geococo.coco_models
===================

.. py:module:: geococo.coco_models


Classes
-------

.. autoapisummary::

   geococo.coco_models.CocoDataset
   geococo.coco_models.Info
   geococo.coco_models.Image
   geococo.coco_models.Annotation
   geococo.coco_models.Category
   geococo.coco_models.RleDict
   geococo.coco_models.Source


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

.. py:class:: CocoDataset

   Bases: :py:obj:`pydantic.BaseModel`


   .. py:attribute:: info
      :type:  Info


   .. py:attribute:: images
      :type:  List[Image]
      :value: []



   .. py:attribute:: annotations
      :type:  List[Annotation]
      :value: []



   .. py:attribute:: categories
      :type:  List[Category]
      :value: []



   .. py:attribute:: sources
      :type:  List[Source]
      :value: []



   .. py:attribute:: next_image_id
      :type:  int


   .. py:attribute:: next_annotation_id
      :type:  int


   .. py:attribute:: next_source_id
      :type:  int


   .. py:method:: _set_ids(values)


   .. py:method:: add_annotation(annotation)


   .. py:method:: add_image(image)


   .. py:method:: add_source(source_path, date_captured)


   .. py:method:: add_categories(category_ids, category_names, super_names)


   .. py:method:: bump_version(bump_method)


   .. py:method:: verify_used_dir(images_dir)


.. py:class:: Info

   Bases: :py:obj:`pydantic.BaseModel`


   .. py:attribute:: version
      :type:  str
      :value: ''



   .. py:attribute:: year
      :type:  Optional[int]
      :value: None



   .. py:attribute:: description
      :type:  Optional[str]
      :value: None



   .. py:attribute:: contributor
      :type:  Optional[str]
      :value: None



   .. py:attribute:: date_created
      :type:  Optional[datetime.datetime]
      :value: None



.. py:class:: Image

   Bases: :py:obj:`pydantic.BaseModel`


   .. py:attribute:: id
      :type:  int


   .. py:attribute:: width
      :type:  int


   .. py:attribute:: height
      :type:  int


   .. py:attribute:: file_name
      :type:  pathlib.Path


   .. py:attribute:: source_id
      :type:  int


   .. py:attribute:: date_captured
      :type:  datetime.datetime


.. py:class:: Annotation

   Bases: :py:obj:`pydantic.BaseModel`


   .. py:attribute:: id
      :type:  int


   .. py:attribute:: image_id
      :type:  int


   .. py:attribute:: category_id
      :type:  int


   .. py:attribute:: segmentation
      :type:  RleDict


   .. py:attribute:: area
      :type:  float


   .. py:attribute:: bbox
      :type:  List[int]


   .. py:attribute:: iscrowd
      :type:  int


.. py:class:: Category

   Bases: :py:obj:`pydantic.BaseModel`


   .. py:attribute:: id
      :type:  int


   .. py:attribute:: name
      :type:  str


   .. py:attribute:: supercategory
      :type:  str


.. py:class:: RleDict

   Bases: :py:obj:`typing_extensions.TypedDict`


   dict() -> new empty dictionary
   dict(mapping) -> new dictionary initialized from a mapping object's
       (key, value) pairs
   dict(iterable) -> new dictionary initialized as if via:
       d = {}
       for k, v in iterable:
           d[k] = v
   dict(**kwargs) -> new dictionary initialized with the name=value pairs
       in the keyword argument list.  For example:  dict(one=1, two=2)


   .. py:attribute:: size
      :type:  List[int]


   .. py:attribute:: counts
      :type:  bytes


.. py:class:: Source

   Bases: :py:obj:`pydantic.BaseModel`


   .. py:attribute:: id
      :type:  int


   .. py:attribute:: file_name
      :type:  pathlib.Path


   .. py:attribute:: date_captured
      :type:  datetime.datetime