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1from diffusers import StableDiffusionInpaintPipeline
2import torch
3from diffusers.utils import load_image, make_image_grid
4import PIL
5
6# 指定模型文件路径
7model_path = "Liangyingping/Lift3Dreamer"
8# 加载模型
9pipe = StableDiffusionInpaintPipeline.from_pretrained(
10 model_path, torch_dtype=torch.float16
11)
12pipe.to("cuda") # 如果有 GPU，可以将模型加载到 GPU 上
13
14init_image = load_image("assets/debug_masked_image.png")
15mask_image = load_image("assets/debug_mask.png")
16W, H = init_image.size
17
18prompt = "a photo of a person"
19image = pipe(
20 prompt=prompt,
21 image=init_image,
22 mask_image=mask_image,
23 h=512, w=512
24).images[0].resize((W, H))
25
26print(image.size, init_image.size)
27
28image2save = make_image_grid([init_image, mask_image, image], rows=1, cols=3)
29image2save.save("image2save_ours.png")@article{LIANG2026,
title = {Lift3Dreamer: Boosting Text-Driven Novel View Synthesis via Lifted 3D Inpainting Model from Single Images.},
journal = {Fundamental Research},
year = {2026},
issn = {2667-3258},
author = {Yingping Liang and Ying Fu and Jiaming Liu and Debing Zhang},
}