Benchmarking Neural Network Robustness to Common Corruptions and Perturbations
Paper • 1903.12261 • Published
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The dataset viewer is not available for this dataset.
Cannot get the config names for the dataset.
Error code: ConfigNamesError
Exception: RuntimeError
Message: Dataset scripts are no longer supported, but found tiny-imagenet-c.py
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 66, in compute_config_names_response
config_names = get_dataset_config_names(
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 161, in get_dataset_config_names
dataset_module = dataset_module_factory(
^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1207, in dataset_module_factory
raise e1 from None
File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1167, in dataset_module_factory
raise RuntimeError(f"Dataset scripts are no longer supported, but found {filename}")
RuntimeError: Dataset scripts are no longer supported, but found tiny-imagenet-c.pyNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Dataset Card for Tiny-ImageNet-C
Dataset Details
Dataset Description
In Tiny ImageNet-C, there are 75,109 corrupted images derived from the original Tiny ImageNet dataset. The images are affected by two different corruption types at five severity levels.
- License: CC BY 4.0
Dataset Sources
- Homepage: https://github.com/hendrycks/robustness
- Paper: Hendrycks, D., & Dietterich, T. (2019). Benchmarking neural network robustness to common corruptions and perturbations. arXiv preprint arXiv:1903.12261.
Dataset Structure
Total images: 75,109
Classes: 200 categories
Splits:
- Test: 75,109 images
Image specs: JPEG format, 64×64 pixels, RGB
Example Usage
Below is a quick example of how to load this dataset via the Hugging Face Datasets library.
from datasets import load_dataset
# Load the dataset
dataset = load_dataset("randall-lab/tiny-imagenet-c", split="test", trust_remote_code=True)
# Access a sample from the dataset
example = dataset[0]
image = example["image"]
label = example["label"]
image.show() # Display the image
print(f"Label: {label}")
Citation
BibTeX:
@article{hendrycks2019benchmarking, title={Benchmarking neural network robustness to common corruptions and perturbations}, author={Hendrycks, Dan and Dietterich, Thomas}, journal={arXiv preprint arXiv:1903.12261}, year={2019} }
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