code: # Copyright (c) 2018 Mengye Ren, Eleni Triantafillou, Sachin Ravi, Jake Snell,
  # Kevin Swersky, Joshua B. Tenenbaum, Hugo Larochelle, Richars S. Zemel.
  #
  # Permission is hereby granted, free of charge, to any person obtaining a copy
  # of this software and associated documentation files (the "Software"), to deal
  # in the Software without restriction, including without limitation the rights
  # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
  # copies of the Software, and to permit persons to whom the Software is
  # furnished to do so, subject to the following conditions:
  #
  # The above copyright notice and this permission notice shall be included in all
  # copies or substantial portions of the Software.
  #
  # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
  # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
  # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
  # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
  # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
  # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
  # SOFTWARE.
  # =============================================================================
  import cv2
  import numpy as np
  import six
  import sys
  import pickle as pkl
  
  from tqdm import tqdm
  
  
  def compress(path, output):
    with np.load(path, mmap_mode="r") as data:
      images = data["images"]
      array = []
      for ii in tqdm(six.moves.xrange(images.shape[0]), desc='compress'):
        im = images[ii]
        im_str = cv2.imencode('.png', im)[1]
        array.append(im_str)
    with open(output, 'wb') as f:
      pkl.dump(array, f, protocol=pkl.HIGHEST_PROTOCOL)
  
  
  def decompress(path, output):
    with open(output, 'rb') as f:
      array = pkl.load(f)
    images = np.zeros([len(array), 84, 84, 3], dtype=np.uint8)
    for ii, item in tqdm(enumerate(array), desc='decompress'):
      im = cv2.imdecode(item, 1)
      images[ii] = im
    np.savez(path, images=images)
  
  
  def main():
    if sys.argv[1] == 'compress':
      compress(sys.argv[2], sys.argv[3])
    elif sys.argv[1] == 'decompress':
      decompress(sys.argv[2], sys.argv[3])
  
  
  if __name__ == '__main__':
    main()
  
apis: numpy.load numpy.savez