Update app.py

app.py

@@ -41,11 +41,15 @@ def get_model_predictions(data_aux, model):
         probabilities = (scores - scores.min()) / (scores.max() - scores.min())
     else:
         class_pred = model.predict([data_aux])[0]
-        probabilities = np.zeros(len(label_encoder.classes_))
+        probabilities = np.zeros(len(label_classes))
         probabilities[class_pred] = 1
 
+    # Add this check
+    if not hasattr(model, 'monotonic_cst'):
+        model.monotonic_cst = None
+
     top_index = np.argmax(probabilities)
-    return label_encoder.inverse_transform([top_index])[0], probabilities[top_index]
+    return label_classes[top_index], probabilities[top_index]
 
 def predict_alphabet(image):
     image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)