floodsr 0.0.1

Flood super-resolution CLI and library using ONNX Runtime.

floodsr

Super-Resolution for flood hazard rasters. Ingests lores water grid and hires DEM and infers a hires water grid using the specified model.

Documentation: https://floodsr.readthedocs.io/en/latest/

Implemented models (see floodsr/models.json):

• ResUNet_16x_DEM: 16x DEM-conditioned ResUNet
• CostGrow (future)

Implemented backend:

• ONNX Runtime

Installation

# recommended: isolated CLI install for users
python -m pip install --user pipx
pipx ensurepath
pipx install floodsr

TestPyPI install:

pipx install --index-url https://test.pypi.org/simple/ --pip-args="--extra-index-url https://pypi.org/simple" floodsr

Developer install:

pip install -e ".[dev]"

Use

Current CLI surface includes model registry, tohr raster execution, and runtime diagnostics.

List available model versions:

# dev shortcut for the CLI
alias floodsr='python -m floodsr.cli'

floodsr models list

Fetch a model by version into the default cache:

floodsr models fetch ResUNet_16x_DEM --force

tohr using HRDEM as DEM

floodsr tohr -f --in tests/data/2407_FHIMP_tile/lowres032.tif 

Run one ToHR pass from raster inputs:

# simple tile
floodsr tohr \
  --in tests/data/2407_FHIMP_tile/lowres032.tif \
  --dem tests/data/2407_FHIMP_tile/hires002_dem.tif  

# larger raster w/ windowing and tiling and rescaling
floodsr tohr \
  --in tests/data/rss_mersch_A/lowres030.tif \
  --dem tests/data/rss_mersch_A/hires002_dem.tif \
  --out pred_sr.tif
 

Run ToHR with explicit local model path:

floodsr tohr \
  --in tests/data/2407_FHIMP_tile/lowres032.tif \
  --dem tests/data/2407_FHIMP_tile/hires002_dem.tif \
  --out ./tmp/pred_sr.tif \
  --model-path _inputs/ResUNet_16x_DEM/model_infer.onnx

Doctor diagnostics:

floodsr doctor