新增二维码识别替换高清图片功能

2024-09-05 13:29:17 +08:00
parent 53a3dcd508
commit de631bef2e
6 changed files with 255 additions and 198 deletions
--- a/photo_review/init.py
+++ b/photo_review/init.py
@@ -2,9 +2,9 @@ import jieba
 from paddlenlp import Taskflow
 from paddleocr import PaddleOCR

-"""
+'''
 项目配置
-"""
+'''
 # 每次从数据库获取的案子数量
 PHHD_BATCH_SIZE = 10
 # 没有查询到案子的等待时间(分钟)
@@ -18,35 +18,35 @@ LAYOUT_ANALYSIS = False
 信息抽取关键词配置
 """
 # 患者姓名
-PATIENT_NAME = ["患者姓名"]
+PATIENT_NAME = ['患者姓名']
 # 入院日期
-ADMISSION_DATE = ["入院日期"]
+ADMISSION_DATE = ['入院日期']
 # 出院日期
-DISCHARGE_DATE = ["出院日期"]
+DISCHARGE_DATE = ['出院日期']
 # 发生医疗费
-MEDICAL_EXPENSES = ["费用总额"]
+MEDICAL_EXPENSES = ['费用总额']
 # 个人现金支付
-PERSONAL_CASH_PAYMENT = ["个人现金支付"]
+PERSONAL_CASH_PAYMENT = ['个人现金支付']
 # 个人账户支付
-PERSONAL_ACCOUNT_PAYMENT = ["个人账户支付"]
+PERSONAL_ACCOUNT_PAYMENT = ['个人账户支付']
 # 个人自费金额
-PERSONAL_FUNDED_AMOUNT = ["自费金额"]
+PERSONAL_FUNDED_AMOUNT = ['自费金额', '个人自费']
 # 医保类别
-MEDICAL_INSURANCE_TYPE = ["医保类型"]
+MEDICAL_INSURANCE_TYPE = ['医保类型']
 # 就诊医院
-HOSPITAL = ["医院"]
+HOSPITAL = ['医院']
 # 就诊科室
-DEPARTMENT = ["科室"]
+DEPARTMENT = ['科室']
 # 主治医生
-DOCTOR = ["主治医生"]
+DOCTOR = ['主治医生']
 # 住院号
-ADMISSION_ID = ["住院号"]
+ADMISSION_ID = ['住院号']
 # 医保结算单号码
-SETTLEMENT_ID = ["医保结算单号码"]
+SETTLEMENT_ID = ['医保结算单号码']
 # 年龄
-AGE = ["年龄"]
+AGE = ['年龄']
 # 大写总额
-UPPERCASE_MEDICAL_EXPENSES = ["大写总额"]
+UPPERCASE_MEDICAL_EXPENSES = ['大写总额']

 SETTLEMENT_LIST_SCHEMA = \
    (PATIENT_NAME + ADMISSION_DATE + DISCHARGE_DATE + MEDICAL_EXPENSES + PERSONAL_CASH_PAYMENT
@@ -58,47 +58,47 @@ DISCHARGE_RECORD_SCHEMA = \

 COST_LIST_SCHEMA = PATIENT_NAME + ADMISSION_DATE + DISCHARGE_DATE + MEDICAL_EXPENSES

-"""
+'''
 别名配置
-"""
+'''
 # 使用别名中的value替换key。考虑到效率问题，只会替换第一个匹配到的key。
 HOSPITAL_ALIAS = {
-    "沐阳": ["沭阳"],
-    "连水": ["涟水"],
-    "唯宁": ["睢宁"],
-    "九〇四": ["904"],
-    "漂水": ["溧水"],
+    '沐阳': ['沭阳'],
+    '连水': ['涟水'],
+    '唯宁': ['睢宁'],  # 雕宁
+    '九〇四': ['904'],
+    '漂水': ['溧水'],
 }
 DEPARTMENT_ALIAS = {
-    "耳鼻喉": ["耳鼻咽喉"],
-    "急症": ["急诊"],
+    '耳鼻喉': ['耳鼻咽喉'],
+    '急症': ['急诊'],
 }

-"""
+'''
 搜索过滤配置
-"""
+'''
 # 默认会过滤单字
-HOSPITAL_FILTER = ["医院", "人民", "第一", "第二", "第三", "大学", "附属"]
+HOSPITAL_FILTER = ['医院', '人民', '第一', '第二', '第三', '大学', '附属']

-DEPARTMENT_FILTER = ["医", "伤", "西", "新"]
+DEPARTMENT_FILTER = ['医', '伤', '西', '新']

-"""
+'''
 分词配置
-"""
-jieba.suggest_freq(("肿瘤", "医院"), True)
-jieba.suggest_freq(("骨", "伤"), True)
-jieba.suggest_freq(("感染", "性"), True)
-jieba.suggest_freq(("胆", "道"), True)
-jieba.suggest_freq(("脾", "胃"), True)
+'''
+jieba.suggest_freq(('肿瘤', '医院'), True)
+jieba.suggest_freq(('骨', '伤'), True)
+jieba.suggest_freq(('感染', '性'), True)
+jieba.suggest_freq(('胆', '道'), True)
+jieba.suggest_freq(('脾', '胃'), True)

-"""
+'''
 模型配置
-"""
-SETTLEMENT_IE = Taskflow("information_extraction", schema=SETTLEMENT_LIST_SCHEMA, model="uie-x-base",
-                         task_path="model/settlement_list_model", layout_analysis=LAYOUT_ANALYSIS, precision='fp16')
-DISCHARGE_IE = Taskflow("information_extraction", schema=DISCHARGE_RECORD_SCHEMA, model="uie-x-base",
-                        task_path="model/discharge_record_model", layout_analysis=LAYOUT_ANALYSIS, precision='fp16')
-COST_IE = Taskflow("information_extraction", schema=COST_LIST_SCHEMA, model="uie-x-base", device_id=1,
-                   task_path="model/cost_list_model", layout_analysis=LAYOUT_ANALYSIS, precision='fp16')
+'''
+SETTLEMENT_IE = Taskflow('information_extraction', schema=SETTLEMENT_LIST_SCHEMA, model='uie-x-base',
+                         task_path='model/settlement_list_model', layout_analysis=LAYOUT_ANALYSIS, precision='fp16')
+DISCHARGE_IE = Taskflow('information_extraction', schema=DISCHARGE_RECORD_SCHEMA, model='uie-x-base',
+                        task_path='model/discharge_record_model', layout_analysis=LAYOUT_ANALYSIS, precision='fp16')
+COST_IE = Taskflow('information_extraction', schema=COST_LIST_SCHEMA, model='uie-x-base', device_id=1,
+                   task_path='model/cost_list_model', layout_analysis=LAYOUT_ANALYSIS, precision='fp16')

 OCR = PaddleOCR(use_angle_cls=False, show_log=False, gpu_id=1, det_db_box_thresh=0.3)
--- a/photo_review/auto_photo_review.py
+++ b/photo_review/auto_photo_review.py
@@ -7,22 +7,23 @@ from collections import defaultdict
 from time import sleep

 import cv2
+import fitz
 import jieba
+import numpy as np
 import requests
+import zxingcpp
 from rapidfuzz import process, fuzz
 from sqlalchemy import update

 from db import MysqlSession
 from db.mysql import BdYljg, BdYlks, ZxIeResult, ZxIeCost, ZxIeDischarge, ZxIeSettlement, ZxPhhd, ZxPhrec
-from doc_dewarp import dewarp
 from log import HOSTNAME
-from paddle_detection import detector
 from photo_review import PATIENT_NAME, ADMISSION_DATE, DISCHARGE_DATE, MEDICAL_EXPENSES, PERSONAL_CASH_PAYMENT, \
    PERSONAL_ACCOUNT_PAYMENT, PERSONAL_FUNDED_AMOUNT, MEDICAL_INSURANCE_TYPE, HOSPITAL, DEPARTMENT, DOCTOR, \
    ADMISSION_ID, SETTLEMENT_ID, AGE, OCR, SETTLEMENT_IE, DISCHARGE_IE, COST_IE, PHHD_BATCH_SIZE, SLEEP_MINUTES, \
    UPPERCASE_MEDICAL_EXPENSES, HOSPITAL_ALIAS, HOSPITAL_FILTER, DEPARTMENT_ALIAS, DEPARTMENT_FILTER
 from ucloud import ufile
-from util import image_util, util
+from util import image_util, util, html_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
@@ -73,6 +74,47 @@ def request_ie_result(task_enum, phrecs):
        raise Exception(f"请求信息抽取结果失败，状态码：{response.status_code}")


+# 尝试从二维码中获取高清图片
+def get_better_image_from_qrcode(image, dpi=150):
+    js_base_url = 'http://einvoice.jsczt.cn'
+    results = zxingcpp.read_barcodes(image)
+    for result in results:
+        pdf = None
+        pdf_path = None
+        try:
+            url = result.text
+            if url.startswith(js_base_url):
+                id_base = html_util.get_jsczt_id_base(url)
+                pdf_url = f'{js_base_url}/download?idBase={id_base}'
+                pdf_path = html_util.download_pdf(pdf_url)
+                # 打开PDF文件
+                pdf = fitz.open(pdf_path)
+                # 选择第一页
+                page = pdf[0]
+                # 定义缩放系数（DPI）
+                default_dpi = 72
+                zoom = dpi / default_dpi
+                # 设置矩阵变换参数
+                mat = fitz.Matrix(zoom, zoom)
+                # 渲染页面
+                pix = page.get_pixmap(matrix=mat)
+                # 将渲染结果转换为OpenCV兼容的格式
+                img = np.frombuffer(pix.samples, dtype=np.uint8).reshape((pix.height, pix.width, -1))
+                img = cv2.cvtColor(img, cv2.COLOR_RGB2BGR)
+                return img, page.get_text()
+            else:
+                logging.getLogger('qr').info(f'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
+        finally:
+            if pdf:
+                pdf.close()
+            if pdf_path:
+                util.delete_temp_file(pdf_path)
+    return None, None
+
+
 # 关键信息提取
 def information_extraction(ie, phrecs, identity):
    result = {}
@@ -83,60 +125,88 @@ def information_extraction(ie, phrecs, identity):

        image = image_util.read(img_path)

-        target_images = []
-        target_images += detector.request_book_areas(image)  # 识别文档区域并裁剪
-        if not target_images:
-            target_images.append(image)  # 识别失败
-        angle_count = defaultdict(int, {"0": 0})  # 分割后图片的最优角度统计
-        for target_image in target_images:
-            dewarped_image = dewarp.dewarp_image(target_image)  # 去扭曲
-            angles = image_util.parse_rotation_angles(dewarped_image)
-            zx_ie_results = []
-            split_results = image_util.split(dewarped_image)
-            for split_result in split_results:
-                if split_result["img"] is None or split_result["img"].size == 0:
-                    continue
-                rotated_img = image_util.rotate(split_result["img"], int(angles[0]))
-                ie_results = [{"result": ie_temp_image(ie, OCR, rotated_img), "angle": angles[0]}]
-                if not ie_results[0]["result"] or len(ie_results[0]["result"]) < len(ie.kwargs.get("schema")):
-                    rotated_img = image_util.rotate(split_result["img"], int(angles[1]))
-                    ie_results.append({"result": ie_temp_image(ie, OCR, rotated_img), "angle": angles[1]})
+        # 尝试从二维码中获取高清图片
+        better_image, text = get_better_image_from_qrcode(image)
+        zx_ie_results = []
+        if better_image is not None:
+            img_angle = '0'
+            image = better_image
+            if text:
+                info_extract = ie(text)[0]
+            else:
+                info_extract = ie_temp_image(ie, OCR, image)
+            ie_result = {'result': info_extract, 'angle': '0'}

-                now = util.get_default_datetime()
-                best_angle = ["0", 0]
-                for ie_result in ie_results:
-                    if not ie_result["result"]:
+            now = util.get_default_datetime()
+            if not ie_result['result']:
+                continue
+
+            result_json = json.dumps(ie_result['result'], ensure_ascii=False)
+            if len(result_json) > 5000:
+                result_json = result_json[:5000]
+            zx_ie_results.append(ZxIeResult(pk_phhd=phrec.pk_phhd, pk_phrec=phrec.pk_phrec, id=identity,
+                                            cfjaddress=phrec.cfjaddress, content=result_json,
+                                            rotation_angle=int(ie_result['angle']),
+                                            x_offset=0, y_offset=0, create_time=now,
+                                            creator=HOSTNAME, update_time=now, updater=HOSTNAME))
+
+            result = merge_result(result, ie_result['result'])
+        else:
+            target_images = []
+            # target_images += detector.request_book_areas(image)  # 识别文档区域并裁剪
+            if not target_images:
+                target_images.append(image)  # 识别失败
+            angle_count = defaultdict(int, {'0': 0})  # 分割后图片的最优角度统计
+            for target_image in target_images:
+                # dewarped_image = dewarp.dewarp_image(target_image)  # 去扭曲
+                dewarped_image = target_image
+                angles = image_util.parse_rotation_angles(dewarped_image)
+
+                split_results = image_util.split(dewarped_image)
+                for split_result in split_results:
+                    if split_result['img'] is None or split_result['img'].size == 0:
                        continue
+                    rotated_img = image_util.rotate(split_result['img'], int(angles[0]))
+                    ie_results = [{'result': ie_temp_image(ie, OCR, rotated_img), 'angle': angles[0]}]
+                    if not ie_results[0]['result'] or len(ie_results[0]['result']) < len(ie.kwargs.get('schema')):
+                        rotated_img = image_util.rotate(split_result['img'], int(angles[1]))
+                        ie_results.append({'result': ie_temp_image(ie, OCR, rotated_img), 'angle': angles[1]})
+                    now = util.get_default_datetime()
+                    best_angle = ['0', 0]
+                    for ie_result in ie_results:
+                        if not ie_result['result']:
+                            continue

-                    result_json = json.dumps(ie_result["result"], ensure_ascii=False)
-                    if len(result_json) > 5000:
-                        result_json = result_json[:5000]
-                    zx_ie_results.append(ZxIeResult(pk_phhd=phrec.pk_phhd, pk_phrec=phrec.pk_phrec, id=identity,
-                                                    cfjaddress=phrec.cfjaddress, content=result_json,
-                                                    rotation_angle=int(ie_result["angle"]),
-                                                    x_offset=split_result["x_offset"],
-                                                    y_offset=split_result["y_offset"], create_time=now,
-                                                    creator=HOSTNAME, update_time=now, updater=HOSTNAME))
+                        result_json = json.dumps(ie_result['result'], ensure_ascii=False)
+                        if len(result_json) > 5000:
+                            result_json = result_json[:5000]
+                        zx_ie_results.append(ZxIeResult(pk_phhd=phrec.pk_phhd, pk_phrec=phrec.pk_phrec, id=identity,
+                                                        cfjaddress=phrec.cfjaddress, content=result_json,
+                                                        rotation_angle=int(ie_result['angle']),
+                                                        x_offset=split_result['x_offset'],
+                                                        y_offset=split_result['y_offset'], create_time=now,
+                                                        creator=HOSTNAME, update_time=now, updater=HOSTNAME))

-                    result = merge_result(result, ie_result["result"])
+                        result = merge_result(result, ie_result['result'])

-                    if len(ie_result["result"]) > best_angle[1]:
-                        best_angle = [ie_result["angle"], len(ie_result["result"])]
+                        if len(ie_result['result']) > best_angle[1]:
+                            best_angle = [ie_result['angle'], len(ie_result['result'])]

-                angle_count[best_angle[0]] += 1
+                    angle_count[best_angle[0]] += 1
+            img_angle = max(angle_count, key=angle_count.get)

-        img_angle = max(angle_count, key=angle_count.get)
-        if img_angle != "0":
+        if img_angle != '0' or better_image is not None:
            image = image_util.rotate(image, int(img_angle))
-            with tempfile.NamedTemporaryFile(delete=False, suffix=".jpg") as temp_file:
+            with tempfile.NamedTemporaryFile(delete=False, suffix='.jpg') as temp_file:
                cv2.imwrite(temp_file.name, image)
            try:
                ufile.upload_file(phrec.cfjaddress, temp_file.name)
-                # 修正旋转角度
-                for zx_ie_result in zx_ie_results:
-                    zx_ie_result.rotation_angle -= int(img_angle)
+                if img_angle != '0':
+                    # 修正旋转角度
+                    for zx_ie_result in zx_ie_results:
+                        zx_ie_result.rotation_angle -= int(img_angle)
            except Exception as e:
-                logging.error(f"上传图片({phrec.cfjaddress})失败", exc_info=e)
+                logging.error(f'上传图片({phrec.cfjaddress})失败', exc_info=e)
            finally:
                util.delete_temp_file(temp_file.name)