LinkinPy Segmentation
linkinpy-segmentation exposes deep-learning segmentation methods as
LinkinPy-compatible command-line tools. The first method uses Cellpose cyto3
for general cell segmentation, following the mAIcrobe idea of first-use model
download and cached inference, but without a napari GUI dependency.
Cellpose Segmentation
linkinpy-cellpose-segment input.tif output_labels.tif --model-type cyto3 --diameter 30
The command stores Cellpose models in:
~/.linkinpy/models/cellpose
On each run it checks whether the requested model files are already present. If they are missing, the command asks Cellpose to download them, then runs inference and writes the segmentation labels as a TIFF image.
LinkinPy Metadata
This package includes linkinpy.yaml, so linkinpy-parse can generate richer
GUI metadata for ImageJ/Fiji and napari.
Development
uv sync
uv run pytest
1 maintainer
Metadata
1 maintainer
Release files for linkinpy-segmentation 0.0.3
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