Cell contents assignment to a non-cell array object.

trainingFeatures=zeros(size(training,2)*training(1).Count,4680);
featureCount=1;
for i=1:size(training,2)
    for j=1:training(i).Count
        trainingFeatures{featureCount,:}=extractHOGFeatures(read(training(i),j));
        trainingLabel{featureCount}=training(i).Description;
        featureCount = featureCount + 1;
    end
    Index{i}=training(i).Description;
end

show's error on

"trainingFeatures{featureCount,:}=extractHOGFeatures(read(training(i),j));"

Answer 1

[James Tursa]

This line

trainingFeatures=zeros(etc);

means that trainingFeatures is a double class matrix.

But this line:

trainingFeatures{featureCount,:}=extractHOGFeatures(read(training(i),j));

treats it as a cell array because of the curly braces. Maybe this is what you intended:

trainingFeatures(featureCount,:)=extractHOGFeatures(read(training(i),j));

[Saira]

How to solve this error?

Error using categorical/subsasgn (line 84)

Cell contents assignment to a non-cell array object.

Error in Trainingcode (line 35)

trainingLabel{featureCount} = TrainingimgSets(i).Description;

Code:

trainingFeatures(featureCount,:) = Features;
trainingLabel{featureCount} = TrainingimgSets(i).Description;    
featureCount = featureCount + 1;
personIndex{i} = TrainingimgSets(i).Description;
%% CNN Classifier
layers = [
    fullyConnectedLayer(7)
    softmaxLayer
    classificationLayer];
options = trainingOptions('sgdm','MaxEpochs',20,'InitialLearnRate',1e-4,'Verbose',false);
trainingLabel = categorical(trainingLabel);
net = trainNetwork(trainingFeatures,trainingLabel,layers,options);

[Image Analyst]

Like it says, trainingLabel is not a cell array. How did you define it earlier? Did you do something like this

trainingLabel = cell(1,1);

or was it produced by a function that returns a cell array? I'm guessing not.

[Saira]

Thanks, this error has been resolved.

[Saira]

How to solve this error?

Error using trainNetwork>iAssertXAndYHaveSameNumberOfObservations (line 604)

X and Y must have the same number of observations.

Error in trainNetwork>iParseInput (line 336)

iAssertXAndYHaveSameNumberOfObservations( X, Y );

Error in trainNetwork (line 68)

[layers, opts, X, Y] = iParseInput(varargin{:});

Error in Trainingcode (line 57)

net = trainNetwork(trainingFeatures,trainingLabel,layers,options);