Metadata-Version: 2.4
Name: napari-adaptive-painting
Version: 0.0.3
Summary: Propagate label annotations in Napari.
Author-email: Mallory Wittwer <mallory.wittwer@epfl.ch>
License: Copyright (c) 2023, Mallory Wittwer
        All rights reserved.
        
        Redistribution and use in source and binary forms, with or without
        modification, are permitted provided that the following conditions are met:
        
        * Redistributions of source code must retain the above copyright notice, this
          list of conditions and the following disclaimer.
        
        * Redistributions in binary form must reproduce the above copyright notice,
          this list of conditions and the following disclaimer in the documentation
          and/or other materials provided with the distribution.
        
        * Neither the name of copyright holder nor the names of its
          contributors may be used to endorse or promote products derived from
          this software without specific prior written permission.
        
        THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
        AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
        IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
        DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
        FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
        DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
        SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
        CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
        OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
        OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
        
Project-URL: homepage, https://github.com/EPFL-Center-for-Imaging/napari-adaptive-painting
Project-URL: repository, https://github.com/EPFL-Center-for-Imaging/napari-adaptive-painting
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Scientific/Engineering :: Image Processing
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: napari[all]>=0.4.16
Requires-Dist: qtpy
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: scikit-image
Dynamic: license-file

![EPFL Center for Imaging logo](https://imaging.epfl.ch/resources/logo-for-gitlab.svg)
# 🖌️ napari-adaptive-painting

Propagate label annotations in Napari.

<p align="center">
    <img src="https://github.com/EPFL-Center-for-Imaging/napari-adaptive-painting/blob/main/assets/screenshot.gif" height="400">
</p>


## Installation

You can install `napari-adaptive-painting` via [pip](https://pypi.org/project/pip/):

    pip install napari-adaptive-painting

## Usage

- Select the plugin from the `Plugins` menu of Napari.
- Open an image to annotate (2D+t or 3D).
- Open, load, or create a `Labels` layer for annotating objects.
- Select the instance label to adaptively paint from the layer controls (tip: use the `Pick mode` to quickly select labels) or draw a new one (in the visible 2D plane).
- Click on *Start*.
- Move along the Z axis (which can also represent time). Whenever the Z plane changes, the label mask is adapted to match the new Z plane.

**Known limitations**

- The plugin won't work if the layers are transposed. Stick to the original layer orientation.

## Contributing

Contributions are 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](http://opensource.org/licenses/BSD-3-Clause) license, "napari-adaptive-painting" is free and open source software.

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

This [napari](https://github.com/napari/napari) plugin is an output of a collaborative project between the [EPFL Center for Imaging](https://imaging.epfl.ch/) and the [De Palma Lab](https://www.epfl.ch/labs/depalma-lab/) in 2024.
