def test_invalid_padding(self):
msg = ("padding should be one of \"REFLECT\", \"CONSTANT\", "
"or \"SYMMETRIC\".")
image = tf.ones(shape=(1, 28, 28, 1))
with self.assertRaisesRegexp(ValueError, msg):
median_filter2d(image, padding="TEST")
def test_invalid_image(self):
msg = "image should be either 3 or 4-dimensional."
for image_shape in [(28, 28), (16, 28, 28, 1, 1)]:
with self.subTest(dim=len(image_shape)):
with self.assertRaisesRegexp(ValueError, msg):
median_filter2d(tf.ones(shape=image_shape))
def test_image_vs_filter(self):
tf_img = tf.zeros([3, 4, 3], tf.int32)
m = tf_img.shape[0]
no = tf_img.shape[1]
ch = tf_img.shape[2]
filter_shape = (3, 5)
with self.assertRaises(ValueError):
median_filter2d(tf_img, filter_shape)
def test_invalid_filter_shape(self):
msg = ("The `filter_shape` argument must be a tuple of 2 integers.")
image = tf.ones(shape=(1, 28, 28, 1))
for filter_shape in [(3, 3, 3), (3, None, 3), None]:
with self.subTest(filter_shape=filter_shape):
with self.assertRaisesRegexp(ValueError, msg):
median_filter2d(image, filter_shape=filter_shape)
def test_invalid_filter_shape_median(filter_shape):
image = tf.ones(shape=(1, 28, 28, 1))
with pytest.raises(ValueError):
median_filter2d(image, filter_shape=filter_shape)
filter_shape = None
with pytest.raises(TypeError):
mean_filter2d(image, filter_shape=filter_shape)
def test_invalid_image(self):
msg = "`image` must be 2/3/4D tensor"
errors = (ValueError, tf.errors.InvalidArgumentError)
for image_shape in [(1, ), (16, 28, 28, 1, 1)]:
with self.subTest(dim=len(image_shape)):
with self.assertRaisesRegexp(errors, msg):
image = tf.ones(shape=image_shape)
self.evaluate(median_filter2d(image))
def test_dimension(self):
tf.compat.v1.disable_eager_execution()
tf_img = tf.compat.v1.placeholder(tf.int32, shape=[3, 4, None])
tf_img1 = tf.compat.v1.placeholder(tf.int32, shape=[3, None, 4])
tf_img2 = tf.compat.v1.placeholder(tf.int32, shape=[None, 3, 4])
with self.assertRaises(TypeError):
median_filter2d(tf_img)
median_filter2d(tf_img1)
median_filter2d(tf_img2)
def _validate_median_filter2d(self,
inputs,
expected_values,
filter_shape=(3, 3)):
values_op = median_filter2d(inputs)
with self.test_session(use_gpu=False) as sess:
if tf.executing_eagerly():
expected_values = expected_values.numpy()
values = values_op.numpy()
else:
expected_values = expected_values.eval()
values = values_op.eval()
self.assertShapeEqual(values, inputs)
self.assertShapeEqual(expected_values, values_op)
self.assertAllClose(expected_values, values)
def test_filter_tuple(self):
tf_img = tf.zeros([3, 4, 3], tf.int32)
for filter_shape in [3, 3.5, 'dt', None]:
with self.assertRaisesRegexp(TypeError,
'Filter shape must be a tuple'):
median_filter2d(tf_img, filter_shape)
filter_shape = (3, 3, 3)
msg = ('Filter shape must be a tuple of 2 integers. '
'Got %s values in tuple' % len(filter_shape))
with self.assertRaisesRegexp(ValueError, msg):
median_filter2d(tf_img, filter_shape)
msg = 'Size of the filter must be Integers'
for filter_shape in [(3.5, 3), (None, 3)]:
with self.assertRaisesRegexp(TypeError, msg):
median_filter2d(tf_img, filter_shape)
def test_invalid_padding_median():
image = tf.ones(shape=(1, 28, 28, 1))
with pytest.raises(ValueError):
median_filter2d(image, padding="TEST")
def test_invalid_image_median(image_shape):
with pytest.raises((ValueError, tf.errors.InvalidArgumentError)):
image = tf.ones(shape=image_shape)
median_filter2d(image)
def test_filter_value(self):
tf_img = tf.zeros([3, 4, 3], tf.int32)
with self.assertRaises(ValueError):
median_filter2d(tf_img, (4, 3))
def test_filter_tuple(self):
tf_img = tf.zeros([3, 4, 3], tf.int32)
with self.assertRaisesRegexp(TypeError,
'Filter shape must be a tuple'):
median_filter2d(tf_img, 3)
median_filter2d(tf_img, 3.5)
median_filter2d(tf_img, 'dt')
median_filter2d(tf_img, None)
filter_shape = (3, 3, 3)
msg = 'Filter shape must be a tuple of 2 integers. ' \
'Got %s values in tuple' % len(filter_shape)
with self.assertRaisesRegexp(ValueError, msg):
median_filter2d(tf_img, filter_shape)
with self.assertRaisesRegexp(TypeError,
'Size of the filter must be Integers'):
median_filter2d(tf_img, (3.5, 3))
median_filter2d(tf_img, (None, 3))
def test_dimension(self):
for image_shape in [(3, 4, None), (3, None, 4), (None, 3, 4)]:
with self.assertRaises(TypeError):
tf_img = tf.compat.v1.placeholder(tf.int32, shape=image_shape)
median_filter2d(tf_img)
def _validate_median_filter2d(self,
inputs,
expected_values,
filter_shape=(3, 3)):
output = median_filter2d(inputs, filter_shape)
self.assertAllClose(output, expected_values)
def test_invalid_padding(self):
msg = 'padding should be one of "REFLECT", "CONSTANT", ' 'or "SYMMETRIC".'
image = tf.ones(shape=(1, 28, 28, 1))
with self.assertRaisesRegexp(ValueError, msg):
median_filter2d(image, padding="TEST")
