Metadata-Version: 2.1
Name: svc-toolkit
Version: 1.1.0
Summary: 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.
Home-page: https://github.com/jljl1337/svc-toolkit
License: MIT
Author: jljl1337
Author-email: lckjack123@gmail.com
Requires-Python: >=3.10,<3.12
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Requires-Dist: huggingface-hub (==0.20.3)
Requires-Dist: librosa (==0.10.1)
Requires-Dist: lightning (==2.1.3)
Requires-Dist: matplotlib (==3.8.1)
Requires-Dist: numpy (==1.26.3)
Requires-Dist: pandas (==2.1.3)
Requires-Dist: pip (==24.0)
Requires-Dist: pyside6 (==6.6.1)
Requires-Dist: pyside6-utils (==1.2.2)
Requires-Dist: pyyaml (==6.0.1)
Requires-Dist: scikit-learn (==1.4.0)
Requires-Dist: scipy (==1.12.0)
Requires-Dist: so-vits-svc-fork (==4.1.40)
Requires-Dist: torch (==2.1.1)
Requires-Dist: torchaudio (==2.1.1)
Requires-Dist: torchmetrics (==1.2.0)
Project-URL: Documentation, https://jljl1337.github.io/svc-toolkit/
Project-URL: Repository, https://github.com/jljl1337/svc-toolkit
Description-Content-Type: text/markdown

# Singing Voice Conversion Toolkit

![Tests](https://github.com/jljl1337/svc-toolkit/actions/workflows/tests.yml/badge.svg)
![Deployment](https://github.com/jljl1337/svc-toolkit/actions/workflows/deployments.yml/badge.svg)
[![Codecov](https://codecov.io/gh/jljl1337/svc-toolkit/graph/badge.svg?token=QBM6OLIG00)](https://codecov.io/gh/jljl1337/svc-toolkit)

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.

## Getting Started

### Installation

1. Install [Python](https://www.python.org/downloads/) (3.10 is recommended, but 3.10 - 3.11 should work)

2. Install [pipx](https://pipx.pypa.io/stable/installation/)

3. 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
```

<details markdown>
<summary>Using NVIDIA GPU</summary>

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
```

</details>

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](https://jljl1337.github.io/svc-toolkit/installation/).

### Usage

#### Windows

```
svct.exe
```

#### macOS/Linux

```
svct
```

For the detailed usage guide, see [Usage](https://jljl1337.github.io/svc-toolkit/usage/).

## Development

For the detailed development guide, see [Development](https://jljl1337.github.io/svc-toolkit/development/).

## About

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`.
