:py:mod:`tonic.datasets.ebssa`
==============================

.. py:module:: tonic.datasets.ebssa


Module Contents
---------------

Classes
~~~~~~~

.. autoapisummary::

   tonic.datasets.ebssa.EBSSA




.. py:class:: EBSSA(save_to: str, split: str = 'labelled', transform: collections.abc.Callable | None = None, target_transform: collections.abc.Callable | None = None, transforms: collections.abc.Callable | None = None)


   Bases: :py:obj:`tonic.dataset.Dataset`

   `EBSSA <https://www.westernsydney.edu.au/icns/resources/reproducible_research3/publication_support_materials2/space_imaging>`_

   There are six different splits provided in this dataset. The labelled section of the dataset contains 84 recordings and 84 label files.
   The unlabelled section of the dataset contains 153 recordings in folders marked "Unlabelled".
   If the automatic download from Google Drive fails, please download the file manually from https://drive.google.com/uc?id=1lCh2HWvxEzzaBHT5TlPuyUn6XPM5OVWN
   and put it in a folder called 'EBSSA'. Then point the path to its parent folder. For example, if you put the data file in 'datasets/EBSSA/labelled_ebssa.h5',
   create the dataset object with 'dataset = tonic.datasets.EBSSA('datasets', split='labelled')'

   ::

       @article{afshar2020event,
           title={Event-based object detection and tracking for space situational awareness},
           author={Afshar, Saeed and Nicholson, Andrew Peter and Van Schaik, Andre and Cohen, Gregory},
           journal={IEEE Sensors Journal},
           volume={20},
           number={24},
           pages={15117--15132},
           year={2020},
           publisher={IEEE}
       }

   :param save_to: Location to save files to on disk.
   :type save_to: string
   :param split: Which split to load. One of "labelled", "unlabelled", "all".
   :type split: string
   :param transform: A callable of transforms to apply to the data.
   :type transform: callable, optional
   :param target_transform: A callable of transforms to apply to the targets/labels.
   :type target_transform: callable, optional
   :param transforms: A callable of transforms that is applied to both data and
                      labels at the same time.
   :type transforms: callable, optional

   .. py:attribute:: file_id
      :value: '1lCh2HWvxEzzaBHT5TlPuyUn6XPM5OVWN'

      

   .. py:attribute:: folder_name
      :value: ''

      

   .. py:attribute:: file_name
      :value: 'labelled_ebssa.h5'

      

   .. py:attribute:: sensor_size
      :value: (240, 180, 2)

      

   .. py:attribute:: dtype

      

   .. py:attribute:: ordering

      

   .. py:method:: __getitem__(index: int) -> tuple[Any, Any]

      :returns: (events, target) where target is dict of bounding box and recording id.


   .. py:method:: __len__()


   .. py:method:: download()

      Downloads from a given url, places into target folder and verifies the file hash.