class_docstr: `MS Coco Detection <https://cocodataset.org/#detection-2016>`_ Dataset.
  
  It requires the `COCO API to be installed <https://github.com/pdollar/coco/tree/master/PythonAPI>`_.
  
  Args:
      root (string): Root directory where images are downloaded to.
      annFile (string): Path to json annotation file.
      transform (callable, optional): A function/transform that takes in a PIL image
          and returns a transformed version. E.g, ``transforms.PILToTensor``
      target_transform (callable, optional): A function/transform that takes in the
          target and transforms it.
      transforms (callable, optional): A function/transform that takes input sample and its target as entry
          and returns a transformed version.
code: def __getitem__(self, index: int) -> Tuple[Any, Any]:
      id = self.ids[index]
      image = self._load_image(id)
      target = self._load_target(id)
  
      if self.transforms is not None:
          image, target = self.transforms(image, target)
  
      return image, target
  
file_path: vision/torchvision/datasets/coco.py
imports: import os.path
  from typing import Any, Callable, List, Optional, Tuple
  from PIL import Image
  from .vision import VisionDataset
label_desc: Use image node_id 4 for calling the CocoDetection obj's underlying member method code with example usage: obj.__getitem__(index) and returns: image,  target