app.py

# # import numpy as np
# # import os 
# # import matplotlib.pyplot as plt

# # import tensorflow as tf 
# # from tqdm import tqdm 
# import pickle
# # load the model from disk
# loaded_model = pickle.load(open(https://huggingface.co/spaces/ashutoshsharma58/project1/blob/main/finalized_model.sav, 'rb'))
# # result = loaded_model.score(X_test, Y_test)
# # print(result)

import streamlit as st
from streamlit_option_menu import option_menu
import classifier


st.write('### Vehicle number plate recognition CNN')
st.write('##### This page is created by Himanshu')
st.markdown('---')


selected = option_menu(None, [ "Classifier"], 
    icons=['house', 'gear-fill'], 
    menu_icon="cast", default_index=0, orientation="vertical",
    styles={
        "icon": {"color": "yellow", "font-size": "20px"}, 
        "nav-link": {"font-size": "20px", "text-align": "left", "margin":"1px", "--hover-color": "#eee"},
        "nav-link-selected": {"background-color": "grey"}
    }
)
    
selected
    

if selected == 'Classifier':
    classifier.run()

#elif selected == 'Home':
#   home.run()