Retrieval-based-Voice-Conversion-WebUI

An easy-to-use Voice Conversion framework based on VITS.

[![madewithlove](https://img.shields.io/badge/made_with-%E2%9D%A4-red?style=for-the-badge&labelColor=orange )](https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI)
[![Open In Colab](https://img.shields.io/badge/Colab-F9AB00?style=for-the-badge&logo=googlecolab&color=525252)](https://colab.research.google.com/github/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/blob/main/Retrieval_based_Voice_Conversion_WebUI.ipynb) [![Licence](https://img.shields.io/github/license/RVC-Project/Retrieval-based-Voice-Conversion-WebUI?style=for-the-badge)](https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/blob/main/LICENSE) [![Huggingface](https://img.shields.io/badge/🤗%20-Spaces-yellow.svg?style=for-the-badge)](https://huggingface.co/lj1995/VoiceConversionWebUI/tree/main/) [![Discord](https://img.shields.io/badge/RVC%20Developers-Discord-7289DA?style=for-the-badge&logo=discord&logoColor=white)](https://discord.gg/HcsmBBGyVk) [**Changelog**](https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/blob/main/docs/Changelog_EN.md) | [**FAQ (Frequently Asked Questions)**](https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/wiki/FAQ-(Frequently-Asked-Questions)) [**English**](../en/README.en.md) | [**中文简体**](../../README.md) | [**日本語**](../jp/README.ja.md) | [**한국어**](../kr/README.ko.md) ([**韓國語**](../kr/README.ko.han.md)) | [**Français**](../fr/README.fr.md) | [**Türkçe**](../tr/README.tr.md) | [**Português**](../pt/README.pt.md)
> Check out our [Demo Video](https://www.bilibili.com/video/BV1pm4y1z7Gm/) here!
Training and inference Webui Real-time voice changing GUI
go-web.bat go-realtime-gui.bat
You can freely choose the action you want to perform. We have achieved an end-to-end latency of 170ms. With the use of ASIO input and output devices, we have managed to achieve an end-to-end latency of 90ms, but it is highly dependent on hardware driver support.
> The dataset for the pre-training model uses nearly 50 hours of high quality audio from the VCTK open source dataset. > High quality licensed song datasets will be added to the training-set often for your use, without having to worry about copyright infringement. > Please look forward to the pretrained base model of RVCv3, which has larger parameters, more training data, better results, unchanged inference speed, and requires less training data for training. ## Features: + Reduce tone leakage by replacing the source feature to training-set feature using top1 retrieval; + Easy + fast training, even on poor graphics cards; + Training with a small amounts of data (>=10min low noise speech recommended); + Model fusion to change timbres (using ckpt processing tab->ckpt merge); + Easy-to-use WebUI; + UVR5 model to quickly separate vocals and instruments; + High-pitch Voice Extraction Algorithm [InterSpeech2023-RMVPE](#Credits) to prevent a muted sound problem. Provides the best results (significantly) and is faster with lower resource consumption than Crepe_full; + AMD/Intel graphics cards acceleration supported; + Intel ARC graphics cards acceleration with IPEX supported. ## Preparing the environment The following commands need to be executed with Python 3.8 or higher. (Windows/Linux) First install the main dependencies through pip: ```bash # Install PyTorch-related core dependencies, skip if installed # Reference: https://pytorch.org/get-started/locally/ pip install torch torchvision torchaudio #For Windows + Nvidia Ampere Architecture(RTX30xx), you need to specify the cuda version corresponding to pytorch according to the experience of https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/issues/21 #pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu117 #For Linux + AMD Cards, you need to use the following pytorch versions: #pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm5.4.2 ``` Then can use poetry to install the other dependencies: ```bash # Install the Poetry dependency management tool, skip if installed # Reference: https://python-poetry.org/docs/#installation curl -sSL https://install.python-poetry.org | python3 - # Install the project dependencies poetry install ``` You can also use pip to install them: ```bash for Nvidia graphics cards pip install -r requirements.txt for AMD/Intel graphics cards on Windows (DirectML)： pip install -r requirements-dml.txt for Intel ARC graphics cards on Linux / WSL using Python 3.10: pip install -r requirements-ipex.txt for AMD graphics cards on Linux (ROCm): pip install -r requirements-amd.txt ``` ------ Mac users can install dependencies via `run.sh`: ```bash sh ./run.sh ``` ## Preparation of other Pre-models RVC requires other pre-models to infer and train. ```bash #Download all needed models from https://huggingface.co/lj1995/VoiceConversionWebUI/tree/main/ python tools/download_models.py ``` Or just download them by yourself from our [Huggingface space](https://huggingface.co/lj1995/VoiceConversionWebUI/tree/main/). Here's a list of Pre-models and other files that RVC needs: ```bash ./assets/hubert/hubert_base.pt ./assets/pretrained ./assets/uvr5_weights Additional downloads are required if you want to test the v2 version of the model. ./assets/pretrained_v2 If you want to test the v2 version model (the v2 version model has changed the input from the 256 dimensional feature of 9-layer Hubert+final_proj to the 768 dimensional feature of 12-layer Hubert, and has added 3 period discriminators), you will need to download additional features ./assets/pretrained_v2 If you want to use the latest SOTA RMVPE vocal pitch extraction algorithm, you need to download the RMVPE weights and place them in the RVC root directory https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/rmvpe.pt For AMD/Intel graphics cards users you need download: https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/rmvpe.onnx ``` ### 2. Install FFmpeg If you have FFmpeg and FFprobe installed on your computer, you can skip this step. #### For Ubuntu/Debian users ```bash sudo apt install ffmpeg ``` #### For MacOS users ```bash brew install ffmpeg ``` #### For Windows users Download these files and place them in the root folder: - [ffmpeg.exe](https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/ffmpeg.exe) - [ffprobe.exe](https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/ffprobe.exe) ## ROCm Support for AMD graphic cards (Linux only) To use ROCm on Linux install all required drivers as described [here](https://rocm.docs.amd.com/en/latest/deploy/linux/os-native/install.html). On Arch use pacman to install the driver: ```` pacman -S rocm-hip-sdk rocm-opencl-sdk ```` You might also need to set these environment variables (e.g. on a RX6700XT): ```` export ROCM_PATH=/opt/rocm export HSA_OVERRIDE_GFX_VERSION=10.3.0 ```` Make sure your user is part of the `render` and `video` group: ```` sudo usermod -aG render $USERNAME sudo usermod -aG video $USERNAME ```` ## Get started ### start up directly Use the following command to start WebUI: ```bash python infer-web.py ``` ### Use the integration package Download and extract file `RVC-beta.7z`, then follow the steps below according to your system: #### For Windows users 双击`go-web.bat` #### For MacOS users ```bash sh ./run.sh ``` ### For Intel IPEX users (Linux Only) ```bash source /opt/intel/oneapi/setvars.sh ``` ## Credits + [ContentVec](https://github.com/auspicious3000/contentvec/) + [VITS](https://github.com/jaywalnut310/vits) + [HIFIGAN](https://github.com/jik876/hifi-gan) + [Gradio](https://github.com/gradio-app/gradio) + [FFmpeg](https://github.com/FFmpeg/FFmpeg) + [Ultimate Vocal Remover](https://github.com/Anjok07/ultimatevocalremovergui) + [audio-slicer](https://github.com/openvpi/audio-slicer) + [Vocal pitch extraction:RMVPE](https://github.com/Dream-High/RMVPE) + The pretrained model is trained and tested by [yxlllc](https://github.com/yxlllc/RMVPE) and [RVC-Boss](https://github.com/RVC-Boss). ## Thanks to all contributors for their efforts