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added a default

app.py

@@ -247,9 +247,18 @@ def apply_example(example):
     ]
 
 # Define the interface
-with gr.Blocks(title="Generative Inference Demo") as demo:
+with gr.Blocks(title="Generative Inference Demo", css="""
+.purple-button {
+    background-color: #8B5CF6 !important;
+    color: white !important;
+    border: none !important;
+}
+.purple-button:hover {
+    background-color: #7C3AED !important;
+}
+""") as demo:
     gr.Markdown("# Generative Inference Demo")
-    gr.Markdown("This demo showcases how neural networks can perceive visual illusions through generative inference.")
+    gr.Markdown("This demo showcases how neural networks can perceive visual illusions and develop Gestalt principles of perceptual organization through generative inference.")
     
     gr.Markdown("""
     **How to use this demo:**
@@ -262,7 +271,7 @@ with gr.Blocks(title="Generative Inference Demo") as demo:
     with gr.Row():
         with gr.Column(scale=1):
             # Inputs
-            image_input = gr.Image(label="Input Image", type="pil")
+            image_input = gr.Image(label="Input Image", type="pil", value=os.path.join("stimuli", "Neon_Color_Circle.jpg"))
             
             with gr.Row():
                 model_choice = gr.Dropdown(
@@ -278,25 +287,25 @@ with gr.Blocks(title="Generative Inference Demo") as demo:
                 )
             
             with gr.Row():
-                eps_slider = gr.Slider(minimum=0.01, maximum=3.0, value=0.5, step=0.01, label="Epsilon (Perturbation Size)")
-                iterations_slider = gr.Slider(minimum=1, maximum=600, value=50, step=1, label="Number of Iterations")  # Updated max to 600
+                eps_slider = gr.Slider(minimum=0.01, maximum=3.0, value=20.0, step=0.01, label="Epsilon (Perturbation Size)")
+                iterations_slider = gr.Slider(minimum=1, maximum=600, value=101, step=1, label="Number of Iterations")  # Updated max to 600
             
             with gr.Row():
-                initial_noise_slider = gr.Slider(minimum=0.0, maximum=1.0, value=0.05, step=0.01, 
+                initial_noise_slider = gr.Slider(minimum=0.0, maximum=1.0, value=0.8, step=0.01, 
                                                label="Initial Noise Ratio")
-                diffusion_noise_slider = gr.Slider(minimum=0.0, maximum=0.05, value=0.01, step=0.001, 
+                diffusion_noise_slider = gr.Slider(minimum=0.0, maximum=0.05, value=0.003, step=0.001, 
                                                 label="Diffusion Noise Ratio")  # Corrected name
                 
             with gr.Row():
-                step_size_slider = gr.Slider(minimum=0.01, maximum=2.0, value=0.5, step=0.01, 
+                step_size_slider = gr.Slider(minimum=0.01, maximum=2.0, value=1.0, step=0.01, 
                                            label="Step Size")  # Added step size slider
                 layer_choice = gr.Dropdown(
                     choices=["all", "conv1", "bn1", "relu", "maxpool", "layer1", "layer2", "layer3", "layer4", "avgpool"],
-                    value="all",
+                    value="layer3",
                     label="Model Layer"
                 )
             
-            run_button = gr.Button("Run Inference", variant="primary")
+            run_button = gr.Button("Run Inference", variant="primary", elem_classes="purple-button")
             
         with gr.Column(scale=2):
             # Outputs