diff --git a/app/service/clothing_seg/service.py b/app/service/clothing_seg/service.py
index a0f3640..7894bff 100644
--- a/app/service/clothing_seg/service.py
+++ b/app/service/clothing_seg/service.py
@@ -33,7 +33,6 @@ class ClothingSeg:
         for data in self.image_data:
             del data["image"]
             del data["clothing"]
-
         return self.image_data
 
     @RunTime
@@ -88,14 +87,16 @@ class ClothingSeg:
                 inputs[0].set_data_from_numpy(input0_data)
 
                 outputs = [
-                    grpcclient.InferRequestedOutput("OUTPUT0"),
+                    # grpcclient.InferRequestedOutput("OUTPUT0"),
                     grpcclient.InferRequestedOutput("OUTPUT1"),
                 ]
+
                 response = self.triton_client.infer("seg_clothing", inputs, request_id=str(1), outputs=outputs)
-                output0_data = response.as_numpy("OUTPUT0")
-                cv2.imwrite("output02.png", output0_data * 100)
+                # output0_data = response.as_numpy("OUTPUT0")
+                # cv2.imwrite("output02.png", output0_data * 100)
                 output1_data = response.as_numpy("OUTPUT1")
                 for alpha in output1_data:
+                    alpha = cv2.resize(alpha, (image.shape[1], image.shape[0]), interpolation=cv2.INTER_CUBIC)
                     x_min, y_min, x_max, y_max = get_bounding_box(alpha)
                     cropped_mask = alpha[y_min:y_max + 1, x_min:x_max + 1]
                     cropped_image = image[y_min:y_max + 1, x_min:x_max + 1]
@@ -121,7 +122,7 @@ def get_bounding_box(mask):
 
     if len(rows) == 0 or len(cols) == 0:
         # 如果没有找到不为 0 的像素，返回全 0 的边界框
-        return (0, 0, 0, 0)
+        return 0, 0, 0, 0
 
     # 计算边界框的坐标
     x_min = np.min(cols)
@@ -129,21 +130,21 @@ def get_bounding_box(mask):
     x_max = np.max(cols)
     y_max = np.max(rows)
 
-    return (x_min, y_min, x_max, y_max)
+    return x_min, y_min, x_max, y_max
 
 
 if __name__ == "__main__":
-    request_data = ClothingSegModel(
+    test_data = ClothingSegModel(
         user_id=89,
         image_data=[
-            {
-                "image_url": "test/clothing_seg/dress.jpg",
-                "image_type": "sketch"
-            },
-            {
-                "image_url": "test/clothing_seg/skirt_559.jpg",
-                "image_type": "sketch"
-            },
+            # {
+            #     "image_url": "test/clothing_seg/dress.jpg",
+            #     "image_type": "sketch"
+            # },
+            # {
+            #     "image_url": "test/clothing_seg/skirt_559.jpg",
+            #     "image_type": "sketch"
+            # },
             {
                 "image_url": "test/clothing_seg/10144613.jpg",
                 "image_type": "product"
@@ -151,6 +152,6 @@ if __name__ == "__main__":
         ]
     )
     start_time = time.time()
-    server = ClothingSeg(request_data)
+    server = ClothingSeg(test_data)
     pprint(server.get_result())
     print(time.time() - start_time)