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  1. README.md +81 -0
  2. dataset_info.json +53 -0
  3. train/data-00000-of-00068.arrow +3 -0
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README.md ADDED
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+ ---
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+ license: mit
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+ task_categories:
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+ - image-classification
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+ language:
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+ - en
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+ tags:
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+ - imagenet
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+ - corruption
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+ - robustness
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+ - computer-vision
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+ - image-classification
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+ size_categories:
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+ - 1M<n<10M
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+ ---
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+
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+ # Corruption Dataset: Defocus_Blur
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+
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+ ## Dataset Description
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+
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+ This dataset contains corrupted versions of ImageNet-1K images using **defocus_blur** corruption. It is part of the ImageNet-C benchmark for evaluating model robustness to common image corruptions.
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+
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+ ### Dataset Structure
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+
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+ - **Train**: 1,281,167 corrupted images
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+ - **Validation**: 50,000 corrupted images
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+ - **Classes**: 1000 ImageNet-1K classes
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+ - **Format**: Arrow (Hugging Face Datasets)
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+
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+ ### Corruption Type: Defocus_Blur
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+
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+ Applies defocus blur, simulating camera focus issues.
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+
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+ ## Usage
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+
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+ ```python
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+ from datasets import load_dataset
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+
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+ # Load the dataset
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+ dataset = load_dataset("MarMaster/corruption-defocus_blur")
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+
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+ # Access train and validation splits
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+ train_dataset = dataset["train"]
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+ val_dataset = dataset["validation"]
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+
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+ # Example usage
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+ for example in train_dataset:
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+ image = example["image"]
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+ class_id = example["class_id"]
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+ filename = example["filename"]
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+ ```
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+
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+ ## Dataset Statistics
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+
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+ - **Total Images**: 1,331,167
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+ - **Train Images**: 1,281,167
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+ - **Validation Images**: 50,000
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+ - **Classes**: 1000
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+ - **Image Format**: RGB
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+ - **Average Image Size**: Variable (ImageNet-1K standard)
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+
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+ ## Citation
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+
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+ If you use this dataset, please cite the original ImageNet-C paper:
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+
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+ ```bibtex
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+ @article{hendrycks2019benchmarking,
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+ title={Benchmarking Neural Network Robustness to Common Corruptions and Perturbations},
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+ author={Hendrycks, Dan and Dietterich, Tom},
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+ journal={Proceedings of the International Conference on Learning Representations},
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+ year={2019}
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+ }
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+ ```
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+
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+ ## License
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+
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+ This dataset is released under the MIT License. The original ImageNet dataset follows its own licensing terms.
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+
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+ ## Contact
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+
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+ For questions or issues, please contact: marcin.osial@[your-institution].edu
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+ "dataset_name": "corruption-defocus_blur",
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+ "dataset_version": "1.0.0",
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+ "description": "ImageNet-Corruption dataset with defocus_blur corruption",
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+ "license": "mit",
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+ "task_categories": [
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+ "image-classification"
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+ ],
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+ "language": [
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+ "en"
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+ ],
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+ "tags": [
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+ "imagenet",
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+ "corruption",
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+ "robustness",
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+ "computer-vision"
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+ ],
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+ "size_categories": "1M<n<10M",
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+ "splits": {
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+ "name": "train",
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+ "validation": {
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+ }
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+ "features": {
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+ "image": {
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+ "dtype": "image",
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+ "_type": "Image"
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+ },
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+ "_type": "Value"
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+ "download_size": 0,
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+ "dataset_size": 0,
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+ "created_at": "2025-10-27 22:37:35",
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+ "corruption_type": "defocus_blur"
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