80 lines
3.1 KiB
Python
80 lines
3.1 KiB
Python
import torch
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import numpy as np
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import logging
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import py3langid
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import re
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# Translate multi-channel audio data to mono-channel (numpy array),
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# support input of ComfyUI standard audio dictionary, tensor, numpy array.
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# 多通道音频数据转单通道(np数组)，支持输入ComfyUI标准音频字典，张量，np数组
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def audio_to_numpy(audio):
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if isinstance(audio, dict):
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audio = audio["waveform"]
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if isinstance(audio, torch.Tensor):
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if audio.shape[0] > 1:
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audio = audio[0]
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logging.warning(
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"Warning-MaskGCT-Audio_to_Numpy-E01: Audio batch is temporarily not supported, the first audio has been selected")
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audio = audio.squeeze()
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audio = np.array(audio.cpu())
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if isinstance(audio, np.ndarray):
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if len(audio.shape) > 1:
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audio = np.mean(audio, axis=0)
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audio = audio.squeeze()
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else:
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logging.error(
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"Error-MaskGCT-Audio_to_Numpy-E02: unsupported audio type", exc_info=True)
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return audio
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# Detect language, input text and supported language list/abbreviations, return language abbreviation and whether it is supported.
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# 检测语言，输入文本 和支持的语言列表/语言缩写，返回语言缩写和是否支持
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def obtain_language(text: str, supported_languages=None):
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language = py3langid.classify(text)[0]
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if supported_languages is None:
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supported = language in ["en", "zh", "ja", "fr", "ko", "de"]
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elif isinstance(supported_languages, str):
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supported = language == supported_languages
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elif isinstance(supported_languages, list):
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supported = language in supported_languages
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else:
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supported = True
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return (language, supported)
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# Slice text into fragments, input text and maximum length, return fragment list and combined fragment list.
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# 切分文本为片段，输入文本和最大长度，返回片段列表和组合的片段列表
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def slice_combination(text, length=100, language=None):
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character_ratio = {"en": 1, "zh": 0.6,
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"ja": 1.3, "fr": 1.5, "ko": 1, "de": 1.75}
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if language is None:
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language = py3langid.classify(text)[0]
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if language not in character_ratio.keys():
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language = "en"
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logging.warning(
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"Warning-MaskGCT-Slice_Combination: language not supported, use default language 'en' instead")
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length = int(length * character_ratio[language])
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if len(text) <= length:
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return ([text], [text])
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else:
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pattern = r'(?<=[，,。.！!\n])'
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fragments = re.split(pattern, text)
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# remove empty fragments
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fragments = [frag for frag in fragments if frag]
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n = len((fragments))
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if n == 1:
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return ([text], [text])
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elif n == 2:
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return (fragments, fragments)
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else:
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result = []
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combined = ""
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for i in range(n):
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combined += fragments[i]
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if len(combined) >= length:
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result.append(combined)
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combined = ""
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elif i == n - 1:
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result.append(combined)
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return (fragments, result)
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