Commit 1be93daf authored by Narcon Nicolas's avatar Narcon Nicolas
Browse files

First commit

parent fad78698
# Use Tensorflow, or not
option(OTB_USE_TENSORFLOW "Enable Tensorflow dependent applications" OFF)
message("Tensorflow support enabled")
# find Tensorflow INCLUDE DIR
set(tensorflow_include_dir "" CACHE PATH "The include directory of tensorflow")
# find Tensorflow LIBRARIES
find_library(TENSORFLOW_CC_LIB NAMES libtensorflow_cc)
find_library(TENSORFLOW_FRAMEWORK_LIB NAMES libtensorflow_framework)
message("Tensorflow support disabled")
##### Configurable Dockerfile with multi-stage build - Author: Vincent Delbar
## Mandatory
# ----------------------------------------------------------------------------
# Init base stage - will be cloned as intermediate build env
FROM $BASE_IMG AS otbtf-base
### System packages
COPY tools/docker/build-deps-*.txt ./
ARG DEBIAN_FRONTEND=noninteractive
RUN apt-get update -y && apt-get upgrade -y \
&& cat build-deps-cli.txt | xargs apt-get install --no-install-recommends -y \
&& apt-get clean && rm -rf /var/lib/apt/lists/*
# Optional GUI
ARG GUI=false
RUN if $GUI; then \
apt-get update -y \
&& cat build-deps-gui.txt | xargs apt-get install --no-install-recommends -y \
&& apt-get clean && rm -rf /var/lib/apt/lists/* ; fi
### Python3 links and pip packages
RUN ln -s /usr/bin/python3 /usr/local/bin/python && ln -s /usr/bin/pip3 /usr/local/bin/pip
# NumPy version is conflicting with system's gdal dep and may require venv
ARG NUMPY_SPEC="==1.19.*"
RUN pip install --no-cache-dir -U pip wheel mock six future deprecated "numpy$NUMPY_SPEC" \
&& pip install --no-cache-dir --no-deps keras_applications keras_preprocessing
# ----------------------------------------------------------------------------
# Tmp builder stage - dangling cache should persist until "docker builder prune"
FROM otbtf-base AS builder
# A smaller value may be required to avoid OOM errors when building OTB GUI
RUN mkdir -p /src/tf /opt/otbtf/bin /opt/otbtf/include /opt/otbtf/lib
WORKDIR /src/tf
RUN git config --global advice.detachedHead false
### TF
ARG TF=v2.5.0
# Install bazelisk (will read .bazelversion and download the right bazel binary - latest by default)
RUN wget -qO /opt/otbtf/bin/bazelisk \
&& chmod +x /opt/otbtf/bin/bazelisk \
&& ln -s /opt/otbtf/bin/bazelisk /opt/otbtf/bin/bazel
ARG BZL_TARGETS="// //tensorflow/tools/pip_package:build_pip_package"
# "--config=opt" will enable 'march=native' (otherwise read comments about CPU compatibilty and edit CC_OPT_FLAGS in
ARG BZL_CONFIGS="--config=nogcp --config=noaws --config=nohdfs --config=opt"
# "--compilation_mode opt" is already enabled by default (see tf repo .bazelrc and
ARG BZL_OPTIONS="--verbose_failures --remote_cache=http://localhost:9090"
# Build
COPY tools/docker/ ./
RUN git clone --single-branch -b $TF \
&& cd tensorflow \
&& export PATH=$PATH:/opt/otbtf/bin \
&& export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/opt/otbtf/lib \
&& bash -c '\
source ../ \
&& ./configure \
&& export TMP=/tmp/bazel \
&& bazel $BZL_CMD --jobs="HOST_CPUS*$CPU_RATIO" ' \
# Installation - split here if you want to check files ^
#RUN cd tensorflow \
&& ./bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/tensorflow_pkg \
&& pip3 install --no-cache-dir --prefix=/opt/otbtf /tmp/tensorflow_pkg/tensorflow*.whl \
&& ln -s /opt/otbtf/lib/python3.* /opt/otbtf/lib/python3 \
&& cp -P bazel-bin/tensorflow/* /opt/otbtf/lib/ \
&& ln -s $(find /opt/otbtf -type d -wholename "*/site-packages/tensorflow/include") /opt/otbtf/include/tf \
# The only missing header in the wheel
&& cp tensorflow/cc/saved_model/tag_constants.h /opt/otbtf/include/tf/tensorflow/cc/saved_model/ \
# Symlink external libs (required for MKL - libiomp5)
&& for f in $(find -L /opt/otbtf/include/tf -wholename "*/external/*/*.so"); do ln -s $f /opt/otbtf/lib/; done \
# Compress and save TF binaries
&& ( ! $ZIP_TF_BIN || zip -9 -j --symlinks /opt/otbtf/tf-$ tensorflow/cc/saved_model/tag_constants.h bazel-bin/tensorflow/* /tmp/tensorflow_pkg/tensorflow*.whl ) \
# Cleaning
&& rm -rf bazel-* /src/tf /root/.cache/ /tmp/*
### OTB
ARG GUI=false
ARG OTB=7.3.0
RUN mkdir /src/otb
WORKDIR /src/otb
# SuperBuild OTB
COPY tools/docker/build-flags-otb.txt ./
RUN git clone --single-branch -b $OTB \
&& mkdir -p build \
&& cd build \
# Set GL/Qt build flags
&& if $GUI; then \
sed -i -r "s/-DOTB_USE_(QT|OPENGL|GL[UFE][WT])=OFF/-DOTB_USE_\1=ON/" ../build-flags-otb.txt; fi \
# Possible ENH: superbuild-all-dependencies switch, with separated build-deps-minimal.txt and build-deps-otbcli.txt)
#&& if $OTB_SUPERBUILD_ALL; then sed -i -r "s/-DUSE_SYSTEM_([A-Z0-9]*)=ON/-DUSE_SYSTEM_\1=OFF/ " ../build-flags-otb.txt; fi \
&& OTB_FLAGS=$(cat "../build-flags-otb.txt") \
&& cmake ../otb/SuperBuild -DCMAKE_INSTALL_PREFIX=/opt/otbtf $OTB_FLAGS \
&& make -j $(python -c "import os; print(round( os.cpu_count() * $CPU_RATIO ))")
### OTBTF - copy (without .git/) or clone repository
COPY . /src/otbtf
#RUN git clone /src/otbtf
RUN ln -s /src/otbtf /src/otb/otb/Modules/Remote/otbtf
# Rebuild OTB with module
RUN cd /src/otb/build/OTB/build \
&& export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/opt/otbtf/lib \
&& export PATH=$PATH:/opt/otbtf/bin \
&& cmake /src/otb/otb \
-Dtensorflow_include_dir=/opt/otbtf/include/tf \
# Forcing TF>=2, this Dockerfile hasn't been tested with v1 + missing link for in the wheel
-DTENSORFLOW_CC_LIB=/opt/otbtf/lib/ \
-DTENSORFLOW_FRAMEWORK_LIB=/opt/otbtf/lib/python3/site-packages/tensorflow/ \
&& make install -j $(python -c "import os; print(round( os.cpu_count() * $CPU_RATIO ))") \
# Cleaning
&& ( $GUI || rm -rf /opt/otbtf/bin/otbgui* ) \
&& ( $KEEP_SRC_OTB || rm -rf /src/otb ) \
&& rm -rf /root/.cache /tmp/*
# Symlink executable python files in PATH
RUN for f in /src/otbtf/python/*.py; do if [ -x $f ]; then ln -s $f /opt/otbtf/bin/; fi; done
# ----------------------------------------------------------------------------
# Final stage
FROM otbtf-base
LABEL maintainer="Remi Cresson <remi.cresson[at]inrae[dot]fr>"
# Copy files from intermediate stage
COPY --from=builder /opt/otbtf /opt/otbtf
COPY --from=builder /src /src
# System-wide ENV
ENV PATH="/opt/otbtf/bin:$PATH"
ENV PYTHONPATH="/opt/otbtf/lib/python3/site-packages:/opt/otbtf/lib/otb/python:/src/otbtf/python"
ENV OTB_APPLICATION_PATH="/opt/otbtf/lib/otb/applications"
# Default user, directory and command (bash is the entrypoint when using 'docker create')
RUN useradd -s /bin/bash -m otbuser
WORKDIR /home/otbuser
# Admin rights without password
RUN if $SUDO; then \
usermod -a -G sudo otbuser \
&& echo "otbuser ALL=(ALL) NOPASSWD:ALL" >> /etc/sudoers; fi
# Set /src/otbtf ownership to otbuser (but you still need 'sudo -i' in order to rebuild TF or OTB)
RUN chown -R otbuser:otbuser /src/otbtf
# This won't prevent ownership problems with volumes if you're not UID 1000
USER otbuser
# User-only ENV
# Test python imports
RUN python -c "import tensorflow"
RUN python -c "import otbtf, tricks"
RUN python -c "import otbApplication as otb; otb.Registry.CreateApplication('ImageClassifierFromDeepFeatures')"
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# OTBTF: Orfeo ToolBox meets TensorFlow
This remote module of the [Orfeo ToolBox]( 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](, 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.
## Features
### OTB Applications
- Sample patches in remote sensing images with `PatchesExtraction`,
- Model training, supporting save/restore/import operations (a model can be trained from scratch or fine-tuned) with `TensorflowModelTrain`,
- Inference with support of OTB streaming mechanism with `TensorflowModelServe`. The streaming mechanism means (1) no limitation with images sizes, (2) inference can be used as a "lego" in any OTB pipeline (using C++ or Python APIs) and preserving streaming, (3) MPI support available (use multiple processing unit to generate one single output image)
### Python
This is a work in progress. For now, `` provides a set of helpers to build deep nets, and `` provides datasets which can be used in Tensorflow pipelines to train networks from python.
## Portfolio
Below are some screen captures of deep learning applications performed at large scale with OTBTF.
- Image to image translation (Spot-7 image --> Wikimedia Map using CGAN)
<img src ="doc/images/pix2pix.png" />
- Landcover mapping (Spot-7 images --> Building map using semantic segmentation)
<img src ="doc/images/landcover.png" />
- Image enhancement (Enhancement of Sentinel-2 images at 1.5m using SRGAN)
<img src ="doc/images/supresol.png" />
You can read more details about these applications on [this blog](
## How to install
For now you have two options: either use the existing **docker image**, or build everything **from source**.
### Docker
Use the latest image from dockerhub:
docker pull mdl4eo/otbtf2.4:cpu
docker run -u otbuser -v $(pwd):/home/otbuser mdl4eo/otbtf2.4:cpu otbcli_PatchesExtraction -help
Read more in the [docker use documentation](doc/
### Build from sources
Read more in the [build from sources documentation](doc/
## How to use
- Reading [the applications documentation](doc/ will help, of course 😉
- A small [tutorial]( on MDL4EO's blog
- in the `python` folder are provided some [ready-to-use deep networks, with documentation and scientific references](doc/
- A book: *Cresson, R. (2020). Deep Learning for Remote Sensing Images with Open Source Software. CRC Press.* Use QGIS, OTB and Tensorflow to perform various kind of deep learning sorcery on remote sensing images (patch-based classification for landcover mapping, semantic segmentation of buildings, optical image restoration from joint SAR/Optical time series).
- Check [our repository]( containing stuff (data and models) to begin with with!
## Contribute
Every one can **contribute** to OTBTF! Don't be shy.
## Cite
title={A framework for remote sensing images processing using deep learning techniques},
author={Cresson, R{\'e}mi},
journal={IEEE Geoscience and Remote Sensing Letters},
# Tensorflow-dependent APPS
SOURCES otbTensorflowModelServe.cxx ${${otb-module}_SYSTEM_INCLUDE_DIRS} "${tensorflow_include_dir}"
SOURCES otbTensorflowModelTrain.cxx ${${otb-module}_SYSTEM_INCLUDE_DIRS} "${tensorflow_include_dir}"
OTB_CREATE_APPLICATION(NAME TrainClassifierFromDeepFeatures
SOURCES otbTrainClassifierFromDeepFeatures.cxx ${${otb-module}_SYSTEM_INCLUDE_DIRS} "${tensorflow_include_dir}"
OTB_CREATE_APPLICATION(NAME ImageClassifierFromDeepFeatures
SOURCES otbImageClassifierFromDeepFeatures.cxx ${${otb-module}_SYSTEM_INCLUDE_DIRS} "${tensorflow_include_dir}"
# Tensorflow-independent APPS
SOURCES otbPatchesSelection.cxx
SOURCES otbPatchesExtraction.cxx
SOURCES otbLabelImageSampleSelection.cxx
SOURCES otbDensePolygonClassStatistics.cxx
Copyright (c) Remi Cresson (IRSTEA). All rights reserved.
This software is distributed WITHOUT ANY WARRANTY; without even
PURPOSE. See the above copyright notices for more information.
#include "otbWrapperApplication.h"
#include "otbWrapperApplicationFactory.h"
#include "otbStatisticsXMLFileWriter.h"
#include "otbWrapperElevationParametersHandler.h"
#include "otbVectorDataToLabelImageFilter.h"
#include "otbImageToNoDataMaskFilter.h"
#include "otbStreamingStatisticsMapFromLabelImageFilter.h"
#include "otbVectorDataIntoImageProjectionFilter.h"
#include "otbImageToVectorImageCastFilter.h"
#include "otbOGR.h"
namespace otb
namespace Wrapper
/** Utility function to negate std::isalnum */
bool IsNotAlphaNum(char c)
return !std::isalnum(c);
class DensePolygonClassStatistics : public Application
/** Standard class typedefs. */
typedef DensePolygonClassStatistics Self;
typedef Application Superclass;
typedef itk::SmartPointer<Self> Pointer;
typedef itk::SmartPointer<const Self> ConstPointer;
/** Standard macro */
itkTypeMacro(DensePolygonClassStatistics, otb::Application);
/** DataObjects typedef */
typedef UInt32ImageType LabelImageType;
typedef UInt8ImageType MaskImageType;
typedef VectorData<> VectorDataType;
/** ProcessObjects typedef */
typedef otb::VectorDataIntoImageProjectionFilter<VectorDataType,
FloatVectorImageType> VectorDataReprojFilterType;
typedef otb::VectorDataToLabelImageFilter<VectorDataType, LabelImageType> RasterizeFilterType;
typedef otb::VectorImage<MaskImageType::PixelType> InternalMaskImageType;
typedef otb::ImageToNoDataMaskFilter<FloatVectorImageType, MaskImageType> NoDataMaskFilterType;
typedef otb::ImageToVectorImageCastFilter<MaskImageType, InternalMaskImageType> CastFilterType;
typedef otb::StreamingStatisticsMapFromLabelImageFilter<InternalMaskImageType,
LabelImageType> StatsFilterType;
typedef otb::StatisticsXMLFileWriter<FloatVectorImageType::PixelType> StatWriterType;
void DoInit() override
SetDescription("Computes statistics on a training polygon set.");
// Documentation
SetDocLongDescription("The application processes a dense set of polygons "
"intended for training (they should have a field giving the associated "
"class). The geometries are analyzed against a support image to compute "
"statistics : \n"
" - number of samples per class\n"
" - number of samples per geometry\n");
SetDocAuthors("Remi Cresson");
SetDocSeeAlso(" ");
AddParameter(ParameterType_InputImage, "in", "Input image");
SetParameterDescription("in", "Support image that will be classified");
AddParameter(ParameterType_InputVectorData, "vec", "Input vectors");
SetParameterDescription("vec","Input geometries to analyze");
AddParameter(ParameterType_OutputFilename, "out", "Output XML statistics file");
SetParameterDescription("out","Output file to store statistics (XML format)");
AddParameter(ParameterType_ListView, "field", "Field Name");
SetParameterDescription("field","Name of the field carrying the class number in the input vectors.");
ElevationParametersHandler::AddElevationParameters(this, "elev");
// Doc example parameter settings
SetDocExampleParameterValue("in", "support_image.tif");
SetDocExampleParameterValue("vec", "variousVectors.shp");
SetDocExampleParameterValue("field", "label");
void DoUpdateParameters() override
if ( HasValue("vec") )
std::string vectorFile = GetParameterString("vec");