Update app.py

app.py

@@ -6,13 +6,7 @@ from tensorflow.keras.models import load_model
 
 
 
-# HF_TOKEN = os.getenv("HF_TOKEN")
-# hf_writer = gr.HuggingFaceDatasetSaver(HF_TOKEN, "weather-madrid-flags")
-
-def predict_energy(f1,f2,f3,f4,f5,f6,f7,f8,f9,f10,f11,f12,f13):
-    # input_feature = [f1,f2,f3,f4,f5,f6,f7,f8,f9,f10,f11,f12,f13]
-    # if f0 is not None: 
-    #     if f= == "Custom LSTM":      
+def predict_energy(f1,f2,f3,f4,f5,f6,f7,f8,f9,f10,f11,f12,f13):    
     
     weather_input = [f1,f2,f3,f4,f5,f6]
     history_input =[f7,f8,f9,f10,f11,f12,f13]
@@ -25,8 +19,6 @@ def predict_energy(f1,f2,f3,f4,f5,f6,f7,f8,f9,f10,f11,f12,f13):
     input_feature = np.concatenate((scaled_weather_input_array[0],history_input_array[0]))
     
     model = load_model('history_7_future_1.h5')
-    # dtc = load('dtc_model.sav')
-    # xgb = load('xgb_model.sav')
 
     output = model.predict(input_feature.reshape(1,1,-1))
     output = output[0][0]
@@ -63,13 +55,8 @@ weather_predictor_app = gr.Interface(fn=predict_energy,
                                       examples = [[2,23,3.93,0.85,2.75,0,0.428821,0.507056,0.658782,0.722878,0.694360,0.657011,0.587121],
                                                   [8,15,23.34,0.45,5.32,0,0.341136,0.337360,0.332931,0.336212,0.338439,0.327198,0.316899],
                                                   [12,8,2.10,0.96,1.34,0.0,0.327180,0.278838,0.253315,0.247601,0.262393,0.326879,0.458636]],
-                                                 # ["Random Forest", 37,28,18,7,4,-2,43,18,4,1019,1016,1010,31,29,16,29,13,0,6,244,2015,7],
-                                                 # ["XGBoost", 16,12,8,11,7,4,94,69,52,1014,1012,1009,10,10,10,14,5,0,5,35,2004,10]],
-                                     title = "Energy Consumption Prediction (London)",
+                                     title = "Energy Consumption Prediction using Custom LSTM (London)",
                                      description="Enter parameters using sliders provided to predict the energy consumption.")
-                                     # theme = "darkhuggingface", 
-                                     # css="footer {visibility: hidden}"
-                                     # flagging_callback=hf_writer
 
 
 weather_predictor_app.launch(share=True)