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classify an image?

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Tathva
Tathva on 15 May 2023
Edited: Tathva on 16 Jul 2023
. Thank you. help has been appreciated
  1 Comment
KSSV
KSSV on 15 May 2023
Save the net and use it. You need to provide inputs in the way you have trained.

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Answers (1)

Sandeep
Sandeep on 22 May 2023
Hi Tathva,
To use a trained neural network in MATLAB to classify a random image, you can use the classify function when you have your trained network stored in an appropriate variable. Assuming that you have your network stored in variable called net a sample implementation is given below,
% Load the pretrained network
load('network.mat');
% Load a random image to classify
im = imread('my_image.jpg');
% Resize the image to the same size as the training images
im = imresize(im,net.Layers(1).InputSize(1:2));
% Classify the image
label = classify(net,im);
% Display the predicted label
disp([char(label)]);
The image is resized to the same size that was used during training of the neural network. We use the classify function to classify the image, which returns the predicted label for the image.
For more insight about the classify function, refer the following documentation: Classify data using trained deep learning neural network

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