[!IMPORTANT]
BirdNet-Behavior is licensed CC BY-NC-SA 4.0 — the same terms as the upstream BirdNET model and BirdNET-Pi.
You may not use this project to build a commercial product. See LICENSE for details.
[!NOTE]
This README describes the development tree (main), not a release. The install commands below fetch the latest release — v0.17.1 on 2026-10-20 — and the container image tagged latest is that release's. Anything this README describes that is newer than v0.17.1 is marked (unreleased); the main one is the default classifier: v0.17.1 installs the BirdNET+ V3.0 preview for everyone and has no --classifier flag. Links to the manual are to the files in this tree, so they match the commit you are reading. The manual for the release you installed is at the site root; the one for this tree is under /dev/; releases from v0.17.1 on also have a /vX.Y.Z/ manual (how the manual is versioned).
What is BirdNet-Behavior?
A rewrite of BirdNET-Pi in Rust, derived from it and licensed accordingly. It listens to a USB microphone or RTSP stream, identifies birds in real time with a BirdNET neural network — BirdNET V2.4, the network BirdNET-Pi runs, by default (unreleased: v0.17.1 installs the BirdNET+ V3.0 preview, which remains an option) — and serves a fast, responsive web dashboard you open in any browser.
It ships as one self-contained binary — about 100 MB (the stripped binaries in the v0.17.1 release archives are 107 488 608 bytes on x86_64 and 99 158 736 on aarch64; the archives you download are 45.2 and 43.0 MB). The ONNX Runtime inference engine and the DuckDB analytics engine are compiled in — there is no Python, no pip, no virtualenv, and nothing else to install. The binary links against the host's system C library, so it targets modern 64-bit Linux (glibc ≥ 2.39 — Raspberry Pi OS Trixie, Debian 13, Ubuntu 24.04); a Docker image carries its own runtime for everything older. Upgrading is replacing one file.
It is a rewrite, and it is derived from BirdNET-Pi (the repository's LICENSE says so), which is why it carries the same licence. See Credits & Attribution.
How it compares to BirdNET-Pi
| BirdNET-Pi (Python) | BirdNet-Behavior (Rust) |
|---|
| Runtime | CPython interpreter + virtualenv | One native binary — no interpreter |
| Install | pip into a venv + system packages | one file, or one curl installer |
| Upgrade | re-resolve pip dependencies | replace one file |
| Inference | TensorFlow Lite (Python) | ONNX Runtime, linked in-process |
| Detection model | BirdNET V2.4 | BirdNET V2.4 by default for a new install, with BirdNET-Pi's defaults, measured against BirdNET-Pi; BirdNET+ V3.0 preview with --classifier birdnet-v3 (unreleased; v0.17.1 installs V3.0 for everyone) |
| Analytics | — | DuckDB behavioral engine, built in |
| HTTPS | reverse proxy (Caddy/nginx) | built in — --tls-mode self-signed or your own certificate |
| Offsite backups | copy them yourself | built in — encrypted on the station, to S3-compatible or SFTP |
| Sound levels | — | ISO 266 third-octave spectrum, IEC 61672 A-weighted |
| Per-source audio filtering | two fixed toggles | a parametric chain, with the response curve drawn as you type |
Behind a path (/birdnet) | own subdomain or port | BIRDNET_BASE_PATH |
| Each release ships | — | signed SLSA provenance + CycloneDX SBOM |
Every BirdNET build is dominated by the model itself — its weights cost the same memory whichever runtime loads them. What Rust removes is the overhead around the model: no interpreter to warm up, no virtualenv, no GIL serializing the request path. Audio capture and the detection loop run on a dedicated thread; the web server answers requests concurrently on a single Tokio runtime. It runs comfortably on a 2 GB Raspberry Pi.
Screenshots
Every screen leads with a plain-English headline, then layers the dense numbers beneath — designed to serve a casual hobbyist and a PhD ornithologist at once. Light + dark themes, fully responsive.
On the phone
The same design system, with all six homes on a bottom tab-bar — iPhone 13 captures.
➡️ See every screen in the Field Guide — every PNG above has a matching docs/book/images/mobile/ capture for the same data and chrome at iPhone 13 width.
Quick start
Both ways below are one command; choose by host. On a Raspberry Pi (OS Trixie) or modern x86_64 Linux, install the native binary: nothing else needs setting up. It downloads and sha256-verifies the binary, installs the classifier (see below), auto-detects your USB mic, asks for your location, and starts a hardened systemd service:
curl --proto '=https' --tlsv1.2 -fsSL https://github.com/tomtom215/BirdNet-Behavior/releases/latest/download/install.sh | sudo bash
Run it exactly as shown — pipe into sudo bash, not sudo bash <(curl …) (the process-substitution form breaks under sudo). On a fresh 64-bit Raspberry Pi OS Trixie image the prebuilt binary runs as-is (glibc 2.39); the installer refuses early, with guidance, on anything older.
This is the beginning of the README. Read the rest at the original. Read the full README ↗
