| Name | featureforest JSON |
| Version |
0.0.7
JSON |
| download |
| home_page | None |
| Summary | A napari plugin for segmentation using vision transformer features |
| upload_time | 2025-01-14 15:57:04 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.10 |
| license | BSD-3-Clause |
| keywords |
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# Feature Forest
[](https://github.com/juglab/featureforest/blob/main/LICENSE)
[](https://pypi.org/project/featureforest)
[](https://python.org)
[](https://github.com/juglab/featureforest/actions)
[](https://codecov.io/gh/juglab/featureforest)
[](https://napari-hub.org/plugins/featureforest)
**A napari plugin for making image annotation using feature space of vision transformers and random forest classifier.**
We developed a *napari* plugin to train a *Random Forest* model using extracted features of vision foundation models and just a few scribble labels provided by the user as input. This approach can do the segmentation of desired objects almost as well as manual segmentations but in a much shorter time with less manual effort.
----------------------------------
## Documentation
You can check the documentation [here](https://juglab.github.io/featureforest/) (⚠️ work in progress!).
## Installation
To install this plugin you need to use [conda] or [mamba] to create an environment and install the requirements. Use commands below to create the environment and install the plugin:
```bash
git clone https://github.com/juglab/featureforest
cd ./featureforest
```
```bash
# for GPU
conda env create -f ./env_gpu.yml
```
```bash
# if you don't have a GPU
conda env create -f ./env_cpu.yml
```
For more detailed installation guide, check out [here](https://juglab.github.io/featureforest/install/).
## Cite us
Seifi, Mehdi, Damian Dalle Nogare, Juan Battagliotti, Vera Galinova, Ananya Kediga Rao, AI4Life Horizon Europe Programme Consortium, Johan Decelle, Florian Jug, and Joran Deschamps. "FeatureForest: the power of foundation models, the usability of random forests." bioRxiv (2024): 2024-12. [DOI: 10.1101/2024.12.12.628025](https://www.biorxiv.org/content/10.1101/2024.12.12.628025v1.full)
## License
Distributed under the terms of the [BSD-3] license,
"featureforest" 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
[napari]: https://github.com/napari/napari
[tox]: https://tox.readthedocs.io/en/latest/
[pip]: https://pypi.org/project/pip/
[PyPI]: https://pypi.org/
[conda]: https://conda.io/projects/conda/en/latest/index.html
[mamba]: https://mamba.readthedocs.io/en/latest/installation/mamba-installation.html
Raw data
{
"_id": null,
"home_page": null,
"name": "featureforest",
"maintainer": null,
"docs_url": null,
"requires_python": ">=3.10",
"maintainer_email": null,
"keywords": null,
"author": null,
"author_email": "Mehdi Seifi <mehdi.seifi@fht.org>, Vera Galinova <vera.galinova@fht.org>",
"download_url": "https://files.pythonhosted.org/packages/3e/09/eb3fe0b15c5dec922d9e8390fa2b5bc97d871b3ab045663557ee36eaa835/featureforest-0.0.7.tar.gz",
"platform": null,
"description": "# Feature Forest\n\n[](https://github.com/juglab/featureforest/blob/main/LICENSE)\n[](https://pypi.org/project/featureforest)\n[](https://python.org)\n[](https://github.com/juglab/featureforest/actions)\n[](https://codecov.io/gh/juglab/featureforest)\n[](https://napari-hub.org/plugins/featureforest)\n\n**A napari plugin for making image annotation using feature space of vision transformers and random forest classifier.** \nWe developed a *napari* plugin to train a *Random Forest* model using extracted features of vision foundation models and just a few scribble labels provided by the user as input. This approach can do the segmentation of desired objects almost as well as manual segmentations but in a much shorter time with less manual effort.\n\n----------------------------------\n\n## Documentation\nYou can check the documentation [here](https://juglab.github.io/featureforest/) (\u26a0\ufe0f work in progress!).\n\n## Installation\nTo install this plugin you need to use [conda] or [mamba] to create an environment and install the requirements. Use commands below to create the environment and install the plugin:\n```bash\ngit clone https://github.com/juglab/featureforest\ncd ./featureforest\n```\n```bash\n# for GPU\nconda env create -f ./env_gpu.yml\n```\n```bash\n# if you don't have a GPU\nconda env create -f ./env_cpu.yml\n```\n\nFor more detailed installation guide, check out [here](https://juglab.github.io/featureforest/install/).\n\n\n## Cite us\n\nSeifi, Mehdi, Damian Dalle Nogare, Juan Battagliotti, Vera Galinova, Ananya Kediga Rao, AI4Life Horizon Europe Programme Consortium, Johan Decelle, Florian Jug, and Joran Deschamps. \"FeatureForest: the power of foundation models, the usability of random forests.\" bioRxiv (2024): 2024-12. [DOI: 10.1101/2024.12.12.628025](https://www.biorxiv.org/content/10.1101/2024.12.12.628025v1.full)\n\n\n## License\n\nDistributed under the terms of the [BSD-3] license,\n\"featureforest\" is free and open source software\n\n## Issues\n\nIf you encounter any problems, please [file an issue] along with a detailed description.\n\n[napari]: https://github.com/napari/napari\n[Cookiecutter]: https://github.com/audreyr/cookiecutter\n[@napari]: https://github.com/napari\n[MIT]: http://opensource.org/licenses/MIT\n[BSD-3]: http://opensource.org/licenses/BSD-3-Clause\n[GNU GPL v3.0]: http://www.gnu.org/licenses/gpl-3.0.txt\n[GNU LGPL v3.0]: http://www.gnu.org/licenses/lgpl-3.0.txt\n[Apache Software License 2.0]: http://www.apache.org/licenses/LICENSE-2.0\n[Mozilla Public License 2.0]: https://www.mozilla.org/media/MPL/2.0/index.txt\n[cookiecutter-napari-plugin]: https://github.com/napari/cookiecutter-napari-plugin\n\n[napari]: https://github.com/napari/napari\n[tox]: https://tox.readthedocs.io/en/latest/\n[pip]: https://pypi.org/project/pip/\n[PyPI]: https://pypi.org/\n[conda]: https://conda.io/projects/conda/en/latest/index.html\n[mamba]: https://mamba.readthedocs.io/en/latest/installation/mamba-installation.html\n",
"bugtrack_url": null,
"license": "BSD-3-Clause",
"summary": "A napari plugin for segmentation using vision transformer features",
"version": "0.0.7",
"project_urls": {
"homepage": "https://featureforest.github.io/",
"repository": "https://github.com/juglab/featureforest"
},
"split_keywords": [],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "4d306ec71f987fa91332b1bbe62f050bdf3f0333657a37a96e67b560bb2623fe",
"md5": "7801e3007a32de116a64ca4f880d9cf9",
"sha256": "40466e59ce7557769a7bb1fd455e191453bd67a68471ef3a1ba4f6aa647db51e"
},
"downloads": -1,
"filename": "featureforest-0.0.7-py3-none-any.whl",
"has_sig": false,
"md5_digest": "7801e3007a32de116a64ca4f880d9cf9",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.10",
"size": 48661,
"upload_time": "2025-01-14T15:57:02",
"upload_time_iso_8601": "2025-01-14T15:57:02.434211Z",
"url": "https://files.pythonhosted.org/packages/4d/30/6ec71f987fa91332b1bbe62f050bdf3f0333657a37a96e67b560bb2623fe/featureforest-0.0.7-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "3e09eb3fe0b15c5dec922d9e8390fa2b5bc97d871b3ab045663557ee36eaa835",
"md5": "4227dad34d3e9143e6883c43f7f8da97",
"sha256": "c77145eb8dc841d30c8ded51d897ce5f810f5839bc61de885e95b10f5c8ea142"
},
"downloads": -1,
"filename": "featureforest-0.0.7.tar.gz",
"has_sig": false,
"md5_digest": "4227dad34d3e9143e6883c43f7f8da97",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.10",
"size": 1504808,
"upload_time": "2025-01-14T15:57:04",
"upload_time_iso_8601": "2025-01-14T15:57:04.417961Z",
"url": "https://files.pythonhosted.org/packages/3e/09/eb3fe0b15c5dec922d9e8390fa2b5bc97d871b3ab045663557ee36eaa835/featureforest-0.0.7.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2025-01-14 15:57:04",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "juglab",
"github_project": "featureforest",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"tox": true,
"lcname": "featureforest"
}
