code: def _fetch_lfw_people(
      data_folder_path,
      slice_=None,
      color=False,
      resize=None,
      min_faces_per_person=0,
  ):
      """Perform the actual data loading for the lfw people dataset
  
      This operation is meant to be cached by a joblib wrapper.
      """
      # scan the data folder content to retain people with more that
      # `min_faces_per_person` face pictures
      person_names, file_paths = [], []
      for person_name in sorted(listdir(data_folder_path)):
          folder_path = join(data_folder_path, person_name)
          if not isdir(folder_path):
              continue
          paths = [join(folder_path, f) for f in listdir(folder_path)]
          n_pictures = len(paths)
          if n_pictures >= min_faces_per_person:
              person_name = person_name.replace("_", " ")
              person_names.extend([person_name] * n_pictures)
              file_paths.extend(paths)
  
      n_faces = len(file_paths)
      if n_faces == 0:
          raise ValueError(
              "min_faces_per_person=%d is too restrictive"
              % min_faces_per_person
          )
  
      target_names = np.unique(person_names)
      target = np.searchsorted(target_names, person_names)
  
      faces = _load_imgs(file_paths, slice_, color, resize)
  
      # shuffle the faces with a deterministic RNG scheme to avoid having
      # all faces of the same person in a row, as it would break some
      # cross validation and learning algorithms such as SGD and online
      # k-means that make an IID assumption
  
      indices = np.arange(n_faces)
      np.random.RandomState(42).shuffle(indices)
      faces, target = faces[indices], target[indices]
      return faces, target, target_names
  
file_path: catboost/contrib/python/scikit-learn/py2/sklearn/datasets/lfw.py
imports: from os import listdir, makedirs, remove, rename
  from os.path import join, exists, isdir
  from sklearn.utils import deprecated
  import logging
  import numpy
  from .base import get_data_home, Bunch
  from ..externals.joblib import Memory
  from ..externals.six import b
label_desc: Use image node_id 4 for calling a global function with example usage: _fetch_lfw_people(data_folder_path, slice_, color, resize, min_faces_per_person) and returns: faces,  target,  target_names