code: def _read_image_buffer(v):
      # read bytes sent via REST API and convert to image tensor
      # in [channels, height, width] format
      byte_string = io.BytesIO(v.file.read()).read()
      image = decode_image(
          torch.frombuffer(byte_string, dtype=torch.uint8)
      )
      return image
  
imports: import argparse
  import io
  import json
  import logging
  import os
  import sys
  import tempfile
  import pandas
  import torch
  from torchvision.io import decode_image
  from ludwig.api import LudwigModel
  from ludwig.constants import AUDIO, COLUMN
  from ludwig.contrib import add_contrib_callback_args
  from ludwig.globals import LUDWIG_VERSION
  from ludwig.utils.print_utils import get_logging_level_registry, print_ludwig
  from ludwig.utils.server_utils import NumpyJSONResponse
label_desc: Use image node_id 3 for calling a global function with example usage: _read_image_buffer(v) and returns: image