floodsr 0.1.3

Flood super-resolution CLI and library using ONNX Runtime.

floodsr

AI-powered super-resolution for flood hazard rasters that turns coarse water grids into sharp, decision-ready inundation maps. Fuse low-res flood grids with high-res DEMs to infer fine-scale flood patterns. Built on PyTorch and GDAL, floodsr is designed for geospatial practitioners who need to enhance flood hazard data for better risk assessment and planning.

• Documentation: https://floodsr.readthedocs.io/en/latest/
• Contribute: https://github.com/cefect/floodsr/blob/master/CONTRIBUTING.md

Implemented models (see floodsr/models.json):

• ResUNet_16x_DEM: 16x DEM-conditioned ResUNet

Installation

see documentation for details.

basic install

pipx install floodsr

extended install

for handling rasters too large for memory, floodsr requires GDAL backends.

# advanced install for VRT workflows
conda create -n floodsr-gdal -c conda-forge python=3.12 gdal -y
conda activate floodsr-gdal
python -m pip install floodsr

Use

See the Getting Started guide for a quick intro to using the CLI.

List available model versions:

Fetch a model by version into the default cache:

floodsr models fetch ResUNet_16x_DEM 

Enhance a low-resolution flood hazard raster to high resolution (tohr), fetching the DEM from the HRDEM Mosaic data source.

floodsr tohr --in lowres032.tif --fetch-hrdem 

Enhance with a local DEM file:

floodsr tohr --in lowres032.tif --dem hires002_dem.tif  

Doctor diagnostics:

floodsr doctor

For more details, see the User Guide.