napari-dinosim 0.1.0

A simple plugin to use DinoSim in napari

DINOSim

A napari plugin for zero-shot image segmentation using DINO vision transformers.

---

Overview

napari-dinoSim allows users to perform zero-shot image segmentation by selecting reference points on an image. The plugin then computes similarity maps based on features extracted by DINOv2 and generates segmentation masks.

For detailed information on the widget's functionality, UI elements, and usage instructions, please refer to the Plugin Documentation. A simple example notebook demonstrating how to use DINOSim via code is also available.

Installation

You can install napari-dinoSim via pip. For GPU support (recommended), ensure you have a compatible PyTorch version installed with CUDA or MPS support.

pip install napari-dinosim

or from source via conda:

# Clone the repository
git clone https://github.com/AAitorG/napari-dinoSim.git
cd napari-dinoSim

# Create and activate the conda environment
conda env create -f environment.yml
conda activate napari-dinosim

Open the Plugin

To launch napari, run the following command in your terminal:

napari

Within the napari interface, locate the DINOSim segmentation plugin in the Plugins section of the top bar.

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 MIT license, "napari-dinoSim" is free and open source software

Citation

Please note that DINOSim is based on a publication. If you use it successfully for your research, please be so kind to cite our work:

@article {Gonzalez-Marfil2025dinosim,
    title = {DINOSim: Zero-Shot Object Detection and Semantic Segmentation on Electron Microscopy Images},
    author = {Gonz{\'a}lez-Marfil, Aitor and G{\'o}mez-de-Mariscal, Estibaliz and Arganda-Carreras, Ignacio},
    journal = {bioRxiv}
    publisher = {Cold Spring Harbor Laboratory},
    url = {https://www.biorxiv.org/content/early/2025/03/13/2025.03.09.642092},
    doi = {10.1101/2025.03.09.642092},
    year = {2025},
}

Issues

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