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This project dynamically allocates traffic signal timings based on real-time vehicle count using a YOLOv5-based object detection model. The system adjusts signal duration to optimize traffic flow, reducing congestion and improving emergency vehicle response times.

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SHENIPRASHANTH/Traffic-Signal-Optimization-using-AI

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Traffic-Signal-Optimization-using-AI

This project dynamically allocates traffic signal timings based on real-time vehicle count using a YOLOv5-based object detection model. The system adjusts signal duration to optimize traffic flow, reducing congestion and improving emergency vehicle response times.

Setup

Clone the repository

git clone https://github.com/reyy/Traffic-SIH.git cd Traffic-SIH/smart

Create and activate a virtual environment

python -m venv venv source venv/bin/activate # On Windows: venv\Scripts\activate

Install dependencies

pip install -r requirements.txt

Run the application

python app.py

Installation Prerequisites

Python 3.7+ Pip Virtual environment (optional but recommended) PyTorch and dependencies for YOLOv5

About

This project dynamically allocates traffic signal timings based on real-time vehicle count using a YOLOv5-based object detection model. The system adjusts signal duration to optimize traffic flow, reducing congestion and improving emergency vehicle response times.

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