def test_point_alignment_without_normalization(self):
image = np.random.randint(0, 255, (40, 40, 3)).astype(np.uint8)
point_aligner = PointAligner({'type': 'point_alignment', 'dst_width': 40, 'dst_height': 40, 'normalize': False})
result = point_aligner(
DataRepresentation(image), {'keypoints': PointAligner.ref_landmarks.reshape(-1).tolist()}
).data
transformation_matrix = point_aligner.transformation_from_points(
point_aligner.ref_landmarks * 40, point_aligner.ref_landmarks * 40
)
expected_result = cv2.warpAffine(image, transformation_matrix, (40, 40), flags=cv2.WARP_INVERSE_MAP)
assert np.array_equal(result, expected_result)
def test_point_alignment_to_negative_destination_height_raise_config_error(
self):
with pytest.raises(ValueError):
PointAligner({
'type': 'point_alignment',
'dst_width': 100,
'dst_height': -100
})
def test_point_alignment_both_provided_size_and_dst_height_dst_width_warn(self):
input_image = np.ones((100, 50, 3))
with pytest.warns(None) as warnings:
point_aligner = PointAligner({'type': 'point_alignment', 'dst_width': 100, 'dst_height': 100, 'size': 200})
assert len(warnings) == 1
result = point_aligner(DataRepresentation(input_image), {}).data
assert result.shape == (100, 50, 3)
def test_point_alignment_with_drawing_points(self):
image = np.random.randint(0, 255, (40, 40, 3)).astype(np.uint8)
point_aligner = PointAligner({
'type': 'point_alignment', 'dst_width': 40, 'dst_height': 40, 'draw_points': True
})
result = point_aligner(
DataRepresentation(image), {'keypoints': PointAligner.ref_landmarks.reshape(-1).tolist()}
).data
transformation_matrix = point_aligner.transformation_from_points(
point_aligner.ref_landmarks * 40, point_aligner.ref_landmarks
)
expected_result = image
for point in PointAligner.ref_landmarks:
cv2.circle(expected_result, (int(point[0]), int(point[1])), 5, (255, 0, 0), -1)
expected_result = cv2.warpAffine(expected_result, transformation_matrix, (40, 40), flags=cv2.WARP_INVERSE_MAP)
assert np.array_equal(result, expected_result)
def test_point_alignment_not_provided_points_im_meta(self):
input_image = np.ones((100, 50, 3))
point_aligner = PointAligner({
'type': 'point_alignment',
'dst_width': 100,
'dst_height': 100
})
result = point_aligner(DataRepresentation(input_image), {}).data
assert result.shape == (100, 50, 3)
def test_point_alignment_provided_only_dst_width_raise_config_error(self):
with pytest.raises(ValueError):
PointAligner({'type': 'point_alignment', 'dst_width': 100})
def test_point_alignment_width_negative_size_raise_config_error(self):
with pytest.raises(ConfigError):
PointAligner({'type': 'point_alignment', 'size': -100})
