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In this work we introduce a large-scale, fine-grained dataset of cars. This dataset, consisting of 197 classes and 16,185 images, represents an order of magnitude increase in size over the only existing fine-grained car dataset [7](14 classes, 1,904 images) and is comparable in size to the largest fine-grained datasets publicly available [9, 3]. The goals of this work are twofold: 1) to describe the difficulties encountered when collecting such a dataset and 2) to present baseline performance for two state-of-the-art methods.