import streamlit as st
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import sklearn
from io import StringIO

# main page

custom_css = """
<style>
    html, body, [data-testid="stAppViewContainer"] {
        background:url('https://images.pexels.com/photos/1435752/pexels-photo-1435752.jpeg?auto=compress&cs=tinysrgb&w=600') no-repeat center center fixed;
        background-size: cover; /* Cover the entire screen */
        font-family: Arial, sans-serif;
        color: #333333;
    }
  </style>"""

# Apply custom CSS
st.markdown(custom_css, unsafe_allow_html=True)  


st.markdown('<div style="text-align: center"><h1>CLASSIFICATION MODEL</h1></div>', unsafe_allow_html=True)
st.markdown('<h2>Upload the Classification Dataset</h2>',unsafe_allow_html=True)
st.file_uploader(label="Choose a file to upload",type=["csv","xlsx","json","txt"])

options = ["Info About the DataSet", "Pre-Processing"]
selection = st.pills("Directions", options, selection_mode="multi")