Commit 66a8c8c3 authored by Cresson Remi's avatar Cresson Remi

DOC: add some nice pictures

parent bcad8381
# OTBTensorflow
This remote module of the [Orfeo ToolBox](https://www.orfeo-toolbox.org) (OTB) aims to provide a deep learning framework targeting remote sensing images processing.
This remote module of the [Orfeo ToolBox](https://www.orfeo-toolbox.org) provides a generic, multi purpose deep learning framework, targeting remote sensing images processing.
It contains a set of new process objects that internally invoke [Tensorflow](https://www.tensorflow.org/), and a bunch of user-oriented applications to perform deep learning with real-world remote sensing images.
Applications can be used to build OTB pipelines from Python or C++ APIs.
*Main highlights*
- Sampling,
- Training, supporting save/restore/import operations (a model can be trained from scratch or fine-tuned),
- Serving models with support of OTB streaming mechanism
- Serving models with support of OTB streaming mechanism. Meaning (1) not limited by images sizes, (2) can be used as a "lego" in any OTB pipeline and preserve streaming, (3) MPI support available (use multiple processing unit to generate one single output image)
*Examples*
<div style="text-align:center"><img src ="doc/pix2pix.png" />
<figure>
<img src="doc/pix2pix.png" alt="Image translation (pix2pix)" />
<figcaption>Transform a Spot-7 image into a Wikimedia Map (pix2pix)</figcaption>
</figure>
</div>
# How to install
This remote module has been tested successfully on Ubuntu 18 and CentOs 7 with CUDA drivers.
This remote module has been tested successfully on Ubuntu 18 and CentOs 7 with last CUDA drivers.
## Build OTB
First, **build the latest *develop* branch of OTB from sources**. You can check the [OTB documentation](https://www.orfeo-toolbox.org/SoftwareGuide/SoftwareGuidech2.html) which details all the steps, if fact it is quite easy thank to the SuperBuild.
......@@ -150,7 +158,8 @@ cp -r /work/tf/tensorflow/third_party /work/tf/installdir/include
cp -r /tmp/proto/include/* /work/tf/installdir/include
cp -r /tmp/eigen/include/eigen3/* /work/tf/installdir/include
cp /work/tf/tensorflow/tensorflow/contrib/makefile/downloads/nsync/public/* /work/tf/installdir/include/
find /work/tf/tensorflow/tensorflow/contrib/makefile/downloads/absl/absl/ -name '*.h' -exec cp --parents \{\} /work/tf/installdir/include/ \;
# the goal of the following command line is to put the absl headers in /work/tf/installdir/include/absl and preserving the folders structure
find /work/tf/tensorflow/tensorflow/contrib/makefile/downloads/absl/absl/ -name '*.h' -exec cp --parents \{\} /work/tf/installdir/include/ \;
# Cleaning
find /work/tf/installdir/ -name "*.cc" -type f -delete
......@@ -489,7 +498,8 @@ otbcli_TensorflowModelServe -source1.il spot7.tif -source1.placeholder x1 -sourc
# Tutorial
A complete tutorial is available at [MDL4EO's blog](https://mdl4eo.irstea.fr/2019/01/04/an-introduction-to-deep-learning-on-remote-sensing-images-tutorial/)
# Contact
You can contact Rémi Cresson if you have any issues with this remote module at remi [dot] cresson [at] irstea [dot] fr
You can contact R��mi Cresson if you have any issues with this remote module at remi [dot] cresson [at] irstea [dot] fr
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