Comments (6)
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
Facial 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.
UV map segmentation
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)
CPM/Color/create_beautygan_uv.py
Line 51 in 315b89d
Glad to help! ᕦ( ͡° ͜ʖ ͡°)ᕤ
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Thank you very much for your reply so soon.
SEGS directory, with what code?
__ segs
|__ makeup
|__ non-makeup
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Hello, which dataset you're talking about?
CPM-Synt-1, CPM-Synt-2, or Makeup Transfer Dataset? Pls check here .
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Makeup Transfer Datase
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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!
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Thank you very much!!!
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Related Issues (20)
- how to render uv map to normal image? HOT 2
- Setup throwing error HOT 3
- the code is too bad! waste my time!!! HOT 1
- It work so bad!!!!!!!!! HOT 1
- ValueError: The passed save_path is not a valid checkpoint: ./PRNet/net-data/256_256_resfcn256_weight HOT 2
- Suggest to loosen the dependency on albumentations HOT 2
- Training on new dataset HOT 3
- I directly input the UV texture image, how should I modify the code? HOT 5
- AttributeError: module 'segmentation_models_pytorch' has no attribute 'utils' HOT 1
- About the MT dataset HOT 2
- No module named 'blend_modes
- MT dataset HOT 1
- image-invariant region mask HOT 1
- No module named 'segmentation_models_pytorch.unet'
- No module named 'blend_modes'
- The corresponding package cannot be installed in colab and locally, because of the mac device? HOT 1
- Part of the face changes? HOT 1
- The performance of the code can not match the picture in README HOT 4
- RuntimeError: Unsupported image type, must be 8bit gray or RGB image. HOT 2
- The sticker order in the Stickers dataset is incorrect HOT 1
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