Deep Learning Toolbox Model for Inception-ResNet-v2 Network

Pretrained Inception-ResNet-v2 network model for image classification

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' )