Add application file

app.py

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+import streamlit as st
+from utils import carga_modelo,genera
+
+## Pagina principal
+st.title("generador de mariposas")
+st.write("este es un modelo lightGan entrenado")
+
+## Barra Lateral
+st.sidebar.subheader("¡Esta mariposa no existe, ¿Puedes creeerlo?")
+st.sidebar.image("assets/logo.png",width=200)
+st.sidebar.caption("Demo creado en vivo")
+
+## Cargamos el modelo
+repo_id = "ceyda/butterfly_cropped_uniq1K_512"
+modelo_gan = carga_modelo(repo_id)
+
+## Generamos 4 mariposas
+
+n_mariposas = 4
+
+def corre():
+    with st.spinner("Generando espera..."):
+        ims = genera(modelo_gan,n_mariposas)
+        st.session_state["ims"] = ims
+
+if "ims" not in st.session_state:
+    st.session_state["ims"]= None
+    corre()        
+
+ims = st.session_state["ims"]
+corre_boton = st.button(
+    "Generar mariposas",
+    on_click=corre,
+    help="Estamos en vuelo, abrocha tu sinturon"
+    )
+
+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)

utils.py

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+import numpy as np
+import torch 
+from huggan.pytorch.lightweight_gan.lightweight_gan import LightweightGAN 
+
+def carga_modelo(model_name="ceyda/butterfly_cropped_uniq1K_512", model_version=None):
+    gan = LightweightGAN.from_pretrained(model_name, version=model_version)
+    gan.eval()
+    return gan
+
+def genera(gan, batch_size=1):
+    with torch.no_grad():
+        ims = gan.G(torch.randn(batch_size,gan.latent_dim)).clamp_(0.0,1.0) * 255
+        ims = ims.permute(0,2,3,1).detach().cpu().numpy().astype(np.uint8)
+        return ims