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 __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
      super().__init__(opts=opts, *args, **kwargs)
  
      # set the collate functions for the dataset
      setattr(
          opts,
          "dataset.collate_fn_name_train",
          "coco_mask_rcnn_collate_fn",
      )
      setattr(
          opts,
          "dataset.collate_fn_name_val",
          "coco_mask_rcnn_collate_fn",
      )
      setattr(
          opts,
          "dataset.collate_fn_name_test",
          "coco_mask_rcnn_collate_fn",
      )
  
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 1 to create a new COCODetectionMaskRCNN object from inherited base classes: COCODetection with example: obj = COCODetectionMaskRCNN(opts)