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import torch
from diffusers import StableDiffusionPipeline
from PIL import Image
from io import BytesIO
from utils import load_unet_model
class TextToImage:
"""
Class to handle Text-to-Image generation using Stable Diffusion XL.
"""
def __init__(self, device="cpu"):
# Model and repository details
model_id = "OFA-Sys/small-stable-diffusion-v0"
self.device = device
self.pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float32).pipe.to(device)
print("Text-to-Image model loaded successfully.")
async def generate_image(self, prompt):
"""
Generate an image from a text prompt.
Args:
prompt (str): The text prompt to generate the image.
Returns:
PIL.Image: The generated image.
"""
with torch.no_grad():
image = self.pipe(
prompt
).images[0]
return image
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