code: def resize_norm_img(img, image_shape, padding=True):
      imgC, imgH, imgW = image_shape
      img = cv2.resize(
          img, (imgW, imgH), interpolation=cv2.INTER_LINEAR
      )
      img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
      img = np.transpose(img, [2, 0, 1]) / 255
      img = np.expand_dims(img, 0)
      img_mean = np.array([0.485, 0.456, 0.406]).reshape((3, 1, 1))
      img_std = np.array([0.229, 0.224, 0.225]).reshape((3, 1, 1))
      img -= img_mean
      img /= img_std
      return img.astype(np.float32)
  
file_path: PaddleDetection/deploy/third_engine/demo_avh/convert_image.py
imports: import os
  import pathlib
  import re
  import sys
  import cv2
  import math
  from PIL import Image
  import numpy
label_desc: Use image node_id 1 for calling a global function with example usage: resize_norm_img(img, image_shape, padding) and returns: img