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Deep Learning Toolbox Model for ResNet-50 Network

Pretrained Resnet-50 network model for image classification

82 Downloads

Updated 16 Sep 2020

ResNet-50 is a pretrained model that has been trained on a subset of the ImageNet database and that won the ImageNet Large-Scale Visual Recognition Challenge (ILSVRC) competition in 2015. The model is trained on more than a million images, has 177 layers in total, corresponding to a 50 layer residual network, and can classify images into 1000 object categories (e.g. keyboard, mouse, pencil, and many animals).
Opening the resnet50.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 R2017b and beyond.
Usage Example:
% Access the trained model
net = resnet50();
% 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 Resnet-50
label = classify(net, I)
% Show the image and the classification results
figure
imshow(I)
text(10,20,char(label),'Color','white')

Comments and Ratings (30)

Nur Nafiiyah

Akhila Podupuganti

cannot install even though I'm trying to install from matlab add on explorer.

Divyanth L G

Fadi Alsuhimat

Hi, I'm using Matlab R2016a. Can you please send me a copy of this tool to karaklove@yahoo.com Thank you

rahimi rusland

hi, can you show how to calculate the accuracy for an image

Shengjiang Kong

It's very well !

Fan Zhang

Any one test it on imagenet validation set? I got 70% accuracy which is about 4-5% lower than keras report of pre-trained resnet50

HIgh Tech Man

Lao WuLve

NAVNISH GOEL

i have download this tool box, how to install for making data set.

Yu-Liang Chen

Garrick Liu

Hi there, I am currently using this architecture as part of my honours project to segment lungs in chest x-rays. However, a major issue I have now is that the images are of 1092x1920 size where as the ResNet can only take in 224 by 224. Would there be any way to get around with this?

Any help or advice would be very much appreciated!

Moe Moe Htay

ranheng ran

Azhar Imran

Azhar Imran

I need this Resnet-50 network for Matlab 2016-b.
Can you please suggest me any solution.

azharimran63@gmail.com

zhangshaungqing

owais muhammad

can to please tell me that how i can obtain its layer by layer code?

software

zhangshaungqing Thanks

zhangshaungqing

I used the following code to successfully train the resnet network without the problems mentioned above.
numClasses = numel(categories(imdsTrain.Labels));
lgraph = removeLayers(lgraph, {'fc1000','fc1000_softmax','ClassificationLayer_fc1000'});
newLayers = [
fullyConnectedLayer(numClasses,'Name','fc','WeightLearnRateFactor',10,'BiasLearnRateFactor',10)
softmaxLayer('Name','softmax')
classificationLayer('Name','classoutput')];
lgraph = addLayers(lgraph,newLayers);
lgraph = connectLayers(lgraph,'avg_pool','fc');

gong bangming

Huawei Tian

"I have the problem with the output of layer 12 is incompatible with the input expected by layer 13."

yes. I also have this problem

layersTransfer = net.Layers(1:end-3);
numClasses = numel(categories(trainingImages.Labels))
layers = [
layersTransfer
fullyConnectedLayer(numClasses,'WeightLearnRateFactor',20,'BiasLearnRateFactor',20)
softmaxLayer
classificationLayer];
netTransfer = trainNetwork(trainingImages,layers,options);

von carlos

dont work, ResNet-50 and i had the same problem of layer 12 is incompatible with layer 13

caesar

I had used ResNet-50 and i had the same problem of layer 12 is incompatible with layer 13 when trying o resume training from a saved checked point

KOSTADINKA Bizheva

Hanbin Zhang

"I have the problem with the output of layer 12 is incompatible with the input expected by layer 13."

yes. I also have this problem

Redha Almahdi

Hello,
I am trying to test the resnet 50 on Dataset consist of 1560 images. I have problem with the output of layer 12 is incompatible with the input expected by layer 13.

Any advice on how could I solve this problem is greatly appreciated

Dayou Jiang

NICE JOB!

cui

good!

adel adel

MATLAB Release Compatibility
Created with R2017b
Compatible with R2017b to R2020b
Platform Compatibility
Windows macOS Linux

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