class_docstr: python -m pytorch_toolbelt.datasets.providers.inria_aerial inria_dataset
code: def get_test_df(self) -> pd.DataFrame:
      test_images = fs.find_images_in_dir(
          os.path.join(self.test_dir, "images")
      )
      df = pd.DataFrame.from_dict({"images": test_images})
      df["rows"] = 5000
      df["cols"] = 5000
      df["location"] = df["images"].apply(
          lambda x: fs.id_from_fname(x).rstrip("0123456789")
      )
      return df
  
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 7 for calling the InriaAerialImageDataset obj's underlying member method code with example usage: obj.get_test_df() and returns: df