class_docstr: `WIDERFace <http://shuoyang1213.me/WIDERFACE/>`_ Dataset.
  
  Args:
      root (string): Root directory where images and annotations are downloaded to.
          Expects the following folder structure if download=False:
  
          .. code::
  
              <root>
                  └── widerface
                      ├── wider_face_split ('wider_face_split.zip' if compressed)
                      ├── WIDER_train ('WIDER_train.zip' if compressed)
                      ├── WIDER_val ('WIDER_val.zip' if compressed)
                      └── WIDER_test ('WIDER_test.zip' if compressed)
      split (string): The dataset split to use. One of {``train``, ``val``, ``test``}.
          Defaults to ``train``.
      transform (callable, optional): A function/transform that takes in a PIL image
          and returns a transformed version. E.g, ``transforms.RandomCrop``
      target_transform (callable, optional): A function/transform that takes in the
          target and transforms it.
      download (bool, optional): If true, downloads the dataset from the internet and
          puts it in root directory. If dataset is already downloaded, it is not
          downloaded again.
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code: def __len__(self) -> int:
      return len(self.img_info)
  
file_path: vision/torchvision/datasets/widerface.py
imports: import os
  from os.path import abspath, expanduser
  from typing import Any, Callable, Dict, List, Optional, Tuple, Union
  import torch
  from PIL import Image
  from .utils import download_and_extract_archive, download_file_from_google_drive, extract_archive, verify_str_arg
  from .vision import VisionDataset
label_desc: Use image node_id 3 for calling the WIDERFace obj's underlying member method code with example usage: obj.__len__() and returns: len