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import os; import numpy as np; import random; from pathlib import Path; from PIL import Image; import streamlit as st; from huggingface_hub import AsyncInferenceClient; import asyncio; import yaml
with open("config.yaml") as f: config = yaml.safe_load(f); username = config["credentials"]["username"]; password = config["credentials"]["password"]
client = AsyncInferenceClient(); DATA_PATH = Path("./data"); DATA_PATH.mkdir(exist_ok=True); MAX_SEED = np.iinfo(np.int32).max; PREDEFINED_SEED = random.randint(0, MAX_SEED)
async def generate_image(prompt, width, height, seed):
try:
seed = int(seed) if seed != -1 else PREDEFINED_SEED
return await client.text_to_image(prompt=prompt, height=height, width=width, model="enhanceaiteam/Flux-uncensored"), 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):
seed = PREDEFINED_SEED; progress_bar = st.progress(0)
image, seed = await generate_image(prompt, width, height, seed)
progress_bar.progress(100)
if isinstance(image, str) and image.startswith("Error"): progress_bar.empty(); return [image, None]
return [save_image(image, seed), save_prompt(prompt, seed)]
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 = sorted(DATA_PATH.glob("*.jpg"), 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():
return {file.stem.replace("prompt_", ""): file for file in DATA_PATH.glob("*.txt") if file.is_file()}
def main():
st.set_page_config(layout="wide")
st.title("Generador de Im谩genes")
st.sidebar.header("Inicio de Sesi贸n")
input_username = st.sidebar.text_input("Usuario")
input_password = st.sidebar.text_input("Contrase帽a", type="password")
if st.sidebar.button("Iniciar Sesi贸n"):
if input_username == username and input_password == password:
st.sidebar.success("Inicio de sesi贸n exitoso!")
prompt = st.sidebar.text_input("Descripci贸n de la imagen", max_chars=500)
width, height = (720, 1280) if st.sidebar.selectbox("Formato", ["9:16", "16:9"]) == "9:16" else (1280, 720)
if st.sidebar.button("Generar Imagen"):
with st.spinner("Generando imagen..."):
result = asyncio.run(gen(prompt, width, height))
if (image_paths := result[0]) and Path(image_paths).exists():
st.image(image_paths, caption="Imagen Generada")
else:
st.error("El archivo de imagen no existe.")
if (prompt_file := result[1]) and Path(prompt_file).exists():
st.write(f"Prompt utilizado: {Path(prompt_file).read_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)
st.image(image, caption=f"Imagen {idx+1}")
st.write(f"Prompt: {Path(prompt_file).read_text() if prompt_file else 'No disponible'}")
if st.button(f"Borrar Imagen {idx+1}", key=f"delete_{idx}"):
try:
os.remove(file)
os.remove(prompt_file) if prompt_file else None
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}")
else:
st.sidebar.error("Usuario o contrase帽a incorrectos.")
else:
st.sidebar.warning("Por favor, inicie sesi贸n.")
if __name__ == "__main__": main() |