code: def main(argv):
      if len(argv) > 1:
          raise app.UsageError("Too many command-line arguments.")
      demo_data_path = "/tmp/demo_data/"
      with tf.Graph().as_default():
          d = DemoDataset(demo_data_path)
          dataset = d.as_dataset("test")
          # implement additional processing and batching here
          dataset_output = dataset.make_one_shot_iterator().get_next()
          images = dataset_output["images"]
          labels = dataset_output["labels"]
  
          with tf.Session() as sess:
              images_, labels_ = sess.run([images, labels])
          print(
              "The shape of images_ is %s" % str(images_.shape)
          )  # pylint: disable=superfluous-parens
          print("The shape of labels_ is %s" % str(labels_.shape))
  
imports: from absl import app
  from absl import flags
  from mediapipe.examples.desktop.media_sequence.demo_dataset import DemoDataset
  import tensorflow
label_desc: Use image node_id 1 for calling a global function with example usage: main(argv) without return types