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Record building YOLO runtime model
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2026-07-06 20:37:12 +02:00
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@@ -4318,6 +4318,13 @@ Tested:
- Deploy-time browser runtime verification passed for frontend, API proxy and icon.
- Live YOLO preflight after the RGB adapter fix passed with generated demo raster tile manifest and `status=ready`.
- Live real YOLO inference smoke after the RGB adapter fix passed: `POST /api/v1/detection/run` returned `status=success`, analysis run `bbd80690-baf3-4e83-8ffb-fdcb07a70c0c`, job `9636ed10-bbde-463f-a47a-6d7706c81e19`, `detection_count=0` and no error code. Zero detections is expected for the generic COCO smoke model on the synthetic demo raster.
- Downloaded `keremberke/yolov8n-building-segmentation` from Hugging Face as an explicit Tower runtime artifact at `/mnt/user/appdata/geointel/models/yolov8n-building-segmentation.pt`.
- Recorded building-model checksum `152d6a9c5c76c9f2fd2fd5cc167efaed7c8c02e31002b15415899710f1d71f98`, matching the Hugging Face file metadata for `best.pt`.
- Applied `.env` with `YOLO_MODEL_PATH=/app/models/yolov8n-building-segmentation.pt` through `scripts/configure_yolo_model.py --model-file ... --apply`.
- Restarted the all-in-one container without rebuild; it remained healthy and published on `0.0.0.0:1202->80/tcp`.
- Live building-model preflight passed with `model_load_ok=true`, `dependencies_available=true`, `torch_version=2.12.1`, `ultralytics_version=8.4.89`, `will_download_models=false` and `will_run_inference=false`.
- Live building-model preflight with generated demo raster tile manifest passed with `status=ready`.
- Live real building-model YOLO inference smoke passed: `POST /api/v1/detection/run` returned `status=success`, analysis run `be609d4a-3e01-42df-bca8-0d5a2289120d`, job `9c8bc26d-7753-4537-ab98-dc31b9029450`, `detection_count=0` and no error code. Zero detections remains expected on the synthetic demo raster.
Open:
- A local YOLO smoke model is now present and configured on Tower, but it is the generic COCO `yolov8n.pt` model. It proves the runtime path, not production-quality aerial building detection.
@@ -4325,11 +4332,12 @@ Open:
Limitations:
- The bundled Tower model file was placed as an operator/runtime artifact under appdata, not committed to Git.
- The configured model is a generic COCO model and should be replaced by a suitable aerial/building detector for meaningful GIS output.
- The active configured model is now a building segmentation YOLO model trained for satellite-building segmentation, but it is still a third-party Hugging Face PyTorch `.pt` artifact and should be treated as an evaluation model until validated on local Belgian/Kempen orthophotos.
- No model download behavior was added to the application; the manual operator placement remains explicit.
- If multiple local model files are present, the operator must choose one with `--model-file` so GeoIntel does not silently activate the wrong model.
Next recommended pass:
- Replace `yolov8n.pt` with a domain-appropriate aerial/building detector before evaluating QA/QC quality. The runtime path is now operational.
- Load a real georeferenced orthophoto/GeoTIFF for the target area, generate raster tiles, run the active building YOLO model and compare persisted detections against reference vector buildings through QA/QC.
## Sprint 104 AI Lab action guardrails (2026-06-24)