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