metadata
license: mit
Unique3d-MVImage-Diffuser Model Card
Example
Note the input image is suppose to be white background.
import torch
import numpy as np
from PIL import Image
from pipeline_img2mvimg import StableDiffusionImage2MVCustomPipeline
pipe = StableDiffusionImage2MVCustomPipeline.from_pretrained(
"Luffuly/unique3d-mv-variation-diffuser",
torch_dtype=torch.float16,
trust_remote_code=True
).to("cuda")
image = Image.open('image.png').convert("RGB")
forward_args = dict(
width=256,
height=256,
width_cond=256,
height_cond=256,
num_images_per_prompt=4,
num_inference_steps=50,
guidance_scale=1.5,
)
out = pipe(image, **forward_args).images
rgb_np = np.hstack([np.array(img) for img in out])
Image.fromarray(rgb_np).save(f"mvimg.png")
Image-to-Normal
please check:
Citation
@misc{wu2024unique3d,
title={Unique3D: High-Quality and Efficient 3D Mesh Generation from a Single Image},
author={Kailu Wu and Fangfu Liu and Zhihan Cai and Runjie Yan and Hanyang Wang and Yating Hu and Yueqi Duan and Kaisheng Ma},
year={2024},
eprint={2405.20343},
archivePrefix={arXiv},
primaryClass={cs.CV}
}