Each image has detailed annotations: 1 subcategory label, 15 part locations, 312 binary attributes and 1 bounding box. It contains 11,788 images of 200 subcategories belonging to birds, 5,994 for training and 5,794 for testing. The **Caltech-UCSD Birds-200-2011** (**CUB-200-2011**) dataset is the most widely-used dataset for fine-grained visual categorization task.
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