new_contents: from __future__ import print_function
  import numpy as np
  from six.moves import cPickle as pickle
  import argparse
  import os
  
  parser = argparse.ArgumentParser()
  parser.add_argument('--pickle', help='Pickle file, check the script readImages to generate this file.', required=True)
  
  args = parser.parse_args()
  
  pickle_file = args.pickle
  
  print("Reading:", pickle_file)
  
  f = open(pickle_file, 'rb')
  data = pickle.load(f)
  train_dataset = data["train_dataset"]
  train_labels = data["train_labels"]
  valid_dataset = data["valid_dataset"]
  valid_labels = data["valid_labels"]
  test_dataset = data["test_dataset"]
  test_labels = data["test_labels"]
  img_head = data["img_head"]
  img_head_label = None
  if "img_head_label" in data:
  	img_head_label = data["img_head_label"]
  
  
  datasplit = {}
  datasplit["train_dataset"] = train_dataset
  datasplit["train_labels"] = train_labels
  datasplit["img_head"] = img_head
  if img_head_label is not None:
  	datasplit["img_head_label"] = img_head_label
  
  print("Split train...")
  f = open(os.path.splitext(pickle_file)[0] + "_train.pickle", 'wb')
  try:
  	pickle.dump(datasplit, f, pickle.HIGHEST_PROTOCOL)
  	f.close()
  except Exception as e:
  	f.close()
  	print("Can't save compressed file, trying without compression")
  	f = open(os.path.splitext(pickle_file)[0] + "_train.pickle", 'wb')
  	pickle.dump(datasplit, f)
  	f.close()
  
  
  print("Split valid and test...")
  datasplit = {}
  datasplit["valid_dataset"] = valid_dataset
  datasplit["valid_labels"] = valid_labels
  datasplit["test_dataset"] = test_dataset
  datasplit["test_labels"] = test_labels
  datasplit["img_head"] = img_head
  if img_head_label is not None:
  	datasplit["img_head_label"] = img_head_label
  
  f = open(os.path.splitext(pickle_file)[0] + "_valid.pickle", 'wb')
  try:
  	pickle.dump(datasplit, f, pickle.HIGHEST_PROTOCOL)
  	f.close()
  except Exception as e:
  	f.close()
  	print("Can't save compressed file, trying without compression")
  	f = open(os.path.splitext(pickle_file)[0] + "_valid.pickle", 'wb')
  	pickle.dump(datasplit, f)
  	f.close()
  
  
subject: Add script to split the data in the pickle files.