YA-WAMF ghcr.io/jellman86/yawamf-monalithic:latest https://github.com/Jellman86/YetAnother-WhosAtMyFeeder/pkgs/container/yawamf-monalithic bridge sh false --user 99:100 https://github.com/Jellman86/YetAnother-WhosAtMyFeeder/issues https://github.com/Jellman86/YetAnother-WhosAtMyFeeder YA-WAMF (Yet Another WhosAtMyFeeder) identifies birds at your feeder from Frigate NVR events using local machine-learning models. It shows a real-time dashboard, correlates visual detections with BirdNET-Go audio, enriches species with taxonomy, and can send notifications. This is the monolithic image (web UI and backend in one container). It needs a running Frigate instance publishing events over MQTT; point it at your Frigate URL below. See the Unraid setup guide for the full walkthrough. HomeAutomation: Other: http://[IP]:[PORT:8080]/ https://raw.githubusercontent.com/Jellman86/YetAnother-WhosAtMyFeeder/main/unraid/yawamf.xml https://raw.githubusercontent.com/Jellman86/YetAnother-WhosAtMyFeeder/main/apps/ui/public/pwa-512x512.png bird birds feeder frigate birdnet classification nvr YA-WAMF identifies birds at your feeder from Frigate NVR events using local ML models, with a real-time dashboard, optional BirdNET-Go audio correlation, taxonomy enrichment, and notifications. Requirements: a reachable Frigate instance and MQTT broker. Configuration is stored in /config and the detections database and media cache live in /data. Optional Intel GPU or NPU acceleration can be enabled by passing the matching device (see the hardware-acceleration guide). 9852 /mnt/user/appdata/ya-wamf/config /mnt/user/appdata/ya-wamf/data http://frigate:5000