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GUI for a Vocal Remover that uses Deep Neural Networks.
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README.md

Ultimate Vocal Remover v5 Command Line Beta

About

This application is a heavily modified version of the vocal remover AI created and posted by GitHub user tsurumeso. You can find tsurumeso's original command line version here. The official v5 GUI is still under developement and will be released some time in Q3 2021. New models for this version will be released at the end of the week.

  • Special Thanks
    • tsurumeso - The engineer who authored the AI code. Thank you for the hard work and dedication you put into the AI application this GUI is built around!
    • aufr33 - Model collaborator and fellow UVR developer. This project wouldn't be what it is without your help, thank you for your continued support!
    • DilanBoskan - The main GUI code contributor. Thank you for helping bring the GUI to life! Your hard work and continued support is greatly appreciated.

Installation

Install Required Applications & Packages

pip install --no-cache-dir -r requirements.txt
pip install torch==1.6.0+cu101 torchvision==0.7.0+cu101 -f https://download.pytorch.org/whl/torch_stable.html

FFmpeg

FFmpeg must be installed and configured in order for the application to be able to process any track that isn't a .wav file. Instructions for installing FFmpeg can be found on YouTube, WikiHow, Reddit, GitHub, and many other sources around the web.

  • Note: If you are experiencing any errors when attempting to process any media files that are not in the .wav format, please ensure FFmpeg is installed & configured correctly.

Running Inferences & Models

Coming Soon

Option Guide

Coming Soon

Models Included

All of the models included in the release were trained on large datasets containing diverse sets of music genres. These are all beta models that may or may not make it into the final release. We are working to have even better models in the final release of v5!

Here's a list of the models included within the v5 beta package -

  • V5 Beta Models
    • 2band_32000 Models
      • MGM-v5-2Band-32000-BETA1.pth - This model does very well on lower frequencies. Frequency cut-off is 16000 kHz. Must be used with 2band_32000.json file!
      • MGM-v5-2Band-32000-BETA2.pth - This model does very well on lower frequencies. Frequency cut-off is 16000 kHz. Must be used with 2band_32000.json file!
      • MGM-v5-KAROKEE-32000-BETA1.pth - Model by aufr33. This model focuses on removing main vocals only, leaving the BV vocals mostly intact. Frequency cut-off is 16000 kHz. Must be used with 2band_32000.json file!
      • MGM-v5-KAROKEE-32000-BETA2-AGR.pth - This model focuses a bit more on removing vocals from lower frequencies.Frequency cut-off is 16000 kHz. Must be used with 2band_32000.json file!
      • MGM-v5-Vocal_2Band-32000-BETA1.pth - This is a model that provides cleaner vocal stems! Frequency cut-off is 16000 kHz. Must be used with 2band_32000.json file!
      • MGM-v5-Vocal_2Band-32000-BETA2.pth - This is a model that provides cleaner vocal stems! Frequency cut-off is 16000 kHz. Must be used with 2band_32000.json file!
    • 3band_44100 Models
      • MGM-v5-3Band-44100-BETA.pth - This model does well removing vocals within the mid-rang frequencies. Frequency cut-off is 18000 kHz. Must be used with 3band_44100.json file!
    • 3band_44100_mid Models
      • MGM-v5-MIDSIDE-44100-BETA1.pth - This model does well removing vocals within the mid-rang frequencies. Frequency cut-off is 18000 kHz. Must be used with 3band_44100_mid.json file!
      • MGM-v5-MIDSIDE-44100-BETA2.pth - This model does well removing vocals within the mid-rang frequencies. Frequency cut-off is 18000 kHz. Must be used with 3band_44100_mid.json file!
    • 4band_44100
      • MGM-v5-4Band-44100-BETA1.pth - This model does very well on lower-mid range frequencies. Frequency cut-off is 20000 kHz. Must be used with 4band_44100.json file!
      • MGM-v5-4Band-44100-BETA2.pth - This model does very well on lower-mid range frequencies. Frequency cut-off is 20000 kHz. Must be used with 4band_44100.json file!

A special thank you to aufr33 for helping me expand the dataset used to train some of these models and for the helpful training tips.

Troubleshooting

Common Issues

  • This application is not compatible with 32-bit versions of Python. Please make sure your version of Python is 64-bit.
  • If FFmpeg is not installed, the application will throw an error if the user attempts to convert a non-WAV file.

Issue Reporting

Please be as detailed as possible when posting a new issue. Make sure to provide any error outputs and/or screenshots/gif's to give us a clearer understanding of the issue you are experiencing.

If you are unable to run conversions under any circumstances and all other resources have been exhausted, please do the following -

  1. Copy and paste the error output shown in the cmd prompt to the issues center on the GitHub repository.

License

The Ultimate Vocal Remover GUI code is MIT-licensed.

Contributing

  • For anyone interested in the ongoing development of Ultimate Vocal Remover please send us a pull request and we will review it. This project is 100% open-source and free for anyone to use and/or modify as they wish.
  • We only maintain the development and support for Ultimate Vocal Remover and the models provided.

References