Example usage for org.opencv.core Mat cols

List of usage examples for org.opencv.core Mat cols

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Introduction

In this page you can find the example usage for org.opencv.core Mat cols.

Prototype

public int cols()

Source Link

Usage

From source file:usefull.LoopImageFiles.java

License:LGPL

public static int countP(Mat f) {
    int countAll = 0;
    for (int m = 0; m < f.cols(); m++) {
        for (int n = 0; n < f.rows(); n++) {
            double[] t = f.get(n, m);
            double value2 = t[0];
            if (value2 == 255.0) {
                countAll++;//from w ww .  j av  a 2  s.  c  o m
            }
        }
    }
    return countAll;
}

From source file:utils.PreProcessing.java

public BufferedImage enhance(BufferedImage img) {
    Utils ut = new Utils();

    ut.Img2GrayScale(img);//from ww w .java  2s  .  c  om
    Mat source = ut.bufferedImageToMat(img);

    Mat destination = new Mat(source.rows(), source.cols(), source.type());

    //Melhora constraste
    //Imgproc.equalizeHist(source, destination);
    //Melhora brilho
    source.convertTo(destination, -1, 2, 60);

    //Suavizao
    // Imgproc.GaussianBlur(source, destination, new Size(11, 11), 0);

    //Melhora a definio
    Imgproc.GaussianBlur(source, destination, new Size(0, 0), 10);
    Core.addWeighted(source, 1.8, destination, -0.8, 0, destination);
    //return ut.convertMatToImage(destination);
    BufferedImage imgRetorno = ut.matToBufferedImage(destination);
    return imgRetorno;
}

From source file:ve.ucv.ciens.ccg.nxtar.MainActivity.java

License:Apache License

@Override
public MarkerData findMarkersInFrame(byte[] frame) {
    if (ocvOn) {//from w  w w .  j  av a 2  s. co m
        if (cameraCalibrated) {
            int[] codes = new int[ProjectConstants.MAXIMUM_NUMBER_OF_MARKERS];
            float[] translations = new float[ProjectConstants.MAXIMUM_NUMBER_OF_MARKERS * 3];
            float[] rotations = new float[ProjectConstants.MAXIMUM_NUMBER_OF_MARKERS * 9];
            MarkerData data;
            Bitmap tFrame, mFrame;
            Mat inImg = new Mat();
            Mat outImg = new Mat();

            // Fill the codes array with -1 to indicate markers that were not found;
            for (int i : codes)
                codes[i] = -1;

            // Decode the input image and convert it to an OpenCV matrix.
            tFrame = BitmapFactory.decodeByteArray(frame, 0, frame.length);
            Utils.bitmapToMat(tFrame, inImg);

            // Find the markers in the input image.
            getMarkerCodesAndLocations(inImg.getNativeObjAddr(), outImg.getNativeObjAddr(), codes,
                    cameraMatrix.getNativeObjAddr(), distortionCoeffs.getNativeObjAddr(), translations,
                    rotations);

            // Encode the output image as a JPEG image.
            mFrame = Bitmap.createBitmap(outImg.cols(), outImg.rows(), Bitmap.Config.RGB_565);
            Utils.matToBitmap(outImg, mFrame);
            mFrame.compress(CompressFormat.JPEG, 100, outputStream);

            // Create and fill the output data structure.
            data = new MarkerData();
            data.outFrame = outputStream.toByteArray();
            data.markerCodes = codes;
            data.rotationMatrices = new Matrix3[ProjectConstants.MAXIMUM_NUMBER_OF_MARKERS];
            data.translationVectors = new Vector3[ProjectConstants.MAXIMUM_NUMBER_OF_MARKERS];

            for (int i = 0, p = 0; i < ProjectConstants.MAXIMUM_NUMBER_OF_MARKERS; i++, p += 3) {
                data.translationVectors[i] = new Vector3(translations[p], translations[p + 1],
                        translations[p + 2]);
            }

            for (int k = 0; k < ProjectConstants.MAXIMUM_NUMBER_OF_MARKERS; k++) {
                data.rotationMatrices[k] = new Matrix3();
                for (int row = 0; row < 3; row++) {
                    for (int col = 0; col < 3; col++) {
                        data.rotationMatrices[k].val[col + (row * 3)] = rotations[col + (row * 3) + (9 * k)];
                    }
                }
            }

            // Clean up memory.
            tFrame.recycle();
            mFrame.recycle();
            outputStream.reset();

            return data;
        } else {
            Gdx.app.debug(TAG, CLASS_NAME + ".findMarkersInFrame(): The camera has not been calibrated.");
            return null;
        }
    } else {
        Gdx.app.debug(TAG, CLASS_NAME + ".findMarkersInFrame(): OpenCV is not ready or failed to load.");
        return null;
    }
}

From source file:video.Mat2Image.java

public void getSpace(Mat mat) {
    this.mat = mat;
    Imgproc.cvtColor(mat, mat, Imgproc.COLOR_RGB2BGR);
    int w = mat.cols(), h = mat.rows();
    if (dat == null || dat.length != w * h * 3)
        dat = new byte[w * h * 3];
    if (img == null || img.getWidth() != w || img.getHeight() != h
            || img.getType() != BufferedImage.TYPE_3BYTE_BGR)
        img = new BufferedImage(w, h, BufferedImage.TYPE_3BYTE_BGR);
}

From source file:video.Mat2Image.java

BufferedImage getImage(Mat mat) {
    getSpace(mat);
    mat.get(0, 0, dat);
    img.getRaster().setDataElements(0, 0, mat.cols(), mat.rows(), dat);

    return img;
}

From source file:video.PictureView.java

public static BufferedImage mat2Img(Mat in) {
    BufferedImage out;/*  www .  ja va  2s  .com*/
    int width = in.cols();
    int height = in.height();
    byte[] data = new byte[width * height * (int) in.elemSize()];
    int type;
    in.get(0, 0, data);

    if (in.channels() == 1) {
        type = BufferedImage.TYPE_BYTE_GRAY;
    } else {
        type = BufferedImage.TYPE_3BYTE_BGR;
    }

    out = new BufferedImage(width, height, type);

    out.getRaster().setDataElements(0, 0, width, height, data);
    return out;
}

From source file:videostream.MulticastServer.java

/**
 * Transforms an OpenCV mat to a byte array
 * @param m The mat to transform/*from   w  w w  . j a v  a2 s .  c  om*/
 * @param format The desired format
 * @return The mat transformed to a byte array
 * @throws IOException 
 */
public byte[] matToByteArray(Mat m, String format) throws IOException {
    // Check if image is grayscale or color
    int type = BufferedImage.TYPE_BYTE_GRAY;
    if (m.channels() > 1) {
        type = BufferedImage.TYPE_3BYTE_BGR;
    }
    // Transfer bytes from Mat to BufferedImage
    int bufferSize = m.channels() * m.cols() * m.rows();
    byte[] b = new byte[bufferSize];
    m.get(0, 0, b); // get all the pixels
    BufferedImage image = new BufferedImage(m.cols(), m.rows(), type);
    final byte[] targetPixels = ((DataBufferByte) image.getRaster().getDataBuffer()).getData();
    System.arraycopy(b, 0, targetPixels, 0, b.length);

    Iterator iter = ImageIO.getImageWritersByFormatName("jpeg");
    ImageWriter writer = (ImageWriter) iter.next();
    ImageWriteParam iwp = writer.getDefaultWriteParam();

    iwp.setCompressionMode(ImageWriteParam.MODE_EXPLICIT);
    iwp.setCompressionQuality(quality);

    ByteArrayOutputStream baos1 = new ByteArrayOutputStream();
    ImageOutputStream ios = ImageIO.createImageOutputStream(baos1);
    writer.setOutput(ios);
    IIOImage Iimage = new IIOImage(image, null, null);
    writer.write(null, Iimage, iwp);
    writer.dispose();

    return baos1.toByteArray();

}

From source file:videostream.MyFrame.java

public Image toBufferedImage(Mat m) {
    // Code from http://stackoverflow.com/questions/15670933/opencv-java-load-image-to-gui

    // Check if image is grayscale or color
    int type = BufferedImage.TYPE_BYTE_GRAY;
    if (m.channels() > 1) {
        type = BufferedImage.TYPE_3BYTE_BGR;
    }/*from   w ww  . jav  a  2 s  .  c o m*/
    // Transfer bytes from Mat to BufferedImage
    int bufferSize = m.channels() * m.cols() * m.rows();
    byte[] b = new byte[bufferSize];
    m.get(0, 0, b); // get all the pixels
    BufferedImage image = new BufferedImage(m.cols(), m.rows(), type);
    final byte[] targetPixels = ((DataBufferByte) image.getRaster().getDataBuffer()).getData();
    System.arraycopy(b, 0, targetPixels, 0, b.length);
    return image;
}

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];//from w w  w.  j  av  a  2  s . com
        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 w  w w .j  ava  2s .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");  
}