true) * 0.02, true);
+                Point2f[] srcPoints = approx.Select(p => new Point2f(p.X, p.Y)).ToArray();
+
+                if (srcPoints.Length != 4)
+                {
+                    Console.WriteLine("未找到平行四边形的四个顶点！");
+                    return image;
+                }
+
+                // 按顺时针顺序对顶点进行排序
+                srcPoints = OrderPoints(srcPoints);
+
+                // 确定目标图像的四个顶点
+                Point2f[] dstPoints = new Point2f[]
+                {
+            new Point2f(0, 0),
+            new Point2f(image.Width - 1, 0),
+            new Point2f(image.Width - 1, image.Height - 1),
+            new Point2f(0, image.Height - 1)
+                };
+
+                // 计算透视变换矩阵
+                Mat transformMatrix = Cv2.GetPerspectiveTransform(srcPoints, dstPoints);
+
+                // 应用透视变换
+                Mat warpedImage = new Mat();
+                Cv2.WarpPerspective(image, warpedImage, transformMatrix, new Size(image.Width, image.Height));
+
+                return warpedImage;
+            }
+
+            private static Point2f[] OrderPoints(Point2f[] points)
+            {
+                // 对顶点进行排序，顺时针顺序
+                Point2f[] orderedPoints = new Point2f[4];
+
+                // 计算质心
+                Point2f center = new Point2f(points.Average(p => p.X), points.Average(p => p.Y));
+
+                foreach (var point in points)
+                {
+                    if (point.X < center.X && point.Y < center.Y)
+                        orderedPoints[0] = point; // 左上
+                    else if (point.X > center.X && point.Y < center.Y)
+                        orderedPoints[1] = point; // 右上
+                    else if (point.X > center.X && point.Y > center.Y)
+                        orderedPoints[2] = point; // 右下
+                    else if (point.X < center.X && point.Y > center.Y)
+                        orderedPoints[3] = point; // 左下
+                }
+
+                return orderedPoints;
+            }
+        }
+    }
+    }
+
+        

HisenceYoloDetection/Form2.Designer.cs

@@ -0,0 +1,87 @@
+namespace HisenceYoloDetection
+{
+    partial class Form2
+    {
+        /// <summary>
+        /// Required designer variable.
+        /// </summary>
+        private System.ComponentModel.IContainer components = null;
+
+        /// <summary>
+        /// Clean up any resources being used.
+        /// </summary>
+        /// <param name="disposing">true if managed resources should be disposed; otherwise, false.</param>
+        protected override void Dispose(bool disposing)
+        {
+            if (disposing && (components != null))
+            {
+                components.Dispose();
+            }
+            base.Dispose(disposing);
+        }
+
+        #region Windows Form Designer generated code
+
+        /// <summary>
+        /// Required method for Designer support - do not modify
+        /// the contents of this method with the code editor.
+        /// </summary>
+        private void InitializeComponent()
+        {
+            button1 = new Button();
+            textBox1 = new TextBox();
+            label1 = new Label();
+            SuspendLayout();
+            // 
+            // button1
+            // 
+            button1.Location = new Point(192, 58);
+            button1.Margin = new Padding(2, 2, 2, 2);
+            button1.Name = "button1";
+            button1.Size = new Size(71, 24);
+            button1.TabIndex = 0;
+            button1.Text = "验证";
+            button1.UseVisualStyleBackColor = true;
+            // 
+            // textBox1
+            // 
+            textBox1.Location = new Point(143, 24);
+            textBox1.Margin = new Padding(2, 2, 2, 2);
+            textBox1.Name = "textBox1";
+            textBox1.Size = new Size(173, 23);
+            textBox1.TabIndex = 1;
+            // 
+            // label1
+            // 
+            label1.AutoSize = true;
+            label1.Location = new Point(58, 24);
+            label1.Margin = new Padding(2, 0, 2, 0);
+            label1.Name = "label1";
+            label1.Size = new Size(68, 17);
+            label1.TabIndex = 2;
+            label1.Text = "输入密码：";
+            label1.Click += label1_Click;
+            // 
+            // Form2
+            // 
+            AutoScaleDimensions = new SizeF(7F, 17F);
+            AutoScaleMode = AutoScaleMode.Font;
+            ClientSize = new Size(429, 92);
+            Controls.Add(label1);
+            Controls.Add(textBox1);
+            Controls.Add(button1);
+            Margin = new Padding(2, 2, 2, 2);
+            Name = "Form2";
+            Text = "验证身份";
+            Load += Form2_Load;
+            ResumeLayout(false);
+            PerformLayout();
+        }
+
+        #endregion
+
+        private Button button1;
+        private TextBox textBox1;
+        private Label label1;
+    }
+}

HisenceYoloDetection/Form2.cs

@@ -0,0 +1,39 @@
+using System;
+using System.Collections.Generic;
+using System.ComponentModel;
+using System.Data;
+using System.Drawing;
+using System.Linq;
+using System.Text;
+using System.Threading.Tasks;
+using System.Windows.Forms;
+
+namespace HisenceYoloDetection
+{
+    public partial class Form2 : Form
+    {
+        public string EnteredPassword { get; private set; }
+        public Form2()
+        {
+            InitializeComponent();
+            button1.Click += button1_Click; // 订阅按钮点击事件
+        }
+
+        private void button1_Click(object sender, EventArgs e)
+        {
+            EnteredPassword = textBox1.Text;
+            DialogResult = DialogResult.OK;
+            Close();
+        }
+
+        private void Form2_Load(object sender, EventArgs e)
+        {
+            CenterToScreen();
+        }
+
+        private void label1_Click(object sender, EventArgs e)
+        {
+
+        }
+    }
+}

HisenceYoloDetection/Form2.resx

@@ -0,0 +1,120 @@
+<?xml version="1.0" encoding="utf-8"?>
+<root>
+  <!--
+    Microsoft ResX Schema 
+
+    Version 2.0
+
+    The primary goals of this format is to allow a simple XML format
+    that is mostly human readable. The generation and parsing of the
+    various data types are done through the TypeConverter classes
+    associated with the data types.
+
+    Example:
+
+    ... ado.net/XML headers & schema ...
+    <resheader name="resmimetype">text/microsoft-resx</resheader>
+    <resheader name="version">2.0</resheader>
+    <resheader name="reader">System.Resources.ResXResourceReader, System.Windows.Forms, ...</resheader>
+    <resheader name="writer">System.Resources.ResXResourceWriter, System.Windows.Forms, ...</resheader>
+    <data name="Name1"><value>this is my long string</value><comment>this is a comment</comment></data>
+    <data name="Color1" type="System.Drawing.Color, System.Drawing">Blue</data>
+    <data name="Bitmap1" mimetype="application/x-microsoft.net.object.binary.base64">
+        <value>[base64 mime encoded serialized .NET Framework object]</value>
+    </data>
+    <data name="Icon1" type="System.Drawing.Icon, System.Drawing" mimetype="application/x-microsoft.net.object.bytearray.base64">
+        <value>[base64 mime encoded string representing a byte array form of the .NET Framework object]</value>
+        <comment>This is a comment</comment>
+    </data>
+
+    There are any number of "resheader" rows that contain simple
+    name/value pairs.
+
+    Each data row contains a name, and value. The row also contains a
+    type or mimetype. Type corresponds to a .NET class that support
+    text/value conversion through the TypeConverter architecture.
+    Classes that don't support this are serialized and stored with the
+    mimetype set.
+
+    The mimetype is used for serialized objects, and tells the
+    ResXResourceReader how to depersist the object. This is currently not
+    extensible. For a given mimetype the value must be set accordingly:
+
+    Note - application/x-microsoft.net.object.binary.base64 is the format
+    that the ResXResourceWriter will generate, however the reader can
+    read any of the formats listed below.
+
+    mimetype: application/x-microsoft.net.object.binary.base64
+    value   : The object must be serialized with
+            : System.Runtime.Serialization.Formatters.Binary.BinaryFormatter
+            : and then encoded with base64 encoding.
+    
+    mimetype: application/x-microsoft.net.object.soap.base64
+    value   : The object must be serialized with
+            : System.Runtime.Serialization.Formatters.Soap.SoapFormatter
+            : and then encoded with base64 encoding.
+
+    mimetype: application/x-microsoft.net.object.bytearray.base64
+    value   : The object must be serialized into a byte array
+            : using a System.ComponentModel.TypeConverter
+            : and then encoded with base64 encoding.
+    -->
+  <xsd:schema id="root" xmlns="" xmlns:xsd="http://www.w3.org/2001/XMLSchema" xmlns:msdata="urn:schemas-microsoft-com:xml-msdata">
+    <xsd:import namespace="http://www.w3.org/XML/1998/namespace" />
+    <xsd:element name="root" msdata:IsDataSet="true">
+      <xsd:complexType>
+        <xsd:choice maxOccurs="unbounded">
+          <xsd:element name="metadata">
+            <xsd:complexType>
+              <xsd:sequence>
+                <xsd:element name="value" type="xsd:string" minOccurs="0" />
+              </xsd:sequence>
+              <xsd:attribute name="name" use="required" type="xsd:string" />
+              <xsd:attribute name="type" type="xsd:string" />
+              <xsd:attribute name="mimetype" type="xsd:string" />
+              <xsd:attribute ref="xml:space" />
+            </xsd:complexType>
+          </xsd:element>
+          <xsd:element name="assembly">
+            <xsd:complexType>
+              <xsd:attribute name="alias" type="xsd:string" />
+              <xsd:attribute name="name" type="xsd:string" />
+            </xsd:complexType>
+          </xsd:element>
+          <xsd:element name="data">
+            <xsd:complexType>
+              <xsd:sequence>
+                <xsd:element name="value" type="xsd:string" minOccurs="0" msdata:Ordinal="1" />
+                <xsd:element name="comment" type="xsd:string" minOccurs="0" msdata:Ordinal="2" />
+              </xsd:sequence>
+              <xsd:attribute name="name" type="xsd:string" use="required" msdata:Ordinal="1" />
+              <xsd:attribute name="type" type="xsd:string" msdata:Ordinal="3" />
+              <xsd:attribute name="mimetype" type="xsd:string" msdata:Ordinal="4" />
+              <xsd:attribute ref="xml:space" />
+            </xsd:complexType>
+          </xsd:element>
+          <xsd:element name="resheader">
+            <xsd:complexType>
+              <xsd:sequence>
+                <xsd:element name="value" type="xsd:string" minOccurs="0" msdata:Ordinal="1" />
+              </xsd:sequence>
+              <xsd:attribute name="name" type="xsd:string" use="required" />
+            </xsd:complexType>
+          </xsd:element>
+        </xsd:choice>
+      </xsd:complexType>
+    </xsd:element>
+  </xsd:schema>
+  <resheader name="resmimetype">
+    <value>text/microsoft-resx</value>
+  </resheader>
+  <resheader name="version">
+    <value>2.0</value>
+  </resheader>
+  <resheader name="reader">
+    <value>System.Resources.ResXResourceReader, System.Windows.Forms, Version=4.0.0.0, Culture=neutral, PublicKeyToken=b77a5c561934e089</value>
+  </resheader>
+  <resheader name="writer">
+    <value>System.Resources.ResXResourceWriter, System.Windows.Forms, Version=4.0.0.0, Culture=neutral, PublicKeyToken=b77a5c561934e089</value>
+  </resheader>
+</root>

HisenceYoloDetection/HisenceYoloDetection.csproj

@@ -2,16 +2,18 @@
 
   <PropertyGroup>
     <OutputType>WinExe</OutputType>
-    <TargetFramework>net7.0-windows</TargetFramework>
+    <TargetFramework>net7.0-windows7.0</TargetFramework>
     <Nullable>enable</Nullable>
     <UseWindowsForms>true</UseWindowsForms>
     <ImplicitUsings>enable</ImplicitUsings>
     <Platforms>AnyCPU;X64</Platforms>
     <AllowUnsafeBlocks>True</AllowUnsafeBlocks>
     <ApplicationIcon>bin\X64\Debug\net7.0-windows\Logo.ico</ApplicationIcon>
+    <AppendTargetFrameworkToOutputPath>output</AppendTargetFrameworkToOutputPath>
   </PropertyGroup>
 
   <ItemGroup>
+    <None Remove="MainForm.resx~RF4efdcc4.TMP" />
     <None Remove="ManagerModelHelper.cs~RF97ff9f.TMP" />
     <None Remove="MelsecPLCTCPDriver.cs~RFacf25a.TMP" />
   </ItemGroup>

HisenceYoloDetection/MainForm.resx

@@ -117,6 +117,9 @@
   <resheader name="writer">
     <value>System.Resources.ResXResourceWriter, System.Windows.Forms, Version=4.0.0.0, Culture=neutral, PublicKeyToken=b77a5c561934e089</value>
   </resheader>
+  <metadata name="contextMenuStrip1.TrayLocation" type="System.Drawing.Point, System.Drawing, Version=4.0.0.0, Culture=neutral, PublicKeyToken=b03f5f7f11d50a3a">
+    <value>569, 17</value>
+  </metadata>
   <metadata name="timer1.TrayLocation" type="System.Drawing.Point, System.Drawing, Version=4.0.0.0, Culture=neutral, PublicKeyToken=b03f5f7f11d50a3a">
     <value>17, 17</value>
   </metadata>
@@ -135,14 +138,11 @@
   <metadata name="timer6.TrayLocation" type="System.Drawing.Point, System.Drawing, Version=4.0.0.0, Culture=neutral, PublicKeyToken=b03f5f7f11d50a3a">
     <value>477, 17</value>
   </metadata>
-  <metadata name="contextMenuStrip1.TrayLocation" type="System.Drawing.Point, System.Drawing, Version=4.0.0.0, Culture=neutral, PublicKeyToken=b03f5f7f11d50a3a">
-    <value>569, 17</value>
-  </metadata>
   <metadata name="backgroundWorker1.TrayLocation" type="System.Drawing.Point, System.Drawing, Version=4.0.0.0, Culture=neutral, PublicKeyToken=b03f5f7f11d50a3a">
     <value>733, 17</value>
   </metadata>
   <metadata name="$this.TrayHeight" type="System.Int32, mscorlib, Version=4.0.0.0, Culture=neutral, PublicKeyToken=b77a5c561934e089">
-    <value>31</value>
+    <value>25</value>
   </metadata>
   <assembly alias="System.Drawing" name="System.Drawing, Version=4.0.0.0, Culture=neutral, PublicKeyToken=b03f5f7f11d50a3a" />
   <data name="$this.Icon" type="System.Drawing.Icon, System.Drawing" mimetype="application/x-microsoft.net.object.bytearray.base64">

HisenceYoloDetection/ManagerModelHelper.cs

@@ -104,83 +104,7 @@ namespace HisenceYoloDetection
             return cslist;
 
         }
-        public static bool IsMatchSQLText(ref Mat detMat, ref XK_HisenceWord XKSQL, ref XK_HisenceWord XKDet)
-        {
        
-            try
-            {
-                string TwoRectstr = XKSQL.TwoRect;
-                string oneBlockWordSql = XKSQL.OneblockMainWord;
-                string twoBlockWordSql = XKSQL.TwoblockMainWord;
-                string threeBlockWordSql = XKSQL.ThreeblockMainWord;
-                string fourBlockWordSql = XKSQL.FourblockMainWord;
-                string fiveBlockWordSql = XKSQL.FiveblockMainWord;
-                string sixBlockWordSql = XKSQL.SixblockMainWord;
-                string sevenBlockWordSql = XKSQL.SevenblockMainWord;
-                string eightBlockWordSql = XKSQL.EightblockMainWord;
-
-                string oneBlockWordDet = XKDet.OneblockMainWord;
-                string twoBlockWordDet = XKDet.TwoblockMainWord;
-                string threeBlockWordDet = XKDet.ThreeblockMainWord;
-                string fourBlockWordDet = XKDet.FourblockMainWord;
-                string fiveBlockWordDet = XKDet.FiveblockMainWord;
-                string sixBlockWordDet = XKDet.SixblockMainWord;
-                string sevenBlockWordDet = XKDet.SevenblockMainWord;
-                string eightBlockWordDet = XKDet.EightblockMainWord;
-
-
-
-                bool OneIF = isMatchStr(oneBlockWordSql, oneBlockWordDet);
-                bool TwoIF = isMatchStr(twoBlockWordSql, twoBlockWordDet);
-                bool ThreeIF = isMatchStr(threeBlockWordSql, threeBlockWordDet);
-                bool FourIF = isMatchStr(fourBlockWordSql, fourBlockWordDet);
-                bool FiveIF = isMatchStr(fiveBlockWordSql, fiveBlockWordDet);
-                bool SixIF = isMatchStr(sixBlockWordSql, sixBlockWordDet);
-                bool SenvenIF = isMatchStr(sevenBlockWordSql, sevenBlockWordDet);
-                bool EightIF = isMatchStr(eightBlockWordSql, eightBlockWordDet);
-                //第二快 卷积匹配
-                string PathSql = XKSQL.TwoblockPath;
-                //
-
-                Rect rectsql = CheckDiffSciHelper.strChangeRect(TwoRectstr);
-                Rect rectDet = CheckDiffSciHelper.strChangeRect(XKDet.TwoRect);
-                bool twoif2 = CheckDiffSciHelper.CheckDiffSci(PathSql, detMat, rectsql, rectDet, (bool)XKSQL.TwoIFWhile, "D://Test");
-                DateTime dt = DateTime.Now;
-                using (StreamWriter sw = new StreamWriter("D://Hisence//logsMatch.log", true))
-                {
-                    string filename = dt.Year.ToString() + dt.Month.ToString() + dt.Day.ToString() + dt.Hour.ToString() + dt.Minute.ToString() + dt.Millisecond.ToString();
-                    sw.WriteLine(filename + "\n");
-                    sw.WriteLine(oneBlockWordSql + "  " + oneBlockWordDet + "\n");
-                    sw.WriteLine(twoBlockWordSql + "  " + twoBlockWordDet + "\n");
-                    sw.WriteLine(threeBlockWordSql + "  " + threeBlockWordDet + "\n");
-                    sw.WriteLine(fourBlockWordSql + "  " + fourBlockWordDet + "\n");
-                    sw.WriteLine(fiveBlockWordSql + "  " + fiveBlockWordDet + "\n");
-                    sw.WriteLine(sixBlockWordSql + "  " + sixBlockWordDet + "\n");
-                    sw.WriteLine(sevenBlockWordSql + "  " + sevenBlockWordDet + "\n");
-                    sw.WriteLine(eightBlockWordSql + "  " + eightBlockWordDet + "\n");
-                    sw.WriteLine(" 卷积匹配 " + twoif2 + "\n");
-                    sw.Flush();
-                }
-                //第三块区域一直都是false
-                if (OneIF && TwoIF && ThreeIF && FourIF && FiveIF && SixIF && SenvenIF && EightIF && twoif2)
-                {
-                    return true;
-                }
-                else
-                {
-                    return false;
-                }
-
-
-
-
-            }
-            catch (Exception ex)
-            {
-                return false;
-            }
-
-        }
         public static bool StrMatch(string SqlText,string DetText)
         {
             // 计算Levenshtein距离
@@ -189,7 +113,7 @@ namespace HisenceYoloDetection
             // 计算相似度（相似度等于1减去标准化的Levenshtein距离）
             double similarity = 1 - ((double)distance / Math.Max(SqlText.Length, DetText.Length));
             bool areEqual = false;
-            if (similarity < 0.5)
+            if (similarity < 0.9)
             {
                 areEqual = false;
             }
@@ -227,10 +151,13 @@ namespace HisenceYoloDetection
         }
         static bool AreMoreThanHalfEqual(string[] array1, string[] array2)
         {
+            string Sqltext = array1.Join("");
+            string Realtext = array2.Join("");
             int io = 0;
-            foreach (string ch1 in array1)
+           
+            foreach (char ch2 in Realtext)
             {
-                foreach (string ch2 in array2)
+                foreach (char ch1 in Sqltext)
                 {
                     if (ch1 == ch2)
                     {
@@ -249,7 +176,7 @@ namespace HisenceYoloDetection
             //int intersectionCount = set1.Intersect(set2).Count();
 
             // 判断交集数量是否超过一半
-            return io > array1.Length / 2;
+            return io >=Sqltext.Length / 2;
         }
         public static bool StrMatch2(string SqlText, string DetText)
         {
@@ -277,7 +204,7 @@ namespace HisenceYoloDetection
                 Console.WriteLine("字符串中不包含数字");
             }
             bool areEqual ;
-            if (numbers2.Length>2&& numbers.Length > 2)
+            if (numbers2.Length>0&& numbers.Length > 0)
             {
                 areEqual = AreMoreThanHalfEqual(numbers, numbers2);
             }

XKRS.UI/Canvas.cs

@@ -399,6 +399,7 @@ namespace XKRS.UI
                 }
 
                 #endregion
+
                 #region  画矩形
                 GPathList.ForEach(path =>
                 {

XKRS.UI/XKRS.UI.csproj

@@ -5,8 +5,14 @@
     <Nullable>enable</Nullable>
     <UseWindowsForms>true</UseWindowsForms>
     <ImplicitUsings>enable</ImplicitUsings>
-    <BaseOutputPath>.\bin\X64\Debug</BaseOutputPath>
+    <!--<BaseOutputPath>.\bin\X64\Debug</BaseOutputPath>-->
     <OutputType>Library</OutputType>
+    <AppendTargetFrameworkToOutputPath>output</AppendTargetFrameworkToOutputPath>
+    <PlatformTarget>x64</PlatformTarget>
+  </PropertyGroup>
+
+  <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|AnyCPU'">
+    <Optimize>False</Optimize>
   </PropertyGroup>
 
   <ItemGroup>