Classify a Photo Using ResNet-50 and MATLAB Online

MATLAB is a powerful tool for technical computing and data analysis. It is widely used in a variety of fields such as engineering, finance, and science. One of the strengths of MATLAB is its ability to work with images and perform image processing tasks.

Most people experienced MATLAB on their PC, but you can also access MATLAB in your browser with MATLAB Online. MATLAB Online is a web-based version of MATLAB that allows users to access the software and its features through a web browser. It eliminates the need to install and configure the software on a local computer, making it accessible from anywhere with an internet connection.

In this project, I will be using MATLAB Online to take a picture with a webcam, classify the image using a pre-trained deep learning model, and display the results.

MATLAB Online Selfie

I selected the ResNet-50 model, which is a deep convolutional neural network (CNN) trained on the ImageNet dataset. ResNet-50 stands for “Residual Network with 50 layers” and was developed by Microsoft Research in 2015. The architecture is known for its ability to train very deep neural networks without the problem of vanishing gradients, which allows for improved performance on image classification tasks. The model is capable of identifying objects in images and classifying them into one of 1000 different categories.

% Connect to webcam
cam = webcam;

% Take a picture
img = snapshot(cam);

% Resize image to [224 224 3]
img = imresize(img, [224 224]);

% Display the picture

% Load pretrained model
net = resnet50;

% Classify image
label = classify(net, img);

% Display label

% Release webcam
clear cam;

What’s really neat is that MATLAB Online can use your webcam. This code takes a photo, resizes it for ResNet-50, shows the output, and classifies the photo.

Old A.I. Thinks My Phone is an iPod

Check out MATLAB Online and run the very latest version of MATLAB and select toolboxes. Everyone should be able to try this project out and get started with image classification.

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