class_docstr: `Caltech-UCSD Birds-200-2011`_ dataset  with annotated points.
  
  .. _`Caltech-UCSD Birds-200-2011`:
      http://www.vision.caltech.edu/visipedia/CUB-200-2011.html
  
  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:`$CHAINER_DATASET_ROOT/pfnet/chainercv/cub`.
      return_bbox (bool): If :obj:`True`, this returns a bounding box
          around a bird. The default value is :obj:`False`.
      prob_map_dir (string): Path to the root of the probability maps.
          If this is :obj:`auto`, this class will automatically download data
          for you under :obj:`$CHAINER_DATASET_ROOT/pfnet/chainercv/cub`.
      return_prob_map (bool): Decide whether to include a probability map of
          the bird in a tuple served for a query. The default value is
          :obj:`False`.
  
  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:`point`, ":math:`(1, 15, 2)`", :obj:`float32`, ":math:`(y, x)`"
      :obj:`visible`, ":math:`(1, 15)`", :obj:`bool`, --
      :obj:`bbox` [#cub_point_1]_, ":math:`(1, 4)`", :obj:`float32`,             ":math:`(y_{min}, x_{min}, y_{max}, x_{max})`"
      :obj:`prob_map` [#cub_point_2]_, ":math:`(H, W)`", :obj:`float32`,             ":math:`[0, 1]`"
  
  .. [#cub_point_1] :obj:`bb` indicates the location of a bird.         It is available if :obj:`return_bbox = True`.
  .. [#cub_point_2] :obj:`prob_map` indicates how likey a bird is located         at each the pixel.         It is available if :obj:`return_prob_map = True`.
code: def _get_img_and_annotations(self, i):
      img = utils.read_image(
          os.path.join(self.data_dir, "images", self.paths[i]),
          color=True,
      )
  
      pnt = np.array(self._point_dict[i], dtype=np.float32)
      vsble = np.array(self._visible_dict[i], dtype=np.bool)
  
      _, H, W = img.shape
      invisible = np.logical_or(
          np.logical_or(pnt[:, 0] > H, pnt[:, 1] > W),
          np.any(pnt < 0, axis=1),
      )
      vsble[invisible] = False
      return img, pnt[None], vsble[None]
  
file_path: chainercv/chainercv/datasets/cub/cub_keypoint_dataset.py
imports: import collections
  import numpy
  import os
  from chainercv.datasets.cub.cub_utils import CUBDatasetBase
  from chainercv import utils
label_desc: Use image node_id 2 for calling the CUBKeypointDataset obj's underlying member method code with example usage: obj._get_img_and_annotations(i) and returns: img,  pnt,  vsble