Moodify is a Flask-based web application that seamlessly integrates facial emotion recognition (FER) with personalized music recommendations. By leveraging advanced algorithms and technologies, Moodify offers users a dynamic and immersive music listening experience tailored to their emotional states and preferences. This implementation serves as the GUI for the proposed model described in my research paper Integrating Facial Emotion Recognition into Music Recommendation Systems.
- Facial Emotion Detection: Users can interact with the application through their webcam, allowing real-time analysis of facial expressions to determine emotional states using YOLOv8.
- Personalized Music Recommendations:
- Your Favorites Suggestions: Offering a selection of top favorite songs aligned with the detected emotion using cosine similarity.
- Currently Popular Suggestions: Based on KNN recommendations, users can explore currently popular songs tailored to their listening profiles.
- Discover New Suggestions: Presenting random popular songs based on the user's listening profile across all emotions using SVD(Singular value decomposition), inviting users to explore new musical avenues.
- Login Authentication: Implemented to provide access to personalized recommendations and past data, ensuring security and enhancing user engagement.
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Login Page:
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Home Page:
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Camera Page:
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Recommendations Page:
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Recommendations After Selecting a Song:
