Real-Time-Traffic-Sign-Detection

This project utilizes the YOLOv8 model for real-time traffic sign detection, classification, and segmentation.

📁 About Dataset

• train/images/: Directory containing training images.
• train/labels/: Directory containing annotation labels for the training images.
• data.yaml: Configuration file for the YOLOv8 training data.

🛠️ Getting Started

Follow these steps to set up and run the project on your local machine.

Prerequisites

Make sure you have Python 3.7+ and Jupyter installed. You can check your Python version with:

python --version

To install Jupyter, run:

pip install notebook

Installation

Install the required dependencies:

1. Clone the repository:

   git clone https://github.com/ganayasser/Real-Time-Traffic-Sign-Detection.git
   cd Real-Time-Traffic-Sign-Detection

2. Install the required dependencies using the requirements.txt file:

   pip install -r requirements.txt

📝Running the Notebook

1. Start Jupyter Notebook:

jupyter notebook

2. Open the notebook file Real-Time-Traffic-Sign-Detection.ipynb from the Jupyter interface.

3. Run the cells to train the YOLOv8 model, evaluate its performance, and test it on images and videos.

📧Contact

For any questions or inquiries, feel free to reach out to me:

• Email: [email protected]