import streamlit as st
from streamlit_extras.switch_page_button import switch_page

st.title("OneFormer")

st.success("""[Original tweet](https://twitter.com/mervenoyann/status/1739707076501221608) (December 26, 2023)""", icon="ℹ️")
st.markdown(""" """)

st.markdown("""
OneFormer: one model to segment them all? 🤯  
I was looking into paperswithcode leaderboards when I came across OneFormer for the first time so it was time to dig in! 
""")
st.markdown(""" """)

st.image("pages/OneFormer/image_1.jpeg", use_column_width=True)
st.markdown(""" """)

st.markdown("""OneFormer is a "truly universal" model for semantic, instance and panoptic segmentation tasks ⚔️  
What makes is truly universal is that it's a single model that is trained only once and can be used across all tasks 👇 
""")
st.markdown(""" """)

st.image("pages/OneFormer/image_2.jpeg", use_column_width=True)
st.markdown(""" """)

st.markdown("""
The enabler here is the text conditioning, i.e. the model is given a text query that states task type along with the appropriate input, and using contrastive loss, the model learns the difference between different task types 👇 
""")
st.markdown(""" """)

st.image("pages/OneFormer/image_3.jpeg", use_column_width=True)
st.markdown(""" """)

st.markdown("""Thanks to 🤗 Transformers, you can easily use the model!  
I have drafted a [notebook](https://t.co/cBylk1Uv20) for you to try right away 😊  
You can also check out the [Space](https://t.co/31GxlVo1W5) without checking out the code itself.
""")
st.markdown(""" """)

st.image("pages/OneFormer/image_4.jpeg", use_column_width=True)
st.markdown(""" """)

st.info("""
Ressources:  
[OneFormer: One Transformer to Rule Universal Image Segmentation](https://arxiv.org/abs/2211.06220) 
by Jitesh Jain, Jiachen Li, MangTik Chiu, Ali Hassani, Nikita Orlov, Humphrey Shi (2022)  
[GitHub](https://github.com/SHI-Labs/OneFormer)  
[Hugging Face documentation](https://huggingface.co/docs/transformers/model_doc/oneformer)""", icon="📚")

st.markdown(""" """)
st.markdown(""" """)
st.markdown(""" """)
col1, col2, col3 = st.columns(3)
with col1:
    if st.button('Previous paper', use_container_width=True):
        switch_page("MobileSAM")
with col2:
    if st.button('Home', use_container_width=True):
        switch_page("Home")
with col3:
    if st.button('Next paper', use_container_width=True):
        switch_page("VITMAE")