app.py

import streamlit as st
import pandas as pd
import pickle

st.title("predict Phone Proces")

#import 
svr1 = 'svr.pkl'
sv = pickle.load(open(svr1, 'rb'))

st.write('Insert feature to predict')
Ratings = st.slider(label='Ratings', min_value=0, max_value=5, value=4, step=1)
Prices = st.slider(label='Prices', min_value=0, max_value=68000, value=11999, step=1)
Ram  = st.selectbox(label='Ram (GB)', options=['0', '1'])
Rom = st.slider(label='Rom(GB)', min_value=0, max_value=200, value=42, step=1)
ScreenSize = st.selectbox(label='Screen Size(Inches)', options=['0', '1'])
FirstCam = st.slider(label='First Cam (MP)', min_value=100000.0, max_value=999999.0, value=420000.0, step=0.01)
SecondCam = st.slider(label='Second Cam  (MP)', min_value=0.0, max_value=99.9, value=42.0, step=0.1)
ThirdCam = st.slider(label='Third Cam  (MP)', min_value=0, max_value=999, value=42, step=1)
FourthCam = st.selectbox(label='Fourth Cam  (MP)', options=['0', '1'])
FrontCam = st.selectbox(label='Front Cam  (MP)', options=['0', '1'])
Battery= st.slider(label='Batery  (mAh)', min_value=0, max_value=999, value=42, step=1)



# color = st.number_input(label='Colour', min_value=240, max_value=255, value=245, step=1)

# convert into dataframe

data = pd.DataFrame({'Ratings': [Ratings],
                'Prices': [Prices],
                'Ram ':[Ram],
                'Rom': [Rom],
                'ScreenSize': [ScreenSize],
                'FirstCam ': [FirstCam],
                'SecondCam': [SecondCam],
                'ThirdCam': [ThirdCam],
                'FourthCam': [FourthCam],
                'FrontCam': [FrontCam],
                'Battery': [Battery]})

# model predict
Phone_price = svr1.predict(data).tolist()[0]

# interpretation
st.write('Predition Result: ')
if Phone_price == 0:
    st.text('Mahal Jon')
else:
    st.text('Sikat')