ImageNet-S (ImageNet-Sketch) is an out-of-domain sketch image dataset aligned to the 1000 ImageNet classes, created to evaluate models' semantic robustness at ImageNet scale. The original release contains roughly 50,000 images (commonly reported as ~50,889 images / ≈50 images per class for the 1000 classes). Images were collected via Google Image queries of the form “sketch of <class>” (searching within a black-and-white color scheme), manually cleaned to remove irrelevant or mislabelled images, and in some cases augmented (flipping/rotations) when fewer than the target number of images were available for a class. The dataset is widely used as an OOD/robustness benchmark for image-classification models. (Sources: original ImageNet-Sketch GitHub, PapersWithCode dataset page, TensorFlow Datasets, Hugging Face dataset cards.)
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