91 lines
3.4 KiB
Python
91 lines
3.4 KiB
Python
# -*- coding: utf-8 -*-
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"""
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票据理赔自动化主模块
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功能清单
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https://liubiren.feishu.cn/docx/WFjTdBpzroUjQvxxrNIcKvGnneh?from=from_copylink
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"""
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from datetime import datetime
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from pathlib import Path
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from case import case_adjust
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from image import image_classify, image_recognize
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if __name__ == "__main__":
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# 初始化文件路径
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file_path = Path(__file__).parent
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# 初始化所有赔案的文件夹路径（需要注意在TraeCN中，文件路径需显式声明）
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folder_path = file_path / "directory"
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folder_path.mkdir(parents=True, exist_ok=True) # 若文件夹路径不存在则创建
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# 遍历文件夹中赔案文件夹并创建赔案档案
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for case_path in [x for x in folder_path.iterdir() if x.is_dir()]:
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# 初始化赔案档案（推送至TPA时，保险公司会提保险分公司名称、报案时间和影像件等，TPA签收后生成赔案号）
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dossier = {
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"report_layer": {
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"case_number": case_path.stem, # 默认为赔案文件夹名称
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"insurer_company": (
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insurer_company := "中银保险有限公司苏州分公司"
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), # 默认为中银保险有限公司苏州分公司
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"report_time": datetime(
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2025, 7, 25, 12, 0, 0
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), # 指定报案时间，默认为 datetime对象
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}, # 报案层
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"images_layer": [], # 影像件层
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"insured_person_layer": {}, # 出险人层
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"liabilities_layer": [], # 理赔责任层
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"receipts_layer": [], # 票据层
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"adjustment_layer": {}, # 理算层
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}
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# 遍历赔案文件夹内所有影像件路径
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for image_index, image_path in enumerate(
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sorted(
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[
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i
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for i in case_path.glob(pattern="*")
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if i.is_file() and i.suffix.lower() in [".jpg", ".jpeg", ".png"]
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],
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key=lambda i: i.stat().st_birthtime, # 根据影像件创建时间顺序排序
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),
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1,
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):
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# 分类影像件、旋正并整合至赔案档案
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image_classify(
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image_index=image_index, image_path=image_path, dossier=dossier
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)
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# 就影像件层按照影像件类型指定排序
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dossier["images_layer"].sort(
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key=lambda i: [
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"居民户口簿",
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"居民身份证(国徽面)",
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"居民身份证(头像面)",
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"居民身份证(国徽、头像面)",
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"中国港澳台地区及境外护照",
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"理赔申请书",
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"增值税发票",
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"医疗门诊收费票据",
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"医疗住院收费票据",
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"医疗费用清单",
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"银行卡",
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"其它",
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].index(i["image_type"])
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)
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# 遍历影像件层内影像件
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for image in dossier["images_layer"]:
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# 识别影像件并整合至赔案档案
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image_recognize(
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image=image,
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insurer_company=insurer_company,
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dossier=dossier,
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)
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# 就票据层按照开票日期和票据号顺序排序
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dossier["receipts_layer"].sort(key=lambda x: (x["date"], x["number"]))
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# 理算赔案并整合至赔案档案
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case_adjust(dossier=dossier)
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