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beaconGIS — Building Damage Assessment QGIS 4 compatibility
QGIS 4 ready Active
Yes — beaconGIS — Building Damage Assessment supports QGIS 4 (declared max version 4.99.0).
AI building-level damage classification from pre/post-disaster RGB imagery, using a Siamese U-Net ensemble running on ONNX Runtime.
About
Classifies buildings into No Damage, Minor, Major, or Destroyed using a two-network deep-learning pipeline (LocalizationUNet + SiameseUNet, SeResNeXt-50 (32x4d) encoder, two-model ensemble) trained on the full public xView2/xBD dataset with Inria Aerial Image Labeling pretraining. xView2 official scorer Combined F1 = 0.7312. Designed for disaster-response teams: includes AOI clipping, CPU Fast Mode for non-GPU machines, automatic CRS-aware pre/post alignment, GSD normalization, offline template-driven SitRep generator (no LLM API), GeoPackage / GeoTIFF mask / JSON sidecar export. Runs entirely on ONNX Runtime (no PyTorch install required). Model weights (~234 MB fp16, CC BY-NC-SA 4.0) are downloaded on first use from the plugin's GitHub release page over plain HTTPS with SHA-256 verification — no account or token required. Outputs are draft assessments for human review — not authoritative ground truth.
| Author | Adem Özel |
|---|---|
| Downloads | 716 |
| Latest version | 1.1.0 |
| Last updated | 2026-06-11 (126 days ago) |
| Min QGIS | 3.16.0 |
| Max QGIS | 4.99.0 |
| QGIS 4 ready | Yes |
| Maintenance | Active |
| Categories | Remote sensing, AI & machine learning |
| Tags | remote sensing, vector, change detection, onnx, humanitarian, deep learning, satellite imagery, building damage, disaster response, xview2, siamese unet, xbd, raster |
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Maintenance: Active = updated within 1 year, Quiet = 1–3 years, Likely abandoned = over 3 years.