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# Read
import streamlit as st
import sys,os
sys.path.append(f'{os.getcwd()}/utils')
from utils.data_users import get_developer_page_layout,get_product_dev_page_layout
print(os.getcwd())
# st.write(st.session_state.user_group)
USER_GROUPS = ["Developer", "Manager", "Practitioner"]
st.set_page_config(layout="wide")
if 'user_group' not in st.session_state:
index_tmp = 0
else:
index_tmp = USER_GROUPS.index(st.session_state['user_group'])
#Sidebar for USER GROUPS
st.sidebar.title("USER GROUPS")
backend = st.sidebar.selectbox(
"Select User-Group ", USER_GROUPS, index=index_tmp
)
st.session_state['user_group'] = backend
# # with st.sidebar:
# st.sidebar.title("🎈Explore Data Panel")
st.title("Explore Data Panel for OCT Image Analysis")
st.write(
"""
##
Examining the data is the key factor for better understanding of the AI system.Therefore,this panel introduces deta-centric approach by providing details regarding forllowing aspect of the data .
""")
list_test = """<ul>
<li>Data Source Information: This tab contains information regarding following aspect of the data:
modality,format, domain, ethical considerations including license and data version. </li>
<li>Exploratory Data Stats: This tab includes exploratory data analysis info covering following aspects: train/validation/test data division,summary statistics, sample visualization from each category.</li>
<li>Data Onboarding: This tab provides details of data pre-processing and post-processing steps applied over the dataset before traning, and data augmentations.</li>
</ul>"""
st.markdown(list_test, unsafe_allow_html=True)
if backend == "Developer":
get_product_dev_page_layout()
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