# Lightweight Segmentation

A lightweight semantic segmentation model based on the Segformer architecture, pretrained on the ADE20K dataset

SlimSAM is an innovative SAM model compression method that efficiently reuses pre-trained SAM through a unified pruning-distillation framework, eliminating the need for extensive repeated training.

SlimSAM is a compressed version of the Segment Anything (SAM) model, significantly reducing parameters and computational requirements through pruning and distillation techniques while maintaining high-quality object segmentation capabilities.