(input_image, which_styles, output_dir)
Stylizes an image into a set of styles and writes them to disk.
Stylizes an image into a set of styles and writes them to disk.
Stylizes an image into a set of styles and writes them to disk .
def _multiple_images(input_image, which_styles, output_dir):
  """Stylizes an image into a set of styles and writes them to disk."""
  with tf.Graph().as_default(), tf.Session() as sess:
    stylized_images = model.transform(
        tf.concat([input_image for _ in range(len(which_styles))], 0),
        alpha=FLAGS.alpha,
        normalizer_params={
            'labels': tf.constant(which_styles),
            'num_categories': FLAGS.num_styles,
            'center': True,
            'scale': True
        })
    _load_checkpoint(sess, FLAGS.checkpoint)

    stylized_images = stylized_images.eval()
    for which, stylized_image in zip(which_styles, stylized_images):
      image_utils.save_np_image(
          stylized_image[None, ...],
          '{}/{}_{}.png'.format(output_dir, FLAGS.output_basename, which))
def _multiple_images ( input_image , which_styles , output_dir ) : with tf . Graph ( ) . as_default ( ) , tf . Session ( ) as sess : stylized_images = model . transform ( tf . concat ( [ input_image for _ in range ( len ( which_styles ) ) ] , 0 ) , alpha = FLAGS . alpha , normalizer_params = { 'labels' : tf . constant ( which_styles ) , 'num_categories' : FLAGS . num_styles , 'center' : True , 'scale' : True } ) _load_checkpoint ( sess , FLAGS . checkpoint ) stylized_images = stylized_images . eval ( ) for which , stylized_image in zip ( which_styles , stylized_images ) : image_utils . save_np_image ( stylized_image [ None , ... ] , '{}/{}_{}.png' . format ( output_dir , FLAGS . output_basename , which ) )