BirdNET-Go

BirdNET-Go is an AI solution for continuous avian monitoring and identification

• 24/7 realtime bird song analysis of soundcard capture, analysis output to log file, SQLite or MySQL
• Utilizes BirdNET AI model trained with more than 6500 bird species
• Local processing, Internet connectivity not required
• Easy to use Web user interface for data visualisation
• Supports over 40 languages for species names
• Advanced features like Deep Detection for improved accuracy and Live Audio Streaming.
• BirdWeather.com API integration
• Realtime log file output can be used as overlay in OBS for bird feeder streams etc.
• Minimal runtime dependencies, BirdNET Tensorflow Lite model is embedded in compiled binary
• Provides endpoint for Prometheus data scraping
• Runs on Windows, Linux and macOS
• Low resource usage, works on Raspberry Pi 3 and equivalent 64-bit single board computers

Installation

Quick install script for Debian, Ubuntu and Raspberry Pi OS based systems:

curl -fsSL https://github.com/tphakala/birdnet-go/raw/main/install.sh -o install.sh
bash ./install.sh

Help Improve BirdNET-Go

I am seeking web developer with experience in Go HTML templating, Tailwind CSS, HTMX, Alpine.js, or similar frameworks to join in enhancing the BirdNET-Go application web UI. Your expertise can make a real difference in how users engage with this app and connect with birdlife. If you have the skills and a keen interest in contributing to a nature-focused project, I'd love to hear from you.

Web Dashboard

For detailed installation instructions, see the installation documentation. For securing your BirdNET-Go installation, see the security documentation. See recommended hardware for optimal performance.

Building

For instructions on how to build the project, see the building documentation.

Usage

```bash BirdNET-Go CLI

Usage: birdnet [command]

Available Commands: authors Print the list of authors benchmark Run performance benchmark directory Analyze all *.wav files in a directory file Analyze an audio file help Help about any command license Print the license of Go-BirdNET rangefilter Manage the range filter database realtime Analyze audio in realtime mode support Generate a support bundle

Flags: --debug Enable debug output -h, --help help for birdnet --locale string Set the locale for labels. Accepts full name or 2-letter code. (default "finnish") --overlap float Overlap value between 0.0 and 2.9 (High values like 2.7 enable Deep Detection) --sensitivity float Sigmoid sensitivity value between 0.0 and 1.5 (default 1) --threshold float Confidency threshold for detections, value between 0.1 to 1.0 (default 0.8)

Use "birdnet [command] --help" for more information about a command.

There is more detailed usage documentation at Wiki

License

Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International

Authors

Tomi P. Hakala

Contributions by Hampus Carlsson, Jan Vrska, @twt--, @aster1sk, @hoover67

Please let me know if you are missing from contributors list!

BirdNET AI model by the K. Lisa Yang Center for Conservation Bioacoustics at the Cornell Lab of Ornithology in collaboration with Chemnitz University of Technology. Stefan Kahl, Connor Wood, Maximilian Eibl, Holger Klinck.

BirdNET label translations by Patrick Levin for BirdNET-Pi project by Patrick McGuire.