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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 :)") | |