Update app.py

app.py

@@ -151,45 +151,30 @@ else:
 
 
 
-st.write("selected_images inner loop:", selected_images)
-st.write("selected_file_names inner loop:", selected_file_names)
-st.write("results inner loop:", results)
+st.write("selected_images info:", selected_images)
+st.write("selected_file_names info:", selected_file_names)
+st.write("results info:", results)
         
 
-    
 # Generate DataFrame button
 if st.button("Generate DataFrame") and selected_images:
     # Create a list to store data for DataFrame
     df_data = []
 
     # Iterate through selected images to gather data
-    for image, file_name, result in zip(selected_images, selected_file_names, results):
-        # Extract image metadata
-
-        #st.write("selected_images inner loop:", selected_images)
-        #st.write("selected_file_names inner loop:", selected_file_names)
-        #st.write("results inner loop:", results)
-        
-        size_kb = image.size[0] * image.size[1] / 1024.0  # Calculating size in KB
-        timestamp = datetime.datetime.now()  # Current timestamp
-        color_type = "Color" if image.mode == 'RGB' else "Grayscale"
-        
+    for result in results:
         # Extract predicted emotions and scores
         emotion_scores = {res["label"].split("_")[-1].capitalize(): res["score"] for res in result}
 
-        # Append image metadata and emotion scores to the list
+        # Append emotion scores to the list
         df_data.append({
-            "Neutral": f"{emotion_scores.get('neutral', 0.0):.4f}",
-            "Happy": f"{emotion_scores.get('happy', 0.0):.4f}",
-            "Sad": f"{emotion_scores.get('sad', 0.0):.4f}",
-            "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}",  # Add this line if 'Fear' is a possible label
-            "File Name": file_name,
-            "Size (KB)": size_kb,
-            "Timestamp": timestamp.strftime('%Y-%m-%d %H:%M:%S'),  # Format timestamp
-            "Color Type": color_type
+            "Neutral": f"{emotion_scores.get('Neutral', 0.0):.4f}",
+            "Happy": f"{emotion_scores.get('Happy', 0.0):.4f}",
+            "Sad": f"{emotion_scores.get('Sad', 0.0):.4f}",
+            "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}"  # Add this line if 'Fear' is a possible label
         })
 
     # Create DataFrame