Update app.py

app.py

@@ -1,3 +1,4 @@
+```python
 import gradio as gr
 from ultralytics import YOLO
 from PIL import Image
@@ -22,7 +23,6 @@ def predict(image):
     
     if class_confidences:
         lines = []
-        # Sort classes by their max confidence (highest first)
         sorted_classes = sorted(
             class_confidences.items(),
             key=lambda x: max(x[1]),
@@ -30,17 +30,11 @@ def predict(image):
         )
         
         for class_name, confidences in sorted_classes:
-            count = len(confidences)
-            avg_conf = round(sum(confidences) / count, 2)
+            avg_conf = round(sum(confidences) / len(confidences), 2)
             max_conf = round(max(confidences), 2)
-            
-            if count > 1:
-                lines.append(f"• {class_name} ({count}x) — avg: {avg_conf}% | best: {max_conf}%")
-            else:
-                lines.append(f"• {class_name} — {max_conf}%")
+            lines.append(f"• {class_name} — avg: {avg_conf}% | best: {max_conf}%")
         
-        total = sum(len(v) for v in class_confidences.values())
-        result_text = f"Detected {total} object(s) in {len(class_confidences)} class(es):\n\n" + "\n".join(lines)
+        result_text = "\n".join(lines)
     else:
         result_text = "No detection"
     
@@ -57,4 +51,5 @@ demo = gr.Interface(
     title="YOLOv8 Detection",
     description="Upload an image and detect objects"
 )
-demo.launch()
+demo.launch()
+```