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import os
import pytesseract
from transformers import AutoTokenizer, AutoModelForTokenClassification, pipeline
from IdentifyModel.cardModel import parse_id_card
# 初始化 Taiwanese BERT 模型
tokenizer = AutoTokenizer.from_pretrained("ckiplab/bert-base-chinese")
model = AutoModelForTokenClassification.from_pretrained("ckiplab/bert-base-chinese-ner")
ner_pipeline = pipeline("ner", model=model, tokenizer=tokenizer)
def llm_recognition(image, validation_type, language):
text = pytesseract.image_to_string(image, lang=language)
ner_results = ner_pipeline(text)
entities = {result['entity']: text[result['start']:result['end']] for result in ner_results}
return parse_id_card(text, validation_type, entities)
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