def load_images_from_files()

in tcav/activation_generator.py [0:0]

• 32 lines of code
• 10 McCabe index (conditional complexity)

  def load_images_from_files(self,
                             filenames,
                             max_imgs=500,
                             do_shuffle=True,
                             run_parallel=True,
                             shape=(299, 299),
                             num_workers=50):
    """Return image arrays from filenames.

    Args:
      filenames: locations of image files.
      max_imgs: maximum number of images from filenames.
      do_shuffle: before getting max_imgs files, shuffle the names or not
      run_parallel: get images in parallel or not
      shape: desired shape of the image
      num_workers: number of workers in parallelization.

    Returns:
      image arrays

    """
    imgs = []
    # First shuffle a copy of the filenames.
    filenames = filenames[:]
    if do_shuffle:
      np.random.shuffle(filenames)

    if run_parallel:
      pool = multiprocessing.Pool(num_workers)
      imgs = pool.map(
          lambda filename: self.load_image_from_file(filename, shape),
          filenames[:max_imgs])
      pool.close()
      imgs = [img for img in imgs if img is not None]
      if len(imgs) <= 1:
        raise ValueError(
            'You must have more than 1 image in each class to run TCAV.')
    else:
      for filename in filenames:
        img = self.load_image_from_file(filename, shape)
        if img is not None:
          imgs.append(img)
        if len(imgs) >= max_imgs:
          break
      if len(imgs) <= 1:
        raise ValueError(
            'You must have more than 1 image in each class to run TCAV.')

    return np.array(imgs)