This project provides concise, modifiable implementations of semantic segmentation models using PyTorch, including FCN, PSPNet, Deeplabv3, Deeplabv3+, DANet, DenseASPP, BiSeNet, and other architectures. It offers training, evaluation, and demo scripts for single and multi-GPU setups with support for common datasets like Pascal VOC. Users can quickly train models by specifying model type, backbone, dataset, learning rate, and epochs.