def test_dataset_load_features_sift(tmpdir):
data = data_generation.create_berlin_test_folder(tmpdir)
assert len(data.images()) == 3
data.config['feature_type'] = 'SIFT'
image = data.images()[0]
points = np.random.random((3, 4))
descriptors = np.random.random((128, 4))
colors = np.random.random((3, 4))
data.save_features(image, points, descriptors, colors)
p, d, c = data.load_features(image)
assert np.allclose(p, points)
assert np.allclose(d, descriptors)
assert np.allclose(c, colors)
def test_run_all(tmpdir):
data = data_generation.create_berlin_test_folder(tmpdir)
run_all_commands = [
commands.extract_metadata,
commands.detect_features,
commands.match_features,
commands.create_tracks,
commands.reconstruct,
commands.mesh,
]
for module in run_all_commands:
command = module.Command()
run_command(command, [data.data_path])
reconstruction = data.load_reconstruction()
assert len(reconstruction[0].shots) == 3
assert len(reconstruction[0].points) > 1000
