Instructions to use torchgeo/fields-of-the-world with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TorchGeo
How to use torchgeo/fields-of-the-world with TorchGeo:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Model weights from the release at https://github.com/fieldsoftheworld/ftw-baselines/releases/tag/Pretrained-Models
The "full" models are trained on all country data in the Fields of The World dataset, while the CCBY models are trained according to the subset described here.
Example usage:
import segmentation_models_pytorch as smp
import torch
model = smp.Unet(
encoder_name="efficientnet-b3",
encoder_weights=None,
in_channels=8,
classes=2
)
model.load_state_dict(torch.load("ftw-2class-full_unet-efficientnetb3_rgbnir_f2444768.pth", weights_only=True))
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