File Exchange

image thumbnail

Deep Learning Toolbox Model for Inception-ResNet-v2 Network

Pretrained Inception-ResNet-v2 network model for image classification


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()

% 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
text(10, 20, char(label), 'Color', 'white' )

Comments and Ratings (9)

hawwei Yang

I am using Matlab R2020a, would you please send me a copy of the Inception-ResNet-v2 Network installation zip file to


lgraph = layerGraph(net); % net.Layers -> net


this model gives me many size errors although the model scales the input data itself.

xuan hau nguyen

do you have some example for transfer learning this model ?

Arjun Desai

I am using this architecture for purely feature extraction (i.e. no testing). How do we subtract the average Image from the net to normalize our input images?

Hi Nicola, We are sorry for the inconvenience. The support for R2018a version will be made available very soon.

Nicola Franzoso

Hi, on matlab r2018a - windows server 2016, it's not possible to install it.
Add-On Manager show me a message: The support package is not compatible with your version of MATLAB or operating system.
Work only with r2017b?

Domonkos Varga

adel adel

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

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!