Datasets:
metadata
license: cc-by-4.0
task_categories:
- image-classification
tags:
- imagenet
- corruption
- robustness
- tta
- test-time-adaptation
pretty_name: TTA ImageNet-C
size_categories:
- 1M<n<10M
configs:
- config_name: gaussian_noise
data_files:
- split: severity_1
path: data/gaussian_noise/severity_1/*.parquet
- split: severity_2
path: data/gaussian_noise/severity_2/*.parquet
- split: severity_3
path: data/gaussian_noise/severity_3/*.parquet
- split: severity_4
path: data/gaussian_noise/severity_4/*.parquet
- split: severity_5
path: data/gaussian_noise/severity_5/*.parquet
- config_name: shot_noise
data_files:
- split: severity_1
path: data/shot_noise/severity_1/*.parquet
- split: severity_2
path: data/shot_noise/severity_2/*.parquet
- split: severity_3
path: data/shot_noise/severity_3/*.parquet
- split: severity_4
path: data/shot_noise/severity_4/*.parquet
- split: severity_5
path: data/shot_noise/severity_5/*.parquet
- config_name: impulse_noise
data_files:
- split: severity_1
path: data/impulse_noise/severity_1/*.parquet
- split: severity_2
path: data/impulse_noise/severity_2/*.parquet
- split: severity_3
path: data/impulse_noise/severity_3/*.parquet
- split: severity_4
path: data/impulse_noise/severity_4/*.parquet
- split: severity_5
path: data/impulse_noise/severity_5/*.parquet
- config_name: defocus_blur
data_files:
- split: severity_1
path: data/defocus_blur/severity_1/*.parquet
- split: severity_2
path: data/defocus_blur/severity_2/*.parquet
- split: severity_3
path: data/defocus_blur/severity_3/*.parquet
- split: severity_4
path: data/defocus_blur/severity_4/*.parquet
- split: severity_5
path: data/defocus_blur/severity_5/*.parquet
- config_name: glass_blur
data_files:
- split: severity_1
path: data/glass_blur/severity_1/*.parquet
- split: severity_2
path: data/glass_blur/severity_2/*.parquet
- split: severity_3
path: data/glass_blur/severity_3/*.parquet
- split: severity_4
path: data/glass_blur/severity_4/*.parquet
- split: severity_5
path: data/glass_blur/severity_5/*.parquet
- config_name: motion_blur
data_files:
- split: severity_1
path: data/motion_blur/severity_1/*.parquet
- split: severity_2
path: data/motion_blur/severity_2/*.parquet
- split: severity_3
path: data/motion_blur/severity_3/*.parquet
- split: severity_4
path: data/motion_blur/severity_4/*.parquet
- split: severity_5
path: data/motion_blur/severity_5/*.parquet
- config_name: zoom_blur
data_files:
- split: severity_1
path: data/zoom_blur/severity_1/*.parquet
- split: severity_2
path: data/zoom_blur/severity_2/*.parquet
- split: severity_3
path: data/zoom_blur/severity_3/*.parquet
- split: severity_4
path: data/zoom_blur/severity_4/*.parquet
- split: severity_5
path: data/zoom_blur/severity_5/*.parquet
- config_name: snow
data_files:
- split: severity_1
path: data/snow/severity_1/*.parquet
- split: severity_2
path: data/snow/severity_2/*.parquet
- split: severity_3
path: data/snow/severity_3/*.parquet
- split: severity_4
path: data/snow/severity_4/*.parquet
- split: severity_5
path: data/snow/severity_5/*.parquet
- config_name: frost
data_files:
- split: severity_1
path: data/frost/severity_1/*.parquet
- split: severity_2
path: data/frost/severity_2/*.parquet
- split: severity_3
path: data/frost/severity_3/*.parquet
- split: severity_4
path: data/frost/severity_4/*.parquet
- split: severity_5
path: data/frost/severity_5/*.parquet
- config_name: fog
data_files:
- split: severity_1
path: data/fog/severity_1/*.parquet
- split: severity_2
path: data/fog/severity_2/*.parquet
- split: severity_3
path: data/fog/severity_3/*.parquet
- split: severity_4
path: data/fog/severity_4/*.parquet
- split: severity_5
path: data/fog/severity_5/*.parquet
- config_name: brightness
data_files:
- split: severity_1
path: data/brightness/severity_1/*.parquet
- split: severity_2
path: data/brightness/severity_2/*.parquet
- split: severity_3
path: data/brightness/severity_3/*.parquet
- split: severity_4
path: data/brightness/severity_4/*.parquet
- split: severity_5
path: data/brightness/severity_5/*.parquet
- config_name: contrast
data_files:
- split: severity_1
path: data/contrast/severity_1/*.parquet
- split: severity_2
path: data/contrast/severity_2/*.parquet
- split: severity_3
path: data/contrast/severity_3/*.parquet
- split: severity_4
path: data/contrast/severity_4/*.parquet
- split: severity_5
path: data/contrast/severity_5/*.parquet
- config_name: elastic_transform
data_files:
- split: severity_1
path: data/elastic_transform/severity_1/*.parquet
- split: severity_2
path: data/elastic_transform/severity_2/*.parquet
- split: severity_3
path: data/elastic_transform/severity_3/*.parquet
- split: severity_4
path: data/elastic_transform/severity_4/*.parquet
- split: severity_5
path: data/elastic_transform/severity_5/*.parquet
- config_name: pixelate
data_files:
- split: severity_1
path: data/pixelate/severity_1/*.parquet
- split: severity_2
path: data/pixelate/severity_2/*.parquet
- split: severity_3
path: data/pixelate/severity_3/*.parquet
- split: severity_4
path: data/pixelate/severity_4/*.parquet
- split: severity_5
path: data/pixelate/severity_5/*.parquet
- config_name: jpeg_compression
data_files:
- split: severity_1
path: data/jpeg_compression/severity_1/*.parquet
- split: severity_2
path: data/jpeg_compression/severity_2/*.parquet
- split: severity_3
path: data/jpeg_compression/severity_3/*.parquet
- split: severity_4
path: data/jpeg_compression/severity_4/*.parquet
- split: severity_5
path: data/jpeg_compression/severity_5/*.parquet
TTA-ImageNet-C
Mirror of ImageNet-C (Hendrycks & Dietterich, ICLR 2019) with a revision pin for reproducible test-time adaptation evaluation.
- Upstream: Zenodo record 2235448
- License: CC BY 4.0 (matches upstream)
- Maintained as part of: TTA-Evaluation-Harness
Citation
@inproceedings{hendrycks2019benchmarking,
title={Benchmarking Neural Network Robustness to Common Corruptions and Perturbations},
author={Hendrycks, Dan and Dietterich, Thomas},
booktitle={ICLR},
year={2019}
}
Structure
- 15 configs: one per corruption type (
gaussian_noise,shot_noise, ...,jpeg_compression). - 5 splits per config:
severity_1throughseverity_5, 50 000 images each (1000 classes x 50). - Labels are
ClassLabelwith 1000 WordNet-ID names in torchvision order (lexicographic on wnid;n01440764= idx 0 = tench).
Usage
from datasets import load_dataset
ds = load_dataset("WNJXYK/TTA-ImageNet-C",
name="gaussian_noise",
split="severity_5",
revision="v1.0")
Provenance
This mirror was built by scripts/publish_imagenetc.py in the
TTA-Evaluation-Harness repo. JPEG bytes are copied 1:1 from the upstream
files - no re-encoding, pixel-for-pixel identical to Hendrycks's release.