class_docstr: Dataset class for the MS COCO Object Detection using Mask RCNN .
  
  Args:
      opts: Command-line arguments
class_docstr_tok: ["Dataset","class","for","the","MS","COCO","Object","Detection","using","Mask","RCNN",".","Args",":","opts",":","Command-line","arguments"]
code: def add_arguments(
      cls, parser: argparse.ArgumentParser
  ) -> argparse.ArgumentParser:
      if cls != COCODetectionMaskRCNN:
          # Don't re-register arguments in subclasses that don't override `add_arguments()`.
          return parser
  
      group = parser.add_argument_group(title=cls.__name__)
      group.add_argument(
          "--dataset.detection.coco-mask-rcnn.use-lsj-aug",
          action="store_true",
          help="Use large scale jitter augmentation for training Mask RCNN model",
      )
  
      return parser
  
file_path: ml-cvnets/data/datasets/detection/coco_mask_rcnn.py
imports: import argparse
  from typing import List, Mapping, Tuple, Union
  import torch
  from torch import Tensor
  from data.collate_fns import COLLATE_FN_REGISTRY
  from data.datasets import DATASET_REGISTRY
  from data.datasets.detection.coco_base import COCODetection
  from data.transforms import image_pil
  from data.transforms.common import Compose
label_desc: Use image node_id 2 for calling the COCODetectionMaskRCNN obj's underlying member method code with example usage: obj.add_arguments(cls, parser) and returns: parser, parser