class_docstr: `Oxford 102 Flower <https://www.robots.ox.ac.uk/~vgg/data/flowers/102/>`_ Dataset.
  
  .. warning::
  
      This class needs `scipy <https://docs.scipy.org/doc/>`_ to load target files from `.mat` format.
  
  Oxford 102 Flower is an image classification dataset consisting of 102 flower categories. The
  flowers were chosen to be flowers commonly occurring in the United Kingdom. Each class consists of
  between 40 and 258 images.
  
  The images have large scale, pose and light variations. In addition, there are categories that
  have large variations within the category, and several very similar categories.
  
  Args:
      root (string): Root directory of the dataset.
      split (string, optional): The dataset split, supports ``"train"`` (default), ``"val"``, or ``"test"``.
      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 _check_integrity(self):
      if not (
          self._images_folder.exists() and self._images_folder.is_dir()
      ):
          return False
  
      for id in ["label", "setid"]:
          filename, md5 = self._file_dict[id]
          if not check_integrity(
              str(self._base_folder / filename), md5
          ):
              return False
      return True
  
file_path: vision/torchvision/datasets/flowers102.py
imports: from pathlib import Path
  from typing import Any, Callable, Optional, Tuple
  import PIL.Image
  from .utils import check_integrity, download_and_extract_archive, download_url, verify_str_arg
  from .vision import VisionDataset
label_desc: Use image node_id 5 for calling the Flowers102 obj's underlying member method code with example usage: obj._check_integrity() and returns: True, False, False