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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) |