Tips & Tricks on training DCGAN on small dataset

Question

I have made a DCGAN which I am trying to train on custom dataset of only 1200 images. I have tried to gather more, but even gathering these 1200 was hard enough. If you are wondering I used Google Chromes extension "Fakun Batch Download Image" to gather my dataset.

TRAINING DETAILS: In training procedure I am simultaneously updating parameters of both, Generator, and Discriminator network. I've read that it works much better then training only one player ( Discriminator ) for K steps and then other ( Generator ) for one.

QUESTION: Should I perform maybe some kind of transformation on all of those images and then merge transformed images with the initial ones, or something similar?