birdnet-team/BirdNET-Analyzer

Health v2 · maintenance only

Adoption not part of the score

1681 stars · 285 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

BirdNET-Analyzer is an open-source Python tool from the Cornell Lab of Ornithology that uses deep learning to identify bird species from audio recordings, supporting over 6,500 species. It can process large batches of audio data or single files and offers CLI, GUI, and library interfaces for scientific bioacoustic analysis.

Use cases

• identify bird species from audio recordings
• process large batches of acoustic monitoring data
• classify birdsong in scientific research
• detect which birds are calling in field recordings
• run bioacoustic analysis without a CS background
• analyze passive acoustic monitoring recordings for avian diversity

When to choose

• you need to identify bird species from audio files or large recording datasets
• you are doing ecological or bioacoustic research and want a well-cited, actively maintained tool
• you want a ready-to-use analyzer with CLI, GUI, and Python API options

When to avoid

• you need to classify non-bird animal sounds or general audio events
• you want to train custom models from scratch (see the BirdNET training tools instead)
• you need real-time embedded deployment on microcontrollers (use BirdNET-Tiny or related repos)

Facets

cli-tool · maturity active

machine-learning deep-learning audio-processing cli machine-learning windows python cli bioacoustics birdsong-classification acoustic-monitoring species-identification cornell-lab-of-ornithology audio natural-language-processing linux macos docker

Member repositories

For agents

markdown · JSON · MCP: product_card(name="birdnet-team/BirdNET-Analyzer")