license: mit
tags:
- image-classification
- computer-vision
- imagenet-c
Nano ImageNet-C (Severity 5)
This is a randomly sampled subset of the ImageNet-C dataset, containing 5,000 images exclusively from corruption severity level 5. It is designed for efficient testing and validation of model robustness.
这是一个从 ImageNet-C 数据集中随机抽样的子集，包含 5000 张仅来自损坏等级为 5 的图像。它旨在用于高效地测试和验证模型的鲁棒性。
How to Generate / 如何生成
This dataset was generated using the create_nano_dataset.py script included in this repository. To ensure reproducibility, the following parameters were used:
本数据集使用此仓库中包含的 create_nano_dataset.py 脚本生成。为确保可复现性，生成时使用了以下参数：
- Source Dataset / 源数据集: The full ImageNet-C dataset is required. / 需要完整的 ImageNet-C 数据集。
- Random Seed / 随机种子:
7600 - Python Version / Python 版本:
3.10.14
Dataset Structure / 数据集结构
The dataset is provided as a single .tar file named nano-imagenet-c.tar in the webdataset format. The internal structure preserves the original ImageNet-C hierarchy: corruption_type/class_name/image.jpg.
数据集以 webdataset 格式打包在名为 nano-imagenet-c.tar 的单个 .tar 文件中。其内部结构保留了原始 ImageNet-C 的层次结构：corruption_type/class_name/image.jpg。
Citation / 引用
If you use this dataset, please cite the original ImageNet-C paper:
如果您使用此数据集，请引用原始 ImageNet-C 的论文：
@inproceedings{danhendrycks2019robustness,
title={Benchmarking Neural Network Robustness to Common Corruptions and Perturbations},
author={Dan Hendrycks and Thomas Dietterich},
booktitle={International Conference on Learning Representations},
year={2019},
url={https://openreview.net/forum?id=HJz6tiCqYm},
}