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import streamlit as st | |
from apps.utils import read_markdown | |
from streamlit_tensorboard import st_tensorboard | |
from .utils import Toc | |
def app(state=None): | |
toc = Toc() | |
st.info("Welcome to our Multilingual-VQA demo. Please use the navigation sidebar to move to our demo, or scroll below to read all about our project. π€") | |
st.header("Table of contents") | |
toc.placeholder() | |
toc.header("Introduction and Motivation") | |
st.write(read_markdown("intro/intro.md")) | |
toc.subheader("Novel Contributions") | |
st.write(read_markdown("intro/contributions.md")) | |
toc.header("Methodology") | |
toc.subheader("Pre-training") | |
st.write(read_markdown("pretraining/intro.md")) | |
# col1, col2 = st.beta_columns([5,5]) | |
st.image( | |
"./misc/article/Multilingual-VQA.png", | |
caption="Masked LM model for Image-text Pre-training.", | |
) | |
toc.subsubheader("MLM Dataset") | |
st.write(read_markdown("pretraining/data.md")) | |
toc.subsubheader("MLM Model") | |
st.write(read_markdown("pretraining/model.md")) | |
toc.subsubheader("MLM Training Logs") | |
st_tensorboard(logdir='./logs/pretrain_logs', port=6006) | |
toc.subheader("Finetuning") | |
toc.subsubheader("VQA Dataset") | |
st.write(read_markdown("finetuning/data.md")) | |
toc.subsubheader("VQA Model") | |
st.write(read_markdown("finetuning/model.md")) | |
toc.subsubheader("VQA Training Logs") | |
st_tensorboard(logdir='./logs/finetune_logs', port=6007) | |
toc.header("Challenges and Technical Difficulties") | |
st.write(read_markdown("challenges.md")) | |
toc.header("Limitations") | |
st.write(read_markdown("limitations.md")) | |
toc.header("Conclusion, Future Work, and Social Impact") | |
toc.subheader("Conclusion") | |
st.write(read_markdown("conclusion_future_work/conclusion.md")) | |
toc.subheader("Future Work") | |
st.write(read_markdown("conclusion_future_work/future_work.md")) | |
toc.subheader("Social Impact") | |
st.write(read_markdown("conclusion_future_work/social_impact.md")) | |
toc.header("References") | |
st.write(read_markdown("references.md")) | |
toc.header("Checkpoints") | |
st.write(read_markdown("checkpoints/checkpoints.md")) | |
toc.subheader("Other Checkpoints") | |
st.write(read_markdown("checkpoints/other_checkpoints.md")) | |
toc.header("Acknowledgements") | |
st.write(read_markdown("acknowledgements.md")) | |
toc.generate() |