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-<div align="center">
-<h1>Retrieval-based-Voice-Conversion-WebUI</h1>
-一个基于VITS的简单易用的变声框架<br><br>
-[![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)
-<img src="https://counter.seku.su/cmoe?name=rvc&theme=r34" /><br>
-[![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/badge/LICENSE-MIT-green.svg?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)
-[**更新日志**](https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/blob/main/docs/Changelog_CN.md) | [**常见问题解答**](https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/wiki/%E5%B8%B8%E8%A7%81%E9%97%AE%E9%A2%98%E8%A7%A3%E7%AD%94) | [**AutoDL·5毛钱训练AI歌手**](https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/wiki/Autodl%E8%AE%AD%E7%BB%83RVC%C2%B7AI%E6%AD%8C%E6%89%8B%E6%95%99%E7%A8%8B) | [**对照实验记录**](https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/wiki/Autodl%E8%AE%AD%E7%BB%83RVC%C2%B7AI%E6%AD%8C%E6%89%8B%E6%95%99%E7%A8%8B](https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/wiki/%E5%AF%B9%E7%85%A7%E5%AE%9E%E9%AA%8C%C2%B7%E5%AE%9E%E9%AA%8C%E8%AE%B0%E5%BD%95)) | [**在线演示**](https://modelscope.cn/studios/FlowerCry/RVCv2demo)
-[**English**](./docs/en/README.en.md) | [**中文简体**](./README.md) | [**日本語**](./docs/jp/README.ja.md) | [**한국어**](./docs/kr/README.ko.md) ([**韓國語**](./docs/kr/README.ko.han.md)) | [**Français**](./docs/fr/README.fr.md) | [**Türkçe**](./docs/tr/README.tr.md) | [**Português**](./docs/pt/README.pt.md)
-</div>
-> 底模使用接近50小时的开源高质量VCTK训练集训练，无版权方面的顾虑，请大家放心使用
-> 请期待RVCv3的底模，参数更大，数据更大，效果更好，基本持平的推理速度，需要训练数据量更少。
-<table>
-   <tr>
-		<td align="center">训练推理界面</td>
-		<td align="center">实时变声界面</td>
-	</tr>
-  <tr>
-		<td align="center"><img src="https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/assets/129054828/092e5c12-0d49-4168-a590-0b0ef6a4f630"></td>
-    <td align="center"><img src="https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/assets/129054828/730b4114-8805-44a1-ab1a-04668f3c30a6"></td>
-	</tr>
-	<tr>
-		<td align="center">go-web.bat</td>
-		<td align="center">go-realtime-gui.bat</td>
-	</tr>
-  <tr>
-    <td align="center">可以自由选择想要执行的操作。</td>
-		<td align="center">我们已经实现端到端170ms延迟。如使用ASIO输入输出设备，已能实现端到端90ms延迟，但非常依赖硬件驱动支持。</td>
-	</tr>
-</table>
-## 简介
-本仓库具有以下特点
-+ 使用top1检索替换输入源特征为训练集特征来杜绝音色泄漏
-+ 即便在相对较差的显卡上也能快速训练
-+ 使用少量数据进行训练也能得到较好结果(推荐至少收集10分钟低底噪语音数据)
-+ 可以通过模型融合来改变音色(借助ckpt处理选项卡中的ckpt-merge)
-+ 简单易用的网页界面
-+ 可调用UVR5模型来快速分离人声和伴奏
-+ 使用最先进的[人声音高提取算法InterSpeech2023-RMVPE](#参考项目)根绝哑音问题。效果最好（显著地）但比crepe_full更快、资源占用更小
-+ A卡I卡加速支持
-点此查看我们的[演示视频](https://www.bilibili.com/video/BV1pm4y1z7Gm/) !
-## 环境配置
-以下指令需在 Python 版本大于3.8的环境中执行。
-### Windows/Linux/MacOS等平台通用方法
-下列方法任选其一。
-#### 1. 通过 pip 安装依赖
-1. 安装Pytorch及其核心依赖，若已安装则跳过。参考自: https://pytorch.org/get-started/locally/
-```bash
-pip install torch torchvision torchaudio
-```
-2. 如果是 win 系统 + Nvidia Ampere 架构(RTX30xx)，根据 #21 的经验，需要指定 pytorch 对应的 cuda 版本
 ```bash
-pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu117
 ```
-3. 根据自己的显卡安装对应依赖
-- N卡
 ```bash
-pip install -r requirements.txt
 ```
-- A卡/I卡
-```bash
-pip install -r requirements-dml.txt
-```
-- A卡ROCM(Linux)
-```bash
-pip install -r requirements-amd.txt
-```
-- I卡IPEX(Linux)
-```bash
-pip install -r requirements-ipex.txt
-```
-#### 2. 通过 poetry 来安装依赖
-安装 Poetry 依赖管理工具，若已安装则跳过。参考自: https://python-poetry.org/docs/#installation
-```bash
-curl -sSL https://install.python-poetry.org | python3 -
-```
-通过 Poetry 安装依赖时，python 建议使用 3.7-3.10 版本，其余版本在安装 llvmlite==0.39.0 时会出现冲突
-```bash
-poetry init -n
-poetry env use "path to your python.exe"
-poetry run pip install -r requirments.txt
-```
-### MacOS
-可以通过 `run.sh` 来安装依赖
-```bash
-sh ./run.sh
-```
-## 其他预模型准备
-RVC需要其他一些预模型来推理和训练。
-你可以从我们的[Hugging Face space](https://huggingface.co/lj1995/VoiceConversionWebUI/tree/main/)下载到这些模型。
-### 1. 下载 assets
-以下是一份清单，包括了所有RVC所需的预模型和其他文件的名称。你可以在`tools`文件夹找到下载它们的脚本。
-- ./assets/hubert/hubert_base.pt
-- ./assets/pretrained
-- ./assets/uvr5_weights
-想使用v2版本模型的话，需要额外下载
-- ./assets/pretrained_v2
-### 2. 安装 ffmpeg
-若ffmpeg和ffprobe已安装则跳过。
-#### Ubuntu/Debian 用户
-```bash
-sudo apt install ffmpeg
-```
-#### MacOS 用户
-```bash
-brew install ffmpeg
-```
-#### Windows 用户
-下载后放置在根目录。
-- 下载[ffmpeg.exe](https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/ffmpeg.exe)
-- 下载[ffprobe.exe](https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/ffprobe.exe)
-### 3. 下载 rmvpe 人声音高提取算法所需文件
-如果你想使用最新的RMVPE人声音高提取算法，则你需要下载音高提取模型参数并放置于RVC根目录。
-- 下载[rmvpe.pt](https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/rmvpe.pt)
-#### 下载 rmvpe 的 dml 环境(可选, A卡/I卡用户)
-- 下载[rmvpe.onnx](https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/rmvpe.onnx)
-### 4. AMD显卡Rocm(可选, 仅Linux)
-如果你想基于AMD的Rocm技术在Linux系统上运行RVC，请先在[这里](https://rocm.docs.amd.com/en/latest/deploy/linux/os-native/install.html)安装所需的驱动。
-若你使用的是Arch Linux，可以使用pacman来安装所需驱动：
-````
-pacman -S rocm-hip-sdk rocm-opencl-sdk
-````
-对于某些型号的显卡，你可能需要额外配置如下的环境变量（如：RX6700XT）：
-````
-export ROCM_PATH=/opt/rocm
-export HSA_OVERRIDE_GFX_VERSION=10.3.0
-````
-同时确保你的当前用户处于`render`与`video`用户组内：
-````
-sudo usermod -aG render $USERNAME
-sudo usermod -aG video $USERNAME
-````
-## 开始使用
-### 直接启动
-使用以下指令来启动 WebUI
-```bash
-python infer-web.py
-```
-若先前使用 Poetry 安装依赖，则可以通过以下方式启动WebUI
-```bash
-poetry run python infer-web.py
-```
-### 使用整合包
-下载并解压`RVC-beta.7z`
-#### Windows 用户
-双击`go-web.bat`
-#### MacOS 用户
-```bash
-sh ./run.sh
-```
-### 对于需要使用IPEX技术的I卡用户(仅Linux)
-```bash
-source /opt/intel/oneapi/setvars.sh
-```
-## 参考项目
-+ [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).
-## 感谢所有贡献者作出的努力
-<a href="https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/graphs/contributors" target="_blank">
-  <img src="https://contrib.rocks/image?repo=RVC-Project/Retrieval-based-Voice-Conversion-WebUI" />
-</a>

+---
+license: mit
+---
+# easyGUI
+`easyGUI` is a user-friendly voice conversion framework based on VITS, designed to eliminate timbre leakage by replacing input features with those from the training set. It's efficient even on lower-end GPUs, requiring only about 10 minutes of low-noise speech data for good results. The framework features a simple web interface, supports A card and I card acceleration, and uses the advanced RMVPE algorithm for pitch extraction.
+## Installation
+### Prerequisites
+- Python 3.8 or higher
+### Installation Steps
+1. **Install Pytorch**:
+   ```bash
+   pip install torch torchvision torchaudio
+   ```
+   For Nvidia Ampere (RTX30xx):
+   ```bash
+   pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu117
+   ```
+2. **Install Dependencies**:
+   - For Nvidia GPUs:
+     ```bash
+     pip install -r requirements.txt
+     ```
+   - For AMD/Intel GPUs:
+     ```bash
+     pip install -r requirements-dml.txt
+     ```
+   - For AMD ROCm (Linux):
+     ```bash
+     pip install -r requirements-amd.txt
+     ```
+   - For Intel IPEX (Linux):
+     ```bash
+     pip install -r requirements-ipex.txt
+     ```
+3. **Install Optional Dependencies** (if needed):
+   ```bash
+   sh ./run.sh  # For MacOS
+   ```
+### Additional Setup
+- **Download Assets**:
+  Download necessary models and files using the scripts in the `tools` directory.
+- **Install FFmpeg**:
+  ```bash
+  sudo apt install ffmpeg  # Ubuntu/Debian
+  brew install ffmpeg      # MacOS
+  ```
+## Usage
+Start the WebUI:
 ```bash
+python demo.py
 ```
+If using Poetry:
 ```bash
+poetry run python demo.py
 ```
+## Features
+- Top1 retrieval to replace input features
+- Fast training on less powerful GPUs
+- Model merging to change timbre
+- Advanced pitch extraction with RMVPE
+---