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Merge pull request #204 from tensorlayer/fix_md
fix vgg link
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README.md

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@@ -44,7 +44,7 @@ TensorFlow Implementation of ["Photo-Realistic Single Image Super-Resolution Usi
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### Prepare Data and Pre-trained VGG
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- 1. You need to download the pretrained VGG19 model in [here](https://mega.nz/#!xZ8glS6J!MAnE91ND_WyfZ_8mvkuSa2YcA7q-1ehfSm-Q1fxOvvs) as [tutorial_vgg19.py](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_vgg19.py) show.
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- 1. You need to download the pretrained VGG19 model in [here](https://github.com/tensorlayer/pretrained-models/tree/master/models) as [tutorial_models_vgg19.py](https://github.com/tensorlayer/tensorlayer/blob/master/examples/pretrained_cnn/tutorial_models_vgg19.py) show.
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- 2. You need to have the high resolution images for training.
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- In this experiment, I used images from [DIV2K - bicubic downscaling x4 competition](http://www.vision.ee.ethz.ch/ntire17/), 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.
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- If you dont want to use DIV2K dataset, you can also use [Yahoo MirFlickr25k](http://press.liacs.nl/mirflickr/mirdownload.html), just simply download it using `train_hr_imgs = tl.files.load_flickr25k_dataset(tag=None)` in `main.py`.

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