Example usage for org.opencv.core Mat rows

Introduction

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

Prototype

public int rows() 

Source Link

Usage

From source file:i2r.snap2inspect.SamplePresentation.java

License:Apache License

public void setImageDynamic(Mat m) {
    // convert to bitmap:
    Bitmap bm = Bitmap.createBitmap(m.cols(), m.rows(), Bitmap.Config.ARGB_8888);
    Utils.matToBitmap(m, bm);/*w  ww. j  a  va2 s .c  o  m*/
    mImageView.setImageBitmap(bm);
}

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From source file:imageanalyzercv.ImageAnalyzerCV.java

/**
 * @param args the command line arguments
 *//*from   w w w .j  a  va  2 s  . com*/
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);
}

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From source file:imagegame.Camera.java

public static BufferedImage mat2BufferedImage(Mat mat) {
    //        MatOfByte buffer = new MatOfByte();
    //        Imgcodecs.imencode(".png", mat, buffer);
    int type = mat.channels() > 1 ? BufferedImage.TYPE_3BYTE_BGR : BufferedImage.TYPE_BYTE_GRAY;
    BufferedImage image = new BufferedImage(mat.cols(), mat.rows(), type);
    mat.get(0, 0, ((DataBufferByte) image.getRaster().getDataBuffer()).getData());
    return image;
    //return new Image(new ByteArrayInputStream(buffer.toArray()));
}

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From source file:imageprocess.HistogramProcessor.java

public static Mat getHistogramImage(Mat image) {

    // Compute histogram first
    Mat hist = getGrayHistogram(image);/*from   w ww  .  ja  v a 2s.com*/
    // Get min and max bin values

    MinMaxLocResult locPeak = Core.minMaxLoc(hist);
    double maxVal = locPeak.maxVal;
    double minVal = locPeak.minVal;

    // Image on which to display histogram
    Mat histImg = new Mat(image.rows(), image.rows(), CV_8U, new Scalar(255));

    // set highest point at 90% of nbins
    int hpt = (int) (0.9 * 256);

    // Draw vertical line for each bin 
    for (int h = 0; h < 256; h++) {

        double[] f = hist.get(h, 0);
        float binVal = (float) f[0];
        int intensity = (int) (binVal * hpt / maxVal);
        Core.line(histImg, new Point(h, 256.0d), new Point(h, 256.0d - intensity), Scalar.all(0));
    }
    return histImg;
}

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From source file:imageprocess.HistogramProcessor.java

public static Mat applyLookUp(Mat image, Mat lookup) {
    // Set output image (always 1-channel)
    Mat result = new Mat(image.rows(), image.cols(), CV_8U);

    //        for (int i = 0; i < image.cols(); i++) {
    //            for (int j = 0; j < image.rows(); j++) {
    //                double[] data = image.get(j, i);
    //                double newIntensity = lookup.get((int)data[0], 0)[0];
    //                result.put(j, i, newIntensity);
    //            }
    //        }//from   ww  w . j  ava  2s. co m
    Core.LUT(image, lookup, result);
    return result;
}

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From source file:imageprocess.ObjectFinder.java

public Mat find(final Mat image, MatOfInt channels, MatOfFloat ranges) {

    Mat result = new Mat();

    if (isIsSparse()) { // call the right function based on histogram type

        Imgproc.calcBackProject(Arrays.asList(image), channels, // vector specifying what histogram dimensions belong to what image channels
                ROIHistogram, // the histogram we are using
                result, // the resulting back projection image
                ranges, // the range of values, for each dimension
                255.0 // the scaling factor is chosen such that a histogram value of 1 maps to 255
        );//w  ww . j  av a 2s. c o m

    } else {
        Imgproc.calcBackProject(Arrays.asList(image), channels, // vector specifying what histogram dimensions belong to what image channels
                ROIHistogram, // the histogram we are using
                result, // the resulting back projection image
                ranges, // the range of values, for each dimension
                255.0 // the scaling factor is chosen such that a histogram value of 1 maps to 255
        );
    }

    // Threshold back projection to obtain a binary image
    Mat thresholded = new Mat(result.rows(), result.cols(), result.type());
    if (getThreshold() > 0.0) {
        Imgproc.threshold(result, thresholded, 255 * getThreshold(), 255, THRESH_BINARY);
    }

    return thresholded;
}

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From source file:imageprocess.PixelProcessor.java

public void salt(Mat image, int n) {
    for (int k = 0; k < n; k++) {
        int i = (int) (Math.random() * image.cols());
        int j = (int) (Math.random() * image.rows());
        if (image.channels() == 1) {
            image.put(j, i, 255);/*from   w w w  .  ja  va  2  s.c o m*/
        } else if (image.channels() == 3) {
            image.put(j, i, new byte[] { (byte) 255, (byte) 255, (byte) 255 });
        }
    }
}

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From source file:interactivespaces.service.image.vision.opencv.MatUtils.java

License:Apache License

/**
 * Converts a {@link Mat} into a {@link BufferedImage}.
 *
 * @param matrix// w w w  . j  ava 2 s  .c  om
 *          Mat of type CV_8UC3 or CV_8UC1
 *
 * @return BufferedImage of type TYPE_3BYTE_BGR or TYPE_BYTE_GRAY
 *
 * @throws SimpleInteractiveSpacesException
 *           the OpenCV Mat type is not supported
 */
public static BufferedImage matToBufferedImage(Mat matrix) throws SimpleInteractiveSpacesException {
    int cols = matrix.cols();
    int rows = matrix.rows();
    int elemSize = (int) matrix.elemSize();
    byte[] data = new byte[cols * rows * elemSize];
    int type;
    matrix.get(0, 0, data);
    switch (matrix.channels()) {
    case 1:
        type = BufferedImage.TYPE_BYTE_GRAY;
        break;
    case 3:
        type = BufferedImage.TYPE_3BYTE_BGR;
        for (int i = 0; i < data.length; i = i + 3) {
            byte b = data[i];
            data[i] = data[i + 2];
            data[i + 2] = b;
        }
        break;
    default:
        throw new SimpleInteractiveSpacesException("The OpenCV Mat type is not supported");
    }

    BufferedImage image = new BufferedImage(cols, rows, type);
    image.getRaster().setDataElements(0, 0, cols, rows, data);

    return image;
}

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From source file:io.appium.java_client.ScreenshotState.java

License:Apache License

/**
 * Compares two valid java bitmaps and calculates similarity score between them.
 *
 * @param refImage   reference image/* w ww  .ja v  a 2  s. co m*/
 * @param tplImage   template
 * @param resizeMode one of possible enum values. Set it either to <em>TEMPLATE_TO_REFERENCE_RESOLUTION</em> or
 *                   <em>REFERENCE_TO_TEMPLATE_RESOLUTION</em> if given bitmaps have different dimensions
 * @return similarity score value in range (-1.0, 1.0). 1.0 is returned if the images are equal
 * @throws ScreenshotComparisonError if provided images are not valid or have
 *                                   different resolution, but resizeMode has been set to <em>NO_RESIZE</em>
 */
public static double getOverlapScore(BufferedImage refImage, BufferedImage tplImage, ResizeMode resizeMode) {
    Mat ref = prepareImageForComparison(refImage);
    if (ref.empty()) {
        throw new ScreenshotComparisonError("Reference image cannot be converted for further comparison");
    }
    Mat tpl = prepareImageForComparison(tplImage);
    if (tpl.empty()) {
        throw new ScreenshotComparisonError("Template image cannot be converted for further comparison");
    }
    switch (resizeMode) {
    case TEMPLATE_TO_REFERENCE_RESOLUTION:
        tpl = resizeFirstMatrixToSecondMatrixResolution(tpl, ref);
        break;
    case REFERENCE_TO_TEMPLATE_RESOLUTION:
        ref = resizeFirstMatrixToSecondMatrixResolution(ref, tpl);
        break;
    default:
        // do nothing
    }

    if (ref.width() != tpl.width() || ref.height() != tpl.height()) {
        throw new ScreenshotComparisonError(
                "Resolutions of template and reference images are expected to be equal. "
                        + "Try different resizeMode value.");
    }

    Mat res = new Mat(ref.rows() - tpl.rows() + 1, ref.cols() - tpl.cols() + 1, CvType.CV_32FC1);
    Imgproc.matchTemplate(ref, tpl, res, Imgproc.TM_CCOEFF_NORMED);
    return Core.minMaxLoc(res).maxVal;
}

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From source file:io.smartspaces.service.image.vision.opencv.MatUtils.java

License:Apache License

/**
 * Converts a {@link Mat} into a {@link BufferedImage}.
 *
 * @param matrix/* w  w w.j  av a  2  s .c om*/
 *          Mat of type CV_8UC3 or CV_8UC1
 *
 * @return BufferedImage of type TYPE_3BYTE_BGR or TYPE_BYTE_GRAY
 *
 * @throws SimpleSmartSpacesException
 *           the OpenCV Mat type is not supported
 */
public static BufferedImage matToBufferedImage(Mat matrix) throws SimpleSmartSpacesException {
    int cols = matrix.cols();
    int rows = matrix.rows();
    int elemSize = (int) matrix.elemSize();
    byte[] data = new byte[cols * rows * elemSize];
    int type;
    matrix.get(0, 0, data);
    switch (matrix.channels()) {
    case 1:
        type = BufferedImage.TYPE_BYTE_GRAY;
        break;
    case 3:
        type = BufferedImage.TYPE_3BYTE_BGR;
        for (int i = 0; i < data.length; i = i + 3) {
            byte b = data[i];
            data[i] = data[i + 2];
            data[i + 2] = b;
        }
        break;
    default:
        throw new SimpleSmartSpacesException("The OpenCV Mat type is not supported");
    }

    BufferedImage image = new BufferedImage(cols, rows, type);
    image.getRaster().setDataElements(0, 0, cols, rows, data);

    return image;
}

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