Add detection calibration sweep
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@@ -189,6 +189,24 @@ operationally only when the selected model genuinely returns no usable
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detections after class filtering; it must be interpreted as model/data quality
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evidence rather than as a successful building extraction result.
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Run a confidence-threshold calibration sweep against the same real-data path:
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```bash
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REAL_RASTER_PATH=/mnt/user/appdata/geointel/storage/operator-data/geel_orthophoto_wms_512.tif \
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REAL_REFERENCE_VECTOR_PATH=/mnt/user/appdata/geointel/storage/operator-data/geel_grb_gbg_buildings.geojson \
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CALIBRATION_THRESHOLDS="0.50 0.35 0.25 0.15" \
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bash scripts/run_detection_calibration_sweep.sh http://192.168.10.150:1202
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```
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The sweep reuses `verify_real_data_detection_qa_workflow.sh` once per
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threshold, so every row is backed by persisted Project, Dataset, AnalysisRun,
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Detection, QualityCheck, Metric and export records. It writes per-threshold
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logs plus `calibration_summary.json` under
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`artifacts/detection-calibration/<timestamp>` unless
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`CALIBRATION_OUTPUT_DIR` is set. This is a calibration/benchmarking tool only:
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it does not seed demo data, enable fixture detections, fetch external data or
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download model weights.
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Docker images install only the GIS runtime by default. To build a local/Tower
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image with PyTorch/Ultralytics available for the configured-YOLO preflight and
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runtime path, set:
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