The napari hub is transitioning to a community-run implementation due to launch in June 2025.
Since October 1, 2024, this version is no longer actively maintained and will not be updated. New plugins and plugin updates will continue to be listed.

Active Learning

napari-activelearning

An active learning plugin for fine tuning of deep learning models.

Workflow step:
Image annotation
Image segmentation

Active learning tools for fine-tuning ML models

License MIT PyPI Python Version tests codecov napari hub

A plugin for running a complete active learning workflow


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

Installation

You can install napari-activelearning via pip:

pip install napari-activelearning

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 MIT license, "napari-activelearning" is free and open source software

Issues

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

Version:

  • 0.0.11

Last updated:

  • 29 November 2024

First released:

  • 31 July 2024

License:

Supported data:

  • Information not submitted

Plugin type:

GitHub activity:

  • Stars: 2
  • Forks: 0
  • Issues + PRs: 0

Python versions supported:

Operating system:

Requirements:

  • napari
  • numpy
  • dask[array]
  • magicgui
  • qtpy
  • scikit-image
  • tensorstore==0.1.59
  • ome-zarr==0.9.0
  • zarr
  • zarrdataset>=0.2.0