I want to represent 128x128 images in a 1x64 vector, and for that I want to use autoencoders.
However, I dont want to build a classifier, I want to build an autoencoder to embedd images.
(I tried build my own autoencoder with CNNs without using the built in autoencoder functions but I can't get good results for some reason)
Following the example I created two autoencoders, and added another one of my own instead of the softmax output and trained them:
encoder1 : 128x128 ->256-> 128x128
encoder2 : 256->128->256
encoder3 : 128->64->128
But how do I combine them?
If I use the "stack" function on these encoders like in the example:
stackednet = stack(encoder1,encoder2,encoder3)
I get this transformation :
128x128 -> 256 -> 128 -> 64
but what I want is this:
128x128 -> 256 -> 128 -> 64 ->128 -> 256 -> 128x128
So basicaly I need to stack this:
stackednet = stack(encoder1-encoder,encoder2-encoder,encoder3-encoder,encoder3-decoder,encoder2-decoder,encoder1-decoder)
Is there a way to extract the encoder and the decoder parts from an Autoencoder object and then stack them?