def test_solarize(dtype):
max_value = F.MAX_VALUES_BY_DTYPE[dtype]
if dtype == np.dtype("float32"):
img = np.arange(2**10, dtype=np.float32) / (2**10)
img = img.reshape([2**5, 2**5])
else:
max_count = 1024
count = min(max_value + 1, 1024)
step = max(1, (max_value + 1) // max_count)
shape = [int(np.sqrt(count))] * 2
img = np.arange(0, max_value + 1, step, dtype=dtype).reshape(shape)
for threshold in [
0, max_value // 3, max_value // 3 * 2, max_value, max_value + 1
]:
check_img = img.copy()
cond = check_img >= threshold
check_img[cond] = max_value - check_img[cond]
result_img = F.solarize(img, threshold=threshold)
assert np.all(np.isclose(result_img, check_img))
assert np.min(result_img) >= 0
assert np.max(result_img) <= max_value
def test_solarize_equal_to_pillow():
img_cv = np.arange(256).astype(np.uint8).reshape([16, 16])
img_pil = Image.fromarray(img_cv)
for i in range(256):
result_albu = F.solarize(img_cv, i)
result_pil = np.array(ImageOps.solarize(img_pil, i))
assert np.all(result_albu == result_pil)
def albumentations(self, img):
return albumentations.solarize(img)
def albumentations_fn(self, image, arg):
return F.solarize(image, threshold=arg)
