GeoSeg Studio
Full-pipeline deep learning semantic segmentation for geospatial raster data.
GeoSeg Studio is a complete deep learning segmentation environment for QGIS. It covers the full workflow in one plugin: prepare training data (clip, split, augment), train your own segmentation model, evaluate performance, run predictions on new rasters, and post-process vector outputs — all without leaving QGIS. Runs on both QGIS 3 (Qt5) and QGIS 4 (Qt6). EXTERNAL DEPENDENCY: PyTorch and torchvision are not bundled. On first run the plugin offers to install them with pip into an isolated virtual environment that it manages itself; nothing outside that environment is modified. This requires an internet connection and about 5 GB of free disk space, and can be skipped or done manually (see requirements.txt). GPU acceleration needs an NVIDIA card with driver 522.06 or newer; the installer detects the driver and preselects a matching CUDA build. On macOS, on AMD/Intel GPUs, and where no suitable NVIDIA driver is present the plugin runs on CPU, which is considerably slower for training.