def test_c_warp_gray():
target_transform = AffineTransform.identity(2).from_vector(initial_params)
warped_im = gray_image.warp_to(template_mask, target_transform,
interpolator='c')
assert(warped_im.shape == gray_template.shape)
assert_allclose(warped_im.pixels, gray_template.pixels)
def setup_error():
target_transform = AffineTransform.identity(2).from_vector(target_params)
original_box = np.array([[0, 0],
[target_shape[0], 0],
[target_shape[0], target_shape[1]],
[0, target_shape[1]]]).T
target_pts = target_transform.apply(original_box.T)
return target_pts, original_box
def residual_wrapper(residual, algorithm, interpolator, expected_error):
image, template, initial_params = setup_conditions(interpolator)
align_algorithm = algorithm(
template, residual, AffineTransform.identity(2).from_vector(
initial_params))
fitting = align_algorithm.align(image, initial_params)
transform = fitting.final_transform
rms_error = compute_fixed_error(transform)
assert_approx_equal(rms_error, expected_error)
def test_cinterp2_warp_multi():
target_transform = AffineTransform.identity(2).from_vector(initial_params)
warped_im = rgb_image.warp_to(template_mask, target_transform,
interpolator='scipy')
assert(warped_im.shape == rgb_template.shape)
assert_allclose(warped_im.pixels, rgb_template.pixels)
def setup_conditions(interpolator):
target_transform = AffineTransform.identity(2).from_vector(target_params)
image_warped = image.warp_to(template_mask, target_transform,
interpolator=interpolator)
return image, image_warped, initial_params
