Wrong input layer size in TrainImagesRegression using the ANN classifier
Description
This bug was reported by a user on the forum
The input layer of the output model produced TrainImagesRegression when using the artificial neural network classifier (ann) always has a size of 1, when it should match the number of bands of the input image. The training does not fail, and a mse is computed. However awhen trying to use the model with ImageRegression an error is thrown by OpenCV:
(FATAL) ImageRegression: itk::ERROR: MultiThreader(000001D5109CC040): Exception occurred during SingleMethodExecute OpenCV(4.1.1) C:\build\otb\build\OPENCV\src\OPENCV\modules\ml\src\ann_mlp.cpp:350: error: (-215:Assertion failed) (type == CV_32F || type == CV_64F) && inputs.cols == layer_sizes[0] in function ‘cv::ml::ANN_MLPImpl::predict’Note that training an artificial neural network model with TrainVectorRegression works correctly, so the problem is likely located in TrainImagesRegression. Also note that TrainImagesClassifier works correctly whn trying to train an artificial neural network for classification.
Steps to reproduce
otbcli_TrainImagesRegression -io.il input.tif -io.ip "predicted_values.tif" -io.out model.txt -classifier ann -classifier.ann.sizes 10
otbcli_ImageRegression -in input.tif -model model.txt -out out.tif leads to the following model :
%YAML:1.0
---
opencv_ml_ann_mlp:
format: 3
layer_sizes: [ 1, 10, 1 ]
[...]but the input image has 4 bands.
Configuration information
OTB 7.2, reproduced on Windows 10 and Ubuntu 16.04