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# A Task is Worth One Word: Learning with Task Prompts for High-Quality Versatile Image Inpainting |
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### [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) |
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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. |
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## 🚀 News |
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**December 18, 2023** |
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*Enhanced PowerPaint Model* |
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- 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. |
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## Next |
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**Stronger Model Weights Coming Soon!** |
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________________ |
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<img src='https://github.com/open-mmlab/mmagic/assets/12782558/acd01391-c73f-4997-aafd-0869aebcc915'/> |
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## Getting Started |
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```bash |
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# Clone the Repository |
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git clone https://github.com/zhuang2002/PowerPaint.git |
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# Navigate to the Repository |
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cd projects/powerpaint |
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# Create Virtual Environment with Conda |
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conda create --name PowerPaint python=3.9 |
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conda activate PowerPaint |
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# Install Dependencies |
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pip install -r requirements.txt |
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# Create Models Folder |
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mkdir models |
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# Set up Git LFS |
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git lfs install |
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# Clone PowerPaint Model |
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git lfs clone https://huggingface.co/JunhaoZhuang/PowerPaint-v1/ ./models |
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``` |
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## Run PowerPaint |
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To run PowerPaint, execute the following command: |
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```bash |
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python gradio_PowerPaint.py |
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``` |
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This command will launch the Gradio interface for PowerPaint. |
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Feel free to explore and create stunning images with PowerPaint! |
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## BibTeX |
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``` |
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@misc{zhuang2023task, |
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title={A Task is Worth One Word: Learning with Task Prompts for High-Quality Versatile Image Inpainting}, |
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author={Junhao Zhuang and Yanhong Zeng and Wenran Liu and Chun Yuan and Kai Chen}, |
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year={2023}, |
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eprint={2312.03594}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CV} |
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} |
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``` |
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