This repository provides a PyTorch extension toolkit for computer vision research, centered around the ResNeSt (Split-Attention Networks) architecture and semantic segmentation models. It includes specialized components such as the Encoding Layer and Synchronized BatchNorm, designed to improve feature representation and training efficiency for CV tasks. The toolkit offers pre-trained models for image classification and segmentation on benchmarks like ADE20K and PASCAL Context.