Traffic-Sign-Detection-AI

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Traffic-Sign-Detection-AI

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AI-driven traffic sign detection and recognition system using YOLOv8 and a diverse dataset including Hong Kong traffic signs, designed for enhancing road safety and efficient traffic management.

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# Traffic Sign Detection AI

## Overview
This repository hosts the code and resources for an advanced AI-driven system developed for the detection and recognition of traffic signs. Our model leverages the YOLOv8 neural network architecture and is trained on a robust dataset from Mapillary, supplemented with local Hong Kong traffic sign images.

## Objectives
- Enhance the accuracy of traffic sign detection and recognition, ensuring real-time operation.
- Equip the system to handle diverse environmental conditions, with a focus on Hong Kong's unique traffic regulations and infrastructure.

## Methodology
1. **YOLOv8 Model**: Employing the YOLOv8 model for efficient and accurate real-time object detection.
2. **Dataset**: Utilizing a comprehensive dataset from Mapillary, enriched with local Hong Kong traffic sign images. 
3. **Training**: Conducting intensive training using an NVIDIA Geforce RTX 4080 graphics card.
4. **Deployment**: Implementing the model in a user-friendly web interface for real-time traffic sign detection.

## Findings & Results
- The system showed a high success rate in detecting standard traffic signs under typical conditions.
- Specific challenges were identified in recognizing unique Hong Kong-specific traffic signs and electronic displays.

## Team Members
- [Tony (hospotho)](https://github.com/hospotho)
- [Soman Fung (skytim12)](https://github.com/skytim12)
- [Flucus ~ NightSky (Flucus)](https://github.com/Flucus)
- [Chan Ka Wing (KelvinSloth)](https://github.com/KelvinSloth)

## References
- The training data can be accessed [here](https://znphp-my.sharepoint.com/personal/flucus_flucus_idv_hk/_layouts/15/onedrive.aspx?id=%2Fpersonal%2Fflucus%5Fflucus%5Fidv%5Fhk%2FDocuments%2FIT114105%2FSEM4%2FITP4514%2Fai%5Fassm%2Ezip&parent=%2Fpersonal%2Fflucus%5Fflucus%5Fidv%5Fhk%2FDocuments%2FIT114105%2FSEM4%2FITP4514&ga=1).

## License
This project is licensed under the terms of the Apache.

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