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
@@ -275,8 +275,23 @@ python scripts/configure_yolo_model.py \
  --apply
 ```

-The smoke loads only the supplied local model file, does not run inference and
-does not download weights.
+When a promotion report recommends an exact model/tile/threshold candidate,
+prefer the guarded activation helper. It validates the report, checks the local
+model asset and writes `.env` only when `--apply` is supplied:
+
+```bash
+python scripts/activate_promoted_yolo_candidate.py \
+  --promotion-report /mnt/user/appdata/geointel/artifacts/detection-model-promotion/split-aware/aoi1024bg512r3e50-high-threshold-split-20260710T222934Z/detection_model_promotion_report.json \
+  --candidate-key 'geointel-building-yolov8s-aoi1024bg512r3e50-pt|512|64|0.35' \
+  --models-dir /mnt/user/appdata/geointel/models \
+  --env-file /mnt/user/appdata/geointel/.env \
+  --json
+```
+
+Add `--apply` only after reviewing the emitted env updates. The smoke and
+activation helpers load no model by default, run no inference and do not
+download weights. Restart or rebuild the runtime after applying because the
+active model is read from `YOLO_MODEL_PATH`.

 Operator-only local training preparation is available when real public model
 candidates are too weak for the target imagery. It is not a browser feature and