Getting error while running alexnet

Question

Tan 2023-5-14

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https://ww2.mathworks.cn/matlabcentral/answers/1962789-getting-error-while-running-alexnet

评论： Walter Roberson 2024-5-2

net =alexnet('Weights','none');
lys = net.Layers();
lys(end-3:end)

getting error:

Unrecognized method, property, or field 'Layers' for class 'nnet.cnn.layer.Layer'.

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Answer 1

Walter Roberson 2023-5-14

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https://ww2.mathworks.cn/matlabcentral/answers/1962789-getting-error-while-running-alexnet#answer_1234469

编辑：Walter Roberson 2023-5-14

When you call alexnet() with 'Weights', 'none' then the result you get back is a Layer array, not a DagNetwork or LayerGraph. The list of layers that you are trying to get is just the same as net itself in this case.

You need the .Layers() if you load in the regular pre-trained alexnet

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Tan 2023-5-14

编辑：Walter Roberson 2023-5-14

在 MATLAB Online 中打开

here is my full coding:

clc
clear all; 
close all;
outputFolder=fullfile('recycle101');
rootFolder=fullfile(outputFolder,'project');
categories={'aluminiumcan','petbottle','drinkcartonbox'};
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=='aluminiumcan',1);
PETBottles=find(imds.Labels=='petbottle',1);
DrinkCartonBox=find(imds.Labels=='drinkcartonbox',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=alexnet;
net =alexnet('Weights','none');
analyzeNetwork(net)
lys = net;
lys(end-3:end)
numClasses = numel(categories(imdsTrain.Labels));
lgraph = layerGraph(lys);
%Replace the classification layers for new task
newFCLayer = fullyConnectedLayer(3,'Name','new_fc','WeightLearnRateFactor',10,'BiasLearnRateFactor',10);
lgraph = replaceLayer(lgraph,'fc8',newFCLayer);
newClassLayer = classificationLayer('Name','new_classoutput');
lgraph = replaceLayer(lgraph,'output',newClassLayer);
%Resize the image
imageSize=lys(1).InputSize;
augmentedTrainingSet=augmentedImageDatastore(imageSize,...
    imdsTrain,'ColorPreprocessing','gray2rgb');
augmentedValidateSet=augmentedImageDatastore(imageSize,...
    imdsValidation,'ColorPreprocessing','gray2rgb');
options = trainingOptions('sgdm', ...
    'MiniBatchSize',4, ...
    'MaxEpochs',8, ...
    'InitialLearnRate',1e-4, ...
    'Shuffle','every-epoch', ...
    'ValidationData',augmentedValidateSet, ...
    'ValidationFrequency',3, ...
    'Verbose',false, ...
    'ExecutionEnvironment','cpu', ...
    'Plots','training-progress');
trainedNet = trainNetwork(augmentedTrainingSet,lgraph,options);
[YPred,probs] = classify(trainedNet,augmentedValidateSet,'ExecutionEnvironment', 'cpu');
YValidation = imdsValidation.Labels;
%Calculate accuracy,error,pecision and recall
accuracy = sum(YPred == YValidation)/numel(YValidation)
error=1-accuracy
confMat=confusionmat(YValidation ,YPred);
confMat=bsxfun(@rdivide,confMat,sum(confMat,2));
z=mean(diag(confMat))
cmt=confMat
sum_of_row= sum(cmt,2)
z=(diag(cmt));
precision = z./sum_of_row ;
overallprecision=mean(precision);
sum_of_column= sum(cmt,1)
recall=z./sum_of_column'
totalrecall=mean(recall);
f1=2*(overallprecision*totalrecall)/(overallprecision+totalrecall)
categories = {'aluminium can','PET bottle','drink carton box'}
label = categorical(categories)
cm  = confusionchart(cmt,label)
cm.RowSummary = 'row-normalized';
cm.ColumnSummary = 'column-normalized';
%%save Network
save simpleDL.mat trainedNet lgraph
%% Testing process
I = imread('plastic73.jpg');
ds=augmentedImageDatastore(imageSize,...
    I,'ColorPreprocessing','gray2rgb');
predictedLabel = trainedNet.classify(ds);
sprintf('The loaded image belongs to %s class', predictedLabel)

mukthi 2024-5-2

Even though showing error as unrecognised function or variable 'alexnet'

Walter Roberson 2024-5-2

@mukthi

"This function requires Deep Learning Toolbox™ Model for AlexNet Network support package. If this support package is not installed, the function provides a download link. Alternatively, see Deep Learning Toolbox Model for AlexNet Network."

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Getting error while running alexnet

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Getting error while running alexnet

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