Otbtf
Deep learning with otb (mirror of https://forgemia.inra.fr/orfeo-toolbox/otbtf)
Install / Use
/learn @remicres/OtbtfREADME
OTBTF: Orfeo ToolBox meets TensorFlow
<p align="center"> <img src="doc/images/logo.png" width="160px"> <br> <a href="https://forgemia.inra.fr/orfeo-toolbox/otbtf/-/releases"> <img src="https://forgemia.inra.fr/orfeo-toolbox/otbtf/-/badges/release.svg"> </a> <a href="https://forgemia.inra.fr/orfeo-toolbox/otbtf/-/commits/develop"> <img src="https://forgemia.inra.fr/orfeo-toolbox/otbtf/badges/develop/pipeline.svg"> </a> <img src='https://readthedocs.org/projects/otbtf/badge/?version=latest' alt='Documentation Status' /> <a href="LICENSE"> <img src="https://img.shields.io/badge/License-Apache%202.0-blue.svg"> </a> <img src="https://img.shields.io/badge/dynamic/json?formatter=metric&color=blue&label=Docker%20pull&query=%24.pull_count&url=https://hub.docker.com/v2/repositories/mdl4eo/otbtf"> </p>OTBTF is a remote module of the Orfeo ToolBox. It provides a generic, multi-purpose deep learning framework, targeting remote sensing images processing. It contains a set of process objects for OTB that internally invoke Tensorflow, and new OTB applications to perform deep learning with real-world remote sensing images. Applications can be used to build OTB pipelines from Python or C++ APIs. OTBTF also includes a python API to build quickly Keras compliant models suited for remote sensing imagery, easy to train in distributed environments.
Documentation
The documentation is available on readthedocs as well as a comprehensive tutorial.
Use
You can use our latest GPU enabled docker images.
docker run --gpus=all -ti mdl4eo/otbtf:latest-gpu otbcli_PatchesExtraction
docker run --gpus=all -ti mdl4eo/otbtf:latest-gpu python -c "import otbtf"
You can also build OTBTF from sources (see the documentation)
Cite
@article{cresson2018framework,
title={A framework for remote sensing images processing using deep learning techniques},
author={Cresson, R{\'e}mi},
journal={IEEE Geoscience and Remote Sensing Letters},
volume={16},
number={1},
pages={25--29},
year={2018},
publisher={IEEE}
}
