app.py

import streamlit as st

from utils import load_model, generate

## Title and write
st.title("Butterfly GAN")
st.write(
    "Light-GAN model trained with 1000 butterfly images taken from the Smithsonian Museum collection."
)

## Sidebar
st.sidebar.subheader("This butterfly does not exist!.")
st.sidebar.image("assets/logo.png", width=200)
st.sidebar.caption(
    f"[Model](https://huggingface.co/ceyda/butterfly_cropped_uniq1K_512) and [Dataset](https://huggingface.co/datasets/huggan/smithsonian_butterflies_subset) used."
)
st.sidebar.caption(f"*Disclaimers:*")
st.sidebar.caption(
    "* This demo is a simplified version of the one created by [Ceyda Cinarel](https://github.com/cceyda) and [Jonathan Whitaker](https://datasciencecastnet.home.blog/) ([link](https://huggingface.co/spaces/huggan/butterfly-gan)) during the hackathon [HugGan](https://github.com/huggingface/community-events)."
)
st.sidebar.caption(
    "* Model based on [paper](https://openreview.net/forum?id=1Fqg133qRaI) *Towards Faster and Stabilized GAN Training for High-fidelity Few-shot Image Synthesis*."
)

## Load model
repo_id = "ceyda/butterfly_cropped_uniq1K_512"
version_model = "57d36a15546909557d9f967f47713236c8288838"
model_gan = load_model(repo_id, version_model)


n_mariposas = 4

## Function that generates butterflies and saves it as a state of the session
def run():
    with st.spinner("Generating, wait a little..."):
        ims = generate(model_gan, n_mariposas)
        st.session_state["ims"] = ims


if "ims" not in st.session_state:
    st.session_state["ims"] = None
    run()

ims = st.session_state["ims"]


run_boton = st.button(
    "Spawn butterflies.",
    on_click=run,
    help="Generate images.",
)

if ims is not None:
    cols = st.columns(n_mariposas)
    for j, im in enumerate(ims):
        i = j % n_mariposas
        cols[i].image(im, use_column_width=True)