spateo.segmentation.external.deepcell
=====================================

.. py:module:: spateo.segmentation.external.deepcell

.. autoapi-nested-parse::

   Use DeepCell for cell identification and labeling.
   https://github.com/vanvalenlab/deepcell-tf

   [Greenwald21]_



Attributes
----------

.. autoapisummary::

   spateo.segmentation.external.deepcell.Application


Functions
---------

.. autoapisummary::

   spateo.segmentation.external.deepcell._deepcell
   spateo.segmentation.external.deepcell.deepcell


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

.. py:data:: Application
   :value: None


.. py:function:: _deepcell(img: numpy.ndarray, model: deepcell.applications.Application, **kwargs) -> numpy.ndarray

   Run DeepCell on the provided image.

   :param img: Image as a Numpy array.
   :param model: DeepCell model to use
   :param \*\*kwargs: Additional keyword arguments to :func:`Application.predict`
                      function.

   :returns: Numpy array containing cell labels.


.. py:function:: deepcell(adata: anndata.AnnData, model: Optional[deepcell.applications.Application] = None, equalize: float = 2.0, layer: str = SKM.STAIN_LAYER_KEY, out_layer: Optional[str] = None, **kwargs)

   Run DeepCell to label cells from a staining image.

   :param adata: Input Anndata
   :param model: DeepCell model to use
   :param equalize: Controls the `clip_limit` argument to the :func:`clahe` function.
                    Set this value to a non-positive value to turn off equalization.
   :param layer: Layer that contains staining image. Defaults to `stain`.
   :param out_layer: Layer to put resulting labels. Defaults to `{layer}_labels`.
   :param \*\*kwargs: Additional keyword arguments to :func:`Application.predict`
                      function.

   :returns: Numpy array containing cell labels.