Multi Camera Activity Analysis
Publicada el 2026-07-29
Descripción de la oferta
I’m building a real-time activity analysis pipeline that ingests live streams from well over ten IP cameras and flags everything that matters to my operations team. The focus is threefold: accurate people counting, reliable intrusion detection, and fluid crowd-movement analysis. At the core I expect a YOLO-based model (v5, v7 or v8—you can advise) running through OpenCV that can scale horizontally as additional RTSP streams come online. Low-latency processing, smart use of GPU resources, and clean separation between detection and business-logic layers are crucial because the system will eventually tie into an existing alert dashboard. Deliverables • End-to-end Python (or C++) code that connects to each camera, performs the detections described above, and outputs structured JSON or MQTT topics I can consume in my backend. • Simple CLI or minimal web UI to visual-debug results from any selected camera feed. • Setup guide covering environment, dependencies, and sample configuration for adding new cameras. • Short performance report demonstrating FPS, detection accuracy, and resource usage with at least ten concurrent streams. If you have prior benchmarks or repos that show similar high-camera-count deployments, that will help us get started faster.
Skills
Fuente original: freelancer