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Metalhead

Dev CI Coverage

Metalhead.jl provides standard machine learning vision models for use with Flux.jl. The architectures in this package make use of pure Flux layers, and they represent the best-practices for creating modules like residual blocks, inception blocks, etc. in Flux. Metalhead also provides some building blocks for more complex models in the Layers module.

Installation

julia> ]add Metalhead

Getting Started

You can find the Metalhead.jl getting started guide here.

Available models

To contribute new models, see our contributing docs.

Image Classification

Model Name Constructor Pre-trained?
AlexNet AlexNet N
ConvMixer ConvMixer N
ConvNeXt ConvNeXt N
DenseNet DenseNet N
EfficientNet EfficientNet N
EfficientNetv2 EfficientNetv2 N
gMLP gMLP N
GoogLeNet GoogLeNet N
Inception-v3 Inceptionv3 N
Inception-v4 Inceptionv4 N
InceptionResNet-v2 InceptionResNetv2 N
MLPMixer MLPMixer N
MobileNetv1 MobileNetv1 N
MobileNetv2 MobileNetv2 N
MobileNetv3 MobileNetv3 N
MNASNet MNASNet N
ResMLP ResMLP N
ResNet ResNet Y
ResNeXt ResNeXt Y
SqueezeNet SqueezeNet Y
Xception Xception N
WideResNet WideResNet Y
VGG VGG Y
Vision Transformer ViT Y

Other Models

Model Name Constructor Pre-trained?
UNet UNet N