lightly-ai/lightly

What it solves

LightlySSL is a computer vision framework designed to make self-supervised learning (SSL) more accessible and easier to implement. It provides a modular system for pre-training models on unlabeled data, reducing the reliance on large, manually labeled datasets for computer vision tasks.

How it works

The framework is built as a modular library in a PyTorch-like style, exposing low-level building blocks such as loss functions and model heads. It allows users to combine different backbone models with various SSL algorithms. It also supports distributed training via PyTorch Lightning to handle larger datasets and compute resources.

Who it’s for

It is intended for computer vision researchers and developers who want to implement and experiment with state-of-the-art self-supervised learning methods without building everything from scratch.

Highlights

• Extensive Model Support: Includes implementations of popular SSL models like MoCo, SimCLR, BYOL, DINO, MAE, and LeJEPA.
• Modular Design: Provides flexible building blocks for loss functions and model heads.
• Cusomization: Supports custom backbone models for pre-training.
• Integration: Fully compatible with PyTorch and PyTorch Lightning for scalable training.