# WaveletSRNet

**Repository Path**: harry56/WaveletSRNet

## Basic Information

- **Project Name**: WaveletSRNet
- **Description**: A pytorch implementation of Paper "Wavelet-srnet: A wavelet-based cnn for multi-scale face super resolution"
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 1
- **Created**: 2020-07-18
- **Last Updated**: 2021-12-11

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# WaveletSRNet
A pytorch implementation of Paper ["Wavelet-srnet: A wavelet-based cnn for multi-scale face super resolution"](http://openaccess.thecvf.com/content_iccv_2017/html/Huang_Wavelet-SRNet_A_Wavelet-Based_ICCV_2017_paper.html)

## Prerequisites
* Python 2.7
* PyTorch

## Run

Use the default hyparameters except changing the parameter "upscale" according to the expected upscaling factor(2, 3, 4 for 4, 8, 16 upcaling factors, respectively).

>CUDA_VISIBLE_DEVICES=1 python main.py --ngpu=1 --test --start_epoch=0  --test_iter=1000  --batchSize=64 --test_batchSize=32 --nrow=4  --upscale=3 --input_height=128 --output_height=128 --crop_height=128 --lr=2e-4  --nEpochs=500 --cuda

## Results

![](https://github.com/hhb072/WaveletSRNet/blob/master/results.png)

## Citation

If you use our codes, please cite the following paper:

 	@inproceedings{huang2017wavelet,
	  title={Wavelet-srnet: A wavelet-based cnn for multi-scale face super resolution},
	  author={Huang, Huaibo and He, Ran and Sun, Zhenan and Tan, Tieniu},
	  booktitle={IEEE International Conference on Computer Vision},
	  pages={1689--1697},    
	  year={2017}
	}

**The released codes are only allowed for non-commercial use.**