Update app.py

app.py

@@ -1,7 +1,5 @@
 from transformers import BlipProcessor, BlipForConditionalGeneration
 from PIL import Image
-import pandas as pd
-import numpy as np
 import gradio as gr
 import tempfile
 import os
@@ -41,7 +39,6 @@ def generate_keywords(caption):
     Returns:
         list: A list of single-word keywords.
     """
-    # Example simple keyword extraction (use a more sophisticated method if needed)
     words = caption.split()
     keywords = list(set(words))[:50]  # Take unique words and limit to 50
     return keywords
@@ -65,7 +62,6 @@ def process_images(image_files):
         caption = generate_image_caption(image)
         if caption:
             keywords = generate_keywords(caption)
-            # Ensure the title is within the 70 to 100 characters range
             title = caption if 70 <= len(caption) <= 100 else caption[:100]
             metadata.append({
                 'filename': filename,
@@ -84,13 +80,13 @@ def process_images(image_files):
             keywords = ','.join(data['keywords'])
             writer.writerow([filename, title, keywords])
     
-    return [Image.open(img_file.name) for img_file in image_files], csv_file_path
+    return [Image.open(image_file.name) for image_file in image_files], csv_file_path
 
 # Define Gradio interface
 iface = gr.Interface(
     fn=process_images,
     inputs=[
-        gr.Files(label="Upload Image Files", type="file", multiple=True)
+        gr.File(label="Upload Image Files", type="file", multiple=True)
     ],
     outputs=[
         gr.Gallery(label="Processed Images"),