new_contents: import numpy as np
  from skimage import measure as ms
  
  
  def ShuffleLabel(Label):
      """
      Shuffles labels in a label image to improve visualization and enhance
      object boundaries.
  
      Parameters
      ----------
      Label : array_like
          A label image generated by segmentation methods.
  
      Returns
      -------
      Shuffled : array_like
          A label image where all values > 0 are randomly shuffled.
  
      See Also
      --------
      CondenseLabel
      """
  
      # get list of unique object labels
      Unique = np.unique(Label.flatten())
  
      # remove background objects (Label == 0)
      Unique = np.delete(Unique, (Unique == 0).nonzero())
  
      # generate shuffled list of object values
      np.random.shuffle(Unique)
  
      # initialize output
      Shuffled = np.zeros(Label.shape)
  
      # get pixel list for each object
      Props = ms.regionprops(Label.astype(np.int))
  
      # fill in new values
      for i in range(len(Unique)):
          print Unique[i]
          Coords = Props[i].coords
          Shuffled[Coords[:, 0], Coords[:, 1]] = Unique[i]
  
      return Shuffled
  
subject: Create ShuffleLabel.py