code: def fetch_atlas_talairach(level_name, data_dir=None, verbose=1):
      """Download the Talairach :term:`Deterministic atlas`.
  
      For more information, see :footcite:t:`talairach_atlas`,
      :footcite:t:`Lancaster2000`,
      and :footcite:t:`Lancaster1997`.
  
      .. versionadded:: 0.4.0
  
      Parameters
      ----------
      level_name : {'hemisphere', 'lobe', 'gyrus', 'tissue', 'ba'}
          Which level of the atlas to use: the hemisphere, the lobe, the gyrus,
          the tissue type or the Brodmann area.
      %(data_dir)s
      %(verbose)s
  
      Returns
      -------
      data : :class:`sklearn.utils.Bunch`
          Dictionary-like object, contains:
  
              - 'maps': 3D :class:`~nibabel.nifti1.Nifti1Image`, image has
                shape ``(141, 172, 110)`` and contains consecutive integer
                values from 0 to the number of regions, which are indices
                in the list of labels.
              - 'labels': :obj:`list` of :obj:`str`. List of region names.
                The list starts with 'Background' (region ID 0 in the image).
              - 'description': :obj:`str`, a short description of the atlas
                and some references.
  
      References
      ----------
      .. footbibliography::
  
      """
      if level_name not in _TALAIRACH_LEVELS:
          raise ValueError(
              f'"level_name" should be one of {_TALAIRACH_LEVELS}'
          )
      talairach_dir = Path(
          get_dataset_dir(
              "talairach_atlas", data_dir=data_dir, verbose=verbose
          )
      )
      img_file = talairach_dir.joinpath(f"{level_name}.nii.gz")
      labels_file = talairach_dir.joinpath(f"{level_name}-labels.json")
      if not img_file.is_file() or not labels_file.is_file():
          _download_talairach(talairach_dir, verbose=verbose)
      atlas_img = check_niimg(str(img_file))
      labels = json.loads(labels_file.read_text("utf-8"))
      description = get_dataset_descr("talairach_atlas").format(
          level_name
      )
      return Bunch(
          maps=atlas_img, labels=labels, description=description
      )
  
imports: import json
  import os
  import re
  import shutil
  import warnings
  import xml.etree.ElementTree
  from pathlib import Path
  from tempfile import mkdtemp
  import nibabel
  import numpy
  import pandas
  from sklearn.utils import Bunch
  from .._utils import check_niimg, fill_doc
  from ..image import get_data, new_img_like, reorder_img
  from ._utils import fetch_files, get_dataset_descr, get_dataset_dir
label_desc: Use image node_id 22 for calling a global function with example usage: fetch_atlas_talairach(level_name, data_dir, verbose) and returns: Bunch