Skip to content
master
Switch branches/tags
Code

Files

Permalink
Failed to load latest commit information.
Type
Name
Latest commit message
Commit time
img
Jul 27, 2017
Jun 19, 2017
Feb 22, 2018
Feb 25, 2020
fix
Jul 28, 2019
Aug 19, 2019
Jul 28, 2019

Super Resolution Examples

We run this script under TensorFlow 2.0 and the TensorLayer 2.0+. For TensorLayer 1.4 version, please check release.

🚀🚀🚀🚀🚀🚀 THIS PROJECT WILL BE CLOSED AND MOVED TO THIS FOLDER IN A MONTH.

🚀🚀🚀🚀🚀🚀 THIS PROJECT WILL BE CLOSED AND MOVED TO THIS FOLDER IN A MONTH.

🚀🚀🚀🚀🚀🚀 THIS PROJECT WILL BE CLOSED AND MOVED TO THIS FOLDER IN A MONTH.

SRGAN Architecture

TensorFlow Implementation of "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network"

Results

Prepare Data and Pre-trained VGG

    1. You need to download the pretrained VGG19 model in here as tutorial_models_vgg19.py show.
    1. You need to have the high resolution images for training.
    • In this experiment, I used images from DIV2K - bicubic downscaling x4 competition, so the hyper-paremeters in config.py (like number of epochs) are seleted basic on that dataset, if you change a larger dataset you can reduce the number of epochs.
    • If you dont want to use DIV2K dataset, you can also use Yahoo MirFlickr25k, just simply download it using train_hr_imgs = tl.files.load_flickr25k_dataset(tag=None) in main.py.
    • If you want to use your own images, you can set the path to your image folder via config.TRAIN.hr_img_path in config.py.

Run

config.TRAIN.img_path = "your_image_folder/"
  • Start training.
python train.py
  • Start evaluation.
python train.py --mode=evaluate 

Reference

Author

Citation

If you find this project useful, we would be grateful if you cite the TensorLayer paper:

@article{tensorlayer2017,
author = {Dong, Hao and Supratak, Akara and Mai, Luo and Liu, Fangde and Oehmichen, Axel and Yu, Simiao and Guo, Yike},
journal = {ACM Multimedia},
title = {{TensorLayer: A Versatile Library for Efficient Deep Learning Development}},
url = {http://tensorlayer.org},
year = {2017}
}

Other Projects

Discussion

License