Datasets

Here are the details for preprocessing datasets in 2 steps. We provide the preprocess tools for

• celeba
• facescrub
• ffhq64
• ffhq256
• metfaces256
• afhqdog256

Note that when using the celeba64 and facescrub64 datasets you can directly use the transform Resize((64,64)) in torchvision on celeba112 and facescrub112 datasets respectively.

Step 1: Download datasets

Celeba

Download celeba dataset from here.

The structure of the dataset is as follows:

<DOWNLOAD_PATH>
├── img_align_celeba
├── identity_CelebA.txt
├── list_attr_celeba.txt
├── list_bbox_celeba.txt
├── list_eval_partition.txt
├── list_landmarks_align_celeba.txt
└── list_landmarks_celeba.txt

For celeba with low resolution, you can directly use your download file above for step 3.

For celeba with high resolution (e.g. $224\times 224$), you need to follow HD-CelebA-Cropper to increase the resolution of the cropped and aligned samples. Run the script of the cropper and replace all the images in img_align_celeba.

python align.py --crop_size_h 224 --crop_size_w 224 --order 3 --save_format png --face_factor 0.65 --n_worker 32

FaceScrub

Use this script to download facescrub and some links are unavailable.

The structure of the dataset is as follows:

<DOWNLOAD_PATH>
├── actors
│   └── faces
└── actresses
    └── faces

FFHQ

For ffhq64, download thumbnails128x128.

For ffhq256, download images1024x1024.

MetFaces

Download here.

afhqdog

Follow StyleGAN2-ada to download afhqdog dataset.

python dataset_tool.py --source=~/downloads/afhq/train/dog --dest=~/datasets/afhqdog.zip

Step 2: Preprocess data

Fill the relative path for relative scripts in examples/standard/datasets and run the scripts. Note that FaceScrub dataset do not need to be preprocessed. The parameters are as follows:

• src_path: The path for the dataset you download.
• dst_path: The path for the preprocessed dataset.
• split_file_path: Only celeba need this parameter. We provide split files to split the dataset into train and test subset for celeba. Split files are available at here. Note that you need to unzip the file.

The file structure of split files for celeba is as follows:

split_files/
├── private_test.txt
├── private_train.txt
└── public.txt