Switch Frigate detection model from YOLO-NAS-S to YOLOv9-c (#246)

## 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

argocd/manifests/frigate/configmap.yaml

@@ -63,12 +63,12 @@ data:
         type: onnx
 
     model:
-      model_type: yolonas
-      width: 320
-      height: 320
+      model_type: yolo-generic
+      width: 640
+      height: 640
       input_tensor: nchw
-      input_dtype: int
-      path: /media/frigate/models/yolo_nas_s.onnx
+      input_dtype: float
+      path: /media/frigate/models/yolov9-c-640.onnx
       labelmap_path: /labelmap/coco-80.txt
 
     record: