images during training are too dark

[liminn]

Hi, thanks for sharing your great work! I follow your recommendation that use the The Paris Dataset to train the network. After training, when I check the result/train/real or result/train/cropped or result/train/recon folder, I found that all the images are too dark, such as this: real image: cropped image: recon image:

The result of inpainting is effective, but why all the image are so dark?

ps: I do not change anything of the code except dataset/train folder.

[silence1114]

I am training now, and I also have encountered this problem. I would like to ask, after you train the model, will the result be so dark too when testing?

[liminn]

@silence1114 I didn't test, beacuse I thought the test during training is same as test solely. Do you have other discoveries?

[C-H-D]

@liminn @silence1114 It's because of the normalize operationtransforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5)),doing unnormalization before output should solve the problem.real_cpu = real_cpu/2.0,real_cpu = real_cpu + 0.5,thenvutils.save_image(real_cpu, 'result/train/real/real_samples_epoch_%03d.png' % (epoch))

[geniusmissm]

@silence1114 ,I could you tell me how to run the procedure in windows，please！I don't quite understand .