Examples with DogArray_F32 org.ddogleg.struct.DogArray_F32 used on opensource projects

Example 1 with DogArray_F32

use of org.ddogleg.struct.DogArray_F32 in project BoofCV by lessthanoptimal.

the class TestRecognitionVocabularyTreeNister2006 method describe.

@Test
void describe() {
    HierarchicalVocabularyTree<Point2D_F64> tree = create2x2Tree();
    // Add a few features at the leaves
    List<Point2D_F64> imageFeatures = new ArrayList<>();
    for (int i = 0; i < 3; i++) {
        imageFeatures.add(new Point2D_F64(-5, -1));
        imageFeatures.add(new Point2D_F64(5, -1));
    }
    // TF-IDF descriptor
    var descWeights = new DogArray_F32();
    var descWords = new DogArray_I32();
    var alg = new RecognitionVocabularyTreeNister2006<Point2D_F64>();
    alg.initializeTree(tree);
    alg.describe(imageFeatures, descWeights, descWords);
    // See if the description is as expected
    assertEquals(4, descWeights.size());
    assertEquals(4, descWords.size());
    // All the expected nodes should have values
    float f1 = descWeights.get(descWords.indexOf(1));
    float f2 = descWeights.get(descWords.indexOf(2));
    float f3 = descWeights.get(descWords.indexOf(3));
    float f5 = descWeights.get(descWords.indexOf(5));
    assertTrue(f1 > 0 && f2 > 0 && f3 > 0 && f5 > 0);
    assertTrue(f1 < f2);
    assertTrue(f3 < f5);
    // L2-norm should be 1.0
    float norm = (float) Math.sqrt(f1 * f1 + f2 * f2 + f3 * f3 + f5 * f5);
    assertEquals(1.0f, norm, UtilEjml.TEST_F32);
}

Example 2 with DogArray_F32

use of org.ddogleg.struct.DogArray_F32 in project BoofCV by lessthanoptimal.

the class TestECoCheckDetector method sampleBitsGray.

/**
 * Create a simple scenario where the bits follow a known pattern.
 */
@Test
void sampleBitsGray() {
    var points = new ArrayList<Point2D_F64>();
    var values = new DogArray_F32();
    int rows = 5;
    int cols = 6;
    int blockSize = 4;
    for (int i = 0; i < rows; i++) {
        for (int j = 0; j < cols; j++) {
            for (int k = 0; k < blockSize; k++) {
                points.add(new Point2D_F64(j * 20, i * 20));
            }
        }
    }
    alg.bitImage.reshape(cols, rows);
    alg.interpolate = new AbstractInterpolatePixelS<>() {

        @Override
        public float get(float x, float y) {
            int i = (int) (y / 20 + 0.5);
            int j = (int) (x / 20 + 0.5);
            return (i + j) % 3 == 0 ? 10 : 200;
        }
    };
    alg.samplePixelGray(points, values);
    alg.graySamplesToBits(values, blockSize, 100);
    for (int i = 0; i < rows; i++) {
        for (int j = 0; j < cols; j++) {
            int expected = (i + j) % 3 == 0 ? 1 : 0;
            assertEquals(expected, alg.bitImage.get(j, i));
        }
    }
}

Example 3 with DogArray_F32

use of org.ddogleg.struct.DogArray_F32 in project BoofCV by lessthanoptimal.

the class TestMultiBaselineDisparityMedian method computeFused.

/**
 * Given an already constructed fused image, compute the disparity image output.
 */
@Test
void computeFused() {
    var alg = new MultiBaselineDisparityMedian();
    intrinsic.width = 10;
    intrinsic.height = 8;
    alg.initialize(intrinsic, new DoNothingPixelTransform_F64());
    // add elements to each fused pixel that will be easy to compute the solution for
    int counter = 0;
    for (int y = 0; y < 8; y++) {
        for (int x = 0; x < 10; x++, counter++) {
            for (int i = 0; i < counter; i++) {
                alg.fused.get(x, y).add(i + 0.5f);
            }
        }
    }
    GrayF32 found = new GrayF32(10, 8);
    assertTrue(alg.computeFused(found));
    // manually compute the solution. Use a brute force approach for median value since it requires no thinking
    DogArray_F32 expected = new DogArray_F32();
    for (int y = 0; y < 8; y++) {
        for (int x = 0; x < 10; x++) {
            if (expected.size == 0)
                assertEquals(Float.MAX_VALUE, found.get(x, y), UtilEjml.TEST_F32);
            else if (expected.size == 1)
                assertEquals(0.5f, found.get(x, y), UtilEjml.TEST_F32);
            else if (expected.size == 2)
                assertEquals(1.0f, found.get(x, y), UtilEjml.TEST_F32);
            else {
                assertEquals(expected.data[expected.size / 2], found.get(x, y), UtilEjml.TEST_F32);
            }
            expected.add(expected.size + 0.5f);
        }
    }
}

Example 4 with DogArray_F32

use of org.ddogleg.struct.DogArray_F32 in project BoofCV by lessthanoptimal.

the class ImplConvolveBox method vertical.

public static void vertical(GrayF32 input, GrayF32 output, int radius, @Nullable GrowArray<DogArray_F32> workspaces) {
    workspaces = BoofMiscOps.checkDeclare(workspaces, DogArray_F32::new);
    // CONCURRENT_REMOVE_LINE
    final DogArray_F32 work = workspaces.grow();
    final int kernelWidth = radius * 2 + 1;
    final int backStep = kernelWidth * input.stride;
    // CONCURRENT_BELOW BoofConcurrency.loopBlocks(radius, output.height-radius, kernelWidth, workspaces, (work, y0,y1)->{
    final int y0 = radius, y1 = output.height - radius;
    float[] totals = BoofMiscOps.checkDeclare(work, input.width, false);
    for (int x = 0; x < input.width; x++) {
        int indexIn = input.startIndex + (y0 - radius) * input.stride + x;
        int indexOut = output.startIndex + output.stride * y0 + x;
        float total = 0;
        int indexEnd = indexIn + input.stride * kernelWidth;
        for (; indexIn < indexEnd; indexIn += input.stride) {
            total += input.data[indexIn];
        }
        totals[x] = total;
        output.data[indexOut] = total;
    }
    // change the order it is processed in to reduce cache misses
    for (int y = y0 + 1; y < y1; y++) {
        int indexIn = input.startIndex + (y + radius) * input.stride;
        int indexOut = output.startIndex + y * output.stride;
        for (int x = 0; x < input.width; x++, indexIn++, indexOut++) {
            float total = totals[x] - (input.data[indexIn - backStep]);
            totals[x] = total += input.data[indexIn];
            output.data[indexOut] = total;
        }
    }
// CONCURRENT_INLINE });
}

Example 5 with DogArray_F32

use of org.ddogleg.struct.DogArray_F32 in project BoofCV by lessthanoptimal.

the class ImplConvolveMean method vertical.

public static void vertical(GrayF32 input, GrayF32 output, int offset, int length, @Nullable GrowArray<DogArray_F32> workspaces) {
    workspaces = BoofMiscOps.checkDeclare(workspaces, DogArray_F32::new);
    // CONCURRENT_REMOVE_LINE
    final DogArray_F32 work = workspaces.grow();
    final int backStep = length * input.stride;
    final int offsetEnd = length - offset - 1;
    final float divisor = length;
    // To reduce cache misses it is processed along rows instead of going down columns, which is
    // more natural for a vertical convolution. For parallel processes this requires building
    // a book keeping array for each thread.
    // CONCURRENT_BELOW BoofConcurrency.loopBlocks(offset, output.height - offsetEnd, length, workspaces, (work, y0,y1)->{
    final int y0 = offset, y1 = output.height - offsetEnd;
    float[] totals = BoofMiscOps.checkDeclare(work, input.width, false);
    for (int x = 0; x < input.width; x++) {
        int indexIn = input.startIndex + (y0 - offset) * input.stride + x;
        int indexOut = output.startIndex + output.stride * y0 + x;
        float total = 0;
        int indexEnd = indexIn + input.stride * length;
        for (; indexIn < indexEnd; indexIn += input.stride) {
            total += input.data[indexIn];
        }
        totals[x] = total;
        output.data[indexOut] = (total / divisor);
    }
    // change the order it is processed in to reduce cache misses
    for (int y = y0 + 1; y < y1; y++) {
        int indexIn = input.startIndex + (y + offsetEnd) * input.stride;
        int indexOut = output.startIndex + y * output.stride;
        for (int x = 0; x < input.width; x++, indexIn++, indexOut++) {
            float total = totals[x] - (input.data[indexIn - backStep]);
            totals[x] = total += input.data[indexIn];
            output.data[indexOut] = (total / divisor);
        }
    }
// CONCURRENT_INLINE });
}