Spaces:
Running
Running
File size: 7,599 Bytes
e552c8f cb5428f f693d07 cb5428f d726590 90986f4 ea513a8 cb5428f ea513a8 cb5428f ea513a8 cb5428f ea513a8 cb5428f 90986f4 ea513a8 cb5428f ea513a8 cb5428f ea513a8 cb5428f 90986f4 d99c194 7c6a22d cb5428f ea513a8 cb5428f 5981fd1 cb5428f 90986f4 e6e9673 |
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 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 |
import os
import zipfile
import yaml
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
from moviepy.editor import ImageSequenceClip
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 configuración: {e}")
credentials = {"username": "", "password": ""}
MAX_SEED = np.iinfo(np.int32).max
client = AsyncInferenceClient()
DATA_PATH = Path("./data")
DATA_PATH.mkdir(exist_ok=True)
PREDEFINED_SEED = random.randint(0, MAX_SEED)
async def generate_image(prompt, width, height, seed, model_name):
try:
if seed == -1:
seed = PREDEFINED_SEED
seed = int(seed)
image = await client.text_to_image(
prompt=prompt, height=height, width=width, model=model_name
)
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, model_name):
combined_prompt = prompt
seed = PREDEFINED_SEED
progress_bar = st.progress(0)
image, seed = await generate_image(combined_prompt, width, height, seed, model_name)
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 delete_all_images():
try:
files = [file for file in DATA_PATH.glob("*.jpg")]
prompts = [file for file in DATA_PATH.glob("*.txt")]
for file in files + prompts:
os.remove(file)
st.success("Todas las imágenes y prompts han sido borrados.")
except Exception as e:
st.error(f"Error al borrar archivos: {e}")
def download_images_as_zip():
zip_path = DATA_PATH / "images.zip"
with zipfile.ZipFile(zip_path, 'w') as zipf:
for file in DATA_PATH.glob("*.jpg"):
zipf.write(file, arcname=file.name)
with open(zip_path, "rb") as zip_file:
st.download_button(label="Descargar imágenes en .zip", data=zip_file, file_name="images.zip", mime="application/zip")
def create_video_from_images():
try:
image_files = sorted(DATA_PATH.glob("*.jpg"))
if not image_files:
st.error("No hay imágenes disponibles para crear un video.")
return
image_sequence = [Image.open(image_file) for image_file in image_files]
frame_rate = 2
clip = ImageSequenceClip([np.array(img) for img in image_sequence], fps=1)
video_path = DATA_PATH / "output_video.mp4"
clip.write_videofile(str(video_path), codec="libx264")
return video_path
except Exception as e:
st.error(f"Error al generar el video: {e}")
return None
def main():
st.set_page_config(layout="wide")
st.title("Generador de Imágenes")
if "authenticated" not in st.session_state:
st.session_state.authenticated = False
if not st.session_state.authenticated:
st.subheader("Iniciar sesión")
username = st.text_input("Usuario")
password = st.text_input("Contraseña", type="password")
if st.button("Ingresar"):
if username == credentials["username"] and password == credentials["password"]:
st.session_state.authenticated = True
st.success("Inicio de sesión exitoso.")
else:
st.error("Usuario o contraseña incorrectos.")
return
st.warning("Este espacio contiene contenido que no es adecuado para todas las audiencias. Se recomienda discreción.")
agree = st.checkbox("Soy mayor de 18 años y entiendo que el contenido puede no ser apropiado.")
if agree:
prompt = st.sidebar.text_input("Descripción de la imagen", max_chars=500)
format_option = st.sidebar.selectbox("Formato", ["9:16", "16:9"])
model_option = st.sidebar.selectbox("Modelo", ["enhanceaiteam/Flux-Uncensored-V2", "enhanceaiteam/Flux-uncensored"])
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, model_option))
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 está 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 st.sidebar.button("Borrar todas las imágenes"):
delete_all_images()
if st.sidebar.button("Descargar imágenes en .zip"):
download_images_as_zip()
if st.button("Generar video con las imágenes"):
video_path = create_video_from_images()
if video_path:
st.video(str(video_path), format="video/mp4")
if __name__ == "__main__":
main() |