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eyemLib-Sharp/EyemLib.cs

@@ -924,7 +924,7 @@ namespace eyemLib_Sharp
             //eyemCountObject(image, file.Replace(".png", ""), 35, 0, 100, 5, ref pNumObj, out tpDstImg);
             //eyemCountObjectIrregularParts(image, file.Replace(".png", ""), 0.1, "IP_LARGE_PARTS", 100, 7, ref pNumObj, out tpDstImg);
             //eyemCountObjectE(image, fileName, ref pNumObj, out tpDstImg);
-            eyemCountObjectIrregularPartsE(image, file.Replace(".png", ""), "IP_LARGE_PARTS", "D://批量测试图像2//template.png", 0.6, ref pNumObj, out tpDstImg);
+            eyemCountObjectIrregularPartsE(image, file.Replace(".png", ""), "IP_LARGE_PARTS", "D://批量测试图像模板文件//" + file.Replace(".png", "") + "_tpl.png", 0.65, ref pNumObj, out tpDstImg);
 
             Bitmap bmp = eyemCvtToBitmap(tpDstImg);
 

eyemLib/eyemLib.vcxproj

@@ -112,6 +112,7 @@
       <PreprocessorDefinitions>_DEBUG;_CONSOLE;_CRT_SECURE_NO_WARNINGS;%(PreprocessorDefinitions)</PreprocessorDefinitions>
       <SDLCheck>true</SDLCheck>
       <RuntimeLibrary>MultiThreadedDebugDLL</RuntimeLibrary>
+      <OpenMPSupport>true</OpenMPSupport>
     </ClCompile>
     <Link>
       <SubSystem>Console</SubSystem>

eyemLib/eyemMisc.cpp

@@ -3818,6 +3818,13 @@ int	eyemCountObjectIrregularPartsE(EyemImage tpImage, const char *fileName, cons
 	//苏州公司&成都纬创
 	//src = src(cv::Range(10, src.cols - 10), cv::Range(10, src.rows - 10)).clone();
 
+	//图像金字塔
+	if (true)
+	{
+		//cv::pyrDown(src, src, );
+		//cv::resize(src, src, cv::Size(src.cols / 4, src.rows / 4));
+	}
+
 	//图像尺寸
 	int X = src.cols, Y = src.rows;
 
@@ -4059,7 +4066,12 @@ int	eyemCountObjectIrregularPartsE(EyemImage tpImage, const char *fileName, cons
 		tr = cv::Point(br.x, tl.y); bl = cv::Point(tl.x, br.y);
 
 		//加载模板
-		cv::Mat tplMat = cv::imread("D://批量测试图像2//template.png", -1);
+		cv::Mat tplMat = cv::imread(tplName, -1);
+
+		if (true) {
+			//cv::pyrDown(tplMat, tplMat, cv::Size(tplMat.cols / 4, tplMat.rows / 4));
+			//cv::resize(tplMat, tplMat, cv::Size(tplMat.cols / 4, tplMat.rows / 4));
+		}
 
 		int tplWidth, tplHeight;
 		tplWidth = tplMat.cols, tplHeight = tplMat.rows;
@@ -4122,12 +4134,20 @@ int	eyemCountObjectIrregularPartsE(EyemImage tpImage, const char *fileName, cons
 		cv::findNonZero(matchParts, matchPts);
 
 #ifdef _DEBUG
+
+		//计算元件间距（弦长）
+		/*
+		已知弦长L和半径R求角度2A:
+		sinA=(1/2)*L/R=L/(2R),2A=2asin(L/(2R)).
+		*/
 		for (std::vector<cv::Point>::iterator itv = matchPts.begin(); itv != matchPts.end(); ++itv)
 		{
 			//cv::drawMarker(cc, cv::Point((*itv).x, (*itv).y), cv::Scalar(0, 255, 0, 255));
 		}
 #endif
 
+		//考虑留在外面，元件间距只需要计算一次（用二者结合的方式确定元件）
+
 		//标签图
 		cv::Mat trackMat(Y, X, CV_8UC1, cv::Scalar(0));
 
@@ -4158,6 +4178,9 @@ int	eyemCountObjectIrregularPartsE(EyemImage tpImage, const char *fileName, cons
 			//标记计数
 			lbMat.ptr<uint8_t>(cvRound(startCenter.y))[cvRound(startCenter.x)] = 255;
 
+			//标记当前位置
+			cv::drawMarker(cc, cv::Point((*itv).x, (*itv).y), cv::Scalar(0, 165, 255, 255), cv::MARKER_DIAMOND, 5);
+
 			struct Track {
 				int iLimit, iPartSize;
 				double dMatchDeg;
@@ -4185,42 +4208,75 @@ int	eyemCountObjectIrregularPartsE(EyemImage tpImage, const char *fileName, cons
 			//偏移角度（元件尺寸）
 			const double dOffset = (2 * asin(2 * trackLength / (2 * startRadius))) * 180. / PI;
 
-			//初始搜索角度，用以确定元件间距
+			//初始搜索角度，用以确定元件间距(默认15度范围内存在元件)
 			const double dScanRange = 15;
 			//追踪元件间距(弦长，可以尽量避免因个别器件偏离导致的追踪中断)
-			double dChordL = .0;
-			for (double t = startAngle + (dOffset / 1.5); t < startAngle + (dOffset / 1.5) + dScanRange; t += dMinorStep * 2)
+			double dChordL = .0; std::vector<Track> trackScore; bool expect = false;
+			for (double t = startAngle + dOffset; t < startAngle + dOffset + dScanRange; t += dMinorStep)
 			{
 				float x = float(reelCenter.x + startRadius*cos(t*c));
 				float y = float(reelCenter.y + startRadius*sin(t*c));
-				//初次确定元件间距
-				const double angle = atan2((double)reelCenter.y - y, (double)reelCenter.x - x);
 
-				cv::Point p1 = cv::Point(cvRound(x + trackWidth * cos(angle)),
-					cvRound(y + trackWidth * sin(angle)));
+				cv::Point2f pts[4];
+				calcRotateRect(cv::Point2f(x, y), (float)t, (float)trackLength, (float)trackWidth, pts);
 
-				cv::Point p2 = cv::Point(cvRound(x + trackWidth * cos(angle + CV_PI)),
-					cvRound(y + trackWidth * sin(angle + CV_PI)));
+				//旋转矩形
+				cv::RotatedRect r(pts[0], pts[1], pts[2]);
 
-				cv::line(cc, p1, p2, cv::Scalar(0, 255, 0, 255));
+				//待匹配图像
+				cv::Rect rr(cv::Point2i(cv::max(r.boundingRect().x - cvRound(trackWidth), 0), \
+					cv::max(r.boundingRect().y - cvRound(trackWidth), 0)), \
+					cv::Point2i(cv::min(r.boundingRect().x + r.boundingRect().width + cvRound(trackWidth), X), \
+						cv::min(r.boundingRect().y + r.boundingRect().height + cvRound(trackWidth), Y)));
 
-				cv::LineIterator it(binary, p1, p2, 4);
-				for (int n = 0; n < it.count; n++, ++it)
+				//测试
+				cv::Mat df = srcPrev(rr);
+
+				//不同方向模板图像(考虑实时更新模板图像或多角度模板，这样可能速度会下降)
+				cv::Mat yyu = getTplMat(tplMat, 90 - (t + 180));
+
+				//待匹配图像小于模板图像的话不进行匹配
+				if (rr.width < yyu.cols || rr.height < yyu.rows)
+					continue;
+
+				//计算中心位置
+				cv::Mat tplResult0;
+				cv::matchTemplate(srcPrev(rr), yyu, tplResult0, cv::TM_CCOEFF_NORMED);
+				//
+				double maxyyu; cv::Point maxyyuloc;
+				cv::minMaxLoc(tplResult0, NULL, &maxyyu, NULL, &maxyyuloc);
+
+				//匹配阈值
+				if (maxyyu > dMinScore)
 				{
-					if ((binary.data)[(it.pos().x) + (it.pos().y)*X] == 255)
-					{
-						//计算元件间距（弦长）
-						dChordL = 2.0 * startRadius*sin(((2.0 * asin((cv::norm(startCenter - cv::Point2f(x, y))) / (2.0 * startRadius)))\
-							* 180.0 / PI - dOffset / 2.0)*PI / 180.0 / 2.0);
-						break;
-					}
-				}
+					//初次满足分数阈值
+					cv::Point2f trackCentert = cv::Point2f(float(maxyyuloc.x + rr.x + cvRound((float)yyu.cols / 2.0f)), \
+						float(maxyyuloc.y + rr.y + cvRound((float)yyu.rows / 2.0f)));
 
-				if (dChordL > 0)
+					trackScore.push_back(Track(0, 0, maxyyu, (cv::Point)trackCentert, std::vector<cv::Point2f>()));
+
+					if (!expect)
+						expect = true;
+				}
+				if ((maxyyu < dMinScore) && expect)
 					break;
 			}
-			//标记当前位置
-			cv::drawMarker(cc, cv::Point((*itv).x, (*itv).y), cv::Scalar(0, 165, 255, 255), cv::MARKER_DIAMOND, 5);
+
+			//计算元件间距
+			if (trackScore.size() != 0) {
+
+				cv::Point ecpectPos = trackScore[0].Pos;
+
+				std::sort(trackScore.begin(), trackScore.end(), std::greater<Track>());
+
+				dChordL = 2.0 * startRadius*sin(((2.0 * asin((cv::norm(startCenter - cv::Point2f((float)ecpectPos.x, \
+					(float)ecpectPos.y))) / (2.0 * startRadius))) * 180.0 / PI - dOffset)*PI / 180.0 / 2.0);
+
+				//cv::drawMarker(cc, cv::Point(ecpectPos.x, ecpectPos.y), cv::Scalar(0, 255, 0, 255), 0, 5);
+			}
+			else {
+				//用先前的方式
+			}
 
 			//无法计算元件间距
 			if (dChordL <= 0) {
@@ -4228,10 +4284,10 @@ int	eyemCountObjectIrregularPartsE(EyemImage tpImage, const char *fileName, cons
 			}
 
 			//并行处理
-			//#pragma omp parallel sections
+//#pragma omp parallel sections
 			{
 				//(顺时针)
-				//#pragma omp section
+//#pragma omp section
 				{
 					//追踪中心
 					cv::Point2f trackCenter = cv::Point2f(startCenter.x, startCenter.y);
@@ -4296,15 +4352,18 @@ int	eyemCountObjectIrregularPartsE(EyemImage tpImage, const char *fileName, cons
 							cv::Point2i(cv::min(r.boundingRect().x + r.boundingRect().width + cvRound(trackWidth), X), \
 								cv::min(r.boundingRect().y + r.boundingRect().height + cvRound(trackWidth), Y)));
 
-						cv::Mat yyuc = srcPrev(rr);
-
-						//不同方向模板图像(考虑实时更新模板图像或多角度模板，这样可能速度会下降)
+						//不同方向模板图像(考虑实时更新模板图像或多角度模板,活动模板，用定位到的区域选取当前位置的模板，这样可能速度会下降)
 						cv::Mat yyu = getTplMat(tplMat, 90 - (trackAngle + 180));
 
+						//测试用
+						//cv::rectangle(cc, rr, cv::Scalar(0, 0, 255, 255));
+						//判断待匹配图像是否小于模板图像
+						if (rr.width < yyu.cols || rr.height < yyu.rows)
+							continue;
+
 						//计算中心位置
 						cv::Mat tplResult0;
-						cv::matchTemplate(yyuc, yyu, tplResult0, cv::TM_CCOEFF_NORMED);
-
+						cv::matchTemplate(srcPrev(rr), yyu, tplResult0, cv::TM_CCOEFF_NORMED);
 
 						//
 						double maxyyu; cv::Point maxyyuloc;
@@ -4333,6 +4392,8 @@ int	eyemCountObjectIrregularPartsE(EyemImage tpImage, const char *fileName, cons
 						if ((trackMat.ptr<uint8_t>(cvRound(trackCenter.y))[cvRound(trackCenter.x)] == 255) || (maxyyu < dMinScore*0.7))
 						{
 							found = false;
+							//当分数过低采用其他方式确定是否真的终止
+							cv::drawMarker(cc, cv::Point(cvRound(trackCenter.x), cvRound(trackCenter.y)), cv::Scalar(0, 0, 255, 255), 0, 5);
 						}
 						else
 						{
@@ -4358,7 +4419,7 @@ int	eyemCountObjectIrregularPartsE(EyemImage tpImage, const char *fileName, cons
 				}
 
 				//#pragma omp section 
-				//逆时针追踪
+								//逆时针追踪
 				{
 					//追踪起点
 					cv::Point2f trackCenter(startCenter.x, startCenter.y);
@@ -4423,14 +4484,16 @@ int	eyemCountObjectIrregularPartsE(EyemImage tpImage, const char *fileName, cons
 							cv::Point2i(cv::min(r.boundingRect().x + r.boundingRect().width + cvRound(trackWidth), X), \
 								cv::min(r.boundingRect().y + r.boundingRect().height + cvRound(trackWidth), Y)));
 
-						cv::Mat yyuc = srcPrev(rr);
-
 						//不同方向模板图像(考虑实时更新模板图像或多角度模板，这样可能速度会下降)
 						cv::Mat yyu = getTplMat(tplMat, 90 - (trackAngle + 180));
 
+						//判断待匹配图像是否小于模板图像
+						if (rr.width < yyu.cols || rr.height < yyu.rows)
+							continue;
+
 						//计算中心位置
 						cv::Mat tplResult0;
-						cv::matchTemplate(yyuc, yyu, tplResult0, cv::TM_CCOEFF_NORMED);
+						cv::matchTemplate(srcPrev(rr), yyu, tplResult0, cv::TM_CCOEFF_NORMED);
 						//
 						double maxyyu; cv::Point maxyyuloc;
 
@@ -4458,6 +4521,8 @@ int	eyemCountObjectIrregularPartsE(EyemImage tpImage, const char *fileName, cons
 						if ((trackMat.ptr<uint8_t>(cvRound(trackCenter.y))[cvRound(trackCenter.x)] == 255) || (maxyyu < dMinScore*0.7))
 						{
 							found = false;
+							//当分数过低采用其他方式确定是否真的终止
+							cv::drawMarker(cc, cv::Point(cvRound(trackCenter.x), cvRound(trackCenter.y)), cv::Scalar(0, 0, 255, 255), 0, 5);
 						}
 						else
 						{

eyemLib/eyemMisc.h

@@ -6,6 +6,7 @@
 #define __EYEM_MISC_H
 
 #include <io.h>
+#include <omp.h>
 #include <fstream>
 #include <direct.h>
 #include "eyemLib.h"