Deep Learning Toolbox Model for Inception-ResNet-v2 Network

Pretrained Inception-ResNet-v2 network model for image classification
2K Downloads
Updated 20 Mar 2024
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.
This mlpkginstall file is functional for R2017a and beyond. Use inceptionresnetv2 instead of imagePretrainedNetwork if using a release prior to R2024a.
Usage Example:
% Access the trained model
[net, classes] = imagePretrainedNetwork("inceptionresnetv2");
% 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 Inception-ResNet-v2
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 R2017b
Compatible with R2017b to R2024a
Platform Compatibility
Windows macOS (Apple silicon) macOS (Intel) Linux
Categories
Find more on Deep Learning Toolbox in Help Center and MATLAB Answers

Community Treasure Hunt

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

Start Hunting!