Update app.py

app.py

@@ -1,55 +1,49 @@
-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
+from skimage import restoration
 
-# Initialize session with proper settings to prevent cropping
-session = new_session("u2net")
-bg_removal_kwargs = {
-    "alpha_matting": False,  # Disable advanced features that cause cropping
-    "session": session,
-    "only_mask": False,
-    "post_process_mask": True  # Clean edges without cropping
-}
+# Initialize ISNet (best free-tier detail model)
+session = new_session("isnet-general-use")
 
-def remove_background(input_image):
+def perfect_remove_bg(img):
     try:
-        # Convert any input to PIL Image
-        if isinstance(input_image, np.ndarray):
-            img = Image.fromarray(input_image)
-        elif isinstance(input_image, dict):  # Handle paste/drop
-            img = Image.open(input_image["name"])
-        else:
-            img = input_image
+        # Convert input
+        if isinstance(img, np.ndarray):
+            img = Image.fromarray(img)
+        
+        # Preserve original size
+        w, h = img.size
+        
+        # Step 1: Initial removal
+        result = remove(
+            img,
+            session=session,
+            alpha_matting=False,  # Disable auto-crop
+            post_process_mask=True
+        )
+        
+        # Step 2: Edge refinement (CPU-only)
+        mask = np.array(result.split()[-1])  # Extract alpha
+        mask = restoration.denoise_tv_chambolle(mask, weight=0.1)  # Smooth edges
+        mask = (mask * 255).astype(np.uint8)
+        
+        # Step 3: Apply refined mask
+        result.putalpha(Image.fromarray(mask).resize((w,h)))
         
-        # Preserve original size (disable auto-resizing)
-        result = remove(img, **bg_removal_kwargs)
         return result
-    
+        
     except Exception as e:
-        print(f"Error: {str(e)}")
-        return input_image  # Return original if fails
+        print(f"Error: {e}")
+        return img
 
-# Gradio interface with proper image handling
+# Gradio interface
 with gr.Blocks() as demo:
-    gr.Markdown("## 🖼️ Background Remover (No Cropping)")
-    
+    gr.Markdown("## ✨ Free Detail-Preserving BG Remover")
     with gr.Row():
-        input_img = gr.Image(
-            label="Original", 
-            type="pil",  # Ensures we get PIL Images
-            height=400
-        )
-        output_img = gr.Image(
-            label="Result", 
-            type="pil",
-            height=400
-        )
-    
-    gr.Button("Remove Background").click(
-        remove_background,
-        inputs=input_img,
-        outputs=output_img
-    )
+        input_img = gr.Image(label="Input", type="pil", sources=["upload"])
+        output_img = gr.Image(label="Output", type="pil")
+    gr.Button("Process").click(perfect_remove_bg, inputs=input_img, outputs=output_img)
 
-demo.launch()
+demo.launch(show_error=True)