Update app.py

app.py

@@ -19,40 +19,39 @@ class_names = [    "Speed limit (20 km/h)",
     "End of speed limit (80 km/h)",
     "Speed limit (100 km/h)",
     "Speed limit (120 km/h)",
-    "No overtaking",
-    "No overtaking vehicles over 3.5 metric tons",
-    "Priority at next intersection",
+    "No passing",
+    "No passing veh over 3.5 tons",
+    "Right-of-way at intersection",
+    "Priority road",
     "Yield",
-    "Stop",
-    "No entry",
     "No vehicles",
-    "No vehicles except motorcycles",
-    "Only motorcycles allowed",
-    "End of no vehicles",
-    "Restriction ends",
-    "Dangerous curve to the left",
-    "Dangerous curve to the right",
+    "Veh > 3.5 tons prohibited",
+    "No entry",
+    "General caution",
+    "Dangerous curve left",
+    "Dangerous curve right",
     "Double curve",
     "Bumpy road",
     "Slippery road",
     "Road narrows on the right",
-    "Roadwork",
+    "Road work",
     "Traffic signals",
-    "Pedestrian crossing",
-    "School zone",
-    "Cycle path",
-    "Parking",
-    "No parking",
-    "No stopping",
-    "No pedestrians",
+    "Pedestrians",
+    "Children crossing",
+    "Bicycles crossing",
+    "Beware of ice/snow",
     "Wild animals crossing",
-    "End of all speed and passing limits",
+    "End speed + passing limits",
     "Turn right ahead",
     "Turn left ahead",
     "Ahead only",
     "Go straight or right",
     "Go straight or left",
-    "Keep right"]  # Update this with your classes
+    "Keep right",
+    "Keep left",
+    "Roundabout mandatory",
+    "End of no passing",
+    "End no passing veh > 3.5 tons"]  # Update this with your classes
 
 # Preprocessing function
 def preprocess_image(image):
@@ -77,7 +76,7 @@ def classify_image(image):
     # Get the class name
     class_name = class_names[predicted_class]
     
-    return f"Predicted Class: {predicted_class}"
+    return f"Predicted Class: {class_name[predicted_class]}"
 
 # Create Gradio interface
 interface = gr.Interface(