  This paper presents SSSegmenation, which is an open source supervised
semantic image segmentation toolbox based on PyTorch. The design of this
toolbox is motivated by MMSegmentation while it is easier to use because of
fewer dependencies and achieves superior segmentation performance under a
comparable training and testing setup. Moreover, the toolbox also provides
plenty of trained weights for popular and contemporary semantic segmentation
methods, including Deeplab, PSPNet, OCRNet, MaskFormer, \emph{etc}. We expect
that this toolbox can contribute to the future development of semantic
segmentation. Codes and model zoos are available at
\href{https://github.com/SegmentationBLWX/sssegmentation/}{SSSegmenation}.
