In this workshop Chris Hoge, Head of Community for Label Studio, will demonstrate how to use Meta's Segment Anything Model to accelerate your image annotation workflow using Label Studio. Image segmentation is one of the most time-consuming types of annotation tasks that an annotation team can take on. By using ML-assisted segmentation, you can increase your annotation speed by 10x to 100x, freeing your labeling team to focus on tasks requiring human expertise and leaving the mundane work to AI systems. We will cover the basics of image segmentation, why the Segment Anything Model (SAM) has become one of the most important foundation models for generating image masks, and how to combine the open source annotation workflow of Label Studio with SAM using the Label Studio Machine Learning Backend.
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