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Live2D Mouth-sync artifact

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pymouth

pymouth 是基于Python的Live2D口型同步库. 你可以用音频文件, 甚至是AI模型输出的ndarray, 就能轻松的让你的Live2D形象开口 唱跳RAP v.
效果演示视频. Demo video

Quick Start

Environment

  • Python>=3.10
  • VTubeStudio>=1.28.0 (可选)

Installation

pip install pymouth

Get Started

  1. 在开始前你需要打开 VTubeStudio 的 Server 开关. 端口一般默认是8001.
    server_start.png

  2. 你需要确定自己Live2D口型同步的支持参数.
    请注意:下面提供一种简单的判断方式,但这种方式会修改(重置)Live2D模型口型部分参数,使用前请备份好自己的模型。
    如果你对自己的模型了如指掌,可以跳过这步。
    setup.png

    • 确认重置参数后,如果出现以下信息,则说明你的模型仅支持 基于分贝的口型同步 db.png
    • 确认重置参数后,如果出现以下信息,则说明你的模型仅支持 基于元音的口型同步 vowel.png
    • 如果VTubeStudio找到了所有参数,并且重置成功,说明两种方式都支持。只需要在接下来的代码中选择一种方式即可.
  3. 下面是两种基于不同方式的Demo.
    你可以找一个音频文件替换some.wav.
    samplerate:音频数据的采样率.
    output_device:输出设备Index. 这里很重要,如果不告诉插件播放设备是哪个,那么插件不会正常工作。 可以参考audio_devices_utils.py

    • 基于分贝的口型同步

      import time
      from pymouth import VTSAdapter, DBAnalyser
      
      def main():
        with VTSAdapter(DBAnalyser()) as a:
            a.action(audio='some.wav', samplerate=44100, output_device=2)
            time.sleep(100000)  # do something
      
      
      if __name__ == "__main__":
        main()
      
    • 基于元音的口型同步

      import time
      from pymouth import VTSAdapter, VowelAnalyser
      
      def main():
        with VTSAdapter(VowelAnalyser()) as a:
            a.action(audio='some.wav', samplerate=44100, output_device=2)
            time.sleep(100000)  # do something
      
      
      if __name__ == "__main__":
        main()
      

      第一次运行程序时, VTubeStudio会弹出插件授权界面, 通过授权后, 插件会在runtime路径下生成pymouth_vts_token.txt文件, 之后运行不会重复授权, 除非token文件丢失或在VTubeStudio移除授权.

API变化

1.3.0版本之后,分析器的对象由用户创建, VowelAnalyser 元音分析仪支持 temperature 参数,这个参数用来控制各个元音的置信度,值越大置信度越低,口型越平滑,反之亦然。temperature 不能为 0
1.3.0对两种 Analyser 进行了算法改进,使口型同步的效果更好。

import asyncio
from pymouth import VTSAdapter, VowelAnalyser


async def main():
    # with VTSAdapter(VowelAnalyser) as a: # 不能再用这种方式创建 Analyser
    with VTSAdapter(VowelAnalyser()) as a: # 需要由用户new出这个对象,temperature 默认为10,可以不填
        a.action(audio='aiueo.wav', samplerate=44100, output_device=2)  # no-block
        await asyncio.sleep(100000)

if __name__ == "__main__":
    asyncio.run(main())

1.2.0版本之后,移除了所有函数的协程调用方式(async/await),协程调用具有传染性,不利于用户维护。
目前只提供阻塞与非阻塞调用方式,非阻塞方式由内部线程池单线程实现,即无论a.action 被调用多少次,都会按照调用的现后顺序播放音频。

  • 如果你仍使用协程启动,可以参考下面的示例
    import asyncio
    from pymouth import VTSAdapter, VowelAnalyser
    
    
    async def main():
        with VTSAdapter(VowelAnalyser()) as a:
            a.action(audio='aiueo.wav', samplerate=44100, output_device=2)  # no-block
            # a.action_block(audio='aiueo.wav', samplerate=44100, output_device=2) # block
            await asyncio.sleep(100000)
    
    
    if __name__ == "__main__":
        asyncio.run(main())
    

About AI

下面是一个比较完整的使用pymouth作为AI TTS消费者的例子。

import queue
import threading
import time
from fish_speech import tts
from pymouth import VTSAdapter, DBAnalyser, VTSPluginInfo


class SpeakMsg:
    def __init__(self, msg: str, required: bool):
        self.msg = msg
        self.required = required
        self.create_timestamp = time.time()
        self.create_datetime = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(self.create_timestamp))


class Speaker:
    def __init__(self):
        self.queue = queue.Queue(1)

    def start(self):
        plugin_info = VTSPluginInfo(plugin_name='kanojyo2',
                                    developer='organics',
                                    authentication_token_path='./pymouth_vts_token.txt',
                                    plugin_icon=None)

        with VTSAdapter(DBAnalyser(), plugin_info=plugin_info) as a:
            while True:
                msg: SpeakMsg = self.queue.get()
                t0 = time.time()
                audio, rate = tts.tts_ndarray(msg.msg)
                print(f'speak time:{time.time() - t0:.02f}')

                a.action(audio=audio, samplerate=rate, output_device=2)

    def speak(self, msg: str, required=True):
        if required:
            self.queue.put(SpeakMsg(msg, required))
        else:
            try:
                self.queue.put_nowait(SpeakMsg(msg, required))
            except queue.Full:
                print("Queue Full")


if __name__ == "__main__":
    speakers = Speaker()
    # 这里的实现只作为参考而不是建议。对于AI等CPU密集型场景,使用线程而不是协程可能会更好。
    threading.Thread(target=speakers.start).start()

More Details

High Level

关键的代码只有两行:

with VTSAdapter(DBAnalyser()) as a:
    a.action(audio='some.wav', samplerate=44100, output_device=2)  # no-block
    # a.action_block(audio='aiueo.wav', samplerate=44100, output_device=2) # block

a.action()非阻塞,会立即返回,由程序内部维护线程池和队列。
a.action_block()阻塞,直到音频播放和处理完毕才会返回,纯同步代码无线程,线程由调用者维护。

VTSAdapter以下是详细的参数说明:

param required default describe
analyser Y 分析仪,必须是 Analyser 的子类,目前支持DBAnalyserVowelAnalyser
db_vts_mouth_param 'MouthOpen' 仅作用于DBAnalyser, VTS中控制mouth_input的参数, 如果不是默认值请自行修改.
vowel_vts_mouth_param dict[str,str] 仅作用于VowelAnalyser, VTS中控制mouth_input的参数, 如果不是默认值请自行修改.
ws_uri str websocket uri 默认:ws://localhost:8001
plugin_info VTSPluginInfo 插件信息,可以自定义

a.action() 会开始处理音频数据. 以下是详细的参数说明:

param required default describe
audio Y 音频数据, 可以是文件path, 可以是SoundFile对象, 也可以是ndarray
samplerate Y 采样率, 这取决与音频数据的采样率, 如果你无法获取到音频数据的采样率, 可以尝试输出设备的采样率.
output_device Y 输出设备Index, 这取决与硬件或虚拟设备. 可用 audio_devices_utils.py 打印当前系统音频设备信息.
finished_callback None 音频处理完成会回调这个方法.
auto_play True 是否自动播放音频,默认为True,会播放音频(自动将audio写入指定output_device)

Low Level

Get Started 演示了一种High Level API 如果你不使用 VTubeStudio 或者想更加灵活的使用, 可以尝试Low Level API. 下面是一个Demo.

import time

from pymouth import DBAnalyser


def callback(y: float, data):
    # Y is the Y coordinate of the model's mouth.
    # Like is 0.4212883452
    print(y)  # do something


with DBAnalyser() as a:
    a.action_noblock('zh.wav', 44100, output_device=2, callback=callback)  # no block
    # a.action_block()  # block
    print("end")
    time.sleep(1000000)
import time

from pymouth import VowelAnalyser


def callback(md: dict[str, float], data):
    """
    md like is:
    {
        'VoiceSilence': 0,
        'VoiceA': 0.6547555255,
        'VoiceI': 0.2872873444,
        'VoiceU': 0.1034789232,
        'VoiceE': 0.3927834533,
        'VoiceO': 0.1927834548,
    }
    """
    print(md)  # do something


with VowelAnalyser() as a:
    a.action_noblock('zh.wav', 44100, output_device=2, callback=callback)  # no block
    # a.action_block() # block
    print("end")
    time.sleep(1000000)

TODO

  • 文档补全
  • Test case

Special Thanks

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