code: def process_image(img):
      img = resize_short(img, target_size=256)
      img = crop_image(img, target_size=DATA_DIM, center=True)
      if img.mode != "RGB":
          img = img.convert("RGB")
      img = np.array(img).astype("float32").transpose((2, 0, 1)) / 255
      img -= img_mean
      img /= img_std
      return img
  
file_path: PaddleHub/modules/image/classification/efficientnetb2_imagenet/data_feed.py
imports: import os
  import time
  from collections import OrderedDict
  import numpy
  from PIL import Image
label_desc: Use image node_id 3 for calling a global function with example usage: process_image(img) and returns: img