This project demonstrates real-time edge AI video analytics on SiMa.ai Modalix hardware. It receives H.264 video over RTSP, decodes the stream, and runs a compiled YOLOv8n object-detection model on the Modalix MLA accelerator. The pipeline preserves a shared timeline between video and inference, ensuring detection metadata stays synchronized with the corresponding frames. Processed H.264 video and object-detection metadata are streamed to Neat Insight, where users can view live bounding boxes, COCO labels, confidence scores, and performance statistics in a browser. The application is configurable for model paths, source streams, thresholds, and Insight endpoints, and includes build, deployment, validation, and health-monitoring instructions for running the complete workflow on a Modalix DevKit.
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