File size: 4,355 Bytes
d232606 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 |
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']
|