Real-time video anomaly detection with automated evidence alerts

Final recorded accuracy of 95.1% before delivery on the trained detection scope.

A Django web application that analyses webcam and uploaded video frame by frame with trained YOLO models, captures anomalies with timestamps and sends automated email alerts, with remote web access.

An applied computer-vision product for monitoring video sources and flagging anomalous events for human review. Detection scope is limited to the classes the model was trained on; this is anomaly detection, not a certified law-enforcement system.

Rolle: Machine-learning and web-application engineering