kdexd commited on
Commit
8f84007
1 Parent(s): eb66921

Update app.py

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Files changed (1) hide show
  1. app.py +10 -18
app.py CHANGED
@@ -16,15 +16,12 @@ def gen_show_caption(sub_prompt=None, cap_prompt=""):
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  st.markdown(
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  f"""
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  <style>
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- red{{
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- color:#c62828
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- }}
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- blue{{
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- color:#2a72d5
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- }}
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  </style>
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- #### <red> r/{subreddit} </red> <blue> {cap_prompt} </blue> {caption}
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  """,
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  unsafe_allow_html=True,
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  )
@@ -65,7 +62,7 @@ cap_prompt = st.sidebar.text_input("Write the start of your caption below", valu
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  _ = st.sidebar.button("Regenerate Caption")
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- st.sidebar.title("Advanced Options:")
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  num_captions = st.sidebar.select_slider(
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  "Number of Captions to Predict", options=[1, 2, 3, 4, 5], value=1
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  )
@@ -76,15 +73,6 @@ nuc_size = st.sidebar.slider(
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  value=0.8,
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  step=0.05,
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  )
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- st.sidebar.markdown(
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- """
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- *Please note that this model was explicitly not trained on images of people, and as a result is not designed to caption images with humans.
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-
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- This demo accompanies our paper RedCaps.
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-
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- Created by Karan Desai, Gaurav Kaul, Zubin Aysola, Justin Johnson
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- """
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- )
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  # ----------------------------------------------------------------------------
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  virtexModel.model.decoder.nucleus_size = nuc_size
@@ -113,8 +101,12 @@ st.markdown("""
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  Caption your own images or try out some of our sample images.
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  You can also generate captions as if they are from specific subreddits,
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  as if they start with a particular prompt, or even both.
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-
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  Tweet your results with `#redcaps`!
 
 
 
 
 
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  """)
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  _, center, _ = st.columns([1, 18, 1])
 
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  st.markdown(
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  f"""
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  <style>
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+ red {{ color:#c62828; font-size: 1.5rem }}
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+ blue {{ color:#2a72d5; font-size: 1.5rem }}
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+ remaining {{ color: black; font-size: 1.5rem }}
 
 
 
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  </style>
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+ - <red> r/{subreddit} </red> <blue> {cap_prompt} </blue><remaining> {caption} </remaining>
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  """,
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  unsafe_allow_html=True,
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  )
 
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  _ = st.sidebar.button("Regenerate Caption")
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+ st.sidebar.title("Advanced Options")
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  num_captions = st.sidebar.select_slider(
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  "Number of Captions to Predict", options=[1, 2, 3, 4, 5], value=1
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  )
 
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  value=0.8,
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  step=0.05,
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  )
 
 
 
 
 
 
 
 
 
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  # ----------------------------------------------------------------------------
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  virtexModel.model.decoder.nucleus_size = nuc_size
 
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  Caption your own images or try out some of our sample images.
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  You can also generate captions as if they are from specific subreddits,
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  as if they start with a particular prompt, or even both.
 
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  Tweet your results with `#redcaps`!
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+
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+ **Note:** This model was not trained on images of people,
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+ hence may not generate accurate captions describing humans.
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+ For more details, visit [redcaps.xyz](https://redcaps.xyz) check out
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+ our [NeurIPS 2021 paper](https://openreview.net/forum?id=VjJxBi1p9zh).
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  """)
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  _, center, _ = st.columns([1, 18, 1])