{"name": "GeoSeg Studio", "package_name": "GeoSegStudio", "description": "Full-pipeline deep learning semantic segmentation for geospatial raster data.", "about": "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 \u2014 all without leaving QGIS.", "homepage": "https://github.com/dronnix-io/GeoSegStudio", "repository": "https://github.com/dronnix-io/GeoSegStudio.git", "tracker": "https://github.com/dronnix-io/GeoSegStudio/issues", "author": "Salar Ghaffarian", "tags": ["raster", "remote sensing", "training", "segmentation", "deep learning", "neural network", "ai", "semantic segmentation", "pytorch", "u-net"], "downloads": 343, "latest_version": "1.0.0", "versions": [{"version": "1.0.0", "experimental": false, "qgis_min": "3.34.0", "qgis_max": "3.99.0", "downloads": 343, "uploaded_by": "salarghaffarian", "upload_datetime": "2026-04-04T17:31:24.076373"}]}