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README_dev_en.md
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README_dev_en.md
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## For Developper
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[English](/README_dev_ja.md)
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## Prerequisit
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- Linux or WSL2 (not tested for Mac )
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- Anaconda
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## Preparation
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1. Create anaconda virtual environment
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```
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$ conda create -n vcclient-dev python=3.10
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$ conda activate vcclient-dev
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```
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2. clone repository
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```
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$ git clone https://github.com/w-okada/voice-changer.git
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$ cd voice-changer
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```
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## For Server Developer
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1. Clone support VC repository
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```
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cd server
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git clone https://github.com/isletennos/MMVC_Client.git MMVC_Client_v13
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git clone https://github.com/isletennos/MMVC_Client.git MMVC_Client_v15
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git clone https://github.com/StarStringStudio/so-vits-svc.git so-vits-svc-40
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git clone https://github.com/StarStringStudio/so-vits-svc.git so-vits-svc-40v2
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cd so-vits-svc-40v2 && git checkout 08c70ff3d2f7958820b715db2a2180f4b7f92f8d && cd -
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git clone https://github.com/yxlllc/DDSP-SVC.git DDSP-SVC
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git clone https://github.com/liujing04/Retrieval-based-Voice-Conversion-WebUI.git RVC
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```
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2. Copy weights
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copy weights of emmbedding or vocoder. These file path can be set as parameter when invoke server.
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(1) hubert_base.pt
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download from [here](https://huggingface.co/lj1995/VoiceConversionWebUI/tree/main)
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(2) content vec
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download ContentVec_legacy_500 from [here](https://github.com/auspicious3000/contentvec)
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(3) hubert_soft
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download from [here](https://github.com/bshall/hubert/releases/download/v0.1/hubert-soft-0d54a1f4.pt)
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(4) vocorder
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download nsf_hifigan_20221211.zip from [here](https://github.com/openvpi/vocoders/releases/tag/nsf-hifigan-v1) and expand it.
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3. Install requirements
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```
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$ pip install -r requirements.txt
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```
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4. Run server
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Run server with the below command. You can replace the path to each weight.
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```
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$ python3 MMVCServerSIO.py -p 18888 --https true \
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--content_vec_500 weights/checkpoint_best_legacy_500.pt \
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--hubert_base weights/hubert_base.pt \
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--hubert_soft weights/hubert-soft-0d54a1f4.pt \
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--nsf_hifigan weights/nsf_hifigan/model
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```
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5. Enjoy developing.
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## For Client Developer
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1. Import modules and initial build
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```
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cd client
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cd lib
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npm install
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npm run build:dev
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cd ../demo
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npm install
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npm run build:dev
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```
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2. Enjoy developing.
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95
README_dev_ja.md
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95
README_dev_ja.md
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@ -0,0 +1,95 @@
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## 開発者向け
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[English](/README_dev_en.md)
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## 前提
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- Linux or WSL2 (not tested for Mac )
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- Anaconda
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## 準備
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1. Anaconda の仮想環境を作成する
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```
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$ conda create -n vcclient-dev python=3.10
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$ conda activate vcclient-dev
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```
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2. リポジトリをクローンする
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```
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$ git clone https://github.com/w-okada/voice-changer.git
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$ cd voice-changer
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```
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## サーバ開発者向け
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1. 外部のリポジトリをサーバ内にクローンする
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```
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cd server
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git clone https://github.com/isletennos/MMVC_Client.git MMVC_Client_v13
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git clone https://github.com/isletennos/MMVC_Client.git MMVC_Client_v15
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git clone https://github.com/StarStringStudio/so-vits-svc.git so-vits-svc-40
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git clone https://github.com/StarStringStudio/so-vits-svc.git so-vits-svc-40v2
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cd so-vits-svc-40v2 && git checkout 08c70ff3d2f7958820b715db2a2180f4b7f92f8d && cd -
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git clone https://github.com/yxlllc/DDSP-SVC.git DDSP-SVC
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git clone https://github.com/liujing04/Retrieval-based-Voice-Conversion-WebUI.git RVC
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```
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2. 外部のモデルの重みを配置する
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copy weights of emmbedding or vocoder. These file path can be set as parameter when invoke server.
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(1) hubert_base.pt
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download from [here](https://huggingface.co/lj1995/VoiceConversionWebUI/tree/main)
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(2) content vec
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download ContentVec_legacy_500 from [here](https://github.com/auspicious3000/contentvec)
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(3) hubert_soft
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download from [here](https://github.com/bshall/hubert/releases/download/v0.1/hubert-soft-0d54a1f4.pt)
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(4) vocorder
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download nsf_hifigan_20221211.zip from [here](https://github.com/openvpi/vocoders/releases/tag/nsf-hifigan-v1) and expand it.
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3. モジュールをインストールする
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```
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$ pip install -r requirements.txt
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```
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4. サーバを起動する
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Run server with the below command. You can replace the path to each weight.
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```
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$ python3 MMVCServerSIO.py -p 18888 --https true \
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--content_vec_500 weights/checkpoint_best_legacy_500.pt \
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--hubert_base weights/hubert_base.pt \
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--hubert_soft weights/hubert-soft-0d54a1f4.pt \
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--nsf_hifigan weights/nsf_hifigan/model
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```
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5. 開発しましょう
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## クライアント開発者向け
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1. モジュールをインストールして、一度ビルドします
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```
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cd client
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cd lib
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npm install
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npm run build:dev
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cd ../demo
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npm install
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npm run build:dev
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```
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2. 開発しましょう
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@ -122,6 +122,8 @@ Clone this repository and use it. Setting up WSL2 is essential for Windows. Addi
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[Explanation video on installing WSL2 and Anaconda](https://youtu.be/fba9Zhsukqw)
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To run on Anaconda venv, see [server developer's guide](README_dev_en.md)
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## Real-time performance
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Conversion is almost instantaneous when using GPU.
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@ -1,25 +1,8 @@
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# uvicorn==0.21.1
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# pyOpenSSL==23.0.0
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# numpy==1.23.5
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# #torch==2.0.0
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# torch==1.13.1
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# resampy==0.4.2
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# matplotlib==3.7.1
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# librosa==0.10.0.post1
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# pyworld==0.3.2
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# python-socketio==5.7.2
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# fastapi==0.94.1
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# onnxruntime-gpu==1.14.1
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# python-multipart==0.0.6
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# fairseq==0.12.2
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# # apt-get update
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# # apt-get install -y emacs mlocate wget git curl gcc g++ make unzip
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# # wget https://repo.anaconda.com/archive/Anaconda3-2022.10-Linux-x86_64.sh
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# # bash Anaconda3-2022.10-Linux-x86_64.sh
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uvicorn==0.21.1
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pyOpenSSL==23.1.1
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numpy==1.23.5
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@ -42,3 +25,4 @@ gin==0.1.6
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gin_config==0.5.0
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einops==0.6.0
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local_attention==1.8.5
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websockets==11.0.2
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