Multi Camera Activity Analysis
Budget: $30 – $250 USD
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.
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.
Related categories:
Python
Machine Learning (ML)
C++ Programming
OpenCL
OpenCV
Computer Vision
Deep Learning
YOLO