BirdNET-PiPy is a self-hosted system that uses the BirdNET deep-learning model to identify birds from their sounds, with an easy-to-use web dashboard for monitoring and exploration. Connect a microphone and run it 24/7 in your backyard on a Raspberry Pi to discover which birds are around you. Try the live demo to see it in action.
- 🐦 Real-time Identification: Detects bird calls locally using the BirdNET model.
- 📊 Modern Dashboard: Vue.js-based interface for visualizing detections and spectrograms.
- 🐳 Containerized: Docker-based architecture for reliability and isolation.
- 📱 Mobile Friendly: Responsive design works on desktop and mobile.
Prerequisites: Raspberry Pi 4/5 (2GB+) running Raspberry Pi OS (64-bit).
Run the automated installer:
curl -fsSL https://raw.githubusercontent.com/Suncuss/BirdNET-PiPy/main/install.sh | sudo bashOnce installed, access the dashboard from any device on the same network:
- Using hostname:
http://<hostname>.local(e.g.,http://raspberrypi.local) - Using IP address:
http://<ip-address>(e.g.,http://192.168.1.100)
- Installation Guide: Detailed hardware requirements and setup instructions.
- Deployment & Administration: Service management, audio architecture, and system internals.
- Privacy and Data Handling: How your audio and data are processed locally on your device.
BirdNET-PiPy uses a containerized microservices architecture with five Docker containers working together to provide real-time bird call detection and a modern web dashboard.
For detailed architecture diagrams including container relationships, audio flow, and data processing pipelines, see Architecture Documentation.
Licensed under CC BY-NC-SA 4.0.
This project is built upon:
- BirdNET - Developed by the K. Lisa Yang Center for Conservation Bioacoustics at the Cornell Lab of Ornithology and Chemnitz University of Technology
- BirdNET-Pi - Original Raspberry Pi implementation by Patrick McGuire
BirdNET-PiPy extends these projects with a modern Vue.js frontend, containerized architecture, and enhanced user interface.
Build by Claude Code and Yudong with ❤️
