The SqueezeNet pretrained model for image classification is a part of the Deep Learning Toolbox in R2020a and does not require a separate installation. If you are using the R2020a version of the Deep Learning Toolbox, you can type ‘squeezenet’ in the command line or access the model directly without installation from the Deep Network Designer App.
If you are using R2018a to R2019b, you'll need to download and install this support package.
SqueezeNet 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, and can classify images into 1000 object categories (e.g. keyboard, mouse, pencil, and many animals).
Opening the squeezenet.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 R2018a and beyond.
net = squeezenet()
% 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(100:sz(1)+99, 100:sz(2)+99, 1:sz(3));
% Classify the image using SqueezeNet
label = classify(net, I)
% Show the image and classification result
text(10, 20, char(label), 'Color', 'white' )
James Ang, does your problem solved. if yes please me solution how you can install squeezenet because i am facing same problem
hi guys I've problem installing this network. In add-on manager it says it's sucessfully installed but I kept getting the error below. Any ideas? many thanks in advance.
>> net = squeezenet
Error using squeezenet (line 51)
squeezenet requires the Deep Learning Toolbox Model for SqueezeNet Network support package. To install this support package, use
the Add-On Explorer.
I noticed an error when attempting to retrain the network.
Error using trainNetwork (line 150)
Layer 'fire2-concat': Missing input. Each layer input must be connected to the output of another layer.
Detected missing inputs:
Any suggestions in correting this issue?
I want to create a special layer to add some special noise to the data. But my matlab version is 2017b, I don't have the example " gaussianNoiseLayer.m". That file should be located at (matlabroot, 'examples', 'nnet', 'main', 'gaussianNoiseLayer.m') in the matlab 2018b version.
I really want to know the coding structure of adding noise layer. If any kind-hearted person has installed the latest version of matlab, can you send a copy of this file to me? email: email@example.com
thank you very much！！
Find the treasures in MATLAB Central and discover how the community can help you!Start Hunting!