def test_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.Rotate(limit=(45, 45), interpolation=interpolation, p=1)
data = aug(image=image, mask=mask)
expected_image = F.rotate(image, 45, interpolation=interpolation, border_mode=cv2.BORDER_REFLECT_101)
expected_mask = F.rotate(mask, 45, 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_maybe_process_in_chunks():
image = np.random.randint(0, 256, (100, 100, 6), np.uint8)
for i in range(1, image.shape[-1] + 1):
before = image[:, :, :i]
after = F.rotate(before, angle=1)
assert before.shape == after.shape
def apply(self, image, mask, rand_h, rand_w, angle, **params):
image_masked = image.copy()
h, w = image_masked.shape[:2]
mask = F.rotate(mask, angle) if self.rotate[1] > 0 else mask
mask = mask[:, :, np.newaxis] if image_masked.ndim == 3 else mask
image_masked *= mask[rand_h:rand_h + h,
rand_w:rand_w + w].astype(image_masked.dtype)
return image_masked
def test_compare_rotate_float_and_shift_scale_rotate_float(float_image):
rotated_img_1 = F.rotate(float_image, angle=60)
rotated_img_2 = F.shift_scale_rotate(float_image,
angle=60,
scale=1,
dx=0,
dy=0)
assert np.array_equal(rotated_img_1, rotated_img_2)
def apply(self, image, mask, rand_h, rand_w, angle, **params):
h, w = image.shape[:2]
if self.fill_value == 255: image = 255 - image
mask = F.rotate(mask, angle) if self.rotate[1] > 0 else mask
mask = mask[:, :, np.newaxis] if image.ndim == 3 else mask
print(np.mean(mask))
image *= mask[rand_h:rand_h + h, rand_w:rand_w + w].astype(image.dtype)
return 255 - image if self.fill_value == 255 else image
def apply(self, image, mask, rand_h, rand_w, angle, **params):
h, w = image.shape[:2]
# print(f'h : {h}, w :{w}')
mask = F.rotate(mask, angle) if self.rotate[1] > 0 else mask
mask = mask[:,:,np.newaxis] if image.ndim == 3 else mask
# print('mask shape : ', mask[rand_h:rand_h+h, rand_w:rand_w+w].astype(image.dtype).shape)
# print('img shape : ', image.shape)
try:
image *= mask[rand_h:rand_h+h, rand_w:rand_w+w].astype(image.dtype)
except :
pass
return image
def apply(self, image, **params):
h, w = image.shape[:2]
if self.masks is None: self.init_masks(h, w)
mask = rng.choice(self.masks)
rand_h = np.random.randint(self.hh - h)
rand_w = np.random.randint(self.hh - w)
angle = np.random.randint(self.rotate[0],
self.rotate[1]) if self.rotate[1] > 0 else 0
mask = F.rotate(mask, angle) if self.rotate[1] > 0 else mask
mask = mask[:, :, np.newaxis] if image.ndim == 3 else mask
image *= mask[rand_h:rand_h + h, rand_w:rand_w + w].astype(image.dtype)
return image
def apply(self, image, mask, rand_h, rand_w, angle, **params):
h, w = image.shape[:2]
mask = F.rotate(mask, angle) if self.rotate[1] > 0 else mask
mask = mask[:, :, np.newaxis] if image.ndim == 3 else mask
# image = np.maximum( image, mask[rand_h : rand_h +h, rand_w: rand_w + w].astype(image.dtype) )
bool_arr = np.random.randint(0, 2, size=image.shape, dtype=bool)
if self.mode != 1:
for i in range(bool_arr.shape[2]):
bool_arr[:, :, i] = np.squeeze(mask[rand_h:rand_h + h,
rand_w:rand_w +
w] == self.fill_val)
else:
for i in range(bool_arr.shape[2]):
bool_arr[:, :, i] = np.squeeze(mask[rand_h:rand_h + h,
rand_w:rand_w +
w] == self.fill_val)
image[bool_arr] = self.fill_val
return image
def apply(self, image, mask, rand_h, rand_w, angle, **params):
mask = F.rotate(mask, angle) if self.rotate[1] > 0 else mask
if (image.shape[2] == 3) | (image.shape[2] == 1): #channel last
h, w = image.shape[:2]
mask = mask[:, :, np.newaxis]
image *= mask[rand_h:rand_h + h,
rand_w:rand_w + w].astype(image.dtype)
else: # channel first
h, w = image.shape[1:]
mask = mask[np.newaxis, :, :]
image *= mask[:, rand_h:rand_h + h,
rand_w:rand_w + w].astype(image.dtype)
# h, w = image.shape[:2]
# mask = F.rotate(mask, angle) if self.rotate[1] > 0 else mask
# mask = mask[:,:,np.newaxis] if image.ndim == 3 else mask
# mask = mask[:, :, np.newaxis] if (image.shape[2]==3) & (image.shape[2]==1) else mask[np.newaxis, :, :]
# image *= mask[rand_h:rand_h+h, rand_w:rand_w+w].astype(image.dtype)
return image
def albumentations(self, img):
return albumentations.rotate(img, angle=-45)
def test_compare_rotate_and_shift_scale_rotate(image):
rotated_img_1 = F.rotate(image, angle=60)
rotated_img_2 = F.shift_scale_rotate(image, angle=60, scale=1, dx=0, dy=0)
assert np.array_equal(rotated_img_1, rotated_img_2)
def apply(self, img, **params):
return [F.rotate(img, angle) for angle in self.angles]
def albumentations(self, img):
return albumentations.rotate(img, angle=-45)
def apply(self, image, mask, rand_h, rand_w, angle, **kwargs):
h, w = image.shape[:2]
mask = F.rotate(mask, angle) if self.rotate[1] > 0 else mask
mask = mask[..., np.newaxis] if image.ndim == 3 else mask
image *= mask[rand_h:rand_h + h, rand_w:rand_w + w].astype(image.dtype)
return image
def apply_to_mask(self, img, **params):
return functional.rotate(img, self.angle, cv2.INTER_NEAREST,
self.border_mode, self.mask_value)
def apply(self, img, interpolation=cv2.INTER_LINEAR, **params):
return functional.rotate(img, self.angle, interpolation,
self.border_mode, self.value)
