Lots of SISR (Single Image Super Resolution) implementations in tensorflow maybe w/ pre-trained model!
maybe later, this repo could be supported via pip package.
Currently, Work-In-Progress
[not available yet :(]
$ git clone https://github.com/kozistr/Awesome-Super-Resolution
$ cd ./Awesome-Super-Resolution
$ pip3 install -r ./requirements.txt
$ python3 train.py [w/ some parameters]
$ python3 eval.py [w/ some parameters]
$ python3 inference.py [w/ some parameters]
- DIV2K
- Flicker2K
- Set*
│
├── assets (dir, images used in readme.md)
├── models
│ ├── vgg16.py (VGG19 model loader)
│ ├── vgg19.py (VGG16 model loader)
│ ├── xxx (dir, model name)
│ │ ├── logs (tensorboard logs)
│ │ ├── config.py (configurations)
│ │ ├── model.py (model script)
│ │ └── readme.md (results & explains)
│ └── ... (dir, model name)
│ └── ...
├── train.py (trainer)
├── eval.py (evaluator)
├── inference.py (inferencer)
├── ops.py (useful tf operators)
├── utils.py (useful image utilities)
├── metrics.py (metrics for evaluating SR Model)
├── dataloader.py (dataset loader / feeder)
└── readme.py (readme)
Name | Summary | Paper | Code |
---|---|---|---|
2015 | |||
SRCNN | Image Super-Resolution Using Deep Convolutional Networks | [arXiv] | [ |
2016 | |||
SRGAN | Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network | [arXiv] | [ |
FSRGAN | Accelerating the Super-Resolution Convolutional Neural Network | [arXiv] | [ |
EnhanceNet | Single Image Super-Resolution Through Automated Texture Synthesis | [arXiv] | [ |
2017 | |||
LapSRN | Deep Laplacian Pyramid Networks for Fast and Accurate Super-Resolution | [arXiv] | [ |
EDSR | Enhanced Deep Residual Networks for Single Image Super-Resolution | [arXiv] | [ |
2018 | |||
RCAN | Image Super-Resolution Using Very Deep Residual Channel Attention Networks | [arXiv] | [ |
ESRGAN | Enhanced SRGAN. Champion PIRM Challenge on Perceptual Super-Resolution | [arXiv] | [ |
FEQE | Fast and Efficient Image Quality Enhancement via Desubpixel Convolutional Neural Networks | [ECCV] | [ |
IDN | Fast and Accurate Single Image Super-Resolution via Information Distillation Network | [ECCV] | [ |
2019 | |||
NNTSR | Image Super-Resolution by Neural Texture Transfer | [arXiv] | [ |
It's on the plan, but, because of the lack of hardware resources, it can be.
- TBD
Any suggestions and PRs and issues are WELCOME :)
HyeongChan Kim / @kozistr