- Call the images one by one
- Do resize
- Save in the different folder
Ho do I change my dataset of images to the same size?
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Hello everyone,
I'm building a CNN model, but first I would like to control the images saiz
since all the dataset images aize are 40*24*1 , and I would like to change it to like 100*60*1
How do I do that ?
this is my code:
clear;
clc;
outputFolder = fullfile("binary_dataset");
rootFolder = fullfile(outputFolder, "Categories");
categories = {'Anomaly','No-Anomaly'}; % names of the folders
imds = imageDatastore(fullfile(rootFolder,categories),'LabelSource','foldernames');
tbl = countEachLabel(imds);
[imdsTrain,imdsValidation] = splitEachLabel(imds, 0.8, 'randomize');
inputSize = [40 24 1];
numClasses = 2;
layers = [
imageInputLayer(inputSize)
convolution2dLayer(5,20,'Padding',1)
batchNormalizationLayer
reluLayer
maxPooling2dLayer(2,'Stride',2)
convolution2dLayer(5,20,'Padding',1)
batchNormalizationLayer
reluLayer
maxPooling2dLayer(2,'Stride',2)
convolution2dLayer(5,20,'Padding',1)
batchNormalizationLayer
reluLayer
maxPooling2dLayer(2,'Stride',2)
fullyConnectedLayer(numClasses)
softmaxLayer
classificationLayer];
options = trainingOptions('adam', ...
'MaxEpochs',1, ...
'ValidationData',imdsValidation, ...
'ValidationFrequency',30, ...
'Verbose',false, ...
'Plots','training-progress');
net = trainNetwork(imdsTrain,layers,options);
YPred = classify(net,imdsValidation);
YValidation = imdsValidation.Labels;
accuracy = mean(YPred == YValidation)
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KALYAN ACHARJYA
2021년 2월 18일
편집: KALYAN ACHARJYA
2021년 2월 18일
Steps:
Later use those folder images (resize images) in CNN
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