GANimation: Anatomically-aware Facial Animation from a Single Image

[Project] [Paper]

Official implementation of GANimation. In this work we introduce a novel GAN conditioning scheme based on Action Units (AU) annotations, which describe in a continuous manifold the anatomical facial movements defining a human expression. Our approach permits controlling the magnitude of activation of each AU and combine several of them. For more information please refer to the paper.

This code was made public to share our research for the benefit of the scientific community. Do NOT use it for immoral purposes.

依赖项与Python环境 Prerequisites

CentOS 7
Install CUDA, cuDNN
Install Python2.7 安装Python2.7
Install PyTorch (version 0.3.1), Torch Vision and dependencies from http://pytorch.org
Install requirements.txt (pip install -r requirements.txt) (更新了该文件，可以直接安装。)

数据准备 Data Preparation

The code requires a directory containing the following files:

imgs/: folder with all image 所有图像.
aus_openface.pkl: dictionary containing the images action units. 面部肌肉表情运动字典.
train_ids.csv: file containing the images names to be used to train. 要训练的所有图像名字.
test_ids.csv: file containing the images names to be used to test. 要测试的所有图像名字.

An example of this directory is shown in sample_dataset/. 这个目录下有一个样例。

To generate the aus_openface.pkl extract each image Action Units with OpenFace and store each output in a csv file the same name as the image. Then run:

python data/prepare_au_annotations.py

依次运行 Run

由于版权问题，作者无权发布数据集，也没有分享生成的模型。如有需要，要自己获得数据、生成模型。

To train:

bash launch/run_train.sh (也可以直接运行Python脚本 / also can run python file directly.)

举个具体的例子 Take an example ：

python train.py --data_dir /data/dl_code/GANimation/sample_dataset --name experiment_1 --batch_size 25

To test:

python test --input_path path/to/img

举个具体的例子 Take an example ：

python test.py --input_path /data/dl_code/GANimation/sample_dataset/imgs/N_0000000356_00190.jpg

遵守协议,表示尊重,添加引用 Citation

If you use this code or ideas from the paper for your research, please cite our paper:

@article{Pumarola_ijcv2019,
    title={GANimation: One-Shot Anatomically Consistent Facial Animation},
    author={A. Pumarola and A. Agudo and A.M. Martinez and A. Sanfeliu and F. Moreno-Noguer},
    booktitle={International Journal of Computer Vision (IJCV)},
    year={2019}
}

参考文献 Reference

[论文阅读：GANimation: Anatomically-aware Facial Animation from a Single Image] (https://blog.csdn.net/tobale/article/details/83587140)

jibbers42 / GANimation