change 'classWeights' in unetLayers

Question

Marco Festugato 2019-9-16

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https://ww2.mathworks.cn/matlabcentral/answers/480648-change-classweights-in-unetlayers

评论： Timothy Lee 2020-6-8

Hello,

im using Unet to perform semantic segmentation (I want to segment liver metastasis). I want to weight 'more' the pixels of the metastasis respect to the background but I can't manage to do it...

Code for creating unet architecture:

lgraph = unetLayers(imageSize, numClasses, 'EncoderDepth', 4);

How can I change the 'classWeights' in lgraph.Layers(end).pixelClassificationLayer in order to do this??

If, for example, I do this:

lgraph.Layers(end).pixelClassificationLayer.classWeights = [2, 0.5];

I receive an error telling me that i have first to put the 'labels' to the 'classes' options in lgraph.Layers(end), but if i do this:

lgraph.Layers(end) = {'metastasis', 'background'};

I receive an error telling that that layer is in 'read only' mode....

Please im getting crazy...

Thanks in advance for any help!

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Answer 1

Raunak Gupta 2019-9-19

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https://ww2.mathworks.cn/matlabcentral/answers/480648-change-classweights-in-unetlayers#answer_392581

Hi,

The unetLayers object in MATLAB is in read only mode and we cannot change the properties of layers as such. You may remove the last layer which is the Segmentation-Layer and can add a new Segmentation-Layer with the properties that are mentioned. Following Code will help.

% Last Layer Name is 'Segmentation-Layer' 
% for checking layer name use :- lgraph.Layers 
lgraph = removeLayers(lgraph,'Segmentation-Layer'); 
layerlast = pixelClassificationLayer('Classes',{'metastatis','background'},'ClassWeights',[2,0.5],'Name','New_segmentation_Layer'); 
layer_to_add = [layerlast]; 
lgraph = addLayers(lgraph,layer_to_add); 

Reference to the functions that are used removeLayers, pixelClassificationLayer, addLayers.

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Marco Festugato 2019-9-19

It worked! Thank u so much :)

Timothy Lee 2020-6-8

By using pixelClassificationLayer with class weights, is this the same as implementing a custom weighted classification layer, as shown in this example:

https://de.mathworks.com/help/deeplearning/ug/create-custom-weighted-cross-entropy-classification-layer.html

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