🚦 TrafficVision: AI-Powered Traffic Density Detection

TrafficVision is an AI-based traffic monitoring system that uses OpenCV and Deep Learning to analyze video footage and detect vehicles in real time. This project leverages a pre-trained SSD MobileNet model to count vehicles and estimate traffic density.

🔹 Features

✅ Real-time Object Detection – Identifies cars, trucks, motorcycles, and bicycles
✅ Traffic Density Analysis – Estimates road congestion levels
✅ Video Processing & Visualization – Draws bounding boxes and labels detected vehicles
✅ Automatic Video Output Saving – Stores processed footage with detected objects

🔧 Technologies Used

• Python
• OpenCV (Computer Vision)
• Deep Learning (SSD MobileNet)
• NumPy & Matplotlib (for additional analysis if needed)

📌 How to Use

1. Clone this repository:

   git clone https://github.com/prajesdas/TrafficVision.git
   cd TrafficVision

2. Install dependencies:

   pip install opencv-python numpy

3. Run the script:

   python traffic_detection.py

📺 Demo

https://drive.google.com/file/d/1ViPx_Tp5F1ZEoWR5Q7-9bdpkH2xaN38g/view?usp=sharing

🚀 Future Enhancements

🔹 Integrate YOLOv8 for better accuracy
🔹 Add Real-time Live Camera Support
🔹 Implement Traffic Flow Prediction Models

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