自动识别耗时检测

docker-compose-time.yml

@@ -0,0 +1,41 @@
+x-env:
+  &template
+  image: fcb_photo_review:2.0.0
+  restart: always
+
+services:
+  det_api:
+    <<: *template
+    build:
+      context: .
+    container_name: det_api
+    hostname: det_api
+    volumes:
+      - ./log:/app/log
+      - ./model:/app/model
+    command: [ "det_api.py" ]
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - device_ids: [ "0" ]
+              capabilities: [ "gpu" ]
+              driver: "nvidia"
+
+  photo_time_test:
+    <<: *template
+    container_name: photo_time_test
+    hostname: photo_time_test
+    volumes:
+      - ./log:/app/log
+      - ./model:/app/model
+    depends_on:
+      - det_api
+    command: [ "photo_review.py" ]
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - device_ids: [ "0", "1" ]
+              capabilities: [ "gpu" ]
+              driver: "nvidia"

photo_review/auto_photo_review.py

@@ -76,32 +76,47 @@ def request_ie_result(task_enum, phrecs):
 def information_extraction(ie, phrecs, identity):
     result = {}
     for phrec in phrecs:
+        ufile_start = time.time()
         img_path = ufile.get_private_url(phrec.cfjaddress)
         if not img_path:
             continue
 
         image = image_util.read(img_path)
+        logging.info(f"获取云图片耗时：{time.time() - ufile_start}s")
         target_images = []
+        book_start = time.time()
         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
+        logging.info(f"检测文档耗时：{time.time() - book_start}s")
         angle_count = defaultdict(int, {"0": 0})  # 分割后图片的最优角度统计
         for target_image in target_images:
+            dewarp_start = time.time()
             dewarped_image = dewarp.dewarp_image(target_image)  # 去扭曲
+            logging.info(f"去扭曲耗时：{time.time() - dewarp_start}s")
+            rotate_start = time.time()
             angles = image_util.parse_rotation_angles(dewarped_image)
+            logging.info(f"检测图片旋转耗时：{time.time() - rotate_start}s")
             zx_ie_results = []
+            split_start = time.time()
             split_results = image_util.split(dewarped_image)
+            logging.info(f"分割图片耗时：{time.time() - split_start}s")
             for split_result in split_results:
                 if split_result["img"] is None or split_result["img"].size == 0:
                     continue
+                rotated_start = time.time()
                 rotated_img = image_util.rotate(split_result["img"], int(angles[0]))
+                logging.info(f"旋转图片耗时：{time.time() - rotated_start}s")
+                ie_start = time.time()
                 ie_results = [{"result": ie_temp_image(ie, OCR, rotated_img), "angle": angles[0]}]
+                logging.info(f"信息抽取耗时：{time.time() - ie_start}s")
                 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]
+                result_start = time.time()
                 for ie_result in ie_results:
                     if not ie_result["result"]:
                         continue
@@ -122,6 +137,7 @@ def information_extraction(ie, phrecs, identity):
                         best_angle = [ie_result["angle"], len(ie_result["result"])]
 
                 angle_count[best_angle[0]] += 1
+                logging.info(f"构建结果耗时：{time.time() - result_start}s")
 
         img_angle = max(angle_count, key=angle_count.get)
         if img_angle != "0":
@@ -129,19 +145,23 @@ def information_extraction(ie, phrecs, identity):
             with tempfile.NamedTemporaryFile(delete=False, suffix=".jpg") as temp_file:
                 cv2.imwrite(temp_file.name, image)
             try:
+                upload_start = time.time()
                 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)
+                logging.info(f"上传图片耗时：{time.time() - upload_start}s")
             except Exception as e:
                 logging.error(f"上传图片({phrec.cfjaddress})失败", exc_info=e)
             finally:
                 util.delete_temp_file(temp_file.name)
 
+        db_start = time.time()
         session = MysqlSession()
         session.add_all(zx_ie_results)
         session.commit()
         session.close()
+        logging.info(f"写入数据库耗时：{time.time() - db_start}s")
 
     return result
 
@@ -260,6 +280,7 @@ def search_department(department):
 
 def settlement_task(pk_phhd, settlement_list, identity):
     settlement_list_ie_result = information_extraction(SETTLEMENT_IE, settlement_list, identity)
+    settlement_start = time.time()
     settlement_data = {
         "pk_phhd": pk_phhd,
         "name": handle_name(get_best_value_in_keys(settlement_list_ie_result, PATIENT_NAME)),
@@ -289,10 +310,12 @@ def settlement_task(pk_phhd, settlement_list, identity):
     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)
+    logging.info(f"处理结算单耗时: {time.time() - settlement_start}s")
 
 
 def discharge_task(pk_phhd, discharge_record, identity):
     discharge_record_ie_result = information_extraction(DISCHARGE_IE, discharge_record, identity)
+    discharge_start = time.time()
     hospitals = get_values_of_keys(discharge_record_ie_result, HOSPITAL)
     departments = get_values_of_keys(discharge_record_ie_result, DEPARTMENT)
     discharge_data = {
@@ -361,10 +384,12 @@ def discharge_task(pk_phhd, discharge_record, identity):
         if best_match:
             discharge_data["pk_ylks"] = best_match[2]
     save_or_update_ie(ZxIeDischarge, pk_phhd, discharge_data)
+    logging.info(f"处理出院记录耗时: {time.time() - discharge_start}s")
 
 
 def cost_task(pk_phhd, cost_list, identity):
     cost_list_ie_result = information_extraction(COST_IE, cost_list, identity)
+    cost_start = time.time()
     cost_data = {
         "pk_phhd": pk_phhd,
         "name": handle_name(get_best_value_in_keys(cost_list_ie_result, PATIENT_NAME)),
@@ -376,9 +401,11 @@ def cost_task(pk_phhd, cost_list, identity):
     cost_data["discharge_date"] = handle_date(cost_data["discharge_date_str"])
     cost_data["medical_expenses"] = handle_decimal(cost_data["medical_expenses_str"])
     save_or_update_ie(ZxIeCost, pk_phhd, cost_data)
+    logging.info(f"处理费用记录耗时: {time.time() - cost_start}s")
 
 
 def photo_review(pk_phhd):
+    phrec_start = time.time()
     settlement_list = []
     discharge_record = []
     cost_list = []
@@ -395,6 +422,7 @@ def photo_review(pk_phhd):
             discharge_record.append(phrec)
         elif phrec.cRectype == "4":
             cost_list.append(phrec)
+    logging.info(f"图片分类耗时：{time.time() - phrec_start}s")
 
     # 同一批图的标识
     identity = int(time.time())
@@ -405,6 +433,7 @@ def photo_review(pk_phhd):
 
 def main():
     while 1:
+        db_start = time.time()
         session = MysqlSession()
         phhds = (session.query(ZxPhhd.pk_phhd)
                  .join(ZxPhrec, ZxPhhd.pk_phhd == ZxPhrec.pk_phhd, isouter=True)
@@ -417,6 +446,7 @@ def main():
         session.execute(update_flag)
         session.commit()
         session.close()
+        logging.info(f"数据库查询耗时：{time.time() - db_start}s")
         if phhds:
             for phhd in phhds:
                 pk_phhd = phhd.pk_phhd