# FSRNET_pytorch

**Repository Path**: exlla/FSRNET_pytorch

## Basic Information

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

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-11-27
- **Last Updated**: 2021-06-09

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# FSRNet Pytorch
Dear friends, 
Thank you for keep tracking in this implementation of FSRNet (CVPR 2018 Oral Paper)

I have been spent the whole summer as an intern in Iluvatar.ai. I have been back to school, so I have time to complete the Project.

I rewrite the Train.py and other model code completely. Now I am uploading pretrained Weights on BaiduNetDisk together with Training Set. 

Based on [WaveletSRNet](https://github.com/hhb072/WaveletSRNet/), I altered the code by adopting FSRNet network structure. 

## Prerequisites

* Python 3.6
* Pytorch 1.0 or newer (Pytorch > 0.4 should be ok)
* matplotlib
* skimage

## Train

Change the option in Train.py to set the dataset's directory. I am using CelebAHQ-MASK as the training set. The GroundTruth is generated by zllrunning/face-parsing.PyTorch(https://github.com/zllrunning/face-parsing.PyTorch) with pretrained model.

Dataset Link: https://pan.baidu.com/s/1HEECUyKI5GOSrd7NPlm-ow  密码:z2ud

## Test

ON GOING :| 
PYTHON AND NOTEBOOK WILL BE PROVIDED.
Pretrained Weights:链接:https://pan.baidu.com/s/1ZkgABGefsMjO6XhhvlBzRA  密码:libl

## Result

## Citation
If you find FSRNet useful in your research, please consider citing (* indicates equal contributions):

	@inproceedings{CT-FSRNet-2018,
	  title={FSRNet: End-to-End Learning Face Super-Resolution with Facial Priors},
	  author={Chen, Yu* and Tai, Ying* and Liu, Xiaoming and Shen, Chunhua and Yang, Jian },
	  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
	  year={2018}
	}