Metadata-Version: 2.1
Name: pytorch_eo
Version: 21.9.25
Summary: DL4EO
Home-page: https://github.com/earthpulse/pytorch_eo
Author: earthpulse
Author-email: it@earthpulse.es
License: MIT
Description: # Pytorch EO
        
        Deep Learning for Earth Observation applications and research.
        
        > 🚧 This project is in early development, so bugs and breaking changes are expected until we reach a stable version.
        
        ## Installation
        
        Make sure that you have the dependencies installed.
        
        ```
        pip install pytorch-eo
        ```
        
        ## Dependencies
        
        Pytorch EO is built on top of:
        
        - [Pytorch](https://pytorch.org/)
        - [Torchvision](https://pytorch.org/vision/stable/index.html)
        - [Pytorch-Lightning](https://www.pytorchlightning.ai/)
        - [Rasterio](https://rasterio.readthedocs.io/en/latest/)
        
        Do you need to learn these libraries first ? NO! You can just get started with our [examples](https://github.com/earthpulse/pytorch_eo/tree/main/examples) and [tutorials](https://github.com/earthpulse/pytorch_eo/tree/main/tutorials). However, if you plan to use Pytorch EO extensively and want to get the most out of it, you may have to become familiar with them.
        
        ## Examples
        
        Learn by doing with our [examples](https://github.com/earthpulse/pytorch_eo/tree/main/examples).
        
        ### Ready to use Datasets
        
        - [EuroSAT](https://github.com/phelber/EuroSAT)
        
        <!-- ### Build your own Datasets
        
        Using SCAN you can annotate your own data and access it directly through Pytorch EO. -->
        
        
        ## Research
        
        Pytorch EO can be a useful tool for research:
        
        - Flexibility to build new models
        - Reproducibility: use same data splits and random seeds to compare with others
        
        See the [examples](https://github.com/earthpulse/pytorch_eo/tree/main/examples).
        
        ## Production
        
        Pytorch EO was built with production in mind from the beginning:
        
        - Optimize model for production
        - Export models to torchscript
        <!-- - Upload models to our Models Universe
        - Use models directly through SPAI -->
        
        See the [examples](https://github.com/earthpulse/pytorch_eo/tree/main/examples).
        
        <!-- ## Documentation
        
        Read our [docs](https://earthpulse.github.io/pytorch_eo/). -->
        
        ## Contributing
        
        Read the [CONTRIBUTING](https://github.com/earthpulse/pytorch_eo/blob/main/CONTRIBUTING.md) guide.
        
Keywords: deep learning,earth observation,neural networks,pytorch,pytorch lightning
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Build Tools
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Description-Content-Type: text/markdown
