“"This is really a BirdNET-Go companion, as it cannot run without." — arnemunthekaas, Hacker News”
You know that feeling when your bird-listening setup identifies a species but leaves you with a dashboard instead of something you want on the wall? Fugleramme turns those detections into a visual collage that you can put on an e-ink panel or open in a browser. You keep BirdNET-Go responsible for listening and classification, so you do not replace its audio pipeline just to get a display. You also avoid generating replacement art because the project ships hand-curated public-domain cut-outs.
Think of BirdNET-Go as the listener and Fugleramme as the picture framer. You connect a microphone to BirdNET-Go, which identifies the bird calls and exposes detections through its API. Fugleramme polls that API, matches each species to an illustration, packs the illustrations into a page, and redraws only when the birds change. You can run the detector on the same machine or point the frame at a reachable BirdNET-Go host; the output goes to an Inky Impression panel or a web kiosk.
If you already run BirdNET-Go, keep a Raspberry Pi or homelab, and want your detections to become ambient wall art, this fits your setup. It also fits you if you want to study a clean split between a sensor service and a rendering service. It does not fit you if you need a standalone bird classifier, commercial-use clearance for the full detector stack, or a centrally supported appliance.
Explore it as an experimental personal or homelab project, not as an organization-grade appliance. The repository ships frequent releases and has a clear local-development route, but the maintainer calls it early development and describes it as a one-person project. Start if you accept hardware setup, a separate BirdNET-Go dependency, and regional artwork gaps.
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