无

eyemLib-Sharp/EyemLib.cs

@@ -1233,7 +1233,6 @@ namespace eyemLib_Sharp
                 Console.WriteLine("读图失败！");
                 return;
             }
-
             Stopwatch sw = new Stopwatch();
             sw.Restart();
             string file = fileName.Split(new string[] { "\\" }, StringSplitOptions.RemoveEmptyEntries)[2];
@@ -1301,7 +1300,7 @@ namespace eyemLib_Sharp
             //tpHsvModel.dpRangeL = new double[] { 100, 43, 46 }; tpHsvModel.dpRangeU = new double[] { 124, 255, 255 };
             //tpHsvModel.dpRangeLExt = new double[] { 0, 0, 0 }; tpHsvModel.dpRangeUExt = new double[] { 0, 0, 0 };
             //eyemClassifier(image);
-            flag = eyemLibImpl(image, out tpDstImg);
+            //flag = eyemLibImpl(image, out tpDstImg);
             //float[] fFeatures = new float[512];
             //eyemExtractWithONNX(image, fFeatures);
             //string ftrs = string.Join(" ", fFeatures).Trim();
@@ -1322,9 +1321,9 @@ namespace eyemLib_Sharp
             //    bitmap.Save("D:\\ResOut\\" + file);
             //}
             //eyemImageFree(ref tpMatchImg);
-            eyemImageFree(ref tpDstImg);
-            eyemImageFree(ref image);
-            return;
+            //eyemImageFree(ref tpDstImg);
+            //eyemImageFree(ref image);
+            //return;
 
             //EyemImage templ, search;
             //flag = eyemImageRead("D://批量测试图像//template.png", -1, out templ);
@@ -1630,7 +1629,7 @@ namespace eyemLib_Sharp
                 bitmap.Save(System.Windows.Forms.Application.StartupPath + "\\ResOut\\" + file);
             }
 
-            //< 解码测试
+            ////< 解码测试
             //int ipNum; EyemBarCode* tpResults;
             //DataCodeHandle hObject;
             //int iRes = eyemDetectAndDecode(image, tpRoi, file.Replace(".png", ""), "QR_CODE|DATA_MATRIX", out hObject, out tpResults, out ipNum, false, 11, 5, 128, 256);

eyemLib/eyemCodeDetector.cpp

@@ -62,6 +62,7 @@ std::vector<std::string> CodeDetector::detectAndDecode(cv::InputArray img, std::
 	}
 	logger.t("__eyemDetectAndDecodeUseNN__detectAndDecode__:图像格式转换完成");
 	_mtx.lock();
+	int x = 0;
 	//识别
 	logger.t("__eyemDetectAndDecodeUseNN__detectAndDecode__:开始识别二维码");
 	std::vector<cv::Rect> bboxes = p->detect(input);

eyemLib/eyemLib.h

@@ -935,7 +935,6 @@ extern "C" {
 	EXPORTS int				eyemDrawCircle(EyemImage tpImage, EyemOcsDXYR tpCircle);
 	EXPORTS int				eyemDrawRectangle(EyemImage tpImag, EyemRect tpRect);
 	EXPORTS int				eyemTrainImageSampler(EyemImage tpImage, int iSize, const char *ccClassName, const char *ccToPath, EyemImage *tpMatchImg, EyemImage *tpDstImg);
-	EXPORTS int				eyemBuildTrainFile(const char *filePath, const char *fileName, bool shuffle = true);
 
 #ifdef __cplusplus
 }

eyemLib/eyemMisc.cpp

@@ -4462,71 +4462,130 @@ int eyemCountObjectIrregularParts(EyemImage tpImage, EyemRect tpRoi, const char
 	}
 	else
 	{
-		//先用自动算法点，如果不行判断为散料
-		int trayNum[4];
-		int iRet = eyemCountObjectE(tpImage, tpRoi, "", trayNum, tpDstImg);
-		if (iRet == FUNC_OK) {
-			//输出结果
-			for (int i = 0; i < 4; i++) {
-				//输出结果
-				ipReelNum[i] = trayNum[i];
-				break;
-			}
-			return FUNC_OK;
-		}
-		else {
-			//判断为散料
-			cv::threshold(srcPrev, binary, 0, 255, cv::THRESH_BINARY | cv::THRESH_OTSU);
-			cv::morphologyEx(binary, binary, cv::MORPH_DILATE, cv::getStructuringElement(cv::MORPH_RECT, cv::Size(25, 25)));
-			//计算直方图
-			int hist[256];
-			for (int y = 0; y < 256; y++) hist[y] = 0;
-			for (int y = 0; y < Y; y++)
+		cv::threshold(srcPrev, binary, 0, 255, cv::THRESH_BINARY | cv::THRESH_OTSU);
+		//假设有部分颜色较深料带影响
+		cv::morphologyEx(binary, binary, cv::MORPH_DILATE, cv::getStructuringElement(cv::MORPH_RECT, cv::Size(5, 5)));
+		//计算直方图
+		int hist[256];
+		for (int y = 0; y < 256; y++) hist[y] = 0;
+		for (int y = 0; y < Y; y++)
+		{
+			uchar *uPtr = srcPrev.data + y * X;
+			for (int x = 0; x < srcPrev.cols; x++, uPtr++)
 			{
-				uchar *uPtr = srcPrev.data + y * X;
-				for (int x = 0; x < srcPrev.cols; x++, uPtr++)
+				if ((binary.data)[(x)+(y)*X] == 255)
 				{
-					if ((binary.data)[(x)+(y)*X] == 255)
-					{
-						hist[*uPtr]++;
-					}
+					hist[*uPtr]++;
 				}
 			}
-			cv::threshold(srcPrev, binary, Otsu(hist) + 5, 255, cv::THRESH_BINARY);
-			std::vector<std::vector<cv::Point>> contours, contourFilter;
-			//连接在一起(散料用)
-			cv::Mat binaryEx;
-			cv::morphologyEx(binary, binaryEx, cv::MORPH_DILATE, cv::getStructuringElement(cv::MORPH_RECT, cv::Size(75, 75)));
+		}
+		cv::threshold(srcPrev, binary, Otsu(hist), 255, cv::THRESH_BINARY);
+		//判断这些连通域相似性（从面积、平均灰度、最大灰度等判断）再确定阈值与面积过滤参数
+		cv::Mat labels, stats, centroids;
+		int nccomps = cv::connectedComponentsWithStats(binary, labels, stats, centroids);
+		//统计每个连通域的信息
+		struct TE
+		{
+			double Area, Mean;
+			TE() {}
+			TE(double Area, double Mean) :Area(Area), Mean(Mean) {}
+		};
+		std::vector<TE> Tes;
+		for (int i = 1; i < nccomps; i++)
+		{
+			auto meanRect = cv::Rect(stats.ptr<int>(i)[cv::CC_STAT_LEFT], stats.ptr<int>(i)[cv::CC_STAT_TOP],
+				stats.ptr<int>(i)[cv::CC_STAT_WIDTH], stats.ptr<int>(i)[cv::CC_STAT_HEIGHT]);
 
-			//掩膜
-			cv::Mat mask(Y, X, CV_8UC1, cv::Scalar(0));
-			cv::findContours(binaryEx, contours, cv::RETR_EXTERNAL, cv::CHAIN_APPROX_NONE);
-			for (int i = 0; i < contours.size(); i++)
+			cv::Mat mask = (labels(meanRect) == i);
+			Tes.push_back(TE(stats.ptr<int>(i)[cv::CC_STAT_AREA], cv::mean(srcPrev(meanRect), mask)[0]));
+		}
+		//确定相似度(每一点计算距离其他点的欧氏距离)
+		struct tMap
+		{
+			TE te;
+			double match;
+			tMap() {}
+			tMap(TE te, double match) :te(te), match(match) {}
+			bool operator >(const tMap &te)const
+			{
+				return match > te.match;
+			}
+			bool operator <(const tMap &te)const
+			{
+				return match < te.match;
+			}
+		};
+		std::vector<tMap> tMaps;
+		for (int i = 0; i < (int)Tes.size(); i++)
+		{
+			double sumMatch = 0.0;
+			for (int j = 0; j < (int)Tes.size(); j++)
+			{
+				sumMatch += std::sqrt(std::pow(Tes[i].Area - Tes[j].Area, 2) + std::pow(Tes[i].Mean - Tes[j].Mean, 2));
+			}
+			tMaps.push_back(tMap(Tes[i], sumMatch));
+		}
+		//排序
+		std::sort(tMaps.begin(), tMaps.end(), std::less<tMap>());
+		//确定单个元件尺寸与灰度值
+		double sinPartsArea = tMaps[0].te.Area; double sinPartsMean = tMaps[0].te.Mean;
+		//根据灰度值重新进行二值化
+		cv::threshold(srcPrev, binary, sinPartsMean*0.75, 255, cv::THRESH_BINARY);
+		//重新计算连通域
+		nccomps = cv::connectedComponentsWithStats(binary, labels, stats, centroids);
+		//对连通域过滤
+		std::vector<uchar> colors(nccomps + 1, 0);
+		for (int i = 1; i < nccomps; i++)
+		{
+			colors[i] = 255;
+			if (stats.ptr<int>(i)[cv::CC_STAT_AREA] <= 2) {
+				colors[i] = 0;
+			}
+		}
+		//过滤
+		cv::parallel_for_(cv::Range(0, Y), [&](const cv::Range& range)->void {
+			for (int y = range.start; y < range.end; y++)
 			{
-				double contourArea = cv::contourArea(contours[i]);
-				if (contourArea > 15000)
+				uint8_t *ptrRow = binary.ptr<uint8_t>(y);
+				for (int x = 0; x < X; x++)
 				{
-					//绘制掩膜
-					cv::drawContours(mask, contours, i, cv::Scalar(255), -1);
+					int label = labels.ptr<int>(y)[x];
+					CV_Assert(0 <= label && label <= nccomps);
+					ptrRow[x] = colors[label];
 				}
 			}
-
-			//粗略计数
-			cv::Mat labels, stats, centroids;
-			int numObj = cv::connectedComponentsWithStats(binary&mask, labels, stats, centroids);
-			//坐标图
-			binary = cv::Scalar(0);
-			//画图
-			double *dpCent = (double *)centroids.data;
-			for (int j = 1; j < numObj; j++)
+		});
+		//确定范围
+		std::vector<std::vector<cv::Point>> contours, contourFilter;
+		//连接在一起(散料用)
+		cv::Mat binaryEx;
+		cv::morphologyEx(binary, binaryEx, cv::MORPH_DILATE, cv::getStructuringElement(cv::MORPH_RECT, cv::Size(95, 95)));
+		//掩膜，用于排除零星干扰
+		cv::Mat mask(Y, X, CV_8UC1, cv::Scalar(0));
+		cv::findContours(binaryEx, contours, cv::RETR_EXTERNAL, cv::CHAIN_APPROX_NONE);
+		for (int i = 0; i < contours.size(); i++)
+		{
+			double contourArea = cv::contourArea(contours[i]);
+			if (contourArea > 15000)
 			{
-				//面积过滤
-				if (stats.ptr<int>(j)[cv::CC_STAT_AREA] > 2) {
-					cv::circle(cc, cv::Point(cvRound((float)dpCent[(0) + (j)* 2]), cvRound((float)dpCent[(1) + (j)* 2])), 1, cv::Scalar(0, 255, 0, 255));
-					binary.at<uchar>(cv::Point(cvRound((float)dpCent[(0) + (j)* 2]), cvRound((float)dpCent[(1) + (j)* 2]))) = 255;
-				}
+				cv::Moments mu = cv::moments(contours[i]);
+				cv::Point2f reelCenter(float(mu.m10 / mu.m00), float(mu.m01 / mu.m00));
+				cv::drawMarker(cc, reelCenter, cv::Scalar(0, 0, 238, 255), 1, 35, 2);
+				//绘制掩膜
+				cv::drawContours(mask, contours, i, cv::Scalar(255), -1);
 			}
 		}
+		//粗略计数
+		int numObj = cv::connectedComponentsWithStats(binary&mask, labels, stats, centroids);
+		//坐标图
+		binary = cv::Scalar(0);
+		//画图
+		for (int j = 1; j < numObj; j++)
+		{
+			cv::Point centroid(cvRound(centroids.ptr<double>(j)[0]), cvRound(centroids.ptr<double>(j)[1]));
+			cv::circle(cc, centroid, 1, cv::Scalar(0, 255, 0, 255));
+			binary.at<uchar>(centroid) = 255;
+		}
 	}
 	//计数
 	std::vector<cv::Point> idx;
@@ -4801,7 +4860,7 @@ int	eyemCountObjectE(EyemImage tpImage, EyemRect tpRoi, const char *fileName, in
 		//判断适用哪种算法
 		if (!useTrackMethod)
 		{
-			const int filterSize = 12;
+			const int filterSize = 17;//因为移远改成17，原12
 			//去掉料盘深色部分干扰
 			const int winSize = sinPartSize > 15 ? 5 : 3;//对于部分器件过小的窗口会漏料
 			cv::Mat srcPrevEx;
@@ -6968,15 +7027,12 @@ int	eyemCountObjectIrregularPartsE(EyemImage tpImage, EyemRect tpRoi, const char
 int eyemAchvMatchMat(EyemImage tpImage, EyemRect tpRoi, EyemImage *tpDstImg)
 {
 	CV_Assert(NULL != tpImage.vpImage);
-
 	cv::Mat image = cv::Mat(tpImage.iHeight, tpImage.iWidth, MAKETYPE(tpImage.iDepth, tpImage.iChannels), tpImage.vpImage).clone();
-
 	if (image.empty())
 		return FUNC_IMAGE_NOT_EXIST;
 	if (image.channels() > 3) {
 		cv::cvtColor(image, image, cv::COLOR_BGRA2BGR);
 	}
-
 	//转单通道
 	if (image.channels() != 1)
 		cv::cvtColor(image, image, cv::COLOR_BGR2GRAY);
@@ -7088,47 +7144,33 @@ int eyemAchvMatchMat(EyemImage tpImage, EyemRect tpRoi, EyemImage *tpDstImg)
 	//画标记
 	cv::putText(cc, "OK", cv::Point(170, 270), cv::FONT_HERSHEY_COMPLEX, 8, cv::Scalar(0, 100, 0, 255), 8);
 	//偏移两侧取更多样本
-	cv::Point Offset[3] = { cv::Point(-90,0),cv::Point(0,0),cv::Point(90,0) };
+	cv::Point Offset[1] = { cv::Point(0,0) };
 	//返回中间一根线的中点位置图像
-	std::vector<cv::Mat> mats; cv::Mat templateMat;
+	cv::Mat templateMat;
 	for (auto&ofset : Offset)
 	{
 		cv::Point nstart = start + ofset; cv::Point nend = end + ofset;
-		//cv::line(cc, nstart, nend, cv::Scalar(0, 255, 0, 255));
-
 		cv::Mat linesample(image2.rows, image2.cols, CV_8UC1, cv::Scalar(0));
 		cv::line(linesample, nstart, nend, cv::Scalar(255), 1);
 
+		//去除中心料盘干扰
+		cv::circle(binary, start, 85, cv::Scalar(0), -1);
+
 		cv::Mat sampleLine;
 		cv::bitwise_and(linesample, binary, sampleLine);
 
 		std::vector<cv::Point> idx;
 		cv::findNonZero(sampleLine, idx);
-		//
-		if (idx.empty())
-		{
+
+		//未发现料盘
+		if (idx.empty()) {
 			return FUNC_CANNOT_CALC;
 		}
 		//保存中间图作为匹配
-		if (ofset.x == 0 && ofset.y == 0)
-		{
-			cv::Point mid = idx[idx.size() / 2];
-			templateMat = src8U(cv::Rect(cv::Point(mid.x - 64, mid.y - 64), cv::Point(mid.x + 64, mid.y + 64))&cv::Rect(0, 0, X, Y)).clone();
-			cv::cvtColor(templateMat, templateMat, cv::COLOR_GRAY2RGB);
-		}
-		int step = (idx.size() / 27);
-		if (step < 1) {
-			step = 1;
-		}
-		for (int i = 0; i < idx.size() - 1; i += step)
-		{
-			auto p = idx[i];
-			cv::Mat mat = src8U(cv::Rect(cv::Point(p.x - 64, p.y - 64), cv::Point(p.x + 64, p.y + 64))&cv::Rect(0, 0, X, Y)).clone();
-			if (mat.cols == mat.rows)
-			{
-				mats.push_back(mat);
-			}
-		}
+		cv::Point mid = idx[idx.size() / 2];
+		templateMat = src8U(cv::Rect(cv::Point(mid.x - 64, mid.y - 64), cv::Point(mid.x + 64, mid.y + 64))&cv::Rect(0, 0, X, Y)).clone();
+		cv::cvtColor(templateMat, templateMat, cv::COLOR_GRAY2RGB);
+		break;
 	}
 	//<输出匹配图像
 	tpDstImg->iWidth = templateMat.cols; tpDstImg->iHeight = templateMat.rows; tpDstImg->iDepth = templateMat.depth(); tpDstImg->iChannels = templateMat.channels();
@@ -7301,7 +7343,6 @@ int eyemInitModel(const char *ccTplName, IntPtr *hModelID)
 	for (std::vector<std::string>::iterator it = fileNames.begin(); it != fileNames.end(); ++it)
 	{
 		std::string fileName = (*it);
-
 		cv::Mat tplMat;	double matchDeg;
 		try
 		{
@@ -7312,37 +7353,26 @@ int eyemInitModel(const char *ccTplName, IntPtr *hModelID)
 			logger.t(logModule + "从本地加载模板文件异常...");
 			return FUNC_CANNOT_CALC;
 		}
-
 		if (!tplMat.empty()) {
-
 			cv::Mat _tplMat;
 			cv::bitwise_not(tplMat, _tplMat);
-
 			//载入模板
 			EyemModelID modelID;
-
 			int _Size = tplMat.cols*tplMat.rows * sizeof(unsigned char);
-
 			//数据
 			logger.t(logModule + "分配模板图像内存...");
 			modelID.vpImage = (unsigned char *)malloc(_Size);
-
 			if (NULL == modelID.vpImage)
 				return FUNC_NOT_ENOUGH_MEM;
-
 			//拷贝数据
 			logger.t(logModule + "拷贝模板数据...");
 			memcpy(modelID.vpImage, _tplMat.data, _Size);
-
 			//位置
 			modelID.iXs = modelID.iYs = 0;
-
 			//宽、高
 			modelID.iWidth = tplMat.cols; modelID.iHeight = tplMat.rows;
-
 			//匹配分数
 			modelID.dMatchDeg = matchDeg;
-
 			//名称?会导致内存泄露吗
 			logger.t(logModule + "分配模板文件名内存...");
 			modelID.lpszName = (char *)CoTaskMemAlloc(128);
@@ -7353,7 +7383,6 @@ int eyemInitModel(const char *ccTplName, IntPtr *hModelID)
 				strcpy(modelID.lpszName, file);
 			}
 			else return FUNC_NOT_ENOUGH_MEM;
-
 			//压入容器末尾
 			logger.t(logModule + "将模板压入容器...");
 			tpModelID->push_back(modelID);
@@ -7361,7 +7390,6 @@ int eyemInitModel(const char *ccTplName, IntPtr *hModelID)
 	}
 	//输出
 	*hModelID = reinterpret_cast<IntPtr>(tpModelID);
-
 	return FUNC_OK;
 }
 
@@ -8280,30 +8308,6 @@ int eyemTrainImageSampler(EyemImage tpImage, int iSize, const char *ccClassName,
 	return FUNC_OK;
 }
 
-int eyemBuildTrainFile(const char *filePath, const char *fileName, bool shuffle)
-{
-	std::vector<std::string> fileNames;
-	cv::glob(filePath, fileNames);
-	//打乱顺序
-	std::random_shuffle(fileNames.begin(), fileNames.end());
-	//写入文件
-	std::ofstream sw(fileName, std::ios::trunc);
-	for (auto&item : fileNames) {
-		std::vector<std::string> items;
-		split(item, "\\", items);
-		//
-		std::vector<std::string> items2(2);
-		split(items[items.size() - 1], ".", items2);
-		if (strcmp(items2[3].c_str(), "png") == 0)
-		{
-			std::string line = "data/val_images/" + items[items.size() - 1] + "\n";
-			sw.write(line.c_str(), line.length());
-			sw.flush();
-		}
-	}
-	sw.close();
-	return FUNC_OK;
-}
 
 #include "eyemStopwatch.h"
 int eyemLibImpl(EyemImage tpImage, EyemImage *tpDstImg)
@@ -8312,32 +8316,33 @@ int eyemLibImpl(EyemImage tpImage, EyemImage *tpDstImg)
 	cv::Mat image = cv::Mat(tpImage.iHeight, tpImage.iWidth, MAKETYPE(tpImage.iDepth, tpImage.iChannels), tpImage.vpImage).clone();
 	if (image.empty())
 		return FUNC_IMAGE_NOT_EXIST;
-	//图像尺寸
-	int X = image.cols, Y = image.rows;
-	//用于去除黑色坏点干扰
-	cv::Mat medBlur;
-	cv::medianBlur(image, medBlur, 3);
-	//去除局部量斑影响（默认亮斑尺寸不会大于15个像素）
-	cv::morphologyEx(medBlur, medBlur, cv::MORPH_ERODE, cv::getStructuringElement(cv::MORPH_RECT, cv::Size(15, 15)));
-	//图像增强
-	double min, max;
-	cv::minMaxLoc(medBlur, &min, &max, NULL);
-	image.convertTo(image, CV_64FC1);
 
-	image -= min;
-	image /= (max - min);
-	image *= 65535;
-	image.convertTo(image, CV_16UC1);
+	////图像尺寸
+	//int X = image.cols, Y = image.rows;
+	////用于去除黑色坏点干扰
+	//cv::Mat medBlur;
+	//cv::medianBlur(image, medBlur, 3);
+	////去除局部量斑影响（默认亮斑尺寸不会大于15个像素）
+	//cv::morphologyEx(medBlur, medBlur, cv::MORPH_ERODE, cv::getStructuringElement(cv::MORPH_RECT, cv::Size(15, 15)));
+	////图像增强
+	//double min, max;
+	//cv::minMaxLoc(medBlur, &min, &max, NULL);
+	//image.convertTo(image, CV_64FC1);
+
+	//image -= min;
+	//image /= (max - min);
+	//image *= 65535;
+	//image.convertTo(image, CV_16UC1);
 
-	cv::Mat image8U;
-	image.convertTo(image8U, CV_8UC1, 1 / 255.);
+	//cv::Mat image8U;
+	//image.convertTo(image8U, CV_8UC1, 1 / 255.);
 
-	cv::cvtColor(image8U, image8U, cv::COLOR_BGR2GRAY);
+	//cv::cvtColor(image8U, image8U, cv::COLOR_BGR2GRAY);
 
-	cv::Mat eqhist;
-	cv::equalizeHist(image8U, eqhist);
+	//cv::Mat eqhist;
+	//cv::equalizeHist(image8U, eqhist);
 
-	cv::imwrite("0.png",image8U);
+	//cv::imwrite("0.png",image8U);
 	return FUNC_OK;
 
 #pragma region