Aditya Agarwal

Please refer to the solution here - https://github.com/YuvalNirkin/fsgan/issues/70

> Hi, > > We have a dataset where a liquid flowing in the water from right to left. We are trying to generate similar videos using StyleGAN-V. But the...

I tried debugging the issue quickly, but the problem seems to be emanating from the value of the parameter `c.resume` in the `train.py` file. Even though the flag `training.resume=latest` is...

For the rainbow jelly dataset, the generated images have a white background whereas the real images have a black background. Please find some samples here --   The training...

I see, I will follow this advice and retrain the network on all the datasets. I don't remember the exact number of k images that I trained the network for,...

I will train with augmentations disabled on the smaller datasets in that case. I don't think generating and manually inverting 2048-generated videos would be a good idea.

@universome I tried running with augmentation disabled using the flag `augpip: noaug`, and I get an AssertionError - `assert c.augpipe is None or c.augpipe in augpipe_specs`. From what I understand,...

Would it be this particular option in the base.yaml file under configs/training? `aug: noaug # One of ['noaug', 'ada', 'fixed']` Also what should be the disc augmentation to avoid the...

So the augmentations specified in the `"augpipe"` parameter are applied. Supplying `noaug` to the "aug" parameter disables augmentations. There are however two other modes that can be supplied - `'ada'`,...

Hahaha yeah, this was when I was in my second year. You should check out my python implementation. Thanks for pointing out @PayasR , I will update it.