code: def normPRED(self, d):
      ma = np.max(d)
      mi = np.min(d)
  
      dn = (d - mi) / (ma - mi)
  
      return dn
  
file_path: PaddleHub/modules/image/semantic_segmentation/U2Net/processor.py
imports: import os
  import cv2
  import numpy
label_desc: Use image node_id 4 for calling the Processor obj's underlying member method code with example usage: obj.normPRED(d) and returns: dn