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Update app.py
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'''
Author : Rupesh Garsondiya
github : @Rupeshgarsondiya
Organization : L.J University
'''
import http
import streamlit as st
from PIL import Image
from train import *
from test import *
# Centering the title using HTML and CSS
class Main:
def __init__(self) -> None:
pass
def run(self):
# Display the image from a URL
st.markdown(
"""
<style>
.img-rounded {
border-radius: 15px;
width: 400px; /* Adjust the width as needed */
}
</style>
<div style="text-align: center;">
<img src="https://sdmntprwestus.oaiusercontent.com/files/00000000-aa04-6230-837a-93950b632544/raw?se=2025-04-05T13%3A32%3A17Z&sp=r&sv=2024-08-04&sr=b&scid=44063bf6-cd40-5f19-a60b-d08902643aad&skoid=acefdf70-07fd-4bd5-a167-a4a9b137d163&sktid=a48cca56-e6da-484e-a814-9c849652bcb3&skt=2025-04-05T11%3A40%3A26Z&ske=2025-04-06T11%3A40%3A26Z&sks=b&skv=2024-08-04&sig=NT8Nf%2BV7/FeGHxin4ip87RagSYj6HCFOzSV%2BiOlkcOU%3D" alt="User Behavior" width="800" height="400"><br>""",
unsafe_allow_html=True
)
st.write()
st.write()
t = test()
t.predict_data()
st.markdown("[GitHub](https://github.com/Rupeshgarsondiya/User-behaviour-classification) | <a href='https://www.linkedin.com/in/rupesh-garsondiya-919817275/' target='_blank'>Linkedin</a>",unsafe_allow_html=True)
# Add a LinkedIn profile hyperlink using HTML
st.markdown("", unsafe_allow_html=True)
# Add copyright notice at the bottom
st.markdown("<hr>", unsafe_allow_html=True) # Horizontal line to separate content
st.markdown(
"<b><p style='text-align: center; font-size: 16px;'>&copy; 2024 Rupesh Garsondiya. All Rights Reserved.</p>",
unsafe_allow_html=True
)
if __name__ == "__main__":
st.markdown("<h1 style='text-align: center;'><b>User behaviour classification on user Behaviour Dataset</b></h1>", unsafe_allow_html=True)
st.markdown("<p ><b> - About this project :</b></p>",unsafe_allow_html=True)
st.write(' - This project is a simple web application that uses a machine learning model to classify user behavior into different categories.')
st.write(' - The model is trained on a dataset of user behavior and can be used to predict the behavior of a new user based on their mobile data.')
run_obj = Main()
run_obj.run()
else :
print("This is a Streamlit app. Please run it using `streamlit run app.py `") # noqa: E501