Erich Blume
d51c180fe6
## Summary - Replace abandoned YOLO-NAS-S (320x320, `yolonas`) with YOLOv9-c (640x640, `yolo-generic`) - YOLOv9-c benefits from CUDA Graphs in Frigate 0.17 on the RTX 4080 - Add `export_yolov9` Dagger pipeline and `frigate-export-model` mise task for reproducible model exports - Model already deployed to `sifaka:/volume1/frigate/models/yolov9-c-640.onnx` ## Config changes - `model_type: yolonas` → `yolo-generic` - `input_dtype: int` → `float` - `width/height: 320` → `640` - `path:` → `yolov9-c-640.onnx` ## Deployment and Testing - [ ] Merge and sync Frigate ArgoCD app: `argocd app sync frigate` - [ ] Verify Frigate starts and detects objects at https://nvr.ops.eblu.me - [ ] Confirm GPU inference via Frigate system metrics Reviewed-on: https://forge.ops.eblu.me/eblume/blumeops/pulls/246
80 lines
2.7 KiB
Markdown
80 lines
2.7 KiB
Markdown
---
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title: Frigate
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modified: 2026-02-22
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tags:
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- service
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- surveillance
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---
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# Frigate
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Open-source network video recorder (NVR) with object detection. Runs cloud-free with all video stored locally on [[sifaka]].
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## Quick Reference
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| Property | Value |
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|----------|-------|
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| **URL** | https://nvr.ops.eblu.me |
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| **Tailscale URL** | https://nvr.tail8d86e.ts.net |
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| **Namespace** | `frigate` |
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| **Image** | `ghcr.io/blakeblackshear/frigate:0.17.0-rc2-tensorrt` |
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| **Upstream** | https://github.com/blakeblackshear/frigate |
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| **Manifests** | `argocd/manifests/frigate/` |
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## Architecture
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```
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ReoLink Camera (GableCam)
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│ RTSP
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▼
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Frigate pod (ringtail k3s)
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├── go2rtc — RTSP restream proxy
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├── FFmpeg — stream decoding
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├── detector — ONNX with CUDA (RTX 4080)
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├── /media/frigate — NFS recordings (sifaka)
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└── /db — SQLite (local PVC)
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│
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└──→ MQTT (Mosquitto) → frigate-notify → ntfy → mobile
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```
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## Cameras
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| Camera | IP | Location | Objects Tracked |
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|--------|----|----------|-----------------|
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| GableCam | `192.168.1.159` | Front gable | person, car, dog, cat, bird |
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Camera credentials are stored in 1Password and synced via [[external-secrets]] to the `frigate-camera` Secret.
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## Detection
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Object detection runs on [[ringtail]]'s RTX 4080 via the ONNX detector with CUDA execution provider (TensorRT). The model is YOLOv9-c at 640x640 (`yolov9-c-640.onnx`, `model_type: yolo-generic`), which benefits from CUDA Graphs in Frigate 0.17. To re-export or change model size, use `mise run frigate-export-model`.
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Two zones are configured: `driveway_entrance` (triggers review alerts for person/car) and `driveway` (triggers review detections).
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## Retention
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| Type | Duration | Mode |
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|------|----------|------|
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| Continuous recording | 3 days | all |
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| Alert clips | 30 days | active objects |
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| Detection clips | 14 days | motion |
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| Snapshots | 14 days | — |
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## Storage
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| Mount | Backend | Size |
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|-------|---------|------|
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| `/media/frigate` | NFS PV on [[sifaka]] (`/volume1/frigate`) | 2 Ti |
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| `/db` | Local PVC (`frigate-database`) | SQLite |
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| `/dev/shm` | Memory-backed `emptyDir` | 512 Mi |
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## Alerting (frigate-notify)
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A separate **frigate-notify** pod (`ghcr.io/0x2142/frigate-notify:v0.3.5`) subscribes to Frigate's MQTT events via Mosquitto and pushes alerts to [[ntfy]] on the `frigate-alerts` topic. Alert messages include action buttons linking back to the Frigate review UI.
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## Related
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- [[ntfy]] - Push notification delivery
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- [[sifaka]] - NAS storage for recordings
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- [[observability]] - Prometheus metrics at `/api/metrics`
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- [[operationalize-reolink-camera]] - Original deployment plan
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