Add guarded promoted YOLO activation

2026-07-11 10:45:06 +02:00
parent 340be960e9
commit b1a4074cc8
13 changed files with 550 additions and 23 deletions
@@ -124,7 +124,8 @@ AI Lab run controls explicitly explain when no raster dataset is available, inst
 - Detection Lab now exposes the `yolo-configured` capability reported by the backend.
 - When `yolo-configured` is selected, users can provide an existing raster tile manifest path.
 - Detection Lab lists local model assets from `GET /api/v1/detection/model-assets` so operators can choose an existing mounted model file instead of editing only one hidden `YOLO_MODEL_PATH` slot.
- Detection Lab exposes explicit operator profiles for the current inactive local AOI1024 building detector: balanced review at threshold `0.15` and conservative review at threshold `0.35`. Applying a profile deliberately selects the local model asset and threshold; it does not approve or promote a default model.
+- Detection Lab exposes explicit operator profiles for the local AOI1024 building detector: balanced review at threshold `0.15` remains candidate-only, while conservative review at threshold `0.35` is marked as the promoted profile after the split-background pure-empty gate passed.
+- Applying a profile deliberately selects the local model asset and threshold for the browser-run request; runtime default activation remains a separate guarded `.env` operation through `scripts/activate_promoted_yolo_candidate.py`.
 - Detection Lab includes a read-only YOLO runtime preflight panel with backend status, dependency visibility, local model configuration, `torch`/`ultralytics` versions, CUDA state and `YOLO_CONFIG_DIR`.
 - The UI still does not download models or create fake detections; backend status and error codes remain the source of truth.