Examples with ConfigPointDetector boofcv.abst.feature.detect.interest.ConfigPointDetector used on opensource projects

Example 6 with ConfigPointDetector

use of boofcv.abst.feature.detect.interest.ConfigPointDetector in project BoofCV by lessthanoptimal.

the class ExampleVideoStabilization method main.

public static void main(String[] args) {
    // Configure the feature detector
    ConfigPointDetector configDetector = new ConfigPointDetector();
    configDetector.type = PointDetectorTypes.SHI_TOMASI;
    configDetector.general.maxFeatures = 300;
    configDetector.general.threshold = 10;
    configDetector.general.radius = 2;
    // Use a KLT tracker
    PointTracker<GrayF32> tracker = FactoryPointTracker.klt(4, configDetector, 3, GrayF32.class, GrayF32.class);
    // This estimates the 2D image motion
    // An Affine2D_F64 model also works quite well.
    ImageMotion2D<GrayF32, Homography2D_F64> motion2D = FactoryMotion2D.createMotion2D(200, 3, 2, 30, 0.6, 0.5, false, tracker, new Homography2D_F64());
    // wrap it so it output color images while estimating motion from gray
    ImageMotion2D<Planar<GrayF32>, Homography2D_F64> motion2DColor = new PlToGrayMotion2D<>(motion2D, GrayF32.class);
    // This fuses the images together
    StitchingFromMotion2D<Planar<GrayF32>, Homography2D_F64> stabilize = FactoryMotion2D.createVideoStitch(0.5, motion2DColor, ImageType.pl(3, GrayF32.class));
    // Load an image sequence
    MediaManager media = DefaultMediaManager.INSTANCE;
    String fileName = UtilIO.pathExample("shake.mjpeg");
    SimpleImageSequence<Planar<GrayF32>> video = media.openVideo(fileName, ImageType.pl(3, GrayF32.class));
    Planar<GrayF32> frame = video.next();
    // The output image size is the same as the input image size
    stabilize.configure(frame.width, frame.height, null);
    // process the first frame
    stabilize.process(frame);
    // Create the GUI for displaying the results + input image
    ImageGridPanel gui = new ImageGridPanel(1, 2);
    gui.setImage(0, 0, new BufferedImage(frame.width, frame.height, BufferedImage.TYPE_INT_RGB));
    gui.setImage(0, 1, new BufferedImage(frame.width, frame.height, BufferedImage.TYPE_INT_RGB));
    gui.autoSetPreferredSize();
    ShowImages.showWindow(gui, "Example Stabilization", true);
    // process the video sequence one frame at a time
    while (video.hasNext()) {
        if (!stabilize.process(video.next()))
            throw new RuntimeException("Don't forget to handle failures!");
        // display the stabilized image
        ConvertBufferedImage.convertTo(frame, gui.getImage(0, 0), true);
        ConvertBufferedImage.convertTo(stabilize.getStitchedImage(), gui.getImage(0, 1), true);
        gui.repaint();
        // throttle the speed just in case it's on a fast computer
        BoofMiscOps.pause(50);
    }
}

Example 7 with ConfigPointDetector

use of boofcv.abst.feature.detect.interest.ConfigPointDetector in project BoofCV by lessthanoptimal.

the class TrackerPointControlPanel method createKltDetectConfig.

static ConfigPointDetector createKltDetectConfig(int maxFeatures) {
    ConfigPointDetector config = new ConfigPointDetector();
    config.type = PointDetectorTypes.SHI_TOMASI;
    config.general.maxFeatures = maxFeatures;
    config.general.radius = 5;
    config.general.threshold = 3.0f;
    return config;
}

Example 8 with ConfigPointDetector

use of boofcv.abst.feature.detect.interest.ConfigPointDetector in project BoofCV by lessthanoptimal.

the class VisualizeMonocularPlaneVisualOdometryApp method createVisualOdometry.

private MonocularPlaneVisualOdometry<I> createVisualOdometry(int whichAlg) {
    Class derivType = GImageDerivativeOps.getDerivativeType(imageClass);
    if (whichAlg == 0) {
        var config = new ConfigPlanarTrackPnP();
        config.tracker.typeTracker = ConfigPointTracker.TrackerType.KLT;
        config.tracker.klt.pyramidLevels = ConfigDiscreteLevels.levels(4);
        config.tracker.klt.templateRadius = 3;
        config.tracker.detDesc.detectPoint.type = PointDetectorTypes.SHI_TOMASI;
        config.tracker.detDesc.detectPoint.general.maxFeatures = 600;
        config.tracker.detDesc.detectPoint.general.radius = 3;
        config.tracker.detDesc.detectPoint.general.threshold = 1;
        config.thresholdAdd = 75;
        config.thresholdRetire = 2;
        config.ransac.iterations = 200;
        config.ransac.inlierThreshold = 1.5;
        return FactoryVisualOdometry.monoPlaneInfinity(config, imageClass);
    } else if (whichAlg == 1) {
        ConfigPKlt configKlt = new ConfigPKlt();
        configKlt.pyramidLevels = ConfigDiscreteLevels.levels(4);
        configKlt.templateRadius = 3;
        ConfigPointDetector configDetector = new ConfigPointDetector();
        configDetector.type = PointDetectorTypes.SHI_TOMASI;
        configDetector.general.maxFeatures = 600;
        configDetector.general.radius = 3;
        configDetector.general.threshold = 1;
        PointTracker<I> tracker = FactoryPointTracker.klt(configKlt, configDetector, imageClass, derivType);
        double cellSize = 0.06;
        double inlierGroundTol = 1.5;
        return FactoryVisualOdometry.monoPlaneOverhead(cellSize, 25, 0.7, inlierGroundTol, 300, 2, 100, 0.5, 0.6, tracker, imageType);
    } else {
        throw new RuntimeException("Unknown selection");
    }
}