diff --git a/CMakeLists.txt b/CMakeLists.txt
index f1b0d6002bd3cb3fd1b8996baec47d89dfa730fd..c31d605bd28213d887e01e20bb954b5bdd8c0342 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -392,6 +392,17 @@ endif()
# Provide an option for generating documentation.
add_subdirectory(Utilities/Doxygen)
+#----------------------------------------------------------------------
+# Provide a target to generate the SuperBuild archive (only for Unix)
+if(UNIX)
+ add_custom_target(SuperBuild-archive
+ COMMAND ./SuperbuildDownloadList.sh
+ ${OTB_BINARY_DIR}/Download
+ ${OTB_BINARY_DIR}
+ WORKING_DIRECTORY ${OTB_SOURCE_DIR}/Utilities/Maintenance
+ )
+endif()
+
# TODO cleanup
# Create target to download data from the OTBData group. This must come after
# all tests have been added that reference the group, so we put it last.
diff --git a/Copyright/Copyright.txt b/Copyright/Copyright.txt
index 6f7788f583a027750cff1a2588e9d007788f4171..eaafdd8042caa0bfd122e6b8067cd6ec2c309c42 100644
--- a/Copyright/Copyright.txt
+++ b/Copyright/Copyright.txt
@@ -21,7 +21,7 @@
See CrispCopyright.txt for details.
* Parts of the code have been developped by Gregoire Mercier.
- See GETCopyright.txt for details.
+ See IMTCopyright.txt for details.
--------------------------- DEPENDENCIES ----------------------------------
Several utilities are mandatory dependencies used by the OTB library :
diff --git a/Copyright/GETCopyright.txt b/Copyright/IMTCopyright.txt
similarity index 78%
rename from Copyright/GETCopyright.txt
rename to Copyright/IMTCopyright.txt
index 7ac8ce5f0c4fd75918cf746f9f9cfbf50fc67a8a..7fb5d5df7ace7e756cd1c3aa3c634d4d8e4738c1 100644
--- a/Copyright/GETCopyright.txt
+++ b/Copyright/IMTCopyright.txt
@@ -1,10 +1,8 @@
Parts of the code have been developped by Gregoire Mercier from
-Groupe des Ecoles des Telecommunications / Ecole Nationale Superieure
-des Telecommunications de Bretagne (GET/ENST Bretagne) during
-CNES R&T contrats funded by the French Centre National d'Etudes
-Spatiales, CNES.
+Institut Mines-Telecom / Telecom Bretagne during CNES R&T contrats
+funded by the French Centre National d'Etudes Spatiales, CNES.
-Copyright (c) GET / ENST Bretagne
+Copyright (c) Institut Mines-Telecom
This code has been integrated into the ORFEO Toolbox (OTB) under
the CeCILL licence version 2. See Licence_CeCILL_V2-en.txt or
diff --git a/Examples/BasicFilters/CMakeLists.txt b/Examples/BasicFilters/CMakeLists.txt
index c8fb34bd1304b95ad7c9f911bdf275115fd10b84..858e0fa5ae8d0fa920aa9e08e4c0aca335c57fe7 100644
--- a/Examples/BasicFilters/CMakeLists.txt
+++ b/Examples/BasicFilters/CMakeLists.txt
@@ -1,10 +1,16 @@
project(BasicFiltersExamples)
+#OTB_USE_MUPARSER is OFF
+if(OTBMathParser_LOADED)
add_executable(BandMathFilterExample BandMathFilterExample.cxx)
target_link_libraries(BandMathFilterExample ${OTB_LIBRARIES})
+endif()
+#OTB_USE_MUPARSERX is OFF
+if(OTBMathParserX_LOADED)
add_executable(BandMathXImageFilterExample BandMathXImageFilterExample.cxx)
target_link_libraries(BandMathXImageFilterExample ${OTB_LIBRARIES})
+endif()
add_executable(DEMToRainbowExample DEMToRainbowExample.cxx)
target_link_libraries(DEMToRainbowExample ${OTB_LIBRARIES})
@@ -21,8 +27,11 @@ target_link_libraries(IndexedToRGBExample ${OTB_LIBRARIES})
add_executable(LeeImageFilter LeeImageFilter.cxx)
target_link_libraries(LeeImageFilter ${OTB_LIBRARIES})
+#OTBMeanShift depends OTBMathParser. But OTB_USE_MUPARSER is OFF
+if(OTBMathParser_LOADED)
add_executable(MeanShiftSegmentationFilterExample MeanShiftSegmentationFilterExample.cxx)
target_link_libraries(MeanShiftSegmentationFilterExample ${OTB_LIBRARIES})
+endif()
add_executable(PrintableImageFilterExample PrintableImageFilterExample.cxx)
target_link_libraries(PrintableImageFilterExample ${OTB_LIBRARIES})
diff --git a/Examples/BasicFilters/test/CMakeLists.txt b/Examples/BasicFilters/test/CMakeLists.txt
index 15da042a010e826cedf26779452177d37a1b5f89..cc6dabe32daa2c486acaed79481b64b63d287baf 100644
--- a/Examples/BasicFilters/test/CMakeLists.txt
+++ b/Examples/BasicFilters/test/CMakeLists.txt
@@ -84,7 +84,7 @@ otb_add_test(NAME bfTeIndexedToRGBExampleTest COMMAND ${OTB_TEST_DRIVER}
${TEMP}/buildingExtractionRGB.png
${TEMP}/buildingExtractionIndexed_scaled.png
)
-
+if(OTBMathParser_LOADED)
otb_add_test(NAME bfTeMeanShiftSegmentationFilterExampleTest COMMAND ${OTB_TEST_DRIVER}
--compare-n-images ${NOTOL} 4
${BASELINE}/MSClusteredOutput.tif
@@ -107,7 +107,7 @@ otb_add_test(NAME bfTeMeanShiftSegmentationFilterExampleTest COMMAND ${OTB_TEST_
100
0.1
)
-
+endif()
# ------- HillShadingExampleTest ----------
otb_add_test(NAME bfTeHillShadingExampleTest COMMAND ${OTB_TEST_DRIVER}
diff --git a/Examples/CMakeLists.txt b/Examples/CMakeLists.txt
index 639761a6c6e94b30538e8febb535134ca33c6b1a..84b3542f4f25ff3f52fa79e88c29e1f1b99bb3ba 100644
--- a/Examples/CMakeLists.txt
+++ b/Examples/CMakeLists.txt
@@ -81,32 +81,12 @@ if(PROJECT_NAME STREQUAL "OTBExamples")
########################## end copied from OTB/CMakeLists.txt ##########################
- #must be updated for new modules!
- set(REQUIRED_MODULES "OTB6S;OTBITK;OTBAnomalyDetection;OTBBoost;OTBCommon;OTBGDAL;OTBOpenThreads;OTBOssim;OTBGeoTIFF;OTBOssimPlugins;OTBOSSIMAdapters;OTBObjectList;OTBMetadata;OTBImageBase;OTBBoostAdapters;OTBGdalAdapters;OTBTinyXML;OTBVectorDataBase;OTBIOGDAL;OTBExtendedFilename;OTBIOBSQ;OTBIOLUM;OTBIOMSTAR;OTBIOMW;OTBIOONERA;OTBIORAD;OTBCurl;OTBCurlAdapters;OTBIOTileMap;OTBStreaming;OTBImageIO;OTBInterpolation;OTBTransform;OTBImageManipulation;OTBTestKernel;OTBPath;OTBVectorDataManipulation;OTBProjection;OTBlibkml;OTBIOKML;OTBVectorDataIO;OTBApplicationEngine;OTBStatistics;OTBChangeDetection;OTBAppChangeDetection;OTBCommandLine;OTBColorMap;OTBMoments;OTBLabelMap;OTBConversion;OTBFuzzy;OTBMuParser;OTBMathParser;OTBSupervised;OTBDempsterShafer;OTBIOXML;OTBIndices;OTBMajorityVoting;OTBSOM;OTBAppClassification;OTBPointSet;OTBSiftFast;OTBDescriptors;OTBAppDescriptors;OTBDimensionalityReduction;OTBAppDimensionalityReduction;OTBSpatialObjects;OTBEdge;OTBAppEdge;OTBImageNoise;OTBAppFiltering;OTBConvolution;OTBPanSharpening;OTBAppFusion;OTBEndmembersExtraction;OTBWavelet;OTBUnmixing;OTBAppHyperspectral;OTBCarto;OTBAppImageUtils;OTBAppIndices;OTBKMZWriter;OTBAppKMZ;OTBAppMathParser;OTBMuParserX;OTBMathParserX;OTBAppMathParserX;OTBAppMoments;OTBAppMorphology;OTBOpticalCalibration;OTBAppOpticalCalibration;OTBAppProjection;OTBSARCalibration;OTBAppSARCalibration;OTBCCOBIA;OTBSmoothing;OTBMeanShift;OTBMetrics;OTBMorphologicalProfiles;OTBLabelling;OTBOGRProcessing;OTBWatersheds;OTBAppSegmentation;OTBDEM;OTBStereo;OTBDisparityMap;OTBAppStereo;OTBAppTest;OTBTextures;OTBAppTextures;OTBAppVectorDataTranslation;OTBAppVectorUtils;OTBCommandLineParser;OTBOpenThreadsAdapters;OTBCloudDetection;OTBComplexImage;OTBCorner;OTBDensity;OTBDisplacementField;OTBLandSatClassifier;OTBLearningBase;OTBMarkov;OTBMorphologicalPyramid;OTBObjectDetection;OTBPolarimetry;OTBRoadExtraction;OTBRCC8;OTBSWIGWrapper;OTBSeamCarving;OTBSimulation;OTBTimeSeries;OTBUrbanArea")
-
- find_package(OTB REQUIRED COMPONENTS ${REQUIRED_MODULES})
- include(${OTB_USE_FILE})
- message(STATUS "Found OTB: ${OTB_USE_FILE}")
-
-else()
- if(NOT OTB_BUILD_DEFAULT_MODULES)
- message(FATAL_ERROR "BUILD_EXAMPLES requires OTB_BUILD_DEFAULT_MODULES to be ON")
- endif()
- # We also need to prevent any OTB_USE_XXX option to be OFF (except mapnik and openjpeg)
- # For now we parse module activation list and test if option is ON. If not the cmake configuration stop.
- #TODO We should provide a better mechanism here wich will deactivate only examples required by deactivated options.
- foreach (_activationOption ${OTB_MODULE_ACTIVATION_OPTION_LIST})
- if(NOT ${_activationOption} AND NOT "x${_activationOption}" STREQUAL "xOTB_USE_MAPNIK" AND NOT "x${_activationOption}" STREQUAL "xOTB_USE_OPENJPEG")
- message(FATAL_ERROR "BUILD_EXAMPLES requires ${_activationOption} to be ON")
- endif()
- endforeach()
-
- find_package(OTB REQUIRED)
- include(${OTB_USE_FILE})
- message(STATUS "Found OTB: ${OTB_USE_FILE}")
-
endif()
+find_package(OTB REQUIRED)
+include(${OTB_USE_FILE})
+message(STATUS "Found OTB: ${OTB_USE_FILE}")
+
set(OTB_TEST_DRIVER otbTestDriver)
if(OTBApplicationEngine_LOADED)
diff --git a/Examples/ChangeDetection/KullbackLeiblerSupervizedDistanceChDet.cxx b/Examples/ChangeDetection/KullbackLeiblerSupervizedDistanceChDet.cxx
index f892976f62dd27fcc5a468ac8644a13ba60aee67..b0bb7279127beed6cefd17c148468488426aac90 100644
--- a/Examples/ChangeDetection/KullbackLeiblerSupervizedDistanceChDet.cxx
+++ b/Examples/ChangeDetection/KullbackLeiblerSupervizedDistanceChDet.cxx
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom / Telecom Bretagne. All rights reserved.
- See GETCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Examples/Classification/CMakeLists.txt b/Examples/Classification/CMakeLists.txt
index 4aa4757783949ef289edc2dac459ff6805d25e64..02db6fd752225dc4bbf2508b347b7c7257dfd155 100644
--- a/Examples/Classification/CMakeLists.txt
+++ b/Examples/Classification/CMakeLists.txt
@@ -6,9 +6,11 @@ target_link_libraries(BayesianPluginClassifier ${OTB_LIBRARIES})
add_executable(ClassificationMapRegularizationExample ClassificationMapRegularizationExample.cxx)
target_link_libraries(ClassificationMapRegularizationExample ${OTB_LIBRARIES})
+#OTBDempsterShafer depends OTBMathParser. But OTB_USE_MUPARSER is OFF
+if(OTBMathParser_LOADED)
add_executable(DempsterShaferFusionOfClassificationMapsExample DempsterShaferFusionOfClassificationMapsExample.cxx)
target_link_libraries(DempsterShaferFusionOfClassificationMapsExample ${OTB_LIBRARIES})
-
+endif()
add_executable(ExpectationMaximizationMixtureModelEstimator ExpectationMaximizationMixtureModelEstimator.cxx)
target_link_libraries(ExpectationMaximizationMixtureModelEstimator ${OTB_LIBRARIES})
diff --git a/Examples/DisparityMap/CMakeLists.txt b/Examples/DisparityMap/CMakeLists.txt
index bd7b2c26c86cd6fb2fdbfa84dbcc28f8f200ecbc..f42b945930e97fd1cfa30117302d08759a1dc44e 100644
--- a/Examples/DisparityMap/CMakeLists.txt
+++ b/Examples/DisparityMap/CMakeLists.txt
@@ -9,8 +9,11 @@ target_link_libraries(NCCRegistrationFilterExample ${OTB_LIBRARIES})
add_executable(SimpleDisparityMapEstimationExample SimpleDisparityMapEstimationExample.cxx)
target_link_libraries(SimpleDisparityMapEstimationExample ${OTB_LIBRARIES})
+#StereoReconstructionExample depends OTBMathParser. But OTB_USE_MUPARSER is OFF
+if(OTBMathParser_LOADED)
add_executable(StereoReconstructionExample StereoReconstructionExample.cxx)
target_link_libraries(StereoReconstructionExample ${OTB_LIBRARIES})
+endif()
if(BUILD_TESTING)
add_subdirectory(test)
diff --git a/Examples/DisparityMap/test/CMakeLists.txt b/Examples/DisparityMap/test/CMakeLists.txt
index d90913ccfcaca5de71692741ba78d7765020168b..9c247434b91ffb8e9116882b05e8538380ae513d 100644
--- a/Examples/DisparityMap/test/CMakeLists.txt
+++ b/Examples/DisparityMap/test/CMakeLists.txt
@@ -17,6 +17,7 @@ otb_add_test(NAME dmTeSimpleDisparityMapEstimationExampleTest COMMAND ${OTB_TEST
100 10 15 10 10 250 0.9
)
+if(OTBMathParser_LOADED)
otb_add_test(NAME dmTeStereoReconstructionExampleTest COMMAND ${OTB_TEST_DRIVER}
--compare-image ${NOTOL}
${BASELINE}/elevationOutput.tif
@@ -28,3 +29,4 @@ otb_add_test(NAME dmTeStereoReconstructionExampleTest COMMAND ${OTB_TEST_DRIVER}
${TEMP}/elevationOutputPrintable.png
140
)
+endif()
\ No newline at end of file
diff --git a/Examples/FeatureExtraction/CMakeLists.txt b/Examples/FeatureExtraction/CMakeLists.txt
index ec46f9fd89a8065e4ac0d0b713aca977c89311eb..edce7bf6fac9ecc829033a2531cf3be9d5f4957c 100644
--- a/Examples/FeatureExtraction/CMakeLists.txt
+++ b/Examples/FeatureExtraction/CMakeLists.txt
@@ -1,8 +1,5 @@
project(FeatureExtractionExamples)
-add_executable(AlignmentsExample AlignmentsExample.cxx)
-target_link_libraries(AlignmentsExample ${OTB_LIBRARIES})
-
add_executable(AssymmetricFusionOfLineDetectorExample AssymmetricFusionOfLineDetectorExample.cxx)
target_link_libraries(AssymmetricFusionOfLineDetectorExample ${OTB_LIBRARIES})
@@ -21,12 +18,21 @@ target_link_libraries(CorrelationLineDetectorExample ${OTB_LIBRARIES})
add_executable(EdgeDensityExample EdgeDensityExample.cxx)
target_link_libraries(EdgeDensityExample ${OTB_LIBRARIES})
+#OTBRoadExtraction depends OTBMathParser. But OTB_USE_MUPARSER is OFF
+if(OTBMathParser_LOADED)
add_executable(ExtractRoadByStepsExample ExtractRoadByStepsExample.cxx)
target_link_libraries(ExtractRoadByStepsExample ${OTB_LIBRARIES})
add_executable(ExtractRoadExample ExtractRoadExample.cxx)
target_link_libraries(ExtractRoadExample ${OTB_LIBRARIES})
+add_executable(ParallelLineDetectionExample ParallelLineDetectionExample.cxx)
+target_link_libraries(ParallelLineDetectionExample ${OTB_LIBRARIES})
+
+add_executable(AlignmentsExample AlignmentsExample.cxx)
+target_link_libraries(AlignmentsExample ${OTB_LIBRARIES})
+endif()
+
add_executable(ExtractSegmentsByStepsExample ExtractSegmentsByStepsExample.cxx)
target_link_libraries(ExtractSegmentsByStepsExample ${OTB_LIBRARIES})
@@ -45,6 +51,9 @@ target_link_libraries(HuMomentsImageFunctionExample ${OTB_LIBRARIES})
if (Module_OTBVectorDataRendering AND OTB_USE_MAPNIK)
add_executable(LineSegmentDetectorExample LineSegmentDetectorExample.cxx)
target_link_libraries(LineSegmentDetectorExample ${OTB_LIBRARIES})
+
+ add_executable(RightAngleDetectionExample RightAngleDetectionExample.cxx)
+ target_link_libraries(RightAngleDetectionExample ${OTB_LIBRARIES})
endif()
add_executable(LocalHoughExample LocalHoughExample.cxx)
@@ -53,17 +62,9 @@ target_link_libraries(LocalHoughExample ${OTB_LIBRARIES})
add_executable(PanTexExample PanTexExample.cxx)
target_link_libraries(PanTexExample ${OTB_LIBRARIES})
-add_executable(ParallelLineDetectionExample ParallelLineDetectionExample.cxx)
-target_link_libraries(ParallelLineDetectionExample ${OTB_LIBRARIES})
-
add_executable(RatioLineDetectorExample RatioLineDetectorExample.cxx)
target_link_libraries(RatioLineDetectorExample ${OTB_LIBRARIES})
-if (Module_OTBVectorDataRendering AND OTB_USE_MAPNIK)
- add_executable(RightAngleDetectionExample RightAngleDetectionExample.cxx)
- target_link_libraries(RightAngleDetectionExample ${OTB_LIBRARIES})
-endif()
-
add_executable(SeamCarvingExample SeamCarvingExample.cxx)
target_link_libraries(SeamCarvingExample ${OTB_LIBRARIES})
diff --git a/Examples/FeatureExtraction/test/CMakeLists.txt b/Examples/FeatureExtraction/test/CMakeLists.txt
index 9e351acd2adf21b663afe76885b8baf7d868e91e..b748caca32cb41a2726011dc662e4836b98b86c2 100644
--- a/Examples/FeatureExtraction/test/CMakeLists.txt
+++ b/Examples/FeatureExtraction/test/CMakeLists.txt
@@ -107,7 +107,7 @@ otb_add_test(NAME feTeRatioLineDetectorExampleTest COMMAND ${OTB_TEST_DRIVER}
)
# ------- AlignmentsExampleTest----------
-
+if(OTBMathParser_LOADED)
otb_add_test(NAME feTeAlignmentsExampleTest COMMAND ${OTB_TEST_DRIVER}
--compare-n-images ${NOTOL} 1
${BASELINE}/QB_SuburbAlign.png
@@ -145,6 +145,8 @@ otb_add_test(NAME feTeExtractRoadExampleTest COMMAND ${OTB_TEST_DRIVER}
337 557 432 859 1.0 0.00005 1.0 0.39269 1.0 10.0 25.
)
+endif()
+
# ------- SeamCarvingExamplesTest----------
otb_add_test(NAME feTeSeamCarvingExampleTest COMMAND ${OTB_TEST_DRIVER}
diff --git a/Examples/IO/CMakeLists.txt b/Examples/IO/CMakeLists.txt
index a3d9b9063fee339286f5cc7b487d49560cf437d1..b4395d43a10ab34ded19381a315d54c89537d8a5 100644
--- a/Examples/IO/CMakeLists.txt
+++ b/Examples/IO/CMakeLists.txt
@@ -30,8 +30,10 @@ target_link_libraries(ImageReadWrite ${OTB_LIBRARIES})
add_executable(ImageSeriesIOExample ImageSeriesIOExample.cxx)
target_link_libraries(ImageSeriesIOExample ${OTB_LIBRARIES})
+if(OTBlibkml_LOADED)
add_executable(ImageToKmzAndMapFileProductExample ImageToKmzAndMapFileProductExample.cxx)
target_link_libraries(ImageToKmzAndMapFileProductExample ${OTB_LIBRARIES})
+endif()
add_executable(MetadataExample MetadataExample.cxx)
target_link_libraries(MetadataExample ${OTB_LIBRARIES})
diff --git a/Examples/IO/test/CMakeLists.txt b/Examples/IO/test/CMakeLists.txt
index d75692eee9a507dd0f5587cf7b209beabfef4565..720b16203b632a95e2d850822f5d722a875c9653 100644
--- a/Examples/IO/test/CMakeLists.txt
+++ b/Examples/IO/test/CMakeLists.txt
@@ -43,6 +43,7 @@ otb_add_test(NAME prTeDEMHandlerExampleTest COMMAND ${OTB_TEST_DRIVER}
0.001
)
+if(OTBlibkml_LOADED)
otb_add_test(NAME ioTeImageToKmzAndMapFileProductExample COMMAND ${OTB_TEST_DRIVER}
Execute $<TARGET_FILE:ImageToKmzAndMapFileProductExample>
${OTB_DATA_ROOT}/Input/Haiti1_sr10.jpeg
@@ -78,6 +79,7 @@ otb_add_test(NAME ioTeImageToKmzAndMapFileProductExample COMMAND ${OTB_TEST_DRIV
42.000000 232.000000 -72.426552 18.540876 0.000000
)
set_property(TEST ioTeImageToKmzAndMapFileProductExample PROPERTY RESOURCE_LOCK web_access)
+endif()
otb_add_test(NAME ioTeTileMapImageIOExampleTest COMMAND ${OTB_TEST_DRIVER}
--compare-image 10.0
diff --git a/Examples/Learning/CMakeLists.txt b/Examples/Learning/CMakeLists.txt
index 4963ecaed02cf4ac4a55240d66352d464e04d13b..cbf51262616e251ee86d0bd3c921ac35cd7b4d92 100644
--- a/Examples/Learning/CMakeLists.txt
+++ b/Examples/Learning/CMakeLists.txt
@@ -12,6 +12,7 @@ target_link_libraries(SOMClassifierExample ${OTB_LIBRARIES})
add_executable(SOMExample SOMExample.cxx)
target_link_libraries(SOMExample ${OTB_LIBRARIES})
+if(OTBLibSVM_LOADED)
add_executable(SVMImageClassificationExample SVMImageClassificationExample.cxx)
target_link_libraries(SVMImageClassificationExample ${OTB_LIBRARIES})
@@ -29,13 +30,15 @@ target_link_libraries(SVMPointSetExample ${OTB_LIBRARIES})
add_executable(SVMPointSetModelEstimatorExample SVMPointSetModelEstimatorExample.cxx)
target_link_libraries(SVMPointSetModelEstimatorExample ${OTB_LIBRARIES})
+endif()
+if(OTBOpenCV_LOADED)
add_executable(TrainMachineLearningModelFromImagesExample TrainMachineLearningModelFromImagesExample.cxx)
target_link_libraries(TrainMachineLearningModelFromImagesExample ${OTB_LIBRARIES})
add_executable(TrainMachineLearningModelFromSamplesExample TrainMachineLearningModelFromSamplesExample.cxx)
target_link_libraries(TrainMachineLearningModelFromSamplesExample ${OTB_LIBRARIES})
-
+endif()
if(BUILD_TESTING)
add_subdirectory(test)
diff --git a/Examples/Learning/SEMModelEstimatorExample.cxx b/Examples/Learning/SEMModelEstimatorExample.cxx
index bb396e906359cb004045e14364768c9dd1657c49..86f3e58f967d80e4c73031f65bd4ad32af0b87e6 100644
--- a/Examples/Learning/SEMModelEstimatorExample.cxx
+++ b/Examples/Learning/SEMModelEstimatorExample.cxx
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) GET / ENST Bretagne. All rights reserved.
- See GETCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Examples/Learning/SOMExample.cxx b/Examples/Learning/SOMExample.cxx
index 056820dd406bd89e45b4dcfb03e98a413e999487..3f56132f43b30be9ecbaeb790f6f1f38b8e8f6ae 100644
--- a/Examples/Learning/SOMExample.cxx
+++ b/Examples/Learning/SOMExample.cxx
@@ -10,7 +10,7 @@
See OTBCopyright.txt for details.
Copyright (c) Institut Telecom; Telecom Bretagne. All rights reserved.
- See GETCopyright.txt for details.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Examples/Learning/SVMGenericKernelImageClassificationExample.cxx b/Examples/Learning/SVMGenericKernelImageClassificationExample.cxx
index e11095a98a716d217f337f4a825db1f3caa308dc..765fe1530831621159d1d11ddbdcb207419961a0 100644
--- a/Examples/Learning/SVMGenericKernelImageClassificationExample.cxx
+++ b/Examples/Learning/SVMGenericKernelImageClassificationExample.cxx
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) GET / ENST Bretagne. All rights reserved.
- See GETCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Examples/Learning/SVMGenericKernelImageModelEstimatorExample.cxx b/Examples/Learning/SVMGenericKernelImageModelEstimatorExample.cxx
index 1e411f9cb66bc1ccc22577cf69d1b94c5a66441e..61494ba7c9b46ac17a52bec3ceac83f83ca1d5d5 100644
--- a/Examples/Learning/SVMGenericKernelImageModelEstimatorExample.cxx
+++ b/Examples/Learning/SVMGenericKernelImageModelEstimatorExample.cxx
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) GET / ENST Bretagne. All rights reserved.
- See GETCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Examples/Learning/test/CMakeLists.txt b/Examples/Learning/test/CMakeLists.txt
index d3918e252e6901babd9924b0dc092e302acc99fb..71e51049f8a57ffdca32b7606c1bcc034e7e467f 100644
--- a/Examples/Learning/test/CMakeLists.txt
+++ b/Examples/Learning/test/CMakeLists.txt
@@ -3,6 +3,7 @@ set(INPUTDATA ${OTB_DATA_ROOT}/Examples)
# ------- SVMImageClassificationExampleTest----------
+if(OTBLibSVM_LOADED)
otb_add_test(NAME leTeSVMImageClassificationExampleTest COMMAND ${OTB_TEST_DRIVER}
--compare-n-images ${NOTOL} 1
${BASELINE}/ROI_QB_MUL_1_SVN_CLASS.png
@@ -26,18 +27,6 @@ otb_add_test(NAME leTeSVMImageEstimatorClassificationMultiExampleTest COMMAND ${
${TEMP}/ROI_QB_MUL_1_SVN_CLASS_MULTI_Rescaled.png
)
-# ------- GenerateTrainingImageExampleTest----------
-
-otb_add_test(NAME leTeGenerateTrainingImageExampleTest COMMAND ${OTB_TEST_DRIVER}
- --compare-n-images ${NOTOL} 1
- ${BASELINE}/ROI_QB_MUL_4_training.png
- ${TEMP}/ROI_QB_MUL_4_training.png
- Execute $<TARGET_FILE:GenerateTrainingImageExample>
- ${INPUTDATA}/ROI_QB_MUL_4.tif
- ${INPUTDATA}/LearningROIs.txt
- ${TEMP}/ROI_QB_MUL_4_training.png
-)
-
# ------- SVMImageModelEstimatorExampleTest----------
otb_add_test(NAME leTeSVMImageModelEstimatorExampleTest COMMAND ${OTB_TEST_DRIVER}
@@ -51,6 +40,18 @@ otb_add_test(NAME leTeSVMImageModelEstimatorExampleTest COMMAND ${OTB_TEST_DRIVE
${TEMP}/svm_image_model.svn
)
+endif()
+# ------- GenerateTrainingImageExampleTest----------
+
+otb_add_test(NAME leTeGenerateTrainingImageExampleTest COMMAND ${OTB_TEST_DRIVER}
+ --compare-n-images ${NOTOL} 1
+ ${BASELINE}/ROI_QB_MUL_4_training.png
+ ${TEMP}/ROI_QB_MUL_4_training.png
+ Execute $<TARGET_FILE:GenerateTrainingImageExample>
+ ${INPUTDATA}/ROI_QB_MUL_4.tif
+ ${INPUTDATA}/LearningROIs.txt
+ ${TEMP}/ROI_QB_MUL_4_training.png
+)
# ------- SOMExampleTest----------
diff --git a/Examples/OBIA/CMakeLists.txt b/Examples/OBIA/CMakeLists.txt
index 202bd7ae29ce81a684e3b81211dd9ba8b3ff1cca..d2f7a79be47c7627549c03ac3f633fdaafb88fa9 100644
--- a/Examples/OBIA/CMakeLists.txt
+++ b/Examples/OBIA/CMakeLists.txt
@@ -12,8 +12,10 @@ target_link_libraries(KeepNObjects ${OTB_LIBRARIES})
add_executable(LabelMapToVectorData LabelMapToVectorData.cxx)
target_link_libraries(LabelMapToVectorData ${OTB_LIBRARIES})
+if(OTBMathParser_LOADED)
add_executable(RadiometricAttributesLabelMapFilterExample RadiometricAttributesLabelMapFilterExample.cxx)
target_link_libraries(RadiometricAttributesLabelMapFilterExample ${OTB_LIBRARIES})
+endif()
add_executable(ShapeAttributeComputation ShapeAttributeComputation.cxx)
target_link_libraries(ShapeAttributeComputation ${OTB_LIBRARIES})
diff --git a/Examples/OBIA/test/CMakeLists.txt b/Examples/OBIA/test/CMakeLists.txt
index 83a32c6339f4503a4fe36a72e982a6ea9bb559a5..f3c92b30ea3d96bd545bc5c333539db8274a8c5a 100644
--- a/Examples/OBIA/test/CMakeLists.txt
+++ b/Examples/OBIA/test/CMakeLists.txt
@@ -22,6 +22,7 @@ otb_add_test(NAME trTeOBIAShapeAttributeComputationTest COMMAND ${OTB_TEST_DRIVE
${TEMP}/OBIAShapeAttribute.txt
)
+if(OTBMathParser_LOADED)
otb_add_test(NAME trTeOBIARadiometricAttributesLabelMapFilterTest COMMAND ${OTB_TEST_DRIVER}
--compare-image ${NOTOL}
${BASELINE}/OBIARadiometricAttributes.png
@@ -38,6 +39,7 @@ otb_add_test(NAME trTeOBIARadiometricAttributesLabelMapFilterTest COMMAND ${OTB_
50
1.0
)
+endif()
otb_add_test(NAME trTeLabelMapToVectorData COMMAND ${OTB_TEST_DRIVER}
Execute $<TARGET_FILE:LabelMapToVectorData>
diff --git a/Examples/Patented/CMakeLists.txt b/Examples/Patented/CMakeLists.txt
index 07210c89bb2bc23db170f3b3d57925bfca0143c3..8648e956aa89809bf1eb6c47c21b1a3436fd0ddf 100644
--- a/Examples/Patented/CMakeLists.txt
+++ b/Examples/Patented/CMakeLists.txt
@@ -3,18 +3,18 @@ project(PatentedExamples)
add_executable(EstimateAffineTransformationExample EstimateAffineTransformationExample.cxx)
target_link_libraries(EstimateAffineTransformationExample ${OTB_LIBRARIES})
+if (OTBSiftFast_LOADED)
add_executable(SIFTDisparityMapEstimation SIFTDisparityMapEstimation.cxx)
target_link_libraries(SIFTDisparityMapEstimation ${OTB_LIBRARIES})
add_executable(SIFTExample SIFTExample.cxx)
target_link_libraries(SIFTExample ${OTB_LIBRARIES})
-if (Module_OTBSiftFast)
- add_executable(SIFTDensityExample SIFTDensityExample.cxx)
- target_link_libraries(SIFTDensityExample ${OTB_LIBRARIES})
+add_executable(SIFTDensityExample SIFTDensityExample.cxx)
+target_link_libraries(SIFTDensityExample ${OTB_LIBRARIES})
- add_executable(SIFTFastExample SIFTFastExample.cxx)
- target_link_libraries(SIFTFastExample ${OTB_LIBRARIES})
+add_executable(SIFTFastExample SIFTFastExample.cxx)
+target_link_libraries(SIFTFastExample ${OTB_LIBRARIES})
endif()
if(BUILD_TESTING)
diff --git a/Examples/Projections/test/CMakeLists.txt b/Examples/Projections/test/CMakeLists.txt
index 768d49630df27a20cf546cbf0dc2e9422ec8640a..fad74a593fa3d4bde04cde96b541e4be13827c86 100644
--- a/Examples/Projections/test/CMakeLists.txt
+++ b/Examples/Projections/test/CMakeLists.txt
@@ -48,7 +48,7 @@ otb_add_test(NAME prTeVectorDataProjectionExampleTest COMMAND ${OTB_TEST_DRIVER}
${BASELINE}/vectorDataProjectionExample.shp
${TEMP}/vectorDataProjectionExample.shp
Execute $<TARGET_FILE:VectorDataProjectionExample>
- ${OTB_DATA_ROOT}/Examples/Capitole-Shadows.kml
+ ${OTB_DATA_ROOT}/Input/Capitole-Shadows.kml
LARGEINPUT{QUICKBIRD/TOULOUSE/000000128955_01_P001_PAN/02APR01105228-P1BS-000000128955_01_P001.TIF}
${TEMP}/vectorDataProjectionExample.shp
)
@@ -58,7 +58,7 @@ otb_add_test(NAME prTeGeometriesProjectionTest COMMAND ${OTB_TEST_DRIVER}
${BASELINE}/geometriesProjectionExample.shp
${TEMP}/geometriesProjectionExample.shp
Execute $<TARGET_FILE:GeometriesProjectionExample>
- ${OTB_DATA_ROOT}/Examples/Capitole-Shadows.shp
+ ${OTB_DATA_ROOT}/Input/Capitole-Shadows.shp
LARGEINPUT{QUICKBIRD/TOULOUSE/000000128955_01_P001_PAN/02APR01105228-P1BS-000000128955_01_P001.TIF}
${TEMP}/geometriesProjectionExample.shp
)
@@ -88,6 +88,10 @@ otb_add_test(NAME prTeEstimateRPCSensorModelExampleTest COMMAND ${OTB_TEST_DRIVE
2803 1942 -22.958868 -42.808235 0.
980 2734 -22.99534 -43.309672 0.
713 2754 -23.007862 -43.365307 0.
+ 72 2955 -23.012153 -43.541331 0.
+ 2884 1898 -22.954691 -42.786188 0.
+ 2539 47 -22.616041 -42.777877 0.
+ 577 183 -22.551654 -43.271813 0.
)
otb_add_test(NAME prTePlaceNameToLonLatExampleTest COMMAND ${OTB_TEST_DRIVER}
diff --git a/Examples/Radiometry/CMakeLists.txt b/Examples/Radiometry/CMakeLists.txt
index 1c1e1bd3de3339396735c49983ca9509886d2c69..48c5d40d071238dd5dcd547fe80ac56f095adb08 100644
--- a/Examples/Radiometry/CMakeLists.txt
+++ b/Examples/Radiometry/CMakeLists.txt
@@ -3,8 +3,11 @@ project(RadiometryExamples)
add_executable(ARVIMultiChannelRAndBAndNIRVegetationIndexImageFilter ARVIMultiChannelRAndBAndNIRVegetationIndexImageFilter.cxx)
target_link_libraries(ARVIMultiChannelRAndBAndNIRVegetationIndexImageFilter ${OTB_LIBRARIES})
+#OTBOpticalCalibration -> OTB6S
+if(OTB6S_LOADED)
add_executable(AtmosphericCorrectionSequencement AtmosphericCorrectionSequencement.cxx)
target_link_libraries(AtmosphericCorrectionSequencement ${OTB_LIBRARIES})
+endif()
add_executable(AVIMultiChannelRAndGAndNIRVegetationIndexImageFilter AVIMultiChannelRAndGAndNIRVegetationIndexImageFilter.cxx)
target_link_libraries(AVIMultiChannelRAndGAndNIRVegetationIndexImageFilter ${OTB_LIBRARIES})
diff --git a/Examples/Radiometry/test/CMakeLists.txt b/Examples/Radiometry/test/CMakeLists.txt
index ff18563ad9aff969b7e84a237a1efd7377c6235e..b77c8c87e51835fe4d227fbed00b77c68f78075c 100644
--- a/Examples/Radiometry/test/CMakeLists.txt
+++ b/Examples/Radiometry/test/CMakeLists.txt
@@ -52,6 +52,7 @@ otb_add_test(NAME raTeNDVIRAndNIRVegetationIndexImageFilterTest COMMAND ${OTB_TE
${TEMP}/NDVIRAndNIRVegetationIndex4.tif
)
+if(OTBOpticalCalibration_LOADED)
otb_add_test(NAME raTeAtmosphericCorrectionSequencementTest COMMAND ${OTB_TEST_DRIVER}
--compare-image ${EPSILON_8}
${BASELINE}/Example_RomaniaAtmosphericCorrectionSequencement.tif
@@ -82,3 +83,4 @@ otb_add_test(NAME raTeAtmosphericCorrectionSequencementTest COMMAND ${OTB_TEST_D
2 # Radius;
0.020 # pixel spacing in kilometers
)
+endif()
\ No newline at end of file
diff --git a/Examples/Segmentation/CMakeLists.txt b/Examples/Segmentation/CMakeLists.txt
index 4fb4b89300757a0a24a675165264b9dacfbc83e0..c8cda537c20a206fbb46e6b670948e1edfb0313b 100644
--- a/Examples/Segmentation/CMakeLists.txt
+++ b/Examples/Segmentation/CMakeLists.txt
@@ -24,8 +24,10 @@ target_link_libraries(OtsuMultipleThresholdImageFilter ${OTB_LIBRARIES})
add_executable(OtsuThresholdImageFilter OtsuThresholdImageFilter.cxx)
target_link_libraries(OtsuThresholdImageFilter ${OTB_LIBRARIES})
-add_executable(StreamingMeanShiftSegmentation StreamingMeanShiftSegmentation.cxx)
-target_link_libraries(StreamingMeanShiftSegmentation ${OTB_LIBRARIES})
+if(OTBMathParser_LOADED)
+ add_executable(StreamingMeanShiftSegmentation StreamingMeanShiftSegmentation.cxx)
+ target_link_libraries(StreamingMeanShiftSegmentation ${OTB_LIBRARIES})
+endif()
add_executable(VectorConfidenceConnected VectorConfidenceConnected.cxx)
target_link_libraries(VectorConfidenceConnected ${OTB_LIBRARIES})
diff --git a/Examples/Segmentation/test/CMakeLists.txt b/Examples/Segmentation/test/CMakeLists.txt
index d43f19ecf89f64747f546278e5a09bb23e6806c2..37d36f1ca5f27611eb1e31dd3951dd2bc56ceb4b 100644
--- a/Examples/Segmentation/test/CMakeLists.txt
+++ b/Examples/Segmentation/test/CMakeLists.txt
@@ -272,7 +272,7 @@ otb_add_test(NAME seTeLabelizeNeighborhoodConnectedImageFilterTest COMMAND ${OTB
# ------- StreamingMeanShiftSegmentationTest ----------
-
+if(OTBMathParser_LOADED)
otb_add_test(NAME seTeStreamingMeanShiftSegmentationTest COMMAND ${OTB_TEST_DRIVER}
# --compare-ogr ${NOTOL}
# ${BASELINE_FILES}/seTeStreamingMeanShiftSegmentationTest.shp
@@ -291,3 +291,4 @@ otb_add_test(NAME seTeStreamingMeanShiftSegmentationTest COMMAND ${OTB_TEST_DRIV
1 #Simplify Flag
0.2 #Simplification tolerance
)
+endif()
\ No newline at end of file
diff --git a/Examples/Simulation/CMakeLists.txt b/Examples/Simulation/CMakeLists.txt
index ece736e87f61817c03a96ce358eebac6c368f355..0e0bc86b13a38327a5e71324c4972491e85c076e 100644
--- a/Examples/Simulation/CMakeLists.txt
+++ b/Examples/Simulation/CMakeLists.txt
@@ -1,14 +1,16 @@
project(SimulationExamples)
+#OTBSimulation -> OTBOpticalCalibration -> OTB6S
+if(OTB6S_LOADED)
add_executable(LAIAndPROSAILToSensorResponse LAIAndPROSAILToSensorResponse.cxx)
target_link_libraries(LAIAndPROSAILToSensorResponse ${OTB_LIBRARIES})
-add_executable(LAIFromNDVIImageTransform LAIFromNDVIImageTransform.cxx)
-target_link_libraries(LAIFromNDVIImageTransform ${OTB_LIBRARIES})
-
add_executable(ProsailModel ProsailModel.cxx)
target_link_libraries(ProsailModel ${OTB_LIBRARIES})
+endif()
+add_executable(LAIFromNDVIImageTransform LAIFromNDVIImageTransform.cxx)
+target_link_libraries(LAIFromNDVIImageTransform ${OTB_LIBRARIES})
if(BUILD_TESTING)
add_subdirectory(test)
diff --git a/Examples/Simulation/test/CMakeLists.txt b/Examples/Simulation/test/CMakeLists.txt
index eed146c98e2e69eb94b99f1bda805b50254f4821..9cb0323021507d2671a12e1af58e015a5d4a796d 100644
--- a/Examples/Simulation/test/CMakeLists.txt
+++ b/Examples/Simulation/test/CMakeLists.txt
@@ -3,6 +3,8 @@ set(INPUTDATA ${OTB_DATA_ROOT}/Examples)
# ------- ProsailModelExampleTest ----------
+#OTBSimulation -> OTBOpticalCalibration -> OTB6S
+if(OTB6S_LOADED)
otb_add_test(NAME siTvProsailModelExampleTest COMMAND ${OTB_TEST_DRIVER}
--compare-ascii ${EPSILON_3}
${BASELINE}/siTvProsailModelExampleTest.txt
@@ -25,20 +27,6 @@ otb_add_test(NAME siTvProsailModelExampleTest COMMAND ${OTB_TEST_DRIVER}
${TEMP}/siTvProsailModelExampleTest.txt
)
-
-otb_add_test(NAME siTvLAIFromNDVIImageTransfromExampleTest COMMAND ${OTB_TEST_DRIVER}
- --compare-image ${EPSILON_8}
- ${OTB_DATA_ROOT}/Baseline/OTB/Images/raRAndNIRVegetationIndex_LAIFromNDVIFormosat2_verySmallFSATSWcRcNir.tif
- ${TEMP}/siTvLAIFromNDVIImageTransfromExampleTest_verySmallFSATSW.tif
- Execute $<TARGET_FILE:LAIFromNDVIImageTransform>
- ${INPUTDATA}/verySmallFSATSW.tif
- ${TEMP}/siTvLAIFromNDVIImageTransfromExampleTest_verySmallFSATSW.tif
- ${TEMP}/verySmallFSATSW_visu.png
- ${TEMP}/siTvLAIFromNDVIImageTransfromExampleTest_verySmallFSATSW_visu.png
- 1 # red
- 4 # nir
-)
-
otb_add_test(NAME siTvLAIAndPROSAILToSensorResponseExampleTest COMMAND ${OTB_TEST_DRIVER}
--compare-image ${EPSILON_8}
${OTBAPP_BASELINE}/siTvLAIAndPROSAILToSensorResponseSmall.tif
@@ -54,3 +42,18 @@ Execute $<TARGET_FILE:LAIAndPROSAILToSensorResponse>
5
${OTB_DATA_ROOT}/Input/
)
+
+endif()
+
+otb_add_test(NAME siTvLAIFromNDVIImageTransfromExampleTest COMMAND ${OTB_TEST_DRIVER}
+ --compare-image ${EPSILON_8}
+ ${OTB_DATA_ROOT}/Baseline/OTB/Images/raRAndNIRVegetationIndex_LAIFromNDVIFormosat2_verySmallFSATSWcRcNir.tif
+ ${TEMP}/siTvLAIFromNDVIImageTransfromExampleTest_verySmallFSATSW.tif
+ Execute $<TARGET_FILE:LAIFromNDVIImageTransform>
+ ${INPUTDATA}/verySmallFSATSW.tif
+ ${TEMP}/siTvLAIFromNDVIImageTransfromExampleTest_verySmallFSATSW.tif
+ ${TEMP}/verySmallFSATSW_visu.png
+ ${TEMP}/siTvLAIFromNDVIImageTransfromExampleTest_verySmallFSATSW_visu.png
+ 1 # red
+ 4 # nir
+)
diff --git a/Modules/Adapters/BoostAdapters/include/otbStringUtils.h b/Modules/Adapters/BoostAdapters/include/otbStringUtils.h
new file mode 100644
index 0000000000000000000000000000000000000000..9c675f695fd19226845e538a84e4c6a4cba3cd7b
--- /dev/null
+++ b/Modules/Adapters/BoostAdapters/include/otbStringUtils.h
@@ -0,0 +1,130 @@
+/*=========================================================================
+
+ Program: ORFEO Toolbox
+ Language: C++
+ Date: $Date$
+ Version: $Revision$
+
+
+ Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
+ See OTBCopyright.txt for details.
+
+
+ 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.
+
+=========================================================================*/
+#ifndef otbStringUtils_h
+#define otbStringUtils_h
+
+#include <string>
+#include <vector>
+#include <limits>
+#include <stdexcept>
+#include <boost/lexical_cast.hpp>
+#include <boost/algorithm/string.hpp>
+#include <boost/algorithm/string/predicate.hpp>
+#include <boost/utility/enable_if.hpp>
+
+namespace otb
+{
+namespace Utils
+{
+template <typename Res, typename In >
+inline
+Res LexicalCast(In const& in, std::string const& kind) {
+ try
+ {
+ return boost::lexical_cast<Res>(in);
+ }
+ catch (boost::bad_lexical_cast &) {
+ std::ostringstream oss;
+ oss << "Cannot decode " << in << " as this is not a valid value for " << kind;
+ throw std::runtime_error(oss.str());
+ }
+}
+
+/**\ingroup Utils
+ * Converts a delimiter separated string into a collection of \c T's.
+ * \tparam Collection type. It shall define \c value_type and \c push_back()
+ * \param[out] ret output collection.
+ * \param[in] str input string
+ * \param[in] errmsg a msg complement used to build the error message to
+be shown if there is \c lexical_cast exception. See \c
+otb:Utils::LexicalCast().
+ * \param delims delimitter characters (space is default)
+ * \throw std::bad_alloc in case of exhausted memory
+ * \throw std::runtime_error in case an element from the input string
+cannot be converted into a valid \c T instance.
+ * \pre delims shall not be null (untested)
+ *
+ * \see \c otb::Utils::LexicalCast()
+ */
+template<typename T>
+void
+ConvertStringToVector(std::string const &str, T& ret, std::string const& errmsg, const char * delims=" ")
+{
+ typedef std::vector<boost::iterator_range<std::string::const_iterator> > ListType;
+
+ ListType splitted;
+
+ boost::split(splitted, str, boost::is_any_of(delims));
+
+ for(size_t i = 0; i < splitted.size(); i++)
+ {
+ typename T::value_type value = LexicalCast<typename T::value_type> (splitted[i], errmsg);
+ ret.push_back(value);
+ }
+}
+
+/**\ingroup Utils
+ * split a given std::string of into key value based on given delimitter
+ * string. default delimitter is '='. If the string does not have a delimitter
+ * the key is set to input string and value is set to defValue.
+ * \param[in] str input string
+ * \param key[out] An std::string reference where key will be stored
+ * \param value[out] a reference of \cT where value will be stored
+ * \param defValue[in] a default value if there is no delimitter fo
+ * \param[in] errmsg a msg complement used to build the error message to
+be shown if there is \c lexical_cast exception. See \cotb:Utils::LexicalCast().
+ * \param delims delimitter characters (space is default)
+ * \throw std::bad_alloc in case of exhausted memory
+ * \throw std::runtime_error in case an element from the input string
+cannot be converted into a valid \c T instance.
+ * \pre delims shall not be null (untested)
+ *
+ * \see \c otb::Utils::LexicalCast()
+ */
+template<typename T>
+void SplitStringToSingleKeyValue(const std::string& str,
+ std::string& key, T& value, const T& defValue,
+ std::string const& errmsg, const std::string delims="=")
+{
+
+ typedef boost::iterator_range<std::string::const_iterator> BoostRangeIteratorType;
+ typedef std::list< BoostRangeIteratorType > ListType;
+
+ ListType splitted;
+
+ boost::split( splitted, str, boost::is_any_of(delims), boost::token_compress_on );
+
+ typename ListType::iterator it = splitted.begin();
+ BoostRangeIteratorType kIt = boost::trim_copy((*it));
+ key.assign( kIt.begin(), kIt.end());
+ ++it;
+
+ if( it != splitted.end())
+ {
+ value = LexicalCast<T>(boost::trim_copy(*it), errmsg);
+ ++it;
+ }
+ else
+ {
+ value = defValue;
+ }
+}
+} // end namespace Utils
+} // end namespace otb
+
+#endif //otbStringUtils_h
diff --git a/Modules/Adapters/OSSIMAdapters/include/otbDEMHandler.h b/Modules/Adapters/OSSIMAdapters/include/otbDEMHandler.h
index 528144e916d3c06135cdb501bd37487718c5042d..7e51a0c79178a1e1e0489cd45eb0c797e6311343 100644
--- a/Modules/Adapters/OSSIMAdapters/include/otbDEMHandler.h
+++ b/Modules/Adapters/OSSIMAdapters/include/otbDEMHandler.h
@@ -107,9 +107,29 @@ public:
/** return true if the directoty contain DEM */
virtual bool IsValidDEMDirectory(const char* DEMDirectory);
- /** Open geoid file. */
- virtual void OpenGeoidFile(const char* geoidFile);
- virtual void OpenGeoidFile(const std::string& geoidFile);
+ /**
+ * \brief Open geoid file given its filename or throw an exception
+ * if geoid-file could not be loaded.
+ *
+ * \param geoidFile The filename of the geoid-file.
+ *
+ * \return <code>true</code> if geoid file has been changed or
+ * <code>false</code> if geod-file have been set before and could
+ * not be changed.
+ */
+ virtual bool OpenGeoidFile(const char* geoidFile);
+
+ /**
+ * \brief Open geoid file given its filename or throw an exception
+ * if geoid-file could not be loaded.
+ *
+ * \param geoidFile The filename of the geoid-file.
+ *
+ * \return <code>true</code> if geoid file has been changed or
+ * <code>false</code> if geod-file have been set before and could
+ * not be changed.
+ */
+ virtual bool OpenGeoidFile(const std::string& geoidFile);
/** Compute the height above MSL(Mean Sea Level) of a geographic point. */
virtual double GetHeightAboveMSL(double lon, double lat) const;
@@ -125,6 +145,11 @@ public:
/** Set the default height above ellipsoid in case no information is available*/
double GetDefaultHeightAboveEllipsoid() const;
+ /**
+ * \return The number of elevation databases in the
+ * <code>ossimElevManager</code>.
+ */
+ unsigned int GetDEMCount() const;
/** Get DEM directory */
std::string GetDEMDirectory(unsigned int idx = 0) const;
@@ -132,14 +157,18 @@ public:
/** Get Goid file */
std::string GetGeoidFile() const;
+ /**
+ * \brief Remove all the ossimElevationDatabases from the
+ * <code>ossimElevManager</code>.
+ */
+ void ClearDEMs();
+
protected:
DEMHandler();
virtual ~DEMHandler() {}
void PrintSelf(std::ostream& os, itk::Indent indent) const;
- ossimElevManager* m_ElevManager;
-
// Ossim does not allow to retrieve the geoid file path
// We therefore must keep it on our side
std::string m_GeoidFile;
diff --git a/Modules/Adapters/OSSIMAdapters/src/otbDEMHandler.cxx b/Modules/Adapters/OSSIMAdapters/src/otbDEMHandler.cxx
index 79b352417c22648288dc5a537bf99707a5f24a09..71b94952260fdcba5b6ed9f65a784976b1eaa3e1 100644
--- a/Modules/Adapters/OSSIMAdapters/src/otbDEMHandler.cxx
+++ b/Modules/Adapters/OSSIMAdapters/src/otbDEMHandler.cxx
@@ -18,6 +18,8 @@
#include "otbDEMHandler.h"
#include "otbMacro.h"
+#include <cassert>
+
#include "ossim/elevation/ossimElevManager.h"
#include "ossim/base/ossimGeoidManager.h"
#include "ossim/base/ossimFilename.h"
@@ -49,23 +51,25 @@ DEMHandler::Pointer DEMHandler::Instance()
DEMHandler
::DEMHandler() :
- m_ElevManager(ossimElevManager::instance()),
m_GeoidFile(""),
m_DefaultHeightAboveEllipsoid(0)
{
- m_ElevManager->setDefaultHeightAboveEllipsoid(m_DefaultHeightAboveEllipsoid);
+ assert( ossimElevManager::instance()!=NULL );
+
+ ossimElevManager::instance()->setDefaultHeightAboveEllipsoid(m_DefaultHeightAboveEllipsoid);
// Force geoid fallback
- m_ElevManager->setUseGeoidIfNullFlag(true);
+ ossimElevManager::instance()->setUseGeoidIfNullFlag(true);
}
void
DEMHandler
::OpenDEMDirectory(const char* DEMDirectory)
{
- ossimFilename ossimDEMDir;
- ossimDEMDir = ossimFilename(DEMDirectory);
+ assert( ossimElevManager::instance()!=NULL );
+
+ ossimFilename ossimDEMDir( DEMDirectory );
- if (!m_ElevManager->loadElevationPath(ossimDEMDir))
+ if (!ossimElevManager::instance()->loadElevationPath(ossimDEMDir))
{
// In ossim elevation database factory code, the
// ossimImageElevationDatabase is explicitly disabled by a #if 0
@@ -82,11 +86,22 @@ DEMHandler
else
{
otbMsgDevMacro(<< "DEM directory contains general elevation image files: " << ossimDEMDir);
- m_ElevManager->addDatabase(imageElevationDatabase.get());
+ ossimElevManager::instance()->addDatabase(imageElevationDatabase.get());
}
}
}
+
+void
+DEMHandler
+::ClearDEMs()
+{
+ assert( ossimElevManager::instance()!=NULL );
+
+ ossimElevManager::instance()->clear();
+}
+
+
void
DEMHandler
::OpenDEMDirectory(const std::string& DEMDirectory)
@@ -98,8 +113,10 @@ bool
DEMHandler
::IsValidDEMDirectory(const char* DEMDirectory)
{
+ assert( ossimElevManager::instance()!=NULL );
+
//Try to load elevation source
- bool result = m_ElevManager->loadElevationPath(DEMDirectory);
+ bool result = ossimElevManager::instance()->loadElevationPath(DEMDirectory);
if (!result)
{
@@ -111,7 +128,7 @@ DEMHandler
return result;
}
-void
+bool
DEMHandler
::OpenGeoidFile(const char* geoidFile)
{
@@ -131,22 +148,31 @@ DEMHandler
// The previous flag will be ignored if
// defaultHeightAboveEllipsoid is not NaN
- m_ElevManager->setDefaultHeightAboveEllipsoid(ossim::nan());
+ assert( ossimElevManager::instance()!=NULL );
+ ossimElevManager::instance()->setDefaultHeightAboveEllipsoid(ossim::nan());
+
+ return true;
}
else
{
otbMsgDevMacro(<< "Failure opening geoid");
geoidPtr.release();
+
+ itkExceptionMacro( << "Failed to open geoid file: '" << geoidFile << "'" );
+
+ return false;
}
}
+
+ return false;
}
-void
+bool
DEMHandler
::OpenGeoidFile(const std::string& geoidFile)
{
- OpenGeoidFile(geoidFile.c_str());
+ return OpenGeoidFile(geoidFile.c_str());
}
double
@@ -155,9 +181,14 @@ DEMHandler
{
double height;
ossimGpt ossimWorldPoint;
+
ossimWorldPoint.lon = lon;
ossimWorldPoint.lat = lat;
- height = m_ElevManager->getHeightAboveMSL(ossimWorldPoint);
+
+ assert( ossimElevManager::instance()!=NULL );
+
+ height = ossimElevManager::instance()->getHeightAboveMSL(ossimWorldPoint);
+
return height;
}
@@ -174,9 +205,13 @@ DEMHandler
{
double height;
ossimGpt ossimWorldPoint;
+
ossimWorldPoint.lon = lon;
ossimWorldPoint.lat = lat;
- height = m_ElevManager->getHeightAboveEllipsoid(ossimWorldPoint);
+
+ assert( ossimElevManager::instance()!=NULL );
+
+ height = ossimElevManager::instance()->getHeightAboveEllipsoid(ossimWorldPoint);
return height;
}
@@ -195,7 +230,10 @@ DEMHandler
// Ossim does not allow to retrieve the default height above
// ellipsoid We therefore must keep it on our side
m_DefaultHeightAboveEllipsoid = h;
- m_ElevManager->setDefaultHeightAboveEllipsoid(h);
+
+ assert( ossimElevManager::instance()!=NULL );
+
+ ossimElevManager::instance()->setDefaultHeightAboveEllipsoid(h);
}
double
@@ -207,13 +245,24 @@ DEMHandler
return m_DefaultHeightAboveEllipsoid;
}
+unsigned int
+DEMHandler
+::GetDEMCount() const
+{
+ assert( ossimElevManager::instance()!=NULL );
+
+ return ossimElevManager::instance()->getNumberOfElevationDatabases();
+}
+
std::string DEMHandler::GetDEMDirectory(unsigned int idx) const
{
std::string demDir = "";
- if(m_ElevManager->getNumberOfElevationDatabases() > 0)
+ if(ossimElevManager::instance()->getNumberOfElevationDatabases() > 0)
{
- demDir = m_ElevManager->getElevationDatabase(idx)->getConnectionString().string();
+ assert( ossimElevManager::instance()!=NULL );
+
+ demDir = ossimElevManager::instance()->getElevationDatabase(idx)->getConnectionString().string();
}
return demDir;
}
diff --git a/Modules/Adapters/OSSIMAdapters/src/otbImageKeywordlist.cxx b/Modules/Adapters/OSSIMAdapters/src/otbImageKeywordlist.cxx
index 0a0309e5f3dba0a46c02262d9a6529903f4fd798..98d873885e84be567549957fb78fa6985d72e2ee 100644
--- a/Modules/Adapters/OSSIMAdapters/src/otbImageKeywordlist.cxx
+++ b/Modules/Adapters/OSSIMAdapters/src/otbImageKeywordlist.cxx
@@ -139,41 +139,51 @@ bool
ImageKeywordlist::
convertToGDALRPC(GDALRPCInfo &rpc) const
{
- ossimKeywordlist geom_kwl;
-
- this->convertToOSSIMKeywordlist(geom_kwl);
-
- if( geom_kwl.hasKey("polynomial_format")) //RK
- {
- ossimRefPtr<ossimRpcModel> rpcModel = new ossimRpcModel;
- if (rpcModel->loadState(geom_kwl))
- {
- ossimRpcModel::rpcModelStruct ossimRpcStruct;
- rpcModel->getRpcParameters(ossimRpcStruct);
+ /* ossimRpcModel::loadState() actually expects certain keyword values to be
+ * present in the keywordlist. So We check a single keyword value
+ * (polynomial_format) first. Even though it is not enough to ensure a valid
+ * ossimRpcModel by checking for presence of one single key but atleast we
+ * are sure about not to create an ossimRpcModel.
+ *
+ * The current mechanism creates ossimRpcModel instance, calls loadState()
+ * and fails. The below check for 'polynomial_format' save us from creating
+ * an ossimRpcModel which will be invalid if the 'polynomial_format' is not
+ * present.
+ */
+ if( m_Keywordlist.find("polynomial_format") != m_Keywordlist.end() )
+ {
+ ossimKeywordlist geom_kwl;
+ this->convertToOSSIMKeywordlist(geom_kwl);
- if (ossimRpcStruct.type == 'B')
+ ossimRefPtr<ossimRpcModel> rpcModel = new ossimRpcModel;
+ if (rpcModel->loadState(geom_kwl))
{
- rpc.dfSAMP_OFF = ossimRpcStruct.sampOffset;
- rpc.dfLINE_OFF = ossimRpcStruct.lineOffset;
- rpc.dfSAMP_SCALE = ossimRpcStruct.sampScale;
- rpc.dfLINE_SCALE = ossimRpcStruct.lineScale;
- rpc.dfLAT_OFF = ossimRpcStruct.latOffset;
- rpc.dfLONG_OFF = ossimRpcStruct.lonOffset;
- rpc.dfHEIGHT_OFF = ossimRpcStruct.hgtOffset;
- rpc.dfLAT_SCALE = ossimRpcStruct.latScale;
- rpc.dfLONG_SCALE = ossimRpcStruct.lonScale;
- rpc.dfHEIGHT_SCALE = ossimRpcStruct.hgtScale;
-
- memcpy(rpc.adfLINE_NUM_COEFF, ossimRpcStruct.lineNumCoef, sizeof(double) * 20);
- memcpy(rpc.adfLINE_DEN_COEFF, ossimRpcStruct.lineDenCoef, sizeof(double) * 20);
- memcpy(rpc.adfSAMP_NUM_COEFF, ossimRpcStruct.sampNumCoef, sizeof(double) * 20);
- memcpy(rpc.adfSAMP_DEN_COEFF, ossimRpcStruct.sampDenCoef, sizeof(double) * 20);
-
- return true;
+ ossimRpcModel::rpcModelStruct ossimRpcStruct;
+ rpcModel->getRpcParameters(ossimRpcStruct);
+
+ if (ossimRpcStruct.type == 'B')
+ {
+ rpc.dfSAMP_OFF = ossimRpcStruct.sampOffset;
+ rpc.dfLINE_OFF = ossimRpcStruct.lineOffset;
+ rpc.dfSAMP_SCALE = ossimRpcStruct.sampScale;
+ rpc.dfLINE_SCALE = ossimRpcStruct.lineScale;
+ rpc.dfLAT_OFF = ossimRpcStruct.latOffset;
+ rpc.dfLONG_OFF = ossimRpcStruct.lonOffset;
+ rpc.dfHEIGHT_OFF = ossimRpcStruct.hgtOffset;
+ rpc.dfLAT_SCALE = ossimRpcStruct.latScale;
+ rpc.dfLONG_SCALE = ossimRpcStruct.lonScale;
+ rpc.dfHEIGHT_SCALE = ossimRpcStruct.hgtScale;
+
+ memcpy(rpc.adfLINE_NUM_COEFF, ossimRpcStruct.lineNumCoef, sizeof(double) * 20);
+ memcpy(rpc.adfLINE_DEN_COEFF, ossimRpcStruct.lineDenCoef, sizeof(double) * 20);
+ memcpy(rpc.adfSAMP_NUM_COEFF, ossimRpcStruct.sampNumCoef, sizeof(double) * 20);
+ memcpy(rpc.adfSAMP_DEN_COEFF, ossimRpcStruct.sampDenCoef, sizeof(double) * 20);
+
+ return true;
+ }
}
- }
- }
- return false;
+ }
+ return false;
}
void
diff --git a/Modules/Adapters/OSSIMAdapters/test/CMakeLists.txt b/Modules/Adapters/OSSIMAdapters/test/CMakeLists.txt
index d11608709f0552643a238bb01042453df869e9d2..42440cd9a65cea1d85f0099a6ba1760664f64e8e 100644
--- a/Modules/Adapters/OSSIMAdapters/test/CMakeLists.txt
+++ b/Modules/Adapters/OSSIMAdapters/test/CMakeLists.txt
@@ -441,6 +441,7 @@ otb_add_test(NAME uaTvDEMHandler_AboveEllipsoid_SRTM_BadGeoid COMMAND otbOSSIMAd
339.513
0.001
)
+set_property(TEST uaTvDEMHandler_AboveEllipsoid_SRTM_BadGeoid PROPERTY WILL_FAIL true)
otb_add_test(NAME uaTvDEMHandler_AboveMSL_SRTM_NoGeoid_NoData COMMAND otbOSSIMAdaptersTestDriver
otbDEMHandlerTest
diff --git a/Modules/Adapters/OSSIMAdapters/test/otbDEMHandlerTest.cxx b/Modules/Adapters/OSSIMAdapters/test/otbDEMHandlerTest.cxx
index 9987db6a5bcd5cd74ac0793cd8e5b0aaea5261f2..09ab37cf7c098c990a0668f176099eda0109ab94 100644
--- a/Modules/Adapters/OSSIMAdapters/test/otbDEMHandlerTest.cxx
+++ b/Modules/Adapters/OSSIMAdapters/test/otbDEMHandlerTest.cxx
@@ -59,7 +59,19 @@ int otbDEMHandlerTest(int argc, char * argv[])
if(geoid != "no")
{
- demHandler->OpenGeoidFile(geoid);
+ try
+ {
+ demHandler->OpenGeoidFile(geoid);
+ }
+ catch( const std::exception & exception )
+ {
+ std::cout
+ << "Exception thrown while opening geod-file '" << geoid << "':" << std::endl
+ << exception.what();
+
+ fail = true;
+ }
+
std::cout<<"GetGeoidFile() = "<<demHandler->GetGeoidFile()<<std::endl;
}
diff --git a/Modules/Applications/AppClassification/app/CMakeLists.txt b/Modules/Applications/AppClassification/app/CMakeLists.txt
index 7613f5a2612a7c62bfe8ecc648dab3f8b0b40436..692aa710eba22f1cf1274dcd08171c063764c9b1 100644
--- a/Modules/Applications/AppClassification/app/CMakeLists.txt
+++ b/Modules/Applications/AppClassification/app/CMakeLists.txt
@@ -65,16 +65,19 @@ otb_create_application(
SOURCES otbKMeansClassification.cxx
LINK_LIBRARIES ${${otb-module}_LIBRARIES})
-set(TrainImagesClassifier_SRC
- otbTrainSVM.cxx otbTrainBoost.cxx otbTrainDecisionTree.cxx
- otbTrainGradientBoostedTree.cxx otbTrainNeuralNetwork.cxx
- otbTrainNormalBayes.cxx otbTrainRandomForests.cxx otbTrainKNN.cxx
- otbTrainLibSVM.cxx
- otbTrainImagesClassifier.cxx)
-
otb_create_application(
NAME TrainImagesClassifier
- SOURCES ${TrainImagesClassifier_SRC}
+ SOURCES otbTrainImagesClassifier.cxx
+ LINK_LIBRARIES ${${otb-module}_LIBRARIES})
+
+otb_create_application(
+ NAME TrainRegression
+ SOURCES otbTrainRegression.cxx
+ LINK_LIBRARIES ${${otb-module}_LIBRARIES})
+
+otb_create_application(
+ NAME PredictRegression
+ SOURCES otbPredictRegression.cxx
LINK_LIBRARIES ${${otb-module}_LIBRARIES})
otb_create_application(
diff --git a/Modules/Applications/AppClassification/app/otbPredictRegression.cxx b/Modules/Applications/AppClassification/app/otbPredictRegression.cxx
new file mode 100644
index 0000000000000000000000000000000000000000..413d70f05d08d50efaef54a0bd38e0c58bd1ca7d
--- /dev/null
+++ b/Modules/Applications/AppClassification/app/otbPredictRegression.cxx
@@ -0,0 +1,275 @@
+/*=========================================================================
+
+ Program: ORFEO Toolbox
+ Language: C++
+ Date: $Date$
+ Version: $Revision$
+
+
+ Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
+ See OTBCopyright.txt for details.
+
+
+ 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 "otbWrapperApplication.h"
+#include "otbWrapperApplicationFactory.h"
+
+#include "itkUnaryFunctorImageFilter.h"
+#include "otbChangeLabelImageFilter.h"
+#include "otbStandardWriterWatcher.h"
+#include "otbStatisticsXMLFileReader.h"
+#include "otbShiftScaleVectorImageFilter.h"
+#include "otbImageClassificationFilter.h"
+#include "otbMultiToMonoChannelExtractROI.h"
+#include "otbImageToVectorImageCastFilter.h"
+#include "otbMachineLearningModelFactory.h"
+
+namespace otb
+{
+namespace Functor
+{
+/**
+ * simple affine function : y = ax+b
+ */
+template<class TInput, class TOutput>
+class AffineFunctor
+{
+public:
+ typedef double InternalType;
+
+ // constructor
+ AffineFunctor() : m_A(1.0),m_B(0.0) {}
+
+ // destructor
+ virtual ~AffineFunctor() {}
+
+ void SetA(InternalType a)
+ {
+ m_A = a;
+ }
+
+ void SetB(InternalType b)
+ {
+ m_B = b;
+ }
+
+ inline TOutput operator()(const TInput & x) const
+ {
+ return static_cast<TOutput>( static_cast<InternalType>(x)*m_A + m_B);
+ }
+private:
+ InternalType m_A;
+ InternalType m_B;
+};
+
+}
+
+namespace Wrapper
+{
+
+class PredictRegression : public Application
+{
+public:
+ /** Standard class typedefs. */
+ typedef PredictRegression Self;
+ typedef Application Superclass;
+ typedef itk::SmartPointer<Self> Pointer;
+ typedef itk::SmartPointer<const Self> ConstPointer;
+
+ /** Standard macro */
+ itkNewMacro(Self);
+
+ itkTypeMacro(PredictRegression, otb::Application);
+
+ /** Filters typedef */
+ typedef UInt8ImageType MaskImageType;
+ typedef itk::VariableLengthVector<FloatVectorImageType::InternalPixelType> MeasurementType;
+ typedef otb::StatisticsXMLFileReader<MeasurementType> StatisticsReader;
+ typedef otb::ShiftScaleVectorImageFilter<FloatVectorImageType, FloatVectorImageType> RescalerType;
+ typedef itk::UnaryFunctorImageFilter<
+ FloatImageType,
+ FloatImageType,
+ otb::Functor::AffineFunctor<float,float> > OutputRescalerType;
+ typedef otb::ImageClassificationFilter<FloatVectorImageType, FloatImageType, MaskImageType> ClassificationFilterType;
+ typedef ClassificationFilterType::Pointer ClassificationFilterPointerType;
+ typedef ClassificationFilterType::ModelType ModelType;
+ typedef ModelType::Pointer ModelPointerType;
+ typedef ClassificationFilterType::ValueType ValueType;
+ typedef ClassificationFilterType::LabelType LabelType;
+ typedef otb::MachineLearningModelFactory<ValueType, LabelType> MachineLearningModelFactoryType;
+
+private:
+ void DoInit()
+ {
+ SetName("PredictRegression");
+ SetDescription("Performs a prediction of the input image according to a regression model file.");
+
+ // Documentation
+ SetDocName("Predict Regression");
+ SetDocLongDescription("This application predict output values from an input"
+ " image, based on a regression model file produced by"
+ " the TrainRegression application. Pixels of the "
+ "output image will contain the predicted values from"
+ "the regression model (single band). The input pixels"
+ " can be optionally centered and reduced according "
+ "to the statistics file produced by the "
+ "ComputeImagesStatistics application. An optional "
+ "input mask can be provided, in which case only "
+ "input image pixels whose corresponding mask value "
+ "is greater than 0 will be processed. The remaining"
+ " of pixels will be given the value 0 in the output"
+ " image.");
+
+ SetDocLimitations("The input image must contain the feature bands used for"
+ " the model training (without the predicted value). "
+ "If a statistics file was used during training by the "
+ "TrainRegression, it is mandatory to use the same "
+ "statistics file for prediction. If an input mask is "
+ "used, its size must match the input image size.");
+ SetDocAuthors("OTB-Team");
+ SetDocSeeAlso("TrainRegression, ComputeImagesStatistics");
+
+ AddDocTag(Tags::Learning);
+
+ AddParameter(ParameterType_InputImage, "in", "Input Image");
+ SetParameterDescription( "in", "The input image to predict.");
+
+ // TODO : use CSV input/output ?
+
+ AddParameter(ParameterType_InputImage, "mask", "Input Mask");
+ SetParameterDescription( "mask", "The mask allows to restrict "
+ "classification of the input image to the area where mask pixel values "
+ "are greater than 0.");
+ MandatoryOff("mask");
+
+ AddParameter(ParameterType_InputFilename, "model", "Model file");
+ SetParameterDescription("model", "A regression model file (produced by "
+ "TrainRegression application).");
+
+ AddParameter(ParameterType_InputFilename, "imstat", "Statistics file");
+ SetParameterDescription("imstat", "A XML file containing mean and standard"
+ " deviation to center and reduce samples before prediction "
+ "(produced by ComputeImagesStatistics application). If this file contains"
+ "one more band than the sample size, the last stat of last band will be"
+ "applied to expand the output predicted value");
+ MandatoryOff("imstat");
+
+ AddParameter(ParameterType_OutputImage, "out", "Output Image");
+ SetParameterDescription( "out", "Output image containing predicted values");
+
+ AddRAMParameter();
+
+ // Doc example parameter settings
+ SetDocExampleParameterValue("in", "QB_1_ortho.tif");
+ SetDocExampleParameterValue("imstat", "EstimateImageStatisticsQB1.xml");
+ SetDocExampleParameterValue("model", "clsvmModelQB1.svm");
+ SetDocExampleParameterValue("out", "clLabeledImageQB1.tif");
+ }
+
+ void DoUpdateParameters()
+ {
+ // Nothing to do here : all parameters are independent
+ }
+
+ void DoExecute()
+ {
+ // Load input image
+ FloatVectorImageType::Pointer inImage = GetParameterImage("in");
+ inImage->UpdateOutputInformation();
+ unsigned int nbFeatures = inImage->GetNumberOfComponentsPerPixel();
+
+ // Load svm model
+ otbAppLogINFO("Loading model");
+ m_Model = MachineLearningModelFactoryType::CreateMachineLearningModel(GetParameterString("model"),
+ MachineLearningModelFactoryType::ReadMode);
+
+ if (m_Model.IsNull())
+ {
+ otbAppLogFATAL(<< "Error when loading model " << GetParameterString("model") << " : unsupported model type");
+ }
+
+ m_Model->Load(GetParameterString("model"));
+ m_Model->SetRegressionMode(true);
+ otbAppLogINFO("Model loaded");
+
+ // Classify
+ m_ClassificationFilter = ClassificationFilterType::New();
+ m_ClassificationFilter->SetModel(m_Model);
+
+ FloatImageType::Pointer outputImage = m_ClassificationFilter->GetOutput();
+
+ // Normalize input image if asked
+ if(IsParameterEnabled("imstat") )
+ {
+ otbAppLogINFO("Input image normalization activated.");
+ // Normalize input image (optional)
+ StatisticsReader::Pointer statisticsReader = StatisticsReader::New();
+ MeasurementType meanMeasurementVector;
+ MeasurementType stddevMeasurementVector;
+ m_Rescaler = RescalerType::New();
+ // Load input image statistics
+ statisticsReader->SetFileName(GetParameterString("imstat"));
+ meanMeasurementVector = statisticsReader->GetStatisticVectorByName("mean");
+ stddevMeasurementVector = statisticsReader->GetStatisticVectorByName("stddev");
+ otbAppLogINFO( "mean used: " << meanMeasurementVector );
+ otbAppLogINFO( "standard deviation used: " << stddevMeasurementVector );
+ if (meanMeasurementVector.Size() == nbFeatures + 1)
+ {
+ double outMean = meanMeasurementVector[nbFeatures];
+ double outStdDev = stddevMeasurementVector[nbFeatures];
+ meanMeasurementVector.SetSize(nbFeatures,false);
+ stddevMeasurementVector.SetSize(nbFeatures,false);
+ m_OutRescaler = OutputRescalerType::New();
+ m_OutRescaler->SetInput(m_ClassificationFilter->GetOutput());
+ m_OutRescaler->GetFunctor().SetA(outStdDev);
+ m_OutRescaler->GetFunctor().SetB(outMean);
+ outputImage = m_OutRescaler->GetOutput();
+ }
+ else if (meanMeasurementVector.Size() != nbFeatures)
+ {
+ otbAppLogFATAL("Wrong number of components in statistics file : "<<meanMeasurementVector.Size());
+ }
+
+ // Rescale vector image
+ m_Rescaler->SetScale(stddevMeasurementVector);
+ m_Rescaler->SetShift(meanMeasurementVector);
+ m_Rescaler->SetInput(inImage);
+
+ m_ClassificationFilter->SetInput(m_Rescaler->GetOutput());
+ }
+ else
+ {
+ otbAppLogINFO("Input image normalization deactivated.");
+ m_ClassificationFilter->SetInput(inImage);
+ }
+
+
+ if(IsParameterEnabled("mask"))
+ {
+ otbAppLogINFO("Using input mask");
+ // Load mask image and cast into LabeledImageType
+ MaskImageType::Pointer inMask = GetParameterUInt8Image("mask");
+
+ m_ClassificationFilter->SetInputMask(inMask);
+ }
+
+ SetParameterOutputImage<FloatImageType>("out", outputImage);
+
+ }
+
+ ClassificationFilterType::Pointer m_ClassificationFilter;
+ ModelPointerType m_Model;
+ RescalerType::Pointer m_Rescaler;
+ OutputRescalerType::Pointer m_OutRescaler;
+
+};
+
+
+}
+}
+
+OTB_APPLICATION_EXPORT(otb::Wrapper::PredictRegression)
diff --git a/Modules/Applications/AppClassification/app/otbTrainImagesClassifier.cxx b/Modules/Applications/AppClassification/app/otbTrainImagesClassifier.cxx
index 1b9358f04832bed66ec463d1510fbb371ea2a3de..de1520dfca4855e523513f8a4542a95bff1cde84 100644
--- a/Modules/Applications/AppClassification/app/otbTrainImagesClassifier.cxx
+++ b/Modules/Applications/AppClassification/app/otbTrainImagesClassifier.cxx
@@ -14,15 +14,95 @@
PURPOSE. See the above copyright notices for more information.
=========================================================================*/
+#include "otbLearningApplicationBase.h"
+#include "otbWrapperApplicationFactory.h"
-#include "otbTrainImagesClassifier.h"
+#include "otbListSampleGenerator.h"
+
+// Statistic XML Reader
+#include "otbStatisticsXMLFileReader.h"
+
+// Validation
+#include "otbConfusionMatrixCalculator.h"
+
+#include "itkTimeProbe.h"
+#include "otbStandardFilterWatcher.h"
+
+// Normalize the samples
+#include "otbShiftScaleSampleListFilter.h"
+
+// List sample concatenation
+#include "otbConcatenateSampleListFilter.h"
+
+// Balancing ListSample
+#include "otbListSampleToBalancedListSampleFilter.h"
+
+// VectorData projection filter
+
+// Extract a ROI of the vectordata
+#include "otbVectorDataIntoImageProjectionFilter.h"
+
+// Elevation handler
+#include "otbWrapperElevationParametersHandler.h"
namespace otb
{
namespace Wrapper
{
-void TrainImagesClassifier::DoInit()
+class TrainImagesClassifier: public LearningApplicationBase<float,int>
+{
+public:
+ /** Standard class typedefs. */
+ typedef TrainImagesClassifier Self;
+ typedef LearningApplicationBase<float,int> Superclass;
+ typedef itk::SmartPointer<Self> Pointer;
+ typedef itk::SmartPointer<const Self> ConstPointer;
+
+ /** Standard macro */
+ itkNewMacro(Self)
+
+ itkTypeMacro(TrainImagesClassifier, otb::Wrapper::LearningApplicationBase)
+
+ typedef Superclass::SampleType SampleType;
+ typedef Superclass::ListSampleType ListSampleType;
+ typedef Superclass::TargetSampleType TargetSampleType;
+ typedef Superclass::TargetListSampleType TargetListSampleType;
+
+ typedef Superclass::SampleImageType SampleImageType;
+ typedef SampleImageType::PixelType PixelType;
+
+ // SampleList manipulation
+ typedef otb::ListSampleGenerator<SampleImageType, VectorDataType> ListSampleGeneratorType;
+
+ typedef otb::Statistics::ConcatenateSampleListFilter<ListSampleType> ConcatenateListSampleFilterType;
+ typedef otb::Statistics::ConcatenateSampleListFilter<TargetListSampleType> ConcatenateLabelListSampleFilterType;
+
+ // Statistic XML file Reader
+ typedef otb::StatisticsXMLFileReader<SampleType> StatisticsReader;
+
+ // Enhance List Sample typedef otb::Statistics::ListSampleToBalancedListSampleFilter<ListSampleType, LabelListSampleType> BalancingListSampleFilterType;
+ typedef otb::Statistics::ShiftScaleSampleListFilter<ListSampleType, ListSampleType> ShiftScaleFilterType;
+
+ // Estimate performance on validation sample
+ typedef otb::ConfusionMatrixCalculator<TargetListSampleType, TargetListSampleType> ConfusionMatrixCalculatorType;
+ typedef ConfusionMatrixCalculatorType::ConfusionMatrixType ConfusionMatrixType;
+ typedef ConfusionMatrixCalculatorType::MapOfIndicesType MapOfIndicesType;
+ typedef ConfusionMatrixCalculatorType::ClassLabelType ClassLabelType;
+
+ // VectorData projection filter
+ typedef otb::VectorDataProjectionFilter<VectorDataType, VectorDataType> VectorDataProjectionFilterType;
+
+ // Extract ROI
+ typedef otb::VectorDataIntoImageProjectionFilter<VectorDataType, SampleImageType> VectorDataReprojectionType;
+
+protected:
+ //using Superclass::AddParameter;
+ //friend void InitSVMParams(TrainImagesClassifier & app);
+
+private:
+
+void DoInit()
{
SetName("TrainImagesClassifier");
SetDescription(
@@ -46,8 +126,6 @@ void TrainImagesClassifier::DoInit()
SetDocAuthors("OTB-Team");
SetDocSeeAlso("OpenCV documentation for machine learning http://docs.opencv.org/modules/ml/doc/ml.html ");
- AddDocTag(Tags::Learning);
-
//Group IO
AddParameter(ParameterType_Group, "io", "Input and output data");
SetParameterDescription("io", "This group of parameters allows to set input and output data.");
@@ -101,24 +179,7 @@ void TrainImagesClassifier::DoInit()
SetParameterDescription("sample.vfn", "Name of the field used to discriminate class labels in the input vector data files.");
SetParameterString("sample.vfn", "Class");
- AddParameter(ParameterType_Choice, "classifier", "Classifier to use for the training");
- SetParameterDescription("classifier", "Choice of the classifier to use for the training.");
-
- //Group LibSVM
-#ifdef OTB_USE_LIBSVM
- InitLibSVMParams();
-#endif
-
-#ifdef OTB_USE_OPENCV
- InitSVMParams();
- InitBoostParams();
- InitDecisionTreeParams();
- InitGradientBoostedTreeParams();
- InitNeuralNetworkParams();
- InitNormalBayesParams();
- InitRandomForestsParams();
- InitKNNParams();
-#endif
+ Superclass::DoInit();
AddRANDParameter();
// Doc example parameter settings
@@ -136,15 +197,14 @@ void TrainImagesClassifier::DoInit()
SetDocExampleParameterValue("classifier.libsvm.opt", "false");
SetDocExampleParameterValue("io.out", "svmModelQB1.txt");
SetDocExampleParameterValue("io.confmatout", "svmConfusionMatrixQB1.csv");
-}
+}
-void TrainImagesClassifier::DoUpdateParameters()
+void DoUpdateParameters()
{
// Nothing to do here : all parameters are independent
}
-
-void TrainImagesClassifier::LogConfusionMatrix(ConfusionMatrixCalculatorType* confMatCalc)
+void LogConfusionMatrix(ConfusionMatrixCalculatorType* confMatCalc)
{
ConfusionMatrixCalculatorType::ConfusionMatrixType matrix = confMatCalc->GetConfusionMatrix();
@@ -215,24 +275,7 @@ void TrainImagesClassifier::LogConfusionMatrix(ConfusionMatrixCalculatorType* co
otbAppLogINFO("Confusion matrix (rows = reference labels, columns = produced labels):\n" << os.str());
}
-void TrainImagesClassifier::Classify(ListSampleType::Pointer validationListSample, LabelListSampleType::Pointer predictedList)
-{
- //Classification
- ModelPointerType model = MachineLearningModelFactoryType::CreateMachineLearningModel(GetParameterString("io.out"),
- MachineLearningModelFactoryType::ReadMode);
-
- if (model.IsNull())
- {
- otbAppLogFATAL(<< "Error when loading model " << GetParameterString("io.out"));
- }
-
- model->Load(GetParameterString("io.out"));
- model->SetInputListSample(validationListSample);
- model->SetTargetListSample(predictedList);
- model->PredictAll();
-}
-
-void TrainImagesClassifier::DoExecute()
+void DoExecute()
{
GetLogger()->Debug("Entering DoExecute\n");
//Create training and validation for list samples and label list samples
@@ -243,8 +286,8 @@ void TrainImagesClassifier::DoExecute()
ConcatenateLabelListSampleFilterType::New();
ConcatenateListSampleFilterType::Pointer concatenateValidationSamples = ConcatenateListSampleFilterType::New();
- MeasurementType meanMeasurementVector;
- MeasurementType stddevMeasurementVector;
+ SampleType meanMeasurementVector;
+ SampleType stddevMeasurementVector;
//--------------------------
// Load measurements from images
@@ -358,7 +401,7 @@ void TrainImagesClassifier::DoExecute()
}
ListSampleType::Pointer listSample;
- LabelListSampleType::Pointer labelListSample;
+ TargetListSampleType::Pointer labelListSample;
//--------------------------
// Balancing training sample (if needed)
// if (IsParameterEnabled("sample.b"))
@@ -384,9 +427,9 @@ void TrainImagesClassifier::DoExecute()
//--------------------------
// Split the data set into training/validation set
ListSampleType::Pointer trainingListSample = listSample;
- LabelListSampleType::Pointer trainingLabeledListSample = labelListSample;
+ TargetListSampleType::Pointer trainingLabeledListSample = labelListSample;
- LabelListSampleType::Pointer validationLabeledListSample = concatenateValidationLabels->GetOutput();
+ TargetListSampleType::Pointer validationLabeledListSample = concatenateValidationLabels->GetOutput();
otbAppLogINFO("Size of training set: " << trainingListSample->Size());
otbAppLogINFO("Size of validation set: " << validationListSample->Size());
otbAppLogINFO("Size of labeled training set: " << trainingLabeledListSample->Size());
@@ -395,88 +438,14 @@ void TrainImagesClassifier::DoExecute()
//--------------------------
// Estimate model
//--------------------------
- LabelListSampleType::Pointer predictedList = LabelListSampleType::New();
- const std::string classifierType = GetParameterString("classifier");
-
- if (classifierType == "libsvm")
- {
- #ifdef OTB_USE_LIBSVM
- TrainLibSVM(trainingListSample, trainingLabeledListSample);
- #else
- otbAppLogFATAL("Module LIBSVM is not installed. You should consider turning OTB_USE_LIBSVM on during cmake configuration.");
- #endif
- }
- else if (classifierType == "svm")
- {
- #ifdef OTB_USE_OPENCV
- TrainSVM(trainingListSample, trainingLabeledListSample);
- #else
- otbAppLogFATAL("Module OPENCV is not installed. You should consider turning OTB_USE_OPENCV on during cmake configuration.");
- #endif
- }
- else if (classifierType == "boost")
- {
- #ifdef OTB_USE_OPENCV
- TrainBoost(trainingListSample, trainingLabeledListSample);
- #else
- otbAppLogFATAL("Module OPENCV is not installed. You should consider turning OTB_USE_OPENCV on during cmake configuration.");
- #endif
- }
- else if (classifierType == "dt")
- {
- #ifdef OTB_USE_OPENCV
- TrainDecisionTree(trainingListSample, trainingLabeledListSample);
- #else
- otbAppLogFATAL("Module OPENCV is not installed. You should consider turning OTB_USE_OPENCV on during cmake configuration.");
- #endif
- }
- else if (classifierType == "gbt")
- {
- #ifdef OTB_USE_OPENCV
- TrainGradientBoostedTree(trainingListSample, trainingLabeledListSample);
- #else
- otbAppLogFATAL("Module OPENCV is not installed. You should consider turning OTB_USE_OPENCV on during cmake configuration.");
- #endif
- }
- else if (classifierType == "ann")
- {
- #ifdef OTB_USE_OPENCV
- TrainNeuralNetwork(trainingListSample, trainingLabeledListSample);
- #else
- otbAppLogFATAL("Module OPENCV is not installed. You should consider turning OTB_USE_OPENCV on during cmake configuration.");
- #endif
- }
- else if (classifierType == "bayes")
- {
- #ifdef OTB_USE_OPENCV
- TrainNormalBayes(trainingListSample, trainingLabeledListSample);
- #else
- otbAppLogFATAL("Module OPENCV is not installed. You should consider turning OTB_USE_OPENCV on during cmake configuration.");
- #endif
- }
- else if (classifierType == "rf")
- {
- #ifdef OTB_USE_OPENCV
- TrainRandomForests(trainingListSample, trainingLabeledListSample);
- #else
- otbAppLogFATAL("Module OPENCV is not installed. You should consider turning OTB_USE_OPENCV on during cmake configuration.");
- #endif
- }
- else if (classifierType == "knn")
- {
- #ifdef OTB_USE_OPENCV
- TrainKNN(trainingListSample, trainingLabeledListSample);
- #else
- otbAppLogFATAL("Module OPENCV is not installed. You should consider turning OTB_USE_OPENCV on during cmake configuration.");
- #endif
- }
-
+ this->Train(trainingListSample,trainingLabeledListSample,GetParameterString("io.out"));
//--------------------------
// Performances estimation
//--------------------------
+ TargetListSampleType::Pointer predictedList = TargetListSampleType::New();
ListSampleType::Pointer performanceListSample=ListSampleType::New();
- LabelListSampleType::Pointer performanceLabeledListSample=LabelListSampleType::New();
+ TargetListSampleType::Pointer performanceLabeledListSample=TargetListSampleType::New();
//Test the input validation set size
if(validationLabeledListSample->Size() != 0)
@@ -491,7 +460,7 @@ void TrainImagesClassifier::DoExecute()
performanceLabeledListSample = trainingLabeledListSample;
}
- Classify(performanceListSample, predictedList);
+ this->Classify(performanceListSample, predictedList, GetParameterString("io.out"));
ConfusionMatrixCalculatorType::Pointer confMatCalc = ConfusionMatrixCalculatorType::New();
@@ -605,11 +574,12 @@ void TrainImagesClassifier::DoExecute()
} // END if (this->HasValue("io.confmatout"))
// TODO: implement hyperplane distance classifier and performance validation (cf. object detection) ?
-
}
+ VectorDataReprojectionType::Pointer vdreproj;
+};
-}
-}
+} // end namespace Wrapper
+} // end namespace otb
OTB_APPLICATION_EXPORT(otb::Wrapper::TrainImagesClassifier)
diff --git a/Modules/Applications/AppClassification/app/otbTrainImagesClassifier.h b/Modules/Applications/AppClassification/app/otbTrainImagesClassifier.h
deleted file mode 100644
index 235613fd56eaa5a265dc66f1e60ad26c849e1a27..0000000000000000000000000000000000000000
--- a/Modules/Applications/AppClassification/app/otbTrainImagesClassifier.h
+++ /dev/null
@@ -1,198 +0,0 @@
-/*=========================================================================
- Program: ORFEO Toolbox
- Language: C++
- Date: $Date$
- Version: $Revision$
-
-
- Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
- See OTBCopyright.txt for details.
-
-
- 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 "otbConfigure.h"
-
-#include "otbWrapperApplicationFactory.h"
-
-#include <iostream>
-
-//Image
-#include "otbVectorImage.h"
-#include "otbVectorData.h"
-#include "otbListSampleGenerator.h"
-
-// ListSample
-#include "itkVariableLengthVector.h"
-
-//Estimator
-#include "otbMachineLearningModelFactory.h"
-
-#ifdef OTB_USE_OPENCV
-# include "otbKNearestNeighborsMachineLearningModel.h"
-# include "otbRandomForestsMachineLearningModel.h"
-# include "otbSVMMachineLearningModel.h"
-# include "otbBoostMachineLearningModel.h"
-# include "otbDecisionTreeMachineLearningModel.h"
-# include "otbGradientBoostedTreeMachineLearningModel.h"
-# include "otbNormalBayesMachineLearningModel.h"
-# include "otbNeuralNetworkMachineLearningModel.h"
-#endif
-
-#ifdef OTB_USE_LIBSVM
-#include "otbLibSVMMachineLearningModel.h"
-#endif
-
-// Statistic XML Reader
-#include "otbStatisticsXMLFileReader.h"
-
-// Validation
-#include "otbConfusionMatrixCalculator.h"
-
-#include "itkTimeProbe.h"
-#include "otbStandardFilterWatcher.h"
-
-// Normalize the samples
-#include "otbShiftScaleSampleListFilter.h"
-
-// List sample concatenation
-#include "otbConcatenateSampleListFilter.h"
-
-// Balancing ListSample
-#include "otbListSampleToBalancedListSampleFilter.h"
-
-// VectorData projection filter
-
-// Extract a ROI of the vectordata
-#include "otbVectorDataIntoImageProjectionFilter.h"
-
-// Elevation handler
-#include "otbWrapperElevationParametersHandler.h"
-
-namespace otb
-{
-namespace Wrapper
-{
-
-class TrainImagesClassifier: public Application
-{
-public:
- /** Standard class typedefs. */
- typedef TrainImagesClassifier Self;
- typedef Application Superclass;
- typedef itk::SmartPointer<Self> Pointer;
- typedef itk::SmartPointer<const Self> ConstPointer;
-
- /** Standard macro */
- itkNewMacro(Self)
-
- itkTypeMacro(TrainImagesClassifier, otb::Application)
-
- typedef FloatVectorImageType::PixelType PixelType;
- typedef FloatVectorImageType::InternalPixelType InternalPixelType;
-
- // Training vectordata
- typedef itk::VariableLengthVector<InternalPixelType> MeasurementType;
-
- // SampleList manipulation
- typedef otb::ListSampleGenerator<FloatVectorImageType, VectorDataType> ListSampleGeneratorType;
-
- typedef ListSampleGeneratorType::ListSampleType ListSampleType;
- typedef ListSampleGeneratorType::LabelType LabelType;
- typedef ListSampleGeneratorType::ListLabelType LabelListSampleType;
- typedef otb::Statistics::ConcatenateSampleListFilter<ListSampleType> ConcatenateListSampleFilterType;
- typedef otb::Statistics::ConcatenateSampleListFilter<LabelListSampleType> ConcatenateLabelListSampleFilterType;
-
- // Statistic XML file Reader
- typedef otb::StatisticsXMLFileReader<MeasurementType> StatisticsReader;
-
- // Enhance List Sample typedef otb::Statistics::ListSampleToBalancedListSampleFilter<ListSampleType, LabelListSampleType> BalancingListSampleFilterType;
- typedef otb::Statistics::ShiftScaleSampleListFilter<ListSampleType, ListSampleType> ShiftScaleFilterType;
-
- // Machine Learning models
- typedef otb::MachineLearningModelFactory<InternalPixelType, ListSampleGeneratorType::ClassLabelType> MachineLearningModelFactoryType;
- typedef MachineLearningModelFactoryType::MachineLearningModelTypePointer ModelPointerType;
-
-#ifdef OTB_USE_OPENCV
- typedef otb::RandomForestsMachineLearningModel<InternalPixelType, ListSampleGeneratorType::ClassLabelType> RandomForestType;
- typedef otb::KNearestNeighborsMachineLearningModel<InternalPixelType, ListSampleGeneratorType::ClassLabelType> KNNType;
- typedef otb::SVMMachineLearningModel<InternalPixelType, ListSampleGeneratorType::ClassLabelType> SVMType;
- typedef otb::BoostMachineLearningModel<InternalPixelType, ListSampleGeneratorType::ClassLabelType> BoostType;
- typedef otb::DecisionTreeMachineLearningModel<InternalPixelType, ListSampleGeneratorType::ClassLabelType> DecisionTreeType;
- typedef otb::GradientBoostedTreeMachineLearningModel<InternalPixelType, ListSampleGeneratorType::ClassLabelType> GradientBoostedTreeType;
- typedef otb::NeuralNetworkMachineLearningModel<InternalPixelType, ListSampleGeneratorType::ClassLabelType> NeuralNetworkType;
- typedef otb::NormalBayesMachineLearningModel<InternalPixelType, ListSampleGeneratorType::ClassLabelType> NormalBayesType;
-#endif
-
-#ifdef OTB_USE_LIBSVM
- typedef otb::LibSVMMachineLearningModel<InternalPixelType, ListSampleGeneratorType::ClassLabelType> LibSVMType;
-#endif
-
- // Estimate performance on validation sample
- typedef otb::ConfusionMatrixCalculator<LabelListSampleType, LabelListSampleType> ConfusionMatrixCalculatorType;
- typedef ConfusionMatrixCalculatorType::ConfusionMatrixType ConfusionMatrixType;
- typedef ConfusionMatrixCalculatorType::MapOfIndicesType MapOfIndicesType;
- typedef ConfusionMatrixCalculatorType::ClassLabelType ClassLabelType;
-
-
- // VectorData projection filter
- typedef otb::VectorDataProjectionFilter<VectorDataType, VectorDataType> VectorDataProjectionFilterType;
-
- // Extract ROI
- typedef otb::VectorDataIntoImageProjectionFilter<VectorDataType, FloatVectorImageType> VectorDataReprojectionType;
-
-protected:
- using Superclass::AddParameter;
- friend void InitSVMParams(TrainImagesClassifier & app);
-
-private:
- void DoInit();
-
- void DoUpdateParameters();
-
- void LogConfusionMatrix(ConfusionMatrixCalculatorType* confMatCalc);
-
-#ifdef OTB_USE_LIBSVM
- void InitLibSVMParams();
-#endif
-
-#ifdef OTB_USE_OPENCV
- void InitBoostParams();
- void InitSVMParams();
- void InitDecisionTreeParams();
- void InitGradientBoostedTreeParams();
- void InitNeuralNetworkParams();
- void InitNormalBayesParams();
- void InitRandomForestsParams();
- void InitKNNParams();
-#endif
-
-#ifdef OTB_USE_LIBSVM
- void TrainLibSVM(ListSampleType::Pointer trainingListSample, LabelListSampleType::Pointer trainingLabeledListSample);
-#endif
-
-#ifdef OTB_USE_OPENCV
- void TrainBoost(ListSampleType::Pointer trainingListSample, LabelListSampleType::Pointer trainingLabeledListSample);
- void TrainSVM(ListSampleType::Pointer trainingListSample, LabelListSampleType::Pointer trainingLabeledListSample);
- void TrainDecisionTree(ListSampleType::Pointer trainingListSample, LabelListSampleType::Pointer trainingLabeledListSample);
- void TrainGradientBoostedTree(ListSampleType::Pointer trainingListSample, LabelListSampleType::Pointer trainingLabeledListSample);
- void TrainNeuralNetwork(ListSampleType::Pointer trainingListSample, LabelListSampleType::Pointer trainingLabeledListSample);
- void TrainNormalBayes(ListSampleType::Pointer trainingListSample, LabelListSampleType::Pointer trainingLabeledListSample);
- void TrainRandomForests(ListSampleType::Pointer trainingListSample, LabelListSampleType::Pointer trainingLabeledListSample);
- void TrainKNN(ListSampleType::Pointer trainingListSample, LabelListSampleType::Pointer trainingLabeledListSample);
-#endif
-
- void Classify(ListSampleType::Pointer validationListSample, LabelListSampleType::Pointer predictedList);
-
- void DoExecute();
-
- VectorDataReprojectionType::Pointer vdreproj;
-};
-
-}
-}
-
-
diff --git a/Modules/Applications/AppClassification/app/otbTrainKNN.cxx b/Modules/Applications/AppClassification/app/otbTrainKNN.cxx
deleted file mode 100644
index bc31cd4fce6c1c0207570161bd6df033e8fbff45..0000000000000000000000000000000000000000
--- a/Modules/Applications/AppClassification/app/otbTrainKNN.cxx
+++ /dev/null
@@ -1,52 +0,0 @@
-/*=========================================================================
- Program: ORFEO Toolbox
- Language: C++
- Date: $Date$
- Version: $Revision$
-
-
- Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
- See OTBCopyright.txt for details.
-
-
- 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 "otbTrainImagesClassifier.h"
-
-
-namespace otb
-{
-namespace Wrapper
-{
-#ifdef OTB_USE_OPENCV
- void TrainImagesClassifier::InitKNNParams()
- {
- AddChoice("classifier.knn", "KNN classifier");
- SetParameterDescription("classifier.knn", "This group of parameters allows to set KNN classifier parameters. "
- "See complete documentation here \\url{http://docs.opencv.org/modules/ml/doc/k_nearest_neighbors.html}.");
-
- //K parameter
- AddParameter(ParameterType_Int, "classifier.knn.k", "Number of Neighbors");
- SetParameterInt("classifier.knn.k", 32);
- SetParameterDescription("classifier.knn.k","The number of neighbors to use.");
-
- }
-
-
- void TrainImagesClassifier::TrainKNN(ListSampleType::Pointer trainingListSample, LabelListSampleType::Pointer trainingLabeledListSample)
- {
- KNNType::Pointer knnClassifier = KNNType::New();
- knnClassifier->SetInputListSample(trainingListSample);
- knnClassifier->SetTargetListSample(trainingLabeledListSample);
- knnClassifier->SetK(GetParameterInt("classifier.knn.k"));
-
- knnClassifier->Train();
- knnClassifier->Save(GetParameterString("io.out"));
- }
-#endif
-} //end namespace wrapper
-} //end namespace otb
diff --git a/Modules/Applications/AppClassification/app/otbTrainRegression.cxx b/Modules/Applications/AppClassification/app/otbTrainRegression.cxx
new file mode 100644
index 0000000000000000000000000000000000000000..82e865194dd0418e98d04c17550df9919f19ff76
--- /dev/null
+++ b/Modules/Applications/AppClassification/app/otbTrainRegression.cxx
@@ -0,0 +1,543 @@
+/*=========================================================================
+ Program: ORFEO Toolbox
+ Language: C++
+ Date: $Date$
+ Version: $Revision$
+
+
+ Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
+ See OTBCopyright.txt for details.
+
+
+ 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 "otbLearningApplicationBase.h"
+#include "otbWrapperApplicationFactory.h"
+
+#include "otbListSampleGenerator.h"
+
+#include "otbImageToEnvelopeVectorDataFilter.h"
+#include "itkPreOrderTreeIterator.h"
+
+// Statistic XML Reader
+#include "otbStatisticsXMLFileReader.h"
+
+#include "itkTimeProbe.h"
+#include "otbStandardFilterWatcher.h"
+
+// Normalize the samples
+#include "otbShiftScaleSampleListFilter.h"
+
+// List sample concatenation
+#include "otbConcatenateSampleListFilter.h"
+
+// Balancing ListSample
+#include "otbListSampleToBalancedListSampleFilter.h"
+
+#include "itkMersenneTwisterRandomVariateGenerator.h"
+
+// Elevation handler
+#include "otbWrapperElevationParametersHandler.h"
+
+namespace otb
+{
+namespace Wrapper
+{
+
+class TrainRegression: public LearningApplicationBase<float,float>
+{
+public:
+ /** Standard class typedefs. */
+ typedef TrainRegression Self;
+ typedef LearningApplicationBase<float,float> Superclass;
+ typedef itk::SmartPointer<Self> Pointer;
+ typedef itk::SmartPointer<const Self> ConstPointer;
+
+ /** Standard macro */
+ itkNewMacro(Self)
+
+ itkTypeMacro(TrainRegression, otb::Wrapper::LearningApplicationBase)
+
+ typedef Superclass::SampleType SampleType;
+ typedef Superclass::ListSampleType ListSampleType;
+ typedef Superclass::TargetSampleType TargetSampleType;
+ typedef Superclass::TargetListSampleType TargetListSampleType;
+
+ typedef Superclass::SampleImageType SampleImageType;
+ typedef SampleImageType::PixelType PixelType;
+
+ // SampleList manipulation
+ typedef otb::ListSampleGenerator<SampleImageType, VectorDataType> ListSampleGeneratorType;
+
+ typedef otb::Statistics::ConcatenateSampleListFilter<ListSampleType> ConcatenateListSampleFilterType;
+ typedef otb::Statistics::ConcatenateSampleListFilter<TargetListSampleType> ConcatenateLabelListSampleFilterType;
+
+ // Statistic XML file Reader
+ typedef otb::StatisticsXMLFileReader<SampleType> StatisticsReader;
+
+ // Enhance List Sample typedef otb::Statistics::ListSampleToBalancedListSampleFilter<ListSampleType, LabelListSampleType> BalancingListSampleFilterType;
+ typedef otb::Statistics::ShiftScaleSampleListFilter<ListSampleType, ListSampleType> ShiftScaleFilterType;
+
+ typedef otb::ImageToEnvelopeVectorDataFilter<SampleImageType,VectorDataType> EnvelopeFilterType;
+
+ typedef itk::PreOrderTreeIterator<VectorDataType::DataTreeType> TreeIteratorType;
+
+ typedef itk::Statistics::MersenneTwisterRandomVariateGenerator RandomGeneratorType;
+
+protected:
+ TrainRegression()
+ {
+ this->m_RegressionFlag = true;
+ }
+
+private:
+
+void DoInit()
+{
+ SetName("TrainRegression");
+ SetDescription(
+ "Train a classifier from multiple images to perform regression.");
+
+ // Documentation
+ SetDocName("Train a regression model");
+ SetDocLongDescription(
+ "This application trains a classifier from multiple input images or a csv "
+ "file, in order to perform regression. Predictors are composed of pixel "
+ "values in each band optionally centered and reduced using an XML "
+ "statistics file produced by the ComputeImagesStatistics application.\n "
+ "The output value for each predictor is assumed to be the last band "
+ "(or the last column for CSV files). Training and validation predictor "
+ "lists are built such that their size is inferior to maximum bounds given "
+ "by the user, and the proportion corresponds to the balance parameter. "
+ "Several classifier parameters can be set depending on the chosen "
+ "classifier. In the validation process, the mean square error is computed\n"
+ " This application is based on LibSVM and on OpenCV Machine Learning "
+ "classifiers, and is compatible with OpenCV 2.3.1 and later.");
+ SetDocLimitations("None");
+ SetDocAuthors("OTB-Team");
+ SetDocSeeAlso("OpenCV documentation for machine learning http://docs.opencv.org/modules/ml/doc/ml.html ");
+
+ //Group IO
+ AddParameter(ParameterType_Group, "io", "Input and output data");
+ SetParameterDescription("io", "This group of parameters allows to set input and output data.");
+ AddParameter(ParameterType_InputImageList, "io.il", "Input Image List");
+ SetParameterDescription("io.il", "A list of input images. First (n-1) bands should contain the predictor. The last band should contain the output value to predict.");
+ AddParameter(ParameterType_InputFilename, "io.csv", "Input CSV file");
+ SetParameterDescription("io.csv","Input CSV file containing the predictors, and the output values in last column. Only used when no input image is given");
+ MandatoryOff("io.csv");
+
+ AddParameter(ParameterType_InputFilename, "io.imstat", "Input XML image statistics file");
+ MandatoryOff("io.imstat");
+ SetParameterDescription("io.imstat",
+ "Input XML file containing the mean and the standard deviation of the input images.");
+ AddParameter(ParameterType_OutputFilename, "io.out", "Output regression model");
+ SetParameterDescription("io.out", "Output file containing the model estimated (.txt format).");
+
+ AddParameter(ParameterType_Float,"io.mse","Mean Square Error");
+ SetParameterDescription("io.mse","Mean square error computed with the validation predictors");
+ SetParameterRole("io.mse",Role_Output);
+ DisableParameter("io.mse");
+
+ //Group Sample list
+ AddParameter(ParameterType_Group, "sample", "Training and validation samples parameters");
+ SetParameterDescription("sample",
+ "This group of parameters allows to set training and validation sample lists parameters.");
+
+ AddParameter(ParameterType_Int, "sample.mt", "Maximum training predictors");
+ //MandatoryOff("mt");
+ SetDefaultParameterInt("sample.mt", 1000);
+ SetParameterDescription("sample.mt", "Maximum number of training predictors (default = 1000) (no limit = -1).");
+
+ AddParameter(ParameterType_Int, "sample.mv", "Maximum validation predictors");
+ // MandatoryOff("mv");
+ SetDefaultParameterInt("sample.mv", 1000);
+ SetParameterDescription("sample.mv", "Maximum number of validation predictors (default = 1000) (no limit = -1).");
+
+ AddParameter(ParameterType_Float, "sample.vtr", "Training and validation sample ratio");
+ SetParameterDescription("sample.vtr",
+ "Ratio between training and validation samples (0.0 = all training, 1.0 = all validation) (default = 0.5).");
+ SetParameterFloat("sample.vtr", 0.5);
+
+ Superclass::DoInit();
+
+ AddRANDParameter();
+
+ // Doc example parameter settings
+ SetDocExampleParameterValue("io.il", "training_dataset.tif");
+ SetDocExampleParameterValue("io.out", "regression_model.txt");
+ SetDocExampleParameterValue("io.imstat", "training_statistics.xml");
+ SetDocExampleParameterValue("classifier", "svm");
+}
+
+void DoUpdateParameters()
+{
+ if (HasValue("io.csv") && IsParameterEnabled("io.csv"))
+ {
+ MandatoryOff("io.il");
+ }
+ else
+ {
+ MandatoryOn("io.il");
+ }
+}
+
+void ParseCSVPredictors(std::string path, ListSampleType* outputList)
+{
+ std::ifstream ifs;
+ ifs.open(path.c_str());
+ unsigned int nbCols = 0;
+ char sep = '\t';
+ std::istringstream iss;
+ SampleType elem;
+ while(!ifs.eof())
+ {
+ std::string line;
+ std::getline(ifs,line);
+ // filter current line
+ while (!line.empty() && (line[0] == ' ' || line[0] == '\t'))
+ {
+ line.erase(line.begin());
+ }
+ while (!line.empty() && ( *(line.end()-1) == ' ' || *(line.end()-1) == '\t' || *(line.end()-1) == '\r'))
+ {
+ line.erase(line.end()-1);
+ }
+
+ // Avoid commented lines or too short ones
+ if (!line.empty() && line[0] != '#')
+ {
+ std::vector<itksys::String> words = itksys::SystemTools::SplitString(line.c_str(),sep);
+ if (nbCols == 0)
+ {
+ // detect separator and feature size
+ if (words.size() < 2)
+ {
+ sep = ' ';
+ words = itksys::SystemTools::SplitString(line.c_str(),sep);
+ }
+ if (words.size() < 2)
+ {
+ sep = ';';
+ words = itksys::SystemTools::SplitString(line.c_str(),sep);
+ }
+ if (words.size() < 2)
+ {
+ sep = ',';
+ words = itksys::SystemTools::SplitString(line.c_str(),sep);
+ }
+ if (words.size() < 2)
+ {
+ otbAppLogFATAL(<< "Can't parse CSV file : less than 2 columns or unknonw separator (knowns ones are tab, space, comma and semi-colon)");
+ }
+ nbCols = words.size();
+ elem.SetSize(nbCols,false);
+ outputList->SetMeasurementVectorSize(nbCols);
+ }
+ else if (words.size() != nbCols )
+ {
+ otbAppLogWARNING(<< "Skip CSV line, wrong number of columns : got "<<words.size() << ", expected "<<nbCols);
+ continue;
+ }
+ elem.Fill(0.0);
+ for (unsigned int i=0 ; i<nbCols ; ++i)
+ {
+ iss.str(words[i]);
+ iss >> elem[i];
+ }
+ outputList->PushBack(elem);
+ }
+ }
+ ifs.close();
+}
+
+void DoExecute()
+{
+ GetLogger()->Debug("Entering DoExecute\n");
+ //Create training and validation for list samples and label list samples
+ ConcatenateListSampleFilterType::Pointer concatenateTrainingSamples = ConcatenateListSampleFilterType::New();
+ ConcatenateListSampleFilterType::Pointer concatenateValidationSamples = ConcatenateListSampleFilterType::New();
+
+ SampleType meanMeasurementVector;
+ SampleType stddevMeasurementVector;
+
+ //--------------------------
+ // Load measurements from images
+ unsigned int nbBands = 0;
+ unsigned int nbFeatures = 0;
+ //Iterate over all input images
+
+ FloatVectorImageListType* imageList = GetParameterImageList("io.il");
+
+ //Iterate over all input images
+ for (unsigned int imgIndex = 0; imgIndex < imageList->Size(); ++imgIndex)
+ {
+ FloatVectorImageType::Pointer image = imageList->GetNthElement(imgIndex);
+ image->UpdateOutputInformation();
+
+ if (imgIndex == 0)
+ {
+ nbBands = image->GetNumberOfComponentsPerPixel();
+ nbFeatures = static_cast<unsigned int>(static_cast<int>(nbBands) - 1);
+ if (nbBands < 2)
+ {
+ otbAppLogFATAL(<< "Need at least two bands per image, got "<<nbBands);
+ }
+ else
+ {
+ if (nbBands != image->GetNumberOfComponentsPerPixel())
+ {
+ otbAppLogFATAL(<< "Image has a different number of components than "
+ "the first one, expected "<<nbBands<<", got "<< image->GetNumberOfComponentsPerPixel());
+ }
+ }
+ }
+
+ // Extract image envelope to feed in sampleGenerator
+ EnvelopeFilterType::Pointer envelopeFilter = EnvelopeFilterType::New();
+ envelopeFilter->SetInput(image);
+ envelopeFilter->SetSamplingRate(0);
+ if (!image->GetProjectionRef().empty())
+ {
+ envelopeFilter->SetOutputProjectionRef(image->GetProjectionRef());
+ }
+
+ // Setup the DEM Handler
+ // otb::Wrapper::ElevationParametersHandler::SetupDEMHandlerFromElevationParameters(this,"elev");
+
+ envelopeFilter->Update();
+
+ VectorDataType::Pointer envelope = envelopeFilter->GetOutput();
+
+ TreeIteratorType itVector(envelope->GetDataTree());
+ for (itVector.GoToBegin(); !itVector.IsAtEnd(); ++itVector)
+ {
+ if (itVector.Get()->IsPolygonFeature())
+ {
+ itVector.Get()->SetFieldAsInt(std::string("class"),1);
+ }
+ }
+
+
+ //Sample list generator
+ ListSampleGeneratorType::Pointer sampleGenerator = ListSampleGeneratorType::New();
+
+ sampleGenerator->SetInput(image);
+ sampleGenerator->SetInputVectorData(envelope);
+
+ sampleGenerator->SetClassKey("class");
+ sampleGenerator->SetMaxTrainingSize(GetParameterInt("sample.mt"));
+ sampleGenerator->SetMaxValidationSize(GetParameterInt("sample.mv"));
+ sampleGenerator->SetValidationTrainingProportion(GetParameterFloat("sample.vtr"));
+ sampleGenerator->SetBoundByMin(false);
+ sampleGenerator->SetPolygonEdgeInclusion(true);
+
+ sampleGenerator->Update();
+
+ //Concatenate training and validation samples from the image
+ concatenateTrainingSamples->AddInput(sampleGenerator->GetTrainingListSample());
+ concatenateValidationSamples->AddInput(sampleGenerator->GetValidationListSample());
+ }
+
+ // if no input image, try CSV
+ if (imageList->Size() == 0)
+ {
+ if (HasValue("io.csv") && IsParameterEnabled("io.csv"))
+ {
+ ListSampleType::Pointer csvListSample = ListSampleType::New();
+ this->ParseCSVPredictors(this->GetParameterString("io.csv"), csvListSample);
+ unsigned int totalCSVSize = csvListSample->Size();
+ if (totalCSVSize == 0)
+ {
+ otbAppLogFATAL("No input image and empty CSV file. Missing input data");
+ }
+ nbBands = csvListSample->GetMeasurementVectorSize();
+ nbFeatures = static_cast<unsigned int>(static_cast<int>(nbBands) - 1);
+ ListSampleType::Pointer csvTrainListSample = ListSampleType::New();
+ ListSampleType::Pointer csvValidListSample = ListSampleType::New();
+ csvTrainListSample->SetMeasurementVectorSize(nbBands);
+ csvValidListSample->SetMeasurementVectorSize(nbBands);
+ double ratio = this->GetParameterFloat("sample.vtr");
+ int trainSize = static_cast<int>(static_cast<double>(totalCSVSize)*(1.0-ratio));
+ int validSize = static_cast<int>(static_cast<double>(totalCSVSize)*(ratio));
+ if (trainSize > this->GetParameterInt("sample.mt"))
+ {
+ trainSize = this->GetParameterInt("sample.mt");
+ }
+ if (validSize > this->GetParameterInt("sample.mv"))
+ {
+ validSize = this->GetParameterInt("sample.mv");
+ }
+ double probaTrain = static_cast<double>(trainSize)/static_cast<double>(totalCSVSize);
+ double probaValid = static_cast<double>(validSize)/static_cast<double>(totalCSVSize);
+
+ RandomGeneratorType::Pointer randomGenerator = RandomGeneratorType::GetInstance();
+ for (unsigned int i=0; i<totalCSVSize; ++i)
+ {
+ double random = randomGenerator->GetUniformVariate(0.0, 1.0);
+ if (random < probaTrain)
+ {
+ csvTrainListSample->PushBack(csvListSample->GetMeasurementVector(i));
+ }
+ else if (random < probaTrain + probaValid)
+ {
+ csvValidListSample->PushBack(csvListSample->GetMeasurementVector(i));
+ }
+ }
+ concatenateTrainingSamples->AddInput(csvTrainListSample);
+ concatenateValidationSamples->AddInput(csvValidListSample);
+ }
+ }
+
+ // Update
+ concatenateTrainingSamples->Update();
+ concatenateValidationSamples->Update();
+
+ if (concatenateTrainingSamples->GetOutput()->Size() == 0)
+ {
+ otbAppLogFATAL("No training samples, cannot perform training.");
+ }
+
+ if (concatenateValidationSamples->GetOutput()->Size() == 0)
+ {
+ otbAppLogWARNING("No validation samples.");
+ }
+
+ if (IsParameterEnabled("io.imstat"))
+ {
+ StatisticsReader::Pointer statisticsReader = StatisticsReader::New();
+ statisticsReader->SetFileName(GetParameterString("io.imstat"));
+ meanMeasurementVector = statisticsReader->GetStatisticVectorByName("mean");
+ stddevMeasurementVector = statisticsReader->GetStatisticVectorByName("stddev");
+ // handle stat file without output normalization
+ if (meanMeasurementVector.Size() == nbFeatures)
+ {
+ meanMeasurementVector.SetSize(nbBands,false);
+ meanMeasurementVector[nbFeatures] = 0.0;
+ stddevMeasurementVector.SetSize(nbBands,false);
+ stddevMeasurementVector[nbFeatures] = 1.0;
+ }
+ }
+ else
+ {
+ meanMeasurementVector.SetSize(nbBands);
+ meanMeasurementVector.Fill(0.);
+ stddevMeasurementVector.SetSize(nbBands);
+ stddevMeasurementVector.Fill(1.);
+ }
+
+ // Shift scale the samples
+ ShiftScaleFilterType::Pointer trainingShiftScaleFilter = ShiftScaleFilterType::New();
+ trainingShiftScaleFilter->SetInput(concatenateTrainingSamples->GetOutput());
+ trainingShiftScaleFilter->SetShifts(meanMeasurementVector);
+ trainingShiftScaleFilter->SetScales(stddevMeasurementVector);
+ trainingShiftScaleFilter->Update();
+
+ ListSampleType::Pointer rawValidationListSample=ListSampleType::New();
+
+ //Test if the validation test is empty
+ if ( concatenateValidationSamples->GetOutput()->Size() != 0 )
+ {
+ ShiftScaleFilterType::Pointer validationShiftScaleFilter = ShiftScaleFilterType::New();
+ validationShiftScaleFilter->SetInput(concatenateValidationSamples->GetOutput());
+ validationShiftScaleFilter->SetShifts(meanMeasurementVector);
+ validationShiftScaleFilter->SetScales(stddevMeasurementVector);
+ validationShiftScaleFilter->Update();
+ rawValidationListSample = validationShiftScaleFilter->GetOutput();
+ }
+
+ // Split between predictors and output values
+ ListSampleType::Pointer rawlistSample = trainingShiftScaleFilter->GetOutput();
+ ListSampleType::Pointer listSample = ListSampleType::New();
+ listSample->SetMeasurementVectorSize(nbFeatures);
+ listSample->Resize(rawlistSample->Size());
+ TargetListSampleType::Pointer labelListSample = TargetListSampleType::New();
+ labelListSample->SetMeasurementVectorSize(1);
+ labelListSample->Resize(rawlistSample->Size());
+
+ ListSampleType::Pointer validationListSample = ListSampleType::New();
+ validationListSample->SetMeasurementVectorSize(nbFeatures);
+ validationListSample->Resize(rawValidationListSample->Size());
+ TargetListSampleType::Pointer validationLabeledListSample = TargetListSampleType::New();
+ validationLabeledListSample->SetMeasurementVectorSize(1);
+ validationLabeledListSample->Resize(rawValidationListSample->Size());
+
+ ListSampleType::MeasurementVectorType elem;
+ TargetListSampleType::MeasurementVectorType outElem;
+ for (ListSampleType::InstanceIdentifier i=0; i<rawlistSample->Size() ; ++i)
+ {
+ elem = rawlistSample->GetMeasurementVector(i);
+ outElem[0] = elem[nbFeatures];
+ labelListSample->SetMeasurementVector(i,outElem);
+ elem.SetSize(nbFeatures,false);
+ listSample->SetMeasurementVector(i,elem);
+ }
+ for (ListSampleType::InstanceIdentifier i=0; i<rawValidationListSample->Size() ; ++i)
+ {
+ elem = rawValidationListSample->GetMeasurementVector(i);
+ outElem[0] = elem[nbFeatures];
+ validationLabeledListSample->SetMeasurementVector(i,outElem);
+ elem.SetSize(nbFeatures,false);
+ validationListSample->SetMeasurementVector(i,elem);
+ }
+
+
+ otbAppLogINFO("Number of training samples: " << concatenateTrainingSamples->GetOutput()->Size());
+ //--------------------------
+ // Split the data set into training/validation set
+ ListSampleType::Pointer trainingListSample = listSample;
+ TargetListSampleType::Pointer trainingLabeledListSample = labelListSample;
+
+ otbAppLogINFO("Size of training set: " << trainingListSample->Size());
+ otbAppLogINFO("Size of validation set: " << validationListSample->Size());
+
+ //--------------------------
+ // Estimate model
+ //--------------------------
+ this->Train(trainingListSample,trainingLabeledListSample,GetParameterString("io.out"));
+
+ //--------------------------
+ // Performances estimation
+ //--------------------------
+ ListSampleType::Pointer performanceListSample;
+ TargetListSampleType::Pointer predictedList = TargetListSampleType::New();
+ predictedList->SetMeasurementVectorSize(1);
+ TargetListSampleType::Pointer performanceLabeledListSample;
+
+ //Test the input validation set size
+ if(validationLabeledListSample->Size() != 0)
+ {
+ performanceListSample = validationListSample;
+ performanceLabeledListSample = validationLabeledListSample;
+ }
+ else
+ {
+ otbAppLogWARNING("The validation set is empty. The performance estimation is done using the input training set in this case.");
+ performanceListSample = trainingListSample;
+ performanceLabeledListSample = trainingLabeledListSample;
+ }
+
+ this->Classify(performanceListSample, predictedList, GetParameterString("io.out"));
+
+ otbAppLogINFO("Training performances");
+ double mse=0.0;
+ TargetListSampleType::MeasurementVectorType predictedElem;
+ for (TargetListSampleType::InstanceIdentifier i=0; i<performanceListSample->Size() ; ++i)
+ {
+ outElem = performanceLabeledListSample->GetMeasurementVector(i);
+ predictedElem = predictedList->GetMeasurementVector(i);
+ mse += (outElem[0] - predictedElem[0]) * (outElem[0] - predictedElem[0]);
+ }
+ mse /= static_cast<double>(performanceListSample->Size());
+ otbAppLogINFO("Mean Square Error = "<<mse);
+ this->SetParameterFloat("io.mse",mse);
+}
+
+};
+
+} // end namespace Wrapper
+} // end namespace otb
+
+OTB_APPLICATION_EXPORT(otb::Wrapper::TrainRegression)
diff --git a/Modules/Applications/AppClassification/include/otbLearningApplicationBase.h b/Modules/Applications/AppClassification/include/otbLearningApplicationBase.h
new file mode 100644
index 0000000000000000000000000000000000000000..9af1259c73ff6356d515588f52887db569f63c43
--- /dev/null
+++ b/Modules/Applications/AppClassification/include/otbLearningApplicationBase.h
@@ -0,0 +1,222 @@
+/*=========================================================================
+ Program: ORFEO Toolbox
+ Language: C++
+ Date: $Date$
+ Version: $Revision$
+
+
+ Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
+ See OTBCopyright.txt for details.
+
+
+ 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.
+
+ =========================================================================*/
+#ifndef __otbLearningApplicationBase_h
+#define __otbLearningApplicationBase_h
+
+#include "otbConfigure.h"
+
+#include "otbWrapperApplication.h"
+
+#include <iostream>
+
+// ListSample
+#include "itkListSample.h"
+#include "itkVariableLengthVector.h"
+
+//Estimator
+#include "otbMachineLearningModelFactory.h"
+
+#ifdef OTB_USE_OPENCV
+# include "otbKNearestNeighborsMachineLearningModel.h"
+# include "otbRandomForestsMachineLearningModel.h"
+# include "otbSVMMachineLearningModel.h"
+# include "otbBoostMachineLearningModel.h"
+# include "otbDecisionTreeMachineLearningModel.h"
+# include "otbGradientBoostedTreeMachineLearningModel.h"
+# include "otbNormalBayesMachineLearningModel.h"
+# include "otbNeuralNetworkMachineLearningModel.h"
+#endif
+
+#ifdef OTB_USE_LIBSVM
+#include "otbLibSVMMachineLearningModel.h"
+#endif
+
+namespace otb
+{
+namespace Wrapper
+{
+
+/** \class LearningApplicationBase
+ * \brief LearningApplicationBase is the base class for application that
+ * use machine learning model.
+ *
+ * This base class offers a DoInit() method to initialize all the parameters
+ * related to machine learning models. They will all be in the choice parameter
+ * named "classifier". The class also offers generic Train() and Classify()
+ * methods. The classes derived from LearningApplicationBase only need these
+ * 3 methods to handle the machine learning model.
+ *
+ * There are multiple machine learning models in OTB, some imported from OpenCV,
+ * and one imported from LibSVM. They all have different parameters. The
+ * purpose of this class is to handle the creation of all parameters related to
+ * machine learning models (in DoInit() ), and to dispatch the calls to
+ * specific train functions in function Train().
+ *
+ * This class is templated over scalar types for input and output values.
+ * Typically, the input value type will be either float of double. The choice
+ * of an output value type depends on the learning mode. This base class
+ * supports both classification and regression modes. For classification
+ * (enabled by default), the output value type corresponds to a class
+ * identifier so integer types suit well. For regression, the output value
+ * should not be an integer type, but rather a floating point type. In addition,
+ * an application deriving this base class for regression should initialize
+ * the m_RegressionFlag to true in their constructor.
+ *
+ * \sa TrainImagesClassifier
+ * \sa TrainRegression
+ *
+ * \ingroup OTBAppClassification
+ */
+template <class TInputValue, class TOutputValue>
+class LearningApplicationBase: public Application
+{
+public:
+ /** Standard class typedefs. */
+ typedef LearningApplicationBase Self;
+ typedef Application Superclass;
+ typedef itk::SmartPointer<Self> Pointer;
+ typedef itk::SmartPointer<const Self> ConstPointer;
+
+ /** Standard macro */
+ itkTypeMacro(LearningApplicationBase, otb::Application)
+
+ typedef TInputValue InputValueType;
+ typedef TOutputValue OutputValueType;
+
+ typedef otb::VectorImage<InputValueType> SampleImageType;
+ typedef typename SampleImageType::PixelType PixelType;
+
+ // Machine Learning models
+ typedef otb::MachineLearningModelFactory<
+ InputValueType, OutputValueType> ModelFactoryType;
+ typedef typename ModelFactoryType::MachineLearningModelTypePointer ModelPointerType;
+ typedef typename ModelFactoryType::MachineLearningModelType ModelType;
+
+ typedef typename ModelType::InputSampleType SampleType;
+ typedef typename ModelType::InputListSampleType ListSampleType;
+
+ typedef typename ModelType::TargetSampleType TargetSampleType;
+ typedef typename ModelType::TargetListSampleType TargetListSampleType;
+ typedef typename ModelType::TargetValueType TargetValueType;
+
+#ifdef OTB_USE_OPENCV
+ typedef otb::RandomForestsMachineLearningModel<InputValueType, OutputValueType> RandomForestType;
+ typedef otb::KNearestNeighborsMachineLearningModel<InputValueType, OutputValueType> KNNType;
+ typedef otb::SVMMachineLearningModel<InputValueType, OutputValueType> SVMType;
+ typedef otb::BoostMachineLearningModel<InputValueType, OutputValueType> BoostType;
+ typedef otb::DecisionTreeMachineLearningModel<InputValueType, OutputValueType> DecisionTreeType;
+ typedef otb::GradientBoostedTreeMachineLearningModel<InputValueType, OutputValueType> GradientBoostedTreeType;
+ typedef otb::NeuralNetworkMachineLearningModel<InputValueType, OutputValueType> NeuralNetworkType;
+ typedef otb::NormalBayesMachineLearningModel<InputValueType, OutputValueType> NormalBayesType;
+#endif
+
+#ifdef OTB_USE_LIBSVM
+ typedef otb::LibSVMMachineLearningModel<InputValueType, OutputValueType> LibSVMType;
+#endif
+
+protected:
+ LearningApplicationBase();
+
+ /** Generic method to train and save the machine learning model. This method
+ * uses specific train methods depending on the chosen model.*/
+ void Train(typename ListSampleType::Pointer trainingListSample,
+ typename TargetListSampleType::Pointer trainingLabeledListSample,
+ std::string modelPath);
+
+ /** Generic method to load a model file and use it to classify a sample list*/
+ void Classify(typename ListSampleType::Pointer validationListSample,
+ typename TargetListSampleType::Pointer predictedList,
+ std::string modelPath);
+
+ /** Init method that creates all the parameters for machine learning models */
+ void DoInit();
+
+ /** Flag to switch between classification and regression mode.
+ * False by default, child classes may change it in their constructor */
+ bool m_RegressionFlag;
+
+private:
+
+ /** Specific Init and Train methods for each machine learning model */
+ //@{
+#ifdef OTB_USE_LIBSVM
+ void InitLibSVMParams();
+
+ void TrainLibSVM(typename ListSampleType::Pointer trainingListSample,
+ typename TargetListSampleType::Pointer trainingLabeledListSample,
+ std::string modelPath);
+#endif
+
+#ifdef OTB_USE_OPENCV
+ void InitBoostParams();
+ void InitSVMParams();
+ void InitDecisionTreeParams();
+ void InitGradientBoostedTreeParams();
+ void InitNeuralNetworkParams();
+ void InitNormalBayesParams();
+ void InitRandomForestsParams();
+ void InitKNNParams();
+
+ void TrainBoost(typename ListSampleType::Pointer trainingListSample,
+ typename TargetListSampleType::Pointer trainingLabeledListSample,
+ std::string modelPath);
+ void TrainSVM(typename ListSampleType::Pointer trainingListSample,
+ typename TargetListSampleType::Pointer trainingLabeledListSample,
+ std::string modelPath);
+ void TrainDecisionTree(typename ListSampleType::Pointer trainingListSample,
+ typename TargetListSampleType::Pointer trainingLabeledListSample,
+ std::string modelPath);
+ void TrainGradientBoostedTree(typename ListSampleType::Pointer trainingListSample,
+ typename TargetListSampleType::Pointer trainingLabeledListSample,
+ std::string modelPath);
+ void TrainNeuralNetwork(typename ListSampleType::Pointer trainingListSample,
+ typename TargetListSampleType::Pointer trainingLabeledListSample,
+ std::string modelPath);
+ void TrainNormalBayes(typename ListSampleType::Pointer trainingListSample,
+ typename TargetListSampleType::Pointer trainingLabeledListSample,
+ std::string modelPath);
+ void TrainRandomForests(typename ListSampleType::Pointer trainingListSample,
+ typename TargetListSampleType::Pointer trainingLabeledListSample,
+ std::string modelPath);
+ void TrainKNN(typename ListSampleType::Pointer trainingListSample,
+ typename TargetListSampleType::Pointer trainingLabeledListSample,
+ std::string modelPath);
+#endif
+ //@}
+};
+
+}
+}
+
+#ifndef OTB_MANUAL_INSTANTIATION
+#include "otbLearningApplicationBase.txx"
+#ifdef OTB_USE_OPENCV
+#include "otbTrainBoost.txx"
+#include "otbTrainDecisionTree.txx"
+#include "otbTrainGradientBoostedTree.txx"
+#include "otbTrainKNN.txx"
+#include "otbTrainNeuralNetwork.txx"
+#include "otbTrainNormalBayes.txx"
+#include "otbTrainRandomForests.txx"
+#include "otbTrainSVM.txx"
+#endif
+#ifdef OTB_USE_LIBSVM
+#include "otbTrainLibSVM.txx"
+#endif
+#endif
+
+#endif
diff --git a/Modules/Applications/AppClassification/include/otbLearningApplicationBase.txx b/Modules/Applications/AppClassification/include/otbLearningApplicationBase.txx
new file mode 100644
index 0000000000000000000000000000000000000000..a545538656efbafd98fa520944b09a183ef87fcb
--- /dev/null
+++ b/Modules/Applications/AppClassification/include/otbLearningApplicationBase.txx
@@ -0,0 +1,177 @@
+/*=========================================================================
+ Program: ORFEO Toolbox
+ Language: C++
+ Date: $Date$
+ Version: $Revision$
+
+
+ Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
+ See OTBCopyright.txt for details.
+
+
+ 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.
+
+ =========================================================================*/
+#ifndef __otbLearningApplicationBase_txx
+#define __otbLearningApplicationBase_txx
+
+#include "otbLearningApplicationBase.h"
+
+namespace otb
+{
+namespace Wrapper
+{
+
+template <class TInputValue, class TOutputValue>
+LearningApplicationBase<TInputValue,TOutputValue>
+::LearningApplicationBase() : m_RegressionFlag(false)
+{
+}
+
+template <class TInputValue, class TOutputValue>
+void
+LearningApplicationBase<TInputValue,TOutputValue>
+::DoInit()
+{
+ AddDocTag(Tags::Learning);
+
+ // main choice parameter that will contain all machine learning options
+ AddParameter(ParameterType_Choice, "classifier", "Classifier to use for the training");
+ SetParameterDescription("classifier", "Choice of the classifier to use for the training.");
+
+ //Group LibSVM
+#ifdef OTB_USE_LIBSVM
+ InitLibSVMParams();
+#endif
+
+#ifdef OTB_USE_OPENCV
+ InitSVMParams();
+ if (!m_RegressionFlag)
+ {
+ InitBoostParams(); // Regression not supported
+ }
+ InitDecisionTreeParams();
+ InitGradientBoostedTreeParams();
+ InitNeuralNetworkParams();
+ if (!m_RegressionFlag)
+ {
+ InitNormalBayesParams(); // Regression not supported
+ }
+ InitRandomForestsParams();
+ InitKNNParams();
+#endif
+}
+
+template <class TInputValue, class TOutputValue>
+void
+LearningApplicationBase<TInputValue,TOutputValue>
+::Classify(typename ListSampleType::Pointer validationListSample,
+ typename TargetListSampleType::Pointer predictedList,
+ std::string modelPath)
+{
+ // load a machine learning model from file and predict the input sample list
+ ModelPointerType model = ModelFactoryType::CreateMachineLearningModel(modelPath,
+ ModelFactoryType::ReadMode);
+
+ if (model.IsNull())
+ {
+ otbAppLogFATAL(<< "Error when loading model " << modelPath);
+ }
+
+ model->Load(modelPath);
+ model->SetRegressionMode(this->m_RegressionFlag);
+ model->SetInputListSample(validationListSample);
+ model->SetTargetListSample(predictedList);
+ model->PredictAll();
+}
+
+template <class TInputValue, class TOutputValue>
+void
+LearningApplicationBase<TInputValue,TOutputValue>
+::Train(typename ListSampleType::Pointer trainingListSample,
+ typename TargetListSampleType::Pointer trainingLabeledListSample,
+ std::string modelPath)
+{
+ // get the name of the chosen machine learning model
+ const std::string modelName = GetParameterString("classifier");
+ // call specific train function
+ if (modelName == "libsvm")
+ {
+ #ifdef OTB_USE_LIBSVM
+ TrainLibSVM(trainingListSample, trainingLabeledListSample, modelPath);
+ #else
+ otbAppLogFATAL("Module LIBSVM is not installed. You should consider turning OTB_USE_LIBSVM on during cmake configuration.");
+ #endif
+ }
+ else if (modelName == "svm")
+ {
+ #ifdef OTB_USE_OPENCV
+ TrainSVM(trainingListSample, trainingLabeledListSample, modelPath);
+ #else
+ otbAppLogFATAL("Module OPENCV is not installed. You should consider turning OTB_USE_OPENCV on during cmake configuration.");
+ #endif
+ }
+ else if (modelName == "boost")
+ {
+ #ifdef OTB_USE_OPENCV
+ TrainBoost(trainingListSample, trainingLabeledListSample, modelPath);
+ #else
+ otbAppLogFATAL("Module OPENCV is not installed. You should consider turning OTB_USE_OPENCV on during cmake configuration.");
+ #endif
+ }
+ else if (modelName == "dt")
+ {
+ #ifdef OTB_USE_OPENCV
+ TrainDecisionTree(trainingListSample, trainingLabeledListSample, modelPath);
+ #else
+ otbAppLogFATAL("Module OPENCV is not installed. You should consider turning OTB_USE_OPENCV on during cmake configuration.");
+ #endif
+ }
+ else if (modelName == "gbt")
+ {
+ #ifdef OTB_USE_OPENCV
+ TrainGradientBoostedTree(trainingListSample, trainingLabeledListSample, modelPath);
+ #else
+ otbAppLogFATAL("Module OPENCV is not installed. You should consider turning OTB_USE_OPENCV on during cmake configuration.");
+ #endif
+ }
+ else if (modelName == "ann")
+ {
+ #ifdef OTB_USE_OPENCV
+ TrainNeuralNetwork(trainingListSample, trainingLabeledListSample, modelPath);
+ #else
+ otbAppLogFATAL("Module OPENCV is not installed. You should consider turning OTB_USE_OPENCV on during cmake configuration.");
+ #endif
+ }
+ else if (modelName == "bayes")
+ {
+ #ifdef OTB_USE_OPENCV
+ TrainNormalBayes(trainingListSample, trainingLabeledListSample, modelPath);
+ #else
+ otbAppLogFATAL("Module OPENCV is not installed. You should consider turning OTB_USE_OPENCV on during cmake configuration.");
+ #endif
+ }
+ else if (modelName == "rf")
+ {
+ #ifdef OTB_USE_OPENCV
+ TrainRandomForests(trainingListSample, trainingLabeledListSample, modelPath);
+ #else
+ otbAppLogFATAL("Module OPENCV is not installed. You should consider turning OTB_USE_OPENCV on during cmake configuration.");
+ #endif
+ }
+ else if (modelName == "knn")
+ {
+ #ifdef OTB_USE_OPENCV
+ TrainKNN(trainingListSample, trainingLabeledListSample, modelPath);
+ #else
+ otbAppLogFATAL("Module OPENCV is not installed. You should consider turning OTB_USE_OPENCV on during cmake configuration.");
+ #endif
+ }
+}
+
+}
+}
+
+#endif
diff --git a/Modules/Applications/AppClassification/app/otbTrainBoost.cxx b/Modules/Applications/AppClassification/include/otbTrainBoost.txx
similarity index 82%
rename from Modules/Applications/AppClassification/app/otbTrainBoost.cxx
rename to Modules/Applications/AppClassification/include/otbTrainBoost.txx
index c107f8016ea1bdecaf2ca9a68c8af259184715c2..23e666bfc1d877072b41312ce0478a8a41036500 100644
--- a/Modules/Applications/AppClassification/app/otbTrainBoost.cxx
+++ b/Modules/Applications/AppClassification/include/otbTrainBoost.txx
@@ -14,16 +14,19 @@
PURPOSE. See the above copyright notices for more information.
=========================================================================*/
-
-#include "otbTrainImagesClassifier.h"
-
+#ifndef __otbTrainBoost_txx
+#define __otbTrainBoost_txx
+#include "otbLearningApplicationBase.h"
namespace otb
{
namespace Wrapper
{
-#ifdef OTB_USE_OPENCV
- void TrainImagesClassifier::InitBoostParams()
+
+ template <class TInputValue, class TOutputValue>
+ void
+ LearningApplicationBase<TInputValue,TOutputValue>
+ ::InitBoostParams()
{
AddChoice("classifier.boost", "Boost classifier");
SetParameterDescription("classifier.boost", "This group of parameters allows to set Boost classifier parameters. "
@@ -55,10 +58,15 @@ namespace Wrapper
SetParameterDescription("classifier.boost.m","Maximum depth of the tree.");
}
-
- void TrainImagesClassifier::TrainBoost(ListSampleType::Pointer trainingListSample, LabelListSampleType::Pointer trainingLabeledListSample)
+ template <class TInputValue, class TOutputValue>
+ void
+ LearningApplicationBase<TInputValue,TOutputValue>
+ ::TrainBoost(typename ListSampleType::Pointer trainingListSample,
+ typename TargetListSampleType::Pointer trainingLabeledListSample,
+ std::string modelPath)
{
- BoostType::Pointer boostClassifier = BoostType::New();
+ typename BoostType::Pointer boostClassifier = BoostType::New();
+ boostClassifier->SetRegressionMode(this->m_RegressionFlag);
boostClassifier->SetInputListSample(trainingListSample);
boostClassifier->SetTargetListSample(trainingLabeledListSample);
boostClassifier->SetBoostType(GetParameterInt("classifier.boost.t"));
@@ -67,9 +75,10 @@ namespace Wrapper
boostClassifier->SetMaxDepth(GetParameterInt("classifier.boost.m"));
boostClassifier->Train();
- boostClassifier->Save(GetParameterString("io.out"));
+ boostClassifier->Save(modelPath);
}
-#endif
} //end namespace wrapper
} //end namespace otb
+
+#endif
diff --git a/Modules/Applications/AppClassification/app/otbTrainDecisionTree.cxx b/Modules/Applications/AppClassification/include/otbTrainDecisionTree.txx
similarity index 86%
rename from Modules/Applications/AppClassification/app/otbTrainDecisionTree.cxx
rename to Modules/Applications/AppClassification/include/otbTrainDecisionTree.txx
index 9f94a7fc6050bb13a2169242619e8232f32d47c3..04df9380caacca8975caf05f8bb0b6b8237d0ff5 100644
--- a/Modules/Applications/AppClassification/app/otbTrainDecisionTree.cxx
+++ b/Modules/Applications/AppClassification/include/otbTrainDecisionTree.txx
@@ -14,15 +14,19 @@
PURPOSE. See the above copyright notices for more information.
=========================================================================*/
-
-#include "otbTrainImagesClassifier.h"
+#ifndef __otbTrainDecisionTree_txx
+#define __otbTrainDecisionTree_txx
+#include "otbLearningApplicationBase.h"
namespace otb
{
namespace Wrapper
{
-#ifdef OTB_USE_OPENCV
-void TrainImagesClassifier::InitDecisionTreeParams()
+
+template <class TInputValue, class TOutputValue>
+void
+LearningApplicationBase<TInputValue,TOutputValue>
+::InitDecisionTreeParams()
{
AddChoice("classifier.dt", "Decision Tree classifier");
SetParameterDescription("classifier.dt",
@@ -81,10 +85,15 @@ void TrainImagesClassifier::InitDecisionTreeParams()
}
-void TrainImagesClassifier::TrainDecisionTree(ListSampleType::Pointer trainingListSample,
- LabelListSampleType::Pointer trainingLabeledListSample)
+template <class TInputValue, class TOutputValue>
+void
+LearningApplicationBase<TInputValue,TOutputValue>
+::TrainDecisionTree(typename ListSampleType::Pointer trainingListSample,
+ typename TargetListSampleType::Pointer trainingLabeledListSample,
+ std::string modelPath)
{
- DecisionTreeType::Pointer classifier = DecisionTreeType::New();
+ typename DecisionTreeType::Pointer classifier = DecisionTreeType::New();
+ classifier->SetRegressionMode(this->m_RegressionFlag);
classifier->SetInputListSample(trainingListSample);
classifier->SetTargetListSample(trainingLabeledListSample);
classifier->SetMaxDepth(GetParameterInt("classifier.dt.max"));
@@ -101,8 +110,10 @@ void TrainImagesClassifier::TrainDecisionTree(ListSampleType::Pointer trainingLi
classifier->SetTruncatePrunedTree(false);
}
classifier->Train();
- classifier->Save(GetParameterString("io.out"));
+ classifier->Save(modelPath);
}
-#endif
+
} //end namespace wrapper
} //end namespace otb
+
+#endif
diff --git a/Modules/Applications/AppClassification/app/otbTrainGradientBoostedTree.cxx b/Modules/Applications/AppClassification/include/otbTrainGradientBoostedTree.txx
similarity index 63%
rename from Modules/Applications/AppClassification/app/otbTrainGradientBoostedTree.cxx
rename to Modules/Applications/AppClassification/include/otbTrainGradientBoostedTree.txx
index c703ad4c57a0d8efb8103dadc64a92701a16d162..b55612581cd1140185ae53eab3ae407c51536b6b 100644
--- a/Modules/Applications/AppClassification/app/otbTrainGradientBoostedTree.cxx
+++ b/Modules/Applications/AppClassification/include/otbTrainGradientBoostedTree.txx
@@ -14,23 +14,34 @@
PURPOSE. See the above copyright notices for more information.
=========================================================================*/
-
-#include "otbTrainImagesClassifier.h"
+#ifndef __otbTrainGradientBoostedTree_txx
+#define __otbTrainGradientBoostedTree_txx
+#include "otbLearningApplicationBase.h"
namespace otb
{
namespace Wrapper
{
-#ifdef OTB_USE_OPENCV
-void TrainImagesClassifier::InitGradientBoostedTreeParams()
+
+template <class TInputValue, class TOutputValue>
+void
+LearningApplicationBase<TInputValue,TOutputValue>
+::InitGradientBoostedTreeParams()
{
AddChoice("classifier.gbt", "Gradient Boosted Tree classifier");
SetParameterDescription(
"classifier.gbt",
"This group of parameters allows to set Gradient Boosted Tree classifier parameters. "
"See complete documentation here \\url{http://docs.opencv.org/modules/ml/doc/gradient_boosted_trees.html}.");
- //LossFunctionType : not exposed, as only one type is used for Classification,
- // the other three are used for regression.
+
+ if (m_RegressionFlag)
+ {
+ AddParameter(ParameterType_Choice, "classifier.gbt.t", "Loss Function Type");
+ SetParameterDescription("classifier.gbt.t","Type of loss functionused for training.");
+ AddChoice("classifier.gbt.t.sqr","Squared Loss");
+ AddChoice("classifier.gbt.t.abs","Absolute Loss");
+ AddChoice("classifier.gbt.t.hub","Huber Loss");
+ }
//WeakCount
AddParameter(ParameterType_Int, "classifier.gbt.w", "Number of boosting algorithm iterations");
@@ -67,10 +78,15 @@ void TrainImagesClassifier::InitGradientBoostedTreeParams()
}
-void TrainImagesClassifier::TrainGradientBoostedTree(
- ListSampleType::Pointer trainingListSample, LabelListSampleType::Pointer trainingLabeledListSample)
+template <class TInputValue, class TOutputValue>
+void
+LearningApplicationBase<TInputValue,TOutputValue>
+::TrainGradientBoostedTree(typename ListSampleType::Pointer trainingListSample,
+ typename TargetListSampleType::Pointer trainingLabeledListSample,
+ std::string modelPath)
{
- GradientBoostedTreeType::Pointer classifier = GradientBoostedTreeType::New();
+ typename GradientBoostedTreeType::Pointer classifier = GradientBoostedTreeType::New();
+ classifier->SetRegressionMode(this->m_RegressionFlag);
classifier->SetInputListSample(trainingListSample);
classifier->SetTargetListSample(trainingLabeledListSample);
classifier->SetWeakCount(GetParameterInt("classifier.gbt.w"));
@@ -78,9 +94,34 @@ void TrainImagesClassifier::TrainGradientBoostedTree(
classifier->SetSubSamplePortion(GetParameterFloat("classifier.gbt.p"));
classifier->SetMaxDepth(GetParameterInt("classifier.gbt.max"));
+ if (m_RegressionFlag)
+ {
+ switch (GetParameterInt("classifier.gbt.t"))
+ {
+ case 0: // SQUARED_LOSS
+ classifier->SetLossFunctionType(CvGBTrees::SQUARED_LOSS);
+ break;
+ case 1: // ABSOLUTE_LOSS
+ classifier->SetLossFunctionType(CvGBTrees::ABSOLUTE_LOSS);
+ break;
+ case 2: // HUBER_LOSS
+ classifier->SetLossFunctionType(CvGBTrees::HUBER_LOSS);
+ break;
+ default:
+ classifier->SetLossFunctionType(CvGBTrees::SQUARED_LOSS);
+ break;
+ }
+ }
+ else
+ {
+ classifier->SetLossFunctionType(CvGBTrees::DEVIANCE_LOSS);
+ }
+
classifier->Train();
- classifier->Save(GetParameterString("io.out"));
+ classifier->Save(modelPath);
}
-#endif
+
} //end namespace wrapper
} //end namespace otb
+
+#endif
diff --git a/Modules/Applications/AppClassification/include/otbTrainKNN.txx b/Modules/Applications/AppClassification/include/otbTrainKNN.txx
new file mode 100644
index 0000000000000000000000000000000000000000..93656003a1b24e601a630393983934bb65b5e797
--- /dev/null
+++ b/Modules/Applications/AppClassification/include/otbTrainKNN.txx
@@ -0,0 +1,86 @@
+/*=========================================================================
+ Program: ORFEO Toolbox
+ Language: C++
+ Date: $Date$
+ Version: $Revision$
+
+
+ Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
+ See OTBCopyright.txt for details.
+
+
+ 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.
+
+ =========================================================================*/
+#ifndef __otbTrainKNN_txx
+#define __otbTrainKNN_txx
+#include "otbLearningApplicationBase.h"
+
+namespace otb
+{
+namespace Wrapper
+{
+
+ template <class TInputValue, class TOutputValue>
+ void
+ LearningApplicationBase<TInputValue,TOutputValue>
+ ::InitKNNParams()
+ {
+ AddChoice("classifier.knn", "KNN classifier");
+ SetParameterDescription("classifier.knn", "This group of parameters allows to set KNN classifier parameters. "
+ "See complete documentation here \\url{http://docs.opencv.org/modules/ml/doc/k_nearest_neighbors.html}.");
+
+ //K parameter
+ AddParameter(ParameterType_Int, "classifier.knn.k", "Number of Neighbors");
+ SetParameterInt("classifier.knn.k", 32);
+ SetParameterDescription("classifier.knn.k","The number of neighbors to use.");
+
+ if (this->m_RegressionFlag)
+ {
+ // Decision rule : mean / median
+ AddParameter(ParameterType_Choice, "classifier.knn.rule", "Decision rule");
+ SetParameterDescription("classifier.knn.rule", "Decision rule for regression output");
+
+ AddChoice("classifier.knn.rule.mean", "Mean of neighbors values");
+ SetParameterDescription("classifier.knn.rule.mean","Returns the mean of neighbors values");
+
+ AddChoice("classifier.knn.rule.median", "Median of neighbors values");
+ SetParameterDescription("classifier.knn.rule.median","Returns the median of neighbors values");
+ }
+ }
+
+ template <class TInputValue, class TOutputValue>
+ void
+ LearningApplicationBase<TInputValue,TOutputValue>
+ ::TrainKNN(typename ListSampleType::Pointer trainingListSample,
+ typename TargetListSampleType::Pointer trainingLabeledListSample,
+ std::string modelPath)
+ {
+ typename KNNType::Pointer knnClassifier = KNNType::New();
+ knnClassifier->SetRegressionMode(this->m_RegressionFlag);
+ knnClassifier->SetInputListSample(trainingListSample);
+ knnClassifier->SetTargetListSample(trainingLabeledListSample);
+ knnClassifier->SetK(GetParameterInt("classifier.knn.k"));
+ if (this->m_RegressionFlag)
+ {
+ std::string decision = this->GetParameterString("classifier.knn.rule");
+ if (decision == "mean")
+ {
+ knnClassifier->SetDecisionRule(KNNType::KNN_MEAN);
+ }
+ else if (decision == "median")
+ {
+ knnClassifier->SetDecisionRule(KNNType::KNN_MEDIAN);
+ }
+ }
+
+ knnClassifier->Train();
+ knnClassifier->Save(modelPath);
+ }
+
+} //end namespace wrapper
+} //end namespace otb
+
+#endif
diff --git a/Modules/Applications/AppClassification/app/otbTrainLibSVM.cxx b/Modules/Applications/AppClassification/include/otbTrainLibSVM.txx
similarity index 52%
rename from Modules/Applications/AppClassification/app/otbTrainLibSVM.cxx
rename to Modules/Applications/AppClassification/include/otbTrainLibSVM.txx
index e117337708d3effd267a462a1d24f8b2f6736e18..928245655fd30d983c970947feef81dbd0c8304f 100644
--- a/Modules/Applications/AppClassification/app/otbTrainLibSVM.cxx
+++ b/Modules/Applications/AppClassification/include/otbTrainLibSVM.txx
@@ -14,16 +14,19 @@
PURPOSE. See the above copyright notices for more information.
=========================================================================*/
-
-#include "otbTrainImagesClassifier.h"
-
+#ifndef __otbTrainLibSVM_txx
+#define __otbTrainLibSVM_txx
+#include "otbLearningApplicationBase.h"
namespace otb
{
namespace Wrapper
{
-#ifdef OTB_USE_LIBSVM
- void TrainImagesClassifier::InitLibSVMParams()
+
+ template <class TInputValue, class TOutputValue>
+ void
+ LearningApplicationBase<TInputValue,TOutputValue>
+ ::InitLibSVMParams()
{
AddChoice("classifier.libsvm", "LibSVM classifier");
SetParameterDescription("classifier.libsvm", "This group of parameters allows to set SVM classifier parameters.");
@@ -34,6 +37,21 @@ namespace Wrapper
AddChoice("classifier.libsvm.k.sigmoid", "Sigmoid");
SetParameterString("classifier.libsvm.k", "linear");
SetParameterDescription("classifier.libsvm.k", "SVM Kernel Type.");
+ AddParameter(ParameterType_Choice, "classifier.libsvm.m", "SVM Model Type");
+ SetParameterDescription("classifier.libsvm.m", "Type of SVM formulation.");
+ if (this->m_RegressionFlag)
+ {
+ AddChoice("classifier.libsvm.m.epssvr", "Epsilon Support Vector Regression");
+ AddChoice("classifier.libsvm.m.nusvr", "Nu Support Vector Regression");
+ SetParameterString("classifier.libsvm.m", "epssvr");
+ }
+ else
+ {
+ AddChoice("classifier.libsvm.m.csvc", "C support vector classification");
+ AddChoice("classifier.libsvm.m.nusvc", "Nu support vector classification");
+ AddChoice("classifier.libsvm.m.oneclass", "Distribution estimation (One Class SVM)");
+ SetParameterString("classifier.libsvm.m", "csvc");
+ }
AddParameter(ParameterType_Float, "classifier.libsvm.c", "Cost parameter C");
SetParameterFloat("classifier.libsvm.c", 1.0);
SetParameterDescription(
@@ -45,12 +63,25 @@ namespace Wrapper
AddParameter(ParameterType_Empty, "classifier.libsvm.prob", "Probability estimation");
MandatoryOff("classifier.libsvm.prob");
SetParameterDescription("classifier.libsvm.prob", "Probability estimation flag.");
- }
+ if (this->m_RegressionFlag)
+ {
+ AddParameter(ParameterType_Float, "classifier.libsvm.eps", "Epsilon");
+ SetParameterFloat("classifier.libsvm.eps", 1e-3);
+ AddParameter(ParameterType_Float, "classifier.libsvm.nu", "Nu");
+ SetParameterFloat("classifier.libsvm.nu", 0.5);
+ }
+ }
- void TrainImagesClassifier::TrainLibSVM(ListSampleType::Pointer trainingListSample, LabelListSampleType::Pointer trainingLabeledListSample)
+ template <class TInputValue, class TOutputValue>
+ void
+ LearningApplicationBase<TInputValue,TOutputValue>
+ ::TrainLibSVM(typename ListSampleType::Pointer trainingListSample,
+ typename TargetListSampleType::Pointer trainingLabeledListSample,
+ std::string modelPath)
{
- LibSVMType::Pointer libSVMClassifier = LibSVMType::New();
+ typename LibSVMType::Pointer libSVMClassifier = LibSVMType::New();
+ libSVMClassifier->SetRegressionMode(this->m_RegressionFlag);
libSVMClassifier->SetInputListSample(trainingListSample);
libSVMClassifier->SetTargetListSample(trainingLabeledListSample);
//SVM Option
@@ -83,9 +114,47 @@ namespace Wrapper
libSVMClassifier->SetKernelType(LINEAR);
break;
}
+ if (this->m_RegressionFlag)
+ {
+ switch (GetParameterInt("classifier.libsvm.m"))
+ {
+ case 0: // EPSILON_SVR
+ libSVMClassifier->SetSVMType(EPSILON_SVR);
+ break;
+ case 1: // NU_SVR
+ libSVMClassifier->SetSVMType(NU_SVR);
+ break;
+ default:
+ libSVMClassifier->SetSVMType(EPSILON_SVR);
+ break;
+ }
+ libSVMClassifier->SetEpsilon(GetParameterFloat("classifier.libsvm.eps"));
+ libSVMClassifier->SetNu(GetParameterFloat("classifier.libsvm.nu"));
+ }
+ else
+ {
+ switch (GetParameterInt("classifier.libsvm.m"))
+ {
+ case 0: // C_SVC
+ libSVMClassifier->SetSVMType(C_SVC);
+ break;
+ case 1: // NU_SVC
+ libSVMClassifier->SetSVMType(NU_SVC);
+ break;
+ case 2: // ONE_CLASS
+ libSVMClassifier->SetSVMType(ONE_CLASS);
+ break;
+ default:
+ libSVMClassifier->SetSVMType(C_SVC);
+ break;
+ }
+ }
+
libSVMClassifier->Train();
- libSVMClassifier->Save(GetParameterString("io.out"));
+ libSVMClassifier->Save(modelPath);
}
-#endif
+
} //end namespace wrapper
} //end namespace otb
+
+#endif
diff --git a/Modules/Applications/AppClassification/app/otbTrainNeuralNetwork.cxx b/Modules/Applications/AppClassification/include/otbTrainNeuralNetwork.txx
similarity index 87%
rename from Modules/Applications/AppClassification/app/otbTrainNeuralNetwork.cxx
rename to Modules/Applications/AppClassification/include/otbTrainNeuralNetwork.txx
index 29b3657ad2ef612a89a83f923cf370c3a9bbbc5c..40f120f69bcaa1df15454070d63e38feda46e960 100644
--- a/Modules/Applications/AppClassification/app/otbTrainNeuralNetwork.cxx
+++ b/Modules/Applications/AppClassification/include/otbTrainNeuralNetwork.txx
@@ -14,16 +14,20 @@
PURPOSE. See the above copyright notices for more information.
=========================================================================*/
-
+#ifndef __otbTrainNeuralNetwork_txx
+#define __otbTrainNeuralNetwork_txx
#include <boost/lexical_cast.hpp>
-#include "otbTrainImagesClassifier.h"
+#include "otbLearningApplicationBase.h"
namespace otb
{
namespace Wrapper
{
-#ifdef OTB_USE_OPENCV
-void TrainImagesClassifier::InitNeuralNetworkParams()
+
+template <class TInputValue, class TOutputValue>
+void
+LearningApplicationBase<TInputValue,TOutputValue>
+::InitNeuralNetworkParams()
{
AddChoice("classifier.ann", "Artificial Neural Network classifier");
SetParameterDescription("classifier.ann",
@@ -119,10 +123,15 @@ void TrainImagesClassifier::InitNeuralNetworkParams()
}
-void TrainImagesClassifier::TrainNeuralNetwork(ListSampleType::Pointer trainingListSample,
- LabelListSampleType::Pointer trainingLabeledListSample)
+template <class TInputValue, class TOutputValue>
+void
+LearningApplicationBase<TInputValue,TOutputValue>
+::TrainNeuralNetwork(typename ListSampleType::Pointer trainingListSample,
+ typename TargetListSampleType::Pointer trainingLabeledListSample,
+ std::string modelPath)
{
- NeuralNetworkType::Pointer classifier = NeuralNetworkType::New();
+ typename NeuralNetworkType::Pointer classifier = NeuralNetworkType::New();
+ classifier->SetRegressionMode(this->m_RegressionFlag);
classifier->SetInputListSample(trainingListSample);
classifier->SetTargetListSample(trainingLabeledListSample);
@@ -153,18 +162,23 @@ void TrainImagesClassifier::TrainNeuralNetwork(ListSampleType::Pointer trainingL
unsigned int nbClasses = 0;
- LabelType currentLabel = 0, prevLabel = 0;
- for (unsigned int itLab = 0; itLab < trainingLabeledListSample->Size(); ++itLab)
+ if (this->m_RegressionFlag)
+ {
+ layerSizes.push_back(1);
+ }
+ else
{
- currentLabel = trainingLabeledListSample->GetMeasurementVector(itLab);
- if ((currentLabel != prevLabel) || (itLab == 0))
+ std::set<TargetValueType> labelSet;
+ TargetSampleType currentLabel;
+ for (unsigned int itLab = 0; itLab < trainingLabeledListSample->Size(); ++itLab)
{
- ++nbClasses;
+ currentLabel = trainingLabeledListSample->GetMeasurementVector(itLab);
+ labelSet.insert(currentLabel[0]);
}
- prevLabel = currentLabel;
+ nbClasses = labelSet.size();
+ layerSizes.push_back(nbClasses);
}
- layerSizes.push_back(nbClasses);
classifier->SetLayerSizes(layerSizes);
switch (GetParameterInt("classifier.ann.f"))
@@ -208,8 +222,10 @@ void TrainImagesClassifier::TrainNeuralNetwork(ListSampleType::Pointer trainingL
classifier->SetEpsilon(GetParameterFloat("classifier.ann.eps"));
classifier->SetMaxIter(GetParameterInt("classifier.ann.iter"));
classifier->Train();
- classifier->Save(GetParameterString("io.out"));
+ classifier->Save(modelPath);
}
-#endif
+
} //end namespace wrapper
} //end namespace otb
+
+#endif
diff --git a/Modules/Applications/AppClassification/app/otbTrainNormalBayes.cxx b/Modules/Applications/AppClassification/include/otbTrainNormalBayes.txx
similarity index 59%
rename from Modules/Applications/AppClassification/app/otbTrainNormalBayes.cxx
rename to Modules/Applications/AppClassification/include/otbTrainNormalBayes.txx
index d33e6eaf9cd79a99120a5176b096a94fb98b190c..d5f3cce8e3ef2ae3fbe02a2b21e99d0004df3944 100644
--- a/Modules/Applications/AppClassification/app/otbTrainNormalBayes.cxx
+++ b/Modules/Applications/AppClassification/include/otbTrainNormalBayes.txx
@@ -14,16 +14,19 @@
PURPOSE. See the above copyright notices for more information.
=========================================================================*/
-
-#include "otbTrainImagesClassifier.h"
-
+#ifndef __otbTrainNormalBayes_txx
+#define __otbTrainNormalBayes_txx
+#include "otbLearningApplicationBase.h"
namespace otb
{
namespace Wrapper
{
-#ifdef OTB_USE_OPENCV
- void TrainImagesClassifier::InitNormalBayesParams()
+
+ template <class TInputValue, class TOutputValue>
+ void
+ LearningApplicationBase<TInputValue,TOutputValue>
+ ::InitNormalBayesParams()
{
AddChoice("classifier.bayes", "Normal Bayes classifier");
SetParameterDescription("classifier.bayes", "Use a Normal Bayes Classifier. "
@@ -31,15 +34,22 @@ namespace Wrapper
}
-
- void TrainImagesClassifier::TrainNormalBayes(ListSampleType::Pointer trainingListSample, LabelListSampleType::Pointer trainingLabeledListSample)
+ template <class TInputValue, class TOutputValue>
+ void
+ LearningApplicationBase<TInputValue,TOutputValue>
+ ::TrainNormalBayes(typename ListSampleType::Pointer trainingListSample,
+ typename TargetListSampleType::Pointer trainingLabeledListSample,
+ std::string modelPath)
{
- NormalBayesType::Pointer classifier = NormalBayesType::New();
+ typename NormalBayesType::Pointer classifier = NormalBayesType::New();
+ classifier->SetRegressionMode(this->m_RegressionFlag);
classifier->SetInputListSample(trainingListSample);
classifier->SetTargetListSample(trainingLabeledListSample);
classifier->Train();
- classifier->Save(GetParameterString("io.out"));
+ classifier->Save(modelPath);
}
-#endif
+
} //end namespace wrapper
} //end namespace otb
+
+#endif
diff --git a/Modules/Applications/AppClassification/app/otbTrainRandomForests.cxx b/Modules/Applications/AppClassification/include/otbTrainRandomForests.txx
similarity index 87%
rename from Modules/Applications/AppClassification/app/otbTrainRandomForests.cxx
rename to Modules/Applications/AppClassification/include/otbTrainRandomForests.txx
index 1798b9d9b59b7ffa2323936084736b6b423a3cb5..a856243a300dfc35d559e683aef21268d8c25a12 100644
--- a/Modules/Applications/AppClassification/app/otbTrainRandomForests.cxx
+++ b/Modules/Applications/AppClassification/include/otbTrainRandomForests.txx
@@ -14,15 +14,19 @@
PURPOSE. See the above copyright notices for more information.
=========================================================================*/
-
-#include "otbTrainImagesClassifier.h"
+#ifndef __otbTrainRandomForests_txx
+#define __otbTrainRandomForests_txx
+#include "otbLearningApplicationBase.h"
namespace otb
{
namespace Wrapper
{
-#ifdef OTB_USE_OPENCV
-void TrainImagesClassifier::InitRandomForestsParams()
+
+template <class TInputValue, class TOutputValue>
+void
+LearningApplicationBase<TInputValue,TOutputValue>
+::InitRandomForestsParams()
{
AddChoice("classifier.rf", "Random forests classifier");
SetParameterDescription("classifier.rf",
@@ -95,10 +99,15 @@ void TrainImagesClassifier::InitRandomForestsParams()
//TerminationCriteria not exposed
}
-void TrainImagesClassifier::TrainRandomForests(ListSampleType::Pointer trainingListSample,
- LabelListSampleType::Pointer trainingLabeledListSample)
+template <class TInputValue, class TOutputValue>
+void
+LearningApplicationBase<TInputValue,TOutputValue>
+::TrainRandomForests(typename ListSampleType::Pointer trainingListSample,
+ typename TargetListSampleType::Pointer trainingLabeledListSample,
+ std::string modelPath)
{
- RandomForestType::Pointer classifier = RandomForestType::New();
+ typename RandomForestType::Pointer classifier = RandomForestType::New();
+ classifier->SetRegressionMode(this->m_RegressionFlag);
classifier->SetInputListSample(trainingListSample);
classifier->SetTargetListSample(trainingLabeledListSample);
classifier->SetMaxDepth(GetParameterInt("classifier.rf.max"));
@@ -110,8 +119,10 @@ void TrainImagesClassifier::TrainRandomForests(ListSampleType::Pointer trainingL
classifier->SetForestAccuracy(GetParameterFloat("classifier.rf.acc"));
classifier->Train();
- classifier->Save(GetParameterString("io.out"));
+ classifier->Save(modelPath);
}
-#endif
+
} //end namespace wrapper
} //end namespace otb
+
+#endif
diff --git a/Modules/Applications/AppClassification/app/otbTrainSVM.cxx b/Modules/Applications/AppClassification/include/otbTrainSVM.txx
similarity index 57%
rename from Modules/Applications/AppClassification/app/otbTrainSVM.cxx
rename to Modules/Applications/AppClassification/include/otbTrainSVM.txx
index a41e103746f5f5d7968f26220791436232caac74..ac0f153ed4f78df8c5a7d838c3e32beed62ddd9f 100644
--- a/Modules/Applications/AppClassification/app/otbTrainSVM.cxx
+++ b/Modules/Applications/AppClassification/include/otbTrainSVM.txx
@@ -14,28 +14,38 @@
PURPOSE. See the above copyright notices for more information.
=========================================================================*/
-
-#include "otbTrainImagesClassifier.h"
-
+#ifndef __otbTrainSVM_txx
+#define __otbTrainSVM_txx
+#include "otbLearningApplicationBase.h"
namespace otb
{
namespace Wrapper
{
-#ifdef OTB_USE_OPENCV
- void TrainImagesClassifier::InitSVMParams()
+
+ template <class TInputValue, class TOutputValue>
+ void
+ LearningApplicationBase<TInputValue,TOutputValue>
+ ::InitSVMParams()
{
AddChoice("classifier.svm", "SVM classifier (OpenCV)");
SetParameterDescription("classifier.svm", "This group of parameters allows to set SVM classifier parameters. "
"See complete documentation here \\url{http://docs.opencv.org/modules/ml/doc/support_vector_machines.html}.");
AddParameter(ParameterType_Choice, "classifier.svm.m", "SVM Model Type");
- AddChoice("classifier.svm.m.csvc", "C support vector classification");
- AddChoice("classifier.svm.m.nusvc", "Nu support vector classification");
- AddChoice("classifier.svm.m.oneclass", "Distribution estimation (One Class SVM)");
- //AddChoice("classifier.svm.m.epssvr", "Epsilon Support Vector Regression");
- //AddChoice("classifier.svm.m.nusvr", "Nu Support Vector Regression");
- SetParameterString("classifier.svm.m", "csvc");
SetParameterDescription("classifier.svm.m", "Type of SVM formulation.");
+ if (this->m_RegressionFlag)
+ {
+ AddChoice("classifier.svm.m.epssvr", "Epsilon Support Vector Regression");
+ AddChoice("classifier.svm.m.nusvr", "Nu Support Vector Regression");
+ SetParameterString("classifier.svm.m", "epssvr");
+ }
+ else
+ {
+ AddChoice("classifier.svm.m.csvc", "C support vector classification");
+ AddChoice("classifier.svm.m.nusvc", "Nu support vector classification");
+ AddChoice("classifier.svm.m.oneclass", "Distribution estimation (One Class SVM)");
+ SetParameterString("classifier.svm.m", "csvc");
+ }
AddParameter(ParameterType_Choice, "classifier.svm.k", "SVM Kernel Type");
AddChoice("classifier.svm.k.linear", "Linear");
AddChoice("classifier.svm.k.rbf", "Gaussian radial basis function");
@@ -52,9 +62,26 @@ namespace Wrapper
"Parameter nu of a SVM optimization problem (NU_SVC / ONE_CLASS)");
SetParameterFloat("classifier.svm.nu", 0.0);
SetParameterDescription("classifier.svm.nu", "Parameter nu of a SVM optimization problem.");
- //AddParameter(ParameterType_Float, "classifier.svm.p", "Parameter epsilon of a SVM optimization problem (EPS_SVR)");
- //SetParameterFloat("classifier.svm.p", 0.0);
- //SetParameterDescription("classifier.svm.p", "Parameter epsilon of a SVM optimization problem (EPS_SVR).");
+ if (this->m_RegressionFlag)
+ {
+ AddParameter(ParameterType_Float, "classifier.svm.p", "Parameter epsilon of a SVM optimization problem (EPS_SVR)");
+ SetParameterFloat("classifier.svm.p", 1.0);
+ SetParameterDescription("classifier.svm.p", "Parameter epsilon of a SVM optimization problem (EPS_SVR).");
+
+ AddParameter(ParameterType_Choice, "classifier.svm.term", "Termination criteria");
+ SetParameterDescription("classifier.svm.term","Termination criteria for iterative algorithm");
+ AddChoice("classifier.svm.term.iter", "Stops when maximum iteration is reached.");
+ AddChoice("classifier.svm.term.eps", "Stops when accuracy is lower than epsilon.");
+ AddChoice("classifier.svm.term.all", "Stops when either iteration or epsilon criteria is true");
+
+ AddParameter(ParameterType_Float, "classifier.svm.iter", "Maximum iteration");
+ SetParameterFloat("classifier.svm.iter", 1000);
+ SetParameterDescription("classifier.svm.iter", "Maximum number of iterations (corresponds to the termination criteria 'iter').");
+
+ AddParameter(ParameterType_Float, "classifier.svm.eps", "Epsilon accuracy threshold");
+ SetParameterFloat("classifier.svm.eps", FLT_EPSILON);
+ SetParameterDescription("classifier.svm.eps", "Epsilon accuracy (corresponds to the termination criteria 'eps').");
+ }
AddParameter(ParameterType_Float, "classifier.svm.coef0", "Parameter coef0 of a kernel function (POLY / SIGMOID)");
SetParameterFloat("classifier.svm.coef0", 0.0);
SetParameterDescription("classifier.svm.coef0", "Parameter coef0 of a kernel function (POLY / SIGMOID).");
@@ -76,9 +103,15 @@ namespace Wrapper
"because the samples are not identically processed within OpenCV.");
}
- void TrainImagesClassifier::TrainSVM(ListSampleType::Pointer trainingListSample, LabelListSampleType::Pointer trainingLabeledListSample)
+ template <class TInputValue, class TOutputValue>
+ void
+ LearningApplicationBase<TInputValue,TOutputValue>
+ ::TrainSVM(typename ListSampleType::Pointer trainingListSample,
+ typename TargetListSampleType::Pointer trainingLabeledListSample,
+ std::string modelPath)
{
- SVMType::Pointer SVMClassifier = SVMType::New();
+ typename SVMType::Pointer SVMClassifier = SVMType::New();
+ SVMClassifier->SetRegressionMode(this->m_RegressionFlag);
SVMClassifier->SetInputListSample(trainingListSample);
SVMClassifier->SetTargetListSample(trainingLabeledListSample);
switch (GetParameterInt("classifier.svm.k"))
@@ -104,36 +137,69 @@ namespace Wrapper
std::cout << "CvSVM::LINEAR = " << CvSVM::LINEAR << std::endl;
break;
}
- switch (GetParameterInt("classifier.svm.m"))
+ if (this->m_RegressionFlag)
{
- case 0: // C_SVC
- SVMClassifier->SetSVMType(CvSVM::C_SVC);
- std::cout << "CvSVM::C_SVC = " << CvSVM::C_SVC << std::endl;
- break;
- case 1: // NU_SVC
- SVMClassifier->SetSVMType(CvSVM::NU_SVC);
- std::cout << "CvSVM::NU_SVC = " << CvSVM::NU_SVC << std::endl;
- break;
- case 2: // ONE_CLASS
- SVMClassifier->SetSVMType(CvSVM::ONE_CLASS);
- std::cout << "CvSVM::ONE_CLASS = " << CvSVM::ONE_CLASS << std::endl;
- break;
- /*case 3: // EPS_SVR
- SVMClassifier->SetSVMType(CvSVM::EPS_SVR);
- std::cout<<"CvSVM::EPS_SVR = "<<CvSVM::EPS_SVR<<std::endl;
- break;
- case 4: // NU_SVR
- SVMClassifier->SetSVMType(CvSVM::NU_SVR);
- std::cout<<"CvSVM::NU_SVR = "<<CvSVM::NU_SVR<<std::endl;
- break; */
- default: // DEFAULT = C_SVC
- SVMClassifier->SetSVMType(CvSVM::C_SVC);
- std::cout << "CvSVM::C_SVC = " << CvSVM::C_SVC << std::endl;
- break;
+ switch (GetParameterInt("classifier.svm.m"))
+ {
+ case 0: // EPS_SVR
+ SVMClassifier->SetSVMType(CvSVM::EPS_SVR);
+ std::cout<<"CvSVM::EPS_SVR = "<<CvSVM::EPS_SVR<<std::endl;
+ break;
+ case 1: // NU_SVR
+ SVMClassifier->SetSVMType(CvSVM::NU_SVR);
+ std::cout<<"CvSVM::NU_SVR = "<<CvSVM::NU_SVR<<std::endl;
+ break;
+ default: // DEFAULT = EPS_SVR
+ SVMClassifier->SetSVMType(CvSVM::EPS_SVR);
+ std::cout << "CvSVM::EPS_SVR = " << CvSVM::EPS_SVR << std::endl;
+ break;
+ }
+ }
+ else
+ {
+ switch (GetParameterInt("classifier.svm.m"))
+ {
+ case 0: // C_SVC
+ SVMClassifier->SetSVMType(CvSVM::C_SVC);
+ std::cout << "CvSVM::C_SVC = " << CvSVM::C_SVC << std::endl;
+ break;
+ case 1: // NU_SVC
+ SVMClassifier->SetSVMType(CvSVM::NU_SVC);
+ std::cout << "CvSVM::NU_SVC = " << CvSVM::NU_SVC << std::endl;
+ break;
+ case 2: // ONE_CLASS
+ SVMClassifier->SetSVMType(CvSVM::ONE_CLASS);
+ std::cout << "CvSVM::ONE_CLASS = " << CvSVM::ONE_CLASS << std::endl;
+ break;
+ default: // DEFAULT = C_SVC
+ SVMClassifier->SetSVMType(CvSVM::C_SVC);
+ std::cout << "CvSVM::C_SVC = " << CvSVM::C_SVC << std::endl;
+ break;
+ }
}
SVMClassifier->SetC(GetParameterFloat("classifier.svm.c"));
SVMClassifier->SetNu(GetParameterFloat("classifier.svm.nu"));
- //SVMClassifier->SetP(GetParameterFloat("classifier.svm.p"));
+ if (this->m_RegressionFlag)
+ {
+ SVMClassifier->SetP(GetParameterFloat("classifier.svm.p"));
+ switch (GetParameterInt("classifier.svm.term"))
+ {
+ case 0: // ITER
+ SVMClassifier->SetTermCriteriaType(CV_TERMCRIT_ITER);
+ break;
+ case 1: // EPS
+ SVMClassifier->SetTermCriteriaType(CV_TERMCRIT_EPS);
+ break;
+ case 2: // ITER+EPS
+ SVMClassifier->SetTermCriteriaType(CV_TERMCRIT_ITER+CV_TERMCRIT_EPS);
+ break;
+ default:
+ SVMClassifier->SetTermCriteriaType(CV_TERMCRIT_ITER);
+ break;
+ }
+ SVMClassifier->SetMaxIter(GetParameterInt("classifier.svm.iter"));
+ SVMClassifier->SetEpsilon(GetParameterFloat("classifier.svm.eps"));
+ }
SVMClassifier->SetCoef0(GetParameterFloat("classifier.svm.coef0"));
SVMClassifier->SetGamma(GetParameterFloat("classifier.svm.gamma"));
SVMClassifier->SetDegree(GetParameterFloat("classifier.svm.degree"));
@@ -142,17 +208,21 @@ namespace Wrapper
SVMClassifier->SetParameterOptimization(true);
}
SVMClassifier->Train();
- SVMClassifier->Save(GetParameterString("io.out"));
+ SVMClassifier->Save(modelPath);
// Update the displayed parameters in the GUI after the training process, for further use of them
SetParameterFloat("classifier.svm.c", static_cast<float> (SVMClassifier->GetOutputC()));
SetParameterFloat("classifier.svm.nu", static_cast<float> (SVMClassifier->GetOutputNu()));
- //SetParameterFloat("classifier.svm.p", static_cast<float> (SVMClassifier->GetOutputP()));
+ if (this->m_RegressionFlag)
+ {
+ SetParameterFloat("classifier.svm.p", static_cast<float> (SVMClassifier->GetOutputP()));
+ }
SetParameterFloat("classifier.svm.coef0", static_cast<float> (SVMClassifier->GetOutputCoef0()));
SetParameterFloat("classifier.svm.gamma", static_cast<float> (SVMClassifier->GetOutputGamma()));
SetParameterFloat("classifier.svm.degree", static_cast<float> (SVMClassifier->GetOutputDegree()));
}
-#endif
} //end namespace wrapper
} //end namespace otb
+
+#endif
diff --git a/Modules/Applications/AppClassification/test/CMakeLists.txt b/Modules/Applications/AppClassification/test/CMakeLists.txt
index c4e275fe5a33fc8e629a13c9016a5584c8a4b0a3..63a5c0918f5df9138ab25e78968b8305743f2409 100644
--- a/Modules/Applications/AppClassification/test/CMakeLists.txt
+++ b/Modules/Applications/AppClassification/test/CMakeLists.txt
@@ -841,3 +841,36 @@ otb_test_application(NAME cdbTvVectorDataDSValidationWrongRoads_LI
${OTBAPP_BASELINE_FILES}/cdbTvVectorDataDSValidationOutpout_LI_wr.shp
${TEMP}/cdbTvVectorDataDSValidationOutpout_LI_wr.shp)
+if(OTB_USE_OPENCV)
+#----------- TrainRegression TESTS ----------------
+# y = 0.01*x^2 + 1.5*x - 300
+otb_test_application(NAME apTvClTrainRegressionTest_monovar
+ APP TrainRegression
+ OPTIONS -io.il ${INPUTDATA}/QB_Toulouse_Ortho_regression.tif
+ -io.imstat ${INPUTDATA}/QB_Toulouse_Ortho_regression.xml
+ -io.out ${TEMP}/apTvClTrainRegressionTest_monovar.rf
+ -sample.mt 20000
+ -sample.mv 20000
+ -sample.vtr 0.5
+ -rand 121212
+ -classifier rf
+ -classifier.rf.ra 0.0001
+ -classifier.rf.max 6
+ -classifier.rf.acc 0.0005
+ VALID --compare-ascii ${NOTOL}
+ ${OTBAPP_BASELINE_FILES}/apTvClTrainRegressionTest_monovar.rf
+ ${TEMP}/apTvClTrainRegressionTest_monovar.rf)
+
+#----------- PredictRegression TESTS ----------------
+otb_test_application(NAME apTvClPredictRegressionTest_monovar
+ APP PredictRegression
+ OPTIONS -in ${INPUTDATA}/QB_Toulouse_Ortho_PAN.tif
+ -model ${OTBAPP_BASELINE_FILES}/apTvClTrainRegressionTest_monovar.rf
+ -imstat ${INPUTDATA}/QB_Toulouse_Ortho_regression.xml
+ -out ${TEMP}/apTvClPredictRegressionTest_monovar.tif
+ VALID --compare-image 1
+ ${OTBAPP_BASELINE}/apTvClPredictRegressionTest_monovar.tif
+ ${TEMP}/apTvClPredictRegressionTest_monovar.tif)
+
+endif()
+
diff --git a/Modules/Applications/AppFiltering/test/CMakeLists.txt b/Modules/Applications/AppFiltering/test/CMakeLists.txt
index d497c9bf8e1b6d51f5668b4ce2ee4be134d91078..984c1830c277999af835fefc934ffcf6bbb2ef8d 100644
--- a/Modules/Applications/AppFiltering/test/CMakeLists.txt
+++ b/Modules/Applications/AppFiltering/test/CMakeLists.txt
@@ -51,8 +51,8 @@ otb_test_application(NAME apTvDespeckleFrost
-filter.frost.rad 5
-filter.frost.deramp 0.1
VALID --compare-image ${EPSILON_7}
- ${BASELINE}/bfFiltreLee_05_05_12.tif
- ${TEMP}/bfFiltreLee_05_05_12_app.tif)
+ ${BASELINE}/bfFiltreFrost_05_05_12_app.tif
+ ${TEMP}/bfFiltreFrost_05_05_12_app.tif)
otb_test_application(NAME apTvDespeckleGammaMAP
APP Despeckle
diff --git a/Modules/Applications/AppImageUtils/app/CMakeLists.txt b/Modules/Applications/AppImageUtils/app/CMakeLists.txt
index 82ef77a5887523595bdf30570c5bdebe3b3c5cdc..637eb926408db14daecc6cfd79401ada43a884a3 100644
--- a/Modules/Applications/AppImageUtils/app/CMakeLists.txt
+++ b/Modules/Applications/AppImageUtils/app/CMakeLists.txt
@@ -89,6 +89,6 @@ otb_create_application(
LINK_LIBRARIES ${${otb-module}_LIBRARIES})
otb_create_application(
- NAME NoDataMask
- SOURCES otbNoDataMask.cxx
+ NAME ManageNoData
+ SOURCES otbManageNoData.cxx
LINK_LIBRARIES ${${otb-module}_LIBRARIES})
diff --git a/Modules/Applications/AppImageUtils/app/otbManageNoData.cxx b/Modules/Applications/AppImageUtils/app/otbManageNoData.cxx
new file mode 100644
index 0000000000000000000000000000000000000000..2449029c861368d5d34121d875608b009e79a530
--- /dev/null
+++ b/Modules/Applications/AppImageUtils/app/otbManageNoData.cxx
@@ -0,0 +1,145 @@
+/*=========================================================================
+
+ Program: ORFEO Toolbox
+ Language: C++
+ Date: $Date$
+ Version: $Revision$
+
+
+ Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
+ See OTBCopyright.txt for details.
+
+
+ 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 "otbWrapperApplication.h"
+#include "otbWrapperApplicationFactory.h"
+
+#include "otbImageToNoDataMaskFilter.h"
+#include "otbChangeNoDataValueFilter.h"
+
+namespace otb
+{
+namespace Wrapper
+{
+
+class ManageNoData : public Application
+{
+public:
+ /** Standard class typedefs. */
+ typedef ManageNoData Self;
+ typedef Application Superclass;
+ typedef itk::SmartPointer<Self> Pointer;
+ typedef itk::SmartPointer<const Self> ConstPointer;
+
+ /** Standard macro */
+ itkNewMacro(Self);
+
+ itkTypeMacro(ManageNoData, otb::Application);
+
+ /** Filters typedef */
+ typedef otb::ImageToNoDataMaskFilter<FloatVectorImageType,UInt8ImageType> FilterType;
+ typedef otb::ChangeNoDataValueFilter<FloatVectorImageType,FloatVectorImageType> ChangeNoDataFilterType;
+
+private:
+ void DoInit()
+ {
+ SetName("ManageNoData");
+ SetDescription("Manage No-Data");
+ // Documentation
+ SetDocName("No Data management");
+ SetDocLongDescription("This application has two modes. The first allows to build a mask of no-data pixels from the no-data flags read from the image file. The second allows to update the change the no-data value of an image (pixels value and metadata). This last mode also allows to replace NaN in images with a proper no-data value. To do so, one should activate the NaN is no-data option.");
+ SetDocLimitations("None");
+ SetDocAuthors("OTB-Team");
+ SetDocSeeAlso("BanMath");
+ AddDocTag("Conversion");
+ AddDocTag("Image Dynamic");
+ AddDocTag(Tags::Manip);
+
+ AddParameter(ParameterType_InputImage, "in", "Input image");
+ SetParameterDescription("in", "Input image");
+
+ AddParameter(ParameterType_OutputImage, "out", "Output Image");
+ SetParameterDescription("out", "Output image");
+
+ AddParameter(ParameterType_Empty,"usenan", "Consider NaN as no-data");
+ SetParameterDescription("usenan","If active, the application will consider NaN as no-data values as well");
+ MandatoryOff("usenan");
+ DisableParameter("usenan");
+
+ AddParameter(ParameterType_Choice,"mode","No-data handling mode");
+ SetParameterDescription("mode","Allows to choose between different no-data handling options");
+
+ AddChoice("mode.buildmask","Build a no-data Mask");
+
+ AddParameter(ParameterType_Float,"mode.buildmask.inv","Inside Value");
+ SetParameterDescription("mode.buildmask.inv","Value given in the output mask to pixels that are not no data pixels");
+ SetDefaultParameterInt("mode.buildmask.inv",1);
+
+ AddParameter(ParameterType_Float,"mode.buildmask.outv","Outside Value");
+ SetParameterDescription("mode.buildmask.outv","Value given in the output mask to pixels that are no data pixels");
+ SetDefaultParameterInt("mode.buildmask.outv",0);
+
+ AddChoice("mode.changevalue","Change the no-data value");
+
+ AddParameter(ParameterType_Float,"mode.changevalue.newv","The new no-data value");
+ SetParameterDescription("mode.changevalue.newv","The new no-data value");
+ SetDefaultParameterInt("mode.changevalue.newv",0);
+
+ SetParameterString("mode","buildmask");
+
+ AddRAMParameter();
+
+ // Doc example parameter settings
+ SetDocExampleParameterValue("in", "QB_Toulouse_Ortho_XS.tif");
+ SetDocExampleParameterValue("out", "QB_Toulouse_Ortho_XS_nodatamask.tif uint8");
+ SetDocExampleParameterValue("mode.buildmask.inv", "255");
+ SetDocExampleParameterValue("mode.buildmask.outv", "0");
+ }
+
+ void DoUpdateParameters()
+ {
+ // Nothing to do here for the parameters : all are independent
+ }
+
+
+ void DoExecute()
+ {
+ FloatVectorImageType::Pointer inputPtr = this->GetParameterImage("in");
+
+ m_Filter = FilterType::New();
+ m_Filter->SetInsideValue(this->GetParameterFloat("mode.buildmask.inv"));
+ m_Filter->SetOutsideValue(this->GetParameterFloat("mode.buildmask.outv"));
+ m_Filter->SetNaNIsNoData(IsParameterEnabled("usenan"));
+ m_Filter->SetInput(inputPtr);
+
+ m_ChangeNoDataFilter = ChangeNoDataFilterType::New();
+ m_ChangeNoDataFilter->SetInput(inputPtr);
+ m_ChangeNoDataFilter->SetNaNIsNoData(IsParameterEnabled("usenan"));
+
+ std::vector<double> newNoData(inputPtr->GetNumberOfComponentsPerPixel(),GetParameterFloat("mode.changevalue.newv"));
+
+ m_ChangeNoDataFilter->SetNewNoDataValues(newNoData);
+
+ if(GetParameterString("mode") == "buildmask")
+ {
+ SetParameterOutputImage("out",m_Filter->GetOutput());
+ }
+ else if(GetParameterString("mode") == "changevalue")
+ {
+ SetParameterOutputImage("out",m_ChangeNoDataFilter->GetOutput());
+ }
+ }
+
+ FilterType::Pointer m_Filter;
+ ChangeNoDataFilterType::Pointer m_ChangeNoDataFilter;
+};
+
+}
+}
+
+OTB_APPLICATION_EXPORT(otb::Wrapper::ManageNoData)
+
diff --git a/Modules/Applications/AppImageUtils/app/otbNoDataMask.cxx b/Modules/Applications/AppImageUtils/app/otbNoDataMask.cxx
deleted file mode 100644
index dd99a9a7949132a1bf64ab95684408b39cee873a..0000000000000000000000000000000000000000
--- a/Modules/Applications/AppImageUtils/app/otbNoDataMask.cxx
+++ /dev/null
@@ -1,107 +0,0 @@
-/*=========================================================================
-
- Program: ORFEO Toolbox
- Language: C++
- Date: $Date$
- Version: $Revision$
-
-
- Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
- See OTBCopyright.txt for details.
-
-
- 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 "otbWrapperApplication.h"
-#include "otbWrapperApplicationFactory.h"
-
-#include "otbImageToNoDataMaskFilter.h"
-
-namespace otb
-{
-namespace Wrapper
-{
-
-
-class NoDataMask : public Application
-{
-public:
- /** Standard class typedefs. */
- typedef NoDataMask Self;
- typedef Application Superclass;
- typedef itk::SmartPointer<Self> Pointer;
- typedef itk::SmartPointer<const Self> ConstPointer;
-
- /** Standard macro */
- itkNewMacro(Self);
-
- itkTypeMacro(NoDataMask, otb::Application);
-
- /** Filters typedef */
- typedef otb::ImageToNoDataMaskFilter<FloatVectorImageType,UInt8ImageType> FilterType;
-
-private:
- void DoInit()
- {
- SetName("NoDataMask");
- SetDescription("NoDataMask");
- // Documentation
- SetDocName("No Data Mask management");
- SetDocLongDescription("This application builds a nodata mask from the no data flags found in metadata or from NaN pixels.");
- SetDocLimitations("None");
- SetDocAuthors("OTB-Team");
- SetDocSeeAlso("BanMath");
- AddDocTag("Conversion");
- AddDocTag("Image Dynamic");
- AddDocTag(Tags::Manip);
-
- AddParameter(ParameterType_InputImage, "in", "Input image");
- SetParameterDescription("in", "Input image");
-
- AddParameter(ParameterType_OutputImage, "out", "Output Image");
- SetParameterDescription("out", "Output image");
-
- AddParameter(ParameterType_Int,"inv","Inside Value");
- SetParameterDescription("inv","Value given in the output mask to pixels that are not no data pixels");
- SetDefaultParameterInt("inv",1);
-
- AddParameter(ParameterType_Int,"outv","Outside Value");
- SetParameterDescription("outv","Value given in the output mask to pixels that are no data pixels");
- SetDefaultParameterInt("outv",0);
-
- AddRAMParameter();
-
- // Doc example parameter settings
- SetDocExampleParameterValue("in", "QB_Toulouse_Ortho_XS.tif");
- SetDocExampleParameterValue("out", "QB_Toulouse_Ortho_XS_nodatamask.tif uint8");
- SetDocExampleParameterValue("inv", "255");
- SetDocExampleParameterValue("outv", "0");
- }
-
- void DoUpdateParameters()
- {
- // Nothing to do here for the parameters : all are independent
- }
-
-
- void DoExecute()
- {
- m_Filter = FilterType::New();
- m_Filter->SetInsideValue(this->GetParameterInt("inv"));
- m_Filter->SetOutsideValue(this->GetParameterInt("outv"));
- m_Filter->SetInput(this->GetParameterImage("in"));
-
- SetParameterOutputImage("out",m_Filter->GetOutput());
- }
-
- FilterType::Pointer m_Filter;
-};
-
-}
-}
-
-OTB_APPLICATION_EXPORT(otb::Wrapper::NoDataMask)
-
diff --git a/Modules/Core/Common/include/otbDecimateImageFilter.h b/Modules/Core/Common/include/otbDecimateImageFilter.h
index d0edccc95bb698f120c46c632efcaa0e349828cb..a171a7670ee7ff27e7adf247faf6e93dfda1e2b8 100644
--- a/Modules/Core/Common/include/otbDecimateImageFilter.h
+++ b/Modules/Core/Common/include/otbDecimateImageFilter.h
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom / Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Core/Common/include/otbDecimateImageFilter.txx b/Modules/Core/Common/include/otbDecimateImageFilter.txx
index b6eeede4ff84046b54e118d783132535959918c9..554c2c6a900fa9d3d5bba9e22d671425a7921d56 100644
--- a/Modules/Core/Common/include/otbDecimateImageFilter.txx
+++ b/Modules/Core/Common/include/otbDecimateImageFilter.txx
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom / Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Core/Common/include/otbImageRegionAdaptativeSplitter.txx b/Modules/Core/Common/include/otbImageRegionAdaptativeSplitter.txx
index 154c73b8c4805ade35f63410d841b2999b2fe751..ef5b28192b5d1f658327d89fa9b8a0b0ec403610 100644
--- a/Modules/Core/Common/include/otbImageRegionAdaptativeSplitter.txx
+++ b/Modules/Core/Common/include/otbImageRegionAdaptativeSplitter.txx
@@ -107,10 +107,14 @@ ImageRegionAdaptativeSplitter<VImageDimension>
// Now we can handle the case where we have a tile hint and a
// non-trivial requested number of splits
SizeType tilesPerDim, splitsPerDim;
-
- tilesPerDim[0] = (m_ImageRegion.GetSize()[0] + m_TileHint[0] -1) / m_TileHint[0];
- tilesPerDim[1] = (m_ImageRegion.GetSize()[1] + m_TileHint[1] -1) / m_TileHint[1];
-
+ IndexType firstTileCovered;
+
+ // First, we need to get which tiles are covered by ROI
+ firstTileCovered[0] = m_ImageRegion.GetIndex()[0] / m_TileHint[0];
+ firstTileCovered[1] = m_ImageRegion.GetIndex()[1] / m_TileHint[1];
+ tilesPerDim[0] = (m_ImageRegion.GetIndex()[0] + m_ImageRegion.GetSize()[0] + m_TileHint[0] -1) / m_TileHint[0] - firstTileCovered[0];
+ tilesPerDim[1] = (m_ImageRegion.GetIndex()[1] + m_ImageRegion.GetSize()[1] + m_TileHint[1] -1) / m_TileHint[1] - firstTileCovered[1];
+
unsigned int totalTiles = tilesPerDim[0] * tilesPerDim[1];
// In this case, we have to group input tiles
@@ -134,13 +138,14 @@ ImageRegionAdaptativeSplitter<VImageDimension>
i = (i+1)%2;
}
+
splitsPerDim[0] = tilesPerDim[0] / groupTiles[0];
+ splitsPerDim[1] = tilesPerDim[1] / groupTiles[1];
// Handle the last small tile if any
if(tilesPerDim[0] % groupTiles[0] > 0)
splitsPerDim[0]++;
- splitsPerDim[1] = tilesPerDim[1] / groupTiles[1];
if(tilesPerDim[1] % groupTiles[1] > 0)
splitsPerDim[1]++;
@@ -157,8 +162,8 @@ ImageRegionAdaptativeSplitter<VImageDimension>
newSplitSize[0] = groupTiles[0] * m_TileHint[0];
newSplitSize[1] = groupTiles[1] * m_TileHint[1];
- newSplitIndex[0] = splitx * newSplitSize[0];
- newSplitIndex[1] = splity * newSplitSize[1];
+ newSplitIndex[0] = firstTileCovered[0] * m_TileHint[0] + splitx * newSplitSize[0];
+ newSplitIndex[1] = firstTileCovered[1] * m_TileHint[1] + splity * newSplitSize[1];
newSplit.SetIndex(newSplitIndex);
newSplit.SetSize(newSplitSize);
@@ -181,7 +186,9 @@ ImageRegionAdaptativeSplitter<VImageDimension>
unsigned int i = 1;
- while(totalTiles * (divideTiles[0] * divideTiles[1]) < m_RequestedNumberOfSplits)
+ // Exit condition if divideTiles=m_TileHint (i.e. no more subdivision available)
+ while(totalTiles * (divideTiles[0] * divideTiles[1]) < m_RequestedNumberOfSplits
+ && (divideTiles[0] < m_TileHint[0] || divideTiles[1] < m_TileHint[1]))
{
if(divideTiles[i] < m_TileHint[i])
{
@@ -195,6 +202,8 @@ ImageRegionAdaptativeSplitter<VImageDimension>
splitSize[0] = (m_TileHint[0] + divideTiles[0] - 1)/ divideTiles[0];
splitSize[1] = (m_TileHint[1] + divideTiles[1] - 1)/ divideTiles[1];
+ RegionType tileHintRegion;
+ tileHintRegion.SetSize(m_TileHint);
// Fill the tiling scheme
for(unsigned int tiley = 0; tiley < tilesPerDim[1]; ++tiley)
{
@@ -208,19 +217,27 @@ ImageRegionAdaptativeSplitter<VImageDimension>
RegionType newSplit;
IndexType newSplitIndex;
- newSplitIndex[0] = tilex * m_TileHint[0] + divx * splitSize[0];
- newSplitIndex[1] = tiley * m_TileHint[1] + divy * splitSize[1];
+ newSplitIndex[0] = (tilex + firstTileCovered[0]) * m_TileHint[0] + divx * splitSize[0];
+ newSplitIndex[1] = (tiley + firstTileCovered[1]) * m_TileHint[1] + divy * splitSize[1];
newSplit.SetIndex(newSplitIndex);
newSplit.SetSize(splitSize);
+ tileHintRegion.SetIndex(0, tilex * m_TileHint[0]);
+ tileHintRegion.SetIndex(1, tiley * m_TileHint[1]);
+
bool cropped = newSplit.Crop(m_ImageRegion);
// If newSplit could not be cropped, it means that it is
// outside m_ImageRegion. In this case we ignore it.
if(cropped)
{
- m_StreamVector.push_back(newSplit);
+ // check that the split stays inside its tile
+ cropped = newSplit.Crop(tileHintRegion);
+ if (cropped)
+ {
+ m_StreamVector.push_back(newSplit);
+ }
}
}
}
diff --git a/Modules/Core/Common/include/otbModelComponentBase.h b/Modules/Core/Common/include/otbModelComponentBase.h
index cdf80a0fa23f9a2b55e079429e7d3519c0532ad4..f8956cd307f52042e506271f6d485cc51c9d8cc1 100644
--- a/Modules/Core/Common/include/otbModelComponentBase.h
+++ b/Modules/Core/Common/include/otbModelComponentBase.h
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Some parts of this code are covered by the GET copyright.
- See GETCopyright.txt for details.
+ Some parts of this code are covered by the IMT copyright.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Core/Common/include/otbModelComponentBase.txx b/Modules/Core/Common/include/otbModelComponentBase.txx
index c3a130cedfccf448019a9b3fc86ecf1084746da6..bfdb3c7e0af35b5bbf60f11db46fb03049f5e781 100644
--- a/Modules/Core/Common/include/otbModelComponentBase.txx
+++ b/Modules/Core/Common/include/otbModelComponentBase.txx
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Some parts of this code are covered by the GET copyright.
- See GETCopyright.txt for details.
+ Some parts of this code are covered by the IMT copyright.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Core/Common/include/otbSubsampledImageRegionConstIterator.h b/Modules/Core/Common/include/otbSubsampledImageRegionConstIterator.h
index ea8276f1677133d38b959bee714127db8ac933a6..ef49212f570bcebe112883c1cb192ee8ddd26017 100644
--- a/Modules/Core/Common/include/otbSubsampledImageRegionConstIterator.h
+++ b/Modules/Core/Common/include/otbSubsampledImageRegionConstIterator.h
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom / Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Core/Common/include/otbSubsampledImageRegionConstIterator.txx b/Modules/Core/Common/include/otbSubsampledImageRegionConstIterator.txx
index 58f1035b3adc70e4d87a28cd45a24472bfbb0bcc..1a9552d1d9475fd19c4741ebf99e31270d578028 100644
--- a/Modules/Core/Common/include/otbSubsampledImageRegionConstIterator.txx
+++ b/Modules/Core/Common/include/otbSubsampledImageRegionConstIterator.txx
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom / Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Core/Common/include/otbSubsampledImageRegionIterator.h b/Modules/Core/Common/include/otbSubsampledImageRegionIterator.h
index eb0e45d7d06350ce55ae0a1e7e49264ab622b95f..0fa6f966784b8e7335849e8fa19df498c8b39b67 100644
--- a/Modules/Core/Common/include/otbSubsampledImageRegionIterator.h
+++ b/Modules/Core/Common/include/otbSubsampledImageRegionIterator.h
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom / Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Core/Common/test/CMakeLists.txt b/Modules/Core/Common/test/CMakeLists.txt
index e32118293bc838491f5be7754ed53d22c35699b3..c40b6a289fdce16ec39937f9db531dbe9d61a38c 100644
--- a/Modules/Core/Common/test/CMakeLists.txt
+++ b/Modules/Core/Common/test/CMakeLists.txt
@@ -78,6 +78,36 @@ otb_add_test(NAME coTvImageRegionAdaptativeSplitterStripLargeStream COMMAND otbC
${TEMP}/coTvImageRegionAdaptativeSplitterStripLargeStreamOutput.txt
)
+otb_add_test(NAME coTvImageRegionAdaptativeSplitterShiftedROILargeStream COMMAND otbCommonTestDriver
+ --compare-ascii ${NOTOL}
+ ${BASELINE_FILES}/coTvImageRegionAdaptativeSplitterShiftedROILargeStreamOutput.txt
+ ${TEMP}/coTvImageRegionAdaptativeSplitterShiftedROILargeStreamOutput.txt
+ otbImageRegionAdaptativeSplitter
+ 1000 1000 4000 4000 2000 2000 5
+ ${TEMP}/coTvImageRegionAdaptativeSplitterShiftedROILargeStreamOutput.txt
+ )
+
+otb_add_test(NAME coTvImageRegionAdaptativeSplitterShiftedROISmallStream COMMAND otbCommonTestDriver
+ --compare-ascii ${NOTOL}
+ ${BASELINE_FILES}/coTvImageRegionAdaptativeSplitterShiftedROISmallStreamOutput.txt
+ ${TEMP}/coTvImageRegionAdaptativeSplitterShiftedROISmallStreamOutput.txt
+ otbImageRegionAdaptativeSplitter
+ 1000 1000 4000 4000 2000 2000 10
+ ${TEMP}/coTvImageRegionAdaptativeSplitterShiftedROISmallStreamOutput.txt
+ )
+
+otb_add_test(NAME coTvImageRegionAdaptativeSplitterMissingLine COMMAND otbCommonTestDriver
+ otbImageRegionAdaptativeSplitter
+ 0 0 1000 1000 1000 1 37
+ ${TEMP}/coTvImageRegionAdaptativeSplitterMissingLine.txt
+ )
+
+otb_add_test(NAME coTvImageRegionAdaptativeSplitterDivideBlock COMMAND otbCommonTestDriver
+ otbImageRegionAdaptativeSplitter
+ 0 0 10 10 5 5 36
+ ${TEMP}/coTvImageRegionAdaptativeSplitterDivideBlock.txt
+ )
+
otb_add_test(NAME coTuRGBAPixelConverter COMMAND otbCommonTestDriver
otbRGBAPixelConverterNew
)
diff --git a/Modules/Core/Common/test/otbImageRegionAdaptativeSplitter.cxx b/Modules/Core/Common/test/otbImageRegionAdaptativeSplitter.cxx
index 638993505239432d2926178eff637ca2b94c6720..66cc0ae45d7159fe3f84b945cdbaf2edf2a903bb 100644
--- a/Modules/Core/Common/test/otbImageRegionAdaptativeSplitter.cxx
+++ b/Modules/Core/Common/test/otbImageRegionAdaptativeSplitter.cxx
@@ -59,16 +59,63 @@ int otbImageRegionAdaptativeSplitter(int itkNotUsed(argc), char * argv[])
unsigned int nbSplits = splitter->GetNumberOfSplits(region, requestedNbSplits);
+ std::vector<RegionType> splits;
outfile<<splitter<<std::endl;
outfile<<"Split map: "<<std::endl;
for(unsigned int i = 0; i < nbSplits; ++i)
{
- outfile<<"Split "<<i<<": "<<splitter->GetSplit(i, requestedNbSplits, region);
+ RegionType tmpRegion = splitter->GetSplit(i, requestedNbSplits, region);
+ splits.push_back(tmpRegion);
+ outfile<<"Split "<<i<<": "<<tmpRegion;
}
outfile.close();
+ // Basic consistency check on split map
+ if (requestedNbSplits != nbSplits)
+ {
+ std::cout << "Wrong number of splits : got "<<nbSplits<<" , expected "<<requestedNbSplits<< std::endl;
+ }
+ IndexType tmpIndex;
+ for (unsigned int i=regionIndex[0] ; i<(regionIndex[0]+regionSize[0]) ; ++i)
+ {
+ for (unsigned int j=regionIndex[1] ; j<(regionIndex[1]+regionSize[1]) ; ++j)
+ {
+ tmpIndex[0] = i;
+ tmpIndex[1] = j;
+ unsigned int count = 0;
+ for (unsigned int k=0 ; k<nbSplits ; ++k )
+ {
+ if (splits[k].IsInside(tmpIndex))
+ {
+ count++;
+ }
+ }
+ if (count == 0)
+ {
+ std::cout << "Index ["<<i<<","<<j<<"] is missing in split map" << std::endl;
+ return EXIT_FAILURE;
+ }
+ if (count > 1)
+ {
+ std::cout << "Index ["<<i<<","<<j<<"] occurs more than once in the split map" << std::endl;
+ return EXIT_FAILURE;
+ }
+ }
+ }
+
+ unsigned int pixelInSplit = 0;
+ for (unsigned int k=0 ; k<nbSplits ; ++k )
+ {
+ pixelInSplit += splits[k].GetSize(0) * splits[k].GetSize(1);
+ }
+ if (pixelInSplit != regionSize[0]*regionSize[1])
+ {
+ std::cout << "Wrong number of pixels in split : got "<<pixelInSplit << " , expected "<< regionSize[0]*regionSize[1] << std::endl;
+ return EXIT_FAILURE;
+ }
+
return EXIT_SUCCESS;
}
diff --git a/Modules/Core/ImageBase/include/otbNoDataHelper.h b/Modules/Core/ImageBase/include/otbNoDataHelper.h
deleted file mode 100644
index 16bfdc4cd85f916804b59d8c7ee05828d47e1897..0000000000000000000000000000000000000000
--- a/Modules/Core/ImageBase/include/otbNoDataHelper.h
+++ /dev/null
@@ -1,75 +0,0 @@
-/*=========================================================================
-
- Program: ORFEO Toolbox
- Language: C++
- Date: $Date$
- Version: $Revision$
-
-
- Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
- See OTBCopyright.txt for details.
-
-
- 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.
-
-=========================================================================*/
-#ifndef __otbNoDataHelper_h
-#define __otbNoDataHelper_h
-#include <vector>
-#include <cassert>
-#include "vnl/vnl_math.h"
-#include <itkVariableLengthVector.h>
-
-namespace otb
-{
-/**
-* Test if the pixel corresponds to a no data pixel according to a
-* vector of no data flags, and a vector of no data values.
-* \param pixel The pixel to test
-* \param flags A vector of size > 1 containing a flag per band to
-* indicate if a no data value is available for this band
-* \param values A vector of size > 1 corresponding to the no data
-* value for each band. If flag is 0, the value will be ignored.
-*/
-template<typename T> bool IsNoData(const T & pixel, const
-std::vector<bool> & flags, const std::vector<double> & values) {
- assert(flags.size()>0);
- assert(values.size()>0);
-
- if(vnl_math_isnan((int)flags[0]))
- return true;
-
-
- if(flags[0])
- {
- return (pixel == values[0]);
- }
- else
- {
- return false;
- }
-}
-/**
- * Specialization of IsNoData function to handle itk::VariableLengthVector
- */
-template <typename T> bool IsNoData(const itk::VariableLengthVector<T> & pixel, const std::vector<bool> & flags, const std::vector<double> & values)
-{
- assert(flags.size()>=pixel.Size());
- assert(values.size()>=pixel.Size());
-
- for(unsigned int i = 0; i < pixel.Size();++i)
- {
- if(vnl_math_isnan(pixel[i]) || (flags[i] && (pixel[i] == values[i])))
- {
- return true;
- }
- }
- return false;
-}
-
-
-} // End namespace otb
-
-#endif
diff --git a/Modules/Core/ImageBase/test/CMakeLists.txt b/Modules/Core/ImageBase/test/CMakeLists.txt
index dd4ecc9d09b0a5477f4d0e66786ffeda21dab34c..46ff70cf251e17e8a4bd2be04073930a7dec7978 100644
--- a/Modules/Core/ImageBase/test/CMakeLists.txt
+++ b/Modules/Core/ImageBase/test/CMakeLists.txt
@@ -28,7 +28,7 @@ set(OTBImageBaseTests
otbImageFunctionAdaptor.cxx
otbMultiChannelExtractROINew.cxx
otbMetaImageFunction.cxx
- otbNoDataHelperTest.cxx
+
)
add_executable(otbImageBaseTestDriver ${OTBImageBaseTests})
@@ -825,6 +825,3 @@ otb_add_test(NAME ioTvOtbVectorImageTestRadarsat COMMAND otbImageBaseTestDriver
otbVectorImageLegacyTest
LARGEINPUT{/RADARSAT1/GOMA/SCENE01/}
${TEMP}/ioOtbVectorImageTestRadarsat.txt)
-
-otb_add_test(NAME coreImageBaseNoDataHelperTest COMMAND otbImageBaseTestDriver
- otbNoDataHelperTest)
diff --git a/Modules/Core/ImageBase/test/otbFlexibleDistanceWithMissingValue.cxx b/Modules/Core/ImageBase/test/otbFlexibleDistanceWithMissingValue.cxx
index ed2a12c0257798f51ca7bf487d189c3f6b4a87cc..8d468f33dcf494d93733375596c7353a031e9513 100644
--- a/Modules/Core/ImageBase/test/otbFlexibleDistanceWithMissingValue.cxx
+++ b/Modules/Core/ImageBase/test/otbFlexibleDistanceWithMissingValue.cxx
@@ -10,7 +10,7 @@
See OTBCopyright.txt for details.
Copyright (c) Institut Telecom; Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Core/ImageBase/test/otbFlexibleDistanceWithMissingValueNew.cxx b/Modules/Core/ImageBase/test/otbFlexibleDistanceWithMissingValueNew.cxx
index d4a76c8923e8bf8d33375e2e4e1d2240510f4411..d6983430adbcdf6683d9e0e22118c631637d3dac 100644
--- a/Modules/Core/ImageBase/test/otbFlexibleDistanceWithMissingValueNew.cxx
+++ b/Modules/Core/ImageBase/test/otbFlexibleDistanceWithMissingValueNew.cxx
@@ -10,7 +10,7 @@
See OTBCopyright.txt for details.
Copyright (c) Institut Telecom; Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Core/ImageBase/test/otbImageBaseTestDriver.cxx b/Modules/Core/ImageBase/test/otbImageBaseTestDriver.cxx
index dcf63d236ebad2c066389989da824836833ab7d9..fc275609cb19c75305902543f926fc37e3cb3f83 100644
--- a/Modules/Core/ImageBase/test/otbImageBaseTestDriver.cxx
+++ b/Modules/Core/ImageBase/test/otbImageBaseTestDriver.cxx
@@ -31,5 +31,4 @@ void RegisterTests()
REGISTER_TEST(otbMultiChannelExtractROINew);
REGISTER_TEST(otbMetaImageFunction);
REGISTER_TEST(otbMetaImageFunctionNew);
- REGISTER_TEST(otbNoDataHelperTest);
}
diff --git a/Modules/Core/Metadata/include/otbImageMetadataInterfaceBase.h b/Modules/Core/Metadata/include/otbImageMetadataInterfaceBase.h
index d9209574b68c59c32b82e7c7894e3855e988a28c..8340cedac73674309f124cc4c8b24499dc3c34b3 100644
--- a/Modules/Core/Metadata/include/otbImageMetadataInterfaceBase.h
+++ b/Modules/Core/Metadata/include/otbImageMetadataInterfaceBase.h
@@ -107,6 +107,12 @@ public:
double GetGCPZ(unsigned int GCPnum) const;
// otbMetadataGetGCPnumMacro(GCPZ, double, GCPnum, unsigned int);
+ /**
+ * Get The no data flags if existing
+ * return False otherwise
+ */
+ bool GetNoDataFlags(std::vector<bool> & flags, std::vector<double> & values) const;
+
/** Get the six coefficients of affine geoTtransform. */
VectorType GetGeoTransform() const;
diff --git a/Modules/Core/Metadata/include/otbNoDataHelper.h b/Modules/Core/Metadata/include/otbNoDataHelper.h
new file mode 100644
index 0000000000000000000000000000000000000000..57d927c78fb7bf737e11e3d6663b3f60cd52d828
--- /dev/null
+++ b/Modules/Core/Metadata/include/otbNoDataHelper.h
@@ -0,0 +1,165 @@
+/*=========================================================================
+
+ Program: ORFEO Toolbox
+ Language: C++
+ Date: $Date$
+ Version: $Revision$
+
+
+ Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
+ See OTBCopyright.txt for details.
+
+
+ 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.
+
+=========================================================================*/
+#ifndef __otbNoDataHelper_h
+#define __otbNoDataHelper_h
+#include <vector>
+#include <cassert>
+#include "vnl/vnl_math.h"
+#include <itkVariableLengthVector.h>
+
+namespace itk
+{
+class MetaDataDictionary;
+}
+
+namespace otb
+{
+
+/**
+ * Reads no data flag from the MetaDataDictionnary dict to flags and values
+ * vectors. Returns true upon success.
+ */
+bool ReadNoDataFlags(const itk::MetaDataDictionary& dict, std::vector<bool> & flags, std::vector<double> & values);
+
+/**
+ * Write no data flags to the MetaDataDictionnary dict from flags and values
+ * vectors. Returns true upon success.
+ */
+void WriteNoDataFlags(const std::vector<bool> & flags, const std::vector<double> & values, itk::MetaDataDictionary& dict);
+
+/**
+* Test if the pixel corresponds to a no data pixel according to a
+* vector of no data flags, and a vector of no data values.
+* \param pixel The pixel to test
+* \param flags A vector of size > 1 containing a flag per band to
+* indicate if a no data value is available for this band
+* \param values A vector of size > 1 corresponding to the no data
+* value for each band. If flag is 0, the value will be ignored.
+* \param nanIsNoData If true, NaN values will be reported as no-data.
+*/
+template<typename T> bool IsNoData(const T & pixel, const
+ std::vector<bool> & flags, const std::vector<double> & values, bool nanIsNoData = false) {
+ assert(flags.size()>0);
+ assert(values.size()>0);
+
+ if(nanIsNoData && vnl_math_isnan(values[0]))
+ return true;
+
+
+ if(flags[0])
+ {
+ return (pixel == values[0]);
+ }
+ else
+ {
+ return false;
+ }
+}
+
+/**
+* Reads a pixel and change the no data value if it is found. No data
+* value is changed either if the pixel value is NaN or if the pixel
+* value equals the no data value and flag is true.
+*
+* \param pixel The pixel to process \param flags A vector of size > 1
+* containing a flag per band to indicate if a no data value is
+* available for this band
+* \param values A vector of size > 1 corresponding to the current no data
+* value for each band. If flag is 0, the value will be ignored.
+* \param newValues A vector of size > 1 corresponding to the new no data
+* value for each band. If flag is 0, the value will be ignored
+* \param nanIsNoData If true, NaN values will be considered as no-data
+* and changed as well.
+*
+*/
+template<typename T> T ChangeNoData(const T & pixel, const
+ std::vector<bool> & flags,
+ const std::vector<double> & values,
+ const std::vector<double> & newValues,
+ bool nanIsNoData = false) {
+ assert(flags.size()>0);
+ assert(values.size()>0);
+ assert(newValues.size()>0);
+
+ if(nanIsNoData && vnl_math_isnan(pixel))
+ {
+ return static_cast<T>(newValues[0]);
+ }
+
+ if(flags[0] && pixel == values[0])
+ {
+ return static_cast<T>(newValues[0]);
+ }
+ return pixel;
+}
+
+
+/**
+ * Specialization of IsNoData function to handle itk::VariableLengthVector
+ */
+template <typename T> bool IsNoData(const itk::VariableLengthVector<T> & pixel, const std::vector<bool> & flags, const std::vector<double> & values, bool nanIsNoData = false)
+{
+ assert(flags.size()>=pixel.Size());
+ assert(values.size()>=pixel.Size());
+
+ for(unsigned int i = 0; i < pixel.Size();++i)
+ {
+ if((nanIsNoData && vnl_math_isnan(pixel[i])) || (flags[i] && (pixel[i] == values[i])))
+ {
+ return true;
+ }
+ }
+ return false;
+}
+
+
+/**
+ * Specialization of ChangeNoData function to handle itk::VariableLengthVector
+ */
+template <typename T> itk::VariableLengthVector<T> ChangeNoData(const itk::VariableLengthVector<T> & pixel,
+ const std::vector<bool> & flags,
+ const std::vector<double> & values,
+ const std::vector<double> & newValues,
+ bool nanIsNoData = false)
+{
+ assert(flags.size()>=pixel.Size());
+ assert(values.size()>=pixel.Size());
+ assert(newValues.size()>=pixel.Size());
+
+ itk::VariableLengthVector<T> outPixel(pixel.Size());
+
+ for(unsigned int i = 0; i < pixel.Size();++i)
+ {
+ if((nanIsNoData && vnl_math_isnan(pixel[i])) || (flags[i] && (pixel[i] == values[i])))
+ {
+ outPixel[i] = newValues[i];
+ }
+ else
+ {
+ outPixel[i] = pixel[i];
+ }
+ }
+
+ return outPixel;
+}
+
+
+
+} // End namespace otb
+
+#endif
diff --git a/Modules/Core/Metadata/otb-module.cmake b/Modules/Core/Metadata/otb-module.cmake
index afaff0b86e39f5762ddb10689628e7ebf1be6e61..240e6a3ee1cec76586a97c0078a34861dfb410ee 100644
--- a/Modules/Core/Metadata/otb-module.cmake
+++ b/Modules/Core/Metadata/otb-module.cmake
@@ -9,12 +9,12 @@ otb_module(OTBMetadata
OTBITK
OTBOSSIMAdapters
OTBCommon
-
+
TEST_DEPENDS
OTBTestKernel
OTBImageIO
OTBImageBase
-
+
DESCRIPTION
"${DOCUMENTATION}"
)
diff --git a/Modules/Core/Metadata/src/CMakeLists.txt b/Modules/Core/Metadata/src/CMakeLists.txt
index bc3c9900f779896fc9396b52c4e36f60c0d77b57..458188d5246599d101d8cfa68384704f8e7929ae 100644
--- a/Modules/Core/Metadata/src/CMakeLists.txt
+++ b/Modules/Core/Metadata/src/CMakeLists.txt
@@ -24,6 +24,7 @@ set(OTBMetadata_SRC
otbSarImageMetadataInterface.cxx
otbPleiadesImageMetadataInterfaceFactory.cxx
otbTerraSarImageMetadataInterfaceFactory.cxx
+ otbNoDataHelper.cxx
)
add_library(OTBMetadata ${OTBMetadata_SRC})
diff --git a/Modules/Core/Metadata/src/otbImageMetadataInterfaceBase.cxx b/Modules/Core/Metadata/src/otbImageMetadataInterfaceBase.cxx
index 784f5847bca5369f0077f9b6441443aae5a35550..013e4f9c77d4932f351b2c17acfd04f4e3d2944e 100644
--- a/Modules/Core/Metadata/src/otbImageMetadataInterfaceBase.cxx
+++ b/Modules/Core/Metadata/src/otbImageMetadataInterfaceBase.cxx
@@ -18,9 +18,11 @@
#include "otbImageMetadataInterfaceBase.h"
+#include "otbNoDataHelper.h"
#include "itkMetaDataObject.h"
#include "itksys/SystemTools.hxx"
+
namespace otb
{
@@ -222,6 +224,12 @@ ImageMetadataInterfaceBase::GetGCPZ(unsigned int GCPnum) const
else return (0);
}
+bool
+ImageMetadataInterfaceBase::GetNoDataFlags(std::vector<bool> & flags, std::vector<double> & values) const
+{
+ return ReadNoDataFlags(this->GetMetaDataDictionary(),flags,values);
+}
+
ImageMetadataInterfaceBase::VectorType
ImageMetadataInterfaceBase::GetGeoTransform() const
{
diff --git a/Modules/Core/Metadata/src/otbNoDataHelper.cxx b/Modules/Core/Metadata/src/otbNoDataHelper.cxx
new file mode 100644
index 0000000000000000000000000000000000000000..b5edf9dc49145ba6aae8e5089cc7a11335bf7037
--- /dev/null
+++ b/Modules/Core/Metadata/src/otbNoDataHelper.cxx
@@ -0,0 +1,43 @@
+/*=========================================================================
+
+ Program: ORFEO Toolbox
+ Language: C++
+ Date: $Date$
+ Version: $Revision$
+
+
+ Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
+ See OTBCopyright.txt for details.
+
+
+ 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 "otbNoDataHelper.h"
+
+#include "itkMetaDataDictionary.h"
+#include "itkMetaDataObject.h"
+#include "otbMetaDataKey.h"
+
+namespace otb
+{
+
+bool ReadNoDataFlags(const itk::MetaDataDictionary& dict, std::vector<bool> & flags, std::vector<double> & values)
+{
+ bool ret = itk::ExposeMetaData<std::vector<bool> >(dict,MetaDataKey::NoDataValueAvailable,flags);
+
+ if (ret)
+ ret = itk::ExposeMetaData<std::vector<double> >(dict,MetaDataKey::NoDataValue,values);
+
+ return ret;
+}
+
+void WriteNoDataFlags(const std::vector<bool> & flags, const std::vector<double> & values, itk::MetaDataDictionary& dict)
+{
+ itk::EncapsulateMetaData<std::vector<bool> >(dict,MetaDataKey::NoDataValueAvailable,flags);
+ itk::EncapsulateMetaData<std::vector<double> >(dict,MetaDataKey::NoDataValue,values);
+}
+
+} // End namespace otb
diff --git a/Modules/Core/Metadata/test/CMakeLists.txt b/Modules/Core/Metadata/test/CMakeLists.txt
index 340324421e76181795985d0e7fea068ddb2fab43..b48fbffaef79197293daba9fec698e7fe0581bfb 100644
--- a/Modules/Core/Metadata/test/CMakeLists.txt
+++ b/Modules/Core/Metadata/test/CMakeLists.txt
@@ -22,6 +22,7 @@ otbTerraSarImageMetadataInterfaceNew.cxx
otbWorldView2ImageMetadataInterfaceNew.cxx
otbDefaultImageMetadataInterface.cxx
otbImageMetadataInterfaceTest2.cxx
+otbNoDataHelperTest.cxx
)
add_executable(otbMetadataTestDriver ${OTBMetadataTests})
@@ -351,3 +352,7 @@ foreach( current_file ${GenericTestSPOT6_DATA_INPUTS} )
${TEMP}/ioTvOpticalImageMetadataInterface_${current_type}_OUT.txt
)
endforeach()
+
+
+otb_add_test(NAME coreMetaDataNoDataHelperTest COMMAND otbMetadataTestDriver
+ otbNoDataHelperTest)
diff --git a/Modules/Core/Metadata/test/otbMetadataTestDriver.cxx b/Modules/Core/Metadata/test/otbMetadataTestDriver.cxx
index d2dfb191518574ccf1829046d59c2ebb5b2550c0..cd06f2f46e9f46fb412b1f30a278374070ac7405 100644
--- a/Modules/Core/Metadata/test/otbMetadataTestDriver.cxx
+++ b/Modules/Core/Metadata/test/otbMetadataTestDriver.cxx
@@ -21,4 +21,5 @@ void RegisterTests()
REGISTER_TEST(otbWorldView2ImageMetadataInterfaceNew);
REGISTER_TEST(otbDefaultImageMetadataInterface);
REGISTER_TEST(otbImageMetadataInterfaceTest2);
+ REGISTER_TEST(otbNoDataHelperTest);
}
diff --git a/Modules/Core/ImageBase/test/otbNoDataHelperTest.cxx b/Modules/Core/Metadata/test/otbNoDataHelperTest.cxx
similarity index 91%
rename from Modules/Core/ImageBase/test/otbNoDataHelperTest.cxx
rename to Modules/Core/Metadata/test/otbNoDataHelperTest.cxx
index 5b32ec74768b446b80c18c3e2d4a643971e5246d..4db9ba0ab9f1bd23ff180ca3edf7577476895d13 100644
--- a/Modules/Core/ImageBase/test/otbNoDataHelperTest.cxx
+++ b/Modules/Core/Metadata/test/otbNoDataHelperTest.cxx
@@ -17,6 +17,7 @@
=========================================================================*/
#include "otbNoDataHelper.h"
+#include "itkMetaDataDictionary.h"
#include "otbMacro.h"
int otbNoDataHelperTest(int itkNotUsed(argc),char * itkNotUsed(argv) [])
@@ -24,6 +25,11 @@ int otbNoDataHelperTest(int itkNotUsed(argc),char * itkNotUsed(argv) [])
std::vector<bool> b1(1,true);
std::vector<double> v1(1,0);
+ itk::MetaDataDictionary dict;
+
+ otb::WriteNoDataFlags(b1,v1,dict);
+ otb::ReadNoDataFlags(dict,b1,v1);
+
otbControlConditionTestMacro(otb::IsNoData(10,b1,v1)," wrong output of IsNoData function");
otbControlConditionTestMacro(!otb::IsNoData(0,b1,v1)," wrong output of IsNoData function");
b1[0]=false;
diff --git a/Modules/Feature/Edge/test/otbHorizontalSobelVectorImageFilter.cxx b/Modules/Feature/Edge/test/otbHorizontalSobelVectorImageFilter.cxx
index 8f77718c38ddbddfd875a63c9a5a321a5d0928f1..a1464ebb8ff2a56b038b8bebc1468e2672d1b028 100644
--- a/Modules/Feature/Edge/test/otbHorizontalSobelVectorImageFilter.cxx
+++ b/Modules/Feature/Edge/test/otbHorizontalSobelVectorImageFilter.cxx
@@ -10,7 +10,7 @@
See OTBCopyright.txt for details.
Copyright (c) Institut Telecom; Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Feature/Edge/test/otbSobelVectorImageFilter.cxx b/Modules/Feature/Edge/test/otbSobelVectorImageFilter.cxx
index e7f0ff418e62447e8930906de208bc73e5f0d3b3..23cad002fa12a3bd9b914e55a30dbf3f3fa2c61f 100644
--- a/Modules/Feature/Edge/test/otbSobelVectorImageFilter.cxx
+++ b/Modules/Feature/Edge/test/otbSobelVectorImageFilter.cxx
@@ -10,7 +10,7 @@
See OTBCopyright.txt for details.
Copyright (c) Institut Telecom; Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Feature/Edge/test/otbVerticalSobelVectorImageFilter.cxx b/Modules/Feature/Edge/test/otbVerticalSobelVectorImageFilter.cxx
index 5a8fffaa3fcd91285a508a38a0b5c7c7d4df5e95..a8439b128914ce180f4be2235d232c1f0116e3e5 100644
--- a/Modules/Feature/Edge/test/otbVerticalSobelVectorImageFilter.cxx
+++ b/Modules/Feature/Edge/test/otbVerticalSobelVectorImageFilter.cxx
@@ -10,7 +10,7 @@
See OTBCopyright.txt for details.
Copyright (c) Institut Telecom; Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Filtering/ChangeDetection/include/otbKullbackLeiblerDistanceImageFilter.h b/Modules/Filtering/ChangeDetection/include/otbKullbackLeiblerDistanceImageFilter.h
index 84ea1ceee6564a4e24529b3d7fc922e9693d6915..cba75ee655fa111f68e62e2583aa81c98a471a20 100644
--- a/Modules/Filtering/ChangeDetection/include/otbKullbackLeiblerDistanceImageFilter.h
+++ b/Modules/Filtering/ChangeDetection/include/otbKullbackLeiblerDistanceImageFilter.h
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom / Telecom Bretagne. All rights reserved.
- See GETCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Filtering/ChangeDetection/include/otbKullbackLeiblerDistanceImageFilter.txx b/Modules/Filtering/ChangeDetection/include/otbKullbackLeiblerDistanceImageFilter.txx
index 809e374422d982e0f414a4b5e3fc771fe320e676..b309f580dd3a8f64474af61c138c8931bfbc27c7 100644
--- a/Modules/Filtering/ChangeDetection/include/otbKullbackLeiblerDistanceImageFilter.txx
+++ b/Modules/Filtering/ChangeDetection/include/otbKullbackLeiblerDistanceImageFilter.txx
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom / Telecom Bretagne. All rights reserved.
- See GETCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Filtering/ChangeDetection/include/otbKullbackLeiblerProfileImageFilter.h b/Modules/Filtering/ChangeDetection/include/otbKullbackLeiblerProfileImageFilter.h
index 370a0384a24c9032b34934963fa3d2613ddc8087..d4a5e93c7fbd588e8837e1e98b9d5a924ae9c44c 100644
--- a/Modules/Filtering/ChangeDetection/include/otbKullbackLeiblerProfileImageFilter.h
+++ b/Modules/Filtering/ChangeDetection/include/otbKullbackLeiblerProfileImageFilter.h
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Some parts of this code are covered by the GET copyright.
- See GETCopyright.txt for details.
+ Some parts of this code are covered by the IMT copyright.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
diff --git a/Modules/Filtering/ChangeDetection/include/otbKullbackLeiblerProfileImageFilter.txx b/Modules/Filtering/ChangeDetection/include/otbKullbackLeiblerProfileImageFilter.txx
index d49f78abc37746079834cd246f39ee281b70761f..1620df7cd64f5851eb1d7a7c8f4e1aee8976738e 100644
--- a/Modules/Filtering/ChangeDetection/include/otbKullbackLeiblerProfileImageFilter.txx
+++ b/Modules/Filtering/ChangeDetection/include/otbKullbackLeiblerProfileImageFilter.txx
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Some parts of this code are covered by the GET copyright.
- See GETCopyright.txt for details.
+ Some parts of this code are covered by the IMT copyright.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
diff --git a/Modules/Filtering/ChangeDetection/include/otbKullbackLeiblerSupervizedDistanceImageFilter.h b/Modules/Filtering/ChangeDetection/include/otbKullbackLeiblerSupervizedDistanceImageFilter.h
index 511f219c2b421bf6772c7d10a885c4d8d52d1ac8..5498cc9cac67f24a45db362f15a7db469054ac5d 100644
--- a/Modules/Filtering/ChangeDetection/include/otbKullbackLeiblerSupervizedDistanceImageFilter.h
+++ b/Modules/Filtering/ChangeDetection/include/otbKullbackLeiblerSupervizedDistanceImageFilter.h
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom / Telecom Bretagne. All rights reserved.
- See GETCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Filtering/ChangeDetection/include/otbKullbackLeiblerSupervizedDistanceImageFilter.txx b/Modules/Filtering/ChangeDetection/include/otbKullbackLeiblerSupervizedDistanceImageFilter.txx
index f0454a6b8031c808b050294bb1cf7bc3906bbcdc..ab78083eda84b40169395d8e0dcb78958260fa76 100644
--- a/Modules/Filtering/ChangeDetection/include/otbKullbackLeiblerSupervizedDistanceImageFilter.txx
+++ b/Modules/Filtering/ChangeDetection/include/otbKullbackLeiblerSupervizedDistanceImageFilter.txx
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom / Telecom Bretagne. All rights reserved.
- See GETCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Filtering/DimensionalityReduction/test/otbAngularProjectionBinaryImageFilter.cxx b/Modules/Filtering/DimensionalityReduction/test/otbAngularProjectionBinaryImageFilter.cxx
index 8a4e4698fcbaee9db714a62a32c95e03cc2f5088..3fa0231e66b61b5145d5126b6c05163ee7d1acc2 100644
--- a/Modules/Filtering/DimensionalityReduction/test/otbAngularProjectionBinaryImageFilter.cxx
+++ b/Modules/Filtering/DimensionalityReduction/test/otbAngularProjectionBinaryImageFilter.cxx
@@ -10,7 +10,7 @@
See OTBCopyright.txt for details.
Copyright (c) Institut Telecom; Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Filtering/DimensionalityReduction/test/otbLocalActivityVectorImageFilter.cxx b/Modules/Filtering/DimensionalityReduction/test/otbLocalActivityVectorImageFilter.cxx
index 52c300533c90bd92c8f6b03636519e4a63f51b8a..c5ff2f8d53f45cdcda76815b82a286884d50fecc 100644
--- a/Modules/Filtering/DimensionalityReduction/test/otbLocalActivityVectorImageFilter.cxx
+++ b/Modules/Filtering/DimensionalityReduction/test/otbLocalActivityVectorImageFilter.cxx
@@ -10,7 +10,7 @@
See OTBCopyright.txt for details.
Copyright (c) Institut Telecom; Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Filtering/ImageManipulation/include/otbBoxAndWhiskerImageFilter.h b/Modules/Filtering/ImageManipulation/include/otbBoxAndWhiskerImageFilter.h
index 8197ec2e66992e6b22caf9c1df006398735b0dd0..7836509dd106b9d7a231c641c08946bb8bae2fe9 100644
--- a/Modules/Filtering/ImageManipulation/include/otbBoxAndWhiskerImageFilter.h
+++ b/Modules/Filtering/ImageManipulation/include/otbBoxAndWhiskerImageFilter.h
@@ -10,7 +10,7 @@
See OTBCopyright.txt for details.
Copyright (c) Institut Telecom; Telecom bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
diff --git a/Modules/Filtering/ImageManipulation/include/otbBoxAndWhiskerImageFilter.txx b/Modules/Filtering/ImageManipulation/include/otbBoxAndWhiskerImageFilter.txx
index 9863ae1b2f68d9d0838c05e58fd6e516311c65c9..f15af8aef16fbf0764a3f9d9b561276898ddadf6 100644
--- a/Modules/Filtering/ImageManipulation/include/otbBoxAndWhiskerImageFilter.txx
+++ b/Modules/Filtering/ImageManipulation/include/otbBoxAndWhiskerImageFilter.txx
@@ -10,7 +10,7 @@
See OTBCopyright.txt for details.
Copyright (c) Institut Telecom; Telecom bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
diff --git a/Modules/Filtering/ImageManipulation/include/otbChangeNoDataValueFilter.h b/Modules/Filtering/ImageManipulation/include/otbChangeNoDataValueFilter.h
new file mode 100644
index 0000000000000000000000000000000000000000..59d4fca6e387e8dae4588678c76a479b91c5ed01
--- /dev/null
+++ b/Modules/Filtering/ImageManipulation/include/otbChangeNoDataValueFilter.h
@@ -0,0 +1,178 @@
+/*=========================================================================
+
+ Program: ORFEO Toolbox
+ Language: C++
+ Date: $Date$
+ Version: $Revision$
+
+
+ Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
+ See OTBCopyright.txt for details.
+
+
+ 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.
+
+=========================================================================*/
+#ifndef __otbChangeNoDataValueFilter_h
+#define __otbChangeNoDataValueFilter_h
+
+#include "itkUnaryFunctorImageFilter.h"
+#include "itkMetaDataObject.h"
+#include "otbMetaDataKey.h"
+#include "otbNoDataHelper.h"
+
+namespace otb
+{
+namespace Functor
+{
+/** \class ChangeNoDataFunctor
+ * \brief Functor used by ChangeNoDataValueFilter
+ *
+ * See ChangeNoDataValueFilter for complete documentation.
+ * \ingroup OTBImageManipulation
+ */
+template <typename TInputPixel, typename TOutputPixel>
+class ChangeNoDataFunctor
+{
+public:
+ ChangeNoDataFunctor():
+ m_Flags(),
+ m_Values(),
+ m_NewValues(),
+ m_NaNIsNoData(false)
+ {}
+ virtual ~ChangeNoDataFunctor(){}
+
+ inline TOutputPixel operator()(const TInputPixel& in) const
+ {
+ return otb::ChangeNoData(in,m_Flags,m_Values,m_NewValues,m_NaNIsNoData);
+ }
+
+ std::vector<bool> m_Flags;
+ std::vector<double> m_Values;
+ std::vector<double> m_NewValues;
+ bool m_NaNIsNoData;
+};
+
+} // End namespace Functor
+
+/** \class ChangeNoDataValueFilter
+ * \brief Change no-data flags and values and replace them in image
+ *
+ * This filter reads the no-data flags (a boolean vector indicating
+ * for each band if a no-data value exists) and values (the actual
+ * value to be used as no-data for each band) from
+ * MetaDataDictionary, and allows to change this value.
+ *
+ * The algorithm is the following: for each pixel, for each channel
+ * in the pixel, if there is a no-data value for this channel
+ * (according to no-data flags) and the current channel value equals
+ * to the no-data value set for this channel, then the value is
+ * changed for the new no-data value specified by the
+ * users. Otherwise, value remains untouched.
+ *
+ * If NaNIsNoData is true:
+ * - NaN values will be considered as no data and replaced as well
+ * - Output image will have no-data flags and values for all bands
+ *
+ * If NaNIsNoData is false:
+ * - Band for which input no-data flags is false will remain
+ * untouched
+ * - Output image will have no-data flags and values only for bands
+ * for which input no-data flag is true.
+ *
+ * \ingroup Streamed
+ * \ingroup MultiThreaded
+ * \ingroup OTBImageManipulation
+ */
+template <typename TInputImage, typename TOutputImage>
+class ChangeNoDataValueFilter
+ : public itk::UnaryFunctorImageFilter<TInputImage,
+ TOutputImage,
+ Functor::ChangeNoDataFunctor<typename TInputImage::PixelType,
+ typename TOutputImage::PixelType> >
+{
+public:
+ typedef Functor::ChangeNoDataFunctor<typename TInputImage::PixelType,typename TOutputImage::PixelType> FunctorType;
+
+ typedef ChangeNoDataValueFilter Self;
+ typedef itk::UnaryFunctorImageFilter<TInputImage,
+ TOutputImage,
+ FunctorType> Superclass;
+ typedef itk::SmartPointer<Self> Pointer;
+ typedef itk::SmartPointer<const Self> ConstPointer;
+
+ /** Type macro */
+ itkNewMacro(Self);
+
+ /** Creation through object factory macro */
+ itkTypeMacro(ChangeNoDataValueFilter, itk::ImageToImageFilter);
+
+ /**
+ * Set the new no-data values
+ * \param newValues The vector of new no-data values (size should be
+ * >= to number of bands)
+ */
+ void SetNewNoDataValues(std::vector<double> & newValues)
+ {
+ this->GetFunctor().m_NewValues = newValues;
+ }
+
+ /**
+ * Set the NaN is no data flags
+ * \param nanIsNoData If true, NaN values will be considered as
+ * no-data as well (default is false)
+ */
+ void SetNaNIsNoData(bool nanIsNoData)
+ {
+ this->GetFunctor().m_NaNIsNoData = nanIsNoData;
+ }
+
+protected:
+ ChangeNoDataValueFilter()
+ {}
+
+ virtual ~ChangeNoDataValueFilter()
+ {}
+
+ virtual void GenerateOutputInformation()
+ {
+ Superclass::GenerateOutputInformation();
+
+ std::vector<bool> noDataValueAvailable;
+ std::vector<double> noDataValues;
+
+ bool ret = ReadNoDataFlags(this->GetInput()->GetMetaDataDictionary(),noDataValueAvailable,noDataValues);
+
+ if(!ret)
+ {
+ noDataValueAvailable.resize(this->GetInput()->GetNumberOfComponentsPerPixel(),false);
+ noDataValues.resize(this->GetInput()->GetNumberOfComponentsPerPixel(),0);
+ }
+
+ this->GetFunctor().m_Flags = noDataValueAvailable;
+ this->GetFunctor().m_Values = noDataValues;
+
+ std::vector<bool> flags = noDataValueAvailable;
+
+ if(this->GetFunctor().m_NaNIsNoData)
+ {
+ flags = std::vector<bool>(flags.size(),true);
+ }
+
+ WriteNoDataFlags(flags,this->GetFunctor().m_NewValues,this->GetOutput()->GetMetaDataDictionary());
+ }
+
+private:
+ ChangeNoDataValueFilter(const Self&); // purposely not implemented
+ void operator =(const Self&); // purposely not implemented
+
+};
+
+} // End namespace otb
+
+
+
+#endif
diff --git a/Modules/Filtering/ImageManipulation/include/otbEuclideanDistanceMetricWithMissingValue.h b/Modules/Filtering/ImageManipulation/include/otbEuclideanDistanceMetricWithMissingValue.h
index e92979c13ae23dc503c4a7a85338f9d5b3018c00..62bbeff2bb2ac17fbce7c6c4f1b7b9a5597f2189 100644
--- a/Modules/Filtering/ImageManipulation/include/otbEuclideanDistanceMetricWithMissingValue.h
+++ b/Modules/Filtering/ImageManipulation/include/otbEuclideanDistanceMetricWithMissingValue.h
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom / Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Filtering/ImageManipulation/include/otbEuclideanDistanceMetricWithMissingValuePow2.h b/Modules/Filtering/ImageManipulation/include/otbEuclideanDistanceMetricWithMissingValuePow2.h
index 6b0d7f4431a4343e990889f1a0686723e4301d0f..6aa3b2e47cc44848247961a76f5844ff5965643b 100644
--- a/Modules/Filtering/ImageManipulation/include/otbEuclideanDistanceMetricWithMissingValuePow2.h
+++ b/Modules/Filtering/ImageManipulation/include/otbEuclideanDistanceMetricWithMissingValuePow2.h
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom / Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Filtering/ImageManipulation/include/otbEuclideanDistanceMetricWithMissingValuePow2.txx b/Modules/Filtering/ImageManipulation/include/otbEuclideanDistanceMetricWithMissingValuePow2.txx
index f83dcc3e59ce9ae73c267aaf521a845b2b9da12e..37c2115f0f2869d4b26bc0490875db58a67eb551 100644
--- a/Modules/Filtering/ImageManipulation/include/otbEuclideanDistanceMetricWithMissingValuePow2.txx
+++ b/Modules/Filtering/ImageManipulation/include/otbEuclideanDistanceMetricWithMissingValuePow2.txx
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom / Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Filtering/ImageManipulation/include/otbFlexibleDistanceWithMissingValue.h b/Modules/Filtering/ImageManipulation/include/otbFlexibleDistanceWithMissingValue.h
index 0df9e91ab920e2263f7cc9c8568d4d84f0d094da..2c948872edaced2683511424babdae1b35ab8d41 100644
--- a/Modules/Filtering/ImageManipulation/include/otbFlexibleDistanceWithMissingValue.h
+++ b/Modules/Filtering/ImageManipulation/include/otbFlexibleDistanceWithMissingValue.h
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom / Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Filtering/ImageManipulation/include/otbFlexibleDistanceWithMissingValue.txx b/Modules/Filtering/ImageManipulation/include/otbFlexibleDistanceWithMissingValue.txx
index c8b77afd3556a93a00f381bea23ea3d97e6a8d39..9bdb74433f09aa97e0fbd201a90b5b30f3861676 100644
--- a/Modules/Filtering/ImageManipulation/include/otbFlexibleDistanceWithMissingValue.txx
+++ b/Modules/Filtering/ImageManipulation/include/otbFlexibleDistanceWithMissingValue.txx
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom / Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Filtering/ImageManipulation/include/otbImageToNoDataMaskFilter.h b/Modules/Filtering/ImageManipulation/include/otbImageToNoDataMaskFilter.h
index 02e09dd22ec43533330cf59a4a41345d5aaa7570..a790b37a0ea031c3695ac7fcb8058d313f51e0ea 100644
--- a/Modules/Filtering/ImageManipulation/include/otbImageToNoDataMaskFilter.h
+++ b/Modules/Filtering/ImageManipulation/include/otbImageToNoDataMaskFilter.h
@@ -27,6 +27,12 @@ namespace otb
{
namespace Functor
{
+/** \class NoDataFunctor
+ * \brief Functor used by ImageToNoDataMaskFilter
+ *
+ * See ImageToNoDataMaskFilter for complete documentation.
+ * \ingroup OTBImageManipulation
+ */
template <typename TInputPixel, typename TOutputPixel>
class NoDataFunctor
{
@@ -35,25 +41,42 @@ public:
m_Flags(),
m_Values(),
m_OutsideValue(0),
- m_InsideValue(1)
+ m_InsideValue(1),
+ m_NaNIsNoData(false)
{}
virtual ~NoDataFunctor(){}
inline TOutputPixel operator()(const TInputPixel& in) const
{
- return otb::IsNoData(in,m_Flags,m_Values)?m_OutsideValue:m_InsideValue;
+ return otb::IsNoData(in,m_Flags,m_Values,m_NaNIsNoData)?m_OutsideValue:m_InsideValue;
}
std::vector<bool> m_Flags;
std::vector<double> m_Values;
TOutputPixel m_OutsideValue;
TOutputPixel m_InsideValue;
+ bool m_NaNIsNoData;
};
} // End namespace Functor
-
+/** \class ImageToNoDataMaskFilter
+ * \brief Builds a no-data mask image from no-data flags and values
+ *
+ * This filter reads the no-data flags (a boolean vector indicating
+ * for each band if a no-data value exists) and values (the actual
+ * value to be used as no-data for each band) from
+ * MetaDataDictionary, and builds a binary mask indicating presence
+ * or absence of no-data for each pixel.
+ *
+ * If NaNIsNoData is true, NaN pixels will also be considered as
+ * no-data pixels.
+ *
+ * \ingroup Streamed
+ * \ingroup MultiThreaded
+ * \ingroup OTBImageManipulation
+ */
template <typename TInputImage, typename TOutputImage>
class ImageToNoDataMaskFilter
: public itk::UnaryFunctorImageFilter<TInputImage,
@@ -77,15 +100,31 @@ public:
/** Creation through object factory macro */
itkTypeMacro(SpectralAngleDistanceImageFilter, itk::ImageToImageFilter);
+ /**
+ * Set inside value of output mask. This value will be used to
+ * indicate absence of no-data for the pixel in the output mask
+ */
void SetInsideValue(const typename TOutputImage::PixelType & value)
{
this->GetFunctor().m_InsideValue = value;
}
-
+ /**
+ * Set outside value of output mask. This value will be used to
+ * indicate presence of no-data for the pixel in the output mask
+ */
void SetOutsideValue(const typename TOutputImage::PixelType & value)
{
this->GetFunctor().m_OutsideValue = value;
}
+ /**
+ * Set the NaN is no data flags
+ * \param nanIsNoData If true, NaN values will be considered as
+ * no-data as well (default is false)
+ */
+ void SetNaNIsNoData(bool nanIsNoData)
+ {
+ this->GetFunctor().m_NaNIsNoData=nanIsNoData;
+ }
protected:
ImageToNoDataMaskFilter()
@@ -97,23 +136,11 @@ protected:
virtual void BeforeThreadedGenerateData()
{
std::vector<bool> noDataValueAvailable;
- bool ret = itk::ExposeMetaData<std::vector<bool> >(this->GetInput()->GetMetaDataDictionary(),MetaDataKey::NoDataValueAvailable,noDataValueAvailable);
-
- if(!ret)
- {
- noDataValueAvailable.resize(this->GetInput()->GetNumberOfComponentsPerPixel(),false);
- }
-
- this->GetFunctor().m_Flags = noDataValueAvailable;
-
std::vector<double> noDataValues;
- ret = itk::ExposeMetaData<std::vector<double> >(this->GetInput()->GetMetaDataDictionary(),MetaDataKey::NoDataValue,noDataValues);
-
- if(!ret)
- {
- noDataValues.resize(this->GetInput()->GetNumberOfComponentsPerPixel(),0);
- }
+ ReadNoDataFlags(this->GetInput()->GetMetaDataDictionary(),noDataValueAvailable,noDataValues);
+
+ this->GetFunctor().m_Flags = noDataValueAvailable;
this->GetFunctor().m_Values = noDataValues;
}
diff --git a/Modules/Filtering/ImageManipulation/include/otbNRIBandImagesToOneNComplexBandsImage.h b/Modules/Filtering/ImageManipulation/include/otbNRIBandImagesToOneNComplexBandsImage.h
new file mode 100644
index 0000000000000000000000000000000000000000..18f1465b0941b453bd5c9330dda92e2873f69d4f
--- /dev/null
+++ b/Modules/Filtering/ImageManipulation/include/otbNRIBandImagesToOneNComplexBandsImage.h
@@ -0,0 +1,92 @@
+/*=========================================================================
+
+ Program: ORFEO Toolbox
+ Language: C++
+ Date: $Date$
+ Version: $Revision$
+
+
+ Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
+ See OTBCopyright.txt for details.
+
+
+ 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.
+
+=========================================================================*/
+#ifndef __otbNRIBandImagesToOneNComplexBandsImage_h
+#define __otbNRIBandImagesToOneNComplexBandsImage_h
+
+#include "itkImageToImageFilter.h"
+#include "itkImage.h"
+#include "itkNumericTraits.h"
+
+/*
+ * Inputs : N images made of two real bands
+ * Output : one single image made of N complex bands
+ *
+ * */
+
+
+namespace otb
+{
+
+
+template <class TInputImage, class TOutputImage>
+class ITK_EXPORT NRIBandImagesToOneNComplexBandsImage : public itk::ImageToImageFilter<TInputImage, TOutputImage>
+{
+public:
+ /** Extract input and output image dimension */
+ itkStaticConstMacro(InputImageDimension,
+ unsigned int,
+ TInputImage::ImageDimension);
+ itkStaticConstMacro(OutputImageDimension,
+ unsigned int,
+ TOutputImage::ImageDimension);
+
+ typedef TInputImage InputImageType;
+ typedef TOutputImage OutputImageType;
+
+ /** standard class typedefs */
+ typedef NRIBandImagesToOneNComplexBandsImage Self;
+ typedef itk::ImageToImageFilter<InputImageType, OutputImageType> Superclass;
+ typedef itk::SmartPointer<Self> Pointer;
+ typedef itk::SmartPointer<const Self> ConstPointer;
+
+ /** Object factory management */
+ itkNewMacro(Self);
+
+ /** typemacro */
+ itkTypeMacro(NRIBandImagesToOneNComplexBandsImage, ImageToImageFilter);
+
+ typedef typename InputImageType::PixelType InputPixelType;
+ typedef typename OutputImageType::PixelType OutputPixelType;
+ typedef typename itk::NumericTraits<InputPixelType>::RealType InputRealType;
+ typedef typename InputImageType::RegionType InputImageRegionType;
+ typedef typename OutputImageType::RegionType OutputImageRegionType;
+
+
+protected:
+ NRIBandImagesToOneNComplexBandsImage();
+ virtual ~NRIBandImagesToOneNComplexBandsImage() {}
+ void PrintSelf(std::ostream& os, itk::Indent indent) const;
+
+ void GenerateOutputInformation(void);
+ void BeforeThreadedGenerateData(void);
+ void ThreadedGenerateData(const OutputImageRegionType& outputRegionForThread,
+ itk::ThreadIdType threadId);
+
+private:
+ NRIBandImagesToOneNComplexBandsImage(const Self &); //purposely not implemented
+ void operator =(const Self&); //purposely not implemented
+
+
+};
+} // end namespace otb
+
+#ifndef OTB_MANUAL_INSTANTIATION
+#include "otbNRIBandImagesToOneNComplexBandsImage.txx"
+#endif
+
+#endif
diff --git a/Modules/Filtering/ImageManipulation/include/otbNRIBandImagesToOneNComplexBandsImage.txx b/Modules/Filtering/ImageManipulation/include/otbNRIBandImagesToOneNComplexBandsImage.txx
new file mode 100644
index 0000000000000000000000000000000000000000..46abbf79efee49136fe17fc0be5d36e9e6ae13cf
--- /dev/null
+++ b/Modules/Filtering/ImageManipulation/include/otbNRIBandImagesToOneNComplexBandsImage.txx
@@ -0,0 +1,139 @@
+/*=========================================================================
+
+ Program: ORFEO Toolbox
+ Language: C++
+ Date: $Date$
+ Version: $Revision$
+
+
+ Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
+ See OTBCopyright.txt for details.
+
+
+ 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.
+
+=========================================================================*/
+#ifndef __otbNRIBandImagesToOneNComplexBandsImage_txx
+#define __otbNRIBandImagesToOneNComplexBandsImage_txx
+
+#include "otbNRIBandImagesToOneNComplexBandsImage.h"
+
+#include "itkImageRegionIterator.h"
+#include "itkImageRegionConstIterator.h"
+#include "itkProgressReporter.h"
+#include "itkVariableLengthVector.h"
+
+
+
+
+namespace otb
+{
+
+/**
+ *
+ */
+template <class TInputImage, class TOutputImage>
+NRIBandImagesToOneNComplexBandsImage<TInputImage, TOutputImage>::NRIBandImagesToOneNComplexBandsImage()
+{
+ //this->SetNumberOfThreads(1);
+}
+
+/**
+ * GenerateOutputInformation
+ */
+template<class TInputImage, class TOutputImage>
+void
+NRIBandImagesToOneNComplexBandsImage<TInputImage, TOutputImage>
+::GenerateOutputInformation(void)
+{
+ Superclass::GenerateOutputInformation();
+
+ unsigned int nbInputs = this->GetNumberOfInputs();
+ this->GetOutput()->SetNumberOfComponentsPerPixel(nbInputs);
+
+}
+
+/**
+ * BeforeThreadedGenerateData
+ */
+template <class TInputImage, class TOutputImage>
+void
+NRIBandImagesToOneNComplexBandsImage<TInputImage, TOutputImage>
+::BeforeThreadedGenerateData(void)
+{
+ unsigned int nbInputs = this->GetNumberOfInputs();
+
+ for (unsigned int i=0; i<nbInputs; i++)
+ if (this->GetInput(i)->GetNumberOfComponentsPerPixel() != 2 )
+ itkExceptionMacro("Input images must be made of two bands and only two (see input #" << i << ").");
+
+}
+
+/**
+ * ThreadedGenerateData
+ */
+template<class TInputImage, class TOutputImage>
+void NRIBandImagesToOneNComplexBandsImage<TInputImage, TOutputImage>::ThreadedGenerateData(
+ const OutputImageRegionType& outputRegionForThread,
+ itk::ThreadIdType threadId
+ )
+{
+
+ // support progress methods/callbacks
+ itk::ProgressReporter progress(this, threadId, outputRegionForThread.GetNumberOfPixels());
+
+ unsigned int nbInputs = this->GetNumberOfInputs();
+
+ itk::VariableLengthVector< std::complex< typename InputPixelType::ValueType > > vlv(nbInputs);
+
+ std::vector< typename itk::ImageRegionConstIterator<TInputImage> > vInIt;
+ for (unsigned int i=0; i<nbInputs; i++)
+ vInIt.push_back( itk::ImageRegionConstIterator<TInputImage>(this->GetInput(i), outputRegionForThread) );
+
+
+ itk::ImageRegionIterator<OutputImageType> outIt;
+ outIt = itk::ImageRegionIterator<OutputImageType>(this->GetOutput(), outputRegionForThread);
+
+ for (unsigned int i=0; i<nbInputs; i++)
+ vInIt[i].GoToBegin();
+ outIt.GoToBegin();
+
+ while (!outIt.IsAtEnd())
+ {
+
+
+ for (unsigned int i=0; i<nbInputs; i++)
+ {
+ vlv[i] = std::complex< typename InputPixelType::ValueType >(vInIt[i].Get()[0],vInIt[i].Get()[1]);
+ //std::cout << "i = " << i << " " << vInIt[i].Get()[0] << " " << vInIt[i].Get()[1] << std::endl;
+ }
+
+
+ outIt.Set(vlv);
+
+ //std::cout << "outIt.Get() = " << outIt.Get() << std::endl;
+
+ for (unsigned int i=0; i<nbInputs; i++)
+ ++vInIt[i];
+ ++outIt;
+
+ progress.CompletedPixel();
+ }
+
+}
+
+/**
+ * Standard "PrintSelf" method
+ */
+template <class TInputImage, class TOutput>
+void
+NRIBandImagesToOneNComplexBandsImage<TInputImage, TOutput>::PrintSelf(std::ostream& os, itk::Indent indent) const
+{
+ Superclass::PrintSelf(os, indent);
+}
+
+} // end namespace otb
+
+#endif
diff --git a/Modules/Filtering/ImageManipulation/include/otbOneRIBandImageToOneComplexBandImage.h b/Modules/Filtering/ImageManipulation/include/otbOneRIBandImageToOneComplexBandImage.h
new file mode 100644
index 0000000000000000000000000000000000000000..745199721496ff2f6b9797cfa5e031ab3ec4ebde
--- /dev/null
+++ b/Modules/Filtering/ImageManipulation/include/otbOneRIBandImageToOneComplexBandImage.h
@@ -0,0 +1,91 @@
+/*=========================================================================
+
+ Program: ORFEO Toolbox
+ Language: C++
+ Date: $Date$
+ Version: $Revision$
+
+
+ Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
+ See OTBCopyright.txt for details.
+
+
+ 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.
+
+=========================================================================*/
+#ifndef __otbOneRIBandImageToOneComplexBandImage_h
+#define __otbOneRIBandImageToOneComplexBandImage_h
+
+#include "itkImageToImageFilter.h"
+#include "itkImage.h"
+#include "itkNumericTraits.h"
+
+
+/*
+ * Inputs : one image made of two real bands
+ * Output : one image made of one complex band
+ *
+ * */
+
+namespace otb
+{
+
+
+template <class TInputImage, class TOutputImage>
+class ITK_EXPORT OneRIBandImageToOneComplexBandImage : public itk::ImageToImageFilter<TInputImage, TOutputImage>
+{
+public:
+ /** Extract input and output image dimension */
+ itkStaticConstMacro(InputImageDimension,
+ unsigned int,
+ TInputImage::ImageDimension);
+ itkStaticConstMacro(OutputImageDimension,
+ unsigned int,
+ TOutputImage::ImageDimension);
+
+ typedef TInputImage InputImageType;
+ typedef TOutputImage OutputImageType;
+
+ /** standard class typedefs */
+ typedef OneRIBandImageToOneComplexBandImage Self;
+ typedef itk::ImageToImageFilter<InputImageType, OutputImageType> Superclass;
+ typedef itk::SmartPointer<Self> Pointer;
+ typedef itk::SmartPointer<const Self> ConstPointer;
+
+ /** Object factory management */
+ itkNewMacro(Self);
+
+ /** typemacro */
+ itkTypeMacro(OneRIBandImageToOneComplexBandImage, ImageToImageFilter);
+
+ typedef typename InputImageType::PixelType InputPixelType;
+ typedef typename OutputImageType::PixelType OutputPixelType;
+ typedef typename itk::NumericTraits<InputPixelType>::RealType InputRealType;
+ typedef typename InputImageType::RegionType InputImageRegionType;
+ typedef typename OutputImageType::RegionType OutputImageRegionType;
+
+
+protected:
+ OneRIBandImageToOneComplexBandImage();
+ virtual ~OneRIBandImageToOneComplexBandImage() {}
+ void PrintSelf(std::ostream& os, itk::Indent indent) const;
+
+ void BeforeThreadedGenerateData(void);
+ void ThreadedGenerateData(const OutputImageRegionType& outputRegionForThread,
+ itk::ThreadIdType threadId);
+
+private:
+ OneRIBandImageToOneComplexBandImage(const Self &); //purposely not implemented
+ void operator =(const Self&); //purposely not implemented
+
+
+};
+} // end namespace otb
+
+#ifndef OTB_MANUAL_INSTANTIATION
+#include "otbOneRIBandImageToOneComplexBandImage.txx"
+#endif
+
+#endif
diff --git a/Modules/Filtering/ImageManipulation/include/otbOneRIBandImageToOneComplexBandImage.txx b/Modules/Filtering/ImageManipulation/include/otbOneRIBandImageToOneComplexBandImage.txx
new file mode 100644
index 0000000000000000000000000000000000000000..8a7003a8eec8066ed212245a9ff0162310f38499
--- /dev/null
+++ b/Modules/Filtering/ImageManipulation/include/otbOneRIBandImageToOneComplexBandImage.txx
@@ -0,0 +1,100 @@
+/*=========================================================================
+
+ Program: ORFEO Toolbox
+ Language: C++
+ Date: $Date$
+ Version: $Revision$
+
+
+ Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
+ See OTBCopyright.txt for details.
+
+
+ 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.
+
+=========================================================================*/
+#ifndef __otbOneRIBandImageToOneComplexBandImage_txx
+#define __otbOneRIBandImageToOneComplexBandImage_txx
+
+#include "otbOneRIBandImageToOneComplexBandImage.h"
+
+#include "itkImageRegionIterator.h"
+#include "itkImageRegionConstIterator.h"
+#include "itkProgressReporter.h"
+
+namespace otb
+{
+
+/**
+ *
+ */
+template <class TInputImage, class TOutputImage>
+OneRIBandImageToOneComplexBandImage<TInputImage, TOutputImage>::OneRIBandImageToOneComplexBandImage()
+{
+ //this->SetNumberOfThreads(1);
+}
+
+/**
+ * BeforeThreadedGenerateData
+ */
+template <class TInputImage, class TOutputImage>
+void
+OneRIBandImageToOneComplexBandImage<TInputImage, TOutputImage>
+::BeforeThreadedGenerateData(void)
+{
+ if (this->GetInput()->GetNumberOfComponentsPerPixel() != 2 )
+ itkExceptionMacro("Input image must be made of two bands and only two.");
+
+}
+
+/**
+ * ThreadedGenerateData
+ */
+template<class TInputImage, class TOutputImage>
+void OneRIBandImageToOneComplexBandImage<TInputImage, TOutputImage>::ThreadedGenerateData(
+ const OutputImageRegionType& outputRegionForThread,
+ itk::ThreadIdType threadId
+ )
+{
+
+ // support progress methods/callbacks
+ itk::ProgressReporter progress(this, threadId, outputRegionForThread.GetNumberOfPixels());
+
+ typename OutputImageType::Pointer output = this->GetOutput();
+ typename InputImageType::ConstPointer input = this->GetInput();
+
+ itk::ImageRegionIterator<OutputImageType> it;
+ itk::ImageRegionConstIterator<TInputImage> itIn;
+
+ itIn = itk::ImageRegionConstIterator<TInputImage>(input, outputRegionForThread);
+ it = itk::ImageRegionIterator<OutputImageType>(output, outputRegionForThread);
+
+ it.GoToBegin();
+ itIn.GoToBegin();
+ while (!it.IsAtEnd())
+ {
+
+ it.Set(static_cast<OutputPixelType>( std::complex< typename InputPixelType::ValueType >(itIn.Get()[0],itIn.Get()[1]) ));
+
+ ++it;
+ ++itIn;
+ progress.CompletedPixel();
+ }
+
+}
+
+/**
+ * Standard "PrintSelf" method
+ */
+template <class TInputImage, class TOutput>
+void
+OneRIBandImageToOneComplexBandImage<TInputImage, TOutput>::PrintSelf(std::ostream& os, itk::Indent indent) const
+{
+ Superclass::PrintSelf(os, indent);
+}
+
+} // end namespace otb
+
+#endif
diff --git a/Modules/Filtering/ImageManipulation/include/otbTwoNRIBandsImageToNComplexBandsImage.h b/Modules/Filtering/ImageManipulation/include/otbTwoNRIBandsImageToNComplexBandsImage.h
new file mode 100644
index 0000000000000000000000000000000000000000..e60a091176e80ff21ba52c3156aa2ba0413b3a13
--- /dev/null
+++ b/Modules/Filtering/ImageManipulation/include/otbTwoNRIBandsImageToNComplexBandsImage.h
@@ -0,0 +1,92 @@
+/*=========================================================================
+
+ Program: ORFEO Toolbox
+ Language: C++
+ Date: $Date$
+ Version: $Revision$
+
+
+ Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
+ See OTBCopyright.txt for details.
+
+
+ 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.
+
+=========================================================================*/
+#ifndef __otbTwoNRIBandsImageToNComplexBandsImage_h
+#define __otbTwoNRIBandsImageToNComplexBandsImage_h
+
+#include "itkImageToImageFilter.h"
+#include "itkImage.h"
+#include "itkNumericTraits.h"
+
+/*
+ * Inputs : one single image made of 2N real bands
+ * Output : one single image made of N complex bands
+ *
+ * */
+
+
+namespace otb
+{
+
+
+template <class TInputImage, class TOutputImage>
+class ITK_EXPORT TwoNRIBandsImageToNComplexBandsImage : public itk::ImageToImageFilter<TInputImage, TOutputImage>
+{
+public:
+ /** Extract input and output image dimension */
+ itkStaticConstMacro(InputImageDimension,
+ unsigned int,
+ TInputImage::ImageDimension);
+ itkStaticConstMacro(OutputImageDimension,
+ unsigned int,
+ TOutputImage::ImageDimension);
+
+ typedef TInputImage InputImageType;
+ typedef TOutputImage OutputImageType;
+
+ /** standard class typedefs */
+ typedef TwoNRIBandsImageToNComplexBandsImage Self;
+ typedef itk::ImageToImageFilter<InputImageType, OutputImageType> Superclass;
+ typedef itk::SmartPointer<Self> Pointer;
+ typedef itk::SmartPointer<const Self> ConstPointer;
+
+ /** Object factory management */
+ itkNewMacro(Self);
+
+ /** typemacro */
+ itkTypeMacro(TwoNRIBandsImageToNComplexBandsImage, ImageToImageFilter);
+
+ typedef typename InputImageType::PixelType InputPixelType;
+ typedef typename OutputImageType::PixelType OutputPixelType;
+ typedef typename itk::NumericTraits<InputPixelType>::RealType InputRealType;
+ typedef typename InputImageType::RegionType InputImageRegionType;
+ typedef typename OutputImageType::RegionType OutputImageRegionType;
+
+
+protected:
+ TwoNRIBandsImageToNComplexBandsImage();
+ virtual ~TwoNRIBandsImageToNComplexBandsImage() {}
+ void PrintSelf(std::ostream& os, itk::Indent indent) const;
+
+ void GenerateOutputInformation(void);
+ void BeforeThreadedGenerateData(void);
+ void ThreadedGenerateData(const OutputImageRegionType& outputRegionForThread,
+ itk::ThreadIdType threadId);
+
+private:
+ TwoNRIBandsImageToNComplexBandsImage(const Self &); //purposely not implemented
+ void operator =(const Self&); //purposely not implemented
+
+
+};
+} // end namespace otb
+
+#ifndef OTB_MANUAL_INSTANTIATION
+#include "otbTwoNRIBandsImageToNComplexBandsImage.txx"
+#endif
+
+#endif
diff --git a/Modules/Filtering/ImageManipulation/include/otbTwoNRIBandsImageToNComplexBandsImage.txx b/Modules/Filtering/ImageManipulation/include/otbTwoNRIBandsImageToNComplexBandsImage.txx
new file mode 100644
index 0000000000000000000000000000000000000000..c61f07a9009b4fe2365f926e55c1a9c4111b27fa
--- /dev/null
+++ b/Modules/Filtering/ImageManipulation/include/otbTwoNRIBandsImageToNComplexBandsImage.txx
@@ -0,0 +1,143 @@
+/*=========================================================================
+
+ Program: ORFEO Toolbox
+ Language: C++
+ Date: $Date$
+ Version: $Revision$
+
+
+ Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
+ See OTBCopyright.txt for details.
+
+
+ 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.
+
+=========================================================================*/
+#ifndef __otbTwoNRIBandsImageToNComplexBandsImage_txx
+#define __otbTwoNRIBandsImageToNComplexBandsImage_txx
+
+#include "otbTwoNRIBandsImageToNComplexBandsImage.h"
+
+#include "itkImageRegionIterator.h"
+#include "itkImageRegionConstIterator.h"
+#include "itkProgressReporter.h"
+#include "itkVariableLengthVector.h"
+
+
+
+
+namespace otb
+{
+
+/**
+ *
+ */
+template <class TInputImage, class TOutputImage>
+TwoNRIBandsImageToNComplexBandsImage<TInputImage, TOutputImage>::TwoNRIBandsImageToNComplexBandsImage()
+{
+ //this->SetNumberOfThreads(1);
+}
+
+/**
+ * GenerateOutputInformation
+ */
+template<class TInputImage, class TOutputImage>
+void
+TwoNRIBandsImageToNComplexBandsImage<TInputImage, TOutputImage>
+::GenerateOutputInformation(void)
+{
+ Superclass::GenerateOutputInformation();
+
+ unsigned int nbCompo = this->GetInput()->GetNumberOfComponentsPerPixel();
+
+ if ( (nbCompo % 2) != 0 )
+ {
+ itkExceptionMacro("Number of bands of the input images must be an even number");
+ }
+ else
+ this->GetOutput()->SetNumberOfComponentsPerPixel(nbCompo/2);
+
+ std::cout << "GenerateOutputInformation : " << this->GetOutput()->GetNumberOfComponentsPerPixel() << std::endl;
+
+}
+
+/**
+ * BeforeThreadedGenerateData
+ */
+template <class TInputImage, class TOutputImage>
+void
+TwoNRIBandsImageToNComplexBandsImage<TInputImage, TOutputImage>
+::BeforeThreadedGenerateData(void)
+{
+ unsigned int nbCompo = this->GetInput()->GetNumberOfComponentsPerPixel();
+
+ if ( (nbCompo % 2) != 0 )
+ itkExceptionMacro("Number of bands of the input images must be an even number");
+
+}
+
+/**
+ * ThreadedGenerateData
+ */
+template<class TInputImage, class TOutputImage>
+void TwoNRIBandsImageToNComplexBandsImage<TInputImage, TOutputImage>::ThreadedGenerateData(
+ const OutputImageRegionType& outputRegionForThread,
+ itk::ThreadIdType threadId
+ )
+{
+
+ unsigned int nbCompo = this->GetInput()->GetNumberOfComponentsPerPixel();
+
+ itk::VariableLengthVector< std::complex< typename InputPixelType::ValueType > > vlv(nbCompo/2);
+
+
+ // support progress methods/callbacks
+ itk::ProgressReporter progress(this, threadId, outputRegionForThread.GetNumberOfPixels());
+
+ itk::ImageRegionConstIterator<TInputImage> inIt;
+ inIt = itk::ImageRegionConstIterator<TInputImage>(this->GetInput(), outputRegionForThread);
+
+ itk::ImageRegionIterator<OutputImageType> outIt;
+ outIt = itk::ImageRegionIterator<OutputImageType>(this->GetOutput(), outputRegionForThread);
+
+
+ inIt.GoToBegin();
+ outIt.GoToBegin();
+
+ while (!outIt.IsAtEnd())
+ {
+
+ unsigned int k=0;
+ for (unsigned int i=0; i<nbCompo-1; i=i+2)
+ {
+ vlv[k] = std::complex< typename InputPixelType::ValueType >(inIt.Get()[i],inIt.Get()[i+1]);
+ k++;
+ }
+
+
+ outIt.Set(vlv);
+
+
+ ++inIt;
+ ++outIt;
+
+ progress.CompletedPixel();
+ }
+
+}
+
+/**
+ * Standard "PrintSelf" method
+ */
+template <class TInputImage, class TOutput>
+void
+TwoNRIBandsImageToNComplexBandsImage<TInputImage, TOutput>::PrintSelf(std::ostream& os, itk::Indent indent) const
+{
+ Superclass::PrintSelf(os, indent);
+}
+
+} // end namespace otb
+
+#endif
diff --git a/Modules/Filtering/ImageManipulation/otb-module.cmake b/Modules/Filtering/ImageManipulation/otb-module.cmake
index ca49464420ecf8215c1d36eacf45005fdcabc6c7..6a141566a1a1453663ce78f55c6ccf0f1742b5c8 100644
--- a/Modules/Filtering/ImageManipulation/otb-module.cmake
+++ b/Modules/Filtering/ImageManipulation/otb-module.cmake
@@ -10,6 +10,7 @@ otb_module(OTBImageManipulation
OTBCommon
OTBITK
OTBImageBase
+ OTBMetadata
OTBInterpolation
OTBObjectList
OTBStreaming
diff --git a/Modules/Filtering/ImageManipulation/test/CMakeLists.txt b/Modules/Filtering/ImageManipulation/test/CMakeLists.txt
index a167f9c62b9244001dddfbc4c2d215ee88fcc9bb..86e9cd72c67dca156fc4fd293c9b220ff186fc21 100644
--- a/Modules/Filtering/ImageManipulation/test/CMakeLists.txt
+++ b/Modules/Filtering/ImageManipulation/test/CMakeLists.txt
@@ -70,6 +70,11 @@ otbSpectralAngleDistanceImageFilter.cxx
otbFunctionWithNeighborhoodToImageFilterNew.cxx
otbEuclideanDistanceMetricWithMissingValue.cxx
otbEuclideanDistanceMetricWithMissingValueNew.cxx
+otbNRIBandImagesToOneNComplexBandsImage.cxx
+otbOneRIBandImageToOneComplexBandImage.cxx
+otbTwoNRIBandsImageToNComplexBandsImage.cxx
+otbChangeNoDataValueFilter.cxx
+otbImageToNoDataMaskFilter.cxx
)
add_executable(otbImageManipulationTestDriver ${OTBImageManipulationTests})
@@ -669,3 +674,39 @@ otb_add_test(NAME bfTvEuclideanDistanceMetricWithMissingValue COMMAND otbImageMa
otbEuclideanDistanceMetricWithMissingValue)
otb_add_test(NAME bfTuEuclideanDistanceMetricWithMissingValueNew COMMAND otbImageManipulationTestDriver
otbEuclideanDistanceMetricWithMissingValueNew)
+
+otb_add_test(NAME bfTvTwoNRIBandsImageToNComplexBandsImage COMMAND otbImageManipulationTestDriver
+ --compare-image ${EPSILON_7}
+ ${BASELINE}/bfTvNRIBandImagesToOneNComplexBandsImage.tif
+ ${TEMP}/bfTvTwoNRIBandsImageToNComplexBandsImage.tif
+ otbTwoNRIBandsImageToNComplexBandsImage
+ ${INPUTDATA}/RSAT_imagery_HH_HV_VV.tif
+ ${TEMP}/bfTvTwoNRIBandsImageToNComplexBandsImage.tif
+ )
+
+
+otb_add_test(NAME bfTvNRIBandImagesToOneNComplexBandsImage COMMAND otbImageManipulationTestDriver
+ --compare-image ${EPSILON_7}
+ ${BASELINE}/bfTvNRIBandImagesToOneNComplexBandsImage.tif
+ ${TEMP}/bfTvNRIBandImagesToOneNComplexBandsImage.tif
+ otbNRIBandImagesToOneNComplexBandsImage
+ ${INPUTDATA}/RSAT_imagery_HH.tif
+ ${INPUTDATA}/RSAT_imagery_HV.tif
+ ${INPUTDATA}/RSAT_imagery_VV.tif
+ ${TEMP}/bfTvNRIBandImagesToOneNComplexBandsImage.tif
+ )
+
+otb_add_test(NAME bfTvOneRIBandImageToOneComplexBandImage COMMAND otbImageManipulationTestDriver
+ --compare-image ${EPSILON_3}
+ ${INPUTDATA}/RSAT_imageryC_HH.tif
+ ${TEMP}/bfTvOneRIBandImageToOneComplexBandImage.tif
+ otbOneRIBandImageToOneComplexBandImage
+ ${INPUTDATA}/RSAT_imagery_HH.tif
+ ${TEMP}/bfTvOneRIBandImageToOneComplexBandImage.tif
+ )
+
+otb_add_test(NAME filteringImageManipulationChangeNoDataValueFilter COMMAND otbImageManipulationTestDriver
+ otbChangeNoDataValueFilter)
+
+otb_add_test(NAME filteringImageManipulationImageToNoDataMaskFilter COMMAND otbImageManipulationTestDriver
+ otbImageToNoDataMaskFilter)
diff --git a/Modules/Filtering/ImageManipulation/test/otbBoxAndWhiskerImageFilterNew.cxx b/Modules/Filtering/ImageManipulation/test/otbBoxAndWhiskerImageFilterNew.cxx
index bace7cb8f528de698a4f949720ee62708eb1edf9..827e79d2191b0babc59220b1ddced3af32253ce9 100644
--- a/Modules/Filtering/ImageManipulation/test/otbBoxAndWhiskerImageFilterNew.cxx
+++ b/Modules/Filtering/ImageManipulation/test/otbBoxAndWhiskerImageFilterNew.cxx
@@ -10,7 +10,7 @@
See OTBCopyright.txt for details.
Copyright (c) Institut Telecom; Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Filtering/ImageManipulation/test/otbChangeNoDataValueFilter.cxx b/Modules/Filtering/ImageManipulation/test/otbChangeNoDataValueFilter.cxx
new file mode 100644
index 0000000000000000000000000000000000000000..db371582435603f927fdd60004275ee41ed9e28e
--- /dev/null
+++ b/Modules/Filtering/ImageManipulation/test/otbChangeNoDataValueFilter.cxx
@@ -0,0 +1,103 @@
+/*=========================================================================
+
+ Program: ORFEO Toolbox
+ Language: C++
+ Date: $Date$
+ Version: $Revision$
+
+
+ Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
+ See OTBCopyright.txt for details.
+
+
+ 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 "otbImage.h"
+#include "otbChangeNoDataValueFilter.h"
+#include "itkImageRegionIterator.h"
+
+int otbChangeNoDataValueFilter(int itkNotUsed(argc),char * itkNotUsed(argv) [])
+{
+
+ // Build an image
+ typedef otb::Image<double> ImageType;
+ ImageType::Pointer img = ImageType::New();
+
+ ImageType::SizeType size;
+ size.Fill(20);
+
+ ImageType::RegionType region;
+ region.SetSize(size);
+
+ // Fill it with a default value
+ img->SetRegions(region);
+ img->Allocate();
+ img->FillBuffer(10);
+
+ // Write no-data flags to it
+ std::vector<bool> flags(1,true);
+ std::vector<double> values(1,-10.);
+ otb::WriteNoDataFlags(flags,values,img->GetMetaDataDictionary());
+
+ // Fill half of the pixels with no-data values
+ itk::ImageRegionIterator<ImageType> it(img,region);
+ unsigned int count = 0;
+ for(it.GoToBegin();!it.IsAtEnd();++it,++count)
+ {
+ if (count%2 == 0)
+ it.Set(-10.);
+ }
+
+ // Instanciate filter
+ typedef otb::ChangeNoDataValueFilter<ImageType,ImageType> FilterType;
+ FilterType::Pointer filter = FilterType::New();
+
+ std::vector<double> newValues(1,-20.);
+
+ filter->SetInput(img);
+ filter->SetNewNoDataValues(newValues);
+ filter->Update();
+
+ // Check output
+ it = itk::ImageRegionIterator<ImageType>(filter->GetOutput(),region);
+ count = 0;
+
+ bool failed = false;
+
+ for(it.GoToBegin();!it.IsAtEnd();++it,++count)
+ {
+ if (count%2 == 0 && it.Get()!=-20.)
+ {
+ std::cerr<<"Pixel should have new no-data value"<<std::endl;
+ failed = true;
+ }
+ else if(count%2 == 1 && it.Get()!=10.)
+ {
+ std::cerr<<"Pixel value should be unchanged"<<std::endl;
+ failed = true;
+ }
+ }
+
+ otb::ReadNoDataFlags(filter->GetOutput()->GetMetaDataDictionary(),flags,values);
+
+ if(flags.empty() || !flags[0])
+ {
+ std::cerr<<"Output no-data flag should be [1] "<<std::endl;
+ failed = true;
+ }
+
+ if(values.empty() || values[0]!=-20)
+ {
+ std::cerr<<"Output no-data value should be [-20.]"<<std::endl;
+ failed = true;
+ }
+
+ if(failed)
+ return EXIT_FAILURE;
+
+ return EXIT_SUCCESS;
+}
diff --git a/Modules/Filtering/ImageManipulation/test/otbEuclideanDistanceMetricWithMissingValue.cxx b/Modules/Filtering/ImageManipulation/test/otbEuclideanDistanceMetricWithMissingValue.cxx
index 6fbf120df973a0f5fb2cf629bfddfac334d29c5e..735ab4835d4c91c4def31ba82a2ccac86676333c 100644
--- a/Modules/Filtering/ImageManipulation/test/otbEuclideanDistanceMetricWithMissingValue.cxx
+++ b/Modules/Filtering/ImageManipulation/test/otbEuclideanDistanceMetricWithMissingValue.cxx
@@ -10,7 +10,7 @@
See OTBCopyright.txt for details.
Copyright (c) Institut Telecom; Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Filtering/ImageManipulation/test/otbEuclideanDistanceMetricWithMissingValueNew.cxx b/Modules/Filtering/ImageManipulation/test/otbEuclideanDistanceMetricWithMissingValueNew.cxx
index ce7620111e718a0d3d1fcc5ea7ecf5593c224180..2b2961961acf065b69dc6b47f8a26e51766f949f 100644
--- a/Modules/Filtering/ImageManipulation/test/otbEuclideanDistanceMetricWithMissingValueNew.cxx
+++ b/Modules/Filtering/ImageManipulation/test/otbEuclideanDistanceMetricWithMissingValueNew.cxx
@@ -10,7 +10,7 @@
See OTBCopyright.txt for details.
Copyright (c) Institut Telecom; Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Filtering/ImageManipulation/test/otbImageManipulationTestDriver.cxx b/Modules/Filtering/ImageManipulation/test/otbImageManipulationTestDriver.cxx
index 361248a4fcbb5551d81813d644053459597fe768..f732d0d2a493a927ccfd34f1f5633d85b3508cf3 100644
--- a/Modules/Filtering/ImageManipulation/test/otbImageManipulationTestDriver.cxx
+++ b/Modules/Filtering/ImageManipulation/test/otbImageManipulationTestDriver.cxx
@@ -76,4 +76,9 @@ void RegisterTests()
REGISTER_TEST(otbFunctionWithNeighborhoodToImageFilterNew);
REGISTER_TEST(otbEuclideanDistanceMetricWithMissingValue);
REGISTER_TEST(otbEuclideanDistanceMetricWithMissingValueNew);
+ REGISTER_TEST(otbNRIBandImagesToOneNComplexBandsImage);
+ REGISTER_TEST(otbOneRIBandImageToOneComplexBandImage);
+ REGISTER_TEST(otbTwoNRIBandsImageToNComplexBandsImage);
+ REGISTER_TEST(otbChangeNoDataValueFilter);
+ REGISTER_TEST(otbImageToNoDataMaskFilter);
}
diff --git a/Modules/Filtering/ImageManipulation/test/otbImageToNoDataMaskFilter.cxx b/Modules/Filtering/ImageManipulation/test/otbImageToNoDataMaskFilter.cxx
new file mode 100644
index 0000000000000000000000000000000000000000..d5c2b4283635847be4947e15791e785ec1924d9d
--- /dev/null
+++ b/Modules/Filtering/ImageManipulation/test/otbImageToNoDataMaskFilter.cxx
@@ -0,0 +1,88 @@
+/*=========================================================================
+
+ Program: ORFEO Toolbox
+ Language: C++
+ Date: $Date$
+ Version: $Revision$
+
+
+ Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
+ See OTBCopyright.txt for details.
+
+
+ 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 "otbImage.h"
+#include "otbImageToNoDataMaskFilter.h"
+#include "itkImageRegionIterator.h"
+
+int otbImageToNoDataMaskFilter(int itkNotUsed(argc),char * itkNotUsed(argv) [])
+{
+
+ // Build an image
+ typedef otb::Image<double> ImageType;
+ ImageType::Pointer img = ImageType::New();
+
+ ImageType::SizeType size;
+ size.Fill(20);
+
+ ImageType::RegionType region;
+ region.SetSize(size);
+
+ // Fill it with a default value
+ img->SetRegions(region);
+ img->Allocate();
+ img->FillBuffer(10);
+
+ // Write no-data flags to it
+ std::vector<bool> flags(1,true);
+ std::vector<double> values(1,-10.);
+ otb::WriteNoDataFlags(flags,values,img->GetMetaDataDictionary());
+
+ // Fill half of the pixels with no-data values
+ itk::ImageRegionIterator<ImageType> it(img,region);
+ unsigned int count = 0;
+ for(it.GoToBegin();!it.IsAtEnd();++it,++count)
+ {
+ if (count%2 == 0)
+ it.Set(-10.);
+ }
+
+ // Instanciate filter
+ typedef otb::ImageToNoDataMaskFilter<ImageType,ImageType> FilterType;
+ FilterType::Pointer filter = FilterType::New();
+
+ filter->SetInput(img);
+ filter->SetInsideValue(255);
+ filter->SetOutsideValue(0);
+ filter->Update();
+
+ // Check output
+ it = itk::ImageRegionIterator<ImageType>(filter->GetOutput(),region);
+ count = 0;
+
+ bool failed = false;
+
+ for(it.GoToBegin();!it.IsAtEnd();++it,++count)
+ {
+ if (count%2 == 0 && it.Get()!=0)
+ {
+ std::cerr<<"Pixel should be masked"<<std::endl;
+ failed = true;
+ }
+ else if(count%2 == 1 && it.Get()!=255)
+ {
+ std::cerr<<"Pixel should not be masked"<<std::endl;
+ failed = true;
+ }
+ }
+
+ if(failed)
+ return EXIT_FAILURE;
+
+ return EXIT_SUCCESS;
+}
diff --git a/Modules/Filtering/ImageManipulation/test/otbLocalGradientVectorImageFilter.cxx b/Modules/Filtering/ImageManipulation/test/otbLocalGradientVectorImageFilter.cxx
index 82de2de31555e30681d946c6177759f632920b0e..9d16be65e81184ea3bdb5c7539b866b9e4529661 100644
--- a/Modules/Filtering/ImageManipulation/test/otbLocalGradientVectorImageFilter.cxx
+++ b/Modules/Filtering/ImageManipulation/test/otbLocalGradientVectorImageFilter.cxx
@@ -10,7 +10,7 @@
See OTBCopyright.txt for details.
Copyright (c) Institut Telecom; Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Filtering/ImageManipulation/test/otbNRIBandImagesToOneNComplexBandsImage.cxx b/Modules/Filtering/ImageManipulation/test/otbNRIBandImagesToOneNComplexBandsImage.cxx
new file mode 100644
index 0000000000000000000000000000000000000000..778f42146ea0b8ddd85ef72a63e121cf245d15c1
--- /dev/null
+++ b/Modules/Filtering/ImageManipulation/test/otbNRIBandImagesToOneNComplexBandsImage.cxx
@@ -0,0 +1,62 @@
+/*=========================================================================
+
+ Program: ORFEO Toolbox
+ Language: C++
+ Date: $Date$
+ Version: $Revision$
+
+
+ Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
+ See OTBCopyright.txt for details.
+
+
+ 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 "itkMacro.h"
+
+#include "otbNRIBandImagesToOneNComplexBandsImage.h"
+
+#include "otbImage.h"
+#include "otbVectorImage.h"
+#include "otbImageFileReader.h"
+#include "otbImageFileWriter.h"
+
+int otbNRIBandImagesToOneNComplexBandsImage(int itkNotUsed(argc), char * argv[])
+{
+
+ typedef double PixelType;
+ typedef otb::VectorImage<PixelType, 2> InputImageType;
+
+ typedef std::complex<double> OutputPixelType;
+ typedef otb::VectorImage<OutputPixelType, 2> OutputImageType;
+
+
+ typedef otb::NRIBandImagesToOneNComplexBandsImage<InputImageType, OutputImageType> FilterType;
+ typedef otb::ImageFileReader<InputImageType> ReaderType;
+ typedef otb::ImageFileWriter<OutputImageType> WriterType;
+
+ ReaderType::Pointer readerA = ReaderType::New();
+ ReaderType::Pointer readerB = ReaderType::New();
+ ReaderType::Pointer readerC = ReaderType::New();
+ FilterType::Pointer filter = FilterType::New();
+ WriterType::Pointer writer = WriterType::New();
+
+
+ readerA->SetFileName(argv[1]);
+ readerB->SetFileName(argv[2]);
+ readerC->SetFileName(argv[3]);
+ writer->SetFileName(argv[4]);
+
+ filter->SetInput(0,readerA->GetOutput());
+ filter->SetInput(1,readerB->GetOutput());
+ filter->SetInput(2,readerC->GetOutput());
+ writer->SetInput(filter->GetOutput());
+ writer->Update();
+
+
+
+ return EXIT_SUCCESS;
+}
diff --git a/Modules/Filtering/ImageManipulation/test/otbOneRIBandImageToOneComplexBandImage.cxx b/Modules/Filtering/ImageManipulation/test/otbOneRIBandImageToOneComplexBandImage.cxx
new file mode 100644
index 0000000000000000000000000000000000000000..bbc4682269f0f3b7ea6f3bc3243810dd80d3099f
--- /dev/null
+++ b/Modules/Filtering/ImageManipulation/test/otbOneRIBandImageToOneComplexBandImage.cxx
@@ -0,0 +1,56 @@
+/*=========================================================================
+
+ Program: ORFEO Toolbox
+ Language: C++
+ Date: $Date$
+ Version: $Revision$
+
+
+ Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
+ See OTBCopyright.txt for details.
+
+
+ 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 "itkMacro.h"
+
+#include "otbOneRIBandImageToOneComplexBandImage.h"
+
+#include "otbImage.h"
+#include "otbVectorImage.h"
+#include "otbImageFileReader.h"
+#include "otbImageFileWriter.h"
+
+int otbOneRIBandImageToOneComplexBandImage(int itkNotUsed(argc), char * argv[])
+{
+
+ typedef double PixelType;
+ typedef otb::VectorImage<PixelType, 2> InputImageType;
+
+ typedef std::complex<double> OutputPixelType;
+ typedef otb::Image<OutputPixelType, 2> OutputImageType;
+
+
+ typedef otb::OneRIBandImageToOneComplexBandImage<InputImageType, OutputImageType> FilterType;
+ typedef otb::ImageFileReader<InputImageType> ReaderType;
+ typedef otb::ImageFileWriter<OutputImageType> WriterType;
+
+ ReaderType::Pointer reader = ReaderType::New();
+ FilterType::Pointer filter = FilterType::New();
+ WriterType::Pointer writer = WriterType::New();
+
+
+ reader->SetFileName(argv[1]);
+ writer->SetFileName(argv[2]);
+
+ filter->SetInput(reader->GetOutput());
+ writer->SetInput(filter->GetOutput());
+ writer->Update();
+
+
+
+ return EXIT_SUCCESS;
+}
diff --git a/Modules/Filtering/ImageManipulation/test/otbTwoNRIBandsImageToNComplexBandsImage.cxx b/Modules/Filtering/ImageManipulation/test/otbTwoNRIBandsImageToNComplexBandsImage.cxx
new file mode 100644
index 0000000000000000000000000000000000000000..b4fed1963178ae79497fcdc18161b99261205dbc
--- /dev/null
+++ b/Modules/Filtering/ImageManipulation/test/otbTwoNRIBandsImageToNComplexBandsImage.cxx
@@ -0,0 +1,56 @@
+/*=========================================================================
+
+ Program: ORFEO Toolbox
+ Language: C++
+ Date: $Date$
+ Version: $Revision$
+
+
+ Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
+ See OTBCopyright.txt for details.
+
+
+ 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 "itkMacro.h"
+
+#include "otbTwoNRIBandsImageToNComplexBandsImage.h"
+
+#include "otbImage.h"
+#include "otbVectorImage.h"
+#include "otbImageFileReader.h"
+#include "otbImageFileWriter.h"
+
+int otbTwoNRIBandsImageToNComplexBandsImage(int itkNotUsed(argc), char * argv[])
+{
+
+ typedef double PixelType;
+ typedef otb::VectorImage<PixelType, 2> InputImageType;
+
+ typedef std::complex<double> OutputPixelType;
+ typedef otb::VectorImage<OutputPixelType, 2> OutputImageType;
+
+
+ typedef otb::TwoNRIBandsImageToNComplexBandsImage<InputImageType, OutputImageType> FilterType;
+ typedef otb::ImageFileReader<InputImageType> ReaderType;
+ typedef otb::ImageFileWriter<OutputImageType> WriterType;
+
+ ReaderType::Pointer reader = ReaderType::New();
+ FilterType::Pointer filter = FilterType::New();
+ WriterType::Pointer writer = WriterType::New();
+
+
+ reader->SetFileName(argv[1]);
+ writer->SetFileName(argv[2]);
+
+ filter->SetInput(0,reader->GetOutput());
+ writer->SetInput(filter->GetOutput());
+ writer->Update();
+
+
+
+ return EXIT_SUCCESS;
+}
diff --git a/Modules/Filtering/Polarimetry/include/otbReciprocalHAlphaImageFilter.h b/Modules/Filtering/Polarimetry/include/otbReciprocalHAlphaImageFilter.h
index 00ec3ff8106defb30c088b4e38e6000a9c0caf61..0967d1747196fa2632a926d3eedfe26692a92927 100644
--- a/Modules/Filtering/Polarimetry/include/otbReciprocalHAlphaImageFilter.h
+++ b/Modules/Filtering/Polarimetry/include/otbReciprocalHAlphaImageFilter.h
@@ -136,7 +136,8 @@ public:
if (p[k]<m_Epsilon) //n=log(n)-->0 when n-->0
plog[k]=0.0;
else
- plog[k]=-p[k]*log(p[k])/log(3);
+ plog[k]=-p[k]*log(p[k])/log(3.0);
+
}
entropy = 0.0;
diff --git a/Modules/Filtering/Polarimetry/include/otbSinclairToCircularCovarianceMatrixFunctor.h b/Modules/Filtering/Polarimetry/include/otbSinclairToCircularCovarianceMatrixFunctor.h
index c3d4f81404863d17f6b9bcd8ae54354d2b35d4eb..08e10da87a53b51cbd79ae565c598240911c4965 100644
--- a/Modules/Filtering/Polarimetry/include/otbSinclairToCircularCovarianceMatrixFunctor.h
+++ b/Modules/Filtering/Polarimetry/include/otbSinclairToCircularCovarianceMatrixFunctor.h
@@ -42,9 +42,9 @@ namespace Functor
* - channel #9 : \f$ S_{rr}.S_{rr}^{*} \f$
*
* With:
- * - \f$ S_{ll} = 0.5 * (-S_{hh}-i*S_{hv}-i*S_{vh}+S_{vv}) \f$
- * - \f$ S_{lr} = 0.5 * (-S_{hh}+i*S_{hv}-i*S_{vh}+S_{vv}) \f$
- * - \f$ S_{rl} = 0.5 * (-S_{hh}-i*S_{hv}+i*S_{vh}-S_{vv}) \f$
+ * - \f$ S_{ll} = 0.5 * (S_{hh}+i*S_{hv}+i*S_{vh}-S_{vv}) \f$
+ * - \f$ S_{lr} = 0.5 * (i*S_{hh}+S_{hv}-S_{vh}+i*S_{vv}) \f$
+ * - \f$ S_{rl} = 0.5 * (i*S_{hh}-S_{hv}+S_{vh}+i*S_{vv}) \f$
* - \f$ S_{rr} = 0.5 * (-S_{hh}+i*S_{hv}+i*S_{vh}+S_{vv}) \f$
*
* Extract from Antennas for radar and communications Harold Mott p 317.
@@ -89,12 +89,14 @@ public:
result.SetSize(m_NumberOfComponentsPerPixel);
const ComplexType jS_hv = S_hv * ComplexType(0., 1.);
const ComplexType jS_vh = S_vh * ComplexType(0., 1.);
-
+ const ComplexType jS_hh = S_hh * ComplexType(0., 1.);
+ const ComplexType jS_vv = S_vv * ComplexType(0., 1.);
+
const ComplexType coef(0.5);
- const ComplexType Sll = coef*( -S_hh-jS_hv-jS_vh+S_vv );
- const ComplexType Slr = coef*( -S_hh+jS_hv-jS_vh-S_vv );
- const ComplexType Srl = coef*( -S_hh-jS_hv+jS_vh-S_vv );
+ const ComplexType Sll = coef*( S_hh+jS_hv+jS_vh-S_vv );
+ const ComplexType Slr = coef*( jS_hh+S_hv-S_vh+jS_vv );
+ const ComplexType Srl = coef*( jS_hh-S_hv+S_vh+jS_vv );
const ComplexType Srr = coef*( -S_hh+jS_hv+jS_vh+S_vv );
//const ComplexType conjSll = vcl_conj(Sll);
diff --git a/Modules/Filtering/Polarimetry/test/otbSinclairToCircularCovarianceMatrixFunctor.cxx b/Modules/Filtering/Polarimetry/test/otbSinclairToCircularCovarianceMatrixFunctor.cxx
index c883bdef933ac1ec90774d660e887c80d54bf66a..030cc9b5d4fdcecd6a6bacd7530423a2cde0baed 100644
--- a/Modules/Filtering/Polarimetry/test/otbSinclairToCircularCovarianceMatrixFunctor.cxx
+++ b/Modules/Filtering/Polarimetry/test/otbSinclairToCircularCovarianceMatrixFunctor.cxx
@@ -31,14 +31,14 @@ int otbSinclairToCircularCovarianceMatrixFunctor(int itkNotUsed(argc), char * it
OutputType outputFunct;
result[0] = ComplexType( 32., 0. );
- result[1] = ComplexType( 0., 24. );
- result[2] = ComplexType( 0., 16.);
- result[3] = ComplexType( -8., 0 );
+ result[1] = ComplexType( 24., 0. );
+ result[2] = ComplexType( 16., 0.);
+ result[3] = ComplexType( 8., 0 );
result[4] = ComplexType( 18., 0. );
result[5] = ComplexType( 12. , 0. );
- result[6] = ComplexType( 0. , 6. );
+ result[6] = ComplexType( 6. , 0. );
result[7] = ComplexType( 8, 0. );
- result[8] = ComplexType( 0, 4. );
+ result[8] = ComplexType( 4., 0. );
result[9] = ComplexType( 2, 0. );
outputFunct = funct.operator ()( ComplexType(1., 4.), ComplexType(2., 3.), ComplexType(3., 2.), ComplexType(4., 1.) );
diff --git a/Modules/Filtering/Projection/include/otbGenericRSResampleImageFilter.txx b/Modules/Filtering/Projection/include/otbGenericRSResampleImageFilter.txx
index a18dabf09aa8fb846a47750566db9bc813af35b7..590688a4212bf79c15184c2c87b6b861fb5dce76 100644
--- a/Modules/Filtering/Projection/include/otbGenericRSResampleImageFilter.txx
+++ b/Modules/Filtering/Projection/include/otbGenericRSResampleImageFilter.txx
@@ -101,6 +101,15 @@ GenericRSResampleImageFilter<TInputImage, TOutputImage>
if (m_EstimateOutputRpcModel)
this->EstimateOutputRpcModel();
+ // Estimate the input rpc model if it is needed
+ if (m_EstimateInputRpcModel && !m_RpcEstimationUpdated)
+ {
+ this->EstimateInputRpcModel();
+ }
+
+ // Instanciate the RS transform
+ this->UpdateTransform();
+
m_Resampler->SetInput(this->GetInput());
m_Resampler->SetTransform(m_Transform);
m_Resampler->SetDisplacementFieldSpacing(this->GetDisplacementFieldSpacing());
@@ -177,15 +186,6 @@ GenericRSResampleImageFilter<TInputImage, TOutputImage>
{
if (this->m_Updating) return;
- // Estimate the input rpc model if it is needed
- if (m_EstimateInputRpcModel && !m_RpcEstimationUpdated)
- {
- this->EstimateInputRpcModel();
- }
-
- // Instanciate the RS transform
- this->UpdateTransform();
-
// Retrieve output requested region
m_Resampler->GetOutput()->SetRequestedRegion(output);
m_Resampler->GetOutput()->PropagateRequestedRegion();
diff --git a/Modules/Filtering/Projection/include/otbOrthoRectificationFilter.txx b/Modules/Filtering/Projection/include/otbOrthoRectificationFilter.txx
index d3e16f52d87338e2542f1223ae94434761ae8830..51bdfecb491266a1054ad32a3c8098aceab67cbd 100644
--- a/Modules/Filtering/Projection/include/otbOrthoRectificationFilter.txx
+++ b/Modules/Filtering/Projection/include/otbOrthoRectificationFilter.txx
@@ -67,6 +67,7 @@ OrthoRectificationFilter<TInputImage, TOutputImage, TMapProjection, TInterpolato
// Fill the GenericRSTransform with those information
this->SetOutputProjectionRef(projectionRef);
+ this->UpdateTransform();
}
}
diff --git a/Modules/Filtering/Projection/include/otbROIdataConversion.h b/Modules/Filtering/Projection/include/otbROIdataConversion.h
index 247f61cad56187e7c870c1ec009ca19abc0bcae0..541eddb93cfd3faa230885c507e29ad4ef1f490c 100644
--- a/Modules/Filtering/Projection/include/otbROIdataConversion.h
+++ b/Modules/Filtering/Projection/include/otbROIdataConversion.h
@@ -9,8 +9,6 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) GET / ENST Bretagne. All rights reserved.
- See GETCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Filtering/Projection/include/otbROIdataConversion.txx b/Modules/Filtering/Projection/include/otbROIdataConversion.txx
index 142bb6fe1b5af7e244c917f896fa4dcc7fe4ef04..b8513a07a84af131eefb692c87db89760c83542f 100644
--- a/Modules/Filtering/Projection/include/otbROIdataConversion.txx
+++ b/Modules/Filtering/Projection/include/otbROIdataConversion.txx
@@ -9,8 +9,6 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) GET / ENST Bretagne. All rights reserved.
- See GETCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Filtering/Wavelet/include/otbSubsampleImageFilter.h b/Modules/Filtering/Wavelet/include/otbSubsampleImageFilter.h
index 0e900decd7f2a71623a1c0842ad4e34b8535c397..92ac96137241a4c65253bfd74c2d6ee6e916b92c 100644
--- a/Modules/Filtering/Wavelet/include/otbSubsampleImageFilter.h
+++ b/Modules/Filtering/Wavelet/include/otbSubsampleImageFilter.h
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom / Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Filtering/Wavelet/include/otbSubsampleImageFilter.txx b/Modules/Filtering/Wavelet/include/otbSubsampleImageFilter.txx
index 2474aca2bcb8e27a38ff4e5d7d1a2dd18b7c8705..0375f3956aad96d52f20f24967927a424ea2ab8f 100644
--- a/Modules/Filtering/Wavelet/include/otbSubsampleImageFilter.txx
+++ b/Modules/Filtering/Wavelet/include/otbSubsampleImageFilter.txx
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom / Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Filtering/Wavelet/include/otbWaveletFilterBank.h b/Modules/Filtering/Wavelet/include/otbWaveletFilterBank.h
index 68b477bffde7552699753dba51bceb4bec214a4b..c219f717e9ae02e2ffbd2ec831b2c8c15c86e1bf 100644
--- a/Modules/Filtering/Wavelet/include/otbWaveletFilterBank.h
+++ b/Modules/Filtering/Wavelet/include/otbWaveletFilterBank.h
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom / Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Filtering/Wavelet/include/otbWaveletFilterBank.txx b/Modules/Filtering/Wavelet/include/otbWaveletFilterBank.txx
index 35ff142ec52b1761702a67f563999ffceb7ef077..21ba8cdf9f7ce65529c33adbe3b6c94a1ad29e85 100644
--- a/Modules/Filtering/Wavelet/include/otbWaveletFilterBank.txx
+++ b/Modules/Filtering/Wavelet/include/otbWaveletFilterBank.txx
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom / Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Filtering/Wavelet/include/otbWaveletGenerator.h b/Modules/Filtering/Wavelet/include/otbWaveletGenerator.h
index ae8a87bb2d336d4433c8b6241f4372390d7dddef..68be4ad16b6f185059b8b7ba14a3f061f9940de6 100644
--- a/Modules/Filtering/Wavelet/include/otbWaveletGenerator.h
+++ b/Modules/Filtering/Wavelet/include/otbWaveletGenerator.h
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom / Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Filtering/Wavelet/include/otbWaveletHighPassOperator.h b/Modules/Filtering/Wavelet/include/otbWaveletHighPassOperator.h
index 1f51a4d287c0f05f0d4f4685b4a08a05d3207a5b..f680eea930fbc073ae371036d74f83c6c21bb9d4 100644
--- a/Modules/Filtering/Wavelet/include/otbWaveletHighPassOperator.h
+++ b/Modules/Filtering/Wavelet/include/otbWaveletHighPassOperator.h
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom / Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Filtering/Wavelet/include/otbWaveletLowPassOperator.h b/Modules/Filtering/Wavelet/include/otbWaveletLowPassOperator.h
index 0742709e72d1b6d1dc942b7deb93bd8cc08533a5..2b612a2099f4c459f089be132c245c2a53466fc8 100644
--- a/Modules/Filtering/Wavelet/include/otbWaveletLowPassOperator.h
+++ b/Modules/Filtering/Wavelet/include/otbWaveletLowPassOperator.h
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom / Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Filtering/Wavelet/include/otbWaveletOperator.h b/Modules/Filtering/Wavelet/include/otbWaveletOperator.h
index c512f906827f3a6cd10d744d7e4019dea083b5a9..a6d9394d3ebfedf3d520f6e904f9510ca392693e 100644
--- a/Modules/Filtering/Wavelet/include/otbWaveletOperator.h
+++ b/Modules/Filtering/Wavelet/include/otbWaveletOperator.h
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom / Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Filtering/Wavelet/include/otbWaveletOperatorBase.h b/Modules/Filtering/Wavelet/include/otbWaveletOperatorBase.h
index c3598d325966ab10cb6887c1075f4472f41c93c3..d17c1dfd9be33fb83d151e7d70b87793ef8b5429 100644
--- a/Modules/Filtering/Wavelet/include/otbWaveletOperatorBase.h
+++ b/Modules/Filtering/Wavelet/include/otbWaveletOperatorBase.h
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom / Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Filtering/Wavelet/include/otbWaveletOperatorBase.txx b/Modules/Filtering/Wavelet/include/otbWaveletOperatorBase.txx
index 2270f2300c3d2eccd98573aa9abae05813798718..8b76a313d3f1b23fbf5970ade6a13c863e91c6ac 100644
--- a/Modules/Filtering/Wavelet/include/otbWaveletOperatorBase.txx
+++ b/Modules/Filtering/Wavelet/include/otbWaveletOperatorBase.txx
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom / Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Filtering/Wavelet/include/otbWaveletPacketDecompositionCosts.h b/Modules/Filtering/Wavelet/include/otbWaveletPacketDecompositionCosts.h
index c07570b9d45e5e3a3193b2d578aabae0e6ecd24e..e87374c43d274f0c3f5ce6777bfb48ceaa472e5f 100644
--- a/Modules/Filtering/Wavelet/include/otbWaveletPacketDecompositionCosts.h
+++ b/Modules/Filtering/Wavelet/include/otbWaveletPacketDecompositionCosts.h
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom / Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Filtering/Wavelet/include/otbWaveletPacketTransform.h b/Modules/Filtering/Wavelet/include/otbWaveletPacketTransform.h
index 76449b94c45ffa32173819f7611ad39e54b471e4..24e4028a5760b819520be49b8e857fb5749f83dd 100644
--- a/Modules/Filtering/Wavelet/include/otbWaveletPacketTransform.h
+++ b/Modules/Filtering/Wavelet/include/otbWaveletPacketTransform.h
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom / Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Filtering/Wavelet/include/otbWaveletPacketTransform.txx b/Modules/Filtering/Wavelet/include/otbWaveletPacketTransform.txx
index dea2820740652abfe27680390e7d041486844882..2d0e628e7261313511f99fee398179cb28bf8844 100644
--- a/Modules/Filtering/Wavelet/include/otbWaveletPacketTransform.txx
+++ b/Modules/Filtering/Wavelet/include/otbWaveletPacketTransform.txx
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom / Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Filtering/Wavelet/include/otbWaveletTransform.h b/Modules/Filtering/Wavelet/include/otbWaveletTransform.h
index 1c16dffe0b8efea7dc1926b7c4c85265b3e59e4c..c80ea8050986d413fceadc1f1e8091ef1480dd1b 100644
--- a/Modules/Filtering/Wavelet/include/otbWaveletTransform.h
+++ b/Modules/Filtering/Wavelet/include/otbWaveletTransform.h
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom / Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Filtering/Wavelet/include/otbWaveletTransform.txx b/Modules/Filtering/Wavelet/include/otbWaveletTransform.txx
index fcccb78421cad5365c80cdd76590c19cd82da81f..93eac94b95f2dfeeba0b94a6c25f0c04af34f475 100644
--- a/Modules/Filtering/Wavelet/include/otbWaveletTransform.txx
+++ b/Modules/Filtering/Wavelet/include/otbWaveletTransform.txx
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom / Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Filtering/Wavelet/src/otbWaveletGenerator.cxx b/Modules/Filtering/Wavelet/src/otbWaveletGenerator.cxx
index 04b4ee18244c3cfcff43bab20434d8319d4df319..9de9df6d6520844cf78db9a6a217897dcf8382e6 100644
--- a/Modules/Filtering/Wavelet/src/otbWaveletGenerator.cxx
+++ b/Modules/Filtering/Wavelet/src/otbWaveletGenerator.cxx
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom / Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Filtering/Wavelet/test/otbSubsampleImageFilter.cxx b/Modules/Filtering/Wavelet/test/otbSubsampleImageFilter.cxx
index a5f08b759b0697062a6d9265804d5fb4712ebc14..10721eedae3fe555851e5252746d3962a13306d6 100644
--- a/Modules/Filtering/Wavelet/test/otbSubsampleImageFilter.cxx
+++ b/Modules/Filtering/Wavelet/test/otbSubsampleImageFilter.cxx
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom / Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Filtering/Wavelet/test/otbSubsampleImageFilterNew.cxx b/Modules/Filtering/Wavelet/test/otbSubsampleImageFilterNew.cxx
index e3ccf387069f3c759f43dcf4d93be5d8e2cf7cae..538cdfed2470e975e65a0cfd8cb2e75eacead012 100644
--- a/Modules/Filtering/Wavelet/test/otbSubsampleImageFilterNew.cxx
+++ b/Modules/Filtering/Wavelet/test/otbSubsampleImageFilterNew.cxx
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom / Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Filtering/Wavelet/test/otbWaveletFilterBank.cxx b/Modules/Filtering/Wavelet/test/otbWaveletFilterBank.cxx
index b90dfbd642ad090ea0303db82811e3efae51d7fd..3878fb7620a0ad9441c922e0a5cded3c925ed6e2 100644
--- a/Modules/Filtering/Wavelet/test/otbWaveletFilterBank.cxx
+++ b/Modules/Filtering/Wavelet/test/otbWaveletFilterBank.cxx
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom / Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Filtering/Wavelet/test/otbWaveletInverseTransformNew.cxx b/Modules/Filtering/Wavelet/test/otbWaveletInverseTransformNew.cxx
index 34ecd1545e8550292b6df8fbc906a04604f996aa..ff27846f6da7852531236e5e37e654be4f0c716a 100644
--- a/Modules/Filtering/Wavelet/test/otbWaveletInverseTransformNew.cxx
+++ b/Modules/Filtering/Wavelet/test/otbWaveletInverseTransformNew.cxx
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom / Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Filtering/Wavelet/test/otbWaveletOperator.cxx b/Modules/Filtering/Wavelet/test/otbWaveletOperator.cxx
index 9b2baa47b05ec857e51de6705d641347a67417d9..a1c215042c39872b115fd6d4257ce1b6d73eedd9 100644
--- a/Modules/Filtering/Wavelet/test/otbWaveletOperator.cxx
+++ b/Modules/Filtering/Wavelet/test/otbWaveletOperator.cxx
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom / Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Filtering/Wavelet/test/otbWaveletOperatorNew.cxx b/Modules/Filtering/Wavelet/test/otbWaveletOperatorNew.cxx
index 866104bb4214c436a392595522ab908794f58c91..712a7a868fcdfc1f6447ab75581dc2b03cfc2002 100644
--- a/Modules/Filtering/Wavelet/test/otbWaveletOperatorNew.cxx
+++ b/Modules/Filtering/Wavelet/test/otbWaveletOperatorNew.cxx
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom / Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Filtering/Wavelet/test/otbWaveletPacketInverseTransformNew.cxx b/Modules/Filtering/Wavelet/test/otbWaveletPacketInverseTransformNew.cxx
index 8735db6bd7c2db507785c62c2ab1e439eb8c8867..b89cc7d40089dff2bcdc2ae8938646b891c56207 100644
--- a/Modules/Filtering/Wavelet/test/otbWaveletPacketInverseTransformNew.cxx
+++ b/Modules/Filtering/Wavelet/test/otbWaveletPacketInverseTransformNew.cxx
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom / Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Filtering/Wavelet/test/otbWaveletPacketTransform.cxx b/Modules/Filtering/Wavelet/test/otbWaveletPacketTransform.cxx
index 5726576a4f779aee308b800f1e3b8b8c774ac825..b7e6d00990606b2b3f9f7abe5d269b3254f8e64a 100644
--- a/Modules/Filtering/Wavelet/test/otbWaveletPacketTransform.cxx
+++ b/Modules/Filtering/Wavelet/test/otbWaveletPacketTransform.cxx
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom / Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Filtering/Wavelet/test/otbWaveletTransform.cxx b/Modules/Filtering/Wavelet/test/otbWaveletTransform.cxx
index 053f5fe52fb11401ee3bca5453484489013b7547..4774374c69fa364f6dbf96b6f76ba93b272f16cf 100644
--- a/Modules/Filtering/Wavelet/test/otbWaveletTransform.cxx
+++ b/Modules/Filtering/Wavelet/test/otbWaveletTransform.cxx
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom / Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/IO/ImageIO/include/otbImageSeriesFileReader.h b/Modules/IO/ImageIO/include/otbImageSeriesFileReader.h
index ada4080d51ca7e55d129ef5be21a42d1a0b0fb8f..75089a2e311d97b571d3344acb7c5b69b8d8ba1e 100644
--- a/Modules/IO/ImageIO/include/otbImageSeriesFileReader.h
+++ b/Modules/IO/ImageIO/include/otbImageSeriesFileReader.h
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom / Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/IO/ImageIO/include/otbImageSeriesFileReader.txx b/Modules/IO/ImageIO/include/otbImageSeriesFileReader.txx
index eaed4aa022564773cef8f2a29129985c93d4cd98..51ad2f02f9ced9ef74f23316fdf339806cd89b78 100644
--- a/Modules/IO/ImageIO/include/otbImageSeriesFileReader.txx
+++ b/Modules/IO/ImageIO/include/otbImageSeriesFileReader.txx
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom / Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/IO/ImageIO/include/otbImageSeriesFileReaderBase.h b/Modules/IO/ImageIO/include/otbImageSeriesFileReaderBase.h
index cb1aa3ae4afe7819a318f306b325df768490cb68..06ce1a68187096b4dd5a12c65551dc6f8f30f70b 100644
--- a/Modules/IO/ImageIO/include/otbImageSeriesFileReaderBase.h
+++ b/Modules/IO/ImageIO/include/otbImageSeriesFileReaderBase.h
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom / Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/IO/ImageIO/include/otbImageSeriesFileReaderBase.txx b/Modules/IO/ImageIO/include/otbImageSeriesFileReaderBase.txx
index 5d355b4d2940c0f9cb10b17cfe3bed46305f78f5..60ddc4d1c5d7986289de9e861a75fd0eab185093 100644
--- a/Modules/IO/ImageIO/include/otbImageSeriesFileReaderBase.txx
+++ b/Modules/IO/ImageIO/include/otbImageSeriesFileReaderBase.txx
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom / Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/IO/ImageIO/test/otbImageSeriesFileReader.cxx b/Modules/IO/ImageIO/test/otbImageSeriesFileReader.cxx
index 47bf8c64c53d0b81819e4c567cd317559dc7f799..aea4736ae9de996593ef4ce78c8c987e84cce103 100644
--- a/Modules/IO/ImageIO/test/otbImageSeriesFileReader.cxx
+++ b/Modules/IO/ImageIO/test/otbImageSeriesFileReader.cxx
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom / Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ Copyright (c) Institut Mines-Telecom. All rights reserved.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Learning/LearningBase/include/otbGaussianModelComponent.h b/Modules/Learning/LearningBase/include/otbGaussianModelComponent.h
index 6937b06d517f6d1e3642c6d6512ba33207442b85..ecc4cb26515708e2408e3d0948bf60c511f56d4b 100644
--- a/Modules/Learning/LearningBase/include/otbGaussianModelComponent.h
+++ b/Modules/Learning/LearningBase/include/otbGaussianModelComponent.h
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Some parts of this code are covered by the GET copyright.
- See GETCopyright.txt for details.
+ Some parts of this code are covered by the IMT copyright.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Learning/LearningBase/include/otbGaussianModelComponent.txx b/Modules/Learning/LearningBase/include/otbGaussianModelComponent.txx
index a1edbe7085a8429dcb27968a199a5aeafed54328..d420d84070ee859167619653435c97ff3c093c9c 100644
--- a/Modules/Learning/LearningBase/include/otbGaussianModelComponent.txx
+++ b/Modules/Learning/LearningBase/include/otbGaussianModelComponent.txx
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Some parts of this code are covered by the GET copyright.
- See GETCopyright.txt for details.
+ Some parts of this code are covered by the IMT copyright.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Learning/LearningBase/include/otbSEMClassifier.h b/Modules/Learning/LearningBase/include/otbSEMClassifier.h
index 6f7e5e76946750ca587dd819963166a0f51e26b6..e23db49440f1168fa424d2a7e8665b09c770aec7 100644
--- a/Modules/Learning/LearningBase/include/otbSEMClassifier.h
+++ b/Modules/Learning/LearningBase/include/otbSEMClassifier.h
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Some parts of this code are covered by the GET copyright.
- See GETCopyright.txt for details.
+ Some parts of this code are covered by the IMT copyright.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Learning/LearningBase/include/otbSEMClassifier.txx b/Modules/Learning/LearningBase/include/otbSEMClassifier.txx
index b4ef42b3e8423882433e97aa0c13ad60311989c5..9222684ae6399ff6e5c4c3440b045934b800dc0e 100644
--- a/Modules/Learning/LearningBase/include/otbSEMClassifier.txx
+++ b/Modules/Learning/LearningBase/include/otbSEMClassifier.txx
@@ -9,8 +9,8 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Some parts of this code are covered by the GET copyright.
- See GETCopyright.txt for details.
+ Some parts of this code are covered by the IMT copyright.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Learning/SOM/include/otbCzihoSOMLearningBehaviorFunctor.h b/Modules/Learning/SOM/include/otbCzihoSOMLearningBehaviorFunctor.h
index 7a68fa6476b91bcec72b558fbacd5ce993e590ea..19fdf31beb0bc714980a6edc086894887b3afd6c 100644
--- a/Modules/Learning/SOM/include/otbCzihoSOMLearningBehaviorFunctor.h
+++ b/Modules/Learning/SOM/include/otbCzihoSOMLearningBehaviorFunctor.h
@@ -10,7 +10,7 @@
See OTBCopyright.txt for details.
Copyright (c) Institut Telecom; Telecom bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Learning/SOM/include/otbCzihoSOMNeighborhoodBehaviorFunctor.h b/Modules/Learning/SOM/include/otbCzihoSOMNeighborhoodBehaviorFunctor.h
index a81df3e33962587b325e28fcc1ae3b5b0de7b3e4..a364d57dc905d8a07259df1891503966f5d0760f 100644
--- a/Modules/Learning/SOM/include/otbCzihoSOMNeighborhoodBehaviorFunctor.h
+++ b/Modules/Learning/SOM/include/otbCzihoSOMNeighborhoodBehaviorFunctor.h
@@ -10,7 +10,7 @@
See OTBCopyright.txt for details.
Copyright (c) Institut Telecom; Telecom bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Learning/SOM/include/otbPeriodicSOM.h b/Modules/Learning/SOM/include/otbPeriodicSOM.h
index 7bc01e4abba9524fabbddc3b6ab46993a3e004d2..835aeff7523fa33e2d75655f72be337d9cfe3143 100644
--- a/Modules/Learning/SOM/include/otbPeriodicSOM.h
+++ b/Modules/Learning/SOM/include/otbPeriodicSOM.h
@@ -10,7 +10,7 @@
See OTBCopyright.txt for details.
Copyright (c) Institut Telecom; Telecom bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Learning/SOM/include/otbPeriodicSOM.txx b/Modules/Learning/SOM/include/otbPeriodicSOM.txx
index 1618b77c550d3837d9b93a97cf0338d5f6be0bb0..352817bbd576b63b19a942cfb1b9d128137a7305 100644
--- a/Modules/Learning/SOM/include/otbPeriodicSOM.txx
+++ b/Modules/Learning/SOM/include/otbPeriodicSOM.txx
@@ -10,7 +10,7 @@
See OTBCopyright.txt for details.
Copyright (c) Institut Telecom; Telecom bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Learning/SOM/include/otbSOM.h b/Modules/Learning/SOM/include/otbSOM.h
index 7205dc75b77a478467cdb83f378fb9a986c10a2d..ff020cd4465b7f993dab49c1dd103fb5f95944de 100644
--- a/Modules/Learning/SOM/include/otbSOM.h
+++ b/Modules/Learning/SOM/include/otbSOM.h
@@ -10,7 +10,7 @@
See OTBCopyright.txt for details.
Copyright (c) Institut Telecom; Telecom bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Learning/SOM/include/otbSOM.txx b/Modules/Learning/SOM/include/otbSOM.txx
index f30b97c1d0d66619149bb13d9ae9b7c82333b5ac..cdc5066cfd1197122946331dd6bc69ee369c0a45 100644
--- a/Modules/Learning/SOM/include/otbSOM.txx
+++ b/Modules/Learning/SOM/include/otbSOM.txx
@@ -10,7 +10,7 @@
See OTBCopyright.txt for details.
Copyright (c) Institut Telecom; Telecom bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
diff --git a/Modules/Learning/SOM/include/otbSOMLearningBehaviorFunctor.h b/Modules/Learning/SOM/include/otbSOMLearningBehaviorFunctor.h
index 3db9aec74fbd8b55739c9a0f0af6891cf602bef6..4e38167100cdf4fca1e5a3ed7c441d99186a2698 100644
--- a/Modules/Learning/SOM/include/otbSOMLearningBehaviorFunctor.h
+++ b/Modules/Learning/SOM/include/otbSOMLearningBehaviorFunctor.h
@@ -10,7 +10,7 @@
See OTBCopyright.txt for details.
Copyright (c) Institut Telecom; Telecom bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Learning/SOM/include/otbSOMMap.h b/Modules/Learning/SOM/include/otbSOMMap.h
index 00276472de2b5328775d3f2f410ce88560a09572..9135f1c731a44dbed499458b7e3a3730444e75d3 100644
--- a/Modules/Learning/SOM/include/otbSOMMap.h
+++ b/Modules/Learning/SOM/include/otbSOMMap.h
@@ -10,7 +10,7 @@
See OTBCopyright.txt for details.
Copyright (c) Institut Telecom; Telecom Bretagne. All right reserved.
-See GETCopyright.txt for details.
+See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
diff --git a/Modules/Learning/SOM/include/otbSOMMap.txx b/Modules/Learning/SOM/include/otbSOMMap.txx
index 9f027e61dfb6954ca67728a23f8df3b5954d83d9..e36e4d6a66a045afd7ea6f04e1662572b840c9d2 100644
--- a/Modules/Learning/SOM/include/otbSOMMap.txx
+++ b/Modules/Learning/SOM/include/otbSOMMap.txx
@@ -10,7 +10,7 @@
See OTBCopyright.txt for details.
Copyright (c) Institut Telecom; Telecom Bretagne. All right reserved.
-See GETCopyright.txt for details.
+See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
diff --git a/Modules/Learning/SOM/include/otbSOMWithMissingValue.h b/Modules/Learning/SOM/include/otbSOMWithMissingValue.h
index 94219310f6d267a00b238c2f9a5774ca9adf7fa7..51aef377d0d4d00c8bd9cacb129177066e0a28b6 100644
--- a/Modules/Learning/SOM/include/otbSOMWithMissingValue.h
+++ b/Modules/Learning/SOM/include/otbSOMWithMissingValue.h
@@ -10,7 +10,7 @@
See OTBCopyright.txt for details.
Copyright (c) Institut Telecom; Telecom bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Learning/SOM/include/otbSOMWithMissingValue.txx b/Modules/Learning/SOM/include/otbSOMWithMissingValue.txx
index 0e62e477129589a5f23b97bdcc65fc1abbba3aef..fdb01dd57090beb4dbca8471925b5b014af2fb05 100644
--- a/Modules/Learning/SOM/include/otbSOMWithMissingValue.txx
+++ b/Modules/Learning/SOM/include/otbSOMWithMissingValue.txx
@@ -10,7 +10,7 @@
See OTBCopyright.txt for details.
Copyright (c) Institut Telecom; Telecom bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Learning/SOM/include/otbSOMbasedImageFilter.h b/Modules/Learning/SOM/include/otbSOMbasedImageFilter.h
index 47b1fb2bb5689192d242c8c5948827fc4ed7b7e0..5935f10ec167d5d27698a3592f8ecfeb415d302c 100644
--- a/Modules/Learning/SOM/include/otbSOMbasedImageFilter.h
+++ b/Modules/Learning/SOM/include/otbSOMbasedImageFilter.h
@@ -10,7 +10,7 @@
See OTBCopyright.txt for details.
Copyright (c) Institut Telecom; Telecom bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
diff --git a/Modules/Learning/SOM/include/otbSOMbasedImageFilter.txx b/Modules/Learning/SOM/include/otbSOMbasedImageFilter.txx
index a5f9b4639ca46236ec63a0e35a38c990eb476626..6e6e4f1a625514aefec8cdb02c4758f89982b936 100644
--- a/Modules/Learning/SOM/include/otbSOMbasedImageFilter.txx
+++ b/Modules/Learning/SOM/include/otbSOMbasedImageFilter.txx
@@ -10,7 +10,7 @@
See OTBCopyright.txt for details.
Copyright (c) Institut Telecom; Telecom bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
diff --git a/Modules/Learning/SOM/test/otbSOMWithMissingValueNew.cxx b/Modules/Learning/SOM/test/otbSOMWithMissingValueNew.cxx
index 75b8fab15896c21ac45617c1d97880bc77fe0a20..3720430043eca83820bc270b0f4fecb0798d3b83 100644
--- a/Modules/Learning/SOM/test/otbSOMWithMissingValueNew.cxx
+++ b/Modules/Learning/SOM/test/otbSOMWithMissingValueNew.cxx
@@ -10,7 +10,7 @@
See OTBCopyright.txt for details.
Copyright (c) Institut Telecom; Telecom bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
diff --git a/Modules/Learning/SOM/test/otbSOMbasedImageFilterNew.cxx b/Modules/Learning/SOM/test/otbSOMbasedImageFilterNew.cxx
index 8e8bbfc1fe48397ba4c0c07d6ca3268413d4327b..a47be5f4e438ca6b6ca69b0d8c8cf05280a73979 100644
--- a/Modules/Learning/SOM/test/otbSOMbasedImageFilterNew.cxx
+++ b/Modules/Learning/SOM/test/otbSOMbasedImageFilterNew.cxx
@@ -10,7 +10,7 @@
See OTBCopyright.txt for details.
Copyright (c) Institut Telecom; Telecom bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
diff --git a/Modules/Learning/SVMLearning/include/otbSVMImageClassificationWithRuleFilter.h b/Modules/Learning/SVMLearning/include/otbSVMImageClassificationWithRuleFilter.h
index 55c06dba46c3fee96df10cb48f18247017981abe..e66afd9c497e81ec7f2a8fd78a72a91c7062fe98 100644
--- a/Modules/Learning/SVMLearning/include/otbSVMImageClassificationWithRuleFilter.h
+++ b/Modules/Learning/SVMLearning/include/otbSVMImageClassificationWithRuleFilter.h
@@ -10,7 +10,7 @@
See OTBCopyright.txt for details.
Copyright (c) Institut Telecom; Telecom bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Learning/SVMLearning/include/otbSVMImageClassificationWithRuleFilter.txx b/Modules/Learning/SVMLearning/include/otbSVMImageClassificationWithRuleFilter.txx
index a10c5ad2f0e2b011ed9a15ce9282be9fc269dcde..cc7ad7f23fe526b3054fdf791783192cc1d412ce 100644
--- a/Modules/Learning/SVMLearning/include/otbSVMImageClassificationWithRuleFilter.txx
+++ b/Modules/Learning/SVMLearning/include/otbSVMImageClassificationWithRuleFilter.txx
@@ -10,7 +10,7 @@
See OTBCopyright.txt for details.
Copyright (c) Institut Telecom; Telecom bretagne. All rights reserved.
- See ITCopyright.txt for details.
+ See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Learning/Supervised/include/otbBoostMachineLearningModel.h b/Modules/Learning/Supervised/include/otbBoostMachineLearningModel.h
index 185d10ba44bf26db0a9444c5eb61025ef4f2899a..a812eca2b8f36708b19e186d7221a0a23cc07f4f 100644
--- a/Modules/Learning/Supervised/include/otbBoostMachineLearningModel.h
+++ b/Modules/Learning/Supervised/include/otbBoostMachineLearningModel.h
@@ -92,6 +92,11 @@ public:
itkGetMacro(MaxDepth, int);
itkSetMacro(MaxDepth, int);
+ /** Train the machine learning model */
+ virtual void Train();
+ /** Predict values using the model */
+ virtual TargetSampleType Predict(const InputSampleType& input, ConfidenceValueType *quality=NULL) const;
+
/** Save the model to file */
virtual void Save(const std::string & filename, const std::string & name="");
@@ -117,11 +122,6 @@ protected:
/** PrintSelf method */
void PrintSelf(std::ostream& os, itk::Indent indent) const;
- /** Train the machine learning model */
- virtual void TrainClassification();
- /** Predict values using the model */
- virtual TargetSampleType PredictClassification(const InputSampleType& input, ConfidenceValueType *quality=NULL) const;
-
private:
BoostMachineLearningModel(const Self &); //purposely not implemented
void operator =(const Self&); //purposely not implemented
diff --git a/Modules/Learning/Supervised/include/otbBoostMachineLearningModel.txx b/Modules/Learning/Supervised/include/otbBoostMachineLearningModel.txx
index 493107f9ff2b8da6c652fc67bc31376664eed1cc..15a9d5c293b8fa61a87b2f714aef15d0379a0686 100644
--- a/Modules/Learning/Supervised/include/otbBoostMachineLearningModel.txx
+++ b/Modules/Learning/Supervised/include/otbBoostMachineLearningModel.txx
@@ -52,7 +52,7 @@ BoostMachineLearningModel<TInputValue,TOutputValue>
template <class TInputValue, class TOutputValue>
void
BoostMachineLearningModel<TInputValue,TOutputValue>
-::TrainClassification()
+::Train()
{
//convert listsample to opencv matrix
cv::Mat samples;
@@ -77,7 +77,7 @@ template <class TInputValue, class TOutputValue>
typename BoostMachineLearningModel<TInputValue,TOutputValue>
::TargetSampleType
BoostMachineLearningModel<TInputValue,TOutputValue>
-::PredictClassification(const InputSampleType & input, ConfidenceValueType *quality) const
+::Predict(const InputSampleType & input, ConfidenceValueType *quality) const
{
//convert listsample to Mat
cv::Mat sample;
diff --git a/Modules/Learning/Supervised/include/otbDecisionTreeMachineLearningModel.h b/Modules/Learning/Supervised/include/otbDecisionTreeMachineLearningModel.h
index 6415fa940e273e5d9074a130ba95a8d8105a4978..651a48f6ee319e2c4171f15741df7e9615205c2d 100644
--- a/Modules/Learning/Supervised/include/otbDecisionTreeMachineLearningModel.h
+++ b/Modules/Learning/Supervised/include/otbDecisionTreeMachineLearningModel.h
@@ -147,11 +147,10 @@ public:
return m_Priors;
}
- /** Setters/Getters to IsRegression flag
- * Default is False
- */
- itkGetMacro(IsRegression, bool);
- itkSetMacro(IsRegression, bool);
+ /** Train the machine learning model */
+ virtual void Train();
+ /** Predict values using the model */
+ virtual TargetSampleType Predict(const InputSampleType& input, ConfidenceValueType *quality=NULL) const;
/** Save the model to file */
virtual void Save(const std::string & filename, const std::string & name="");
@@ -178,11 +177,6 @@ protected:
/** PrintSelf method */
void PrintSelf(std::ostream& os, itk::Indent indent) const;
- /** Train the machine learning model */
- virtual void TrainClassification();
- /** Predict values using the model */
- virtual TargetSampleType PredictClassification(const InputSampleType& input, ConfidenceValueType *quality=NULL) const;
-
private:
DecisionTreeMachineLearningModel(const Self &); //purposely not implemented
void operator =(const Self&); //purposely not implemented
@@ -196,7 +190,6 @@ private:
int m_MaxCategories;
int m_CVFolds;
bool m_Use1seRule;
- bool m_IsRegression;
bool m_TruncatePrunedTree;
std::vector<float> m_Priors;
diff --git a/Modules/Learning/Supervised/include/otbDecisionTreeMachineLearningModel.txx b/Modules/Learning/Supervised/include/otbDecisionTreeMachineLearningModel.txx
index ada456e94c35ff1467e97b8301a5e4a315fa35f6..283fb039c35fd04aea4cc2a63c580ee665014ab4 100644
--- a/Modules/Learning/Supervised/include/otbDecisionTreeMachineLearningModel.txx
+++ b/Modules/Learning/Supervised/include/otbDecisionTreeMachineLearningModel.txx
@@ -38,9 +38,9 @@ DecisionTreeMachineLearningModel<TInputValue,TOutputValue>
m_MaxCategories(10),
m_CVFolds(10),
m_Use1seRule(true),
- m_IsRegression(false),
m_TruncatePrunedTree(true)
{
+ this->m_IsRegressionSupported = true;
}
@@ -55,7 +55,7 @@ DecisionTreeMachineLearningModel<TInputValue,TOutputValue>
template <class TInputValue, class TOutputValue>
void
DecisionTreeMachineLearningModel<TInputValue,TOutputValue>
-::TrainClassification()
+::Train()
{
//convert listsample to opencv matrix
cv::Mat samples;
@@ -73,7 +73,7 @@ DecisionTreeMachineLearningModel<TInputValue,TOutputValue>
cv::Mat var_type = cv::Mat(this->GetInputListSample()->GetMeasurementVectorSize() + 1, 1, CV_8U );
var_type.setTo(cv::Scalar(CV_VAR_NUMERICAL) ); // all inputs are numerical
- if (!m_IsRegression) //Classification
+ if (!this->m_RegressionMode) //Classification
var_type.at<uchar>(this->GetInputListSample()->GetMeasurementVectorSize(), 0) = CV_VAR_CATEGORICAL;
m_DTreeModel->train(samples,CV_ROW_SAMPLE,labels,cv::Mat(),cv::Mat(),var_type,cv::Mat(),params);
@@ -83,7 +83,7 @@ template <class TInputValue, class TOutputValue>
typename DecisionTreeMachineLearningModel<TInputValue,TOutputValue>
::TargetSampleType
DecisionTreeMachineLearningModel<TInputValue,TOutputValue>
-::PredictClassification(const InputSampleType & input, ConfidenceValueType *quality) const
+::Predict(const InputSampleType & input, ConfidenceValueType *quality) const
{
//convert listsample to Mat
cv::Mat sample;
diff --git a/Modules/Learning/Supervised/include/otbGradientBoostedTreeMachineLearningModel.h b/Modules/Learning/Supervised/include/otbGradientBoostedTreeMachineLearningModel.h
index 3126f44c0ff7073def41f025df615e74013b590b..f10a89c68066f8ee6bbacc252b4088fa057157be 100644
--- a/Modules/Learning/Supervised/include/otbGradientBoostedTreeMachineLearningModel.h
+++ b/Modules/Learning/Supervised/include/otbGradientBoostedTreeMachineLearningModel.h
@@ -100,6 +100,11 @@ public:
itkGetMacro(UseSurrogates, bool);
itkSetMacro(UseSurrogates, bool);
+ /** Train the machine learning model */
+ virtual void Train();
+ /** Predict values using the model */
+ virtual TargetSampleType Predict(const InputSampleType& input, ConfidenceValueType *quality=NULL) const;
+
/** Save the model to file */
virtual void Save(const std::string & filename, const std::string & name="");
@@ -125,11 +130,6 @@ protected:
/** PrintSelf method */
void PrintSelf(std::ostream& os, itk::Indent indent) const;
- /** Train the machine learning model */
- virtual void TrainClassification();
- /** Predict values using the model */
- virtual TargetSampleType PredictClassification(const InputSampleType& input, ConfidenceValueType *quality=NULL) const;
-
private:
GradientBoostedTreeMachineLearningModel(const Self &); //purposely not implemented
void operator =(const Self&); //purposely not implemented
@@ -142,7 +142,6 @@ private:
double m_SubSamplePortion;
int m_MaxDepth;
bool m_UseSurrogates;
- bool m_IsRegression;
};
diff --git a/Modules/Learning/Supervised/include/otbGradientBoostedTreeMachineLearningModel.txx b/Modules/Learning/Supervised/include/otbGradientBoostedTreeMachineLearningModel.txx
index 595f1bb060b8ffbcb533352915f41b69c2bd1458..d08abec0290776a5d6a7ddfd3df27e6b5216d620 100644
--- a/Modules/Learning/Supervised/include/otbGradientBoostedTreeMachineLearningModel.txx
+++ b/Modules/Learning/Supervised/include/otbGradientBoostedTreeMachineLearningModel.txx
@@ -36,9 +36,9 @@ GradientBoostedTreeMachineLearningModel<TInputValue,TOutputValue>
m_Shrinkage(0.01),
m_SubSamplePortion(0.8),
m_MaxDepth(3),
- m_UseSurrogates(false),
- m_IsRegression(false)
+ m_UseSurrogates(false)
{
+ this->m_IsRegressionSupported = true;
}
@@ -53,7 +53,7 @@ GradientBoostedTreeMachineLearningModel<TInputValue,TOutputValue>
template <class TInputValue, class TOutputValue>
void
GradientBoostedTreeMachineLearningModel<TInputValue,TOutputValue>
-::TrainClassification()
+::Train()
{
//convert listsample to opencv matrix
cv::Mat samples;
@@ -62,7 +62,6 @@ GradientBoostedTreeMachineLearningModel<TInputValue,TOutputValue>
cv::Mat labels;
otb::ListSampleToMat<TargetListSampleType>(this->GetTargetListSample(),labels);
-
CvGBTreesParams params = CvGBTreesParams(m_LossFunctionType, m_WeakCount, m_Shrinkage, m_SubSamplePortion,
m_MaxDepth, m_UseSurrogates);
@@ -70,7 +69,7 @@ GradientBoostedTreeMachineLearningModel<TInputValue,TOutputValue>
cv::Mat var_type = cv::Mat(this->GetInputListSample()->GetMeasurementVectorSize() + 1, 1, CV_8U );
var_type.setTo(cv::Scalar(CV_VAR_NUMERICAL) ); // all inputs are numerical
- if (!m_IsRegression) //Classification
+ if (!this->m_RegressionMode) //Classification
var_type.at<uchar>(this->GetInputListSample()->GetMeasurementVectorSize(), 0) = CV_VAR_CATEGORICAL;
m_GBTreeModel->train(samples,CV_ROW_SAMPLE,labels,cv::Mat(),cv::Mat(),var_type,cv::Mat(),params, false);
@@ -80,7 +79,7 @@ template <class TInputValue, class TOutputValue>
typename GradientBoostedTreeMachineLearningModel<TInputValue,TOutputValue>
::TargetSampleType
GradientBoostedTreeMachineLearningModel<TInputValue,TOutputValue>
-::PredictClassification(const InputSampleType & input, ConfidenceValueType *quality) const
+::Predict(const InputSampleType & input, ConfidenceValueType *quality) const
{
//convert listsample to Mat
cv::Mat sample;
diff --git a/Modules/Learning/Supervised/include/otbImageClassificationFilter.txx b/Modules/Learning/Supervised/include/otbImageClassificationFilter.txx
index 88d2ad012441455cc2c2d221e79e175731b3e31f..b0a5d5e3e842ec986dfc2400736b84e2a405bb53 100644
--- a/Modules/Learning/Supervised/include/otbImageClassificationFilter.txx
+++ b/Modules/Learning/Supervised/include/otbImageClassificationFilter.txx
@@ -118,7 +118,7 @@ ImageClassificationFilter<TInputImage, TOutputImage, TMaskImage>
}
// setup iterator for confidence map
- bool computeConfidenceMap(m_UseConfidenceMap && m_Model->HasConfidenceIndex());
+ bool computeConfidenceMap(m_UseConfidenceMap && m_Model->HasConfidenceIndex() && !m_Model->GetRegressionMode());
ConfidenceMapIteratorType confidenceIt;
if (computeConfidenceMap)
{
diff --git a/Modules/Learning/Supervised/include/otbKNearestNeighborsMachineLearningModel.h b/Modules/Learning/Supervised/include/otbKNearestNeighborsMachineLearningModel.h
index b8524b7fb677aff35b706a54b87b6a917251754b..3f29a10af3ed6b46d700684eddeab80a5076c17a 100644
--- a/Modules/Learning/Supervised/include/otbKNearestNeighborsMachineLearningModel.h
+++ b/Modules/Learning/Supervised/include/otbKNearestNeighborsMachineLearningModel.h
@@ -58,12 +58,23 @@ public:
itkGetMacro(K, int);
itkSetMacro(K, int);
- /** Setters/Getters to IsRegression flag
- * Default is False
- * \see http://docs.opencv.org/modules/ml/doc/k_nearest_neighbors.html
+ /** Decision rule once the KNN are found :
+ * [for classification]
+ * - KNN_VOTING : output value with maximum occurences (for classification)
+ * [for regression]
+ * - KNN_MEAN : output mean value of neighbors
+ * - KNN_MEDIAN : output median value of neighbors
*/
- itkGetMacro(IsRegression, bool);
- itkSetMacro(IsRegression, bool);
+ enum {KNN_VOTING, KNN_MEAN, KNN_MEDIAN};
+
+ /** Setters/Getters to the decision rule */
+ itkGetMacro(DecisionRule, int);
+ itkSetMacro(DecisionRule, int);
+
+ /** Train the machine learning model */
+ virtual void Train();
+ /** Predict values using the model */
+ virtual TargetSampleType Predict(const InputSampleType& input, ConfidenceValueType *quality=NULL) const;
/** Save the model to file */
virtual void Save(const std::string & filename, const std::string & name="");
@@ -90,18 +101,14 @@ protected:
/** PrintSelf method */
void PrintSelf(std::ostream& os, itk::Indent indent) const;
- /** Train the machine learning model */
- virtual void TrainClassification();
- /** Predict values using the model */
- virtual TargetSampleType PredictClassification(const InputSampleType& input, ConfidenceValueType *quality=NULL) const;
-
private:
KNearestNeighborsMachineLearningModel(const Self &); //purposely not implemented
void operator =(const Self&); //purposely not implemented
CvKNearest * m_KNearestModel;
int m_K;
- bool m_IsRegression;
+
+ int m_DecisionRule;
};
} // end namespace otb
diff --git a/Modules/Learning/Supervised/include/otbKNearestNeighborsMachineLearningModel.txx b/Modules/Learning/Supervised/include/otbKNearestNeighborsMachineLearningModel.txx
index e890b9137ac284848eda3c10885bfd736a4c28ac..fd33b7c9061fc3ce66c70cf9ea5c4c7780c42dc8 100644
--- a/Modules/Learning/Supervised/include/otbKNearestNeighborsMachineLearningModel.txx
+++ b/Modules/Learning/Supervised/include/otbKNearestNeighborsMachineLearningModel.txx
@@ -23,6 +23,7 @@
#include "otbOpenCVUtils.h"
#include <fstream>
+#include <set>
#include "itkMacro.h"
namespace otb
@@ -33,9 +34,10 @@ KNearestNeighborsMachineLearningModel<TInputValue,TTargetValue>
::KNearestNeighborsMachineLearningModel() :
m_KNearestModel (new CvKNearest),
m_K(32),
- m_IsRegression(false)
+ m_DecisionRule(KNN_VOTING)
{
this->m_ConfidenceIndex = true;
+ this->m_IsRegressionSupported = true;
}
@@ -50,7 +52,7 @@ KNearestNeighborsMachineLearningModel<TInputValue,TTargetValue>
template <class TInputValue, class TTargetValue>
void
KNearestNeighborsMachineLearningModel<TInputValue,TTargetValue>
-::TrainClassification()
+::Train()
{
//convert listsample to opencv matrix
cv::Mat samples;
@@ -59,26 +61,44 @@ KNearestNeighborsMachineLearningModel<TInputValue,TTargetValue>
cv::Mat labels;
otb::ListSampleToMat<TargetListSampleType>(this->GetTargetListSample(), labels);
+ // update decision rule if needed
+ if (this->m_RegressionMode)
+ {
+ if (this->m_DecisionRule == KNN_VOTING)
+ {
+ this->SetDecisionRule(KNN_MEAN);
+ }
+ }
+ else
+ {
+ if (this->m_DecisionRule != KNN_VOTING)
+ {
+ this->SetDecisionRule(KNN_VOTING);
+ }
+ }
+
//train the KNN model
- m_KNearestModel->train(samples, labels, cv::Mat(), m_IsRegression, m_K, false);
+ m_KNearestModel->train(samples, labels, cv::Mat(), this->m_RegressionMode, m_K, false);
}
template <class TInputValue, class TTargetValue>
typename KNearestNeighborsMachineLearningModel<TInputValue,TTargetValue>
::TargetSampleType
KNearestNeighborsMachineLearningModel<TInputValue,TTargetValue>
-::PredictClassification(const InputSampleType & input, ConfidenceValueType *quality) const
+::Predict(const InputSampleType & input, ConfidenceValueType *quality) const
{
//convert listsample to Mat
cv::Mat sample;
otb::SampleToMat<InputSampleType>(input, sample);
float result;
+ cv::Mat nearest(1,m_K,CV_32FC1);
+ result = m_KNearestModel->find_nearest(sample, m_K,0,0,&nearest,0);
+ // compute quality if asked (only happens in classification mode)
if (quality != NULL)
{
- cv::Mat nearest(1,m_K,CV_32FC1);
- result = m_KNearestModel->find_nearest(sample, m_K,0,0,&nearest,0);
+ assert(!this->m_RegressionMode);
unsigned int accuracy = 0;
for (int k=0 ; k < m_K ; ++k)
{
@@ -89,9 +109,22 @@ KNearestNeighborsMachineLearningModel<TInputValue,TTargetValue>
}
(*quality) = static_cast<ConfidenceValueType>(accuracy);
}
- else
+
+ // Decision rule :
+ // VOTING is OpenCV default behaviour for classification
+ // MEAN is OpenCV default behaviour for regression
+ // MEDIAN : only case that must be handled here
+ if (this->m_DecisionRule == KNN_MEDIAN)
{
- result = m_KNearestModel->find_nearest(sample, m_K);
+ std::multiset<float> values;
+ for (int k=0 ; k < m_K ; ++k)
+ {
+ values.insert(nearest.at<float>(0,k));
+ }
+ std::multiset<float>::iterator median = values.begin();
+ int pos = (m_K >> 1);
+ for (int k=0 ; k < pos ; ++k , ++median) {}
+ result = *median;
}
TargetSampleType target;
@@ -106,12 +139,17 @@ KNearestNeighborsMachineLearningModel<TInputValue,TTargetValue>
::Save(const std::string & filename, const std::string & itkNotUsed(name))
{
//there is no m_KNearestModel->save(filename.c_str(), name.c_str()).
- //We need to save the K parameter and IsRegression flag used and the samples.
+ //We need to save the K parameter, IsRegression flag, DecisionRule and the samples.
std::ofstream ofs(filename.c_str());
//Save K parameter and IsRegression flag.
ofs << "K=" << m_K << "\n";
- ofs << "IsRegression=" << m_IsRegression << "\n";
+ ofs << "IsRegression=" << this->m_RegressionMode << "\n";
+ // Save the DecisionRule if regression
+ if (this->m_RegressionMode)
+ {
+ ofs << "DecisionRule=" << m_DecisionRule << "\n";
+ }
//Save the samples. First column is the Label and other columns are the sample data.
typename InputListSampleType::ConstIterator sampleIt = this->GetInputListSample()->Begin();
@@ -154,8 +192,15 @@ KNearestNeighborsMachineLearningModel<TInputValue,TTargetValue>
std::getline(ifs, line);
pos = line.find_first_of("=", 0);
nextpos = line.find_first_of(" \n\r", pos+1);
- this->SetIsRegression(boost::lexical_cast<bool>(line.substr(pos+1, nextpos-pos-1)));
-
+ this->SetRegressionMode(boost::lexical_cast<bool>(line.substr(pos+1, nextpos-pos-1)));
+ //third line is the DecisionRule parameter (only for regression)
+ if (this->m_RegressionMode)
+ {
+ std::getline(ifs, line);
+ pos = line.find_first_of("=", 0);
+ nextpos = line.find_first_of(" \n\r", pos+1);
+ this->SetDecisionRule(boost::lexical_cast<int>(line.substr(pos+1, nextpos-pos-1)));
+ }
//Clear previous listSample (if any)
typename InputListSampleType::Pointer samples = InputListSampleType::New();
typename TargetListSampleType::Pointer labels = TargetListSampleType::New();
diff --git a/Modules/Learning/Supervised/include/otbLibSVMMachineLearningModel.h b/Modules/Learning/Supervised/include/otbLibSVMMachineLearningModel.h
index 18eba7fbb28d336967ac669d05cda51bc5ebdc4c..622923753e37d1216de669a9724c72b979015f83 100644
--- a/Modules/Learning/Supervised/include/otbLibSVMMachineLearningModel.h
+++ b/Modules/Learning/Supervised/include/otbLibSVMMachineLearningModel.h
@@ -59,6 +59,11 @@ public:
itkNewMacro(Self);
itkTypeMacro(SVMMachineLearningModel, MachineLearningModel);
+ /** Train the machine learning model */
+ virtual void Train();
+ /** Predict values using the model */
+ virtual TargetSampleType Predict(const InputSampleType& input, ConfidenceValueType *quality=NULL) const;
+
/** Save the model to file */
virtual void Save(const std::string &filename, const std::string & name="");
@@ -75,23 +80,40 @@ public:
//@}
//Setters/Getters to SVM model
- // itkGetMacro(SVMType, int);
- // itkSetMacro(SVMType, int);
+ otbGetObjectMemberMacro(SVMestimator, SVMType, int);
+ otbSetObjectMemberMacro(SVMestimator, SVMType, int);
+
+ otbGetObjectMemberMacro(SVMestimator, KernelType, int);
+ otbSetObjectMemberMacro(SVMestimator, KernelType, int);
+
+ otbGetObjectMemberMacro(SVMestimator, C, double);
+ otbSetObjectMemberMacro(SVMestimator, C, double);
- itkGetMacro(KernelType, int);
- itkSetMacro(KernelType, int);
+ // TODO : we should harmonize this parameter name : ParameterOptimization -> ParametersOptimization
+ bool GetParameterOptimization()
+ {
+ return this->m_SVMestimator->GetParametersOptimization();
+ }
+ void SetParameterOptimization(bool value)
+ {
+ this->m_SVMestimator->SetParametersOptimization(value);
+ this->Modified();
+ }
- itkGetMacro(C, float);
- itkSetMacro(C, float);
+ otbGetObjectMemberMacro(SVMestimator, DoProbabilityEstimates, bool);
+ void SetDoProbabilityEstimates(bool value)
+ {
+ this->m_SVMestimator->DoProbabilityEstimates(value);
+ }
- itkGetMacro(ParameterOptimization, bool);
- itkSetMacro(ParameterOptimization, bool);
-
- itkGetMacro(DoProbabilityEstimates, bool);
- itkSetMacro(DoProbabilityEstimates, bool);
+ otbGetObjectMemberMacro(SVMestimator, Epsilon, double);
+ otbSetObjectMemberMacro(SVMestimator, Epsilon, double);
- // itkGetMacro(Epsilon, int);
- // itkSetMacro(Epsilon, int);
+ otbGetObjectMemberMacro(SVMestimator, P, double);
+ otbSetObjectMemberMacro(SVMestimator, P, double);
+
+ otbGetObjectMemberMacro(SVMestimator, Nu, double);
+ otbSetObjectMemberMacro(SVMestimator, Nu, double);
protected:
/** Constructor */
@@ -103,19 +125,10 @@ protected:
/** PrintSelf method */
void PrintSelf(std::ostream& os, itk::Indent indent) const;
- /** Train the machine learning model */
- virtual void TrainClassification();
- /** Predict values using the model */
- virtual TargetSampleType PredictClassification(const InputSampleType& input, ConfidenceValueType *quality=NULL) const;
-
private:
LibSVMMachineLearningModel(const Self &); //purposely not implemented
void operator =(const Self&); //purposely not implemented
- int m_KernelType;
- float m_C;
- bool m_ParameterOptimization;
- bool m_DoProbabilityEstimates;
typename SVMEstimatorType::Pointer m_SVMestimator;
};
} // end namespace otb
diff --git a/Modules/Learning/Supervised/include/otbLibSVMMachineLearningModel.txx b/Modules/Learning/Supervised/include/otbLibSVMMachineLearningModel.txx
index 24e91e54a25406d100a8cae8f4b09741f124e80f..e95e97543d3a67537c848c8933165d5907370400 100644
--- a/Modules/Learning/Supervised/include/otbLibSVMMachineLearningModel.txx
+++ b/Modules/Learning/Supervised/include/otbLibSVMMachineLearningModel.txx
@@ -20,10 +20,6 @@
#include <fstream>
#include "otbLibSVMMachineLearningModel.h"
-//#include "otbOpenCVUtils.h"
-
-// SVM estimator
-//#include "otbSVMSampleListModelEstimator.h"
namespace otb
{
@@ -32,15 +28,14 @@ template <class TInputValue, class TOutputValue>
LibSVMMachineLearningModel<TInputValue,TOutputValue>
::LibSVMMachineLearningModel()
{
- // m_SVMModel = new CvSVM;
- // m_SVMType = CvSVM::C_SVC;
- m_KernelType = LINEAR;
- // m_TermCriteriaType = CV_TERMCRIT_ITER;
- m_C = 1.0;
- // m_Epsilon = 1e-6;
- m_ParameterOptimization = false;
- m_DoProbabilityEstimates = false;
m_SVMestimator = SVMEstimatorType::New();
+ m_SVMestimator->SetSVMType(C_SVC);
+ m_SVMestimator->SetC(1.0);
+ m_SVMestimator->SetKernelType(LINEAR);
+ m_SVMestimator->SetParametersOptimization(false);
+ m_SVMestimator->DoProbabilityEstimates(false);
+ //m_SVMestimator->SetEpsilon(1e-6);
+ this->m_IsRegressionSupported = true;
}
@@ -55,7 +50,7 @@ LibSVMMachineLearningModel<TInputValue,TOutputValue>
template <class TInputValue, class TOutputValue>
void
LibSVMMachineLearningModel<TInputValue,TOutputValue>
-::TrainClassification()
+::Train()
{
// Set up SVM's parameters
// CvSVMParams params;
@@ -64,25 +59,19 @@ LibSVMMachineLearningModel<TInputValue,TOutputValue>
// params.term_crit = cvTermCriteria(m_TermCriteriaType, m_MaxIter, m_Epsilon);
// // Train the SVM
-
- m_SVMestimator->SetC(m_C);
- m_SVMestimator->SetKernelType(m_KernelType);
- m_SVMestimator->SetParametersOptimization(m_ParameterOptimization);
- m_SVMestimator->DoProbabilityEstimates(m_DoProbabilityEstimates);
-
m_SVMestimator->SetInputSampleList(this->GetInputListSample());
m_SVMestimator->SetTrainingSampleList(this->GetTargetListSample());
m_SVMestimator->Update();
- this->m_ConfidenceIndex = m_DoProbabilityEstimates;
+ this->m_ConfidenceIndex = this->GetDoProbabilityEstimates();
}
template <class TInputValue, class TOutputValue>
typename LibSVMMachineLearningModel<TInputValue,TOutputValue>
::TargetSampleType
LibSVMMachineLearningModel<TInputValue,TOutputValue>
-::PredictClassification(const InputSampleType & input, ConfidenceValueType *quality) const
+::Predict(const InputSampleType & input, ConfidenceValueType *quality) const
{
TargetSampleType target;
diff --git a/Modules/Learning/Supervised/include/otbMachineLearningModel.h b/Modules/Learning/Supervised/include/otbMachineLearningModel.h
index ba0ca60d224fa138fe5a9e8e702993555394559b..b18e39e15c89fabff9ff2c640122740e710972f5 100644
--- a/Modules/Learning/Supervised/include/otbMachineLearningModel.h
+++ b/Modules/Learning/Supervised/include/otbMachineLearningModel.h
@@ -97,10 +97,10 @@ public:
//@}
/** Train the machine learning model */
- void Train();
+ virtual void Train() =0;
/** Predict values using the model */
- TargetSampleType Predict(const InputSampleType& input, ConfidenceValueType *quality = NULL) const;
+ virtual TargetSampleType Predict(const InputSampleType& input, ConfidenceValueType *quality = NULL) const = 0;
/** Classify all samples in InputListSample and fill TargetListSample with the associated label */
void PredictAll();
@@ -140,6 +140,12 @@ public:
itkGetObjectMacro(TargetListSample,TargetListSampleType);
//@}
+ /**\name Use model in regression mode */
+ //@{
+ itkGetMacro(RegressionMode,bool);
+ void SetRegressionMode(bool flag);
+ //@}
+
protected:
/** Constructor */
MachineLearningModel();
@@ -156,22 +162,14 @@ protected:
/** Target list sample */
typename TargetListSampleType::Pointer m_TargetListSample;
- /** Train the machine learning model */
- virtual void TrainRegression()
- {
- itkGenericExceptionMacro(<< "Regression mode not implemented.");
- }
- virtual void TrainClassification() = 0;
- /** Predict values using the model */
- virtual TargetSampleType PredictRegression(const InputSampleType& itkNotUsed(input)) const
- {
- itkGenericExceptionMacro(<< "Regression mode not implemented.");
- }
-
- virtual TargetSampleType PredictClassification(const InputSampleType& input, ConfidenceValueType *quality = NULL) const = 0;
-
+ /** flag to choose between classification and regression modes */
bool m_RegressionMode;
+ /** flag that indicates if the model supports regression, child
+ * classes should modify it in their constructor if they support
+ * regression mode */
+ bool m_IsRegressionSupported;
+
/** flag that tells if the model support confidence index output */
bool m_ConfidenceIndex;
private:
diff --git a/Modules/Learning/Supervised/include/otbMachineLearningModel.txx b/Modules/Learning/Supervised/include/otbMachineLearningModel.txx
index b4b6127c11c252c3d5a73d0a50716d48da6e7a49..8cc82055fe1a7a08594a01f3d9aeba6dfc12d927 100644
--- a/Modules/Learning/Supervised/include/otbMachineLearningModel.txx
+++ b/Modules/Learning/Supervised/include/otbMachineLearningModel.txx
@@ -25,7 +25,10 @@ namespace otb
template <class TInputValue, class TOutputValue, class TConfidenceValue>
MachineLearningModel<TInputValue,TOutputValue,TConfidenceValue>
-::MachineLearningModel() : m_RegressionMode(false),m_ConfidenceIndex(false)
+::MachineLearningModel() :
+ m_RegressionMode(false),
+ m_IsRegressionSupported(false),
+ m_ConfidenceIndex(false)
{}
@@ -37,23 +40,17 @@ MachineLearningModel<TInputValue,TOutputValue,TConfidenceValue>
template <class TInputValue, class TOutputValue, class TConfidenceValue>
void
MachineLearningModel<TInputValue,TOutputValue,TConfidenceValue>
-::Train()
+::SetRegressionMode(bool flag)
{
- if(m_RegressionMode)
- return this->TrainRegression();
- else
- return this->TrainClassification();
-}
-
-template <class TInputValue, class TOutputValue, class TConfidenceValue>
-typename MachineLearningModel<TInputValue,TOutputValue,TConfidenceValue>::TargetSampleType
-MachineLearningModel<TInputValue,TOutputValue,TConfidenceValue>
-::Predict(const InputSampleType& input, ConfidenceValueType *quality) const
-{
- if(m_RegressionMode)
- return this->PredictRegression(input);
- else
- return this->PredictClassification(input,quality);
+ if (flag && !m_IsRegressionSupported)
+ {
+ itkGenericExceptionMacro(<< "Regression mode not implemented.");
+ }
+ if (m_RegressionMode != flag)
+ {
+ m_RegressionMode = flag;
+ this->Modified();
+ }
}
template <class TInputValue, class TOutputValue, class TConfidenceValue>
diff --git a/Modules/Learning/Supervised/include/otbNeuralNetworkMachineLearningModel.h b/Modules/Learning/Supervised/include/otbNeuralNetworkMachineLearningModel.h
index 2eab72042d9ff5b3228df2d628ee0618127b01f4..fa1abade18cce80abb493406fabbcebbe97c9ddc 100644
--- a/Modules/Learning/Supervised/include/otbNeuralNetworkMachineLearningModel.h
+++ b/Modules/Learning/Supervised/include/otbNeuralNetworkMachineLearningModel.h
@@ -151,6 +151,11 @@ public:
itkGetMacro(Epsilon, double);
itkSetMacro(Epsilon, double);
+ /** Train the machine learning model */
+ virtual void Train();
+ /** Predict values using the model */
+ virtual TargetSampleType Predict(const InputSampleType& input, ConfidenceValueType *quality=NULL) const;
+
/** Save the model to file */
virtual void Save(const std::string & filename, const std::string & name="");
@@ -178,15 +183,14 @@ protected:
/** PrintSelf method */
void PrintSelf(std::ostream& os, itk::Indent indent) const;
- /** Train the machine learning model */
- virtual void TrainClassification();
- /** Predict values using the model */
- virtual TargetSampleType PredictClassification(const InputSampleType& input, ConfidenceValueType *quality=NULL) const;
-
private:
NeuralNetworkMachineLearningModel(const Self &); //purposely not implemented
void operator =(const Self&); //purposely not implemented
+ void CreateNetwork();
+ CvANN_MLP_TrainParams SetNetworkParameters();
+ void SetupNetworkAndTrain(cv::Mat& labels);
+
CvANN_MLP * m_ANNModel;
int m_TrainMethod;
int m_ActivateFunction;
diff --git a/Modules/Learning/Supervised/include/otbNeuralNetworkMachineLearningModel.txx b/Modules/Learning/Supervised/include/otbNeuralNetworkMachineLearningModel.txx
index 01c31811d7c793630dfcfe5f0026cc6b7be73356..b76e6dd70d3f57741ac83ef9ce448362d9e942fc 100644
--- a/Modules/Learning/Supervised/include/otbNeuralNetworkMachineLearningModel.txx
+++ b/Modules/Learning/Supervised/include/otbNeuralNetworkMachineLearningModel.txx
@@ -43,6 +43,7 @@ NeuralNetworkMachineLearningModel<TInputValue, TOutputValue>::NeuralNetworkMachi
m_CvMatOfLabels(0)
{
this->m_ConfidenceIndex = true;
+ this->m_IsRegressionSupported = true;
}
template<class TInputValue, class TOutputValue>
@@ -52,7 +53,7 @@ NeuralNetworkMachineLearningModel<TInputValue, TOutputValue>::~NeuralNetworkMach
cvReleaseMat(&m_CvMatOfLabels);
}
-/** Train the machine learning model */
+/** Sets the topology of the NN */
template<class TInputValue, class TOutputValue>
void NeuralNetworkMachineLearningModel<TInputValue, TOutputValue>::SetLayerSizes(const std::vector<unsigned int> layers)
{
@@ -72,10 +73,14 @@ template<class TInputValue, class TOutputValue>
void NeuralNetworkMachineLearningModel<TInputValue, TOutputValue>::LabelsToMat(const TargetListSampleType * labels,
cv::Mat & output)
{
- unsigned int nbSamples = labels->Size();
+ unsigned int nbSamples = 0;
+ if (labels != NULL)
+ {
+ nbSamples = labels->Size();
+ }
// Check for valid listSample
- if (labels != NULL && nbSamples > 0)
+ if (nbSamples > 0)
{
// Build an iterator
typename TargetListSampleType::ConstIterator labelSampleIt = labels->Begin();
@@ -130,9 +135,8 @@ void NeuralNetworkMachineLearningModel<TInputValue, TOutputValue>::LabelsToMat(c
}
}
-/** Train the machine learning model */
template<class TInputValue, class TOutputValue>
-void NeuralNetworkMachineLearningModel<TInputValue, TOutputValue>::TrainClassification()
+void NeuralNetworkMachineLearningModel<TInputValue, TOutputValue>::CreateNetwork()
{
//Create the neural network
const unsigned int nbLayers = m_LayerSizes.size();
@@ -147,14 +151,11 @@ void NeuralNetworkMachineLearningModel<TInputValue, TOutputValue>::TrainClassifi
}
m_ANNModel->create(layers, m_ActivateFunction, m_Alpha, m_Beta);
+}
- //convert listsample to opencv matrix
- cv::Mat samples;
- otb::ListSampleToMat<InputListSampleType>(this->GetInputListSample(), samples);
-
- cv::Mat matOutputANN;
- LabelsToMat(this->GetTargetListSample(), matOutputANN);
-
+template<class TInputValue, class TOutputValue>
+CvANN_MLP_TrainParams NeuralNetworkMachineLearningModel<TInputValue, TOutputValue>::SetNetworkParameters()
+{
CvANN_MLP_TrainParams params;
params.train_method = m_TrainMethod;
params.bp_dw_scale = m_BackPropDWScale;
@@ -163,14 +164,43 @@ void NeuralNetworkMachineLearningModel<TInputValue, TOutputValue>::TrainClassifi
params.rp_dw_min = m_RegPropDWMin;
CvTermCriteria term_crit = cvTermCriteria(m_TermCriteriaType, m_MaxIter, m_Epsilon);
params.term_crit = term_crit;
+ return params;
+}
+template<class TInputValue, class TOutputValue>
+void NeuralNetworkMachineLearningModel<TInputValue, TOutputValue>::SetupNetworkAndTrain(cv::Mat& labels)
+{
+ //convert listsample to opencv matrix
+ cv::Mat samples;
+ otb::ListSampleToMat<InputListSampleType>(this->GetInputListSample(), samples);
+ this->CreateNetwork();
+ CvANN_MLP_TrainParams params = this->SetNetworkParameters();
//train the Neural network model
- m_ANNModel->train(samples, matOutputANN, cv::Mat(), cv::Mat(), params);
+ m_ANNModel->train(samples, labels, cv::Mat(), cv::Mat(), params);
+}
+
+/** Train the machine learning model for classification*/
+template<class TInputValue, class TOutputValue>
+void NeuralNetworkMachineLearningModel<TInputValue, TOutputValue>::Train()
+{
+ //Transform the targets into a matrix of labels
+ cv::Mat matOutputANN;
+ if (this->m_RegressionMode)
+ {
+ // MODE REGRESSION
+ otb::ListSampleToMat<TargetListSampleType>(this->GetTargetListSample(), matOutputANN);
+ }
+ else
+ {
+ // MODE CLASSIFICATION : store the map between internal labels and output labels
+ LabelsToMat(this->GetTargetListSample(), matOutputANN);
+ }
+ this->SetupNetworkAndTrain(matOutputANN);
}
template<class TInputValue, class TOutputValue>
typename NeuralNetworkMachineLearningModel<TInputValue, TOutputValue>::TargetSampleType NeuralNetworkMachineLearningModel<
- TInputValue, TOutputValue>::PredictClassification(const InputSampleType & input, ConfidenceValueType *quality) const
+ TInputValue, TOutputValue>::Predict(const InputSampleType & input, ConfidenceValueType *quality) const
{
//convert listsample to Mat
cv::Mat sample;
@@ -183,6 +213,15 @@ typename NeuralNetworkMachineLearningModel<TInputValue, TOutputValue>::TargetSam
TargetSampleType target;
float currentResponse = 0;
float maxResponse = response.at<float> (0, 0);
+
+ if (this->m_RegressionMode)
+ {
+ // MODE REGRESSION : only output first response
+ target[0] = maxResponse;
+ return target;
+ }
+
+ // MODE CLASSIFICATION : find the highest response
float secondResponse = -1e10;
target[0] = m_CvMatOfLabels->data.i[0];
diff --git a/Modules/Learning/Supervised/include/otbNormalBayesMachineLearningModel.h b/Modules/Learning/Supervised/include/otbNormalBayesMachineLearningModel.h
index 31b5373ce16510512aa90065e151408a764898ed..8ecfcd2b51d607169b30dcc86dd59d2096d728f4 100644
--- a/Modules/Learning/Supervised/include/otbNormalBayesMachineLearningModel.h
+++ b/Modules/Learning/Supervised/include/otbNormalBayesMachineLearningModel.h
@@ -52,6 +52,11 @@ public:
itkNewMacro(Self);
itkTypeMacro(NormalBayesMachineLearningModel, MachineLearningModel);
+ /** Train the machine learning model */
+ virtual void Train();
+ /** Predict values using the model */
+ virtual TargetSampleType Predict(const InputSampleType& input, ConfidenceValueType *quality=NULL) const;
+
/** Save the model to file */
virtual void Save(const std::string & filename, const std::string & name="");
@@ -77,11 +82,6 @@ protected:
/** PrintSelf method */
void PrintSelf(std::ostream& os, itk::Indent indent) const;
- /** Train the machine learning model */
- virtual void TrainClassification();
- /** Predict values using the model */
- virtual TargetSampleType PredictClassification(const InputSampleType& input, ConfidenceValueType *quality=NULL) const;
-
private:
NormalBayesMachineLearningModel(const Self &); //purposely not implemented
void operator =(const Self&); //purposely not implemented
diff --git a/Modules/Learning/Supervised/include/otbNormalBayesMachineLearningModel.txx b/Modules/Learning/Supervised/include/otbNormalBayesMachineLearningModel.txx
index bfc163553ddb58eb7e3e9f2150fc9cb63dbfaca2..7538f02c8818fcd07851f26044724992d4747af5 100644
--- a/Modules/Learning/Supervised/include/otbNormalBayesMachineLearningModel.txx
+++ b/Modules/Learning/Supervised/include/otbNormalBayesMachineLearningModel.txx
@@ -45,7 +45,7 @@ NormalBayesMachineLearningModel<TInputValue,TOutputValue>
template <class TInputValue, class TOutputValue>
void
NormalBayesMachineLearningModel<TInputValue,TOutputValue>
-::TrainClassification()
+::Train()
{
//convert listsample to opencv matrix
cv::Mat samples;
@@ -61,7 +61,7 @@ template <class TInputValue, class TOutputValue>
typename NormalBayesMachineLearningModel<TInputValue,TOutputValue>
::TargetSampleType
NormalBayesMachineLearningModel<TInputValue,TOutputValue>
-::PredictClassification(const InputSampleType & input, ConfidenceValueType *quality) const
+::Predict(const InputSampleType & input, ConfidenceValueType *quality) const
{
//convert listsample to Mat
cv::Mat sample;
diff --git a/Modules/Learning/Supervised/include/otbRandomForestsMachineLearningModel.h b/Modules/Learning/Supervised/include/otbRandomForestsMachineLearningModel.h
index 20aff52a7e200f47f9127005addc442d25fd5799..ec62b761358634daa8e268c1488770bb801d3543 100644
--- a/Modules/Learning/Supervised/include/otbRandomForestsMachineLearningModel.h
+++ b/Modules/Learning/Supervised/include/otbRandomForestsMachineLearningModel.h
@@ -59,6 +59,11 @@ public:
itkNewMacro(Self);
itkTypeMacro(RandomForestsMachineLearningModel, MachineLearningModel);
+ /** Train the machine learning model */
+ virtual void Train();
+ /** Predict values using the model */
+ virtual TargetSampleType Predict(const InputSampleType& input, ConfidenceValueType *quality=NULL) const;
+
/** Save the model to file */
virtual void Save(const std::string & filename, const std::string & name="");
@@ -115,9 +120,6 @@ public:
itkGetMacro(TerminationCriteria, int);
itkSetMacro(TerminationCriteria, int);
- itkGetMacro(RegressionMode, bool);
- itkSetMacro(RegressionMode, bool);
-
/** Returns a matrix containing variable importance */
VariableImportanceMatrixType GetVariableImportance();
@@ -139,11 +141,6 @@ protected:
/* /\** Target list sample *\/ */
/* typename TargetListSampleType::Pointer m_TargetListSample; */
- /** Train the machine learning model */
- virtual void TrainClassification();
- /** Predict values using the model */
- virtual TargetSampleType PredictClassification(const InputSampleType& input, ConfidenceValueType *quality=NULL) const;
-
private:
RandomForestsMachineLearningModel(const Self &); //purposely not implemented
void operator =(const Self&); //purposely not implemented
@@ -208,8 +205,6 @@ private:
float m_ForestAccuracy;
/** The type of the termination criteria */
int m_TerminationCriteria;
- /** Perform regression instead of classification */
- bool m_RegressionMode;
};
} // end namespace otb
diff --git a/Modules/Learning/Supervised/include/otbRandomForestsMachineLearningModel.txx b/Modules/Learning/Supervised/include/otbRandomForestsMachineLearningModel.txx
index 0797c2fabf18077612470b70604d8a3492a64446..78642f1212ac9d75dc75d3bd9e9482d73bc948dc 100644
--- a/Modules/Learning/Supervised/include/otbRandomForestsMachineLearningModel.txx
+++ b/Modules/Learning/Supervised/include/otbRandomForestsMachineLearningModel.txx
@@ -32,17 +32,17 @@ RandomForestsMachineLearningModel<TInputValue,TOutputValue>
m_RFModel (new CvRTrees),
m_MaxDepth(5),
m_MinSampleCount(10),
- m_RegressionAccuracy(0),
+ m_RegressionAccuracy(0.01),
m_ComputeSurrogateSplit(false),
m_MaxNumberOfCategories(10),
m_CalculateVariableImportance(false),
m_MaxNumberOfVariables(0),
m_MaxNumberOfTrees(100),
m_ForestAccuracy(0.01),
- m_TerminationCriteria(CV_TERMCRIT_ITER | CV_TERMCRIT_EPS),
- m_RegressionMode(false)
+ m_TerminationCriteria(CV_TERMCRIT_ITER | CV_TERMCRIT_EPS)
{
this->m_ConfidenceIndex = true;
+ this->m_IsRegressionSupported = true;
}
@@ -65,7 +65,7 @@ RandomForestsMachineLearningModel<TInputValue,TOutputValue>
template <class TInputValue, class TOutputValue>
void
RandomForestsMachineLearningModel<TInputValue,TOutputValue>
-::TrainClassification()
+::Train()
{
//convert listsample to opencv matrix
cv::Mat samples;
@@ -96,7 +96,7 @@ RandomForestsMachineLearningModel<TInputValue,TOutputValue>
cv::Mat var_type = cv::Mat(this->GetInputListSample()->GetMeasurementVectorSize() + 1, 1, CV_8U );
var_type.setTo(cv::Scalar(CV_VAR_NUMERICAL) ); // all inputs are numerical
- if(m_RegressionMode)
+ if(this->m_RegressionMode)
var_type.at<uchar>(this->GetInputListSample()->GetMeasurementVectorSize(), 0) = CV_VAR_NUMERICAL;
else
var_type.at<uchar>(this->GetInputListSample()->GetMeasurementVectorSize(), 0) = CV_VAR_CATEGORICAL;
@@ -110,7 +110,7 @@ template <class TInputValue, class TOutputValue>
typename RandomForestsMachineLearningModel<TInputValue,TOutputValue>
::TargetSampleType
RandomForestsMachineLearningModel<TInputValue,TOutputValue>
-::PredictClassification(const InputSampleType & value, ConfidenceValueType *quality) const
+::Predict(const InputSampleType & value, ConfidenceValueType *quality) const
{
//convert listsample to Mat
cv::Mat sample;
diff --git a/Modules/Learning/Supervised/include/otbSVMMachineLearningModel.h b/Modules/Learning/Supervised/include/otbSVMMachineLearningModel.h
index 406bdd10e6b04a808fbd2be168e0f7504aa79578..569ab321427925e1e662d941d2be1a398fda54cc 100644
--- a/Modules/Learning/Supervised/include/otbSVMMachineLearningModel.h
+++ b/Modules/Learning/Supervised/include/otbSVMMachineLearningModel.h
@@ -51,6 +51,11 @@ public:
itkNewMacro(Self);
itkTypeMacro(SVMMachineLearningModel, MachineLearningModel);
+ /** Train the machine learning model */
+ virtual void Train();
+ /** Predict values using the model */
+ virtual TargetSampleType Predict(const InputSampleType& input, ConfidenceValueType *quality=NULL) const;
+
/** Save the model to file */
virtual void Save(const std::string & filename, const std::string & name="");
@@ -126,11 +131,6 @@ protected:
/** PrintSelf method */
void PrintSelf(std::ostream& os, itk::Indent indent) const;
- /** Train the machine learning model */
- virtual void TrainClassification();
- /** Predict values using the model */
- virtual TargetSampleType PredictClassification(const InputSampleType& input, ConfidenceValueType *quality=NULL) const;
-
private:
SVMMachineLearningModel(const Self &); //purposely not implemented
void operator =(const Self&); //purposely not implemented
diff --git a/Modules/Learning/Supervised/include/otbSVMMachineLearningModel.txx b/Modules/Learning/Supervised/include/otbSVMMachineLearningModel.txx
index 064db060d1670146d4b618d94fa529017475758e..9d0b7d685948ebf67b070c6a16fcc9e6f760ea34 100644
--- a/Modules/Learning/Supervised/include/otbSVMMachineLearningModel.txx
+++ b/Modules/Learning/Supervised/include/otbSVMMachineLearningModel.txx
@@ -50,6 +50,7 @@ SVMMachineLearningModel<TInputValue,TOutputValue>
m_OutputP(0)
{
this->m_ConfidenceIndex = true;
+ this->m_IsRegressionSupported = true;
}
@@ -64,8 +65,16 @@ SVMMachineLearningModel<TInputValue,TOutputValue>
template <class TInputValue, class TOutputValue>
void
SVMMachineLearningModel<TInputValue,TOutputValue>
-::TrainClassification()
+::Train()
{
+ // Check that the SVM type is compatible with the chosen mode (classif/regression)
+ if ( bool(m_SVMType == CvSVM::NU_SVR || m_SVMType == CvSVM::EPS_SVR) != this->m_RegressionMode)
+ {
+ itkGenericExceptionMacro("SVM type incompatible with chosen mode (classification or regression."
+ "SVM types for classification are C_SVC, NU_SVC, ONE_CLASS. "
+ "SVM types for regression are NU_SVR, EPS_SVR");
+ }
+
//convert listsample to opencv matrix
cv::Mat samples;
otb::ListSampleToMat<InputListSampleType>(this->GetInputListSample(), samples);
@@ -109,7 +118,7 @@ template <class TInputValue, class TOutputValue>
typename SVMMachineLearningModel<TInputValue,TOutputValue>
::TargetSampleType
SVMMachineLearningModel<TInputValue,TOutputValue>
-::PredictClassification(const InputSampleType & input, ConfidenceValueType *quality) const
+::Predict(const InputSampleType & input, ConfidenceValueType *quality) const
{
//convert listsample to Mat
cv::Mat sample;
@@ -135,10 +144,10 @@ void
SVMMachineLearningModel<TInputValue,TOutputValue>
::Save(const std::string & filename, const std::string & name)
{
- if (name == "")
- m_SVMModel->save(filename.c_str(), 0);
- else
- m_SVMModel->save(filename.c_str(), name.c_str());
+ if (name == "")
+ m_SVMModel->save(filename.c_str(), 0);
+ else
+ m_SVMModel->save(filename.c_str(), name.c_str());
}
template <class TInputValue, class TOutputValue>
@@ -147,9 +156,9 @@ SVMMachineLearningModel<TInputValue,TOutputValue>
::Load(const std::string & filename, const std::string & name)
{
if (name == "")
- m_SVMModel->load(filename.c_str(), 0);
+ m_SVMModel->load(filename.c_str(), 0);
else
- m_SVMModel->load(filename.c_str(), name.c_str());
+ m_SVMModel->load(filename.c_str(), name.c_str());
}
template <class TInputValue, class TOutputValue>
@@ -157,29 +166,29 @@ bool
SVMMachineLearningModel<TInputValue,TOutputValue>
::CanReadFile(const std::string & file)
{
- std::ifstream ifs;
- ifs.open(file.c_str());
-
- if(!ifs)
- {
- std::cerr<<"Could not read file "<<file<<std::endl;
- return false;
- }
-
- while (!ifs.eof())
- {
- std::string line;
- std::getline(ifs, line);
-
- //if (line.find(m_SVMModel->getName()) != std::string::npos)
- if (line.find(CV_TYPE_NAME_ML_SVM) != std::string::npos)
+ std::ifstream ifs;
+ ifs.open(file.c_str());
+
+ if(!ifs)
+ {
+ std::cerr<<"Could not read file "<<file<<std::endl;
+ return false;
+ }
+
+ while (!ifs.eof())
+ {
+ std::string line;
+ std::getline(ifs, line);
+
+ //if (line.find(m_SVMModel->getName()) != std::string::npos)
+ if (line.find(CV_TYPE_NAME_ML_SVM) != std::string::npos)
{
- //std::cout<<"Reading a "<<CV_TYPE_NAME_ML_SVM<<" model"<<std::endl;
- return true;
+ //std::cout<<"Reading a "<<CV_TYPE_NAME_ML_SVM<<" model"<<std::endl;
+ return true;
}
- }
- ifs.close();
- return false;
+ }
+ ifs.close();
+ return false;
}
template <class TInputValue, class TOutputValue>
diff --git a/Modules/Learning/Supervised/test/CMakeLists.txt b/Modules/Learning/Supervised/test/CMakeLists.txt
index 7ffe8757b490c64081ffb6fe424a582d382d4df5..abca168f4f7794ea1a9133370c65555593b9bf19 100644
--- a/Modules/Learning/Supervised/test/CMakeLists.txt
+++ b/Modules/Learning/Supervised/test/CMakeLists.txt
@@ -7,6 +7,7 @@ otbConfusionMatrixMeasurementsTest.cxx
otbMachineLearningModelCanRead.cxx
otbTrainMachineLearningModel.cxx
otbImageClassificationFilter.cxx
+otbMachineLearningRegressionTests.cxx
)
add_executable(otbSupervisedTestDriver ${OTBSupervisedTests})
diff --git a/Modules/Learning/Supervised/test/otbMachineLearningRegressionTests.cxx b/Modules/Learning/Supervised/test/otbMachineLearningRegressionTests.cxx
new file mode 100644
index 0000000000000000000000000000000000000000..f54a9a96adc5a60f18f2a2411ff0e078ad5aba6d
--- /dev/null
+++ b/Modules/Learning/Supervised/test/otbMachineLearningRegressionTests.cxx
@@ -0,0 +1,669 @@
+/*=========================================================================
+
+ Program: ORFEO Toolbox
+ Language: C++
+ Date: $Date$
+ Version: $Revision$
+
+
+ Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
+ See OTBCopyright.txt for details.
+
+
+ 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 "otbConfigure.h"
+
+#include "itkMersenneTwisterRandomVariateGenerator.h"
+
+#ifdef OTB_USE_OPENCV
+#include "otbNeuralNetworkMachineLearningModel.h"
+#include "otbSVMMachineLearningModel.h"
+#include "otbBoostMachineLearningModel.h"
+#include "otbDecisionTreeMachineLearningModel.h"
+#include "otbGradientBoostedTreeMachineLearningModel.h"
+#include "otbKNearestNeighborsMachineLearningModel.h"
+#include "otbRandomForestsMachineLearningModel.h"
+#endif
+
+#ifdef OTB_USE_LIBSVM
+#include "otbLibSVMMachineLearningModel.h"
+#endif
+
+typedef float PrecisionType;
+typedef otb::MachineLearningModel<PrecisionType,PrecisionType> MachineLearningModelRegressionType;
+typedef MachineLearningModelRegressionType::InputValueType InputValueRegressionType;
+typedef MachineLearningModelRegressionType::InputSampleType InputSampleRegressionType;
+typedef MachineLearningModelRegressionType::InputListSampleType InputListSampleRegressionType;
+typedef MachineLearningModelRegressionType::TargetValueType TargetValueRegressionType;
+typedef MachineLearningModelRegressionType::TargetSampleType TargetSampleRegressionType;
+typedef MachineLearningModelRegressionType::TargetListSampleType TargetListSampleRegressionType;
+typedef itk::Statistics::MersenneTwisterRandomVariateGenerator RandomGeneratorType;
+
+const double epsilon = 0.1;
+
+typedef struct RegressionTestParamStruct
+{
+ double vMin;
+ double vMax;
+ size_t count;
+ double eps;
+} RegressionTestParam;
+
+template <typename TPrecision>
+struct LinearFunctionSampleGenerator
+{
+ typedef TPrecision PrecisionType;
+ LinearFunctionSampleGenerator(TPrecision a, TPrecision b)
+ : m_a(a), m_b(b), m_NbInputVars(1), m_NbOutputVars(1) {
+ m_isl = InputListSampleRegressionType::New();
+ m_tsl = TargetListSampleRegressionType::New();
+ };
+ void GenerateSamples(TPrecision sMin, TPrecision sMax, size_t nbSamples)
+ {
+ m_isl->Clear();
+ m_tsl->Clear();
+ m_isl->SetMeasurementVectorSize(m_NbInputVars);
+ m_tsl->SetMeasurementVectorSize(m_NbOutputVars);
+
+ RandomGeneratorType::Pointer randomGenerator = RandomGeneratorType::GetInstance();
+ InputSampleRegressionType inputSample;
+ inputSample.SetSize(m_NbInputVars);
+ TargetSampleRegressionType outputSample;
+
+ TPrecision sampleStep = (sMax-sMin)/nbSamples;
+ for(size_t i=0; i<nbSamples; ++i)
+ {
+ TPrecision x = randomGenerator->GetUniformVariate(0.0, 1.0) * static_cast<TPrecision>(nbSamples);
+ TPrecision inputValue = sMin+ x*sampleStep;
+ inputSample[0] = inputValue;
+ outputSample[0] = m_a*inputValue+m_b;
+ m_isl->PushBack(inputSample);
+ m_tsl->PushBack(outputSample);
+ }
+ }
+
+ TPrecision m_a;
+ TPrecision m_b;
+ const size_t m_NbInputVars;
+ const size_t m_NbOutputVars;
+ InputListSampleRegressionType::Pointer m_isl;
+ TargetListSampleRegressionType::Pointer m_tsl;
+};
+
+template <typename TPrecision>
+struct BilinearFunctionSampleGenerator
+{
+ typedef TPrecision PrecisionType;
+ BilinearFunctionSampleGenerator(TPrecision a, TPrecision b, TPrecision c)
+ : m_a(a), m_b(b), m_c(c), m_NbInputVars(2), m_NbOutputVars(1) {
+ m_isl = InputListSampleRegressionType::New();
+ m_tsl = TargetListSampleRegressionType::New();
+ };
+ void GenerateSamples(TPrecision sMin, TPrecision sMax, size_t nbSamples)
+ {
+ m_isl->Clear();
+ m_tsl->Clear();
+ m_isl->SetMeasurementVectorSize(m_NbInputVars);
+ m_tsl->SetMeasurementVectorSize(m_NbOutputVars);
+
+ RandomGeneratorType::Pointer randomGenerator = RandomGeneratorType::GetInstance();
+ InputSampleRegressionType inputSample;
+ inputSample.SetSize(m_NbInputVars);
+ TargetSampleRegressionType outputSample;
+
+ TPrecision sampleStep = (sMax-sMin)/nbSamples;
+ for(size_t i=0; i<nbSamples; ++i)
+ {
+ TPrecision x = randomGenerator->GetUniformVariate(0.0, 1.0) * static_cast<TPrecision>(nbSamples);
+ TPrecision inputValue1 = sMin+ x*sampleStep;
+ x = randomGenerator->GetUniformVariate(0.0, 1.0) * static_cast<TPrecision>(nbSamples);
+ TPrecision inputValue2 = sMin+ x*sampleStep;
+ inputSample[0] = inputValue1;
+ inputSample[1] = inputValue2;
+ outputSample[0] = m_a*inputValue1+m_b*inputValue2+m_c;
+ m_isl->PushBack(inputSample);
+ m_tsl->PushBack(outputSample);
+ }
+ }
+
+ TPrecision m_a;
+ TPrecision m_b;
+ TPrecision m_c;
+ const size_t m_NbInputVars;
+ const size_t m_NbOutputVars;
+ InputListSampleRegressionType::Pointer m_isl;
+ TargetListSampleRegressionType::Pointer m_tsl;
+};
+
+template <typename TPrecision>
+struct PolynomialFunctionSampleGenerator
+{
+ typedef TPrecision PrecisionType;
+ PolynomialFunctionSampleGenerator(std::vector<TPrecision> c)
+ : m_c(c), m_NbInputVars(1), m_NbOutputVars(1) {
+ m_isl = InputListSampleRegressionType::New();
+ m_tsl = TargetListSampleRegressionType::New();
+ };
+ void GenerateSamples(TPrecision sMin, TPrecision sMax, size_t nbSamples)
+ {
+ m_isl->Clear();
+ m_tsl->Clear();
+ m_isl->SetMeasurementVectorSize(m_NbInputVars);
+ m_tsl->SetMeasurementVectorSize(m_NbOutputVars);
+
+ RandomGeneratorType::Pointer randomGenerator = RandomGeneratorType::GetInstance();
+ InputSampleRegressionType inputSample;
+ inputSample.SetSize(m_NbInputVars);
+ TargetSampleRegressionType outputSample;
+
+ TPrecision sampleStep = (sMax-sMin)/nbSamples;
+ for(size_t i=0; i<nbSamples; ++i)
+ {
+ TPrecision x = randomGenerator->GetUniformVariate(0.0, 1.0) * static_cast<TPrecision>(nbSamples);
+ TPrecision inputValue = sMin+ x*sampleStep;
+ inputSample[0] = inputValue;
+ TPrecision y = 0.0;
+ for (unsigned int j=0; j<m_c.size() ; ++j)
+ {
+ y += m_c[j] * pow(static_cast<double>(inputValue), static_cast<double>(j));
+ }
+ outputSample[0] = y;
+ m_isl->PushBack(inputSample);
+ m_tsl->PushBack(outputSample);
+ }
+ }
+
+ std::vector<TPrecision> m_c;
+ const size_t m_NbInputVars;
+ const size_t m_NbOutputVars;
+ InputListSampleRegressionType::Pointer m_isl;
+ TargetListSampleRegressionType::Pointer m_tsl;
+};
+
+template <typename SampleGeneratorType, typename RegressionType>
+int testRegression(SampleGeneratorType& sg, RegressionType& rgrsn, RegressionTestParam param)
+{
+ std::cout << "Generating training samples" << std::endl;
+ sg.GenerateSamples(param.vMin, param.vMax, param.count);
+
+ rgrsn->SetInputListSample(sg.m_isl);
+ rgrsn->SetTargetListSample(sg.m_tsl);
+ std::cout << "Training" << std::endl;
+ rgrsn->Train();
+
+ std::cout << "Generate validation samples"<<std::endl;
+ sg.GenerateSamples(param.vMin, param.vMax, param.count);
+
+ std::cout << "Validation" << std::endl;
+ //Check the prediction accuracy
+ typename InputListSampleRegressionType::Iterator sampleIt = sg.m_isl->Begin();
+ typename TargetListSampleRegressionType::Iterator resultIt = sg.m_tsl->Begin();
+ typename InputListSampleRegressionType::Iterator sampleLast = sg.m_isl->End();
+ typename TargetListSampleRegressionType::Iterator resultLast = sg.m_tsl->End();
+ typename SampleGeneratorType::PrecisionType rmse = 0.0;
+ while(sampleIt != sampleLast && resultIt != resultLast)
+ {
+ //typename SampleGeneratorType::PrecisionType invalue = sampleIt.GetMeasurementVector()[0];
+ typename SampleGeneratorType::PrecisionType prediction = rgrsn->Predict(sampleIt.GetMeasurementVector())[0];
+ typename SampleGeneratorType::PrecisionType expected = resultIt.GetMeasurementVector()[0];
+ rmse += std::pow(prediction - expected, static_cast<PrecisionType>(2.0));
+ ++sampleIt;
+ ++resultIt;
+ }
+
+ rmse = sqrt( rmse / static_cast<double>(param.count) );
+ std::cout << "RMSE = "<< rmse << std::endl;
+ if(rmse > param.eps)
+ {
+ std::cout << "Failed : RMSE above expected precision !" << std::endl;
+ return EXIT_FAILURE;
+ }
+
+ return EXIT_SUCCESS;
+}
+
+#ifdef OTB_USE_LIBSVM
+MachineLearningModelRegressionType::Pointer getLibSVMRegressionModel()
+{
+ typedef otb::LibSVMMachineLearningModel<InputValueRegressionType,
+ TargetValueRegressionType>
+ libsvmType;
+ libsvmType::Pointer regression = libsvmType::New();
+ regression->SetRegressionMode(true);
+ regression->SetSVMType(EPSILON_SVR);
+ regression->SetKernelType(RBF);
+ regression->SetEpsilon(1e-5);
+ regression->SetParameterOptimization(true);
+ return regression.GetPointer();
+}
+
+int otbLibSVMRegressionTests(int itkNotUsed(argc),
+ char * itkNotUsed(argv) [])
+{
+ int status = EXIT_SUCCESS;
+ int ret;
+ MachineLearningModelRegressionType::Pointer regression;
+
+ RegressionTestParam param;
+ param.vMin = -0.5;
+ param.vMax = 0.5;
+ param.count = 200;
+ param.eps = 0.1;
+
+ std::cout << "Testing regression on a linear monovariate function" << std::endl;
+ LinearFunctionSampleGenerator<PrecisionType> lfsg(2.0, 1.0);
+ regression = getLibSVMRegressionModel();
+ ret = testRegression(lfsg,regression,param);
+ if (ret == EXIT_FAILURE)
+ {
+ status = EXIT_FAILURE;
+ }
+ std::cout << "Testing regression on a bilinear function" << std::endl;
+ BilinearFunctionSampleGenerator<PrecisionType> bfsg(2.0,-1.0,1.0);
+ regression = getLibSVMRegressionModel();
+ ret = testRegression(bfsg,regression,param);
+ if (ret == EXIT_FAILURE)
+ {
+ status = EXIT_FAILURE;
+ }
+ std::cout << "Testing regression on a polynomial function" << std::endl;
+ std::vector<PrecisionType> coeffs;
+ coeffs.push_back(0.0);
+ coeffs.push_back(-1.0);
+ coeffs.push_back(0.0);
+ coeffs.push_back(4.0);
+ PolynomialFunctionSampleGenerator<PrecisionType> pfsg(coeffs);
+ regression = getLibSVMRegressionModel();
+ ret = testRegression(pfsg,regression,param);
+ if (ret == EXIT_FAILURE)
+ {
+ status = EXIT_FAILURE;
+ }
+ return status;
+}
+
+#endif
+
+#ifdef OTB_USE_OPENCV
+MachineLearningModelRegressionType::Pointer getNeuralNetworkRegressionModel(unsigned int nbInputVar)
+{
+ typedef otb::NeuralNetworkMachineLearningModel<InputValueRegressionType,
+ TargetValueRegressionType>
+ NeuralNetworkType;
+ NeuralNetworkType::Pointer regression = NeuralNetworkType::New();
+
+ regression->SetRegressionMode(1);
+ regression->SetTrainMethod(CvANN_MLP_TrainParams::BACKPROP);
+ std::vector<unsigned int> layerSizes;
+ layerSizes.push_back(nbInputVar);
+ layerSizes.push_back(5);
+ layerSizes.push_back(1);
+ regression->SetLayerSizes(layerSizes);
+ regression->SetActivateFunction(CvANN_MLP::SIGMOID_SYM);
+ regression->SetAlpha(1.0);
+ regression->SetBeta(1.0);
+ regression->SetBackPropDWScale(0.1);
+ regression->SetBackPropMomentScale(0.1);
+ regression->SetRegPropDW0(0.1);
+ regression->SetRegPropDWMin(1e-7);
+ regression->SetTermCriteriaType(CV_TERMCRIT_EPS);
+ regression->SetEpsilon(1e-5);
+ regression->SetMaxIter(1e4);
+ return regression.GetPointer();
+}
+
+int otbNeuralNetworkRegressionTests(int itkNotUsed(argc),
+ char * itkNotUsed(argv) [])
+{
+ int status = EXIT_SUCCESS;
+ int ret;
+ MachineLearningModelRegressionType::Pointer regression;
+
+ RegressionTestParam param;
+ param.vMin = -0.5;
+ param.vMax = 0.5;
+ param.count = 20000;
+ param.eps = 0.1;
+
+ std::cout << "Testing regression on a linear monovariate function" << std::endl;
+ LinearFunctionSampleGenerator<PrecisionType> lfsg(2.0, 1.0);
+ regression = getNeuralNetworkRegressionModel(1);
+ ret = testRegression(lfsg,regression,param);
+ if (ret == EXIT_FAILURE)
+ {
+ status = EXIT_FAILURE;
+ }
+ std::cout << "Testing regression on a bilinear function" << std::endl;
+ BilinearFunctionSampleGenerator<PrecisionType> bfsg(2.0,-1.0,1.0);
+ regression = getNeuralNetworkRegressionModel(2);
+ ret = testRegression(bfsg,regression,param);
+ if (ret == EXIT_FAILURE)
+ {
+ status = EXIT_FAILURE;
+ }
+ std::cout << "Testing regression on a polynomial function" << std::endl;
+ std::vector<PrecisionType> coeffs;
+ coeffs.push_back(0.0);
+ coeffs.push_back(-1.0);
+ coeffs.push_back(0.0);
+ coeffs.push_back(4.0);
+ PolynomialFunctionSampleGenerator<PrecisionType> pfsg(coeffs);
+ regression = getNeuralNetworkRegressionModel(1);
+ ret = testRegression(pfsg,regression,param);
+ if (ret == EXIT_FAILURE)
+ {
+ status = EXIT_FAILURE;
+ }
+ return status;
+}
+
+
+MachineLearningModelRegressionType::Pointer getSVMRegressionModel()
+{
+ typedef otb::SVMMachineLearningModel<InputValueRegressionType,
+ TargetValueRegressionType>
+ SVMType;
+ SVMType::Pointer regression = SVMType::New();
+
+ regression->SetRegressionMode(1);
+ regression->SetSVMType(CvSVM::NU_SVR);
+ regression->SetNu(0.5);
+ regression->SetKernelType(CvSVM::RBF);
+ regression->SetTermCriteriaType(CV_TERMCRIT_ITER+CV_TERMCRIT_EPS);
+ regression->SetMaxIter(100000);
+ regression->SetEpsilon(1e-5);
+ regression->SetParameterOptimization(true);
+ return regression.GetPointer();
+}
+
+int otbSVMRegressionTests(int itkNotUsed(argc),
+ char * itkNotUsed(argv) [])
+{
+ int status = EXIT_SUCCESS;
+ int ret;
+ MachineLearningModelRegressionType::Pointer regression;
+
+ RegressionTestParam param;
+ param.vMin = -0.5;
+ param.vMax = 0.5;
+ param.count = 200;
+ param.eps = 0.1;
+
+ std::cout << "Testing regression on a linear monovariate function" << std::endl;
+ LinearFunctionSampleGenerator<PrecisionType> lfsg(2.0, 1.0);
+ regression = getSVMRegressionModel();
+ ret = testRegression(lfsg,regression,param);
+ if (ret == EXIT_FAILURE)
+ {
+ status = EXIT_FAILURE;
+ }
+ std::cout << "Testing regression on a bilinear function" << std::endl;
+ BilinearFunctionSampleGenerator<PrecisionType> bfsg(2.0,-1.0,1.0);
+ regression = getSVMRegressionModel();
+ ret = testRegression(bfsg,regression,param);
+ if (ret == EXIT_FAILURE)
+ {
+ status = EXIT_FAILURE;
+ }
+ std::cout << "Testing regression on a polynomial function" << std::endl;
+ std::vector<PrecisionType> coeffs;
+ coeffs.push_back(0.0);
+ coeffs.push_back(-1.0);
+ coeffs.push_back(0.0);
+ coeffs.push_back(4.0);
+ PolynomialFunctionSampleGenerator<PrecisionType> pfsg(coeffs);
+ regression = getSVMRegressionModel();
+ ret = testRegression(pfsg,regression,param);
+ if (ret == EXIT_FAILURE)
+ {
+ status = EXIT_FAILURE;
+ }
+ return status;
+}
+
+
+MachineLearningModelRegressionType::Pointer getDecisionTreeRegressionModel()
+{
+ typedef otb::DecisionTreeMachineLearningModel<InputValueRegressionType,
+ TargetValueRegressionType>
+ DTreeType;
+ DTreeType::Pointer regression = DTreeType::New();
+ regression->SetRegressionMode(true);
+ regression->SetRegressionAccuracy(0.005);
+ return regression.GetPointer();
+}
+
+int otbDecisionTreeRegressionTests(int itkNotUsed(argc),
+ char * itkNotUsed(argv) [])
+{
+ int status = EXIT_SUCCESS;
+ int ret;
+ MachineLearningModelRegressionType::Pointer regression;
+
+ RegressionTestParam param;
+ param.vMin = -0.5;
+ param.vMax = 0.5;
+ param.count = 200;
+ param.eps = 0.1;
+
+ std::cout << "Testing regression on a linear monovariate function" << std::endl;
+ LinearFunctionSampleGenerator<PrecisionType> lfsg(2.0, 1.0);
+ regression = getDecisionTreeRegressionModel();
+ ret = testRegression(lfsg,regression,param);
+ if (ret == EXIT_FAILURE)
+ {
+ status = EXIT_FAILURE;
+ }
+ std::cout << "Testing regression on a bilinear function" << std::endl;
+ BilinearFunctionSampleGenerator<PrecisionType> bfsg(2.0,-1.0,1.0);
+ regression = getDecisionTreeRegressionModel();
+ // increase the number of training samples for bilinear function
+ param.count = 1000;
+ ret = testRegression(bfsg,regression,param);
+ if (ret == EXIT_FAILURE)
+ {
+ status = EXIT_FAILURE;
+ }
+ std::cout << "Testing regression on a polynomial function" << std::endl;
+ std::vector<PrecisionType> coeffs;
+ coeffs.push_back(0.0);
+ coeffs.push_back(-1.0);
+ coeffs.push_back(0.0);
+ coeffs.push_back(4.0);
+ PolynomialFunctionSampleGenerator<PrecisionType> pfsg(coeffs);
+ param.count = 200;
+ regression = getDecisionTreeRegressionModel();
+ ret = testRegression(pfsg,regression,param);
+ if (ret == EXIT_FAILURE)
+ {
+ status = EXIT_FAILURE;
+ }
+ return status;
+}
+
+
+MachineLearningModelRegressionType::Pointer getGradientBoostedTreeRegressionModel()
+{
+ typedef otb::GradientBoostedTreeMachineLearningModel<InputValueRegressionType,
+ TargetValueRegressionType>
+ GBTreeType;
+ GBTreeType::Pointer regression = GBTreeType::New();
+ regression->SetRegressionMode(true);
+ regression->SetShrinkage(0.1);
+ regression->SetSubSamplePortion(0.8);
+ regression->SetLossFunctionType(CvGBTrees::SQUARED_LOSS);
+ return regression.GetPointer();
+}
+
+int otbGradientBoostedTreeRegressionTests(int itkNotUsed(argc),
+ char * itkNotUsed(argv) [])
+{
+ int status = EXIT_SUCCESS;
+ int ret;
+ MachineLearningModelRegressionType::Pointer regression;
+
+ RegressionTestParam param;
+ param.vMin = -0.5;
+ param.vMax = 0.5;
+ param.count = 200;
+ param.eps = 0.1;
+
+ std::cout << "Testing regression on a linear monovariate function" << std::endl;
+ LinearFunctionSampleGenerator<PrecisionType> lfsg(2.0, 1.0);
+ regression = getGradientBoostedTreeRegressionModel();
+ ret = testRegression(lfsg,regression,param);
+ if (ret == EXIT_FAILURE)
+ {
+ status = EXIT_FAILURE;
+ }
+ std::cout << "Testing regression on a bilinear function" << std::endl;
+ BilinearFunctionSampleGenerator<PrecisionType> bfsg(2.0,-1.0,1.0);
+ // increase number of training samples for bilinear function
+ param.count = 1000;
+ regression = getGradientBoostedTreeRegressionModel();
+ ret = testRegression(bfsg,regression,param);
+ if (ret == EXIT_FAILURE)
+ {
+ status = EXIT_FAILURE;
+ }
+ std::cout << "Testing regression on a polynomial function" << std::endl;
+ std::vector<PrecisionType> coeffs;
+ coeffs.push_back(0.0);
+ coeffs.push_back(-1.0);
+ coeffs.push_back(0.0);
+ coeffs.push_back(4.0);
+ PolynomialFunctionSampleGenerator<PrecisionType> pfsg(coeffs);
+ param.count = 200;
+ regression = getGradientBoostedTreeRegressionModel();
+ ret = testRegression(pfsg,regression,param);
+ if (ret == EXIT_FAILURE)
+ {
+ status = EXIT_FAILURE;
+ }
+ return status;
+}
+
+
+MachineLearningModelRegressionType::Pointer getKNearestNeighborsRegressionModel()
+{
+ typedef otb::KNearestNeighborsMachineLearningModel<InputValueRegressionType,
+ TargetValueRegressionType>
+ KNNType;
+ KNNType::Pointer regression = KNNType::New();
+ regression->SetRegressionMode(true);
+ regression->SetK(5);
+ regression->SetDecisionRule(KNNType::KNN_MEDIAN);
+ return regression.GetPointer();
+}
+
+int otbKNearestNeighborsRegressionTests(int itkNotUsed(argc),
+ char * itkNotUsed(argv) [])
+{
+ int status = EXIT_SUCCESS;
+ int ret;
+ MachineLearningModelRegressionType::Pointer regression;
+
+ RegressionTestParam param;
+ param.vMin = -0.5;
+ param.vMax = 0.5;
+ param.count = 200;
+ param.eps = 0.1;
+
+ std::cout << "Testing regression on a linear monovariate function" << std::endl;
+ LinearFunctionSampleGenerator<PrecisionType> lfsg(2.0, 1.0);
+ regression = getKNearestNeighborsRegressionModel();
+ ret = testRegression(lfsg,regression,param);
+ if (ret == EXIT_FAILURE)
+ {
+ status = EXIT_FAILURE;
+ }
+ std::cout << "Testing regression on a bilinear function" << std::endl;
+ BilinearFunctionSampleGenerator<PrecisionType> bfsg(2.0,-1.0,1.0);
+ regression = getKNearestNeighborsRegressionModel();
+ ret = testRegression(bfsg,regression,param);
+ if (ret == EXIT_FAILURE)
+ {
+ status = EXIT_FAILURE;
+ }
+ std::cout << "Testing regression on a polynomial function" << std::endl;
+ std::vector<PrecisionType> coeffs;
+ coeffs.push_back(0.0);
+ coeffs.push_back(-1.0);
+ coeffs.push_back(0.0);
+ coeffs.push_back(4.0);
+ PolynomialFunctionSampleGenerator<PrecisionType> pfsg(coeffs);
+ regression = getKNearestNeighborsRegressionModel();
+ ret = testRegression(pfsg,regression,param);
+ if (ret == EXIT_FAILURE)
+ {
+ status = EXIT_FAILURE;
+ }
+ return status;
+}
+
+
+MachineLearningModelRegressionType::Pointer getRandomForestsRegressionModel()
+{
+ typedef otb::RandomForestsMachineLearningModel<InputValueRegressionType,
+ TargetValueRegressionType>
+ RFType;
+ RFType::Pointer regression = RFType::New();
+ regression->SetRegressionMode(true);
+ regression->SetRegressionAccuracy(0.005);
+ return regression.GetPointer();
+}
+
+
+int otbRandomForestsRegressionTests(int itkNotUsed(argc),
+ char * itkNotUsed(argv) [])
+{
+ int status = EXIT_SUCCESS;
+ int ret;
+ MachineLearningModelRegressionType::Pointer regression;
+
+ RegressionTestParam param;
+ param.vMin = -0.5;
+ param.vMax = 0.5;
+ param.count = 200;
+ param.eps = 0.1;
+
+ std::cout << "Testing regression on a linear monovariate function" << std::endl;
+ LinearFunctionSampleGenerator<PrecisionType> lfsg(2.0, 1.0);
+ regression = getRandomForestsRegressionModel();
+ ret = testRegression(lfsg,regression,param);
+ if (ret == EXIT_FAILURE)
+ {
+ status = EXIT_FAILURE;
+ }
+ std::cout << "Testing regression on a bilinear function" << std::endl;
+ BilinearFunctionSampleGenerator<PrecisionType> bfsg(2.0,-1.0,1.0);
+ // increase number of training samples for bilinear function
+ param.count = 1000;
+ regression = getRandomForestsRegressionModel();
+ ret = testRegression(bfsg,regression,param);
+ if (ret == EXIT_FAILURE)
+ {
+ status = EXIT_FAILURE;
+ }
+ std::cout << "Testing regression on a polynomial function" << std::endl;
+ std::vector<PrecisionType> coeffs;
+ coeffs.push_back(0.0);
+ coeffs.push_back(-1.0);
+ coeffs.push_back(0.0);
+ coeffs.push_back(4.0);
+ PolynomialFunctionSampleGenerator<PrecisionType> pfsg(coeffs);
+ param.count = 200;
+ regression = getRandomForestsRegressionModel();
+ ret = testRegression(pfsg,regression,param);
+ if (ret == EXIT_FAILURE)
+ {
+ status = EXIT_FAILURE;
+ }
+ return status;
+}
+#endif
diff --git a/Modules/Learning/Supervised/test/otbSupervisedTestDriver.cxx b/Modules/Learning/Supervised/test/otbSupervisedTestDriver.cxx
index e498bd082ed53ec2862ea5b99913b6b7de897b38..2bf373c87f9f0579df333951b83ae818739d25c2 100644
--- a/Modules/Learning/Supervised/test/otbSupervisedTestDriver.cxx
+++ b/Modules/Learning/Supervised/test/otbSupervisedTestDriver.cxx
@@ -28,6 +28,7 @@ void RegisterTests()
#ifdef OTB_USE_LIBSVM
REGISTER_TEST(otbLibSVMMachineLearningModelNew);
REGISTER_TEST(otbLibSVMMachineLearningModel);
+ REGISTER_TEST(otbLibSVMRegressionTests);
#endif
#ifdef OTB_USE_OPENCV
@@ -48,8 +49,14 @@ void RegisterTests()
REGISTER_TEST(otbDecisionTreeMachineLearningModel);
REGISTER_TEST(otbGradientBoostedTreeMachineLearningModelNew);
REGISTER_TEST(otbGradientBoostedTreeMachineLearningModel);
- #endif
+ REGISTER_TEST(otbNeuralNetworkRegressionTests);
+ REGISTER_TEST(otbSVMRegressionTests);
+ REGISTER_TEST(otbDecisionTreeRegressionTests);
+ REGISTER_TEST(otbGradientBoostedTreeRegressionTests);
+ REGISTER_TEST(otbKNearestNeighborsRegressionTests);
+ REGISTER_TEST(otbRandomForestsRegressionTests);
+#endif
- REGISTER_TEST(otbImageClassificationFilterNew);
+ REGISTER_TEST(otbImageClassificationFilterNew);
REGISTER_TEST(otbImageClassificationFilter);
}
diff --git a/Modules/Learning/Supervised/test/otbTrainMachineLearningModel.cxx b/Modules/Learning/Supervised/test/otbTrainMachineLearningModel.cxx
index 39a2a2f7628c98aca338093af70d1d75d35badee..64d69a120a2dd2cd8e3418ef248ff8c12324f6ed 100644
--- a/Modules/Learning/Supervised/test/otbTrainMachineLearningModel.cxx
+++ b/Modules/Learning/Supervised/test/otbTrainMachineLearningModel.cxx
@@ -381,20 +381,12 @@ int otbSVMMachineLearningRegressionModel(int argc, char * argv[])
SVMType::Pointer classifier = SVMType::New();
//Init SVM type in regression mode
- //Available mode for regression in openCV are eps_svr and nu_svr
+ classifier->SetRegressionMode(1);
classifier->SetSVMType(CvSVM::EPS_SVR);
- //classifier->SetSVMType(CvSVM::NU_SVR);
-
- //P should be >0. Increasing value give better result. Need to investigate why.
classifier->SetP(10);
-
- //IN case you're using nu_svr you should set nu to a positive value between 0
- //and 1.
- //classifier->SetNu(0.9);
-
- //Use RBF kernel.Don't know what is recommended in case of svm regression
classifier->SetKernelType(CvSVM::RBF);
+
classifier->SetInputListSample(samples);
classifier->SetTargetListSample(labels);
classifier->Train();
@@ -432,6 +424,7 @@ int otbSVMMachineLearningRegressionModel(int argc, char * argv[])
}
else
{
+ std::cout << age << "\t" << predicted->GetMeasurementVector(0)[0] << "\n";
return EXIT_FAILURE;
}
}
@@ -447,9 +440,9 @@ int otbKNearestNeighborsMachineLearningModel(int argc, char * argv[])
{
if (argc != 3 )
{
- std::cout<<"Wrong number of arguments "<<std::endl;
- std::cout<<"Usage : sample file, output file"<<std::endl;
- return EXIT_FAILURE;
+ std::cout<<"Wrong number of arguments "<<std::endl;
+ std::cout<<"Usage : sample file, output file"<<std::endl;
+ return EXIT_FAILURE;
}
typedef otb::KNearestNeighborsMachineLearningModel<InputValueType,TargetValueType> KNearestNeighborsType;
@@ -528,11 +521,11 @@ int otbRandomForestsMachineLearningModelNew(int itkNotUsed(argc), char * itkNotU
int otbRandomForestsMachineLearningModel(int argc, char * argv[])
{
if (argc != 3 )
- {
+ {
std::cout<<"Wrong number of arguments "<<std::endl;
std::cout<<"Usage : sample file, output file "<<std::endl;
return EXIT_FAILURE;
- }
+ }
typedef otb::RandomForestsMachineLearningModel<InputValueType,TargetValueType> RandomForestType;
InputListSampleType::Pointer samples = InputListSampleType::New();
@@ -620,9 +613,9 @@ int otbBoostMachineLearningModel(int argc, char * argv[])
{
if (argc != 3 )
{
- std::cout<<"Wrong number of arguments "<<std::endl;
- std::cout<<"Usage : sample file, output file "<<std::endl;
- return EXIT_FAILURE;
+ std::cout<<"Wrong number of arguments "<<std::endl;
+ std::cout<<"Usage : sample file, output file "<<std::endl;
+ return EXIT_FAILURE;
}
typedef otb::BoostMachineLearningModel<InputValueType, TargetValueType> BoostType;
diff --git a/Modules/Learning/Supervised/test/tests-libsvm.cmake b/Modules/Learning/Supervised/test/tests-libsvm.cmake
index 04764df301cb2b2fa7f1951d023495ddf93b5b4b..30dc7eec130d6baa87a8fd37296ce7501548dc7c 100644
--- a/Modules/Learning/Supervised/test/tests-libsvm.cmake
+++ b/Modules/Learning/Supervised/test/tests-libsvm.cmake
@@ -22,3 +22,7 @@ otb_add_test(NAME leTuLibSVMMachineLearningModelCanRead COMMAND otbSupervisedTes
${TEMP}/libsvm_model.txt
)
set_property(TEST leTuLibSVMMachineLearningModelCanRead PROPERTY DEPENDS leTvLibSVMMachineLearningModel)
+
+otb_add_test(NAME leTvLibSVMMachineLearningModelReg COMMAND otbSupervisedTestDriver
+ otbLibSVMRegressionTests
+ )
diff --git a/Modules/Learning/Supervised/test/tests-opencv.cmake b/Modules/Learning/Supervised/test/tests-opencv.cmake
index 55855a4aa912a3b3497bb9b8d9f2bc69d6dccea4..3be269fe8d8e7f17f85f9e4d11c944feb2dc3e02 100644
--- a/Modules/Learning/Supervised/test/tests-opencv.cmake
+++ b/Modules/Learning/Supervised/test/tests-opencv.cmake
@@ -10,6 +10,32 @@ otb_add_test(NAME leTvANNMachineLearningModel COMMAND otbSupervisedTestDriver
${TEMP}/ann_model.txt
)
+# ------------------ Regression tests --------------------
+otb_add_test(NAME leTvANNMachineLearningModelReg COMMAND otbSupervisedTestDriver
+ otbNeuralNetworkRegressionTests
+ )
+
+otb_add_test(NAME leTvSVMMachineLearningModelReg COMMAND otbSupervisedTestDriver
+ otbSVMRegressionTests
+ )
+
+otb_add_test(NAME leTvDecisionTreeMachineLearningModelReg COMMAND otbSupervisedTestDriver
+ otbDecisionTreeRegressionTests
+ )
+
+otb_add_test(NAME leTvGradientBoostedTreeMachineLearningModelReg COMMAND otbSupervisedTestDriver
+ otbGradientBoostedTreeRegressionTests
+ )
+
+otb_add_test(NAME leTvKNearestNeighborsMachineLearningModelReg COMMAND otbSupervisedTestDriver
+ otbKNearestNeighborsRegressionTests
+ )
+
+otb_add_test(NAME leTvRandomForestsMachineLearningModelReg COMMAND otbSupervisedTestDriver
+ otbRandomForestsRegressionTests
+ )
+# --------------------------------------------------------------
+
otb_add_test(NAME leTuSVMMachineLearningModelNew COMMAND otbSupervisedTestDriver
otbSVMMachineLearningModelNew)
diff --git a/Modules/Segmentation/Conversion/test/otbOGRDataSourceToLabelImageFilter.cxx b/Modules/Segmentation/Conversion/test/otbOGRDataSourceToLabelImageFilter.cxx
index 681dbc61f6632d6c9c2bec7629c840fcdf021501..745f1b01c173852e09de0fccabe9adca795f0ffb 100644
--- a/Modules/Segmentation/Conversion/test/otbOGRDataSourceToLabelImageFilter.cxx
+++ b/Modules/Segmentation/Conversion/test/otbOGRDataSourceToLabelImageFilter.cxx
@@ -9,8 +9,6 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom; Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Segmentation/Conversion/test/otbPolygonizationRasterizationTest.cxx b/Modules/Segmentation/Conversion/test/otbPolygonizationRasterizationTest.cxx
index df6921448a8e451d49df493344143ac7f2416e32..abb25628684c026b0a46d7159d616c708d4bde15 100644
--- a/Modules/Segmentation/Conversion/test/otbPolygonizationRasterizationTest.cxx
+++ b/Modules/Segmentation/Conversion/test/otbPolygonizationRasterizationTest.cxx
@@ -9,8 +9,6 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom; Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Segmentation/Conversion/test/otbVectorDataRasterizeFilter.cxx b/Modules/Segmentation/Conversion/test/otbVectorDataRasterizeFilter.cxx
index 2e073dd958d0911abb49bfab8f73206e9c4bc2af..e9032ae96fbec36579f503d863cb68725287c528 100644
--- a/Modules/Segmentation/Conversion/test/otbVectorDataRasterizeFilter.cxx
+++ b/Modules/Segmentation/Conversion/test/otbVectorDataRasterizeFilter.cxx
@@ -9,8 +9,6 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom; Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Segmentation/Conversion/test/otbVectorDataToLabelImageFilter.cxx b/Modules/Segmentation/Conversion/test/otbVectorDataToLabelImageFilter.cxx
index 04619bd5a928dc2d70f5373dc5872c36f6ea7fd6..229b5b622f7681c485f51b1a81e719ae2511d8ba 100644
--- a/Modules/Segmentation/Conversion/test/otbVectorDataToLabelImageFilter.cxx
+++ b/Modules/Segmentation/Conversion/test/otbVectorDataToLabelImageFilter.cxx
@@ -9,8 +9,6 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom; Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/Modules/Segmentation/Conversion/test/otbVectorDataToLabelImageFilterWithoutReader.cxx b/Modules/Segmentation/Conversion/test/otbVectorDataToLabelImageFilterWithoutReader.cxx
index 4b00e88ba2ab3f103d9d629c5a064bd2c9da3e9c..8dd0bc3d5af301881a4f583a82fc306b82611a95 100644
--- a/Modules/Segmentation/Conversion/test/otbVectorDataToLabelImageFilterWithoutReader.cxx
+++ b/Modules/Segmentation/Conversion/test/otbVectorDataToLabelImageFilterWithoutReader.cxx
@@ -9,8 +9,6 @@
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
- Copyright (c) Institut Telecom; Telecom Bretagne. All rights reserved.
- See ITCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
diff --git a/SuperBuild/CMake/External_gdal.cmake b/SuperBuild/CMake/External_gdal.cmake
index a76075af1adfc2996686a606df020c750f99f151..61ce0d3b757c83b8f1755191f190832a650110ec 100644
--- a/SuperBuild/CMake/External_gdal.cmake
+++ b/SuperBuild/CMake/External_gdal.cmake
@@ -51,9 +51,9 @@ else()
INSTALL_DIR ${SB_INSTALL_PREFIX}
DOWNLOAD_DIR ${DOWNLOAD_LOCATION}
DEPENDS ${${proj}_DEPENDENCIES}
- UPDATE_COMMAND ${CMAKE_COMMAND} -E copy_directory ${GDAL_SB_SRC} ${GDAL_SB_BUILD_DIR}
- PATCH_COMMAND ${CMAKE_COMMAND} -E touch ${GDAL_SB_SRC}/config.rpath
- CONFIGURE_COMMAND
+ UPDATE_COMMAND ${CMAKE_COMMAND} -E copy_directory ${GDAL_SB_SRC} ${GDAL_SB_BUILD_DIR}
+ PATCH_COMMAND ${CMAKE_COMMAND} -E touch ${GDAL_SB_SRC}/config.rpath COMMAND ${CMAKE_COMMAND} -E copy ${CMAKE_SOURCE_DIR}/patches/GDAL/GNUmakefile ${GDAL_SB_SRC}/swig/python/GNUmakefile
+ CONFIGURE_COMMAND
# use 'env' because CTest launcher doesn't perform shell interpretation
${SB_ENV_CONFIGURE_CMD}
${GDAL_SB_BUILD_DIR}/configure
@@ -86,7 +86,7 @@ else()
INSTALL_DIR ${SB_INSTALL_PREFIX}
DOWNLOAD_DIR ${DOWNLOAD_LOCATION}
DEPENDS ${${proj}_DEPENDENCIES}
- PATCH_COMMAND ${CMAKE_COMMAND} -E copy_directory ${GDAL_SB_SRC} ${GDAL_SB_BUILD_DIR}
+ PATCH_COMMAND ${CMAKE_COMMAND} -E copy_directory ${GDAL_SB_SRC} ${GDAL_SB_BUILD_DIR} COMMAND ${CMAKE_COMMAND} -E copy ${CMAKE_SOURCE_DIR}/patches/GDAL/GNUmakefile ${GDAL_SB_SRC}/swig/python/GNUmakefile
CONFIGURE_COMMAND ${CMAKE_COMMAND} -E copy ${CMAKE_SOURCE_DIR}/patches/${proj}/ogrsqlitevirtualogr.cpp
${GDAL_SB_BUILD_DIR}/ogr/ogrsf_frmts/sqlite/ogrsqlitevirtualogr.cpp
BUILD_COMMAND nmake /f ${GDAL_SB_BUILD_DIR}/makefile.vc MSVC_VER=${MSVC_VERSION} EXT_NMAKE_OPT=${CMAKE_BINARY_DIR}/nmake_gdal_extra.opt
diff --git a/SuperBuild/patches/GDAL/GNUmakefile b/SuperBuild/patches/GDAL/GNUmakefile
new file mode 100644
index 0000000000000000000000000000000000000000..71f029d8726dbf9cda8644471ceee789f1e279cf
--- /dev/null
+++ b/SuperBuild/patches/GDAL/GNUmakefile
@@ -0,0 +1,95 @@
+
+
+include ../../GDALmake.opt
+
+ifndef PYTHON
+ PYTHON=python
+endif
+
+all: build
+
+BINDING = python
+include ../SWIGmake.base
+
+PACKAGE_DIR=osgeo
+SWIGOUTPUTDIR=extensions/
+
+SCRIPTS = `ls ./scripts`
+PY_COMMANDS = epsg_tr.py gdalchksum.py gdal2xyz.py gcps2wld.py \
+ gdalimport.py gdal_merge.py pct2rgb.py rgb2pct.py \
+ gcps2vec.py
+PY_MODULES = ${PACKAGE_DIR}/gdal.py ${PACKAGE_DIR}/ogr.py ${PACKAGE_DIR}/osr.py ${PACKAGE_DIR}/gdalconst.py ${PACKAGE_DIR}/gdal_array.py
+
+clean:
+ -rm -f ${PACKAGE_DIR}/*.pyc
+ -rm -rf build
+ -rm -f *.pyc
+ -rm -rf *.egg-info
+ -rm -f *.so ./osgeo/*.so
+ -rm -rf dist
+
+SWIGARGS += -outdir "${PACKAGE_DIR}"
+
+
+veryclean: clean
+ -rm -f ${WRAPPERS} ${PY_MODULES}
+ -rm -f ${SWIGOUTPUTDIR}/gdal_wrap.cpp
+ -rm -f ${SWIGOUTPUTDIR}/gdalconst_wrap.c
+ -rm -f ${SWIGOUTPUTDIR}/ogr_wrap.cpp
+ -rm -f ${SWIGOUTPUTDIR}/osr_wrap.cpp
+ -rm -f ${SWIGOUTPUTDIR}/gdal_array_wrap.cpp
+
+gdal_wrap.cpp: ../include/python/gdal_python.i
+
+ogr_wrap.cpp: ../include/python/ogr_python.i
+
+osr_wrap.cpp: ../include/python/osr_python.i
+
+gdal_array_wrap.cpp: ../include/gdal_array.i ../include/python/typemaps_python.i
+ $(SWIG) $(SWIGARGS) $(SWIGDEFINES) -I$(GDAL_ROOT) -c++ -$(BINDING) -o $(SWIGOUTPUTDIR)$@ gdal_array.i
+
+# A few hacks (cat, mv) : the first one for SWIG < 1.3.36 and the second one for SWIG <= 1.3.39 python 3.X on 64bit platforms
+# The python3.2.patch is from https://sourceforge.net/tracker/?func=detail&aid=3057804&group_id=1645&atid=101645
+# and is no longer necessary with swig 2.0.4
+generate: ${WRAPPERS} gdal_array_wrap.cpp
+ for i in gdal_wrap.cpp gdalconst_wrap.c ogr_wrap.cpp osr_wrap.cpp gdal_array_wrap.cpp; do sed "s/PyErr_Format(PyExc_RuntimeError, mesg)/PyErr_SetString(PyExc_RuntimeError, mesg)/" ${SWIGOUTPUTDIR}/$$i | sed "s/int len;/Py_ssize_t len;/" > ${SWIGOUTPUTDIR}/$$i.tmp; mv -f ${SWIGOUTPUTDIR}/$$i.tmp ${SWIGOUTPUTDIR}/$$i; done
+ -grep "1\.3\.40" extensions/gdal_wrap.cpp >/dev/null && patch -p0 < python3.2.patch
+ -grep "1\.3\.40" extensions/gdal_wrap.cpp >/dev/null && cat python3.2.patch | sed "s/gdal_wrap/ogr_wrap/" | patch -p0
+ -grep "1\.3\.40" extensions/gdal_wrap.cpp >/dev/null && cat python3.2.patch | sed "s/gdal_wrap/osr_wrap/" | patch -p0
+ -grep "1\.3\.40" extensions/gdal_wrap.cpp >/dev/null && cat python3.2.patch | sed "s/gdal_wrap\.cpp/gdalconst_wrap\.c/" | patch -p0
+ -grep "1\.3\.40" extensions/gdal_wrap.cpp >/dev/null && cat python3.2.patch | sed "s/gdal_wrap/gdal_array_wrap/" | patch -p0
+
+build:
+ $(PYTHON) setup.py build
+
+egg:
+ $(PYTHON) setup.py bdist_egg
+
+install:
+
+ifeq ($(PY_HAVE_SETUPTOOLS),1)
+ $(PYTHON) setup.py install --prefix=$(DESTDIR)$(prefix) --install-purelib=$(prefix)/lib --install-scripts=$(prefix)/bin --install-platlib=$(prefix)/lib
+else
+ $(PYTHON) setup.py install --prefix=$(DESTDIR)$(prefix)
+endif
+
+ for f in $(SCRIPTS) ; do $(INSTALL) ./scripts/$$f $(DESTDIR)$(INST_BIN) ; done
+
+docs:
+ $(PYTHON) ../include/python/docs/doxy2swig.py ../../ogr/xml/ogrlayer_8cpp.xml ../include/python/docs/ogr_layer_docs.i OGRLayerShadow OGR_L_
+
+ $(PYTHON) ../include/python/docs/doxy2swig.py ../../ogr/xml/ogrgeometry_8cpp.xml ../include/python/docs/ogr_geometry_docs.i OGRGeometryShadow OGR_G_
+
+ $(PYTHON) ../include/python/docs/doxy2swig.py ../../ogr/xml/ogrdatasource_8cpp.xml ../include/python/docs/ogr_datasource_docs.i OGRDataSourceShadow OGR_DS_
+
+
+ $(PYTHON) ../include/python/docs/doxy2swig.py ../../ogr/xml/ogrsfdriver_8cpp.xml ../include/python/docs/ogr_driver_docs.i OGRDriverShadow OGR_Dr_
+
+ $(PYTHON) ../include/python/docs/doxy2swig.py ../../ogr/xml/ogrfeature_8cpp.xml ../include/python/docs/ogr_feature_docs.i OGRFeatureShadow OGR_F_
+
+ $(PYTHON) ../include/python/docs/doxy2swig.py ../../ogr/xml/ogrfeaturedefn_8cpp.xml ../include/python/docs/ogr_featuredef_docs.i OGRFeatureDefnShadow OGR_FD_
+
+ $(PYTHON) ../include/python/docs/doxy2swig.py ../../ogr/xml/ogrfielddefn_8cpp.xml ../include/python/docs/ogr_fielddef_docs.i OGRFieldDefnShadow OGR_Fld_
+
+epydoc: generate
+ epydoc --config epydoc.conf
diff --git a/Utilities/Maintenance/SuperbuildDownloadList.sh b/Utilities/Maintenance/SuperbuildDownloadList.sh
index e0cc7033b1933fc5d8943747184a249d51d01f5c..2cb32210b12d8d28a5c985047956271ad4e970e2 100755
--- a/Utilities/Maintenance/SuperbuildDownloadList.sh
+++ b/Utilities/Maintenance/SuperbuildDownloadList.sh
@@ -1,2 +1,62 @@
#/bin/bash
-grep -h -E "^[^#]*\"https?://.*(\.tar\.gz|\.tar\.bz2|\.tgz|\.tar\.xz|\.zip|export=download).*\"" ../../SuperBuild/CMake/*.cmake | grep -o -E "https?://[^\"]*" | sed "s/\/download$//" | sort | uniq
+
+if [ $# -eq 2 ]; then
+DOWNLOAD_DIR=$(readlink -f $1)
+OUTPUT_DIR=$(readlink -f $2)
+else
+echo 'Usage: '$0' <download_directory> <archive_output_directory>'
+exit 1
+fi
+
+SB_CMAKE_DIR_REL=$(dirname $0)/../../SuperBuild/CMake
+SB_CMAKE_DIR=$(readlink -f ${SB_CMAKE_DIR_REL})
+
+DOWNLOAD_LIST=$(grep -h -E "^[^#]*\"https?://.*(\.tar\.gz|\.tar\.bz2|\.tgz|\.tar\.xz|\.zip|export=download).*\"" ${SB_CMAKE_DIR}/*.cmake | grep -o -E "https?://[^\"]*" | sed "s/\/\(download\)\?$//" | sort | uniq)
+
+DOWNLOAD_NAMES=
+
+mkdir -p ${DOWNLOAD_DIR}
+cd ${DOWNLOAD_DIR}
+
+echo "Start downloads..."
+
+for url in ${DOWNLOAD_LIST}; do
+ # clean log file
+ echo "" >download.log
+
+ file_name=$(echo "${url}" | grep -o -E "[^\/]+$")
+ docs_google=$(echo "${file_name}" | grep -F "export=download")
+ if [ "${docs_google}" = "" ]; then
+ echo "Download ${file_name}..."
+ wget -N ${url} -o download.log
+ else
+ # look into the original file for a valid download name
+ file_name=$(grep -h -A 3 -B 3 -F "${url}" ${SB_CMAKE_DIR}/*.cmake | grep -E "^[^#]*DOWNLOAD_NAME" | grep -o -E "[^ ]*\.(tar\.gz|tar\.bz2|tar\.xz|zip)" | uniq)
+ if [ -z "$file_name" ]; then
+ echo "Can't find correct filename for url ${url} : skip download"
+ else
+ echo "Download ${file_name}..."
+ wget -O ${file_name} ${url} -o download.log
+ fi
+ fi
+
+ download_errors=$(grep "ERROR" download.log)
+ if [ "$download_errors" != "" ]; then
+ echo "=== Error downloading ${file_name} ==="
+ cat download.log
+ else
+ if [ "$file_name" != "" ]; then
+ DOWNLOAD_NAMES="${DOWNLOAD_NAMES} ${file_name}"
+ fi
+ fi
+done
+
+rm download.log
+
+echo "Create archive..."
+
+cd ${OUTPUT_DIR}
+tar -cjf SuperBuild-archives.tar.bz2 -C ${DOWNLOAD_DIR} ${DOWNLOAD_NAMES}
+
+echo "Compute md5sum..."
+md5sum SuperBuild-archives.tar.bz2 >SuperBuild-archives.md5