import copy import json import logging import os import re import shutil import time import uuid from collections import defaultdict from time import sleep import cv2 import jieba import numpy as np import zxingcpp from rapidfuzz import process, fuzz from sqlalchemy import update from db import MysqlSession from db.mysql import BdYljg, BdYlks, ZxIeCost, ZxIeDischarge, ZxIeSettlement, ZxPhhd, ZxPhrec, ZxIeReview, ZxIeResult from log import HOSTNAME from photo_review import PHHD_BATCH_SIZE, SLEEP_MINUTES, HOSPITAL_ALIAS, HOSPITAL_FILTER, DEPARTMENT_ALIAS, \ DEPARTMENT_FILTER, DISCHARGE_KEY, set_batch_id, get_batch_id from services.paddle_services import IE_KEY from ucloud import ufile, BUCKET from util import image_util, common_util, html_util, model_util from util.data_util import handle_date, handle_decimal, parse_department, handle_name, handle_insurance_type, \ handle_original_data, handle_hospital, handle_department, handle_id, handle_age, parse_money, parse_hospital, \ parse_page_num, handle_tiny_int def parse_qrcode(img_path, image_id): """ 解析二维码，尝试从中获取高清图片 :param img_path: 待解析图片 :param image_id: 图片id :return: 解析结果 """ def _parse_pdf_url(pdf_url_to_parse): local_pdf_path = None img_name, img_ext = common_util.parse_save_path(img_path) try: local_pdf_path = html_util.download_pdf(pdf_url_to_parse) pdf_imgs = image_util.pdf_to_imgs(local_pdf_path) # 结算单部分 better_settlement_path = common_util.get_processed_img_path(f'{img_name}.better_settlement.jpg') cv2.imwrite(better_settlement_path, pdf_imgs[0][0]) # 费用清单部分 better_cost_path = common_util.get_processed_img_path(f'{img_name}.better_cost.jpg') total_height = sum([p[0].shape[0] for p in pdf_imgs[1:]]) common_width = pdf_imgs[1][0].shape[1] better_cost_img = np.zeros((total_height, common_width, 3), dtype=np.uint8) current_y = 0 for pdf in pdf_imgs[1:]: height = pdf[0].shape[0] better_cost_img[current_y:current_y + height, :, :] = pdf[0] current_y += height # cost_text += pdf[1] # 费用清单文本暂时没用到 cv2.imwrite(better_cost_path, better_cost_img) return better_settlement_path, pdf_imgs[0][1], better_cost_path except Exception as ex: logging.getLogger('error').error('解析pdf失败！', exc_info=ex) return None, None, None finally: if local_pdf_path: common_util.delete_temp_file(local_pdf_path) jsczt_base_url = 'http://einvoice.jsczt.cn' try: img = cv2.imread(img_path) results = zxingcpp.read_barcodes(img, text_mode=zxingcpp.TextMode.HRI) except Exception as e: logging.getLogger('error').info('二维码识别失败', exc_info=e) results = [] for result in results: try: url = result.text if url.startswith(jsczt_base_url): id_base = html_util.get_jsczt_id_base(url) if not id_base: continue pdf_url = f'{jsczt_base_url}/download?idBase={id_base}' return _parse_pdf_url(pdf_url) elif '/yldzpjqr/invoice/query/issueinfo' in url: # 无锡医院 pdf_url = html_util.get_wx_pdf_url(url) if not pdf_url: continue return _parse_pdf_url(pdf_url) elif '/dzfp/tz3y' in url: # 泰州市第三人民医院 pdf_url = html_util.get_tz3y_pdf_url(url) if not pdf_url: continue return _parse_pdf_url(pdf_url) elif url.startswith('http://weixin.qq.com'): # 无效地址 continue else: logging.getLogger('qr').info(f'[{image_id}]中有未知二维码内容：{url}') except Exception as e: logging.getLogger('error').error('从二维码中获取高清图片时出错', exc_info=e) continue return None, None, None # 关键信息提取 def information_extraction(phrec, pk_phhd): """ 处理单张图片 :param phrec:图片信息 :param pk_phhd:案子主键 :return:记录类型，信息抽取结果 """ img_path = common_util.get_processed_img_path(phrec.cfjaddress) if not os.path.exists(img_path): original_img_path = common_util.get_img_path(phrec.cfjaddress) if not original_img_path: img_url = ufile.get_private_url(phrec.cfjaddress) if not img_url: return None, None, None original_img_path = common_util.save_to_local(img_url) shutil.copy2(original_img_path, img_path) if image_util.is_photo(img_path): book_img_path = model_util.det_book(img_path) # 识别文档区域并裁剪 dewarped_img_path = model_util.dewarp(book_img_path) # 去扭曲 else: # todo:也可能是图片，后续添加细分逻辑 dewarped_img_path = img_path angles = model_util.clas_orientation(dewarped_img_path) ocr_text = '' info_extract = [] rec_type = None for angle in angles: ocr_result = [] rotated_img = image_util.rotate(dewarped_img_path, int(angle)) split_results = image_util.split(rotated_img) for split_result in split_results: if split_result['img'] is None: continue a4_img = image_util.expand_to_a4_size(split_result['img']) ocr_result += model_util.ocr(a4_img) tmp_ocr_text = common_util.ocr_result_to_text(ocr_result) tmp_rec_type = model_util.clas_text(tmp_ocr_text) if ocr_text else None if not tmp_rec_type: rec_dict = { '1': '基本医保结算单', '3': '出院记录', '4': '费用清单', } tmp_rec_type = rec_dict.get(phrec.cRectype) if tmp_rec_type == '基本医保结算单': tmp_info_extract = model_util.ie_settlement(rotated_img, common_util.ocr_result_to_layout(ocr_result)) elif tmp_rec_type == '出院记录': tmp_info_extract = model_util.ie_discharge(rotated_img, common_util.ocr_result_to_layout(ocr_result)) elif tmp_rec_type == '费用清单': tmp_info_extract = model_util.ie_cost(rotated_img, common_util.ocr_result_to_layout(ocr_result)) else: tmp_info_extract = [] if len(tmp_info_extract) > len(info_extract): info_extract = tmp_info_extract ocr_text = tmp_ocr_text rec_type = tmp_rec_type if info_extract: result_json = json.dumps(info_extract, ensure_ascii=False) if len(result_json) > 5000: result_json = result_json[:5000] now = common_util.get_default_datetime() session = MysqlSession() session.add(ZxIeResult(pk_phhd=pk_phhd, pk_phrec=phrec.pk_phrec, id=get_batch_id(), cfjaddress=phrec.cfjaddress, content=result_json, create_time=now, creator=HOSTNAME, update_time=now, updater=HOSTNAME)) session.commit() session.close() return rec_type, info_extract, ocr_text # 从keys中获取准确率最高的value def get_best_value_of_key(source, key): # 最终结果 result = None # 最大可能性 best_probability = 0 values = source.get(key) if values: for value in values: for v in value: text = v.get("text") probability = v.get("probability") if text and probability > best_probability: result = text best_probability = probability return result # 从keys中获取所有value组成list def get_values_of_key(source, key): result = [] values = source.get(key) if values: for value in values: for v in value: v = v.get("text") if v: result.append(v) # 去重 return list(set(result)) def save_or_update_ie(table, pk_phhd, data): data = {k: v for k, v in data.items() if v is not None and v != ""} obj = table(**data) session = MysqlSession() db_data = session.query(table).filter_by(pk_phhd=pk_phhd).one_or_none() now = common_util.get_default_datetime() if db_data: # 更新 db_data.update_time = now db_data.creator = HOSTNAME for k, v in data.items(): setattr(db_data, k, v) else: # 新增 obj.create_time = now obj.creator = HOSTNAME obj.update_time = now obj.updater = HOSTNAME session.add(obj) session.commit() session.close() def search_hospital(hospital): def _filter_search_keywords(keywords): keywords = [x for x in keywords if x not in HOSPITAL_FILTER and len(x) > 1] result1 = "" result2 = "" for keyword in keywords: if "医院" in keyword: break result2 = result1 result1 = keyword result = [result1] if result2: result.append(result2) return result cut_list = jieba.lcut(hospital, HMM=False) session = MysqlSession() yljg = session.query(BdYljg.pk_yljg, BdYljg.name).filter(BdYljg.name.like(f"%{'%'.join(cut_list)}%")).all() if not yljg: filter_keywords = _filter_search_keywords(cut_list) for filter_keyword in filter_keywords: yljg = session.query(BdYljg.pk_yljg, BdYljg.name).filter(BdYljg.name.like(f"%{filter_keyword}%")).all() if yljg: break session.close() yljg = {row.pk_yljg: row.name for row in yljg} best_match = process.extractOne(hospital, yljg, scorer=fuzz.partial_token_set_ratio) return best_match def search_department(department): def _filter_search_keywords(keywords): keywords = [x for x in keywords if x not in DEPARTMENT_FILTER] return keywords cut_list = jieba.lcut(department, HMM=False) session = MysqlSession() cut_list = _filter_search_keywords(cut_list) if not cut_list: return None ylks = session.query(BdYlks.pk_ylks, BdYlks.name).filter(BdYlks.name.like(f"%{'%'.join(cut_list)}%")).all() if not ylks: filter_keywords = cut_list for filter_keyword in filter_keywords: ylks = session.query(BdYlks.pk_ylks, BdYlks.name).filter(BdYlks.name.like(f"%{filter_keyword}%")).all() if ylks: break session.close() ylks = {row.pk_ylks: row.name for row in ylks} best_match = process.extractOne(department, ylks, scorer=fuzz.token_ratio) if best_match and best_match[0] in ["内科", "外科"]: # 降低内科、外科的优先级 best_match = list(best_match) best_match[1] -= 100 return best_match def settlement_task(pk_phhd, settlement_list_ie_result): settlement_data = { "pk_phhd": pk_phhd, "name": handle_name(get_best_value_of_key(settlement_list_ie_result, IE_KEY['name'])), "admission_date_str": handle_original_data( get_best_value_of_key(settlement_list_ie_result, IE_KEY['admission_date'])), "discharge_date_str": handle_original_data( get_best_value_of_key(settlement_list_ie_result, IE_KEY['discharge_date'])), "personal_cash_payment_str": handle_original_data( get_best_value_of_key(settlement_list_ie_result, IE_KEY['personal_cash_payment'])), "personal_account_payment_str": handle_original_data( get_best_value_of_key(settlement_list_ie_result, IE_KEY['personal_account_payment'])), "personal_funded_amount_str": handle_original_data( get_best_value_of_key(settlement_list_ie_result, IE_KEY['personal_funded_amount'])), "medical_insurance_type_str": handle_original_data( get_best_value_of_key(settlement_list_ie_result, IE_KEY['medical_insurance_type'])), "admission_id": handle_id(get_best_value_of_key(settlement_list_ie_result, IE_KEY['admission_id'])), "settlement_id": handle_id(get_best_value_of_key(settlement_list_ie_result, IE_KEY['settlement_id'])), } settlement_data["admission_date"] = handle_date(settlement_data["admission_date_str"]) settlement_data["admission_date"] = handle_date(settlement_data["admission_date_str"]) settlement_data["discharge_date"] = handle_date(settlement_data["discharge_date_str"]) settlement_data["personal_cash_payment"] = handle_decimal(settlement_data["personal_cash_payment_str"]) settlement_data["personal_account_payment"] = handle_decimal(settlement_data["personal_account_payment_str"]) settlement_data["personal_funded_amount"] = handle_decimal(settlement_data["personal_funded_amount_str"]) settlement_data["medical_insurance_type"] = handle_insurance_type(settlement_data["medical_insurance_type_str"]) parse_money_result = parse_money( get_best_value_of_key(settlement_list_ie_result, IE_KEY['uppercase_medical_expenses']), get_best_value_of_key(settlement_list_ie_result, IE_KEY['medical_expenses'])) settlement_data["medical_expenses_str"] = handle_original_data(parse_money_result[0]) settlement_data["medical_expenses"] = parse_money_result[1] save_or_update_ie(ZxIeSettlement, pk_phhd, settlement_data) return settlement_data def discharge_task(pk_phhd, discharge_record_ie_result): hospitals = get_values_of_key(discharge_record_ie_result, IE_KEY['hospital']) departments = get_values_of_key(discharge_record_ie_result, IE_KEY['department']) discharge_data = { "pk_phhd": pk_phhd, "hospital": handle_hospital(",".join(hospitals)), "department": handle_department(",".join(departments)), "name": handle_name(get_best_value_of_key(discharge_record_ie_result, IE_KEY['name'])), "admission_date_str": handle_original_data( get_best_value_of_key(discharge_record_ie_result, IE_KEY['admission_date'])), "discharge_date_str": handle_original_data( get_best_value_of_key(discharge_record_ie_result, IE_KEY['discharge_date'])), "doctor": handle_name(get_best_value_of_key(discharge_record_ie_result, IE_KEY['doctor'])), "admission_id": handle_id(get_best_value_of_key(discharge_record_ie_result, IE_KEY['admission_id'])), "age": handle_age(get_best_value_of_key(discharge_record_ie_result, IE_KEY['age'])), } discharge_data["admission_date"] = handle_date(discharge_data["admission_date_str"]) discharge_data["discharge_date"] = handle_date(discharge_data["discharge_date_str"]) if hospitals: match_hospitals = [] for hospital in hospitals: parsed_hospitals = parse_hospital(hospital) for parsed_hospital in parsed_hospitals: search_result = search_hospital(parsed_hospital) match_hospitals.append(search_result) if search_result and search_result[1] == 100: break for hospital_alias_key in HOSPITAL_ALIAS.keys(): if hospital_alias_key in parsed_hospital: for hospital_alias in HOSPITAL_ALIAS[hospital_alias_key]: new_hospital = parsed_hospital.replace(hospital_alias_key, hospital_alias) match_hospitals.append(search_hospital(new_hospital)) break best_match = None best_score = 0 for match_hospital in match_hospitals: if match_hospital and match_hospital[1] > best_score: best_match = match_hospital best_score = match_hospital[1] if best_score == 100: break if best_match: discharge_data["pk_yljg"] = best_match[2] if departments: match_departments = [] for department in departments: parsed_departments = parse_department(department) for parsed_department in parsed_departments: search_result = search_department(parsed_department) match_departments.append(search_result) if search_result and search_result[1] == 100: break for department_alias_key in DEPARTMENT_ALIAS.keys(): if department_alias_key in parsed_department: for department_alias in DEPARTMENT_ALIAS[department_alias_key]: new_department = parsed_department.replace(department_alias_key, department_alias) match_departments.append(search_department(new_department)) break best_match = None best_score = -1000 for match_department in match_departments: if match_department and match_department[1] > best_score: best_match = match_department best_score = match_department[1] if best_score == 100: break if best_match: discharge_data["pk_ylks"] = best_match[2] save_or_update_ie(ZxIeDischarge, pk_phhd, discharge_data) return discharge_data def cost_task(pk_phhd, cost_list_ie_result): cost_data = { "pk_phhd": pk_phhd, "name": handle_name(get_best_value_of_key(cost_list_ie_result, IE_KEY['name'])), "admission_date_str": handle_original_data( get_best_value_of_key(cost_list_ie_result, IE_KEY['admission_date'])), "discharge_date_str": handle_original_data( get_best_value_of_key(cost_list_ie_result, IE_KEY['discharge_date'])), "medical_expenses_str": handle_original_data( get_best_value_of_key(cost_list_ie_result, IE_KEY['medical_expenses'])) } cost_data["admission_date"] = handle_date(cost_data["admission_date_str"]) cost_data["discharge_date"] = handle_date(cost_data["discharge_date_str"]) cost_data["medical_expenses"] = handle_decimal(cost_data["medical_expenses_str"]) if cost_list_ie_result.get(IE_KEY['page']): page_nums, page_count = parse_page_num(cost_list_ie_result[IE_KEY['page']]) cost_data['page_nums'] = handle_original_data(','.join(page_nums)) cost_data['page_count'] = handle_tiny_int(page_count) save_or_update_ie(ZxIeCost, pk_phhd, cost_data) return cost_data def parse_pdf_text(settlement_text): pattern = (r'(?:交款人：(.*?)\n|住院时间：(.*?)至(.*?)\n|\(小写\)(.*?)\n|个人现金支付：(.*?)\n|个人账户支付：(.*?)\n' r'|个人自费：(.*?)\n|医保类型：(.*?)\n|住院科别：(.*?)\n|住院号：(.*?)\n|票据号码：(.*?)\n|)') # 查找所有匹配项 matches = re.findall(pattern, settlement_text) results = {} keys = ['患者姓名', '入院日期', '出院日期', '费用总额', '个人现金支付', '个人账户支付', '个人自费', '医保类型', '科室', '住院号', '医保结算单号码'] for match in matches: for key, value in zip(keys, match): if value: results[key] = [[{'text': value, 'probability': 1}]] settlement_key = ['患者姓名', '入院日期', '出院日期', '费用总额', '个人现金支付', '个人账户支付', '个人自费', '医保类型', '住院号', '医保结算单号码'] discharge_key = ['科室', '患者姓名', '入院日期', '出院日期', '住院号'] cost_key = ['患者姓名', '入院日期', '出院日期', '费用总额'] settlement_result = {key: copy.copy(results[key]) for key in settlement_key if key in results} discharge_result = {key: copy.copy(results[key]) for key in discharge_key if key in results} cost_result = {key: copy.copy(results[key]) for key in cost_key if key in results} return settlement_result, discharge_result, cost_result def photo_review(pk_phhd, name): """ 处理单个报销案子 :param pk_phhd: 报销单主键 :param name: 报销人姓名 """ settlement_result = defaultdict(list) discharge_result = defaultdict(list) cost_result = defaultdict(list) session = MysqlSession() phrecs = session.query(ZxPhrec.pk_phrec, ZxPhrec.cRectype, ZxPhrec.cfjaddress).filter( ZxPhrec.pk_phhd == pk_phhd ).order_by(ZxPhrec.cRectype, ZxPhrec.rowno).all() session.close() # 同一批图的标识 set_batch_id(uuid.uuid4().hex) processed_img_dir = common_util.get_processed_img_path('') os.makedirs(processed_img_dir, exist_ok=True) has_pdf = False # 是否获取到了pdf，获取到可以直接利用pdf更快的获取信息 better_settlement_path = None better_cost_path = None settlement_text = '' qrcode_img_id = None for phrec in phrecs: original_img_path = common_util.get_img_path(phrec.cfjaddress) if not original_img_path: img_url = ufile.get_private_url(phrec.cfjaddress) if not img_url: continue original_img_path = common_util.save_to_local(img_url) img_path = common_util.get_processed_img_path(phrec.cfjaddress) shutil.copy2(original_img_path, img_path) # 尝试从二维码中获取高清图片 better_settlement_path, settlement_text, better_cost_path = parse_qrcode(img_path, phrec.cfjaddress) if better_settlement_path: has_pdf = True qrcode_img_id = phrec.cfjaddress break discharge_text = '' if has_pdf: settlement_result, discharge_result, cost_result = parse_pdf_text(settlement_text) discharge_ie_result = defaultdict(list) is_cost_updated = False for phrec in phrecs: if phrec.cRectype == '1': if phrec.cfjaddress == qrcode_img_id: try: ufile.copy_file(BUCKET, phrec.cfjaddress, "drg2015", phrec.cfjaddress) ufile.upload_file(phrec.cfjaddress, better_settlement_path) except Exception as e: logging.error("更新结算单pdf图片出错", exc_info=e) elif phrec.cRectype == '3': rec_type, ie_result, ocr_text = information_extraction(phrec, pk_phhd) if rec_type == '出院记录': discharge_text += ocr_text for key, value in ie_result.items(): discharge_ie_result[key].append(value) # 暂不替换费用清单 # elif phrec.cRectype == '4': # if not is_cost_updated: # try: # ufile.copy_file(BUCKET, phrec.cfjaddress, "drg2015", phrec.cfjaddress) # ufile.upload_file(phrec.cfjaddress, better_cost_path) # except Exception as e: # logging.error("更新费用清单pdf图片出错", exc_info=e) # finally: # is_cost_updated = True # 合并出院记录 for key, value in discharge_ie_result.items(): ie_value = get_best_value_of_key(discharge_ie_result, key) pdf_value = discharge_result.get(key)[0][0]['text'] if discharge_result.get(key) else '' similarity_ratio = fuzz.ratio(ie_value, pdf_value) if similarity_ratio < 60: discharge_result[key] = [[{'text': ie_value, 'probability': 1}]] else: for phrec in phrecs: rec_type, ie_result, ocr_text = information_extraction(phrec, pk_phhd) if rec_type == '基本医保结算单': rec_result = settlement_result elif rec_type == '出院记录': rec_result = discharge_result discharge_text += ocr_text elif rec_type == '费用清单': rec_result = cost_result else: rec_result = None if rec_result is not None: for key, value in ie_result.items(): rec_result[key].append(value) # 删除多余图片 if os.path.exists(processed_img_dir) and os.path.isdir(processed_img_dir): shutil.rmtree(processed_img_dir) settlement_data = settlement_task(pk_phhd, settlement_result) discharge_data = discharge_task(pk_phhd, discharge_result) cost_data = cost_task(pk_phhd, cost_result) # 三项资料完整性判断 # 三项资料缺项判断 review_result = { 'pk_phhd': pk_phhd, 'has_settlement': bool(settlement_result), 'has_discharge': bool(discharge_result), 'has_cost': bool(cost_result), } if (review_result['has_settlement'] and settlement_data.get('personal_account_payment') and settlement_data.get('personal_cash_payment') and settlement_data.get('medical_expenses')): review_result['has_settlement'] &= ( float(settlement_data['personal_account_payment']) + float(settlement_data['personal_cash_payment']) < float(settlement_data['medical_expenses']) ) if has_pdf: review_result['has_discharge'] &= bool(discharge_text) # 三项资料缺页判断 page_description = [] if review_result['has_discharge']: for discharge_item in DISCHARGE_KEY: if not any(key in discharge_text for key in DISCHARGE_KEY[discharge_item]): page_description.append(f"《出院记录》缺页") break if review_result['has_cost']: cost_missing_page = {} if cost_data.get('page_nums'): page_nums = cost_data['page_nums'].split(',') required_set = set(range(1, cost_data['page_count'] + 1)) page_set = set(page_nums) cost_missing_page = required_set - page_set if cost_missing_page: page_description.append(f"《住院费用清单》，缺第{','.join(cost_missing_page)}页") if page_description: review_result['full_page'] = False review_result['page_description'] = ';'.join(page_description) else: review_result['full_page'] = True review_result['integrity'] = (review_result['has_settlement'] and review_result['has_discharge'] and review_result['has_cost'] and review_result['full_page']) # 三项资料一致性判断 # 姓名一致性 name_list = [settlement_data['name'], discharge_data['name'], cost_data['name']] if sum(not bool(n) for n in name_list) > 1: # 有2个及以上空值直接认为都不一致 review_result['name_match'] = '0' else: unique_name = set(name_list) if len(unique_name) == 1: review_result['name_match'] = '1' if name == unique_name.pop() else '5' elif len(unique_name) == 2: if settlement_data['name'] != discharge_data['name'] and settlement_data['name'] != cost_data['name']: review_result['name_match'] = '2' elif discharge_data['name'] != settlement_data['name'] and discharge_data['name'] != cost_data['name']: review_result['name_match'] = '3' else: review_result['name_match'] = '4' else: review_result['name_match'] = '0' # 住院日期一致性 if (settlement_data['admission_date'] and discharge_data['admission_date'] and settlement_data['discharge_date'] and discharge_data['discharge_date'] and settlement_data['admission_date'] == discharge_data['admission_date'] and settlement_data['discharge_date'] == discharge_data['discharge_date']): review_result['admission_date_match'] = '1' else: review_result['admission_date_match'] = '0' # 出院日期一致性 discharge_date_list = [settlement_data['discharge_date'], discharge_data['discharge_date'], cost_data['discharge_date']] if sum(not bool(d) for d in discharge_date_list) > 1: review_result['discharge_date_match'] = '0' else: unique_discharge_date = set(discharge_date_list) if len(unique_discharge_date) == 1: review_result['discharge_date_match'] = '1' elif len(unique_discharge_date) == 2: if (settlement_data['discharge_date'] != discharge_data['discharge_date'] and settlement_data['discharge_date'] != cost_data['discharge_date']): review_result['discharge_date_match'] = '2' elif (discharge_data['discharge_date'] != settlement_data['discharge_date'] and discharge_data['discharge_date'] != cost_data['discharge_date']): review_result['discharge_date_match'] = '3' else: review_result['discharge_date_match'] = '4' else: review_result['discharge_date_match'] = '0' review_result['consistency'] = ( review_result['name_match'] == '1' and review_result['admission_date_match'] == '1' and review_result['discharge_date_match'] == '1') review_result['success'] = review_result['integrity'] and review_result['consistency'] save_or_update_ie(ZxIeReview, pk_phhd, review_result) def main(): """ 照片审核批量控制 """ while 1: session = MysqlSession() phhds = (session.query(ZxPhhd.pk_phhd, ZxPhhd.cXm) .join(ZxPhrec, ZxPhhd.pk_phhd == ZxPhrec.pk_phhd, isouter=True) .filter(ZxPhhd.exsuccess_flag == "1") .filter(ZxPhrec.pk_phrec.isnot(None)) .order_by(ZxPhhd.priority_num.desc()) .distinct().limit(PHHD_BATCH_SIZE).all()) # 将状态改为正在识别中 pk_phhd_values = [phhd.pk_phhd for phhd in phhds] update_flag = (update(ZxPhhd).where(ZxPhhd.pk_phhd.in_(pk_phhd_values)).values(exsuccess_flag="2")) session.execute(update_flag) session.commit() session.close() if phhds: for phhd in phhds: pk_phhd = phhd.pk_phhd logging.info(f"开始识别：{pk_phhd}") start_time = time.time() photo_review(pk_phhd, phhd.cXm) # 识别完成更新标识 session = MysqlSession() update_flag = (update(ZxPhhd).where(ZxPhhd.pk_phhd == pk_phhd).values( exsuccess_flag="8", ref_id1=HOSTNAME, checktime=common_util.get_default_datetime(), fFSYLFY=time.time() - start_time)) session.execute(update_flag) session.commit() session.close() else: # 没有查询到新案子，等待一段时间后再查 logging.info(f"暂未查询到需要识别的案子，等待{SLEEP_MINUTES}分钟...") sleep(SLEEP_MINUTES * 60)