Update app.py

app.py

@@ -1,5 +1,4 @@
 import gradio as gr
-from gradio import inputs, outputs  # Import inputs and outputs from gradio
 import torch
 from PIL import Image
 import pandas as pd
@@ -9,12 +8,8 @@ from transformers import AutoTokenizer, AutoModelForCausalLM, AutoProcessor
 import tensorflow as tf
 import tensorflow_hub as hub
 import io
-import tempfile
 from sklearn.metrics.pairwise import cosine_similarity
-
-
-
-# Import logging module
+import tempfile  # Add this import
 import logging
 
 # Configure logging
@@ -85,7 +80,7 @@ def generate_caption(processor, model, image):
     logging.info('Finished generate_caption')
     return generated_caption
 
-
+# Function to save dataframe results to a CSV string for download
 def save_dataframe_to_csv(df):
     csv_buffer = io.StringIO()
     df.to_csv(csv_buffer, index=False)
@@ -134,10 +129,8 @@ def process_images_and_statements(image):
             'Final Combined Score': f"{final_score:.2f}%"  # Format as percentage with two decimal places
         }, ignore_index=True)
 
-    logging.info
     logging.info('Finished process_images_and_statements')
 
-    # Return the DataFrame directly as output (no need to convert to HTML)
     # Save results_df to a CSV file
     csv_results = save_dataframe_to_csv(results_df)
     
@@ -152,10 +145,10 @@ output_csv = gr.outputs.File(label="Download CSV")
 iface = gr.Interface(
     fn=process_images_and_statements,
     inputs=image_input,
-    outputs=[output_df, output_csv],
+    outputs=[output_df, output_csv],  # Include both the DataFrame and CSV file outputs
     title="Image Captioning and Image-Text Matching",
     theme='sudeepshouche/minimalist',
-    css=".output { flex-direction: column; } .output .outputs { width: 100%; }"
+    css=".output { flex-direction: column; } .output .outputs { width: 100%; }"  # Custom CSS
 )
 
-iface.launch()
+iface.launch()