Update app.py

app.py

@@ -1,25 +1,55 @@
-import gradio as gr
+import cv2
 import numpy as np
-from PIL import Image
-from rembg import remove, new_session
+from PIL import Image, ImageFilter
+from rembg import new_session, remove
+from skimage import filters, restoration
 
-# Initialize session (will auto-download model)
-session = new_session("isnet-general-use")
+# Initialize best free-tier models
+isnet_session = new_session("isnet-general-use")  # Best details
+u2net_session = new_session("u2net")  # Fallback model
 
-def remove_bg(image):
+def perfect_remove_bg(img):
     try:
-        if isinstance(image, np.ndarray):
-            image = Image.fromarray(image)
-        return remove(image, session=session)
+        # Convert input and preserve original size
+        if isinstance(img, np.ndarray):
+            img = Image.fromarray(img)
+        w, h = img.size
+        
+        # Step 1: Primary removal with ISNet (best details)
+        result = remove(img, session=isnet_session)
+        
+        # Step 2: Edge refinement
+        mask = np.array(result.split()[-1])
+        
+        # Edge-preserving smoothing
+        mask = filters.rank.mean(
+            mask.astype(np.uint8), 
+            np.ones((3,3), np.uint8)
+        
+        # Step 3: Combine with 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)))
+        
+        return result
+        
     except Exception as e:
-        print(f"Error: {e}")
-        return image
+        print(f"⚠️ Error: {e}")
+        return remove(img, session=u2net_session)  # Fallback
 
-with gr.Blocks() as demo:
-    gr.Markdown("## 🆓 Free Background Remover")
+# Gradio interface
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    gr.Markdown("""<h1><center>✨ Ultimate Free Background Remover</center></h1>""")
     with gr.Row():
-        input_img = gr.Image(label="Input", type="pil")
-        output_img = gr.Image(label="Output", type="pil")
-    gr.Button("Remove BG").click(remove_bg, inputs=input_img, outputs=output_img)
+        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
+        )
 
-demo.launch()
+demo.launch(show_error=True)