Update app.py

app.py

@@ -1,6 +1,7 @@
 import pandas as pd
 import gradio as gr
 
+# Create the dataset based on the table you provided
 data = {
     "Method": ["GPT-4o", "GPT-4o-mini", "Gemini-1.5-Pro", "Gemini-1.5-Flash", "Qwen2-VL-2B"],
     "MM Understanding & Reasoning": [57.90, 48.82, 46.67, 45.58, 40.59],
@@ -13,14 +14,20 @@ data = {
     "Remote Sensing Understanding": [22.85, 16.93, 17.07, 14.95, 12.56]
 }
 
+# Convert the dataset into a DataFrame
 df = pd.DataFrame(data)
 
+# Calculate the average score for each model across the different tasks
+df['Average Score'] = df.iloc[:, 1:].mean(axis=1)
+
+# Function to display the data in a Gradio interface
 def display_data():
     return df
 
+# Create the Gradio interface
 with gr.Blocks() as demo:
     gr.Markdown("# Model Performance Across Various Understanding Tasks")
-    gr.Markdown("This table shows the performance of different models across various tasks including OCR, chart understanding, video, medical imaging, and more.")
-    gr.Dataframe(value=df, label="Model Performance", interactive=False)
+    gr.Markdown("This table shows the performance of different models across various tasks including OCR, chart understanding, video, medical imaging, and more. An average score is also calculated for each model.")
+    gr.Dataframe(value=df, label="Model Performance with Average Scores", interactive=False)
 
 demo.launch()