fixed errors

app.py

@@ -11,6 +11,14 @@ def update_table(query, min_size, max_size, selected_tasks=None):
         filtered_df = filtered_df[selected_columns]
     return filtered_df
 
+def update_table_v2(query, min_size, max_size, selected_tasks=None):
+    df = v2.get_df()
+    filtered_df = v2.search_and_filter_models(df, query, min_size, max_size)
+    if selected_tasks and len(selected_tasks) > 0:
+        selected_columns = v2.BASE_COLS + selected_tasks
+        filtered_df = filtered_df[selected_columns]
+    return filtered_df
+
 with gr.Blocks() as block:
     gr.Markdown(LEADERBOARD_INTRODUCTION)
     
@@ -101,7 +109,7 @@ with gr.Blocks() as block:
         with gr.TabItem("📊 MMEB-V2", elem_id="qa-tab-table1", id=2):
             with gr.Row():
                 with gr.Accordion("Citation", open=False):
-                    citation_button = gr.Textbox(
+                    citation_button2 = gr.Textbox(
                         value=v2.CITATION_BUTTON_TEXT,
                         label=CITATION_BUTTON_LABEL,
                         elem_id="citation-button",
@@ -155,30 +163,30 @@ with gr.Blocks() as block:
             
             refresh_button2 = gr.Button("Refresh")
             
-            # def update_with_tasks(*args):
-            #     return update_table(*args)
+            def update_with_tasks_v2(*args):
+                return update_table_v2(*args)
 
             search_bar2.change(
-                fn=update_with_tasks, 
+                fn=update_with_tasks_v2, 
                 inputs=[search_bar2, min_size_slider2, max_size_slider2, tasks_select2], 
                 outputs=data_component2
             )
             min_size_slider2.change(
-                fn=update_with_tasks, 
+                fn=update_with_tasks_v2, 
                 inputs=[search_bar2, min_size_slider2, max_size_slider2, tasks_select2], 
                 outputs=data_component2
             )
             max_size_slider2.change(
-                fn=update_with_tasks, 
+                fn=update_with_tasks_v2, 
                 inputs=[search_bar2, min_size_slider2, max_size_slider2, tasks_select2], 
                 outputs=data_component2
             )
             tasks_select2.change(
-                fn=update_with_tasks, 
+                fn=update_with_tasks_v2, 
                 inputs=[search_bar2, min_size_slider2, max_size_slider2, tasks_select2], 
                 outputs=data_component2
             )
-            # refresh_button.click(fn=refresh_data, outputs=data_component)
+            refresh_button.click(fn=v2.refresh_data, outputs=data_component)
 
         # table 3
         with gr.TabItem("📝 About", elem_id="qa-tab-table2", id=3):

utils_v2.py

@@ -71,7 +71,9 @@ def calculate_score(raw_scores=None):
     Algorithm summary: 
     """
     def get_avg(sum_score, leng):
-        return sum_score / leng if leng > 0 else 0.0
+        avg = sum_score / leng if leng > 0 else 0.0
+        avg = round(avg, 2)  # Round to 2 decimal places
+        return avg
     
     avg_scores = {}
     overall_scores_summary = {} # Stores the scores sum and length for each modality and all datasets
@@ -126,4 +128,22 @@ def get_df():
     df['Rank'] = range(1, len(df) + 1)
     df = create_hyperlinked_names(df)
 
-    return df
+    return df
+
+def refresh_data():
+    df = get_df()
+    return df[COLUMN_NAMES]
+
+def search_and_filter_models(df, query, min_size, max_size):
+    filtered_df = df.copy()
+    
+    if query:
+        filtered_df = filtered_df[filtered_df['Models'].str.contains(query, case=False, na=False)]
+
+    size_mask = filtered_df['Model Size(B)'].apply(lambda x: 
+        (min_size <= 1000.0 <= max_size) if x == 'unknown' 
+        else (min_size <= x <= max_size))
+    
+    filtered_df = filtered_df[size_mask]
+    
+    return filtered_df[COLUMN_NAMES]