vcrmn/hisence-yolo-detection
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更改了卷积匹配（可以试一试，不一定好用）

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820689062 2024-06-27 18:09:39 +08:00
parent 2db802c899
commit 733500850e
1 changed files with 31 additions and 84 deletions
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91
HisenceYoloDetection/CheckDiffSciHelper.cs
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@ -31,7 +31,6 @@ namespace HisenceYoloDetection
Console.WriteLine($"Error loading image {path1}"); Console.WriteLine($"Error loading image {path1}");
return false; return false;
} }
// Cv2.Resize(img1, img1, new Size(550, 270));
Mat gimg1 = new Mat(); Mat gimg1 = new Mat();
Cv2.CvtColor(img1, gimg1, ColorConversionCodes.BGR2GRAY); Cv2.CvtColor(img1, gimg1, ColorConversionCodes.BGR2GRAY);
Mat thr1 = new Mat(); Mat thr1 = new Mat();
@ -45,21 +44,16 @@ namespace HisenceYoloDetection
Cv2.Threshold(gimg1, thr1, 0, 255, ThresholdTypes.Binary | ThresholdTypes.Otsu); Cv2.Threshold(gimg1, thr1, 0, 255, ThresholdTypes.Binary | ThresholdTypes.Otsu);
} }
// 读取和处理第二张图片 // 读取和处理第二张图片
Mat img2 = MatDet.Clone(); Mat img2 = MatDet.Clone();
if (img2.Empty()) if (img2.Empty())
{ {
// Console.WriteLine($"Error loading image {path2}");
return false; return false;
} }
// Cv2.Resize(img2, img2, new Size(550, 270));
Mat gimg2 = new Mat(); Mat gimg2 = new Mat();
Cv2.CvtColor(img2, gimg2, ColorConversionCodes.BGR2GRAY); Cv2.CvtColor(img2, gimg2, ColorConversionCodes.BGR2GRAY);
Mat thr2 = new Mat(); Mat thr2 = new Mat();
//Cv2.Threshold(gimg2, thr2, 0, 255, ThresholdTypes.BinaryInv | ThresholdTypes.Otsu);
if (IfWhiteWord) if (IfWhiteWord)
{ {
Cv2.Threshold(gimg2, thr2, 0, 255, ThresholdTypes.BinaryInv | ThresholdTypes.Otsu); Cv2.Threshold(gimg2, thr2, 0, 255, ThresholdTypes.BinaryInv | ThresholdTypes.Otsu);
@ -68,77 +62,32 @@ namespace HisenceYoloDetection
{ {
Cv2.Threshold(gimg2, thr2, 0, 255, ThresholdTypes.Binary | ThresholdTypes.Otsu); Cv2.Threshold(gimg2, thr2, 0, 255, ThresholdTypes.Binary | ThresholdTypes.Otsu);
} }
// Cv2.Threshold(gimg2, thr2, 0, 255, ThresholdTypes.Binary | ThresholdTypes.Otsu);
// 裁剪和设置为黑色
//Rect area2 = new Rect(148,30,229,222);
sqlrect.Width += 20; sqlrect.Width += 20;
detrect.Width += 20; detrect.Width += 20;
Mat matCutblack1 = new Mat(thr1, sqlrect); Mat matCutblack1 = new Mat(thr1, sqlrect);
if (IfWhiteWord)
{
matCutblack1.SetTo(Scalar.Black); matCutblack1.SetTo(Scalar.Black);
}
else
{
matCutblack1.SetTo(Scalar.Black);
}
Mat matCutblack2 = new Mat(thr2, detrect); Mat matCutblack2 = new Mat(thr2, detrect);
if (IfWhiteWord)
{
matCutblack2.SetTo(Scalar.Black); matCutblack2.SetTo(Scalar.Black);
}
else
{
matCutblack2.SetTo(Scalar.Black);
}
Cv2.Resize(thr1, thr1, new Size(550, 270)); Cv2.Resize(thr1, thr1, new Size(550, 270));
Cv2.Resize(thr2, thr2, new Size(550, 270)); Cv2.Resize(thr2, thr2, new Size(550, 270));
DateTime dt = DateTime.Now; DateTime dt = DateTime.Now;
string filename= dt.Year.ToString() + dt.Month.ToString() + dt.Day.ToString() + dt.Hour.ToString() + dt.Minute.ToString() + dt.Millisecond.ToString(); string filename = dt.ToString("yyyyMMddHHmmssfff");
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 // 创建和应用卷积核
Mat filter1 = new Mat(15, 15, MatType.CV_32F, new Scalar(0)); Mat filter1 = new Mat(7, 7, MatType.CV_32F, new Scalar(0.025));
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(); 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(); Mat final_result2 = new Mat();
Cv2.Filter2D(thr2, final_result2, -1, filter1, anchor: new Point(-1, -1), 0, BorderTypes.Reflect); Cv2.Filter2D(thr1, final_result1, -1, filter1, 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(thr2, final_result2, -1, filter1, new Point(-1, -1), 0, BorderTypes.Reflect);
Cv2.Filter2D(final_result2, final_result2, -1, filter1, anchor: new Point(-1, -1), 0, BorderTypes.Reflect);
//裁剪才行
//string savePath2 = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path1) + "_final_result1.png");
//// 保存结果
////string savePath = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path2) + "_diff.png");
//Cv2.ImWrite(savePath2, final_result1);
//string savePath = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path1) + "_final_result2.png");
//// 保存结果
////string savePath = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path2) + "_diff.png");
//Cv2.ImWrite(savePath, final_result2);
// 计算图像差异 // 计算图像差异
Mat devIMG = new Mat(); Mat devIMG = new Mat();
@ -147,20 +96,21 @@ namespace HisenceYoloDetection
Cv2.Subtract(final_result2, final_result1, devIMG_); Cv2.Subtract(final_result2, final_result1, devIMG_);
// 对差异图像应用阈值 // 对差异图像应用阈值
Cv2.Threshold(devIMG, devIMG, 50, 255, ThresholdTypes.Binary); double threshold = 20.0; // 调低阈值
Cv2.Threshold(devIMG_, devIMG_, 50, 255, ThresholdTypes.Binary); Cv2.Threshold(devIMG, devIMG, threshold, 255, ThresholdTypes.Binary);
Cv2.Threshold(devIMG_, devIMG_, threshold, 255, ThresholdTypes.Binary);
// 结合差异 // 结合差异
Mat sumIMG = new Mat(); Mat sumIMG = new Mat();
Cv2.Add(devIMG, devIMG_, sumIMG); Cv2.Add(devIMG, devIMG_, sumIMG);
// 应用形态学操作 // 形态学操作
Mat kernelCL = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 3)); Mat kernelCL = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(3, 3));
Mat blackhatImg = new Mat(); Mat blackhatImg = new Mat();
Cv2.Dilate(sumIMG, blackhatImg, kernelCL); Cv2.Dilate(sumIMG, blackhatImg, kernelCL); // 使用膨胀操作
// 处理轮廓和保存结果 // 检测和绘制轮廓
Point[][] contours = new Point[10000][]; Point[][] contours;
Cv2.FindContours(blackhatImg, out contours, out _, RetrievalModes.Tree, ContourApproximationModes.ApproxSimple); Cv2.FindContours(blackhatImg, out contours, out _, RetrievalModes.Tree, ContourApproximationModes.ApproxSimple);
bool isMatch = true; bool isMatch = true;
foreach (var contour in contours) foreach (var contour in contours)
@ -168,8 +118,6 @@ namespace HisenceYoloDetection
if (Cv2.ContourArea(contour) <= 100) if (Cv2.ContourArea(contour) <= 100)
{ {
Cv2.DrawContours(blackhatImg, new Point[][] { contour }, -1, Scalar.Black, thickness: Cv2.FILLED); Cv2.DrawContours(blackhatImg, new Point[][] { contour }, -1, Scalar.Black, thickness: Cv2.FILLED);
// 框选轮廓
} }
else else
{ {
@ -179,17 +127,16 @@ namespace HisenceYoloDetection
} }
} }
// 保存最终结果
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); Cv2.ImWrite(savePath2, img2);
string savePath = Path.Combine(saveDir, Path.GetFileNameWithoutExtension(path1) + filename + "_diff.png"); 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; return isMatch;
} }
public static Rect strChangeRect(string strrect) public static Rect strChangeRect(string strrect)
{ {
if (!string.IsNullOrEmpty(strrect)) if (!string.IsNullOrEmpty(strrect))