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import os | |
import numpy as np | |
import random | |
from pathlib import Path | |
from PIL import Image | |
import streamlit as st | |
import yaml | |
from huggingface_hub import AsyncInferenceClient | |
import asyncio | |
MAX_SEED = np.iinfo(np.int32).max | |
client = AsyncInferenceClient() | |
DATA_PATH = Path("./data") | |
DATA_PATH.mkdir(exist_ok=True) | |
# Cargar credenciales desde archivo config.yaml | |
try: | |
with open("config.yaml", "r") as file: | |
credentials = yaml.safe_load(file) | |
except Exception as e: | |
st.error(f"Error al cargar el archivo de configuraci贸n: {e}") | |
credentials = {"username": "", "password": ""} # Valores predeterminados | |
PREDEFINED_SEED = random.randint(0, MAX_SEED) | |
async def generate_image(prompt, width, height, seed): | |
try: | |
if seed == -1: | |
seed = PREDEFINED_SEED | |
seed = int(seed) | |
image = await client.text_to_image( | |
prompt=prompt, height=height, width=width, model="enhanceaiteam/Flux-uncensored" | |
) | |
return image, seed | |
except Exception as e: | |
return f"Error al generar imagen: {e}", None | |
def save_prompt(prompt_text, seed): | |
try: | |
prompt_file_path = DATA_PATH / f"prompt_{seed}.txt" | |
with open(prompt_file_path, "w") as prompt_file: | |
prompt_file.write(prompt_text) | |
return prompt_file_path | |
except Exception as e: | |
st.error(f"Error al guardar el prompt: {e}") | |
return None | |
async def gen(prompt, width, height): | |
combined_prompt = prompt | |
seed = PREDEFINED_SEED | |
progress_bar = st.progress(0) | |
image, seed = await generate_image(combined_prompt, width, height, seed) | |
progress_bar.progress(100) | |
if isinstance(image, str) and image.startswith("Error"): | |
progress_bar.empty() | |
return [image, None] | |
image_path = save_image(image, seed) | |
prompt_file_path = save_prompt(combined_prompt, seed) | |
return [str(image_path), str(prompt_file_path)] | |
def save_image(image, seed): | |
try: | |
image_path = DATA_PATH / f"image_{seed}.jpg" | |
image.save(image_path, format="JPEG") | |
return image_path | |
except Exception as e: | |
st.error(f"Error al guardar la imagen: {e}") | |
return None | |
def get_storage(): | |
files = [file for file in DATA_PATH.glob("*.jpg") if file.is_file()] | |
files.sort(key=lambda x: x.stat().st_mtime, reverse=True) | |
usage = sum([file.stat().st_size for file in files]) | |
return [str(file.resolve()) for file in files], f"Uso total: {usage/(1024.0 ** 3):.3f}GB" | |
def get_prompts(): | |
prompt_files = [file for file in DATA_PATH.glob("*.txt") if file.is_file()] | |
return {file.stem.replace("prompt_", ""): file for file in prompt_files} | |
def main(): | |
st.set_page_config(layout="wide") | |
st.title("Flux Uncensored") | |
if "logged_in" not in st.session_state: | |
st.session_state.logged_in = False | |
if not st.session_state.logged_in: | |
username = st.text_input("Usuario") | |
password = st.text_input("Contrase帽a", type="password") | |
if st.button("Iniciar Sesi贸n"): | |
if username == credentials["username"] and password == credentials["password"]: | |
st.session_state.logged_in = True | |
st.success("Inicio de sesi贸n exitoso.") | |
else: | |
st.error("Usuario o contrase帽a incorrectos.") | |
else: | |
prompt = st.sidebar.text_input("Descripci贸n de la imagen", max_chars=500) | |
format_option = st.sidebar.selectbox("Formato", ["9:16", "16:9"]) | |
width, height = (720, 1280) if format_option == "9:16" else (1280, 720) | |
if st.sidebar.button("Generar Imagen"): | |
with st.spinner("Generando imagen..."): | |
result = asyncio.run(gen(prompt, width, height)) | |
image_paths = result[0] | |
prompt_file = result[1] | |
if image_paths: | |
if Path(image_paths).exists(): | |
st.image(image_paths, caption="Imagen Generada") | |
else: | |
st.error("El archivo de imagen no existe.") | |
if prompt_file and Path(prompt_file).exists(): | |
prompt_text = Path(prompt_file).read_text() | |
st.write(f"Prompt utilizado: {prompt_text}") | |
else: | |
st.write("El archivo del prompt no est谩 disponible.") | |
files, usage = get_storage() | |
st.text(usage) | |
cols = st.columns(6) | |
prompts = get_prompts() | |
for idx, file in enumerate(files): | |
with cols[idx % 6]: | |
image = Image.open(file) | |
prompt_file = prompts.get(Path(file).stem.replace("image_", ""), None) | |
prompt_text = Path(prompt_file).read_text() if prompt_file else "No disponible" | |
st.image(image, caption=f"Imagen {idx+1}") | |
st.write(f"Prompt: {prompt_text}") | |
if st.button(f"Borrar Imagen {idx+1}", key=f"delete_{idx}"): | |
try: | |
os.remove(file) | |
if prompt_file: | |
os.remove(prompt_file) | |
st.success(f"Imagen {idx+1} y su prompt fueron borrados.") | |
except Exception as e: | |
st.error(f"Error al borrar la imagen o prompt: {e}") | |
if __name__ == "__main__": | |
main() |