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                    "fugleramme\nE-ink bird frame for Raspberry Pi - real-time bird detection by audio, fully local AI, rendered as real, hand-cut 1800s bird illustrations.\n\n  \n  \n  Sorry about the dirty window - squirrels have been stealing the bird food.\n\n\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\nNoteStill in early development: expect the odd bug and a few unpolished edges, with plenty more features to come.\n\nLive on fugleramme.arnegiacomo.dev running from my kitchen window and displaying the actual birds currently heard in my garden (Bergen, Norway).\nHardware, install and operations docs: arnegiacomo.dev/fugleramme\nHow it works\nBirdNET-Go listens on a mic and handles the\nclassifier. Fugleramme polls its api, matches each species to\nan illustration, then packs them onto a page, and redraws only when the birds change - on\nan Inky Impression e-ink panel, and\nas a web kiosk serving the same view. There's an admin page that lets you configure what\nto show, and automatic updates and such.\nIf you already run BirdNET-Go, point the frame at it instead - on the same machine or anywhere else reachable from your network.\nTipThe e-ink panel is not required, although it's recommended for the intended experience. Without one, Fugleramme runs web-only - show the\nkiosk on a display over HDMI, or open it from any device on the network.\n\nHardware\nA Raspberry Pi 5, an Inky Impression 13.3\"\n(Spectra 6), a mic and an A4 frame. Full parts list, recommendations and alternatives: Hardware.\nArt\nHalf the point of this project is showing off some amazing public-domain natural-history\nillustrations. Over 800 cut-outs covering more than 400 species, every one taken from a\nreal plate and hand-curated for this project (no art is AI-generated, though some has been\nretouched with AI).\nEach detected species is matched to its illustration, background-removed, and packed onto\na textured paper page with the larger birds toward the centre, sized by body mass. An empty\nwindow shows a bare perch.\nThe plates are Scandinavian, British and central European, so the Nordics, the British Isles and Germany\nare best covered. Elsewhere not so much (yet). Broader European and North American\ncoverage is in the works!\nSee Adding artwork for manual cutout steps.\n\n\n\nNo detections\nA few visitors\nA full garden\n\n\n\n\n\n\n\n\n\n\nInspiration and related projects\nThe look came from a WWF Verdens naturfond poster by Axel Thorenfeldt\nhanging on my wall, the live-frame idea from AvianVisitors that I saw on Instagram,\nand the detection from BirdNET-Go - I wanted a version of that poster showing the actual birds in my garden.\nSimilar projects:\n\nAvianVisitors - BirdNET-Pi, AI-generated illustrations and photo cutouts\ninky-bird-frame - BirdNET, field-journal illustrations on an Inky panel\nHABirdDashboard - BirdNET-Go, a collage card for Home Assistant\nbelkins-birdnet - BirdNET-Pi, AI-generated kach\u014d-e style illustrations\n\nFugleramme shares no code or art with them.\nRun locally (for development)\nuv sync                                       # set up venv\nuv run fugleramme-fake-detector               # stand-in BirdNET-Go on :8090\nuv run fugleramme-dev                         # start service on :8080 with hot-reload\nThe fake detector's flags, and working against a real station instead:\nRunning it without a Pi.\nInstall on a Raspberry Pi\nFrom the pi (assuming you have the hardware up and running):\ncurl -fsSL https://raw.githubusercontent.com/arnegiacomo/fugleramme/main/install.sh | bash\nAsks where BirdNET-Go should live and which ports to use, clones the repo, installs the required deps, and starts the frame as a systemd service. NB! Will probably require a reboot on a fresh system.\nFrom a blank SD card, see the full install guide.\nRun in a container\ndocker run -d -p 8080:8080 -v fugleramme:/data \\\n  -e FUGLERAMME_DETECTOR_URL=http://birdnet.local:8080 \\\n  ghcr.io/arnegiacomo/fugleramme\nOr build the image from a checkout:\ndocker build -t fugleramme .\ndocker run --rm -p 8080:8080 -v fugleramme:/data \\\n  -e FUGLERAMME_DETECTOR_URL=http://birdnet.local:8080 fugleramme\nKiosk on :8080, admin on :8080/admin, everything it persists in /data.\nOn a Linux box with a USB mic, this brings up BirdNET-Go alongside it:\ncurl -fsSL https://raw.githubusercontent.com/arnegiacomo/fugleramme/main/examples/docker-compose.yml -o docker-compose.yml\ndocker compose up -d\nSee Container for more info.\nContributing\nContributions are very welcome and encouraged - fixes, docs and artwork most of all. Thanks to\neveryone who has contributed\nso far \u2764\ufe0f\n\nSomething is broken - a bug report\nA question, an idea, or a frame you have built - the\nFAQ first, then\nDiscussions\nA fix, a doc change, or a bird you have cut - open a PR, no issue needed\n\nSee Contributing for more info.\nLicense\n\nCode: MIT - see LICENSE.\nDetection (BirdNET-Go, installed\nseparately as a container): CC BY-NC-SA 4.0, non-commercial only. BirdNET model\nby the Cornell Lab of Ornithology and Chemnitz University of Technology,\ntaxonomy data powered by eBird.org.\nBird images: each style folder carries its own terms and sources, and its\nmanifest links the plate every file was cut from. classic is\nCC BY-SA 4.0 - see\nassets/artwork/classic/ATTRIBUTION.md.\nLabel fonts (assets/fonts/): SIL OFL 1.1 - see\nassets/fonts/ATTRIBUTION.md.\nBird sizes (assets/bird_sizes.csv): body mass from AVONET (Tobias et al.\n2022, Ecology Letters, doi:10.1111/ele.13898),\nCC BY 4.0.\nBirdNET scientific-name aliases (assets/birdnet_aliases.json):\nOpenFauna's compiled taxonomic alias\nmap, CC BY-SA 4.0 - see assets/ATTRIBUTION.md.\n\nPrebuilt frames\nI've built a few of these. If you'd like one rather than building it yourself,\nplease get in touch."
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