subiendo utils y app

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 Light GAN entrenado')
+
+#Barra lateral
+st.sidebar.subheader('!Esta mariposa no existe, puedes creelo')
+st.sidebar.image('assets/logo.png', width=200)
+st.sidebar.caption('Demo creado')
+
+#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, espero un poco...')
+    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(
+    'Genera mariposas porfa',
+    on_click=corre,
+    help='Estamos en vuelo, abrocha tu cinturon'
+)
+
+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_widht=True)

utils.py

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+import numpy as np
+import torch
+from huggan.pytorch.lightweights_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).deatch().cpu().numpy().astype(np.uint8)
+    return ims
+