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https://github.com/MIC-DKFZ/napari-sam

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Host: GitHub
URL: https://github.com/MIC-DKFZ/napari-sam
Owner: MIC-DKFZ
License: apache-2.0
Created: 2023-04-06T11:02:03.000Z (almost 2 years ago)
Default Branch: main
Last Pushed: 2024-03-04T15:41:39.000Z (10 months ago)
Last Synced: 2024-10-03T03:28:56.215Z (3 months ago)
Language: Python
Size: 6.76 MB
Stars: 221
Watchers: 9
Forks: 24
Open Issues: 8
Metadata Files:
- Readme: README.md
- License: LICENSE

Awesome Lists containing this project

awesome-segment-anything-extensions - Repo

README

        # Segment Anything Model (SAM) in Napari

[![License Apache Software License 2.0](https://img.shields.io/pypi/l/napari-sam.svg?color=green)](https://github.com/MIC-DKFZ/napari-sam/raw/main/LICENSE)

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

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

[![tests](https://github.com/MIC-DKFZ/napari-sam/workflows/tests/badge.svg)](https://github.com/MIC-DKFZ/napari-sam/actions)

[![codecov](https://codecov.io/gh/MIC-DKFZ/napari-sam/branch/main/graph/badge.svg)](https://codecov.io/gh/MIC-DKFZ/napari-sam)

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

Segment anything with our **Napari** integration of Meta AI's new **Segment Anything Model (SAM)**!

SAM is the new segmentation system from Meta AI capable of **one-click segmentation of any object**, and now, our plugin neatly integrates this into Napari.

We have already **extended** SAM's click-based foreground separation to full **click-based semantic segmentation and instance segmentation**!

At last, our SAM integration supports both **2D and 3D images**!

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

Everything mode             |  Click-based semantic segmentation mode |  Click-based instance segmentation mode

:-------------------------:|:-------------------------:|:-------------------------:

![](https://github.com/MIC-DKFZ/napari-sam/raw/main/cats_everything.png)  |  ![](https://github.com/MIC-DKFZ/napari-sam/raw/main/cats_semantic.png)  |  ![](https://github.com/MIC-DKFZ/napari-sam/raw/main/cats_instance.png)

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

SAM in Napari demo



https://user-images.githubusercontent.com/3471895/236152620-0de983db-954b-4480-97b9-901ee82f8edd.mp4



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

## Installation

The plugin requires `python>=3.8`, as well as `pytorch>=1.7` and `torchvision>=0.8`. Please follow the instructions here to install both PyTorch and TorchVision dependencies. Installing both PyTorch and TorchVision with CUDA support is strongly recommended.

Install Napari via [pip]:

    

    pip install napari[all]

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

    pip install git+https://github.com/facebookresearch/segment-anything.git

    pip install napari-sam

To install latest development version :

    pip install git+https://github.com/MIC-DKFZ/napari-sam.git

## Usage

Start Napari from the console with:

    napari

Then navigate to `Plugins -> Segment Anything (napari-sam)` and drag & drop an image into Napari. At last create, a labels layer that will be used for the SAM predictions, by clicking in the layer list on the third button.

You can then auto-download one of the available SAM models (this can take 1-2 minutes),  activate one of the annotations & segmentation modes, and you are ready to go!

## 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 [Apache Software License 2.0] license,

"napari-sam" 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/MIC-DKFZ/napari-sam/issues

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

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

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

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

# Acknowledgements





napari-sam is developed and maintained by the Applied Computer Vision Lab (ACVL) of [Helmholtz Imaging](http://helmholtz-imaging.de) 

and the [Division of Medical Image Computing](https://www.dkfz.de/en/mic/index.php) at the 

[German Cancer Research Center (DKFZ)](https://www.dkfz.de/en/index.html).