How to solve this error: "Error using DAGNetwork/activations (line 245) Incorrectly defined MiniBatchable Datastore. Error in read method of C:\Program Files\MATL​AB\R2020b\​toolbox\ma​tlab\datas​toreio\+ma​tlab\+io\+​datastore\​@ImageData​store\read​.m"

8 ビュー (過去 30 日間)
Hi,
I have the following code to extract the features from certain layer of ResNet101 deep learning model. However, after training the network, I am unable to extract the features from the layer specified below.
imds=imageDatastore('C:\Users\Manisha\Test', 'IncludeSubfolders', true, 'LabelSource','foldernames'); % There are two subfolders
tbl = countEachLabel(imds);
minSetCount = min(tbl{:,2});
imds = splitEachLabel(imds, minSetCount, 'randomize');
tbl = countEachLabel(imds)
[imdsTrain, imdsTest] = splitEachLabel(imds, 0.75, 'randomize');
net = resnet101;
numClasses = numel(categories(imds.Labels));
lgraph = layerGraph(net);
newFCLayer = fullyConnectedLayer(numClasses,'Name','new_fc','WeightLearnRateFactor',15,'BiasLearnRateFactor',15);
lgraph = replaceLayer(lgraph,'fc1000',newFCLayer);
newClassLayer = classificationLayer('Name','new_classoutput');
lgraph = replaceLayer(lgraph,'ClassificationLayer_predictions',newClassLayer);
lgraph = replaceLayer(lgraph,'ClassificationLayer_fc1000',newClassLayer);
tbl1 = countEachLabel(imdsTrain)
tbl2 = countEachLabel(imdsTest)
inputSize = net.Layers(1).InputSize;
augimdsTrain = augmentedImageDatastore(inputSize(1:2),imdsTrain);%'DataAugmentation',imageAugmenter);
imageAugmenter = imageDataAugmenter('RandRotation',[-90,90])
augimdsTest = augmentedImageDatastore(inputSize(1:2),imdsTest, 'DataAugmentation',imageAugmenter);
options = trainingOptions('adam', ...
'ExecutionEnvironment','gpu',...
'MiniBatchSize',12, ...
'MaxEpochs',20, ...
'InitialLearnRate',1e-4, ...
'Shuffle','every-epoch', ...
'ValidationFrequency',10, ...
'Verbose',true, ...
'Plots','training-progress');
trainedNet = trainNetwork(augimdsTrain,lgraph,options);
featureLayer = 'pool5'
trainingFeatures = activations(trainedNet, augimdsTrain, featureLayer, ...
'MiniBatchSize', 12, 'OutputAs', 'rows'); % error in this line
label_train = [zeros(tbl1.Count(1),1); ones(tbl1.Count(1),1)];
testFeatures = activations(trainedNet, augimdsTest, featureLayer, ...
'MiniBatchSize', 12, 'OutputAs', 'rows');
label_test = [zeros(tbl2.Count(1),1); ones(tbl2.Count(2),1)];

回答 (1 件)

Madhav Thakker
Madhav Thakker 2021 年 5 月 18 日
Hi Manisha,
If you want your custom datastore to be MiniBatchable, the read function MUST output a 2 column table, as noted in this documentation link. https://in.mathworks.com/help/deeplearning/ug/develop-custom-mini-batch-datastore.html#mw_1fbbfc62-d6e2-4e7c-843f-67b467135050
Hope this helps.

カテゴリ

Help Center および File ExchangeImage Data Workflows についてさらに検索

製品


リリース

R2020b

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by