class_docstr: Normalize an image.
  Args:
      mean (list|tuple): The mean value of a data set. Default: [0.5, 0.5, 0.5].
      std (list|tuple): The standard deviation of a data set. Default: [0.5, 0.5, 0.5].
  Raises:
      ValueError: When mean/std is not list or any value in std is 0.
docstr: Args:
      im (np.ndarray): The Image data.
      label (np.ndarray, optional): The label data. Default: None.
  Returns:
      (tuple). When label is None, it returns (im, ), otherwise it returns (im, label).
docstr_tok: ["Args",":","im","(","np.ndarray",")",":","The","Image","data",".","label","(","np.ndarray",",","optional",")",":","The","label","data",".","Default",":","None",".","Returns",":","(","tuple",")",".","When","label","is","None",",","it","returns","(","im",",",")",",","otherwise","it","returns","(","im",",","label",")","."]
code: def __call__(self, im: np.ndarray, label: np.ndarray = None) -> Tuple:
      """
      Args:
          im (np.ndarray): The Image data.
          label (np.ndarray, optional): The label data. Default: None.
      Returns:
          (tuple). When label is None, it returns (im, ), otherwise it returns (im, label).
      """
  
      mean = np.array(self.mean)[np.newaxis, np.newaxis, :]
      std = np.array(self.std)[np.newaxis, np.newaxis, :]
      im = F.normalize(im, mean, std)
  
      if label is None:
          return (im,)
      else:
          return (im, label)
  
imports: import os
  import random
  from typing import Callable, Union, List, Tuple
  import cv2
  import numpy
  from PIL import Image
  import paddlehub.vision.functional
label_desc: Use image node_id 2 for calling the Normalize obj's underlying member method code with example usage: obj.__call__(im, label) and returns: im, im,  label