Upload app.py

app.py

@@ -112,42 +112,25 @@ def detect_manipulation(image):
     
     return result_image
 
-# Custom CSS to match your design
+# Custom CSS for styling
 custom_css = """
-#component-0 {
-    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
-    padding: 20px;
-}
-
-.gradio-container {
-    max-width: 1200px !important;
-    margin: auto !important;
-}
-
 #title {
     text-align: center;
-    color: white;
-    font-size: 3em;
-    margin-bottom: 10px;
-    text-shadow: 2px 2px 4px rgba(0,0,0,0.2);
+    font-size: 2.5em;
+    font-weight: bold;
+    margin-bottom: 0.5em;
+    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+    -webkit-background-clip: text;
+    -webkit-text-fill-color: transparent;
+    background-clip: text;
 }
-
 #subtitle {
     text-align: center;
-    color: white;
     font-size: 1.2em;
-    margin-bottom: 30px;
-    opacity: 0.95;
+    color: #666;
+    margin-bottom: 1em;
 }
-
-.main-card {
-    background: white;
-    border-radius: 20px;
-    padding: 40px;
-    box-shadow: 0 20px 60px rgba(0,0,0,0.3);
-}
-
-#info-box {
+#info {
     background: #e8f4fd;
     border-left: 4px solid #2196F3;
     padding: 15px;
@@ -155,81 +138,26 @@ custom_css = """
     margin-bottom: 20px;
     color: #1976D2;
 }
-
-.upload-container .transition {
-    border: 3px dashed #667eea !important;
-    border-radius: 15px !important;
-    background: #f8f9ff !important;
-}
-
-.upload-container .transition:hover {
-    border-color: #764ba2 !important;
-    background: #f0f2ff !important;
-}
-
-button.primary {
-    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%) !important;
-    border: none !important;
-    color: white !important;
-    border-radius: 25px !important;
-    padding: 12px 30px !important;
-    font-size: 1em !important;
-}
-
-button.primary:hover {
-    transform: translateY(-2px);
-    box-shadow: 0 5px 15px rgba(102, 126, 234, 0.4) !important;
-}
-
-.output-image {
-    border-radius: 15px;
-    box-shadow: 0 5px 15px rgba(0,0,0,0.1);
-}
 """
 
-# Create Gradio interface
-with gr.Blocks(css=custom_css, theme=gr.themes.Soft()) as demo:
-    gr.HTML("""
-        <div id="title">🎯 RADAR</div>
-        <div id="subtitle">ReliAble iDentification of inpainted AReas</div>
-    """)
+# Create simple interface
+with gr.Blocks(css=custom_css, title="RADAR - Image Manipulation Detection") as demo:
+    gr.HTML('<h1 id="title">🎯 RADAR</h1>')
+    gr.HTML('<p id="subtitle">ReliAble iDentification of inpainted AReas</p>')
     
-    with gr.Column(elem_classes="main-card"):
-        gr.HTML("""
-            <div id="info-box">
-                <strong>ℹ️ About RADAR:</strong> Upload an image to detect and localize regions 
-                that have been manipulated using diffusion-based inpainting models. 
-                The output shows a heatmap where red areas indicate detected manipulations.
-            </div>
-        """)
-        
-        with gr.Row():
-            with gr.Column():
-                input_image = gr.Image(
-                    label="Upload Image",
-                    type="pil",
-                    elem_classes="upload-container"
-                )
-                submit_btn = gr.Button("🔍 Detect Manipulations", variant="primary", size="lg")
-            
-            with gr.Column():
-                output_image = gr.Image(
-                    label="Manipulation Heatmap",
-                    type="pil",
-                    elem_classes="output-image"
-                )
-        
-        gr.Examples(
-            examples=[
-                # Add paths to your example images here
-                # ["examples/example1.png"],
-                # ["examples/example2.png"],
-            ],
-            inputs=input_image,
-            outputs=output_image,
-            fn=detect_manipulation,
-            cache_examples=False,
-        )
+    gr.HTML('''
+        <div id="info">
+            <strong>ℹ️ About RADAR:</strong> Upload an image to detect and localize regions 
+            that have been manipulated using diffusion-based inpainting models. 
+            The output shows a heatmap where red areas indicate detected manipulations.
+        </div>
+    ''')
+    
+    with gr.Row():
+        input_image = gr.Image(label="Upload Image", type="pil")
+        output_image = gr.Image(label="Manipulation Heatmap", type="pil")
+    
+    submit_btn = gr.Button("🔍 Detect Manipulations", variant="primary")
     
     # Connect the button
     submit_btn.click(