Contextual Residual Aggregation for Ultra High-Resolution Image Inpainting
If the codes helps you in reserach, please cite the following paper:
@misc{yi2020contextual,
title={Contextual Residual Aggregation for Ultra High-Resolution Image Inpainting},
author={Zili Yi and Qiang Tang and Shekoofeh Azizi and Daesik Jang and Zhan Xu},
year={2020},
eprint={2005.09704},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
get dependancies installed on the conda environment, see requirements.txt for details. The following package are required:
- tensorflow-gpu
- opencv
- scipy
- pyyaml
- neuralgym
- easydict
run the following script to start training. 200000~300000 steps would be enough for good converngence
python train.py
python test.py --image_dir='./data/test/images' --mask_dir='./data/test/masks' --output_dir='outputs' --checkpoint_dir='./model_logs/places2' --input_size=512 --times=8
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