I am trying to deploy a siamese net with opencv. Basically, I understand as a siamese net, a net where I have two inputs, a sequential model and a concatenated output. Critically, both inputs share the same weights. The model looks like this:
in1, in2 => sequential => concatenate & dense
In Keras/Tensorflow this is no problem. I am even able to freeze and load the net in opencv, but when i try the forward pass, I get the following error:
/opencv/modules/dnn/src/dnn.cpp:418: error: (-215:Assertion failed) inputs.size() == requiredOutputs in function 'getMemoryShapes'
assuming my inputs are called L and R, i first set:
net.setInputsNames( std::vector<String>{ "L", "R" } );
and then,
net.setInput(inBlobL, "L" );
net.setInput(inBlobR, "R" );
I make sure to resize the input images properly. Does anyone have an idea whether what I am trying to do is possible at all?
Or do I have to find a workaround?