Error using nnet.cnn.L​ayerGraph>​iValidateL​ayerName (line 654) Layer 'Classific​ationLayer​_predictio​ns' does not exist. Error in nnet.cnn.L​ayerGraph/​replaceLay​er (line 397)

2021 12 15
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更新时间：2021 12 16
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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)
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_predictions',newClassLayer);

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 采纳的回答

yanqi liu
yanqi liu 2021-12-15

1 个投票

may be use
lgraph = replaceLayer(lgraph,'ClassificationLayer_fc1000',newClassLayer);

6 个评论
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TAN HOR YAN
TAN HOR YAN 2021-12-15
Owhh is works!!
Thank you so much!
May I know what is the different between ClassificationLayer_fc1000 and ClassificationLayer_predictions?
yanqi liu
yanqi liu 2021-12-15
Ran in:
Ran in:
yes，sir，when we see the layers，we can find the Classification Output name，such as
net = resnet50('Weights','none');
lys = net.Layers;
lys(end-3:end)
ans =
4×1 Layer array with layers: 1 'avg_pool' 2-D Global Average Pooling 2-D global average pooling 2 'fc1000' Fully Connected 1000 fully connected layer 3 'fc1000_softmax' Softmax softmax 4 'ClassificationLayer_fc1000' Classification Output crossentropyex
TAN HOR YAN
TAN HOR YAN 2021-12-15
Can I email my coding for you to check and give me some advice?
yanqi liu
yanqi liu 2021-12-16
yes，sir，may be send me the file and some information to do analysis，the email address is
cvdeeplearning@qq.com

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