def test_imgaug_on_multichannel_different():
sample = np.ones((240, 180, 5)) * 0.5
result = augmentation(sample,
mode=DATA_AUGMENTATION_DIFFERENT_EACH_CHANNEL)
assert not np.all(result[0] == result[1])
assert result.shape == (240, 180, 5)
def test_imgaug_on_multichannel_no():
sample = np.random.rand(240, 180, 5)
result = augmentation(sample, mode=DATA_AUGMENTATION_NO)
assert result.shape == (240, 180, 5)
def test_imgaug_on_multichannel_same():
sample = np.ones((240, 180, 5)) * 0.5
result = augmentation(sample, mode=DATA_AUGMENTATION_SAME_PER_CHANNEL)
# assert np.all(result[0] == result[1]) # cannot be ensured currently
assert result.shape == (240, 180, 5)
