class_docstr: normalize image such as substract mean, divide std
      
class_docstr_tok: ["normalize","image","such","as","substract","mean",",","divide","std"]
code: def __init__(
      self, scale=None, mean=None, std=None, order="chw", **kwargs
  ):
      if isinstance(scale, str):
          scale = eval(scale)
      self.scale = np.float32(
          scale if scale is not None else 1.0 / 255.0
      )
      mean = mean if mean is not None else [0.485, 0.456, 0.406]
      std = std if std is not None else [0.229, 0.224, 0.225]
  
      shape = (3, 1, 1) if order == "chw" else (1, 1, 3)
      self.mean = np.array(mean).reshape(shape).astype("float32")
      self.std = np.array(std).reshape(shape).astype("float32")
  
imports: import numpy
  import paddle
  import os
  import cv2
  import glob
label_desc: Use image node_id 1 to create a new NormalizeImage object from inherited base classes: object with example: obj = NormalizeImage(scale, mean, std, order)