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I'm not familiar with the implementationd details, but convolutions usually use zero-padding. If you use circular padding instead, your network can learn tileable features.

In pytorch for example, you can supply padding_mode = 'circular' to Conv2D.

I'd like to add to this, since I had nothing but trouble installing whatever was necessary, and kept getting the "Microsoft Visual C++ 14.0 is required" error. Finally I've managed to fix this by going here: https://visualstudio.microsoft.com/vs/older-downloads/ and then under "Redistributables and Build Tools" downloading and installing the "Microsoft Build Tools 2015 Update 3". Then the installation went through without an error.

FYI the alpha release is now live here.

There's room for improvement especially with masked textures - I've tried a few different techniques but I'm not 100% happy with any particular one. Not sure how other people handle alpha masking.

No I get it, but the results I seen where other people had remastered other games with AI algorithms were way better than anything I had achieved with just Gigapixel. I have since ran the texture images through a site called https://letsenhance.io/boost and brought out more hidden detail with their texture enhancement option. I have since taken the images I ran through there, and ran those again through Gigapixel and they are looking much better than they ever did before, more akin to what I was hoping for.

I would still welcome anybody that would like to help retexture our playermodels though like in the same vein as that 1942 4K remaster mod. That was what I was hoping to have done eventually but having the most difficult time finding a person interested in doing it. Which is why I went this route.

It's possible to use ImageMagick to transfer the alpha of one image to another.

convert (file without alpha) (file with alpha) -compose CopyOpacity -composite output.png

I wrote a batch script for getting it done in Linux a few months ago, but I don't know how to do it in Windows.

I downloaded it from here: http://www.radgametools.com/bnkdown.htm

Password works for me. Make sure you open it with 7zip and type it in exactly (uppercase and no spaces).

Visual Guide

If you don't know where Python.exe is, you can use voidtool's Everything to search through all filenames.

I used Win+Shift+S to make and edit the screenshot. (The snipping tool is old news)

Yes and no. It is a complicated answer, one that you don't have to worry about right now it seems from what I have been looking at.

So with pyTorch, if you install it with the binaries aka not from source, you don't have to install the CUDA toolkit or CuDNN, since pyTorch comes packaged with those binaries. So if you used conda or pip to install pyTorch you don't need to install the CUDA toolkit or CuDNN. But one of the issues with that, is that it likely installs the binaries you ask it to include. So if you installed pyTorch when you had your 1070ti installed, you would ask it to install the binaries for Cuda 9.2.

So the downside is that pytorch is using those binaries instead of the updated CUDA Toolkit or an updated CuDNN if you had installed those. Now the good thing is that we can easily check to see what version of CUDA your pytorch install is using.

It is as simple as entering these commands into a command prompt

python import torch torch.version.cuda

There is no () in the 3rd line this time.

If it returns anything that is not 10.x or higher, than means you need to update pytorch to use the latests CUDA and CuDNN binaries and that is as simple as just installing pytorch again using Conda or Pip. There is no need to uninstall pytorch first, as the installing process will handle that for you.

https://pytorch.org/get-started/locally/