| import streamlit as st |
| import pandas as pd |
| import requests |
| import json |
|
|
| st.write(""" # Mobile Price-Range Prediction""") |
| st.sidebar.header("Choose Phone Specs") |
|
|
| def input_features(): |
| battery_power = st.sidebar.slider("battery power",500,2000,1000) |
| pix_height = st.sidebar.slider("pix height",0,2000,1000) |
| pix_width = st.sidebar.slider("pix width",0,2000,1000) |
| ram = st.sidebar.slider("ram",400,4000,2000) |
| data = {"battery_power":battery_power, |
| "px_height":pix_height, |
| "px_width":pix_width, |
| "ram":ram} |
| feats = pd.DataFrame(data,index=[0]) |
| return feats, data |
|
|
| feats, data = input_features() |
|
|
| st.subheader("Phone Specs") |
| st.write(feats) |
|
|
| if st.button("Result"): |
| res = requests.post(url = "http://0.0.0.0:8008/predict", data=json.dumps(data)).text |
| st.subheader(f"Predicted Price Range: {res}") |
