How do I use my trained CNN model to predict new pictures?

Hello there,

I created simple classification model using the following example:

https://www.mathworks.com/help/deeplearning/gs/create-simple-deep-learning-classification-network.html#CreateSimpleDeepLearningClassificationNetworkExample-4

and I got 91% accuracy, now I want to use this CNN model to try it on new images, 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('sgdm', ...
    'MaxEpochs',200, ...
    '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)

Answer 1

[Abhishek Gupta]

Hi,

As per my understanding, you want to make predictions for new input using your trained network. You can do the same using the 'predict()' function in MATLAB: -

predictions = predict(net,newImages);

For more information, check out the documentation here: -

https://www.mathworks.com/help/deeplearning/ref/seriesnetwork.predict.html