Error using layerGraph (line 48) The value of 'Layers' is invalid. Layers must be an array of layers.

Question

TAN HOR YAN 2021-12-15

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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/1611225-error-using-layergraph-line-48-the-value-of-layers-is-invalid-layers-must-be-an-array-of-layers

回答： yanqi liu 2021-12-16

采纳的回答： yanqi liu

clc

clear all

outputFolder=fullfile('recycle101');

rootFolder=fullfile(outputFolder,'recycle');

categories={'Aluminium Can','PET Bottles','Drink Carton Box'};

imds=imageDatastore(fullfile(rootFolder,categories),'LabelSource','foldernames');

tbl=countEachLabel(imds)

minSetCount=min(tbl{:,2});

[imdsTrain,imdsValidation] = splitEachLabel(imds,0.7,'randomized');

countEachLabel(imds);

%randomly choose file for aluminium can, PET bottles, and drink carton box

AluminiumCan=find(imds.Labels=='Aluminium Can',1);

PETBottles=find(imds.Labels=='PET Bottles',1);

DrinkCartonBox=find(imds.Labels=='Drink Carton Box',1);

%plot image that was pick randomly

figure

subplot(2,2,1);

imshow(readimage(imds,AluminiumCan));

subplot(2,2,2);

imshow(readimage(imds,PETBottles));

subplot(2,2,3);

imshow(readimage(imds,DrinkCartonBox));

%Load pre-trained network

net = resnet50;

analyzeNetwork(net)

net = resnet50('Weights','none');

lys = net.Layers;

lys(end-3:end)

numClasses = numel(categories(imdsTrain.Labels));

lgraph = layerGraph(net);

%Replace the classification layers for new task

newFCLayer = fullyConnectedLayer(3,'Name','new_fc','WeightLearnRateFactor',10,'BiasLearnRateFactor',10);

lgraph = replaceLayer(lgraph,'fc1000',newFCLayer);

newClassLayer = classificationLayer('Name','new_classoutput');

lgraph = replaceLayer(lgraph,'ClassificationLayer_fc1000',newClassLayer);

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Answer 1

yanqi liu 2021-12-16

1
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/1611225-error-using-layergraph-line-48-the-value-of-layers-is-invalid-layers-must-be-an-array-of-layers#answer_856170

在 MATLAB Online 中打开

yes，sir，may be change the net definition，such as

%Load pre-trained network
net = resnet50;
%analyzeNetwork(net)
%net = resnet50('Weights','none');
%lys = net.Layers;
%lys(end-3:end)
numClasses = numel(categories(imdsTrain.Labels));
lgraph = layerGraph(net);
%Replace the classification layers for new task
newFCLayer = fullyConnectedLayer(numClasses,'Name','new_fc','WeightLearnRateFactor',10,'BiasLearnRateFactor',10);
lgraph = replaceLayer(lgraph,'fc1000',newFCLayer);
newClassLayer = classificationLayer('Name','new_classoutput');
lgraph = replaceLayer(lgraph,'ClassificationLayer_fc1000',newClassLayer);
analyzeNetwork(lgraph)