we added app.py, requirements and utils.py

app.py

@@ -1,7 +1,44 @@
 import streamlit as st
+from utils import carga_modelo, genera
 
+## pagina principal
 
-st.title("Este es mi demo")
-st.markdown("Esta es mi descripción")
-x = st.slider("Selecciona un Valor")
-st.write(x, "el cuadrado es", x*x)
+st.title("Generador de Mariposas")
+st.write("Este es un modelo Light GAN pre entrenado")
+
+##Barra lateral
+
+st.sidebar.subheader("Esta Mariposa no existe! haha")
+st.sidebar.image("assets/logo.png", width = 200)
+st.sidebar.caption("Dema creado usando Streamlit")
+
+
+## Cargamos el modelo
+repo_id = "ceyda/butterfly_cropped_uniq1K_512"
+modelo_gan = carga_modelo(repo_id)
+
+##Generamos 4 mariposas
+n_mariposas = 4
+
+
+def run_model():
+    with st.spinner("Generando Mariposa... :)")
+    ims = genera(modelo_gan, n_mariposas)
+    st.session_state["ims"] = ims
+if "ims" not in st.session_state:
+    st.session_state["ims"] = None
+    run_model()
+ims = st.session_state["ims"]
+
+run_model_button = st.button(
+"Genera Mariposa",
+on_click = run_model()
+help="Estamos generando la Mariposa "
+
+)
+
+if ims is not None:
+    clos = st.columns(n_mariposas)
+    for jo, im in enumerate(ims):
+        i = j% n_mariposas
+        cols[i].image(im, use_colum_width=True)

utils.py

@@ -0,0 +1,15 @@
+import numpy as np
+import torch
+from huggan.pytorch.lightweight_gan.lightweight_gan import LightweightGAN
+
+def carga_modelo(modelo_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).deatch().cpu().numpy().astype(np.uint8)
+
+    return ims