{"name":"napari-dinosim","display_name":"DINOSim Segmentation","visibility":"public","icon":"","categories":["Annotation","Segmentation","Acquisition"],"schema_version":"0.2.1","on_activate":null,"on_deactivate":null,"contributions":{"commands":[{"id":"napari-dinosim.make_container_widget","title":"DINOSim Widget","python_name":"napari_dinosim:DINOSim_widget","short_title":null,"category":null,"icon":null,"enablement":null}],"readers":null,"writers":null,"widgets":[{"command":"napari-dinosim.make_container_widget","display_name":"DINOSim Widget","autogenerate":false}],"sample_data":null,"themes":null,"menus":{},"submenus":null,"keybindings":null,"configuration":[]},"package_metadata":{"metadata_version":"2.4","name":"napari-dinosim","version":"0.1.3","dynamic":["license-file"],"platform":null,"supported_platform":null,"summary":"A simple plugin to use DINOSim in napari","description":"# DINOSim\n\n[![License: MIT](https://img.shields.io/pypi/l/napari-dinosim.svg?color=blue)](https://github.com/AAitorG/napari-DINOSim/raw/main/LICENSE)\n[![biorxiv](https://img.shields.io/badge/bioRxiv-Paper-bd2635.svg)](https://doi.org/10.1101/2025.03.09.642092)\n[![PyPI](https://img.shields.io/pypi/v/napari-DINOSim.svg?color=green)](https://pypi.org/project/napari-DINOSim)\n[![Python Version](https://img.shields.io/pypi/pyversions/napari-DINOSim.svg?color=green)](https://python.org)\n[![tests](https://github.com/AAitorG/napari-DINOSim/workflows/tests/badge.svg)](https://github.com/AAitorG/napari-DINOSim/actions)\n[![napari hub](https://img.shields.io/endpoint?url=https://api.napari-hub.org/shields/napari-dinosim)](https://napari-hub.org/plugins/napari-dinosim)\n\n![DINOSim-simple](docs/DINOSim-simplest.png)\n\nA [napari] plugin for zero-shot image segmentation using DINOv2 vision transformers.\n\n----------------------------------\n\n## Overview\n\n`napari-DINOSim` enables zero-shot image segmentation by selecting reference points on an image. The plugin leverages DINOv2's powerful feature extraction capabilities to compute similarity maps and generate segmentation masks.\n\nFor detailed information about the widget's functionality, UI elements, and usage instructions, please refer to the [Plugin Documentation](./docs/plugin_documentation.md). A simple [example notebook](./src/DINOSim_example.ipynb) demonstrating how to use DINOSim programmatically is also available.\n\n## Installation\n\nYou can install `napari-DINOSim` via [pip]:\n\n```sh\npip install napari-dinosim\n```\n\nor from source using [conda]:\n\n```bash\n# Clone the repository\ngit clone https://github.com/AAitorG/napari-DINOSim.git\ncd napari-DINOSim\n\n# Create and activate the conda environment\nconda env create -f environment.yml\nconda activate napari-dinosim\n```\n\n## Usage\n\nTo launch napari, run the following command in your terminal:\n\n```sh\nnapari\n```\n\nWithin the napari interface, locate and click the `DINOSim segmentation` plugin in the Plugins section of the top bar. You can then:\n1. Drag and drop your image into the napari viewer\n2. Select points on the objects you want to segment\n3. The plugin will automatically generate segmentation masks based on your selections\n\nFor more detailed instructions and examples, please refer to our [Plugin Documentation](./docs/plugin_documentation.md).\n\n## License\n\nDistributed under the terms of the [MIT] license,\n\"napari-DINOSim\" is free and open source software.\n\n## Citation\n\nPlease note that DINOSim is based on a [publication](https://doi.org/10.1101/2025.03.09.642092). If you use DINOSim in your research, please be so kind to cite our work:\n\n```bibtex\n@article {Gonzalez-Marfil2025dinosim,\n    title = {DINOSim: Zero-Shot Object Detection and Semantic Segmentation on Electron Microscopy Images},\n    author = {Gonz{\\'a}lez-Marfil, Aitor and G{\\'o}mez-de-Mariscal, Estibaliz and Arganda-Carreras, Ignacio},\n    journal = {bioRxiv},\n    publisher = {Cold Spring Harbor Laboratory},\n    url = {https://www.biorxiv.org/content/early/2025/03/13/2025.03.09.642092},\n    doi = {10.1101/2025.03.09.642092},\n    year = {2025}\n}\n```\n\n## Contributing\n\nContributions are very welcome! Tests can be run with [tox]. Please ensure the test coverage at least stays the same before submitting a pull request.\n\n## Issues\n\nIf you encounter any problems, please [file an issue](https://github.com/AAitorG/napari-DINOSim/issues) along with a detailed description.\n\n[napari]: https://github.com/napari/napari\n[MIT]: http://opensource.org/licenses/MIT\n[tox]: https://tox.readthedocs.io/en/latest/\n[pip]: https://pypi.org/project/pip/\n[conda]: https://docs.conda.io/en/latest/miniconda.html\n","description_content_type":"text/markdown","keywords":null,"home_page":null,"download_url":null,"author":"Aitor Gonzalez-Marfil","author_email":"aitorgacad@gmail.com","maintainer":null,"maintainer_email":null,"license":"MIT License\n\nCopyright (c) 2025 Aitor González-Marfil\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE.\n","classifier":["Development Status :: 3 - Alpha","Framework :: napari","Intended Audience :: Developers","Intended Audience :: Science/Research","License :: OSI Approved :: MIT License","Operating System :: OS Independent","Programming Language :: Python","Programming Language :: Python :: 3","Programming Language :: Python :: 3 :: Only","Programming Language :: Python :: 3.9","Programming Language :: Python :: 3.10","Programming Language :: Python :: 3.11","Programming Language :: Python :: 3.12","Topic :: Scientific/Engineering :: Image Processing","Topic :: Scientific/Engineering :: Artificial Intelligence"],"requires_dist":["numpy","magicgui","qtpy","torch","torchvision","tqdm","pillow","matplotlib","opencv-python","tifffile","napari[all]","tox; extra == \"testing\"","pytest>=8.3.5; extra == \"testing\"","pytest-qt>=4.4.0; extra == \"testing\"","pytest-xvfb>=3.0.0; extra == \"testing\"","pytest-cov>=6.0; extra == \"testing\"","pyqt5>=5.15.11; extra == \"testing\"","napari>=0.5.6; extra == \"testing\"","magicgui>=0.10.0; extra == \"testing\""],"requires_python":"<3.13,>=3.9","requires_external":null,"project_url":["Documentation, https://github.com/AAitorG/napari-DINOSim#readme","Repository, https://github.com/AAitorG/napari-DINOSim","Issues, https://github.com/AAitorG/napari-DINOSim/issues"],"provides_extra":["testing"],"provides_dist":null,"obsoletes_dist":null},"npe1_shim":false}