5
$\begingroup$

If we have a grayscale network ("Input" -> {1, Automatic, Automatic}), it can be applied on both gray and color image by:

ColorCombine[net/@ColorSeparate[img]]

But I want to turn this into an end-to-end network and that is easy to deploy.

So it should be adapted to the number of color channels.

We can find some equivalent layers for normal functions.

  • ColorSeparate: no such equivalent form
  • Map : NetMapOperator, it's a 4-tensor
  • ColorCombine : CatenateLayer[1]

So how do I build an external network to adapt to this?

$\endgroup$
2
$\begingroup$
ClearAll[net];
net[n_Integer] :=
 NetChain[
   {
    (* color separate *)
    ReplicateLayer[1],
    TransposeLayer[],

    (* map *)
    NetMapOperator[{ConvolutionLayer[32, {3, 3}]}],

    (* color combine *)
    FlattenLayer[1, "Input" -> {n, Automatic, Automatic, Automatic}]
    },
   "Input" -> {n, Automatic, Automatic}
   ] // NetInitialize
net[3]

enter image description here

Dimensions@net[3]@RandomReal[1, {3, 128, 128}]

{96, 126, 126}

Dimensions@net[1]@RandomReal[1, {1, 128, 128}]

{32, 126, 126}

$\endgroup$

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.