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# A Task is Worth One Word: Learning with Task Prompts for High-Quality Versatile Image Inpainting
### [Project Page](https://powerpaint.github.io/) | [Paper](https://arxiv.org/abs/2312.03594) | [Online Demo(OpenXlab)](https://openxlab.org.cn/apps/detail/rangoliu/PowerPaint#basic-information)
This README provides a step-by-step guide to download the repository, set up the required virtual environment named "PowerPaint" using conda, and run PowerPaint with or without ControlNet.
## 🚀 News
**December 18, 2023**
*Enhanced PowerPaint Model*
- We are delighted to announce the release of more stable model weights. These refined weights can now be accessed on [Hugging Face](https://huggingface.co/JunhaoZhuang/PowerPaint-v1/tree/main). The `gradio_PowerPaint.py` file and [Online Demo](https://openxlab.org.cn/apps/detail/rangoliu/PowerPaint) have also been updated as part of this release.
## Next
**Stronger Model Weights Coming Soon！**
________________
<img src='https://github.com/open-mmlab/mmagic/assets/12782558/acd01391-c73f-4997-aafd-0869aebcc915'/>
## Getting Started
```bash
# Clone the Repository
git clone https://github.com/zhuang2002/PowerPaint.git
# Navigate to the Repository
cd projects/powerpaint
# Create Virtual Environment with Conda
conda create --name PowerPaint python=3.9
conda activate PowerPaint
# Install Dependencies
pip install -r requirements.txt
# Create Models Folder
mkdir models
# Set up Git LFS
git lfs install
# Clone PowerPaint Model
git lfs clone https://huggingface.co/JunhaoZhuang/PowerPaint-v1/ ./models
```
## Run PowerPaint
To run PowerPaint, execute the following command:
```bash
python gradio_PowerPaint.py
```
This command will launch the Gradio interface for PowerPaint.
Feel free to explore and create stunning images with PowerPaint!
## BibTeX
```
@misc{zhuang2023task,
title={A Task is Worth One Word: Learning with Task Prompts for High-Quality Versatile Image Inpainting},
author={Junhao Zhuang and Yanhong Zeng and Wenran Liu and Chun Yuan and Kai Chen},
year={2023},
eprint={2312.03594},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
```
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