FluxML/Metalhead.jl

Computer vision models for Flux

55
/ 100
Established

This is for machine learning engineers and researchers who want to build and train computer vision models in Julia. It provides a collection of established neural network architectures, like ResNet and EfficientNet, that you can use as building blocks. You input your image datasets and these models help you train systems to recognize objects, classify images, or segment parts of an image.

349 stars.

Use this if you are a machine learning practitioner working with image data and the Flux.jl deep learning framework in Julia, and you need pre-defined, robust model architectures for tasks like image classification or segmentation.

Not ideal if you are not familiar with deep learning concepts, the Julia programming language, or the Flux.jl framework.

image-classification computer-vision deep-learning neural-networks image-segmentation
No Package No Dependents
Maintenance 6 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 23 / 25

How are scores calculated?

Stars

349

Forks

67

Language

Julia

License

Last pushed

Jan 05, 2026

Commits (30d)

0

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