Deep Learning Toolbox Model for VGG-16 Network

by MathWorks Deep Learning Toolbox Team
Pretrained VGG-16 network model for image classification
3.0
(21)
9.3K Downloads
Updated 20 Mar 2024
VGG-16 is a pretrained Convolutional Neural Network (CNN) that has been trained on approximately 1.2 million images from the ImageNet Dataset (http://image-net.org/index) by the Visual Geometry Group at University of Oxford (http://www.robots.ox.ac.uk/~vgg/research/very_deep/).
The model has 16 layers and can classify images into 1000 object categories (e.g. keyboard, mouse, coffee mug, pencil).
Opening the vgg16.mlpkginstall file from your operating system or from within MATLAB will initiate the installation process for the release you have.
This mlpkginstall file is functional for R2017a and beyond. Use vgg16 instead of imagePretrainedNetwork if using a release prior to R2024a.
Usage Example:
% Access the trained model
[net, classes] = imagePretrainedNetwork("vgg16");
% See details of the architecture
net.Layers
% Read the image to classify
I = imread('peppers.png');
% Adjust size of the image
sz = net.Layers(1).InputSize
I = I(1:sz(1),1:sz(2),1:sz(3));
% Classify the image using VGG-16
scores = predict(net, single(I));
label = scores2label(scores, classes)
% Show the image and the classification results
figure
imshow(I)
text(10,20,char(label),'Color','white')
MATLAB Release Compatibility
Created with R2017a
Compatible with R2017a to R2024a
Platform Compatibility
Windows macOS (Apple silicon) macOS (Intel) Linux
Categories
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