增加检测矫正后用时上升比较明显，常规启用photo_review_6来弥补

det_test.py

@@ -1,10 +0,0 @@
-import time
-
-from paddle_detection import detector
-from util import image_util
-
-if __name__ == '__main__':
-    image = image_util.read("paddle_detection/docs/images/000000014439.jpg")
-    start = time.time()
-    images = detector.get_book_areas(image)
-    print(f"耗时：{time.time() - start}")

docker-compose.yml

@@ -1,6 +1,6 @@
 x-env:
   &template
-  image: fcb_photo_review:1.13.6
+  image: fcb_photo_review:1.13.7
   restart: always
 
 services:
@@ -94,23 +94,23 @@ services:
               capabilities: [ "gpu" ]
               driver: "nvidia"
 
-#  photo_review_6:
-#    <<: *template
-#    container_name: photo_review_6
-#    hostname: photo_review_6
-#    volumes:
-#      - ./log:/app/log
-#      - ./model:/app/model
-#    depends_on:
-#      - photo_review_5
-#    command: [ "photo_review.py" ]
-#    deploy:
-#      resources:
-#        reservations:
-#          devices:
-#            - device_ids: [ "0", "1" ]
-#              capabilities: [ "gpu" ]
-#              driver: "nvidia"
+  photo_review_6:
+    <<: *template
+    container_name: photo_review_6
+    hostname: photo_review_6
+    volumes:
+      - ./log:/app/log
+      - ./model:/app/model
+    depends_on:
+      - photo_review_5
+    command: [ "photo_review.py" ]
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - device_ids: [ "0", "1" ]
+              capabilities: [ "gpu" ]
+              driver: "nvidia"
 
   photo_mask_1:
     <<: *template
@@ -119,7 +119,7 @@ services:
     volumes:
       - ./log:/app/log
     depends_on:
-      - photo_review_5
+      - photo_review_6
     command: [ "photo_mask.py", "--clean", "True" ]
     deploy:
       resources:

photo_review/auto_photo_review.py

@@ -82,16 +82,12 @@ def information_extraction(ie, phrecs, identity):
 
         image = image_util.read(img_path)
         target_images = []
-        det_time = time.time()
         target_images += detector.get_book_areas(image)  # 识别文档区域并裁剪
-        logging.info(f"det耗时：{time.time() - det_time}")
         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:
-            dewarp_time = time.time()
             dewarped_image = dewarp.dewarp_image(target_image)  # 去扭曲
-            logging.info(f"dewarp耗时：{time.time() - dewarp_time}")
             angles = image_util.parse_rotation_angles(dewarped_image)
             zx_ie_results = []
             split_results = image_util.split(dewarped_image)