增加旋钮识别
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@ -10,7 +10,7 @@ using System.Threading.Tasks;
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using static System.Net.Mime.MediaTypeNames;
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using Point = OpenCvSharp.Point;
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using Size = OpenCvSharp.Size;
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using System;
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using OpenCvSharp;
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using OpenCvSharp.Features2D;
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using OpenCvSharp.Flann;
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@ -20,6 +20,8 @@ namespace HisenceYoloDetection
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{
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public static class CheckDiffSciHelper
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{
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public static Mat ProcessImage(Mat image, Rect fillRect)
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{
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// 获取图像尺寸
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@ -229,20 +231,6 @@ namespace HisenceYoloDetection
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{
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Cv2.DrawContours(blackhatImg, new Point[][] { contour }, -1, Scalar.Black, thickness: Cv2.FILLED);
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// 框选轮廓
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string savePath2 = Path.Combine("D:\\Hisence\\Test\\2\\ng", Path.GetFileNameWithoutExtension(path1) + filename + "_Rect.png");
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// 保存结果
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//string savePath = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path2) + "_diff.png");
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Cv2.ImWrite(savePath2, img2);
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string savePath = Path.Combine("D:\\Hisence\\Test\\2\\ng", Path.GetFileNameWithoutExtension(path1) + filename + "_diff.png");
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// 保存结果
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//string savePath = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path2) + "_diff.png");
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Cv2.ImWrite(savePath, blackhatImg);
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}
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else
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{
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Rect boundingRect = Cv2.BoundingRect(contour);
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Cv2.Rectangle(img2, boundingRect, Scalar.Red, thickness: 2);
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isMatch = false;
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string savePath2 = Path.Combine("D:\\Hisence\\Test\\2\\ok", Path.GetFileNameWithoutExtension(path1) + filename + "_Rect.png");
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// 保存结果
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//string savePath = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path2) + "_diff.png");
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@ -252,8 +240,32 @@ namespace HisenceYoloDetection
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//string savePath = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path2) + "_diff.png");
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Cv2.ImWrite(savePath, blackhatImg);
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}
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else
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{
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Rect boundingRect = Cv2.BoundingRect(contour);
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Cv2.Rectangle(img2, boundingRect, Scalar.Red, thickness: 2);
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isMatch = false;
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string savePath2 = Path.Combine("D:\\Hisence\\Test\\2\\ng", Path.GetFileNameWithoutExtension(path1) + filename + "_Rect.png");
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// 保存结果
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//string savePath = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path2) + "_diff.png");
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Cv2.ImWrite(savePath2, img2);
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string savePath = Path.Combine("D:\\Hisence\\Test\\2\\ng", Path.GetFileNameWithoutExtension(path1) + filename + "_diff.png");
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// 保存结果
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//string savePath = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path2) + "_diff.png");
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Cv2.ImWrite(savePath, blackhatImg);
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}
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}
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// 新增的白色面积占比判断
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double whiteArea1 = Cv2.CountNonZero(thr1);
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double whiteArea2 = Cv2.CountNonZero(thr2);
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double ratio1 = whiteArea1 / (thr1.Rows * thr1.Cols);
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double ratio2 = whiteArea2 / (thr2.Rows * thr2.Cols);
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if (Math.Abs(ratio1 - ratio2) >= 0.9)
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{
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isMatch = true;
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}
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return isMatch;
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}
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@ -1605,25 +1605,7 @@ namespace HisenceYoloDetection
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//2第一次拍照
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//if (IfCam2Triger)
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{
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// IfCam2Triger = false;
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//OCR识别
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//MLRequest req = new MLRequest();
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//req.currentMat = Cam2ImgShowBar;
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////req.currentMat = Cv2.ImRead("D:\\Hisence\\类型\\1\\bar.jpg");
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////相机识别的字符串
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//string IOcrBAr = DetMachineBar(ref req);
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//DateTime dt = DateTime.Now;
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//using (StreamWriter sw = new StreamWriter("D://Hisence//logsBar.log", true))
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//{
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// string filename = dt.Year.ToString() + dt.Month.ToString() + dt.Day.ToString() + dt.Hour.ToString() + dt.Minute.ToString() + dt.Millisecond.ToString();
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// sw.WriteLine(filename + "\n");
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// sw.WriteLine(IOcrBAr + "\n");
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// sw.Flush();
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//}
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// IOcrBAr = "BatchW9659ModelWNHPI74SCPSDE";
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// IOcrBAr = "W821PWMS27106WD2";
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// IOcrBAr=
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//根据条码数据库比对
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_runHandleAfter.Reset();
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if (xKNow == null)
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@ -1654,22 +1636,7 @@ namespace HisenceYoloDetection
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if (xKNow.Detect != "")
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{
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////此时运行的洗衣机是和之前一个语言模型
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//if (IfChangeLanguage == IOcrBAr)
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//{
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//}
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//else
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//{
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// //本地存在这个OCR.josn参数
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// if (File.Exists(xKNow.OcrParm))
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// {
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// paddleOcrModel.Load(xKNow.OcrParm, "CPU");
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// IfChangeLanguage = IOcrBAr;
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// }
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//}
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myLog("型号匹配成功" + IOcrBAr, DateTime.Now);
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}
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@ -1689,10 +1656,10 @@ namespace HisenceYoloDetection
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Defet_OnDetectionDone(whiteMat, 1);
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Defet_OnDetectionDone(whiteMat, 2);
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Defet_OnDetectionDone(whiteMat, 3);
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Defet_OnDetectionDone(whiteMat, 4);
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Defet_OnDetectionDone(whiteMat, 5);
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Defet_OnDetectionDone(whiteMat, 6);
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Defet_OnDetectionDone(whiteMat, 7);
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//Defet_OnDetectionDone(whiteMat, 4);
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//Defet_OnDetectionDone(whiteMat, 5);
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//Defet_OnDetectionDone(whiteMat, 6);
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//Defet_OnDetectionDone(whiteMat, 7);
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XK_HisenceWord xK_MatchDet = new XK_HisenceWord();
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xK_MatchDet.TwoIFWhile = xK_HisenceSQLWord.TwoIFWhile;
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@ -1818,48 +1785,48 @@ namespace HisenceYoloDetection
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OKOrNGShow.Image = NGbitmap;
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}));
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//melsecPLCTCPDriver.WriteInt(RedLightingAdress, 1);//红灯
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//melsecPLCTCPDriver.WriteInt(YellowLightingAdress, 0);//黄灯
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//melsecPLCTCPDriver.WriteInt(GreenLightingAdress, 0);//绿灯
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//melsecPLCTCPDriver.WriteInt(WaringAdress, 1);//报警
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melsecPLCTCPDriver.WriteInt(RedLightingAdress, 1);//红灯
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melsecPLCTCPDriver.WriteInt(YellowLightingAdress, 0);//黄灯
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melsecPLCTCPDriver.WriteInt(GreenLightingAdress, 0);//绿灯
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melsecPLCTCPDriver.WriteInt(WaringAdress, 1);//报警
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////加上人为判断是否是NG洗衣机
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//DialogResult dr = MessageBox.Show("是否误检？", "是否误检", MessageBoxButtons.OKCancel, MessageBoxIcon.Question);
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//if (dr == DialogResult.OK)
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//{
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//加上人为判断是否是NG洗衣机
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DialogResult dr = MessageBox.Show("是否误检？", "是否误检", MessageBoxButtons.OKCancel, MessageBoxIcon.Question);
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if (dr == DialogResult.OK)
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{
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// melsecPLCTCPDriver.WriteInt(RedLightingAdress, 0);//红灯
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// melsecPLCTCPDriver.WriteInt(GreenLightingAdress, 1);//绿灯
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// melsecPLCTCPDriver.WriteInt(WaringAdress, 0);//报警
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melsecPLCTCPDriver.WriteInt(RedLightingAdress, 0);//红灯
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melsecPLCTCPDriver.WriteInt(GreenLightingAdress, 1);//绿灯
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melsecPLCTCPDriver.WriteInt(WaringAdress, 0);//报警
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// OKDsums++;
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// WUsums++;
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// this.Invoke(new Action(() =>
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// {
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// double percent = (double)WUsums / AllDsums;
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// string percentText = percent.ToString("0.0%");//最后percentText的值为10.0%
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// textBox1.Text = percentText;
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// OKOrNGShow.Image = OKbitmap;
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// }));
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// myLog("匹配失败", DateTime.Now);
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//}
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//else
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//{
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// NGDsums++;
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OKDsums++;
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WUsums++;
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this.Invoke(new Action(() =>
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{
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double percent = (double)WUsums / AllDsums;
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string percentText = percent.ToString("0.0%");//最后percentText的值为10.0%
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textBox1.Text = percentText;
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OKOrNGShow.Image = OKbitmap;
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}));
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myLog("匹配失败", DateTime.Now);
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}
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else
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{
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NGDsums++;
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// melsecPLCTCPDriver.WriteInt(WaringAdress, 0);//报警
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// melsecPLCTCPDriver.WriteInt(RedLightingAdress, 0);//红灯
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// melsecPLCTCPDriver.WriteInt(GreenLightingAdress, 1);//绿灯
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melsecPLCTCPDriver.WriteInt(WaringAdress, 0);//报警
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melsecPLCTCPDriver.WriteInt(RedLightingAdress, 0);//红灯
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melsecPLCTCPDriver.WriteInt(GreenLightingAdress, 1);//绿灯
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// this.Invoke(new Action(() =>
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// {
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// OKOrNGShow.Image = NGbitmap;
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// }));
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// myLog("匹配成功", DateTime.Now);
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//}
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this.Invoke(new Action(() =>
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{
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OKOrNGShow.Image = NGbitmap;
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}));
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myLog("匹配成功", DateTime.Now);
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}
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@ -3423,6 +3390,7 @@ namespace HisenceYoloDetection
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Rect rectsql = CheckDiffSciHelper.strChangeRect(SQlxK_HisenceWord.TwoRect);
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Rect rectDet = CheckDiffSciHelper.strChangeRect(xK_HisenceWord.TwoRect);
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juanjiMatch = CheckDiffSciHelper.CheckDiffSci(PathSql, CutBlockMat, rectsql, rectDet, (bool)SQlxK_HisenceWord.TwoIFWhile, "D://Hisence//Test");
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// juanjiMatch = true;
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@ -3454,8 +3422,8 @@ namespace HisenceYoloDetection
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Rect rect = new Rect(0, 0, 0, 0);
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string PathSql = SQlxK_HisenceWord.ThreeblockPath;
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juanjiMatch = CheckDiffSciHelper1.CheckDiffSci(PathSql, CutBlockMat, rect, rect, false, "D://Hisence//Test1");
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bool iswhite = IsMostlyWhite(PathSql);
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juanjiMatch = CheckDiffSciHelper1.CheckDiffSci(PathSql, CutBlockMat, rect, rect, iswhite, "D://Hisence//Test1");
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if (!OneIF1 || !juanjiMatch)
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{
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OneIF = true;//待修改6.28
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@ -3644,6 +3612,72 @@ namespace HisenceYoloDetection
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}
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static bool IsMostlyWhite(string imagePath)
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{
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Bitmap bitmap = new Bitmap(imagePath);
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int width = bitmap.Width;
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int height = bitmap.Height;
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int blackCount = 0;
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int whiteCount = 0;
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for (int y = 0; y < height; y++)
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{
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for (int x = 0; x < width; x++)
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{
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Color pixelColor = bitmap.GetPixel(x, y);
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int r = pixelColor.R;
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int g = pixelColor.G;
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int b = pixelColor.B;
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// 判断是否为黑色
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if (r <= 70 && g <= 70 && b <= 70)
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{
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blackCount++;
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}
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else
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{
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whiteCount++;
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}
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}
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}
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int totalPixels = width * height;
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double blackRatio = (double)blackCount / totalPixels;
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// 如果黑色比例大于等于0.6，返回false，否则返回true
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return blackRatio < 0.6;
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}
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static string matchBtnColor(Mat img, Rect rect)
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{
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// 提取指定区域
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Mat roi = new Mat(img, rect);
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// 计算平均颜色
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Scalar mean = Cv2.Mean(roi);
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// 获取平均颜色的RGB值
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double r = mean.Val2;
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double g = mean.Val1;
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double b = mean.Val0;
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// 计算平均灰度值
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double averageGray = (r + g + b) / 3;
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// 判断颜色类别
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if (averageGray < 60)
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{
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return "黑色";
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}
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else if (averageGray >= 60 && averageGray <= 150)
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{
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return "银色";
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}
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else
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{
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return "白色";
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}
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}
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private void bnGetParam2_Click_1(object sender, EventArgs e)
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{
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@ -3765,5 +3799,10 @@ namespace HisenceYoloDetection
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{
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}
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private void label27_Click(object sender, EventArgs e)
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{
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}
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}
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}
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