Update app.py

app.py

@@ -7,8 +7,7 @@ import pandas as pd
 # This line loads your entire model from the .keras file.
 model = tf.keras.models.load_model("adversarially_trained_model.keras")
 print("output_shape:", model.output_shape)           # e.g., (None, 5)
-CLASS_NAMES = [f'class_{i}' for i in range(23)]# Class names based on the attack mapping from the notebook
-print(CLASS_NAMES)
+CLASS_NAMES = ["normal", "dos", "probe", "r2l", "u2r"]
 
 def preprocess_single_record(record: dict, scaler, df_reference: pd.DataFrame) -> np.ndarray: