web-demos/hugging_face/README.md

Get Started

1. Install ProPainter Dependencies You can follow the Dependencies and Installation

2. Install Demo Dependencies

cd web-demos/hugging_face

# install python dependencies 
pip3 install -r requirements.txt

# Run the demo
python app.py

Usage Guidance

• Step 1: Upload your video and click the Get video info button.

• Step 2:

  1. [Optional] Specify the tracking period for the currently added mask by dragging the Track start frame or Track end frame.
  2. Click the image on the left to select the mask area.
  3. • Click Add mask if you are satisfied with the mask, or
     • [Optional] Click Clear clicks if you want to reselect the mask area, or
     • [Optional] Click Remove mask to remove all masks.
  4. [Optional] Go back to step 2.1 to add another mask.

• Step 3:

  1. Click the Tracking button to track the masks for the whole video.
  2. [Optional] Select the ProPainter parameters if the ProPainter Parameters dropdown.
  3. Then click Inpainting to get the inpainting results.

You can always refer to the Highlighted Text box on the page for guidance on the next step!

Citation

If you find our repo useful for your research, please consider citing our paper:

@inproceedings{zhou2023propainter,
   title={{ProPainter}: Improving Propagation and Transformer for Video Inpainting},
   author={Zhou, Shangchen and Li, Chongyi and Chan, Kelvin C.K and Loy, Chen Change},
   booktitle={Proceedings of IEEE International Conference on Computer Vision (ICCV)},
   year={2023}
}

License

This project is licensed under NTU S-Lab License 1.0. Redistribution and use should follow this license.

Acknowledgements

The project harnesses the capabilities from Track Anything, Segment Anything, Cutie, and E2FGVI. Thanks for their awesome works.