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GrayScale data

Open AboMad opened this issue 4 years ago • 0 comments

Hi there, I am trying to apply this SNGAN implementation on grayscale cell images, my data size is quite enough large ~ 100,000 images. I have used resnet architecture models edited by adding an extra layer to generate/discriminate 64 pxl images and gan loss. By training the model about 15K iterations (~ 10 epochs) I could not recognize visual improvement for the generated samples as they suffer from checkboard and grid artifacts. The training curves are shown below:

Disc_losses Gen_losses

I am not sure if I have to train for a longer time (more epochs), however, the training curves and the visual samples indicate abnormal case! Any advice, please.

AboMad avatar Aug 15 '20 11:08 AboMad