Examples with Mat org.bytedeco.opencv.opencv_core.Mat used on opensource projects

Example 36 with Mat

use of org.bytedeco.opencv.opencv_core.Mat in project qupath by qupath.

the class OpenCVTools method matToSimpleImage.

/**
 * Convert a Mat to a {@link SimpleImage}.
 * @param mat
 * @param channel
 * @return
 */
public static SimpleImage matToSimpleImage(Mat mat, int channel) {
    Mat temp = mat;
    if (mat.channels() > 1) {
        temp = new Mat();
        opencv_core.extractChannel(mat, temp, channel);
    }
    float[] pixels = extractPixels(temp, (float[]) null);
    return SimpleImages.createFloatImage(pixels, mat.cols(), mat.rows());
}

Example 37 with Mat

use of org.bytedeco.opencv.opencv_core.Mat in project qupath by qupath.

the class OpenCVTools method getCircularStructuringElement.

/**
 * Create a Mat depicting a circle of the specified radius.
 * <p>
 * Pixels within the circle have the value 1, pixels outside are 0.
 *
 * @param radius
 * @return
 * @deprecated {@link #createDisk(int, boolean)} gives more reliable shapes.
 */
@Deprecated
public static Mat getCircularStructuringElement(int radius) {
    // TODO: Find out why this doesn't just call a standard request for a strel...
    Mat strel = new Mat(radius * 2 + 1, radius * 2 + 1, opencv_core.CV_8UC1, Scalar.ZERO);
    opencv_imgproc.circle(strel, new Point(radius, radius), radius, Scalar.ONE, -1, opencv_imgproc.LINE_8, 0);
    return strel;
}

Example 38 with Mat

use of org.bytedeco.opencv.opencv_core.Mat in project qupath by qupath.

the class OpenCVTools method shrinkLabels.

/**
 * Shrink labels to a single point.
 * This works by effectively iterating through each label, and retaining only the labeled pixel that is closest to the centroid
 * of all pixels with the same label - setting all other pixels within the component to zero.
 *
 * @param mat label mat (must be CV_32S)
 * @return the labeled image, with only one pixel per label greater than zero
 */
public static Mat shrinkLabels(Mat mat) {
    if (mat.channels() != 1)
        throw new IllegalArgumentException("shrinkLabels requires a single-channel mat, but input has " + mat.channels() + " channels");
    var points = labelsToPoints(mat);
    var mat2 = new Mat(mat.rows(), mat.cols(), mat.type(), Scalar.ZERO);
    try (IntIndexer idx2 = mat2.createIndexer()) {
        for (var p : points) {
            idx2.putDouble(p.inds, p.getValue());
        }
    }
    return mat2;
}

Example 39 with Mat

use of org.bytedeco.opencv.opencv_core.Mat in project qupath by qupath.

the class OpenCVTools method labelImage.

/**
 * Create a labelled image from a binary image using findContours and drawContours.
 * @param matBinary
 * @param matLabels
 * @param contourRetrievalMode defined within OpenCV findContours
 * @deprecated Use {@link #label(Mat, Mat, int)} instead.
 */
@Deprecated
public static void labelImage(Mat matBinary, Mat matLabels, int contourRetrievalMode) {
    MatVector contours = new MatVector();
    Mat hierarchy = new Mat();
    opencv_imgproc.findContours(matBinary, contours, hierarchy, contourRetrievalMode, opencv_imgproc.CHAIN_APPROX_SIMPLE);
    Point offset = new Point(0, 0);
    for (int c = 0; c < contours.size(); c++) {
        opencv_imgproc.drawContours(matLabels, contours, c, Scalar.all(c + 1), -1, 8, hierarchy, 2, offset);
    }
    hierarchy.close();
    contours.close();
}

Example 40 with Mat

use of org.bytedeco.opencv.opencv_core.Mat in project qupath by qupath.

the class OpenCVTools method matToBufferedImage.

/**
 * Convert a Mat to a BufferedImage.
 * <p>
 * If no ColorModel is specified, a grayscale model will be used for single-channel 8-bit
 * images and RGB/ARGB for 3/4 channel 8-bit images.
 * <p>
 * For all other cases a ColorModel should be specified for meaningful display.
 *
 * @param mat
 * @param colorModel
 * @return
 */
public static BufferedImage matToBufferedImage(final Mat mat, ColorModel colorModel) {
    int type;
    int bpp = 0;
    switch(mat.depth()) {
        case opencv_core.CV_8U:
            type = DataBuffer.TYPE_BYTE;
            bpp = 8;
            break;
        case opencv_core.CV_8S:
            // Byte is unsigned
            type = DataBuffer.TYPE_SHORT;
            bpp = 16;
            break;
        case opencv_core.CV_16U:
            type = DataBuffer.TYPE_USHORT;
            bpp = 16;
            break;
        case opencv_core.CV_16S:
            type = DataBuffer.TYPE_SHORT;
            bpp = 16;
            break;
        case opencv_core.CV_32S:
            type = DataBuffer.TYPE_INT;
            bpp = 32;
            break;
        case opencv_core.CV_32F:
            type = DataBuffer.TYPE_FLOAT;
            bpp = 32;
            break;
        default:
            logger.warn("Unknown Mat depth {}, will default to CV64F ({})", mat.depth(), opencv_core.CV_64F);
        case opencv_core.CV_64F:
            type = DataBuffer.TYPE_DOUBLE;
            bpp = 64;
    }
    // Create a suitable raster
    int width = mat.cols();
    int height = mat.rows();
    int channels = mat.channels();
    // We might generate an image for a special case
    BufferedImage img = null;
    // Handle some special cases
    if (colorModel == null) {
        if (type == DataBuffer.TYPE_BYTE) {
            if (channels == 1) {
                img = new BufferedImage(width, height, BufferedImage.TYPE_BYTE_GRAY);
            // TODO: Set the bytes
            } else if (channels == 3) {
                img = new BufferedImage(width, height, BufferedImage.TYPE_INT_RGB);
            } else if (channels == 4) {
                img = new BufferedImage(width, height, BufferedImage.TYPE_INT_ARGB);
            }
        }
    } else if (colorModel instanceof IndexColorModel) {
        img = new BufferedImage(width, height, BufferedImage.TYPE_BYTE_INDEXED, (IndexColorModel) colorModel);
    }
    // Create the image
    WritableRaster raster;
    if (img != null) {
        raster = img.getRaster();
    } else if (colorModel != null) {
        raster = colorModel.createCompatibleWritableRaster(width, height);
        img = new BufferedImage(colorModel, raster, false, null);
    } else {
        // Create some kind of raster we can use
        var sampleModel = new BandedSampleModel(type, width, height, channels);
        raster = WritableRaster.createWritableRaster(sampleModel, null);
        // We do need a ColorModel or some description
        colorModel = ColorModelFactory.getDummyColorModel(bpp * channels);
        img = new BufferedImage(colorModel, raster, false, null);
    }
    MatVector matvector = new MatVector();
    opencv_core.split(mat, matvector);
    // We don't know which of the 3 supported array types will be needed yet...
    int[] pixelsInt = null;
    float[] pixelsFloat = null;
    double[] pixelsDouble = null;
    for (int b = 0; b < channels; b++) {
        // Extract pixels for the current channel
        Mat matChannel = matvector.get(b);
        Indexer indexer = matChannel.createIndexer();
        if (indexer instanceof UByteIndexer) {
            if (pixelsInt == null)
                pixelsInt = new int[width * height];
            ((UByteIndexer) indexer).get(0L, pixelsInt);
        } else if (indexer instanceof UShortIndexer) {
            if (pixelsInt == null)
                pixelsInt = new int[width * height];
            ((UShortIndexer) indexer).get(0L, pixelsInt);
        } else if (indexer instanceof FloatIndexer) {
            if (pixelsFloat == null)
                pixelsFloat = new float[width * height];
            ((FloatIndexer) indexer).get(0L, pixelsFloat);
        } else if (indexer instanceof DoubleIndexer) {
            if (pixelsDouble == null)
                pixelsDouble = new double[width * height];
            ((DoubleIndexer) indexer).get(0L, pixelsDouble);
        } else {
            if (pixelsDouble == null)
                pixelsDouble = new double[width * height];
            // This is inefficient, but unlikely to occur too often
            pixelsDouble = new double[width * height];
            for (int y = 0; y < height; y++) {
                for (int x = 0; x < width; x++) {
                    pixelsDouble[y * width + x] = indexer.getDouble(y, x, b);
                }
            }
        }
        // Set the samples
        if (pixelsInt != null)
            raster.setSamples(0, 0, width, height, b, pixelsInt);
        else if (pixelsFloat != null)
            raster.setSamples(0, 0, width, height, b, pixelsFloat);
        else if (pixelsDouble != null)
            raster.setSamples(0, 0, width, height, b, pixelsDouble);
    }
    return img;
}