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| import streamlit as st | |
| from apps.utils import read_markdown | |
| from .streamlit_tensorboard import st_tensorboard, kill_tensorboard | |
| from .utils import Toc | |
| def app(state=None): | |
| #kill_tensorboard() | |
| 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. 🤗 In case the sidebar isn't properly rendered, please change to a smaller window size and back to full screen.") | |
| st.header("Table of Contents") | |
| toc.placeholder() | |
| toc.header("Introduction and Motivation") | |
| st.info("**News**: Two days back, a paper using CLIP-Vision and BERT has been posted on arXiv! The paper uses LXMERT objectives and achieves 80% on the English VQAv2 dataset. It would be interesting to see how it performs on our multilingual dataset. Check it out here: https://arxiv.org/pdf/2107.06383.pdf") | |
| st.write(read_markdown("intro/intro_part_1.md")) | |
| with st.beta_expander("FasterRCNN Approach"): | |
| st.write(read_markdown("intro/faster_rcnn_approach.md")) | |
| st.write(read_markdown("intro/intro_part_2.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.write("Click on the expandable region to see the TensorBoard logs.") | |
| st.info("In case the TensorBoard logs are not displayed, please visit this link: https://huggingface.co/flax-community/multilingual-vqa-pt-ckpts/tensorboard") | |
| with st.beta_expander("MLM TensorBoard 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.write("Click on the expandable region to see the TensorBoard logs.") | |
| st.info("In case the TensorBoard logs are not displayed, please visit this link: https://huggingface.co/flax-community/multilingual-vqa-pt-60k-ft/tensorboard") | |
| with st.beta_expander("VQA TensorBoard Logs"): | |
| st_tensorboard(logdir='./logs/finetune_logs', port=6007) | |
| toc.header("Challenges and Technical Difficulties") | |
| st.write(read_markdown("challenges.md")) | |
| toc.header("Limitations and Bias") | |
| 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") | |
| toc.subheader("Papers") | |
| st.write(read_markdown("references/papers.md")) | |
| toc.subheader("Useful Links") | |
| st.write(read_markdown("references/useful_links.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() |