80 lines
3.0 KiB
Markdown
80 lines
3.0 KiB
Markdown
# livekit-cameras
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Publishes 20 Logitech C920 webcam streams (video + cleaned audio) to a
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LiveKit room.
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Each camera becomes one LiveKit participant (`cam-01` .. `cam-20`) that
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publishes:
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- a camera video track (1280x720 @ 30 fps by default, MJPG from V4L2)
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- a microphone audio track (16 kHz mono, cleaned with speechbrain)
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## Layout
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```
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run.py orchestrator: discovery + per-camera worker processes
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run_worker.py one camera: ffmpeg capture -> LiveKit track publish
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discovery.py serial-based camera <-> ALSA card discovery
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audio_cleanup.py speechbrain SpectralMaskEnhancement (16 kHz) + fallback
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tokens.py LiveKit JWT generation
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config.py .env / environment configuration
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prefetch_model.py one-time speechbrain model download
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generate_udev_rules.py (re)generate udev pinning + slots.json from live state
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slots.json stable slot map: cam-NN -> USB serial, /dev/camNN, ALSA card
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```
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## Setup
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```bash
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uv venv --python 3.12
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uv pip install -p .venv/bin/python -r pyproject.toml # or: uv sync
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cp .env.example .env # then fill in LIVEKIT_URL / API_KEY / API_SECRET
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.venv/bin/python prefetch_model.py # download speechbrain model once
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```
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## Stable camera identity (cam-01 is always cam-01)
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Each C920 has a unique built-in USB serial — that is the camera's UUID.
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udev rules (`/etc/udev/rules.d/99-c920-pin.rules`, generated from the live
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state) bind every slot to a serial, so identity survives reboots, hub
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reordering, and any connect sequence:
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- video: `/dev/cam01` .. `/dev/cam20` (primary UVC node; `.meta` = metadata)
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- audio: fixed ALSA card per slot, `hw:2,0` .. `hw:21,0` (SOUND_CARD_INDEX)
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`discovery.py` assigns identities from `slots.json` (serial lookup, with a
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port-based fallback for cameras not yet in the map). To re-map slots (e.g.
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after physically swapping cameras), regenerate:
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```bash
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.venv/bin/python generate_udev_rules.py --write
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sudo udevadm control --reload-rules
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sudo udevadm trigger --subsystem-match=video4linux --action=add
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sudo udevadm trigger --subsystem-match=sound --action=add
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```
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## Run
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```bash
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.venv/bin/python run.py # all 20 cameras
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.venv/bin/python run.py --cameras 1,5 # subset
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.venv/bin/python run.py --once # status report after timeout
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```
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## Audio cleanup
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The mic audio is cleaned per chunk (default 200 ms) by
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`speechbrain/metricgan-plus-voicebank` (16 kHz, CPU). One worker process per
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camera loads the model once and reuses it; on this 28-core box all 20 stay
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real-time. `ENHANCE_MODE=off` (or a failed model load with `auto`) falls back
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to a lightweight high-pass + soft-clip DSP path so streams still work.
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## Notes
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- Video uses MJPG directly from the UVC interface (`ffmpeg -f v4l2
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-input_format mjpeg`) — cheap, and converts to BGRA for LiveKit.
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- Audio: ALSA mics on these C920s deliver 16 kHz **stereo** only; the worker
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downmixes to mono for LiveKit.
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- Camera <-> card pairing is resolved by matching USB port paths under /sys,
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so each mic belongs to its own camera.
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- Workers auto-restart (up to 10 times) if a camera drops.
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