timlenardo/celeb-faces-128x128 dataset hosted on Hugging Face and contributed by the HF Datasets community

Nykiz/pixel-images-128x128 dataset hosted on Hugging Face and contributed by the HF Datasets community

Original dataset: https://www.kaggle.com/arnaud58/flickrfaceshq-dataset-ffhq

This dataset contains the same images as the FFHQ dataset, downscaled to 256x256, 128x128, and 64x64 pixels, to make them easier to use in smaller generative models.

This datasets consists of various real images, as well as their corresponding depth images. The original real images can be found under the directory "input". The corresponding depth images of the aforementioned RGB faces images, can be found under the directory "depth128x128" with a smaller dimension of only 128x128 pixels. The folder "PTI" is the image generated from the PTI inverted code, based on the initial real images. The results from PTI inversion result to these generated images. The latent code from a slightly different PTI inversion can be found as numpy arrays under the directory "latent" and then again, the results from this method, are found under the directory "latent_synthesis"

Repack Information

This repository contains a complete repack of ILSVRC/imagenet-1k in Parquet format with the following data transformations:

Images were center-cropped to square to the minimum height/width dimension. Images were then rescaled to 256x256 using Lanczos resampling. This dataset is available at benjamin-paine/imagenet-1k-256x256 Images were then rescaled to 128x128 using Lanczos resampling. This dataset is available at benjamin-paine/imagenet-1k-128x128. Images were… See the full description on the dataset page: https://huggingface.co/datasets/benjamin-paine/imagenet-1k-64x64.

CelebA-128x128

CelebA with attrs at 128x128 resolution.

  Dataset Information

The attributes are binary attributes. The dataset is already split into train/test/validation sets. This dataset has been reduced so there's 160k train samples.

  Citation

@inproceedings{liu2015faceattributes, title = {Deep Learning Face Attributes in the Wild}, author = {Liu, Ziwei and Luo, Ping and Wang, Xiaogang and Tang, Xiaoou}, booktitle = {Proceedings of International… See the full description on the dataset page: https://huggingface.co/datasets/tpremoli/CelebA-attrs-160k.