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Deep Learning Toolbox Model for Inception-ResNet-v2 Network

Pretrained Inception-ResNet-v2 network model for image classification

1.2K Downloads

Updated 10 Mar 2021

Inception-ResNet-v2 is a pretrained model that has been trained on a subset of the ImageNet database. The model is trained on more than a million images, has 825 layers in total, and can classify images into 1000 object categories (e.g. keyboard, mouse, pencil, and many animals).
Opening the inceptionresnetv2.mlpkginstall file from your operating system or from within MATLAB will initiate the installation process for the release you have.
Usage Example:
net = inceptionresnetv2()
net.Layers
plot(net)

% Read the image to classify
I = imread('peppers.png');

% Crop image to the input size of the network
sz = net.Layers(1).InputSize
I = I(1:sz(1), 1:sz(2), 1:sz(3));

% Classify the image using Inception-ResNet-v2
label = classify(net, I)

% Show the image and classification result
figure
imshow(I)
text(10, 20, char(label), 'Color', 'white' )

MATLAB Release Compatibility
Created with R2017b
Compatible with R2017b to R2021a
Platform Compatibility
Windows macOS Linux

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