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Jul 15, 2019
Jul 15, 2019
Jul 15, 2019
Jul 15, 2019
Jul 15, 2019

DMT

TensorFlow implementation of Disentangled Makeup Transfer with Generative Adversarial Network

The facial images are disentangled into identity codes and makeup codes to achieve diverse scenarios of makeup transfer

Results

pairwise makeup transfer

interpolated makeup transfer

hybrid makeup transfer

multimodal makeup transfer

Files

  • main.py: the main code
  • dmt.pb: the pre-trained model
  • faces: images of makeup and non-makeup faces
  • output: the generated images

Usage

python main.py

If you want to use other non-makeup or makeup images, set the paths to the target images

no_makeup = os.path.join('faces', 'no_makeup', 'xfsy_0055.png')
makeup_a = os.path.join('faces', 'makeup', 'XMY-074.png')
makeup_b = os.path.join('faces', 'makeup', 'vFG112.png')

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