ML-supported lo-fi music generator
We trained a VAE model in PyTorch to represent a lo-fi track as a vector of 100 features. A lo-fi track consists of chords, melodies, and other musical parameters. The web client uses Tone.js to make a dusty lo-fi track out of these parameters.
If you only want to tinker around with the client, you will only need the client
folder. This will use the project's server as the backend.
If you want to deploy your own model, you can either train your own model (see the instructions in the model
) or download the pre-trained checkpoint from here. Once you have deployed the server, change the server address inside client\src\api.ts
.
npm install
to install the dependencies.npm run serve
to develop or npm run build
to build a distributable.By default, this uses the project's server as the backend. You can also train your own model and deploy your own server.
See the model folder for details. Once you have trained your model, put the checkpoint in the checkpoints
folder.
See the server folder for details. You can use the provided Dockerfile. Don't forget to change the API url in the client.
Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.
If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement".
git checkout -b feature/AmazingFeature
)git commit -m 'Add some AmazingFeature'
)git push origin feature/AmazingFeature
)Big thanks to ZOOPRA UG for hosting the server!