feat 测试批量上传图片

fix

app/service/design/items/pipelines/keypoints.py

@@ -28,7 +28,7 @@ class KeypointDetection(object):
     # self.client.close()
     # print(f"client close time : {time.time() - start_time}")
 
-    @ ClassCallRunTime
+    # @ClassCallRunTime
     def __call__(self, result):
         # logging.info("KeypointDetection run ")
         if result['name'] in ['blouse', 'skirt', 'dress', 'outwear', 'trousers', 'tops', 'bottoms']:  # 查询是否有数据 且类别相同 相同则直接读 不同则推理后更新

app/service/design/items/pipelines/loading.py

@@ -13,7 +13,7 @@ class LoadImageFromFile(object):
         self.print_dict = print_dict
         # self.minio_client = Minio(f"{MINIO_URL}", access_key=MINIO_ACCESS, secret_key=MINIO_SECRET, secure=MINIO_SECURE)
 
-    @ClassCallRunTime
+    # @ClassCallRunTime
     def __call__(self, result):
         result['image'], result['pre_mask'] = self.read_image(self.path)
         result['gray'] = cv2.cvtColor(result['image'], cv2.COLOR_BGR2GRAY)

app/service/design/items/pipelines/painting.py

@@ -14,7 +14,7 @@ class Painting(object):
     def __init__(self, painting_flag=True):
         self.painting_flag = painting_flag
 
-    @ClassCallRunTime
+    # @ClassCallRunTime
     def __call__(self, result):
         if result['name'] not in ['hairstyle', 'earring'] and self.painting_flag and result['color'] != 'none':
             dim_image_h, dim_image_w = result['image'].shape[0:2]
@@ -87,7 +87,7 @@ class PrintPainting(object):
     def __init__(self, print_flag=True):
         self.print_flag = print_flag
 
-    @ClassCallRunTime
+    # @ClassCallRunTime
     def __call__(self, result):
         single_print = result['print']['single']
         overall_print = result['print']['overall']

app/service/design/items/pipelines/scale.py

@@ -11,7 +11,7 @@ class Scaling(object):
     def __init__(self):
         pass
 
-    @ClassCallRunTime
+    # @ClassCallRunTime
     def __call__(self, result):
         if result['keypoint'] in ['waistband', 'shoulder', 'head_point']:
             # milvus_db_keypoint_cache

app/service/design/items/pipelines/segmentation.py

@@ -15,7 +15,7 @@ class Segmentation(object):
         self.device = device
         self.debug = debug
 
-    @ClassCallRunTime
+    # @ClassCallRunTime
     def __call__(self, result):
         _, seg_result = self.load_seg_result(result["image_id"])
         if not _:

app/service/design/items/pipelines/split.py

@@ -18,7 +18,7 @@ class Split(object):
     Split image into front and back layer according to the segmentation result
     """
 
-    @ClassCallRunTime
+    # @ClassCallRunTime
     # KNet
     def __call__(self, result):
         try: