A web application built with Next.js for the frontend and Flask for the backend, enabling users to upload images for vehicle detection and counting.

• Features
• Prerequisites
• Installation
• Usage
• Docker
• Contributing
• License

• Vehicle Detection: Upload an image and detect vehicles using YOLO (You Only Look Once) object detection algorithm.
• Vehicle Counting: Count the number of cars, trucks, buses, and motorcycles detected in the image.
• Visual Results: View the original and processed images with vehicle counts displayed.

Before you begin, ensure you have met the following requirements:

• Python and pip installed on your machine for the backend.
• Docker installed on your machine for containerization.

cd vehicle-detection

1. Navigate to the project directory:

cd vehicle-detection

2. Install frontend dependencies:

cd frontend
npm install

3. Install backend dependencies:

cd ../backend
pip install -r requirements.txt

1. Start the backend Flask server:

cd ../backend
python app.py

The server will start running at `http://localhost:8080`.

2. Start the frontend Next.js server:

cd ../frontend
npm run dev

The frontend server will start running at `http://localhost:3000`.

3. Open your web browser and go to http://localhost:3000 to access the application.

4. Upload an image and click "Detect Vehicles" to initiate the vehicle detection process.

You can also run the application using Docker. Follow these steps:

1. Build the Docker image:

docker-compose build

2. Start the Docker containers:

docker-compose up

The frontend will be accessible at `http://localhost:3000` and the backend at `http://localhost:8080`.

Contributions are welcome! Please feel free to submit a pull request or open an issue for any bugs, feature requests, or suggestions.

To contribute to this project, follow these steps:

1. Fork the repository.
2. Create a new branch (git checkout -b feature-branch).
3. Make your changes.
4. Commit your changes (git commit -am 'Add new feature').
5. Push to the branch (git push origin feature-branch).
6. Create a new Pull Request.

This project is licensed under the MIT License - see the LICENSE file for details.