Spaces:
Running
Running
File size: 1,883 Bytes
1922d6a 6084ee7 1922d6a 6084ee7 667dfe4 1922d6a 4f84b19 1922d6a 3e02b14 1922d6a 9940a0d 1922d6a 3e02b14 1922d6a |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 |
import base64
import io
from huggingface_hub import InferenceClient
import streamlit as st
from PIL import Image
# Configuraci贸n
hf_token = st.secrets["HF_TOKEN"]
client = InferenceClient(repo_id="black-forest-labs/FLUX.1-schnell", token=hf_token)
def get_image_result(prompt, init_image=None):
if init_image:
img_buffer = io.BytesIO()
init_image.save(img_buffer, format="PNG")
img_bytes = img_buffer.getvalue()
encoded_image = base64.b64encode(img_bytes).decode('utf-8')
else:
encoded_image = None
try:
output = client.img2img(prompt=prompt, image=encoded_image, strength=0.75)
img_data = base64.b64decode(output['generated_image'])
return Image.open(io.BytesIO(img_data))
except Exception as e:
st.error(f"Error en la generaci贸n de la imagen: {str(e)}")
return None
# Interfaz de Streamlit
st.title("Generaci贸n de Im谩genes img2img con Flux")
st.sidebar.header("Opciones de generaci贸n")
prompt = st.sidebar.text_input("Escribe tu prompt:", value="Una escena futurista en una ciudad verde")
uploaded_file = st.sidebar.file_uploader("Sube una imagen base (opcional)", type=["jpg", "png"])
if st.sidebar.button("Generar Imagen"):
if uploaded_file:
init_image = Image.open(uploaded_file).convert("RGB")
st.image(init_image, caption="Imagen Base", use_column_width=True)
else:
init_image = None
with st.spinner('Generando imagen...'):
generated_image = get_image_result(prompt, init_image)
if generated_image:
st.image(generated_image, caption="Imagen Generada", use_column_width=True)
img_bytes = io.BytesIO()
generated_image.save(img_bytes, format="PNG")
st.download_button(label="Descargar imagen", data=img_bytes.getvalue(), file_name="generated_image.png", mime="image/png")
|