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)