def test_collapse_laplacian_pyramid(): img = load_image(TEST_IMAGE_PATH) pyramid = create_laplacian_image_pyramid(img, 5) display_image_pyramid(pyramid) img_collapsed = collapse_laplacian_pyramid(pyramid) display_image(img, "Original") display_image(img_collapsed, "Recomposed", wait=True) assert (img == img_collapsed).all()
def test_collapse_laplacian_pyramid(): img = load_image(TEST_IMAGE_PATH) pyramid = create_laplacian_image_pyramid(img, 5) display_image_pyramid(pyramid) img_collapsed = collapse_laplacian_pyramid(pyramid) display_image(img, "Original") display_image(img_collapsed, "Recomposed", wait=True) assert (img == img_collapsed).all()
def test_create_laplacian_image_pyramid(): pyramid_depth = 3 img = load_image(TEST_IMAGE_PATH) pyramid = create_laplacian_image_pyramid(img, pyramid_depth) display_image_pyramid(pyramid) means = [np.average(f) for f in pyramid] deviations = [np.std(f) for f in pyramid] assert len(pyramid) == pyramid_depth assert np.std(deviations) > 0.01 # one of the images is just the original sized down photo. there should be significantly more variance in that photo assert pyramid[0].shape == img.shape assert pyramid[1].shape[0] < pyramid[0].shape[0] assert pyramid[2].shape[0] < pyramid[1].shape[0]
def test_create_laplacian_image_pyramid(): pyramid_depth = 3 img = load_image(TEST_IMAGE_PATH) pyramid = create_laplacian_image_pyramid(img, pyramid_depth) display_image_pyramid(pyramid) means = [np.average(f) for f in pyramid] deviations = [np.std(f) for f in pyramid] assert len(pyramid) == pyramid_depth assert np.std( deviations ) > 0.01 # one of the images is just the original sized down photo. there should be significantly more variance in that photo assert pyramid[0].shape == img.shape assert pyramid[1].shape[0] < pyramid[0].shape[0] assert pyramid[2].shape[0] < pyramid[1].shape[0]