docstr: Normalize the image.
  
  Operators:
      1.(optional) Scale the image to [0,1]
      2. Each pixel minus mean and is divided by std
docstr_tok: ["Normalize","the","image",".","Operators",":","1",".","(","optional",")","Scale","the","image","to","[","0,1","]","2",".","Each","pixel","minus","mean","and","is","divided","by","std"]
code: def __call__(self, im):
      """Normalize the image.
  
      Operators:
          1.(optional) Scale the image to [0,1]
          2. Each pixel minus mean and is divided by std
      """
      im = im.astype(np.float32, copy=False)
      if self.is_channel_first:
          mean = np.array(self.mean)[:, np.newaxis, np.newaxis]
          std = np.array(self.std)[:, np.newaxis, np.newaxis]
      else:
          mean = np.array(self.mean)[np.newaxis, np.newaxis, :]
          std = np.array(self.std)[np.newaxis, np.newaxis, :]
      if self.is_scale:
          im = im / 255.0
      im -= mean
      im /= std
      return im
  
imports: from __future__ import absolute_import
  from __future__ import print_function
  from __future__ import division
  import os
  import random
  import cv2
  import numpy
  from PIL import Image
label_desc: Use image node_id 2 for calling the NormalizeImage obj's underlying member method code with example usage: obj.__call__(im) and returns: im