List of usage examples for org.opencv.core Mat width
public int width()
From source file:com.ibm.streamsx.edgevideo.device.FaceDetector.java
License:Open Source License
public Mat resize(Mat frame) { Mat resized = new Mat(); Imgproc.resize(frame, resized, new Size(frame.width() / resizeFactor, frame.height() / resizeFactor)); return resized; }
From source file:com.ibm.streamsx.edgevideo.device.MyPanel.java
License:Open Source License
public boolean matToBufferedImage(Mat mat, int bufferedImageType) { int width = mat.width(), height = mat.height(), channels = mat.channels(); byte[] sourcePixels = new byte[width * height * channels]; mat.get(0, 0, sourcePixels);/*from w w w .j av a2s . c o m*/ // create new image and get reference to backing data image = new BufferedImage(width, height, bufferedImageType); final byte[] targetPixels = ((DataBufferByte) image.getRaster().getDataBuffer()).getData(); System.arraycopy(sourcePixels, 0, targetPixels, 0, sourcePixels.length); return true; }
From source file:com.joravasal.keyface.CameraAccessView.java
License:Open Source License
public Mat correctCameraImage(Mat image) { //Log.i(tag, "Correcting image rotation"); //Check rotation of device int rotation = ((KeyFaceActivity) this.getContext()).getWindowManager().getDefaultDisplay().getRotation(); switch (rotation) { case Surface.ROTATION_0: int degrees = 90; //Mirror (y axis) if front camera and rotation in any case Mat imageResult = new Mat(); //For some reason to rotate the image properly, we have to set the center like this Point center = new Point(image.width() / 2, image.width() / 2); Mat transform = Imgproc.getRotationMatrix2D(center, degrees, 1.0); try {/*from ww w. j av a 2s .co m*/ Imgproc.warpAffine(image, imageResult, transform, new Size(image.height(), image.width())); } catch (CvException e) { System.err.println(e.getMessage()); } if (KeyFaceActivity.cameraRearActive) Core.flip(imageResult, imageResult, -1); else Core.flip(imageResult, imageResult, 1); return imageResult; case Surface.ROTATION_90: //Mirror on y axis if front camera if (!KeyFaceActivity.cameraRearActive) Core.flip(image, image, 1); break; case Surface.ROTATION_180: //Never gets here but just in case: break; case Surface.ROTATION_270: //Mirror on the x axis if rear camera, both axis if front camera if (KeyFaceActivity.cameraRearActive) Core.flip(image, image, -1); else Core.flip(image, image, 0); break; default: break; } return image; }
From source file:com.mitzuli.core.ocr.OcrPreprocessor.java
License:Open Source License
/** * Binarizes and cleans the input image for OCR, saving debugging images in the given directory. * * @param input the input image, which is recycled by this method, so the caller should make a defensive copy of it if necessary. * @param debugDir the directory to write the debugging images to, or null to disable debugging. * @return the preprocessed image.//from ww w .ja v a 2s. c om */ static Image preprocess(final Image input, final File debugDir) { // TODO Temporary workaround to allow to manually enable debugging (the global final variable should be used) boolean DEBUG = debugDir != null; // Initialization final Mat mat = input.toGrayscaleMat(); final Mat debugMat = DEBUG ? input.toRgbMat() : null; input.recycle(); final Mat aux = new Mat(mat.size(), CvType.CV_8UC1); final Mat binary = new Mat(mat.size(), CvType.CV_8UC1); if (DEBUG) Image.fromMat(mat).write(new File(debugDir, "1_input.jpg")); // Binarize the input image in mat through adaptive Gaussian thresholding Imgproc.adaptiveThreshold(mat, binary, 255, Imgproc.ADAPTIVE_THRESH_GAUSSIAN_C, Imgproc.THRESH_BINARY, 51, 13); // Imgproc.adaptiveThreshold(mat, binary, 255, Imgproc.ADAPTIVE_THRESH_GAUSSIAN_C, Imgproc.THRESH_BINARY, 31, 7); // Edge detection Imgproc.morphologyEx(mat, mat, Imgproc.MORPH_OPEN, KERNEL_3X3); // Open Imgproc.morphologyEx(mat, aux, Imgproc.MORPH_CLOSE, KERNEL_3X3); // Close Core.addWeighted(mat, 0.5, aux, 0.5, 0, mat); // Average Imgproc.morphologyEx(mat, mat, Imgproc.MORPH_GRADIENT, KERNEL_3X3); // Gradient Imgproc.threshold(mat, mat, 0, 255, Imgproc.THRESH_BINARY | Imgproc.THRESH_OTSU); // Edge map if (DEBUG) Image.fromMat(mat).write(new File(debugDir, "2_edges.jpg")); // Extract word level connected-components from the dilated edge map Imgproc.dilate(mat, mat, KERNEL_3X3); if (DEBUG) Image.fromMat(mat).write(new File(debugDir, "3_dilated_edges.jpg")); final List<MatOfPoint> wordCCs = new ArrayList<MatOfPoint>(); Imgproc.findContours(mat, wordCCs, new Mat(), Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE); // Filter word level connected-components individually and calculate their average attributes final List<MatOfPoint> individuallyFilteredWordCCs = new ArrayList<MatOfPoint>(); final List<MatOfPoint> removedWordCCs = new ArrayList<MatOfPoint>(); double avgWidth = 0, avgHeight = 0, avgArea = 0; for (MatOfPoint cc : wordCCs) { final Rect boundingBox = Imgproc.boundingRect(cc); if (boundingBox.height >= 6 // bounding box height >= 6 && boundingBox.area() >= 50 // bounding box area >= 50 && (double) boundingBox.width / (double) boundingBox.height >= 0.25 // bounding box aspect ratio >= 1:4 && boundingBox.width <= 0.75 * mat.width() // bounding box width <= 0.75 image width && boundingBox.height <= 0.75 * mat.height()) // bounding box height <= 0.75 image height { individuallyFilteredWordCCs.add(cc); avgWidth += boundingBox.width; avgHeight += boundingBox.height; avgArea += boundingBox.area(); } else { if (DEBUG) removedWordCCs.add(cc); } } wordCCs.clear(); avgWidth /= individuallyFilteredWordCCs.size(); avgHeight /= individuallyFilteredWordCCs.size(); avgArea /= individuallyFilteredWordCCs.size(); if (DEBUG) { Imgproc.drawContours(debugMat, removedWordCCs, -1, BLUE, -1); removedWordCCs.clear(); } // Filter word level connected-components in relation to their average attributes final List<MatOfPoint> filteredWordCCs = new ArrayList<MatOfPoint>(); for (MatOfPoint cc : individuallyFilteredWordCCs) { final Rect boundingBox = Imgproc.boundingRect(cc); if (boundingBox.width >= 0.125 * avgWidth // bounding box width >= 0.125 average width && boundingBox.width <= 8 * avgWidth // bounding box width <= 8 average width && boundingBox.height >= 0.25 * avgHeight // bounding box height >= 0.25 average height && boundingBox.height <= 4 * avgHeight) // bounding box height <= 4 average height { filteredWordCCs.add(cc); } else { if (DEBUG) removedWordCCs.add(cc); } } individuallyFilteredWordCCs.clear(); if (DEBUG) { Imgproc.drawContours(debugMat, filteredWordCCs, -1, GREEN, -1); Imgproc.drawContours(debugMat, removedWordCCs, -1, PURPLE, -1); removedWordCCs.clear(); } // Extract paragraph level connected-components mat.setTo(BLACK); Imgproc.drawContours(mat, filteredWordCCs, -1, WHITE, -1); final List<MatOfPoint> paragraphCCs = new ArrayList<MatOfPoint>(); Imgproc.morphologyEx(mat, aux, Imgproc.MORPH_CLOSE, KERNEL_30X30); Imgproc.findContours(aux, paragraphCCs, new Mat(), Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE); // Filter paragraph level connected-components according to the word level connected-components inside final List<MatOfPoint> textCCs = new ArrayList<MatOfPoint>(); for (MatOfPoint paragraphCC : paragraphCCs) { final List<MatOfPoint> wordCCsInParagraphCC = new ArrayList<MatOfPoint>(); aux.setTo(BLACK); Imgproc.drawContours(aux, Collections.singletonList(paragraphCC), -1, WHITE, -1); Core.bitwise_and(mat, aux, aux); Imgproc.findContours(aux, wordCCsInParagraphCC, new Mat(), Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE); final Rect boundingBox = Imgproc.boundingRect(paragraphCC); final double center = mat.size().width / 2; final double distToCenter = center > boundingBox.x + boundingBox.width ? center - boundingBox.x - boundingBox.width : center < boundingBox.x ? boundingBox.x - center : 0.0; if (DEBUG) { System.err.println("****************************************"); System.err.println("\tArea: " + boundingBox.area()); System.err.println("\tDistance to center: " + distToCenter); System.err.println("\tCCs inside: " + wordCCsInParagraphCC.size()); } if ((wordCCsInParagraphCC.size() >= 10 || wordCCsInParagraphCC.size() >= 0.3 * filteredWordCCs.size()) && mat.size().width / distToCenter >= 4) { textCCs.addAll(wordCCsInParagraphCC); if (DEBUG) { System.err.println("\tText: YES"); Imgproc.drawContours(debugMat, Collections.singletonList(paragraphCC), -1, DARK_GREEN, 5); } } else { if (DEBUG) { System.err.println("\tText: NO"); Imgproc.drawContours(debugMat, Collections.singletonList(paragraphCC), -1, DARK_RED, 5); } } } filteredWordCCs.clear(); paragraphCCs.clear(); mat.setTo(WHITE); Imgproc.drawContours(mat, textCCs, -1, BLACK, -1); textCCs.clear(); if (DEBUG) Image.fromMat(debugMat).write(new File(debugDir, "4_filtering.jpg")); // Obtain the final text mask from the filtered connected-components Imgproc.erode(mat, mat, KERNEL_15X15); Imgproc.morphologyEx(mat, mat, Imgproc.MORPH_OPEN, KERNEL_30X30); if (DEBUG) Image.fromMat(mat).write(new File(debugDir, "5_text_mask.jpg")); // Apply the text mask to the binarized image if (DEBUG) Image.fromMat(binary).write(new File(debugDir, "6_binary.jpg")); binary.setTo(WHITE, mat); if (DEBUG) Image.fromMat(binary).write(new File(debugDir, "7_binary_text.jpg")); // Dewarp the text using Leptonica Pix pixs = Image.fromMat(binary).toGrayscalePix(); Pix pixsDewarp = Dewarp.dewarp(pixs, 0, Dewarp.DEFAULT_SAMPLING, 5, true); final Image result = Image.fromGrayscalePix(pixsDewarp); if (DEBUG) result.write(new File(debugDir, "8_dewarp.jpg")); // Clean up pixs.recycle(); mat.release(); aux.release(); binary.release(); if (debugMat != null) debugMat.release(); return result; }
From source file:com.mycompany.mavenproject1.GenericResource.java
/** * Retrieves representation of an instance of com.mycompany.mavenproject1.GenericResource * @return an instance of java.lang.String *///from ww w .j ava 2s.c o m @GET @Produces(MediaType.APPLICATION_JSON) public JsonObject getXml() { //TODO return proper representation object JsonBuilderFactory factory = Json.createBuilderFactory(null); String filename = "D:\\1Downloads\\Firefox downloads\\stock.jpg"; Mat img; img = Imgcodecs.imread(filename); int width = img.width(); int height = img.height(); System.out.println("w= " + width + " h= " + height); Analyzer analyzer = new Analyzer(filename); analyzer.setFrame(0, 0, width, height); Individual ind = new Individual(analyzer); ind.generateIndividual(width, height); System.out.println("\n\nTHE RESULT: " + analyzer.calcCombinedAestheticScore()); Population myPop = new Population(200, true, width, height, analyzer); long startTime = System.currentTimeMillis(); int generationCount = 0; while (generationCount < 500) { generationCount++; System.out.println( "Generation: " + generationCount + " Fittest: " + myPop.getFittest().getAestheticScore()); //myPop = CropAlgorithm.evolvePopulation(myPop); CropAlgorithm cropAlg = new CropAlgorithm(analyzer); myPop = cropAlg.evolvePopulation(myPop, width, height); System.out.println("-------------------------------------------------ACTUAL BEST: " + myPop.getFittest().getAestheticScore() + " " + myPop.getFittest().toString()); } System.out.println("Solution found!"); System.out.println("Generation: " + generationCount); System.out.println("Genes:"); Individual fittest = myPop.getFittest(); System.out.println(fittest); double score = fittest.getAestheticScore(); System.out.println(fittest.getAestheticScore()); int x = (int) fittest.getX(); int y = (int) fittest.getY(); int w = (int) fittest.getWidth(); int h = (int) fittest.getHeight(); Rect roi = new Rect(x, y, w, h); Mat cropped = new Mat(img, roi); Imgcodecs.imwrite("D:\\1Downloads\\Firefox downloads\\cropped\\torocko.jpg", cropped); long estimatedTime = System.currentTimeMillis() - startTime; System.out.println("IDOOO==== " + estimatedTime); JsonObject value = factory.createObjectBuilder().add("value", score).add("x", x).add("y", y).add("width", w) .add("height", h).build(); System.out.println("-------------------------------"); return value; }
From source file:com.orange.documentare.core.image.connectedcomponents.ConnectedComponentsDetector.java
License:Open Source License
/** * Retrieve image connected components/*from w ww.j ava2 s .c o m*/ * @param imageMat * @return connected components */ public ConnectedComponents detect(Mat imageMat) { return detect(imageMat, new SimpleConnectedComponentsFilter(imageMat.width())); }
From source file:com.randhirkumar.webcam.MainFrameForm.java
public void displayScreen() { Mat webcamImage = new Mat(); VideoCapture videoCapture = new VideoCapture(0); if (videoCapture.isOpened()) { while (true) { videoCapture.read(webcamImage); if (!webcamImage.empty()) { setSize(webcamImage.width() + 50, webcamImage.height() + 70); webcamImage = processor.detect(webcamImage); cameraPanel.convertMatToImage(webcamImage); cameraPanel.repaint();/*from w w w . java2 s.com*/ } else { System.out.println("Problem"); break; } } } }
From source file:com.shootoff.camera.Camera.java
License:Open Source License
public static BufferedImage matToBufferedImage(Mat matBGR) { BufferedImage image = new BufferedImage(matBGR.width(), matBGR.height(), BufferedImage.TYPE_3BYTE_BGR); final byte[] targetPixels = ((DataBufferByte) image.getRaster().getDataBuffer()).getData(); matBGR.get(0, 0, targetPixels);/* ww w . j ava 2 s . co m*/ return image; }
From source file:com.sikulix.api.Image.java
License:Open Source License
private Mat get() { Mat mContent = new Mat(); if (urlImg != null) { File imgFile = new File(urlImg.getPath()); mContent = Highgui.imread(imgFile.getAbsolutePath()); if (!mContent.empty()) { log.debug("get: loaded: (%dx%s) %s", mContent.width(), mContent.height(), urlImg); } else {/*from w w w .j a v a2 s .c om*/ log.error("get: not loaded: %s", urlImg); } } return mContent; }
From source file:com.sikulix.api.Image.java
License:Open Source License
private static long getMatSize(Mat mat) { return mat.channels() * mat.width() * mat.height(); }