Examples with FastArray org.ddogleg.struct.FastArray used on opensource projects

Example 6 with FastArray

use of org.ddogleg.struct.FastArray in project BoofCV by lessthanoptimal.

the class CompareConvertedDescriptionsApp method describeImage.

public static <TD extends TupleDesc<TD>> FastArray<TD> describeImage(GrayF32 input, InterestPointDetector<GrayF32> detector, DescribePointRadiusAngle<GrayF32, TD> describe, List<Point2D_F64> location) {
    FastArray<TD> list = new FastArray<>(describe.getDescriptionType());
    System.out.println("Detecting");
    detector.detect(input);
    System.out.println("Describing");
    describe.setImage(input);
    for (int i = 0; i < detector.getNumberOfFeatures(); i++) {
        Point2D_F64 p = detector.getLocation(i);
        double radius = detector.getRadius(i);
        double ori = detector.getOrientation(i);
        TD d = describe.createDescription();
        if (describe.process(p.x, p.y, ori, radius, d)) {
            list.add(d);
            location.add(p.copy());
        }
    }
    return list;
}

Example 7 with FastArray

use of org.ddogleg.struct.FastArray in project BoofCV by lessthanoptimal.

the class TestFeatureSelectNBest method tooFewFeatures.

/**
 * The size of N is less than the number of points
 */
@Test
void tooFewFeatures() {
    GrayF32 intensity = new GrayF32(10, 20);
    intensity.set(5, 10, -3);
    intensity.set(4, 10, -3.5f);
    intensity.set(5, 11, 0);
    intensity.set(8, 8, 10);
    QueueCorner detected = new QueueCorner();
    detected.append(5, 10);
    detected.append(4, 10);
    detected.append(5, 11);
    detected.append(8, 8);
    var found = new FastArray<>(Point2D_I16.class);
    FeatureSelectNBest<Point2D_I16> alg = new FeatureSelectNBest<>(new SampleIntensityImage.I16());
    alg.select(intensity, -1, -1, true, null, detected, 20, found);
    assertEquals(4, found.size);
}

Example 8 with FastArray

use of org.ddogleg.struct.FastArray in project BoofCV by lessthanoptimal.

the class TestFeatureSelectUniform method checkAllCells.

/**
 * Makes sure it found features in all cells
 */
@Test
void checkAllCells() {
    // every pixel is a corner
    QueueCorner detected = new QueueCorner();
    for (int y = 0; y < height; y++) {
        for (int x = 0; x < width; x++) {
            detected.grow().setTo(x, y);
        }
    }
    int cellSize = 10;
    var found = new FastArray<>(Point2D_I16.class);
    FeatureSelectUniform<Point2D_I16> alg = createAlgorithm();
    // make it easy to know the cell size
    alg.configUniform = new TestFeatureSelectUniform.HackedConfig(cellSize);
    // it should spread out the detections evenly throughout the cells
    checkSpread(detected, cellSize, 1, found, alg);
    checkSpread(detected, cellSize, 2, found, alg);
}

Example 9 with FastArray

use of org.ddogleg.struct.FastArray in project BoofCV by lessthanoptimal.

the class TestAssociateNearestNeighbor_ST method scoreRatio.

/**
 * See if associations are skipped if the ratio is too low
 */
@Test
void scoreRatio() {
    Dummy<TupleDesc_F64> nn = new Dummy<>();
    // src = assoc[i] where src is the index of the source feature and i is the index of the dst feature
    nn.assoc = new int[] { 2, 0, 1, -1, 4, -1, -1, 2, 2, 1 };
    nn.distanceScale = 2.0;
    AssociateNearestNeighbor_ST<TupleDesc_F64> alg = new AssociateNearestNeighbor_ST<>(nn, TupleDesc_F64.class);
    FastArray<TupleDesc_F64> src = new FastArray<>(TupleDesc_F64.class);
    FastArray<TupleDesc_F64> dst = new FastArray<>(TupleDesc_F64.class);
    for (int i = 0; i < 5; i++) {
        src.add(new TupleDesc_F64(10));
    }
    for (int i = 0; i < 10; i++) {
        dst.add(new TupleDesc_F64(10));
    }
    alg.setSource(src);
    alg.setDestination(dst);
    alg.setRatioUsesSqrt(false);
    // threshold should reject everything
    alg.setScoreRatioThreshold(0.49);
    alg.associate();
    assertEquals(0, alg.getMatches().size);
    // everything should be accepted
    alg.setScoreRatioThreshold(0.51);
    alg.associate();
    assertEquals(10, alg.getMatches().size);
    alg.setRatioUsesSqrt(true);
    alg.setScoreRatioThreshold(1.0 / Math.sqrt(2.0) - 0.001);
    alg.associate();
    assertEquals(0, alg.getMatches().size);
    alg.setScoreRatioThreshold(1.0 / Math.sqrt(2.0) + 0.001);
    alg.associate();
    assertEquals(10, alg.getMatches().size);
}

Example 10 with FastArray

use of org.ddogleg.struct.FastArray in project BoofCV by lessthanoptimal.

the class TestFeatureSelectUniformBest method everyCellHasPrior.

void everyCellHasPrior(boolean positive) {
    int width = 30;
    int height = 20;
    // One detected feature in each cell and two priors
    QueueCorner prior = new QueueCorner();
    QueueCorner detected = new QueueCorner();
    int cellSize = 10;
    for (int y = 0; y < height; y += cellSize) {
        for (int x = 0; x < width; x += cellSize) {
            detected.grow().setTo(x + 2, y + 2);
            prior.grow().setTo(x + 2, y + 2);
            prior.grow().setTo(x + 1, y + 1);
        }
    }
    var found = new FastArray<>(Point2D_I16.class);
    FeatureSelectUniformBest<Point2D_I16> alg = createAlgorithm();
    // make it easy to know the cell size
    alg.configUniform = new HackedConfig(cellSize);
    // a bug earlier aborted because the total count didn't change when every cell had a prior in it
    alg.select(intensity, -1, -1, positive, prior, detected, 6, found);
    assertEquals(6, found.size);
}