diff --git a/py/drop_shadow_v2.py b/py/drop_shadow_v2.py
index a962e31..10239b0 100644
--- a/py/drop_shadow_v2.py
+++ b/py/drop_shadow_v2.py
@@ -1,3 +1,4 @@
+from PIL import Image
 from .imagefunc import *
 
 NODE_NAME = 'DropShadowV2'
@@ -12,7 +13,6 @@ class DropShadowV2:
 
         return {
             "required": {
-                "background_image": ("IMAGE", ),  #
                 "layer_image": ("IMAGE",),  #
                 "invert_mask": ("BOOLEAN", {"default": True}),  # 反转mask
                 "blend_mode": (chop_mode_v2,),  # 混合模式
@@ -24,6 +24,7 @@ class DropShadowV2:
                 "shadow_color": ("STRING", {"default": "#000000"}),  # 背景颜色
             },
             "optional": {
+                "background_image": ("IMAGE", ),  #
                 "layer_mask": ("MASK",),  #
             }
         }
@@ -33,11 +34,18 @@ class DropShadowV2:
     FUNCTION = 'drop_shadow_v2'
     CATEGORY = '😺dzNodes/LayerStyle'
 
-    def drop_shadow_v2(self, background_image, layer_image,
-                  invert_mask, blend_mode, opacity, distance_x, distance_y,
-                  grow, blur, shadow_color,
-                  layer_mask=None
-                  ):
+    def drop_shadow_v2(self, layer_image, invert_mask, blend_mode, opacity,
+                       distance_x, distance_y, grow, blur, shadow_color,
+                       background_image=None, layer_mask=None
+                       ):
+
+        # If background image is empty, create transparent background
+        # image for each layer image
+        if background_image == None:
+            background_image = []
+            for l in layer_image:
+                m = tensor2pil(l)
+            background_image.append(pil2tensor(Image.new('RGBA', (m.width, m.height), (0, 0, 0, 0))))
 
         b_images = []
         l_images = []
@@ -65,7 +73,7 @@ class DropShadowV2:
         max_batch = max(len(b_images), len(l_images), len(l_masks))
         distance_x = -distance_x
         distance_y = -distance_y
-        shadow_color = Image.new("RGB", tensor2pil(l_images[0]).size, color=shadow_color)
+        shadow_color = Image.new("RGBA", tensor2pil(l_images[0]).size, color=shadow_color)
 
         for i in range(max_batch):
             background_image = b_images[i] if i < len(b_images) else b_images[-1]
@@ -73,7 +81,7 @@ class DropShadowV2:
             _mask = l_masks[i] if i < len(l_masks) else l_masks[-1]
 
             # preprocess
-            _canvas = tensor2pil(background_image).convert('RGB')
+            _canvas = tensor2pil(background_image).convert('RGBA')
             _layer = tensor2pil(layer_image)
 
             if _mask.size != _layer.size: