Examples with AssociatedIndex boofcv.struct.feature.AssociatedIndex used on opensource projects

Example 6 with AssociatedIndex

use of boofcv.struct.feature.AssociatedIndex in project BoofCV by lessthanoptimal.

the class CompareConvertedDescriptionsApp method visualize.

public static <TD extends TupleDesc> void visualize(String title, BufferedImage image1, BufferedImage image2, InterestPointDetector<GrayF32> detector, DescribeRegionPoint<GrayF32, TD> describe, ScoreAssociation<TD> scorer) {
    AssociateDescription<TD> assoc = FactoryAssociation.greedy(scorer, Double.MAX_VALUE, false);
    List<Point2D_F64> locationSrc = new ArrayList<>();
    List<Point2D_F64> locationDst = new ArrayList<>();
    GrayF32 input1 = ConvertBufferedImage.convertFrom(image1, (GrayF32) null);
    GrayF32 input2 = ConvertBufferedImage.convertFrom(image2, (GrayF32) null);
    FastQueue<TD> listSrc = describeImage(input1, detector, describe, locationSrc);
    FastQueue<TD> listDst = describeImage(input2, detector, describe, locationDst);
    assoc.setSource(listSrc);
    assoc.setDestination(listDst);
    assoc.associate();
    FastQueue<AssociatedIndex> matches = assoc.getMatches();
    AssociationPanel panel = new AssociationPanel(20);
    panel.setImages(image1, image2);
    panel.setAssociation(locationSrc, locationDst, matches);
    ShowImages.showWindow(panel, title);
}

Example 7 with AssociatedIndex

use of boofcv.struct.feature.AssociatedIndex in project BoofCV by lessthanoptimal.

the class DetectDescribeAssociate method updateTrackState.

/**
 * Update each track's location and description (if configured to do so) mark tracks as being associated.
 */
protected void updateTrackState(FastQueue<AssociatedIndex> matches) {
    // update tracks
    for (int i = 0; i < matches.size; i++) {
        AssociatedIndex indexes = matches.data[i];
        PointTrack track = tracksAll.get(indexes.src);
        Point2D_F64 loc = locDst.data[indexes.dst];
        track.set(loc.x, loc.y);
        tracksActive.add(track);
        // update the description
        if (updateDescription) {
            ((Desc) track.getDescription()).setTo(featDst.get(indexes.dst));
        }
        isAssociated[indexes.src] = true;
    }
}

Example 8 with AssociatedIndex

use of boofcv.struct.feature.AssociatedIndex in project BoofCV by lessthanoptimal.

the class DetectDescribeAssociateTwoPass method updateTrackLocation.

/**
 * Update each track's location only and not its description.  Update the active list too
 */
protected void updateTrackLocation(FastQueue<AssociatedIndex> matches) {
    tracksActive.clear();
    for (int i = 0; i < matches.size; i++) {
        AssociatedIndex indexes = matches.data[i];
        PointTrack track = tracksAll.get(indexes.src);
        Point2D_F64 loc = locDst.data[indexes.dst];
        track.set(loc.x, loc.y);
        tracksActive.add(track);
    }
    this.matches = matches;
}

Example 9 with AssociatedIndex

use of boofcv.struct.feature.AssociatedIndex in project BoofCV by lessthanoptimal.

the class ExampleMultiviewSceneReconstruction method initialize.

/**
 * Initialize the 3D world given these two images.  imageA is assumed to be the origin of the world.
 */
private void initialize(int imageA, int imageB) {
    System.out.println("Initializing 3D world using " + imageA + " and " + imageB);
    // Compute the 3D pose and find valid image features
    Se3_F64 motionAtoB = new Se3_F64();
    List<AssociatedIndex> inliers = new ArrayList<>();
    if (!estimateStereoPose(imageA, imageB, motionAtoB, inliers))
        throw new RuntimeException("The first image pair is a bad keyframe!");
    motionWorldToCamera[imageB].set(motionAtoB);
    estimatedImage[imageB] = true;
    processedImage[imageB] = true;
    // create tracks for only those features in the inlier list
    FastQueue<Point2D_F64> pixelsA = imagePixels.get(imageA);
    FastQueue<Point2D_F64> pixelsB = imagePixels.get(imageB);
    List<Feature3D> tracksA = imageFeature3D.get(imageA);
    List<Feature3D> tracksB = imageFeature3D.get(imageB);
    GrowQueue_I32 colorsA = imageColors.get(imageA);
    for (int i = 0; i < inliers.size(); i++) {
        AssociatedIndex a = inliers.get(i);
        Feature3D t = new Feature3D();
        t.color = colorsA.get(a.src);
        t.obs.grow().set(pixelsA.get(a.src));
        t.obs.grow().set(pixelsB.get(a.dst));
        t.frame.add(imageA);
        t.frame.add(imageB);
        // compute the 3D coordinate of the feature
        Point2D_F64 pa = pixelsA.get(a.src);
        Point2D_F64 pb = pixelsB.get(a.dst);
        if (!triangulate.triangulate(pa, pb, motionAtoB, t.worldPt))
            continue;
        // the feature has to be in front of the camera
        if (t.worldPt.z > 0) {
            featuresAll.add(t);
            tracksA.add(t);
            tracksB.add(t);
        }
    }
    // adjust the scale so that it's not excessively large or small
    normalizeScale(motionWorldToCamera[imageB], tracksA);
}

Example 10 with AssociatedIndex

use of boofcv.struct.feature.AssociatedIndex in project BoofCV by lessthanoptimal.

the class TestAssociateStereo2D method positive.

/**
 * Very simple positive case with only a perfect observation and descriptor
 */
@Test
public void positive() {
    Point3D_F64 X = new Point3D_F64(0.02, -0.5, 3);
    SfmTestHelper.renderPointPixel(param, X, leftP, rightP);
    pointsLeft.grow().set(leftP);
    pointsRight.grow().set(rightP);
    descLeft.grow();
    descRight.grow();
    AssociateStereo2D<TupleDesc_F64> alg = new AssociateStereo2D<>(scorer, 0.5, TupleDesc_F64.class);
    alg.setCalibration(param);
    alg.setSource(pointsLeft, descLeft);
    alg.setDestination(pointsRight, descRight);
    alg.associate();
    FastQueue<AssociatedIndex> matches = alg.getMatches();
    assertEquals(1, matches.size);
}