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Add operator YOLO dataset quality audit
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2026-07-09 01:45:52 +02:00
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@@ -436,3 +436,9 @@ This file now starts with the current implementation status. Older preparation/b
- [ ] Add more AOIs after the tile-level baseline so the next local model attempt is not limited to Geel/Mol/Turnhout.
- [ ] Add negative/background AOIs so the next tile dataset is not all positive tiles.
- [ ] Improve positive training coverage/label quality before the next higher-capacity model attempt; simply extending the same hardneg r8 run is not enough.
# Sprint 146 - Operator YOLO dataset quality audit
- [x] Add a dataset/label-quality audit for generated operator YOLO tile datasets.
- [x] Report sample coverage, validation coverage, repeated hard-negative pressure and YOLO label area integrity.
- [x] Wire the audit script into the readiness syntax gate.
- [ ] Use live audit output to decide whether the next model pass needs more positive AOIs, label cleanup or unique hard negatives.