iNaturalist 2017 large scale image classification dataset

[Oisin Mac Aodha]

We are pleased to announce a new image classification challenge featuring over 5,000 natural categories - from Abaeis nicippe to Zosterops lateralis. 

The dataset contains 675,000 training images and includes many visually similar species, captured in a wide variety of situations, by different individuals, from all over the world. The goal of the competition is to push the state of the art in automatic image classification for real world data that features fine-grained categories, big class imbalances, and large numbers of classes.

Results will be presented at the Fine-Grained Visual Categorization Workshop held at CVPR 2017 this summer. 

For more details please check out the competition website.

[Oisin Mac Aodha]

We are pleased to announce a new image classification challenge featuring over 5,000 natural categories - from Abaeis nicippe to Zosterops lateralis.

The dataset contains 675,000 training images and includes many visually similar species, captured in a wide variety of situations, by different individuals, from all over the world. The goal of the competition is to push the state of the art in automatic image classification for real world data that features fine-grained categories, big class imbalances, and large numbers of classes.

Results will be presented at the Fine-Grained Visual Categorization Workshop held at CVPR 2017 this summer.

http://www.fgvc.org/

For more details please check out the competition website.

https://github.com/visipedia/inat_comp