Update app.py

app.py

@@ -148,6 +148,7 @@ else:
     st.error("Results list is empty.")
 
 
+
 # Generate DataFrame button
 if st.button("Generate DataFrame") and selected_images:
     # Create a list to store data for DataFrame
@@ -158,7 +159,7 @@ if st.button("Generate DataFrame") and selected_images:
         # Extract image metadata
         size_kb = image.size[0] * image.size[1] / 1024.0  # Calculating size in KB
         timestamp = datetime.datetime.now()  # Current timestamp
-        color_type = "Color" if len(image.getbands()) > 1 else "Grayscale"
+        color_type = "Color" if image.mode == 'RGB' else "Grayscale"
         
         # Extract predicted emotions and scores
         emotion_scores = {res["label"].split("_")[-1].capitalize(): res["score"] for res in result}
@@ -171,10 +172,10 @@ if st.button("Generate DataFrame") and selected_images:
             "Angry": f"{emotion_scores.get('Angry', 0.0):.4f}",
             "Disgust": f"{emotion_scores.get('Disgust', 0.0):.4f}",
             "Surprise": f"{emotion_scores.get('Surprise', 0.0):.4f}",
-            "Fear": f"{emotion_scores.get('Fear', 0.0):.4f}",
+            "Fear": f"{emotion_scores.get('Fear', 0.0):.4f}",  # Add this line if 'Fear' is a possible label
             "File Name": file_name,
             "Size (KB)": size_kb,
-            "Timestamp": timestamp,
+            "Timestamp": timestamp.strftime('%Y-%m-%d %H:%M:%S'),  # Format timestamp
             "Color Type": color_type
         })
 
@@ -183,3 +184,4 @@ if st.button("Generate DataFrame") and selected_images:
 
     # Display DataFrame
     st.write(df)
+