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import streamlit as st
import numpy as np
import pickle
import streamlit.components.v1 as components
from sklearn.preprocessing import LabelEncoder
le = LabelEncoder()
# Load the pickled model
def load_model():
return pickle.load(open('Waiter_tips_Prediction_linear.pkl', 'rb')) #change
# Function for model prediction
def model_prediction(model, features):
predicted = str(model.predict(features))
return predicted
def transform(text):
text = le.fit_transform(text)
return text[0]
def app_design():
# Add input fields for High, Open, and Low values
image = '43.png' #change
st.image(image, use_column_width=True)
st.subheader("Enter the following values:") #change
total_bill = st.number_input("Total Bill")
sex = st.selectbox("Sex",('Male','Female'))
if sex == 'Male':
sex = 1
else:
sex = 0
size = st.number_input("Size")
day = st.text_input("Day")
day = transform([day])
time = st.text_input("Time")
time = transform([time])
smoker = st.text_input("Smoker")
smoker = transform([smoker])
# Create a feature list from the user inputs
features = [[total_bill,sex,size,day,time,smoker]]
# Load the model
model = load_model()
# Make a prediction when the user clicks the "Predict" button
if st.button('Predict Tip'):
predicted_value = model_prediction(model, features)
st.success(f"The Tip is: {predicted_value}")
def about_hidevs():
components.html("""
<div>
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<p class="subtitle"><a class="link" href="https://hidevscommunity.wixsite.com/hidevs" target="__blank">Website</a>
<a class="link" href="https://www.youtube.com/@HidevsCommunity1307/" target="__blank">YouTube</a>
<a class="link" href="https://www.instagram.com/hidevs_community/" target="__blank">Instagram</a>
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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="Waiter tip Prediction",
page_icon=":chart_with_upwards_trend:",
)
st.title("Welcome to our Waiter Tip Prediction App!")
app_design()
st.header("About HiDevs Community")
about_hidevs()
if __name__ == '__main__':
main() |