How to Build a Background Removal Tool with Segment Anything & Vision Agents
Blog post from Stream
In the outlined process, a real-time background removal tool is developed using Vision Agents and Stream Video, capitalizing on models like SAM 2 and YOLO11n to handle person detection and segmentation. The approach involves a Python agent joining a Stream call as a participant to process video frames, allowing for a local preview with a virtual background while keeping the raw video intact for recordings. By utilizing a participant pattern, the solution circumvents the need for complex transport and codec handling, enabling seamless integration with Stream's server SDK. The system's architecture supports configurable settings for background customization and utilizes efficient processing techniques, such as morphological operations and Gaussian blur, to refine segmentation masks for a smooth compositing result. This setup allows for flexible adaptation to other real-time video processing tasks, demonstrating the potential of Vision Agents and Stream Video in enhancing video call experiences with minimal overhead.
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