def data_prep_function_train(x, p_transform=p_transform, p_augmentation=p_augmentation, **kwargs): x = np.array(x) x = np.swapaxes(x,0,2) x = x / 255. x = x.astype(np.float32) x = data_transforms.lossless(x, p_augmentation, rng) return x
def data_prep_function_train(x, p_transform=p_transform, p_augmentation=p_augmentation, **kwargs): x = x.convert('RGB') x = np.array(x) x = data_transforms.rescale(x, 0.5) x = np.swapaxes(x, 0, 2) x = x / 255. x -= mean x /= std x = x.astype(np.float32) x = data_transforms.lossless(x, p_augmentation, rng) return x