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https://github.com/zoccoler/napari-signal-classifier


https://github.com/zoccoler/napari-signal-classifier

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# napari-signal-classifier



[![License BSD-3](https://img.shields.io/pypi/l/napari-signal-classifier.svg?color=green)](https://github.com/zoccoler/napari-signal-classifier/raw/main/LICENSE)

[![PyPI](https://img.shields.io/pypi/v/napari-signal-classifier.svg?color=green)](https://pypi.org/project/napari-signal-classifier)

[![Python Version](https://img.shields.io/pypi/pyversions/napari-signal-classifier.svg?color=green)](https://python.org)

[![tests](https://github.com/zoccoler/napari-signal-classifier/workflows/tests/badge.svg)](https://github.com/zoccoler/napari-signal-classifier/actions)

[![codecov](https://codecov.io/gh/zoccoler/napari-signal-classifier/branch/main/graph/badge.svg)](https://codecov.io/gh/zoccoler/napari-signal-classifier)

[![napari hub](https://img.shields.io/endpoint?url=https://api.napari-hub.org/shields/napari-signal-classifier)](https://napari-hub.org/plugins/napari-signal-classifier)



A napari plugin that classifies annotated signals stored in a table in the .features of a Labels layer using scikit-learn RandomForest classifier.



It also provides a sub-signal classifier that can be used to classify sub-signals inside time-series. First it detects sub-sginals with a template matching algorithm and then classifies them also using scikit-learn RandomForest classifier.



This plugin employs and works in synergy with the [napari-signal-selector plugin](https://github.com/zoccoler/napari-signal-selector?tab=readme-ov-file#napari-signal-selector). Take a look at it to see how to annotate signals in a plotter linked to a napari Labels layer with the .features attribute.



# Quick Demo



## Napari Signal Classifier



![demo](https://github.com/zoccoler/napari-signal-classifier/raw/main/images/signal_classifier_demo.gif)



## Napari Sub-Signal Classifier



![demo](https://github.com/zoccoler/napari-signal-classifier/raw/main//images/sub_signal_classifier_demo.gif)



----------------------------------



This [napari] plugin was generated with [Cookiecutter] using [@napari]'s [cookiecutter-napari-plugin] template.



## Installation



You can install `napari-signal-classifier` via [pip]:



    pip install napari-signal-classifier



To install latest development version :



    pip install git+https://github.com/zoccoler/napari-signal-classifier.git



## Contributing



Contributions are very welcome. Tests can be run with [tox], please ensure

the coverage at least stays the same before you submit a pull request.



## License



Distributed under the terms of the [BSD-3] license,

"napari-signal-classifier" is free and open source software



## Issues



If you encounter any problems, please [file an issue] along with a detailed description.



[napari]: https://github.com/napari/napari

[Cookiecutter]: https://github.com/audreyr/cookiecutter

[@napari]: https://github.com/napari

[MIT]: http://opensource.org/licenses/MIT

[BSD-3]: http://opensource.org/licenses/BSD-3-Clause

[GNU GPL v3.0]: http://www.gnu.org/licenses/gpl-3.0.txt

[GNU LGPL v3.0]: http://www.gnu.org/licenses/lgpl-3.0.txt

[Apache Software License 2.0]: http://www.apache.org/licenses/LICENSE-2.0

[Mozilla Public License 2.0]: https://www.mozilla.org/media/MPL/2.0/index.txt

[cookiecutter-napari-plugin]: https://github.com/napari/cookiecutter-napari-plugin



[file an issue]: https://github.com/zoccoler/napari-signal-classifier/issues



[napari]: https://github.com/napari/napari

[tox]: https://tox.readthedocs.io/en/latest/

[pip]: https://pypi.org/project/pip/

[PyPI]: https://pypi.org/