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
