class_docstr: Dataset class for `Stanford Online Products Dataset`_.
  
  .. _`Stanford Online Products Dataset`:
      http://cvgl.stanford.edu/projects/lifted_struct
  
  The :obj:`split` selects train and test split of the dataset as done in
  [#]_. The train split contains the first 11318 classes and the test
  split contains the remaining 11316 classes.
  
  .. [#] Hyun Oh Song, Yu Xiang, Stefanie Jegelka, Silvio Savarese.
      `Deep Metric Learning via Lifted Structured Feature Embedding        <https://arxiv.org/abs/1511.06452>`_. arXiv 2015.
  
  Args:
      data_dir (string): Path to the root of the training data. If this is
          :obj:`auto`, this class will automatically download data for you
          under :obj:`$CHAINER_DATASET_ROOT/pfnet/chainercv/online_products`.
      split ({'train', 'test'}): Select a split of the dataset.
  
  This dataset returns the following data.
  
  .. csv-table::
      :header: name, shape, dtype, format
  
      :obj:`img`, ":math:`(3, H, W)`", :obj:`float32`,         "RGB, :math:`[0, 255]`"
      :obj:`label`, scalar, :obj:`int32`, ":math:`[0, \#class - 1]`"
      :obj:`super_label`, scalar, :obj:`int32`,         ":math:`[0, \#super\_class - 1]`"
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code: def _get_super_label(self, i):
      return self.super_class_ids[i]
  
file_path: chainercv/chainercv/datasets/online_products/online_products_dataset.py
imports: import filelock
  import numpy
  import os
  from chainer.dataset import download
  from chainercv.chainer_experimental.datasets.sliceable import GetterDataset
  from chainercv import utils
label_desc: Use image node_id 5 for calling the OnlineProductsDataset obj's underlying member method code with example usage: obj._get_super_label(i) and returns: self