Image Segmentation using SAM

This project explores Meta’s Segment Anything Model (SAM) for high-accuracy image segmentation. It automatically generates object masks from images without needing prior training on specific object classes.

Used for comparing segmentation performance across medical, natural, and industrial datasets, this project shows how SAM can be integrated into real-time systems like smart surveillance or object tracking.