add keras model

.gitignore

@@ -4,5 +4,4 @@ venv
 __pycache__/
 *.tf
 data
-*.keras
 *.csv

src/main.py

@@ -6,9 +6,10 @@ import paho.mqtt.client as mqtt
 
         
 def main():
-    rtu_data_pipeline = RTUPipeline(scaler_path="rtu/models/scaler_1.pkl")
+    rtu_data_pipeline = RTUPipeline(scaler_path="src/rtu/models/scaler_1.pkl")
+    print(rtu_data_pipeline.scaler)
     rtu_anomalizer = RTUAnomalizer(
-        prediction_model_path="rtu/models/lstm_4rtu_smooth_02.keras",
+        prediction_model_path="src/rtu/models/lstm_4rtu_smooth_02.keras",
         clustering_model_paths=[
             "rtu/models/kmeans_model1.pkl",
             "rtu/models/kmeans_model2.pkl",
@@ -36,7 +37,6 @@ def main():
     
     
 if __name__=='__main__':
-    # 
     main()
    
     

src/rtu/RTUPipeline.py

@@ -66,7 +66,7 @@ class RTUPipeline:
         self.df = pd.DataFrame(columns = self.column_names)
 
     def get_scaler(self, scaler_path):
-        return scaler_path
+        return joblib.load(scaler_path)
 
     def get_window(self, df):
         len_df = np.len(df)