class_docstr: Base Dataset class for Image Segmentation datasets. Sub-classes must define `ignore_label`
  and `background_idx` variable.
  
  Args:
      opts: Command-line arguments
class_docstr_tok: ["Base","Dataset","class","for","Image","Segmentation","datasets",".","Sub-classes","must","define","`","ignore_label","`","and","`","background_idx","`","variable",".","Args",":","opts",":","Command-line","arguments"]
docstr: Class index to RGB color mapping. The list index corresponds to class id.
  Note that the color list is flattened.
docstr_tok: ["Class","index","to","RGB","color","mapping",".","The","list","index","corresponds","to","class","id",".","Note","that","the","color","list","is","flattened","."]
code: def color_palette() -> List[int]:
      """Class index to RGB color mapping. The list index corresponds to class id.
      Note that the color list is flattened."""
      # Child classes may override this method (optionally)
      return Colormap().get_color_map_list()
  
imports: import argparse
  import os
  from typing import List, Mapping, Optional, Tuple, Union
  import numpy
  import torch
  from PIL import Image
  from torch import Tensor
  from data.datasets.dataset_base import BaseImageDataset
  from data.transforms import image_pil
  from data.transforms.common import Compose
  from utils import logger
  from utils.color_map import Colormap
label_desc: Use image node_id 9 for calling the BaseImageSegmentationDataset obj's underlying member method code with example usage: obj.color_palette() and returns: Colormap