Record AOI512 YOLO candidate gate

2026-07-09 04:19:48 +02:00
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 # Changelog

+## Sprint 147 AOI512 YOLOv8s scale-match candidate gate (2026-07-09)
+
+- Built and audited an AOI-scale YOLO dataset at `512px` tile size to test whether the previous `160px` training scale was the main quality blocker.
+- Trained Tower-local model asset `geointel-building-yolov8s-aoi512e80-pt` from `/app/storage/operator-data/yolo-building-aoi512-uniquehardneg`.
+- Ran 7 positive AOI sweeps, a 17,156-feature evidence portfolio, a 9-sample hard-negative/background matrix and a promotion report.
+- Result: the candidate is rejected. The best threshold `0.25` reached mean positive F1 `0.13511851520077328` and still produced max background detections `56`.
+- Conclusion: scale-match training helps the training validation curve but does not solve operational persisted QA/QC quality. The next model pass needs better positive AOI coverage and label strategy, not only more epochs or another threshold.
+- No API contract, migration, frontend behavior, provider fetching, model download or active model configuration changed.
+
 ## Sprint 146 Unique hard-negative YOLOv8s candidate gate (2026-07-09)

 - Fixed the all-in-one Docker image so the operator YOLO training wrapper is available at `/app/scripts/train_operator_yolo_detector.sh`.