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Web-EmoRec is a web-based emotion recognition system that leverages machine learning and deep learning techniques to detect and classify human emotions in real-time. It features a user-friendly interface, live webcam integration, and advanced analytics to enhance emotional awareness and communication.

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Im-Mohammed/Web-EmoRec

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🌟 Web-EmoRec


🎥 Demo

A video showcasing real-time emotion recognition via webcam interface.

🔗 Watch Demo


🚀 Overview

Web-EmoRec is a web-based emotion recognition system that uses advanced machine learning techniques to analyze and classify human emotions.
This project aims to enhance communication and emotional awareness through real-time emotion detection and feedback.


🌟 Features

  • 🎭 Emotion Detection: Recognizes basic emotions such as happiness, sadness, anger, surprise, and more.
  • 📸 Real-Time Analysis: Utilizes a webcam for live emotion recognition.
  • 💡 Interactive Interface: User-friendly web interface for seamless interaction.
  • 📊 Analytics Dashboard: Visualize detected emotions over time.

🛠️ Technology Stack

  • Frontend: HTML, CSS, JavaScript
  • Backend: Python, Django Framework
  • Machine Learning: TensorFlow, OpenCV
  • Deployment: [Platform details, e.g., AWS, Heroku, etc.]

📂 Project Structure

.
├── static/                 # Static assets (CSS, JS, images)
├── templates/              # HTML templates
├── models/                 # Pre-trained emotion recognition models
├── app/                    # Django app files
├── requirements.txt        # Dependencies
└── README.md               # Project documentation

🖥️ How to Run the Project

  1. Clone the Repository:

    git clone https://github.com/Im-Mohammed/Web-EmoRec.git
  2. Navigate to the Project Directory:

    cd Web-EmoRec
  3. Install Dependencies:

    pip install -r requirements.txt
  4. Run the Django Development Server:

    python manage.py runserver
  5. Access the Application: Open your browser and go to: http://127.0.0.1:8000


🤝 Contributing

Contributions are welcome! Follow these steps to contribute:

  1. Fork the repository.

  2. Create a new branch:

    git checkout -b feature/YourFeatureName
  3. Commit your changes:

    git commit -m "Add your message here"
  4. Push to the branch:

    git push origin feature/YourFeatureName
  5. Open a pull request.


📜 License

This project is licensed under the Apache 2.0 License.


📧 Contact

Mohammed 🌐 GitHub: Im-Mohammed


❤️ Acknowledgments

  • Inspiration: The need for enhanced emotional awareness and communication.

About

Web-EmoRec is a web-based emotion recognition system that leverages machine learning and deep learning techniques to detect and classify human emotions in real-time. It features a user-friendly interface, live webcam integration, and advanced analytics to enhance emotional awareness and communication.

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