Green Path (Traffic sign Classification)

This project aims to enhance road safety by using a Convolutional Neural Network (CNN) model for real-time traffic sign detection with 97.94% accuracy. It includes a user reporting system for reporting locations and incidents with detailed descriptions and integrates the traffic sign detection model into a responsive web application. Additionally, it provides a comprehensive learning page for users to study all traffic signs.

• Real-time Traffic Sign Detection: Utilizes a CNN model to accurately detect and classify traffic signs.
• User Reporting System: Allows users to report locations and incidents with detailed descriptions.
• Responsive Web Application: Ensures compatibility across various devices.
• Learning Page: A comprehensive section for users to study traffic signs, enhancing knowledge and safety.

• Python 3.6 or higher
• Git
• Virtualenv

git clone https://github.com/yourusername/traffic-sign-detection.git
cd traffic-sign-detection

virtualenv venv
source venv/bin/activate  # On Windows use `venv\Scripts\activate`

pip install -r requirements.txt

1. Database Setup: Configure your database settings in the config.py file.
2. Model Weights: Download the pre-trained CNN model weights and place them in the models/ directory.
3. Environment Variables: Create a .env file in the root directory and set up necessary environment variables (e.g., API keys, database URL).

python app.py

Open your browser and go to http://localhost:5001.

• Real-time Detection: Upload images or use the live camera feed to detect traffic signs.
• Reporting: Submit reports about traffic incidents with location and description details.
• Learning Page: Browse and learn about various traffic signs.

We welcome contributions! Please fork the repository and create a pull request with your changes.

This project is licensed under the MIT License.

1. Download Python: Go to the official Python website and download the latest version of Python for your operating system.

2. Install Python:

   • Windows: Run the downloaded executable file and follow the installation prompts. Make sure to check the box that says "Add Python to PATH".
   • macOS: Open the downloaded .pkg file and follow the installation instructions.
   • Linux: Use the package manager for your distribution (e.g., sudo apt-get install python3).

3. Verify Installation:

   • Open a terminal (Command Prompt on Windows) and run:

     python --version

4. Install Pip:

   • Pip is the package installer for Python. It is included by default with Python 3.4 and later. To ensure you have it installed, run:

     python -m ensurepip --upgrade

5. Install Virtualenv:

   • Virtualenv helps to create isolated Python environments. Install it using pip:

     pip install virtualenv