def test_motion_blur_samples_transform(ks, img_6x6_rgb):
blur = slt.Blur(p=1, blur_type="mo", k_size=ks)
random.seed(42)
dc = slc.DataContainer(img_6x6_rgb, "I")
for i in range(100):
blur.sample_transform(dc)
if isinstance(ks, int):
assert blur.state_dict["motion_kernel"].shape[0] == ks
else:
assert blur.state_dict["motion_kernel"].shape == ks
def test_blur_samples_correctly(blur_t, k_size, sigma, img_6x6_rgb):
dc = slc.DataContainer(img_6x6_rgb, "I")
trf = slt.Blur(blur_type=blur_t, k_size=k_size, gaussian_sigma=sigma)
trf.sample_transform(dc)
if isinstance(k_size, int):
k_size = (k_size, )
if sigma is None:
sigma = 1
assert trf.state_dict["k_size"] in k_size
assert trf.state_dict["sigma"] == sigma
def create_train_transforms(size):
return solt.Stream([
slt.JPEGCompression(p=0.5,quality_range=(60,100)),
slt.Noise(p=0.25),
slt.Brightness(),
slt.Contrast(),
slt.Flip(),
slt.Rotate90(),
solt.SelectiveStream([
slt.GammaCorrection(gamma_range=0.5, p=1),
slt.Noise(gain_range=0.1, p=1),
slt.SaltAndPepper(),
slt.Blur(),
], n=3),
slt.Rotate(angle_range=(-10, 10), p=0.5),
slt.Resize((size,size)),
])
def test_complex_transform_serialization():
stream = slc.Stream([
slt.Flip(axis=1, p=0.5),
slc.SelectiveStream([
slt.Rotate(angle_range=(-45, -45), p=1, padding="r"),
slt.Rotate90(1, p=1),
slt.Rotate(angle_range=(45, 45), p=1, padding="r"),
]),
slt.Crop((350, 350)),
slc.SelectiveStream([
slt.GammaCorrection(gamma_range=0.5, p=1),
slt.Noise(gain_range=0.1, p=1),
slt.Blur()
],
n=3),
slt.Projection(
affine_transforms=slc.Stream([
slt.Rotate(angle_range=(-45, 45), p=1),
slt.Scale(range_x=(0.8, 1.5),
range_y=(0.8, 1.5),
p=1,
same=False),
]),
v_range=(1e-4, 1e-3),
p=1,
),
slc.SelectiveStream(
[
slt.CutOut(40, p=1),
slt.CutOut(30, p=1),
slt.CutOut(20, p=1),
slt.CutOut(40, p=1),
slc.Stream(),
slc.Stream(),
slc.Stream(),
],
n=3,
),
])
assert slu.from_yaml(stream.to_yaml()).to_yaml() == slu.from_yaml(
stream.to_yaml()).to_yaml()
def test_blur_arguments(blur_t, k_size, sigma, to_catch, img_6x6_rgb):
dc = slc.DataContainer(img_6x6_rgb, "I")
with pytest.raises(to_catch):
b = slt.Blur(blur_type=blur_t, k_size=k_size, gaussian_sigma=sigma)
b.sample_transform(dc)