Plan/AiLLM.py

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)