diff --git a/.dockerignore b/.dockerignore deleted file mode 100644 index 4eca27be..00000000 --- a/.dockerignore +++ /dev/null @@ -1,8 +0,0 @@ -docs -logs -output -reference -SoVITS_weights -GPT_weights -TEMP -.git diff --git a/Dockerfile b/Dockerfile deleted file mode 100644 index 80cd9f3a..00000000 --- a/Dockerfile +++ /dev/null @@ -1,42 +0,0 @@ -# Base CUDA image -FROM cnstark/pytorch:2.0.1-py3.9.17-cuda11.8.0-ubuntu20.04 - -LABEL maintainer="breakstring@hotmail.com" -LABEL version="dev-20240209" -LABEL description="Docker image for GPT-SoVITS" - - -# Install 3rd party apps -ENV DEBIAN_FRONTEND=noninteractive -ENV TZ=Etc/UTC -RUN apt-get update && \ - apt-get install -y --no-install-recommends tzdata ffmpeg libsox-dev parallel aria2 git git-lfs && \ - git lfs install && \ - rm -rf /var/lib/apt/lists/* - -# Copy only requirements.txt initially to leverage Docker cache -WORKDIR /workspace -COPY requirements.txt /workspace/ -RUN pip install --no-cache-dir -r requirements.txt - -# Define a build-time argument for image type -ARG IMAGE_TYPE=full - -# Conditional logic based on the IMAGE_TYPE argument -# Always copy the Docker directory, but only use it if IMAGE_TYPE is not "elite" -COPY ./Docker /workspace/Docker -# elite 类型的镜像里面不包含额外的模型 -RUN if [ "$IMAGE_TYPE" != "elite" ]; then \ - chmod +x /workspace/Docker/download.sh && \ - /workspace/Docker/download.sh && \ - python /workspace/Docker/download.py && \ - python -m nltk.downloader averaged_perceptron_tagger cmudict; \ - fi - - -# Copy the rest of the application -COPY . /workspace - -EXPOSE 9871 9872 9873 9874 9880 - -CMD ["python", "webui.py"] diff --git a/GPT_SoVITS_Inference.ipynb b/GPT_SoVITS_Inference.ipynb deleted file mode 100644 index a5b55325..00000000 --- a/GPT_SoVITS_Inference.ipynb +++ /dev/null @@ -1,152 +0,0 @@ -{ - "nbformat": 4, - "nbformat_minor": 0, - "metadata": { - "colab": { - "provenance": [] - }, - "kernelspec": { - "name": "python3", - "display_name": "Python 3" - }, - "accelerator": "GPU" - }, - "cells": [ - { - "cell_type": "markdown", - "source": [ - "# Credits for bubarino giving me the huggingface import code (感谢 bubarino 给了我 huggingface 导入代码)" - ], - "metadata": { - "id": "himHYZmra7ix" - } - }, - { - "cell_type": "code", - "metadata": { - "id": "e9b7iFV3dm1f" - }, - "source": [ - "!git clone https://github.com/RVC-Boss/GPT-SoVITS.git\n", - "%cd GPT-SoVITS\n", - "!apt-get update && apt-get install -y --no-install-recommends tzdata ffmpeg libsox-dev parallel aria2 git git-lfs && git lfs install\n", - "!pip install -r requirements.txt" - ], - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "code", - "source": [ - "# @title Download pretrained models 下载预训练模型\n", - "!mkdir -p /content/GPT-SoVITS/GPT_SoVITS/pretrained_models\n", - "!mkdir -p /content/GPT-SoVITS/tools/damo_asr/models\n", - "!mkdir -p /content/GPT-SoVITS/tools/uvr5\n", - "%cd /content/GPT-SoVITS/GPT_SoVITS/pretrained_models\n", - "!git clone https://huggingface.co/lj1995/GPT-SoVITS\n", - "%cd /content/GPT-SoVITS/tools/damo_asr/models\n", - "!git clone https://www.modelscope.cn/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch.git\n", - "!git clone https://www.modelscope.cn/damo/speech_fsmn_vad_zh-cn-16k-common-pytorch.git\n", - "!git clone https://www.modelscope.cn/damo/punc_ct-transformer_zh-cn-common-vocab272727-pytorch.git\n", - "# @title UVR5 pretrains 安装uvr5模型\n", - "%cd /content/GPT-SoVITS/tools/uvr5\n", - "!git clone https://huggingface.co/Delik/uvr5_weights\n", - "!git config core.sparseCheckout true\n", - "!mv /content/GPT-SoVITS/GPT_SoVITS/pretrained_models/GPT-SoVITS/* /content/GPT-SoVITS/GPT_SoVITS/pretrained_models/" - ], - "metadata": { - "id": "0NgxXg5sjv7z", - "cellView": "form" - }, - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "code", - "source": [ - "#@title Create folder models 创建文件夹模型\n", - "import os\n", - "base_directory = \"/content/GPT-SoVITS\"\n", - "folder_names = [\"SoVITS_weights\", \"GPT_weights\"]\n", - "\n", - "for folder_name in folder_names:\n", - " if os.path.exists(os.path.join(base_directory, folder_name)):\n", - " print(f\"The folder '{folder_name}' already exists. (文件夹'{folder_name}'已经存在。)\")\n", - " else:\n", - " os.makedirs(os.path.join(base_directory, folder_name))\n", - " print(f\"The folder '{folder_name}' was created successfully! (文件夹'{folder_name}'已成功创建！)\")\n", - "\n", - "print(\"All folders have been created. (所有文件夹均已创建。)\")" - ], - "metadata": { - "cellView": "form", - "id": "cPDEH-9czOJF" - }, - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "code", - "source": [ - "import requests\n", - "import zipfile\n", - "import shutil\n", - "import os\n", - "\n", - "#@title Import model 导入模型 (HuggingFace)\n", - "hf_link = 'https://huggingface.co/modelloosrvcc/Nagisa_Shingetsu_GPT-SoVITS/resolve/main/Nagisa.zip' #@param {type: \"string\"}\n", - "\n", - "output_path = '/content/'\n", - "\n", - "response = requests.get(hf_link)\n", - "with open(output_path + 'file.zip', 'wb') as file:\n", - " file.write(response.content)\n", - "\n", - "with zipfile.ZipFile(output_path + 'file.zip', 'r') as zip_ref:\n", - " zip_ref.extractall(output_path)\n", - "\n", - "os.remove(output_path + \"file.zip\")\n", - "\n", - "source_directory = output_path\n", - "SoVITS_destination_directory = '/content/GPT-SoVITS/SoVITS_weights'\n", - "GPT_destination_directory = '/content/GPT-SoVITS/GPT_weights'\n", - "\n", - "for filename in os.listdir(source_directory):\n", - " if filename.endswith(\".pth\"):\n", - " source_path = os.path.join(source_directory, filename)\n", - " destination_path = os.path.join(SoVITS_destination_directory, filename)\n", - " shutil.move(source_path, destination_path)\n", - "\n", - "for filename in os.listdir(source_directory):\n", - " if filename.endswith(\".ckpt\"):\n", - " source_path = os.path.join(source_directory, filename)\n", - " destination_path = os.path.join(GPT_destination_directory, filename)\n", - " shutil.move(source_path, destination_path)\n", - "\n", - "print(f'Model downloaded. (模型已下载。)')" - ], - "metadata": { - "cellView": "form", - "id": "vbZY-LnM0tzq" - }, - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "code", - "source": [ - "# @title launch WebUI 启动WebUI\n", - "!/usr/local/bin/pip install ipykernel\n", - "!sed -i '10s/False/True/' /content/GPT-SoVITS/config.py\n", - "%cd /content/GPT-SoVITS/\n", - "!/usr/local/bin/python webui.py" - ], - "metadata": { - "id": "4oRGUzkrk8C7", - "cellView": "form" - }, - "execution_count": null, - "outputs": [] - } - ] -} \ No newline at end of file diff --git a/README.md b/README.md index f6fe3d77..36ee3958 100644 --- a/README.md +++ b/README.md @@ -1,153 +1,25 @@ # Jarod's NOTE -Working on turning this into a package. Right now, the API *does in fact* work to make requests to and this can be installed. Will get instrucitons out sometime in the future. +Working on turning this into a package. Right now, the API *does in fact* work to make requests to and this can be installed. -
+## Quick Install and Usage +Ideally, do this all inside of a venv for package isolation +1. Install by doing: + ``` + pip install git+https://github.com/JarodMica/GPT-SoVITS.git + ``` +2. Make sure torch is installed with CUDA enabled. Reccomend to run `pip uninstall torch` to uninstall torch, then reinstall with the following. I chose 2.4.0+cu121: + ``` + pip install torch==2.4.0 torchvision==0.19.0 torchaudio==2.4.0 --index-url https://download.pytorch.org/whl/cu121 + ``` - -

GPT-SoVITS-WebUI

-A Powerful Few-shot Voice Conversion and Text-to-Speech WebUI.

- -[![madewithlove](https://img.shields.io/badge/made_with-%E2%9D%A4-red?style=for-the-badge&labelColor=orange)](https://github.com/RVC-Boss/GPT-SoVITS) - -RVC-Boss%2FGPT-SoVITS | Trendshift - - - -[![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-Boss/GPT-SoVITS/blob/main/colab_webui.ipynb) -[![License](https://img.shields.io/badge/LICENSE-MIT-green.svg?style=for-the-badge)](https://github.com/RVC-Boss/GPT-SoVITS/blob/main/LICENSE) -[![Huggingface](https://img.shields.io/badge/🤗%20-online%20demo-yellow.svg?style=for-the-badge)](https://huggingface.co/spaces/lj1995/GPT-SoVITS-v2) -[![Discord](https://img.shields.io/discord/1198701940511617164?color=%23738ADB&label=Discord&style=for-the-badge)](https://discord.gg/dnrgs5GHfG) - -**English** | [**中文简体**](./docs/cn/README.md) | [**日本語**](./docs/ja/README.md) | [**한국어**](./docs/ko/README.md) | [**Türkçe**](./docs/tr/README.md) - -
- ---- - -## Features: - -1. **Zero-shot TTS:** Input a 5-second vocal sample and experience instant text-to-speech conversion. - -2. **Few-shot TTS:** Fine-tune the model with just 1 minute of training data for improved voice similarity and realism. - -3. **Cross-lingual Support:** Inference in languages different from the training dataset, currently supporting English, Japanese, Korean, Cantonese and Chinese. - -4. **WebUI Tools:** Integrated tools include voice accompaniment separation, automatic training set segmentation, Chinese ASR, and text labeling, assisting beginners in creating training datasets and GPT/SoVITS models. - -**Check out our [demo video](https://www.bilibili.com/video/BV12g4y1m7Uw) here!** - -Unseen speakers few-shot fine-tuning demo: - -https://github.com/RVC-Boss/GPT-SoVITS/assets/129054828/05bee1fa-bdd8-4d85-9350-80c060ab47fb - -**User guide: [简体中文](https://www.yuque.com/baicaigongchang1145haoyuangong/ib3g1e) | [English](https://rentry.co/GPT-SoVITS-guide#/)** - -## Installation - -For users in China, you can [click here](https://www.codewithgpu.com/i/RVC-Boss/GPT-SoVITS/GPT-SoVITS-Official) to use AutoDL Cloud Docker to experience the full functionality online. - -### Tested Environments - -- Python 3.9, PyTorch 2.0.1, CUDA 11 -- Python 3.10.13, PyTorch 2.1.2, CUDA 12.3 -- Python 3.9, PyTorch 2.2.2, macOS 14.4.1 (Apple silicon) -- Python 3.9, PyTorch 2.2.2, CPU devices - -_Note: numba==0.56.4 requires py<3.11_ - -### Windows - -If you are a Windows user (tested with win>=10), you can [download the integrated package](https://huggingface.co/lj1995/GPT-SoVITS-windows-package/resolve/main/GPT-SoVITS-beta.7z?download=true) and double-click on _go-webui.bat_ to start GPT-SoVITS-WebUI. - -**Users in China can [download the package here](https://www.yuque.com/baicaigongchang1145haoyuangong/ib3g1e/dkxgpiy9zb96hob4#KTvnO).** - -### Linux - -```bash -conda create -n GPTSoVits python=3.9 -conda activate GPTSoVits -bash install.sh +Now to use it, so far I've only tested it with the api_v2.py. Given that the install above went fine, you should now be able to run: ``` - -### macOS - -**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: - -```bash -conda create -n GPTSoVits python=3.9 -conda activate GPTSoVits -pip install -r requirements.txt -``` - -### Install Manually - -#### Install FFmpeg - -##### Conda Users - -```bash -conda install ffmpeg -``` - -##### Ubuntu/Debian Users - -```bash -sudo apt install ffmpeg -sudo apt install libsox-dev -conda install -c conda-forge 'ffmpeg<7' -``` - -##### Windows Users - -Download and place [ffmpeg.exe](https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/ffmpeg.exe) and [ffprobe.exe](https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/ffprobe.exe) in the GPT-SoVITS root. - -Install [Visual Studio 2017](https://aka.ms/vs/17/release/vc_redist.x86.exe) (Korean TTS Only) - -##### MacOS Users -```bash -brew install ffmpeg -``` - -#### Install Dependences - -```bash -pip install -r requirements.txt -``` - -### Using Docker - -#### docker-compose.yaml configuration - -0. Regarding image tags: Due to rapid updates in the codebase and the slow process of packaging and testing images, please check [Docker Hub](https://hub.docker.com/r/breakstring/gpt-sovits) for the currently packaged latest images and select as per your situation, or alternatively, build locally using a Dockerfile according to your own needs. -1. Environment Variables： - -- is_half: Controls half-precision/double-precision. This is typically the cause if the content under the directories 4-cnhubert/5-wav32k is not generated correctly during the "SSL extracting" step. Adjust to True or False based on your actual situation. - -2. Volumes Configuration，The application's root directory inside the container is set to /workspace. The default docker-compose.yaml lists some practical examples for uploading/downloading content. -3. shm_size： The default available memory for Docker Desktop on Windows is too small, which can cause abnormal operations. Adjust according to your own situation. -4. Under the deploy section, GPU-related settings should be adjusted cautiously according to your system and actual circumstances. - -#### Running with docker compose - -``` -docker compose -f "docker-compose.yaml" up -d -``` - -#### Running with docker command - -As above, modify the corresponding parameters based on your actual situation, then run the following command: - -``` -docker run --rm -it --gpus=all --env=is_half=False --volume=G:\GPT-SoVITS-DockerTest\output:/workspace/output --volume=G:\GPT-SoVITS-DockerTest\logs:/workspace/logs --volume=G:\GPT-SoVITS-DockerTest\SoVITS_weights:/workspace/SoVITS_weights --workdir=/workspace -p 9880:9880 -p 9871:9871 -p 9872:9872 -p 9873:9873 -p 9874:9874 --shm-size="16G" -d breakstring/gpt-sovits:xxxxx +gpt_sovits_api ``` +Which will bootup local server that you can make requests to. Checkout `test.py` and `test_streaming.py` to get an idea for how you might be able to use the API. ## Pretrained Models - -**Users in China can [download all these models here](https://www.yuque.com/baicaigongchang1145haoyuangong/ib3g1e/dkxgpiy9zb96hob4#nVNhX).** +Probably don't need to follow the instructions for the below, these are just kept here for reference for now. 1. Download pretrained models from [GPT-SoVITS Models](https://huggingface.co/lj1995/GPT-SoVITS) and place them in `GPT_SoVITS/pretrained_models`. @@ -159,193 +31,8 @@ docker run --rm -it --gpus=all --env=is_half=False --volume=G:\GPT-SoVITS-Docker 5. For English or Japanese ASR (additionally), download models from [Faster Whisper Large V3](https://huggingface.co/Systran/faster-whisper-large-v3) and place them in `tools/asr/models`. Also, [other models](https://huggingface.co/Systran) may have the similar effect with smaller disk footprint. -## Dataset Format - -The TTS annotation .list file format: - -``` -vocal_path|speaker_name|language|text -``` - -Language dictionary: - -- 'zh': Chinese -- 'ja': Japanese -- 'en': English -- 'ko': Korean -- 'yue': Cantonese - -Example: - -``` -D:\GPT-SoVITS\xxx/xxx.wav|xxx|en|I like playing Genshin. -``` - -## Finetune and inference - - ### Open WebUI - - #### Integrated Package Users - - Double-click `go-webui.bat`or use `go-webui.ps1` - if you want to switch to V1,then double-click`go-webui-v1.bat` or use `go-webui-v1.ps1` - - #### Others - - ```bash - python webui.py - ``` - - if you want to switch to V1,then - - ```bash - python webui.py v1 - ``` -Or maunally switch version in WebUI - - ### Finetune - - #### Path Auto-filling is now supported - - 1.Fill in the audio path - - 2.Slice the audio into small chunks - - 3.Denoise(optinal) - - 4.ASR - - 5.Proofreading ASR transcriptions - - 6.Go to the next Tab, then finetune the model - - ### Open Inference WebUI - - #### Integrated Package Users - - Double-click `go-webui-v2.bat` or use `go-webui-v2.ps1` ,then open the inference webui at `1-GPT-SoVITS-TTS/1C-inference` - - #### Others - - ```bash - python GPT_SoVITS/inference_webui.py - ``` - OR - - ```bash - python webui.py - ``` -then open the inference webui at `1-GPT-SoVITS-TTS/1C-inference` - - ## V2 Release Notes - -New Features: - -1. Support Korean and Cantonese - -2. An optimized text frontend - -3. Pre-trained model extended from 2k hours to 5k hours - -4. Improved synthesis quality for low-quality reference audio - - [more details](https://github.com/RVC-Boss/GPT-SoVITS/wiki/GPT%E2%80%90SoVITS%E2%80%90v2%E2%80%90features-(%E6%96%B0%E7%89%B9%E6%80%A7) ) - -Use v2 from v1 environment: - -1. `pip install -r requirements.txt` to update some packages - -2. Clone the latest codes from github. - -3. Download v2 pretrained models from [huggingface](https://huggingface.co/lj1995/GPT-SoVITS/tree/main/gsv-v2final-pretrained) and put them into `GPT_SoVITS\pretrained_models\gsv-v2final-pretrained`. - - Chinese v2 additional: [G2PWModel_1.1.zip](https://paddlespeech.bj.bcebos.com/Parakeet/released_models/g2p/G2PWModel_1.1.zip)（Download G2PW models, unzip and rename to `G2PWModel`, and then place them in `GPT_SoVITS/text`. - -## Todo List - -- [x] **High Priority:** - - - [x] Localization in Japanese and English. - - [x] User guide. - - [x] Japanese and English dataset fine tune training. - -- [ ] **Features:** - - [x] Zero-shot voice conversion (5s) / few-shot voice conversion (1min). - - [x] TTS speaking speed control. - - [ ] ~~Enhanced TTS emotion control.~~ - - [ ] Experiment with changing SoVITS token inputs to probability distribution of GPT vocabs (transformer latent). - - [x] Improve English and Japanese text frontend. - - [ ] Develop tiny and larger-sized TTS models. - - [x] Colab scripts. - - [ ] Try expand training dataset (2k hours -> 10k hours). - - [x] better sovits base model (enhanced audio quality) - - [ ] model mix - -## (Additional) Method for running from the command line -Use the command line to open the WebUI for UVR5 -``` -python tools/uvr5/webui.py "" -``` - -This is how the audio segmentation of the dataset is done using the command line -``` -python audio_slicer.py \ - --input_path "" \ - --output_root "" \ - --threshold \ - --min_length \ - --min_interval - --hop_size -``` -This is how dataset ASR processing is done using the command line(Only Chinese) -``` -python tools/asr/funasr_asr.py -i -o -``` -ASR processing is performed through Faster_Whisper(ASR marking except Chinese) - -(No progress bars, GPU performance may cause time delays) -``` -python ./tools/asr/fasterwhisper_asr.py -i -o -l -p -``` -A custom list save path is enabled - ## Credits -Special thanks to the following projects and contributors: +Special thanks to the RVC-Boss for getting this wonderful tool up and going, as well as all of the other attributions used to build it: -### Theoretical Research -- [ar-vits](https://github.com/innnky/ar-vits) -- [SoundStorm](https://github.com/yangdongchao/SoundStorm/tree/master/soundstorm/s1/AR) -- [vits](https://github.com/jaywalnut310/vits) -- [TransferTTS](https://github.com/hcy71o/TransferTTS/blob/master/models.py#L556) -- [contentvec](https://github.com/auspicious3000/contentvec/) -- [hifi-gan](https://github.com/jik876/hifi-gan) -- [fish-speech](https://github.com/fishaudio/fish-speech/blob/main/tools/llama/generate.py#L41) -### Pretrained Models -- [Chinese Speech Pretrain](https://github.com/TencentGameMate/chinese_speech_pretrain) -- [Chinese-Roberta-WWM-Ext-Large](https://huggingface.co/hfl/chinese-roberta-wwm-ext-large) -### Text Frontend for Inference -- [paddlespeech zh_normalization](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/paddlespeech/t2s/frontend/zh_normalization) -- [LangSegment](https://github.com/juntaosun/LangSegment) -- [g2pW](https://github.com/GitYCC/g2pW) -- [pypinyin-g2pW](https://github.com/mozillazg/pypinyin-g2pW) -- [paddlespeech g2pw](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/paddlespeech/t2s/frontend/g2pw) -### WebUI Tools -- [ultimatevocalremovergui](https://github.com/Anjok07/ultimatevocalremovergui) -- [audio-slicer](https://github.com/openvpi/audio-slicer) -- [SubFix](https://github.com/cronrpc/SubFix) -- [FFmpeg](https://github.com/FFmpeg/FFmpeg) -- [gradio](https://github.com/gradio-app/gradio) -- [faster-whisper](https://github.com/SYSTRAN/faster-whisper) -- [FunASR](https://github.com/alibaba-damo-academy/FunASR) - -Thankful to @Naozumi520 for providing the Cantonese training set and for the guidance on Cantonese-related knowledge. - -## Thanks to all contributors for their efforts - - - - +**Original Repo:** https://github.com/RVC-Boss/GPT-SoVITS \ No newline at end of file diff --git a/colab_webui.ipynb b/colab_webui.ipynb deleted file mode 100644 index 838f8264..00000000 --- a/colab_webui.ipynb +++ /dev/null @@ -1,97 +0,0 @@ -{ - "nbformat": 4, - "nbformat_minor": 0, - "metadata": { - "colab": { - "provenance": [], - "include_colab_link": true - }, - "kernelspec": { - "name": "python3", - "display_name": "Python 3" - }, - "accelerator": "GPU" - }, - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "view-in-github", - "colab_type": "text" - }, - "source": [ - "\"Open" - ] - }, - { - "cell_type": "markdown", - "source": [ - "环境配置 environment" - ], - "metadata": { - "id": "_o6a8GS2lWQM" - } - }, - { - "cell_type": "code", - "metadata": { - "id": "e9b7iFV3dm1f" - }, - "source": [ - "!pip install -q condacolab\n", - "# Setting up condacolab and installing packages\n", - "import condacolab\n", - "condacolab.install_from_url(\"https://repo.anaconda.com/miniconda/Miniconda3-py39_23.11.0-2-Linux-x86_64.sh\")\n", - "%cd -q /content\n", - "!git clone https://github.com/RVC-Boss/GPT-SoVITS\n", - "!conda install -y -q -c pytorch -c nvidia cudatoolkit\n", - "%cd -q /content/GPT-SoVITS\n", - "!conda install -y -q -c conda-forge gcc gxx ffmpeg cmake -c pytorch -c nvidia\n", - "!/usr/local/bin/pip install -r requirements.txt" - ], - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "code", - "source": [ - "# @title Download pretrained models 下载预训练模型\n", - "!mkdir -p /content/GPT-SoVITS/GPT_SoVITS/pretrained_models\n", - "!mkdir -p /content/GPT-SoVITS/tools/damo_asr/models\n", - "!mkdir -p /content/GPT-SoVITS/tools/uvr5\n", - "%cd /content/GPT-SoVITS/GPT_SoVITS/pretrained_models\n", - "!git clone https://huggingface.co/lj1995/GPT-SoVITS\n", - "%cd /content/GPT-SoVITS/tools/damo_asr/models\n", - "!git clone https://www.modelscope.cn/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch.git\n", - "!git clone https://www.modelscope.cn/damo/speech_fsmn_vad_zh-cn-16k-common-pytorch.git\n", - "!git clone https://www.modelscope.cn/damo/punc_ct-transformer_zh-cn-common-vocab272727-pytorch.git\n", - "# @title UVR5 pretrains 安装uvr5模型\n", - "%cd /content/GPT-SoVITS/tools/uvr5\n", - "%rm -r uvr5_weights\n", - "!git clone https://huggingface.co/Delik/uvr5_weights\n", - "!git config core.sparseCheckout true\n", - "!mv /content/GPT-SoVITS/GPT_SoVITS/pretrained_models/GPT-SoVITS/* /content/GPT-SoVITS/GPT_SoVITS/pretrained_models/" - ], - "metadata": { - "id": "0NgxXg5sjv7z" - }, - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "code", - "source": [ - "# @title launch WebUI 启动WebUI\n", - "!/usr/local/bin/pip install ipykernel\n", - "!sed -i '10s/False/True/' /content/GPT-SoVITS/config.py\n", - "%cd /content/GPT-SoVITS/\n", - "!/usr/local/bin/python webui.py" - ], - "metadata": { - "id": "4oRGUzkrk8C7" - }, - "execution_count": null, - "outputs": [] - } - ] -} diff --git a/docker-compose.yaml b/docker-compose.yaml deleted file mode 100644 index aca8ab9e..00000000 --- a/docker-compose.yaml +++ /dev/null @@ -1,32 +0,0 @@ -version: '3.8' - -services: - gpt-sovits: - image: breakstring/gpt-sovits:latest # please change the image name and tag base your environment. If the tag contains the word 'elite', such as "latest-elite", it indicates that the image does not include the necessary models such as GPT-SoVITS, UVR5, Damo ASR, etc. You will need to download them yourself and map them into the container. - container_name: gpt-sovits-container - environment: - - is_half=False - - is_share=False - volumes: - - ./output:/workspace/output - - ./logs:/workspace/logs - - ./SoVITS_weights:/workspace/SoVITS_weights - - ./reference:/workspace/reference - working_dir: /workspace - ports: - - "9880:9880" - - "9871:9871" - - "9872:9872" - - "9873:9873" - - "9874:9874" - shm_size: 16G - deploy: - resources: - reservations: - devices: - - driver: nvidia - count: "all" - capabilities: [gpu] - stdin_open: true - tty: true - restart: unless-stopped diff --git a/dockerbuild.sh b/dockerbuild.sh deleted file mode 100755 index 3a4a1e18..00000000 --- a/dockerbuild.sh +++ /dev/null @@ -1,21 +0,0 @@ -#!/bin/bash - -# 获取当前日期，格式为 YYYYMMDD -DATE=$(date +%Y%m%d) -# 获取最新的 Git commit 哈希值的前 7 位 -COMMIT_HASH=$(git rev-parse HEAD | cut -c 1-7) - -# 构建 full 版本的镜像 -docker build --build-arg IMAGE_TYPE=full -t breakstring/gpt-sovits:latest . -# 为同一个镜像添加带日期的标签 -docker tag breakstring/gpt-sovits:latest breakstring/gpt-sovits:dev-$DATE -# 为同一个镜像添加带当前代码库Commit哈希值的标签 -docker tag breakstring/gpt-sovits:latest breakstring/gpt-sovits:dev-$COMMIT_HASH - - -# 构建 elite 版本的镜像(无模型下载步骤，需手工将模型下载安装进容器) -docker build --build-arg IMAGE_TYPE=elite -t breakstring/gpt-sovits:latest-elite . -# 为同一个镜像添加带日期的标签 -docker tag breakstring/gpt-sovits:latest-elite breakstring/gpt-sovits:dev-$DATE-elite -# 为同一个镜像添加带当前代码库Commit哈希值的标签 -docker tag breakstring/gpt-sovits:latest-elite breakstring/gpt-sovits:dev-$COMMIT_HASH-elite diff --git a/go-webui.bat b/go-webui.bat deleted file mode 100644 index 398f6d9b..00000000 --- a/go-webui.bat +++ /dev/null @@ -1,2 +0,0 @@ -runtime\python.exe webui.py zh_CN -pause diff --git a/go-webui.ps1 b/go-webui.ps1 deleted file mode 100644 index 8962732a..00000000 --- a/go-webui.ps1 +++ /dev/null @@ -1,4 +0,0 @@ -$ErrorActionPreference = "SilentlyContinue" -chcp 65001 -& "$PSScriptRoot\runtime\python.exe" "$PSScriptRoot\webui.py zh_CN" -pause diff --git a/gpt-sovits_kaggle.ipynb b/gpt-sovits_kaggle.ipynb deleted file mode 100644 index 84ecd89c..00000000 --- a/gpt-sovits_kaggle.ipynb +++ /dev/null @@ -1,218 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": null, - "id": "45857cb2", - "metadata": { - "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19", - "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5", - "execution": { - "iopub.execute_input": "2024-02-18T14:43:46.735480Z", - "iopub.status.busy": "2024-02-18T14:43:46.735183Z", - "iopub.status.idle": "2024-02-18T14:48:10.724175Z", - "shell.execute_reply": "2024-02-18T14:48:10.723059Z" - }, - "papermill": { - "duration": 263.994935, - "end_time": "2024-02-18T14:48:10.726613", - "exception": false, - "start_time": "2024-02-18T14:43:46.731678", - "status": "completed" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "!git clone https://github.com/RVC-Boss/GPT-SoVITS.git\n", - "%cd GPT-SoVITS\n", - "!apt-get update && apt-get install -y --no-install-recommends tzdata ffmpeg libsox-dev parallel aria2 git git-lfs && git lfs install\n", - "!pip install -r requirements.txt" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "b9d346b4", - "metadata": { - "execution": { - "iopub.execute_input": "2024-02-18T14:48:10.815802Z", - "iopub.status.busy": "2024-02-18T14:48:10.814899Z", - "iopub.status.idle": "2024-02-18T14:50:31.253276Z", - "shell.execute_reply": "2024-02-18T14:50:31.252024Z" - }, - "papermill": { - "duration": 140.484893, - "end_time": "2024-02-18T14:50:31.255720", - "exception": false, - "start_time": "2024-02-18T14:48:10.770827", - "status": "completed" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "# @title Download pretrained models 下载预训练模型\n", - "!mkdir -p /kaggle/working/GPT-SoVITS/GPT_SoVITS/pretrained_models\n", - "!mkdir -p /kaggle/working/GPT-SoVITS/tools/asr/models\n", - "!mkdir -p /kaggle/working/GPT-SoVITS/tools/uvr5\n", - "%cd /kaggle/working/GPT-SoVITS/GPT_SoVITS/pretrained_models\n", - "!git clone https://huggingface.co/lj1995/GPT-SoVITS\n", - "%cd /kaggle/working/GPT-SoVITS/tools/asr/models\n", - "!git clone https://www.modelscope.cn/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch.git\n", - "!git clone https://www.modelscope.cn/damo/speech_fsmn_vad_zh-cn-16k-common-pytorch.git\n", - "!git clone https://www.modelscope.cn/damo/punc_ct-transformer_zh-cn-common-vocab272727-pytorch.git\n", - "# # @title UVR5 pretrains 安装uvr5模型\n", - "%cd /kaggle/working/GPT-SoVITS/tools/uvr5\n", - "!git clone https://huggingface.co/Delik/uvr5_weights\n", - "!git config core.sparseCheckout true\n", - "!mv /kaggle/working/GPT-SoVITS/GPT_SoVITS/pretrained_models/GPT-SoVITS/* /kaggle/working/GPT-SoVITS/GPT_SoVITS/pretrained_models/" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "ea94d245", - "metadata": { - "execution": { - "iopub.execute_input": "2024-02-18T14:29:01.071549Z", - "iopub.status.busy": "2024-02-18T14:29:01.070592Z", - "iopub.status.idle": "2024-02-18T14:40:45.318368Z", - "shell.execute_reply": "2024-02-18T14:40:45.317130Z", - "shell.execute_reply.started": "2024-02-18T14:29:01.071512Z" - }, - "papermill": { - "duration": null, - "end_time": null, - "exception": false, - "start_time": "2024-02-18T14:50:31.309013", - "status": "running" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "# @title launch WebUI 启动WebUI\n", - "%cd /kaggle/working/GPT-SoVITS/\n", - "!npm install -g localtunnel\n", - "import subprocess\n", - "import threading\n", - "import time\n", - "import socket\n", - "import urllib.request\n", - "def iframe_thread(port):\n", - " while True:\n", - " time.sleep(0.5)\n", - " sock= socket.socket(socket.AF_INET, socket.SOCK_STREAM)\n", - " result = sock.connect_ex(('127.0.0.1', port))\n", - " if result == 0:\n", - " break\n", - " sock.close()\n", - "\n", - " from colorama import Fore, Style\n", - " print (Fore.GREEN + \"\\nIP: \", Fore. RED, urllib.request.urlopen('https://ipv4.icanhazip.com').read().decode('utf8').strip(\"\\n\"), \"\\n\", Style. RESET_ALL)\n", - " p = subprocess.Popen([\"lt\", \"--port\", \"{}\".format(port)], stdout=subprocess.PIPE)\n", - " for line in p.stdout:\n", - " print(line.decode(), end='')\n", - "threading.Thread (target=iframe_thread, daemon=True, args=(9874,)).start()\n", - "\n", - "!python webui.py" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "dda88a6d", - "metadata": { - "execution": { - "iopub.execute_input": "2024-02-18T14:40:56.880608Z", - "iopub.status.busy": "2024-02-18T14:40:56.879879Z" - }, - "papermill": { - "duration": null, - "end_time": null, - "exception": null, - "start_time": null, - "status": "pending" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "# 开启推理页面\n", - "%cd /kaggle/working/GPT-SoVITS/\n", - "!npm install -g localtunnel\n", - "import subprocess\n", - "import threading\n", - "import time\n", - "import socket\n", - "import urllib.request\n", - "def iframe_thread(port):\n", - " while True:\n", - " time.sleep(0.5)\n", - " sock= socket.socket(socket.AF_INET, socket.SOCK_STREAM)\n", - " result = sock.connect_ex(('127.0.0.1', port))\n", - " if result == 0:\n", - " break\n", - " sock.close()\n", - "\n", - " from colorama import Fore, Style\n", - " print (Fore.GREEN + \"\\nIP: \", Fore. RED, urllib.request.urlopen('https://ipv4.icanhazip.com').read().decode('utf8').strip(\"\\n\"), \"\\n\", Style. RESET_ALL)\n", - " p = subprocess.Popen([\"lt\", \"--port\", \"{}\".format(port)], stdout=subprocess.PIPE)\n", - " for line in p.stdout:\n", - " print(line.decode(), end='')\n", - "threading.Thread (target=iframe_thread, daemon=True, args=(9872,)).start()\n", - "\n", - "!python ./GPT_SoVITS/inference_webui.py" - ] - } - ], - "metadata": { - "kaggle": { - "accelerator": "nvidiaTeslaT4", - "dataSources": [ - { - "datasetId": 4459328, - "sourceId": 7649639, - "sourceType": "datasetVersion" - } - ], - "dockerImageVersionId": 30646, - "isGpuEnabled": true, - "isInternetEnabled": true, - "language": "python", - "sourceType": "notebook" - }, - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.13" - }, - "papermill": { - "default_parameters": {}, - "duration": null, - "end_time": null, - "environment_variables": {}, - "exception": null, - "input_path": "__notebook__.ipynb", - "output_path": "__notebook__.ipynb", - "parameters": {}, - "start_time": "2024-02-18T14:43:44.011910", - "version": "2.5.0" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/install.sh b/install.sh deleted file mode 100644 index 8dadb26d..00000000 --- a/install.sh +++ /dev/null @@ -1,6 +0,0 @@ -#!/bin/bash -conda install -c conda-forge gcc -conda install -c conda-forge gxx -conda install ffmpeg cmake -conda install pytorch==2.1.1 torchvision==0.16.1 torchaudio==2.1.1 pytorch-cuda=11.8 -c pytorch -c nvidia -pip install -r requirements.txt diff --git a/pyproject.toml b/pyproject.toml index 2ee1d234..cd500100 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -5,7 +5,7 @@ build-backend = "setuptools.build_meta" [project] name = "GPT_SoVITS" dynamic = ["version"] -description = "" +description = "A packaged version of GPT_SoVITS designed to be installable" readme = "README.md" license = {text = "MIT License"} classifiers = [ @@ -50,11 +50,12 @@ dependencies = [ "opencc==1.1.1; sys_platform == 'linux'", "python_mecab_ko; sys_platform != 'win32'", "fastapi<0.112.2", + "sounddevice" ] [project.urls] -Homepage = "https://github.com/RVC-Boss/GPT-SoVITS" +Homepage = "https://github.com/JarodMica/GPT-SoVITS/tree/main" [project.scripts] "gpt_sovits_api" = "GPT_SoVITS.api_v2:main" diff --git a/test.py b/test.py new file mode 100644 index 00000000..ecc007e2 --- /dev/null +++ b/test.py @@ -0,0 +1,35 @@ +import requests + +# API configuration +host = '127.0.0.1' +port = 9880 +url = f'http://{host}:{port}/tts' + +# Parameters for the request +params = { + 'text': 'ははは、それはいいよね！でもなんか対処法ではないよなこれ対処法ではないけどそもそもの話みたいなことを言ってんのか', + 'text_lang': 'ja', + 'ref_audio_path': 'test.wav', + 'prompt_lang': 'ja', + 'prompt_text': 'でもなんか対処法ではないよなこれ対処法ではないけどそもそもの話みたいなことを言ってんのか', + 'text_split_method': 'cut0', + 'batch_size': 1, + 'media_type': 'wav', + 'streaming_mode': False, +} + +try: + # Send the GET request + response = requests.get(url, params=params) + + # Check if the request was successful + if response.status_code == 200: + # Save the audio content to a file + with open('output.wav', 'wb') as f: + f.write(response.content) + print('Audio saved to output.wav') + else: + print(f'Error: {response.status_code}') + print(response.json()) +except requests.exceptions.RequestException as e: + print(f'An error occurred: {e}') diff --git a/test_streaming.py b/test_streaming.py new file mode 100644 index 00000000..ca667096 --- /dev/null +++ b/test_streaming.py @@ -0,0 +1,89 @@ +import requests +import wave +import io +import sounddevice as sd + +# API configuration +host = '127.0.0.1' +port = 9880 +url = f'http://{host}:{port}/tts' + +# Parameters for the request +params = { + 'text': 'ふふふ、それはいいよね！でもなんか対処法ではないよなこれ対処法ではないけどそもそもの話みたいなことを言ってんのか', + 'text_lang': 'ja', + 'ref_audio_path': 'test.wav', + 'prompt_lang': 'ja', + 'prompt_text': 'でもなんか対処法ではないよなこれ対処法ではないけどそもそもの話みたいなことを言ってんのか', + 'text_split_method': 'cut0', + 'batch_size': 1, + 'media_type': 'wav', + 'streaming_mode': True, +} + +while True: + input("Waiting for enter") + try: + # Send the GET request with streaming enabled + response = requests.get(url, params=params, stream=True) + + # Check if the request was successful + if response.status_code == 200: + buffer = b'' # Buffer to hold data until header is processed + header_size = 44 # Standard WAV header size + header_parsed = False + stream = None + + for chunk in response.iter_content(chunk_size=4096): + if chunk: + if not header_parsed: + buffer += chunk + if len(buffer) >= header_size: + # Parse WAV header + wav_header = buffer[:header_size] + wav_file = wave.open(io.BytesIO(wav_header), 'rb') + channels = wav_file.getnchannels() + sample_width = wav_file.getsampwidth() + sample_rate = wav_file.getframerate() + wav_file.close() + + # Map sample_width to dtype + dtype_map = {1: 'int8', 2: 'int16', 3: 'int24', 4: 'int32'} + dtype = dtype_map.get(sample_width, 'int16') + + # Open audio stream + stream = sd.RawOutputStream( + samplerate=sample_rate, + channels=channels, + dtype=dtype, + blocksize=0, # Use default block size + ) + + stream.start() + + # Write any remaining data after the header + data = buffer[header_size:] + if data: + stream.write(data) + header_parsed = True + buffer = b'' # Clear buffer + else: + # Play audio data + if stream: + stream.write(chunk) + # Clean up + if stream: + stream.stop() + stream.close() + print('Audio playback completed.') + else: + print(f'Error: {response.status_code}') + # Print the error message from the API + try: + print(response.json()) + except ValueError: + print(response.text) + except requests.exceptions.RequestException as e: + print(f'An error occurred: {e}') + except Exception as e: + print(f'An error occurred: {e}') diff --git a/webui.py b/webui.py deleted file mode 100644 index d510370f..00000000 --- a/webui.py +++ /dev/null @@ -1,1054 +0,0 @@ -import os,sys -if len(sys.argv)==1:sys.argv.append('v2') -version="v1"if sys.argv[1]=="v1" else"v2" -os.environ["version"]=version -now_dir = os.getcwd() -sys.path.insert(0, now_dir) -import warnings -warnings.filterwarnings("ignore") -import json,yaml,torch,pdb,re,shutil -import platform -import psutil -import signal -torch.manual_seed(233333) -tmp = os.path.join(now_dir, "TEMP") -os.makedirs(tmp, exist_ok=True) -os.environ["TEMP"] = tmp -if(os.path.exists(tmp)): - for name in os.listdir(tmp): - if(name=="jieba.cache"):continue - path="%s/%s"%(tmp,name) - delete=os.remove if os.path.isfile(path) else shutil.rmtree - try: - delete(path) - except Exception as e: - print(str(e)) - pass -import site -import traceback -site_packages_roots = [] -for path in site.getsitepackages(): - if "packages" in path: - site_packages_roots.append(path) -if(site_packages_roots==[]):site_packages_roots=["%s/runtime/Lib/site-packages" % now_dir] -#os.environ["OPENBLAS_NUM_THREADS"] = "4" -os.environ["no_proxy"] = "localhost, 127.0.0.1, ::1" -os.environ["all_proxy"] = "" -for site_packages_root in site_packages_roots: - if os.path.exists(site_packages_root): - try: - with open("%s/users.pth" % (site_packages_root), "w") as f: - f.write( - "%s\n%s/tools\n%s/tools/asr\n%s/GPT_SoVITS\n%s/tools/uvr5" - % (now_dir, now_dir, now_dir, now_dir, now_dir) - ) - break - except PermissionError as e: - traceback.print_exc() -from tools import my_utils -import shutil -import pdb -from subprocess import Popen -import signal -from config import python_exec,infer_device,is_half,exp_root,webui_port_main,webui_port_infer_tts,webui_port_uvr5,webui_port_subfix,is_share -from tools.i18n.i18n import I18nAuto, scan_language_list -language=sys.argv[-1] if sys.argv[-1] in scan_language_list() else "Auto" -os.environ["language"]=language -i18n = I18nAuto(language=language) -from scipy.io import wavfile -from tools.my_utils import load_audio, check_for_existance, check_details -from multiprocessing import cpu_count -# os.environ['PYTORCH_ENABLE_MPS_FALLBACK'] = '1' # 当遇到mps不支持的步骤时使用cpu -try: - import gradio.analytics as analytics - analytics.version_check = lambda:None -except:... -import gradio as gr -n_cpu=cpu_count() - -ngpu = torch.cuda.device_count() -gpu_infos = [] -mem = [] -if_gpu_ok = False - -# 判断是否有能用来训练和加速推理的N卡 -ok_gpu_keywords={"10","16","20","30","40","A2","A3","A4","P4","A50","500","A60","70","80","90","M4","T4","TITAN","L4","4060","H"} -set_gpu_numbers=set() -if torch.cuda.is_available() or ngpu != 0: - for i in range(ngpu): - gpu_name = torch.cuda.get_device_name(i) - if any(value in gpu_name.upper()for value in ok_gpu_keywords): - # A10#A100#V100#A40#P40#M40#K80#A4500 - if_gpu_ok = True # 至少有一张能用的N卡 - gpu_infos.append("%s\t%s" % (i, gpu_name)) - set_gpu_numbers.add(i) - mem.append(int(torch.cuda.get_device_properties(i).total_memory/ 1024/ 1024/ 1024+ 0.4)) -# # 判断是否支持mps加速 -# if torch.backends.mps.is_available(): -# if_gpu_ok = True -# gpu_infos.append("%s\t%s" % ("0", "Apple GPU")) -# mem.append(psutil.virtual_memory().total/ 1024 / 1024 / 1024) # 实测使用系统内存作为显存不会爆显存 - -if if_gpu_ok and len(gpu_infos) > 0: - gpu_info = "\n".join(gpu_infos) - default_batch_size = min(mem) // 2 -else: - gpu_info = ("%s\t%s" % ("0", "CPU")) - gpu_infos.append("%s\t%s" % ("0", "CPU")) - set_gpu_numbers.add(0) - default_batch_size = int(psutil.virtual_memory().total/ 1024 / 1024 / 1024 / 2) -gpus = "-".join([i[0] for i in gpu_infos]) -default_gpu_numbers=str(sorted(list(set_gpu_numbers))[0]) -def fix_gpu_number(input):#将越界的number强制改到界内 - try: - if(int(input)not in set_gpu_numbers):return default_gpu_numbers - except:return input - return input -def fix_gpu_numbers(inputs): - output=[] - try: - for input in inputs.split(","):output.append(str(fix_gpu_number(input))) - return ",".join(output) - except: - return inputs - -pretrained_sovits_name=["GPT_SoVITS/pretrained_models/gsv-v2final-pretrained/s2G2333k.pth", "GPT_SoVITS/pretrained_models/s2G488k.pth"] -pretrained_gpt_name=["GPT_SoVITS/pretrained_models/gsv-v2final-pretrained/s1bert25hz-5kh-longer-epoch=12-step=369668.ckpt", "GPT_SoVITS/pretrained_models/s1bert25hz-2kh-longer-epoch=68e-step=50232.ckpt"] - -pretrained_model_list = (pretrained_sovits_name[-int(version[-1])+2],pretrained_sovits_name[-int(version[-1])+2].replace("s2G","s2D"),pretrained_gpt_name[-int(version[-1])+2],"GPT_SoVITS/pretrained_models/chinese-roberta-wwm-ext-large","GPT_SoVITS/pretrained_models/chinese-hubert-base") - -_='' -for i in pretrained_model_list: - if os.path.exists(i):... - else:_+=f'\n {i}' -if _: - print("warning:",i18n('以下模型不存在:')+_) - -_ =[[],[]] -for i in range(2): - if os.path.exists(pretrained_gpt_name[i]):_[0].append(pretrained_gpt_name[i]) - else:_[0].append("")##没有下pretrained模型的，说不定他们是想自己从零训底模呢 - if os.path.exists(pretrained_sovits_name[i]):_[-1].append(pretrained_sovits_name[i]) - else:_[-1].append("") -pretrained_gpt_name,pretrained_sovits_name = _ - -SoVITS_weight_root=["SoVITS_weights_v2","SoVITS_weights"] -GPT_weight_root=["GPT_weights_v2","GPT_weights"] -for root in SoVITS_weight_root+GPT_weight_root: - os.makedirs(root,exist_ok=True) -def get_weights_names(): - SoVITS_names = [name for name in pretrained_sovits_name if name!=""] - for path in SoVITS_weight_root: - for name in os.listdir(path): - if name.endswith(".pth"): SoVITS_names.append("%s/%s" % (path, name)) - GPT_names = [name for name in pretrained_gpt_name if name!=""] - for path in GPT_weight_root: - for name in os.listdir(path): - if name.endswith(".ckpt"): GPT_names.append("%s/%s" % (path, name)) - return SoVITS_names, GPT_names - -SoVITS_names,GPT_names = get_weights_names() -for path in SoVITS_weight_root+GPT_weight_root: - os.makedirs(path,exist_ok=True) - - -def custom_sort_key(s): - # 使用正则表达式提取字符串中的数字部分和非数字部分 - parts = re.split('(\d+)', s) - # 将数字部分转换为整数，非数字部分保持不变 - parts = [int(part) if part.isdigit() else part for part in parts] - return parts - -def change_choices(): - SoVITS_names, GPT_names = get_weights_names() - return {"choices": sorted(SoVITS_names,key=custom_sort_key), "__type__": "update"}, {"choices": sorted(GPT_names,key=custom_sort_key), "__type__": "update"} - -p_label=None -p_uvr5=None -p_asr=None -p_denoise=None -p_tts_inference=None - -def kill_proc_tree(pid, including_parent=True): - try: - parent = psutil.Process(pid) - except psutil.NoSuchProcess: - # Process already terminated - return - - children = parent.children(recursive=True) - for child in children: - try: - os.kill(child.pid, signal.SIGTERM) # or signal.SIGKILL - except OSError: - pass - if including_parent: - try: - os.kill(parent.pid, signal.SIGTERM) # or signal.SIGKILL - except OSError: - pass - -system=platform.system() -def kill_process(pid): - if(system=="Windows"): - cmd = "taskkill /t /f /pid %s" % pid - os.system(cmd) - else: - kill_proc_tree(pid) - - -def change_label(path_list): - global p_label - if(p_label==None): - check_for_existance([path_list]) - path_list=my_utils.clean_path(path_list) - cmd = '"%s" tools/subfix_webui.py --load_list "%s" --webui_port %s --is_share %s'%(python_exec,path_list,webui_port_subfix,is_share) - yield i18n("打标工具WebUI已开启"), {'__type__':'update','visible':False}, {'__type__':'update','visible':True} - print(cmd) - p_label = Popen(cmd, shell=True) - elif(p_label!=None): - kill_process(p_label.pid) - p_label=None - yield i18n("打标工具WebUI已关闭"), {'__type__':'update','visible':True}, {'__type__':'update','visible':False} - -def change_uvr5(): - global p_uvr5 - if(p_uvr5==None): - cmd = '"%s" tools/uvr5/webui.py "%s" %s %s %s'%(python_exec,infer_device,is_half,webui_port_uvr5,is_share) - yield i18n("UVR5已开启"), {'__type__':'update','visible':False}, {'__type__':'update','visible':True} - print(cmd) - p_uvr5 = Popen(cmd, shell=True) - elif(p_uvr5!=None): - kill_process(p_uvr5.pid) - p_uvr5=None - yield i18n("UVR5已关闭"), {'__type__':'update','visible':True}, {'__type__':'update','visible':False} - -def change_tts_inference(bert_path,cnhubert_base_path,gpu_number,gpt_path,sovits_path, batched_infer_enabled): - global p_tts_inference - if batched_infer_enabled: - cmd = '"%s" GPT_SoVITS/inference_webui_fast.py "%s"'%(python_exec, language) - else: - cmd = '"%s" GPT_SoVITS/inference_webui.py "%s"'%(python_exec, language) - if(p_tts_inference==None): - os.environ["gpt_path"]=gpt_path if "/" in gpt_path else "%s/%s"%(GPT_weight_root,gpt_path) - os.environ["sovits_path"]=sovits_path if "/"in sovits_path else "%s/%s"%(SoVITS_weight_root,sovits_path) - os.environ["cnhubert_base_path"]=cnhubert_base_path - os.environ["bert_path"]=bert_path - os.environ["_CUDA_VISIBLE_DEVICES"]=fix_gpu_number(gpu_number) - os.environ["is_half"]=str(is_half) - os.environ["infer_ttswebui"]=str(webui_port_infer_tts) - os.environ["is_share"]=str(is_share) - yield i18n("TTS推理进程已开启"), {'__type__':'update','visible':False}, {'__type__':'update','visible':True} - print(cmd) - p_tts_inference = Popen(cmd, shell=True) - elif(p_tts_inference!=None): - kill_process(p_tts_inference.pid) - p_tts_inference=None - yield i18n("TTS推理进程已关闭"), {'__type__':'update','visible':True}, {'__type__':'update','visible':False} - -from tools.asr.config import asr_dict -def open_asr(asr_inp_dir, asr_opt_dir, asr_model, asr_model_size, asr_lang, asr_precision): - global p_asr - if(p_asr==None): - asr_inp_dir=my_utils.clean_path(asr_inp_dir) - asr_opt_dir=my_utils.clean_path(asr_opt_dir) - check_for_existance([asr_inp_dir]) - cmd = f'"{python_exec}" tools/asr/{asr_dict[asr_model]["path"]}' - cmd += f' -i "{asr_inp_dir}"' - cmd += f' -o "{asr_opt_dir}"' - cmd += f' -s {asr_model_size}' - cmd += f' -l {asr_lang}' - cmd += f" -p {asr_precision}" - output_file_name = os.path.basename(asr_inp_dir) - output_folder = asr_opt_dir or "output/asr_opt" - output_file_path = os.path.abspath(f'{output_folder}/{output_file_name}.list') - yield "ASR任务开启：%s"%cmd, {"__type__":"update","visible":False}, {"__type__":"update","visible":True}, {"__type__":"update"}, {"__type__":"update"}, {"__type__":"update"} - print(cmd) - p_asr = Popen(cmd, shell=True) - p_asr.wait() - p_asr=None - yield f"ASR任务完成, 查看终端进行下一步", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}, {"__type__":"update","value":output_file_path}, {"__type__":"update","value":output_file_path}, {"__type__":"update","value":asr_inp_dir} - else: - yield "已有正在进行的ASR任务，需先终止才能开启下一次任务", {"__type__":"update","visible":False}, {"__type__":"update","visible":True}, {"__type__":"update"}, {"__type__":"update"}, {"__type__":"update"} - # return None - -def close_asr(): - global p_asr - if(p_asr!=None): - kill_process(p_asr.pid) - p_asr=None - return "已终止ASR进程", {"__type__":"update","visible":True}, {"__type__":"update","visible":False} -def open_denoise(denoise_inp_dir, denoise_opt_dir): - global p_denoise - if(p_denoise==None): - denoise_inp_dir=my_utils.clean_path(denoise_inp_dir) - denoise_opt_dir=my_utils.clean_path(denoise_opt_dir) - check_for_existance([denoise_inp_dir]) - cmd = '"%s" tools/cmd-denoise.py -i "%s" -o "%s" -p %s'%(python_exec,denoise_inp_dir,denoise_opt_dir,"float16"if is_half==True else "float32") - - yield "语音降噪任务开启：%s"%cmd, {"__type__":"update","visible":False}, {"__type__":"update","visible":True}, {"__type__":"update"}, {"__type__":"update"} - print(cmd) - p_denoise = Popen(cmd, shell=True) - p_denoise.wait() - p_denoise=None - yield f"语音降噪任务完成, 查看终端进行下一步", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}, {"__type__":"update","value":denoise_opt_dir}, {"__type__":"update","value":denoise_opt_dir} - else: - yield "已有正在进行的语音降噪任务，需先终止才能开启下一次任务", {"__type__":"update","visible":False}, {"__type__":"update","visible":True}, {"__type__":"update"}, {"__type__":"update"} - # return None - -def close_denoise(): - global p_denoise - if(p_denoise!=None): - kill_process(p_denoise.pid) - p_denoise=None - return "已终止语音降噪进程", {"__type__":"update","visible":True}, {"__type__":"update","visible":False} - -p_train_SoVITS=None -def open1Ba(batch_size,total_epoch,exp_name,text_low_lr_rate,if_save_latest,if_save_every_weights,save_every_epoch,gpu_numbers1Ba,pretrained_s2G,pretrained_s2D): - global p_train_SoVITS - if(p_train_SoVITS==None): - with open("GPT_SoVITS/configs/s2.json")as f: - data=f.read() - data=json.loads(data) - s2_dir="%s/%s"%(exp_root,exp_name) - os.makedirs("%s/logs_s2"%(s2_dir),exist_ok=True) - if check_for_existance([s2_dir],is_train=True): - check_details([s2_dir],is_train=True) - if(is_half==False): - data["train"]["fp16_run"]=False - batch_size=max(1,batch_size//2) - data["train"]["batch_size"]=batch_size - data["train"]["epochs"]=total_epoch - data["train"]["text_low_lr_rate"]=text_low_lr_rate - data["train"]["pretrained_s2G"]=pretrained_s2G - data["train"]["pretrained_s2D"]=pretrained_s2D - data["train"]["if_save_latest"]=if_save_latest - data["train"]["if_save_every_weights"]=if_save_every_weights - data["train"]["save_every_epoch"]=save_every_epoch - data["train"]["gpu_numbers"]=gpu_numbers1Ba - data["model"]["version"]=version - data["data"]["exp_dir"]=data["s2_ckpt_dir"]=s2_dir - data["save_weight_dir"]=SoVITS_weight_root[-int(version[-1])+2] - data["name"]=exp_name - data["version"]=version - tmp_config_path="%s/tmp_s2.json"%tmp - with open(tmp_config_path,"w")as f:f.write(json.dumps(data)) - - cmd = '"%s" GPT_SoVITS/s2_train.py --config "%s"'%(python_exec,tmp_config_path) - yield "SoVITS训练开始：%s"%cmd, {"__type__":"update","visible":False}, {"__type__":"update","visible":True} - print(cmd) - p_train_SoVITS = Popen(cmd, shell=True) - p_train_SoVITS.wait() - p_train_SoVITS=None - yield "SoVITS训练完成", {"__type__":"update","visible":True}, {"__type__":"update","visible":False} - else: - yield "已有正在进行的SoVITS训练任务，需先终止才能开启下一次任务", {"__type__":"update","visible":False}, {"__type__":"update","visible":True} - -def close1Ba(): - global p_train_SoVITS - if(p_train_SoVITS!=None): - kill_process(p_train_SoVITS.pid) - p_train_SoVITS=None - return "已终止SoVITS训练", {"__type__":"update","visible":True}, {"__type__":"update","visible":False} - -p_train_GPT=None -def open1Bb(batch_size,total_epoch,exp_name,if_dpo,if_save_latest,if_save_every_weights,save_every_epoch,gpu_numbers,pretrained_s1): - global p_train_GPT - if(p_train_GPT==None): - with open("GPT_SoVITS/configs/s1longer.yaml"if version=="v1"else "GPT_SoVITS/configs/s1longer-v2.yaml")as f: - data=f.read() - data=yaml.load(data, Loader=yaml.FullLoader) - s1_dir="%s/%s"%(exp_root,exp_name) - os.makedirs("%s/logs_s1"%(s1_dir),exist_ok=True) - if check_for_existance([s1_dir],is_train=True): - check_details([s1_dir],is_train=True) - if(is_half==False): - data["train"]["precision"]="32" - batch_size = max(1, batch_size // 2) - data["train"]["batch_size"]=batch_size - data["train"]["epochs"]=total_epoch - data["pretrained_s1"]=pretrained_s1 - data["train"]["save_every_n_epoch"]=save_every_epoch - data["train"]["if_save_every_weights"]=if_save_every_weights - data["train"]["if_save_latest"]=if_save_latest - data["train"]["if_dpo"]=if_dpo - data["train"]["half_weights_save_dir"]=GPT_weight_root[-int(version[-1])+2] - data["train"]["exp_name"]=exp_name - data["train_semantic_path"]="%s/6-name2semantic.tsv"%s1_dir - data["train_phoneme_path"]="%s/2-name2text.txt"%s1_dir - data["output_dir"]="%s/logs_s1"%s1_dir - # data["version"]=version - - os.environ["_CUDA_VISIBLE_DEVICES"]=fix_gpu_numbers(gpu_numbers.replace("-",",")) - os.environ["hz"]="25hz" - tmp_config_path="%s/tmp_s1.yaml"%tmp - with open(tmp_config_path, "w") as f:f.write(yaml.dump(data, default_flow_style=False)) - # cmd = '"%s" GPT_SoVITS/s1_train.py --config_file "%s" --train_semantic_path "%s/6-name2semantic.tsv" --train_phoneme_path "%s/2-name2text.txt" --output_dir "%s/logs_s1"'%(python_exec,tmp_config_path,s1_dir,s1_dir,s1_dir) - cmd = '"%s" GPT_SoVITS/s1_train.py --config_file "%s" '%(python_exec,tmp_config_path) - yield "GPT训练开始：%s"%cmd, {"__type__":"update","visible":False}, {"__type__":"update","visible":True} - print(cmd) - p_train_GPT = Popen(cmd, shell=True) - p_train_GPT.wait() - p_train_GPT=None - yield "GPT训练完成", {"__type__":"update","visible":True}, {"__type__":"update","visible":False} - else: - yield "已有正在进行的GPT训练任务，需先终止才能开启下一次任务", {"__type__":"update","visible":False}, {"__type__":"update","visible":True} - -def close1Bb(): - global p_train_GPT - if(p_train_GPT!=None): - kill_process(p_train_GPT.pid) - p_train_GPT=None - return "已终止GPT训练", {"__type__":"update","visible":True}, {"__type__":"update","visible":False} - -ps_slice=[] -def open_slice(inp,opt_root,threshold,min_length,min_interval,hop_size,max_sil_kept,_max,alpha,n_parts): - global ps_slice - inp = my_utils.clean_path(inp) - opt_root = my_utils.clean_path(opt_root) - check_for_existance([inp]) - if(os.path.exists(inp)==False): - yield "输入路径不存在", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}, {"__type__": "update"}, {"__type__": "update"}, {"__type__": "update"} - return - if os.path.isfile(inp):n_parts=1 - elif os.path.isdir(inp):pass - else: - yield "输入路径存在但既不是文件也不是文件夹", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}, {"__type__": "update"}, {"__type__": "update"}, {"__type__": "update"} - return - if (ps_slice == []): - for i_part in range(n_parts): - cmd = '"%s" tools/slice_audio.py "%s" "%s" %s %s %s %s %s %s %s %s %s''' % (python_exec,inp, opt_root, threshold, min_length, min_interval, hop_size, max_sil_kept, _max, alpha, i_part, n_parts) - print(cmd) - p = Popen(cmd, shell=True) - ps_slice.append(p) - yield "切割执行中", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True}, {"__type__": "update"}, {"__type__": "update"}, {"__type__": "update"} - for p in ps_slice: - p.wait() - ps_slice=[] - yield "切割结束", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}, {"__type__": "update", "value":opt_root}, {"__type__": "update", "value":opt_root}, {"__type__": "update", "value":opt_root} - else: - yield "已有正在进行的切割任务，需先终止才能开启下一次任务", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True}, {"__type__": "update"}, {"__type__": "update"}, {"__type__": "update"} - -def close_slice(): - global ps_slice - if (ps_slice != []): - for p_slice in ps_slice: - try: - kill_process(p_slice.pid) - except: - traceback.print_exc() - ps_slice=[] - return "已终止所有切割进程", {"__type__": "update", "visible": True}, {"__type__": "update", "visible": False} - -ps1a=[] -def open1a(inp_text,inp_wav_dir,exp_name,gpu_numbers,bert_pretrained_dir): - global ps1a - inp_text = my_utils.clean_path(inp_text) - inp_wav_dir = my_utils.clean_path(inp_wav_dir) - if check_for_existance([inp_text,inp_wav_dir], is_dataset_processing=True): - check_details([inp_text,inp_wav_dir], is_dataset_processing=True) - if (ps1a == []): - opt_dir="%s/%s"%(exp_root,exp_name) - config={ - "inp_text":inp_text, - "inp_wav_dir":inp_wav_dir, - "exp_name":exp_name, - "opt_dir":opt_dir, - "bert_pretrained_dir":bert_pretrained_dir, - } - gpu_names=gpu_numbers.split("-") - all_parts=len(gpu_names) - for i_part in range(all_parts): - config.update( - { - "i_part": str(i_part), - "all_parts": str(all_parts), - "_CUDA_VISIBLE_DEVICES": fix_gpu_number(gpu_names[i_part]), - "is_half": str(is_half) - } - ) - os.environ.update(config) - cmd = '"%s" GPT_SoVITS/prepare_datasets/1-get-text.py'%python_exec - print(cmd) - p = Popen(cmd, shell=True) - ps1a.append(p) - yield "文本进程执行中", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True} - for p in ps1a: - p.wait() - opt = [] - for i_part in range(all_parts): - txt_path = "%s/2-name2text-%s.txt" % (opt_dir, i_part) - with open(txt_path, "r", encoding="utf8") as f: - opt += f.read().strip("\n").split("\n") - os.remove(txt_path) - path_text = "%s/2-name2text.txt" % opt_dir - with open(path_text, "w", encoding="utf8") as f: - f.write("\n".join(opt) + "\n") - ps1a=[] - if len("".join(opt)) > 0: - yield "文本进程成功", {"__type__": "update", "visible": True}, {"__type__": "update", "visible": False} - else: - yield "文本进程失败", {"__type__": "update", "visible": True}, {"__type__": "update", "visible": False} - else: - yield "已有正在进行的文本任务，需先终止才能开启下一次任务", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True} - -def close1a(): - global ps1a - if (ps1a != []): - for p1a in ps1a: - try: - kill_process(p1a.pid) - except: - traceback.print_exc() - ps1a=[] - return "已终止所有1a进程", {"__type__": "update", "visible": True}, {"__type__": "update", "visible": False} - -ps1b=[] -def open1b(inp_text,inp_wav_dir,exp_name,gpu_numbers,ssl_pretrained_dir): - global ps1b - inp_text = my_utils.clean_path(inp_text) - inp_wav_dir = my_utils.clean_path(inp_wav_dir) - if check_for_existance([inp_text,inp_wav_dir], is_dataset_processing=True): - check_details([inp_text,inp_wav_dir], is_dataset_processing=True) - if (ps1b == []): - config={ - "inp_text":inp_text, - "inp_wav_dir":inp_wav_dir, - "exp_name":exp_name, - "opt_dir":"%s/%s"%(exp_root,exp_name), - "cnhubert_base_dir":ssl_pretrained_dir, - "is_half": str(is_half) - } - gpu_names=gpu_numbers.split("-") - all_parts=len(gpu_names) - for i_part in range(all_parts): - config.update( - { - "i_part": str(i_part), - "all_parts": str(all_parts), - "_CUDA_VISIBLE_DEVICES": fix_gpu_number(gpu_names[i_part]), - } - ) - os.environ.update(config) - cmd = '"%s" GPT_SoVITS/prepare_datasets/2-get-hubert-wav32k.py'%python_exec - print(cmd) - p = Popen(cmd, shell=True) - ps1b.append(p) - yield "SSL提取进程执行中", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True} - for p in ps1b: - p.wait() - ps1b=[] - yield "SSL提取进程结束", {"__type__":"update","visible":True}, {"__type__":"update","visible":False} - else: - yield "已有正在进行的SSL提取任务，需先终止才能开启下一次任务", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True} - -def close1b(): - global ps1b - if (ps1b != []): - for p1b in ps1b: - try: - kill_process(p1b.pid) - except: - traceback.print_exc() - ps1b=[] - return "已终止所有1b进程", {"__type__": "update", "visible": True}, {"__type__": "update", "visible": False} - -ps1c=[] -def open1c(inp_text,exp_name,gpu_numbers,pretrained_s2G_path): - global ps1c - inp_text = my_utils.clean_path(inp_text) - if check_for_existance([inp_text,''], is_dataset_processing=True): - check_details([inp_text,''], is_dataset_processing=True) - if (ps1c == []): - opt_dir="%s/%s"%(exp_root,exp_name) - config={ - "inp_text":inp_text, - "exp_name":exp_name, - "opt_dir":opt_dir, - "pretrained_s2G":pretrained_s2G_path, - "s2config_path":"GPT_SoVITS/configs/s2.json", - "is_half": str(is_half) - } - gpu_names=gpu_numbers.split("-") - all_parts=len(gpu_names) - for i_part in range(all_parts): - config.update( - { - "i_part": str(i_part), - "all_parts": str(all_parts), - "_CUDA_VISIBLE_DEVICES": fix_gpu_number(gpu_names[i_part]), - } - ) - os.environ.update(config) - cmd = '"%s" GPT_SoVITS/prepare_datasets/3-get-semantic.py'%python_exec - print(cmd) - p = Popen(cmd, shell=True) - ps1c.append(p) - yield "语义token提取进程执行中", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True} - for p in ps1c: - p.wait() - opt = ["item_name\tsemantic_audio"] - path_semantic = "%s/6-name2semantic.tsv" % opt_dir - for i_part in range(all_parts): - semantic_path = "%s/6-name2semantic-%s.tsv" % (opt_dir, i_part) - with open(semantic_path, "r", encoding="utf8") as f: - opt += f.read().strip("\n").split("\n") - os.remove(semantic_path) - with open(path_semantic, "w", encoding="utf8") as f: - f.write("\n".join(opt) + "\n") - ps1c=[] - yield "语义token提取进程结束", {"__type__":"update","visible":True}, {"__type__":"update","visible":False} - else: - yield "已有正在进行的语义token提取任务，需先终止才能开启下一次任务", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True} - -def close1c(): - global ps1c - if (ps1c != []): - for p1c in ps1c: - try: - kill_process(p1c.pid) - except: - traceback.print_exc() - ps1c=[] - return "已终止所有语义token进程", {"__type__": "update", "visible": True}, {"__type__": "update", "visible": False} -#####inp_text,inp_wav_dir,exp_name,gpu_numbers1a,gpu_numbers1Ba,gpu_numbers1c,bert_pretrained_dir,cnhubert_base_dir,pretrained_s2G -ps1abc=[] -def open1abc(inp_text,inp_wav_dir,exp_name,gpu_numbers1a,gpu_numbers1Ba,gpu_numbers1c,bert_pretrained_dir,ssl_pretrained_dir,pretrained_s2G_path): - global ps1abc - inp_text = my_utils.clean_path(inp_text) - inp_wav_dir = my_utils.clean_path(inp_wav_dir) - if check_for_existance([inp_text,inp_wav_dir], is_dataset_processing=True): - check_details([inp_text,inp_wav_dir], is_dataset_processing=True) - if (ps1abc == []): - opt_dir="%s/%s"%(exp_root,exp_name) - try: - #############################1a - path_text="%s/2-name2text.txt" % opt_dir - if(os.path.exists(path_text)==False or (os.path.exists(path_text)==True and len(open(path_text,"r",encoding="utf8").read().strip("\n").split("\n"))<2)): - config={ - "inp_text":inp_text, - "inp_wav_dir":inp_wav_dir, - "exp_name":exp_name, - "opt_dir":opt_dir, - "bert_pretrained_dir":bert_pretrained_dir, - "is_half": str(is_half) - } - gpu_names=gpu_numbers1a.split("-") - all_parts=len(gpu_names) - for i_part in range(all_parts): - config.update( - { - "i_part": str(i_part), - "all_parts": str(all_parts), - "_CUDA_VISIBLE_DEVICES": fix_gpu_number(gpu_names[i_part]), - } - ) - os.environ.update(config) - cmd = '"%s" GPT_SoVITS/prepare_datasets/1-get-text.py'%python_exec - print(cmd) - p = Popen(cmd, shell=True) - ps1abc.append(p) - yield "进度：1a-ing", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True} - for p in ps1abc:p.wait() - - opt = [] - for i_part in range(all_parts):#txt_path="%s/2-name2text-%s.txt"%(opt_dir,i_part) - txt_path = "%s/2-name2text-%s.txt" % (opt_dir, i_part) - with open(txt_path, "r",encoding="utf8") as f: - opt += f.read().strip("\n").split("\n") - os.remove(txt_path) - with open(path_text, "w",encoding="utf8") as f: - f.write("\n".join(opt) + "\n") - assert len("".join(opt)) > 0, "1Aa-文本获取进程失败" - yield "进度：1a-done", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True} - ps1abc=[] - #############################1b - config={ - "inp_text":inp_text, - "inp_wav_dir":inp_wav_dir, - "exp_name":exp_name, - "opt_dir":opt_dir, - "cnhubert_base_dir":ssl_pretrained_dir, - } - gpu_names=gpu_numbers1Ba.split("-") - all_parts=len(gpu_names) - for i_part in range(all_parts): - config.update( - { - "i_part": str(i_part), - "all_parts": str(all_parts), - "_CUDA_VISIBLE_DEVICES": fix_gpu_number(gpu_names[i_part]), - } - ) - os.environ.update(config) - cmd = '"%s" GPT_SoVITS/prepare_datasets/2-get-hubert-wav32k.py'%python_exec - print(cmd) - p = Popen(cmd, shell=True) - ps1abc.append(p) - yield "进度：1a-done, 1b-ing", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True} - for p in ps1abc:p.wait() - yield "进度：1a1b-done", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True} - ps1abc=[] - #############################1c - path_semantic = "%s/6-name2semantic.tsv" % opt_dir - if(os.path.exists(path_semantic)==False or (os.path.exists(path_semantic)==True and os.path.getsize(path_semantic)<31)): - config={ - "inp_text":inp_text, - "exp_name":exp_name, - "opt_dir":opt_dir, - "pretrained_s2G":pretrained_s2G_path, - "s2config_path":"GPT_SoVITS/configs/s2.json", - } - gpu_names=gpu_numbers1c.split("-") - all_parts=len(gpu_names) - for i_part in range(all_parts): - config.update( - { - "i_part": str(i_part), - "all_parts": str(all_parts), - "_CUDA_VISIBLE_DEVICES": fix_gpu_number(gpu_names[i_part]), - } - ) - os.environ.update(config) - cmd = '"%s" GPT_SoVITS/prepare_datasets/3-get-semantic.py'%python_exec - print(cmd) - p = Popen(cmd, shell=True) - ps1abc.append(p) - yield "进度：1a1b-done, 1cing", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True} - for p in ps1abc:p.wait() - - opt = ["item_name\tsemantic_audio"] - for i_part in range(all_parts): - semantic_path = "%s/6-name2semantic-%s.tsv" % (opt_dir, i_part) - with open(semantic_path, "r",encoding="utf8") as f: - opt += f.read().strip("\n").split("\n") - os.remove(semantic_path) - with open(path_semantic, "w",encoding="utf8") as f: - f.write("\n".join(opt) + "\n") - yield "进度：all-done", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True} - ps1abc = [] - yield "一键三连进程结束", {"__type__": "update", "visible": True}, {"__type__": "update", "visible": False} - except: - traceback.print_exc() - close1abc() - yield "一键三连中途报错", {"__type__": "update", "visible": True}, {"__type__": "update", "visible": False} - else: - yield "已有正在进行的一键三连任务，需先终止才能开启下一次任务", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True} - -def close1abc(): - global ps1abc - if (ps1abc != []): - for p1abc in ps1abc: - try: - kill_process(p1abc.pid) - except: - traceback.print_exc() - ps1abc=[] - return "已终止所有一键三连进程", {"__type__": "update", "visible": True}, {"__type__": "update", "visible": False} - -def switch_version(version_): - os.environ['version']=version_ - global version - version = version_ - if pretrained_sovits_name[-int(version[-1])+2] !='' and pretrained_gpt_name[-int(version[-1])+2] !='':... - else: - gr.Warning(i18n(f'未下载{version.upper()}模型')) - return {'__type__':'update', 'value':pretrained_sovits_name[-int(version[-1])+2]}, {'__type__':'update', 'value':pretrained_sovits_name[-int(version[-1])+2].replace("s2G","s2D")}, {'__type__':'update', 'value':pretrained_gpt_name[-int(version[-1])+2]}, {'__type__':'update', 'value':pretrained_gpt_name[-int(version[-1])+2]}, {'__type__':'update', 'value':pretrained_sovits_name[-int(version[-1])+2]} - -if os.path.exists('GPT_SoVITS/text/G2PWModel'):... -else: - cmd = '"%s" GPT_SoVITS/download.py'%python_exec - p = Popen(cmd, shell=True) - p.wait() - -def sync(text): - return {'__type__':'update','value':text} -with gr.Blocks(title="GPT-SoVITS WebUI") as app: - gr.Markdown( - value= - i18n("本软件以MIT协议开源, 作者不对软件具备任何控制力, 使用软件者、传播软件导出的声音者自负全责.
如不认可该条款, 则不能使用或引用软件包内任何代码和文件. 详见根目录LICENSE.") - ) - gr.Markdown( - value= - i18n("中文教程文档：https://www.yuque.com/baicaigongchang1145haoyuangong/ib3g1e") - ) - - with gr.Tabs(): - with gr.TabItem(i18n("0-前置数据集获取工具")):#提前随机切片防止uvr5爆内存->uvr5->slicer->asr->打标 - gr.Markdown(value=i18n("0a-UVR5人声伴奏分离&去混响去延迟工具")) - with gr.Row(): - with gr.Column(scale=3): - with gr.Row(): - uvr5_info = gr.Textbox(label=i18n("UVR5进程输出信息")) - open_uvr5 = gr.Button(value=i18n("开启UVR5-WebUI"),variant="primary",visible=True) - close_uvr5 = gr.Button(value=i18n("关闭UVR5-WebUI"),variant="primary",visible=False) - gr.Markdown(value=i18n("0b-语音切分工具")) - with gr.Row(): - with gr.Column(scale=3): - with gr.Row(): - slice_inp_path=gr.Textbox(label=i18n("音频自动切分输入路径，可文件可文件夹"),value="") - slice_opt_root=gr.Textbox(label=i18n("切分后的子音频的输出根目录"),value="output/slicer_opt") - with gr.Row(): - threshold=gr.Textbox(label=i18n("threshold:音量小于这个值视作静音的备选切割点"),value="-34") - min_length=gr.Textbox(label=i18n("min_length:每段最小多长，如果第一段太短一直和后面段连起来直到超过这个值"),value="4000") - min_interval=gr.Textbox(label=i18n("min_interval:最短切割间隔"),value="300") - hop_size=gr.Textbox(label=i18n("hop_size:怎么算音量曲线，越小精度越大计算量越高（不是精度越大效果越好）"),value="10") - max_sil_kept=gr.Textbox(label=i18n("max_sil_kept:切完后静音最多留多长"),value="500") - with gr.Row(): - _max=gr.Slider(minimum=0,maximum=1,step=0.05,label=i18n("max:归一化后最大值多少"),value=0.9,interactive=True) - alpha=gr.Slider(minimum=0,maximum=1,step=0.05,label=i18n("alpha_mix:混多少比例归一化后音频进来"),value=0.25,interactive=True) - with gr.Row(): - n_process=gr.Slider(minimum=1,maximum=n_cpu,step=1,label=i18n("切割使用的进程数"),value=4,interactive=True) - slicer_info = gr.Textbox(label=i18n("语音切割进程输出信息")) - open_slicer_button=gr.Button(i18n("开启语音切割"), variant="primary",visible=True) - close_slicer_button=gr.Button(i18n("终止语音切割"), variant="primary",visible=False) - gr.Markdown(value=i18n("0bb-语音降噪工具")) - with gr.Row(): - with gr.Column(scale=3): - with gr.Row(): - denoise_input_dir=gr.Textbox(label=i18n("降噪音频文件输入文件夹"),value="") - denoise_output_dir=gr.Textbox(label=i18n("降噪结果输出文件夹"),value="output/denoise_opt") - with gr.Row(): - denoise_info = gr.Textbox(label=i18n("语音降噪进程输出信息")) - open_denoise_button = gr.Button(i18n("开启语音降噪"), variant="primary",visible=True) - close_denoise_button = gr.Button(i18n("终止语音降噪进程"), variant="primary",visible=False) - gr.Markdown(value=i18n("0c-中文批量离线ASR工具")) - with gr.Row(): - with gr.Column(scale=3): - with gr.Row(): - asr_inp_dir = gr.Textbox( - label=i18n("输入文件夹路径"), - value="D:\\GPT-SoVITS\\raw\\xxx", - interactive=True, - ) - asr_opt_dir = gr.Textbox( - label = i18n("输出文件夹路径"), - value = "output/asr_opt", - interactive = True, - ) - with gr.Row(): - asr_model = gr.Dropdown( - label = i18n("ASR 模型"), - choices = list(asr_dict.keys()), - interactive = True, - value="达摩 ASR (中文)" - ) - asr_size = gr.Dropdown( - label = i18n("ASR 模型尺寸"), - choices = ["large"], - interactive = True, - value="large" - ) - asr_lang = gr.Dropdown( - label = i18n("ASR 语言设置"), - choices = ["zh","yue"], - interactive = True, - value="zh" - ) - asr_precision = gr.Dropdown( - label = i18n("数据类型精度"), - choices = ["float32"], - interactive = True, - value="float32" - ) - with gr.Row(): - asr_info = gr.Textbox(label=i18n("ASR进程输出信息")) - open_asr_button = gr.Button(i18n("开启离线批量ASR"), variant="primary",visible=True) - close_asr_button = gr.Button(i18n("终止ASR进程"), variant="primary",visible=False) - - def change_lang_choices(key): #根据选择的模型修改可选的语言 - # return gr.Dropdown(choices=asr_dict[key]['lang']) - return {"__type__": "update", "choices": asr_dict[key]['lang'],"value":asr_dict[key]['lang'][0]} - def change_size_choices(key): # 根据选择的模型修改可选的模型尺寸 - # return gr.Dropdown(choices=asr_dict[key]['size']) - return {"__type__": "update", "choices": asr_dict[key]['size'],"value":asr_dict[key]['size'][-1]} - def change_precision_choices(key): #根据选择的模型修改可选的语言 - if key =="Faster Whisper (多语种)": - if default_batch_size <= 4: - precision = 'int8' - elif is_half: - precision = 'float16' - else: - precision = 'float32' - else: - precision = 'float32' - # return gr.Dropdown(choices=asr_dict[key]['precision']) - return {"__type__": "update", "choices": asr_dict[key]['precision'],"value":precision} - asr_model.change(change_lang_choices, [asr_model], [asr_lang]) - asr_model.change(change_size_choices, [asr_model], [asr_size]) - asr_model.change(change_precision_choices, [asr_model], [asr_precision]) - - - gr.Markdown(value=i18n("0d-语音文本校对标注工具")) - with gr.Row(): - with gr.Column(scale=3): - with gr.Row(): - path_list = gr.Textbox( - label=i18n(".list标注文件的路径"), - value="D:\\RVC1006\\GPT-SoVITS\\raw\\xxx.list", - interactive=True, - ) - label_info = gr.Textbox(label=i18n("打标工具进程输出信息")) - - open_label = gr.Button(value=i18n("开启打标WebUI"),variant="primary",visible=True) - close_label = gr.Button(value=i18n("关闭打标WebUI"),variant="primary",visible=False) - open_label.click(change_label, [path_list], [label_info,open_label,close_label]) - close_label.click(change_label, [path_list], [label_info,open_label,close_label]) - open_uvr5.click(change_uvr5, [], [uvr5_info,open_uvr5,close_uvr5]) - close_uvr5.click(change_uvr5, [], [uvr5_info,open_uvr5,close_uvr5]) - - with gr.TabItem(i18n("1-GPT-SoVITS-TTS")): - with gr.Row(): - with gr.Row(): - exp_name = gr.Textbox(label=i18n("*实验/模型名"), value="xxx", interactive=True) - gpu_info = gr.Textbox(label=i18n("显卡信息"), value=gpu_info, visible=True, interactive=False) - version_checkbox = gr.Radio(label=i18n("版本"),value=version,choices=['v1','v2']) - with gr.Row(): - pretrained_s2G = gr.Textbox(label=i18n("预训练的SoVITS-G模型路径"), value=pretrained_sovits_name[-int(version[-1])+2], interactive=True, lines=2, max_lines=3,scale=9) - pretrained_s2D = gr.Textbox(label=i18n("预训练的SoVITS-D模型路径"), value=pretrained_sovits_name[-int(version[-1])+2].replace("s2G","s2D"), interactive=True, lines=2, max_lines=3,scale=9) - pretrained_s1 = gr.Textbox(label=i18n("预训练的GPT模型路径"), value=pretrained_gpt_name[-int(version[-1])+2], interactive=True, lines=2, max_lines=3,scale=10) - with gr.TabItem(i18n("1A-训练集格式化工具")): - gr.Markdown(value=i18n("输出logs/实验名目录下应有23456开头的文件和文件夹")) - with gr.Row(): - with gr.Row(): - inp_text = gr.Textbox(label=i18n("*文本标注文件"),value=r"D:\RVC1006\GPT-SoVITS\raw\xxx.list",interactive=True,scale=10) - with gr.Row(): - inp_wav_dir = gr.Textbox( - label=i18n("*训练集音频文件目录"), - # value=r"D:\RVC1006\GPT-SoVITS\raw\xxx", - interactive=True, - placeholder=i18n("填切割后音频所在目录！读取的音频文件完整路径=该目录-拼接-list文件里波形对应的文件名（不是全路径）。如果留空则使用.list文件里的绝对全路径。"), scale=10 - ) - gr.Markdown(value=i18n("1Aa-文本内容")) - with gr.Row(): - with gr.Row(): - gpu_numbers1a = gr.Textbox(label=i18n("GPU卡号以-分割，每个卡号一个进程"),value="%s-%s"%(gpus,gpus),interactive=True) - with gr.Row(): - bert_pretrained_dir = gr.Textbox(label=i18n("预训练的中文BERT模型路径"),value="GPT_SoVITS/pretrained_models/chinese-roberta-wwm-ext-large",interactive=False,lines=2) - with gr.Row(): - button1a_open = gr.Button(i18n("开启文本获取"), variant="primary",visible=True) - button1a_close = gr.Button(i18n("终止文本获取进程"), variant="primary",visible=False) - with gr.Row(): - info1a=gr.Textbox(label=i18n("文本进程输出信息")) - gr.Markdown(value=i18n("1Ab-SSL自监督特征提取")) - with gr.Row(): - with gr.Row(): - gpu_numbers1Ba = gr.Textbox(label=i18n("GPU卡号以-分割，每个卡号一个进程"),value="%s-%s"%(gpus,gpus),interactive=True) - with gr.Row(): - cnhubert_base_dir = gr.Textbox(label=i18n("预训练的SSL模型路径"),value="GPT_SoVITS/pretrained_models/chinese-hubert-base",interactive=False,lines=2) - with gr.Row(): - button1b_open = gr.Button(i18n("开启SSL提取"), variant="primary",visible=True) - button1b_close = gr.Button(i18n("终止SSL提取进程"), variant="primary",visible=False) - with gr.Row(): - info1b=gr.Textbox(label=i18n("SSL进程输出信息")) - gr.Markdown(value=i18n("1Ac-语义token提取")) - with gr.Row(): - with gr.Row(): - gpu_numbers1c = gr.Textbox(label=i18n("GPU卡号以-分割，每个卡号一个进程"),value="%s-%s"%(gpus,gpus),interactive=True) - with gr.Row(): - pretrained_s2G_ = gr.Textbox(label=i18n("预训练的SoVITS-G模型路径"), value=pretrained_sovits_name[-int(version[-1])+2], interactive=False,lines=2) - with gr.Row(): - button1c_open = gr.Button(i18n("开启语义token提取"), variant="primary",visible=True) - button1c_close = gr.Button(i18n("终止语义token提取进程"), variant="primary",visible=False) - with gr.Row(): - info1c=gr.Textbox(label=i18n("语义token提取进程输出信息")) - gr.Markdown(value=i18n("1Aabc-训练集格式化一键三连")) - with gr.Row(): - with gr.Row(): - button1abc_open = gr.Button(i18n("开启一键三连"), variant="primary",visible=True) - button1abc_close = gr.Button(i18n("终止一键三连"), variant="primary",visible=False) - with gr.Row(): - info1abc=gr.Textbox(label=i18n("一键三连进程输出信息")) - - pretrained_s2G.change(sync,[pretrained_s2G],[pretrained_s2G_]) - open_asr_button.click(open_asr, [asr_inp_dir, asr_opt_dir, asr_model, asr_size, asr_lang, asr_precision], [asr_info,open_asr_button,close_asr_button,path_list,inp_text,inp_wav_dir]) - close_asr_button.click(close_asr, [], [asr_info,open_asr_button,close_asr_button]) - open_slicer_button.click(open_slice, [slice_inp_path,slice_opt_root,threshold,min_length,min_interval,hop_size,max_sil_kept,_max,alpha,n_process], [slicer_info,open_slicer_button,close_slicer_button,asr_inp_dir,denoise_input_dir,inp_wav_dir]) - close_slicer_button.click(close_slice, [], [slicer_info,open_slicer_button,close_slicer_button]) - open_denoise_button.click(open_denoise, [denoise_input_dir,denoise_output_dir], [denoise_info,open_denoise_button,close_denoise_button,asr_inp_dir,inp_wav_dir]) - close_denoise_button.click(close_denoise, [], [denoise_info,open_denoise_button,close_denoise_button]) - - button1a_open.click(open1a, [inp_text,inp_wav_dir,exp_name,gpu_numbers1a,bert_pretrained_dir], [info1a,button1a_open,button1a_close]) - button1a_close.click(close1a, [], [info1a,button1a_open,button1a_close]) - button1b_open.click(open1b, [inp_text,inp_wav_dir,exp_name,gpu_numbers1Ba,cnhubert_base_dir], [info1b,button1b_open,button1b_close]) - button1b_close.click(close1b, [], [info1b,button1b_open,button1b_close]) - button1c_open.click(open1c, [inp_text,exp_name,gpu_numbers1c,pretrained_s2G], [info1c,button1c_open,button1c_close]) - button1c_close.click(close1c, [], [info1c,button1c_open,button1c_close]) - button1abc_open.click(open1abc, [inp_text,inp_wav_dir,exp_name,gpu_numbers1a,gpu_numbers1Ba,gpu_numbers1c,bert_pretrained_dir,cnhubert_base_dir,pretrained_s2G], [info1abc,button1abc_open,button1abc_close]) - button1abc_close.click(close1abc, [], [info1abc,button1abc_open,button1abc_close]) - with gr.TabItem(i18n("1B-微调训练")): - gr.Markdown(value=i18n("1Ba-SoVITS训练。用于分享的模型文件输出在SoVITS_weights下。")) - with gr.Row(): - with gr.Column(): - with gr.Row(): - batch_size = gr.Slider(minimum=1,maximum=40,step=1,label=i18n("每张显卡的batch_size"),value=default_batch_size,interactive=True) - total_epoch = gr.Slider(minimum=1,maximum=25,step=1,label=i18n("总训练轮数total_epoch，不建议太高"),value=8,interactive=True) - with gr.Row(): - text_low_lr_rate = gr.Slider(minimum=0.2,maximum=0.6,step=0.05,label=i18n("文本模块学习率权重"),value=0.4,interactive=True) - save_every_epoch = gr.Slider(minimum=1,maximum=25,step=1,label=i18n("保存频率save_every_epoch"),value=4,interactive=True) - with gr.Column(): - with gr.Column(): - if_save_latest = gr.Checkbox(label=i18n("是否仅保存最新的ckpt文件以节省硬盘空间"), value=True, interactive=True, show_label=True) - if_save_every_weights = gr.Checkbox(label=i18n("是否在每次保存时间点将最终小模型保存至weights文件夹"), value=True, interactive=True, show_label=True) - with gr.Row(): - gpu_numbers1Ba = gr.Textbox(label=i18n("GPU卡号以-分割，每个卡号一个进程"), value="%s" % (gpus), interactive=True) - with gr.Row(): - with gr.Row(): - button1Ba_open = gr.Button(i18n("开启SoVITS训练"), variant="primary",visible=True) - button1Ba_close = gr.Button(i18n("终止SoVITS训练"), variant="primary",visible=False) - with gr.Row(): - info1Ba=gr.Textbox(label=i18n("SoVITS训练进程输出信息")) - gr.Markdown(value=i18n("1Bb-GPT训练。用于分享的模型文件输出在GPT_weights下。")) - with gr.Row(): - with gr.Column(): - with gr.Row(): - batch_size1Bb = gr.Slider(minimum=1,maximum=40,step=1,label=i18n("每张显卡的batch_size"),value=default_batch_size,interactive=True) - total_epoch1Bb = gr.Slider(minimum=2,maximum=50,step=1,label=i18n("总训练轮数total_epoch"),value=15,interactive=True) - with gr.Row(): - save_every_epoch1Bb = gr.Slider(minimum=1,maximum=50,step=1,label=i18n("保存频率save_every_epoch"),value=5,interactive=True) - if_dpo = gr.Checkbox(label=i18n("是否开启dpo训练选项(实验性)"), value=False, interactive=True, show_label=True) - with gr.Column(): - with gr.Column(): - if_save_latest1Bb = gr.Checkbox(label=i18n("是否仅保存最新的ckpt文件以节省硬盘空间"), value=True, interactive=True, show_label=True) - if_save_every_weights1Bb = gr.Checkbox(label=i18n("是否在每次保存时间点将最终小模型保存至weights文件夹"), value=True, interactive=True, show_label=True) - with gr.Row(): - gpu_numbers1Bb = gr.Textbox(label=i18n("GPU卡号以-分割，每个卡号一个进程"), value="%s" % (gpus), interactive=True) - with gr.Row(): - with gr.Row(): - button1Bb_open = gr.Button(i18n("开启GPT训练"), variant="primary",visible=True) - button1Bb_close = gr.Button(i18n("终止GPT训练"), variant="primary",visible=False) - with gr.Row(): - info1Bb=gr.Textbox(label=i18n("GPT训练进程输出信息")) - button1Ba_open.click(open1Ba, [batch_size,total_epoch,exp_name,text_low_lr_rate,if_save_latest,if_save_every_weights,save_every_epoch,gpu_numbers1Ba,pretrained_s2G,pretrained_s2D], [info1Ba,button1Ba_open,button1Ba_close]) - button1Ba_close.click(close1Ba, [], [info1Ba,button1Ba_open,button1Ba_close]) - button1Bb_open.click(open1Bb, [batch_size1Bb,total_epoch1Bb,exp_name,if_dpo,if_save_latest1Bb,if_save_every_weights1Bb,save_every_epoch1Bb,gpu_numbers1Bb,pretrained_s1], [info1Bb,button1Bb_open,button1Bb_close]) - button1Bb_close.click(close1Bb, [], [info1Bb,button1Bb_open,button1Bb_close]) - with gr.TabItem(i18n("1C-推理")): - gr.Markdown(value=i18n("选择训练完存放在SoVITS_weights和GPT_weights下的模型。默认的一个是底模，体验5秒Zero Shot TTS用。")) - with gr.Row(): - with gr.Row(): - GPT_dropdown = gr.Dropdown(label=i18n("*GPT模型列表"), choices=sorted(GPT_names,key=custom_sort_key),value=pretrained_gpt_name[0],interactive=True) - SoVITS_dropdown = gr.Dropdown(label=i18n("*SoVITS模型列表"), choices=sorted(SoVITS_names,key=custom_sort_key),value=pretrained_sovits_name[0],interactive=True) - with gr.Row(): - gpu_number_1C=gr.Textbox(label=i18n("GPU卡号,只能填1个整数"), value=gpus, interactive=True) - refresh_button = gr.Button(i18n("刷新模型路径"), variant="primary") - refresh_button.click(fn=change_choices,inputs=[],outputs=[SoVITS_dropdown,GPT_dropdown]) - with gr.Row(): - with gr.Row(): - batched_infer_enabled = gr.Checkbox(label=i18n("启用并行推理版本(推理速度更快)"), value=False, interactive=True, show_label=True) - with gr.Row(): - open_tts = gr.Button(value=i18n("开启TTS推理WebUI"),variant='primary',visible=True) - close_tts = gr.Button(value=i18n("关闭TTS推理WebUI"),variant='primary',visible=False) - with gr.Row(): - tts_info = gr.Textbox(label=i18n("TTS推理WebUI进程输出信息")) - open_tts.click(change_tts_inference, [bert_pretrained_dir,cnhubert_base_dir,gpu_number_1C,GPT_dropdown,SoVITS_dropdown, batched_infer_enabled], [tts_info,open_tts,close_tts]) - close_tts.click(change_tts_inference, [bert_pretrained_dir,cnhubert_base_dir,gpu_number_1C,GPT_dropdown,SoVITS_dropdown, batched_infer_enabled], [tts_info,open_tts,close_tts]) - version_checkbox.change(switch_version,[version_checkbox],[pretrained_s2G,pretrained_s2D,pretrained_s1,GPT_dropdown,SoVITS_dropdown]) - with gr.TabItem(i18n("2-GPT-SoVITS-变声")):gr.Markdown(value=i18n("施工中，请静候佳音")) - app.queue().launch(#concurrency_count=511, max_size=1022 - server_name="0.0.0.0", - inbrowser=True, - share=is_share, - server_port=webui_port_main, - quiet=True, - )