code: def resize_norm_img_abinet(self, img, image_shape):
      imgC, imgH, imgW = image_shape
  
      resized_image = cv2.resize(
          img, (imgW, imgH), interpolation=cv2.INTER_LINEAR
      )
      resized_image = resized_image.astype("float32")
      resized_image = resized_image / 255.0
  
      mean = np.array([0.485, 0.456, 0.406])
      std = np.array([0.229, 0.224, 0.225])
      resized_image = (resized_image - mean[None, None, ...]) / std[
          None, None, ...
      ]
      resized_image = resized_image.transpose((2, 0, 1))
      resized_image = resized_image.astype("float32")
  
      return resized_image
  
imports: import os
  import sys
  from PIL import Image
  import cv2
  import numpy
  import math
  import time
  import traceback
  import paddle
  import tools.infer.utility
  from ppocr.postprocess import build_post_process
  from ppocr.utils.logging import get_logger
  from ppocr.utils.utility import get_image_file_list, check_and_read
label_desc: Use image node_id 10 for calling the TextRecognizer obj's underlying member method code with example usage: obj.resize_norm_img_abinet(img, image_shape) and returns: resized_image