Feature Forest

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 (⚠️ work in progress!).

Installation

We provided install.sh for Linux & Mac OS users, and install.bat for Windows users.
First you need to clone the repo:

git clone https://github.com/juglab/featureforest
cd ./featureforest

Now run the installation script:

# Linux or Mac OS
sh ./install.sh

# Windows
./install.bat

For developers that want to contribute to FeatureForest, you need to use this command to install the dev dependencies:

pip install -U "featureforest[dev]"

And make sure you have pre-commit installed in your environment, before committing changes:

pre-commit install

For more detailed installation guide, check out here.

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

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.