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Semantic segmentation plays a vital role in computer vision tasks, enablingprecise pixel-level understanding of images. In this paper, we present acomprehensive library for semantic segmentation, which contains implementationsof popular segmentation models like SegNet, FCN, UNet, and PSPNet. We alsoevaluate and compare these models on several datasets, offering researchers andpractitioners a powerful toolset for tackling diverse segmentation challenges.

Image Segmentation Keras : Implementation of Segnet, FCN, UNet, PSPNet and other models in Keras