I am doing CNN image classification, but i keep getting this error ; Error using trainNetwork Unexpected input size: All observations must have the same channel and spatial Di
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outputFolder=fullfile('seaTech');
rootFolder=fullfile(outputFolder,'seacreaturesDataset');
categories={'Crab','Shark','Starfish','Turtle','Octopus'};
imds=imageDatastore(fullfile(rootFolder,categories),'LabelSource','foldernames');
tbl=countEachLabel(imds)
figure;
perm = randperm(500,20);
for i = 1:20
subplot(4,5,i);
imshow(imds.Files{perm(i)});
end
img = readimage(imds,1);
size(img)
numTrainFiles = 75;
[imdsTrain,imdsValidation] = splitEachLabel(imds,numTrainFiles,'randomize');
layers = [
imageInputLayer([100 100 3])
convolution2dLayer(3,8,'Padding','same')
batchNormalizationLayer
reluLayer
maxPooling2dLayer(1,'Stride',1)
convolution2dLayer(3,16,'Padding','same')
batchNormalizationLayer
reluLayer
maxPooling2dLayer(1,'Stride',1)
convolution2dLayer(3,32,'Padding','same')
batchNormalizationLayer
reluLayer
fullyConnectedLayer(5)
softmaxLayer
classificationLayer];
options = trainingOptions('sgdm', ...
'InitialLearnRate',0.01, ...
'MaxEpochs',4, ...
'Shuffle','every-epoch', ...
'ValidationData',imdsValidation, ...
'ValidationFrequency',30, ...
'Verbose',false, ...
'Plots','training-progress');
net = trainNetwork(imdsTrain,layers,options)
2 Comments
KSSV
on 23 Jan 2023
What are the dimensions of your input images? They all should be of same size. If not consdier getting them into same size using imresize
Answers (1)
TED MOSBY
on 15 Nov 2024
Edited: TED MOSBY
on 18 Nov 2024
The error means that there might be inconsistencies in the dimensions or channels of the images within your‘imageDatastore’. Even though you resized the images to[100 100], there can be differences in the number of channels (e.g., some images might be grayscale with a single channel, while others are RGB with three channels).
For that you can:
Ensure All Images Have 3 Channels:
for i = 1:size(d)
I = imread(fullfile(f, d(i,:)));
I = imresize(I, [100 100]);
if size(I, 3) == 1
I = cat(3, I, I, I); % Convert grayscale to RGB
end
imwrite(I, fullfile('NewShark', strcat(num2str(i), '.png')));
Verify All Images in the Datastore:
for i = 1:numel(imds.Files)
img = readimage(imds, i);
if size(img, 1) ~= 100 || size(img, 2) ~= 100 || size(img, 3) ~= 3
error('Image %d does not match the required size or channel count.', i);
end
end
Update the ImageDatastore:
imds = imageDatastore(fullfile(rootFolder, categories), 'LabelSource', 'foldernames');
Hope this helps!
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