diff --git a/.clang-format b/.clang-format
new file mode 100644
index 0000000000000000000000000000000000000000..0b9a40282f8a247085847be735807513844c0301
--- /dev/null
+++ b/.clang-format
@@ -0,0 +1,134 @@
+BasedOnStyle: Mozilla
+Language: Cpp
+AccessModifierOffset: -2
+AlignAfterOpenBracket: Align
+AlignConsecutiveAssignments: false
+AlignConsecutiveDeclarations: true
+AlignEscapedNewlines: Left
+AlignOperands: true
+AlignTrailingComments: true
+# clang 9.0 AllowAllArgumentsOnNextLine: true
+# clang 9.0 AllowAllConstructorInitializersOnNextLine: true
+AllowAllParametersOfDeclarationOnNextLine: false
+AllowShortBlocksOnASingleLine: false
+AllowShortCaseLabelsOnASingleLine: false
+AllowShortFunctionsOnASingleLine: Inline
+# clang 9.0 AllowShortLambdasOnASingleLine: All
+# clang 9.0 features AllowShortIfStatementsOnASingleLine: Never
+AllowShortIfStatementsOnASingleLine: false
+AllowShortLoopsOnASingleLine: false
+AlwaysBreakAfterDefinitionReturnType: None
+AlwaysBreakAfterReturnType: All
+AlwaysBreakBeforeMultilineStrings: false
+AlwaysBreakTemplateDeclarations: Yes
+BinPackArguments: false
+BinPackParameters: false
+BreakBeforeBraces: Custom
+BraceWrapping:
+ # clang 9.0 feature AfterCaseLabel: false
+ AfterClass: true
+ AfterControlStatement: true
+ AfterEnum: true
+ AfterFunction: true
+ AfterNamespace: true
+ AfterObjCDeclaration: true
+ AfterStruct: true
+ AfterUnion: true
+ AfterExternBlock: true
+ BeforeCatch: true
+ BeforeElse: true
+## This is the big change from historical ITK formatting!
+# Historically ITK used a style similar to https://en.wikipedia.org/wiki/Indentation_style#Whitesmiths_style
+# with indented braces, and not indented code. This style is very difficult to automatically
+# maintain with code beautification tools. Not indenting braces is more common among
+# formatting tools.
+ IndentBraces: false
+ SplitEmptyFunction: false
+ SplitEmptyRecord: false
+ SplitEmptyNamespace: false
+BreakBeforeBinaryOperators: None
+#clang 6.0 BreakBeforeInheritanceComma: true
+BreakInheritanceList: BeforeComma
+BreakBeforeTernaryOperators: true
+#clang 6.0 BreakConstructorInitializersBeforeComma: true
+BreakConstructorInitializers: BeforeComma
+BreakAfterJavaFieldAnnotations: false
+BreakStringLiterals: true
+## The following line allows larger lines in non-documentation code
+ColumnLimit: 120
+CommentPragmas: '^ IWYU pragma:'
+CompactNamespaces: false
+ConstructorInitializerAllOnOneLineOrOnePerLine: false
+ConstructorInitializerIndentWidth: 2
+ContinuationIndentWidth: 2
+Cpp11BracedListStyle: false
+DerivePointerAlignment: false
+DisableFormat: false
+ExperimentalAutoDetectBinPacking: false
+FixNamespaceComments: true
+ForEachMacros:
+ - foreach
+ - Q_FOREACH
+ - BOOST_FOREACH
+IncludeBlocks: Preserve
+IncludeCategories:
+ - Regex: '^"(llvm|llvm-c|clang|clang-c)/'
+ Priority: 2
+ - Regex: '^(<|"(gtest|gmock|isl|json)/)'
+ Priority: 3
+ - Regex: '.*'
+ Priority: 1
+IncludeIsMainRegex: '(Test)?$'
+IndentCaseLabels: true
+IndentPPDirectives: AfterHash
+IndentWidth: 2
+IndentWrappedFunctionNames: false
+JavaScriptQuotes: Leave
+JavaScriptWrapImports: true
+KeepEmptyLinesAtTheStartOfBlocks: true
+MacroBlockBegin: ''
+MacroBlockEnd: ''
+MaxEmptyLinesToKeep: 2
+NamespaceIndentation: None
+ObjCBinPackProtocolList: Auto
+ObjCBlockIndentWidth: 2
+ObjCSpaceAfterProperty: true
+ObjCSpaceBeforeProtocolList: false
+PenaltyBreakAssignment: 2
+PenaltyBreakBeforeFirstCallParameter: 19
+PenaltyBreakComment: 300
+## The following line allows larger lines in non-documentation code
+PenaltyBreakFirstLessLess: 120
+PenaltyBreakString: 1000
+PenaltyBreakTemplateDeclaration: 10
+PenaltyExcessCharacter: 1000000
+PenaltyReturnTypeOnItsOwnLine: 200
+PointerAlignment: Middle
+ReflowComments: true
+# We may want to sort the includes as a separate pass
+SortIncludes: false
+# We may want to revisit this later
+SortUsingDeclarations: false
+SpaceAfterCStyleCast: false
+# SpaceAfterLogicalNot: false
+SpaceAfterTemplateKeyword: true
+SpaceBeforeAssignmentOperators: true
+SpaceBeforeCpp11BracedList: false
+SpaceBeforeCtorInitializerColon: true
+SpaceBeforeInheritanceColon: true
+SpaceBeforeParens: ControlStatements
+SpaceBeforeRangeBasedForLoopColon: true
+SpaceInEmptyParentheses: false
+SpacesBeforeTrailingComments: 1
+SpacesInAngles: false
+SpacesInContainerLiterals: false
+SpacesInCStyleCastParentheses: false
+SpacesInParentheses: false
+SpacesInSquareBrackets: false
+Standard: Cpp11
+StatementMacros:
+ - Q_UNUSED
+ - QT_REQUIRE_VERSION
+TabWidth: 2
+UseTab: Never
+...
diff --git a/.gitattributes b/.gitattributes
new file mode 100644
index 0000000000000000000000000000000000000000..4fb662854f3175a3c793711a89b0c4942f3cdb6a
--- /dev/null
+++ b/.gitattributes
@@ -0,0 +1,8 @@
+*.png filter=lfs diff=lfs merge=lfs -text
+*.jp2 filter=lfs diff=lfs merge=lfs -text
+*.tif filter=lfs diff=lfs merge=lfs -text
+*.data-* filter=lfs diff=lfs merge=lfs -text
+*.gpkg filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.jpg filter=lfs diff=lfs merge=lfs -text
+*.jpeg filter=lfs diff=lfs merge=lfs -text
diff --git a/.gitlab-ci.yml b/.gitlab-ci.yml
new file mode 100644
index 0000000000000000000000000000000000000000..9a9bd290b399b4875779d39ba5d6986df3b40621
--- /dev/null
+++ b/.gitlab-ci.yml
@@ -0,0 +1,119 @@
+image: gitlab-registry.irstea.fr/remi.cresson/otbtf:2.4-cpu-basic-testing
+
+variables:
+ OTB_BUILD: /src/otb/build/OTB/build # Local OTB build directory
+ OTBTF_SRC: /src/otbtf # Local OTBTF source directory
+ OTB_TEST_DIR: $OTB_BUILD/Testing/Temporary # OTB testing directory
+ ARTIFACT_TEST_DIR: $CI_PROJECT_DIR/testing
+ CRC_BOOK_TMP: /tmp/crc_book_tests_tmp
+
+workflow:
+ rules:
+ - if: $CI_MERGE_REQUEST_ID # Execute jobs in merge request context
+ - if: $CI_COMMIT_BRANCH == 'develop' # Execute jobs when a new commit is pushed to develop branch
+
+stages:
+ - Build
+ - Static Analysis
+ - Test
+ - Applications Test
+
+.update_otbtf_src: &update_otbtf_src
+ - sudo rm -rf $OTBTF_SRC && sudo ln -s $PWD $OTBTF_SRC # Replace local OTBTF source directory
+
+.compile_otbtf: &compile_otbtf
+ - cd $OTB_BUILD && sudo make install -j$(nproc --all) # Rebuild OTB with new OTBTF sources
+
+.install_pytest: &install_pytest
+ - pip3 install pytest pytest-cov pytest-order # Install pytest stuff
+
+before_script:
+ - *update_otbtf_src
+
+build:
+ stage: Build
+ allow_failure: false
+ script:
+ - *compile_otbtf
+
+flake8:
+ stage: Static Analysis
+ allow_failure: true
+ script:
+ - sudo apt update && sudo apt install flake8 -y
+ - python -m flake8 --max-line-length=120 $OTBTF_SRC/python
+
+pylint:
+ stage: Static Analysis
+ allow_failure: true
+ script:
+ - sudo apt update && sudo apt install pylint -y
+ - pylint --disable=too-many-nested-blocks,too-many-locals,too-many-statements,too-few-public-methods,too-many-instance-attributes,too-many-arguments --ignored-modules=tensorflow --max-line-length=120 --logging-format-style=new $OTBTF_SRC/python
+
+codespell:
+ stage: Static Analysis
+ allow_failure: true
+ script:
+ - sudo pip install codespell && codespell
+
+cppcheck:
+ stage: Static Analysis
+ allow_failure: true
+ script:
+ - sudo apt update && sudo apt install cppcheck -y
+ - cd $OTBTF_SRC/ && cppcheck --enable=all --error-exitcode=1 -I include/ --suppress=missingInclude --suppress=unusedFunction .
+
+ctest:
+ stage: Test
+ script:
+ - *compile_otbtf
+ - sudo rm -rf $OTB_TEST_DIR/* # Empty testing temporary folder (old files here)
+ - cd $OTB_BUILD/ && sudo ctest -L OTBTensorflow # Run ctest
+ after_script:
+ - cp -r $OTB_TEST_DIR $ARTIFACT_TEST_DIR
+ artifacts:
+ paths:
+ - $ARTIFACT_TEST_DIR/*.*
+ expire_in: 1 week
+ when: on_failure
+
+.applications_test_base:
+ stage: Applications Test
+ rules:
+ # Only for MR targeting 'develop' branch because applications tests are slow
+ - if: $CI_MERGE_REQUEST_ID && $CI_MERGE_REQUEST_TARGET_BRANCH_NAME == 'develop'
+ artifacts:
+ when: on_failure
+ paths:
+ - $CI_PROJECT_DIR/report_*.xml
+ - $ARTIFACT_TEST_DIR/*.*
+ expire_in: 1 week
+
+crc_book:
+ extends: .applications_test_base
+ script:
+ - *compile_otbtf
+ - *install_pytest
+ - cd $CI_PROJECT_DIR
+ - mkdir -p $CRC_BOOK_TMP
+ - TMPDIR=$CRC_BOOK_TMP DATADIR=$CI_PROJECT_DIR/test/data python -m pytest --junitxml=$CI_PROJECT_DIR/report_tutorial.xml $OTBTF_SRC/test/tutorial_unittest.py
+ after_script:
+ - mkdir -p $ARTIFACT_TEST_DIR
+ - cp $CRC_BOOK_TMP/*.* $ARTIFACT_TEST_DIR/
+
+sr4rs:
+ extends: .applications_test_base
+ script:
+ - *compile_otbtf
+ - *install_pytest
+ - cd $CI_PROJECT_DIR
+ - wget -O sr4rs_sentinel2_bands4328_france2020_savedmodel.zip
+ https://nextcloud.inrae.fr/s/boabW9yCjdpLPGX/download/sr4rs_sentinel2_bands4328_france2020_savedmodel.zip
+ - unzip -o sr4rs_sentinel2_bands4328_france2020_savedmodel.zip
+ - wget -O sr4rs_data.zip https://nextcloud.inrae.fr/s/qMLLyKCDieqmgWz/download
+ - unzip -o sr4rs_data.zip
+ - rm -rf sr4rs
+ - git clone https://github.com/remicres/sr4rs.git
+ - export PYTHONPATH=$PYTHONPATH:$PWD/sr4rs
+ - python -m pytest --junitxml=$CI_PROJECT_DIR/report_sr4rs.xml $OTBTF_SRC/test/sr4rs_unittest.py
+
diff --git a/CMakeLists.txt b/CMakeLists.txt
index f0bc92a6ca6ae979dbf029c86285932851460746..0a4d646a95ba9bf3cae8b93687b0a72522060dc3 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -15,7 +15,7 @@ if(OTB_USE_TENSORFLOW)
find_library(TENSORFLOW_FRAMEWORK_LIB NAMES libtensorflow_framework)
set(TENSORFLOW_LIBS "${TENSORFLOW_CC_LIB}" "${TENSORFLOW_FRAMEWORK_LIB}")
-
+ set(OTBTensorflow_THIRD_PARTY "this is a hack to skip header_tests")
else()
message("Tensorflow support disabled")
endif()
diff --git a/CONTRIBUTORS.md b/CONTRIBUTORS.md
new file mode 100644
index 0000000000000000000000000000000000000000..cd39540e7c15ad843a6f52502ea717faf1c0e38a
--- /dev/null
+++ b/CONTRIBUTORS.md
@@ -0,0 +1,8 @@
+- Remi Cresson
+- Nicolas Narcon
+- Benjamin Commandre
+- Vincent Delbar
+- Loic Lozac'h
+- Pratyush Das
+- Doctor Who
+- Jordi Inglada
diff --git a/Dockerfile b/Dockerfile
index 53e3f777910b643ae8780a14a3d7bbeb64342bf9..c9aa6e9fcb40cba228c9a4d2c0634eb055e38fdf 100644
--- a/Dockerfile
+++ b/Dockerfile
@@ -47,7 +47,7 @@ RUN wget -qO /opt/otbtf/bin/bazelisk https://github.com/bazelbuild/bazelisk/rele
&& ln -s /opt/otbtf/bin/bazelisk /opt/otbtf/bin/bazel
ARG BZL_TARGETS="//tensorflow:libtensorflow_cc.so //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 build-env-tf.sh)
+# "--config=opt" will enable 'march=native' (otherwise read comments about CPU compatibility and edit CC_OPT_FLAGS in build-env-tf.sh)
ARG BZL_CONFIGS="--config=nogcp --config=noaws --config=nohdfs --config=opt"
# "--compilation_mode opt" is already enabled by default (see tf repo .bazelrc and configure.py)
ARG BZL_OPTIONS="--verbose_failures --remote_cache=http://localhost:9090"
@@ -77,7 +77,7 @@ RUN git clone --single-branch -b $TF https://github.com/tensorflow/tensorflow.gi
# 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
- && ( ! $ZIP_TF_BIN || zip -9 -j --symlinks /opt/otbtf/tf-$TF.zip tensorflow/cc/saved_model/tag_constants.h bazel-bin/tensorflow/libtensorflow_cc.so* /tmp/tensorflow_pkg/tensorflow*.whl ) \
+ && ( ! $ZIP_TF_BIN || zip -9 -j --symlinks /opt/otbtf/tf-$TF.zip tensorflow/cc/saved_model/tag_constants.h tensorflow/cc/saved_model/signature_constants.h bazel-bin/tensorflow/libtensorflow_cc.so* /tmp/tensorflow_pkg/tensorflow*.whl ) \
# Cleaning
&& rm -rf bazel-* /src/tf /root/.cache/ /tmp/*
diff --git a/LICENSE b/LICENSE
index a1a86c14aa32ced5bb3489db5ce76447e7e18bda..236ca02805e38ec6a5a3112472a62879155b1846 100644
--- a/LICENSE
+++ b/LICENSE
@@ -188,7 +188,7 @@
identification within third-party archives.
Copyright 2018-2019 Rémi Cresson (IRSTEA)
- Copyright 2020 Rémi Cresson (INRAE)
+ Copyright 2020-2021 Rémi Cresson (INRAE)
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
diff --git a/README.md b/README.md
index a18961b3038b680b4a52f86666bc2ef8005a18d9..d29b7a6429fd126812cbdc6e7066d1b41a3350b1 100644
--- a/README.md
+++ b/README.md
@@ -18,21 +18,23 @@ Applications can be used to build OTB pipelines from Python or C++ APIs.
### Python
-This is a work in progress. For now, `tricks.py` provides a set of helpers to build deep nets, and `otbtf.py` provides datasets which can be used in Tensorflow pipelines to train networks from python.
+`otbtf.py` targets python developers that want to train their own model from python with TensorFlow or Keras.
+It provides various classes for datasets and iterators to handle the _patches images_ generated from the `PatchesExtraction` OTB application.
+For instance, the `otbtf.Dataset` class provides a method `get_tf_dataset()` which returns a `tf.dataset` that can be used in your favorite TensorFlow pipelines, or convert your patches into TFRecords.
-## Portfolio
+`tricks.py` is here for backward compatibility with codes based on OTBTF 1.x and 2.x.
-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" />
+## Examples
+Below are some screen captures of deep learning applications performed at large scale with OTBTF.
- 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)
+ - Super resolution (Sentinel-2 images upsampled with the [SR4RS software](https://github.com/remicres/sr4rs), which is based on OTBTF)
<img src ="doc/images/supresol.png" />
-You can read more details about these applications on [this blog](https://mdl4eo.irstea.fr/2019/)
+ - Image to image translation (Spot-7 image --> Wikimedia Map using CGAN. So unnecessary but fun!)
+<img src ="doc/images/pix2pix.png" />
## How to install
@@ -42,8 +44,8 @@ For now you have two options: either use the existing **docker image**, or build
Use the latest image from dockerhub:
```
-docker pull mdl4eo/otbtf2.5:cpu
-docker run -u otbuser -v $(pwd):/home/otbuser mdl4eo/otbtf2.5:cpu otbcli_PatchesExtraction -help
+docker pull mdl4eo/otbtf3.0:cpu
+docker run -u otbuser -v $(pwd):/home/otbuser mdl4eo/otbtf3.0:cpu otbcli_PatchesExtraction -help
```
Read more in the [docker use documentation](doc/DOCKERUSE.md).
@@ -59,10 +61,11 @@ Read more in the [build from sources documentation](doc/HOWTOBUILD.md).
- in the `python` folder are provided some [ready-to-use deep networks, with documentation and scientific references](doc/EXAMPLES.md).
- 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](https://github.com/remicres/otbtf_tutorials_resources) containing stuff (data and models) to begin with with!
+- Finally, take a look in the `test` folder. You will find plenty of command lines for applications tests!
## Contribute
-Every one can **contribute** to OTBTF! Don't be shy.
+Every one can **contribute** to OTBTF. Just open a PR :)
## Cite
diff --git a/RELEASE_NOTES.txt b/RELEASE_NOTES.txt
new file mode 100644
index 0000000000000000000000000000000000000000..764033051413016bf2de6441b15a915fe76840a0
--- /dev/null
+++ b/RELEASE_NOTES.txt
@@ -0,0 +1,99 @@
+Version 3.0.0-beta (20 nov 2021)
+----------------------------------------------------------------
+* Use Tensorflow 2 API everywhere. Everything is backward compatible (old models can still be used).
+* Support models with no-named inputs and outputs. OTBTF now can resolve the names! :) Just in the same order as they are defined in the computational graph.
+* Support user placeholders of type vector (int, float or bool)
+* More unit tests, spell check, better static analysis of C++ and python code
+* Improve the handling of 3-dimensional output tensors, + more explanation in error messages about output tensors dimensions.
+* Improve `PatchesSelection` to locate patches centers with corners or pixels centers depending if the patch size is odd or even.
+
+Version 2.5 (20 oct 2021)
+----------------------------------------------------------------
+* Fix a bug in otbtf.py. The `PatchesImagesReader` wasn't working properly when the streaming was disabled.
+* Improve the documentation on docker build and docker use (Thanks to Vincent@LaTelescop and Doctor-Who).
+
+Version 2.4 (11 apr 2021)
+----------------------------------------------------------------
+* Fix a bug: The output image origin was sometimes shifted from a fraction of pixel. This issue happened only with multi-inputs models that have inputs of different spacing.
+* Improvement: The output image largest possible region is now computed on the maximum possible area within the expression field. Before that, the largest possible region was too much cropped when an expression field > 1 was used. Now output images are a bit larger when a non unitary expression field is used.
+
+Version 2.3 (30 mar 2021)
+----------------------------------------------------------------
+* More supported numeric types for tensors:
+ * `tensorflow::DT_FLOAT`
+ * `tensorflow::DT_DOUBLE`
+ * `tensorflow::DT_UINT64`
+ * `tensorflow::DT_INT64`
+ * `tensorflow::DT_UINT32`
+ * `tensorflow::DT_INT32`
+ * `tensorflow::DT_UINT16`
+ * `tensorflow::DT_INT16`
+ * `tensorflow::DT_UINT8`
+* Update instructions to use docker
+
+Version 2.2 (29 jan 2021)
+----------------------------------------------------------------
+* Huge enhancement of the docker image build (from Vincent@LaTeleScop)
+
+Version 2.1 (17 nov 2020)
+----------------------------------------------------------------
+* New OTBTF python classes to train the models:
+ * `PatchesReaderBase`: base abstract class for patches readers. Users/developers can implement their own from it!
+ * `PatchesImagesReader`: a class implementing `PatchesReaderBase` to access the patches images, as they are produced by the OTBTF PatchesExtraction application.
+ * `IteratorBase`: base class to iterate on `PatchesReaderBase`-derived readers.
+ * `RandomIterator`: an iterator implementing `IteratorBase` designed to randomly access elements.
+ * `Dataset`: generic class to build datasets, consisting essentially of the assembly of a `PatchesReaderBase`-derived reader, and a `IteratorBase`-derived iterator. The `Dataset` handles the gathering of the data using a thread. It can be used as a `tf.dataset` to feed computational graphs.
+ * `DatasetFromPatchesImages`: a `Dataset` that uses a `PatchesImagesReader` to allow users/developers to stream their patches generated using the OTBTF PatchesExtraction through a `tf.dataset` which implements a streaming mechanism, enabling low memory footprint and high performance I/O thank to a threaded reading mechanism.
+* Fix in dockerfile (from Pratyush Das) to work with WSL2
+
+Version 2.0 (29 may 2020)
+----------------------------------------------------------------
+* Now using TensorFlow 2.0! Some minor migration of python models, because we stick with `tf.compat.v1`.
+* Python functions to read patches now use GDAL
+* Lighter docker images (thanks to Vincent@LaTeleScop)
+
+Version 1.8.0 (14 jan 2020)
+----------------------------------------------------------------
+* PatchesExtraction supports no-data (a different value for each source can be set)
+* New sampling strategy available in PatchesSelection (balanced strategy)
+
+Version 1.7.0 (15 oct 2019)
+----------------------------------------------------------------
+* Add a new application for patches selection (experimental)
+* New docker images that are GPU-enabled using NVIDIA runtime
+
+Version 1.6.0 (18 jul 2019)
+----------------------------------------------------------------
+* Fix a bug related to coordinates tolerance (TensorflowModelTrain can now use patches that do not occupy physically the same space)
+* Fix dockerfile (add important environment variables, add a non-root user, add an example how to run the docker image)
+* Document the provided Gaetano et al. two-branch CNN
+
+Version 1.5.1 (18 jun 2019)
+----------------------------------------------------------------
+* Ubuntu bionic dockerfile + instructions
+* Doc tags for QGIS3 integration
+* Add cmake tests (3 models are tested in various configuration on Pan/XS images)
+* PatchesExtraction writes patches images with physical spacing
+
+Version 1.3.0 (18 nov 2018)
+----------------------------------------------------------------
+* Add 3 models that can be directly trained with TensorflowModelTrain (one CNN net, one FCN net, one 2-branch CNN net performing separately on PAN and XS images)
+* Fix a bug occurring when using a scale factor <> 1 with a non-unit expression field
+* Fix incorrect batch size in learning filters when batch size was not a multiple of number of batches
+* Add some documentation
+
+Version 1.2.0 (29 sep 2018)
+----------------------------------------------------------------
+* Fix typos in documentation
+* Add a new application for dense polygon classes statistics
+* Fix a bug in validation step
+* Add streaming option of training/validation
+* Document filters classes
+* Change applications parameters names and roles
+* Add a python application that converts a graph into a savedmodel
+* Adjust tiling to expression field
+* Update license
+
+Version 1.0.0 (16 may 2018)
+----------------------------------------------------------------
+* First release of OTBTF!
diff --git a/app/otbDensePolygonClassStatistics.cxx b/app/otbDensePolygonClassStatistics.cxx
index 8ee2283e2edc542d4a389756d23de48c9a00c367..fa7c2701db9bbe959ec2787f8e04c1fd6915cd3e 100644
--- a/app/otbDensePolygonClassStatistics.cxx
+++ b/app/otbDensePolygonClassStatistics.cxx
@@ -1,6 +1,7 @@
/*=========================================================================
- Copyright (c) Remi Cresson (IRSTEA). All rights reserved.
+ Copyright (c) 2018-2019 IRSTEA
+ Copyright (c) 2020-2021 INRAE
This software is distributed WITHOUT ANY WARRANTY; without even
@@ -8,18 +9,24 @@
PURPOSE. See the above copyright notices for more information.
=========================================================================*/
-#include "otbWrapperApplication.h"
+#include "itkFixedArray.h"
+#include "itkObjectFactory.h"
#include "otbWrapperApplicationFactory.h"
+// Application engine
+#include "otbStandardFilterWatcher.h"
+#include "itkFixedArray.h"
+
+// Filters
#include "otbStatisticsXMLFileWriter.h"
#include "otbWrapperElevationParametersHandler.h"
-
#include "otbVectorDataToLabelImageFilter.h"
#include "otbImageToNoDataMaskFilter.h"
#include "otbStreamingStatisticsMapFromLabelImageFilter.h"
#include "otbVectorDataIntoImageProjectionFilter.h"
#include "otbImageToVectorImageCastFilter.h"
+// OGR
#include "otbOGR.h"
namespace otb
@@ -36,15 +43,14 @@ class DensePolygonClassStatistics : public Application
{
public:
/** Standard class typedefs. */
- typedef DensePolygonClassStatistics Self;
+ typedef DensePolygonClassStatistics Self;
typedef Application Superclass;
typedef itk::SmartPointer<Self> Pointer;
typedef itk::SmartPointer<const Self> ConstPointer;
/** Standard macro */
itkNewMacro(Self);
-
- itkTypeMacro(DensePolygonClassStatistics, otb::Application);
+ itkTypeMacro(DensePolygonClassStatistics, Application);
/** DataObjects typedef */
typedef UInt32ImageType LabelImageType;
@@ -66,14 +72,7 @@ public:
typedef otb::StatisticsXMLFileWriter<FloatVectorImageType::PixelType> StatWriterType;
-
-private:
- DensePolygonClassStatistics()
- {
-
- }
-
- void DoInit() override
+ void DoInit()
{
SetName("DensePolygonClassStatistics");
SetDescription("Computes statistics on a training polygon set.");
@@ -87,7 +86,6 @@ private:
" - number of samples per geometry\n");
SetDocLimitations("None");
SetDocAuthors("Remi Cresson");
- SetDocSeeAlso(" ");
AddDocTag(Tags::Learning);
@@ -114,67 +112,11 @@ private:
SetDocExampleParameterValue("field", "label");
SetDocExampleParameterValue("out","polygonStat.xml");
- SetOfficialDocLink();
- }
-
- void DoUpdateParameters() override
- {
- if ( HasValue("vec") )
- {
- std::string vectorFile = GetParameterString("vec");
- ogr::DataSource::Pointer ogrDS =
- ogr::DataSource::New(vectorFile, ogr::DataSource::Modes::Read);
- ogr::Layer layer = ogrDS->GetLayer(0);
- ogr::Feature feature = layer.ogr().GetNextFeature();
-
- ClearChoices("field");
-
- for(int iField=0; iField<feature.ogr().GetFieldCount(); iField++)
- {
- std::string key, item = feature.ogr().GetFieldDefnRef(iField)->GetNameRef();
- key = item;
- std::string::iterator end = std::remove_if(key.begin(),key.end(),IsNotAlphaNum);
- std::transform(key.begin(), end, key.begin(), tolower);
-
- OGRFieldType fieldType = feature.ogr().GetFieldDefnRef(iField)->GetType();
-
- if(fieldType == OFTString || fieldType == OFTInteger || fieldType == OFTInteger64)
- {
- std::string tmpKey="field."+key.substr(0, end - key.begin());
- AddChoice(tmpKey,item);
- }
- }
- }
-
- // Check that the extension of the output parameter is XML (mandatory for
- // StatisticsXMLFileWriter)
- // Check it here to trigger the error before polygons analysis
-
- if ( HasValue("out") )
- {
- // Store filename extension
- // Check that the right extension is given : expected .xml
- const std::string extension = itksys::SystemTools::GetFilenameLastExtension(this->GetParameterString("out"));
-
- if (itksys::SystemTools::LowerCase(extension) != ".xml")
- {
- otbAppLogFATAL( << extension << " is a wrong extension for parameter \"out\": Expected .xml" );
- }
- }
}
- void DoExecute() override
+ void DoExecute()
{
- // Filters
- VectorDataReprojFilterType::Pointer m_VectorDataReprojectionFilter;
- RasterizeFilterType::Pointer m_RasterizeFIDFilter;
- RasterizeFilterType::Pointer m_RasterizeClassFilter;
- NoDataMaskFilterType::Pointer m_NoDataFilter;
- CastFilterType::Pointer m_NoDataCastFilter;
- StatsFilterType::Pointer m_FIDStatsFilter;
- StatsFilterType::Pointer m_ClassStatsFilter;
-
// Retrieve the field name
std::vector<int> selectedCFieldIdx = GetSelectedItems("field");
@@ -253,14 +195,72 @@ private:
fidMap.erase(intNoData);
classMap.erase(intNoData);
- StatWriterType::Pointer statWriter = StatWriterType::New();
- statWriter->SetFileName(this->GetParameterString("out"));
- statWriter->AddInputMap<StatsFilterType::LabelPopulationMapType>("samplesPerClass",classMap);
- statWriter->AddInputMap<StatsFilterType::LabelPopulationMapType>("samplesPerVector",fidMap);
- statWriter->Update();
+ m_StatWriter = StatWriterType::New();
+ m_StatWriter->SetFileName(this->GetParameterString("out"));
+ m_StatWriter->AddInputMap<StatsFilterType::LabelPopulationMapType>("samplesPerClass", classMap);
+ m_StatWriter->AddInputMap<StatsFilterType::LabelPopulationMapType>("samplesPerVector", fidMap);
+ m_StatWriter->Update();
}
-
+
+ void DoUpdateParameters()
+ {
+ if (HasValue("vec"))
+ {
+ std::string vectorFile = GetParameterString("vec");
+ ogr::DataSource::Pointer ogrDS =
+ ogr::DataSource::New(vectorFile, ogr::DataSource::Modes::Read);
+ ogr::Layer layer = ogrDS->GetLayer(0);
+ ogr::Feature feature = layer.ogr().GetNextFeature();
+
+ ClearChoices("field");
+
+ for(int iField=0; iField<feature.ogr().GetFieldCount(); iField++)
+ {
+ std::string key, item = feature.ogr().GetFieldDefnRef(iField)->GetNameRef();
+ key = item;
+ std::string::iterator end = std::remove_if(key.begin(),key.end(),IsNotAlphaNum);
+ std::transform(key.begin(), end, key.begin(), tolower);
+
+ OGRFieldType fieldType = feature.ogr().GetFieldDefnRef(iField)->GetType();
+
+ if(fieldType == OFTString || fieldType == OFTInteger || fieldType == OFTInteger64)
+ {
+ std::string tmpKey="field."+key.substr(0, end - key.begin());
+ AddChoice(tmpKey,item);
+ }
+ }
+ }
+
+ // Check that the extension of the output parameter is XML (mandatory for
+ // StatisticsXMLFileWriter)
+ // Check it here to trigger the error before polygons analysis
+
+ if (HasValue("out"))
+ {
+ // Store filename extension
+ // Check that the right extension is given : expected .xml
+ const std::string extension = itksys::SystemTools::GetFilenameLastExtension(this->GetParameterString("out"));
+
+ if (itksys::SystemTools::LowerCase(extension) != ".xml")
+ {
+ otbAppLogFATAL( << extension << " is a wrong extension for parameter \"out\": Expected .xml" );
+ }
+ }
+ }
+
+
+
+private:
+ // Filters
+ VectorDataReprojFilterType::Pointer m_VectorDataReprojectionFilter;
+ RasterizeFilterType::Pointer m_RasterizeFIDFilter;
+ RasterizeFilterType::Pointer m_RasterizeClassFilter;
+ NoDataMaskFilterType::Pointer m_NoDataFilter;
+ CastFilterType::Pointer m_NoDataCastFilter;
+ StatsFilterType::Pointer m_FIDStatsFilter;
+ StatsFilterType::Pointer m_ClassStatsFilter;
+ StatWriterType::Pointer m_StatWriter;
};
diff --git a/app/otbImageClassifierFromDeepFeatures.cxx b/app/otbImageClassifierFromDeepFeatures.cxx
index f861da418c6ce4a257e673132fe8fda04fb6bc6f..f3ffd2731307ecd0e0f7afdb5f6e78b9a4ac4163 100644
--- a/app/otbImageClassifierFromDeepFeatures.cxx
+++ b/app/otbImageClassifierFromDeepFeatures.cxx
@@ -1,6 +1,7 @@
/*=========================================================================
- Copyright (c) Remi Cresson (IRSTEA). All rights reserved.
+ Copyright (c) 2018-2019 IRSTEA
+ Copyright (c) 2020-2021 INRAE
This software is distributed WITHOUT ANY WARRANTY; without even
@@ -60,7 +61,6 @@ private:
// Populate group
ShareParameter(ss_key_group.str(), "tfmodel." + ss_key_group.str(), ss_desc_group.str());
-
}
@@ -106,10 +106,8 @@ private:
ShareParameter("out" , "classif.out" , "Output image" , "Output image" );
ShareParameter("confmap" , "classif.confmap" , "Confidence map image", "Confidence map image");
ShareParameter("ram" , "classif.ram" , "Ram" , "Ram" );
-
}
-
void DoUpdateParameters()
{
UpdateInternalParameters("classif");
@@ -121,12 +119,8 @@ private:
GetInternalApplication("classif")->SetParameterInputImage("in", GetInternalApplication("tfmodel")->GetParameterOutputImage("out"));
UpdateInternalParameters("classif");
ExecuteInternal("classif");
- } // DOExecute()
-
- void AfterExecuteAndWriteOutputs()
- {
- // Nothing to do
}
+
};
} // namespace Wrapper
} // namespace otb
diff --git a/app/otbLabelImageSampleSelection.cxx b/app/otbLabelImageSampleSelection.cxx
index 5364453d84f4c99f28bab2c938a0af220db02b6d..50396fa0ac4ded119bd31268327fea4032b15f2f 100644
--- a/app/otbLabelImageSampleSelection.cxx
+++ b/app/otbLabelImageSampleSelection.cxx
@@ -1,6 +1,7 @@
/*=========================================================================
- Copyright (c) Remi Cresson (IRSTEA). All rights reserved.
+ Copyright (c) 2018-2019 IRSTEA
+ Copyright (c) 2020-2021 INRAE
This software is distributed WITHOUT ANY WARRANTY; without even
@@ -34,7 +35,7 @@ class LabelImageSampleSelection : public Application
{
public:
/** Standard class typedefs. */
- typedef LabelImageSampleSelection Self;
+ typedef LabelImageSampleSelection Self;
typedef Application Superclass;
typedef itk::SmartPointer<Self> Pointer;
typedef itk::SmartPointer<const Self> ConstPointer;
@@ -384,4 +385,4 @@ private:
} // end namespace wrapper
} // end namespace otb
-OTB_APPLICATION_EXPORT( otb::Wrapper::LabelImageSampleSelection )
+OTB_APPLICATION_EXPORT(otb::Wrapper::LabelImageSampleSelection)
diff --git a/app/otbPatchesExtraction.cxx b/app/otbPatchesExtraction.cxx
index df13cbc3353e7cfaafec13126077d4c6c8def571..7b0ce4565e687da42bdf9adb71cadd883acd56cc 100644
--- a/app/otbPatchesExtraction.cxx
+++ b/app/otbPatchesExtraction.cxx
@@ -1,6 +1,7 @@
/*=========================================================================
- Copyright (c) Remi Cresson (IRSTEA). All rights reserved.
+ Copyright (c) 2018-2019 IRSTEA
+ Copyright (c) 2020-2021 INRAE
This software is distributed WITHOUT ANY WARRANTY; without even
@@ -55,8 +56,6 @@ public:
TFSourceType m_ImageSource; // Image source
FloatVectorImageType::SizeType m_PatchSize; // Patch size
- unsigned int m_NumberOfElements; // Number of output samples
-
std::string m_KeyIn; // Key of input image list
std::string m_KeyOut; // Key of output samples image
std::string m_KeyPszX; // Key for samples sizes X
@@ -137,10 +136,6 @@ public:
}
}
- void DoUpdateParameters()
- {
- }
-
void DoInit()
{
@@ -238,6 +233,12 @@ public:
}
}
+
+
+ void DoUpdateParameters()
+ {
+ }
+
private:
std::vector<SourceBundle> m_Bundles;
@@ -246,4 +247,4 @@ private:
} // end namespace wrapper
} // end namespace otb
-OTB_APPLICATION_EXPORT( otb::Wrapper::PatchesExtraction )
+OTB_APPLICATION_EXPORT(otb::Wrapper::PatchesExtraction)
diff --git a/app/otbPatchesSelection.cxx b/app/otbPatchesSelection.cxx
index 170fc9b6e1f2c958abeef47c202d41ea170751d7..5d8165a019764a50a5f3301877cb364108c1f92c 100644
--- a/app/otbPatchesSelection.cxx
+++ b/app/otbPatchesSelection.cxx
@@ -1,6 +1,7 @@
/*=========================================================================
- Copyright (c) Remi Cresson (IRSTEA). All rights reserved.
+ Copyright (c) 2018-2019 IRSTEA
+ Copyright (c) 2020-2021 INRAE
This software is distributed WITHOUT ANY WARRANTY; without even
@@ -67,7 +68,7 @@ class PatchesSelection : public Application
{
public:
/** Standard class typedefs. */
- typedef PatchesSelection Self;
+ typedef PatchesSelection Self;
typedef Application Superclass;
typedef itk::SmartPointer<Self> Pointer;
typedef itk::SmartPointer<const Self> ConstPointer;
@@ -99,11 +100,6 @@ public:
typedef itk::MaskImageFilter<UInt8ImageType, UInt8ImageType, UInt8ImageType> MaskImageFilterType;
- void DoUpdateParameters()
- {
- }
-
-
void DoInit()
{
@@ -166,22 +162,15 @@ public:
{
public:
SampleBundle(){}
- SampleBundle(unsigned int nClasses){
- dist = DistributionType(nClasses);
- id = 0;
+ explicit SampleBundle(unsigned int nClasses): dist(DistributionType(nClasses)), id(0), black(true){
(void) point;
- black = true;
(void) index;
}
~SampleBundle(){}
- SampleBundle(const SampleBundle & other){
- dist = other.GetDistribution();
- id = other.GetSampleID();
- point = other.GetPosition();
- black = other.GetBlack();
- index = other.GetIndex();
- }
+ SampleBundle(const SampleBundle & other): dist(other.GetDistribution()), id(other.GetSampleID()),
+ point(other.GetPosition()), black(other.GetBlack()), index(other.GetIndex())
+ {}
DistributionType GetDistribution() const
{
@@ -252,6 +241,10 @@ public:
int userOffX = GetParameterInt("grid.offsetx");
int userOffY = GetParameterInt("grid.offsety");
+ // Tell if the patch size is odd or even
+ const bool isEven = GetParameterInt("grid.psize") % 2 == 0;
+ otbAppLogINFO("Patch size is even: " << isEven);
+
// Explicit streaming over the morphed mask, based on the RAM parameter
typedef otb::RAMDrivenStrippedStreamingManager<UInt8ImageType> StreamingManagerType;
StreamingManagerType::Pointer m_StreamingManager = StreamingManagerType::New();
@@ -327,9 +320,13 @@ public:
// Compute coordinates
UInt8ImageType::PointType geo;
inputImage->TransformIndexToPhysicalPoint(inIt.GetIndex(), geo);
- DataNodeType::PointType point;
- point[0] = geo[0];
- point[1] = geo[1];
+
+ // Update geo if we want the corner or the center
+ if (isEven)
+ {
+ geo[0] -= 0.5 * std::abs(inputImage->GetSpacing()[0]);
+ geo[1] -= 0.5 * std::abs(inputImage->GetSpacing()[1]);
+ }
// Lambda call
lambda(pos, geo);
@@ -538,7 +535,7 @@ public:
PopulateVectorData(seed);
}
- void PopulateVectorData(std::vector<SampleBundle> & samples)
+ void PopulateVectorData(const std::vector<SampleBundle> & samples)
{
// Get data tree
DataTreeType::Pointer treeTrain = m_OutVectorDataTrain->GetDataTree();
@@ -656,6 +653,11 @@ public:
}
+
+ void DoUpdateParameters()
+ {
+ }
+
private:
RadiusType m_Radius;
IsNoDataFilterType::Pointer m_NoDataFilter;
diff --git a/app/otbTensorflowModelServe.cxx b/app/otbTensorflowModelServe.cxx
index 0aa9d71ec29345ecd332062d030e3ca0ea70eab6..47a8c95730443c0c3345933d71f63a1bcbcb556d 100644
--- a/app/otbTensorflowModelServe.cxx
+++ b/app/otbTensorflowModelServe.cxx
@@ -1,6 +1,7 @@
/*=========================================================================
- Copyright (c) Remi Cresson (IRSTEA). All rights reserved.
+ Copyright (c) 2018-2019 IRSTEA
+ Copyright (c) 2020-2021 INRAE
This software is distributed WITHOUT ANY WARRANTY; without even
@@ -16,9 +17,8 @@
#include "otbStandardFilterWatcher.h"
#include "itkFixedArray.h"
-// Tensorflow stuff
-#include "tensorflow/core/public/session.h"
-#include "tensorflow/core/platform/env.h"
+// Tensorflow SavedModel
+#include "tensorflow/cc/saved_model/loader.h"
// Tensorflow model filter
#include "otbTensorflowMultisourceModelFilter.h"
@@ -62,10 +62,6 @@ public:
/** Typedefs for images */
typedef FloatVectorImageType::SizeType SizeType;
- void DoUpdateParameters()
- {
- }
-
//
// Store stuff related to one source
//
@@ -120,9 +116,12 @@ public:
AddParameter(ParameterType_InputImageList, ss_key_in.str(), ss_desc_in.str() );
AddParameter(ParameterType_Int, ss_key_dims_x.str(), ss_desc_dims_x.str());
SetMinimumParameterIntValue (ss_key_dims_x.str(), 1);
+ SetDefaultParameterInt (ss_key_dims_x.str(), 1);
AddParameter(ParameterType_Int, ss_key_dims_y.str(), ss_desc_dims_y.str());
SetMinimumParameterIntValue (ss_key_dims_y.str(), 1);
+ SetDefaultParameterInt (ss_key_dims_y.str(), 1);
AddParameter(ParameterType_String, ss_key_ph.str(), ss_desc_ph.str());
+ MandatoryOff (ss_key_ph.str());
// Add a new bundle
ProcessObjectsBundle bundle;
@@ -166,7 +165,7 @@ public:
// Input model
AddParameter(ParameterType_Group, "model", "model parameters");
- AddParameter(ParameterType_Directory, "model.dir", "TensorFlow model_save directory");
+ AddParameter(ParameterType_Directory, "model.dir", "TensorFlow SavedModel directory");
MandatoryOn ("model.dir");
SetParameterDescription ("model.dir", "The model directory should contains the model Google Protobuf (.pb) and variables");
@@ -175,6 +174,8 @@ public:
SetParameterDescription ("model.userplaceholders", "Syntax to use is \"placeholder_1=value_1 ... placeholder_N=value_N\"");
AddParameter(ParameterType_Bool, "model.fullyconv", "Fully convolutional");
MandatoryOff ("model.fullyconv");
+ AddParameter(ParameterType_StringList, "model.tagsets", "Which tags (i.e. v1.MetaGraphDefs) to load from the saved model. Currently, only one tag is supported. Can be retrieved by running `saved_model_cli show --dir your_model_dir --all`");
+ MandatoryOff ("model.tagsets");
// Output tensors parameters
AddParameter(ParameterType_Group, "output", "Output tensors parameters");
@@ -182,7 +183,7 @@ public:
SetDefaultParameterFloat ("output.spcscale", 1.0);
SetParameterDescription ("output.spcscale", "The output image size/scale and spacing*scale where size and spacing corresponds to the first input");
AddParameter(ParameterType_StringList, "output.names", "Names of the output tensors");
- MandatoryOn ("output.names");
+ MandatoryOff ("output.names");
// Output Field of Expression
AddParameter(ParameterType_Int, "output.efieldx", "The output expression field (width)");
@@ -246,15 +247,14 @@ public:
{
// Load the Tensorflow bundle
- tf::LoadModel(GetParameterAsString("model.dir"), m_SavedModel);
+ tf::LoadModel(GetParameterAsString("model.dir"), m_SavedModel, GetParameterStringList("model.tagsets"));
// Prepare inputs
PrepareInputs();
// Setup filter
m_TFFilter = TFModelFilterType::New();
- m_TFFilter->SetGraph(m_SavedModel.meta_graph_def.graph_def());
- m_TFFilter->SetSession(m_SavedModel.session.get());
+ m_TFFilter->SetSavedModel(&m_SavedModel);
m_TFFilter->SetOutputTensors(GetParameterStringList("output.names"));
m_TFFilter->SetOutputSpacingScale(GetParameterFloat("output.spcscale"));
otbAppLogINFO("Output spacing ratio: " << m_TFFilter->GetOutputSpacingScale());
@@ -328,6 +328,11 @@ public:
SetParameterOutputImage("out", m_TFFilter->GetOutput());
}
}
+
+
+ void DoUpdateParameters()
+ {
+ }
private:
@@ -335,7 +340,7 @@ private:
StreamingFilterType::Pointer m_StreamFilter;
tensorflow::SavedModelBundle m_SavedModel; // must be alive during all the execution of the application !
- std::vector<ProcessObjectsBundle> m_Bundles;
+ std::vector<ProcessObjectsBundle> m_Bundles;
}; // end of class
diff --git a/app/otbTensorflowModelTrain.cxx b/app/otbTensorflowModelTrain.cxx
index b37c72c3df7a297dda0857030d47bbe1e08cad61..e79019980537f873efc85cc8dd22e4bd05fce82e 100644
--- a/app/otbTensorflowModelTrain.cxx
+++ b/app/otbTensorflowModelTrain.cxx
@@ -1,6 +1,7 @@
/*=========================================================================
- Copyright (c) Remi Cresson (IRSTEA). All rights reserved.
+ Copyright (c) 2018-2019 IRSTEA
+ Copyright (c) 2020-2021 INRAE
This software is distributed WITHOUT ANY WARRANTY; without even
@@ -16,9 +17,8 @@
#include "otbStandardFilterWatcher.h"
#include "itkFixedArray.h"
-// Tensorflow stuff
-#include "tensorflow/core/public/session.h"
-#include "tensorflow/core/platform/env.h"
+// Tensorflow SavedModel
+#include "tensorflow/cc/saved_model/loader.h"
// Tensorflow model train
#include "otbTensorflowMultisourceModelTrain.h"
@@ -185,6 +185,8 @@ public:
MandatoryOff ("model.restorefrom");
AddParameter(ParameterType_String, "model.saveto", "Save model to path");
MandatoryOff ("model.saveto");
+ AddParameter(ParameterType_StringList, "model.tagsets", "Which tags (i.e. v1.MetaGraphDefs) to load from the saved model. Currently, only one tag is supported. Can be retrieved by running `saved_model_cli show --dir your_model_dir --all`");
+ MandatoryOff ("model.tagsets");
// Training parameters group
AddParameter(ParameterType_Group, "training", "Training parameters");
@@ -360,7 +362,7 @@ public:
//
// Get user placeholders
//
- TrainModelFilterType::DictType GetUserPlaceholders(const std::string key)
+ TrainModelFilterType::DictType GetUserPlaceholders(const std::string & key)
{
TrainModelFilterType::DictType dict;
TrainModelFilterType::StringList expressions = GetParameterStringList(key);
@@ -407,13 +409,15 @@ public:
{
// Load the Tensorflow bundle
- tf::LoadModel(GetParameterAsString("model.dir"), m_SavedModel);
+ tf::LoadModel(GetParameterAsString("model.dir"), m_SavedModel, GetParameterStringList("model.tagsets"));
- // Check if we have to restore variables from somewhere
+ // Check if we have to restore variables from somewhere else
if (HasValue("model.restorefrom"))
{
const std::string path = GetParameterAsString("model.restorefrom");
otbAppLogINFO("Restoring model from " + path);
+
+ // Load SavedModel variables
tf::RestoreModel(path, m_SavedModel);
}
@@ -422,8 +426,7 @@ public:
// Setup training filter
m_TrainModelFilter = TrainModelFilterType::New();
- m_TrainModelFilter->SetGraph(m_SavedModel.meta_graph_def.graph_def());
- m_TrainModelFilter->SetSession(m_SavedModel.session.get());
+ m_TrainModelFilter->SetSavedModel(&m_SavedModel);
m_TrainModelFilter->SetOutputTensors(GetParameterStringList("training.outputtensors"));
m_TrainModelFilter->SetTargetNodesNames(GetParameterStringList("training.targetnodes"));
m_TrainModelFilter->SetBatchSize(GetParameterInt("training.batchsize"));
@@ -446,8 +449,7 @@ public:
otbAppLogINFO("Set validation mode to classification validation");
m_ValidateModelFilter = ValidateModelFilterType::New();
- m_ValidateModelFilter->SetGraph(m_SavedModel.meta_graph_def.graph_def());
- m_ValidateModelFilter->SetSession(m_SavedModel.session.get());
+ m_ValidateModelFilter->SetSavedModel(&m_SavedModel);
m_ValidateModelFilter->SetBatchSize(GetParameterInt("training.batchsize"));
m_ValidateModelFilter->SetUserPlaceholders(GetUserPlaceholders("validation.userplaceholders"));
m_ValidateModelFilter->SetInputPlaceholders(m_InputPlaceholdersForValidation);
diff --git a/app/otbTrainClassifierFromDeepFeatures.cxx b/app/otbTrainClassifierFromDeepFeatures.cxx
index ae1e5d949bbb97d2c8587299d16d9b46f1a12e6a..39ac41898a450159a4c50133883006c4466bcb51 100644
--- a/app/otbTrainClassifierFromDeepFeatures.cxx
+++ b/app/otbTrainClassifierFromDeepFeatures.cxx
@@ -1,6 +1,7 @@
/*=========================================================================
- Copyright (c) Remi Cresson (IRSTEA). All rights reserved.
+ Copyright (c) 2018-2019 IRSTEA
+ Copyright (c) 2020-2021 INRAE
This software is distributed WITHOUT ANY WARRANTY; without even
@@ -120,11 +121,6 @@ private:
GetInternalApplication("train")->AddImageToParameterInputImageList("io.il", GetInternalApplication("tfmodel")->GetParameterOutputImage("out"));
UpdateInternalParameters("train");
ExecuteInternal("train");
- } // DOExecute()
-
- void AfterExecuteAndWriteOutputs()
- {
- // Nothing to do
}
};
diff --git a/doc/APPLICATIONS.md b/doc/APPLICATIONS.md
index 69282cd543576f66a790f9619f6f75b31b4e1514..25d739fb863e3939d8bb4cbdbd0fe4050766f10a 100644
--- a/doc/APPLICATIONS.md
+++ b/doc/APPLICATIONS.md
@@ -59,7 +59,7 @@ When using a model in OTBTF, the important thing is to know the following parame
-The **scale factor** descibes the physical change of spacing of the outputs, typically introduced in the model by non unitary strides in pooling or convolution operators.
+The **scale factor** describes the physical change of spacing of the outputs, typically introduced in the model by non unitary strides in pooling or convolution operators.
For each output, it is expressed relatively to one single input of the model called the _reference input source_.
Additionally, the names of the _target nodes_ must be known (e.g. "optimizer").
Also, the names of _user placeholders_, typically scalars placeholders that are used to control some parameters of the model, must be know (e.g. "dropout_rate").
@@ -356,7 +356,7 @@ But here, we will just perform some fine tuning of our model.
The **SavedModel** is located in the `outmodel` directory.
Our model is quite basic: it has two input placeholders, **x1** and **y1** respectively for input patches (with size 16x16) and input reference labels (with size 1x1).
We named **prediction** the tensor that predict the labels and the optimizer that perform the stochastic gradient descent is an operator named **optimizer**.
-We perform the fine tuning and we export the new model variables directly in the _outmodel/variables_ folder, overwritting the existing variables of the model.
+We perform the fine tuning and we export the new model variables directly in the _outmodel/variables_ folder, overwriting the existing variables of the model.
We use the **TensorflowModelTrain** application to perform the training of this existing model.
```
otbcli_TensorflowModelTrain -model.dir /path/to/oursavedmodel -training.targetnodesnames optimizer -training.source1.il samp_patches.tif -training.source1.patchsizex 16 -training.source1.patchsizey 16 -training.source1.placeholder x1 -training.source2.il samp_labels.tif -training.source2.patchsizex 1 -training.source2.patchsizey 1 -training.source2.placeholder y1 -model.saveto /path/to/oursavedmodel/variables/variables
diff --git a/doc/DOCKERUSE.md b/doc/DOCKERUSE.md
index 8d326c272bbb76973fa29f937279c553e6ff1c37..34e58cc3eab4a170e8e4abd445da8a826890b8bb 100644
--- a/doc/DOCKERUSE.md
+++ b/doc/DOCKERUSE.md
@@ -20,6 +20,10 @@ Here is the list of OTBTF docker images hosted on [dockerhub](https://hub.docker
| **mdl4eo/otbtf2.5:cpu** | Ubuntu Focal | r2.5 | 7.4.0 | CPU, few optimization | no | 5.2,6.1,7.0,7.5,8.6|
| **mdl4eo/otbtf2.5:gpu** | Ubuntu Focal | r2.5 | 7.4.0 | GPU | no | 5.2,6.1,7.0,7.5,8.6|
| **mdl4eo/otbtf2.5:gpu-dev** | Ubuntu Focal | r2.5 | 7.4.0 | GPU (dev) | yes | 5.2,6.1,7.0,7.5,8.6|
+| **mdl4eo/otbtf3.0:cpu-basic** | Ubuntu Focal | r2.5 | 7.4.0 | CPU, no optimization | no | 5.2,6.1,7.0,7.5,8.6|
+| **mdl4eo/otbtf3.0:cpu-basic-dev** | Ubuntu Focal | r2.5 | 7.4.0 | CPU, no optimization (dev) | yes | 5.2,6.1,7.0,7.5,8.6|
+| **mdl4eo/otbtf3.0:gpu** | Ubuntu Focal | r2.5 | 7.4.0 | GPU | yes | 5.2,6.1,7.0,7.5,8.6|
+| **mdl4eo/otbtf3.0:gpu-dev** | Ubuntu Focal | r2.5 | 7.4.0 | GPU (dev) | yes | 5.2,6.1,7.0,7.5,8.6|
- `cpu` tagged docker images are compiled without optimization.
- `gpu` tagged docker images are suited for **NVIDIA GPUs**. They use CUDA/CUDNN support.
@@ -107,7 +111,7 @@ This section is largely inspired from the [moringa docker help](https://gitlab.i
## Useful diagnostic commands
-Here are some usefull commands.
+Here are some useful commands.
```bash
docker info # System info
diff --git a/doc/images/classif_map.png b/doc/images/classif_map.png
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diff --git a/doc/images/docker_desktop_1.jpeg b/doc/images/docker_desktop_1.jpeg
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diff --git a/doc/images/docker_desktop_2.jpeg b/doc/images/docker_desktop_2.jpeg
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diff --git a/doc/images/landcover.png b/doc/images/landcover.png
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diff --git a/doc/images/logo.png b/doc/images/logo.png
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diff --git a/doc/images/model_training.png b/doc/images/model_training.png
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diff --git a/doc/images/patches_extraction.png b/doc/images/patches_extraction.png
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diff --git a/doc/images/pix2pix.png b/doc/images/pix2pix.png
index 1c79652ff0bae389cbee1c7cde40b2d46f20f089..5df6b349acb27a04419fb226c2085a757cb6fe40 100644
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diff --git a/doc/images/savedmodel_simple_cnn.png b/doc/images/savedmodel_simple_cnn.png
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diff --git a/doc/images/savedmodel_simple_fcnn.png b/doc/images/savedmodel_simple_fcnn.png
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diff --git a/doc/images/savedmodel_simple_pxs_fcn.png b/doc/images/savedmodel_simple_pxs_fcn.png
index 169e9703faa25b3e934d888b637a0f7ecd182ed8..bfb72eab3b9d0de7488e386b2403adbd8eadb9e2 100644
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diff --git a/doc/images/schema.png b/doc/images/schema.png
index df80fcc1cdbcc58e081e13a4918d3652e649c5ab..f5788e33078f20299e0275d1b8a950fcfda35882 100644
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diff --git a/doc/images/supresol.png b/doc/images/supresol.png
index efff2fd23176e0fab501ced42aa24c56a2a77a9b..310d36abce642b6c3813c0c21f31c28e2904124a 100644
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diff --git a/include/otbTensorflowCommon.cxx b/include/otbTensorflowCommon.cxx
index b93717ed3aa5806f364ebcaa1d73edfa25c45f6b..662c9d3e979c5e67ccf9effc4564c9d9fd5c6d0e 100644
--- a/include/otbTensorflowCommon.cxx
+++ b/include/otbTensorflowCommon.cxx
@@ -1,7 +1,7 @@
/*=========================================================================
- Copyright (c) 2018-2019 Remi Cresson (IRSTEA)
- Copyright (c) 2020-2021 Remi Cresson (INRAE)
+ Copyright (c) 2018-2019 IRSTEA
+ Copyright (c) 2020-2021 INRAE
This software is distributed WITHOUT ANY WARRANTY; without even
diff --git a/include/otbTensorflowCommon.h b/include/otbTensorflowCommon.h
index e8db4b8b361e9a1277f96ce50aba4027ffc5d251..fbd7281035185c2acc3a56dac3850a23d76280df 100644
--- a/include/otbTensorflowCommon.h
+++ b/include/otbTensorflowCommon.h
@@ -1,7 +1,7 @@
/*=========================================================================
- Copyright (c) 2018-2019 Remi Cresson (IRSTEA)
- Copyright (c) 2020-2021 Remi Cresson (INRAE)
+ Copyright (c) 2018-2019 IRSTEA
+ Copyright (c) 2020-2021 INRAE
This software is distributed WITHOUT ANY WARRANTY; without even
@@ -18,6 +18,9 @@
#include <string>
#include <algorithm>
#include <functional>
+#include "itkMacro.h"
+#include "itkImageRegionConstIterator.h"
+#include "itkImageRegionIterator.h"
namespace otb {
namespace tf {
diff --git a/include/otbTensorflowCopyUtils.cxx b/include/otbTensorflowCopyUtils.cxx
index 116aafb0b5fb1fe5b00f830291c0218fdb3f6bdf..e969051102c6babaaa2aa3433dd25bafb64af18e 100644
--- a/include/otbTensorflowCopyUtils.cxx
+++ b/include/otbTensorflowCopyUtils.cxx
@@ -1,7 +1,7 @@
/*=========================================================================
- Copyright (c) 2018-2019 Remi Cresson (IRSTEA)
- Copyright (c) 2020-2021 Remi Cresson (INRAE)
+ Copyright (c) 2018-2019 IRSTEA
+ Copyright (c) 2020-2021 INRAE
This software is distributed WITHOUT ANY WARRANTY; without even
@@ -11,27 +11,31 @@
=========================================================================*/
#include "otbTensorflowCopyUtils.h"
-namespace otb {
-namespace tf {
+namespace otb
+{
+namespace tf
+{
//
// Display a TensorShape
//
-std::string PrintTensorShape(const tensorflow::TensorShape & shp)
+std::string
+PrintTensorShape(const tensorflow::TensorShape & shp)
{
std::stringstream s;
- unsigned int nDims = shp.dims();
+ unsigned int nDims = shp.dims();
s << "{" << shp.dim_size(0);
- for (unsigned int d = 1 ; d < nDims ; d++)
+ for (unsigned int d = 1; d < nDims; d++)
s << ", " << shp.dim_size(d);
- s << "}" ;
+ s << "}";
return s.str();
}
//
// Display infos about a tensor
//
-std::string PrintTensorInfos(const tensorflow::Tensor & tensor)
+std::string
+PrintTensorInfos(const tensorflow::Tensor & tensor)
{
std::stringstream s;
s << "Tensor ";
@@ -39,17 +43,19 @@ std::string PrintTensorInfos(const tensorflow::Tensor & tensor)
s << "shape is " << PrintTensorShape(tensor.shape());
// Data type
s << " data type is " << tensor.dtype();
+ s << " (" << tf::GetDataTypeAsString(tensor.dtype()) << ")";
return s.str();
}
//
// Create a tensor with the good datatype
//
-template<class TImage>
-tensorflow::Tensor CreateTensor(tensorflow::TensorShape & shape)
+template <class TImage>
+tensorflow::Tensor
+CreateTensor(tensorflow::TensorShape & shape)
{
tensorflow::DataType ts_dt = GetTensorflowDataType<typename TImage::InternalPixelType>();
- tensorflow::Tensor out_tensor(ts_dt, shape);
+ tensorflow::Tensor out_tensor(ts_dt, shape);
return out_tensor;
}
@@ -58,32 +64,35 @@ tensorflow::Tensor CreateTensor(tensorflow::TensorShape & shape)
// Populate a tensor with the buffered region of a vector image using std::copy
// Warning: tensor datatype must be consistent with the image value type
//
-template<class TImage>
-void PopulateTensorFromBufferedVectorImage(const typename TImage::Pointer bufferedimagePtr, tensorflow::Tensor & out_tensor)
+template <class TImage>
+void
+PopulateTensorFromBufferedVectorImage(const typename TImage::Pointer bufferedimagePtr, tensorflow::Tensor & out_tensor)
{
- size_t n_elem = bufferedimagePtr->GetNumberOfComponentsPerPixel() *
- bufferedimagePtr->GetBufferedRegion().GetNumberOfPixels();
- std::copy_n(bufferedimagePtr->GetBufferPointer(),
- n_elem,
- out_tensor.flat<typename TImage::InternalPixelType>().data());
+ size_t n_elem =
+ bufferedimagePtr->GetNumberOfComponentsPerPixel() * bufferedimagePtr->GetBufferedRegion().GetNumberOfPixels();
+ std::copy_n(
+ bufferedimagePtr->GetBufferPointer(), n_elem, out_tensor.flat<typename TImage::InternalPixelType>().data());
}
//
// Recopy an VectorImage region into a 4D-shaped tensorflow::Tensor ({-1, sz_y, sz_x, sz_bands})
//
-template<class TImage, class TValueType=typename TImage::InternalPixelType>
-void RecopyImageRegionToTensor(const typename TImage::Pointer inputPtr, const typename TImage::RegionType & region,
- tensorflow::Tensor & tensor, unsigned int elemIdx) // element position along the 1st dimension
+template <class TImage, class TValueType = typename TImage::InternalPixelType>
+void
+RecopyImageRegionToTensor(const typename TImage::Pointer inputPtr,
+ const typename TImage::RegionType & region,
+ tensorflow::Tensor & tensor,
+ unsigned int elemIdx) // element position along the 1st dimension
{
typename itk::ImageRegionConstIterator<TImage> inIt(inputPtr, region);
- unsigned int nBands = inputPtr->GetNumberOfComponentsPerPixel();
- auto tMap = tensor.tensor<TValueType, 4>();
+ unsigned int nBands = inputPtr->GetNumberOfComponentsPerPixel();
+ auto tMap = tensor.tensor<TValueType, 4>();
for (inIt.GoToBegin(); !inIt.IsAtEnd(); ++inIt)
{
const int y = inIt.GetIndex()[1] - region.GetIndex()[1];
const int x = inIt.GetIndex()[0] - region.GetIndex()[0];
- for (unsigned int band = 0 ; band < nBands ; band++)
+ for (unsigned int band = 0; band < nBands; band++)
tMap(elemIdx, y, x, band) = inIt.Get()[band];
}
}
@@ -92,9 +101,12 @@ void RecopyImageRegionToTensor(const typename TImage::Pointer inputPtr, const ty
// Type-agnostic version of the 'RecopyImageRegionToTensor' function
// TODO: add some numeric types
//
-template<class TImage>
-void RecopyImageRegionToTensorWithCast(const typename TImage::Pointer inputPtr, const typename TImage::RegionType & region,
- tensorflow::Tensor & tensor, unsigned int elemIdx) // element position along the 1st dimension
+template <class TImage>
+void
+RecopyImageRegionToTensorWithCast(const typename TImage::Pointer inputPtr,
+ const typename TImage::RegionType & region,
+ tensorflow::Tensor & tensor,
+ unsigned int elemIdx) // element position along the 1st dimension
{
tensorflow::DataType dt = tensor.dtype();
if (dt == tensorflow::DT_FLOAT)
@@ -110,21 +122,25 @@ void RecopyImageRegionToTensorWithCast(const typename TImage::Pointer inputPtr,
else if (dt == tensorflow::DT_INT32)
RecopyImageRegionToTensor<TImage, int>(inputPtr, region, tensor, elemIdx);
else if (dt == tensorflow::DT_UINT16)
- RecopyImageRegionToTensor<TImage, unsigned short int> (inputPtr, region, tensor, elemIdx);
+ RecopyImageRegionToTensor<TImage, unsigned short int>(inputPtr, region, tensor, elemIdx);
else if (dt == tensorflow::DT_INT16)
RecopyImageRegionToTensor<TImage, short int>(inputPtr, region, tensor, elemIdx);
else if (dt == tensorflow::DT_UINT8)
- RecopyImageRegionToTensor<TImage, unsigned char> (inputPtr, region, tensor, elemIdx);
+ RecopyImageRegionToTensor<TImage, unsigned char>(inputPtr, region, tensor, elemIdx);
else
- itkGenericExceptionMacro("TF DataType "<< dt << " not currently implemented !");
+ itkGenericExceptionMacro("TF DataType " << dt << " not currently implemented !");
}
//
// Sample a centered patch (from index)
//
-template<class TImage>
-void SampleCenteredPatch(const typename TImage::Pointer inputPtr, const typename TImage::IndexType & centerIndex, const typename TImage::SizeType & patchSize,
- tensorflow::Tensor & tensor, unsigned int elemIdx)
+template <class TImage>
+void
+SampleCenteredPatch(const typename TImage::Pointer inputPtr,
+ const typename TImage::IndexType & centerIndex,
+ const typename TImage::SizeType & patchSize,
+ tensorflow::Tensor & tensor,
+ unsigned int elemIdx)
{
typename TImage::IndexType regionStart;
regionStart[0] = centerIndex[0] - patchSize[0] / 2;
@@ -136,9 +152,13 @@ void SampleCenteredPatch(const typename TImage::Pointer inputPtr, const typename
//
// Sample a centered patch (from coordinates)
//
-template<class TImage>
-void SampleCenteredPatch(const typename TImage::Pointer inputPtr, const typename TImage::PointType & centerCoord, const typename TImage::SizeType & patchSize,
- tensorflow::Tensor & tensor, unsigned int elemIdx)
+template <class TImage>
+void
+SampleCenteredPatch(const typename TImage::Pointer inputPtr,
+ const typename TImage::PointType & centerCoord,
+ const typename TImage::SizeType & patchSize,
+ tensorflow::Tensor & tensor,
+ unsigned int elemIdx)
{
// Assuming tensor is of shape {-1, sz_y, sz_x, sz_bands}
// Get the index of the center
@@ -147,41 +167,48 @@ void SampleCenteredPatch(const typename TImage::Pointer inputPtr, const typename
SampleCenteredPatch<TImage>(inputPtr, centerIndex, patchSize, tensor, elemIdx);
}
-// Return the number of channels that the output tensor will occupy in the output image
//
+// Return the number of channels from the TensorShapeProto
// shape {n} --> 1 (e.g. a label)
-// shape {n, c} --> c (e.g. a vector)
-// shape {x, y, c} --> c (e.g. a patch)
-// shape {n, x, y, c} --> c (e.g. some patches)
+// shape {n, c} --> c (e.g. a pixel)
+// shape {n, x, y} --> 1 (e.g. a mono-channel patch)
+// shape {n, x, y, c} --> c (e.g. a multi-channel patch)
//
-tensorflow::int64 GetNumberOfChannelsForOutputTensor(const tensorflow::Tensor & tensor)
+tensorflow::int64
+GetNumberOfChannelsFromShapeProto(const tensorflow::TensorShapeProto & proto)
{
- const tensorflow::TensorShape shape = tensor.shape();
- const int nDims = shape.dims();
+ const int nDims = proto.dim_size();
if (nDims == 1)
+ // e.g. a batch prediction, as flat tensor
+ return 1;
+ if (nDims == 3)
+ // typically when the last dimension in squeezed following a
+ // computation that does not keep dimensions (e.g. reduce_sum, etc.)
return 1;
- return shape.dim_size(nDims - 1);
+ // any other dimension: we assume that the last dimension represent the
+ // number of channels in the output image.
+ return proto.dim(nDims - 1).size();
}
//
// Copy a tensor into the image region
-// TODO: Enable to change mapping from source tensor to image to make it more generic
-//
-// Right now, only the following output tensor shapes can be processed:
-// shape {n} --> 1 (e.g. a label)
-// shape {n, c} --> c (e.g. a vector)
-// shape {x, y, c} --> c (e.g. a multichannel image)
//
-template<class TImage, class TValueType>
-void CopyTensorToImageRegion(const tensorflow::Tensor & tensor, const typename TImage::RegionType & bufferRegion,
- typename TImage::Pointer outputPtr, const typename TImage::RegionType & outputRegion, int & channelOffset)
+template <class TImage, class TValueType>
+void
+CopyTensorToImageRegion(const tensorflow::Tensor & tensor,
+ const typename TImage::RegionType & bufferRegion,
+ typename TImage::Pointer outputPtr,
+ const typename TImage::RegionType & outputRegion,
+ int & channelOffset)
{
// Flatten the tensor
auto tFlat = tensor.flat<TValueType>();
- // Get the size of the last component of the tensor (see 'GetNumberOfChannelsForOutputTensor(...)')
- const tensorflow::int64 outputDimSize_C = GetNumberOfChannelsForOutputTensor(tensor);
+ // Get the number of component of the output image
+ tensorflow::TensorShapeProto proto;
+ tensor.shape().AsProto(&proto);
+ const tensorflow::int64 outputDimSize_C = GetNumberOfChannelsFromShapeProto(proto);
// Number of columns (size x of the buffer)
const tensorflow::int64 nCols = bufferRegion.GetSize(0);
@@ -191,15 +218,15 @@ void CopyTensorToImageRegion(const tensorflow::Tensor & tensor, const typename T
const tensorflow::int64 nElmI = bufferRegion.GetNumberOfPixels() * outputDimSize_C;
if (nElmI != nElmT)
{
- itkGenericExceptionMacro("Number of elements in the tensor is " << nElmT <<
- " but image outputRegion has " << nElmI <<
- " values to fill.\nBuffer region:\n" << bufferRegion <<
- "\nNumber of components: " << outputDimSize_C <<
- "\nTensor shape:\n " << PrintTensorShape(tensor.shape()) <<
- "\nPlease check the input(s) field of view (FOV), " <<
- "the output field of expression (FOE), and the " <<
- "output spacing scale if you run the model in fully " <<
- "convolutional mode (how many strides in your model?)");
+ itkGenericExceptionMacro("Number of elements in the tensor is " << nElmT
+ << " but image outputRegion has " << nElmI << " values to fill.\n"
+ << "Buffer region is: \n" << bufferRegion << "\n"
+ << "Number of components in the output image: " << outputDimSize_C << "\n"
+ << "Tensor shape: " << PrintTensorShape(tensor.shape()) << "\n"
+ << "Please check the input(s) field of view (FOV), "
+ << "the output field of expression (FOE), and the "
+ << "output spacing scale if you run the model in fully "
+ << "convolutional mode (how many strides in your model?)");
}
// Iterate over the image
@@ -212,145 +239,217 @@ void CopyTensorToImageRegion(const tensorflow::Tensor & tensor, const typename T
// TODO: it could be useful to change the tensor-->image mapping here.
// e.g use a lambda for "pos" calculation
const int pos = outputDimSize_C * (y * nCols + x);
- for (unsigned int c = 0 ; c < outputDimSize_C ; c++)
- outIt.Get()[channelOffset + c] = tFlat( pos + c);
+ for (unsigned int c = 0; c < outputDimSize_C; c++)
+ outIt.Get()[channelOffset + c] = tFlat(pos + c);
}
// Update the offset
channelOffset += outputDimSize_C;
-
}
//
// Type-agnostic version of the 'CopyTensorToImageRegion' function
-// TODO: add some numeric types
//
-template<class TImage>
-void CopyTensorToImageRegion(const tensorflow::Tensor & tensor, const typename TImage::RegionType & bufferRegion,
- typename TImage::Pointer outputPtr, const typename TImage::RegionType & region, int & channelOffset)
+template <class TImage>
+void
+CopyTensorToImageRegion(const tensorflow::Tensor & tensor,
+ const typename TImage::RegionType & bufferRegion,
+ typename TImage::Pointer outputPtr,
+ const typename TImage::RegionType & region,
+ int & channelOffset)
{
tensorflow::DataType dt = tensor.dtype();
if (dt == tensorflow::DT_FLOAT)
- CopyTensorToImageRegion<TImage, float> (tensor, bufferRegion, outputPtr, region, channelOffset);
+ CopyTensorToImageRegion<TImage, float>(tensor, bufferRegion, outputPtr, region, channelOffset);
else if (dt == tensorflow::DT_DOUBLE)
- CopyTensorToImageRegion<TImage, double> (tensor, bufferRegion, outputPtr, region, channelOffset);
+ CopyTensorToImageRegion<TImage, double>(tensor, bufferRegion, outputPtr, region, channelOffset);
+ else if (dt == tensorflow::DT_UINT64)
+ CopyTensorToImageRegion<TImage, unsigned long long int>(tensor, bufferRegion, outputPtr, region, channelOffset);
else if (dt == tensorflow::DT_INT64)
CopyTensorToImageRegion<TImage, long long int>(tensor, bufferRegion, outputPtr, region, channelOffset);
+ else if (dt == tensorflow::DT_UINT32)
+ CopyTensorToImageRegion<TImage, unsigned int>(tensor, bufferRegion, outputPtr, region, channelOffset);
else if (dt == tensorflow::DT_INT32)
- CopyTensorToImageRegion<TImage, int> (tensor, bufferRegion, outputPtr, region, channelOffset);
+ CopyTensorToImageRegion<TImage, int>(tensor, bufferRegion, outputPtr, region, channelOffset);
+ else if (dt == tensorflow::DT_UINT16)
+ CopyTensorToImageRegion<TImage, unsigned short int>(tensor, bufferRegion, outputPtr, region, channelOffset);
+ else if (dt == tensorflow::DT_INT16)
+ CopyTensorToImageRegion<TImage, short int>(tensor, bufferRegion, outputPtr, region, channelOffset);
+ else if (dt == tensorflow::DT_UINT8)
+ CopyTensorToImageRegion<TImage, unsigned char>(tensor, bufferRegion, outputPtr, region, channelOffset);
else
- itkGenericExceptionMacro("TF DataType "<< dt << " not currently implemented !");
-
+ itkGenericExceptionMacro("TF DataType " << dt << " not currently implemented !");
}
//
// Compare two string lowercase
//
-bool iequals(const std::string& a, const std::string& b)
+bool
+iequals(const std::string & a, const std::string & b)
{
- return std::equal(a.begin(), a.end(),
- b.begin(), b.end(),
- [](char cha, char chb) {
- return tolower(cha) == tolower(chb);
- });
+ return std::equal(
+ a.begin(), a.end(), b.begin(), b.end(), [](char cha, char chb) { return tolower(cha) == tolower(chb); });
}
-// Convert an expression into a dict
-//
+// Convert a value into a tensor
// Following types are supported:
// -bool
// -int
// -float
+// -vector of float
+//
+// e.g. "true", "0.2", "14", "(1.2, 4.2, 4)"
//
-// e.g. is_training=true, droptout=0.2, nfeat=14
-std::pair<std::string, tensorflow::Tensor> ExpressionToTensor(std::string expression)
+// TODO: we could add some other types (e.g. string)
+tensorflow::Tensor
+ValueToTensor(std::string value)
{
- std::pair<std::string, tensorflow::Tensor> dict;
+ std::vector<std::string> values;
- std::size_t found = expression.find("=");
- if (found != std::string::npos)
- {
- // Find name and value
- std::string name = expression.substr(0, found);
- std::string value = expression.substr(found+1);
+ // Check if value is a vector or a scalar
+ const bool has_left = (value[0] == '(');
+ const bool has_right = value[value.size() - 1] == ')';
- dict.first = name;
+ // Check consistency
+ bool is_vec = false;
+ if (has_left || has_right)
+ {
+ is_vec = true;
+ if (!has_left || !has_right)
+ itkGenericExceptionMacro("Error parsing vector expression (missing parentheses ?)" << value);
+ }
+
+ // Scalar --> Vector for generic processing
+ if (!is_vec)
+ {
+ values.push_back(value);
+ }
+ else
+ {
+ // Remove "(" and ")" chars
+ std::string trimmed_value = value.substr(1, value.size() - 2);
+
+ // Split string into vector using "," delimiter
+ std::regex rgx("\\s*,\\s*");
+ std::sregex_token_iterator iter{ trimmed_value.begin(), trimmed_value.end(), rgx, -1 };
+ std::sregex_token_iterator end;
+ values = std::vector<std::string>({ iter, end });
+ }
+
+ // Find type
+ bool has_dot = false;
+ bool is_digit = true;
+ for (auto & val : values)
+ {
+ has_dot = has_dot || val.find(".") != std::string::npos;
+ is_digit = is_digit && val.find_first_not_of("-0123456789.") == std::string::npos;
+ }
+
+ // Create tensor
+ tensorflow::TensorShape shape({values.size()});
+ tensorflow::Tensor out(tensorflow::DT_BOOL, shape);
+ if (is_digit)
+ {
+ if (has_dot)
+ out = tensorflow::Tensor(tensorflow::DT_FLOAT, shape);
+ else
+ out = tensorflow::Tensor(tensorflow::DT_INT32, shape);
+ }
+
+ // Fill tensor
+ unsigned int idx = 0;
+ for (auto & val : values)
+ {
- // Find type
- std::size_t found_dot = value.find(".") != std::string::npos;
- std::size_t is_digit = value.find_first_not_of("0123456789.") == std::string::npos;
- if (is_digit)
+ if (is_digit)
+ {
+ if (has_dot)
{
- if (found_dot)
+ // FLOAT
+ try
{
- // FLOAT
- try
- {
- float val = std::stof(value);
- tensorflow::Tensor out(tensorflow::DT_FLOAT, tensorflow::TensorShape());
- out.scalar<float>()() = val;
- dict.second = out;
-
- }
- catch(...)
- {
- itkGenericExceptionMacro("Error parsing name="
- << name << " with value=" << value << " as float");
- }
-
+ out.flat<float>()(idx) = std::stof(val);
}
- else
+ catch (...)
{
- // INT
- try
- {
- int val = std::stoi(value);
- tensorflow::Tensor out(tensorflow::DT_INT32, tensorflow::TensorShape());
- out.scalar<int>()() = val;
- dict.second = out;
-
- }
- catch(...)
- {
- itkGenericExceptionMacro("Error parsing name="
- << name << " with value=" << value << " as int");
- }
-
+ itkGenericExceptionMacro("Error parsing value \"" << val << "\" as float");
}
}
else
{
- // BOOL
- bool val = true;
- if (iequals(value, "true"))
- {
- val = true;
- }
- else if (iequals(value, "false"))
+ // INT
+ try
{
- val = false;
+ out.flat<int>()(idx) = std::stoi(val);
}
- else
+ catch (...)
{
- itkGenericExceptionMacro("Error parsing name="
- << name << " with value=" << value << " as bool");
+ itkGenericExceptionMacro("Error parsing value \"" << val << "\" as int");
}
- tensorflow::Tensor out(tensorflow::DT_BOOL, tensorflow::TensorShape());
- out.scalar<bool>()() = val;
- dict.second = out;
}
-
}
else
{
- itkGenericExceptionMacro("The following expression is not valid: "
- << "\n\t" << expression
- << ".\nExpression must be in the form int_value=1 or float_value=1.0 or bool_value=true.");
+ // BOOL
+ bool ret = true;
+ if (iequals(val, "true"))
+ {
+ ret = true;
+ }
+ else if (iequals(val, "false"))
+ {
+ ret = false;
+ }
+ else
+ {
+ itkGenericExceptionMacro("Error parsing value \"" << val << "\" as bool");
+ }
+ out.flat<bool>()(idx) = ret;
}
+ idx++;
+ }
+ otbLogMacro(Debug, << "Returning tensor: "<< out.DebugString());
+
+ return out;
+}
+
+// Convert an expression into a dict
+//
+// Following types are supported:
+// -bool
+// -int
+// -float
+// -vector of float
+//
+// e.g. is_training=true, droptout=0.2, nfeat=14, x=(1.2, 4.2, 4)
+std::pair<std::string, tensorflow::Tensor>
+ExpressionToTensor(std::string expression)
+{
+ std::pair<std::string, tensorflow::Tensor> dict;
- return dict;
+ std::size_t found = expression.find("=");
+ if (found != std::string::npos)
+ {
+ // Find name and value
+ std::string name = expression.substr(0, found);
+ std::string value = expression.substr(found + 1);
+
+ dict.first = name;
+
+ // Transform value into tensorflow::Tensor
+ dict.second = ValueToTensor(value);
+ }
+ else
+ {
+ itkGenericExceptionMacro("The following expression is not valid: "
+ << "\n\t" << expression << ".\nExpression must be in one of the following form:"
+ << "\n- int32_value=1 \n- float_value=1.0 \n- bool_value=true."
+ << "\n- float_vec=(1.0, 5.253, 2)");
+ }
+
+ return dict;
}
} // end namespace tf
diff --git a/include/otbTensorflowCopyUtils.h b/include/otbTensorflowCopyUtils.h
index 47ad6cf2366137ac9719158069ac0d91ffef5813..174587913beb5a73f78cbffe614aef23c78c8147 100644
--- a/include/otbTensorflowCopyUtils.h
+++ b/include/otbTensorflowCopyUtils.h
@@ -1,7 +1,7 @@
/*=========================================================================
- Copyright (c) 2018-2019 Remi Cresson (IRSTEA)
- Copyright (c) 2020-2021 Remi Cresson (INRAE)
+ Copyright (c) 2018-2019 IRSTEA
+ Copyright (c) 2020-2021 INRAE
This software is distributed WITHOUT ANY WARRANTY; without even
@@ -15,18 +15,24 @@
// ITK exception
#include "itkMacro.h"
+// OTB log
+#include "otbMacro.h"
+
// ITK image iterators
#include "itkImageRegionIterator.h"
#include "itkImageRegionConstIterator.h"
// tensorflow::tensor
#include "tensorflow/core/framework/tensor.h"
+#include "tensorflow/core/framework/tensor_shape.h"
+#include "tensorflow/core/framework/tensor_shape.pb.h"
// tensorflow::datatype <--> ImageType::InternalPixelType
#include "otbTensorflowDataTypeBridge.h"
// STD
#include <string>
+#include <regex>
namespace otb {
namespace tf {
@@ -63,8 +69,8 @@ void SampleCenteredPatch(const typename TImage::Pointer inputPtr, const typename
template<class TImage>
void SampleCenteredPatch(const typename TImage::Pointer inputPtr, const typename TImage::PointType & centerCoord, const typename TImage::SizeType & patchSize, tensorflow::Tensor & tensor, unsigned int elemIdx);
-// Return the number of channels that the output tensor will occupy in the output image
-tensorflow::int64 GetNumberOfChannelsForOutputTensor(const tensorflow::Tensor & tensor);
+// Return the number of channels from the TensorflowShapeProto
+tensorflow::int64 GetNumberOfChannelsFromShapeProto(const tensorflow::TensorShapeProto & proto);
// Copy a tensor into the image region
template<class TImage, class TValueType>
@@ -74,6 +80,9 @@ void CopyTensorToImageRegion(const tensorflow::Tensor & tensor, typename TImage:
template<class TImage>
void CopyTensorToImageRegion(const tensorflow::Tensor & tensor, const typename TImage::RegionType & bufferRegion, typename TImage::Pointer outputPtr, const typename TImage::RegionType & outputRegion, int & channelOffset);
+// Convert a value into a tensor
+tensorflow::Tensor ValueToTensor(std::string value);
+
// Convert an expression into a dict
std::pair<std::string, tensorflow::Tensor> ExpressionToTensor(std::string expression);
diff --git a/include/otbTensorflowDataTypeBridge.cxx b/include/otbTensorflowDataTypeBridge.cxx
index 5a421c92ae0828a2cd39d91e06b6b0eb9aaa9aab..a510cb4ea5ecab0c1505e690d79922b2299ddc0d 100644
--- a/include/otbTensorflowDataTypeBridge.cxx
+++ b/include/otbTensorflowDataTypeBridge.cxx
@@ -1,7 +1,7 @@
/*=========================================================================
- Copyright (c) 2018-2019 Remi Cresson (IRSTEA)
- Copyright (c) 2020-2021 Remi Cresson (INRAE)
+ Copyright (c) 2018-2019 IRSTEA
+ Copyright (c) 2020-2021 INRAE
This software is distributed WITHOUT ANY WARRANTY; without even
@@ -80,5 +80,13 @@ bool HasSameDataType(const tensorflow::Tensor & tensor)
return GetTensorflowDataType<Type>() == tensor.dtype();
}
+//
+// Return the datatype as string
+//
+tensorflow::string GetDataTypeAsString(tensorflow::DataType dt)
+{
+ return tensorflow::DataTypeString(dt);
+}
+
} // end namespace tf
} // end namespace otb
diff --git a/include/otbTensorflowDataTypeBridge.h b/include/otbTensorflowDataTypeBridge.h
index 16e9dd23e63beff92f092bfe75fe899afe78b478..af6be18d335761b7261e6b8c7288cf9b07122bc8 100644
--- a/include/otbTensorflowDataTypeBridge.h
+++ b/include/otbTensorflowDataTypeBridge.h
@@ -1,7 +1,7 @@
/*=========================================================================
- Copyright (c) 2018-2019 Remi Cresson (IRSTEA)
- Copyright (c) 2020-2021 Remi Cresson (INRAE)
+ Copyright (c) 2018-2019 IRSTEA
+ Copyright (c) 2020-2021 INRAE
This software is distributed WITHOUT ANY WARRANTY; without even
@@ -27,6 +27,9 @@ tensorflow::DataType GetTensorflowDataType();
template<class Type>
bool HasSameDataType(const tensorflow::Tensor & tensor);
+// Return datatype as string
+tensorflow::string GetDataTypeAsString(tensorflow::DataType dt);
+
} // end namespace tf
} // end namespace otb
diff --git a/include/otbTensorflowGraphOperations.cxx b/include/otbTensorflowGraphOperations.cxx
index 16300f6c341a75a65947ed5bb7512d7d1187dbc7..d40c4da6a2f49a86cb28069094b4ab9f0cc5b231 100644
--- a/include/otbTensorflowGraphOperations.cxx
+++ b/include/otbTensorflowGraphOperations.cxx
@@ -1,7 +1,7 @@
/*=========================================================================
- Copyright (c) 2018-2019 Remi Cresson (IRSTEA)
- Copyright (c) 2020-2021 Remi Cresson (INRAE)
+ Copyright (c) 2018-2019 IRSTEA
+ Copyright (c) 2020-2021 INRAE
This software is distributed WITHOUT ANY WARRANTY; without even
@@ -11,161 +11,180 @@
=========================================================================*/
#include "otbTensorflowGraphOperations.h"
-namespace otb {
-namespace tf {
+namespace otb
+{
+namespace tf
+{
+
//
-// Restore a model from a path
+// Load SavedModel variables
//
-void RestoreModel(const tensorflow::tstring path, tensorflow::SavedModelBundle & bundle)
+void
+RestoreModel(const tensorflow::tstring path, tensorflow::SavedModelBundle & bundle)
{
tensorflow::Tensor checkpointPathTensor(tensorflow::DT_STRING, tensorflow::TensorShape());
checkpointPathTensor.scalar<tensorflow::tstring>()() = path;
- std::vector<std::pair<std::string, tensorflow::Tensor>> feed_dict =
- {{bundle.meta_graph_def.saver_def().filename_tensor_name(), checkpointPathTensor}};
- auto status = bundle.session->Run(feed_dict, {}, {bundle.meta_graph_def.saver_def().restore_op_name()}, nullptr);
+ std::vector<std::pair<std::string, tensorflow::Tensor>> feed_dict = {
+ { bundle.meta_graph_def.saver_def().filename_tensor_name(), checkpointPathTensor }
+ };
+ auto status = bundle.session->Run(feed_dict, {}, { bundle.meta_graph_def.saver_def().restore_op_name() }, nullptr);
if (!status.ok())
- {
- itkGenericExceptionMacro("Can't restore the input model: " << status.ToString() );
- }
+ {
+ itkGenericExceptionMacro("Can't restore the input model: " << status.ToString());
+ }
}
//
-// Restore a model from a path
+// Save SavedModel variables
//
-void SaveModel(const tensorflow::tstring path, tensorflow::SavedModelBundle & bundle)
+void
+SaveModel(const tensorflow::tstring path, tensorflow::SavedModelBundle & bundle)
{
tensorflow::Tensor checkpointPathTensor(tensorflow::DT_STRING, tensorflow::TensorShape());
checkpointPathTensor.scalar<tensorflow::tstring>()() = path;
- std::vector<std::pair<std::string, tensorflow::Tensor>> feed_dict =
- {{bundle.meta_graph_def.saver_def().filename_tensor_name(), checkpointPathTensor}};
- auto status = bundle.session->Run(feed_dict, {}, {bundle.meta_graph_def.saver_def().save_tensor_name()}, nullptr);
+ std::vector<std::pair<std::string, tensorflow::Tensor>> feed_dict = {
+ { bundle.meta_graph_def.saver_def().filename_tensor_name(), checkpointPathTensor }
+ };
+ auto status = bundle.session->Run(feed_dict, {}, { bundle.meta_graph_def.saver_def().save_tensor_name() }, nullptr);
if (!status.ok())
- {
- itkGenericExceptionMacro("Can't restore the input model: " << status.ToString() );
- }
+ {
+ itkGenericExceptionMacro("Can't restore the input model: " << status.ToString());
+ }
}
//
-// Load a session and a graph from a folder
+// Load a SavedModel
//
-void LoadModel(const tensorflow::tstring path, tensorflow::SavedModelBundle & bundle)
+void
+LoadModel(const tensorflow::tstring path, tensorflow::SavedModelBundle & bundle, std::vector<std::string> tagList)
{
+ // If the tag list is empty, we push back the default tag for model serving
+ if (tagList.size() == 0)
+ tagList.push_back(tensorflow::kSavedModelTagServe);
+ // std::vector --> std::unordered_list
+ std::unordered_set<std::string> tagSets;
+ std::copy(tagList.begin(), tagList.end(), std::inserter(tagSets, tagSets.end())); // copy in unordered_set
+
+ // Call to tensorflow::LoadSavedModel
tensorflow::RunOptions runoptions;
runoptions.set_trace_level(tensorflow::RunOptions_TraceLevel_FULL_TRACE);
- auto status = tensorflow::LoadSavedModel(tensorflow::SessionOptions(), runoptions,
- path, {tensorflow::kSavedModelTagServe}, &bundle);
+ auto status = tensorflow::LoadSavedModel(tensorflow::SessionOptions(), runoptions, path, tagSets, &bundle);
if (!status.ok())
- {
- itkGenericExceptionMacro("Can't load the input model: " << status.ToString() );
- }
-
+ {
+ itkGenericExceptionMacro("Can't load the input model: " << status.ToString());
+ }
}
-//
-// Load a graph from a .meta file
-//
-tensorflow::GraphDef LoadGraph(std::string filename)
-{
- tensorflow::MetaGraphDef meta_graph_def;
- auto status = tensorflow::ReadBinaryProto(tensorflow::Env::Default(), filename, &meta_graph_def);
- if (!status.ok())
- {
- itkGenericExceptionMacro("Can't load the input model: " << status.ToString() );
- }
-
- return meta_graph_def.graph_def();
-}
-//
// Get the following attributes of the specified tensors (by name) of a graph:
+// - layer name, as specified in the model
// - shape
// - datatype
-// Here we assume that the node's output is a tensor
-//
-void GetTensorAttributes(const tensorflow::GraphDef & graph, std::vector<std::string> & tensorsNames,
- std::vector<tensorflow::TensorShapeProto> & shapes, std::vector<tensorflow::DataType> & dataTypes)
+void
+GetTensorAttributes(const tensorflow::protobuf::Map<std::string, tensorflow::TensorInfo> layers,
+ std::vector<std::string> & tensorsNames,
+ std::vector<std::string> & layerNames,
+ std::vector<tensorflow::TensorShapeProto> & shapes,
+ std::vector<tensorflow::DataType> & dataTypes)
{
// Allocation
shapes.clear();
- shapes.reserve(tensorsNames.size());
dataTypes.clear();
- dataTypes.reserve(tensorsNames.size());
+ layerNames.clear();
- // Get infos
- for (std::vector<std::string>::iterator nameIt = tensorsNames.begin();
- nameIt != tensorsNames.end(); ++nameIt)
- {
- bool found = false;
- for (int i = 0 ; i < graph.node_size() ; i++)
- {
- tensorflow::NodeDef node = graph.node(i);
+ // Debug infos
+ otbLogMacro(Debug, << "Nodes contained in the model: ");
+ for (auto const & layer : layers)
+ otbLogMacro(Debug, << "\t" << layer.first);
+ // When the user doesn't specify output.names, m_OutputTensors defaults to an empty list that we can not iterate over.
+ // We change it to a list containing an empty string [""]
+ if (tensorsNames.size() == 0)
+ {
+ otbLogMacro(Debug, << "No output.name specified. Using a default list with one empty string.");
+ tensorsNames.push_back("");
+ }
- if (node.name().compare((*nameIt)) == 0)
- {
- found = true;
+ // Next, we fill layerNames
+ int k = 0; // counter used for tensorsNames
+ for (auto const & name: tensorsNames)
+ {
+ bool found = false;
+ tensorflow::TensorInfo tensor_info;
- // Set default to DT_FLOAT
- tensorflow::DataType ts_dt = tensorflow::DT_FLOAT;
+ // If the user didn't specify the placeholdername, choose the kth layer inside the model
+ if (name.size() == 0)
+ {
+ found = true;
+ // select the k-th element of `layers`
+ auto it = layers.begin();
+ std::advance(it, k);
+ layerNames.push_back(it->second.name());
+ tensor_info = it->second;
+ otbLogMacro(Debug, << "Input " << k << " corresponds to " << it->first << " in the model");
+ }
- // Default (input?) tensor type
- auto test_is_output = node.attr().find("T");
- if (test_is_output != node.attr().end())
- {
- ts_dt = node.attr().at("T").type();
- }
- auto test_has_dtype = node.attr().find("dtype");
- if (test_has_dtype != node.attr().end())
- {
- ts_dt = node.attr().at("dtype").type();
- }
- auto test_output_type = node.attr().find("output_type");
- if (test_output_type != node.attr().end())
+ // Else, if the user specified the placeholdername, find the corresponding layer inside the model
+ else
+ {
+ otbLogMacro(Debug, << "Searching for corresponding node of: " << name << "... ");
+ for (auto const & layer : layers)
+ {
+ // layer is a pair (name, tensor_info)
+ // cf https://stackoverflow.com/questions/63181951/how-to-get-graph-or-graphdef-from-a-given-model
+ std::string layername = layer.first;
+ if (layername.substr(0, layername.find(":")).compare(name) == 0)
{
- // if there is an output type, we take it instead of the
- // datatype of the input tensor
- ts_dt = node.attr().at("output_type").type();
+ found = true;
+ layerNames.push_back(layer.second.name());
+ tensor_info = layer.second;
+ otbLogMacro(Debug, << "Found: " << layer.second.name() << " in the model");
}
- dataTypes.push_back(ts_dt);
+ } // next layer
+ } // end else
- // Get the tensor's shape
- // Here we assure it's a tensor, with 1 shape
- tensorflow::TensorShapeProto ts_shp = node.attr().at("_output_shapes").list().shape(0);
- shapes.push_back(ts_shp);
- }
- }
+ k += 1;
if (!found)
{
- itkGenericExceptionMacro("Tensor name \"" << (*nameIt) << "\" not found" );
+ itkGenericExceptionMacro("Tensor name \"" << name << "\" not found. \n"
+ << "You can list all inputs/outputs of your SavedModel by "
+ << "running: \n\t `saved_model_cli show --dir your_model_dir --all`");
}
- }
+ // Default tensor type
+ tensorflow::DataType ts_dt = tensor_info.dtype();
+ dataTypes.push_back(ts_dt);
+ // Get the tensor's shape
+ // Here we assure it's a tensor, with 1 shape
+ tensorflow::TensorShapeProto ts_shp = tensor_info.tensor_shape();
+ shapes.push_back(ts_shp);
+ } // next tensor name
}
//
// Print a lot of stuff about the specified nodes of the graph
//
-void PrintNodeAttributes(const tensorflow::GraphDef & graph, std::vector<std::string> & nodesNames)
+void
+PrintNodeAttributes(const tensorflow::GraphDef & graph, const std::vector<std::string> & nodesNames)
{
std::cout << "Go through graph:" << std::endl;
std::cout << "#\tname" << std::endl;
- for (int i = 0 ; i < graph.node_size() ; i++)
+ for (int i = 0; i < graph.node_size(); i++)
{
tensorflow::NodeDef node = graph.node(i);
std::cout << i << "\t" << node.name() << std::endl;
- for (std::vector<std::string>::iterator nameIt = nodesNames.begin();
- nameIt != nodesNames.end(); ++nameIt)
+ for (auto const & name: nodesNames)
{
- if (node.name().compare((*nameIt)) == 0)
+ if (node.name().compare(name) == 0)
{
std::cout << "Node " << i << " : " << std::endl;
std::cout << "\tName: " << node.name() << std::endl;
- std::cout << "\tinput_size() : " << node.input_size() << std::endl;
+ std::cout << "\tinput_size(): " << node.input_size() << std::endl;
std::cout << "\tPrintDebugString --------------------------------";
std::cout << std::endl;
node.PrintDebugString();
@@ -173,20 +192,19 @@ void PrintNodeAttributes(const tensorflow::GraphDef & graph, std::vector<std::st
// display all attributes of the node
std::cout << "\tAttributes of the node: " << std::endl;
- for (auto attr = node.attr().begin() ; attr != node.attr().end() ; attr++)
+ for (auto attr = node.attr().begin(); attr != node.attr().end(); attr++)
{
- std::cout << "\t\tKey :" << attr->first << std::endl;
- std::cout << "\t\tValue.value_case() :" << attr->second.value_case() << std::endl;
+ std::cout << "\t\tKey: " << attr->first << std::endl;
+ std::cout << "\t\tValue.value_case(): " << attr->second.value_case() << std::endl;
std::cout << "\t\tPrintDebugString --------------------------------";
std::cout << std::endl;
attr->second.PrintDebugString();
std::cout << "\t\t-------------------------------------------------" << std::endl;
std::cout << std::endl;
} // next attribute
- } // node name match
- } // next node name
- } // next node of the graph
-
+ } // node name match
+ } // next node name
+ } // next node of the graph
}
} // end namespace tf
diff --git a/include/otbTensorflowGraphOperations.h b/include/otbTensorflowGraphOperations.h
index 4b4e93c016a09eaab5182ceb6800126665ccad92..6ad4a4e29880e10a5f10cbc4f1e945db9ca3c6a6 100644
--- a/include/otbTensorflowGraphOperations.h
+++ b/include/otbTensorflowGraphOperations.h
@@ -1,7 +1,7 @@
/*=========================================================================
- Copyright (c) 2018-2019 Remi Cresson (IRSTEA)
- Copyright (c) 2020-2021 Remi Cresson (INRAE)
+ Copyright (c) 2018-2019 IRSTEA
+ Copyright (c) 2020-2021 INRAE
This software is distributed WITHOUT ANY WARRANTY; without even
@@ -24,30 +24,30 @@
// ITK exception
#include "itkMacro.h"
+// OTB log
+#include "otbMacro.h"
+
namespace otb {
namespace tf {
-// Restore a model from a path
+// Load SavedModel variables
void RestoreModel(const tensorflow::tstring path, tensorflow::SavedModelBundle & bundle);
-// Restore a model from a path
+// Save SavedModel variables
void SaveModel(const tensorflow::tstring path, tensorflow::SavedModelBundle & bundle);
-// Load a session and a graph from a folder
-void LoadModel(const tensorflow::tstring path, tensorflow::SavedModelBundle & bundle);
-
-// Load a graph from a .meta file
-tensorflow::GraphDef LoadGraph(std::string filename);
+// Load SavedModel
+void LoadModel(const tensorflow::tstring path, tensorflow::SavedModelBundle & bundle, std::vector<std::string> tagList);
// Get the following attributes of the specified tensors (by name) of a graph:
// - shape
// - datatype
// Here we assume that the node's output is a tensor
-void GetTensorAttributes(const tensorflow::GraphDef & graph, std::vector<std::string> & tensorsNames,
+void GetTensorAttributes(const tensorflow::protobuf::Map<std::string, tensorflow::TensorInfo> layers, std::vector<std::string> & tensorsNames,
std::vector<tensorflow::TensorShapeProto> & shapes, std::vector<tensorflow::DataType> & dataTypes);
// Print a lot of stuff about the specified nodes of the graph
-void PrintNodeAttributes(const tensorflow::GraphDef & graph, std::vector<std::string> & nodesNames);
+void PrintNodeAttributes(const tensorflow::GraphDef & graph, const std::vector<std::string> & nodesNames);
} // end namespace tf
} // end namespace otb
diff --git a/include/otbTensorflowMultisourceModelBase.h b/include/otbTensorflowMultisourceModelBase.h
index 9fb0a79ce7e48144af182dc02063f3c8911c7b7b..d10648ea00afc6fc624fc9ffac8e19bbdffdf4f2 100644
--- a/include/otbTensorflowMultisourceModelBase.h
+++ b/include/otbTensorflowMultisourceModelBase.h
@@ -1,7 +1,7 @@
/*=========================================================================
- Copyright (c) 2018-2019 Remi Cresson (IRSTEA)
- Copyright (c) 2020-2021 Remi Cresson (INRAE)
+ Copyright (c) 2018-2019 IRSTEA
+ Copyright (c) 2020-2021 INRAE
This software is distributed WITHOUT ANY WARRANTY; without even
@@ -15,10 +15,12 @@
#include "itkProcessObject.h"
#include "itkNumericTraits.h"
#include "itkSimpleDataObjectDecorator.h"
+#include "itkImageToImageFilter.h"
// Tensorflow
#include "tensorflow/core/public/session.h"
#include "tensorflow/core/platform/env.h"
+#include "tensorflow/cc/saved_model/signature_constants.h"
// Tensorflow helpers
#include "otbTensorflowGraphOperations.h"
@@ -45,8 +47,7 @@ namespace otb
* be the same. If not, an exception will be thrown during the method
* GenerateOutputInformation().
*
- * The TensorFlow graph and session must be set using the SetGraph() and
- * SetSession() methods.
+ * The TensorFlow SavedModel pointer must be set using the SetSavedModel() method.
*
* Target nodes names of the TensorFlow graph that must be triggered can be set
* with the SetTargetNodesNames.
@@ -103,10 +104,11 @@ public:
typedef std::vector<tensorflow::Tensor> TensorListType;
/** Set and Get the Tensorflow session and graph */
- void SetGraph(tensorflow::GraphDef graph) { m_Graph = graph; }
- tensorflow::GraphDef GetGraph() { return m_Graph ; }
- void SetSession(tensorflow::Session * session) { m_Session = session; }
- tensorflow::Session * GetSession() { return m_Session; }
+ void SetSavedModel(tensorflow::SavedModelBundle * saved_model) {m_SavedModel = saved_model;}
+ tensorflow::SavedModelBundle * GetSavedModel() {return m_SavedModel;}
+
+ /** Get the SignatureDef */
+ tensorflow::SignatureDef GetSignatureDef();
/** Model parameters */
void PushBackInputTensorBundle(std::string name, SizeType receptiveField, ImagePointerType image);
@@ -129,8 +131,8 @@ public:
itkGetMacro(OutputExpressionFields, SizeListType);
/** User placeholders */
- void SetUserPlaceholders(DictType dict) { m_UserPlaceholders = dict; }
- DictType GetUserPlaceholders() { return m_UserPlaceholders; }
+ void SetUserPlaceholders(const DictType & dict) {m_UserPlaceholders = dict;}
+ DictType GetUserPlaceholders() {return m_UserPlaceholders;}
/** Target nodes names */
itkSetMacro(TargetNodesNames, StringList);
@@ -157,8 +159,7 @@ private:
void operator=(const Self&); //purposely not implemented
// Tensorflow graph and session
- tensorflow::GraphDef m_Graph; // The TensorFlow graph
- tensorflow::Session * m_Session; // The TensorFlow session
+ tensorflow::SavedModelBundle * m_SavedModel; // The TensorFlow model
// Model parameters
StringList m_InputPlaceholders; // Input placeholders names
@@ -174,6 +175,10 @@ private:
TensorShapeProtoList m_InputTensorsShapes; // Input tensors shapes
TensorShapeProtoList m_OutputTensorsShapes; // Output tensors shapes
+ // Layer names inside the model corresponding to inputs and outputs
+ StringList m_InputLayers; // List of input names, as contained in the model
+ StringList m_OutputLayers; // List of output names, as contained in the model
+
}; // end class
diff --git a/include/otbTensorflowMultisourceModelBase.hxx b/include/otbTensorflowMultisourceModelBase.hxx
index 02c98baeea3ec32f36f6a707a6a99d75fc99e79c..752b7c9d61a861d260dc4dfac89efb66e772a42b 100644
--- a/include/otbTensorflowMultisourceModelBase.hxx
+++ b/include/otbTensorflowMultisourceModelBase.hxx
@@ -1,7 +1,7 @@
/*=========================================================================
- Copyright (c) 2018-2019 Remi Cresson (IRSTEA)
- Copyright (c) 2020-2021 Remi Cresson (INRAE)
+ Copyright (c) 2018-2019 IRSTEA
+ Copyright (c) 2020-2021 INRAE
This software is distributed WITHOUT ANY WARRANTY; without even
@@ -20,27 +20,56 @@ namespace otb
template <class TInputImage, class TOutputImage>
TensorflowMultisourceModelBase<TInputImage, TOutputImage>
::TensorflowMultisourceModelBase()
- {
- m_Session = nullptr;
+{
Superclass::SetCoordinateTolerance(itk::NumericTraits<double>::max() );
Superclass::SetDirectionTolerance(itk::NumericTraits<double>::max() );
- }
+
+ m_SavedModel = NULL;
+}
+
+template <class TInputImage, class TOutputImage>
+tensorflow::SignatureDef
+TensorflowMultisourceModelBase<TInputImage, TOutputImage>
+::GetSignatureDef()
+{
+ auto signatures = this->GetSavedModel()->GetSignatures();
+ tensorflow::SignatureDef signature_def;
+
+ if (signatures.size() == 0)
+ {
+ itkExceptionMacro("There are no available signatures for this tag-set. \n" <<
+ "Please check which tag-set to use by running "<<
+ "`saved_model_cli show --dir your_model_dir --all`");
+ }
+
+ // If serving_default key exists (which is the default for TF saved model), choose it as signature
+ // Else, choose the first one
+ if (signatures.contains(tensorflow::kDefaultServingSignatureDefKey))
+ {
+ signature_def = signatures.at(tensorflow::kDefaultServingSignatureDefKey);
+ }
+ else
+ {
+ signature_def = signatures.begin()->second;
+ }
+ return signature_def;
+}
template <class TInputImage, class TOutputImage>
void
TensorflowMultisourceModelBase<TInputImage, TOutputImage>
::PushBackInputTensorBundle(std::string placeholder, SizeType receptiveField, ImagePointerType image)
- {
+{
Superclass::PushBackInput(image);
m_InputReceptiveFields.push_back(receptiveField);
m_InputPlaceholders.push_back(placeholder);
- }
+}
template <class TInputImage, class TOutputImage>
std::stringstream
TensorflowMultisourceModelBase<TInputImage, TOutputImage>
::GenerateDebugReport(DictType & inputs)
- {
+{
// Create a debug report
std::stringstream debugReport;
@@ -51,43 +80,53 @@ TensorflowMultisourceModelBase<TInputImage, TOutputImage>
// Describe inputs
for (unsigned int i = 0 ; i < this->GetNumberOfInputs() ; i++)
- {
+ {
const ImagePointerType inputPtr = const_cast<TInputImage*>(this->GetInput(i));
const RegionType reqRegion = inputPtr->GetRequestedRegion();
debugReport << "Input #" << i << ":\n";
debugReport << "Requested region: " << reqRegion << "\n";
- debugReport << "Tensor shape (\"" << inputs[i].first << "\": " << tf::PrintTensorShape(inputs[i].second.shape()) << "\n";
- }
+ debugReport << "Tensor \"" << inputs[i].first << "\": " << tf::PrintTensorInfos(inputs[i].second) << "\n";
+ }
// Show user placeholders
debugReport << "User placeholders:\n" ;
for (auto& dict: this->GetUserPlaceholders())
- {
- debugReport << dict.first << " " << tf::PrintTensorInfos(dict.second) << "\n" << std::endl;
- }
+ {
+ debugReport << "Tensor \"" << dict.first << "\": " << tf::PrintTensorInfos(dict.second) << "\n" << std::endl;
+ }
return debugReport;
- }
+}
template <class TInputImage, class TOutputImage>
void
TensorflowMultisourceModelBase<TInputImage, TOutputImage>
::RunSession(DictType & inputs, TensorListType & outputs)
- {
+{
// Add the user's placeholders
- for (auto& dict: this->GetUserPlaceholders())
- {
- inputs.push_back(dict);
- }
+ std::copy(this->GetUserPlaceholders().begin(), this->GetUserPlaceholders().end(), std::back_inserter(inputs));
// Run the TF session here
// The session will initialize the outputs
+ // `inputs` corresponds to a mapping {name, tensor}, with the name being specified by the user when calling TensorFlowModelServe
+ // we must adapt it to `inputs_new`, that corresponds to a mapping {layerName, tensor}, with the layerName being from the model
+ DictType inputs_new;
+ int k = 0;
+ for (auto& dict: inputs)
+ {
+ DictElementType element = {m_InputLayers[k], dict.second};
+ inputs_new.push_back(element);
+ k+=1;
+ }
+
// Run the session, evaluating our output tensors from the graph
- auto status = this->GetSession()->Run(inputs, m_OutputTensors, m_TargetNodesNames, &outputs);
- if (!status.ok()) {
+ auto status = this->GetSavedModel()->session.get()->Run(inputs_new, m_OutputLayers, m_TargetNodesNames, &outputs);
+
+ if (!status.ok())
+ {
// Create a debug report
std::stringstream debugReport = GenerateDebugReport(inputs);
@@ -96,16 +135,14 @@ TensorflowMultisourceModelBase<TInputImage, TOutputImage>
itkExceptionMacro("Can't run the tensorflow session !\n" <<
"Tensorflow error message:\n" << status.ToString() << "\n"
"OTB Filter debug message:\n" << debugReport.str() );
-
}
-
- }
+}
template <class TInputImage, class TOutputImage>
void
TensorflowMultisourceModelBase<TInputImage, TOutputImage>
::GenerateOutputInformation()
- {
+{
// Check that the number of the following is the same
// - input placeholders names
@@ -113,30 +150,27 @@ TensorflowMultisourceModelBase<TInputImage, TOutputImage>
// - input images
const unsigned int nbInputs = this->GetNumberOfInputs();
if (nbInputs != m_InputReceptiveFields.size() || nbInputs != m_InputPlaceholders.size())
- {
+ {
itkExceptionMacro("Number of input images is " << nbInputs <<
" but the number of input patches size is " << m_InputReceptiveFields.size() <<
" and the number of input tensors names is " << m_InputPlaceholders.size());
- }
-
- // Check that the number of the following is the same
- // - output tensors names
- // - output expression fields
- if (m_OutputExpressionFields.size() != m_OutputTensors.size())
- {
- itkExceptionMacro("Number of output tensors names is " << m_OutputTensors.size() <<
- " but the number of output fields of expression is " << m_OutputExpressionFields.size());
- }
+ }
//////////////////////////////////////////////////////////////////////////////////////////
// Get tensors information
//////////////////////////////////////////////////////////////////////////////////////////
-
- // Get input and output tensors datatypes and shapes
- tf::GetTensorAttributes(m_Graph, m_InputPlaceholders, m_InputTensorsShapes, m_InputTensorsDataTypes);
- tf::GetTensorAttributes(m_Graph, m_OutputTensors, m_OutputTensorsShapes, m_OutputTensorsDataTypes);
-
- }
+ // Set all subelement of the model
+ auto signaturedef = this->GetSignatureDef();
+
+ // Given the inputs/outputs names that the user specified, get the names of the inputs/outputs contained in the model
+ // and other infos (shapes, dtypes)
+ // For example, for output names specified by the user m_OutputTensors = ['s2t', 's2t_pad'],
+ // this will return m_OutputLayers = ['PartitionedCall:0', 'PartitionedCall:1']
+ // In case the user hasn't named the output, e.g. m_OutputTensors = [''],
+ // this will return the first output m_OutputLayers = ['PartitionedCall:0']
+ tf::GetTensorAttributes(signaturedef.inputs(), m_InputPlaceholders, m_InputLayers, m_InputTensorsShapes, m_InputTensorsDataTypes);
+ tf::GetTensorAttributes(signaturedef.outputs(), m_OutputTensors, m_OutputLayers, m_OutputTensorsShapes, m_OutputTensorsDataTypes);
+}
} // end namespace otb
diff --git a/include/otbTensorflowMultisourceModelFilter.h b/include/otbTensorflowMultisourceModelFilter.h
index 46a273af36f9a4aefd6a365ca36b9557eebab37e..36d781dd1519b964adce741a8adbcb1385b0c729 100644
--- a/include/otbTensorflowMultisourceModelFilter.h
+++ b/include/otbTensorflowMultisourceModelFilter.h
@@ -1,7 +1,7 @@
/*=========================================================================
- Copyright (c) 2018-2019 Remi Cresson (IRSTEA)
- Copyright (c) 2020-2021 Remi Cresson (INRAE)
+ Copyright (c) 2018-2019 IRSTEA
+ Copyright (c) 2020-2021 INRAE
This software is distributed WITHOUT ANY WARRANTY; without even
@@ -17,15 +17,13 @@
// Iterator
#include "itkImageRegionConstIteratorWithOnlyIndex.h"
-// Tensorflow helpers
-#include "otbTensorflowGraphOperations.h"
-#include "otbTensorflowDataTypeBridge.h"
-#include "otbTensorflowCopyUtils.h"
-
// Tile hint
#include "itkMetaDataObject.h"
#include "otbMetaDataKey.h"
+// OTB log
+#include "otbMacro.h"
+
namespace otb
{
diff --git a/include/otbTensorflowMultisourceModelFilter.hxx b/include/otbTensorflowMultisourceModelFilter.hxx
index 91c5384ea1b508fcd359c120a067ed99c4a11126..d208f01a8deb1834b98f64c1230423d44b2cfe7a 100644
--- a/include/otbTensorflowMultisourceModelFilter.hxx
+++ b/include/otbTensorflowMultisourceModelFilter.hxx
@@ -1,7 +1,7 @@
/*=========================================================================
- Copyright (c) 2018-2019 Remi Cresson (IRSTEA)
- Copyright (c) 2020-2021 Remi Cresson (INRAE)
+ Copyright (c) 2018-2019 IRSTEA
+ Copyright (c) 2020-2021 INRAE
This software is distributed WITHOUT ANY WARRANTY; without even
@@ -201,15 +201,19 @@ TensorflowMultisourceModelFilter<TInputImage, TOutputImage>
//////////////////////////////////////////////////////////////////////////////////////////
// If the output spacing is not specified, we use the first input image as grid reference
- m_OutputSpacing = this->GetInput(0)->GetSignedSpacing();
+ // OTBTF assumes that the output image has the following geometric properties:
+ // (1) Image origin is the top-left pixel
+ // (2) Image pixel spacing has positive x-spacing and negative y-spacing
+ m_OutputSpacing = this->GetInput(0)->GetSpacing(); // GetSpacing() returns abs. spacing
+ m_OutputSpacing[1] *= -1.0; // Force negative y-spacing
m_OutputSpacing[0] *= m_OutputSpacingScale;
m_OutputSpacing[1] *= m_OutputSpacingScale;
- PointType extentInf, extentSup;
- extentSup.Fill(itk::NumericTraits<double>::max());
- extentInf.Fill(itk::NumericTraits<double>::NonpositiveMin());
// Compute the extent of each input images and update the extent or the output image.
// The extent of the output image is the intersection of all input images extents.
+ PointType extentInf, extentSup;
+ extentSup.Fill(itk::NumericTraits<double>::max());
+ extentInf.Fill(itk::NumericTraits<double>::NonpositiveMin());
for (unsigned int imageIndex = 0 ; imageIndex < this->GetNumberOfInputs() ; imageIndex++)
{
ImageType * currentImage = static_cast<ImageType *>(
@@ -267,17 +271,22 @@ TensorflowMultisourceModelFilter<TInputImage, TOutputImage>
unsigned int outputPixelSize = 0;
for (auto& protoShape: this->GetOutputTensorsShapes())
{
- // The number of components per pixel is the last dimension of the tensor
- int dim_size = protoShape.dim_size();
- unsigned int nComponents = 1;
- if (1 < dim_size && dim_size <= 4)
- {
- nComponents = protoShape.dim(dim_size-1).size();
- }
- else if (dim_size > 4)
+ // Find the number of components
+ if (protoShape.dim_size() > 4)
{
- itkExceptionMacro("Dim_size=" << dim_size << " currently not supported.");
+ itkExceptionMacro("dim_size=" << protoShape.dim_size() << " currently not supported. "
+ "Keep in mind that output tensors must have 1, 2, 3 or 4 dimensions. "
+ "In the case of 1-dimensional tensor, the first dimension is for the batch, "
+ "and we assume that the output tensor has 1 channel. "
+ "In the case of 2-dimensional tensor, the first dimension is for the batch, "
+ "and the second is the number of components. "
+ "In the case of 3-dimensional tensor, the first dimension is for the batch, "
+ "and other dims are for (x, y). "
+ "In the case of 4-dimensional tensor, the first dimension is for the batch, "
+ "and the second and the third are for (x, y). The last is for the number of "
+ "channels. ");
}
+ unsigned int nComponents = tf::GetNumberOfChannelsFromShapeProto(protoShape);
outputPixelSize += nComponents;
}
@@ -329,7 +338,7 @@ TensorflowMultisourceModelFilter<TInputImage, TOutputImage>
if (!OutputRegionToInputRegion(requestedRegion, inRegion, inputImage) )
{
// Image does not overlap requested region: set requested region to null
- itkDebugMacro( << "Image #" << i << " :\n" << inRegion << " is outside the requested region");
+ otbLogMacro(Debug, << "Image #" << i << " :\n" << inRegion << " is outside the requested region");
inRegion.GetModifiableIndex().Fill(0);
inRegion.GetModifiableSize().Fill(0);
}
@@ -393,6 +402,7 @@ TensorflowMultisourceModelFilter<TInputImage, TOutputImage>
// Create input tensors list
DictType inputs;
+
// Populate input tensors
for (unsigned int i = 0 ; i < nInputs ; i++)
{
@@ -462,6 +472,7 @@ TensorflowMultisourceModelFilter<TInputImage, TOutputImage>
} // next input tensor
// Run session
+ // TODO: see if we print some info about inputs/outputs of the model e.g. m_OutputTensors
TensorListType outputs;
this->RunSession(inputs, outputs);
@@ -485,7 +496,7 @@ TensorflowMultisourceModelFilter<TInputImage, TOutputImage>
catch( itk::ExceptionObject & err )
{
std::stringstream debugMsg = this->GenerateDebugReport(inputs);
- itkExceptionMacro("Error occured during tensor to image conversion.\n"
+ itkExceptionMacro("Error occurred during tensor to image conversion.\n"
<< "Context: " << debugMsg.str()
<< "Error:" << err);
}
diff --git a/include/otbTensorflowMultisourceModelLearningBase.h b/include/otbTensorflowMultisourceModelLearningBase.h
index ba130453ff73a810e3cb25a15e577bea63c78377..0663f17a3f6367d5f5fe0ebbc76b1ca71d64957d 100644
--- a/include/otbTensorflowMultisourceModelLearningBase.h
+++ b/include/otbTensorflowMultisourceModelLearningBase.h
@@ -1,7 +1,7 @@
/*=========================================================================
- Copyright (c) 2018-2019 Remi Cresson (IRSTEA)
- Copyright (c) 2020-2021 Remi Cresson (INRAE)
+ Copyright (c) 2018-2019 IRSTEA
+ Copyright (c) 2020-2021 INRAE
This software is distributed WITHOUT ANY WARRANTY; without even
@@ -100,7 +100,7 @@ protected:
TensorflowMultisourceModelLearningBase();
virtual ~TensorflowMultisourceModelLearningBase() {};
- virtual void GenerateOutputInformation(void);
+ virtual void GenerateOutputInformation(void) override;
virtual void GenerateInputRequestedRegion();
diff --git a/include/otbTensorflowMultisourceModelLearningBase.hxx b/include/otbTensorflowMultisourceModelLearningBase.hxx
index 353478292169c211bc1992549a3b814212f9b59f..28b2328b8b82c49896ed40a1edd18fba5cebd7a7 100644
--- a/include/otbTensorflowMultisourceModelLearningBase.hxx
+++ b/include/otbTensorflowMultisourceModelLearningBase.hxx
@@ -1,7 +1,7 @@
/*=========================================================================
- Copyright (c) 2018-2019 Remi Cresson (IRSTEA)
- Copyright (c) 2020-2021 Remi Cresson (INRAE)
+ Copyright (c) 2018-2019 IRSTEA
+ Copyright (c) 2020-2021 INRAE
This software is distributed WITHOUT ANY WARRANTY; without even
diff --git a/include/otbTensorflowMultisourceModelTrain.h b/include/otbTensorflowMultisourceModelTrain.h
index 8f8983ca0acd20533d9a94936f4d4f1bbec175ea..8ec4c38c369d532a706746c9674197ad766f657b 100644
--- a/include/otbTensorflowMultisourceModelTrain.h
+++ b/include/otbTensorflowMultisourceModelTrain.h
@@ -1,7 +1,7 @@
/*=========================================================================
- Copyright (c) 2018-2019 Remi Cresson (IRSTEA)
- Copyright (c) 2020-2021 Remi Cresson (INRAE)
+ Copyright (c) 2018-2019 IRSTEA
+ Copyright (c) 2020-2021 INRAE
This software is distributed WITHOUT ANY WARRANTY; without even
diff --git a/include/otbTensorflowMultisourceModelTrain.hxx b/include/otbTensorflowMultisourceModelTrain.hxx
index e7b68dac9567ebb73065a368cee3cc8e4ef94992..272dd6390668bd233c5ec41b99ff2b088ef313c3 100644
--- a/include/otbTensorflowMultisourceModelTrain.hxx
+++ b/include/otbTensorflowMultisourceModelTrain.hxx
@@ -1,7 +1,7 @@
/*=========================================================================
- Copyright (c) 2018-2019 Remi Cresson (IRSTEA)
- Copyright (c) 2020-2021 Remi Cresson (INRAE)
+ Copyright (c) 2018-2019 IRSTEA
+ Copyright (c) 2020-2021 INRAE
This software is distributed WITHOUT ANY WARRANTY; without even
diff --git a/include/otbTensorflowMultisourceModelValidate.h b/include/otbTensorflowMultisourceModelValidate.h
index f4a95406f06d5b5c1318cf1e5eb8ca16cdfb995e..322f6a24e288db9d9acf202e72ffe04ff8d8a8d4 100644
--- a/include/otbTensorflowMultisourceModelValidate.h
+++ b/include/otbTensorflowMultisourceModelValidate.h
@@ -1,7 +1,7 @@
/*=========================================================================
- Copyright (c) 2018-2019 Remi Cresson (IRSTEA)
- Copyright (c) 2020-2021 Remi Cresson (INRAE)
+ Copyright (c) 2018-2019 IRSTEA
+ Copyright (c) 2020-2021 INRAE
This software is distributed WITHOUT ANY WARRANTY; without even
diff --git a/include/otbTensorflowMultisourceModelValidate.hxx b/include/otbTensorflowMultisourceModelValidate.hxx
index c7673c8fc79abcfe322b02e5ee765aa9e560914e..8ec685ba81c1ae51111a077e8170dd227be7241e 100644
--- a/include/otbTensorflowMultisourceModelValidate.hxx
+++ b/include/otbTensorflowMultisourceModelValidate.hxx
@@ -1,7 +1,7 @@
/*=========================================================================
- Copyright (c) 2018-2019 Remi Cresson (IRSTEA)
- Copyright (c) 2020-2021 Remi Cresson (INRAE)
+ Copyright (c) 2018-2019 IRSTEA
+ Copyright (c) 2020-2021 INRAE
This software is distributed WITHOUT ANY WARRANTY; without even
@@ -98,7 +98,7 @@ TensorflowMultisourceModelValidate<TInputImage>
/**
* Perform the validation
* The session is ran over the entire set of batches.
- * Output is then validated agains the references images,
+ * Output is then validated against the references images,
* and a confusion matrix is built.
*/
template <class TInputImage>
diff --git a/include/otbTensorflowSampler.h b/include/otbTensorflowSampler.h
index d71eba7af1fc6a9d4e24405e0c087c520d456d9d..bd363bc8ee191ce7506ca012b68171f6d8bdc828 100644
--- a/include/otbTensorflowSampler.h
+++ b/include/otbTensorflowSampler.h
@@ -1,7 +1,7 @@
/*=========================================================================
- Copyright (c) 2018-2019 Remi Cresson (IRSTEA)
- Copyright (c) 2020-2021 Remi Cresson (INRAE)
+ Copyright (c) 2018-2019 IRSTEA
+ Copyright (c) 2020-2021 INRAE
This software is distributed WITHOUT ANY WARRANTY; without even
diff --git a/include/otbTensorflowSampler.hxx b/include/otbTensorflowSampler.hxx
index 9611d93453b1040aa23602a6d24f7159969902eb..8c0ea7459ad5e1ac0060438e3c6a73b760fc535a 100644
--- a/include/otbTensorflowSampler.hxx
+++ b/include/otbTensorflowSampler.hxx
@@ -1,7 +1,7 @@
/*=========================================================================
- Copyright (c) 2018-2019 Remi Cresson (IRSTEA)
- Copyright (c) 2020-2021 Remi Cresson (INRAE)
+ Copyright (c) 2018-2019 IRSTEA
+ Copyright (c) 2020-2021 INRAE
This software is distributed WITHOUT ANY WARRANTY; without even
@@ -154,7 +154,7 @@ TensorflowSampler<TInputImage, TVectorData>
m_OutputPatchImages.push_back(newImage);
}
- itk::ProgressReporter progess(this, 0, nTotal);
+ itk::ProgressReporter progress(this, 0, nTotal);
// Iterate on the vector data
itVector.GoToBegin();
@@ -218,8 +218,8 @@ TensorflowSampler<TInputImage, TVectorData>
rejected++;
}
- // Update progres
- progess.CompletedPixel();
+ // Update progress
+ progress.CompletedPixel();
}
diff --git a/include/otbTensorflowSamplingUtils.cxx b/include/otbTensorflowSamplingUtils.cxx
index 5a8b8e3c03225c855479adc07f371b730cec787e..5cf88f6b171b61c9576b4ca68d855a0d6059d42f 100644
--- a/include/otbTensorflowSamplingUtils.cxx
+++ b/include/otbTensorflowSamplingUtils.cxx
@@ -1,7 +1,7 @@
/*=========================================================================
- Copyright (c) 2018-2019 Remi Cresson (IRSTEA)
- Copyright (c) 2020-2021 Remi Cresson (INRAE)
+ Copyright (c) 2018-2019 IRSTEA
+ Copyright (c) 2020-2021 INRAE
This software is distributed WITHOUT ANY WARRANTY; without even
diff --git a/include/otbTensorflowSamplingUtils.h b/include/otbTensorflowSamplingUtils.h
index 93879301cf5341a2d479e8752d6af3c4d9ed6ee5..585f90132ea71509fe2a08ff8f56aa1eac2abb3f 100644
--- a/include/otbTensorflowSamplingUtils.h
+++ b/include/otbTensorflowSamplingUtils.h
@@ -1,7 +1,7 @@
/*=========================================================================
- Copyright (c) 2018-2019 Remi Cresson (IRSTEA)
- Copyright (c) 2020-2021 Remi Cresson (INRAE)
+ Copyright (c) 2018-2019 IRSTEA
+ Copyright (c) 2020-2021 INRAE
This software is distributed WITHOUT ANY WARRANTY; without even
@@ -27,23 +27,17 @@ public:
typedef typename TImage::PixelType ValueType;
typedef vnl_vector<float> CountsType;
- Distribution(unsigned int nClasses){
- m_NbOfClasses = nClasses;
- m_Dist = CountsType(nClasses, 0);
-
+ explicit Distribution(unsigned int nClasses): m_NbOfClasses(nClasses), m_Dist(CountsType(nClasses, 0))
+ {
}
- Distribution(unsigned int nClasses, float fillValue){
- m_NbOfClasses = nClasses;
- m_Dist = CountsType(nClasses, fillValue);
-
+ Distribution(unsigned int nClasses, float fillValue): m_NbOfClasses(nClasses), m_Dist(CountsType(nClasses, fillValue))
+ {
}
- Distribution(){
- m_NbOfClasses = 2;
- m_Dist = CountsType(m_NbOfClasses, 0);
+ Distribution(): m_NbOfClasses(2), m_Dist(CountsType(m_NbOfClasses, 0))
+ {
}
- Distribution(const Distribution & other){
- m_Dist = other.Get();
- m_NbOfClasses = m_Dist.size();
+ Distribution(const Distribution & other): m_Dist(other.Get()), m_NbOfClasses(m_Dist.size())
+ {
}
~Distribution(){}
diff --git a/include/otbTensorflowSource.h b/include/otbTensorflowSource.h
index f569c720f2143c81d7608072cd51f6eac746076d..1556997f9a20c02c1f5f9fd80f92c0fc38270657 100644
--- a/include/otbTensorflowSource.h
+++ b/include/otbTensorflowSource.h
@@ -1,7 +1,7 @@
/*=========================================================================
- Copyright (c) 2018-2019 Remi Cresson (IRSTEA)
- Copyright (c) 2020-2021 Remi Cresson (INRAE)
+ Copyright (c) 2018-2019 IRSTEA
+ Copyright (c) 2020-2021 INRAE
This software is distributed WITHOUT ANY WARRANTY; without even
@@ -25,9 +25,9 @@ namespace otb
{
/*
- * This is a simple helper to create images concatenation.
+ * This is a helper for images concatenation.
* Images must have the same size.
- * This is basically the common input type used in every OTB-TF applications.
+ * This is the common input type used in every OTB-TF applications.
*/
template<class TImage>
class TensorflowSource
@@ -60,7 +60,7 @@ public:
// Get the source output
FloatVectorImagePointerType Get();
- TensorflowSource(){};
+ TensorflowSource();
virtual ~TensorflowSource (){};
private:
diff --git a/include/otbTensorflowSource.hxx b/include/otbTensorflowSource.hxx
index bb3de775aa889b3fd0ffaa7324dc2f03ba5159e8..2ad575866fda4ba7baa9dc494c44bcc38b79f0cd 100644
--- a/include/otbTensorflowSource.hxx
+++ b/include/otbTensorflowSource.hxx
@@ -1,7 +1,7 @@
/*=========================================================================
- Copyright (c) 2018-2019 Remi Cresson (IRSTEA)
- Copyright (c) 2020-2021 Remi Cresson (INRAE)
+ Copyright (c) 2018-2019 IRSTEA
+ Copyright (c) 2020-2021 INRAE
This software is distributed WITHOUT ANY WARRANTY; without even
@@ -17,12 +17,21 @@
namespace otb
{
+//
+// Constructor
+//
+template <class TImage>
+TensorflowSource<TImage>
+::TensorflowSource()
+{}
+
//
// Prepare the big stack of images
//
template <class TImage>
void
-TensorflowSource<TImage>::Set(FloatVectorImageListType * inputList)
+TensorflowSource<TImage>
+::Set(FloatVectorImageListType * inputList)
{
// Create one stack for input images list
m_Concatener = ListConcatenerFilterType::New();
diff --git a/include/otbTensorflowStreamerFilter.h b/include/otbTensorflowStreamerFilter.h
index eee73f875f47c7190fde3e3367b0af0381b51ddb..4730d3691cd3bd64954091c3bfdbb5bb7422d870 100644
--- a/include/otbTensorflowStreamerFilter.h
+++ b/include/otbTensorflowStreamerFilter.h
@@ -1,7 +1,7 @@
/*=========================================================================
- Copyright (c) 2018-2019 Remi Cresson (IRSTEA)
- Copyright (c) 2020-2021 Remi Cresson (INRAE)
+ Copyright (c) 2018-2019 IRSTEA
+ Copyright (c) 2020-2021 INRAE
This software is distributed WITHOUT ANY WARRANTY; without even
diff --git a/include/otbTensorflowStreamerFilter.hxx b/include/otbTensorflowStreamerFilter.hxx
index 5e5622be542b4849f016e8d2e8494974c75fd6da..59904a54f3df99048dfa383e22dad0ee7bef9784 100644
--- a/include/otbTensorflowStreamerFilter.hxx
+++ b/include/otbTensorflowStreamerFilter.hxx
@@ -1,7 +1,7 @@
/*=========================================================================
- Copyright (c) 2018-2019 Remi Cresson (IRSTEA)
- Copyright (c) 2020-2021 Remi Cresson (INRAE)
+ Copyright (c) 2018-2019 IRSTEA
+ Copyright (c) 2020-2021 INRAE
This software is distributed WITHOUT ANY WARRANTY; without even
diff --git a/python/ckpt2savedmodel.py b/python/ckpt2savedmodel.py
index cbb72bb941f4fbe4c06af9e3baa5883ca3646887..117203bafd89bcbfaa272952323434dac4046a8b 100755
--- a/python/ckpt2savedmodel.py
+++ b/python/ckpt2savedmodel.py
@@ -2,8 +2,8 @@
# -*- coding: utf-8 -*-
# ==========================================================================
#
-# Copyright 2018-2019 Remi Cresson (IRSTEA)
-# Copyright 2020 Remi Cresson (INRAE)
+# Copyright 2018-2019 IRSTEA
+# Copyright 2020-2021 INRAE
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
@@ -18,23 +18,37 @@
# limitations under the License.
#
# ==========================================================================*/
+"""
+This application converts a checkpoint into a SavedModel, that can be used in
+TensorflowModelTrain or TensorflowModelServe OTB applications.
+This is intended to work mostly with tf.v1 models, since the models in tf.v2
+can be more conveniently exported as SavedModel (see how to build a model with
+keras in Tensorflow 2).
+"""
import argparse
from tricks import ckpt_to_savedmodel
-# Parser
-parser = argparse.ArgumentParser()
-parser.add_argument("--ckpt", help="Checkpoint file (without the \".meta\" extension)", required=True)
-parser.add_argument("--inputs", help="Inputs names (e.g. [\"x_cnn_1:0\", \"x_cnn_2:0\"])", required=True, nargs='+')
-parser.add_argument("--outputs", help="Outputs names (e.g. [\"prediction:0\", \"features:0\"])", required=True,
- nargs='+')
-parser.add_argument("--model", help="Output directory for SavedModel", required=True)
-parser.add_argument('--clear_devices', dest='clear_devices', action='store_true')
-parser.set_defaults(clear_devices=False)
-params = parser.parse_args()
-if __name__ == "__main__":
+def main():
+ """
+ Main function
+ """
+ parser = argparse.ArgumentParser()
+ parser.add_argument("--ckpt", help="Checkpoint file (without the \".meta\" extension)", required=True)
+ parser.add_argument("--inputs", help="Inputs names (e.g. [\"x_cnn_1:0\", \"x_cnn_2:0\"])", required=True, nargs='+')
+ parser.add_argument("--outputs", help="Outputs names (e.g. [\"prediction:0\", \"features:0\"])", required=True,
+ nargs='+')
+ parser.add_argument("--model", help="Output directory for SavedModel", required=True)
+ parser.add_argument('--clear_devices', dest='clear_devices', action='store_true')
+ parser.set_defaults(clear_devices=False)
+ params = parser.parse_args()
+
ckpt_to_savedmodel(ckpt_path=params.ckpt,
inputs=params.inputs,
outputs=params.outputs,
savedmodel_path=params.model,
clear_devices=params.clear_devices)
+
+
+if __name__ == "__main__":
+ main()
diff --git a/python/create_savedmodel_ienco-m3_patchbased.py b/python/examples/tensorflow_v1x/create_savedmodel_ienco-m3_patchbased.py
similarity index 99%
rename from python/create_savedmodel_ienco-m3_patchbased.py
rename to python/examples/tensorflow_v1x/create_savedmodel_ienco-m3_patchbased.py
index fdb772278bb0ffd9db4844be70a8eae7ef6ff8c6..2a3ad56f2e8ad0aea07ae34766944e43e580d6b0 100755
--- a/python/create_savedmodel_ienco-m3_patchbased.py
+++ b/python/examples/tensorflow_v1x/create_savedmodel_ienco-m3_patchbased.py
@@ -1,6 +1,6 @@
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
-# ==========================================================================
+# =========================================================================
#
# Copyright 2018-2019 Remi Cresson, Dino Ienco (IRSTEA)
# Copyright 2020-2021 Remi Cresson, Dino Ienco (INRAE)
@@ -17,7 +17,7 @@
# See the License for the specific language governing permissions and
# limitations under the License.
#
-# ==========================================================================*/
+# =========================================================================
# Reference:
#
@@ -26,12 +26,12 @@
# Satellite Data Fusion. IEEE Journal of Selected Topics in Applied Earth
# Observations and Remote Sensing, 11(12), 4939-4949.
+import argparse
from tricks import create_savedmodel
import tensorflow.compat.v1 as tf
import tensorflow.compat.v1.nn.rnn_cell as rnn
-tf.disable_v2_behavior()
-import argparse
+tf.disable_v2_behavior()
parser = argparse.ArgumentParser()
parser.add_argument("--nunits", type=int, default=1024, help="number of units")
@@ -63,7 +63,7 @@ def RnnAttention(x, nunits, nlayer, n_dims, n_timetamps, is_training_ph):
cell = rnn.GRUCell(nunits)
cells.append(cell)
cell = tf.compat.v1.contrib.rnn.MultiRNNCell(cells)
- # SIGNLE LAYER: single GRUCell, nunits hidden units each
+ # SINGLE LAYER: single GRUCell, nunits hidden units each
else:
cell = rnn.GRUCell(nunits)
outputs, _ = tf.compat.v1.nn.static_rnn(cell, x, dtype="float32")
diff --git a/python/create_savedmodel_maggiori17_fullyconv.py b/python/examples/tensorflow_v1x/create_savedmodel_maggiori17_fullyconv.py
similarity index 95%
rename from python/create_savedmodel_maggiori17_fullyconv.py
rename to python/examples/tensorflow_v1x/create_savedmodel_maggiori17_fullyconv.py
index 32843e764c22249c36a8089af132e453e42114e9..7c2bed5c40c537a55d2f39e904faa6f3c66e506f 100755
--- a/python/create_savedmodel_maggiori17_fullyconv.py
+++ b/python/examples/tensorflow_v1x/create_savedmodel_maggiori17_fullyconv.py
@@ -1,6 +1,6 @@
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
-#==========================================================================
+# =========================================================================
#
# Copyright 2018-2019 Remi Cresson (IRSTEA)
# Copyright 2020-2021 Remi Cresson (INRAE)
@@ -17,7 +17,7 @@
# See the License for the specific language governing permissions and
# limitations under the License.
#
-#==========================================================================*/
+# =========================================================================
# Reference:
#
@@ -79,7 +79,7 @@ with tf.compat.v1.Graph().as_default():
activation=tf.nn.crelu)
# Deconv = conv on the padded/strided input, that is an (5+1)*4
- deconv1 = tf.compat.v1.layers.conv2d_transpose(inputs=conv4, filters=1, strides=(4,4), kernel_size=[8, 8],
+ deconv1 = tf.compat.v1.layers.conv2d_transpose(inputs=conv4, filters=1, strides=(4, 4), kernel_size=[8, 8],
padding="valid", activation=tf.nn.sigmoid)
n = tf.shape(deconv1)[0]
diff --git a/python/create_savedmodel_pxs_fcn.py b/python/examples/tensorflow_v1x/create_savedmodel_pxs_fcn.py
similarity index 100%
rename from python/create_savedmodel_pxs_fcn.py
rename to python/examples/tensorflow_v1x/create_savedmodel_pxs_fcn.py
diff --git a/python/create_savedmodel_simple_cnn.py b/python/examples/tensorflow_v1x/create_savedmodel_simple_cnn.py
similarity index 100%
rename from python/create_savedmodel_simple_cnn.py
rename to python/examples/tensorflow_v1x/create_savedmodel_simple_cnn.py
diff --git a/python/create_savedmodel_simple_fcn.py b/python/examples/tensorflow_v1x/create_savedmodel_simple_fcn.py
similarity index 100%
rename from python/create_savedmodel_simple_fcn.py
rename to python/examples/tensorflow_v1x/create_savedmodel_simple_fcn.py
diff --git a/python/otbtf.py b/python/otbtf.py
index 6a5e35d97f97efb298114004c9cc269101c24a41..a23d5237b701b9ca245fa9b850162ca2ec52e064 100644
--- a/python/otbtf.py
+++ b/python/otbtf.py
@@ -1,8 +1,8 @@
# -*- coding: utf-8 -*-
# ==========================================================================
#
-# Copyright 2018-2019 Remi Cresson (IRSTEA)
-# Copyright 2020 Remi Cresson (INRAE)
+# Copyright 2018-2019 IRSTEA
+# Copyright 2020-2021 INRAE
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
@@ -17,57 +17,57 @@
# limitations under the License.
#
# ==========================================================================*/
+"""
+Contains stuff to help working with TensorFlow and geospatial data in the
+OTBTF framework.
+"""
import threading
import multiprocessing
import time
+import logging
+from abc import ABC, abstractmethod
import numpy as np
import tensorflow as tf
import gdal
-import logging
-from abc import ABC, abstractmethod
-"""
-------------------------------------------------------- Helpers --------------------------------------------------------
-"""
+# ----------------------------------------------------- Helpers --------------------------------------------------------
def gdal_open(filename):
"""
Open a GDAL raster
:param filename: raster file
- :return: a GDAL ds instance
+ :return: a GDAL dataset instance
"""
- ds = gdal.Open(filename)
- if ds is None:
+ gdal_ds = gdal.Open(filename)
+ if gdal_ds is None:
raise Exception("Unable to open file {}".format(filename))
- return ds
+ return gdal_ds
-def read_as_np_arr(ds, as_patches=True):
+def read_as_np_arr(gdal_ds, as_patches=True):
"""
Read a GDAL raster as numpy array
- :param ds: GDAL ds instance
+ :param gdal_ds: a GDAL dataset instance
:param as_patches: if True, the returned numpy array has the following shape (n, psz_x, psz_x, nb_channels). If
False, the shape is (1, psz_y, psz_x, nb_channels)
:return: Numpy array of dim 4
"""
- buffer = ds.ReadAsArray()
- szx = ds.RasterXSize
+ buffer = gdal_ds.ReadAsArray()
+ size_x = gdal_ds.RasterXSize
if len(buffer.shape) == 3:
buffer = np.transpose(buffer, axes=(1, 2, 0))
if not as_patches:
- n = 1
- szy = ds.RasterYSize
+ n_elems = 1
+ size_y = gdal_ds.RasterYSize
else:
- n = int(ds.RasterYSize / szx)
- szy = szx
- return np.float32(buffer.reshape((n, szy, szx, ds.RasterCount)))
+ n_elems = int(gdal_ds.RasterYSize / size_x)
+ size_y = size_x
+ return np.float32(buffer.reshape((n_elems, size_y, size_x, gdal_ds.RasterCount)))
-"""
----------------------------------------------------- Buffer class ------------------------------------------------------
-"""
+# -------------------------------------------------- Buffer class ------------------------------------------------------
class Buffer:
@@ -80,19 +80,27 @@ class Buffer:
self.container = []
def size(self):
+ """
+ Returns the buffer size
+ """
return len(self.container)
- def add(self, x):
- self.container.append(x)
- assert (self.size() <= self.max_length)
+ def add(self, new_element):
+ """
+ Add an element in the buffer
+ :param new_element: new element to add
+ """
+ self.container.append(new_element)
+ assert self.size() <= self.max_length
def is_complete(self):
+ """
+ Return True if the buffer is at full capacity
+ """
return self.size() == self.max_length
-"""
------------------------------------------------- PatchesReaderBase class -----------------------------------------------
-"""
+# ---------------------------------------------- PatchesReaderBase class -----------------------------------------------
class PatchesReaderBase(ABC):
@@ -106,7 +114,6 @@ class PatchesReaderBase(ABC):
Return one sample.
:return One sample instance, whatever the sample structure is (dict, numpy array, ...)
"""
- pass
@abstractmethod
def get_stats(self) -> dict:
@@ -129,7 +136,6 @@ class PatchesReaderBase(ABC):
"std": np.array([...])},
}
"""
- pass
@abstractmethod
def get_size(self):
@@ -137,12 +143,9 @@ class PatchesReaderBase(ABC):
Returns the total number of samples
:return: number of samples (int)
"""
- pass
-"""
------------------------------------------------ PatchesImagesReader class ----------------------------------------------
-"""
+# --------------------------------------------- PatchesImagesReader class ----------------------------------------------
class PatchesImagesReader(PatchesReaderBase):
@@ -174,66 +177,64 @@ class PatchesImagesReader(PatchesReaderBase):
:param use_streaming: if True, the patches are read on the fly from the disc, nothing is kept in memory.
"""
- assert (len(filenames_dict.values()) > 0)
+ assert len(filenames_dict.values()) > 0
- # ds dict
- self.ds = dict()
- for src_key, src_filenames in filenames_dict.items():
- self.ds[src_key] = []
- for src_filename in src_filenames:
- self.ds[src_key].append(gdal_open(src_filename))
+ # gdal_ds dict
+ self.gdal_ds = {key: [gdal_open(src_fn) for src_fn in src_fns] for key, src_fns in filenames_dict.items()}
- if len(set([len(ds_list) for ds_list in self.ds.values()])) != 1:
+ # check number of patches in each sources
+ if len({len(ds_list) for ds_list in self.gdal_ds.values()}) != 1:
raise Exception("Each source must have the same number of patches images")
# streaming on/off
self.use_streaming = use_streaming
- # ds check
- nb_of_patches = {key: 0 for key in self.ds}
+ # gdal_ds check
+ nb_of_patches = {key: 0 for key in self.gdal_ds}
self.nb_of_channels = dict()
- for src_key, ds_list in self.ds.items():
- for ds in ds_list:
- nb_of_patches[src_key] += self._get_nb_of_patches(ds)
+ for src_key, ds_list in self.gdal_ds.items():
+ for gdal_ds in ds_list:
+ nb_of_patches[src_key] += self._get_nb_of_patches(gdal_ds)
if src_key not in self.nb_of_channels:
- self.nb_of_channels[src_key] = ds.RasterCount
+ self.nb_of_channels[src_key] = gdal_ds.RasterCount
else:
- if self.nb_of_channels[src_key] != ds.RasterCount:
+ if self.nb_of_channels[src_key] != gdal_ds.RasterCount:
raise Exception("All patches images from one source must have the same number of channels!"
"Error happened for source: {}".format(src_key))
if len(set(nb_of_patches.values())) != 1:
raise Exception("Sources must have the same number of patches! Number of patches: {}".format(nb_of_patches))
- # ds sizes
- src_key_0 = list(self.ds)[0] # first key
- self.ds_sizes = [self._get_nb_of_patches(ds) for ds in self.ds[src_key_0]]
+ # gdal_ds sizes
+ src_key_0 = list(self.gdal_ds)[0] # first key
+ self.ds_sizes = [self._get_nb_of_patches(ds) for ds in self.gdal_ds[src_key_0]]
self.size = sum(self.ds_sizes)
# if use_streaming is False, we store in memory all patches images
if not self.use_streaming:
- patches_list = {src_key: [read_as_np_arr(ds) for ds in self.ds[src_key]] for src_key in self.ds}
- self.patches_buffer = {src_key: np.concatenate(patches_list[src_key], axis=0) for src_key in self.ds}
+ patches_list = {src_key: [read_as_np_arr(ds) for ds in self.gdal_ds[src_key]] for src_key in self.gdal_ds}
+ self.patches_buffer = {src_key: np.concatenate(patches_list[src_key], axis=0) for src_key in self.gdal_ds}
def _get_ds_and_offset_from_index(self, index):
offset = index
- for i, ds_size in enumerate(self.ds_sizes):
+ idx = None
+ for idx, ds_size in enumerate(self.ds_sizes):
if offset < ds_size:
break
offset -= ds_size
- return i, offset
+ return idx, offset
@staticmethod
- def _get_nb_of_patches(ds):
- return int(ds.RasterYSize / ds.RasterXSize)
+ def _get_nb_of_patches(gdal_ds):
+ return int(gdal_ds.RasterYSize / gdal_ds.RasterXSize)
@staticmethod
- def _read_extract_as_np_arr(ds, offset):
- assert (ds is not None)
- psz = ds.RasterXSize
+ def _read_extract_as_np_arr(gdal_ds, offset):
+ assert gdal_ds is not None
+ psz = gdal_ds.RasterXSize
yoff = int(offset * psz)
- assert (yoff + psz <= ds.RasterYSize)
- buffer = ds.ReadAsArray(0, yoff, psz, psz)
+ assert yoff + psz <= gdal_ds.RasterYSize
+ buffer = gdal_ds.ReadAsArray(0, yoff, psz, psz)
if len(buffer.shape) == 3:
buffer = np.transpose(buffer, axes=(1, 2, 0))
return np.float32(buffer)
@@ -248,14 +249,14 @@ class PatchesImagesReader(PatchesReaderBase):
...
"src_key_M": np.array((psz_y_M, psz_x_M, nb_ch_M))}
"""
- assert (0 <= index)
- assert (index < self.size)
+ assert index >= 0
+ assert index < self.size
if not self.use_streaming:
- res = {src_key: self.patches_buffer[src_key][index, :, :, :] for src_key in self.ds}
+ res = {src_key: self.patches_buffer[src_key][index, :, :, :] for src_key in self.gdal_ds}
else:
i, offset = self._get_ds_and_offset_from_index(index)
- res = {src_key: self._read_extract_as_np_arr(self.ds[src_key][i], offset) for src_key in self.ds}
+ res = {src_key: self._read_extract_as_np_arr(self.gdal_ds[src_key][i], offset) for src_key in self.gdal_ds}
return res
@@ -278,7 +279,7 @@ class PatchesImagesReader(PatchesReaderBase):
axis = (0, 1) # (row, col)
def _filled(value):
- return {src_key: value * np.ones((self.nb_of_channels[src_key])) for src_key in self.ds}
+ return {src_key: value * np.ones((self.nb_of_channels[src_key])) for src_key in self.gdal_ds}
_maxs = _filled(0.0)
_mins = _filled(float("inf"))
@@ -298,17 +299,15 @@ class PatchesImagesReader(PatchesReaderBase):
"max": _maxs[src_key],
"mean": rsize * _sums[src_key],
"std": np.sqrt(rsize * _sqsums[src_key] - np.square(rsize * _sums[src_key]))
- } for src_key in self.ds}
- logging.info("Stats: {}".format(stats))
+ } for src_key in self.gdal_ds}
+ logging.info("Stats: {}", stats)
return stats
def get_size(self):
return self.size
-"""
-------------------------------------------------- IteratorBase class ---------------------------------------------------
-"""
+# ----------------------------------------------- IteratorBase class ---------------------------------------------------
class IteratorBase(ABC):
@@ -320,9 +319,7 @@ class IteratorBase(ABC):
pass
-"""
------------------------------------------------- RandomIterator class --------------------------------------------------
-"""
+# ---------------------------------------------- RandomIterator class --------------------------------------------------
class RandomIterator(IteratorBase):
@@ -352,9 +349,7 @@ class RandomIterator(IteratorBase):
np.random.shuffle(self.indices)
-"""
---------------------------------------------------- Dataset class ------------------------------------------------------
-"""
+# ------------------------------------------------- Dataset class ------------------------------------------------------
class Dataset:
@@ -389,10 +384,12 @@ class Dataset:
self.output_shapes[src_key] = np_arr.shape
self.output_types[src_key] = tf.dtypes.as_dtype(np_arr.dtype)
- logging.info("output_types: {}".format(self.output_types))
- logging.info("output_shapes: {}".format(self.output_shapes))
+ logging.info("output_types: {}", self.output_types)
+ logging.info("output_shapes: {}", self.output_shapes)
# buffers
+ if self.size <= buffer_length:
+ buffer_length = self.size
self.miner_buffer = Buffer(buffer_length)
self.mining_lock = multiprocessing.Lock()
self.consumer_buffer = Buffer(buffer_length)
@@ -434,12 +431,12 @@ class Dataset:
This function dumps the miner_buffer into the consumer_buffer, and restart the miner_thread
"""
# Wait for miner to finish his job
- t = time.time()
+ date_t = time.time()
self.miner_thread.join()
- self.tot_wait += time.time() - t
+ self.tot_wait += time.time() - date_t
# Copy miner_buffer.container --> consumer_buffer.container
- self.consumer_buffer.container = [elem for elem in self.miner_buffer.container]
+ self.consumer_buffer.container = self.miner_buffer.container.copy()
# Clear miner_buffer.container
self.miner_buffer.container.clear()
@@ -454,27 +451,24 @@ class Dataset:
"""
# Fill the miner_container until it's full
while not self.miner_buffer.is_complete():
- try:
- index = next(self.iterator)
- with self.mining_lock:
- new_sample = self.patches_reader.get_sample(index=index)
- self.miner_buffer.add(new_sample)
- except Exception as e:
- logging.warning("Error during collecting samples: {}".format(e))
+ index = next(self.iterator)
+ with self.mining_lock:
+ new_sample = self.patches_reader.get_sample(index=index)
+ self.miner_buffer.add(new_sample)
def _summon_miner_thread(self):
"""
Create and starts the thread for the data collect
"""
- t = threading.Thread(target=self._collect)
- t.start()
- return t
+ new_thread = threading.Thread(target=self._collect)
+ new_thread.start()
+ return new_thread
def _generator(self):
"""
Generator function, used for the tf dataset
"""
- for elem in range(self.size):
+ for _ in range(self.size):
yield self.read_one_sample()
def get_tf_dataset(self, batch_size, drop_remainder=True):
@@ -486,7 +480,7 @@ class Dataset:
"""
if batch_size <= 2 * self.miner_buffer.max_length:
logging.warning("Batch size is {} but dataset buffer has {} elements. Consider using a larger dataset "
- "buffer to avoid I/O bottleneck".format(batch_size, self.miner_buffer.max_length))
+ "buffer to avoid I/O bottleneck", batch_size, self.miner_buffer.max_length)
return self.tf_dataset.batch(batch_size, drop_remainder=drop_remainder)
def get_total_wait_in_seconds(self):
@@ -497,9 +491,7 @@ class Dataset:
return self.tot_wait
-"""
-------------------------------------------- DatasetFromPatchesImages class ---------------------------------------------
-"""
+# ----------------------------------------- DatasetFromPatchesImages class ---------------------------------------------
class DatasetFromPatchesImages(Dataset):
diff --git a/python/tricks.py b/python/tricks.py
index fe4c5deaedb4095275f7161143a23ad968b10392..b31b14c39ddd89498983ea457c16b15f2c5409df 100644
--- a/python/tricks.py
+++ b/python/tricks.py
@@ -1,8 +1,8 @@
# -*- coding: utf-8 -*-
# ==========================================================================
#
-# Copyright 2018-2019 Remi Cresson (IRSTEA)
-# Copyright 2020 Remi Cresson (INRAE)
+# Copyright 2018-2019 IRSTEA
+# Copyright 2020-2021 INRAE
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
@@ -17,54 +17,42 @@
# limitations under the License.
#
# ==========================================================================*/
-import gdal
-import numpy as np
+"""
+This module contains a set of python functions to interact with geospatial data
+and TensorFlow models.
+Starting from OTBTF >= 3.0.0, tricks is only used as a backward compatible stub
+for TF 1.X versions.
+"""
import tensorflow.compat.v1 as tf
from deprecated import deprecated
-
+from otbtf import gdal_open, read_as_np_arr as read_as_np_arr_from_gdal_ds
tf.disable_v2_behavior()
+@deprecated(version="3.0.0", reason="Please use otbtf.read_image_as_np() instead")
def read_image_as_np(filename, as_patches=False):
"""
- Read an image as numpy array.
- @param filename File name of patches image
- @param as_patches True if the image must be read as patches
- @return 4D numpy array [batch, h, w, c]
+ Read a patches-image as numpy array.
+ :param filename: File name of the patches-image
+ :param as_patches: True if the image must be read as patches
+ :return 4D numpy array [batch, h, w, c] (batch = 1 when as_patches is False)
"""
# Open a GDAL dataset
- ds = gdal.Open(filename)
- if ds is None:
- raise Exception("Unable to open file {}".format(filename))
-
- # Raster infos
- n_bands = ds.RasterCount
- szx = ds.RasterXSize
- szy = ds.RasterYSize
-
- # Raster array
- myarray = ds.ReadAsArray()
-
- # Re-order bands (when there is > 1 band)
- if (len(myarray.shape) == 3):
- axes = (1, 2, 0)
- myarray = np.transpose(myarray, axes=axes)
+ gdal_ds = gdal_open(filename)
- if (as_patches):
- n = int(szy / szx)
- return myarray.reshape((n, szx, szx, n_bands))
-
- return myarray.reshape((1, szy, szx, n_bands))
+ # Return patches
+ return read_as_np_arr_from_gdal_ds(gdal_ds=gdal_ds, as_patches=as_patches)
+@deprecated(version="3.0.0", reason="Please consider using TensorFlow >= 2 to build your nets")
def create_savedmodel(sess, inputs, outputs, directory):
"""
- Create a SavedModel
- @param sess TF session
- @param inputs List of inputs names (e.g. ["x_cnn_1:0", "x_cnn_2:0"])
- @param outputs List of outputs names (e.g. ["prediction:0", "features:0"])
- @param directory Path for the generated SavedModel
+ Create a SavedModel from TF 1.X graphs
+ :param sess: The Tensorflow V1 session
+ :param inputs: List of inputs names (e.g. ["x_cnn_1:0", "x_cnn_2:0"])
+ :param outputs: List of outputs names (e.g. ["prediction:0", "features:0"])
+ :param directory: Path for the generated SavedModel
"""
print("Create a SavedModel in " + directory)
graph = tf.compat.v1.get_default_graph()
@@ -72,14 +60,16 @@ def create_savedmodel(sess, inputs, outputs, directory):
outputs_names = {o: graph.get_tensor_by_name(o) for o in outputs}
tf.compat.v1.saved_model.simple_save(sess, directory, inputs=inputs_names, outputs=outputs_names)
+
+@deprecated(version="3.0.0", reason="Please consider using TensorFlow >= 2 to build and save your nets")
def ckpt_to_savedmodel(ckpt_path, inputs, outputs, savedmodel_path, clear_devices=False):
"""
- Read a Checkpoint and build a SavedModel
- @param ckpt_path Path to the checkpoint file (without the ".meta" extension)
- @param inputs List of inputs names (e.g. ["x_cnn_1:0", "x_cnn_2:0"])
- @param outputs List of outputs names (e.g. ["prediction:0", "features:0"])
- @param savedmodel_path Path for the generated SavedModel
- @param clear_devices Clear TF devices positionning (True/False)
+ Read a Checkpoint and build a SavedModel for some TF 1.X graph
+ :param ckpt_path: Path to the checkpoint file (without the ".meta" extension)
+ :param inputs: List of inputs names (e.g. ["x_cnn_1:0", "x_cnn_2:0"])
+ :param outputs: List of outputs names (e.g. ["prediction:0", "features:0"])
+ :param savedmodel_path: Path for the generated SavedModel
+ :param clear_devices: Clear TensorFlow devices positioning (True/False)
"""
tf.compat.v1.reset_default_graph()
with tf.compat.v1.Session() as sess:
@@ -90,33 +80,17 @@ def ckpt_to_savedmodel(ckpt_path, inputs, outputs, savedmodel_path, clear_device
# Create a SavedModel
create_savedmodel(sess, inputs=inputs, outputs=outputs, directory=savedmodel_path)
-@deprecated
+
+@deprecated(version="3.0.0", reason="Please use otbtf.read_image_as_np() instead")
def read_samples(filename):
- """
+ """
Read a patches image.
@param filename: raster file name
"""
- return read_image_as_np(filename, as_patches=True)
+ return read_image_as_np(filename, as_patches=True)
-@deprecated
-def CreateSavedModel(sess, inputs, outputs, directory):
- """
- Create a SavedModel
- @param sess TF session
- @param inputs List of inputs names (e.g. ["x_cnn_1:0", "x_cnn_2:0"])
- @param outputs List of outputs names (e.g. ["prediction:0", "features:0"])
- @param directory Path for the generated SavedModel
- """
- create_savedmodel(sess, inputs, outputs, directory)
-@deprecated
-def CheckpointToSavedModel(ckpt_path, inputs, outputs, savedmodel_path, clear_devices=False):
- """
- Read a Checkpoint and build a SavedModel
- @param ckpt_path Path to the checkpoint file (without the ".meta" extension)
- @param inputs List of inputs names (e.g. ["x_cnn_1:0", "x_cnn_2:0"])
- @param outputs List of outputs names (e.g. ["prediction:0", "features:0"])
- @param savedmodel_path Path for the generated SavedModel
- @param clear_devices Clear TF devices positionning (True/False)
- """
- ckpt_to_savedmodel(ckpt_path, inputs, outputs, savedmodel_path, clear_devices)
+# Aliases for backward compatibility
+# pylint: disable=invalid-name
+CreateSavedModel = create_savedmodel
+CheckpointToSavedModel = ckpt_to_savedmodel
diff --git a/test/CMakeLists.txt b/test/CMakeLists.txt
index f2f176f4f7c583810e34408947bee725e07bbe09..a4260dfe9103806d0ca716022da525da0ee06fca 100644
--- a/test/CMakeLists.txt
+++ b/test/CMakeLists.txt
@@ -1,5 +1,24 @@
otb_module_test()
+# Unit tests
+set(${otb-module}Tests
+ otbTensorflowTests.cxx
+ otbTensorflowCopyUtilsTests.cxx)
+
+add_executable(otbTensorflowTests ${${otb-module}Tests})
+
+target_include_directories(otbTensorflowTests PRIVATE ${tensorflow_include_dir})
+target_link_libraries(otbTensorflowTests ${${otb-module}-Test_LIBRARIES} ${TENSORFLOW_CC_LIB} ${TENSORFLOW_FRAMEWORK_LIB})
+otb_module_target_label(otbTensorflowTests)
+
+# CopyUtilsTests
+otb_add_test(NAME floatValueToTensorTest COMMAND otbTensorflowTests floatValueToTensorTest)
+otb_add_test(NAME intValueToTensorTest COMMAND otbTensorflowTests intValueToTensorTest)
+otb_add_test(NAME boolValueToTensorTest COMMAND otbTensorflowTests boolValueToTensorTest)
+otb_add_test(NAME floatVecValueToTensorTest COMMAND otbTensorflowTests floatVecValueToTensorTest)
+otb_add_test(NAME intVecValueToTensorTest COMMAND otbTensorflowTests intVecValueToTensorTest)
+otb_add_test(NAME boolVecValueToTensorTest COMMAND otbTensorflowTests boolVecValueToTensorTest)
+
# Directories
set(DATADIR ${CMAKE_CURRENT_SOURCE_DIR}/data)
set(MODELSDIR ${CMAKE_CURRENT_SOURCE_DIR}/models)
@@ -9,12 +28,19 @@ set(IMAGEXS ${DATADIR}/xs_subset.tif)
set(IMAGEPAN ${DATADIR}/pan_subset.tif)
set(IMAGEPXS ${DATADIR}/pxs_subset.tif)
set(IMAGEPXS2 ${DATADIR}/pxs_subset2.tif)
+set(PATCHESA ${DATADIR}/Sentinel-2_B4328_10m_patches_A.jp2)
+set(PATCHESB ${DATADIR}/Sentinel-2_B4328_10m_patches_B.jp2)
+set(LABELSA ${DATADIR}/Sentinel-2_B4328_10m_labels_A.tif)
+set(LABELSB ${DATADIR}/Sentinel-2_B4328_10m_labels_B.tif)
+set(PATCHES01 ${DATADIR}/Sentinel-2_B4328_10m_patches_A.jp2)
+set(PATCHES11 ${DATADIR}/Sentinel-2_B4328_10m_patches_B.jp2)
# Input models
set(MODEL1 ${MODELSDIR}/model1)
set(MODEL2 ${MODELSDIR}/model2)
set(MODEL3 ${MODELSDIR}/model3)
set(MODEL4 ${MODELSDIR}/model4)
+set(MODEL5 ${MODELSDIR}/model5)
# Output images and baselines
set(MODEL1_PB_OUT apTvClTensorflowModelServeCNN16x16PB.tif)
@@ -23,6 +49,91 @@ set(MODEL2_FC_OUT apTvClTensorflowModelServeCNN8x8_32x32FC.tif)
set(MODEL3_PB_OUT apTvClTensorflowModelServeFCNN16x16PB.tif)
set(MODEL3_FC_OUT apTvClTensorflowModelServeFCNN16x16FC.tif)
set(MODEL4_FC_OUT apTvClTensorflowModelServeFCNN64x64to32x32.tif)
+set(MODEL1_SAVED model1_updated)
+set(PATCHESIMG_01 patchimg_01.tif)
+set(PATCHESIMG_11 patchimg_11.tif)
+set(MODEL5_OUT reduce_sum.tif)
+
+#----------- Patches selection ----------------
+set(PATCHESPOS_01 ${TEMP}/out_train_32.gpkg)
+set(PATCHESPOS_02 ${TEMP}/out_valid_32.gpkg)
+set(PATCHESPOS_11 ${TEMP}/out_train_33.gpkg)
+set(PATCHESPOS_12 ${TEMP}/out_valid_33.gpkg)
+# Even patches
+otb_test_application(NAME PatchesSelectionEven
+ APP PatchesSelection
+ OPTIONS
+ -in ${IMAGEPXS2}
+ -grid.step 32
+ -grid.psize 32
+ -outtrain ${PATCHESPOS_01}
+ -outvalid ${PATCHESPOS_02}
+ )
+
+# Odd patches
+otb_test_application(NAME PatchesSelectionOdd
+ APP PatchesSelection
+ OPTIONS
+ -in ${IMAGEPXS2}
+ -grid.step 32
+ -grid.psize 33
+ -outtrain ${PATCHESPOS_11}
+ -outvalid ${PATCHESPOS_12}
+ )
+
+#----------- Patches extraction ----------------
+# Even patches
+otb_test_application(NAME PatchesExtractionEven
+ APP PatchesExtraction
+ OPTIONS
+ -source1.il ${IMAGEPXS2}
+ -source1.patchsizex 32
+ -source1.patchsizey 32
+ -source1.out ${TEMP}/${PATCHESIMG_01}
+ -vec ${PATCHESPOS_01}
+ -field id
+ VALID --compare-image ${EPSILON_6}
+ ${DATADIR}/${PATCHESIMG_01}
+ ${TEMP}/${PATCHESIMG_01}
+ )
+
+# Odd patches
+otb_test_application(NAME PatchesExtractionOdd
+ APP PatchesExtraction
+ OPTIONS
+ -source1.il ${IMAGEPXS2}
+ -source1.patchsizex 33
+ -source1.patchsizey 33
+ -source1.out ${TEMP}/${PATCHESIMG_11}
+ -vec ${PATCHESPOS_11}
+ -field id
+ VALID --compare-image ${EPSILON_6}
+ ${DATADIR}/${PATCHESIMG_11}
+ ${TEMP}/${PATCHESIMG_11}
+ )
+
+#----------- Model training : 1-branch CNN (16x16) Patch-Based ----------------
+set(ENV{OTB_LOGGER_LEVEL} DEBUG)
+otb_test_application(NAME TensorflowModelTrainCNN16x16PB
+ APP TensorflowModelTrain
+ OPTIONS
+ -training.epochs 10
+ -training.source1.il ${PATCHESA}
+ -training.source1.placeholder "x"
+ -training.source2.il ${LABELSA}
+ -training.source2.placeholder "y"
+ -validation.source1.il ${PATCHESB}
+ -validation.source2.il ${LABELSB}
+ -validation.source1.name "x"
+ -validation.source2.name "prediction"
+ -training.source1.patchsizex 16 -training.source1.patchsizey 16
+ -training.source2.patchsizex 1 -training.source2.patchsizey 1
+ -model.dir ${MODEL1}
+ -model.saveto ${MODEL1_SAVED}
+ -training.targetnodes "optimizer"
+ -validation.mode "class"
+ )
+set_tests_properties(TensorflowModelTrainCNN16x16PB PROPERTIES ENVIRONMENT "OTB_LOGGER_LEVEL=DEBUG;$ENV{OTB_LOGGER_LEVEL}")
#----------- Model serving : 1-branch CNN (16x16) Patch-Based ----------------
otb_test_application(NAME TensorflowModelServeCNN16x16PB
@@ -34,6 +145,7 @@ otb_test_application(NAME TensorflowModelServeCNN16x16PB
VALID --compare-image ${EPSILON_6}
${DATADIR}/${MODEL1_PB_OUT}
${TEMP}/${MODEL1_PB_OUT})
+set_tests_properties(TensorflowModelServeCNN16x16PB PROPERTIES ENVIRONMENT "OTB_LOGGER_LEVEL=DEBUG}")
#----------- Model serving : 2-branch CNN (8x8, 32x32) Patch-Based ----------------
otb_test_application(NAME apTvClTensorflowModelServeCNN8x8_32x32PB
@@ -47,7 +159,8 @@ otb_test_application(NAME apTvClTensorflowModelServeCNN8x8_32x32PB
VALID --compare-image ${EPSILON_6}
${DATADIR}/${MODEL2_PB_OUT}
${TEMP}/${MODEL2_PB_OUT})
-set_tests_properties(apTvClTensorflowModelServeCNN8x8_32x32PB PROPERTIES ENVIRONMENT "OTB_TF_NSOURCES=2;$ENV{OTB_TF_NSOURCES}")
+set_tests_properties(apTvClTensorflowModelServeCNN8x8_32x32PB PROPERTIES ENVIRONMENT "OTB_LOGGER_LEVEL=DEBUG;OTB_TF_NSOURCES=2;$ENV{OTB_TF_NSOURCES}")
+
#----------- Model serving : 2-branch CNN (8x8, 32x32) Fully-Conv ----------------
set(ENV{OTB_TF_NSOURCES} 2)
@@ -62,7 +175,7 @@ otb_test_application(NAME apTvClTensorflowModelServeCNN8x8_32x32FC
VALID --compare-image ${EPSILON_6}
${DATADIR}/${MODEL2_FC_OUT}
${TEMP}/${MODEL2_FC_OUT})
-set_tests_properties(apTvClTensorflowModelServeCNN8x8_32x32FC PROPERTIES ENVIRONMENT "OTB_TF_NSOURCES=2;$ENV{OTB_TF_NSOURCES}")
+set_tests_properties(apTvClTensorflowModelServeCNN8x8_32x32FC PROPERTIES ENVIRONMENT "OTB_LOGGER_LEVEL=DEBUG;OTB_TF_NSOURCES=2;$ENV{OTB_TF_NSOURCES}")
#----------- Model serving : 1-branch FCNN (16x16) Patch-Based ----------------
set(ENV{OTB_TF_NSOURCES} 1)
@@ -75,6 +188,8 @@ otb_test_application(NAME apTvClTensorflowModelServeFCNN16x16PB
VALID --compare-image ${EPSILON_6}
${DATADIR}/${MODEL3_PB_OUT}
${TEMP}/${MODEL3_PB_OUT})
+set_tests_properties(apTvClTensorflowModelServeFCNN16x16PB PROPERTIES ENVIRONMENT "OTB_LOGGER_LEVEL=DEBUG}")
+
#----------- Model serving : 1-branch FCNN (16x16) Fully-conv ----------------
set(ENV{OTB_TF_NSOURCES} 1)
@@ -87,10 +202,11 @@ otb_test_application(NAME apTvClTensorflowModelServeFCNN16x16FC
VALID --compare-image ${EPSILON_6}
${DATADIR}/${MODEL3_FC_OUT}
${TEMP}/${MODEL3_FC_OUT})
+set_tests_properties(apTvClTensorflowModelServeFCNN16x16FC PROPERTIES ENVIRONMENT "OTB_LOGGER_LEVEL=DEBUG}")
#----------- Model serving : 1-branch FCNN (64x64)-->(32x32), Fully-conv ----------------
set(ENV{OTB_TF_NSOURCES} 1)
-otb_test_application(NAME apTvClTensorflowModelServeFCNN64x64to32x32.tif
+otb_test_application(NAME apTvClTensorflowModelServeFCNN64x64to32x32
APP TensorflowModelServe
OPTIONS -source1.il ${IMAGEPXS2}
-source1.rfieldx 64 -source1.rfieldy 64 -source1.placeholder x
@@ -100,5 +216,46 @@ otb_test_application(NAME apTvClTensorflowModelServeFCNN64x64to32x32.tif
VALID --compare-image ${EPSILON_6}
${DATADIR}/${MODEL4_FC_OUT}
${TEMP}/${MODEL4_FC_OUT})
+set_tests_properties(apTvClTensorflowModelServeFCNN64x64to32x32 PROPERTIES ENVIRONMENT "OTB_LOGGER_LEVEL=DEBUG}")
+
+#----------- Test various output tensor shapes ----------------
+# We test the following output shapes on one monochannel image:
+# [None]
+# [None, 1]
+# [None, None, None]
+# [None, None, None, 1]
+set(ENV{OTB_TF_NSOURCES} 1)
+otb_test_application(NAME outputTensorShapesTest1pb
+ APP TensorflowModelServe
+ OPTIONS -source1.il ${IMAGEPAN} -model.dir ${MODEL5} -out ${TEMP}/${MODEL5_OUT} -output.names "tf.reshape"
+ VALID --compare-image ${EPSILON_6} ${IMAGEPAN} ${TEMP}/${MODEL5_OUT})
+otb_test_application(NAME outputTensorShapesTest1fc
+ APP TensorflowModelServe
+ OPTIONS -source1.il ${IMAGEPAN} -model.dir ${MODEL5} -model.fullyconv on -out ${TEMP}/${MODEL5_OUT} -output.names "tf.reshape"
+ VALID --compare-image ${EPSILON_6} ${IMAGEPAN} ${TEMP}/${MODEL5_OUT})
+otb_test_application(NAME outputTensorShapesTest2pb
+ APP TensorflowModelServe
+ OPTIONS -source1.il ${IMAGEPAN} -model.dir ${MODEL5} -out ${TEMP}/${MODEL5_OUT} -output.names "tf.reshape_1"
+ VALID --compare-image ${EPSILON_6} ${IMAGEPAN} ${TEMP}/${MODEL5_OUT})
+otb_test_application(NAME outputTensorShapesTest2fc
+ APP TensorflowModelServe
+ OPTIONS -source1.il ${IMAGEPAN} -model.dir ${MODEL5} -model.fullyconv on -out ${TEMP}/${MODEL5_OUT} -output.names "tf.reshape_1"
+ VALID --compare-image ${EPSILON_6} ${IMAGEPAN} ${TEMP}/${MODEL5_OUT})
+otb_test_application(NAME outputTensorShapesTest3pb
+ APP TensorflowModelServe
+ OPTIONS -source1.il ${IMAGEPAN} -model.dir ${MODEL5} -out ${TEMP}/${MODEL5_OUT} -output.names "tf.reshape_2"
+ VALID --compare-image ${EPSILON_6} ${IMAGEPAN} ${TEMP}/${MODEL5_OUT})
+otb_test_application(NAME outputTensorShapesTest3fc
+ APP TensorflowModelServe
+ OPTIONS -source1.il ${IMAGEPAN} -model.dir ${MODEL5} -model.fullyconv on -out ${TEMP}/${MODEL5_OUT} -output.names "tf.reshape_2"
+ VALID --compare-image ${EPSILON_6} ${IMAGEPAN} ${TEMP}/${MODEL5_OUT})
+otb_test_application(NAME outputTensorShapesTest4pb
+ APP TensorflowModelServe
+ OPTIONS -source1.il ${IMAGEPAN} -model.dir ${MODEL5} -out ${TEMP}/${MODEL5_OUT} -output.names "tf.reshape_3"
+ VALID --compare-image ${EPSILON_6} ${IMAGEPAN} ${TEMP}/${MODEL5_OUT})
+otb_test_application(NAME outputTensorShapesTest4fc
+ APP TensorflowModelServe
+ OPTIONS -source1.il ${IMAGEPAN} -model.dir ${MODEL5} -model.fullyconv on -out ${TEMP}/${MODEL5_OUT} -output.names "tf.reshape_3"
+ VALID --compare-image ${EPSILON_6} ${IMAGEPAN} ${TEMP}/${MODEL5_OUT})
diff --git a/test/data/RF_model_from_deep_features_map.tif b/test/data/RF_model_from_deep_features_map.tif
new file mode 100644
index 0000000000000000000000000000000000000000..8d01ec195605327cb613eed99b3bebc5bb2c5583
--- /dev/null
+++ b/test/data/RF_model_from_deep_features_map.tif
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7c603c85a80e6d59d18fe686a827e77066dbedb76c53fb6c35c7ed291d20cf34
+size 1316
diff --git a/test/data/Sentinel-2_B4328_10m_labels_A.tif b/test/data/Sentinel-2_B4328_10m_labels_A.tif
new file mode 100644
index 0000000000000000000000000000000000000000..63fa4e2e8209aabd881087754c97fc615553e283
--- /dev/null
+++ b/test/data/Sentinel-2_B4328_10m_labels_A.tif
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0501bdcb5d8580ba9202aa2fb5fd057234387a0ffff12fbccc71d9899dd67463
+size 3286
diff --git a/test/data/Sentinel-2_B4328_10m_labels_B.tif b/test/data/Sentinel-2_B4328_10m_labels_B.tif
new file mode 100644
index 0000000000000000000000000000000000000000..0b0edfa08641a1ecb142105db6b80411dbfd838b
--- /dev/null
+++ b/test/data/Sentinel-2_B4328_10m_labels_B.tif
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d430731c2560e40094cf9fe2d8d7c55ead665229f7ffef30b564258c1944beaf
+size 3286
diff --git a/test/data/Sentinel-2_B4328_10m_patches_A.jp2 b/test/data/Sentinel-2_B4328_10m_patches_A.jp2
new file mode 100644
index 0000000000000000000000000000000000000000..fb686f59c9f168e902a7201d03b3859e155f49ec
--- /dev/null
+++ b/test/data/Sentinel-2_B4328_10m_patches_A.jp2
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d14d17d4a90d0d989623a5798056ba0b2074e6f595a408af45a9c35afbfdd84d
+size 756503
diff --git a/test/data/Sentinel-2_B4328_10m_patches_B.jp2 b/test/data/Sentinel-2_B4328_10m_patches_B.jp2
new file mode 100644
index 0000000000000000000000000000000000000000..e34e865f8c0321d77ab95dc3831e6b66da56f65b
--- /dev/null
+++ b/test/data/Sentinel-2_B4328_10m_patches_B.jp2
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:50d7fcfb6de506824143f998cdac3bde1921e1805cb2cc741d8145006722d4e3
+size 758859
diff --git a/test/data/amsterdam_labels_A.tif b/test/data/amsterdam_labels_A.tif
new file mode 100644
index 0000000000000000000000000000000000000000..a7b0dbcf01de410b0e5f8303ede2e5cdefda9db2
--- /dev/null
+++ b/test/data/amsterdam_labels_A.tif
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:bdd9ecd2e54992d712ee44fc05a91bc38f25bfa6c6cbcdc11874fe9070a4fc0f
+size 11411
diff --git a/test/data/amsterdam_labels_B.tif b/test/data/amsterdam_labels_B.tif
new file mode 100644
index 0000000000000000000000000000000000000000..fff31bcfd6b0c4f0d498cf79ce626de9937a6100
--- /dev/null
+++ b/test/data/amsterdam_labels_B.tif
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5ce48d4d57f46ca39d940ead160d7968f9b6c2a62b4f6b49132372d1a8916622
+size 11362
diff --git a/test/data/amsterdam_patches_A.tif b/test/data/amsterdam_patches_A.tif
new file mode 100644
index 0000000000000000000000000000000000000000..41323cf2dd8645e28952fdcd9db7bb8cd2542d8d
--- /dev/null
+++ b/test/data/amsterdam_patches_A.tif
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b8d606712ba9b1493ffd02c08135c5d1072d2bc1e64228d00425f17cc62280c9
+size 3840365
diff --git a/test/data/amsterdam_patches_B.tif b/test/data/amsterdam_patches_B.tif
new file mode 100644
index 0000000000000000000000000000000000000000..ace9beebf09fd5066ded88bdbf3fec05f752456e
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+"""
+This test checks that the output tensor shapes are supported.
+The input of this model must be a mono channel image.
+All 4 different output shapes supported in OTBTF are tested.
+
+"""
+import tensorflow as tf
+
+# Input
+x = tf.keras.Input(shape=[None, None, None], name="x") # [b, h, w, c=1]
+
+# Create reshaped outputs
+shape = tf.shape(x)
+b = shape[0]
+h = shape[1]
+w = shape[2]
+y1 = tf.reshape(x, shape=(b*h*w,)) # [b*h*w]
+y2 = tf.reshape(x, shape=(b*h*w, 1)) # [b*h*w, 1]
+y3 = tf.reshape(x, shape=(b, h, w)) # [b, h, w]
+y4 = tf.reshape(x, shape=(b, h, w, 1)) # [b, h, w, 1]
+
+# Create model
+model = tf.keras.Model(inputs={"x": x}, outputs={"y1": y1, "y2": y2, "y3": y3, "y4": y4})
+model.save("model5")
+
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diff --git a/test/models/model5/variables/variables.index b/test/models/model5/variables/variables.index
new file mode 100644
index 0000000000000000000000000000000000000000..b5dcd195566dfe545927b250de2a228c55c829c4
Binary files /dev/null and b/test/models/model5/variables/variables.index differ
diff --git a/test/otbTensorflowCopyUtilsTests.cxx b/test/otbTensorflowCopyUtilsTests.cxx
new file mode 100644
index 0000000000000000000000000000000000000000..5b9586460aa1e0cc51a115ea1a6031ebd3cf805e
--- /dev/null
+++ b/test/otbTensorflowCopyUtilsTests.cxx
@@ -0,0 +1,116 @@
+/*=========================================================================
+
+ Copyright (c) 2018-2019 IRSTEA
+ Copyright (c) 2020-2021 INRAE
+
+
+ This software is distributed WITHOUT ANY WARRANTY; without even
+ the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
+ PURPOSE. See the above copyright notices for more information.
+
+=========================================================================*/
+#include "otbTensorflowCopyUtils.h"
+#include "tensorflow/core/framework/tensor.h"
+#include "tensorflow/core/framework/tensor_shape.h"
+#include "itkMacro.h"
+
+template<typename T>
+int compare(tensorflow::Tensor & t1, tensorflow::Tensor & t2)
+{
+ std::cout << "Compare " << t1.DebugString() << " and " << t2.DebugString() << std::endl;
+ if (t1.dims() != t2.dims())
+ {
+ std::cout << "dims() differ!" << std::endl;
+ return EXIT_FAILURE;
+ }
+ if (t1.dtype() != t2.dtype())
+ {
+ std::cout << "dtype() differ!" << std::endl;
+ return EXIT_FAILURE;
+ }
+ if (t1.NumElements() != t2.NumElements())
+ {
+ std::cout << "NumElements() differ!" << std::endl;
+ return EXIT_FAILURE;
+ }
+ for (unsigned int i = 0; i < t1.NumElements(); i++)
+ if (t1.flat<T>()(i) != t2.flat<T>()(i))
+ {
+ std::cout << "scalar " << i << " differ!" << std::endl;
+ return EXIT_FAILURE;
+ }
+ // Else
+ std::cout << "Tensors are equals :)" << std::endl;
+ return EXIT_SUCCESS;
+}
+
+template<typename T>
+int genericValueToTensorTest(tensorflow::DataType dt, std::string expr, T value)
+{
+ tensorflow::Tensor t = otb::tf::ValueToTensor(expr);
+ tensorflow::Tensor t_ref(dt, tensorflow::TensorShape({1}));
+ t_ref.scalar<T>()() = value;
+
+ return compare<T>(t, t_ref);
+}
+
+int floatValueToTensorTest(int itkNotUsed(argc), char * itkNotUsed(argv)[])
+{
+ return genericValueToTensorTest<float>(tensorflow::DT_FLOAT, "0.1234", 0.1234)
+ && genericValueToTensorTest<float>(tensorflow::DT_FLOAT, "-0.1234", -0.1234) ;
+}
+
+int intValueToTensorTest(int itkNotUsed(argc), char * itkNotUsed(argv)[])
+{
+ return genericValueToTensorTest<int>(tensorflow::DT_INT32, "1234", 1234)
+ && genericValueToTensorTest<int>(tensorflow::DT_INT32, "-1234", -1234);
+}
+
+int boolValueToTensorTest(int itkNotUsed(argc), char * itkNotUsed(argv)[])
+{
+ return genericValueToTensorTest<bool>(tensorflow::DT_BOOL, "true", true)
+ && genericValueToTensorTest<bool>(tensorflow::DT_BOOL, "True", true)
+ && genericValueToTensorTest<bool>(tensorflow::DT_BOOL, "False", false)
+ && genericValueToTensorTest<bool>(tensorflow::DT_BOOL, "false", false);
+}
+
+template<typename T>
+int genericVecValueToTensorTest(tensorflow::DataType dt, std::string expr, std::vector<T> values, std::size_t size)
+{
+ tensorflow::Tensor t = otb::tf::ValueToTensor(expr);
+ tensorflow::Tensor t_ref(dt, tensorflow::TensorShape({size}));
+ unsigned int i = 0;
+ for (auto value: values)
+ {
+ t_ref.flat<T>()(i) = value;
+ i++;
+ }
+
+ return compare<T>(t, t_ref);
+}
+
+int floatVecValueToTensorTest(int itkNotUsed(argc), char * itkNotUsed(argv)[])
+{
+ return genericVecValueToTensorTest<float>(tensorflow::DT_FLOAT,
+ "(0.1234, -1,-20,2.56 ,3.5)",
+ std::vector<float>({0.1234, -1, -20, 2.56 ,3.5}),
+ 5);
+}
+
+int intVecValueToTensorTest(int itkNotUsed(argc), char * itkNotUsed(argv)[])
+{
+ return genericVecValueToTensorTest<int>(tensorflow::DT_INT32,
+ "(1234, -1,-20,256 ,35)",
+ std::vector<int>({1234, -1, -20, 256 ,35}),
+ 5);
+}
+
+int boolVecValueToTensorTest(int itkNotUsed(argc), char * itkNotUsed(argv)[])
+{
+ return genericVecValueToTensorTest<bool>(tensorflow::DT_BOOL,
+ "(true, false,True, False)",
+ std::vector<bool>({true, false, true, false}),
+ 4);
+}
+
+
diff --git a/test/otbTensorflowTests.cxx b/test/otbTensorflowTests.cxx
new file mode 100644
index 0000000000000000000000000000000000000000..50e9a91a57b85feecccf44b49b5c3b57f7e69ec3
--- /dev/null
+++ b/test/otbTensorflowTests.cxx
@@ -0,0 +1,23 @@
+/*=========================================================================
+
+ Copyright (c) 2018-2019 IRSTEA
+ Copyright (c) 2020-2021 INRAE
+
+
+ This software is distributed WITHOUT ANY WARRANTY; without even
+ the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
+ PURPOSE. See the above copyright notices for more information.
+
+=========================================================================*/
+#include "otbTestMain.h"
+
+void RegisterTests()
+{
+ REGISTER_TEST(floatValueToTensorTest);
+ REGISTER_TEST(intValueToTensorTest);
+ REGISTER_TEST(boolValueToTensorTest);
+ REGISTER_TEST(floatVecValueToTensorTest);
+ REGISTER_TEST(intVecValueToTensorTest);
+ REGISTER_TEST(boolVecValueToTensorTest);
+}
+
diff --git a/test/sr4rs_unittest.py b/test/sr4rs_unittest.py
new file mode 100644
index 0000000000000000000000000000000000000000..89c3945f153304d04d35c23ef34513cf668120bc
--- /dev/null
+++ b/test/sr4rs_unittest.py
@@ -0,0 +1,60 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+
+import unittest
+import os
+from pathlib import Path
+import test_utils
+
+
+def command_train_succeed(extra_opts=""):
+ root_dir = os.environ["CI_PROJECT_DIR"]
+ ckpt_dir = "/tmp/"
+
+ def _input(file_name):
+ return "{}/sr4rs_data/input/{}".format(root_dir, file_name)
+
+ command = "python {}/sr4rs/code/train.py ".format(root_dir)
+ command += "--lr_patches "
+ command += _input("DIM_SPOT6_MS_202007290959110_ORT_ORTHO-MS-193_posA_s2.jp2 ")
+ command += _input("DIM_SPOT7_MS_202004111036186_ORT_ORTHO-MS-081_posA_s2.jp2 ")
+ command += _input("DIM_SPOT7_MS_202006201000507_ORT_ORTHO-MS-054_posA_s2.jp2 ")
+ command += "--hr_patches "
+ command += _input("DIM_SPOT6_MS_202007290959110_ORT_ORTHO-MS-193_posA_s6_cal.jp2 ")
+ command += _input("DIM_SPOT7_MS_202004111036186_ORT_ORTHO-MS-081_posA_s6_cal.jp2 ")
+ command += _input("DIM_SPOT7_MS_202006201000507_ORT_ORTHO-MS-054_posA_s6_cal.jp2 ")
+ command += "--save_ckpt {} ".format(ckpt_dir)
+ command += "--depth 4 "
+ command += "--nresblocks 1 "
+ command += "--epochs 1 "
+ command += extra_opts
+ os.system(command)
+ file = Path("{}/checkpoint".format(ckpt_dir))
+ return file.is_file()
+
+
+class SR4RSv1Test(unittest.TestCase):
+
+ def test_train_nostream(self):
+ self.assertTrue(command_train_succeed())
+
+ def test_train_stream(self):
+ self.assertTrue(command_train_succeed(extra_opts="--streaming"))
+
+ def test_inference(self):
+ root_dir = os.environ["CI_PROJECT_DIR"]
+ out_img = "/tmp/sr4rs.tif"
+ baseline = "{}/sr4rs_data/baseline/sr4rs.tif".format(root_dir)
+
+ command = "python {}/sr4rs/code/sr.py ".format(root_dir)
+ command += "--input {}/sr4rs_data/input/".format(root_dir)
+ command += "SENTINEL2B_20200929-104857-489_L2A_T31TEJ_C_V2-2_FRE_10m.tif "
+ command += "--savedmodel {}/sr4rs_sentinel2_bands4328_france2020_savedmodel/ ".format(root_dir)
+ command += "--output '{}?&box=256:256:512:512'".format(out_img)
+ os.system(command)
+
+ self.assertTrue(test_utils.compare(baseline, out_img))
+
+
+if __name__ == '__main__':
+ unittest.main()
diff --git a/test/test_utils.py b/test/test_utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..c07301e91bb2eab4a808d53beaa46396c3ea82fc
--- /dev/null
+++ b/test/test_utils.py
@@ -0,0 +1,56 @@
+import otbApplication
+import os
+
+
+def get_nb_of_channels(raster):
+ """
+ Return the number of channels in the input raster
+ :param raster: raster filename (str)
+ :return the number of channels in the image (int)
+ """
+ info = otbApplication.Registry.CreateApplication("ReadImageInfo")
+ info.SetParameterString("in", raster)
+ info.ExecuteAndWriteOutput()
+ return info.GetParameterInt('numberbands')
+
+
+def compare(raster1, raster2, tol=0.01):
+ """
+ Return True if the two rasters have the same contents in each bands
+ :param raster1: raster 1 filename (str)
+ :param raster2: raster 2 filename (str)
+ :param tol: tolerance (float)
+ """
+ n_bands1 = get_nb_of_channels(raster1)
+ n_bands2 = get_nb_of_channels(raster2)
+ if n_bands1 != n_bands2:
+ print("The images have not the same number of channels")
+ return False
+
+ for i in range(1, 1 + n_bands1):
+ comp = otbApplication.Registry.CreateApplication('CompareImages')
+ comp.SetParameterString('ref.in', raster1)
+ comp.SetParameterInt('ref.channel', i)
+ comp.SetParameterString('meas.in', raster2)
+ comp.SetParameterInt('meas.channel', i)
+ comp.Execute()
+ mae = comp.GetParameterFloat('mae')
+ if mae > tol:
+ print("The images have not the same content in channel {} "
+ "(Mean average error: {})".format(i, mae))
+ return False
+ return True
+
+
+def resolve_paths(filename, var_list):
+ """
+ Retrieve environment variables in paths
+ :param filename: file name
+ :params var_list: variable list
+ :return filename with retrieved environment variables
+ """
+ new_filename = filename
+ for var in var_list:
+ new_filename = new_filename.replace("${}".format(var), os.environ[var])
+ print("Resolve filename...\n\tfilename: {}, \n\tnew filename: {}".format(filename, new_filename))
+ return new_filename
diff --git a/test/tutorial_unittest.py b/test/tutorial_unittest.py
new file mode 100644
index 0000000000000000000000000000000000000000..7934862f348326de13a11eef4c81a4fe6512cec6
--- /dev/null
+++ b/test/tutorial_unittest.py
@@ -0,0 +1,513 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+import pytest
+import unittest
+import os
+from pathlib import Path
+import test_utils
+
+INFERENCE_MAE_TOL = 10.0 # Dummy value: we don't really care of the mae value but rather the image size etc
+
+
+def resolve_paths(path):
+ """
+ Resolve a path with the environment variables
+ """
+ return test_utils.resolve_paths(path, var_list=["TMPDIR", "DATADIR"])
+
+
+def run_command(command):
+ """
+ Run a command
+ :param command: the command to run
+ """
+ full_command = resolve_paths(command)
+ print("Running command: \n\t {}".format(full_command))
+ os.system(full_command)
+
+
+def run_command_and_test_exist(command, file_list):
+ """
+ :param command: the command to run (str)
+ :param file_list: list of files to check
+ :return True or False
+ """
+ run_command(command)
+ print("Checking if files exist...")
+ for file in file_list:
+ print("\t{}".format(file))
+ path = Path(resolve_paths(file))
+ if not path.is_file():
+ print("File {} does not exist!".format(file))
+ return False
+ print("\tOk")
+ return True
+
+
+def run_command_and_compare(command, to_compare_dict, tol=0.01):
+ """
+ :param command: the command to run (str)
+ :param to_compare_dict: a dict of {baseline1: output1, ..., baselineN: outputN}
+ :param tol: tolerance (float)
+ :return True or False
+ """
+
+ run_command(command)
+ for baseline, output in to_compare_dict.items():
+ if not test_utils.compare(resolve_paths(baseline), resolve_paths(output), tol):
+ print("Baseline {} and output {} differ.".format(baseline, output))
+ return False
+ return True
+
+
+class TutorialTest(unittest.TestCase):
+
+ @pytest.mark.order(1)
+ def test_sample_selection(self):
+ self.assertTrue(
+ run_command_and_test_exist(
+ command="otbcli_LabelImageSampleSelection "
+ "-inref $DATADIR/terrain_truth_epsg32654_A.tif "
+ "-nodata 255 "
+ "-outvec $TMPDIR/outvec_A.gpkg",
+ file_list=["$TMPDIR/outvec_A.gpkg"]))
+ self.assertTrue(
+ run_command_and_test_exist(
+ command="otbcli_LabelImageSampleSelection "
+ "-inref $DATADIR/terrain_truth_epsg32654_B.tif "
+ "-nodata 255 "
+ "-outvec $TMPDIR/outvec_B.gpkg",
+ file_list=["$TMPDIR/outvec_B.gpkg"]))
+
+ @pytest.mark.order(2)
+ def test_patches_extraction(self):
+ self.assertTrue(
+ run_command_and_compare(
+ command="otbcli_PatchesExtraction "
+ "-source1.il $DATADIR/s2_stack.jp2 "
+ "-source1.out $TMPDIR/s2_patches_A.tif "
+ "-source1.patchsizex 16 "
+ "-source1.patchsizey 16 "
+ "-vec $TMPDIR/outvec_A.gpkg "
+ "-field class "
+ "-outlabels $TMPDIR/s2_labels_A.tif",
+ to_compare_dict={"$DATADIR/s2_patches_A.tif": "$TMPDIR/s2_patches_A.tif",
+ "$DATADIR/s2_labels_A.tif": "$TMPDIR/s2_labels_A.tif"}))
+ self.assertTrue(
+ run_command_and_compare(
+ command="otbcli_PatchesExtraction "
+ "-source1.il $DATADIR/s2_stack.jp2 "
+ "-source1.out $TMPDIR/s2_patches_B.tif "
+ "-source1.patchsizex 16 "
+ "-source1.patchsizey 16 "
+ "-vec $TMPDIR/outvec_B.gpkg "
+ "-field class "
+ "-outlabels $TMPDIR/s2_labels_B.tif",
+ to_compare_dict={"$DATADIR/s2_patches_B.tif": "$TMPDIR/s2_patches_B.tif",
+ "$DATADIR/s2_labels_B.tif": "$TMPDIR/s2_labels_B.tif"}))
+
+ @pytest.mark.order(3)
+ def test_generate_model1(self):
+ run_command("git clone https://github.com/remicres/otbtf_tutorials_resources.git "
+ "$TMPDIR/otbtf_tuto_repo")
+ self.assertTrue(
+ run_command_and_test_exist(
+ command="python $TMPDIR/otbtf_tuto_repo/01_patch_based_classification/models/create_model1.py "
+ "$TMPDIR/model1",
+ file_list=["$TMPDIR/model1/saved_model.pb"]))
+
+ @pytest.mark.order(4)
+ def test_model1_train(self):
+ self.assertTrue(
+ run_command_and_test_exist(
+ command="otbcli_TensorflowModelTrain "
+ "-training.source1.il $DATADIR/s2_patches_A.tif "
+ "-training.source1.patchsizex 16 "
+ "-training.source1.patchsizey 16 "
+ "-training.source1.placeholder x "
+ "-training.source2.il $DATADIR/s2_labels_A.tif "
+ "-training.source2.patchsizex 1 "
+ "-training.source2.patchsizey 1 "
+ "-training.source2.placeholder y "
+ "-model.dir $TMPDIR/model1 "
+ "-training.targetnodes optimizer "
+ "-training.epochs 10 "
+ "-validation.mode class "
+ "-validation.source1.il $DATADIR/s2_patches_B.tif "
+ "-validation.source1.name x "
+ "-validation.source2.il $DATADIR/s2_labels_B.tif "
+ "-validation.source2.name prediction "
+ "-model.saveto $TMPDIR/model1/variables/variables",
+ file_list=["$TMPDIR/model1/variables/variables.index"]
+ )
+ )
+
+ @pytest.mark.order(5)
+ def test_model1_inference_pb(self):
+ self.assertTrue(
+ run_command_and_compare(
+ command="otbcli_TensorflowModelServe "
+ "-source1.il $DATADIR/s2_stack.jp2 "
+ "-source1.rfieldx 16 "
+ "-source1.rfieldy 16 "
+ "-source1.placeholder x "
+ "-model.dir $TMPDIR/model1 "
+ "-output.names prediction "
+ "-out \"$TMPDIR/classif_model1.tif?&box=4000:4000:1000:1000\" uint8",
+ to_compare_dict={"$DATADIR/classif_model1.tif": "$TMPDIR/classif_model1.tif"},
+ tol=INFERENCE_MAE_TOL))
+
+ @pytest.mark.order(6)
+ def test_model1_inference_fcn(self):
+ self.assertTrue(
+ run_command_and_compare(
+ command="otbcli_TensorflowModelServe "
+ "-source1.il $DATADIR/s2_stack.jp2 "
+ "-source1.rfieldx 16 "
+ "-source1.rfieldy 16 "
+ "-source1.placeholder x "
+ "-model.dir $TMPDIR/model1 "
+ "-output.names prediction "
+ "-model.fullyconv on "
+ "-output.spcscale 4 "
+ "-out \"$TMPDIR/classif_model1.tif?&box=1000:1000:256:256\" uint8",
+ to_compare_dict={"$DATADIR/classif_model1.tif": "$TMPDIR/classif_model1.tif"},
+ tol=INFERENCE_MAE_TOL))
+
+ @pytest.mark.order(7)
+ def test_rf_sampling(self):
+ self.assertTrue(
+ run_command_and_test_exist(
+ command="otbcli_SampleExtraction "
+ "-in $DATADIR/s2_stack.jp2 "
+ "-vec $TMPDIR/outvec_A.gpkg "
+ "-field class "
+ "-out $TMPDIR/pixelvalues_A.gpkg",
+ file_list=["$TMPDIR/pixelvalues_A.gpkg"]))
+ self.assertTrue(
+ run_command_and_test_exist(
+ command="otbcli_SampleExtraction "
+ "-in $DATADIR/s2_stack.jp2 "
+ "-vec $TMPDIR/outvec_B.gpkg "
+ "-field class "
+ "-out $TMPDIR/pixelvalues_B.gpkg",
+ file_list=["$TMPDIR/pixelvalues_B.gpkg"]))
+
+ @pytest.mark.order(8)
+ def test_rf_training(self):
+ self.assertTrue(
+ run_command_and_test_exist(
+ command="otbcli_TrainVectorClassifier "
+ "-io.vd $TMPDIR/pixelvalues_A.gpkg "
+ "-valid.vd $TMPDIR/pixelvalues_B.gpkg "
+ "-feat value_0 value_1 value_2 value_3 "
+ "-cfield class "
+ "-classifier rf "
+ "-io.out $TMPDIR/randomforest_model.yaml ",
+ file_list=["$TMPDIR/randomforest_model.yaml"]))
+
+ @pytest.mark.order(9)
+ def test_generate_model2(self):
+ self.assertTrue(
+ run_command_and_test_exist(
+ command="python $TMPDIR/otbtf_tuto_repo/01_patch_based_classification/models/create_model2.py "
+ "$TMPDIR/model2",
+ file_list=["$TMPDIR/model2/saved_model.pb"]))
+
+ @pytest.mark.order(10)
+ def test_model2_train(self):
+ self.assertTrue(
+ run_command_and_test_exist(
+ command="otbcli_TensorflowModelTrain "
+ "-training.source1.il $DATADIR/s2_patches_A.tif "
+ "-training.source1.patchsizex 16 "
+ "-training.source1.patchsizey 16 "
+ "-training.source1.placeholder x "
+ "-training.source2.il $DATADIR/s2_labels_A.tif "
+ "-training.source2.patchsizex 1 "
+ "-training.source2.patchsizey 1 "
+ "-training.source2.placeholder y "
+ "-model.dir $TMPDIR/model2 "
+ "-training.targetnodes optimizer "
+ "-training.epochs 10 "
+ "-validation.mode class "
+ "-validation.source1.il $DATADIR/s2_patches_B.tif "
+ "-validation.source1.name x "
+ "-validation.source2.il $DATADIR/s2_labels_B.tif "
+ "-validation.source2.name prediction "
+ "-model.saveto $TMPDIR/model2/variables/variables",
+ file_list=["$TMPDIR/model2/variables/variables.index"]))
+
+ @pytest.mark.order(11)
+ def test_model2_inference_fcn(self):
+ self.assertTrue(
+ run_command_and_compare(command="otbcli_TensorflowModelServe "
+ "-source1.il $DATADIR/s2_stack.jp2 "
+ "-source1.rfieldx 16 "
+ "-source1.rfieldy 16 "
+ "-source1.placeholder x "
+ "-model.dir $TMPDIR/model2 "
+ "-model.fullyconv on "
+ "-output.names prediction "
+ "-out \"$TMPDIR/classif_model2.tif?&box=4000:4000:1000:1000\" uint8",
+ to_compare_dict={"$DATADIR/classif_model2.tif": "$TMPDIR/classif_model2.tif"},
+ tol=INFERENCE_MAE_TOL))
+
+ @pytest.mark.order(12)
+ def test_model2rf_train(self):
+ self.assertTrue(
+ run_command_and_test_exist(
+ command="otbcli_TrainClassifierFromDeepFeatures "
+ "-source1.il $DATADIR/s2_stack.jp2 "
+ "-source1.rfieldx 16 "
+ "-source1.rfieldy 16 "
+ "-source1.placeholder x "
+ "-model.dir $TMPDIR/model2 "
+ "-model.fullyconv on "
+ "-optim.tilesizex 999999 "
+ "-optim.tilesizey 128 "
+ "-output.names features "
+ "-vd $TMPDIR/outvec_A.gpkg "
+ "-valid $TMPDIR/outvec_B.gpkg "
+ "-sample.vfn class "
+ "-sample.bm 0 "
+ "-classifier rf "
+ "-out $TMPDIR/RF_model_from_deep_features.yaml",
+ file_list=["$TMPDIR/RF_model_from_deep_features.yaml"]))
+
+ @pytest.mark.order(13)
+ def test_model2rf_inference(self):
+ self.assertTrue(
+ run_command_and_compare(
+ command="otbcli_ImageClassifierFromDeepFeatures "
+ "-source1.il $DATADIR/s2_stack.jp2 "
+ "-source1.rfieldx 16 "
+ "-source1.rfieldy 16 "
+ "-source1.placeholder x "
+ "-deepmodel.dir $TMPDIR/model2 "
+ "-deepmodel.fullyconv on "
+ "-output.names features "
+ "-model $TMPDIR/RF_model_from_deep_features.yaml "
+ "-out \"$TMPDIR/RF_model_from_deep_features_map.tif?&box=4000:4000:1000:1000\" uint8",
+ to_compare_dict={
+ "$DATADIR/RF_model_from_deep_features_map.tif": "$TMPDIR/RF_model_from_deep_features_map.tif"},
+ tol=INFERENCE_MAE_TOL))
+
+ @pytest.mark.order(14)
+ def test_patch_extraction_20m(self):
+ self.assertTrue(
+ run_command_and_compare(
+ command="OTB_TF_NSOURCES=2 otbcli_PatchesExtraction "
+ "-source1.il $DATADIR/s2_20m_stack.jp2 "
+ "-source1.patchsizex 8 "
+ "-source1.patchsizey 8 "
+ "-source1.out $TMPDIR/s2_20m_patches_A.tif "
+ "-source2.il $DATADIR/s2_stack.jp2 "
+ "-source2.patchsizex 16 "
+ "-source2.patchsizey 16 "
+ "-source2.out $TMPDIR/s2_10m_patches_A.tif "
+ "-vec $TMPDIR/outvec_A.gpkg "
+ "-field class "
+ "-outlabels $TMPDIR/s2_10m_labels_A.tif uint8",
+ to_compare_dict={"$DATADIR/s2_10m_labels_A.tif": "$TMPDIR/s2_10m_labels_A.tif",
+ "$DATADIR/s2_10m_patches_A.tif": "$TMPDIR/s2_10m_patches_A.tif",
+ "$DATADIR/s2_20m_patches_A.tif": "$TMPDIR/s2_20m_patches_A.tif"}))
+ self.assertTrue(
+ run_command_and_compare(
+ command="OTB_TF_NSOURCES=2 otbcli_PatchesExtraction "
+ "-source1.il $DATADIR/s2_20m_stack.jp2 "
+ "-source1.patchsizex 8 "
+ "-source1.patchsizey 8 "
+ "-source1.out $TMPDIR/s2_20m_patches_B.tif "
+ "-source2.il $DATADIR/s2_stack.jp2 "
+ "-source2.patchsizex 16 "
+ "-source2.patchsizey 16 "
+ "-source2.out $TMPDIR/s2_10m_patches_B.tif "
+ "-vec $TMPDIR/outvec_B.gpkg "
+ "-field class "
+ "-outlabels $TMPDIR/s2_10m_labels_B.tif uint8",
+ to_compare_dict={"$DATADIR/s2_10m_labels_B.tif": "$TMPDIR/s2_10m_labels_B.tif",
+ "$DATADIR/s2_10m_patches_B.tif": "$TMPDIR/s2_10m_patches_B.tif",
+ "$DATADIR/s2_20m_patches_B.tif": "$TMPDIR/s2_20m_patches_B.tif"}))
+
+ @pytest.mark.order(15)
+ def test_generate_model3(self):
+ self.assertTrue(
+ run_command_and_test_exist(
+ command="python $TMPDIR/otbtf_tuto_repo/01_patch_based_classification/models/create_model3.py "
+ "$TMPDIR/model3",
+ file_list=["$TMPDIR/model3/saved_model.pb"]))
+
+ @pytest.mark.order(16)
+ def test_model3_train(self):
+ self.assertTrue(
+ run_command_and_test_exist(
+ command="OTB_TF_NSOURCES=2 otbcli_TensorflowModelTrain "
+ "-training.source1.il $DATADIR/s2_20m_patches_A.tif "
+ "-training.source1.patchsizex 8 "
+ "-training.source1.patchsizey 8 "
+ "-training.source1.placeholder x1 "
+ "-training.source2.il $DATADIR/s2_10m_patches_A.tif "
+ "-training.source2.patchsizex 16 "
+ "-training.source2.patchsizey 16 "
+ "-training.source2.placeholder x2 "
+ "-training.source3.il $DATADIR/s2_10m_labels_A.tif "
+ "-training.source3.patchsizex 1 "
+ "-training.source3.patchsizey 1 "
+ "-training.source3.placeholder y "
+ "-model.dir $TMPDIR/model3 "
+ "-training.targetnodes optimizer "
+ "-training.epochs 10 "
+ "-validation.mode class "
+ "-validation.source1.il $DATADIR/s2_20m_patches_B.tif "
+ "-validation.source1.name x1 "
+ "-validation.source2.il $DATADIR/s2_10m_patches_B.tif "
+ "-validation.source2.name x2 "
+ "-validation.source3.il $DATADIR/s2_10m_labels_B.tif "
+ "-validation.source3.name prediction "
+ "-model.saveto $TMPDIR/model3/variables/variables",
+ file_list=["$TMPDIR/model3/variables/variables.index"]))
+
+ @pytest.mark.order(17)
+ def test_model3_inference_pb(self):
+ self.assertTrue(
+ run_command_and_compare(
+ command=
+ "OTB_TF_NSOURCES=2 otbcli_TensorflowModelServe "
+ "-source1.il $DATADIR/s2_20m_stack.jp2 "
+ "-source1.rfieldx 8 "
+ "-source1.rfieldy 8 "
+ "-source1.placeholder x1 "
+ "-source2.il $DATADIR/s2_stack.jp2 "
+ "-source2.rfieldx 16 "
+ "-source2.rfieldy 16 "
+ "-source2.placeholder x2 "
+ "-model.dir $TMPDIR/model3 "
+ "-output.names prediction "
+ "-out \"$TMPDIR/classif_model3_pb.tif?&box=2000:2000:500:500&gdal:co:compress=deflate\"",
+ to_compare_dict={"$DATADIR/classif_model3_pb.tif": "$TMPDIR/classif_model3_pb.tif"},
+ tol=INFERENCE_MAE_TOL))
+
+ @pytest.mark.order(18)
+ def test_model3_inference_fcn(self):
+ self.assertTrue(
+ run_command_and_compare(
+ command=
+ "OTB_TF_NSOURCES=2 otbcli_TensorflowModelServe "
+ "-source1.il $DATADIR/s2_20m_stack.jp2 "
+ "-source1.rfieldx 8 "
+ "-source1.rfieldy 8 "
+ "-source1.placeholder x1 "
+ "-source2.il $DATADIR/s2_stack.jp2 "
+ "-source2.rfieldx 16 "
+ "-source2.rfieldy 16 "
+ "-source2.placeholder x2 "
+ "-model.dir $TMPDIR/model3 "
+ "-model.fullyconv on "
+ "-output.names prediction "
+ "-out \"$TMPDIR/classif_model3_fcn.tif?&box=2000:2000:500:500&gdal:co:compress=deflate\"",
+ to_compare_dict={"$DATADIR/classif_model3_fcn.tif": "$TMPDIR/classif_model3_fcn.tif"},
+ tol=INFERENCE_MAE_TOL))
+
+ @pytest.mark.order(19)
+ def test_generate_model4(self):
+ self.assertTrue(
+ run_command_and_test_exist(
+ command="python $TMPDIR/otbtf_tuto_repo/02_semantic_segmentation/models/create_model4.py "
+ "$TMPDIR/model4",
+ file_list=["$TMPDIR/model4/saved_model.pb"]))
+
+ @pytest.mark.order(20)
+ def test_patches_selection_semseg(self):
+ self.assertTrue(
+ run_command_and_test_exist(
+ command="otbcli_PatchesSelection "
+ "-in $DATADIR/fake_spot6.jp2 "
+ "-grid.step 64 "
+ "-grid.psize 64 "
+ "-outtrain $TMPDIR/outvec_A_semseg.gpkg "
+ "-outvalid $TMPDIR/outvec_B_semseg.gpkg",
+ file_list=["$TMPDIR/outvec_A_semseg.gpkg",
+ "$TMPDIR/outvec_B_semseg.gpkg"]))
+
+ @pytest.mark.order(21)
+ def test_patch_extraction_semseg(self):
+ self.assertTrue(
+ run_command_and_compare(
+ command="OTB_TF_NSOURCES=2 otbcli_PatchesExtraction "
+ "-source1.il $DATADIR/fake_spot6.jp2 "
+ "-source1.patchsizex 64 "
+ "-source1.patchsizey 64 "
+ "-source1.out \"$TMPDIR/amsterdam_patches_A.tif?&gdal:co:compress=deflate\" "
+ "-source2.il $TMPDIR/otbtf_tuto_repo/02_semantic_segmentation/"
+ "amsterdam_dataset/terrain_truth/amsterdam_labelimage.tif "
+ "-source2.patchsizex 64 "
+ "-source2.patchsizey 64 "
+ "-source2.out \"$TMPDIR/amsterdam_labels_A.tif?&gdal:co:compress=deflate\" "
+ "-vec $TMPDIR/outvec_A_semseg.gpkg "
+ "-field id ",
+ to_compare_dict={"$DATADIR/amsterdam_labels_A.tif": "$TMPDIR/amsterdam_labels_A.tif",
+ "$DATADIR/amsterdam_patches_A.tif": "$TMPDIR/amsterdam_patches_A.tif"}))
+ self.assertTrue(
+ run_command_and_compare(
+ command="OTB_TF_NSOURCES=2 otbcli_PatchesExtraction "
+ "-source1.il $DATADIR/fake_spot6.jp2 "
+ "-source1.patchsizex 64 "
+ "-source1.patchsizey 64 "
+ "-source1.out \"$TMPDIR/amsterdam_patches_B.tif?&gdal:co:compress=deflate\" "
+ "-source2.il $TMPDIR/otbtf_tuto_repo/02_semantic_segmentation/"
+ "amsterdam_dataset/terrain_truth/amsterdam_labelimage.tif "
+ "-source2.patchsizex 64 "
+ "-source2.patchsizey 64 "
+ "-source2.out \"$TMPDIR/amsterdam_labels_B.tif?&gdal:co:compress=deflate\" "
+ "-vec $TMPDIR/outvec_B_semseg.gpkg "
+ "-field id ",
+ to_compare_dict={"$DATADIR/amsterdam_labels_B.tif": "$TMPDIR/amsterdam_labels_B.tif",
+ "$DATADIR/amsterdam_patches_B.tif": "$TMPDIR/amsterdam_patches_B.tif"}))
+
+ @pytest.mark.order(22)
+ def test_model4_train(self):
+ self.assertTrue(
+ run_command_and_test_exist(
+ command="OTB_TF_NSOURCES=1 otbcli_TensorflowModelTrain "
+ "-training.source1.il $DATADIR/amsterdam_patches_A.tif "
+ "-training.source1.patchsizex 64 "
+ "-training.source1.patchsizey 64 "
+ "-training.source1.placeholder x "
+ "-training.source2.il $DATADIR/amsterdam_labels_A.tif "
+ "-training.source2.patchsizex 64 "
+ "-training.source2.patchsizey 64 "
+ "-training.source2.placeholder y "
+ "-model.dir $TMPDIR/model4 "
+ "-training.targetnodes optimizer "
+ "-training.epochs 10 "
+ "-validation.mode class "
+ "-validation.source1.il $DATADIR/amsterdam_patches_B.tif "
+ "-validation.source1.name x "
+ "-validation.source2.il $DATADIR/amsterdam_labels_B.tif "
+ "-validation.source2.name prediction "
+ "-model.saveto $TMPDIR/model4/variables/variables",
+ file_list=["$TMPDIR/model4/variables/variables.index"]))
+
+ @pytest.mark.order(23)
+ def test_model4_inference(self):
+ self.assertTrue(
+ run_command_and_compare(
+ command=
+ "otbcli_TensorflowModelServe "
+ "-source1.il $DATADIR/fake_spot6.jp2 "
+ "-source1.rfieldx 64 "
+ "-source1.rfieldy 64 "
+ "-source1.placeholder x "
+ "-model.dir $TMPDIR/model4 "
+ "-model.fullyconv on "
+ "-output.names prediction_fcn "
+ "-output.efieldx 32 "
+ "-output.efieldy 32 "
+ "-out \"$TMPDIR/classif_model4.tif?&gdal:co:compress=deflate\" uint8",
+ to_compare_dict={"$DATADIR/classif_model4.tif": "$TMPDIR/classif_model4.tif"},
+ tol=INFERENCE_MAE_TOL))
+
+
+if __name__ == '__main__':
+ unittest.main()
diff --git a/tools/docker/README.md b/tools/docker/README.md
index 8722b52e539303319b50a9de8ca3f11ff721597e..4246b74d33b88ee1daa38c2f3de7ab44911f0917 100644
--- a/tools/docker/README.md
+++ b/tools/docker/README.md
@@ -74,7 +74,7 @@ docker build --network='host' -t otbtf:oldstable-gpu --build-arg BASE_IMG=nvidia
### Build for another machine and save TF compiled files
```bash
-# Use same ubuntu and CUDA version than your target machine, beware of CC optimization and CPU compatibilty
+# Use same ubuntu and CUDA version than your target machine, beware of CC optimization and CPU compatibility
# (set env variable CC_OPT_FLAGS and avoid "-march=native" if your Docker's CPU is optimized with AVX2/AVX512 but your target CPU isn't)
docker build --network='host' -t otbtf:custom --build-arg BASE_IMG=nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04 \
--build-arg TF=v2.5.0 --build-arg ZIP_TF_BIN=true .
@@ -146,7 +146,7 @@ $ mapla
```
## Common errors
-Buid :
+Build :
`Error response from daemon: manifest for nvidia/cuda:11.0-cudnn8-devel-ubuntu20.04 not found: manifest unknown: manifest unknown`
=> Image is missing from dockerhub