code: def shape_to_np(shape, dtype="int"):
      # initialize the list of (x, y)-coordinates
      coords = np.zeros((shape.num_parts, 2), dtype=dtype)
  
      # loop over all facial landmarks and convert them
      # to a 2-tuple of (x, y)-coordinates
      for i in range(0, shape.num_parts):
          coords[i] = (shape.part(i).x, shape.part(i).y)
  
      # return the list of (x, y)-coordinates
      return coords
  
imports: from collections import OrderedDict
  import numpy
  import cv2
label_desc: Use image node_id 2 for calling a global function with example usage: shape_to_np(shape, dtype) and returns: coords