BrushNet: A Plug-and-Play Image Inpainting Model with Decomposed Dual-Branch Diffusion
Paper • 2403.06976 • Published • 2
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("ameerazam08/BrushNet", torch_dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]BrushNet
This repository contains the gradio demo of the paper "BrushNet: A Plug-and-Play Image Inpainting Model with Decomposed Dual-Branch Diffusion"
Keywords: Image Inpainting, Diffusion Models, Image Generation
Xuan Ju12, Xian Liu12, Xintao Wang1*, Yuxuan Bian2, Ying Shan1, Qiang Xu2*
1ARC Lab, Tencent PCG 2The Chinese University of Hong Kong *Corresponding Author
Project Page | Code | Arxiv | Data | Video |
🤝🏼 Cite Us
@misc{ju2024brushnet,
title={BrushNet: A Plug-and-Play Image Inpainting Model with Decomposed Dual-Branch Diffusion},
author={Xuan Ju and Xian Liu and Xintao Wang and Yuxuan Bian and Ying Shan and Qiang Xu},
year={2024},
eprint={2403.06976},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
💖 Acknowledgement
Our code is modified based on diffusers, thanks to all the contributors!
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