import torch
from terratorch.tasks import SemanticSegmentationTask

# Load the model
model = SemanticSegmentationTask.load_from_checkpoint("path/to/checkpoint.ckpt")
model.eval()

# Your inference code here

Training Data

The model was trained on flood simulation data from multiple US counties, including:

DEM data from USGS National Map
Precipitation data from NOAA Atlas 14
Simulated flood depth labels

Performance

The model achieves state-of-the-art performance on flood segmentation tasks across diverse geographical regions.

Limitations

Model is trained primarily on US geographical data
Performance may vary on international datasets
Requires specific input preprocessing

Citation

If you use this model in your research, please cite:

@misc{flood-foundation-model-prithvi-100m,
  title={Flood Risk Foundation Model: Prithvi-100M},
  author={FloodRisk-DL Team},
  year={2024},
  url={https://huggingface.co/chrimerss/flood-foundation-prithvi-100m}
}