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Multi-class multi-instance segmentation is the task of identifying masks for multiple object classes and multiple instances of the same class within an image. The Segment Anything Model (SAM) is a new foundation model designed for promptable multi-class multi-instance segmentation. SAM is able to segment objects in any image using a pre-defined point grid as an input prompt in the ``everything'' mode. However, out of the box SAM tends to output part or sub-part segmentation masks (under-segmentation) in different real-world applications.