Update app.py

app.py

@@ -1,10 +1,10 @@
-import cv2
 import numpy as np
 from PIL import Image
 from rembg import new_session, remove
 from skimage import filters
+import gradio as gr
 
-# Initialize sessions
+# Initialize models
 isnet_session = new_session("isnet-general-use")
 u2net_session = new_session("u2net")
 
@@ -13,23 +13,24 @@ def perfect_remove_bg(img):
         # Convert input
         if isinstance(img, np.ndarray):
             img = Image.fromarray(img)
-        w, h = img.size
         
         # ISNet for details
         result = remove(img, session=isnet_session)
         mask = np.array(result.split()[-1])
         
-        # Fixed edge refinement
+        # Edge refinement
         mask = filters.rank.mean(
-            mask.astype(np.uint8), 
-            footprint=np.ones((3,3), np.uint8)  # Correct syntax
+            mask.astype(np.uint8),
+            footprint=np.ones((3,3), np.uint8)
         )
         
-        # U²Net for confidence areas
+        # U²Net for confidence areas (FIXED PARENTHESES)
         u2net_mask = np.array(remove(img, session=u2net_session).split()[-1]
-        final_mask = np.where(u2net_mask > 200, mask, u2net_mask)
         
+        # Combine masks
+        final_mask = np.where(u2net_mask > 200, mask, u2net_mask)
         result.putalpha(Image.fromarray(final_mask))
+        
         return result
         
     except Exception as e: