code: def image_transform(instance):
      """converts the input image of Bytes Array into Tensor
  
      Args:
          instance (dict): The request input to make an inference
          request for.
  
      Returns:
          list: Returns the data key's value and converts that into a list
          after converting it into a tensor
      """
      byte_array = base64.b64decode(instance["data"])
      image = Image.open(io.BytesIO(byte_array))
      instance["data"] = image_processing(image).tolist()
      logging.info(instance)
      return instance
  
file_path: serve/kubernetes/kserve/image_transformer/image_transformer/image_transformer.py
imports: import base64
  import io
  import json
  import logging
  from typing import Dict, List
  import kserve
  import torchvision.transforms
  import tornado
  from kserve.model import Model
  from PIL import Image
label_desc: Use image node_id 1 for calling a global function with example usage: image_transform(instance) and returns: instance