Echo/fcb_photo_review
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补充缺页判断

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liuyebo
2024-10-10 11:24:16 +08:00
parent 15fe5d4f0d
commit e4b58e30c0
4 changed files with 56 additions and 8 deletions
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photo_review/auto_photo_review.py
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@@ -21,7 +21,8 @@ from services.paddle_services import IE_KEY
from ucloud import ufile
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
handle_original_data, handle_hospital, handle_department, handle_id, handle_age, parse_money, parse_hospital, \
parse_page_num, handle_tiny_int
# 尝试从二维码中获取高清图片
@@ -124,6 +125,7 @@ def information_extraction(phrec, pk_phhd, identity):
info_extract = model_util.ie_settlement(
better_img_path, common_util.ocr_result_to_layout(model_util.ocr(better_img_path))
)
ocr_text = None # 此处肯定不是出院记录，后续用不到
else:
target_image = model_util.det_book(img_path) # 识别文档区域并裁剪
dewarped_image = model_util.dewarp(target_image) # 去扭曲
@@ -158,7 +160,7 @@ def information_extraction(phrec, pk_phhd, identity):
creator=HOSTNAME, update_time=now, updater=HOSTNAME))
session.commit()
session.close()
return rec_type, info_extract
return rec_type, info_extract, ocr_text
# 从keys中获取准确率最高的value
@@ -395,6 +397,9 @@ def cost_task(pk_phhd, cost_list_ie_result):
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"])
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
@@ -416,19 +421,24 @@ def photo_review(pk_phhd, name):
session.close()
# 同一批图的标识
identity = int(time.time())
discharge_text = ''
for phrec in phrecs:
rec_type, ie_result = information_extraction(phrec, pk_phhd, identity)
rec_type, ie_result, ocr_text = information_extraction(phrec, pk_phhd, identity)
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] += value
if key == '页码':
rec_result[key].append(value) # 页码要区分来源，所以多包一层
else:
rec_result[key] += value
settlement_data = settlement_task(pk_phhd, settlement_result)
discharge_data = discharge_task(pk_phhd, discharge_result)
@@ -447,8 +457,26 @@ def photo_review(pk_phhd, name):
review_result['has_discharge'] = bool(discharge_result)
review_result['has_cost'] = bool(cost_result)
# 三项资料缺页判断
# TODO:缺页需要对页码进行抽取，暂未训练相关模型
review_result['full_page'] = True
page_description = []
# todo:关键词需根据实际情况调整
discharge_key = ['入院诊断', '入院日期', '出院日期', '出院诊断', '入院情况', '诊疗经过', '出院情况', '出院医嘱']
if not all(key in discharge_text for key in discharge_key):
page_description.append('《出院记录》缺页')
cost_missing_page = {}
if cost_data['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
if (review_result['has_settlement'] and review_result['has_discharge'] and review_result['has_cost']
and review_result['full_page']):