In computer vision, semantic segmentation is the task of classifying every pixel in an image with a class from a known set of labels such that pixels with the same label share certain characteristics. It generates a segmentation mask of the input images. For example, the following images show a segmentation mask of the cat label.

In November 2018, Amazon SageMaker announced the launch of the SageMaker semantic segmentation algorithm. With this algorithm, you can train your models with a public dataset or your own dataset. Popular image segmentation datasets include the Common Objects in Context (COCO) dataset and PASCAL Visual Object Classes (PASCAL VOC), but the classes of their labels are limited and you may want to train a model on target objects that aren’t included in the public datasets. In this case, you can use Amazon SageMaker Ground Truth to

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