List of usage examples for org.opencv.imgcodecs Imgcodecs CV_LOAD_IMAGE_UNCHANGED
int CV_LOAD_IMAGE_UNCHANGED
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From source file:com.oetermann.imageclassifier.ImageClassifier.java
License:Open Source License
public String matchName(String matcherName, byte[] data, int minMatches) { return matchName(matcherName, Imgcodecs.imdecode(new MatOfByte(data), Imgcodecs.CV_LOAD_IMAGE_UNCHANGED), minMatches);/*from www . ja v a 2 s . c o m*/ }
From source file:ru.caramel.juniperbot.web.service.OpenCVService.java
License:Open Source License
public static Mat getMat(BufferedImage image) throws IOException { ByteArrayOutputStream byteArrayOutputStream = new ByteArrayOutputStream(); ImageIO.write(image, "jpg", byteArrayOutputStream); byteArrayOutputStream.flush();/*from w ww . j a va 2 s.co m*/ return Imgcodecs.imdecode(new MatOfByte(byteArrayOutputStream.toByteArray()), Imgcodecs.CV_LOAD_IMAGE_UNCHANGED); }
From source file:uom.research.thalassemia.logic.BloodCellsManipulationImpl.java
/** * do Blood Cell Processing.// w w w .j a va 2 s . co m * * @throws Exception Exception */ @Override public void doBloodCellProcessing() throws Exception { if (imageFile.isFile()) { // Load Native Library System.loadLibrary(Core.NATIVE_LIBRARY_NAME); // Load Selected File onto Original Mat original = Imgcodecs.imread(imageFile.getAbsolutePath(), Imgcodecs.CV_LOAD_IMAGE_UNCHANGED); // Create Mats with Original Mat's Size gray = original.clone(); smooth = original.clone(); canny = original.clone(); threshold = original.clone(); red = original.clone(); laplacian = original.clone(); circularsMat = original.clone(); ellipsesMat = original.clone(); // Sets Gray Scale to gray Map Imgproc.cvtColor(original, gray, Imgproc.COLOR_BGR2HSV); grayImage = convertMapToImage(gray); // Sest Red Colour Range Min and Max Scalar minc = new Scalar(95, 150, 75, 0); Scalar maxc = new Scalar(145, 255, 255, 0); // Sets Red Colour Mat for Given Range Core.inRange(original, maxc, maxc, red); redImage = convertMapToImage(red); int type = BufferedImage.TYPE_INT_RGB; //gray = Imgcodecs.imdecode(original, type); image = new BufferedImage(original.cols(), original.rows(), type); //Imgproc.GaussianBlur(mGray, mGray, new Size(15,15),50); //redImage = new BufferedImage(original.width(), original.height(), BufferedImage.TYPE_INT_RGB); //byte[] data2 = ((DataBufferByte) redImage.getRaster().getDataBuffer()).getData(); Imgproc.threshold(gray, threshold, 155, 255, Imgproc.THRESH_BINARY); //Imgproc.Laplacian(gray, laplacian, CvType.CV_8UC3);//CV_8UC1); //laplacianImage = convertMapToImage(laplacian); thresholdImage = convertMapToImage(threshold); Imgproc.Canny(threshold, canny, 50, 100, 3, false); cannyImage = convertMapToImage(canny); //Imgproc.cvtColor(canny, canny, Imgproc.COLOR_BGR2GRAY); circles = new Mat(); int imageArea = original.width() * original.height(); if (imageArea > 5100000) { Imgproc.HoughCircles(canny, circles, Imgproc.CV_HOUGH_GRADIENT, 8, //Inverse ratio 220, //Minimum distance between the centers of the detected circles. default 100 100, //Higher threshold for canny edge detector. default100 200, //Threshold at the center detection stage. default 200 90, //min radius. default 50 130 //max radius. default 90 ); } else if (imageArea > 1309500) { Imgproc.HoughCircles(canny, circles, Imgproc.CV_HOUGH_GRADIENT, 8, //Inverse ratio 110, //Minimum distance between the centers of the detected circles. default 100 100, //Higher threshold for canny edge detector. default100 150, //Threshold at the center detection stage. default 200 50, //min radius. default 50 67 //max radius. default 90 ); } else if (imageArea > 540000) { Imgproc.HoughCircles(canny, circles, Imgproc.CV_HOUGH_GRADIENT, 8, //Inverse ratio 110, //Minimum distance between the centers of the detected circles. default 100 100, //Higher threshold for canny edge detector. default100 200, //Threshold at the center detection stage. default 200 30, //min radius. default 50 65 //max radius. default 90 ); } else if (imageArea > 400000) { Imgproc.HoughCircles(canny, circles, Imgproc.CV_HOUGH_GRADIENT, 8, //Inverse ratio 50, //Minimum distance between the centers of the detected circles. default 100 60, //Higher threshold for canny edge detector. default100 100, //Threshold at the center detection stage. default 200 25, //min radius. default 50 40 //max radius. default 90 ); } if (circles.cols() > 0) { for (int x = 0; x < circles.cols(); x++) { double vCircle[] = circles.get(0, x); if (vCircle == null) { break; } Point pt = new Point(Math.round(vCircle[0]), Math.round(vCircle[1])); int radius = (int) Math.round(vCircle[2]); radiusList.add(radius); // draw the found circle Imgproc.circle(circularsMat, pt, radius, new Scalar(0, 255, 0), 3); } } // set Pallor circles circlesPallor = new Mat(); if (imageArea > 5100000) { Imgproc.HoughCircles(canny, circlesPallor, Imgproc.CV_HOUGH_GRADIENT, 8, //Inverse ratio 220, //Minimum distance between the centers of the detected circles 100, //Higher threshold for canny edge detector 150, //Threshold at the center detection stage 0, //min radius 70 //max radius ); } else if (imageArea > 1309500) { Imgproc.HoughCircles(canny, circlesPallor, Imgproc.CV_HOUGH_GRADIENT, 8, //Inverse ratio 110, //Minimum distance between the centers of the detected circles 50, //Higher threshold for canny edge detector 100, //Threshold at the center detection stage 0, //min radius 45 //max radius ); } else if (imageArea > 540000) { Imgproc.HoughCircles(canny, circlesPallor, Imgproc.CV_HOUGH_GRADIENT, 8, //Inverse ratio 100, //Minimum distance between the centers of the detected circles 50, //Higher threshold for canny edge detector 100, //Threshold at the center detection stage 0, //min radius 35 //max radius ); } else if (imageArea > 400000) { Imgproc.HoughCircles(canny, circlesPallor, Imgproc.CV_HOUGH_GRADIENT, 8, //Inverse ratio 50, //Minimum distance between the centers of the detected circles 10, //Higher threshold for canny edge detector 30, //Threshold at the center detection stage 0, //min radius 25 //max radius ); } if (circlesPallor.cols() > 0) { for (int x = 0; x < circlesPallor.cols(); x++) { double vCircle[] = circlesPallor.get(0, x); if (vCircle == null) { break; } Point pt = new Point(Math.round(vCircle[0]), Math.round(vCircle[1])); int radius = (int) Math.round(vCircle[2]); //radiusList.add(radius); // draw the found circle Imgproc.circle(circularsMat, pt, radius, new Scalar(0, 0, 255), 0); } } // set Ellipses contours = new ArrayList<>(); Imgproc.findContours(canny, contours, new Mat(), Imgproc.RETR_LIST, Imgproc.CHAIN_APPROX_SIMPLE); MatOfPoint allcontours = new MatOfPoint(); for (MatOfPoint mat : contours) { mat.copyTo(allcontours); RotatedRect boundingEllipse = null; if (allcontours.toArray().length > 4) { MatOfPoint newMat1 = new MatOfPoint(allcontours.toArray()); MatOfPoint2f newMat2 = new MatOfPoint2f(allcontours.toArray()); Rect boundingRect = Imgproc.boundingRect(newMat1); boundingEllipse = Imgproc.fitEllipse(newMat2); } if (boundingEllipse != null) { Imgproc.ellipse(ellipsesMat, boundingEllipse, new Scalar(255, 0, 0), 2); } } circleCount = circles.cols(); circularsImage = convertMapToImage(circularsMat); ellipsesImage = convertMapToImage(ellipsesMat); } }