Update app.py

app.py

@@ -12,7 +12,6 @@ import time
 import uuid
 import shutil
 
-# Load the pre-trained model
 print("Loading model...")
 net = BriaRMBG.from_pretrained("briaai/RMBG-1.4")
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
@@ -20,14 +19,12 @@ net.to(device)
 net.eval()
 print(f"Model loaded on {device}")
 
-# Create output directory if it doesn't exist
 OUTPUT_DIR = "output_images"
 os.makedirs(OUTPUT_DIR, exist_ok=True)
 
 def resize_image(image, max_size=1024):
     width, height = image.size
     aspect_ratio = width / height
-    
     if width > max_size or height > max_size:
         if width > height:
             new_width = max_size
@@ -35,16 +32,12 @@ def resize_image(image, max_size=1024):
         else:
             new_height = max_size
             new_width = int(max_size * aspect_ratio)
-        image = image.resize((new_width, new_height), Image.LANCZOS)
-    
+        image = resize_image.resize((new_width, new_height), Image.LANCZOS)
     return image
 
-# ... existing imports and model loading code ...
-
 def process(image, progress=gr.Progress()):
     if image is None:
         return None, None
-    
     try:
         progress(0, desc="Starting processing...")
         orig_image = Image.fromarray(image)
@@ -54,7 +47,6 @@ def process(image, progress=gr.Progress()):
         process_image = resize_image(orig_image)
         w, h = process_image.size
         
-        # Convert image to tensor
         im_np = np.array(process_image)
         im_tensor = torch.tensor(im_np, dtype=torch.float32).permute(2, 0, 1)
         im_tensor = torch.unsqueeze(im_tensor, 0)
@@ -89,238 +81,91 @@ 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
 
-# ... rest of the code remains the same ...
+css = """
+@import url('https://fonts.googleapis.com/css2?family=Orbitron:wght@400;500;700&display=swap');
 
-# 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"
-    )
+.container { max-width: 850px; margin: 0 auto; padding: 20px; }
 
-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)
-        
-    except Exception as e:
-        print(f"Error processing image: {str(e)}")
-        return None, None
+.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;
+}
 
-# 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;
-        }
+.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;
     }
-    
-    @media (max-width: 768px) {
-        .title-text { font-size: 1.8em; }
-        .subtitle-text { font-size: 1em; }
-        .image-container { padding: 10px; }
-        .download-btn { padding: 10px 20px; }
+    to {
+        text-shadow: 0 0 10px #ff00de, 0 0 20px #ff00de, 0 0 30px #ff00de;
     }
-""") as demo:
+}
+
+@media (max-width: 768px) {
+    .title-text { font-size: 1.8em; }
+    .subtitle-text { font-size: 1em; }
+    .image-container { padding: 10px; }
+    .download-btn { padding: 10px 20px; }
+}
+"""
+
+with gr.Blocks(css=css) as demo:
     gr.Markdown("""
         <h1 class="title-text">AI Background Removal</h1>
         <p class="subtitle-text">Remove backgrounds instantly using advanced AI technology</p>
@@ -336,9 +181,8 @@ with gr.Blocks(css="""
             
             output_image = gr.Image(
                 label="Result",
-                type="filepath",
-                elem_classes="image-container",
-                visible=True
+                type="numpy",
+                elem_classes="image-container"
             )
             
             download_file = gr.File(
@@ -347,7 +191,6 @@ with gr.Blocks(css="""
                 elem_classes="download-btn"
             )
     
-    # Automatic processing when image is uploaded
     input_image.change(
         fn=process,
         inputs=input_image,