code: def normalise_zero_one(image):
      """Image normalisation. Normalises image to fit [0, 1] range."""
  
      image = image.astype(np.float32)
  
      minimum = np.min(image)
      maximum = np.max(image)
  
      if maximum > minimum:
          ret = (image - minimum) / (maximum - minimum)
      else:
          ret = image * 0.0
      return ret
  
file_path: DLTK/dltk/io/preprocessing.py
imports: from __future__ import unicode_literals
  from __future__ import print_function
  from __future__ import division
  from __future__ import absolute_import
  import numpy
label_desc: Use image node_id 2 for calling a global function with example usage: normalise_zero_one(image) and returns: ret