Merge pull request #914 from cloudxu/readme_update
Removing ongoing work session in READMEbabysor-patch-1
Vega
GitHub
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README-CN.md
26
README-CN.md
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🌍 **Webserver Ready** 可伺服你的训练结果，供远程调用
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### 进行中的工作
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* GUI/客户端大升级与合并
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- [x] 初始化框架 `./mkgui` （基于streamlit + fastapi）和 [技术设计](https://vaj2fgg8yn.feishu.cn/docs/doccnvotLWylBub8VJIjKzoEaee)
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- [x] 增加 Voice Cloning and Conversion的演示页面
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- [x] 增加Voice Conversion的预处理preprocessing 和训练 training 页面
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- [ ] 增加其他的的预处理preprocessing 和训练 training 页面
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* 模型后端基于ESPnet2升级
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## 开始
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### 1. 安装要求
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@ -56,7 +43,7 @@
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#### 1.2 M1芯片Mac环境配置（Inference Time)
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> 以下环境按x86-64搭建，使用原生的`demo_toolbox.py`，可作为在不改代码情况下快速使用的workaround。
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>
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>
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> 如需使用M1芯片训练，因`demo_toolbox.py`依赖的`PyQt5`不支持M1，则应按需修改代码，或者尝试使用`web.py`。
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* 安装`PyQt5`，参考[这个链接](https://stackoverflow.com/a/68038451/20455983)
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@ -81,11 +68,11 @@
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* 安装`ctc-segmentation`
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> 因上述方法没有成功，选择从[github](https://github.com/lumaku/ctc-segmentation) clone源码手动编译
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* `git clone https://github.com/lumaku/ctc-segmentation.git` 克隆到任意位置
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* `cd ctc-segmentation`
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* `cd ctc-segmentation`
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* `source /PathToMockingBird/venv/bin/activate` 假设一开始未开启，打开MockingBird项目的虚拟环境
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* `cythonize -3 ctc_segmentation/ctc_segmentation_dyn.pyx`
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* `cythonize -3 ctc_segmentation/ctc_segmentation_dyn.pyx`
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* `/usr/bin/arch -x86_64 python setup.py build` 要注意明确用x86-64架构编译
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* `/usr/bin/arch -x86_64 python setup.py install --optimize=1 --skip-build`用x86-64架构安装
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* `/usr/bin/arch -x86_64 python setup.py install --optimize=1 --skip-build`用x86-64架构安装
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* 安装其他依赖
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* `/usr/bin/arch -x86_64 pip install torch torchvision torchaudio` 这里用pip安装`PyTorch`，明确架构是x86
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* `pip install -r requirements.txt`
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* 运行
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> 参考[这个链接](https://youtrack.jetbrains.com/issue/PY-46290/Allow-running-Python-under-Rosetta-2-in-PyCharm-for-Apple-Silicon)
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> 参考[这个链接](https://youtrack.jetbrains.com/issue/PY-46290/Allow-running-Python-under-Rosetta-2-in-PyCharm-for-Apple-Silicon)
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，让项目跑在x86架构环境上
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* `vim /PathToMockingBird/venv/bin/pythonM1`
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* 写入以下代码
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想像柯南拿着变声器然后发出毛利小五郎的声音吗？本项目现基于PPG-VC，引入额外两个模块（PPG extractor + PPG2Mel）, 可以实现变声功能。（文档不全，尤其是训练部分，正在努力补充中）
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#### 4.0 准备环境
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* 确保项目以上环境已经安装ok，运行`pip install espnet` 来安装剩余的必要包。
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* 下载以下模型 链接：https://pan.baidu.com/s/1bl_x_DHJSAUyN2fma-Q_Wg
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* 下载以下模型 链接：https://pan.baidu.com/s/1bl_x_DHJSAUyN2fma-Q_Wg
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提取码：gh41
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* 24K采样率专用的vocoder（hifigan）到 *vocoder\saved_models\xxx*
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* 预训练的ppg特征encoder(ppg_extractor)到 *ppg_extractor\saved_models\xxx*
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@ -294,4 +281,3 @@ voc_pad =2
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24
README.md
24
README.md
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@ -18,14 +18,6 @@
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### [DEMO VIDEO](https://www.bilibili.com/video/BV17Q4y1B7mY/)
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### Ongoing Works(Helps Needed)
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* Major upgrade on GUI/Client and unifying web and toolbox
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[X] Init framework `./mkgui` and [tech design](https://vaj2fgg8yn.feishu.cn/docs/doccnvotLWylBub8VJIjKzoEaee)
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[X] Add demo part of Voice Cloning and Conversion
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[X] Add preprocessing and training for Voice Conversion
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[ ] Add preprocessing and training for Encoder/Synthesizer/Vocoder
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* Major upgrade on model backend based on ESPnet2(not yet started)
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## Quick Start
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### 1. Install Requirements
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#### 1.2 Setup with a M1 Mac
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> The following steps are a workaround to directly use the original `demo_toolbox.py`without the changing of codes.
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>
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>
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> Since the major issue comes with the PyQt5 packages used in `demo_toolbox.py` not compatible with M1 chips, were one to attempt on training models with the M1 chip, either that person can forgo `demo_toolbox.py`, or one can try the `web.py` in the project.
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##### 1.2.1 Install `PyQt5`, with [ref](https://stackoverflow.com/a/68038451/20455983) here.
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pip install pyqt5
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```
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##### 1.2.2 Install `pyworld` and `ctc-segmentation`
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> Both packages seem to be unique to this project and are not seen in the original [Real-Time Voice Cloning](https://github.com/CorentinJ/Real-Time-Voice-Cloning) project. When installing with `pip install`, both packages lack wheels so the program tries to directly compile from c code and could not find `Python.h`.
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* Install `pyworld`
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* `brew install python` `Python.h` can come with Python installed by brew
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* `export CPLUS_INCLUDE_PATH=/opt/homebrew/Frameworks/Python.framework/Headers` The filepath of brew-installed `Python.h` is unique to M1 MacOS and listed above. One needs to manually add the path to the environment variables.
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* `pip install pyworld` that should do.
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* Install`ctc-segmentation`
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> Same method does not apply to `ctc-segmentation`, and one needs to compile it from the source code on [github](https://github.com/lumaku/ctc-segmentation).
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* `git clone https://github.com/lumaku/ctc-segmentation.git`
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* `cd ctc-segmentation`
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> Same method does not apply to `ctc-segmentation`, and one needs to compile it from the source code on [github](https://github.com/lumaku/ctc-segmentation).
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* `git clone https://github.com/lumaku/ctc-segmentation.git`
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* `cd ctc-segmentation`
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* `source /PathToMockingBird/venv/bin/activate` If the virtual environment hasn't been deployed, activate it.
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* `cythonize -3 ctc_segmentation/ctc_segmentation_dyn.pyx`
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* `cythonize -3 ctc_segmentation/ctc_segmentation_dyn.pyx`
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* `/usr/bin/arch -x86_64 python setup.py build` Build with x86 architecture.
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* `/usr/bin/arch -x86_64 python setup.py install --optimize=1 --skip-build`Install with x86 architecture.
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* `/usr/bin/arch -x86_64 pip install torch torchvision torchaudio` Pip installing `PyTorch` as an example, articulate that it's installed with x86 architecture
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* `pip install ffmpeg` Install ffmpeg
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* `pip install -r requirements.txt` Install other requirements.
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##### 1.2.4 Run the Inference Time (with Toolbox)
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> To run the project on x86 architecture. [ref](https://youtrack.jetbrains.com/issue/PY-46290/Allow-running-Python-under-Rosetta-2-in-PyCharm-for-Apple-Silicon).
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* `vim /PathToMockingBird/venv/bin/pythonM1` Create an executable file `pythonM1` to condition python interpreter at `/PathToMockingBird/venv/bin`.
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