text: # USAGE
  # python evaluate_shape_predictor.py --predictor eye_predictor.dat --xml ibug_300W_large_face_landmark_dataset/labels_ibug_300W_train_eyes.xml
  # python evaluate_shape_predictor.py --predictor eye_predictor.dat --xml ibug_300W_large_face_landmark_dataset/labels_ibug_300W_test_eyes.xml
  
  # import the necessary packages
  import argparse
  import dlib
  
  # construct the argument parser and parse the arguments
  ap = argparse.ArgumentParser()
  ap.add_argument("-p", "--predictor", required=True,
  	help="path to trained dlib shape predictor model")
  ap.add_argument("-x", "--xml", required=True,
  	help="path to input training/testing XML file")
  args = vars(ap.parse_args())
  
  # compute the error over the supplied data split and display it to
  # our screen
  print("[INFO] evaluating shape predictor...")
  error = dlib.test_shape_predictor(args["xml"], args["predictor"])
  print("[INFO] error: {}".format(error))