code: def process_image(org_im, face):
      pts = (
          np.array(
              [
                  face["left"],
                  face["top"],
                  face["right"],
                  face["top"],
                  face["left"],
                  face["bottom"],
                  face["right"],
                  face["bottom"],
              ]
          )
          .reshape(4, 2)
          .astype(np.float32)
      )
      image_in, M = crop(org_im, pts)
      image_in = image_in / 256.0
      image_in = color_normalize(
          image_in, mean=np.array([0.5, 0.5, 0.5])
      )
      image_in = (
          image_in.astype(np.float32)
          .transpose([2, 0, 1])
          .reshape(-1, 3, 128, 128)
      )
      return image_in
  
file_path: PaddleHub/modules/image/face_detection/pyramidbox_lite_mobile_mask/data_feed.py
imports: import math
  import os
  import time
  from collections import OrderedDict
  import cv2
  import numpy
label_desc: Use image node_id 4 for calling a global function with example usage: process_image(org_im, face) and returns: image_in