ImageNet 256x256 is a commonly used resized variant of the ImageNet ILSVRC2012 (ImageNet-1k) image classification dataset where images have been resized / center-cropped and rescaled to 256x256 pixels. The underlying dataset (ILSVRC2012) contains 1.28M training images, 50K validation images and 100K test images across 1000 classes. The 256x256 variant is provided as a convenience for faster downloads and for workflows that perform random crops (e.g., 224x224 crops from 256). This variant is widely used in image-generation and generative-model evaluation papers (e.g., for computing FID and Inception Score using 50K generated images — 50 samples per class for the 1000 classes). The dataset is not a new collection but a transformed / resized version of the standard ImageNet (ILSVRC2012) split. Representative Hugging Face repacks include evanarlian/imagenet_1k_resized_256 and benjamin-paine/imagenet-1k-256x256 which describe the exact resize/center-crop procedures and point to the original ImageNet/ILSVRC references.
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