Update app.py

app.py

@@ -25,7 +25,6 @@ OUTPUT_DIR = "output_images"
 os.makedirs(OUTPUT_DIR, exist_ok=True)
 
 def resize_image(image, max_size=1024):
-    """Resize image while maintaining aspect ratio"""
     width, height = image.size
     aspect_ratio = width / height
     
@@ -41,7 +40,6 @@ def resize_image(image, max_size=1024):
     return image
 
 def process(image, progress=gr.Progress()):
-    """Process the image and remove background"""
     if image is None:
         return None, None
     
@@ -89,6 +87,154 @@ def process(image, progress=gr.Progress()):
         filepath = os.path.join(OUTPUT_DIR, filename)
         new_im.save(filepath, format='PNG', quality=100)
         
+        # Convert to RGBA array for display
+        output_array = np.array(new_im.convert('RGBA'))
+        
+        progress(1.0, desc="Done!")
+        return output_array, gr.File.update(value=filepath, visible=True)
+        
+    except Exception as e:
+        print(f"Error processing image: {str(e)}")
+        return None, None
+
+# Gradio interface
+with gr.Blocks(css="""
+    @import url('https://fonts.googleapis.com/css2?family=Orbitron:wght@400;500;700&display=swap');
+    
+    .container { max-width: 850px; margin: 0 auto; padding: 20px; }
+    
+    .title-text {
+        color: #ff00de;
+        font-family: 'Orbitron', sans-serif;
+        font-size: 2.5em;
+        text-align: center;
+        margin: 20px 0;
+        text-shadow: 0 0 10px rgba(255, 0, 222, 0.7);
+        animation: glow 2s ease-in-out infinite alternate;
+    }
+    
+    .subtitle-text {
+        color: #00ffff;
+        text-align: center;
+        margin-bottom: 30px;
+        font-size: 1.2em;
+        text-shadow: 0 0 8px rgba(0, 255, 255, 0.7);
+    }
+    
+    .image-container {
+        background: rgba(10, 10, 30, 0.3);
+        border-radius: 15px;
+        padding: 20px;
+        margin: 10px 0;
+        border: 2px solid #00ffff;
+        box-shadow: 0 0 15px rgba(0, 255, 255, 0.2);
+        transition: all 0.3s ease;
+    }
+    
+    .image-container:hover {
+        box-shadow: 0 0 20px rgba(0, 255, 255, 0.4);
+        transform: translateY(-2px);
+    }
+    
+    .download-btn {
+        background: linear-gradient(45deg, #00ffff, #ff00de);
+        border: none;
+        padding: 12px 25px;
+        border-radius: 8px;
+        color: white;
+        font-family: 'Orbitron', sans-serif;
+        cursor: pointer;
+        transition: all 0.3s ease;
+        margin-top: 10px;
+        text-align: center;
+        text-transform: uppercase;
+        letter-spacing: 1px;
+    }
+    
+    .download-btn:hover {
+        transform: translateY(-2px);
+        box-shadow: 0 5px 15px rgba(0, 255, 255, 0.4);
+    }
+    
+    @keyframes glow {
+        from {
+            text-shadow: 0 0 5px #ff00de, 0 0 10px #ff00de, 0 0 15px #ff00de;
+        }
+        to {
+            text-shadow: 0 0 10px #ff00de, 0 0 20px #ff00de, 0 0 30px #ff00de;
+        }
+    }
+    
+    @media (max-width: 768px) {
+        .title-text { font-size: 1.8em; }
+        .subtitle-text { font-size: 1em; }
+        .image-container { padding: 10px; }
+        .download-btn { padding: 10px 20px; }
+    }
+""") as demo:
+    gr.Markdown("""
+        <h1 class="title-text">AI Background Removal</h1>
+        <p class="subtitle-text">Remove backgrounds instantly using advanced AI technology</p>
+    """)
+    
+    with gr.Row():
+        with gr.Column():
+            input_image = gr.Image(
+                label="Upload Image",
+                type="numpy",
+                elem_classes="image-container"
+            )
+            
+            output_image = gr.Image(
+                label="Result",
+                type="numpy",  # Changed from filepath to numpy
+                elem_classes="image-container"
+            )
+            
+            download_file = gr.File(
+                label="Download Processed Image",
+                visible=False,
+                elem_classes="download-btn"
+            )
+    
+    # Automatic processing when image is uploaded
+    input_image.change(
+        fn=process,
+        inputs=input_image,
+        outputs=[output_image, download_file],
+        api_name="process_image"
+    )
+
+if __name__ == "__main__":
+    demo.launch()        
+        progress(0.4, desc="Processing with AI model...")
+        if torch.cuda.is_available():
+            im_tensor = im_tensor.cuda()
+        
+        with torch.no_grad():
+            result = net(im_tensor)
+        
+        progress(0.6, desc="Post-processing...")
+        result = torch.squeeze(F.interpolate(result[0][0], size=(h, w), mode='bilinear'), 0)
+        ma = torch.max(result)
+        mi = torch.min(result)
+        result = (result - mi) / (ma - mi)
+        
+        result_array = (result * 255).cpu().data.numpy().astype(np.uint8)
+        pil_mask = Image.fromarray(np.squeeze(result_array))
+        
+        if pil_mask.size != original_size:
+            pil_mask = pil_mask.resize(original_size, Image.LANCZOS)
+        
+        new_im = orig_image.copy()
+        new_im.putalpha(pil_mask)
+        
+        progress(0.8, desc="Saving result...")
+        unique_id = str(uuid.uuid4())[:8]
+        filename = f"background_removed_{unique_id}.png"
+        filepath = os.path.join(OUTPUT_DIR, filename)
+        new_im.save(filepath, format='PNG', quality=100)
+        
         progress(1.0, desc="Done!")
         return gr.Image.update(value=filepath, visible=True), gr.File.update(value=filepath, visible=True)