update apperance

app.py

@@ -22,19 +22,21 @@ MODEL_INFO = [
 ]
 
 # Column Names for DataFrame
-COLUMN_NAMES = MODEL_INFO + DISCIPLINES + ["Average"]
+COLUMN_NAMES = MODEL_INFO + DISCIPLINES
 
 # Data Types for DataFrame
-DATA_TITILE_TYPE = ['markdown'] + ['number'] * len(DISCIPLINES) + ['number']
+DATA_TITILE_TYPE = ['markdown'] + ['number'] * len(DISCIPLINES)
 
 # Leaderboard Introduction
 LEADERBOARD_INTRODUCTION = """# MMWorld Leaderboard
 
 *"Towards Multi-discipline Multi-faceted World Model Evaluation in Videos"*  
 🏆 Welcome to the leaderboard of the **MMWorld**! 🎦 *A new benchmark for multi-discipline, multi-faceted multimodal video understanding*  
-[![GitHub](https://img.shields.io/badge/Code-GitHub-black?logo=github)](https://github.com/eric-ai-lab/MMWorld) 
 
 <div style="display: flex; flex-wrap: wrap; align-items: center; gap: 10px;">
+<a href='https://github.com/eric-ai-lab/MMWorld'>
+  <img src='https://img.shields.io/badge/Code-GitHub-black?logo=github'>
+</a>
 <a href='https://arxiv.org/abs/2406.08407'>
   <img src='https://img.shields.io/badge/cs.CV-Paper-b31b1b?logo=arxiv&logoColor=red'>
 </a>
@@ -47,8 +49,7 @@ LEADERBOARD_INTRODUCTION = """# MMWorld Leaderboard
 
 SUBMIT_INTRODUCTION = """# Submit on MMWorld Benchmark Introduction
 
-## 🎈
-Please obtain the evaluation file `*.json` by running MMWorld in Github and upload the json file below.
+## 🎈 Please obtain the evaluation file `*.json` by running MMWorld in Github and upload the json file below.
 
 ⚠️ The contact information you filled in will not be made public. 
 """
@@ -106,24 +107,15 @@ data = {
 # Create DataFrame
 df_full = pd.DataFrame(data)
 
-# Function to calculate average score
-def calculate_average(df, disciplines):
-    df['Average'] = df[disciplines].mean(axis=1)
-    return df
-
 # Function to get leaderboard DataFrame based on selected disciplines
 def get_leaderboard_df(selected_disciplines):
     if not selected_disciplines:
         selected_disciplines = DISCIPLINES  # If none selected, default to all
     # Copy the full DataFrame
     df = df_full.copy()
-    # Calculate the average based on selected disciplines
-    df['Average'] = df[selected_disciplines].mean(axis=1)
     # Select columns to display
-    columns_to_display = MODEL_INFO + selected_disciplines + ['Average']
+    columns_to_display = MODEL_INFO + selected_disciplines
     df = df[columns_to_display]
-    # Sort by Average descending
-    df = df.sort_values(by='Average', ascending=False)
     return df
 
 # Function to convert scores to two decimal places
@@ -229,7 +221,7 @@ with block:
             with gr.Row():
                 with gr.Column():
                     model_name_textbox = gr.Textbox(
-                        label="**Model name**", placeholder="Required field"
+                        label="Model name", placeholder="Required field"
                     )
                     revision_name_textbox = gr.Textbox(
                         label="Revision Model Name (Optional)", placeholder="GPT4V"
@@ -237,13 +229,13 @@ with block:
 
                 with gr.Column():
                     model_link = gr.Textbox(
-                        label="**Project Page/Paper Link**", placeholder="Required field"
+                        label="Project Page/Paper Link", placeholder="Required field"
                     )
                     team_name = gr.Textbox(
                         label="Your Team Name (If left blank, it will be user upload)", placeholder="User Upload"
                     )
                     contact_email = gr.Textbox(
-                        label="E-Mail (**Will not be displayed**)", placeholder="Required field"
+                        label="E-Mail (Will not be displayed)", placeholder="Required field"
                     )
 
             with gr.Column():