main_page.py

import os
import streamlit as st
import pandas as pd
import numpy as np

from st_pages import Page, show_pages, Section, add_indentation
from PIL import Image
#from utils import authenticate_drive



##################################################################################
#                              PAGE CONFIGURATION                                #
##################################################################################

st.set_page_config(layout="wide")
#add_indentation()




##################################################################################
#                              GOOGLE DRIVE CONNEXION                            #
##################################################################################

# if ["drive_oauth"] not in st.session_state:
#     st.session_state["drive_oauth"] = authenticate_drive()

# drive_oauth = st.session_state["drive_oauth"]




##################################################################################
#                                   TITLE                                        #
##################################################################################


st.image("images/AI.jpg")
st.markdown(" ")

col1, col2 = st.columns([0.65,0.35], gap="medium")

with col1:
    st.title("AI and Data Science Examples")
    st.subheader("HEC Paris, 2023-2024")
    st.markdown("""**Course provided by Shirish C. SRIVASTAVA** <br>
                **Hi! PARIS Engineering team**: Laurène DAVID, Salma HOUIDI and Maeva N'GUESSAN""", unsafe_allow_html=True)
#st.markdown("in collaboration with Hi! PARIS engineers: Laurène DAVID, Salma HOUIDI and Maeva N'GUESSAN")

with col2:
#Hi! PARIS collaboration mention
    st.markdown("  ")
    st.markdown("  ")
    st.markdown("  ")
    image_hiparis = Image.open('images/hi-paris.png')
    st.image(image_hiparis, width=150)
    
    url = "https://www.hi-paris.fr/"
    #st.markdown("This app was funded by the Hi! PARIS Center")
    st.markdown("""###### **Made in collaboration with [Hi! PARIS](%s)** """ % url, unsafe_allow_html=True)


st.markdown(" ")
st.divider()


# #Hi! PARIS collaboration mention
# st.markdown("  ")
# image_hiparis = Image.open('images/hi-paris.png')
# st.image(image_hiparis, width=150)
# url = "https://www.hi-paris.fr/"
# st.markdown("**The app was made in collaboration with [Hi! PARIS](%s)**" % url)




##################################################################################
#                              DASHBOARD/SIDEBAR                                 #
##################################################################################


# AI use case pages
show_pages(
    [
        Page("main_page.py", "Home Page", "🏠"),
        Section(name=" ", icon=""),
        Section(name=" ", icon=""),
        
        Section(name="Machine Learning", icon="1️⃣"),
            Page("pages/supervised_unsupervised_page.py", "1| Supervised vs Unsupervised 🔍", ""), 
            Page("pages/timeseries_analysis.py", "2| Time Series Forecasting 📈", ""),
            Page("pages/recommendation_system.py", "3| Recommendation systems 🛒", ""),
        
        Section(name="Natural Language Processing", icon="2️⃣"),
            Page("pages/topic_modeling.py", "1| Topic Modeling 📚", ""),
            Page("pages/sentiment_analysis.py", "2| Sentiment Analysis 👍", ""),
        
        Section(name="Computer Vision", icon="3️⃣"),
            Page("pages/image_classification.py", "1| Image Classification 🖼️", ""),
            Page("pages/object_detection.py", "2| Object Detection 📹", ""),

        Page("pages/go_further.py", "🚀 Go further")
    ]
)



##################################################################################
#                               PAGE CONTENT                                     #
##################################################################################


st.header("About the app")


st.info("""The **AI and Data Science Examples** app was created as a tool to introduce students to the field of Data Science by showcasing real-life applications of AI.
        It includes use cases using traditional Machine Learning algorithms on structured data, as well as models that analyze unstructured data (text, images,...).""")

st.markdown(" ")

st.markdown("""The app is structured into three sections:
- 1️⃣ **Machine Learning**: This first section covers use cases where structured data (data in a tabular format) is fed to an AI model.
            You will find pages on *Supervised/Unsupervised Learning*, *Time Series Forecasting* and AI powered *Recommendation Systems*.
- 2️⃣ **Natural Language Processing** (NLP): This second section showcases AI applications where large amounts of text data is analyzed using Deep Learning models.
            Pages on *Topic Modeling* and *Sentiment Analysis*, which are types of NLP models, can be found in this section.
- 3️⃣ **Computer Vision**: This final section covers a sub-field of AI called Computer Vision which deals with image/video data.
    The field of Computer Vision includes *Image classification* and *Object Detection*, which are both featured in this section.
            """)

st.image("images/ML_domains.png", 
         caption="""This figure showcases a selection of sub-fields in Artificial Intelligence, such as traditional 
                    Machine Learning, NLP, Computer Vision and Robotics.""")


# st.markdown(" ")
# st.markdown(" ")
# st.markdown("## Want to learn more about AI ?")
# st.markdown("""**Hi! PARIS**, a multidisciplinary center on Data Analysis and AI founded by Institut Polytechnique de Paris and HEC Paris, 
#             hosts every year a **Data Science Bootcamp** for students of all levels.""")