SSSegmenation: An Open Source Supervised Semantic Segmentation Toolbox Based on PyTorch

• URL: http://arxiv.org/abs/2305.17091v1
• Date: Fri, 26 May 2023 17:02:42 GMT
• Title: SSSegmenation: An Open Source Supervised Semantic Segmentation Toolbox Based on PyTorch
• Authors: Zhenchao Jin
• Abstract summary: SSSegmenation is an open source supervised semantic image segmentation toolbox based on PyTorch. It 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.
• Score: 1.52292571922932
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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}.

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