Function TEST

test/homography.cpp:224–290

using af::loadImage;

TEST(Homography, CPP) {
    UNSUPPORTED_BACKEND(AF_BACKEND_ONEAPI);
    IMAGEIO_ENABLED_CHECK();

    vector<dim4> inDims;
    vector<string> inFiles;
    vector<vector<float>> gold;

    readImageTests(string(TEST_DIR "/homography/tux.test"), inDims, inFiles,
                   gold);

    inFiles[0].insert(0, string(TEST_DIR "/homography/"));

    const float size_ratio = 0.5f;

    array train_img = loadImage(inFiles[0].c_str(), false);
    array query_img = resize(size_ratio, train_img);
    dim4 tDims      = train_img.dims();

    features feat_train, feat_query;
    array desc_train, desc_query;
    orb(feat_train, desc_train, train_img, 20, 2000, 1.2, 8, true);
    orb(feat_query, desc_query, query_img, 20, 2000, 1.2, 8, true);

    array idx, dist;
    hammingMatcher(idx, dist, desc_train, desc_query, 0, 1);

    array train_idx = where(dist < 30);
    array query_idx = idx(train_idx);

    array feat_train_x           = feat_train.getX()(train_idx);
    array feat_train_y           = feat_train.getY()(train_idx);
    array feat_train_score       = feat_train.getScore()(train_idx);
    array feat_train_orientation = feat_train.getOrientation()(train_idx);
    array feat_train_size        = feat_train.getSize()(train_idx);
    array feat_query_x           = feat_query.getX()(query_idx);
    array feat_query_y           = feat_query.getY()(query_idx);
    array feat_query_score       = feat_query.getScore()(query_idx);
    array feat_query_orientation = feat_query.getOrientation()(query_idx);
    array feat_query_size        = feat_query.getSize()(query_idx);

    array H;
    int inliers = 0;
    homography(H, inliers, feat_train_x, feat_train_y, feat_query_x,
                                  feat_query_y, AF_HOMOGRAPHY_RANSAC, 3.0f, 1000, f32);

    float* gold_t = new float[8];
    for (int i = 0; i < 8; i++) gold_t[i] = 0.f;
    gold_t[2] = tDims[1] * size_ratio;
    gold_t[3] = tDims[1] * size_ratio;
    gold_t[5] = tDims[0] * size_ratio;
    gold_t[6] = tDims[0] * size_ratio;

    array t = perspectiveTransform<float>(train_img.dims(), H);

    float* out_t = new float[4 * 2];
    t.host(out_t);