The benchmarks section lists all benchmarks using a given dataset or any of
its variants. We use variants to distinguish between results evaluated on
slightly different versions of the same dataset. For example, ImageNet 32⨉32
and ImageNet 64⨉64 are variants of the ImageNet dataset.
OpenImages V6 is a large-scale dataset ,
consists of 9 million training images, 41,620 validation
samples, and 125,456 test samples. It is a partially annotated dataset, with 9,600 trainable classes