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Deep Learning Toolbox Model for SqueezeNet Network

Pretrained SqueezeNet model for image classification

38 Downloads

Updated 11 Sep 2019

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.

Usage Example:

net = squeezenet()
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(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
figure
imshow(I)
text(10, 20, char(label), 'Color', 'white' )

Comments and Ratings (7)

Awais Khan

James Ang, does your problem solved. if yes please me solution how you can install squeezenet because i am facing same problem

James Ang

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.

Hi,

I noticed an error when attempting to retrain the network.

Error using trainNetwork (line 150)
Invalid network.

Caused by:
Layer 'fire2-concat': Missing input. Each layer input must be connected to the output of another layer.
Detected missing inputs:
input 'in2'

Any suggestions in correting this issue?

Michael

jianY xu

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: xjy1236@sina.com
thank you very much!!

adel adel

MATLAB Release Compatibility
Created with R2018a
Compatible with R2018a to R2019b
Platform Compatibility
Windows macOS Linux