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Metalhead

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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

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Computer vision models for Flux

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