SAM is a C++ image segmentation model built from scratch. It performs pixel-level segmentation on images, identifying object boundaries without requiring any additional code or annotations. Based on Meta's Segment Anything Model, SAM leverages a Transformer architecture for end-to-end image segmentation prediction. It offers a simple and easy-to-use C++ interface, supporting both command-line and graphical user interface modes. SAM efficiently runs on CPUs, boasting a compact model size while maintaining good segmentation accuracy. It's ideal for deploying and utilizing image segmentation models in resource-constrained embedded environments where high performance is required but GPUs are unavailable.