List of usage examples for org.opencv.core Mat copyTo
public void copyTo(Mat m)
From source file:imageanalyzercv.ImageAnalyzerCV.java
/** * @param args the command line arguments *//*from w w w. j av a 2s . co m*/ public static void main(String[] args) { System.out.println("path: " + System.getProperty("java.library.path")); System.loadLibrary("opencv_java300"); Mat m = Highgui.imread("/Users/chintan/Downloads/software/image_analyis/mydata/SAM_0763.JPG"); System.out.println("m = " + m.height()); MatOfKeyPoint points = new MatOfKeyPoint(); FeatureDetector.create(FeatureDetector.SURF).detect(m, points); Mat m2 = Highgui.imread("/Users/chintan/Downloads/software/image_analyis/mydata/SAM_0764.JPG"); System.out.println("m = " + m2.height()); MatOfKeyPoint points2 = new MatOfKeyPoint(); FeatureDetector.create(FeatureDetector.SURF).detect(m2, points2); DescriptorExtractor SurfExtractor = DescriptorExtractor.create(DescriptorExtractor.BRISK); Mat imag1Desc = new Mat(); SurfExtractor.compute(m, points, imag1Desc); Mat imag2Desc = new Mat(); SurfExtractor.compute(m2, points2, imag2Desc); MatOfDMatch matches = new MatOfDMatch(); Mat imgd = new Mat(); imag1Desc.copyTo(imgd); System.out.println(imgd.size()); DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE_HAMMING).match(imag2Desc, imag1Desc, (MatOfDMatch) matches); double min_distance = 1000.0; double max_distance = 0.0; DMatch[] matchArr = matches.toArray(); for (int i = 0; i < matchArr.length; i++) { if (matchArr[i].distance > max_distance) max_distance = matchArr[i].distance; if (matchArr[i].distance < min_distance) min_distance = matchArr[i].distance; } ArrayList<DMatch> good_matches = new ArrayList<DMatch>(); System.out.println("Min Distance: " + min_distance + " Max distance: " + max_distance); double totalScore = 0.0; for (int j = 0; j < imag1Desc.rows() && j < matchArr.length; j++) { if ((matchArr[j].distance <= (11 * min_distance)) && (matchArr[j].distance >= min_distance * 1)) { good_matches.add(matchArr[j]); //System.out.println(matchArr[j]); totalScore = totalScore + matchArr[j].distance; } //good_matches.add(matchArr[j]); } System.out.println((1 - (totalScore / (good_matches.size() * ((max_distance + min_distance) / 2)))) * 100); // System.out.println(matches.toList().size()); Mat out = new Mat(); MatOfDMatch mats = new MatOfDMatch(); mats.fromList(good_matches); Features2d.drawMatches(m2, points2, m, points, mats, out); Highgui.imwrite("/Users/chintan/Downloads/one2.jpg", out); }
From source file:javaapplication1.Ocv.java
public void makeFacesGray(String filter, String input, String output) { // load the filter and create a classifier with it File f = new File(filter); final CascadeClassifier faceDetector = new CascadeClassifier(this.filter); // load the image and read it into a matrix File f2 = new File(input); final Mat image = Highgui.imread(this.input); // run a face detector on the image MatOfRect faceDetections = new MatOfRect(); faceDetector.detectMultiScale(image, faceDetections); // inform about faces detected System.out.println(String.format("Detected %s faces", faceDetections.toArray().length)); // make each face gray for (Rect rect : faceDetections.toArray()) { // get a shallow copy of the submatrix for the face Mat sub = image.submat(rect); // convert it to gray, then back to BGR Imgproc.cvtColor(sub, sub, Imgproc.COLOR_BGR2GRAY, 1); Imgproc.cvtColor(sub, sub, Imgproc.COLOR_GRAY2BGR, 3); // copy back to the original image sub.copyTo(image.submat(rect)); }//from www . ja v a2s. c om // save file Highgui.imwrite(this.output, image); }
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 *///www .java 2 s.co m 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:logic.featurepointextractor.EyeBrowsFPE.java
/** * getSkeleton obtain thin 1-pixel region from contour. * @param src input binary image//from w ww .j a v a2 s . c o m * @return binary image */ private Mat getSkeleton(Mat src) { Mat skel = new Mat(src.rows(), src.cols(), CV_8UC1, new Scalar(0)); Mat element = Imgproc.getStructuringElement(Imgproc.MORPH_CROSS, new Size(3, 3)); Mat tmp = new Mat(); Mat eroded = new Mat(); boolean done = false; do { Imgproc.morphologyEx(src, eroded, Imgproc.MORPH_ERODE, element); Imgproc.morphologyEx(eroded, tmp, Imgproc.MORPH_DILATE, element); Core.subtract(src, tmp, tmp); Core.bitwise_or(skel, tmp, skel); eroded.copyTo(src); done = (Core.countNonZero(src) == 0); } while (!done); return skel; }
From source file:net.bsrc.cbod.opencv.OpenCV.java
public static Mat copyImage(Mat org) { Mat copy = new Mat(); org.copyTo(copy); return copy; }
From source file:openbjk.Identificador.java
public Mat norm_0_255(Mat input) { Mat dst = null;/*from ww w . ja v a 2s .c om*/ switch (input.channels()) { case 1: Core.normalize(input, dst, 0, 255, 2, CvType.CV_8UC1); break; case 3: Core.normalize(input, dst, 0, 255, 2, CvType.CV_8UC3); break; default: input.copyTo(dst); } return dst; }
From source file:opencltest.YetAnotherTestT.java
public static void main(String[] args) { System.loadLibrary(Core.NATIVE_LIBRARY_NAME); Mat kernel = new Mat(3, 3, CV_8UC1); kernel.put(0, 0, new double[] { 0, 1, 0, 1, 1, 1, 0, 1, 0 }); Mat source = Imgcodecs.imread("test.smaller.png"); Mat blur = new Mat(); Mat edges = new Mat(); Mat dilated = new Mat(); Imgproc.GaussianBlur(source, blur, new Size(13, 13), 0); Imgproc.Canny(blur, edges, 10, 30, 5, false); // Imgproc.cvtColor(edges, edges, Imgproc.COLOR_RGB2GRAY); // Imgproc.adaptiveThreshold(edges, edges, 255, ADAPTIVE_THRESH_MEAN_C, THRESH_BINARY, 5, 2); // Core.bitwise_not(edges, edges); // Imgproc.dilate(edges, edges, kernel); // Imgproc.dilate(edges, dilated, kernel); dilated = edges;//ww w . j av a 2 s. c o m // Core.bitwise_not(edges, edges); Mat lines = new Mat(); Imgproc.HoughLinesP(dilated, lines, 1, Math.PI / 180, 300, 10, 70); Mat empty = new Mat(source.height(), source.width(), source.type()); // paintLines(empty, lines); List<MatOfPoint> contours = new ArrayList<>(); Mat hier = new Mat(); Imgproc.findContours(edges, contours, hier, Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE); Mat foundSquare = new Mat(source.height(), source.width(), CvType.CV_8UC4); source.copyTo(foundSquare); List<Double> hor = new ArrayList<>(); for (Iterator<MatOfPoint> iterator = contours.iterator(); iterator.hasNext();) { MatOfPoint next = iterator.next(); Rect bounding = Imgproc.boundingRect(next); int tr = 20; if (diffLessThan(bounding.size().width - 40, tr) && diffLessThan(bounding.size().height - 40, tr)) { Imgproc.rectangle(empty, bounding.tl(), bounding.br(), randomColor(), 3); // hor.add(bounding.x + 0.0); hor.add(bounding.x + bounding.width / 2.0 + 0.0); drawRect(bounding, foundSquare); } } Imgcodecs.imwrite("test_2.png", source); Imgcodecs.imwrite("test_3.png", dilated); Imgcodecs.imwrite("test_4.png", empty); Imgcodecs.imwrite("test_h.png", foundSquare); hor.sort(Double::compare); double low = hor.get(0); double hih = hor.get(hor.size() - 1); double n = hor.size(); Function<Double, Double> K = (d) -> (Math.abs(d) <= 1) ? ((3.0 / 4.0) * (1 - (d * d))) : 0;//epanechnikov kernel List<Double> result = new ArrayList<>(); double h = 10; for (int i = 0; i < source.width() + 1; i++) result.add(0.0); for (double d = low; d <= hih; d += 1) { double sum = 0; for (Double di : hor) { sum += K.apply((d - di) / h); } result.set((int) d, sum / (n * h)); System.out.println(sum / (n * h)); } normalize(result, 255); Mat test = new Mat(source.height(), source.width(), source.type()); source.copyTo(test); draw(result, test); Imgcodecs.imwrite("test_uwot.png", test); }
From source file:opencv.CaptchaDetection.java
/*** * ?/* w ww. ja v a 2s .c o m*/ * @param src * @return */ private static String dect_number(List<Mat> src) { String answer = ""; for (Mat numRoi : src) { Mat zoomNum = new Mat(numRoi.rows() * 2, numRoi.cols() * 2, CvType.CV_8UC1, new Scalar(0)); numRoi.copyTo( zoomNum.submat(new Rect(numRoi.cols() / 2, numRoi.rows() / 2, numRoi.cols(), numRoi.rows()))); double matchMin = Double.MAX_VALUE; int matchSample = 0; for (Map.Entry<Integer, List<Mat>> iter : sampleMat.entrySet()) { for (Mat sample : iter.getValue()) { int result_cols = zoomNum.cols() - sample.cols() + 1; int result_rows = zoomNum.rows() - sample.rows() + 1; Mat resultImg = new Mat(result_rows, result_cols, CvType.CV_32FC1); Imgproc.matchTemplate(zoomNum, sample, resultImg, Imgproc.TM_SQDIFF); Core.MinMaxLocResult mmr = Core.minMaxLoc(resultImg); if (matchMin > mmr.minVal) { matchMin = mmr.minVal; matchSample = iter.getKey(); } } } answer += matchSample / 2; //out.println("NumRio\tmatch sample : " + matchSample + "\tmatch value : " + matchMin); } //out.println("Answer is : " + answer); return answer; }
From source file:opencvdemos.BallGame.java
License:Apache License
private Image grabFrame() { // Init everything Image imageToShow = null;//w w w.ja v a 2 s . c om Mat frame = new Mat(); // Check if the capture is open if (this.capture.isOpened()) { try { // Read the current frame this.capture.read(frame); // Flip image for easy object manipulation Core.flip(frame, frame, 1); // If the frame is not empty, process it if (!frame.empty()) { // Init Mat blurredImage = new Mat(); Mat hsvImage = new Mat(); Mat mask = new Mat(); Mat morphOutput = new Mat(); // Remove some noise Imgproc.blur(frame, blurredImage, new Size(7, 7)); // Convert the frame to HSV Imgproc.cvtColor(blurredImage, hsvImage, Imgproc.COLOR_BGR2HSV); // Get thresholding values from the UI // Remember: H ranges 0-180, S and V range 0-255 Scalar minValues = new Scalar(this.hueStart.getValue(), this.saturationStart.getValue(), this.valueStart.getValue()); Scalar maxValues = new Scalar(this.hueStop.getValue(), this.saturationStop.getValue(), this.valueStop.getValue()); // Show the current selected HSV range String valuesToPrint = "Hue range: " + minValues.val[0] + "-" + maxValues.val[0] + ". Sat. range: " + minValues.val[1] + "-" + maxValues.val[1] + ". Value range: " + minValues.val[2] + "-" + maxValues.val[2]; hsvCurrentValues.setText(valuesToPrint); // Threshold HSV image to select object Core.inRange(hsvImage, minValues, maxValues, mask); // Show the partial output maskImage.getGraphics().drawImage(this.mat2Image(mask), 0, 0, 205, 154, null); // Morphological operators // Dilate with large element, erode with small ones Mat dilateElement = Imgproc.getStructuringElement(Imgproc.MORPH_RECT, new Size(24, 24)); Mat erodeElement = Imgproc.getStructuringElement(Imgproc.MORPH_RECT, new Size(12, 12)); Imgproc.erode(mask, morphOutput, erodeElement); Imgproc.erode(mask, morphOutput, erodeElement); Imgproc.dilate(mask, morphOutput, dilateElement); Imgproc.dilate(mask, morphOutput, dilateElement); // Show the partial output morphImage.getGraphics().drawImage(this.mat2Image(morphOutput), 0, 0, 205, 154, null); // Find the object(s) contours and show them frame = this.findAndDrawObjects(morphOutput, frame); // Calculate centers and move ball Mat temp = new Mat(); morphOutput.copyTo(temp); List<MatOfPoint> contours = new ArrayList<>(); Imgproc.findContours(temp, contours, new Mat(), Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE); for (int i = 0; i < contours.size(); i++) { Rect objectBoundingRectangle = Imgproc.boundingRect(contours.get(i)); int x = objectBoundingRectangle.x + objectBoundingRectangle.width / 2; int y = objectBoundingRectangle.y + objectBoundingRectangle.height / 2; // Move ball if (!ballChanged) { if (b.x > objectBoundingRectangle.x && b.x < objectBoundingRectangle.x + objectBoundingRectangle.width && b.y > objectBoundingRectangle.y && b.y < objectBoundingRectangle.y + objectBoundingRectangle.height) { b.dx = -b.dx; b.dy = -b.dy; ballChanged = true; } } // Show crosshair Imgproc.circle(frame, new Point(x, y), 20, new Scalar(0, 255, 0), 2); Imgproc.line(frame, new Point(x, y), new Point(x, y - 25), new Scalar(0, 255, 0), 2); Imgproc.line(frame, new Point(x, y), new Point(x, y + 25), new Scalar(0, 255, 0), 2); Imgproc.line(frame, new Point(x, y), new Point(x - 25, y), new Scalar(0, 255, 0), 2); Imgproc.line(frame, new Point(x, y), new Point(x + 25, y), new Scalar(0, 255, 0), 2); Imgproc.putText(frame, "Tracking object at (" + x + "," + y + ")", new Point(x, y), 1, 1, new Scalar(255, 0, 0), 2); } ballChanged = false; // Move and draw the ball if (b.dx < 0) b.dx = ballSpeed.getValue() * -1; else b.dx = ballSpeed.getValue(); if (b.dy < 0) b.dy = ballSpeed.getValue() * -1; else b.dy = ballSpeed.getValue(); b.move(); Imgproc.circle(frame, new Point(b.x, b.y), b.r, new Scalar(255, 0, 255), -1); // convert the Mat object (OpenCV) to Image (Java AWT) imageToShow = mat2Image(frame); } } catch (Exception e) { // log the error System.err.println("Exception during the frame elaboration: " + e); } } return imageToShow; }
From source file:org.akvo.caddisfly.sensor.colorimetry.strip.util.ResultUtil.java
License:Open Source License
@NonNull public static Mat concatenate(@NonNull Mat m1, @NonNull Mat m2) { int width = Math.max(m1.cols(), m2.cols()); int height = m1.rows() + m2.rows(); Mat result = new Mat(height, width, CvType.CV_8UC3, new Scalar(MAX_RGB_INT_VALUE, MAX_RGB_INT_VALUE, MAX_RGB_INT_VALUE)); // rect works with x, y, width, height Rect roi1 = new Rect(0, 0, m1.cols(), m1.rows()); Mat roiMat1 = result.submat(roi1);//from w ww. ja va2 s. co m m1.copyTo(roiMat1); Rect roi2 = new Rect(0, m1.rows(), m2.cols(), m2.rows()); Mat roiMat2 = result.submat(roi2); m2.copyTo(roiMat2); return result; }