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import regex as re
try:
from config import config
LANGUAGE_IDENTIFICATION_LIBRARY = (
config.webui_config.language_identification_library
)
except:
LANGUAGE_IDENTIFICATION_LIBRARY = "langid"
module = LANGUAGE_IDENTIFICATION_LIBRARY.lower()
langid_languages = [
"af",
"am",
"an",
"ar",
"as",
"az",
"be",
"bg",
"bn",
"br",
"bs",
"ca",
"cs",
"cy",
"da",
"de",
"dz",
"el",
"en",
"eo",
"es",
"et",
"eu",
"fa",
"fi",
"fo",
"fr",
"ga",
"gl",
"gu",
"he",
"hi",
"hr",
"ht",
"hu",
"hy",
"id",
"is",
"it",
"ja",
"jv",
"ka",
"kk",
"km",
"kn",
"ko",
"ku",
"ky",
"la",
"lb",
"lo",
"lt",
"lv",
"mg",
"mk",
"ml",
"mn",
"mr",
"ms",
"mt",
"nb",
"ne",
"nl",
"nn",
"no",
"oc",
"or",
"pa",
"pl",
"ps",
"pt",
"qu",
"ro",
"ru",
"rw",
"se",
"si",
"sk",
"sl",
"sq",
"sr",
"sv",
"sw",
"ta",
"te",
"th",
"tl",
"tr",
"ug",
"uk",
"ur",
"vi",
"vo",
"wa",
"xh",
"zh",
"zu",
]
def classify_language(text: str, target_languages: list = None) -> str:
if module == "fastlid" or module == "fasttext":
from fastlid import fastlid, supported_langs
classifier = fastlid
if target_languages != None:
target_languages = [
lang for lang in target_languages if lang in supported_langs
]
fastlid.set_languages = target_languages
elif module == "langid":
import langid
classifier = langid.classify
if target_languages != None:
target_languages = [
lang for lang in target_languages if lang in langid_languages
]
langid.set_languages(target_languages)
else:
raise ValueError(f"Wrong module {module}")
lang = classifier(text)[0]
return lang
def classify_zh_ja(text: str) -> str:
for idx, char in enumerate(text):
unicode_val = ord(char)
# 检测日语字符
if 0x3040 <= unicode_val <= 0x309F or 0x30A0 <= unicode_val <= 0x30FF:
return "ja"
# 检测汉字字符
if 0x4E00 <= unicode_val <= 0x9FFF:
# 检查周围的字符
next_char = text[idx + 1] if idx + 1 < len(text) else None
if next_char and (
0x3040 <= ord(next_char) <= 0x309F or 0x30A0 <= ord(next_char) <= 0x30FF
):
return "ja"
return "zh"
def split_alpha_nonalpha(text, mode=1):
if mode == 1:
pattern = r"(?<=[\u4e00-\u9fff\u3040-\u30FF\d\s])(?=[\p{Latin}])|(?<=[\p{Latin}\s])(?=[\u4e00-\u9fff\u3040-\u30FF\d])"
elif mode == 2:
pattern = r"(?<=[\u4e00-\u9fff\u3040-\u30FF\s])(?=[\p{Latin}\d])|(?<=[\p{Latin}\d\s])(?=[\u4e00-\u9fff\u3040-\u30FF])"
else:
raise ValueError("Invalid mode. Supported modes are 1 and 2.")
return re.split(pattern, text)
if __name__ == "__main__":
text = "这是一个测试文本"
print(classify_language(text))
print(classify_zh_ja(text)) # "zh"
text = "これはテストテキストです"
print(classify_language(text))
print(classify_zh_ja(text)) # "ja"
text = "vits和Bert-VITS2是tts模型。花费3days.花费3天。Take 3 days"
print(split_alpha_nonalpha(text, mode=1))
# output: ['vits', '和', 'Bert-VITS', '2是', 'tts', '模型。花费3', 'days.花费3天。Take 3 days']
print(split_alpha_nonalpha(text, mode=2))
# output: ['vits', '和', 'Bert-VITS2', '是', 'tts', '模型。花费', '3days.花费', '3', '天。Take 3 days']
text = "vits 和 Bert-VITS2 是 tts 模型。花费3days.花费3天。Take 3 days"
print(split_alpha_nonalpha(text, mode=1))
# output: ['vits ', '和 ', 'Bert-VITS', '2 ', '是 ', 'tts ', '模型。花费3', 'days.花费3天。Take ', '3 ', 'days']
text = "vits 和 Bert-VITS2 是 tts 模型。花费3days.花费3天。Take 3 days"
print(split_alpha_nonalpha(text, mode=2))
# output: ['vits ', '和 ', 'Bert-VITS2 ', '是 ', 'tts ', '模型。花费', '3days.花费', '3', '天。Take ', '3 ', 'days']
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