update readme

Author: zsdonghao

README.md

@@ -23,14 +23,17 @@ TensorFlow Implementation of ["Photo-Realistic Single Image Super-Resolution Usi
 </a>
 
 ### Prepare Data and Pre-trained VGG
-- In this experiment, we used images from [DIV2K - bicubic downscaling x4 competition](http://www.vision.ee.ethz.ch/ntire17/), besides [Yahoo MirFlickr25k](http://press.liacs.nl/mirflickr/mirdownload.html) is also a good choice. Alternatively, you can use your own data by setting your image folder in `config.py`.
 
-- Download VGG model as [tutorial_vgg19.py](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_vgg19.py) show.
+- 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.
+- 2. You need to have the high resolution images for training.
+  -  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. 
+  -  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`. 
+  -  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
-- Set your image folder in `config.py`.
+- Set your image folder in `config.py`, if you download [DIV2K - bicubic downscaling x4 competition](http://www.vision.ee.ethz.ch/ntire17/) dataset, you dont need to change it.
 
 ```python
 config.TRAIN.img_path = "your_image_folder/"