A self-contained singing voice conversion application using the so-vits-svc architecture, with Deep U-Net model for vocal separation feature and easy to use GUI.
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Install Python (3.10 is recommended, but 3.10 - 3.11 should work)
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Install pipx
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Install the package by running this following terminal command if you only have one Python version installed:
pipx install svc-toolkit
To install with a specific Python version, use the --python
flag. For example, to install with Python 3.10:
pipx install svc-toolkit --python 3.10
Using NVIDIA GPU
To use the package with NVIDIA GPU, you need to upgrade the following dependencies:
pipx inject svc-toolkit torch==2.1.1 torchaudio==2.1.1 --pip-args="-U" --index-url https://download.pytorch.org/whl/cu121
For CUDA version 11.*, you can change the cu121
to cu118
. So the command will be:
pipx inject svc-toolkit torch==2.1.1 torchaudio==2.1.1 --pip-args="-U" --index-url https://download.pytorch.org/whl/cu118
Note that AMD GPUs are not actively supported, but you can try using the package with the CPU version of PyTorch.
For other installation options, see Installation.
svct.exe
svct
For the detailed usage guide, see Usage.
For the detailed development guide, see Development.
This project is the implementation of the final year project for the Bachelor of
Science in Computer Science, Department of Computer Science, City University of Hong
Kong, named "Singing Voice Conversion from Fully Mixed Track with GUI", with project code
23CS062
.