code: def __init__(self, args, sess, generated_image):
      self.sess = sess
  
      self.model_path = args.landmark_model
      n_landmarks = 84
      FLAGS.n_landmarks = 84
  
      net_model = networks.DNFaceMultiView("")
      with tf.variable_scope("net"):
          (
              self.lms_heatmap_prediction,
              states,
          ) = net_model._build_network(
              generated_image,
              datas=None,
              is_training=False,
              n_channels=n_landmarks,
          )
          self.pts_predictions = tf_heatmap_to_lms(
              self.lms_heatmap_prediction
          )
          variables = tf.all_variables()
          variables_to_restore = [
              v for v in variables if v.name.split("/")[0] == "net"
          ]
          self.saver = tf.train.Saver(variables_to_restore)
  
imports: import tensorflow
  from external.landmark_detector import networks
  from external.landmark_detector.flags import FLAGS
label_desc: Use image node_id 1 to create a new Landmark_Handler object  with example: obj = Landmark_Handler(args, sess, generated_image)