🎶 Emotion-Based Background Music Selector

This project is a deep learning-based web application that detects user emotions in real-time and selects background music tailored to their mood. Using facial emotion recognition and music recommendations, it brings a personalized, interactive music experience to users. Ideal for improving focus, relaxation, and enjoyment based on the user's emotional state.

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🔗 Features

• Real-Time Emotion Detection: Uses a webcam to capture facial expressions, which are analyzed by a deep learning model.
• Music Recommendations: Suggests background music that aligns with the detected emotions.
• Seamless Integration: Automatically updates music suggestions based on changing emotions.
• Simple User Interface: Easy-to-use design that makes real-time feedback and control intuitive.

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📋 Technologies

• Frontend:

  • React.js: For a dynamic, responsive UI to capture and display emotions in real time.
  • JavaScript/HTML/CSS: Core web technologies for handling webcam input, interactions, and layout.

• Backend:

  • Flask/FastAPI: Serves as an API backend to handle emotion detection and music recommendation logic.
  • TensorFlow/Keras: For building and running the emotion recognition model.
  • Spotify API: Fetches playlists and songs based on mood tags, providing the music selection.

• Data & Model:

  • FER-2013 Dataset: Used for training the emotion detection model.
  • Emotion Detection Model: A Convolutional Neural Network (CNN) trained on the FER-2013 dataset for classifying facial emotions.

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📦 Setup

Prerequisites

• Python 3.7+
• Node.js & npm
• Spotify Developer Account

Installation Steps

1. Clone the Repository:

   git clone https://github.com/your-username/emotion-music-selector.git
   cd emotion-music-selector

2. Backend Setup:

   • Install Dependencies:

     pip install -r requirements.txt

   • Train/Load the Model:
     • Either train the model using the FER-2013 dataset or load a pre-trained model.
     • Place the model file in the models directory.

3. Spotify API Setup:

   • Register on Spotify Developer Dashboard and create an app to get your API keys.
   • Create a .env file in the root directory with:

     SPOTIFY_CLIENT_ID=your_client_id
     SPOTIFY_CLIENT_SECRET=your_client_secret
     

4. Frontend Setup:

   • Navigate to Frontend:

     cd frontend

   • Install Dependencies:

     npm install

   • Run Frontend:

     npm start

5. Start the Backend Server:

   • Navigate back to the main directory and run:

     python app.py

6. Open in Browser:

   • Go to http://localhost:3000 to interact with the application.

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🎮 Usage Guide

1. Access Webcam: Grant permission to access the webcam, which will capture facial expressions in real-time.
2. Emotion Detection: The app detects your current emotion based on facial analysis and displays it.
3. Music Selection: Depending on your mood, the app fetches a playlist from Spotify and begins playback.

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🎨 Emotion to Music Mapping

Emotion	Music Category
Happy	Upbeat, Pop, Dance
Sad	Acoustic, Slow
Angry	Heavy Rock
Neutral	Chill, Lo-Fi
Surprised	Random/Experimental

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🛠️ Future Improvements

• Additional Emotions: Support a wider range of emotions.
• Improved Model: Fine-tune the model with a larger, diverse dataset.
• Enhanced Music Mapping: Allow users to customize their music preferences for each emotion.

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🤝 Contributing

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

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📄 License

This project is licensed under the MIT License.

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🌐 Acknowledgements

• FER-2013 Dataset
• Spotify API
• Inspiration from various emotion-based music recommendation research papers