{"name": "AI Edit by TerraLab", "package_name": "AI_Edit", "description": "Show a project on real aerial imagery, from a text prompt: a redevelopment before it is built, a street planted with trees, a flood, or an orthophoto redrawn as a clean site plan. Land cover maps, cloud and object removal too. Georeferenced output.", "about": "Show a project before it exists, on the aerial imagery you already have open\n\n\u2022 Select an area, write what you want, get the result back as a georeferenced layer on the same extent and CRS as your source imagery, tagged as AI-generated\n\n\u2022 The most used case: an orthophoto redrawn as a clean illustrative site plan. Then redevelopments, planted streets, densified blocks, parks, solar farms, flood and sea level scenarios, enhanced aerials, clouds and cars removed, land cover drawn as flat colours\n\n\u2022 Works on any raster on your map: GeoTIFF, JPG, PNG, and online basemaps (WMS, XYZ tiles). Vector layers and other rasters can guide the result as references\n\n\u2022 Guide the result: reference images or layers, a sketch on the map, iterations, and a before/after slider\n\n\u2022 Vectorize: a generated map with flat colours becomes editable polygons, exported to GeoPackage, Shapefile or GeoJSON\n\n\u2022 100+ ready-made prompts, ranked by what people actually run, or write your own\n\n\u2022 What it is not: a preview, not a document. No dimensions, no legal value, not a site plan for a permit. Not a detector: for building, tree or parcel outlines with real geometry, use AI Segmentation. Not a prediction: a flood scenario is an illustration\n\n\u2022 Windows, macOS, Linux, no GPU needed. Free tier without a card. Powered by Google's Nano Banana image model, run on TerraLab servers", "homepage": "https://terra-lab.ai/ai-edit", "repository": "https://github.com/TerraLabAI/QGIS_AI-Edit", "tracker": "https://github.com/TerraLabAI/QGIS_AI-Edit/issues", "author": "Yvann and Lilien from TerraLab", "tags": ["ai", "remote sensing", "ia", "drone", "satellite imagery", "raster", "artificial intelligence", "vegetation", "urban planning", "geotiff", "generative ai", "image generation", "image editing", "machine learning", "terrain", "deep learning", "satellite", "cloud removal", "nano banana", "vectorization", "super resolution", "land use", "upscaling", "digitizing", "land cover", "classification", "vector", "sentinel", "uav", "ortofoto", "restoration", "remote-sensing", "shapefile", "vetor", "orthomosaic", "flood", "landsat", "precision agriculture", "aerial", "orthophoto", "urbanisme", "flooding", "landcover", "simulation", "inundation", "inpainting", "georreferenciamento", "climate change", "archaeology", "copernicus", "cloud masking", "image classification", "neural network", "sentinel-2", "agriculture", "gpkg", "feature extraction", "image processing", "multispectral", "building detection", "geojson", "computer vision", "urban", "energy", "lulc", "cartography", "solar", "enhancement", "colorization", "satellite images", "buildings", "georeferencing"], "downloads": 28379, "latest_version": "1.10.0", "versions": [{"version": "1.10.0", "experimental": false, "qgis_min": "3.22.0", "qgis_max": "4.99.0", "downloads": 777, "uploaded_by": "yvannbarbot", "upload_datetime": "2026-09-28T10:49:37.879549"}, {"version": "1.9.1", "experimental": false, "qgis_min": "3.22.0", "qgis_max": "4.99.0", "downloads": 512, "uploaded_by": "yvannbarbot", "upload_datetime": "2026-09-24T12:18:00.703414"}, {"version": "1.9.0", "experimental": false, "qgis_min": "3.22.0", "qgis_max": "4.99.0", "downloads": 558, "uploaded_by": "yvannbarbot", "upload_datetime": "2026-09-18T11:51:12.430306"}]}