Record corrected AOI1024 promotion report
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2026-07-09 14:52:52 +02:00
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- Trained inactive local model asset `geointel-building-yolov8s-aoi1024visible025e50-pt` from the AOI1024 dataset. Ultralytics validation ended at approximately precision `0.275`, recall `0.331`, mAP50 `0.188` and mAP50-95 `0.0716`.
- Redeployed Tower and verified the previously failing Geel low-threshold persisted YOLO/QA path now completes instead of returning `504`; the run produced F1 `0.09136212624584718`, so the model remains rejected for default use.
- Ran the full four-sample AOI1024 positive matrix and nine-sample hard-negative matrix. Best positive result was Westerlo threshold `0.15` with F1 `0.28703703703703703`; background pressure still reached 59 detections at threshold `0.25`, 107 at `0.15` and 226 at `0.05`.
- Generated the AOI1024 promotion report after the parser fix; recommended candidate remains `none`.
- Generated the AOI1024 promotion report after the parser fix; recommended candidate remains `none`. Mean positive F1 stayed below gate for all thresholds: `0.13307746028311157` at `0.05`, `0.13900227809255514` at `0.15` and `0.09694707724016788` at `0.25`.
- The candidate remains inactive and must pass persisted detection QA/QC plus background/hard-negative promotion gates before default activation.
- No API contract, migration, product feature, provider fetching, fake detection data or active model default changed.
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- mixed background candidates still produced false-positive pressure: max detections were `59` at threshold `0.25`, `107` at `0.15` and `226` at `0.05`
- Fixed `scripts/build_detection_model_promotion_report.py` after discovering it accepted `multi_sample_quality_summary.json` but counted positive samples as `0`. The report now supports both `samples[].runs[]` portfolios and `items[]` multi-sample summaries.
- AOI1024 promotion report path: `artifacts/detection-model-promotion/aoi1024visible025e50-full/detection_model_promotion_report.md`; recommendation remains `none`.
- Corrected AOI1024 promotion decision after parser fix:
- threshold `0.05`: 4 positive samples, 9 background samples, mean F1 `0.13307746028311157`, max background detections `226`
- threshold `0.15`: 4 positive samples, 9 background samples, mean F1 `0.13900227809255514`, max background detections `107`
- threshold `0.25`: 4 positive samples, 9 background samples, mean F1 `0.09694707724016788`, max background detections `59`
## Known limitations