This repo contains BirdNET models and scripts for processing large amounts of audio data or single audio files. This is the most advanced version of BirdNET for acoustic analyses and we will keep this repository up-to-date with new models and improved interfaces to enable scientists with no CS background to run the analysis.
Feel free to use BirdNET for your acoustic analyses and research. If you do, please cite as:
@article{kahl2021birdnet,
title={BirdNET: A deep learning solution for avian diversity monitoring},
author={Kahl, Stefan and Wood, Connor M and Eibl, Maximilian and Klinck, Holger},
journal={Ecological Informatics},
volume={61},
pages={101236},
year={2021},
publisher={Elsevier}
}You can access documentation for this project here.
You can download installers for Windows and macOS from the releases page.
Developed by the K. Lisa Yang Center for Conservation Bioacoustics at the Cornell Lab of Ornithology in collaboration with Chemnitz University of Technology.
Go to https://birdnet.cornell.edu to learn more about the project.
Want to use BirdNET to analyze a large dataset? Don't hesitate to contact us: [email protected]
Have a question, remark, or feature request? Please start a new issue thread to let us know. Feel free to submit a pull request.
- Source Code: The source code for this project is licensed under the MIT License.
- Models: The models used in this project are licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0).
Please ensure you review and adhere to the specific license terms provided with each model.
Please note that all educational and research purposes are considered non-commercial use and it is therefore freely permitted to use BirdNET models in any way.
Feel free to clone this repository and contribute to the project. We are always looking for new ideas and improvements. If you have any questions, please don't hesitate to ask.
Let us know if you have any ideas for new features or improvements or submit a pull request.
Help us to improve the documentation!
Install sphinx and all required themes + plugins with pip install sphinx sphinx_rtd_theme sphinx-argparse.
Run sphinx-build docs docs/_build.
Navigate to BirdNET-Analyzer/docs/_build and open index.html with a browser of your choice.
This project is supported by Jake Holshuh (Cornell class of ´69) and The Arthur Vining Davis Foundations. Our work in the K. Lisa Yang Center for Conservation Bioacoustics is made possible by the generosity of K. Lisa Yang to advance innovative conservation technologies to inspire and inform the conservation of wildlife and habitats.
The development of BirdNET is supported by the German Federal Ministry of Education and Research through the project “BirdNET+” (FKZ 01|S22072). The German Federal Ministry for the Environment, Nature Conservation and Nuclear Safety contributes through the “DeepBirdDetect” project (FKZ 67KI31040E). In addition, the Deutsche Bundesstiftung Umwelt supports BirdNET through the project “RangerSound” (project 39263/01).
BirdNET is a joint effort of partners from academia and industry. Without these partnerships, this project would not have been possible. Thank you!
