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i_naturalist2017

This dataset contains a total of 5,089 categories, across 579,184 training images and 95,986 validation images. For the training set, the distribution of images per category follows the observation frequency of that category by the iNaturalist community.

Although the original dataset contains some images with bounding boxes, currently, only image-level annotations are provided (single label/image). In addition, the organizers have not published the test labels, so we only provide the test images (label = -1).

Split Examples
'test' 182,707
'train' 579,184
'validation' 95,986
  • Feature structure:
FeaturesDict({
    'id': Text(shape=(), dtype=tf.string),
    'image': Image(shape=(None, None, 3), dtype=tf.uint8),
    'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=5089),
    'supercategory': ClassLabel(shape=(), dtype=tf.int64, num_classes=13),
})
  • Feature documentation:
Feature Class Shape Dtype Description
FeaturesDict
id Text tf.string
image Image (None, None, 3) tf.uint8
label ClassLabel tf.int64
supercategory ClassLabel tf.int64

Visualization

  • Citation:
@InProceedings{Horn_2018_CVPR,
author = {
Van Horn, Grant and Mac Aodha, Oisin and Song, Yang and Cui, Yin and Sun, Chen
and Shepard, Alex and Adam, Hartwig and Perona, Pietro and Belongie, Serge},
title = {The INaturalist Species Classification and Detection Dataset},
booktitle = {
The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2018}
}