Update app.py

app.py

@@ -1,55 +1,47 @@
 import cv2
 import numpy as np
-from PIL import Image, ImageFilter
+from PIL import Image
 from rembg import new_session, remove
-from skimage import filters, restoration
+from skimage import filters
 
-# Initialize best free-tier models
-isnet_session = new_session("isnet-general-use")  # Best details
-u2net_session = new_session("u2net")  # Fallback model
+# Initialize sessions
+isnet_session = new_session("isnet-general-use")
+u2net_session = new_session("u2net")
 
 def perfect_remove_bg(img):
     try:
-        # Convert input and preserve original size
+        # Convert input
         if isinstance(img, np.ndarray):
             img = Image.fromarray(img)
         w, h = img.size
         
-        # Step 1: Primary removal with ISNet (best details)
+        # ISNet for details
         result = remove(img, session=isnet_session)
-        
-        # Step 2: Edge refinement
         mask = np.array(result.split()[-1])
         
-        # Edge-preserving smoothing
+        # Fixed edge refinement
         mask = filters.rank.mean(
             mask.astype(np.uint8), 
-            np.ones((3,3), np.uint8)
+            footprint=np.ones((3,3), np.uint8)  # Correct syntax
+        )
         
-        # Step 3: Combine with U²Net for confidence areas
+        # U²Net for confidence areas
         u2net_mask = np.array(remove(img, session=u2net_session).split()[-1]
-        final_mask = np.where(u2net_mask > 200, mask, u2net_mask)  # Trust U²Net in clear areas
-        
-        # Step 4: Apply refined mask
-        result.putalpha(Image.fromarray(final_mask).resize((w,h)))
+        final_mask = np.where(u2net_mask > 200, mask, u2net_mask)
         
+        result.putalpha(Image.fromarray(final_mask))
         return result
         
     except Exception as e:
-        print(f"⚠️ Error: {e}")
-        return remove(img, session=u2net_session)  # Fallback
+        print(f"Error: {e}")
+        return remove(img, session=u2net_session)
 
 # Gradio interface
-with gr.Blocks(theme=gr.themes.Soft()) as demo:
-    gr.Markdown("""<h1><center>✨ Ultimate Free Background Remover</center></h1>""")
+with gr.Blocks() as demo:
+    gr.Markdown("## ✨ Professional BG Remover")
     with gr.Row():
-        input_img = gr.Image(label="Upload", type="pil", height=400)
-        output_img = gr.Image(label="Result", type="pil", height=400)
-    with gr.Row():
-        gr.Button("Remove Background", variant="primary").click(
-            perfect_remove_bg,
-            inputs=input_img,
-            outputs=output_img
-        )
+        input_img = gr.Image(label="Input", type="pil")
+        output_img = gr.Image(label="Output", type="pil")
+    gr.Button("Process").click(perfect_remove_bg, inputs=input_img, outputs=output_img)
 
-demo.launch(show_error=True)
+demo.launch()