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: Read the annotations of the image at index 'idx' to find its target and
  copy it to its associated folder
docstr_tok: ["Read","the","annotations","of","the","image","at","index","'idx","'","to","find","its","target","and","copy","it","to","its","associated","folder"]
code: def __getitem__(self, idx: int) -> bool:
      """
      Read the annotations of the image at index 'idx' to find its target and
      copy it to its associated folder
      """
      image_name = self.image_names[idx]
      distance = self._get_closest_vehicle_distance(
          self.annotation_names[idx]
      )
      target = self._get_target_bin(distance)
      split = "train" if idx in self.training_set_ids else "val"
      shutil.copy(
          src=os.path.join(self.image_folder, image_name),
          dst=os.path.join(self.output_path, split, target, image_name),
      )
      return True
  
file_path: vissl/extra_scripts/datasets/create_kitti_dist_data_files.py
imports: import argparse
  import bisect
  import math
  import os
  import shutil
  from typing import Set
  import numpy
  from torch.utils.data import DataLoader
  from tqdm import tqdm
  from vissl.utils.download import download_and_extract_archive
label_desc: Use image node_id 3 for calling the KITTIDistance obj's underlying member method code with example usage: obj.__getitem__(idx) and returns: True