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import gradio as gr
import numpy as np
import pickle
from tensorflow.keras.models import load_model
model=load_model('Best_GRU_solar_insolation_model.keras')
with open('scaler.pkl','rb') as f:
scaler=pickle.load(f)
def is_leap_year(year):
return(year%4==0 and year%100!=0)or(year%400==0)
def is_valid_day(year,month,day):
days_in_month={1:31,2:28,3:31,4:30,5:31,6:30,7:31,8:31,9:30,10:31,11:30,12:31}
if month==2:
if is_leap_year(year):
return 1<=day<=29
else:
return 1<=day<=28
return 1<=day<=days_in_month.get(month,31)
def preprocess_input(year,month,day,hour):
day_sin=np.sin(2*np.pi*day/31)
day_cos=np.cos(2*np.pi*day/31)
month_sin=np.sin(2*np.pi*month/12)
month_cos=np.cos(2*np.pi*month/12)
hour_sin=np.sin(2*np.pi*hour/24)
hour_cos=np.cos(2*np.pi*hour/24)
input_data=np.array([year,day_sin,day_cos,month_sin,month_cos,hour_sin,hour_cos]).reshape(1,-1)
input_scaled=scaler.transform(input_data)
return np.expand_dims(input_scaled,axis=-1)
def predict_solar_insolation(year,month,day,hour):
if not(1<=month<=12):
return"Invalid month! Please enter a value between 1 and 12."
if not is_valid_day(year,month,day):
return f"Invalid day! Please enter a valid day for month {month}."
if not(0<=hour<24):
return"Invalid hour! Please enter a value between 0 and 23."
input_data=preprocess_input(year,month,day,hour)
prediction=model.predict(input_data)
return round(float(prediction[0][0]),3)if float(prediction[0][0])>10 else 0
app=gr.Interface(fn=predict_solar_insolation,
inputs=[gr.Number(label="Year"),
gr.Number(label="Month"),
gr.Number(label="Day"),
gr.Number(label="Hour")],
outputs="text")
app.launch() |