项目架构调整，模型全部采用接口调用

Dockerfile

@@ -1,5 +1,5 @@
 # 使用官方的paddle镜像作为基础
-FROM registry.baidubce.com/paddlepaddle/paddle:2.6.1-gpu-cuda12.0-cudnn8.9-trt8.6
+FROM python:3.10-alpine
 
 # 设置工作目录
 WORKDIR /app
@@ -15,9 +15,7 @@ ENV PYTHONUNBUFFERED=1 \
 COPY requirements.txt /app/requirements.txt
 COPY packages /app/packages
 RUN ln -snf /usr/share/zoneinfo/$TZ /etc/localtime && echo '$TZ' > /etc/timezone \
-    && pip install --no-cache-dir -r requirements.txt \
+    && pip install --no-cache-dir -r requirements.txt
-    && pip uninstall -y onnxruntime onnxruntime-gpu \
-    && pip install onnxruntime-gpu==1.18.0 --extra-index-url https://aiinfra.pkgs.visualstudio.com/PublicPackages/_packaging/onnxruntime-cuda-12/pypi/simple/
 
 # 将当前目录内容复制到容器的/app内
 COPY . /app

README.md

@@ -125,4 +125,6 @@ bash update.sh
     1. 新增文档检测功能
     2. 新增扭曲矫正功能
 21. 版本号：1.14.0
-    1. 新增二维码识别替换高清图片功能
+    1. 新增二维码识别替换高清图片功能
+22. 版本号：2.0.0
+    1. 项目架构调整，模型全部采用接口调用

docker-compose.yml

@@ -1,46 +1,108 @@
-x-env:
+x-base:
-  &template
+  &base_template
-  image: fcb_photo_review:1.14.6
   restart: always
 
-x-review:
+x-project:
-  &review_template
+  &project_template
-  <<: *template
+  <<: *base_template
+  image: fcb_photo_review:1.14.6
+  volumes:
+    - ./log:/app/log
+
+x-paddle:
+  &paddle_template
+  <<: *base_template
+  image: fcb_paddle:0.0.1
   volumes:
     - ./log:/app/log
     - ./model:/app/model
-  deploy:
-    resources:
-      reservations:
-        devices:
-          - device_ids: [ '0', '1' ]
-            capabilities: [ 'gpu' ]
-            driver: 'nvidia'
-
-x-mask:
-  &mask_template
-  <<: *template
-  volumes:
-    - ./log:/app/log
-  deploy:
-    resources:
-      reservations:
-        devices:
-          - device_ids: [ '1' ]
-            capabilities: [ 'gpu' ]
-            driver: 'nvidia'
 
 services:
-  det_api:
+  ocr_api:
-    <<: *template
+    <<: *paddle_template
     build:
-      context: .
+      context: ./services/paddle_services
+    container_name: ocr_api
+    hostname: ocr_api
+    command: [ '-w 5 ./services/ocr_api:app --bind 0.0.0.0:5001' ]
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - device_ids: [ '0' ]
+              capabilities: [ 'gpu' ]
+              driver: 'nvidia'
+
+  settlement_api:
+    <<: *paddle_template
+    container_name: settlement_api
+    hostname: settlement_api
+    command: [ '-w 5 ./services/settlement_api:app --bind 0.0.0.0:5002' ]
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - device_ids: [ '0' ]
+              capabilities: [ 'gpu' ]
+              driver: 'nvidia'
+
+  discharge_api:
+    <<: *paddle_template
+    container_name: discharge_api
+    hostname: discharge_api
+    command: [ '-w 5 ./services/discharge_api:app --bind 0.0.0.0:5003' ]
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - device_ids: [ '0' ]
+              capabilities: [ 'gpu' ]
+              driver: 'nvidia'
+
+  cost_api:
+    <<: *paddle_template
+    container_name: cost_api
+    hostname: cost_api
+    command: [ '-w 5 ./services/cost_api:app --bind 0.0.0.0:5004' ]
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - device_ids: [ '1' ]
+              capabilities: [ 'gpu' ]
+              driver: 'nvidia'
+
+  clas_api:
+    <<: *paddle_template
+    container_name: clas_api
+    hostname: clas_api
+    command: [ '-w 5 ./services/clas_api:app --bind 0.0.0.0:5005' ]
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - device_ids: [ '0' ]
+              capabilities: [ 'gpu' ]
+              driver: 'nvidia'
+
+  det_api:
+    <<: *paddle_template
     container_name: det_api
     hostname: det_api
-    volumes:
+    command: [ '-w 5 ./services/det_api:app --bind 0.0.0.0:5006' ]
-      - ./log:/app/log
+    deploy:
-      - ./model:/app/model
+      resources:
-#    command: [ 'det_api.py' ]
+        reservations:
+          devices:
+            - device_ids: [ '1' ]
+              capabilities: [ 'gpu' ]
+              driver: 'nvidia'
+
+  dewarp_api:
+    <<: *paddle_template
+    container_name: dewarp_api
+    hostname: dewarp_api
+    command: [ '-w 5 ./services/dewarp_api:app --bind 0.0.0.0:5007' ]
     deploy:
       resources:
         reservations:
@@ -50,15 +112,23 @@ services:
               driver: 'nvidia'
 
   photo_review_1:
-    <<: *review_template
+    <<: *project_template
+    build:
+      context: .
     container_name: photo_review_1
     hostname: photo_review_1
     depends_on:
+      - ocr_api
+      - settlement_api
+      - discharge_api
+      - cost_api
+      - clas_api
       - det_api
+      - dewarp_api
     command: [ 'photo_review.py', '--clean', 'True' ]
 
   photo_review_2:
-    <<: *review_template
+    <<: *project_template
     container_name: photo_review_2
     hostname: photo_review_2
     depends_on:
@@ -66,7 +136,7 @@ services:
     command: [ 'photo_review.py' ]
 
   photo_review_3:
-    <<: *review_template
+    <<: *project_template
     container_name: photo_review_3
     hostname: photo_review_3
     depends_on:
@@ -74,7 +144,7 @@ services:
     command: [ 'photo_review.py' ]
 
   photo_review_4:
-    <<: *review_template
+    <<: *project_template
     container_name: photo_review_4
     hostname: photo_review_4
     depends_on:
@@ -82,7 +152,7 @@ services:
     command: [ 'photo_review.py' ]
 
   photo_review_5:
-    <<: *review_template
+    <<: *project_template
     container_name: photo_review_5
     hostname: photo_review_5
     depends_on:
@@ -90,33 +160,23 @@ services:
     command: [ 'photo_review.py' ]
 
   photo_mask_1:
-    <<: *mask_template
+    <<: *project_template
     container_name: photo_mask_1
     hostname: photo_mask_1
     depends_on:
-      - photo_review_5
+      - ocr_api
+      - settlement_api
+      - discharge_api
+      - cost_api
+      - clas_api
+      - det_api
+      - dewarp_api
     command: [ 'photo_mask.py', '--clean', 'True' ]
 
   photo_mask_2:
-    <<: *mask_template
+    <<: *project_template
     container_name: photo_mask_2
     hostname: photo_mask_2
     depends_on:
       - photo_mask_1
-    command: [ 'photo_mask.py' ]
+    command: [ 'photo_mask.py' ]
-#
-#  photo_review_6:
-#    <<: *review_template
-#    container_name: photo_review_6
-#    hostname: photo_review_6
-#    depends_on:
-#      - photo_mask_2
-#    command: [ 'photo_review.py' ]
-#
-#  photo_review_7:
-#    <<: *review_template
-#    container_name: photo_review_7
-#    hostname: photo_review_7
-#    depends_on:
-#      - photo_review_6
-#    command: [ 'photo_review.py' ]

photo_review/__init__.py

@@ -1,6 +1,4 @@
 import jieba
-from paddlenlp import Taskflow
-from paddleocr import PaddleOCR
 
 '''
 项目配置
@@ -11,52 +9,6 @@ PHHD_BATCH_SIZE = 10
 SLEEP_MINUTES = 5
 # 是否发送报错邮件
 SEND_ERROR_EMAIL = True
-# 是否开启布局分析
-LAYOUT_ANALYSIS = False
-
-"""
-信息抽取关键词配置
-"""
-# 患者姓名
-PATIENT_NAME = ['患者姓名']
-# 入院日期
-ADMISSION_DATE = ['入院日期']
-# 出院日期
-DISCHARGE_DATE = ['出院日期']
-# 发生医疗费
-MEDICAL_EXPENSES = ['费用总额']
-# 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']
-# 个人自费金额
-PERSONAL_FUNDED_AMOUNT = ['自费金额', '个人自费']
-# 医保类别
-MEDICAL_INSURANCE_TYPE = ['医保类型']
-# 就诊医院
-HOSPITAL = ['医院']
-# 就诊科室
-DEPARTMENT = ['科室']
-# 主治医生
-DOCTOR = ['主治医生']
-# 住院号
-ADMISSION_ID = ['住院号']
-# 医保结算单号码
-SETTLEMENT_ID = ['医保结算单号码']
-# 年龄
-AGE = ['年龄']
-# 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
-     + PERSONAL_ACCOUNT_PAYMENT + PERSONAL_FUNDED_AMOUNT + MEDICAL_INSURANCE_TYPE + ADMISSION_ID + SETTLEMENT_ID
-     + UPPERCASE_MEDICAL_EXPENSES)
-
-DISCHARGE_RECORD_SCHEMA = \
-    HOSPITAL + DEPARTMENT + PATIENT_NAME + ADMISSION_DATE + DISCHARGE_DATE + DOCTOR + ADMISSION_ID + AGE
-
-COST_LIST_SCHEMA = PATIENT_NAME + ADMISSION_DATE + DISCHARGE_DATE + MEDICAL_EXPENSES
 
 '''
 别名配置
@@ -90,15 +42,3 @@ 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')
-
-OCR = PaddleOCR(use_angle_cls=False, show_log=False, gpu_id=1, det_db_box_thresh=0.3)

photo_review/auto_photo_review.py

@@ -18,15 +18,15 @@ from sqlalchemy import update
 from db import MysqlSession
 from db.mysql import BdYljg, BdYlks, ZxIeResult, ZxIeCost, ZxIeDischarge, ZxIeSettlement, ZxPhhd, ZxPhrec
 from log import HOSTNAME
-from photo_review import PATIENT_NAME, ADMISSION_DATE, DISCHARGE_DATE, MEDICAL_EXPENSES, PERSONAL_CASH_PAYMENT, \
+from photo_review import PHHD_BATCH_SIZE, SLEEP_MINUTES, HOSPITAL_ALIAS, HOSPITAL_FILTER, DEPARTMENT_ALIAS, \
+    DEPARTMENT_FILTER
+from services 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, \
+    ADMISSION_ID, SETTLEMENT_ID, AGE, UPPERCASE_MEDICAL_EXPENSES
-    UPPERCASE_MEDICAL_EXPENSES, HOSPITAL_ALIAS, HOSPITAL_FILTER, DEPARTMENT_ALIAS, DEPARTMENT_FILTER
 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, \
+from util.data_util import handle_date, handle_decimal, parse_department, handle_name, handle_insurance_type, \
-    handle_insurance_type, handle_original_data, handle_hospital, handle_department, handle_id, handle_age, parse_money, \
+    handle_original_data, handle_hospital, handle_department, handle_id, handle_age, parse_money, parse_hospital
-    parse_hospital
 
 
 # 合并信息抽取结果

requirements.txt

@@ -1,16 +1,11 @@
 numpy==1.26.4
-onnxconverter-common==1.14.0
+OpenCC==1.1.6  # 中文繁简转换
-OpenCC==1.1.6
 opencv-python==4.6.0.66
-paddle2onnx==1.2.3
-paddleclas==2.5.2
-paddlenlp==2.6.1
-paddleocr==2.7.3
 pillow==10.4.0
 pymysql==1.1.1
 requests==2.32.3
-sqlacodegen==2.3.0.post1
+sqlacodegen==2.3.0.post1  # 实体类生成
-sqlalchemy==1.4.52
+sqlalchemy==1.4.52  # ORM框架
-tenacity==8.5.0
+tenacity==8.5.0  # 重试
-ufile==3.2.9
+ufile==3.2.9  # 云空间
-zxing-cpp==2.2.0
+zxing-cpp==2.2.0  # 二维码识别

services/__init__.py

@@ -0,0 +1,34 @@
+"""
+信息抽取关键词配置
+"""
+
+# 患者姓名
+PATIENT_NAME = ['患者姓名']
+# 入院日期
+ADMISSION_DATE = ['入院日期']
+# 出院日期
+DISCHARGE_DATE = ['出院日期']
+# 发生医疗费
+MEDICAL_EXPENSES = ['费用总额']
+# 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']
+# 个人自费金额
+PERSONAL_FUNDED_AMOUNT = ['自费金额', '个人自费']
+# 医保类别
+MEDICAL_INSURANCE_TYPE = ['医保类型']
+# 就诊医院
+HOSPITAL = ['医院']
+# 就诊科室
+DEPARTMENT = ['科室']
+# 主治医生
+DOCTOR = ['主治医生']
+# 住院号
+ADMISSION_ID = ['住院号']
+# 医保结算单号码
+SETTLEMENT_ID = ['医保结算单号码']
+# 年龄
+AGE = ['年龄']
+# 大写总额
+UPPERCASE_MEDICAL_EXPENSES = ['大写总额']

services/clas_api.py

@@ -1,26 +1,26 @@
 from flask import Flask, request
 from paddleclas import PaddleClas
 
-from util.common_util import process_request
+from utils import process_request
 
 app = Flask(__name__)
-CLAS = PaddleClas(model_name="text_image_orientation")
+CLAS = PaddleClas(model_name='text_image_orientation')
 
 
 @app.route('/clas/orientation', methods=['POST'])
 @process_request
 def orientation():
     """
-    判断图片旋转角度，逆时针旋转该角度后为正。可能值["0", "90", "180", "270"]
+    判断图片旋转角度，逆时针旋转该角度后为正。可能值['0', '90', '180', '270']
     :return: 最有可能的两个角度
     """
     img_path = request.form.get('img_path')
     clas_result = CLAS.predict(input_data=img_path)
     clas_result = next(clas_result)[0]
-    if clas_result["scores"][0] < 0.5:
+    if clas_result['scores'][0] < 0.5:
         return ['0', '90']
-    return clas_result["label_names"]
+    return clas_result['label_names']
 
 
 if __name__ == '__main__':
-    app.run('0.0.0.0', 5002)
+    app.run('0.0.0.0', 5005)

services/cost_api.py

@@ -0,0 +1,24 @@
+import json
+
+from flask import Flask, request
+from paddlenlp import Taskflow
+
+from utils import process_request
+from . import PATIENT_NAME, ADMISSION_DATE, DISCHARGE_DATE, MEDICAL_EXPENSES
+
+app = Flask(__name__)
+COST_LIST_SCHEMA = PATIENT_NAME + ADMISSION_DATE + DISCHARGE_DATE + MEDICAL_EXPENSES
+COST = Taskflow('information_extraction', schema=COST_LIST_SCHEMA, model='uie-x-base',
+                task_path='../model/cost_list_model', layout_analysis=False, precision='fp16')
+
+
+@app.route('/nlp/cost', methods=['POST'])
+@process_request
+def cost():
+    img_path = request.form.get('img_path')
+    layout = request.form.get('layout')
+    return COST({'doc': img_path, 'layout': json.loads(layout)})
+
+
+if __name__ == '__main__':
+    app.run('0.0.0.0', 5004)

services/det_api.py

@@ -3,9 +3,8 @@ import os.path
 import cv2
 from flask import Flask, request
 
-from paddle_detection import detector
+from paddle_services.paddle_detection import detector
-from util import image_util
+from utils import process_request, parse_img_path
-from util.common_util import process_request
 
 app = Flask(__name__)
 
@@ -14,10 +13,9 @@ app = Flask(__name__)
 @process_request
 def books():
     img_path = request.form.get('img_path')
-    image = cv2.imread(img_path)
+    result = detector.get_book_areas(img_path)
-    result = detector.get_book_areas(image)
 
-    dirname, img_name, ext = image_util.parse_path(img_path)
+    dirname, img_name, ext = parse_img_path(img_path)
     books_path = []
     for i in range(len(result)):
         save_path = os.path.join(dirname, img_name + '_book_' + str(i) + '.' + ext)
@@ -27,4 +25,4 @@ def books():
 
 
 if __name__ == '__main__':
-    app.run('0.0.0.0', 5000)
+    app.run('0.0.0.0', 5006)

services/dewarp_api.py

@@ -3,9 +3,8 @@ import os
 import cv2
 from flask import Flask, request
 
-from doc_dewarp import dewarp
+from paddle_services.doc_dewarp import dewarper
-from util import image_util
+from utils import process_request, parse_img_path
-from util.common_util import process_request
 
 app = Flask(__name__)
 
@@ -15,12 +14,12 @@ app = Flask(__name__)
 def dewarp():
     img_path = request.form.get('img_path')
     img = cv2.imread(img_path)
-    dewarped_img = dewarp.dewarp_image(img)
+    dewarped_img = dewarper.dewarp_image(img)
-    dirname, img_name, ext = image_util.parse_path(img_path)
+    dirname, img_name, ext = parse_img_path(img_path)
     save_path = os.path.join(dirname, img_name + '_dewarped.' + ext)
     cv2.imwrite(save_path, dewarped_img)
     return save_path
 
 
 if __name__ == '__main__':
-    app.run('0.0.0.0', 5001)
+    app.run('0.0.0.0', 5007)

services/discharge_api.py

@@ -0,0 +1,26 @@
+import json
+
+from flask import Flask, request
+from paddlenlp import Taskflow
+
+from utils import process_request
+from . import HOSPITAL, DEPARTMENT, PATIENT_NAME, ADMISSION_DATE, DISCHARGE_DATE, DOCTOR, ADMISSION_ID, AGE
+
+app = Flask(__name__)
+DISCHARGE_RECORD_SCHEMA = (
+        HOSPITAL + DEPARTMENT + PATIENT_NAME + ADMISSION_DATE + DISCHARGE_DATE + DOCTOR + ADMISSION_ID + AGE
+)
+DISCHARGE = Taskflow('information_extraction', schema=DISCHARGE_RECORD_SCHEMA, model='uie-x-base',
+                     task_path='../model/discharge_record_model', layout_analysis=False, precision='fp16')
+
+
+@app.route('/nlp/discharge', methods=['POST'])
+@process_request
+def discharge():
+    img_path = request.form.get('img_path')
+    layout = request.form.get('layout')
+    return DISCHARGE({'doc': img_path, 'layout': json.loads(layout)})
+
+
+if __name__ == '__main__':
+    app.run('0.0.0.0', 5003)

services/ocr_api.py

@@ -0,0 +1,18 @@
+from flask import Flask, request
+from paddleocr import PaddleOCR
+
+from utils import process_request
+
+app = Flask(__name__)
+OCR = PaddleOCR(use_angle_cls=False, show_log=False, gpu_id=0, det_db_box_thresh=0.3)
+
+
+@app.route('/ocr', methods=['POST'])
+@process_request
+def ocr():
+    img_path = request.form.get('img_path')
+    return OCR.ocr(img_path, cls=False)
+
+
+if __name__ == '__main__':
+    app.run('0.0.0.0', 5001)

services/paddle_services/Dockerfile

@@ -0,0 +1,29 @@
+# 使用官方的paddle镜像作为基础
+FROM registry.baidubce.com/paddlepaddle/paddle:2.6.1-gpu-cuda12.0-cudnn8.9-trt8.6
+
+# 设置工作目录
+WORKDIR /app
+
+# 设置环境变量
+ENV PYTHONUNBUFFERED=1 \
+    # 设置时区
+    TZ=Asia/Shanghai \
+    # 设置pip镜像地址，加快安装速度
+    PIP_INDEX_URL=https://pypi.tuna.tsinghua.edu.cn/simple
+
+# 安装依赖
+COPY requirements.txt /app/requirements.txt
+COPY packages /app/packages
+RUN ln -snf /usr/share/zoneinfo/$TZ /etc/localtime && echo '$TZ' > /etc/timezone \
+    && pip install --no-cache-dir -r requirements.txt \
+    && pip uninstall -y onnxruntime onnxruntime-gpu \
+    && pip install onnxruntime-gpu==1.18.0 --extra-index-url https://aiinfra.pkgs.visualstudio.com/PublicPackages/_packaging/onnxruntime-cuda-12/pypi/simple/
+
+# 将当前目录内容复制到容器的/app内
+COPY . /app
+
+# 暴露端口
+# EXPOSE 8081
+
+# 运行api接口，具体接口在命令行或docker-compose.yml文件中定义
+ENTRYPOINT ["gunicorn"]

services/paddle_services/doc_dewarp/__init__.py

@@ -1,4 +1,7 @@
+import os.path
+
 from onnxruntime import InferenceSession
 
-DOC_TR = InferenceSession("model/dewarp_model/doc_tr_pp.onnx",
+MODEL_PATH = os.path.join(os.path.dirname(os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))),
-                          providers=["CUDAExecutionProvider"], provider_options=[{"device_id": 0}])
+                          'model', 'dewarp_model', 'doc_tr_pp.onnx')
+DOC_TR = InferenceSession(MODEL_PATH, providers=['CUDAExecutionProvider'], provider_options=[{'device_id': 0}])

services/paddle_services/doc_dewarp/dewarper.py

@@ -11,10 +11,10 @@ def dewarp_image(image):
     y = to_tensor(image)
 
     img = np.transpose(img, (2, 0, 1))
-    bm = DOC_TR.run(None, {"image": img[None,]})[0]
+    bm = DOC_TR.run(None, {'image': img[None,]})[0]
     bm = paddle.to_tensor(bm)
     bm = paddle.nn.functional.interpolate(
-        bm, y.shape[2:], mode="bilinear", align_corners=False
+        bm, y.shape[2:], mode='bilinear', align_corners=False
     )
     bm_nhwc = np.transpose(bm, (0, 2, 3, 1))
     out = paddle.nn.functional.grid_sample(y, (bm_nhwc / 288 - 0.5) * 2)

services/paddle_services/paddle_detection/__init__.py

@@ -1,4 +1,8 @@
+import os
+
 from onnxruntime import InferenceSession
 
-PADDLE_DET = InferenceSession("model/object_det_model/ppyoloe_plus_crn_l_80e_coco_w_nms.onnx",
+MODEL_DIR = os.path.join(os.path.dirname(os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))),
-                              providers=["CPUExecutionProvider"], provider_options=[{"device_id": 0}])
+                         'model', 'object_det_model')
+PADDLE_DET = InferenceSession(os.path.join(MODEL_DIR, 'ppyoloe_plus_crn_l_80e_coco_w_nms.onnx'),
+                              providers=['CPUExecutionProvider'], provider_options=[{'device_id': 0}])

services/paddle_services/paddle_detection/detector.py

@@ -1,13 +1,13 @@
-import tempfile
+import os.path
 from collections import defaultdict
 
 import cv2
 import numpy as np
 
-from paddle_detection import PADDLE_DET
+from util import image_util
-from paddle_detection.deploy.third_engine.onnx.infer import PredictConfig
+from . import PADDLE_DET, MODEL_DIR
-from paddle_detection.deploy.third_engine.onnx.preprocess import Compose
+from .deploy.third_engine.onnx.infer import PredictConfig
-from util import image_util, common_util
+from .deploy.third_engine.onnx.preprocess import Compose
 
 
 def predict_image(infer_config, predictor, img_path):
@@ -15,7 +15,7 @@ def predict_image(infer_config, predictor, img_path):
     transforms = Compose(infer_config.preprocess_infos)
     # predict image
     inputs = transforms(img_path)
-    inputs["image"] = np.array(inputs["image"]).astype('float32')
+    inputs['image'] = np.array(inputs['image']).astype('float32')
     inputs_name = [var.name for var in predictor.get_inputs()]
     inputs = {k: inputs[k][None,] for k in inputs_name}
 
@@ -25,25 +25,23 @@ def predict_image(infer_config, predictor, img_path):
     result = defaultdict(list)
     for bbox in bboxes:
         if bbox[0] > -1 and bbox[1] > infer_config.draw_threshold:
-            result[bbox[0]].append({"score": bbox[1], "box": bbox[2:]})
+            result[bbox[0]].append({'score': bbox[1], 'box': bbox[2:]})
     return result
 
 
 def detect_image(img_path):
-    infer_cfg = "model/object_det_model/infer_cfg.yml"
+    infer_cfg = os.path.join(MODEL_DIR, 'infer_cfg.yml')
     # load infer config
     infer_config = PredictConfig(infer_cfg)
 
     return predict_image(infer_config, PADDLE_DET, img_path)
 
 
-def get_book_areas(image):
+def get_book_areas(img_path):
-    with tempfile.NamedTemporaryFile(delete=False, suffix=".jpg") as temp_file:
+    detect_result = detect_image(img_path)
-        cv2.imwrite(temp_file.name, image)
-    detect_result = detect_image(temp_file.name)
-    common_util.delete_temp_file(temp_file.name)
     book_areas = detect_result[73]
     result = []
+    image = cv2.imread(img_path)
     for book_area in book_areas:
-        result.append(image_util.capture(image, book_area["box"]))
+        result.append(image_util.capture(image, book_area['box']))
     return result

services/paddle_services/requestments.txt

@@ -0,0 +1,16 @@
+numpy==1.26.4
+onnxconverter-common==1.14.0
+OpenCC==1.1.6
+opencv-python==4.6.0.66
+paddle2onnx==1.2.3
+paddleclas==2.5.2
+paddlenlp==2.6.1
+paddleocr==2.7.3
+pillow==10.4.0
+pymysql==1.1.1
+requests==2.32.3
+sqlacodegen==2.3.0.post1
+sqlalchemy==1.4.52
+tenacity==8.5.0
+ufile==3.2.9
+zxing-cpp==2.2.0

services/settlement_api.py

@@ -0,0 +1,30 @@
+import json
+
+from flask import Flask, request
+from paddlenlp import Taskflow
+
+from utils import process_request
+from . import PATIENT_NAME, ADMISSION_DATE, DISCHARGE_DATE, MEDICAL_EXPENSES, PERSONAL_CASH_PAYMENT, \
+    PERSONAL_ACCOUNT_PAYMENT, PERSONAL_FUNDED_AMOUNT, MEDICAL_INSURANCE_TYPE, ADMISSION_ID, SETTLEMENT_ID, \
+    UPPERCASE_MEDICAL_EXPENSES
+
+app = Flask(__name__)
+SETTLEMENT_LIST_SCHEMA = (
+        PATIENT_NAME + ADMISSION_DATE + DISCHARGE_DATE + MEDICAL_EXPENSES + PERSONAL_CASH_PAYMENT
+        + PERSONAL_ACCOUNT_PAYMENT + PERSONAL_FUNDED_AMOUNT + MEDICAL_INSURANCE_TYPE + ADMISSION_ID + SETTLEMENT_ID
+        + UPPERCASE_MEDICAL_EXPENSES
+)
+SETTLEMENT_IE = Taskflow('information_extraction', schema=SETTLEMENT_LIST_SCHEMA, model='uie-x-base',
+                         task_path='../model/settlement_list_model', layout_analysis=False, precision='fp16')
+
+
+@app.route('/nlp/settlement', methods=['POST'])
+@process_request
+def settlement():
+    img_path = request.form.get('img_path')
+    layout = request.form.get('layout')
+    return SETTLEMENT_IE({'doc': img_path, 'layout': json.loads(layout)})
+
+
+if __name__ == '__main__':
+    app.run('0.0.0.0', 5002)

services/utils.py

@@ -0,0 +1,26 @@
+import logging
+import os
+
+from flask import jsonify
+
+
+def process_request(func):
+    """
+    api通用处理函数
+    """
+
+    def wrapper(*args, **kwargs):
+        try:
+            result = func(*args, **kwargs)
+            return jsonify(result), 200
+        except Exception as e:
+            logging.getLogger('error').error(f'Error: {e}', exc_info=e)
+            return jsonify({'error': str(e)}), 500
+
+    return wrapper
+
+
+def parse_img_path(img_path):
+    dirname = os.path.dirname(img_path)
+    img_name, ext = os.path.basename(img_path).rsplit('.', 1)
+    return dirname, img_name, ext

util/common_util.py

@@ -2,10 +2,9 @@ import logging
 import os
 from datetime import datetime
 
-from flask import jsonify
 from opencc import OpenCC
 
-from util import string_util
+from util import string_util, model_util
 
 
 # 获取yyyy-MM-dd HH:mm:ss格式的当前时间
@@ -37,7 +36,7 @@ def get_ocr_layout(ocr, img_path):
         return True
 
     layout = []
-    ocr_result = ocr.ocr(img_path, cls=False)
+    ocr_result = model_util.request_ocr(img_path)
     ocr_result = ocr_result[0]
     if not ocr_result:
         return layout
@@ -218,19 +217,3 @@ def chinese_money_to_number(chinese_money_amount):
 def traditional_to_simple_chinese(traditional_chinese):
     converter = OpenCC('t2s')
     return converter.convert(traditional_chinese)
-
-
-def process_request(func):
-    """
-    api通用处理函数
-    """
-
-    def wrapper(*args, **kwargs):
-        try:
-            result = func(*args, **kwargs)
-            return jsonify(result), 200
-        except Exception as e:
-            logging.getLogger('error').error(f'Error: {e}')
-            return jsonify({'error': str(e)}), 500
-
-    return wrapper

util/image_util.py

@@ -283,9 +283,3 @@ def save_to_local(img_url, save_path=None):
         file.write(response.content)
 
     return save_path
-
-
-def parse_path(img_path):
-    dirname = os.path.dirname(img_path)
-    img_name, ext = os.path.basename(img_path).rsplit('.', 1)
-    return dirname, img_name, ext

util/model_util.py

@@ -1,9 +1,93 @@
+import json
 import logging
 
 import requests
 from tenacity import retry, stop_after_attempt, wait_random
 
 
+@retry(stop=stop_after_attempt(3), wait=wait_random(1, 3), reraise=True,
+       after=lambda x: logging.warning('OCR识别失败！'))
+def request_ocr(img_path):
+    """
+    请求图片OCR识别接口
+    :param img_path: 待识别图片路径
+    :return: 识别结果
+    """
+    url = 'http://ocr_api:5001/ocr'
+    response = requests.post(url, {'img_path': img_path})
+    if response.status_code == 200:
+        return response.json()
+    else:
+        return None
+
+
+@retry(stop=stop_after_attempt(3), wait=wait_random(1, 3), reraise=True,
+       after=lambda x: logging.warning('抽取基本医保结算单失败！'))
+def request_discharge_info(img_path, layout):
+    """
+    请求基本医保结算单信息抽取接口
+    :param img_path: 待抽取图片路径
+    :param layout: 图片ocr信息
+    :return: 抽取结果
+    """
+    url = 'http://settlement_api:5002/nlp/settlement'
+    response = requests.post(url, {'img_path': img_path, 'layout': json.dumps(layout)})
+    if response.status_code == 200:
+        return response.json()
+    else:
+        return None
+
+
+@retry(stop=stop_after_attempt(3), wait=wait_random(1, 3), reraise=True,
+       after=lambda x: logging.warning('抽取出院记录失败！'))
+def request_discharge_info(img_path, layout):
+    """
+    请求出院记录信息抽取接口
+    :param img_path: 待抽取图片路径
+    :param layout: 图片ocr信息
+    :return: 抽取结果
+    """
+    url = 'http://discharge_api:5003/nlp/discharge'
+    response = requests.post(url, {'img_path': img_path, 'layout': json.dumps(layout)})
+    if response.status_code == 200:
+        return response.json()
+    else:
+        return None
+
+
+@retry(stop=stop_after_attempt(3), wait=wait_random(1, 3), reraise=True,
+       after=lambda x: logging.warning('抽取费用清单失败！'))
+def request_cost_info(img_path, layout):
+    """
+    请求费用清单信息抽取接口
+    :param img_path: 待抽取图片路径
+    :param layout: 图片ocr信息
+    :return: 抽取结果
+    """
+    url = 'http://cost_api:5004/nlp/cost'
+    response = requests.post(url, {'img_path': img_path, 'layout': json.dumps(layout)})
+    if response.status_code == 200:
+        return response.json()
+    else:
+        return None
+
+
+@retry(stop=stop_after_attempt(3), wait=wait_random(1, 3), reraise=True,
+       after=lambda x: logging.warning('获取图片方向失败！'))
+def request_image_orientation(img_path):
+    """
+    请求图片方向分类接口
+    :param img_path: 待分类图片路径
+    :return: 最有可能的两个图片方向
+    """
+    url = 'http://clas_api:5005/clas/orientation'
+    response = requests.post(url, {'img_path': img_path})
+    if response.status_code == 200:
+        return response.json()
+    else:
+        return ['0', '90']
+
+
 @retry(stop=stop_after_attempt(3), wait=wait_random(1, 3), reraise=True,
        after=lambda x: logging.warning('获取文档区域失败！'))
 def request_book_areas(img_path):
@@ -12,7 +96,7 @@ def request_book_areas(img_path):
     :param img_path: 待识别图片路径
     :return: 文档图片路径列表
     """
-    url = 'http://det_api:5000/det/books'
+    url = 'http://det_api:5006/det/books'
     response = requests.post(url, {'img_path': img_path})
     if response.status_code == 200:
         return response.json()
@@ -28,25 +112,9 @@ def request_dewarped_image(img_path):
     :param img_path: 待矫正图片路径
     :return: 矫正后的图片路径
     """
-    url = 'http://det_api:5001/dewarp'
+    url = 'http://127.0.0.1:5007/dewarp'
     response = requests.post(url, {'img_path': img_path})
     if response.status_code == 200:
         return response.json()
     else:
         return img_path
-
-
-@retry(stop=stop_after_attempt(3), wait=wait_random(1, 3), reraise=True,
-       after=lambda x: logging.warning('获取图片方向失败！'))
-def request_image_orientation(img_path):
-    """
-    请求图片方向分类接口
-    :param img_path: 待分类图片路径
-    :return: 最有可能的两个图片方向
-    """
-    url = 'http://det_api:5002/clas/orientation'
-    response = requests.post(url, {'img_path': img_path})
-    if response.status_code == 200:
-        return response.json()
-    else:
-        return ['0', '90']