I’ve been experimenting with pix2pix and I’m literally loving it. This is such a great tool to create various image to image mappings.
I’ve currently made some modifications to get it to support 48-bit PNG support. This allows to represent 65536 values instead of the usual 256 values allowing for a higher resolution of data to be stored in an image. The network doesn’t really care because it all gets converted to float values anyway.
Hope this helps someone. I’ve forked the repo at: https://github.com/tharindu-mathew/pytorch-CycleGAN-and-pix2pix
Vid2vid seems to be a promising technique for video synthesis using GANs, as of 2019, which is similar in spirit to it’s image counterpart, pix2pix. When setting this up, I found there are some additional requirements needed, than what’s stated at: https://github.com/NVIDIA/vid2vid.
I created my own environment.yml to make this setup easier (pytorch is specifically for CUDA 9.1, CUDNN 7.1.2, but you can edit the yml file and swap out this version based on the available pytorch versions, and it should work).
The gist is available at: https://gist.github.com/tharindu-mathew/7f79433d92d884fa662f6ccf023537e1