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mu-gan's Introduction

MU-GAN: Facial Attribute Editing based on Multi-attention Mechanism

Official implementation of MU-GAN

Requirements

*Python 3

*PyTorch 0.4.0

Useage

Train:

sudo CUDA_VISIBLE_DEVICES=x python3 train.py --img_size 128 --experiment_name 128_shortcut1_inject1_none --gpu --num_workers x --batch_size x

Test:

sudo CUDA_VISIBLE_DEVICES=x python3 test_x_x.py --experiment_name 128_shortcut1_inject1_none --test_int 1.0 --gpu --load_epoch x

Todo

Currently, the different variants of the code are in a mess. We will reorganize the code when we return to school.

Acknowledgements

This code refers to the projects:AttGAN-PyTorch Thanks for their excellent work！

mu-gan's People

Contributors

susir1996 avatar

Stargazers

zhangss avatar Abraham avatar avatar Tunan avatar avatar Rishikesh (ऋषिकेश) avatar Jason Liu avatar avatar avatar Biao Yang avatar welbeckzhou avatar Miles Gray avatar

Watchers

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Forkers

olavgg xiaolongcheng rcxd

mu-gan's Issues

Regarding Attribute Classfication accuracy

Hi,

I would like to appreciate your work on facial attribute manipulation.
Great work!!!!

I'm interested in re-implementing your work for a better understanding of facial attribute manipulation.
During the re-implementation process, while evaluating attribute classification accuracy using ResNet, I'm getting an accuracy of 35% using Resnet18 and 45% using ResNet101.

Could you please help me in providing the details of the Resnet variant used during your implementation and also the hyperparameters used for training the ResNet model?

Thanks in advance.

Regards,
Padmashree

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