UI: more compact layout

app.py

@@ -235,47 +235,48 @@ def run_inference(sample_idx):
 
 # --- Gradio UI ---
 
-with gr.Blocks(title="MMRM Demo", theme=gr.themes.Soft()) as demo:
+with gr.Blocks(title="MMRM Demo", theme=gr.themes.Soft(spacing_size="sm", text_size="sm")) as demo:
     gr.Markdown("# MMRM: Multimodal Multitask Restoring Model")
-    gr.Markdown("Interactive demo comparing MMRM with baselines on real-world damaged characters.")
+    gr.Markdown("Comparing MMRM with baselines on real-world damaged characters.")
     
     with gr.Row():
-        sample_dropdown = gr.Dropdown(
-            choices=[x[1] for x in sample_options], # Use index as value
-            type="value",
-            label="Select Real-World Sample",
-            info="Choose a sample from the real-world dataset."
-        )
-        sample_dropdown.choices = sample_options
-        
-        run_btn = gr.Button("Run Inference", variant="primary")
-    
-    gr.Markdown("### Input")
-    with gr.Row():
-        input_image = gr.Image(label="Damaged Character (Input)", type="pil", height=200, width=200)
-        input_text = gr.Textbox(label="Context Info", lines=3)
-        
-    gr.Markdown("### Model Predictions")
-    with gr.Row():
-        with gr.Column():
-            gr.Markdown("**Zero-shot (Pre-trained)**")
-            zs_output = gr.Label(num_top_classes=5, label="GuwenBERT (Base)")
-            
-        with gr.Column():
-            gr.Markdown("**Textual Baseline**")
-            text_output = gr.Label(num_top_classes=5, label="RoBERTa (Finetuned)")
+        # --- Left Column: Inputs ---
+        with gr.Column(scale=1):
+            gr.Markdown("### Input Selection")
+            with gr.Row():
+                sample_dropdown = gr.Dropdown(
+                    choices=[x[1] for x in sample_options], # Use index as value
+                    type="value",
+                    label="Select Sample",
+                    container=False,
+                    scale=3
+                )
+                sample_dropdown.choices = sample_options
+                run_btn = gr.Button("Run", variant="primary", scale=1, min_width=60)
             
-        with gr.Column():
-            gr.Markdown("**Visual Baseline**")
-            visual_output = gr.Label(num_top_classes=5, label="ResNet50")
+            with gr.Row():
+                input_image = gr.Image(label="Damaged Input", type="pil", height=250)
             
-        with gr.Column():
-            gr.Markdown("**MMRM (Ours)**")
-            mmrm_output = gr.Label(num_top_classes=5, label="Multimodal")
+            with gr.Row():
+                input_text = gr.Textbox(label="Context Info", lines=5)
+
+        # --- Right Column: Outputs ---
+        with gr.Column(scale=2):
+            gr.Markdown("### Model Predictions")
+            with gr.Row():
+                with gr.Column(min_width=80):
+                    zs_output = gr.Label(num_top_classes=3, label="Zero-shot")
+                with gr.Column(min_width=80):
+                    text_output = gr.Label(num_top_classes=3, label="Textual")
+                with gr.Column(min_width=80):
+                    visual_output = gr.Label(num_top_classes=3, label="Visual")
+                with gr.Column(min_width=80):
+                    mmrm_output = gr.Label(num_top_classes=3, label="MMRM")
             
-    gr.Markdown("### Intermediate Process: Visual Restoration")
-    with gr.Row():
-        restored_output = gr.Image(label="Restored Image (MMRM Output)", type="pil", height=200, width=200)
+            with gr.Row():
+                with gr.Column():
+                    gr.Markdown("### Visual Restoration")
+                    restored_output = gr.Image(label="MMRM Output", type="pil", height=250)
 
     # Event
     run_btn.click(