code: def test_confounds2df(tmp_path, fmriprep_version):
      """Check auto-detect of confonds from an fMRI nii image."""
      img_nii, _ = create_tmp_filepath(
          tmp_path,
          copy_confounds=True,
          fmriprep_version=fmriprep_version,
      )
      confounds, _ = load_confounds(img_nii)
      assert "trans_x" in confounds.columns
  
imports: import re
  import numpy
  import pandas
  import pytest
  from nibabel import Nifti1Image
  from scipy.stats import pearsonr
  from sklearn.preprocessing import scale
  from nilearn._utils.data_gen import create_fake_bids_dataset
  from nilearn._utils.fmriprep_confounds import to_camel_case
  from nilearn.conftest import _rng
  from nilearn.interfaces.bids import get_bids_files
  from nilearn.interfaces.fmriprep import load_confounds
  from nilearn.interfaces.fmriprep.load_confounds import _check_strategy, _load_single_confounds_file
  from nilearn.interfaces.fmriprep.tests._testing import create_tmp_filepath, get_legal_confound
  from nilearn.maskers import NiftiMasker
label_desc: Use image node_id 10 for calling a global function with example usage: test_confounds2df(tmp_path, fmriprep_version) without return types