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app.py
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app.py
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import streamlit as st
import pickle
import numpy as np
pipe = pickle.load(open('model.pkl', 'rb'))
st.title('Car Price Predictor')
km_driven = st.number_input('Enter Km driven')
selected_fuel_type = st.selectbox('Select fuel type', ['Diesel', 'Petrol'])
selected_seller_type = st.selectbox(
'Select seller type', ['Individual', 'Dealer'])
selected_transmission = st.selectbox(
'Select transmission', ['Manual', 'Automatic'])
selected_owner = st.selectbox('Select owner', [
'First Owner', 'Second Owner', 'Third Owner', 'Fourth & Above Owner'])
mileage = st.number_input('Enter mileage km/l')
engine = st.number_input('Enter engine cc')
max_power = st.number_input('Max Power in bhp')
seats = st.number_input('Number of seats')
purchase_year = st.number_input('Purchase Year')
brands = ['Maruti', 'Hyundai', 'Mahindra', 'Tata', 'Honda', 'Ford', 'Toyota',
'Chevrolet', 'Renault', 'Volkswagen', 'Nissan', 'Skoda', 'Datsun']
selected_brand = st.selectbox('Select brand', brands)
if st.button('Predict Price'):
input_query = np.array([[km_driven, selected_fuel_type, selected_seller_type, selected_transmission,
selected_owner, mileage, engine, max_power, seats, 2020-purchase_year, selected_brand]])
price = pipe.predict(input_query)[0]
st.header(f"Your Extimated Price: {int(price)}")