def test_shift_scale_rotate_interpolation(interpolation):
image = np.random.randint(low=0,
high=256,
size=(100, 100, 3),
dtype=np.uint8)
mask = np.random.randint(low=0, high=2, size=(100, 100), dtype=np.uint8)
aug = A.ShiftScaleRotate(shift_limit=(0.2, 0.2),
scale_limit=(1.1, 1.1),
rotate_limit=(45, 45),
interpolation=interpolation,
p=1)
data = aug(image=image, mask=mask)
expected_image = FGeometric.shift_scale_rotate(
image,
angle=45,
scale=2.1,
dx=0.2,
dy=0.2,
interpolation=interpolation,
border_mode=cv2.BORDER_REFLECT_101)
expected_mask = FGeometric.shift_scale_rotate(
mask,
angle=45,
scale=2.1,
dx=0.2,
dy=0.2,
interpolation=cv2.INTER_NEAREST,
border_mode=cv2.BORDER_REFLECT_101)
assert np.array_equal(data["image"], expected_image)
assert np.array_equal(data["mask"], expected_mask)
def test_shift_scale_separate_shift_x_shift_y(image, mask):
aug = A.ShiftScaleRotate(shift_limit=(0.3, 0.3),
shift_limit_y=(0.4, 0.4),
scale_limit=0,
rotate_limit=0,
p=1)
data = aug(image=image, mask=mask)
expected_image = FGeometric.shift_scale_rotate(
image,
angle=0,
scale=1,
dx=0.3,
dy=0.4,
interpolation=cv2.INTER_LINEAR,
border_mode=cv2.BORDER_REFLECT_101)
expected_mask = FGeometric.shift_scale_rotate(
mask,
angle=0,
scale=1,
dx=0.3,
dy=0.4,
interpolation=cv2.INTER_NEAREST,
border_mode=cv2.BORDER_REFLECT_101)
assert np.array_equal(data["image"], expected_image)
assert np.array_equal(data["mask"], expected_mask)
def test_compare_rotate_float_and_shift_scale_rotate_float(float_image):
rotated_img_1 = FGeometric.rotate(float_image, angle=60)
rotated_img_2 = FGeometric.shift_scale_rotate(float_image,
angle=60,
scale=1,
dx=0,
dy=0)
assert np.array_equal(rotated_img_1, rotated_img_2)
def test_scale_from_shift_scale_rotate(target):
img = np.array(
[[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12], [13, 14, 15, 16]],
dtype=np.uint8)
expected = np.array(
[[6, 7, 7, 8], [10, 11, 11, 12], [10, 11, 11, 12], [14, 15, 15, 16]],
dtype=np.uint8)
img, expected = convert_2d_to_target_format([img, expected], target=target)
scaled_img = FGeometric.shift_scale_rotate(img,
angle=0,
scale=2,
dx=0,
dy=0,
interpolation=cv2.INTER_NEAREST,
border_mode=cv2.BORDER_CONSTANT)
assert np.array_equal(scaled_img, expected)
def test_scale_float_from_shift_scale_rotate(target):
img = np.array(
[[0.01, 0.02, 0.03, 0.04], [0.05, 0.06, 0.07, 0.08],
[0.09, 0.10, 0.11, 0.12], [0.13, 0.14, 0.15, 0.16]],
dtype=np.float32,
)
expected = np.array(
[[0.06, 0.07, 0.07, 0.08], [0.10, 0.11, 0.11, 0.12],
[0.10, 0.11, 0.11, 0.12], [0.14, 0.15, 0.15, 0.16]],
dtype=np.float32,
)
img, expected = convert_2d_to_target_format([img, expected], target=target)
scaled_img = FGeometric.shift_scale_rotate(img,
angle=0,
scale=2,
dx=0,
dy=0,
interpolation=cv2.INTER_NEAREST,
border_mode=cv2.BORDER_CONSTANT)
assert_array_almost_equal_nulp(scaled_img, expected)
def albumentations(self, img):
return shift_scale_rotate(img, angle=-45, scale=2, dx=0.2, dy=0.2)
