The iNaturalist 2017 dataset (iNat) contains 675,170 training and validation images from 5,089 natural fine-grained categories. Those categories belong to 13 super-categories including Plantae (Plant), Insecta (Insect), Aves (Bird), Mammalia (Mammal), and so on. The iNat dataset is highly imbalanced with dramatically different number of images per category. For example, the largest super-category “Plantae (Plant)” has 196,613 images from 2,101 categories; whereas the smallest super-category “Protozoa” only has 381 images from 4 categories.
Source: Large Scale Fine-Grained Categorization and Domain-Specific Transfer Learning
Image Source: https://github.com/visipedia/inat_comp/tree/master/2017
Variants: iNat2021-mini, iNat2021, iNaturalist Fine-Grained Geolocation, iNaturalist 2018 - 5-shot, iNaturalist 2018 - 1-shot, iNaturalist 2018 - 10-shot, iNaturalist 2019, iNaturalist 2018, iNaturalist (227-way multi-shot), iNaturalist
This dataset is used in 3 benchmarks:
Recent papers with results on this dataset: