List of usage examples for org.opencv.features2d DescriptorMatcher FLANNBASED
int FLANNBASED
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From source file:bikecalibration.ROIDetection.java
/** * This function processes the image that contains the ROIs. It returns the * array of nodes found in the image./* www.j a v a 2 s . c o m*/ * * @param image * @return Array of nodes */ public Node[] processImage(Mat image) { Node[] outputNodes = new Node[ROIs.size()]; // convert the scene mat to gray scale Mat grayImage = new Mat(); Imgproc.cvtColor(image, grayImage, Imgproc.COLOR_BGR2GRAY); // create a feature detector FeatureDetector detector = FeatureDetector.create(FeatureDetector.SURF); List<MatOfKeyPoint> keypoints_objects = new ArrayList<>(); MatOfKeyPoint keypoints_scene = new MatOfKeyPoint(); detector.detect(ROIs, keypoints_objects); detector.detect(grayImage, keypoints_scene); // create a descriptor extractor DescriptorExtractor extractor = DescriptorExtractor.create(DescriptorExtractor.SURF); List<Mat> descriptor_objects = new ArrayList<>(); Mat descriptor_scene = new Mat(); extractor.compute(ROIs, keypoints_objects, descriptor_objects); extractor.compute(grayImage, keypoints_scene, descriptor_scene); // create a descriptor matcher DescriptorMatcher matcher = DescriptorMatcher.create(DescriptorMatcher.FLANNBASED); List<MatOfDMatch> matches = new ArrayList<>(); descriptor_objects.stream().map((descriptor_object) -> { MatOfDMatch match = new MatOfDMatch(); matcher.match(descriptor_object, descriptor_scene, match); return match; }).forEach((match) -> { matches.add(match); }); ArrayList<ArrayList<DMatch>> matchesList = new ArrayList<>(); matches.stream().forEach((match) -> { matchesList.add((ArrayList<DMatch>) match.toList()); }); double max_dist = 100; double min_dist = 0; return null; }
From source file:com.oetermann.imageclassifier.MatchFinderWrapper.java
License:Open Source License
public MatchFinderWrapper(String fromFile) { matcher = DescriptorMatcher.create(DescriptorMatcher.FLANNBASED); matcher.read(fromFile);//from ww w. j av a 2s .c o m this.matchesPerImage = new double[matcher.getTrainDescriptors().size()]; imageNames = new String[matcher.getTrainDescriptors().size()]; for (int i = 0; i < imageNames.length; i++) { imageNames[i] = "Image#" + i; } }
From source file:com.oetermann.imageclassifier.MatchFinderWrapper.java
License:Open Source License
public MatchFinderWrapper(List<String> images, List<Mat> descriptors) { matcher = DescriptorMatcher.create(DescriptorMatcher.FLANNBASED); descriptors.stream().forEach((descriptor) -> { descriptor.convertTo(descriptor, CvType.CV_32F); });//from w w w . ja v a 2 s. c o m matcher.add(descriptors); matcher.train(); matchesPerImage = new double[descriptors.size()]; imageNames = new String[images.size()]; for (int i = 0; i < images.size(); i++) { String name = images.get(i); imageNames[i] = name.substring(name.lastIndexOf('/') + 1, name.contains(".descr") ? name.indexOf(".descr") : name.length()); } }
From source file:com.seleniumtests.util.imaging.ImageDetector.java
License:Apache License
/** * Compute the rectangle where the searched picture is and the rotation angle between both images * Throw {@link ImageSearchException} if picture is not found * @return/* w w w.ja v a2s . c om*/ * @Deprecated Kept here for information, but open CV 3 does not include SURF anymore for java build */ public void detectCorrespondingZone() { Mat objectImageMat = Imgcodecs.imread(objectImage.getAbsolutePath(), Imgcodecs.CV_LOAD_IMAGE_COLOR); Mat sceneImageMat = Imgcodecs.imread(sceneImage.getAbsolutePath(), Imgcodecs.CV_LOAD_IMAGE_COLOR); FeatureDetector surf = FeatureDetector.create(FeatureDetector.SURF); MatOfKeyPoint objectKeyPoints = new MatOfKeyPoint(); MatOfKeyPoint sceneKeyPoints = new MatOfKeyPoint(); surf.detect(objectImageMat, objectKeyPoints); surf.detect(sceneImageMat, sceneKeyPoints); DescriptorExtractor surfExtractor = DescriptorExtractor.create(DescriptorExtractor.SURF); Mat objectDescriptor = new Mat(); Mat sceneDescriptor = new Mat(); surfExtractor.compute(objectImageMat, objectKeyPoints, objectDescriptor); surfExtractor.compute(sceneImageMat, sceneKeyPoints, sceneDescriptor); try { Mat outImage = new Mat(); Features2d.drawKeypoints(objectImageMat, objectKeyPoints, outImage); String tempFile = File.createTempFile("img", ".png").getAbsolutePath(); writeComparisonPictureToFile(tempFile, outImage); } catch (IOException e) { } // http://stackoverflow.com/questions/29828849/flann-for-opencv-java DescriptorMatcher matcher = DescriptorMatcher.create(DescriptorMatcher.FLANNBASED); MatOfDMatch matches = new MatOfDMatch(); if (objectKeyPoints.toList().isEmpty()) { throw new ImageSearchException("No keypoints in object to search, check it's not uniformly coloured: " + objectImage.getAbsolutePath()); } if (sceneKeyPoints.toList().isEmpty()) { throw new ImageSearchException( "No keypoints in scene, check it's not uniformly coloured: " + sceneImage.getAbsolutePath()); } if (objectDescriptor.type() != CvType.CV_32F) { objectDescriptor.convertTo(objectDescriptor, CvType.CV_32F); } if (sceneDescriptor.type() != CvType.CV_32F) { sceneDescriptor.convertTo(sceneDescriptor, CvType.CV_32F); } matcher.match(objectDescriptor, sceneDescriptor, matches); double maxDist = 0; double minDist = 10000; for (int i = 0; i < objectDescriptor.rows(); i++) { double dist = matches.toList().get(i).distance; if (dist < minDist) { minDist = dist; } if (dist > maxDist) { maxDist = dist; } } logger.debug("-- Max dist : " + maxDist); logger.debug("-- Min dist : " + minDist); LinkedList<DMatch> goodMatches = new LinkedList<>(); MatOfDMatch gm = new MatOfDMatch(); for (int i = 0; i < objectDescriptor.rows(); i++) { if (matches.toList().get(i).distance < detectionThreshold) { goodMatches.addLast(matches.toList().get(i)); } } gm.fromList(goodMatches); Features2d.drawMatches(objectImageMat, objectKeyPoints, sceneImageMat, sceneKeyPoints, gm, imgMatch, Scalar.all(-1), Scalar.all(-1), new MatOfByte(), Features2d.NOT_DRAW_SINGLE_POINTS); if (goodMatches.isEmpty()) { throw new ImageSearchException("Cannot find matching zone"); } LinkedList<Point> objList = new LinkedList<>(); LinkedList<Point> sceneList = new LinkedList<>(); List<KeyPoint> objectKeyPointsList = objectKeyPoints.toList(); List<KeyPoint> sceneKeyPointsList = sceneKeyPoints.toList(); for (int i = 0; i < goodMatches.size(); i++) { objList.addLast(objectKeyPointsList.get(goodMatches.get(i).queryIdx).pt); sceneList.addLast(sceneKeyPointsList.get(goodMatches.get(i).trainIdx).pt); } MatOfPoint2f obj = new MatOfPoint2f(); obj.fromList(objList); MatOfPoint2f scene = new MatOfPoint2f(); scene.fromList(sceneList); // Calib3d.RANSAC could be used instead of 0 Mat hg = Calib3d.findHomography(obj, scene, 0, 5); Mat objectCorners = new Mat(4, 1, CvType.CV_32FC2); Mat sceneCorners = new Mat(4, 1, CvType.CV_32FC2); objectCorners.put(0, 0, new double[] { 0, 0 }); objectCorners.put(1, 0, new double[] { objectImageMat.cols(), 0 }); objectCorners.put(2, 0, new double[] { objectImageMat.cols(), objectImageMat.rows() }); objectCorners.put(3, 0, new double[] { 0, objectImageMat.rows() }); Core.perspectiveTransform(objectCorners, sceneCorners, hg); // points of object Point po1 = new Point(objectCorners.get(0, 0)); Point po2 = new Point(objectCorners.get(1, 0)); Point po3 = new Point(objectCorners.get(2, 0)); Point po4 = new Point(objectCorners.get(3, 0)); // point of object in scene Point p1 = new Point(sceneCorners.get(0, 0)); // top left Point p2 = new Point(sceneCorners.get(1, 0)); // top right Point p3 = new Point(sceneCorners.get(2, 0)); // bottom right Point p4 = new Point(sceneCorners.get(3, 0)); // bottom left logger.debug(po1); logger.debug(po2); logger.debug(po3); logger.debug(po4); logger.debug(p1); // top left logger.debug(p2); // top right logger.debug(p3); // bottom right logger.debug(p4); // bottom left if (debug) { try { // translate corners p1.set(new double[] { p1.x + objectImageMat.cols(), p1.y }); p2.set(new double[] { p2.x + objectImageMat.cols(), p2.y }); p3.set(new double[] { p3.x + objectImageMat.cols(), p3.y }); p4.set(new double[] { p4.x + objectImageMat.cols(), p4.y }); Imgproc.line(imgMatch, p1, p2, new Scalar(0, 255, 0), 1); Imgproc.line(imgMatch, p2, p3, new Scalar(0, 255, 0), 1); Imgproc.line(imgMatch, p3, p4, new Scalar(0, 255, 0), 1); Imgproc.line(imgMatch, p4, p1, new Scalar(0, 255, 0), 1); showResultingPicture(imgMatch); } catch (IOException e) { } } // check rotation angles checkRotationAngle(p1, p2, p3, p4, po1, po2, po3, po4); // rework on scene points as new, we are sure the object rotation is 0, 90, 180 or 270 reworkOnScenePoints(p1, p2, p3, p4); // check that aspect ratio of the detected height and width are the same checkDetectionZoneAspectRatio(p1, p2, p4, po1, po2, po4); recordDetectedRectangle(p1, p2, p3, p4); }
From source file:overwatchteampicker.OverwatchTeamPicker.java
public static ReturnValues findImage(String template, String source, int flag) { File lib = null;/*from w w w .j a v a 2 s . c o m*/ BufferedImage image = null; try { image = ImageIO.read(new File(source)); } catch (Exception e) { e.printStackTrace(); } String os = System.getProperty("os.name"); String bitness = System.getProperty("sun.arch.data.model"); if (os.toUpperCase().contains("WINDOWS")) { if (bitness.endsWith("64")) { lib = new File("C:\\Users\\POWERUSER\\Downloads\\opencv\\build\\java\\x64\\" + System.mapLibraryName("opencv_java2413")); } else { lib = new File("libs//x86//" + System.mapLibraryName("opencv_java2413")); } } System.load(lib.getAbsolutePath()); String tempObject = "images\\hero_templates\\" + template + ".png"; String source_pic = source; Mat objectImage = Highgui.imread(tempObject, Highgui.CV_LOAD_IMAGE_GRAYSCALE); Mat sceneImage = Highgui.imread(source_pic, Highgui.CV_LOAD_IMAGE_GRAYSCALE); MatOfKeyPoint objectKeyPoints = new MatOfKeyPoint(); FeatureDetector featureDetector = FeatureDetector.create(FeatureDetector.SURF); featureDetector.detect(objectImage, objectKeyPoints); KeyPoint[] keypoints = objectKeyPoints.toArray(); MatOfKeyPoint objectDescriptors = new MatOfKeyPoint(); DescriptorExtractor descriptorExtractor = DescriptorExtractor.create(DescriptorExtractor.SURF); descriptorExtractor.compute(objectImage, objectKeyPoints, objectDescriptors); // Create the matrix for output image. Mat outputImage = new Mat(objectImage.rows(), objectImage.cols(), Highgui.CV_LOAD_IMAGE_COLOR); Scalar newKeypointColor = new Scalar(255, 0, 0); Features2d.drawKeypoints(objectImage, objectKeyPoints, outputImage, newKeypointColor, 0); // Match object image with the scene image MatOfKeyPoint sceneKeyPoints = new MatOfKeyPoint(); MatOfKeyPoint sceneDescriptors = new MatOfKeyPoint(); featureDetector.detect(sceneImage, sceneKeyPoints); descriptorExtractor.compute(sceneImage, sceneKeyPoints, sceneDescriptors); Mat matchoutput = new Mat(sceneImage.rows() * 2, sceneImage.cols() * 2, Highgui.CV_LOAD_IMAGE_COLOR); Scalar matchestColor = new Scalar(0, 255, 25); List<MatOfDMatch> matches = new LinkedList<MatOfDMatch>(); DescriptorMatcher descriptorMatcher = DescriptorMatcher.create(DescriptorMatcher.FLANNBASED); descriptorMatcher.knnMatch(objectDescriptors, sceneDescriptors, matches, 2); LinkedList<DMatch> goodMatchesList = new LinkedList<DMatch>(); float nndrRatio = .78f; for (int i = 0; i < matches.size(); i++) { MatOfDMatch matofDMatch = matches.get(i); DMatch[] dmatcharray = matofDMatch.toArray(); DMatch m1 = dmatcharray[0]; DMatch m2 = dmatcharray[1]; if (m1.distance <= m2.distance * nndrRatio) { goodMatchesList.addLast(m1); } } if (goodMatchesList.size() >= 4) { List<KeyPoint> objKeypointlist = objectKeyPoints.toList(); List<KeyPoint> scnKeypointlist = sceneKeyPoints.toList(); LinkedList<Point> objectPoints = new LinkedList<>(); LinkedList<Point> scenePoints = new LinkedList<>(); for (int i = 0; i < goodMatchesList.size(); i++) { objectPoints.addLast(objKeypointlist.get(goodMatchesList.get(i).queryIdx).pt); scenePoints.addLast(scnKeypointlist.get(goodMatchesList.get(i).trainIdx).pt); } MatOfPoint2f objMatOfPoint2f = new MatOfPoint2f(); objMatOfPoint2f.fromList(objectPoints); MatOfPoint2f scnMatOfPoint2f = new MatOfPoint2f(); scnMatOfPoint2f.fromList(scenePoints); Mat homography = Calib3d.findHomography(objMatOfPoint2f, scnMatOfPoint2f, Calib3d.RANSAC, 3); Mat obj_corners = new Mat(4, 1, CvType.CV_32FC2); Mat scene_corners = new Mat(4, 1, CvType.CV_32FC2); obj_corners.put(0, 0, new double[] { 0, 0 }); obj_corners.put(1, 0, new double[] { objectImage.cols(), 0 }); obj_corners.put(2, 0, new double[] { objectImage.cols(), objectImage.rows() }); obj_corners.put(3, 0, new double[] { 0, objectImage.rows() }); Core.perspectiveTransform(obj_corners, scene_corners, homography); Mat img = Highgui.imread(source_pic, Highgui.CV_LOAD_IMAGE_COLOR); Core.line(img, new Point(scene_corners.get(0, 0)), new Point(scene_corners.get(1, 0)), new Scalar(0, 255, 255), 4); Core.line(img, new Point(scene_corners.get(1, 0)), new Point(scene_corners.get(2, 0)), new Scalar(255, 255, 0), 4); Core.line(img, new Point(scene_corners.get(2, 0)), new Point(scene_corners.get(3, 0)), new Scalar(0, 255, 0), 4); Core.line(img, new Point(scene_corners.get(3, 0)), new Point(scene_corners.get(0, 0)), new Scalar(0, 255, 0), 4); MatOfDMatch goodMatches = new MatOfDMatch(); goodMatches.fromList(goodMatchesList); Features2d.drawMatches(objectImage, objectKeyPoints, sceneImage, sceneKeyPoints, goodMatches, matchoutput, matchestColor, newKeypointColor, new MatOfByte(), 2); if (new Point(scene_corners.get(0, 0)).x < new Point(scene_corners.get(1, 0)).x && new Point(scene_corners.get(0, 0)).y < new Point(scene_corners.get(2, 0)).y) { System.out.println("found " + template); Highgui.imwrite("points.jpg", outputImage); Highgui.imwrite("matches.jpg", matchoutput); Highgui.imwrite("final.jpg", img); if (flag == 0) { ReturnValues retVal = null; int y = (int) new Point(scene_corners.get(3, 0)).y; int yHeight = (int) new Point(scene_corners.get(3, 0)).y - (int) new Point(scene_corners.get(2, 0)).y; if (y < image.getHeight() * .6) { //if found hero is in upper half of image then return point 3,0 retVal = new ReturnValues(y + (int) (image.getHeight() * .01), yHeight); } else { //if found hero is in lower half of image then return point 2,0 y = (int) new Point(scene_corners.get(2, 0)).y; retVal = new ReturnValues(y + (int) (image.getHeight() * .3), yHeight); } return retVal; } else if (flag == 1) { int[] xPoints = new int[4]; int[] yPoints = new int[4]; xPoints[0] = (int) (new Point(scene_corners.get(0, 0)).x); xPoints[1] = (int) (new Point(scene_corners.get(1, 0)).x); xPoints[2] = (int) (new Point(scene_corners.get(2, 0)).x); xPoints[3] = (int) (new Point(scene_corners.get(3, 0)).x); yPoints[0] = (int) (new Point(scene_corners.get(0, 0)).y); yPoints[1] = (int) (new Point(scene_corners.get(1, 0)).y); yPoints[2] = (int) (new Point(scene_corners.get(2, 0)).y); yPoints[3] = (int) (new Point(scene_corners.get(3, 0)).y); ReturnValues retVal = new ReturnValues(xPoints, yPoints); return retVal; } } } return null; }
From source file:View.Signature.java
public static int sift(String routeVal, String route, String n_img1, String n_img2, String extension) { String bookObject = routeVal + n_img2 + extension; String bookScene = route + n_img1 + extension; //System.out.println("Iniciando SIFT"); //java.lang.System.out.print("Abriendo imagenes | "); Mat objectImage = Highgui.imread(bookObject, Highgui.CV_LOAD_IMAGE_COLOR); Mat sceneImage = Highgui.imread(bookScene, Highgui.CV_LOAD_IMAGE_COLOR); MatOfKeyPoint objectKeyPoints = new MatOfKeyPoint(); FeatureDetector featureDetector = FeatureDetector.create(FeatureDetector.SIFT); //java.lang.System.out.print("Encontrar keypoints con SIFT | "); featureDetector.detect(objectImage, objectKeyPoints); KeyPoint[] keypoints = objectKeyPoints.toArray(); MatOfKeyPoint objectDescriptors = new MatOfKeyPoint(); DescriptorExtractor descriptorExtractor = DescriptorExtractor.create(DescriptorExtractor.SIFT); //java.lang.System.out.print("Computando descriptores | "); descriptorExtractor.compute(objectImage, objectKeyPoints, objectDescriptors); // Create the matrix for output image. Mat outputImage = new Mat(objectImage.rows(), objectImage.cols(), Highgui.CV_LOAD_IMAGE_COLOR); Scalar newKeypointColor = new Scalar(255, 0, 0); //java.lang.System.out.print("Dibujando keypoints en imagen base | "); Features2d.drawKeypoints(objectImage, objectKeyPoints, outputImage, newKeypointColor, 0); // Match object image with the scene image MatOfKeyPoint sceneKeyPoints = new MatOfKeyPoint(); MatOfKeyPoint sceneDescriptors = new MatOfKeyPoint(); //java.lang.System.out.print("Detectando keypoints en imagen base | "); featureDetector.detect(sceneImage, sceneKeyPoints); //java.lang.System.out.print("Computando descriptores en imagen base | "); descriptorExtractor.compute(sceneImage, sceneKeyPoints, sceneDescriptors); Mat matchoutput = new Mat(sceneImage.rows() * 2, sceneImage.cols() * 2, Highgui.CV_LOAD_IMAGE_COLOR); Scalar matchestColor = new Scalar(0, 255, 0); List<MatOfDMatch> matches = new LinkedList<MatOfDMatch>(); DescriptorMatcher descriptorMatcher = DescriptorMatcher.create(DescriptorMatcher.FLANNBASED); //java.lang.System.out.print("Encontrando matches entre imagenes | "); descriptorMatcher.knnMatch(objectDescriptors, sceneDescriptors, matches, 2); //java.lang.System.out.println("Calculando buenos matches"); LinkedList<DMatch> goodMatchesList = new LinkedList<DMatch>(); float nndrRatio = 0.7f; java.lang.System.out.println(matches.size()); for (int i = 0; i < matches.size(); i++) { MatOfDMatch matofDMatch = matches.get(i); DMatch[] dmatcharray = matofDMatch.toArray(); DMatch m1 = dmatcharray[0];// w w w. ja v a 2 s . c o m DMatch m2 = dmatcharray[1]; if (m1.distance <= m2.distance * nndrRatio) { goodMatchesList.addLast(m1); } } if (goodMatchesList.size() >= 7) { //java.lang.System.out.println("Match enontrado!!! Matches: "+goodMatchesList.size()); //if(goodMatchesList.size()>max){ //cambio = 1; //} List<KeyPoint> objKeypointlist = objectKeyPoints.toList(); List<KeyPoint> scnKeypointlist = sceneKeyPoints.toList(); LinkedList<Point> objectPoints = new LinkedList<>(); LinkedList<Point> scenePoints = new LinkedList<>(); for (int i = 0; i < goodMatchesList.size(); i++) { objectPoints.addLast(objKeypointlist.get(goodMatchesList.get(i).queryIdx).pt); scenePoints.addLast(scnKeypointlist.get(goodMatchesList.get(i).trainIdx).pt); } MatOfPoint2f objMatOfPoint2f = new MatOfPoint2f(); objMatOfPoint2f.fromList(objectPoints); MatOfPoint2f scnMatOfPoint2f = new MatOfPoint2f(); scnMatOfPoint2f.fromList(scenePoints); Mat homography = Calib3d.findHomography(objMatOfPoint2f, scnMatOfPoint2f, Calib3d.RANSAC, 3); Mat obj_corners = new Mat(4, 1, CvType.CV_32FC2); Mat scene_corners = new Mat(4, 1, CvType.CV_32FC2); obj_corners.put(0, 0, new double[] { 0, 0 }); obj_corners.put(1, 0, new double[] { objectImage.cols(), 0 }); obj_corners.put(2, 0, new double[] { objectImage.cols(), objectImage.rows() }); obj_corners.put(3, 0, new double[] { 0, objectImage.rows() }); //System.out.println("Transforming object corners to scene corners..."); Core.perspectiveTransform(obj_corners, scene_corners, homography); Mat img = Highgui.imread(bookScene, Highgui.CV_LOAD_IMAGE_COLOR); Core.line(img, new Point(scene_corners.get(0, 0)), new Point(scene_corners.get(1, 0)), new Scalar(0, 255, 0), 4); Core.line(img, new Point(scene_corners.get(1, 0)), new Point(scene_corners.get(2, 0)), new Scalar(0, 255, 0), 4); Core.line(img, new Point(scene_corners.get(2, 0)), new Point(scene_corners.get(3, 0)), new Scalar(0, 255, 0), 4); Core.line(img, new Point(scene_corners.get(3, 0)), new Point(scene_corners.get(0, 0)), new Scalar(0, 255, 0), 4); //java.lang.System.out.println("Dibujando imagen de coincidencias"); MatOfDMatch goodMatches = new MatOfDMatch(); goodMatches.fromList(goodMatchesList); Features2d.drawMatches(objectImage, objectKeyPoints, sceneImage, sceneKeyPoints, goodMatches, matchoutput, matchestColor, newKeypointColor, new MatOfByte(), 2); String n_outputImage = route + "results\\" + n_img2 + "_outputImage_sift" + extension; String n_matchoutput = route + "results\\" + n_img2 + "_matchoutput_sift" + extension; String n_img = route + "results\\" + n_img2 + "_sift" + extension; Highgui.imwrite(n_outputImage, outputImage); Highgui.imwrite(n_matchoutput, matchoutput); //Highgui.imwrite(n_img, img); java.lang.System.out.println(goodMatches.size().height); double result = goodMatches.size().height * 100 / matches.size(); java.lang.System.out.println((int) result); //double result =goodMatches.size().height; if (result > 100) { return 100; } else if (result <= 100 && result > 85) { return 85; } else if (result <= 85 && result > 50) { return 50; } else if (result <= 50 && result > 25) { return 25; } else { return 0; } } else { //java.lang.System.out.println("Firma no encontrada"); } return 0; //System.out.println("Terminando SIFT"); }
From source file:View.SignatureLib.java
public static int sift(String routeRNV, String routeAdherent) { String bookObject = routeAdherent; String bookScene = routeRNV;//w ww . j a va 2 s. co m //System.out.println("Iniciando SIFT"); //java.lang.System.out.print("Abriendo imagenes | "); Mat objectImage = Highgui.imread(bookObject, Highgui.CV_LOAD_IMAGE_COLOR); Mat sceneImage = Highgui.imread(bookScene, Highgui.CV_LOAD_IMAGE_COLOR); MatOfKeyPoint objectKeyPoints = new MatOfKeyPoint(); FeatureDetector featureDetector = FeatureDetector.create(FeatureDetector.SIFT); //java.lang.System.out.print("Encontrar keypoints con SIFT | "); featureDetector.detect(objectImage, objectKeyPoints); KeyPoint[] keypoints = objectKeyPoints.toArray(); MatOfKeyPoint objectDescriptors = new MatOfKeyPoint(); DescriptorExtractor descriptorExtractor = DescriptorExtractor.create(DescriptorExtractor.SIFT); //java.lang.System.out.print("Computando descriptores | "); descriptorExtractor.compute(objectImage, objectKeyPoints, objectDescriptors); // Create the matrix for output image. Mat outputImage = new Mat(objectImage.rows(), objectImage.cols(), Highgui.CV_LOAD_IMAGE_COLOR); Scalar newKeypointColor = new Scalar(255, 0, 0); //java.lang.System.out.print("Dibujando keypoints en imagen base | "); Features2d.drawKeypoints(objectImage, objectKeyPoints, outputImage, newKeypointColor, 0); // Match object image with the scene image MatOfKeyPoint sceneKeyPoints = new MatOfKeyPoint(); MatOfKeyPoint sceneDescriptors = new MatOfKeyPoint(); //java.lang.System.out.print("Detectando keypoints en imagen base | "); featureDetector.detect(sceneImage, sceneKeyPoints); //java.lang.System.out.print("Computando descriptores en imagen base | "); descriptorExtractor.compute(sceneImage, sceneKeyPoints, sceneDescriptors); Mat matchoutput = new Mat(sceneImage.rows() * 2, sceneImage.cols() * 2, Highgui.CV_LOAD_IMAGE_COLOR); Scalar matchestColor = new Scalar(0, 255, 0); List<MatOfDMatch> matches = new LinkedList<MatOfDMatch>(); DescriptorMatcher descriptorMatcher = DescriptorMatcher.create(DescriptorMatcher.FLANNBASED); //java.lang.System.out.println(sceneDescriptors); if (sceneDescriptors.empty()) { java.lang.System.out.println("Objeto no encontrado"); return 0; } descriptorMatcher.knnMatch(objectDescriptors, sceneDescriptors, matches, 2); //java.lang.System.out.println("Calculando buenos matches"); LinkedList<DMatch> goodMatchesList = new LinkedList<DMatch>(); float nndrRatio = 0.7f; for (int i = 0; i < matches.size(); i++) { MatOfDMatch matofDMatch = matches.get(i); DMatch[] dmatcharray = matofDMatch.toArray(); DMatch m1 = dmatcharray[0]; DMatch m2 = dmatcharray[1]; if (m1.distance <= m2.distance * nndrRatio) { goodMatchesList.addLast(m1); } } if (goodMatchesList.size() >= 7) { max = goodMatchesList.size(); List<KeyPoint> objKeypointlist = objectKeyPoints.toList(); List<KeyPoint> scnKeypointlist = sceneKeyPoints.toList(); LinkedList<Point> objectPoints = new LinkedList<>(); LinkedList<Point> scenePoints = new LinkedList<>(); for (int i = 0; i < goodMatchesList.size(); i++) { objectPoints.addLast(objKeypointlist.get(goodMatchesList.get(i).queryIdx).pt); scenePoints.addLast(scnKeypointlist.get(goodMatchesList.get(i).trainIdx).pt); } MatOfPoint2f objMatOfPoint2f = new MatOfPoint2f(); objMatOfPoint2f.fromList(objectPoints); MatOfPoint2f scnMatOfPoint2f = new MatOfPoint2f(); scnMatOfPoint2f.fromList(scenePoints); Mat homography = Calib3d.findHomography(objMatOfPoint2f, scnMatOfPoint2f, Calib3d.RANSAC, 3); Mat obj_corners = new Mat(4, 1, CvType.CV_32FC2); Mat scene_corners = new Mat(4, 1, CvType.CV_32FC2); obj_corners.put(0, 0, new double[] { 0, 0 }); obj_corners.put(1, 0, new double[] { objectImage.cols(), 0 }); obj_corners.put(2, 0, new double[] { objectImage.cols(), objectImage.rows() }); obj_corners.put(3, 0, new double[] { 0, objectImage.rows() }); //System.out.println("Transforming object corners to scene corners..."); Core.perspectiveTransform(obj_corners, scene_corners, homography); Mat img = Highgui.imread(bookScene, Highgui.CV_LOAD_IMAGE_COLOR); Core.line(img, new Point(scene_corners.get(0, 0)), new Point(scene_corners.get(1, 0)), new Scalar(0, 255, 0), 4); Core.line(img, new Point(scene_corners.get(1, 0)), new Point(scene_corners.get(2, 0)), new Scalar(0, 255, 0), 4); Core.line(img, new Point(scene_corners.get(2, 0)), new Point(scene_corners.get(3, 0)), new Scalar(0, 255, 0), 4); Core.line(img, new Point(scene_corners.get(3, 0)), new Point(scene_corners.get(0, 0)), new Scalar(0, 255, 0), 4); //java.lang.System.out.println("Dibujando imagen de coincidencias"); MatOfDMatch goodMatches = new MatOfDMatch(); goodMatches.fromList(goodMatchesList); Features2d.drawMatches(objectImage, objectKeyPoints, sceneImage, sceneKeyPoints, goodMatches, matchoutput, matchestColor, newKeypointColor, new MatOfByte(), 2); String n_outputImage = "../pre/outputImage_sift.jpg"; String n_matchoutput = "../pre/matchoutput_sift.jpg"; String n_img = "../pre/sift.jpg"; Highgui.imwrite(n_outputImage, outputImage); Highgui.imwrite(n_matchoutput, matchoutput); Highgui.imwrite(n_img, img); java.lang.System.out.println(goodMatches.size().height); double result = goodMatches.size().height;//*100/matches.size(); int score = 0; if (result > 26) { score = 100; } else if (result <= 26 && result > 22) { score = 85; } else if (result <= 22 && result > 17) { score = 50; } else if (result <= 17 && result > 11) { score = 25; } else { score = 0; } java.lang.System.out.println("Score: " + score); return score; } else { java.lang.System.out.println("Objeto no encontrado"); return 0; } //System.out.println("Terminando SIFT"); }