From 3025a56f36ae81a554ba2061f58fcf6c7f1322e1 Mon Sep 17 00:00:00 2001 From: Pavol Debnar Date: Mon, 3 Apr 2023 15:59:36 +0200 Subject: [PATCH] added template matching; updated neigbouring function --- src/pointbase.cpp | 942 ++++++++++++++++++++++++++++++++++++++++------ src/test | Bin 157000 -> 250872 bytes 2 files changed, 836 insertions(+), 106 deletions(-) diff --git a/src/pointbase.cpp b/src/pointbase.cpp index af3de4b..acbb9e8 100644 --- a/src/pointbase.cpp +++ b/src/pointbase.cpp @@ -67,7 +67,9 @@ class PointBase { //cout << "x: " << coords["depthPos"]["x"].asDouble() << std::endl; //cout << "y: " << coords["depthPos"]["y"].asDouble() << std::endl; Point2d newPoint = Point2d(coords["depthPos"]["x"].asDouble() , coords["depthPos"]["y"].asDouble()); + newPoint.x = fmod(newPoint.x,360.0) ; pathMap[newPoint] = filePath; + points.push_back(newPoint); imgWidthDeg = coords["rectangle"]["w"].asDouble(); @@ -166,13 +168,13 @@ class PointBase { double xDifference = inputPoint.x - points[i].x; - + /* if(abs(yDifference)<15 && (xDifference<45) && (xDifference>0)) { resultVector.push_back(points[i]); toDoVector.push_back(points[i]); points.erase(points.begin()+i); - + continue; } @@ -182,6 +184,7 @@ class PointBase { resultVector.push_back(points[i]); toDoVector.push_back(points[i]); points.erase(points.begin()+i); + continue; } @@ -191,7 +194,7 @@ class PointBase { resultVector.push_back(points[i]); toDoVector.push_back(points[i]); points.erase(points.begin()+i); - + continue; } @@ -201,7 +204,16 @@ class PointBase { resultVector.push_back(points[i]); toDoVector.push_back(points[i]); points.erase(points.begin()+i); - + continue; + }*/ + + + if(abs(yDifference)<0.9*imgHeightDeg && abs(xDifference)<0.8*imgWidthDeg) + { + resultVector.push_back(points[i]); + toDoVector.push_back(points[i]); + points.erase(points.begin()+i); + continue; } } return resultVector; @@ -381,10 +393,19 @@ class PointBase { - void cumdump(int imgWidth,int imgHeight) - { + void cumdump(int imgW,int imgH) + { //sift takes too long if images are large, so we shrink them + int imgWidth = imgW; + int imgHeight = imgH; + if (imgWidth > 1000) + { + imgWidth = int(0.4*imgWidth); + imgHeight = int(0.4*imgHeight); + } - + int placeCounter =0; + int roiCounter = 0; + int tempMatchCounter =0; std::vector edges; edges = getEdgeValues(); @@ -393,10 +414,10 @@ class PointBase { double minY=edges[2]; double maxY=edges[3]; - int windowHeight = (int)(maxY*(imgHeight/imgHeightDeg))+imgHeight; + int windowHeight = (int)(maxY*(imgHeight/imgHeightDeg))+imgHeight*2; int windowWidth = (int)((360/imgWidthDeg)*imgWidth) + imgWidth; - Mat img = Mat::zeros(windowHeight,windowWidth,CV_8UC3); + Mat img = Mat::zeros(windowHeight,windowWidth,CV_8UC1); rectangle(img,Point(3,3),Point(15,15),Scalar(128,128, 0),2,2,0); int imgIdx = 0; @@ -494,7 +515,13 @@ class PointBase { pngPath = pngPath + "png"; cout << "file: " << pngPath << std::endl; - Mat imgSmall = imread(pngPath,IMREAD_COLOR); + Mat imgSmall = imread(pngPath,IMREAD_GRAYSCALE); + //resizing + cout << "w:" < clahe = cv::createCLAHE(4.0, cv::Size(8,8)); + clahe->apply(imgSmall,imgSmall); cout<< cv::typeToString( imgSmall.type() ); cout < windowHeight) yHeight = windowHeight - yLoc; //create the ROI + cout << "AM DOING ROI \n \n"; Mat roi; roi = img(Rect(xLoc, yLoc, xWitdth, yHeight)); /*imshow("roi",roi); @@ -561,7 +596,7 @@ class PointBase { drawMatches(roi,keypointsROI,imgSmall,keypointsImg,matches,imageMatches); cv::namedWindow("matches"); cv::imshow("matches",imageMatches); - cv::waitKey(0); + //cv::waitKey(0); @@ -596,7 +631,9 @@ class PointBase { cout<<"TU BY MALI BYT MATCHE " <<'\n'; std::vector< DMatch > good_matches; //float ratio = 0.4; // As in Lowe's paper; can be tuned - for (float ratio = 0.4; good_matches.size()<2; ratio+=0.05) + /* + //this is continous worsening of the ratio in order to get good matches - after 0.4 the results were getting kinda bad tho + for (float ratio = 0.4; good_matches.size()<3; ratio+=0.05) { good_matches.clear(); cout << "RATIO: " < obj; @@ -630,103 +672,179 @@ class PointBase { } - + //find a transformation based on good matches //we do not need a Homography, since we deal with affine transformations (no viewport transf. are expected) //Mat H = findHomography( Mat(obj), Mat(scene), RANSAC ); - Mat H = estimateAffinePartial2D( Mat(obj), Mat(scene), noArray(),RANSAC ); - - cv::Mat resultWarp; - cv::Mat resultBlend,roiMask,imgWarpedMask,overlapMask,overlapDST,roiDT, imgDT; - //warpPerspective(imgSmall,roi,H,cv::Size(roi.cols,roi.rows)); - warpAffine(imgSmall,resultWarp,H,cv::Size(roi.cols,roi.rows)); - /*cv::Mat half(result,cv::Rect(0,0,imgSmall.cols,imgSmall.rows)); - result.copyTo(roi);*/ - imshow("imgSmall", imgSmall); - imshow( "resultWarp", resultWarp ); - imshow("roi", roi); - cv::waitKey(0); - + Mat H; + if(good_matches.size()>=3) H = estimateAffinePartial2D( Mat(obj), Mat(scene), noArray(),RANSAC ); - //cv::addWeighted( roi, 0.5, resultWarp, 0.5, 0.0, resultBlend); - //thresholding roi and img, in order to create image masks - threshold(roi,roiMask,1,255,CV_8U); - threshold(resultWarp,imgWarpedMask,1,255,CV_8U); - - multiply(roiMask,imgWarpedMask,overlapMask); - //we need to change type in order for img multiplication to work in OpenCV - cv::cvtColor(overlapMask,overlapMask,COLOR_BGR2GRAY); - cv::cvtColor(roiMask,roiMask,COLOR_BGR2GRAY); - cv::cvtColor(imgWarpedMask,imgWarpedMask,COLOR_BGR2GRAY); - cv::cvtColor(roi,roi,COLOR_BGR2GRAY); - cv::cvtColor(resultWarp,resultWarp,COLOR_BGR2GRAY); - - //the blending function is DistanceTransform(img1)/(DT(img1)+DT(img2)) - DT is created from the masks - distanceTransform(roiMask,roiDT,DIST_L2, 3); - distanceTransform(imgWarpedMask,imgDT,DIST_L2, 3); - //normalize(overlapDST, overlapDST, 0.0, 1.0, NORM_MINMAX); - + //here we check for errors - either there were not enough good matches, OR an affine transformation could not be estimated + //we use template matching if errors occured + if(good_matches.size()<3 || H.empty()) + { + tempMatchCounter++; + Mat workRoi, workImg; + workRoi = roi.clone(); + workImg = imgSmall.clone(); + + GaussianBlur(roi, workRoi, Size(3, 3), 0); + GaussianBlur(imgSmall, workImg, Size(3, 3), 0); + + Canny(workRoi, workRoi, 100, 200, 3, false); + Canny(workImg, workImg, 100, 200, 3, false); + + Mat result; + double min_val, max_val; + Point min_loc, max_loc; + matchTemplate(workRoi,workImg,result,TM_CCOEFF); + minMaxLoc(result,&min_val,&max_val,&min_loc,&max_loc); + + + Mat roiMask, roiDT, imgWarpedMask,imgDT,roiMaskFinal,imgMaskFinal,imgNew; + threshold(roi,roiMask,1,255,CV_8U); + imgWarpedMask = Mat::zeros(roi.rows,roi.cols,CV_8U); + imgWarpedMask(Rect(max_loc.x,max_loc.y,imgSmall.cols,imgSmall.rows))=1.0; + + + distanceTransform(roiMask,roiDT,DIST_L2, 3); + distanceTransform(imgWarpedMask,imgDT,DIST_L2, 3); + normalize(roiDT, roiDT, 0.0, 1.0, NORM_MINMAX); + normalize(imgDT, imgDT, 0.0, 1.0, NORM_MINMAX); + + cv::divide(roiDT,(roiDT+imgDT),roiMaskFinal); + cv::divide(imgDT,(roiDT+imgDT),imgMaskFinal); + + + + normalize(roiMaskFinal, roiMaskFinal, 0.0, 255.0, NORM_MINMAX); + normalize(imgMaskFinal, imgMaskFinal, 0.0, 255.0, NORM_MINMAX); + imgNew = Mat::zeros(roi.rows,roi.cols,CV_8U); + imgSmall.copyTo(imgNew(Rect(max_loc.x , max_loc.y , imgSmall.cols,imgSmall.rows))); + + + roiMaskFinal.convertTo(roiMaskFinal,CV_8UC1); + imgMaskFinal.convertTo(imgMaskFinal,CV_8UC1); + roi.convertTo(roi,CV_32FC1); + imgNew.convertTo(imgNew,CV_32FC1); + roiMaskFinal.convertTo(roiMaskFinal,CV_32FC1); + imgMaskFinal.convertTo(imgMaskFinal,CV_32FC1); + + + multiply(roiMaskFinal,roi,roi); + cout< 1000) + { + imgWidth = int(0.4*imgWidth); + imgHeight = int(0.4*imgHeight); + } + + + std::vector edges; + edges = getEdgeValues(); + double minX=edges[0]; + double maxX=edges[1]; + double minY=edges[2]; + double maxY=edges[3]; + + int windowHeight = (int)(maxY*(imgHeight/imgHeightDeg))+imgHeight*2; + int windowWidth = (int)((360/imgWidthDeg)*imgWidth) + imgWidth; + + Mat img = Mat::zeros(windowHeight,windowWidth,CV_8UC1); + rectangle(img,Point(3,3),Point(15,15),Scalar(128,128, 0),2,2,0); + + int imgIdx = 0; + //main loop + while (!points.empty()) + { + //take the first point from the left and find adjts. to it + Point2d p = points[0]; + vector stitchQueue; + stitchQueue.push_back(p); + points.erase(points.begin()); + + vector temp = getAdjacents(p); //find adj. of first point - inits toDo vector + + + if (toDoVector.empty()) //if first point has no adjts. - log him as singleton + { + ofstream singletonsFile("singletons.log", ios_base::app); + if(!singletonsFile) + { + singletonsFile << "x: " << p.x << std::endl; + singletonsFile << "y: " << p.y << std::endl; + singletonsFile << pathMap[Point2d(p.x,p.y) ] << std::endl; + singletonsFile.close(); + } + else + { + ofstream sing; + sing.open("singletons.log",ios_base::app); + sing << "x: " << p.x << std::endl; + sing << "y: " << p.y << std::endl; + sing << pathMap[Point2d(p.x,p.y) ] << std::endl; + sing.close(); + } + stitchQueue.pop_back(); + continue; + } + + //finds adjacencies to every point + while(!toDoVector.empty()) + { + Point2d p2 = toDoVector[0]; + stitchQueue.push_back(p2); + temp = getAdjacents(p2); + toDoVector.erase(toDoVector.begin()); + } + + //stitching + // Define object to store the stitched image + /* a funct was created for this, see getEdgeValues() + double minX=999; + double maxX=0; + double minY=900000; + double maxY=0; + + for (Point2d coords: stitchQueue) + { + if (coords.x < minX) minX=coords.x; + if (coords.x > maxX) maxX=coords.x; + if (coords.y < minY) minY=coords.y; + if (coords.y > maxY) maxY=coords.y; + } + */ + + int xDiff = (int)round(maxX)-(int)round(minX); + int yDiff = (int)round(maxY)-(int)round(minY); + cout < clahe = cv::createCLAHE(4.0, cv::Size(8,8)); + clahe->apply(imgSmall,imgSmall); + cout<< cv::typeToString( imgSmall.type() ); + + cout < windowWidth) xWitdth = windowWidth - xLoc; + if (yLoc + yHeight > windowHeight) yHeight = windowHeight - yLoc; + + //create the ROI + Mat roi; //we dont need to apply CLAHE to ROI, since it consists of images which have clahe already applied + roi = img(Rect(xLoc, yLoc, xWitdth, yHeight)); + + Mat roiEdit, imgSmallEdit; + roiEdit = roi.clone(); + imgSmallEdit = imgSmall.clone(); + + + GaussianBlur(roi, roiEdit, Size(3, 3), 0); + GaussianBlur(imgSmall, imgSmallEdit, Size(3, 3), 0); + + Canny(roiEdit, roiEdit, 100, 200, 3, false); + Canny(imgSmallEdit, imgSmallEdit, 100, 200, 3, false); + + + //vector rectHolder; + //Mat rect1,rect2,rect3,rect4,rect5; + int rectH = imgSmall.rows, rectW = imgSmall.cols; + /* + Point2d coord1 = Point2d(int(imgWidth*0.1),int(imgHeight*0.1)); + Point2d coord2 = Point2d(int(imgWidth*0.1),int(imgHeight*0.7)); + Point2d coord3 = Point2d(int(imgWidth*0.5),int(imgHeight*0.5)); + Point2d coord4 = Point2d(int(imgWidth*0.7),int(imgHeight*0.2)); + Point2d coord5 = Point2d(int(imgWidth*0.7),int(imgHeight*0.7)); + */ + //vector coordRects; + /* + coordRects.push_back(coord1); + coordRects.push_back(coord2); + coordRects.push_back(coord3); + coordRects.push_back(coord4); + coordRects.push_back(coord5); + */ + + /* + vector coordRects; + vector rects; + + for (int y= 0; y results; + double min_val, max_val; + Point min_loc, max_loc; + double globMax = 0.0; + int minIDX = 0; + Mat result; + + + for (int i = 0; i < rects.size(); i++) + { + + matchTemplate(roiEdit,rects[i],result,TM_CCOEFF); + results.push_back(result); + + + minMaxLoc(result,&min_val,&max_val,&min_loc,&max_loc); + if (max_val>globMax) + { + globMax=max_val; + minIDX = i; + } + } + + minMaxLoc(results[minIDX],&min_val,&max_val,&min_loc,&max_loc); + + + cout << "SIZE:"<< results[minIDX].size() << '\n'; + cout << "IDX:" << minIDX << "\n"; + */ + //min_loc is the top left of the best of the five sub-rois + //the top left of where to put the small img is min_loc - coordrects[minIDX] + + Mat result; + double min_val, max_val; + Point min_loc, max_loc; + matchTemplate(roiEdit,imgSmallEdit,result,TM_CCOEFF); + minMaxLoc(result,&min_val,&max_val,&min_loc,&max_loc); + + + //debug stuff + Mat roiWithLocation, chosenSmallRoiImg; + imshow("matchResult",result); + roiWithLocation= roiEdit.clone(); + chosenSmallRoiImg = imgSmallEdit.clone(); + rectangle(roiWithLocation,max_loc,Point(max_loc.x+rectW,max_loc.y+rectH),Scalar(128,128, 0),2,2,0); + rectangle(chosenSmallRoiImg,max_loc,Point(rectW,rectH),Scalar(128,128, 0),2,2,0); + imshow("roiWithLocation",roiWithLocation); + imshow("chosenSmallRoiImg",chosenSmallRoiImg); + + //cout<<"HOW MANY RECTS " <stitch(imgs, pano); + if (status != Stitcher::OK) + { + // Check if images could not be stitched + // status is OK if images are stitched successfully + cout << "Can't stitch images\n"; + } + else + { + + string resultName = "result" + to_string(imgIdx) +".jpg"; + + // Store a new image stitched from the given + //set of images as "result.jpg" + imwrite(resultName, pano); + + // Show the result + imshow(resultName, pano); + + + waitKey(0); + } + */ + + } + + imwrite("result0GIOJSDFI.png", img); + } + + + + +}; + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/src/test b/src/test index 2b7e26a7e466fefd85f5c0bd3246bbe3402b839f..aa10e1e17653879e595b10a40c34809ce2d39792 100755 GIT binary patch literal 250872 zcmdqK34B!56+b=!qDaMnilTLiJ5;~~2#W;`%jlq>DG=WGYtCb%1Z{8msQj*9Jp}A zuz|yd4w_dvXfTUFa?uzRQ>UMmAA(z&2&c@*zBo|9)c*E4o4$SE>$5(%smnq4{%uHX z+_SD3VDHBpfw&p}ZdDB{@qU;3 z{1^3p58m%ppXu#B{JS6j9>Bi`@o#JC^K%z*5H#+-7%@B>%uJMO08f7y8Z`y-Z}_{!H$){P!D=$JXr zE$uP?>y8K4pVwvoK{xa+dpdeakHu&F&N=RPm$Y0o?XbxGH`ZJ}_JHAkIC8+9>)yZm zlFZ8%-+K3v6A#W=cz=(l@4T@l?c@W7j|;!@$b#UVTKCLSc^~X=beDe($6G@h>4z{Kg%7gg^eNz5Vf_ z0Q#o`o;!SBmMCaBy>Oejzj$My>mz@t071_etasCbo}toB5C>I 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