Update app.py

app.py

@@ -6,6 +6,7 @@ from sklearn.preprocessing import LabelEncoder, StandardScaler, OneHotEncoder
 from sklearn.impute import KNNImputer
 from sklearn.decomposition import PCA
 import pickle
+from tensorflow.keras.models import load_model
 
 
 
@@ -18,8 +19,9 @@ def predict(age, workclass, education, marital_status, occupation, relationship,
     "hours-per-week":[hours_per_week], "native-country":[native_country]}
     df = pd.DataFrame(data=columns)
     fixed_features = cleaning_features(df)
-    with open('ann_model.pkl', 'rb') as ann_model_file:
-        ann_model = pickle.load(ann_model_file)
+    # with open('ann_model.pkl', 'rb') as ann_model_file:
+    #     ann_model = pickle.load(ann_model_file)
+    ann_model = load_model('ann_model.h5')
     prediction = ann_model.predict(fixed_features)
     # prediction = 1
     return "Income >50K" if prediction == 1 else "Income <=50K"