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Parent(s):
11b875a
subiendo utils y app a hugginface
Browse files
app.py
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import streamlit as st
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from utils import carga_modelo, genera
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##pagina principal
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st.title("Generador de mariposas")
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st.write("modelo Light GAN utilizado para aprender :D")
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##barra lateral
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st.sidebar.subheader("!Esta mariposa no existe, ¿puedes creerlo?")
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st.sidebar.image("assets/logo.png", width=200)
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st.sidebar.caption("Demo creado en vivo.")
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##Cargamos el modelo
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repo_id = "ceyda/butterfly_cropped_uniq1K_512"
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modelo_gan = carga_modelo(repo_id)
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##numero de mariposas (4 en este caso)
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n_mariposas = 4
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def corre():
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with st.spinner("Generando, espera un poco..."):
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ims = genera(modelo_gan, n_mariposas)
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st.session_state["ims"] = ims #estamos pasando informacion de uno a otro
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if "ims" not in st.session_state:
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st.session_state["ims"] = None
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corre()
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ims = st.session_state["ims"]
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corre_boton = st.button(
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"Genera mariposa porfa",
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on_click=corre,
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help="Estamos en vuelo, aprocha el cinturón"
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)
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if ims is not None:
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cols = st.columns(n_mariposas)
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for j, im in enumerate(ims):
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i = j % n_mariposas
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cols[i].image(im, use_column_width=True)
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utils.py
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import numpy as np
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import torch
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from huggan.pytorch.lightweight_gan.lightweight_gan import LightweightGAN
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def carga_modelo(model_name="ceyda/butterfly_cropped_uniq1K_512", model_version=None):
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gan = LightweightGAN.from_pretrained(model_name, vesion=model_version)
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gan.eval()
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return gan
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def genera(gan, batch_size=1):
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with torch.no_grad():
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ims = gan.G(torch.randn(batch_size, gan.latent_dim)).clamp_(0.0,1.0)*255
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ims = ims.permute(0,2,3,1).deatch().cpu().numpy().astype(np.uint8)
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return ims
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