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"""
Streamlit app – generates 1-10 MNIST-style digits using your trained cGAN
Run: streamlit run app.py
"""
import streamlit as st
import tensorflow as tf
import numpy as np
from PIL import Image
LATENT_DIM = 100
NUM_CLASSES = 10
MODEL_FILE = "generator_full.keras" # <— same name you downloaded
# ---------- 1. Load generator only once per worker ----------
@st.cache_resource(show_spinner="Cargando modelo…")
def load_generator(model_path=MODEL_FILE):
# load_model includes architecture, so no need to rebuild by hand
return tf.keras.models.load_model(model_path, compile=False)
gen = load_generator()
# ---------- 2. Streamlit UI ----------
st.title("✍️ Generador de dígitos manuscritos (cGAN, 20 epochs)")
digit = st.number_input("Dígito (0-9)", min_value=0, max_value=9, value=4, step=1)
num = 5
if st.button("Generar"):
z = tf.random.normal([num, LATENT_DIM])
lbl = tf.constant([[digit]] * num)
imgs = (gen([z, lbl], training=False) + 1) / 2 # scale [-1,1] → [0,1]
cols = st.columns(num)
for c, img in zip(cols, imgs.numpy().squeeze()):
c.image(Image.fromarray((img * 255).astype("uint8"), "L"), use_column_width=True)
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