code: def resize_images(
      path,
      max_workers=defaults.cpus,
      max_size=None,
      recurse=False,
      dest=Path("."),
      n_channels=3,
      ext=None,
      img_format=None,
      resample=BILINEAR,
      resume=None,
      **kwargs,
  ):
      "Resize files on path recursively to dest to max_size"
      path = Path(path)
      if resume is None and dest != Path("."):
          resume = False
      os.makedirs(dest, exist_ok=True)
      files = get_image_files(path, recurse=recurse)
      files = [o.relative_to(path) for o in files]
      parallel(
          resize_image,
          files,
          src=path,
          n_workers=max_workers,
          max_size=max_size,
          dest=dest,
          n_channels=n_channels,
          ext=ext,
          img_format=img_format,
          resample=resample,
          resume=resume,
          **kwargs,
      )
  
file_path: fastai/fastai/vision/utils.py
imports: from __future__ import annotations
  import uuid
  from ..torch_basics import *
  from ..data.all import *
  from .core import *
  from fastdownload import download_url
  from pathlib import Path
label_desc: Use image node_id 8 for calling a global function with example usage: resize_images(path, max_workers, max_size, recurse, dest, n_channels, ext, img_format, resample, resume) without return types