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"]
code: def __init__(
      self, image_folder: str, annotation_folder: str, output_path: str
  ):
      self.image_folder = image_folder
      self.annotation_folder = annotation_folder
      self.output_path = output_path
      self.image_names = sorted(os.listdir(image_folder))
      self.annotation_names = sorted(os.listdir(annotation_folder))
      self.nb_samples = len(self.image_names)
      self.training_set_ids = self._get_training_set_ids(ratio=0.8)
  
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 1 to create a new KITTIDistance object  with example: obj = KITTIDistance(image_folder, annotation_folder, output_path)