The FGVC-Aircraft dataset contains images of aircraft from 102 different aircraft model variants.

FGVC-Aircraft contains 10,200 images of aircraft, with 100 images for each of 102 different aircraft model variants, most of which are airplanes. The (main) aircraft in each image is annotated with a tight bounding box and a hierarchical airplane model label. Aircraft models are organized in a four-levels hierarchy. The four levels, from finer to coarser, are:

Model, e.g. Boeing 737-76J. Since certain models are nearly visually indistinguishable, this level is not used in the evaluation. Variant, e.g. Boeing 737-700. A variant collapses all the models that are visually indistinguishable into one class. The dataset comprises 102 different variants. Family, e.g. Boeing 737. The dataset comprises 70 different families. Manufacturer, e.g. Boeing. The dataset comprises 41 different manufacturers. The data is divided into three equally-sized training, validation and test subsets.

The dataset contains 10,200 images of aircraft, with 100 images for each of 102 different aircraft model variants, most of which are airplanes. The (main) aircraft in each image is annotated with a tight bounding box and a hierarchical airplane model label.

Aircraft models are organized in a four-levels hierarchy. The four levels, from finer to coarser, are:

Model, e.g. Boeing 737-76J. Since certain models are nearly visually indistinguishable, this level is not used in the evaluation.
Variant, e.g. Boeing 737-700. A variant collapses all the models that are visually indistinguishable into one class. The dataset comprises 102 different variants.
Family, e.g. Boeing 737. The dataset comprises 70 different families.
Manufacturer, e.g. Boeing. The dataset comprises 41 different manufacturers.

The data is divided into three equally-sized training, validation and test subsets. The first two sets can be used for development, and the latter should be used for final evaluation only.