spateo.segmentation.external.deepcell¶

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

Attributes¶

Application

Functions¶

`_deepcell`(→ numpy.ndarray)	Run DeepCell on the provided image.
`deepcell`(adata[, model, equalize, layer, out_layer])	Run DeepCell to label cells from a staining image.

Module Contents¶

spateo.segmentation.external.deepcell.Application = None[source]¶

spateo.segmentation.external.deepcell._deepcell(img: numpy.ndarray, model: deepcell.applications.Application, **kwargs) → numpy.ndarray[source]¶

Run DeepCell on the provided image.

Parameters:

img: Image as a Numpy array.
model: DeepCell model to use
**kwargs: Additional keyword arguments to Application.predict() function.

Returns:

Numpy array containing cell labels.

spateo.segmentation.external.deepcell.deepcell(adata: anndata.AnnData, model: deepcell.applications.Application | None = None, equalize: float = 2.0, layer: str = SKM.STAIN_LAYER_KEY, out_layer: str | None = None, **kwargs)[source]¶

Run DeepCell to label cells from a staining image.

Parameters:

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

Returns:

Numpy array containing cell labels.