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))
