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import streamlit as st
import numpy as np
import pickle
import streamlit.components.v1 as components
# Load the pickled model
def load_model():
return pickle.load(open('bike_share_demand_pred_li.pkl', 'rb'))
# Function for model prediction
def model_prediction(model, features):
predicted = str(round(model.predict(features)[0][0]))
return predicted
def app_design():
# Add input fields for High, Open, and Low values
image = '3.png'
st.image(image, use_column_width=True)
st.subheader("Enter the following values:")
season = st.selectbox('Season',('Spring', 'Summer', 'Fall','Winter'))
if season == 'Spring':
season = 1
elif season == 'Summer':
season = 2
elif season == 'Fall':
season = 3
elif season == 'Winter':
season = 4
holiday = st.number_input('Holiday')
workingday = st.number_input('Workingday')
weather = st.number_input('Weather')
temp = st.number_input('Temp')
atemp = st.number_input('Atemp')
humidity = st.number_input('Humidity')
windspeed = st.number_input('Windspeed')
casual = st.number_input('Casual')
registered = st.number_input('Registered')
# Create a feature list from the user inputs
features = [[season, holiday, workingday, weather, temp, atemp, humidity, windspeed, casual, registered]]
# Load the model
model = load_model()
# Make a prediction when the user clicks the "Predict" button
if st.button('Predict Bike Demands'):
predicted_value = model_prediction(model, features)
st.success(f"The Bike demands are : {predicted_value[0]}")
def about_hidevs():
components.html("""
<div>
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</div>
""",
height=600)
def main():
# Set the app title and add your website name and logo
st.set_page_config(
page_title="Bike Sharing Demand Prediction",
page_icon=":chart_with_upwards_trend:",
)
st.title("Welcome to our Bike Sharing Demand Prediction App!")
app_design()
st.header("About HiDevs Community")
about_hidevs()
if __name__ == '__main__':
main()
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