Metadata-Version: 2.4
Name: napari-maskel
Version: 1.3.1
Summary: napari plugin for maskel: skeletonization and feature extraction for branching structures
License-Expression: MIT
Project-URL: Homepage, https://github.com/bionetslab/napari-maskel
Project-URL: Repository, https://github.com/bionetslab/napari-maskel
Project-URL: Documentation, https://bionetslab.github.io/napari-maskel/
Project-URL: Changelog, https://github.com/bionetslab/napari-maskel/releases
Classifier: Framework :: napari
Requires-Python: >=3.13
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: maskel<3.0.0,>=2.0.2
Requires-Dist: pandas
Requires-Dist: napari
Requires-Dist: napari-assistant>=0.6.0
Requires-Dist: napari-simpleitk-image-processing>=0.4.9
Requires-Dist: napari-skimage>=0.6.0
Requires-Dist: pyyaml>=6.0.3
Requires-Dist: superqt
Provides-Extra: dev
Requires-Dist: pytest>=9.0.2; extra == "dev"
Requires-Dist: napari[pyqt6]; extra == "dev"
Provides-Extra: docs
Requires-Dist: mkdocs>=1.6; extra == "docs"
Requires-Dist: mkdocs-material>=9.5; extra == "docs"
Dynamic: license-file

# napari-maskel
##### Simon Wittmann, Dominik Pysch, Stefan Uderhardt, David B. Blumenthal, Anna Möller
[![PyPI version](https://img.shields.io/pypi/v/napari-maskel.svg)](https://pypi.org/project/napari-maskel/)
[![Python version](https://img.shields.io/badge/python-3.13+-blue.svg)](https://www.python.org/)
[![License](https://img.shields.io/badge/license-MIT-green.svg)](LICENSE)

napari plugin for [maskel](https://github.com/bionetslab/maskel): skeletonization and graph-based feature extraction for branching biological structures — vasculature, fibers, neurites, and other network-like objects — with interactive visualization of branches and node features.

## Quick start

1. Install napari itself first if you haven't, with a Qt backend (e.g. `pip install "napari[all]"`), then the plugin: `pip install napari-maskel` (this also installs `maskel`).
2. In napari, open a segmentation mask (2D or 3D) and convert it to a **labels layer**.
3. Run **Analyze mask (Maskel)** from the Plugins menu, pick that layer as the input, and configure the extraction/cleanup parameters.
4. Click **Analyze mask** to add the resulting branches/nodes/summary/radius layers to the viewer, and inspect them with napari's built-in feature table widget.

![3D binary mask analyzed in napari-maskel](https://raw.githubusercontent.com/bionetslab/napari-maskel/main/docs/assets/screenshots/3d-binary-features.png)

See the [full documentation](https://bionetslab.github.io/napari-maskel/) for every configurable parameter, the 2D multi-label workflow, and sharing recipes with the [maskel](https://bionetslab.github.io/maskel/) CLI for batch processing.

## License

napari-maskel is released under the **MIT License**. See [LICENSE](LICENSE) for details.
