Examples with GeneralFeatureDetector boofcv.alg.feature.detect.interest.GeneralFeatureDetector used on opensource projects

Example 1 with GeneralFeatureDetector

use of boofcv.alg.feature.detect.interest.GeneralFeatureDetector in project BoofCV by lessthanoptimal.

the class CompareFeatureExtractorApp method doProcess.

private synchronized void doProcess() {
    // System.out.println("radius "+radius+" min separation "+minSeparation+" thresholdFraction "+thresholdFraction+" numFeatures "+numFeatures);
    deriv.setInput(grayImage);
    D derivX = deriv.getDerivative(true);
    D derivY = deriv.getDerivative(false);
    D derivXX = deriv.getDerivative(true, true);
    D derivYY = deriv.getDerivative(false, false);
    D derivXY = deriv.getDerivative(true, false);
    // todo modifying buffered images which might be actively being displayed, could mess up swing
    intensityAlg.process(grayImage, derivX, derivY, derivXX, derivYY, derivXY);
    GrayF32 intensity = intensityAlg.getIntensity();
    intensityImage = VisualizeImageData.colorizeSign(intensityAlg.getIntensity(), null, ImageStatistics.maxAbs(intensity));
    float max = ImageStatistics.maxAbs(intensity);
    float threshold = max * thresholdFraction;
    NonMaxSuppression extractor = FactoryFeatureExtractor.nonmax(new ConfigExtract(minSeparation, threshold, radius, true));
    GeneralFeatureDetector<T, D> detector = new GeneralFeatureDetector<>(intensityAlg, extractor);
    detector.setMaxFeatures(numFeatures);
    detector.process(grayImage, derivX, derivY, derivXX, derivYY, derivXY);
    QueueCorner foundCorners = detector.getMaximums();
    render.reset();
    for (int i = 0; i < foundCorners.size(); i++) {
        Point2D_I16 p = foundCorners.get(i);
        render.addPoint(p.x, p.y, 3, Color.RED);
    }
    Graphics2D g2 = workImage.createGraphics();
    g2.drawImage(input, 0, 0, grayImage.width, grayImage.height, null);
    render.draw(g2);
    drawImage();
}

Example 2 with GeneralFeatureDetector

use of boofcv.alg.feature.detect.interest.GeneralFeatureDetector in project BoofCV by lessthanoptimal.

the class VisualizeStereoVisualOdometryApp method createStereoDepth.

private StereoVisualOdometry<I> createStereoDepth(int whichAlg) {
    Class derivType = GImageDerivativeOps.getDerivativeType(imageType);
    StereoDisparitySparse<I> disparity = FactoryStereoDisparity.regionSparseWta(2, 150, 3, 3, 30, -1, true, imageType);
    PkltConfig kltConfig = new PkltConfig();
    kltConfig.templateRadius = 3;
    kltConfig.pyramidScaling = new int[] { 1, 2, 4, 8 };
    if (whichAlg == 0) {
        ConfigGeneralDetector configDetector = new ConfigGeneralDetector(600, 3, 1);
        PointTrackerTwoPass<I> tracker = FactoryPointTrackerTwoPass.klt(kltConfig, configDetector, imageType, derivType);
        return FactoryVisualOdometry.stereoDepth(1.5, 120, 2, 200, 50, false, disparity, tracker, imageType);
    } else if (whichAlg == 1) {
        ConfigGeneralDetector configExtract = new ConfigGeneralDetector(600, 3, 1);
        GeneralFeatureDetector detector = FactoryPointTracker.createShiTomasi(configExtract, derivType);
        DescribeRegionPoint describe = FactoryDescribeRegionPoint.brief(null, imageType);
        ScoreAssociateHamming_B score = new ScoreAssociateHamming_B();
        AssociateDescription2D<TupleDesc_B> associate = new AssociateDescTo2D<>(FactoryAssociation.greedy(score, 150, true));
        PointTrackerTwoPass tracker = FactoryPointTrackerTwoPass.dda(detector, describe, associate, null, 1, imageType);
        return FactoryVisualOdometry.stereoDepth(1.5, 80, 3, 200, 50, false, disparity, tracker, imageType);
    } else if (whichAlg == 2) {
        PointTracker<I> tracker = FactoryPointTracker.combined_ST_SURF_KLT(new ConfigGeneralDetector(600, 3, 0), kltConfig, 50, null, null, imageType, derivType);
        PointTrackerTwoPass<I> twopass = new PointTrackerToTwoPass<>(tracker);
        return FactoryVisualOdometry.stereoDepth(1.5, 80, 3, 200, 50, false, disparity, twopass, imageType);
    } else if (whichAlg == 3) {
        ConfigGeneralDetector configDetector = new ConfigGeneralDetector(600, 3, 1);
        PointTracker<I> trackerLeft = FactoryPointTracker.klt(kltConfig, configDetector, imageType, derivType);
        PointTracker<I> trackerRight = FactoryPointTracker.klt(kltConfig, configDetector, imageType, derivType);
        DescribeRegionPoint describe = FactoryDescribeRegionPoint.surfFast(null, imageType);
        return FactoryVisualOdometry.stereoDualTrackerPnP(90, 2, 1.5, 1.5, 200, 50, trackerLeft, trackerRight, describe, imageType);
    } else if (whichAlg == 4) {
        // GeneralFeatureIntensity intensity =
        // FactoryIntensityPoint.hessian(HessianBlobIntensity.Type.TRACE,defaultType);
        GeneralFeatureIntensity intensity = FactoryIntensityPoint.shiTomasi(1, false, imageType);
        NonMaxSuppression nonmax = FactoryFeatureExtractor.nonmax(new ConfigExtract(2, 50, 0, true, false, true));
        GeneralFeatureDetector general = new GeneralFeatureDetector(intensity, nonmax);
        general.setMaxFeatures(600);
        DetectorInterestPointMulti detector = new GeneralToInterestMulti(general, 2, imageType, derivType);
        // DescribeRegionPoint describe = FactoryDescribeRegionPoint.brief(new ConfigBrief(true),defaultType);
        // DescribeRegionPoint describe = FactoryDescribeRegionPoint.pixelNCC(5,5,defaultType);
        DescribeRegionPoint describe = FactoryDescribeRegionPoint.surfFast(null, imageType);
        DetectDescribeMulti detDescMulti = new DetectDescribeMultiFusion(detector, null, describe);
        return FactoryVisualOdometry.stereoQuadPnP(1.5, 0.5, 75, Double.MAX_VALUE, 300, 50, detDescMulti, imageType);
    } else {
        throw new RuntimeException("Unknown selection");
    }
}

Example 3 with GeneralFeatureDetector

use of boofcv.alg.feature.detect.interest.GeneralFeatureDetector in project BoofCV by lessthanoptimal.

the class FactoryDetectPoint method createGeneral.

public static <T extends ImageGray<T>, D extends ImageGray<D>> GeneralFeatureDetector<T, D> createGeneral(GeneralFeatureIntensity<T, D> intensity, ConfigGeneralDetector config) {
    // create a copy since it's going to modify the detector config
    ConfigGeneralDetector foo = new ConfigGeneralDetector();
    foo.setTo(config);
    config = foo;
    config.ignoreBorder += config.radius;
    NonMaxSuppression extractor = FactoryFeatureExtractor.nonmax(config);
    GeneralFeatureDetector<T, D> det = new GeneralFeatureDetector<>(intensity, extractor);
    det.setMaxFeatures(config.maxFeatures);
    return det;
}

Example 4 with GeneralFeatureDetector

use of boofcv.alg.feature.detect.interest.GeneralFeatureDetector in project BoofCV by lessthanoptimal.

the class TestWrapVisOdomQuadPnP method createAlgorithm.

@Override
public StereoVisualOdometry<GrayF32> createAlgorithm() {
    GeneralFeatureIntensity intensity = FactoryIntensityPoint.shiTomasi(1, false, GrayF32.class);
    NonMaxSuppression nonmax = FactoryFeatureExtractor.nonmax(new ConfigExtract(2, 1, 0, true, false, true));
    GeneralFeatureDetector<GrayF32, GrayF32> general = new GeneralFeatureDetector<>(intensity, nonmax);
    general.setMaxFeatures(600);
    DetectorInterestPointMulti detector = new GeneralToInterestMulti(general, 2, GrayF32.class, GrayF32.class);
    DescribeRegionPoint describe = FactoryDescribeRegionPoint.surfFast(null, GrayF32.class);
    DetectDescribeMulti detDescMulti = new DetectDescribeMultiFusion(detector, null, describe);
    return FactoryVisualOdometry.stereoQuadPnP(1.5, 0.5, 200, Double.MAX_VALUE, 300, 50, detDescMulti, GrayF32.class);
}

Example 5 with GeneralFeatureDetector

use of boofcv.alg.feature.detect.interest.GeneralFeatureDetector in project BoofCV by lessthanoptimal.

the class VisualizeDepthVisualOdometryApp method changeSelectedAlgortihm.

private void changeSelectedAlgortihm(int whichAlg) {
    this.whichAlg = whichAlg;
    AlgType prevAlgType = this.algType;
    Class imageType = GrayU8.class;
    Class derivType = GImageDerivativeOps.getDerivativeType(imageType);
    DepthSparse3D<GrayU16> sparseDepth = new DepthSparse3D.I<>(1e-3);
    PkltConfig pkltConfig = new PkltConfig();
    pkltConfig.templateRadius = 3;
    pkltConfig.pyramidScaling = new int[] { 1, 2, 4, 8 };
    algType = AlgType.UNKNOWN;
    if (whichAlg == 0) {
        algType = AlgType.FEATURE;
        ConfigGeneralDetector configDetector = new ConfigGeneralDetector(600, 3, 1);
        PointTrackerTwoPass tracker = FactoryPointTrackerTwoPass.klt(pkltConfig, configDetector, imageType, derivType);
        alg = FactoryVisualOdometry.depthDepthPnP(1.5, 120, 2, 200, 50, false, sparseDepth, tracker, imageType, GrayU16.class);
    } else if (whichAlg == 1) {
        algType = AlgType.FEATURE;
        ConfigGeneralDetector configExtract = new ConfigGeneralDetector(600, 3, 1);
        GeneralFeatureDetector detector = FactoryPointTracker.createShiTomasi(configExtract, derivType);
        DescribeRegionPoint describe = FactoryDescribeRegionPoint.brief(null, imageType);
        ScoreAssociateHamming_B score = new ScoreAssociateHamming_B();
        AssociateDescription2D<TupleDesc_B> associate = new AssociateDescTo2D<>(FactoryAssociation.greedy(score, 150, true));
        PointTrackerTwoPass tracker = FactoryPointTrackerTwoPass.dda(detector, describe, associate, null, 1, imageType);
        alg = FactoryVisualOdometry.depthDepthPnP(1.5, 80, 3, 200, 50, false, sparseDepth, tracker, imageType, GrayU16.class);
    } else if (whichAlg == 2) {
        algType = AlgType.FEATURE;
        PointTracker tracker = FactoryPointTracker.combined_ST_SURF_KLT(new ConfigGeneralDetector(600, 3, 1), pkltConfig, 50, null, null, imageType, derivType);
        PointTrackerTwoPass twopass = new PointTrackerToTwoPass<>(tracker);
        alg = FactoryVisualOdometry.depthDepthPnP(1.5, 120, 3, 200, 50, false, sparseDepth, twopass, imageType, GrayU16.class);
    } else if (whichAlg == 3) {
        algType = AlgType.DIRECT;
        alg = FactoryVisualOdometry.depthDirect(sparseDepth, ImageType.pl(3, GrayF32.class), GrayU16.class);
    } else {
        throw new RuntimeException("Unknown selection");
    }
    if (algType != prevAlgType) {
        switch(prevAlgType) {
            case FEATURE:
                mainPanel.remove(featurePanel);
                break;
            case DIRECT:
                mainPanel.remove(directPanel);
                break;
            default:
                mainPanel.remove(algorithmPanel);
                break;
        }
        switch(algType) {
            case FEATURE:
                mainPanel.add(featurePanel, BorderLayout.NORTH);
                break;
            case DIRECT:
                mainPanel.add(directPanel, BorderLayout.NORTH);
                break;
            default:
                mainPanel.add(algorithmPanel, BorderLayout.NORTH);
                break;
        }
        mainPanel.invalidate();
    }
    setImageTypes(alg.getVisualType(), ImageType.single(alg.getDepthType()));
}