Update app.py

app.py

@@ -64,7 +64,7 @@ with block:
             
             # Leaderboard section with method and metric selectors
             leaderboard_method_selector = gr.CheckboxGroup(
-                choices=method_names, label="Select method_names for Leaderboard", value=method_names, interactive=True
+                choices=method_names, label="Select Methods for Leaderboard", value=method_names, interactive=True
             )
             leaderboard_metric_selector = gr.CheckboxGroup(
                 choices=metric_names, label="Select Metrics for Leaderboard", value=metric_names, interactive=True
@@ -75,7 +75,7 @@ with block:
             baseline_header = ["method_name"] + metric_names
             baseline_datatype = ['markdown'] + ['number'] * len(metric_names)
 
-            with gr.Row(show_progress=True):
+            with gr.Row(show_progress=True, variant='panel'):
                 data_component = gr.components.Dataframe(
                     value=baseline_value,
                     headers=baseline_header,
@@ -84,7 +84,7 @@ with block:
                     interactive=False,
                     visible=True,
                 )
-    
+
             # Update leaderboard when method/metric selection changes
             leaderboard_method_selector.change(
                 update_leaderboard, 
@@ -97,7 +97,15 @@ with block:
                 outputs=data_component
             )
 
-
+            with gr.Row():
+                gr.Markdown(
+                    """
+                    **Below, you can visualize the results displayed in the Leaderboard.**
+                    Once you choose a benchmark type, the related options for metrics, datasets, and other parameters will become visible. 
+                    Select the methods and metrics of interest from the options above to generate visualizations. 
+                    """
+                )
+            
             # Dropdown for benchmark type
             benchmark_type_selector = gr.Dropdown(choices=list(benchmark_specific_metrics.keys()), label="Select Benchmark Type")
 
@@ -114,8 +122,9 @@ with block:
             # Button to draw the plot for the selected benchmark
 
             plot_button = gr.Button("Plot")
-                
-            plot_output = gr.Image(label="Plot")
+
+            with gr.Row(show_progress=True, variant='panel'):
+                plot_output = gr.Image(label="Plot")
                 
             # Update selectors when benchmark type changes
             benchmark_type_selector.change(