diff --git a/apps/rmbg/service.py b/apps/rmbg/service.py
index 9293950..7e96842 100644
--- a/apps/rmbg/service.py
+++ b/apps/rmbg/service.py
@@ -122,6 +122,7 @@ class RmbgService:
         mask = pred_pil.resize(image_size)
         image.putalpha(mask)
         
+        # 单张处理保留 gc.collect()，确保及时释放内存
         if torch.cuda.is_available():
             torch.cuda.empty_cache()
             gc.collect()
@@ -139,10 +140,6 @@ class RmbgService:
             transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]),
         ])
         
-        # 批处理前清理显存
-        if torch.cuda.is_available():
-            torch.cuda.empty_cache()
-        
         batch_tensors = []
         for image, image_size, index in images_with_info:
             batch_tensors.append(transform_image(image))
@@ -165,9 +162,9 @@ class RmbgService:
         del input_batch
         if isinstance(model_output, (list, tuple)):
             del model_output
-        if torch.cuda.is_available():
-            torch.cuda.empty_cache()
         
+        # 复用 ToPILImage 转换器，避免重复创建对象
+        to_pil = transforms.ToPILImage()
         results = []
         for i, (image, image_size, index) in enumerate(images_with_info):
             if len(preds.shape) == 4:
@@ -177,7 +174,7 @@ class RmbgService:
             else:
                 pred = preds[i].squeeze()
             
-            pred_pil = transforms.ToPILImage()(pred)
+            pred_pil = to_pil(pred)
             mask = pred_pil.resize(image_size)
             result_image = image.copy()
             result_image.putalpha(mask)
@@ -186,10 +183,9 @@ class RmbgService:
         # 释放 preds
         del preds
         
-        # 批处理后再次清理显存
+        # 批处理后清理显存（移除 gc.collect()，减少阻塞）
         if torch.cuda.is_available():
             torch.cuda.empty_cache()
-            gc.collect()
         
         return results