Hi all, how to create image datasets. I need them to train neural networks. I have about 15 to 20 images and I need to turn these images into an image dataset. Please.
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Nurul Farhana Mohd Fadzli on 16 May 2022
Commented: yanqi liu on 20 May 2022
I have tried to find the way to build image dataset but all of the example are using Python. But i want to use Matlab. Please help me.
This is easy to do in MATLAB! You can put all your images into a folder and use the imageDatastore command.
Assuming the folder of images is on the path, here is an example:
imds = imageDatastore("name_of_image_folder");
What you do next depends on your application. In your original question, you asked what you need to make a dataset. The code I provided should be sufficient for that.
More Answers (1)
yes，sir，may be use cnn transfer to train model，such as
% use image folder to get dataset
imds = imageDatastore('MerchData','IncludeSubfolders',true,'LabelSource','foldernames');
[imdsTrain,imdsValidation] = splitEachLabel(imds,0.7,'randomized');
% use Alexnet to get cnn model
alex_net = alexnet;
class_number = length(unique(imds.Labels));
alex_net_share = alex_net.Layers(1:end-3);
alex_net_add = [
layers_1 = [alex_net_share
augimdsTrain = augmentedImageDatastore([227 227],imdsTrain);
augimdsValidation = augmentedImageDatastore([227 227],imdsValidation);
miniBatchSize = 10;
valFrequency = floor(numel(augimdsTrain.Files)/miniBatchSize);
options = trainingOptions('sgdm', ...
trainedNet = trainNetwork(augimdsTrain,layers_1,options);
[YPred,probs] = classify(trainedNet,augimdsValidation);
accuracy = mean(YPred == imdsValidation.Labels)
idx = randperm(numel(imdsValidation.Files),4);
for i = 1:4
I = readimage(imdsValidation,idx(i));
label = YPred(idx(i));
title(string(label) + ", " + num2str(100*max(probs(idx(i),:)),3) + "%");
yes，sir，let us check the folder MerchData，we can find that one subfolder is one class，so if use our data，we can just make a new subfolder， and use name as subfolder name
then put images in it，and run code
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