Not that instead of using output of one application as input. I used Baseline data of the first application as input of the second one. It does not strickly break the dependency between the tests but avoid to push new images to the OTB-Data repository.

ENH: Update the constructors of all the available classifiers with the OpenCV default parameters in TrainImagesClassifier

BUG: Inversion of parameters in the constructor of the GBT classifier in the TrainImagesClassifier application

TEST: Add tests of several classifiers for the OpenCV framework in the TrainImagesClassifier application

TEST: Add an otbConfusionMatrixConcatenateTest to merge several confusion matrices and measure parameters over the merged one

ENH: Replacing the 3 SVM classification applications to handle the OpenCV machine learning framework

ENH: Add measurements of the confusion matrix in the LOG of the otbComputeConfusionMatrix application

ENH: Removal of the numbers of reference and produced labels input parameters in the otbComputeConfusionMatrix application

ENH: Simplification of the computation of the belief functions of the complementary sets in otbDSFusionOfClassifiersImageFilter

ENH: Handling the extended headers of input confusion matrices files in otbDSFusionOfClassifiersImageFilterTest

ENH: Definition of a format for confusion matrix files in otbComputeConfusionMatrix and otbFusionOfClassifications applications