HisenceYoloDetection/CheckDiffSciHelper.cs

@@ -1,70 +1,20 @@
 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  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>
@@ -72,24 +22,23 @@ 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, ref Mat ResultMat,Rect sqlrect, Rect detrect, bool IfWhiteWord, string saveDir,string SN)
+        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。。
+            // 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));
+          //  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);
+                 Cv2.Threshold(gimg1, thr1, 0, 255, ThresholdTypes.BinaryInv | ThresholdTypes.Otsu);
             }
             else
             {
@@ -101,16 +50,12 @@ namespace HisenceYoloDetection
 
             // 读取和处理第二张图片
             Mat img2 = MatDet.Clone();
-            ResultMat= MatDet.Clone();
             if (img2.Empty())
             {
-                // Console.WriteLine($"Error loading image {path2}");
+               // Console.WriteLine($"Error loading image {path2}");
                 return false;
             }
-            // Cv2.Resize(img2, img2, new Size(550, 270));
+           // 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();
@@ -123,15 +68,14 @@ 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);
@@ -151,17 +95,17 @@ namespace HisenceYoloDetection
             }
             Cv2.Resize(thr1, thr1, new Size(550, 270));
             Cv2.Resize(thr2, thr2, new Size(550, 270));
-            DateTime dt = DateTime.Now;
+            DateTime dt= DateTime.Now;
-            string filename = SN;
+           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");
+            string savePath4 = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path1) + filename+"_thr1.png");
             // 保存结果
        
-            //Cv2.ImWrite(savePath4, thr1);
+            Cv2.ImWrite(savePath4, thr1);
-            //string savePath3 = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path1) + filename + "_thr2.png");
+            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));
@@ -182,12 +126,12 @@ namespace HisenceYoloDetection
 
 
             //string savePath2 = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path1) + "_final_result1.png");
-            ////保存结果
+            //// 保存结果
-            //string savePath = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path2) + "_diff.png");
+            ////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
+            //// 保存结果
-            //string savePath = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path2) + "_diff.png");
+            ////string savePath = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path2) + "_diff.png");
             //Cv2.ImWrite(savePath, final_result2);
 
 
@@ -201,17 +145,10 @@ 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, 20, 255, ThresholdTypes.Binary);
+            Cv2.Threshold(devIMG, devIMG, 50, 255, ThresholdTypes.Binary);
-            Cv2.Threshold(devIMG_, devIMG_, 20, 255, ThresholdTypes.Binary);
+            Cv2.Threshold(devIMG_, devIMG_, 50, 255, ThresholdTypes.Binary);
 
             // 结合差异
             Mat sumIMG = new Mat();
@@ -223,60 +160,36 @@ namespace HisenceYoloDetection
             Cv2.Dilate(sumIMG, blackhatImg, kernelCL);
 
             // 处理轮廓和保存结果
-            Point[][] contours = new Point[10000][];
+           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)
+                if (Cv2.ContourArea(contour) <= 100)
                 {
                     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;
+                    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
+            string savePath2 = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path1) + filename+"_Rect.png");
-            double whiteArea1 = Cv2.CountNonZero(thr1);
+            // 保存结果
-            double whiteArea2 = Cv2.CountNonZero(thr2);
+            //string savePath = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path2) + "_diff.png");
-            double ratio1 = whiteArea1 / (thr1.Rows * thr1.Cols);
+            Cv2.ImWrite(savePath2, img2);
-            double ratio2 = whiteArea2 / (thr2.Rows * thr2.Cols);
+            string savePath = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path1) + filename+"_diff.png");
-
+            // 保存结果
-            if (Math.Abs(ratio1 - ratio2) >= 0.90)
+            //string savePath = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path2) + "_diff.png");
-            {
+            Cv2.ImWrite(savePath, blackhatImg);
-                isMatch = true;
-            }
-
             return isMatch;
         }
 
-
-
         public static Rect strChangeRect(string strrect)
         {
             if (!string.IsNullOrEmpty(strrect))
@@ -289,15 +202,14 @@ namespace HisenceYoloDetection
 
                 Rect rect = new Rect(areaX, areaY, areaWidth, areaHeight);
                 return rect;
-            }
+            }else
-            else
             {
-                return new Rect(0, 0, 0, 0);
+                return new Rect(0,0,0, 0);
             }
             
         }
 
-        public static string rectChangeStr(Rect area)
+        public static string  rectChangeStr(Rect area)
         {
             string[] rectsql = new string[4];
             rectsql[0] = Convert.ToString(area.X);
@@ -308,324 +220,123 @@ namespace HisenceYoloDetection
             string strrect = rectsql.Join(",");
             return strrect;
         }
-        public static class CheckDiffSciHelper1
+        //public static void CheckDiffSci(string path1, string path2, bool IfWhiteWord, string saveDir)
-        {
+        //{
-            /// <summary>
+        //    // 读取和处理第一张图片
-            /// 
+        //    Mat img1 = Cv2.ImRead(path1, ImreadModes.Color);
-            /// </summary>
+        //    if (img1.Empty())
-            /// <param name="path1">标准图像</param>
+        //    {
-            /// <param name="path2">要对比的图像</param>
+        //        Console.WriteLine($"Error loading image {path1}");
-            /// <param name="IfWhiteWord"> 白板黑字为true </param>
+        //        return;
-            /// <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)
+        //    Cv2.Resize(img1, img1, new Size(550, 270));
-            {
+        //    Mat gimg1 = new Mat();
-                // 读取和处理第一张图片
+        //    Cv2.CvtColor(img1, gimg1, ColorConversionCodes.BGR2GRAY);
-                Mat img1 = Cv2.ImRead(path1, ImreadModes.Color);
+        //    Mat thr1 = new Mat();
 
-                if (img1.Empty())
+        //    if (IfWhiteWord)
-                {
+        //    {
-                    Console.WriteLine($"Error loading image {path1}");
+        //        Cv2.Threshold(gimg1, thr1, 0, 255, ThresholdTypes.BinaryInv | ThresholdTypes.Otsu);
-                    return false;
+        //    }
-                }
+        //    else
-                //  Cv2.Resize(img1, img1, new Size(550, 270));
+        //    {
-                img1 = RemoveBorders(img1);
+        //        Cv2.Threshold(gimg1, thr1, 0, 255, ThresholdTypes.Binary | ThresholdTypes.Otsu);
-                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);
 
-                // 读取和处理第二张图片
+        //    string savePath3 = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path2) + "_thr2.png");
-                Mat img2 = MatDet.Clone();
+        //    // 保存结果
-                if (img2.Empty())
+        //    //string savePath = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path2) + "_diff.png");
-                {
+        //    Cv2.ImWrite(savePath3, thr2);
-                    // 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);
-                }
 
+        //    // 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));
 
-                //Rect  area2 = new Rect(148,30,229,222);
+        //    // 应用卷积
-                sqlrect.Width += 20;
+        //    Mat final_result1 = new Mat();
-                sqlrect.Height += 20;
+        //    Cv2.Filter2D(thr1, final_result1, -1, filter1, anchor: new Point(-1, -1), 0, BorderTypes.Reflect);
-                detrect.Width += 20;
+        //    Cv2.Filter2D(final_result1, final_result1, -1, filter1, anchor: new Point(-1, -1), 0, BorderTypes.Reflect);
-                detrect.Height += 20;
+        //    Cv2.Filter2D(final_result1, final_result1, -1, filter1, anchor: new Point(-1, -1), 0, BorderTypes.Reflect);
-                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");
+        //    Mat final_result2 = new Mat();
-                // 保存结果
+        //    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.ImWrite(savePath4, thr1);
+        //    // 计算图像差异
-               // string savePath3 = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path1) + filename + "_thr2.png");
+        //    Mat devIMG = new Mat();
-                // 保存结果
+        //    Mat devIMG_ = new Mat();
+        //    Cv2.Subtract(final_result1, final_result2, devIMG);
+        //    Cv2.Subtract(final_result2, final_result1, devIMG_);
 
-               // Cv2.ImWrite(savePath3, thr2);
+        //    // 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);
 
-                // 创建卷积核
+        //    // 结合差异
+        //    Mat sumIMG = new Mat();
+        //    Cv2.Add(devIMG, devIMG_, sumIMG);
 
-                Mat filter1 = new Mat(15, 15, MatType.CV_32F, new Scalar(0));
+        //    // 应用形态学操作
-                filter1.Row(7).SetTo(new Scalar(0.025));
+        //    Mat kernelCL = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 3));
-                filter1.Col(7).SetTo(new Scalar(0.025));
+        //    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
 
-                // 应用卷积
+        //        }
-                Mat final_result1 = new Mat();
+        //        else
-                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);
+        //            Rect boundingRect = Cv2.BoundingRect(contour);
-                Cv2.Filter2D(final_result1, final_result1, -1, filter1, anchor: new Point(-1, -1), 0, BorderTypes.Reflect);
+        //            Cv2.Rectangle(img2, boundingRect, Scalar.Red, thickness: 2);
-
+        //        }
-                //Cv2.Filter2D(final_result1, final_result1, -1, filter2, anchor: new Point(-1, -1), 0, BorderTypes.Reflect);
+        //    }
-
+        //    string savePath2 = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path2) + "_Rect.png");
-                Mat final_result2 = new Mat();
+        //    // 保存结果
-                Cv2.Filter2D(thr2, final_result2, -1, filter1, anchor: new Point(-1, -1), 0, BorderTypes.Reflect);
+        //    //string savePath = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path2) + "_diff.png");
-                Cv2.Filter2D(final_result2, final_result2, -1, filter1, anchor: new Point(-1, -1), 0, BorderTypes.Reflect);
+        //    Cv2.ImWrite(savePath2, img2);
-                Cv2.Filter2D(final_result2, final_result2, -1, filter1, anchor: new Point(-1, -1), 0, BorderTypes.Reflect);
+        //    string savePath = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path2) + "_diff.png");
-
+        //    // 保存结果
-                //Cv2.Filter2D(final_result2, final_result2, -1, filter2, anchor: new Point(-1, -1), 0, BorderTypes.Reflect);
+        //    //string savePath = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path2) + "_diff.png");
-                //裁剪才行
+        //    Cv2.ImWrite(savePath, blackhatImg);
-
+        //}
-
-                //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, 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();
-                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
-
-                    }
-                    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);
-                //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);
-                return isMatch;
-            }
-
-           public static void ResizeImage(string inputPath, string outputPath, int newWidth, int newHeight, int quality)
-            {
-                // 加载原始图像
-                using (Mat originalImage = Cv2.ImRead(inputPath))
-                {
-                    // 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));
-
-                        // 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}");
-                    }
-                }
-            }
-
-            static void SaveJpeg(string path, Mat image, int quality)
-            {
-                // 设置JPEG编码参数
-                var encodeParams = new[] { new ImageEncodingParam(ImwriteFlags.JpegQuality, quality) };
-
-                // 保存图像
-                Cv2.ImWrite(path, image, encodeParams);
-            }
-            static Mat RemoveBorders(Mat image)
-            {
-                // 将图像转换为灰度图
-                Mat grayImage = new Mat();
-                Cv2.CvtColor(image, grayImage, ColorConversionCodes.BGR2GRAY);
-
-                // 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);
-
-                // 查找轮廓
-                Point[][] contours;
-                HierarchyIndex[] hierarchy;
-                Cv2.FindContours(invertedBinaryImage, out contours, out hierarchy, RetrievalModes.External, ContourApproximationModes.ApproxSimple);
-
-                // 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

@@ -1,87 +0,0 @@
-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

@@ -1,39 +0,0 @@
-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

@@ -1,120 +0,0 @@
-<?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

@@ -2,18 +2,16 @@
 
   <PropertyGroup>
     <OutputType>WinExe</OutputType>
-    <TargetFramework>net7.0-windows7.0</TargetFramework>
+    <TargetFramework>net7.0-windows</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

@@ -117,9 +117,6 @@
   <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>
@@ -138,11 +135,14 @@
   <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="$this.TrayHeight" type="System.Int32, mscorlib, Version=4.0.0.0, Culture=neutral, PublicKeyToken=b77a5c561934e089">
-    <value>25</value>
+    <value>31</value>
   </metadata>
   <assembly alias="System.Drawing" name="System.Drawing, Version=4.0.0.0, Culture=neutral, PublicKeyToken=b03f5f7f11d50a3a" />
   <data name="$this.Icon" type="System.Drawing.Icon, System.Drawing" mimetype="application/x-microsoft.net.object.bytearray.base64">

HisenceYoloDetection/ManagerModelHelper.cs

@@ -104,7 +104,83 @@ 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
@@ -113,7 +189,7 @@ 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 < 0.9)
+            if (similarity < 0.5)
             {
                 areEqual = false;
             }
@@ -151,13 +227,10 @@ 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 (char ch1 in Sqltext)
+                foreach (string ch2 in array2)
                 {
                     if (ch1 == ch2)
                     {
@@ -176,7 +249,7 @@ namespace HisenceYoloDetection
             //int intersectionCount = set1.Intersect(set2).Count();
 
             // 判断交集数量是否超过一半
-            return io >=Sqltext.Length / 2;
+            return io > array1.Length / 2;
         }
         public static bool StrMatch2(string SqlText, string DetText)
         {
@@ -204,7 +277,7 @@ namespace HisenceYoloDetection
                 Console.WriteLine("字符串中不包含数字");
             }
             bool areEqual ;
-            if (numbers2.Length>0&& numbers.Length > 0)
+            if (numbers2.Length>2&& numbers.Length > 2)
             {
                 areEqual = AreMoreThanHalfEqual(numbers, numbers2);
             }

HisenceYoloDetection/TCPClienDriver.cs

@@ -18,9 +18,9 @@ namespace HisenceYoloDetection
         public void Strart()
         {
             client = new TcpClient();
-            client.Host = "192.168.3.100";
+           client.Host = "192.168.3.100";
             client.Port= 9004;
-             //client.Host = "127.0.0.1";
+            //client.Host = "127.0.0.1";
            //client.Port = 9000;
             client.Connect();
             

XKRS.UI/Canvas.cs

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

XKRS.UI/XKRS.UI.csproj

@@ -5,14 +5,8 @@
     <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>