at least ready

app.py

@@ -33,6 +33,10 @@ def predict_breed(image):
     predicted_class_index = np.argmax(predictions[0])
     predicted_class = unique_breeds[predicted_class_index]
     confidence = predictions[0][predicted_class_index] * 100  # Convert to percentage
+    
+    # Replace underscores with spaces in the class name
+    predicted_class = predicted_class.replace('_', ' ')
+    
     return image, f"{predicted_class} ({confidence:.2f}%)"
 
 # Create Gradio interface