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: The distance are separate into 4 bins:
  - one bin when no vehicle is in the image
  - three equally sized bins (with thresholds 8, 20 and inf)
docstr_tok: ["The","distance","are","separate","into","4","bins",":","-","one","bin","when","no","vehicle","is","in","the","image","-","three","equally","sized","bins","(","with","thresholds","8",",","20","and","inf",")"]
code: def _get_target_bin(self, distance: float) -> str:
      """
      The distance are separate into 4 bins:
      - one bin when no vehicle is in the image
      - three equally sized bins (with thresholds 8, 20 and inf)
      """
      target = bisect.bisect_left(self.THRESHOLDS, distance)
      return self.LABELS[target]
  
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 6 for calling the KITTIDistance obj's underlying member method code with example usage: obj._get_target_bin(distance) and returns: self