ResNet-18 is a convolutional neural network that is trained on more than a million images from the ImageNet database. As a result, the network has learned rich feature representations for a wide range of images. The network can classify images into 1000 object categories, such as keyboard, mouse, pencil, and many animals.
The network has an image input size of 224-by-224-by-3.
Usage This repository requires MATLAB (R2018b and above) and the Deep Learning Toolbox.
This repository provides three functions:
resnet18Layers: Creates an untrained network with the network architecture of ResNet-18 assembleResNet18: Creates a ResNet-18 network with weights trained on ImageNet data resnet18Example: Demonstrates how to classify an image using a trained ResNet-18 network To construct an untrained ResNet-18 network to train from scratch, type the following at the MATLAB command line:
lgraph = resnet18Layers; The untrained network is returned as a layerGraph object.
To construct a trained ResNet-18 network suitable for use in image classification, type the following at the MATLAB command line:
net = assembleResNet18; The trained network is returned as a DAGNetwork object.
To classify an image with the network:
img = imresize(imread("peppers.png"),[224 224]); predLabel = classify(net, img); imshow(img); title(string(predLabel)); Documentation For more information about the ResNet-18 pre-trained model, see the resnet18 function page in the MATLAB Deep Learning Toolbox documentation. ResNet-18 in MATLAB This repository demonstrates the construction of a residual deep neural network from scratch in MATLAB. You can use the code in this repository as a foundation for building residual networks with different numbers of residual blocks.
You can also create a trained ResNet-18 network from inside MATLAB by installing the Deep Learning Toolbox Model for ResNet-18 Network support package. Type resnet18 at the command line. If the Deep Learning Toolbox Model for ResNet-18 Network support package is not installed, then the function provides a link to the required support package in the Add-On Explorer. To install the support package, click the link, and then click Install.
Alternatively, you can download the ResNet-18 pre-trained model from the MathWorks File Exchange, at Deep Learning Toolbox Model for ResNet-18 Network.
You can create an untrained ResNet-18 network from inside MATLAB by importing a trained ResNet-18 network into the Deep Network Designer App and selecting Export > Generate Code. The exported code will generate an untrained network with the network architecture of ResNet-18.