Music Genre Classification (MGC) is a website that allows users to identify the genre of the track that has been entered and offers similar songs. The application lets you save the searched song after registration. What's more logged user has access to their search history.
The project was created for the purpose of completing the courses - Software Engineering and Application Software - team project.
-
Clone the repository:
git clone https://github.com/mdziegielewska/Music-Genre-Classification.git -
Install dependencies
pip install -r requirements.txt
- Python
- Django
- Cypress
- Software Ideas Modeler
- app: Contains the core web application code, including frontend and backend components, as well as the machine learning model for genre classification (training data and results).
- documentation: Houses comprehensive project documentation, such as class diagrams, state machines, use cases, UI designs, cost estimates, test cases, feasibility reports, system requirements, and the project brief.
- Enhance model accuracy: Explore advanced deep learning architectures (e.g., transformers, recurrent neural networks) and feature engineering techniques to improve genre classification precision.
- Expand genre coverage: Incorporate a wider range of music genres, including subgenres and niche categories, to enhance the application's versatility.
- User interface enhancements: Improve the user interface with features like mood-based recommendations, collaborative filtering, and social sharing.
- Mobile application development: Create a mobile app version of MGC for increased accessibility and user convenience.