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

Example 26 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 27 with Mat

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

the class TestOpenCVTools method testScalar.

@Test
public void testScalar() {
    double[] values = new double[] { -100, 123.4, 0, -0, 12023.423 };
    try (var scope = new PointerScope()) {
        // Test floats
        for (int type : new int[] { opencv_core.CV_32F, opencv_core.CV_64F }) {
            for (double value : values) {
                Mat mat = OpenCVTools.scalarMat(value, type);
                assertEquals(1, mat.rows());
                assertEquals(1, mat.cols());
                assertEquals(1, mat.channels());
                assertEquals(value, mat.createIndexer().getDouble(0L), 1e-3);
            }
        }
        // Test floats with channels
        for (int c : new int[] { 1, 2, 3, 4, 5, 6, 7, 8 }) {
            for (double value : values) {
                Mat mat = OpenCVTools.scalarMatWithType(value, opencv_core.CV_32FC(c));
                assertEquals(1, mat.rows());
                assertEquals(1, mat.cols());
                assertEquals(c, mat.channels());
                double[] doubles = new double[c];
                Arrays.fill(doubles, value);
                assertArrayEquals(doubles, OpenCVTools.extractDoubles(mat), 1e-3);
            }
        }
        // Test unsigned integers
        for (int type : new int[] { opencv_core.CV_8U }) {
            for (double value : values) {
                Mat mat = OpenCVTools.scalarMat(value, type);
                assertEquals(1, mat.rows());
                assertEquals(1, mat.cols());
                assertEquals(1, mat.channels());
                double val = Math.min(255, Math.max(0, Math.round(value)));
                assertEquals(val, mat.createIndexer().getDouble(0L));
            }
        }
        // Test signed integers
        for (int type : new int[] { opencv_core.CV_32S }) {
            for (double value : values) {
                Mat mat = OpenCVTools.scalarMat(value, type);
                assertEquals(1, mat.rows());
                assertEquals(1, mat.cols());
                assertEquals(1, mat.channels());
                double val = Math.round(value);
                assertEquals(val, mat.createIndexer().getDouble(0L));
            }
        }
    }
}

Example 28 with Mat

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

the class TestOpenCVTools method testPercentiles.

@Test
public void testPercentiles() {
    int[] minValues = { -2, 0, 1 };
    int[] maxValues = { 1, 10, 101 };
    opencv_core.setRNGSeed(100);
    for (int min : minValues) {
        for (int max : maxValues) {
            var values = IntStream.range(min, max + 1).asDoubleStream().toArray();
            var stats = new DescriptiveStatistics(values);
            var mat = new Mat(values);
            opencv_core.randShuffle(mat);
            assertEquals(stats.getPercentile(50), OpenCVTools.median(mat));
            assertEquals((min + max) / 2.0, OpenCVTools.median(mat));
            assertEquals(max, OpenCVTools.maximum(mat));
            assertEquals(min, OpenCVTools.minimum(mat));
            assertArrayEquals(new double[] { min, stats.getPercentile(50), max }, OpenCVTools.percentiles(mat, 1e-9, 50, 100));
            double[] newValues = new double[values.length + 30];
            Arrays.fill(newValues, Double.NaN);
            System.arraycopy(values, 0, newValues, 0, values.length);
            mat.close();
            mat = new Mat(newValues);
            opencv_core.randShuffle(mat);
            assertEquals(stats.getPercentile(50), OpenCVTools.median(mat));
            assertEquals((min + max) / 2.0, OpenCVTools.median(mat));
            assertEquals(max, OpenCVTools.maximum(mat));
            assertEquals(min, OpenCVTools.minimum(mat));
            assertArrayEquals(new double[] { min, stats.getPercentile(50), max }, OpenCVTools.percentiles(mat, 1e-9, 50, 100));
            mat.close();
        }
    }
}

Example 29 with Mat

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

the class OpenCVTools method matToImagePlus.

/**
 * Convert an OpenCV {@code MatVector} into an ImageJ {@code ImagePlus}.
 *
 * @param title
 * @param mats
 * @return
 */
public static ImagePlus matToImagePlus(String title, Mat... mats) {
    ImageStack stack = null;
    int nChannels = 1;
    for (Mat mat : mats) {
        if (stack == null) {
            stack = new ImageStack(mat.cols(), mat.rows());
        } else if (mat.channels() != nChannels) {
            throw new IllegalArgumentException("Number of channels must be the same for all Mats!");
        }
        if (mat.channels() == 1) {
            ImageProcessor ip = matToImageProcessor(mat);
            stack.addSlice(ip);
        } else {
            nChannels = mat.channels();
            MatVector split = new MatVector();
            opencv_core.split(mat, split);
            for (int c = 0; c < split.size(); c++) stack.addSlice(matToImageProcessor(split.get(c)));
        }
    }
    ImagePlus imp = new ImagePlus(title, stack);
    imp.setDimensions(nChannels, mats.length, 1);
    return nChannels == 1 ? imp : new CompositeImage(imp);
}

Example 30 with Mat

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

the class OpenCVTools method filterZ.

/**
 * Filter filter along entries in the input list.
 * <p>
 * If each Mat in the list can be considered a consecutive 2D image plane from a z-stack,
 * this can be considered filtering along the z-dimension.
 *
 * @param mats
 * @param kernelZ
 * @param ind3D if -1, return filtered results for all mats, otherwise only return results for the mat at the specified ind3D
 * @param border
 * @return
 */
public static List<Mat> filterZ(List<Mat> mats, Mat kernelZ, int ind3D, int border) {
    /*
		 * We can avoid the rigmarole of applying the full filtering 
		 * by instead simply calculating the weighted sum corresponding to the convolution 
		 * around the z-slice of interest only.
		 */
    // ind3D >= 0;
    boolean doWeightedSums = true;
    if (doWeightedSums) {
        // Extract kernel values
        int ks = (int) kernelZ.total();
        double[] kernelArray = new double[ks];
        DoubleIndexer idx = kernelZ.createIndexer();
        idx.get(0L, kernelArray);
        idx.release();
        if (ind3D >= 0) {
            // Calculate weights for each image
            Mat result = filterSingleZ(mats, kernelArray, ind3D, border);
            return Arrays.asList(result);
        } else {
            List<Mat> output = new ArrayList<>();
            for (int i = 0; i < mats.size(); i++) {
                Mat result = filterSingleZ(mats, kernelArray, i, border);
                output.add(result);
            }
            return output;
        }
    }
    // Create a an array of images reshaped as column vectors
    Mat[] columns = new Mat[mats.size()];
    int nRows = 0;
    for (int i = 0; i < mats.size(); i++) {
        Mat mat = mats.get(i);
        nRows = mat.rows();
        columns[i] = mat.reshape(mat.channels(), mat.rows() * mat.cols());
    }
    // Concatenate columns, effectively meaning z dimension now along rows
    Mat matConcatZ = new Mat();
    opencv_core.hconcat(new MatVector(columns), matConcatZ);
    // Apply z filtering along rows
    if (kernelZ.rows() > 1)
        kernelZ = kernelZ.t().asMat();
    // Mat empty = new Mat(1, 1, opencv_core.CV_64FC1, Scalar.ONE);
    // opencv_imgproc.sepFilter2D(matConcatZ, matConcatZ, opencv_core.CV_32F, kernelZ, empty, null, 0.0, border);
    opencv_imgproc.filter2D(matConcatZ, matConcatZ, opencv_core.CV_32F, kernelZ, null, 0.0, border);
    int start = 0;
    int end = mats.size();
    if (ind3D >= 0) {
        start = ind3D;
        end = ind3D + 1;
    }
    // Reshape to create output list
    List<Mat> output = new ArrayList<>();
    for (int i = start; i < end; i++) {
        output.add(matConcatZ.col(i).clone().reshape(matConcatZ.channels(), nRows));
    }
    return output;
}