Birdjournal: Identify Birds by Sound, Offline, with Open-Source AI

说明与用途

Birdjournal 让鸟类爱好者在离线环境下通过声音识别鸟类，结合 BirdNET 检测和本地 LLM 生成日志。

问题

Beginner birdwatchers need a way to identify bird species from audio recordings without internet or cloud services.

结果

On a 46‑second recording of a Coppersmith Barbet, BirdNET detected the species at 100% confidence in all 16 three‑second windows, and the LLM produced a concise journal entry in English.

工作流

• Record audio (.wav/.mp3) on a walk
• Run python main.py <audio> --place "<city>, <state>" --lat <lat> --lon <lon> --out <output>
• BirdNET identifies species and applies a geo filter
• A local LLM (default Qwen2.5 3B via Ollama) generates a short field‑journal entry
• Output is written to the specified markdown file

证据

BirdNET detected the barbet at 100% confidence in all 16 of its 3-second windows, with the location filter set to Sikar.

来源

The idea is that the screen is the shortest part of the experience. You go outside, record, and listen. The tool does its work afterwards.

来源

My first prompt let the small model invent facts that weren't in the detections, such as calling the barbet "colorful and melodious".

来源