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from home import read_markdown_file
import streamlit as st
def app():
#st.title("Examples & Applications")
st.markdown("<h1 style='text-align: center; color: #9900FF;'> Examples & Applications </h1>", unsafe_allow_html=True)
st.markdown("<h2 style='text-align: center; color: #874c91; font-weight:bold;'> Complex Queries -Image Retrieval </h2>", unsafe_allow_html=True)
st.write(
"""
Even though we trained the Italian CLIP model on way less examples(~1.4M) than the original
OpenAI's CLIP (~400M), our training choices and quality datasets led to impressive results!
Here, we present some of **the most impressive text-image associations** learned by our model.
Remember you can head to the **Text to Image** section of the demo at any time to test your own🤌 Italian queries!
"""
)
st.markdown("### 1. Actors in Scenes")
st.markdown("These examples were taken from the CC dataset")
st.subheader("Una coppia")
st.markdown("*A couple*")
st.image("static/img/examples/couple_0.jpeg")
col1, col2 = st.beta_columns(2)
col1.subheader("Una coppia con il tramonto sullo sfondo")
col1.markdown("*A couple with the sunset in the background*")
col1.image("static/img/examples/couple_1.jpeg")
col2.subheader("Una coppia che passeggia sulla spiaggia")
col2.markdown("*A couple walking on the beach*")
col2.image("static/img/examples/couple_2.jpeg")
st.subheader("Una coppia che passeggia sulla spiaggia al tramonto")
st.markdown("*A couple walking on the beach at sunset*")
st.image("static/img/examples/couple_3.jpeg")
st.markdown("### 2. Dresses")
st.markdown("These examples were taken from the Unsplash dataset")
col1, col2 = st.beta_columns(2)
col1.subheader("Un vestito primaverile")
col1.markdown("*A dress for the spring*")
col1.image("static/img/examples/vestito1.png")
col2.subheader("Un vestito autunnale")
col2.markdown("*A dress for the autumn*")
col2.image("static/img/examples/vestito_autunnale.png")
#st.markdown("## Image Classification")
st.markdown("<h2 style='text-align: center; color: #874c91; font-weight:bold;'> Zero Shot Image Classification </h2>", unsafe_allow_html=True)
st.markdown("We report this cool example provided by the "
"[DALLE-mini team](https://github.com/borisdayma/dalle-mini). "
"Is the DALLE-mini logo an *avocado* or an armchair (*poltrona*)?")
st.image("static/img/examples/dalle_mini.png")
st.markdown("It seems it's half an armchair and half an avocado! We thank the DALLE-mini team for the great idea :)")
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