Update app.py

app.py

@@ -1,22 +1,41 @@
 import streamlit as st
 import pandas as pd
 
-def display_csv(file_path):
+def display_csv(file_path, columns_to_display):
     # Load the CSV file using pandas
     df = pd.read_csv(file_path)
-    # Display the dataframe as a table
-    st.write(df, height=500, width=1000)  # Adjust height and width as needed
+    # Select only the specified columns
+    df_selected_columns = df[columns_to_display]
+    # Display the selected columns as a table
+    st.write(df_selected_columns, height=500, width=1000, unsafe_allow_html=True)
 
 def main():
     # Hardcoded file path
     file_path = "merged-averaged-model_timings_2.1.0_12.1_NVIDIA_A10G_False.csv"
+    # Columns to display
+    columns_to_display = [
+        "model_name", "pretrained", "avg_score", "image_time", "text_time", 
+         "image_shape", "text_shape", 
+        "output shape", 
+        "params (M)", "FLOPs (B)"
+    ]  # Specify the columns you want to display
     
     # Add a text caption
-    st.header("CLIP benchmarks - retrieval and inference")
-    st.write("CLIP benchmarks for inference and retrieval performance. Image size, context length and output dimensions are also presented. A10G, CUDA 12.1, Torch 2.1.0")
+    st.header("CSV Viewer")
+    st.write("This app displays the contents of selected columns from a CSV file.")
+    
+    # Call the display_csv function with the hardcoded file path and selected columns
+    display_csv(file_path, columns_to_display)
 
-    # Call the display_csv function with the hardcoded file path
-    display_csv(file_path)
+    # Custom CSS to make the app full screen
+    st.markdown("""
+    <style>
+    .reportview-container {
+        width: 100%;
+        height: 100%;
+    }
+    </style>
+    """, unsafe_allow_html=True)
 
 if __name__ == "__main__":
     main()