Closed bladenow closed 3 years ago
Thanks for your interest! (🖒^^)🖒 To be clear, could you provide more details about the "mask"? (Eg: facial segmentation, UV-map-segmentation, etc.). Without further information, I'm not sure I can address your question properly.
But in general, I hope you're looking for "one of these masks": facial segmentation or UV-segmentation
To get facial segmentation, I used [face-parsing.Pytorch]
_(Face-parsing will give you facial attributes such as upper lip, lower lip, left eye, right eye, hair, etc. Check here for details)_
P.s: Existing makeup datasets (LADN, BeautyGAN) already have facial segmentation within them.
Check how to get "respective UV-map texture of each image and its segmentation mask", section 2 - Get UV texture (To be specific, uv_seg is what you need) https://github.com/VinAIResearch/CPM/blob/315b89dc8bef70fde99fdf4c7b3f35e9c8c2e461/Color/create_beautygan_uv.py#L51
Glad to help! ᕦ( ͡° ͜ʖ ͡°)ᕤ
Thank you very much for your reply so soon. SEGS directory, with what code?
segs | makeup |__ non-makeup
Hello, which dataset you're talking about? CPM-Synt-1, CPM-Synt-2, or Makeup Transfer Dataset? Pls check here .
Makeup Transfer Datase
Oh I think you're talking about Makeup Transfer Dataset (published with BeautyGAN paper). They already provided facial segmentation masks!
In their paper, they said that they used PSPNet. Please check in their paper.
For me, I recommend using face-parsing.Pytorch. Please check!
Thank you very much!!!
Thank you very much for your great work! Can you publish data preprocessing code? Is there no code to extract the mask or I missed it