Varn1t/TraffiQ

Computer Vision pipeline that tracks vehicles and people in traffic footage and reports counts + congestion level.

🚀 Extract and analyze high-accuracy georeferenced vehicle trajectories from bird's-eye-view aerial video using computer vision and deep learning, for scalable urban traffic analysis.

Machine learning and Structure-from-Motion tools for estimating vehicle speed from imagery for traffic monitoring, road safety, and autonomous systems research.

Detect, count, and track truck traffic on any highway on Earth using nothing but free Sentinel-2 imagery and a browser.

Create a digital-twin style traffic visualization using only mp4 CCTV footage and its Google Maps location.

Traffic Monitor built with edge ML for object detection and radar for speed monitoring

Real-time lane and car detection system using YOLOv8 and OpenCV, with distance estimation for vehicles. Ideal for autonomous driving and traffic analysis.