List of usage examples for org.opencv.core Point Point
public Point(double[] vals)
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/*from ww w . j av a2 s . 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:gov.nasa.jpl.memex.pooledtimeseries.PoT.java
License:Apache License
static void updateOpticalHistogram(double[][][] hist, Mat flow) { int d1 = hist.length; int d2 = hist[0].length; int d3 = hist[0][0].length; int step = 4; // 5; for (int x = 0; x < frame_width; x += step) { int x_type = (int) (x * d1 / frame_width); for (int y = 0; y < frame_height; y += step) { int y_type = (int) (y * d2 / frame_height); Point fxy = new Point(flow.get(y, x)); double size = (fxy.x + fxy.y) * (fxy.x + fxy.y); if (size < 9) { continue; // 25 } else { int f_type = opticalFlowType(fxy, d3); hist[x_type][y_type][f_type]++; }//w w w . j a v a 2 s .co m } } }
From source file:org.surmon.pattern.editor2d.components.Mapping.java
public static List<MatOfPoint> process(Mat source, List<Particle> particles) { Mat partImage = new Mat(source.size(), CvType.CV_8UC1); // Draw particles as images Point p;/*from ww w.j ava 2s .co m*/ for (Particle part : particles) { p = new Point(part.getPosition().toArray()); Core.circle(partImage, p, 1, new Scalar(255)); } // Blur with Gaussian kernel Mat blured = new Mat(); Imgproc.GaussianBlur(partImage, blured, new Size(101, 101), -1, -1); // Equalize histogram List<Mat> eqChannels = new ArrayList<>(); List<Mat> channels = new ArrayList<>(); Core.split(blured, channels); for (Mat channel : channels) { Mat eqImage = new Mat(); Imgproc.equalizeHist(channel, eqImage); eqChannels.add(eqImage); } Mat eqResult = new Mat(); Core.merge(eqChannels, eqResult); // Binary threshold Mat bin = new Mat(); Imgproc.threshold(eqResult, bin, 0, 255, Imgproc.THRESH_OTSU); // Imgproc.threshold(eqResult, bin, 10, 255, Imgproc.THRESH_BINARY); // Find contours Mat imMat = bin.clone(); Mat canny_output = new Mat(); Mat hierarchy = new Mat(); int thresh = 100; //median filter: List<MatOfPoint> borders = new ArrayList<>(); Imgproc.Canny(imMat, canny_output, thresh, thresh * 2); Imgproc.findContours(canny_output, borders, hierarchy, Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE); // Find contours return borders; // Mat result = source.clone(); // Imgproc.drawContours(result, borders, -1, new Scalar(255, 0, 255)); // // return result; }
From source file:org.usfirst.frc.team2084.CMonster2016.vision.Target.java
License:Open Source License
/** * Creates a new possible target based on the specified blob and calculates * its score./* w ww . j a va2 s . co m*/ * * @param p the shape of the possible target */ public Target(MatOfPoint contour, Mat grayImage) { // Simplify contour to make the corner finding algorithm work better MatOfPoint2f fContour = new MatOfPoint2f(); contour.convertTo(fContour, CvType.CV_32F); Imgproc.approxPolyDP(fContour, fContour, VisionParameters.getGoalApproxPolyEpsilon(), true); fContour.convertTo(contour, CvType.CV_32S); this.contour = contour; // Check area, and don't do any calculations if it is not valid if (validArea = validateArea()) { // Find a bounding rectangle RotatedRect rect = Imgproc.minAreaRect(fContour); Point[] rectPoints = new Point[4]; rect.points(rectPoints); for (int j = 0; j < rectPoints.length; j++) { Point rectPoint = rectPoints[j]; double minDistance = Double.MAX_VALUE; Point point = null; for (int i = 0; i < contour.rows(); i++) { Point contourPoint = new Point(contour.get(i, 0)); double dist = distance(rectPoint, contourPoint); if (dist < minDistance) { minDistance = dist; point = contourPoint; } } rectPoints[j] = point; } MatOfPoint2f rectMat = new MatOfPoint2f(rectPoints); // Refine the corners to improve accuracy Imgproc.cornerSubPix(grayImage, rectMat, new Size(4, 10), new Size(-1, -1), new TermCriteria(TermCriteria.EPS + TermCriteria.COUNT, 30, 0.1)); rectPoints = rectMat.toArray(); // Identify each corner SortedMap<Double, List<Point>> x = new TreeMap<>(); Arrays.stream(rectPoints).forEach((p) -> { List<Point> points; if ((points = x.get(p.x)) == null) { x.put(p.x, points = new LinkedList<>()); } points.add(p); }); int i = 0; for (Iterator<List<Point>> it = x.values().iterator(); it.hasNext();) { List<Point> s = it.next(); for (Point p : s) { switch (i) { case 0: topLeft = p; break; case 1: bottomLeft = p; break; case 2: topRight = p; break; case 3: bottomRight = p; } i++; } } // Organize corners if (topLeft.y > bottomLeft.y) { Point p = bottomLeft; bottomLeft = topLeft; topLeft = p; } if (topRight.y > bottomRight.y) { Point p = bottomRight; bottomRight = topRight; topRight = p; } // Create corners for centroid calculation corners = new MatOfPoint2f(rectPoints); // Calculate center Moments moments = Imgproc.moments(corners); center = new Point(moments.m10 / moments.m00, moments.m01 / moments.m00); // Put the points in the correct order for solvePNP rectPoints[0] = topLeft; rectPoints[1] = topRight; rectPoints[2] = bottomLeft; rectPoints[3] = bottomRight; // Recreate corners in the new order corners = new MatOfPoint2f(rectPoints); widthTop = distance(topLeft, topRight); widthBottom = distance(bottomLeft, bottomRight); width = (widthTop + widthBottom) / 2.0; heightLeft = distance(topLeft, bottomLeft); heightRight = distance(topRight, bottomRight); height = (heightLeft + heightRight) / 2.0; Mat tvec = new Mat(); // Calculate target's location Calib3d.solvePnP(OBJECT_POINTS, corners, CAMERA_MAT, DISTORTION_MAT, rotation, tvec, false, Calib3d.CV_P3P); // ======================================= // Position and Orientation Transformation // ======================================= double armAngle = VisionResults.getArmAngle(); // Flip y axis to point upward Core.multiply(tvec, SIGN_NORMALIZATION_MATRIX, tvec); // Shift origin to arm pivot point, on the robot's centerline CoordinateMath.translate(tvec, CAMERA_X_OFFSET, CAMERA_Y_OFFSET, ARM_LENGTH); // Align axes with ground CoordinateMath.rotateX(tvec, -armAngle); Core.add(rotation, new MatOfDouble(armAngle, 0, 0), rotation); // Shift origin to robot center of rotation CoordinateMath.translate(tvec, 0, ARM_PIVOT_Y_OFFSET, -ARM_PIVOT_Z_OFFSET); double xPosFeet = tvec.get(0, 0)[0]; double yPosFeet = tvec.get(1, 0)[0]; double zPosFeet = tvec.get(2, 0)[0]; // Old less effective aiming heading and distance calculation // double pixelsToFeet = TARGET_WIDTH / width; // distance = (TARGET_WIDTH * HighGoalProcessor.IMAGE_SIZE.width // / (2 * width ** Math.tan(VisionParameters.getFOVAngle() / 2))); // double xPosFeet = (center.x - (HighGoalProcessor.IMAGE_SIZE.width // / 2)) * pixelsToFeet; // double yPosFeet = -(center.y - // (HighGoalProcessor.IMAGE_SIZE.height / 2)) * pixelsToFeet; distance = Math.sqrt(xPosFeet * xPosFeet + zPosFeet * zPosFeet); position = new Point3(xPosFeet, yPosFeet, zPosFeet); xGoalAngle = Math.atan(xPosFeet / zPosFeet); yGoalAngle = Math.atan(yPosFeet / zPosFeet); validate(); score = calculateScore(); } else { valid = false; } }
From source file:overwatchteampicker.OverwatchTeamPicker.java
public static ReturnValues findImage(String template, String source, int flag) { File lib = null;/*from w ww. j a v a 2 s. c om*/ 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:samples.LWF.java
private static void save_meshed_images(double[][] puntos, File carpetaalmacen, File image, Mat mat, int[][] delaunay_triangles) { Mat mat_copy = mat.clone();/*from w w w . ja va 2s. co m*/ int radii = 1000; for (double[] punto : puntos) { Imgproc.ellipse(mat_copy, new Point(punto), new Size(radii, radii), 0, 0, 0, new Scalar(0, 255, 0)); // Imgproc.line(mat_copy, null, null, null); } for (int[] tri : faceTemplateTriangles) { Imgproc.line(mat_copy, new Point(puntos[tri[0] - 1]), new Point(puntos[tri[1] - 1]), new Scalar(0, 255, 0)); Imgproc.line(mat_copy, new Point(puntos[tri[1] - 1]), new Point(puntos[tri[2] - 1]), new Scalar(0, 255, 0)); Imgproc.line(mat_copy, new Point(puntos[tri[2] - 1]), new Point(puntos[tri[0] - 1]), new Scalar(0, 255, 0)); } Imgcodecs.imwrite(carpetaalmacen.getAbsolutePath() + "\\" + image.getName(), mat_copy); }
From source file:simeav.Utils.java
public static ArrayList<Point> detectarVertices(Mat original) { MatOfPoint corners = new MatOfPoint(); Imgproc.goodFeaturesToTrack(original, corners, 100, 0.01, 0, new Mat(), 2, false, 0.04); Mat vertices = Mat.zeros(original.size(), CvType.CV_8UC3); for (int i = 0; i < corners.height(); i++) { Core.circle(vertices, new Point(corners.get(i, 0)), 8, new Scalar(180, 170, 5), -1); }//from ww w . j a va 2s .co m Mat imGrises = new Mat(); Mat bw = new Mat(); Imgproc.cvtColor(vertices, imGrises, Imgproc.COLOR_BGR2GRAY); Imgproc.Canny(imGrises, bw, 100, 150, 5, true); Mat jerarquia = new Mat(); ArrayList<MatOfPoint> contornos = new ArrayList<>(); Imgproc.findContours(bw.clone(), contornos, jerarquia, Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE); ArrayList<Point> mc = Utils.getCentros(contornos); Mat resultado = Mat.zeros(original.size(), CvType.CV_8UC3); for (int i = 0; i < contornos.size(); i++) { Scalar color = new Scalar(180, 170, 5); // Imgproc.drawContours(resultado, contornos, i, color, 2, 8, jerarquia, 0, new Point()); Core.circle(resultado, mc.get(i), 4, color, -1, 8, 0); } return mc; }
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;/*from www.j a va2 s . c o 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"); }
From source file:vinylsleevedetection.Analyze.java
public void Check() { count = 1;// ww w . j a v a2 s.c o m //load openCV library System.loadLibrary(Core.NATIVE_LIBRARY_NAME); //for loop to compare source images to user image for (int j = 1; j < 4; j++) { //source image location (record sleeve) String Object = "E:\\Users\\Jamie\\Documents\\NetBeansProjects\\VinylSleeveDetection\\Source\\" + j + ".jpg"; //user image location String Scene = "E:\\Users\\Jamie\\Documents\\NetBeansProjects\\VinylSleeveDetection\\Output\\camera.jpg"; //load images Mat objectImage = Imgcodecs.imread(Object, Imgcodecs.CV_LOAD_IMAGE_COLOR); Mat sceneImage = Imgcodecs.imread(Scene, Imgcodecs.CV_LOAD_IMAGE_COLOR); //use BRISK feature detection MatOfKeyPoint objectKeyPoints = new MatOfKeyPoint(); FeatureDetector featureDetector = FeatureDetector.create(FeatureDetector.BRISK); //perform feature detection on source image featureDetector.detect(objectImage, objectKeyPoints); KeyPoint[] keypoints = objectKeyPoints.toArray(); //use descriptor extractor MatOfKeyPoint objectDescriptors = new MatOfKeyPoint(); DescriptorExtractor descriptorExtractor = DescriptorExtractor.create(DescriptorExtractor.BRISK); descriptorExtractor.compute(objectImage, objectKeyPoints, objectDescriptors); Mat outputImage = new Mat(objectImage.rows(), objectImage.cols(), Imgcodecs.CV_LOAD_IMAGE_COLOR); Scalar newKeypointColor = new Scalar(255, 0, 0); Features2d.drawKeypoints(objectImage, objectKeyPoints, outputImage, newKeypointColor, 0); 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, Imgcodecs.CV_LOAD_IMAGE_COLOR); Scalar matchestColor = new Scalar(0, 255, 0); List<MatOfDMatch> matches = new LinkedList<>(); DescriptorMatcher descriptorMatcher = DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE); descriptorMatcher.knnMatch(objectDescriptors, sceneDescriptors, matches, 2); 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 the number of good mathces is more than 150 a match is found if (goodMatchesList.size() > 150) { System.out.println("Object Found"); 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 = Imgcodecs.imread(Scene, Imgcodecs.CV_LOAD_IMAGE_COLOR); //draw a green square around the matched object Imgproc.line(img, new Point(scene_corners.get(0, 0)), new Point(scene_corners.get(1, 0)), new Scalar(0, 255, 0), 10); Imgproc.line(img, new Point(scene_corners.get(1, 0)), new Point(scene_corners.get(2, 0)), new Scalar(0, 255, 0), 10); Imgproc.line(img, new Point(scene_corners.get(2, 0)), new Point(scene_corners.get(3, 0)), new Scalar(0, 255, 0), 10); Imgproc.line(img, new Point(scene_corners.get(3, 0)), new Point(scene_corners.get(0, 0)), new Scalar(0, 255, 0), 10); MatOfDMatch goodMatches = new MatOfDMatch(); goodMatches.fromList(goodMatchesList); Features2d.drawMatches(objectImage, objectKeyPoints, sceneImage, sceneKeyPoints, goodMatches, matchoutput, matchestColor, newKeypointColor, new MatOfByte(), 2); //output image with match, image of the match locations and keypoints image String folder = "E:\\Users\\Jamie\\Documents\\NetBeansProjects\\VinylSleeveDetection\\Output\\"; Imgcodecs.imwrite(folder + "outputImage.jpg", outputImage); Imgcodecs.imwrite(folder + "matchoutput.jpg", matchoutput); Imgcodecs.imwrite(folder + "found.jpg", img); count = j; break; } else { System.out.println("Object Not Found"); count = 0; } } }