Realtime Semantic Segmentation

We developed a real-time semantic segmentation models for identifying humans in video streams across web, Windows, and macOS. Designed a comprehensive library, abstracting complex tasks such as pre and post-processing and multithreading, allowing seamless client integration. This impactful project significantly enhanced the efficiency and ease of deploying advanced segmentation capabilities in diverse applications, without clients navigating the technical depths.