update app.py

app.py

@@ -354,6 +354,9 @@ def predict_with_metadata(url):
         le_ar = music_avg_rating_le
         sound_type = "Music"
 
+    # 3️ Prétraitement seulement si durée ok
+    df_processed = preprocess_sound(df_raw)
+    
     # Supprimer les colonnes qui ne faisaient pas partie du training
     cols_to_remove = ["avg_rating", "num_downloads_class"]
     df_for_model = df_processed.drop(columns=[c for c in cols_to_remove if c in df_processed.columns])
@@ -365,8 +368,7 @@ def predict_with_metadata(url):
     pred_avg_rating_enc = model_ar.predict(df_for_model)[0]
     pred_avg_rating = le_ar.inverse_transform([pred_avg_rating_enc])[0]
 
-    # 3️ Prétraitement seulement si durée ok
-    df_processed = preprocess_sound(df_raw)
+