List of usage examples for org.opencv.core RotatedRect points
public void points(Point pt[])
From source file:LicenseDetection.java
public void run() { // ------------------ set up tesseract for later use ------------------ ITesseract tessInstance = new Tesseract(); tessInstance.setDatapath("/Users/BradWilliams/Downloads/Tess4J"); tessInstance.setLanguage("eng"); // ------------------ Save image first ------------------ Mat img;/*from www .j a va 2 s.c o m*/ img = Imgcodecs.imread(getClass().getResource("/resources/car_2_shopped2.jpg").getPath()); Imgcodecs.imwrite("/Users/BradWilliams/ComputerVisionOut/True_Image.png", img); // ------------------ Convert to grayscale ------------------ Mat imgGray = new Mat(); Imgproc.cvtColor(img, imgGray, Imgproc.COLOR_BGR2GRAY); Imgcodecs.imwrite("/Users/BradWilliams/ComputerVisionOut/Gray.png", imgGray); // ------------------ Blur so edge detection wont pick up noise ------------------ Mat imgGaussianBlur = new Mat(); Imgproc.GaussianBlur(imgGray, imgGaussianBlur, new Size(3, 3), 0); Imgcodecs.imwrite("/Users/BradWilliams/ComputerVisionOut/gaussian_blur.png", imgGaussianBlur); // ****************** Create image that will be cropped at end of program before OCR *************************** // ------------------ Binary theshold for OCR (used later)------------------ Mat imgThresholdOCR = new Mat(); Imgproc.adaptiveThreshold(imgGaussianBlur, imgThresholdOCR, 255, Imgproc.ADAPTIVE_THRESH_MEAN_C, Imgproc.THRESH_BINARY, 7, 10); //Imgproc.threshold(imgSobel,imgThreshold,120,255,Imgproc.THRESH_TOZERO); Imgcodecs.imwrite("/Users/BradWilliams/ComputerVisionOut/imgThresholdOCR.png", imgThresholdOCR); // ------------------ Erosion operation------------------ Mat kern = Imgproc.getStructuringElement(Imgproc.CV_SHAPE_CROSS, new Size(3, 3)); Mat imgErodeOCR = new Mat(); Imgproc.morphologyEx(imgThresholdOCR, imgErodeOCR, Imgproc.MORPH_DILATE, kern); //Imgproc.MORPH_DILATE is performing erosion, wtf? Imgcodecs.imwrite("/Users/BradWilliams/ComputerVisionOut/imgErodeOCR.png", imgErodeOCR); //------------------ Dilation operation ------------------ Mat kernall = Imgproc.getStructuringElement(Imgproc.CV_SHAPE_RECT, new Size(3, 3)); Mat imgDilateOCR = new Mat(); Imgproc.morphologyEx(imgErodeOCR, imgDilateOCR, Imgproc.MORPH_ERODE, kernall); Imgcodecs.imwrite("/Users/BradWilliams/ComputerVisionOut/imgDilateOCR.png", imgDilateOCR); // ************************************************************************************************************* // // ------------------ Close operation (dilation followed by erosion) to reduce noise ------------------ // Mat k = Imgproc.getStructuringElement(Imgproc.CV_SHAPE_RECT, new Size(3, 3)); // Mat imgCloseOCR = new Mat(); // Imgproc.morphologyEx(imgThresholdOCR,imgCloseOCR,1,k); // Imgcodecs.imwrite("/Users/BradWilliams/ComputerVisionOut/imgCloseOCR.png", imgCloseOCR); // ------------------ Sobel vertical edge detection ------------------ Mat imgSobel = new Mat(); Imgproc.Sobel(imgGaussianBlur, imgSobel, -1, 1, 0); Imgcodecs.imwrite("/Users/BradWilliams/ComputerVisionOut/imgSobel.png", imgSobel); // ------------------ Binary theshold ------------------ Mat imgThreshold = new Mat(); Imgproc.adaptiveThreshold(imgSobel, imgThreshold, 255, Imgproc.ADAPTIVE_THRESH_MEAN_C, Imgproc.THRESH_BINARY, 99, -60); //Imgproc.threshold(imgSobel,imgThreshold,120,255,Imgproc.THRESH_TOZERO); Imgcodecs.imwrite("/Users/BradWilliams/ComputerVisionOut/imgThreshold.png", imgThreshold); // // ------------------ Open operation (erosion followed by dilation) ------------------ // Mat ker = Imgproc.getStructuringElement(Imgproc.CV_SHAPE_CROSS, new Size(3, 2)); // Mat imgOpen = new Mat(); // Imgproc.morphologyEx(imgThreshold,imgOpen,0,ker); // Imgcodecs.imwrite("/Users/BradWilliams/ComputerVisionOut/imgOpen.png", imgOpen); // ------------------ Close operation (dilation followed by erosion) to reduce noise ------------------ Mat kernel = Imgproc.getStructuringElement(Imgproc.CV_SHAPE_RECT, new Size(22, 8)); Mat imgClose = new Mat(); Imgproc.morphologyEx(imgThreshold, imgClose, 1, kernel); Imgcodecs.imwrite("/Users/BradWilliams/ComputerVisionOut/imgClose.png", imgClose); // ------------------ Find contours ------------------ List<MatOfPoint> contours = new ArrayList<>(); Imgproc.findContours(imgClose, contours, new Mat(), Imgproc.RETR_LIST, Imgproc.CHAIN_APPROX_SIMPLE); // **************************** DEBUG CODE ************************** Mat contourImg = new Mat(imgClose.size(), imgClose.type()); for (int i = 0; i < contours.size(); i++) { Imgproc.drawContours(contourImg, contours, i, new Scalar(255, 255, 255), -1); } Imgcodecs.imwrite("/Users/BradWilliams/ComputerVisionOut/contours.png", contourImg); // ****************************************************************** // -------------- Convert contours -------------------- //Convert to MatOfPoint2f so that minAreaRect can be called List<MatOfPoint2f> newContours = new ArrayList<>(); for (MatOfPoint mat : contours) { MatOfPoint2f newPoint = new MatOfPoint2f(mat.toArray()); newContours.add(newPoint); } //Get minAreaRects List<RotatedRect> minAreaRects = new ArrayList<>(); for (MatOfPoint2f mat : newContours) { RotatedRect rect = Imgproc.minAreaRect(mat); /* --------------- BUG WORK AROUND ------------ Possible bug: When converting from MatOfPoint2f to RotatectRect the width height were reversed and the angle was -90 degrees from what it would be if the width and height were correct. When painting rectangle in image, the correct boxes were produced, but performing calculations on rect.angle rect.width, or rect.height yielded unwanted results. The following work around is buggy but works for my purpose */ if (rect.size.width < rect.size.height) { double temp; temp = rect.size.width; rect.size.width = rect.size.height; rect.size.height = temp; rect.angle = rect.angle + 90; } //check aspect ratio and area and angle if (rect.size.width / rect.size.height > 1 && rect.size.width / rect.size.height < 5 && rect.size.width * rect.size.height > 10000 && rect.size.width * rect.size.height < 50000 && Math.abs(rect.angle) < 20) { minAreaRects.add(rect); } //minAreaRects.add(rect); } // **************************** DEBUG CODE ************************** /* The following code is used to draw the rectangles on top of the original image for debugging purposes */ //Draw Rotated Rects Point[] vertices = new Point[4]; Mat imageWithBoxes = img; // Draw color rectangles on top of binary contours // Mat imageWithBoxes = new Mat(); // Mat temp = imgDilateOCR; // Imgproc.cvtColor(temp, imageWithBoxes, Imgproc.COLOR_GRAY2RGB); for (RotatedRect rect : minAreaRects) { rect.points(vertices); for (int i = 0; i < 4; i++) { Imgproc.line(imageWithBoxes, vertices[i], vertices[(i + 1) % 4], new Scalar(0, 0, 255), 2); } } Imgcodecs.imwrite("/Users/BradWilliams/ComputerVisionOut/imgWithBoxes.png", imageWithBoxes); // ****************************************************************** // **************************** DEBUG CODE ************************** // for(RotatedRect rect : minAreaRects) { // System.out.println(rect.toString()); // } // ****************************************************************** /* In order to rotate image without cropping it: 1. Create new square image with dimension = diagonal of initial image. 2. Draw initial image into the center of new image. Insert initial image at ROI (Region of Interest) in new image 3. Rotate new image */ //Find diagonal/hypotenuse int hypotenuse = (int) Math.sqrt((img.rows() * img.rows()) + (img.cols() * img.cols())); //New Mat with hypotenuse as height and width Mat rotateSpace = new Mat(hypotenuse, hypotenuse, 0); int ROI_x = (rotateSpace.width() - imgClose.width()) / 2; //x start of ROI int ROI_y = (rotateSpace.height() - imgClose.height()) / 2; //x start of ROI //designate region of interest Rect r = new Rect(ROI_x, ROI_y, imgClose.width(), imgClose.height()); //Insert image into region of interest imgDilateOCR.copyTo(rotateSpace.submat(r)); Mat rotatedTemp = new Mat(); //Mat to hold temporarily rotated mat Mat rectMat = new Mat();//Mat to hold rect contents (needed for looping through pixels) Point[] rectVertices = new Point[4];//Used to build rect to make ROI Rect rec = new Rect(); List<RotatedRect> edgeDensityRects = new ArrayList<>(); //populate new arraylist with rects that satisfy edge density int count = 0; //Loop through Rotated Rects and find edge density for (RotatedRect rect : minAreaRects) { count++; rect.center = new Point((float) ROI_x + rect.center.x, (float) ROI_y + rect.center.y); //rotate image to math orientation of rotated rect rotate(rotateSpace, rotatedTemp, rect.center, rect.angle); //remove rect rotation rect.angle = 0; //get vertices from rotatedRect rect.points(rectVertices); // **************************** DEBUG CODE ************************** // // for (int k = 0; k < 4; k++) { // System.out.println(rectVertices[k]); // Imgproc.line(rotatedTemp, rectVertices[k], rectVertices[(k + 1) % 4], new Scalar(0, 0, 255), 2); // } // // Imgcodecs.imwrite("/Users/BradWilliams/ComputerVisionOut/rotated" + count + ".png", rotatedTemp); // ***************************************************************** //build rect to use as ROI rec = new Rect(rectVertices[1], rectVertices[3]); rectMat = rotatedTemp.submat(rec); Imgcodecs.imwrite("/Users/BradWilliams/ComputerVisionOut/extracted" + count + ".png", rectMat); //find edge density // // ------------------------ edge density check NOT IMPLEMENTED -------------------- // /* // Checking for edge density was not necessary for this image so it was not implemented due to lack of time // */ // for(int i = 0; i < rectMat.rows(); ++i){ // for(int j = 0; j < rectMat.cols(); ++j){ // // //add up white pixels // } // } // // //check number of white pixels against total pixels // //only add rects to new arraylist that satisfy threshold edgeDensityRects.add(rect); } // **************************** DEBUG CODE ************************** Imgcodecs.imwrite("/Users/BradWilliams/ComputerVisionOut/rotatedSpace.png", rotateSpace); //Imgcodecs.imwrite("/Users/BradWilliams/ComputerVisionOut/rotatedSpaceROTATED.png", rotatedTemp); //System.out.println(imgGray.type()); // ***************************************************************** // if there is only one rectangle left, its the license plate if (edgeDensityRects.size() == 1) { String result = ""; //Hold result from OCR BufferedImage bimg; Mat cropped; cropped = rectMat.submat(new Rect(20, 50, rectMat.width() - 40, rectMat.height() - 70)); Imgcodecs.imwrite("/Users/BradWilliams/ComputerVisionOut/rectMatCropped.png", cropped); bimg = matToBufferedImage(cropped); BufferedImage image = bimg; try { result = tessInstance.doOCR(image); } catch (TesseractException e) { System.err.println(e.getMessage()); } for (int i = 0; i < 10; ++i) { } result = result.replace("\n", ""); System.out.println(result); CarProfDBImpl db = new CarProfDBImpl(); db.connect("localhost:3306/computer_vision", "root", "*******"); CarProf c = db.getCarProf(result); System.out.print(c.toString()); db.close(); } }
From source file:karthik.Barcode.CandidateMatrixBarcode.java
License:Open Source License
CandidateResult NormalizeCandidateRegion(double angle) { /* candidateRegion is the RotatedRect which contains a candidate region for the barcode // angle is the rotation angle or USE_ROTATED_RECT_ANGLE for this function to // estimate rotation angle from the rect parameter // returns Mat containing cropped area(region of interest) with just the barcode // The barcode region is from the *original* image, not the scaled image // the cropped area is also rotated as necessary to be horizontal or vertical rather than skewed // Some parts of this function are from http://felix.abecassis.me/2011/10/opencv-rotation-deskewing/ // and http://stackoverflow.com/questions/22041699/rotate-an-image-without-cropping-in-opencv-in-c */// ww w . j av a 2 s. c om double rotation_angle; CandidateResult result = new CandidateResult(); // scale candidate region back up to original size to return cropped part from *original* image // need the 1.0 there to force floating-point arithmetic from int values double scale_factor = img_details.src_original.rows() / (1.0 * img_details.src_grayscale.rows()); // expand the region found - this helps capture the entire code including the border zone candidateRegion.size.width += 2 * params.RECT_WIDTH; candidateRegion.size.height += 2 * params.RECT_HEIGHT; // calculate location of rectangle in original image and its corner points RotatedRect scaledRegion = new RotatedRect(candidateRegion.center, candidateRegion.size, candidateRegion.angle); scaledRegion.center.x = scaledRegion.center.x * scale_factor; scaledRegion.center.y = scaledRegion.center.y * scale_factor; scaledRegion.size.height *= scale_factor; scaledRegion.size.width *= scale_factor; scaledRegion.points(img_details.scaledCorners); // lets get the coordinates of the ROI in the original image and save it result.ROI_coords = Arrays.copyOf(img_details.scaledCorners, 4); // get the bounding rectangle of the ROI by sorting its corner points // we do it manually because RotatedRect can generate corner points outside the Mat area Arrays.sort(img_details.scaledCorners, CandidateBarcode.get_x_comparator()); int leftCol = (int) img_details.scaledCorners[0].x; int rightCol = (int) img_details.scaledCorners[3].x; leftCol = (leftCol < 0) ? 0 : leftCol; rightCol = (rightCol > img_details.src_original.cols() - 1) ? img_details.src_original.cols() - 1 : rightCol; Arrays.sort(img_details.scaledCorners, CandidateBarcode.get_y_comparator()); int topRow = (int) img_details.scaledCorners[0].y; int bottomRow = (int) img_details.scaledCorners[3].y; topRow = (topRow < 0) ? 0 : topRow; bottomRow = (bottomRow > img_details.src_original.rows() - 1) ? img_details.src_original.rows() - 1 : bottomRow; Mat ROI_region = img_details.src_original.submat(topRow, bottomRow, leftCol, rightCol); // create a container that is a square with side = diagonal of ROI. // this is large enough to accommodate the ROI region with rotation without cropping it int orig_rows = bottomRow - topRow; int orig_cols = rightCol - leftCol; int diagonal = (int) Math.sqrt(orig_rows * orig_rows + orig_cols * orig_cols); int newWidth = diagonal + 1; int newHeight = diagonal + 1; int offsetX = (newWidth - orig_cols) / 2; int offsetY = (newHeight - orig_rows) / 2; Mat enlarged_ROI_container = new Mat(newWidth, newHeight, img_details.src_original.type()); enlarged_ROI_container.setTo(ZERO_SCALAR); // copy ROI to centre of container and rotate it ROI_region.copyTo(enlarged_ROI_container.rowRange(offsetY, offsetY + orig_rows).colRange(offsetX, offsetX + orig_cols)); Point enlarged_ROI_container_centre = new Point(enlarged_ROI_container.rows() / 2.0, enlarged_ROI_container.cols() / 2.0); Mat rotated = Mat.zeros(enlarged_ROI_container.size(), enlarged_ROI_container.type()); if (angle == Barcode.USE_ROTATED_RECT_ANGLE) rotation_angle = estimate_barcode_orientation(); else rotation_angle = angle; // perform the affine transformation img_details.rotation_matrix = Imgproc.getRotationMatrix2D(enlarged_ROI_container_centre, rotation_angle, 1.0); img_details.rotation_matrix.convertTo(img_details.rotation_matrix, CvType.CV_32F); // convert type so matrix multip. works properly img_details.newCornerCoord.setTo(ZERO_SCALAR); // convert scaledCorners to contain locations of corners in enlarged_ROI_container Mat img_details.scaledCorners[0] = new Point(offsetX, offsetY); img_details.scaledCorners[1] = new Point(offsetX, offsetY + orig_rows); img_details.scaledCorners[2] = new Point(offsetX + orig_cols, offsetY); img_details.scaledCorners[3] = new Point(offsetX + orig_cols, offsetY + orig_rows); // calculate the new location for each corner point of the rectangle ROI after rotation for (int r = 0; r < 4; r++) { img_details.coord.put(0, 0, img_details.scaledCorners[r].x); img_details.coord.put(1, 0, img_details.scaledCorners[r].y); Core.gemm(img_details.rotation_matrix, img_details.coord, 1, img_details.delta, 0, img_details.newCornerCoord); updatePoint(img_details.newCornerPoints.get(r), img_details.newCornerCoord.get(0, 0)[0], img_details.newCornerCoord.get(1, 0)[0]); } rotated.setTo(ZERO_SCALAR); Imgproc.warpAffine(enlarged_ROI_container, rotated, img_details.rotation_matrix, enlarged_ROI_container.size(), Imgproc.INTER_CUBIC); // sort rectangles points in order by first sorting all 4 points based on x // we then sort the first two based on y and then the next two based on y // this leaves the array in order top-left, bottom-left, top-right, bottom-right Collections.sort(img_details.newCornerPoints, CandidateBarcode.get_x_comparator()); Collections.sort(img_details.newCornerPoints.subList(0, 2), CandidateBarcode.get_y_comparator()); Collections.sort(img_details.newCornerPoints.subList(2, 4), CandidateBarcode.get_y_comparator()); // calc height and width of rectangular region double height = length(img_details.newCornerPoints.get(1), img_details.newCornerPoints.get(0)); double width = length(img_details.newCornerPoints.get(2), img_details.newCornerPoints.get(0)); // create destination points for warpPerspective to map to updatePoint(img_details.transformedPoints.get(0), 0, 0); updatePoint(img_details.transformedPoints.get(1), 0, height); updatePoint(img_details.transformedPoints.get(2), width, 0); updatePoint(img_details.transformedPoints.get(3), width, height); Mat perspectiveTransform = Imgproc.getPerspectiveTransform( Converters.vector_Point2f_to_Mat(img_details.newCornerPoints), Converters.vector_Point2f_to_Mat(img_details.transformedPoints)); Mat perspectiveOut = Mat.zeros((int) height + 2, (int) width + 2, CvType.CV_32F); Imgproc.warpPerspective(rotated, perspectiveOut, perspectiveTransform, perspectiveOut.size(), Imgproc.INTER_CUBIC); result.ROI = perspectiveOut; return result; }
From source file:org.openpnp.vision.FluentCv.java
License:Open Source License
public static void drawRotatedRect(Mat mat, RotatedRect rect, Color color, int thickness) { Point points[] = new Point[4]; rect.points(points); Scalar color_ = colorToScalar(color); for (int j = 0; j < 4; ++j) { Core.line(mat, points[j], points[(j + 1) % 4], color_, thickness); }//from w w w. j a va 2 s . c o m }
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 w w . j a va2 s . c om * * @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; } }