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

Example 1 with ConfigFastHessian

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

the class CompareConvertedDescriptionsApp method main.

public static void main(String[] args) {
    String file1 = UtilIO.pathExample("stitch/kayak_01.jpg");
    String file2 = UtilIO.pathExample("stitch/kayak_02.jpg");
    InterestPointDetector<GrayF32> detector = FactoryInterestPoint.fastHessian(new ConfigFastHessian(1, 10, -1, 2, 9, 4, 4));
    DescribeRegionPoint<GrayF32, TupleDesc_F64> describeA = (DescribeRegionPoint) FactoryDescribeRegionPoint.surfStable(null, GrayF32.class);
    ConvertTupleDesc<TupleDesc_F64, TupleDesc_S8> converter = FactoryConvertTupleDesc.real_F64_S8(describeA.createDescription().size());
    DescribeRegionPoint<GrayF32, TupleDesc_S8> describeB = new DescribeRegionPointConvert<>(describeA, converter);
    ScoreAssociation<TupleDesc_F64> scoreA = FactoryAssociation.scoreSad(TupleDesc_F64.class);
    ScoreAssociation<TupleDesc_S8> scoreB = FactoryAssociation.scoreSad(TupleDesc_S8.class);
    BufferedImage image1 = UtilImageIO.loadImage(file1);
    BufferedImage image2 = UtilImageIO.loadImage(file2);
    visualize("Original", image1, image2, detector, describeA, scoreA);
    visualize("Modified", image1, image2, detector, describeB, scoreB);
    System.out.println("Done");
}

Example 2 with ConfigFastHessian

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

the class ExamplePointFeatureTracker method createSURF.

/**
 * Creates a SURF feature tracker.
 */
public void createSURF() {
    ConfigFastHessian configDetector = new ConfigFastHessian();
    configDetector.maxFeaturesPerScale = 250;
    configDetector.extractRadius = 3;
    configDetector.initialSampleSize = 2;
    tracker = FactoryPointTracker.dda_FH_SURF_Fast(configDetector, null, null, imageType);
}

Example 3 with ConfigFastHessian

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

the class ExampleImageStitching method stitch.

/**
 * Given two input images create and display an image where the two have been overlayed on top of each other.
 */
public static <T extends ImageGray<T>> void stitch(BufferedImage imageA, BufferedImage imageB, Class<T> imageType) {
    T inputA = ConvertBufferedImage.convertFromSingle(imageA, null, imageType);
    T inputB = ConvertBufferedImage.convertFromSingle(imageB, null, imageType);
    // Detect using the standard SURF feature descriptor and describer
    DetectDescribePoint detDesc = FactoryDetectDescribe.surfStable(new ConfigFastHessian(1, 2, 200, 1, 9, 4, 4), null, null, imageType);
    ScoreAssociation<BrightFeature> scorer = FactoryAssociation.scoreEuclidean(BrightFeature.class, true);
    AssociateDescription<BrightFeature> associate = FactoryAssociation.greedy(scorer, 2, true);
    // fit the images using a homography.  This works well for rotations and distant objects.
    ModelMatcher<Homography2D_F64, AssociatedPair> modelMatcher = FactoryMultiViewRobust.homographyRansac(null, new ConfigRansac(60, 3));
    Homography2D_F64 H = computeTransform(inputA, inputB, detDesc, associate, modelMatcher);
    renderStitching(imageA, imageB, H);
}

Example 4 with ConfigFastHessian

use of boofcv.abst.feature.detect.interest.ConfigFastHessian in project narchy by automenta.

the class ExampleStereoTwoViewsOneCamera method computeMatches.

/**
 * Use the associate point feature example to create a list of {@link AssociatedPair} for use in computing the
 * fundamental matrix.
 */
public void computeMatches(GrayF32 left, GrayF32 right) {
    DetectDescribePoint detDesc = FactoryDetectDescribe.surfStable(new ConfigFastHessian(1, 2, 0, 1, 9, 4, 4), null, null, GrayF32.class);
    // DetectDescribePoint detDesc = FactoryDetectDescribe.sift(null,new ConfigSiftDetector(2,0,200,5),null,null);
    ScoreAssociation<BrightFeature> scorer = FactoryAssociation.scoreEuclidean(BrightFeature.class, true);
    AssociateDescription<BrightFeature> associate = FactoryAssociation.greedy(scorer, 0.9, true);
    ExampleAssociatePoints<GrayF32, BrightFeature> findMatches = new ExampleAssociatePoints<>(detDesc, associate, GrayF32.class);
    findMatches.associate(left, right);
    FastQueue<AssociatedIndex> matchIndexes = associate.getMatches();
    matchedFeatures.clear();
    for (int i = 0; i < matchIndexes.size; i++) {
        AssociatedIndex a = matchIndexes.get(i);
        matchedFeatures.add(new AssociatedPair(findMatches.pointsA.get(a.src), findMatches.pointsB.get(a.dst)));
    }
}

Example 5 with ConfigFastHessian

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

the class VideoDetectInterestPoints method perform.

public static <T extends ImageGray<T>, D extends ImageGray<D>> void perform(String fileName, Class<T> imageType, Class<D> derivType) {
    SimpleImageSequence<T> sequence = BoofVideoManager.loadManagerDefault().load(fileName, ImageType.single(imageType));
    int maxCorners = 200;
    int radius = 2;
    // if null then no orientation will be computed
    OrientationImageAverage<T> orientation = null;
    orientation = FactoryOrientationAlgs.nogradient(1.0 / 2.0, radius, imageType);
    InterestPointDetector<T> detector;
    detector = FactoryInterestPoint.fastHessian(new ConfigFastHessian(1, 2, 100, 2, 9, 4, 4));
    // FeatureScaleSpace<T,D> feature = FactoryInterestPointAlgs.hessianScaleSpace(radius,1,maxCorners,defaultType,derivType);
    // detector = FactoryInterestPoint.wrapDetector(feature,new double[]{1,2,4,6,8,12},defaultType);
    VideoDetectInterestPoints<T> display = new VideoDetectInterestPoints<>(sequence, detector, orientation);
    display.process();
}