blackteay/GPT-SoVITS
1
0
Fork 0
mirror of https://github.com/RVC-Boss/GPT-SoVITS.git synced 2025-10-05 22:20:01 +08:00
Code Issues Packages Projects Releases Wiki Activity

Update Install.sh, Support multi download source

Browse Source
This commit is contained in:
XXXXRT666 2025-04-18 07:42:40 +01:00 committed by GitHub
parent 12f3f96ef9
commit 83dcc1f87b
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
7 changed files with 141 additions and 61 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

10
README.md
View File

@ -64,7 +64,7 @@ If you are a Windows user (tested with win>=10), you can [download the integrate
```bash
conda create -n GPTSoVits python=3.9
conda activate GPTSoVits
bash install.sh
bash install.sh --source <HF|HF-Mirror|ModelScope> [--download-uvr5]
```
### macOS
@ -72,14 +72,12 @@ bash install.sh
**Note: The models trained with GPUs on Macs result in significantly lower quality compared to those trained on other devices, so we are temporarily using CPUs instead.**
1. Install Xcode command-line tools by running `xcode-select --install`.
2. Install FFmpeg by running `brew install ffmpeg`.
3. Install the program by running the following commands:
2. Install the program by running the following commands:
```bash
conda create -n GPTSoVits python=3.9
conda activate GPTSoVits
pip install -r extra-req.txt --no-deps
pip install -r requirements.txt
bash install.sh --source <HF|HF-Mirror|ModelScope> [--download-uvr5]
```
### Install Manually
@ -146,7 +144,7 @@ docker run --rm -it --gpus=all --env=is_half=False --volume=G:\GPT-SoVITS-Docker
## Pretrained Models
**If `install.sh` runs successfully, you may skip No.1 & No.2**
**If `install.sh` runs successfully, you may skip No.1,2,3**
**Users in China can [download all these models here](https://www.yuque.com/baicaigongchang1145haoyuangong/ib3g1e/dkxgpiy9zb96hob4#nVNhX).**

40
colab_webui.ipynb
View File

@ -20,6 +20,13 @@
"# 环境配置, 只需运行一次"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 1."
]
},
{
"cell_type": "code",
"execution_count": null,
@ -57,7 +64,14 @@
"\n",
"conda activate GPT-SoVITS\n",
"\n",
"bash install.sh"
"bash install.sh --source HF --download-uvr5"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 2."
]
},
{
@ -71,30 +85,6 @@
"%cd -q /content/GPT-SoVITS"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# UVR5 Model Download (Run Once Only)\n",
"# UVR5 模型下载, 只需运行一次"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "0NgxXg5sjv7z"
},
"outputs": [],
"source": [
"%cd -q /content/GPT-SoVITS\n",
"!wget https://www.modelscope.cn/models/XXXXRT/UVR5Weights4GSV/resolve/master/uvr5_weights.zip\n",
"!unzip uvr5_weights.zip\n",
"!rm -rf uvr5_weights.zip\n",
"!mv uvr5_weights/* tools/uvr5/uvr5_weights\n",
"!rm -rf uvr5_weights"
]
},
{
"cell_type": "markdown",
"metadata": {},

10
docs/cn/README.md
View File

@ -64,7 +64,7 @@ https://github.com/RVC-Boss/GPT-SoVITS/assets/129054828/05bee1fa-bdd8-4d85-9350-
```bash
conda create -n GPTSoVits python=3.9
conda activate GPTSoVits
bash install.sh
bash install.sh --source <HF|HF-Mirror|ModelScope> [--download-uvr5]
```
### macOS
@ -72,14 +72,12 @@ bash install.sh
**注: 在 Mac 上使用 GPU 训练的模型效果显著低于其他设备训练的模型, 所以我们暂时使用 CPU 进行训练.**
1. 运行 `xcode-select --install` 安装 Xcode command-line tools.
2. 运行 `brew install ffmpeg` 安装 FFmpeg.
3. 完成上述步骤后, 运行以下的命令来安装本项目:
2. 运行以下的命令来安装本项目:
```bash
conda create -n GPTSoVits python=3.9
conda activate GPTSoVits
pip install -r extra-req.txt --no-deps
pip install -r requirements.txt
bash install.sh --source <HF|HF-Mirror|ModelScope> [--download-uvr5]
```
### 手动安装
@ -148,7 +146,7 @@ docker run --rm -it --gpus=all --env=is_half=False --volume=G:\GPT-SoVITS-Docker
## 预训练模型
**若成功运行`install.sh`可跳过 No.1 & No.2**
**若成功运行`install.sh`可跳过 No.1,2,3**
**中国地区的用户可以[在此处下载这些模型](https://www.yuque.com/baicaigongchang1145haoyuangong/ib3g1e/dkxgpiy9zb96hob4#nVNhX).**

10
docs/ja/README.md
View File

@ -58,7 +58,7 @@ Windows ユーザー: (Windows 10 以降でテスト済み)、[統合パッケ
```bash
conda create -n GPTSoVits python=3.9
conda activate GPTSoVits
bash install.sh
bash install.sh --source <HF|HF-Mirror|ModelScope> [--download-uvr5]
```
### macOS
@ -66,14 +66,12 @@ bash install.sh
**注: Mac で GPU を使用して訓練されたモデルは、他のデバイスで訓練されたモデルと比較して著しく品質が低下するため、当面は CPU を使用して訓練することを強く推奨します.**
1. `xcode-select --install` を実行して、Xcode コマンドラインツールをインストールします.
2. `brew install ffmpeg` を実行して FFmpeg をインストールします.
3. 上記の手順を完了した後、以下のコマンドを実行してこのプロジェクトをインストールします.
2. 以下のコマンドを実行してこのプロジェクトをインストールします.
```bash
conda create -n GPTSoVits python=3.9
conda activate GPTSoVits
pip install -r extra-req.txt --no-deps
pip install -r requirements.txt
bash install.sh --source <HF|HF-Mirror|ModelScope> [--download-uvr5]
```
### 手動インストール
@ -140,7 +138,7 @@ docker run --rm -it --gpus=all --env=is_half=False --volume=G:\GPT-SoVITS-Docker
## 事前訓練済みモデル
**`install.sh`が正常に実行された場合、No.1 & No.2 はスキップしてかまいません.**
**`install.sh`が正常に実行された場合、No.1,2,3 はスキップしてかまいません.**
1. [GPT-SoVITS Models](https://huggingface.co/lj1995/GPT-SoVITS) から事前訓練済みモデルをダウンロードし、`GPT_SoVITS/pretrained_models` ディレクトリに配置してください.

10
docs/ko/README.md
View File

@ -58,7 +58,7 @@ Windows 사용자라면 (win>=10에서 테스트됨), [통합 패키지를 다
```bash
conda create -n GPTSoVits python=3.9
conda activate GPTSoVits
bash install.sh
bash install.sh --source <HF|HF-Mirror|ModelScope> [--download-uvr5]
```
### macOS
@ -66,14 +66,12 @@ bash install.sh
**주의: Mac에서 GPU로 훈련된 모델은 다른 OS에서 훈련된 모델에 비해 품질이 낮습니다. 해당 문제를 해결하기 전까지 MacOS에선 CPU를 사용하여 훈련을 진행합니다.**
1. `xcode-select --install`을 실행하여 Xcode 커맨드라인 도구를 설치하세요.
2. `brew install ffmpeg` 명령어를 실행하여 FFmpeg를 설치합니다.
3. 위의 단계를 완료한 후, 다음 명령어를 실행하여 이 프로젝트를 설치하세요.
2. 다음 명령어를 실행하여 이 프로젝트를 설치하세요.
```bash
conda create -n GPTSoVits python=3.9
conda activate GPTSoVits
pip install -r extra-req.txt --no-deps
pip install -r requirements.txt
bash install.sh --source <HF|HF-Mirror|ModelScope> [--download-uvr5]
```
### 수동 설치
@ -145,7 +143,7 @@ docker run --rm -it --gpus=all --env=is_half=False --volume=G:\GPT-SoVITS-Docker
## 사전 학습된 모델
**`install.sh`가 성공적으로 실행되면 No.1 & No.2 은 건너뛰어도 됩니다.**
**`install.sh`가 성공적으로 실행되면 No.1,2,3 은 건너뛰어도 됩니다.**
1. [GPT-SoVITS Models](https://huggingface.co/lj1995/GPT-SoVITS) 에서 사전 학습된 모델을 다운로드하고, `GPT_SoVITS/pretrained_models` 디렉토리에 배치하세요.

10
docs/tr/README.md
View File

@ -60,7 +60,7 @@ Eğer bir Windows kullanıcısıysanız (win>=10 ile test edilmiştir), [entegre
```bash
conda create -n GPTSoVits python=3.9
conda activate GPTSoVits
bash install.sh
bash install.sh --source <HF|HF-Mirror|ModelScope> [--download-uvr5]
```
### macOS
@ -68,14 +68,12 @@ bash install.sh
**Not: Mac'lerde GPU'larla eğitilen modeller, diğer cihazlarda eğitilenlere göre önemli ölçüde daha düşük kalitede sonuç verir, bu nedenle geçici olarak CPU'lar kullanıyoruz.**
1. `xcode-select --install` komutunu çalıştırarak Xcode komut satırı araçlarını yükleyin.
2. FFmpeg'i yüklemek için `brew install ffmpeg` komutunu çalıştırın.
3. Aşağıdaki komutları çalıştırarak programı yükleyin:
2. Aşağıdaki komutları çalıştırarak programı yükleyin:
```bash
conda create -n GPTSoVits python=3.9
conda activate GPTSoVits
pip install -r extra-req.txt --no-deps
pip install -r requirements.txt
bash install.sh --source <HF|HF-Mirror|ModelScope> [--download-uvr5]
```
### El ile Yükleme
@ -140,7 +138,7 @@ docker run --rm -it --gpus=all --env=is_half=False --volume=G:\GPT-SoVITS-Docker
## Önceden Eğitilmiş Modeller
**Eğer `install.sh` başarıyla çalıştırılırsa, No.1 & No.2 adımını atlayabilirsiniz.**
**Eğer `install.sh` başarıyla çalıştırılırsa, No.1,2,3 adımını atlayabilirsiniz.**
1. [GPT-SoVITS Models](https://huggingface.co/lj1995/GPT-SoVITS) üzerinden önceden eğitilmiş modelleri indirip `GPT_SoVITS/pretrained_models` dizinine yerleştirin.

112
install.sh
View File

@ -9,6 +9,92 @@ set -e
trap 'echo "Error Occured at \"$BASH_COMMAND\" with exit code $?"; exit 1' ERR
is_HF=false
is_HF_MIRROR=false
is_MODELSCOPE=false
DOWNLOAD_UVR5=false
print_help() {
echo "Usage: bash install.sh [OPTIONS]"
echo ""
echo "Options:"
echo " --source HF|HF-Mirror|ModelScope Specify the model source (REQUIRED)"
echo " --download-uvr5 Enable downloading the UVR5 model"
echo " -h, --help Show this help message and exit"
echo ""
echo "Examples:"
echo " bash install.sh --source HF --download-uvr5"
echo " bash install.sh --source ModelScope"
}
# Show help if no arguments provided
if [[ $# -eq 0 ]]; then
print_help
exit 0
fi
# Parse arguments
while [[ $# -gt 0 ]]; do
case "$1" in
--source)
case "$2" in
HF)
is_HF=true
;;
HF-Mirror)
is_HF_MIRROR=true
;;
ModelScope)
is_MODELSCOPE=true
;;
*)
echo "Error: Invalid Download Source: $2"
echo "Choose From: [HF, HF-Mirror, ModelScope]"
exit 1
;;
esac
shift 2
;;
--download-uvr5)
DOWNLOAD_UVR5=true
shift
;;
-h|--help)
print_help
exit 0
;;
*)
echo "Unknown Argument: $1"
echo "Use -h or --help to see available options."
exit 1
;;
esac
done
if ! $is_HF && ! $is_HF_MIRROR && ! $is_MODELSCOPE; then
echo "Error: Download Source is REQUIRED"
echo ""
print_help
exit 1
fi
if $is_HF; then
PRETRINED_URL="https://huggingface.co/XXXXRT/GPT-SoVITS-Pretrained/resolve/main/pretrained_models.zip"
G2PW_URL="https://huggingface.co/XXXXRT/GPT-SoVITS-Pretrained/resolve/main/G2PWModel.zip"
UVR5_URL="https://huggingface.co/XXXXRT/GPT-SoVITS-Pretrained/resolve/main/uvr5_weights.zip"
LANG_DETECT_URL="https://huggingface.co/XXXXRT/GPT-SoVITS-Pretrained/blob/main/lid.176.bin.zip"
elif $is_HF_MIRROR; then
PRETRINED_URL="https://hf-mirror.com/XXXXRT/GPT-SoVITS-Pretrained/resolve/main/pretrained_models.zip"
G2PW_URL="https://hf-mirror.com/XXXXRT/GPT-SoVITS-Pretrained/resolve/main/G2PWModel.zip"
UVR5_URL="https://hf-mirror.com/XXXXRT/GPT-SoVITS-Pretrained/resolve/main/uvr5_weights.zip"
LANG_DETECT_URL="https://hf-mirror.com/XXXXRT/GPT-SoVITS-Pretrained/blob/main/lid.176.bin.zip"
elif $is_MODELSCOPE; then
PRETRINED_URL="https://www.modelscope.cn/models/XXXXRT/GPT-SoVITS-Pretrained/resolve/master/pretrained_models.zip"
G2PW_URL="https://www.modelscope.cn/models/XXXXRT/GSV-G2PW/resolve/master/G2PWModel.zip"
UVR5_URL="https://www.modelscope.cn/models/XXXXRT/UVR5Weights4GSV/resolve/master/uvr5_weights.zip"
LANG_DETECT_URL="https://www.modelscope.cn/models/XXXXRT/GSV-Lang-Detect/resolve/master/lid.176.bin.zip"
fi
# 安装构建工具
# Install build tools
echo "Installing GCC..."
@ -31,7 +117,7 @@ if find "GPT_SoVITS/pretrained_models" -mindepth 1 ! -name '.gitignore' | grep -
echo "Pretrained Model Exists"
else
echo "Download Pretrained Models"
wget --tries=25 --wait=5 --read-timeout=40 --retry-on-http-error=404 "https://www.modelscope.cn/models/XXXXRT/GPT-SoVITS-Pretrained/resolve/master/pretrained_models.zip"
wget --tries=25 --wait=5 --read-timeout=40 --retry-on-http-error=404 "$PRETRINED_URL"
unzip pretrained_models.zip
rm -rf pretrained_models.zip
@ -42,25 +128,39 @@ fi
# Download G2PW Models
if [ ! -d "GPT_SoVITS/text/G2PWModel" ]; then
echo "Download G2PWModel"
wget --tries=25 --wait=5 --read-timeout=40 --retry-on-http-error=404 "https://www.modelscope.cn/models/kamiorinn/g2pw/resolve/master/G2PWModel_1.1.zip"
wget --tries=25 --wait=5 --read-timeout=40 --retry-on-http-error=404 "$G2PW_URL"
unzip G2PWModel_1.1.zip
rm -rf G2PWModel_1.1.zip
mv G2PWModel_1.1 GPT_SoVITS/text/G2PWModel
unzip G2PWModel.zip
rm -rf G2PWModel.zip
mv G2PWModel GPT_SoVITS/text/G2PWModel
else
echo "G2PWModel Exists"
fi
if [ ! -d "GPT_SoVITS/pretrained_models/fast_langdetect" ]; then
echo "Download Fast Langdetect Model"
wget --tries=25 --wait=5 --read-timeout=40 --retry-on-http-error=404 "https://dl.fbaipublicfiles.com/fasttext/supervised-models/lid.176.bin"
wget --tries=25 --wait=5 --read-timeout=40 --retry-on-http-error=404 "$LANG_DETECT_URL"
unzip lid.176.bin.zip
rm -rf lid.176.bin.zip
mkdir "GPT_SoVITS/pretrained_models/fast_langdetect"
mv "lid.176.bin" "GPT_SoVITS/pretrained_models/fast_langdetect"
else
echo "Fast Langdetect Model Exists"
fi
if [ "$DOWNLOAD_UVR5" = "true" ] && find "tools/uvr5/uvr5_weights" -mindepth 1 ! -name '.gitignore' | grep -q .; then
echo "Download UVR5 Model"
wget --tries=25 --wait=5 --read-timeout=40 --retry-on-http-error=404 "$UVR5_URL"
unzip uvr5_weights.zip
rm -rf uvr5_weights.zip
mv uvr5_weights/* tools/uvr5/uvr5_weights
rm -rf uvr5_weights
else
echo "UVR5 Model Exists"
fi
# 设置编译环境
# Set up build environment
export CMAKE_MAKE_PROGRAM="$CONDA_PREFIX/bin/cmake"