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dilate_labels

patchworks.dilate_labels(fn: Callable[[np.ndarray], np.ndarray], iterations: int = 1, *, use_gpu: bool = False) -> Callable[[np.ndarray], np.ndarray]

Wrap a segmentation callable to grow its labels after each tile.

Applies a single-pass grey dilation to whatever fn returns, before tile_process/stage_tile trim the overlap halo and merge across tile boundaries — so dilated labels still stitch correctly at tile edges.

Parameters:

Name Type Description Default
fn Callable[[ndarray], ndarray]

Any segmentation function with the tile_process/stage_tile contract (one tile in, integer label array out).

 required
iterations int

Pixels to grow each label by (grey-dilation footprint size 2 * iterations + 1, single pass). Default 1. Values <= 0 disable dilation — fn is returned unwrapped.

 1
use_gpu bool

Dilate via cupyx instead of scipy. Independent of whatever backend fn itself uses internally.

 False

Returns:

Type Description
Callable[[ndarray], ndarray]

Picklable function ready for tile_process/stage_tile. If iterations <= 0, this is fn itself.
Source code in src/patchworks/_postprocess.py 
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def dilate_labels(
    fn: Callable[[np.ndarray], np.ndarray],
    iterations: int = 1,
    *,
    use_gpu: bool = False,
) -> Callable[[np.ndarray], np.ndarray]:
    """Wrap a segmentation callable to grow its labels after each tile.

    Applies a single-pass grey dilation to whatever ``fn`` returns, before
    ``tile_process``/``stage_tile`` trim the overlap halo and merge across
    tile boundaries — so dilated labels still stitch correctly at tile
    edges.

    Parameters
    ----------
    fn : Callable[[np.ndarray], np.ndarray]
        Any segmentation function with the ``tile_process``/``stage_tile``
        contract (one tile in, integer label array out).
    iterations : int, optional
        Pixels to grow each label by (grey-dilation footprint size
        ``2 * iterations + 1``, single pass). Default 1. Values ``<= 0``
        disable dilation — ``fn`` is returned unwrapped.
    use_gpu : bool, optional
        Dilate via cupyx instead of scipy. Independent of whatever backend
        ``fn`` itself uses internally.

    Returns
    -------
    Callable[[np.ndarray], np.ndarray]
        Picklable function ready for ``tile_process``/``stage_tile``. If
        ``iterations <= 0``, this is ``fn`` itself.
    """
    if iterations <= 0:
        return fn
    return partial(_run, fn=fn, iterations=iterations, use_gpu=use_gpu)