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zllrunning

face-parsing.PyTorch

Using modified BiSeNet for face parsing in PyTorch.

ModelsVision modelsPython
Open on GitHub
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2.59k
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497
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This week
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Created 2019-04-18 · Updated 2026-10-10 · #8494 today
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zllrunning

zllrunning/face-parsing.PyTorch is ranked 8,494 with 2,593 stars.

Same-category comparison

zllrunning/face-parsing.PyTorch is ranked 8,494 among these 8 peers; baaivision/Painter is ranked 8,488.

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Key parameters and specifications
Key parameters and specifications
ParameterValue
LanguagePython
CategoryModels
SubcategoryVision models
Stars2,593
Forks497
Contributors1
Created date2019-04-18
Updated date2026-10-10
Stars in 1 day0
Stars in 7 days1
Rank8,494
Previous rank8,555
Rank change61
7-day stars rank9,335
Previous 7-day stars rank7,788
7-day stars rank change-1,547
Total stars rank5,129
Previous total stars rank5,122
Total stars rank change-7
CountryChina
README summary

PyTorch Contents Training Demo References Training 1. Train the model using CelebAMask-HQ dataset: Just run the train script: If you do not wish to train the model, you can download our pre-trained model and save it in . Evaluate the trained model using: Face makeup using parsing maps **face-makeup. PyTorch** Hair Lip Original Input Color References BiSeNet

Frequently asked questions

How many stars and forks are recorded?

zllrunning/face-parsing.PyTorch has 2,593 stars and 497 forks.

What is the repository rank?

zllrunning/face-parsing.PyTorch is ranked 8,494.

What language and category are recorded?

zllrunning/face-parsing.PyTorch has 2,593 stars, uses Python and belongs to Models.

Which repository is closest in rank?

zllrunning/face-parsing.PyTorch is compared with baaivision/Painter, ranked 8,488 with 2,600 stars.

README

face-parsing.PyTorch

[![](https://github.com/zllrunning/face-parsing.PyTorch/blob/master/6.jpg)](https://github.com/zllrunning/face-parsing.PyTorch)

Contents

Training

  1. Prepare training data: -- download CelebAMask-HQ dataset

    -- change file path in the prepropess_data.py and run

python prepropess_data.py
  1. Train the model using CelebAMask-HQ dataset: Just run the train script:
    $ CUDA_VISIBLE_DEVICES=0,1 python -m torch.distributed.launch --nproc_per_node=2 train.py

If you do not wish to train the model, you can download our pre-trained model and save it in res/cp.

Demo

  1. Evaluate the trained model using:
# evaluate using GPU
python test.py

Face makeup using parsing maps

face-makeup.PyTorch

 

Hair

Lip

Original Input

Color

References

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