# RN

**Repository Path**: jasonli666/RN

## Basic Information

- **Project Name**: RN
- **Description**: No description available
- **Primary Language**: Python
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-10-08
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Region Normalization for Image Inpainting

The paper can be found [here](https://arxiv.org/abs/1911.10375). If you have any question about the paper/codes, you can contact me through Email(yutao666@mail.ustc.edu.cn).

Please run the codes where the python is Version 3.x and pytorch>=0.4.

PS: The results of this version codes are better than those in the paper. The original base inpainting model that RN uses is not very stable (the result variance is a bit large) and we only reported conservative results. However, we optimized the base model and improved its robustness after the pulication so that the results now are better.

## Preparation
Before running the codes, you should prepare training/evaluation image file list (flist) and mask file list (flist). You can refer to the folowing command to generate .flist file:
```
python flist.py --path your_dataset_folder --output xxx.flist
```

## Training
There are some hyperparameters that you can adjust in the main.py. To train the model, you can run:
```
python main.py --bs 14 --gpus 2 --prefix rn --img_flist your_training_images.flist --mask_flist your_training_masks.flist
```
PS: You can set the "--bs" and "--gpus" to any number as you like. The above is just an example.

## Evaluation
To evaluate the model, you can use GPU or CPU to run.

For GPU:
```
python eval.py --bs your_batch_size --model your_checkpoint_path --img_flist your_eval_images.flist --mask_flist your_eval_masks.flist
```

For CPU:
```
python eval.py --cpu --bs your_batch_size --model your_checkpoint_path --img_flist your_eval_images.flist --mask_flist your_eval_masks.flist
```

PS: The pretrained model under folder './pretrained_model/' is trained from Places2 dataset with [Irregular Mask](https://nv-adlr.github.io/publication/partialconv-inpainting) dataset. **Please train RN from scratch if you test data not from Places2 or using regular mask.**

## Cite Us
Please cite us if you find this work helps.

```
@inproceedings{yu2020region,
  title={Region Normalization for Image Inpainting.},
  author={Yu, Tao and Guo, Zongyu and Jin, Xin and Wu, Shilin and Chen, Zhibo and Li, Weiping and Zhang, Zhizheng and Liu, Sen},
  booktitle={AAAI},
  pages={12733--12740},
  year={2020}
}
```

## Appreciation
The codes refer to [EdgeConnect](https://github.com/knazeri/edge-connect). Thanks for the authors of it！