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Add operator YOLO training dataset tooling
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2026-07-07 05:19:16 +02:00
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# Changelog
## Sprint 129 Operator YOLO training dataset tooling (2026-07-07)
- Added `scripts/export_operator_yolo_dataset.py` to convert prepared operator orthophoto/GRB sample pairs into a standard local YOLO detection dataset with `dataset.yaml`, train/validation image folders, label folders and `yolo_dataset_summary.json`.
- Added `scripts/train_operator_yolo_detector.sh` as an operator-only training smoke wrapper that uses an existing local base `.pt` model and writes a trained local `.pt` artifact plus `training_summary.json`.
- Added readiness coverage for the exporter Python compile check and training wrapper shell syntax.
- Added regression coverage in `backend/tests/test_sprint129_operator_yolo_training_dataset.py`.
- Updated operator documentation for dataset export, training smoke usage and the requirement to benchmark any trained model through the existing real-data Detection + QA matrix before treating it as useful.
- No Training Studio UI, API contract change, provider fetching, model auto-provisioning or app-side model training behavior was introduced.
## Sprint 128 Stronger building model runtime benchmark (2026-07-07)
- Added `keremberke/yolov8s-building-segmentation` as an explicit Tower runtime model asset at `/mnt/user/appdata/geointel/models/yolov8s-building-segmentation.pt`; the file is not committed to Git.