The-AI-Summer/self-attention-cv

Health v2 · maintenance only

Adoption not part of the score

1214 stars · 152 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A PyTorch library implementing various self-attention mechanisms and transformer building blocks for computer vision, including multi-head attention, axial attention, Vision Transformers, and TransUNet. It is pip-installable and built with einsum and einops.

Use cases

• implement vision transformer for image classification
• add self-attention blocks to a CNN in PyTorch
• build a TransUNet segmentation model
• learn how multi-head self-attention works with code
• use axial attention for image feature maps
• experiment with transformer encoder blocks in PyTorch

When to choose

• you need ready-made PyTorch implementations of vision attention modules
• you want a lightweight pip-installable library for ViT-style models
• you are studying or prototyping attention mechanisms for images

When to avoid

• you need production-grade, actively maintained transformer code
• you work in TensorFlow or JAX instead of PyTorch
• you need large-scale pretrained vision models rather than building blocks

Facets

library · maturity maintenance

machine-learning deep-learning image-processing deep-learning computer-vision machine-learning artificial-intelligence python cross-platform pytorch self-attention transformer vision-transformer einops attention-mechanism transunet axial-attention gpu

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