Examples with ImageOp qupath.opencv.ops.ImageOp used on opensource projects

Example 1 with ImageOp

use of qupath.opencv.ops.ImageOp in project qupath by qupath.

the class SimpleThresholdCommand method updateClassification.

private void updateClassification() {
    // for (var viewer : qupath.getViewers()) {
    // var imageData = viewer.getImageData();
    // if (imageData == null) {
    // selectedOverlay.set(null);
    // viewer.resetCustomPixelLayerOverlay();
    // }
    // }
    var channel = selectedChannel.get();
    var thresholdValue = threshold.get();
    var resolution = selectedResolution.get();
    if (channel == null || thresholdValue == null || resolution == null) {
        resetOverlays();
        return;
    }
    var feature = selectedPrefilter.get();
    double sigmaValue = sigma.get();
    PixelClassifier classifier;
    List<ImageOp> ops = new ArrayList<>();
    if (feature != null && sigmaValue > 0) {
        ops.add(feature.buildOp(sigmaValue));
    }
    ops.add(ImageOps.Threshold.threshold(threshold.get()));
    Map<Integer, PathClass> classifications = new LinkedHashMap<>();
    classifications.put(0, classificationsBelow.getSelectionModel().getSelectedItem());
    classifications.put(1, classificationsAbove.getSelectionModel().getSelectedItem());
    var op = ImageOps.Core.sequential(ops);
    var transformer = ImageOps.buildImageDataOp(channel).appendOps(op);
    classifier = PixelClassifiers.createClassifier(transformer, resolution.getPixelCalibration(), classifications);
    // Create classifier
    var overlay = PixelClassificationOverlay.create(qupath.getOverlayOptions(), classifier);
    overlay.setLivePrediction(true);
    var previousOverlay = selectedOverlay.get();
    if (previousOverlay != null)
        previousOverlay.stop();
    selectedOverlay.set(overlay);
    this.currentClassifier.set(classifier);
    ensureOverlays();
}

Example 2 with ImageOp

use of qupath.opencv.ops.ImageOp in project qupath by qupath.

the class DensityMapDataOp method buildOpAndChannels.

private void buildOpAndChannels() {
    logger.trace("Building density map op with type {}", densityType);
    String baseChannelName;
    ImageChannel lastChannel = null;
    List<ImageOp> sequentialOps = new ArrayList<>();
    switch(densityType) {
        case GAUSSIAN:
            if (radius > 0) {
                double sigma = radius;
                sequentialOps.add(ImageOps.Filters.gaussianBlur(sigma));
                // Scale so that central value ~1 - this is a closer match to the alternative sum filter
                sequentialOps.add(ImageOps.Core.multiply(2 * Math.PI * sigma * sigma));
            }
            baseChannelName = "Gaussian weighted counts ";
            break;
        case PERCENT:
            int[] extractInds = IntStream.range(0, primaryObjects.size()).toArray();
            if (radius > 0) {
                sequentialOps.add(ImageOps.Filters.sum(radius));
                sequentialOps.add(ImageOps.Core.round());
            }
            if (extractInds.length > 0) {
                // Duplicate the image, then
                // - On the first duplicate, remove the last channel and divide all the other channels by its values
                // - On the second duplicate, extract the last channel (so as to retain its values)
                // Finally merge the last channel back
                // The outcome should be that the last channel is unchanged, while the other channels are divided by the last
                // channel elementwise.
                sequentialOps.addAll(Arrays.asList(ImageOps.Core.splitMerge(ImageOps.Core.sequential(ImageOps.Core.splitDivide(ImageOps.Channels.extract(extractInds), ImageOps.Core.sequential(ImageOps.Channels.extract(extractInds.length), ImageOps.Channels.repeat(extractInds.length))), // Convert to percent
                ImageOps.Core.multiply(100.0)), ImageOps.Channels.extract(extractInds.length))));
            } else {
                // Values will be 1 and NaN (a possibly-zero value being divided by itself)
                sequentialOps.add(ImageOps.Core.splitDivide(null, null));
            }
            baseChannelName = "";
            if (!primaryObjects.isEmpty())
                lastChannel = ImageChannel.getInstance(DensityMaps.CHANNEL_ALL_OBJECTS, null);
            break;
        case SUM:
        default:
            if (radius > 0) {
                sequentialOps.add(ImageOps.Filters.sum(radius));
                sequentialOps.add(ImageOps.Core.round());
            }
            baseChannelName = "";
    }
    var channelNames = primaryObjects.keySet().stream().map(n -> baseChannelName + n).toArray(String[]::new);
    var channels = new ArrayList<>(ImageChannel.getChannelList(channelNames));
    if (lastChannel != null)
        channels.add(lastChannel);
    if (channels.isEmpty())
        this.channels = Collections.singletonList(ImageChannel.getInstance(DensityMaps.CHANNEL_ALL_OBJECTS, null));
    else
        this.channels = Collections.unmodifiableList(channels);
    sequentialOps.add(ImageOps.Core.ensureType(PixelType.FLOAT32));
    this.op = ImageOps.Core.sequential(sequentialOps);
}

Example 3 with ImageOp

use of qupath.opencv.ops.ImageOp in project qupath by qupath.

the class DensityMapDataOp method appendOps.

@Override
public ImageDataOp appendOps(ImageOp... ops) {
    if (ops.length == 0)
        return this;
    ImageOp opNew;
    if (ops.length > 1)
        opNew = ImageOps.Core.sequential(ops);
    else
        opNew = ops[0];
    var dataOp = new DensityMapDataOp(radius, primaryObjects, allObjects, densityType);
    dataOp.op = ImageOps.Core.sequential(dataOp.op, opNew);
    dataOp.channels = opNew.getChannels(dataOp.channels);
    return dataOp;
}

Example 4 with ImageOp

use of qupath.opencv.ops.ImageOp in project qupath by qupath.

the class OpenCVDnn method createBlobFunction.

private BlobFunction<Mat> createBlobFunction() {
    var ops = new ArrayList<ImageOp>();
    if (mean != null) {
        // TODO: Trim scalar array if needed
        double[] scalarArray = new double[4];
        mean.get(scalarArray);
        ops.add(ImageOps.Core.subtract(scalarArray));
    }
    if (scale != 1)
        ops.add(ImageOps.Core.multiply(scale));
    ImageOp preprocess;
    if (ops.isEmpty())
        preprocess = null;
    else if (ops.size() == 1)
        preprocess = ops.get(0);
    else
        preprocess = ImageOps.Core.sequential(ops);
    return new DefaultBlobFunction(preprocess, size, crop);
}