turning traffic management thriught ai

computer vision–based traffic analytics system that transforms raw traffic video streams into meaningful real-time insights using YOLO (You Only Look Once), a state-of-the-art object detection model.

Key Features Implemented

🔹 Real-Time Vehicle Detection & Classification
Developed a system capable of detecting and classifying multiple vehicle categories such as cars, trucks, buses, and motorcycles from live and recorded video streams.
Used pretrained YOLO models to achieve fast, accurate, and efficient inference suitable for real-time applications.

🔹 Vehicle Tracking & Intelligent Counting
Integrated object tracking to assign a unique ID to every detected vehicle across frames.
Implemented a virtual counting line mechanism to monitor vehicle movement and calculate traffic flow accurately.
Designed tracking-based counting logic to prevent duplicate counts even in dense traffic conditions.

🔹 Handling Real-World Traffic Challenges
Addressed practical challenges such as vehicle occlusion, overlapping objects, motion blur, and varying traffic density.
Improved system stability and tracking consistency to maintain reliable performance in crowded traffic scenarios.

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