code: def _process_second_level_input(second_level_input):
      """Process second_level_input."""
      if isinstance(second_level_input, pd.DataFrame):
          return _process_second_level_input_as_dataframe(
              second_level_input
          )
      elif hasattr(second_level_input, "__iter__") and isinstance(
          second_level_input[0], FirstLevelModel
      ):
          return _process_second_level_input_as_firstlevelmodels(
              second_level_input
          )
      else:
          return mean_img(second_level_input), None
  
imports: import sys
  import time
  from warnings import warn
  import numpy
  import pandas
  from joblib import Memory
  from nibabel import Nifti1Image
  from sklearn.base import clone
  from nilearn._utils import fill_doc, stringify_path
  from nilearn._utils.niimg_conversions import check_niimg
  from nilearn.glm._base import BaseGLM
  from nilearn.glm.contrasts import compute_contrast, expression_to_contrast_vector
  from nilearn.glm.first_level import FirstLevelModel, run_glm
  from nilearn.glm.first_level.design_matrix import make_second_level_design_matrix
  from nilearn.glm.regression import RegressionResults, SimpleRegressionResults
  from nilearn.image import mean_img
  from nilearn.maskers import NiftiMasker
  from nilearn.mass_univariate import permuted_ols
label_desc: Use image node_id 17 for calling a global function with example usage: _process_second_level_input(second_level_input) and returns: _process_second_level_input_as_dataframe, _process_second_level_input_as_firstlevelmodels, mean_img,  None