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https://github.com/nilboy/pixel-recursive-super-resolution

Tensorflow implementation of pixel-recursive-super-resolution(Google Brain paper: https://arxiv.org/abs/1702.00783)
https://github.com/nilboy/pixel-recursive-super-resolution

pixelcnn pixelrnn super-resolution tensorflow

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Tensorflow implementation of pixel-recursive-super-resolution(Google Brain paper: https://arxiv.org/abs/1702.00783)

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# Pixel Recursive Super Resolution

TensorFlow implementation of [Pixel Recursive Super Resolution](https://arxiv.org/abs/1702.00783). This implementation contains:

![model](./assets/model.png)

## Requirements

- Python 2.7
- [Skimage](http://scikit-image.org/)
- [TensorFlow](https://www.tensorflow.org/) 1.0

## Usage

First, download data [celebA](http://mmlab.ie.cuhk.edu.hk/projects/CelebA.html)

$ mkdir data
$ cd data
$ ln -s $celebA_path celebA

Then, create image_list file:

$ python tools/create_img_lists.py --dataset=data/celebA --outfile=data/train.txt

To train model on gpu:

$ python tools/train.py
(or $ python tools/train.py --device_id=0)

To train model on cpu:
$ python tools/train.py --use_gpu=False

## Samples

Training after 30000 iteration.

![sample.png](./assets/sample.png)

## Training details

cross entropy loss:

![curve.png](./assets/curve.png)

## Author

nilboy / [@nilboy](https://github.com/nilboy)