class_docstr: Dataset class for the ADE20K dataset
  
  The structure of the dataset should be something like this: ::
  
  ADEChallengeData2016/annotations/training/*.png
  ADEChallengeData2016/annotations/validation/*.png
  
  ADEChallengeData2016/images/training/*.jpg
  ADEChallengeData2016/images/validation/*.jpg
  
  Args:
      opts: Command-line arguments
class_docstr_tok: ["Dataset","class","for","the","ADE20K","dataset","The","structure","of","the","dataset","should","be","something","like","this",":",":",":","ADEChallengeData2016\/annotations\/training\/","*",".png","ADEChallengeData2016\/annotations\/validation\/","*",".png","ADEChallengeData2016\/images\/training\/","*",".jpg","ADEChallengeData2016\/images\/validation\/","*",".jpg","Args",":","opts",":","Command-line","arguments"]
docstr: Class index (index of a list corresponds to class id) to class name
docstr_tok: ["Class","index","(","index","of","a","list","corresponds","to","class","id",")","to","class","name"]
code: def class_names() -> List[str]:
      """Class index (index of a list corresponds to class id) to class name"""
      return [
          "background",
          "wall",
          "building",
          "sky",
          "floor",
          "tree",
          "ceiling",
          "road",
          "bed ",
          "windowpane",
          "grass",
          "cabinet",
          "sidewalk",
          "person",
          "earth",
          "door",
          "table",
          "mountain",
          "plant",
          "curtain",
          "chair",
          "car",
          "water",
          "painting",
          "sofa",
          "shelf",
          "house",
          "sea",
          "mirror",
          "rug",
          "field",
          "armchair",
          "seat",
          "fence",
          "desk",
          "rock",
          "wardrobe",
          "lamp",
          "bathtub",
          "railing",
          "cushion",
          "base",
          "box",
          "column",
          "signboard",
          "chest of drawers",
          "counter",
          "sand",
          "sink",
          "skyscraper",
          "fireplace",
          "refrigerator",
          "grandstand",
          "path",
          "stairs",
          "runway",
          "case",
          "pool table",
          "pillow",
          "screen door",
          "stairway",
          "river",
          "bridge",
          "bookcase",
          "blind",
          "coffee table",
          "toilet",
          "flower",
          "book",
          "hill",
          "bench",
          "countertop",
          "stove",
          "palm",
          "kitchen island",
          "computer",
          "swivel chair",
          "boat",
          "bar",
          "arcade machine",
          "hovel",
          "bus",
          "towel",
          "light",
          "truck",
          "tower",
          "chandelier",
          "awning",
          "streetlight",
          "booth",
          "television receiver",
          "airplane",
          "dirt track",
          "apparel",
          "pole",
          "land",
          "bannister",
          "escalator",
          "ottoman",
          "bottle",
          "buffet",
          "poster",
          "stage",
          "van",
          "ship",
          "fountain",
          "conveyer belt",
          "canopy",
          "washer",
          "plaything",
          "swimming pool",
          "stool",
          "barrel",
          "basket",
          "waterfall",
          "tent",
          "bag",
          "minibike",
          "cradle",
          "oven",
          "ball",
          "food",
          "step",
          "tank",
          "trade name",
          "microwave",
          "pot",
          "animal",
          "bicycle",
          "lake",
          "dishwasher",
          "screen",
          "blanket",
          "sculpture",
          "hood",
          "sconce",
          "vase",
          "traffic light",
          "tray",
          "ashcan",
          "fan",
          "pier",
          "crt screen",
          "plate",
          "monitor",
          "bulletin board",
          "shower",
          "radiator",
          "glass",
          "clock",
          "flag",
      ]
  
file_path: ml-cvnets/data/datasets/segmentation/ade20k.py
imports: import argparse
  import os
  from typing import List
  import numpy
  from data.datasets import DATASET_REGISTRY
  from data.datasets.segmentation.base_segmentation import BaseImageSegmentationDataset
label_desc: Use image node_id 4 for calling the ADE20KDataset obj's underlying member method code with example usage: obj.class_names() and returns: list