Getting the output from intermediate layers in the mobilenetv2 network

[letdivedeep]

@hollance

I am trying to get the intermediate layer(add_node) output and merge it into the existing model outputs (confidences and coordinates)

Experiments :

• Was able to get the add output from the ssd model, also passed this output as an input to decode model stage where i just add a dummy permute node.
• In the NMS model, it has a fixed set of inputs and outputs set by (confidenceInputFeatureName, confidenceOutputFeatureName ..etc) didn't find anything to forcefully create a new input as its set by the NMS_suppression.proto file
• So thought of creating a new model part that takes input as the NMS outputs(confidences and coordinates) and the previous decode layer add_output.

with this the coreml model is created as attached below.

But while loading it on through python it gives

an error saying:
RuntimeWarning: You will not be able to run predict() on this Core ML model. Underlying exception message was: Error compiling model: "Error reading protobuf spec. validator error: Pipeline: Input 'confidence' of model 'CoreML.Specification.ModelDescription' does not match the type previously specified by the pipeline input or the output of a previous model.".

I am assuming this error is prompted bcoz the new model created is taking the input, not from the intermediate layer. Can we add a dummy node in the NMS model to bypass this ... any thoughts on this will be helpful or even is this the correct way of doing it.

I have attached the coreml and convert pythod code used

Archive.zip

[hollance]

You don't need to make another model. It should be sufficient to just create a new output on the SSD model, then make an output with the same name in the pipeline model. You don't need to pass this output through the other models.

[letdivedeep]

Kudos

@hollance. Thanks for your reply.

I tried the above approach, it worked.