| |
| import torch |
| from diffusers import StableDiffusion3Pipeline |
| import random |
|
|
| class ImageGenerator: |
| def __init__(self, repo: str): |
| self.repo = repo |
| self.pipeline = StableDiffusion3Pipeline.from_pretrained(self.repo, torch_dtype=torch.float16, local_files_only = True) |
| self.pipeline.enable_model_cpu_offload() |
|
|
| def generate_image(self, prompt: str, width: int = 1024, height: int = 1024, scale_factor: float = 4.5, steps: int = 28, seed: int = None): |
| seed = seed if seed is not None else random.randint(0, 2**32 - 1) |
| print(f"using {seed} to generate image...") |
| generator = torch.Generator("cuda").manual_seed(seed) |
| image = self.pipeline( |
| prompt, |
| negative_prompt="", |
| width=width, |
| height=height, |
| num_inference_steps=steps, |
| guidance_scale=scale_factor, |
| max_sequence_length=512, |
| generator=generator, |
| ).images[0] |
| return image |
| |
| Sd_repo = "/tmp/pretrainmodel/stable-diffusion-3.5-medium-ungated" |
| sd_model = ImageGenerator(Sd_repo) |
| prompt = "A close-up portrait of an Asian girl with blunt bangs and big eyes, side profile, holding a red apple on top of her head, in a winter beach setting. She looks very happy, with snowflakes gently falling on her hair. The scene is captured with a high-quality DSLR camera, showcasing natural light and bokeh effects, with a fresh, crisp light and shadow play, reminiscent of a snowy film scene." |
| image = sd_model.generate_image(prompt) |
|
|
