def test_no_flip_layer(self): a = np.array([[0, 1], [2, 3]]) flip_layer = RandomFlipLayer(flip_axes=[0], flip_probability=0) flip_layer.randomise(spatial_rank=2) transformed_a = flip_layer(a) with self.cached_session() as sess: self.assertTrue(np.array_equal(transformed_a, a))
def test_no_flip_layer(self): a = np.array([[0, 1], [2, 3]]) flip_layer = RandomFlipLayer(flip_axes=[0], flip_probability=0) flip_layer.randomise(spatial_rank=2) transformed_a = flip_layer(a) with self.test_session() as sess: self.assertTrue(np.array_equal(transformed_a, a))
def test_1d_flip(self): a = np.array([[0, 1], [2, 3]]) flip_layer = RandomFlipLayer(flip_axes=[0], flip_probability=1) flip_layer.randomise(spatial_rank=2) transformed_a = flip_layer._apply_transformation(a) with self.test_session() as sess: self.assertTrue( np.array_equal(transformed_a, np.array([[2, 3], [0, 1]])))
def test_2d_flip_layer_1(self): a = np.array([[0, 1], [2, 3]]) a = {'image': a} flip_layer = RandomFlipLayer(flip_axes=[0], flip_probability=1) flip_layer.randomise(spatial_rank=2) transformed_a = flip_layer(a) with self.test_session() as sess: self.assertTrue( np.array_equal(transformed_a['image'], np.array([[2, 3], [0, 1]])))
def test_3d_flip(self): a = np.zeros(24).reshape(2, 3, 4) a[0, 0, 0] = 1 flip_layer = RandomFlipLayer(flip_axes=[0, 1, 2], flip_probability=1) flip_layer.randomise(spatial_rank=3) transformed_a = flip_layer._apply_transformation(a) with self.cached_session() as sess: # cube of zeros with opposite corner as 1 expected_a = np.zeros(24).reshape(2, 3, 4) expected_a[-1, -1, -1] = 1 self.assertTrue(np.array_equal(transformed_a, expected_a))
def test_3d_flip(self): a = np.zeros(24).reshape(2, 3, 4) a[0, 0, 0] = 1 flip_layer = RandomFlipLayer(flip_axes=[0, 1, 2], flip_probability=1) flip_layer.randomise(spatial_rank=3) transformed_a = flip_layer._apply_transformation(a) with self.test_session() as sess: # cube of zeros with opposite corner as 1 expected_a = np.zeros(24).reshape(2, 3, 4) expected_a[-1, -1, -1] = 1 self.assertTrue(np.array_equal(transformed_a, expected_a))