code: def export_to_obj(mesh, output_obj_path: str = None):
      if output_obj_path is None:
          output_obj_path = tempfile.NamedTemporaryFile(
              suffix=".obj"
          ).name
  
      verts = mesh.verts.detach().cpu().numpy()
      faces = mesh.faces.cpu().numpy()
  
      vertex_colors = np.stack(
          [
              mesh.vertex_channels[x].detach().cpu().numpy()
              for x in "RGB"
          ],
          axis=1,
      )
      vertices = [
          "{} {} {} {} {} {}".format(*coord, *color)
          for coord, color in zip(
              verts.tolist(), vertex_colors.tolist()
          )
      ]
  
      faces = [
          "f {} {} {}".format(
              str(tri[0] + 1), str(tri[1] + 1), str(tri[2] + 1)
          )
          for tri in faces.tolist()
      ]
  
      combined_data = ["v " + vertex for vertex in vertices] + faces
  
      with open(output_obj_path, "w") as f:
          f.writelines("\n".join(combined_data))
  
imports: import functools
  import importlib
  import inspect
  import io
  import logging
  import multiprocessing
  import os
  import random
  import re
  import struct
  import sys
  import tempfile
  import time
  import unittest
  import urllib.parse
  from contextlib import contextmanager
  from distutils.util import strtobool
  from io import BytesIO, StringIO
  from pathlib import Path
  from typing import List, Optional, Union
  import numpy
  import PIL.Image
  import PIL.ImageOps
  import requests
  from numpy.linalg import norm
  from packaging import version
  from .import_utils import BACKENDS_MAPPING, is_compel_available, is_flax_available, is_note_seq_available, is_onnx_available, is_opencv_available, is_peft_available, is_torch_available, is_torch_version, is_torchsde_available, is_transformers_available
  from .logging import get_logger
label_desc: Use image node_id 28 for calling a global function with example usage: export_to_obj(mesh, output_obj_path) without return types