Metadata-Version: 2.1
Name: napari-floodfill
Version: 0.0.1
Summary: Livewire-based annotation of objects.
Home-page: https://github.com/MalloryWittwer/napari-floodfill.git
Author: Mallory Wittwer
Author-email: mallory.wittwer@epfl.ch
License: BSD-3-Clause
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Topic :: Scientific/Engineering :: Image Processing
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy
Requires-Dist: magicgui
Requires-Dist: qtpy
Requires-Dist: napari[all] >=0.4.16
Requires-Dist: scikit-image
Provides-Extra: testing
Requires-Dist: tox ; extra == 'testing'
Requires-Dist: pytest ; extra == 'testing'
Requires-Dist: pytest-cov ; extra == 'testing'
Requires-Dist: pytest-qt ; extra == 'testing'
Requires-Dist: napari ; extra == 'testing'
Requires-Dist: pyqt5 ; extra == 'testing'

# 🌊 napari-floodfill

Interactive object annotation in Napari using a *flood fill* tool. This tool is based on the [`flood`](https://scikit-image.org/docs/stable/api/skimage.segmentation.html#skimage.segmentation.flood) function of Scikit-image.

<p align="center">
    <img src="https://github.com/MalloryWittwer/napari-floodfill/blob/main/assets/screenshot.gif" height="400">
</p>

## Installation

You can install `napari-floodfill` via [pip]:

    pip install napari-floodfill

## Usage

- Select the plugin from the `Plugins` menu of Napari.
- Open an image to annotate (2D, RGB, 2D+t, or 3D).
- Click on the button "Start flood fill" or press `S`. A new `Labels` layer *Flood fill (current edit)* should appear.
- With the *Flood fill* layer selected, move your cursor arounda nd click on the image to annotate objects.
- Double-click to confirm the annotation of an object and move to the next.

**Options and parameters**
- *Auto-increment label index*: Tick this option to increment the label index every time a new object is annotated (e.g. if you are annotating multiple objects).
- *Intensity range*: Pixels outside of this range will not trigger the flood fill computation. The extremities of the range represent the absolute minimum and maximum of the image. Set the range somewhere to the left if you are annotating dark objects on a bright background, or to the right if you are annotating bright objects.
- *Flood fill tolerance*: Controls the extent of the flood fill. A higher value will fill more pixels. The value selected is relative to the image intensity range.

## Contributing

Contributions are very welcome. Please get in touch if you'd like to be involved in improving or extending the package.

## License

Distributed under the terms of the [BSD-3] license,
"napari-floodfill" is free and open source software

## Issues

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

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

[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

[napari]: https://github.com/napari/napari
[tox]: https://tox.readthedocs.io/en/latest/
[pip]: https://pypi.org/project/pip/
[PyPI]: https://pypi.org/
