def test_normalize_std_image(): pixels = np.ones((120, 120, 3)) pixels[..., 0] = 0.5 pixels[..., 1] = 0.2345 image = Image(pixels) image.normalize_std_inplace() assert_allclose(np.mean(image.pixels), 0, atol=1e-10) assert_allclose(np.std(image.pixels), 1)
def test_normalize_std_image_per_channel(): pixels = np.random.randn(120, 120, 3) pixels[..., 1] *= 9 pixels[..., 0] += -3 pixels[..., 2] /= 140 image = Image(pixels) image.normalize_std_inplace(mode='per_channel') assert_allclose( np.mean(image.as_vector(keep_channels=True), axis=0), 0, atol=1e-10) assert_allclose( np.std(image.as_vector(keep_channels=True), axis=0), 1)
def test_normalize_std_image_per_channel(): pixels = np.random.randn(120, 120, 3) pixels[..., 1] *= 9 pixels[..., 0] += -3 pixels[..., 2] /= 140 image = Image(pixels) image.normalize_std_inplace(mode='per_channel') assert_allclose(np.mean(image.as_vector(keep_channels=True), axis=0), 0, atol=1e-10) assert_allclose(np.std(image.as_vector(keep_channels=True), axis=0), 1)