Promote focused small-building detector

2026-07-13 12:15:27 +02:00
parent b3f7c3ca63
commit 1689dce928
20 changed files with 546 additions and 61 deletions
@@ -124,7 +124,7 @@ 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 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.
+- Detection Lab exposes explicit operator profiles for mounted local building detectors. The focused small-building model is the recommended recall-balanced `0.15` profile; the previous expanded-AOI `0.15` model remains available for higher precision, and the background-aware `0.35` model remains the conservative review choice. Applying a profile never downloads weights, changes runtime environment or starts inference automatically.
 - 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.