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import gradio as gr
from diffusers import DiffusionPipeline
from PIL import Image
import torch
# Cargar pipeline (float32 para CPU)
model_id = "stabilityai/stable-diffusion-x4-upscaler"
pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-x4-upscaler", dtype=torch.bfloat16, device_map="cuda")
# Función de Gradio
def upscaler_gradio(imagen):
if imagen is None:
return None
img = Image.fromarray(imagen) # convertir de NumPy a PIL
prompt = "A high quality, detailed, and visually clear image"
result = pipe(prompt=prompt, image=img).images[0]
return result
# Interfaz Gradio
demo = gr.Interface(
fn=upscaler_gradio,
inputs=gr.Image(type="numpy"),
outputs=gr.Image(),
title="Upscaler Difusión",
description="Sube una imagen y el modelo la mejorará y aumentará resolución 4×."
)
demo.launch()
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