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Document remote-sensing YOLO candidate benchmark
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2026-07-07 23:13:36 +02:00
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@@ -416,6 +416,25 @@ Lommel-heide across all tested thresholds. It also regressed dense-AOI F1
against `geointel-building-yolov8n-expanded160e50-pt`, so it is useful model
quality evidence but not a V1 default.
An external remote-sensing YOLOv8l candidate was also benchmarked as an
operator-provided local model asset:
```bash
mkdir -p models
curl -L --fail \
-o models/yolo-remote-sensing-photovoltaic-v8l-detect-1000.pt \
https://huggingface.co/agademer/yolo-remote-sensing-photovoltaic/resolve/main/yolo-remote-sensing-photovoltaic-v8l-solar-farms-and-cities-v20260331-detect-1000_epochs.pt
```
GeoIntel exposed the file as
`yolo-remote-sensing-photovoltaic-v8l-detect-1000-pt` with SHA256
`242ff4ab889569278f0eb9fcd22eb2c4bf2a52e48d05d89cc7cfa7941165d203`, and
YOLO preflight loaded it without downloads. On the live dense matrix it missed
most buildings and scored far below `geointel-building-yolov8n-expanded160e50-pt`
on Geel, Mol, Turnhout and Retie. On Kasterlee-bos it was clean and precise,
but that sparse-AOI behavior is not enough for V1 extraction. Keep it as
benchmark evidence only, not as a default model.
Export calibration QA evidence for visual review:
```bash