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  • Rank 103,930 (Top 3 %)
  • Language
    Python
  • License
    MIT License
  • Created over 7 years ago
  • Updated over 1 year ago

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Repository Details

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

Pixel Recursive Super Resolution

TensorFlow implementation of Pixel Recursive Super Resolution. This implementation contains:

model

Requirements

Usage

First, download data celebA

$ 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

Training details

cross entropy loss:

curve.png

Author

nilboy / @nilboy