class_docstr: Dataset used to parallelize the transformation of the dataset via a DataLoader
class_docstr_tok: ["Dataset","used","to","parallelize","the","transformation","of","the","dataset","via","a","DataLoader"]
docstr: Find all the video paths and the corresponding labels
docstr_tok: ["Find","all","the","video","paths","and","the","corresponding","labels"]
code: def _init_dataset(self):
      """
      Find all the video paths and the corresponding labels
      """
      for label in os.listdir(self.split_path):
          label_path = os.path.join(self.split_path, label)
          if not os.path.isdir(label_path):
              continue
  
          for file_name in os.listdir(label_path):
              file_ext = os.path.splitext(file_name)[1]
              if file_ext == ".mp4":
                  self.video_paths.append(
                      os.path.join(label_path, file_name)
                  )
                  self.video_labels.append(label)
  
file_path: vissl/extra_scripts/datasets/create_k700_data_files.py
imports: import argparse
  import os
  from typing import Optional, Tuple
  import numpy
  from PIL import Image
  from torch.utils.data import DataLoader
  from torchvision.datasets.utils import download_url
  from tqdm import tqdm
  from vissl.utils.download import download_and_extract_archive
  from vissl.utils.io import save_file
label_desc: Use image node_id 2 for calling the KineticsMiddleFrameDataset obj's underlying member method code with example usage: obj._init_dataset() without return types