search

Junshk / CinCGAN-pytorch

Unofficial Implementation of "Unsupervised Image Super-Resolution using Cycle-in-Cycle Generative Adversarial Networks" in CVPR 2018.
142 stars 27 forks source link

training data issue #10

Open wl082013 opened 5 years ago

wl082013 commented 5 years ago

Thank you Junshk so much for your good work. I tried to implement the code you wrote but since the instruction is quite ambiguous so I could not run it successfully. Could you help clarify how the training data is allocated? For instance, in the paper, it is said the HR images Z are from 400-800 training images from DIV2K, and input LR X are from 1-400 images. Besides, for Y (intermediate) are from the bicubic downsampling of HR images of Z, which means Y are also numbered as 401-800. However, when I tried the code it is said that '../dataset/DIV2K/DIV2K_train_HR/0015.png', which means you did not actually divide the HR and LR raw data from DIV2K right? Furthermore, the code is quite hard to understand, so could you please update or make a concise version? Thanks for you help.

PonderK commented 5 years ago

Hello, i have the same problems with you. I can not understand how to set the dataset just according to
such a ambiguous readme. Can you give me some suggesstions?Thank you very much! @Junshk @wl082013

wl082013 commented 4 years ago

Hi I did not run the code~! Have you tried successfully?