In this system, we provide an overview of how music can affect the user's mood and how to choose the right music tracks to improve the user's moods. The implemented system can detect the user's emotions. The emotions that the system can detect were happy, sad, angry, neutral, or surprised. After determining the user’s emotion, the proposed system provided the user with a playlist that contains music matches that detected the mood.
The project is to develop an Emotion Based Music Recommender which is on web based application meant for users to minimize their efforts in managing large playlists.
Once the emotion is detected, playlist of songs suitable to the mood of the user will be presented to user over YouTube
- Streamlit
- Opencv
- Keras
- Mediapipe
- Tensorflow
- Numpy
- Face Detection
- Feature Extraction
- Emotion Detection
- Music Recommendation
