SDXLImageGenerator.py

import torch
from diffusers import DiffusionPipeline
import time

class SDXLImageGenerator:
    def __init__(self):
        # Check if cuda is available
        self.use_cuda = torch.cuda.is_available()
        # Set proper device based on cuda availability
        self.device = torch.device("cuda" if self.use_cuda else "cpu")

        print("CUDA: ", self.device)

        # Load the pipeline
        self.pipe = DiffusionPipeline.from_pretrained(
            "stabilityai/stable-diffusion-xl-base-1.0",
            torch_dtype=torch.float16,
            use_safetensors=True,
            variant="fp16"
        )
        self.pipe.to(self.device)

    def generate_images(self, prompts):
        images = []
        start_time = time.time()
        for i, prompt in enumerate(prompts):
            gen_image = self.pipe(prompt=prompt).images[0]
            images.append(gen_image)

        end_time = time.time()
        print("Total Time SDXL: %4f seconds" % (end_time - start_time))
        return images