mirror of
https://github.com/Deepshift/DeepCreamPy.git
synced 2024-12-03 01:02:56 +00:00
18 lines
1.2 KiB
Markdown
18 lines
1.2 KiB
Markdown
# FAQ
|
|
|
|
## Where can I get your training data?
|
|
I can't say what my data sources are because too many people downloading from them could cause them to block scraping.
|
|
[Danbooru2018](https://www.gwern.net/Danbooru2018) is a good starting point.
|
|
|
|
## Where can I get your training code?
|
|
My training code is is modified from Forty-lock's project [PEPSI](https://github.com/Forty-lock/PEPSI), which is the official implementation of the paper [PEPSI : Fast Image Inpainting With Parallel Decoding Network](http://openaccess.thecvf.com/content_CVPR_2019/html/Sagong_PEPSI__Fast_Image_Inpainting_With_Parallel_Decoding_Network_CVPR_2019_paper.html). [PEPSI](https://github.com/Forty-lock/PEPSI) is licensed under the MIT license.
|
|
|
|
## Why aren't black and white images supported? Black and white images seem easier to decensor than color images.
|
|
Black and white images contain screentone patterns which are difficult for neural networks to replicate.
|
|
|
|
## Some censor bars are transparent, but DeepCreamPy ignores the partially visible art. Could you train a neural network that doesn't?
|
|
It's on my to-do list, but it's not a high priority.
|
|
|
|
## Does this work with real life porn?
|
|
DeepCreamPy is not trained on real life porn, so it will not work with real life porn.
|