eoml 0.9.1

library to manage GIS operation

EOML - Earth Observation Machine Learning

A Python library for managing GIS operations and machine learning workflows for remote sensing applications.

Overview

EOML provides a comprehensive toolkit for processing Earth observation data and building machine learning models for satellite imagery analysis. The library integrates rasterio, PyTorch, and Google Earth Engine to streamline geospatial machine learning workflows.

Features

• PyTorch Integration: Pre-built CNN architectures and training utilities for remote sensing

Installation

PyPI

pip install eoml

Developement mode

Installation in development mode:

pip install -e .

Running Tests

pytest tests/

Contributing

Contributions are welcome! Please ensure code follows the project style and includes appropriate docstrings.

License

MIT License

Author

Thibaud Vantalon Email: [e-mail] Organization: CGIAR

Citation

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

@software{eoml,
  author = {Vantalon, Thibaud},
  title = {EOML: Earth Observation Machine Learning},
  year = {2024},
  url = {https://ciatgit.ciat.cgiar.org/Data_driven_sustainability_public/terra-i/eoml#}
}