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Corruption Dataset: Jpeg_Compression
Dataset Description
This dataset contains corrupted versions of ImageNet-1K images using jpeg_compression corruption. It is part of the ImageNet-C benchmark for evaluating model robustness to common image corruptions.
Dataset Structure
- Train: 1,281,167 corrupted images
- Validation: 50,000 corrupted images
- Classes: 1000 ImageNet-1K classes
- Format: Arrow (Hugging Face Datasets)
Corruption Type: Jpeg_Compression
Applies JPEG compression artifacts.
Usage
from datasets import load_dataset
# Load the dataset
dataset = load_dataset("MarMaster/corruption-jpeg_compression")
# Access train and validation splits
train_dataset = dataset["train"]
val_dataset = dataset["validation"]
# Example usage
for example in train_dataset:
image = example["image"]
class_id = example["class_id"]
filename = example["filename"]
Dataset Statistics
- Total Images: 1,331,167
- Train Images: 1,281,167
- Validation Images: 50,000
- Classes: 1000
- Image Format: RGB
- Average Image Size: Variable (ImageNet-1K standard)
Citation
If you use this dataset, please cite the original ImageNet-C paper:
@article{hendrycks2019benchmarking,
title={Benchmarking Neural Network Robustness to Common Corruptions and Perturbations},
author={Hendrycks, Dan and Dietterich, Tom},
journal={Proceedings of the International Conference on Learning Representations},
year={2019}
}
License
This dataset is released under the MIT License. The original ImageNet dataset follows its own licensing terms.
Contact
For questions or issues, please contact: marcin.osial@[your-institution].edu
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