A video showcasing real-time emotion recognition via webcam interface.
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.
- 🎭 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.
- Frontend: HTML, CSS, JavaScript
- Backend: Python, Django Framework
- Machine Learning: TensorFlow, OpenCV
- Deployment: [Platform details, e.g., AWS, Heroku, etc.]
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├── 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
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Clone the Repository:
git clone https://github.com/Im-Mohammed/Web-EmoRec.git
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Navigate to the Project Directory:
cd Web-EmoRec -
Install Dependencies:
pip install -r requirements.txt
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Run the Django Development Server:
python manage.py runserver
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Access the Application: Open your browser and go to: http://127.0.0.1:8000
Contributions are welcome! Follow these steps to contribute:
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Fork the repository.
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Create a new branch:
git checkout -b feature/YourFeatureName
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Commit your changes:
git commit -m "Add your message here" -
Push to the branch:
git push origin feature/YourFeatureName
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Open a pull request.
This project is licensed under the Apache 2.0 License.
Mohammed 🌐 GitHub: Im-Mohammed
- Inspiration: The need for enhanced emotional awareness and communication.