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MakeupGAN
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MakeupGAN
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# MakeupGAN This is an implementation of a unpaired MakeUp Generator Architecture for GAN on tensorflow. The model generates makeup image from no-makeup face or vice versa. # Getting Started * ([BeautyGAN.py](/libs/network/BeautyGAN.py), [config.py](/libs/configs/config.py)): These files are the main MakeupGAN network. * ([datapipe.py](/datasets/datapipe.py)): This file's role is loading and changing to tensor your dataset taht are in makeup_dataset folder which is consist of image and segs(mask) folder. The image folder contain makeup image and no-makeup image folder and the segs folder have 3 partial region that are eye, shadow, lips. * ([pretrained_models](/pretrained_models)): you put the pretrained ([VGG 19](http://download.tensorflow.org/models/vgg_19_2016_08_28.tar.gz)) model in this folder. * ([train.py](/train.py)): this file is for training. To train this network ''' python train.py ''' * ([inference.py](/inference.py)): this file is for inference. we have 2 inference mode that are reference style and random style and you set True or False on --rand_style value. To run this file ''' python infernece.py ''' # Result <table > <tr > <td><center>no-makeup</center></td> <td><center>makeup</center></td> </tr> <tr> <td> <center><img src="/result/case2/oriA.jpg"></center> </td> <td> <center><img src="/result/case2/oriB.jpg"></center> </td> </tr> <tr > <td><center>Generated makeup image</center></td> <td><center>Generated no-makeup image</center></td> </tr> <tr> <td> <center><img src="/result/case2/fake_AB.jpg"></center> </td> <td> <center><img src="/result/case2/fake_BA.jpg"></center> </td> </tr> </table>
