BatiScan IA
AI building mapping for QGIS: detect building footprints on satellite imagery (no points needed), or turn field-collected building points into footprints with Segment Anything.
BatiScan maps buildings from satellite or aerial imagery with AI. The automatic mode uses the BatiScan Sahel v2 model, a U-Net trained on nine villages of Mali (30 cm/px), from round huts to rectangular metal and earth roofs; it separates adjacent buildings and processes a whole village in seconds on a CPU. The model (98 MB) is downloaded on first use and is provided for research and testing, not for commercial use. BatiScan also turns building points collected in the field into footprints with Segment Anything (MobileSAM in ONNX, no PyTorch needed), offers a click-to-map tool, a points-versus-footprints quality report, and export of image/mask tiles to train a model for your own area. Any Deepness-compatible ONNX segmentation model can be added. Works with GeoTIFF orthophotos and XYZ/WMS basemaps (Google, Bing, Esri...). Requires the Python packages onnxruntime and opencv, which the plugin offers to install on first use. Less accurate on dense urban areas and very large buildings.