nebulatris / vibescape Goto Github PK

Vibescape is an emotion music recommender system that provides a unique and personalized music streaming experience. It utilizes facial emotion detection to analyze the user's emotions and recommend songs that match their mood. The application supports streaming from popular platforms such as Spotify, SoundCloud, and YouTube.

Live Demo here

• Emotion-based Music Recommendation: Vibescape uses facial emotion detection to analyze the user's emotions and recommends songs that match their mood.
• Streaming from Multiple Platforms: Users can stream music from their favorite platforms including Spotify, SoundCloud, and YouTube.
• Personalized Playlists: The application creates personalized playlists based on the user's emotions and preferences.
• User-Friendly Interface: Vibescape offers an intuitive and easy-to-use interface for a seamless music streaming experience.

1. Clone the repository:

   git clone https://github.com/NebulaTris/vibescape.git
   cd vibescape

2. Install the required dependencies using pip:

   pip install -r requirements.txt

1. Run the Streamlit app:

   streamlit run 1_🎵_Homepage.py

2. Open your web browser and go to http://localhost:8501 to access the Vibescape application.

Vibescape uses facial emotion detection to analyze the user's emotions. Make sure your device has a camera enabled to utilize this feature effectively.

Vibescape supports music streaming from the following platforms:

• Spotify
• SoundCloud
• YouTube

Contributions are welcome! If you'd like to contribute to Vibescape, please follow these steps:

1. Fork the repository.
2. Create a new branch for your feature/bugfix.
3. Commit your changes and push to your fork.
4. Submit a pull request with a detailed description of your changes.

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