SAM.cpp
S
Sam.cpp
Overview :
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.
Target Users :
Sam is designed for image segmentation tasks in embedded environments like drones and autonomous vehicles, particularly when GPU and complex framework utilization is restricted. It can also serve as a tool for researchers to rapidly validate algorithm concepts.
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Use Cases
Using SAM's command line to perform segmentation prediction on an image file and output the resulting mask image
Integrating SAM into your own C++ project to implement image segmentation functionality through simple API calls
Deploying the SAM model on resource-constrained embedded devices like drones for real-time segmentation
Features
Transformer-based end-to-end image segmentation
No need for additional code or annotations
Simple and easy-to-use C++ interface
Support for command-line and graphical user interface
Efficient CPU inference implementation
Lightweight model
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