MKZuziak/cifar10h
CIFAR-10H Hugging Face Dataset This repository contains a Hugging Face dataset build of CIFAR-10H, an extension of the CIFAR-10 test set with human-annotated label distributions. Dataset Description CIFAR-10H adds human uncertainty information to the CIFAR-10 test images by providing: expert_probs: probability distributions over the 10 CIFAR-10 classes expert_counts: raw human vote counts for each class expert_argmax: one-hot encoded labels from the… See the full description on the dataset page: https://huggingface.co/datasets/MKZuziak/cifar10h.
CIFAR-10H Hugging Face Dataset
This repository contains a Hugging Face dataset build of CIFAR-10H, an extension of the CIFAR-10 test set with human-annotated label distributions.
Dataset Description
CIFAR-10H adds human uncertainty information to the CIFAR-10 test images by providing:
expert_probs: probability distributions over the 10 CIFAR-10 classesexpert_counts: raw human vote counts for each classexpert_argmax: one-hot encoded labels from the human-majority choice- 'exper_correct': boolean value encoding if expert was correct based on the human-majority choice.
The dataset is constructed from the original CIFAR-10 test images together with the CIFAR-10H annotation files.
Original Citation
Please credit the original CIFAR-10H authors when using this dataset:
Peterson, Joshua C.; Battleday, Ruairidh M.; Griffiths, Thomas L.; Russakovsky, Olga. "Human uncertainty makes classification more robust." arXiv preprint arXiv:1908.07086, 2019.
Source repository: https://github.com/jcpeterson/cifar-10h
This HuggingFace conversion was done Zuziak, Maciej K.