class_docstr: Dataset class for the COCO dataset that maps classes to PASCAL VOC classes
  
  Args:
      opts: command-line arguments
class_docstr_tok: ["Dataset","class","for","the","COCO","dataset","that","maps","classes","to","PASCAL","VOC","classes","Args",":","opts",":","command-line","arguments"]
docstr: PASCAL VOC classes names
docstr_tok: ["PASCAL","VOC","classes","names"]
code: def class_names() -> List[str]:
      """PASCAL VOC classes names"""
      return [
          "background",
          "aeroplane",
          "bicycle",
          "bird",
          "boat",
          "bottle",
          "bus",
          "car",
          "cat",
          "chair",
          "cow",
          "diningtable",
          "dog",
          "horse",
          "motorbike",
          "person",
          "potted_plant",
          "sheep",
          "sofa",
          "train",
          "tv_monitor",
      ]
  
file_path: ml-cvnets/data/datasets/segmentation/coco_segmentation.py
imports: import argparse
  import os
  from typing import List, Mapping, Optional, Tuple, Union
  import numpy
  from pycocotools import mask
  from pycocotools.coco import COCO
  from torch import Tensor
  from data.datasets import DATASET_REGISTRY
  from data.datasets.segmentation.base_segmentation import BaseImageSegmentationDataset
label_desc: Use image node_id 5 for calling the COCOSegmentationDataset obj's underlying member method code with example usage: obj.class_names() and returns: list