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

Example 11 with Mat

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

the class DetectCytokeratinCV method updateArea.

private static void updateArea(final MatVector contours, final Mat hierarchy, final Area area, int row, int depth) {
    IntIndexer indexer = hierarchy.createIndexer();
    while (row >= 0) {
        int[] data = new int[4];
        // TODO: Check indexing after switch to JavaCPP!!!
        indexer.get(0, row, data);
        // hierarchy.get(0, row, data);
        Mat contour = contours.get(row);
        // Don't include isolated pixels - otherwise add or remove, as required
        if (contour.rows() > 2) {
            Path2D path = getContour(contour);
            if (depth % 2 == 0)
                area.add(new Area(path));
            else
                area.subtract(new Area(path));
        }
        // Deal with any sub-contours
        if (data[2] >= 0)
            updateArea(contours, hierarchy, area, data[2], depth + 1);
        // Move to next contour in this hierarchy level
        row = data[0];
    }
}

Example 12 with Mat

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

the class DetectCytokeratinCV method getArea.

/**
 * Get an Area object corresponding to contours in a binary image from OpenCV.
 * @param mat
 * @return
 */
private static Area getArea(final Mat mat) {
    if (mat.empty())
        return null;
    // Identify all contours
    MatVector contours = new MatVector();
    Mat hierarchy = new Mat();
    opencv_imgproc.findContours(mat, contours, hierarchy, opencv_imgproc.RETR_TREE, opencv_imgproc.CHAIN_APPROX_SIMPLE);
    if (contours.empty()) {
        hierarchy.close();
        return null;
    }
    Area area = new Area();
    updateArea(contours, hierarchy, area, 0, 0);
    hierarchy.close();
    return area;
}

Example 13 with Mat

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

the class WatershedNucleiCV method watershedDistanceTransformSplit.

private static void watershedDistanceTransformSplit(Mat matBinary, int maxFilterRadius) {
    Mat matWatershedSeedsBinary;
    // Create a background mask
    Mat matBackground = new Mat();
    compare(matBinary, new Mat(1, 1, CV_32FC1, Scalar.WHITE), matBackground, CMP_NE);
    // Separate by shape using the watershed transform
    Mat matDistanceTransform = new Mat();
    opencv_imgproc.distanceTransform(matBinary, matDistanceTransform, opencv_imgproc.CV_DIST_L2, opencv_imgproc.CV_DIST_MASK_PRECISE);
    // Find local maxima
    matWatershedSeedsBinary = new Mat();
    opencv_imgproc.dilate(matDistanceTransform, matWatershedSeedsBinary, OpenCVTools.getCircularStructuringElement(maxFilterRadius));
    compare(matDistanceTransform, matWatershedSeedsBinary, matWatershedSeedsBinary, CMP_EQ);
    matWatershedSeedsBinary.setTo(new Mat(1, 1, matWatershedSeedsBinary.type(), Scalar.ZERO), matBackground);
    // Dilate slightly to merge nearby maxima
    opencv_imgproc.dilate(matWatershedSeedsBinary, matWatershedSeedsBinary, OpenCVTools.getCircularStructuringElement(2));
    // Create labels for watershed
    Mat matLabels = new Mat(matDistanceTransform.size(), CV_32F, Scalar.ZERO);
    OpenCVTools.labelImage(matWatershedSeedsBinary, matLabels, opencv_imgproc.RETR_CCOMP);
    // Remove everything outside the thresholded region
    matLabels.setTo(new Mat(1, 1, matLabels.type(), Scalar.ZERO), matBackground);
    // Do watershed
    // 8-connectivity is essential for the watershed lines to be preserved - otherwise OpenCV's findContours could not be used
    ProcessingCV.doWatershed(matDistanceTransform, matLabels, 0.1, true);
    // Update the binary image to remove the watershed lines
    multiply(matBinary, matLabels, matBinary, 1, matBinary.type());
}

Example 14 with Mat

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

the class DefaultBlobFunction method toBlob.

@Override
public Mat toBlob(Mat... mats) {
    // Preprocess the images
    var preprocessed = new Mat[mats.length];
    int ind = 0;
    for (var mat : mats) {
        var temp = mat.clone();
        if (preprocessing != null) {
            temp = preprocessing.apply(temp);
        }
        if (inputSize != null) {
            if (crop) {
                int w = inputSize.width();
                int h = inputSize.height();
                double factor = Math.max(w / (double) temp.cols(), h / (double) temp.rows());
                opencv_imgproc.resize(temp, temp, new Size(), factor, factor, opencv_imgproc.INTER_LINEAR);
                int x = (temp.cols() - w) / 2;
                int y = (temp.rows() - h) / 2;
                temp.put(OpenCVTools.crop(temp, x, y, w, h));
            } else {
                opencv_imgproc.resize(temp, temp, inputSize, 0, 0, opencv_imgproc.INTER_LINEAR);
            }
        }
        preprocessed[ind] = temp;
        ind++;
    }
    // Convert images to blob
    return DnnTools.blobFromImages(preprocessed);
}

Example 15 with Mat

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

the class DnnTools method blobFromImages.

/**
 * Create an OpenCV blob from a batch of Mats with optional scaling, resizing and cropping.
 * @param mats input images
 * @param scaleFactor scale factor
 * @param size input width and height
 * @param mean mean values for subtraction
 * @param swapRB swap red and blue of the mean values
 * @param crop center crop after resizing if needed
 * @return a blob with axis order NCHW
 */
public static Mat blobFromImages(Collection<Mat> mats, double scaleFactor, Size size, Scalar mean, boolean swapRB, boolean crop) {
    // if (mat.depth() != opencv_core.CV_32F) {
    // var mat2 = new Mat();
    // mat.convertTo(mat2, opencv_core.CV_32F);
    // mat2 = mat;
    // }
    Mat blob = null;
    Mat first = mats.iterator().next();
    int nChannels = first.channels();
    if (nChannels == 1 || nChannels == 3 || nChannels == 4) {
        if (mats.size() == 1)
            blob = opencv_dnn.blobFromImage(first, scaleFactor, size, mean, swapRB, crop, opencv_core.CV_32F);
        else
            blob = opencv_dnn.blobFromImages(new MatVector(mats.toArray(Mat[]::new)), scaleFactor, size, mean, swapRB, crop, opencv_core.CV_32F);
    } else {
        // TODO: Don't have any net to test this with currently...
        logger.warn("Attempting to reshape an image with " + nChannels + " channels - this may not work! " + "Only 1, 3 and 4 full supported, preprocessing will be ignored.");
        // Blob is a 4D Tensor [NCHW]
        int[] shape = new int[4];
        Arrays.fill(shape, 1);
        int nRows = first.size(0);
        int nCols = first.size(1);
        shape[0] = mats.size();
        shape[1] = nChannels;
        shape[2] = nRows;
        shape[3] = nCols;
        // for (int s = 1; s <= Math.min(nDims, 3); s++) {
        // shape[s] = mat.size(s-1);
        // }
        blob = new Mat(shape, opencv_core.CV_32F);
        var idxBlob = blob.createIndexer();
        long[] indsBlob = new long[4];
        int n = 0;
        for (var mat : mats) {
            indsBlob[0] = n++;
            long[] indsMat = new long[4];
            var idxMat = mat.createIndexer();
            for (int r = 0; r < nRows; r++) {
                indsMat[0] = r;
                indsBlob[2] = r;
                for (int c = 0; c < nCols; c++) {
                    indsMat[1] = c;
                    indsBlob[3] = c;
                    for (int channel = 0; channel < nChannels; channel++) {
                        indsMat[2] = channel;
                        indsBlob[1] = channel;
                        double val = idxMat.getDouble(indsMat);
                        idxBlob.putDouble(indsBlob, val);
                    }
                }
            }
            idxMat.close();
        }
        idxBlob.close();
    }
    return blob;
}