def test_applies_rotation(self):
deformation_field = deformation_utils.create_2d_deformation_field(
raw_image_center_pos_pix=tf.constant([1.0, 1.0]),
raw_image_element_size_um=tf.constant([1.0, 1.0]),
net_input_spatial_shape=[3, 3],
net_input_element_size_um=tf.constant([1.0, 1.0]),
control_grid_spacings_pix=[2.0, 2.0],
deformations_magnitudes_um=tf.constant([0.0, 0.0]),
rotation_angle=tf.constant(np.pi / 4.),
scale_factors=tf.constant([1.0, 1.0]),
mirror_factors=tf.constant([1, 1]),
shearing_coefs=tf.constant([0.0, 0.0]),
cropping_offset_pix=tf.constant([0.0, 0.0]))
expected_output = np.array([[[-0.4142135624, 1.],
[0.2928932188, 1.7071067812],
[1., 2.4142135624]],
[[0.2928932188, 0.2928932188], [1., 1.],
[1.7071067812, 1.7071067812]],
[[1., -0.4142135624],
[1.7071067812, 0.2928932188],
[2.4142135624, 1]]])
with self.session() as sess:
np.testing.assert_allclose(expected_output,
sess.run(deformation_field),
atol=_ARRAY_COMPARE_TOLERANCE)
def test_oddEvenErrorHandling(self):
with tf.Session():
deform = deformation_utils.create_2d_deformation_field(
np.array([101, 101]) / 2,
raw_image_element_size_um=tf.constant([1., 1.]),
net_input_spatial_shape=[50, 101],
net_input_element_size_um=tf.constant([2., 1.]),
control_grid_spacings_pix=[10, 10],
deformations_magnitudes_um=tf.constant((0., 0.)),
rotation_angle=tf.constant(0.),
scale_factors=tf.constant((1., 1.)),
mirror_factors=tf.constant((1., 1.)),
shearing_coefs=tf.constant((0., 0., 0., 0.)),
cropping_offset_pix=tf.constant((0., 0.)))
with self.assertRaisesWithPredicateMatch(
tf.errors.InvalidArgumentError,
"factor must be odd as input and output size is even"):
deform.eval()
def test_applies_cropping_offset(self):
deformation_field = deformation_utils.create_2d_deformation_field(
raw_image_center_pos_pix=tf.constant([1.0, 1.0]),
raw_image_element_size_um=tf.constant([1.0, 1.0]),
net_input_spatial_shape=[3, 3],
net_input_element_size_um=tf.constant([1.0, 1.0]),
control_grid_spacings_pix=[2.0, 2.0],
deformations_magnitudes_um=tf.constant([0.0, 0.0]),
rotation_angle=tf.constant(0.0),
scale_factors=tf.constant([1.0, 1.0]),
mirror_factors=tf.constant([1, 1]),
shearing_coefs=tf.constant([0.0, 0.0]),
cropping_offset_pix=tf.constant([2.0, 3.0]))
expected_output = np.array([[[2, 3], [2, 4], [2, 5]],
[[3, 3], [3, 4], [3, 5]],
[[4, 3], [4, 4], [4, 5]]])
with self.session() as sess:
np.testing.assert_allclose(expected_output,
sess.run(deformation_field),
atol=_ARRAY_COMPARE_TOLERANCE)
def test_applies_multiple_transforms_together(self):
deformation_field = deformation_utils.create_2d_deformation_field(
raw_image_center_pos_pix=tf.constant([1.0, 1.0]),
raw_image_element_size_um=tf.constant([1.0, 1.0]),
net_input_spatial_shape=[3, 3],
net_input_element_size_um=tf.constant([1.0, 1.0]),
control_grid_spacings_pix=[2.0, 2.0],
deformations_magnitudes_um=tf.constant([0.0, 0.0]),
rotation_angle=tf.constant(np.pi / 2.),
scale_factors=tf.constant([1.0, 2.0]),
mirror_factors=tf.constant([1, -1]),
shearing_coefs=tf.constant([0.1, 0.0]),
cropping_offset_pix=tf.constant([3.0, 5.0]))
expected_output = np.array([[[3., 3.9], [4., 4.], [5., 4.1]],
[[3., 5.9], [4., 6.], [5., 6.1]],
[[3., 7.9], [4., 8.], [5., 8.1]]])
with self.session() as sess:
np.testing.assert_allclose(expected_output,
sess.run(deformation_field),
atol=_ARRAY_COMPARE_TOLERANCE)
