class_docstr: python -m pytorch_toolbelt.datasets.providers.inria_aerial inria_dataset
code: def init_from_folder(
      cls, data_dir: Union[str, Path], download: bool = False
  ):
      data_dir = os.path.expanduser(data_dir)
  
      if download:
          if not cls.download_and_extract(data_dir):
              raise RuntimeError("Download and extract failed")
  
      return cls(os.path.join(data_dir, "AerialImageDataset"))
  
imports: import os
  import subprocess
  import warnings
  from pathlib import Path
  from typing import Union, Optional, Tuple
  import hashlib
  import numpy
  import pandas
  import torch
  import zipfile
  from sklearn.model_selection import GroupKFold
  from pytorch_toolbelt.utils import fs
label_desc: Use image node_id 2 for calling the InriaAerialImageDataset obj's underlying member method code with example usage: obj.init_from_folder(cls, data_dir, download) and returns: cls