Metro AI App Recipe — DLSPS + WebRTC + Mosquitto + Node-RED + Grafana + Nginx

Build an end-to-end {{OBJECT}}-analytics stack on Intel hardware in ./{{STACK_DIR}}/ with Docker Compose. Vertical-agnostic: the same seven-container topology serves any DL Streamer / OpenVINO CV pipeline — only the model, class filter, alert rule, dashboard, and topics differ. Follows the open-edge-platform Metro Vision AI App Recipe MediaMTX + Coturn + WebRTC path, streamlined (no Prometheus/OTel). Scenescape is off by default (opt-in multi-camera analysis). Data-flow and routing are detailed in Reference architecture below.

When to use this skill

Use when building an object-detection, classification, object-counting, or zone/line-crossing alerting pipeline for any vertical (see table below). Optionally adds a Scenescape multi-camera path, or a lightweight demo/PoC single app when no full stack is needed.