hi i export alexnet from matlab with onnx , but i dont have same features at layers so i checked the average image.
as i see there is issue with the average image.
i tried to import the network to c++(it passed some process use python cntk to dnn) and tested with all inputs zeros but i see with subtruction layer we have not same average image !
% convnet is alexnet
while in c++ output of layer data_Sub (first subtruction layer) . when all inputs are zero i suppose it should be the negative of the average .
i also check the channels and the values if there was some mix in rgb or some rotation but there is nothing clear here.
also as i see with other frameworks( tensorflow ..) and other netwroks vgg,googlnet
there is diffrence in implementation of the deep learning net . so i dont see way to have same featurs in matlab and python and c++ . only to retrain on the images in python or c++ .