# AttGAN-Tensorflow **Repository Path**: idoltgy/AttGAN-Tensorflow ## Basic Information - **Project Name**: AttGAN-Tensorflow - **Description**: AttGAN Tensorflow, AttGAN: Facial Attribute Editing by Only Changing What You Want - **Primary Language**: Unknown - **License**: MIT - **Default Branch**: master - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2020-08-28 - **Last Updated**: 2020-12-19 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README ***New*** - 11 Jan 2020: We clean up the code to make it more readable! The old version is here: [v1](https://github.com/LynnHo/AttGAN-Tensorflow/tree/v1).

     

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[AttGAN](https://ieeexplore.ieee.org/document/8718508?source=authoralert)
[TIP Nov. 2019](https://ieeexplore.ieee.org/document/8718508?source=authoralert), [arXiv Nov. 2017](https://arxiv.org/pdf/1711.10678v1.pdf)

**TensorFlow** implementation of **AttGAN**: Facial Attribute Editing by Only Changing What You Want.

## Related - Other implementations of AttGAN - [AttGAN-PyTorch](https://github.com/elvisyjlin/AttGAN-PyTorch) by Yu-Jing Lin - [AttGAN-PaddlePaddle](https://github.com/PaddlePaddle/models/tree/develop/PaddleCV/gan) by ceci3 and zhumanyu (**AttGAN is one of the official reproduced models of [PaddlePaddle](https://github.com/PaddlePaddle?type=source)**) - Closely related works - **An excellent work built upon our code - [STGAN](https://github.com/csmliu/STGAN) (CVPR 2019) by Ming Liu** - [Changing-the-Memorability](https://github.com/acecreamu/Changing-the-Memorability) (CVPR 2019 MBCCV Workshop) by acecreamu - [Fashion-AttGAN](https://github.com/ChanningPing/Fashion_Attribute_Editing) (CVPR 2019 FSS-USAD Workshop) by Qing Ping - An unofficial [demo video](https://www.youtube.com/watch?v=gnN4ZjEWe-8) of AttGAN by 王一凡 ## Exemplar Results - See [results.md](./results.md) for more results, we try **higher resolution** and **more attributes** (all **40** attributes!!!) - Inverting 13 attributes respectively from left to right: *Input, Reconstruction, Bald, Bangs, Black_Hair, Blond_Hair, Brown_Hair, Bushy_Eyebrows, Eyeglasses, Male, Mouth_Slightly_Open, Mustache, No_Beard, Pale_Skin, Young* ## Usage - Environment - Python 3.6 - TensorFlow 1.15 - OpenCV, scikit-image, tqdm, oyaml - *we recommend [Anaconda](https://www.anaconda.com/distribution/#download-section) or [Miniconda](https://docs.conda.io/en/latest/miniconda.html#linux-installers), then you can create the AttGAN environment with commands below* ```console conda create -n AttGAN python=3.6 source activate AttGAN conda install -c anaconda opencv conda install -c anaconda scikit-image conda install -c anaconda tqdm conda install -c conda-forge oyaml conda install -c anaconda tensorflow-gpu=1.15 ``` - Data Preparation - Option 1: [CelebA](http://openaccess.thecvf.com/content_iccv_2015/papers/Liu_Deep_Learning_Face_ICCV_2015_paper.pdf)-unaligned (higher quality than the aligned data, 10.2GB) - download the dataset - img_celeba.7z (move to **./data/img_celeba/img_celeba.7z**): [Google Drive](https://drive.google.com/drive/folders/0B7EVK8r0v71pTUZsaXdaSnZBZzg) or [Baidu Netdisk](https://pan.baidu.com/s/1eSNpdRG#list/path=%2Fsharelink2785600790-938296576863897%2FCelebA%2FImg&parentPath=%2Fsharelink2785600790-938296576863897) - annotations.zip (move to **./data/img_celeba/annotations.zip**): [Google Drive](https://drive.google.com/file/d/1xd-d1WRnbt3yJnwh5ORGZI3g-YS-fKM9/view?usp=sharing) - unzip and process the data ```console 7z x ./data/img_celeba/img_celeba.7z/img_celeba.7z.001 -o./data/img_celeba/ unzip ./data/img_celeba/annotations.zip -d ./data/img_celeba/ python ./scripts/align.py ``` - Option 2: CelebA-HQ (we use the data from [CelebAMask-HQ](https://github.com/switchablenorms/CelebAMask-HQ), 3.2GB) - CelebAMask-HQ.zip (move to **./data/CelebAMask-HQ.zip**): [Google Drive](https://drive.google.com/open?id=1badu11NqxGf6qM3PTTooQDJvQbejgbTv) or [Baidu Netdisk](https://pan.baidu.com/s/1wN1E-B1bJ7mE1mrn9loj5g) - unzip and process the data ```console unzip ./data/CelebAMask-HQ.zip -d ./data/ python ./scripts/split_CelebA-HQ.py ``` - Run AttGAN - *NOTICE: if you create a new conda environment, remember to activate it before any command* ```console source activate AttGAN ``` - training (see [examples.md](./examples.md) for more training commands) ```console \\ for CelebA CUDA_VISIBLE_DEVICES=0 \ python train.py \ --load_size 143 \ --crop_size 128 \ --model model_128 \ --experiment_name AttGAN_128 \\ for CelebA-HQ CUDA_VISIBLE_DEVICES=0 \ python train.py \ --img_dir ./data/CelebAMask-HQ/CelebA-HQ-img \ --train_label_path ./data/CelebAMask-HQ/train_label.txt \ --val_label_path ./data/CelebAMask-HQ/val_label.txt \ --load_size 128 \ --crop_size 128 \ --n_epochs 200 \ --epoch_start_decay 100 \ --model model_128 \ --experiment_name AttGAN_128_CelebA-HQ ``` - testing - **single** attribute editing (inversion) ```console \\ for CelebA CUDA_VISIBLE_DEVICES=0 \ python test.py \ --experiment_name AttGAN_128 \\ for CelebA-HQ CUDA_VISIBLE_DEVICES=0 \ python test.py \ --img_dir ./data/CelebAMask-HQ/CelebA-HQ-img \ --test_label_path ./data/CelebAMask-HQ/test_label.txt \ --experiment_name AttGAN_128_CelebA-HQ ``` - **multiple** attribute editing (inversion) example ```console \\ for CelebA CUDA_VISIBLE_DEVICES=0 \ python test_multi.py \ --test_att_names Bushy_Eyebrows Pale_Skin \ --experiment_name AttGAN_128 ``` - attribute sliding example ```console \\ for CelebA CUDA_VISIBLE_DEVICES=0 \ python test_slide.py \ --test_att_name Pale_Skin \ --test_int_min -2 \ --test_int_max 2 \ --test_int_step 0.5 \ --experiment_name AttGAN_128 ``` - loss visualization ```console CUDA_VISIBLE_DEVICES='' \ tensorboard \ --logdir ./output/AttGAN_128/summaries \ --port 6006 ``` - convert trained model to .pb file ```console python to_pb.py --experiment_name AttGAN_128 ``` - Using Trained Weights - alternative trained weights (move to **./output/\*.zip**) - [AttGAN_128.zip](https://drive.google.com/file/d/1Oy4F1xtYdxj4iyiLyaEd-dkGIJ0mwo41/view?usp=sharing) (987.5MB) - *including G, D, and the state of the optimizer* - [AttGAN_128_generator_only.zip](https://drive.google.com/file/d/1lcQ-ijNrGD4919eJ5Dv-7ja5rsx5p0Tp/view?usp=sharing) (161.5MB) - *G only* - [AttGAN_384_generator_only.zip](https://drive.google.com/open?id=1scaKWcWIpTfsV0yrWCI-wg_JDmDsKKm1) (91.1MB) - unzip the file (AttGAN_128.zip for example) ```console unzip ./output/AttGAN_128.zip -d ./output/ ``` - testing (see above) - Example for Custom Dataset - [AttGAN-Cartoon](https://github.com/LynnHo/AttGAN-Cartoon-Tensorflow) ## Citation If you find [AttGAN](https://ieeexplore.ieee.org/document/8718508?source=authoralert) useful in your research work, please consider citing: @ARTICLE{8718508, author={Z. {He} and W. {Zuo} and M. {Kan} and S. {Shan} and X. {Chen}}, journal={IEEE Transactions on Image Processing}, title={AttGAN: Facial Attribute Editing by Only Changing What You Want}, year={2019}, volume={28}, number={11}, pages={5464-5478}, keywords={Face;Facial features;Task analysis;Decoding;Image reconstruction;Hair;Gallium nitride;Facial attribute editing;attribute style manipulation;adversarial learning}, doi={10.1109/TIP.2019.2916751}, ISSN={1057-7149}, month={Nov},}