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

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Abdulaziz Alotaibi
Abdulaziz Alotaibi 2021-2-16
回答： Abhishek Gupta 2021-2-19
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)

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采纳的回答

Abhishek Gupta
Abhishek Gupta 2021-2-19
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

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