code: def test_video_dataset_filenames(self):
      self.create_video_dataset()
      all_filenames = self.filenames
  
      def filename_img_fits_video(filename_img: str):
          for filename_video in all_filenames:
              filename_video = filename_video[: -1 * len(".avi")]
              if filename_video in filename_img:
                  return True
          return False
  
      n_samples = int(len(all_filenames) / 2)
      np.random.seed(42)
      filenames = np.random.choice(
          all_filenames, n_samples, replace=False
      )
  
      dataset = LightlyDataset(
          input_dir=self.input_dir, filenames=filenames
      )
  
      filenames_dataset = dataset.get_filenames()
      for image, target, filename in dataset:
          self.assertIsInstance(image, Image)
          self.assertTrue(filename_img_fits_video(filename))
  
          self.assertIsInstance(filename, str)
          self.assertIn(filename, filenames_dataset)
  
imports: import os
  import shutil
  import tempfile
  import unittest
  from typing import List, Tuple
  import numpy
  import torchvision
  from PIL.Image import Image
  from lightly.data import LightlyDataset
  from lightly.data._utils import check_images
label_desc: Use image node_id 16 for calling the TestLightlyDataset obj's underlying member method code with example usage: obj.test_video_dataset_filenames() and returns: False, True