- Description:
The iNaturalist dataset 2021 contains a total of 10,000 species. The full
training dataset contains nearly 2.7M images. To make the dataset more
accessible we have also created a "mini" training dataset with 50 examples per
species for a total of 500K images. The full training train
split overlaps
with the mini
split. The val set contains for each species 10 validation
images (100K in total). There are a total of 500,000 test images in the
public_test
split (without ground-truth labels).
Homepage: https://github.com/visipedia/inat_comp/tree/master/2021
Source code:
tfds.image_classification.i_naturalist2021.INaturalist2021
Versions:
1.0.0
: Initial release.2.0.0
: Update: Class indices follow the order in the JSON train file.2.0.1
(default): Update: Include the example id as provided in the JSON files.
Download size:
316.54 GiB
Dataset size:
318.45 GiB
Auto-cached (documentation): No
Splits:
Split | Examples |
---|---|
'mini' |
500,000 |
'test' |
500,000 |
'train' |
2,686,843 |
'val' |
100,000 |
- Feature structure:
FeaturesDict({
'file_id': Text(shape=(), dtype=string),
'id': Scalar(shape=(), dtype=int64),
'image': Image(shape=(None, None, 3), dtype=uint8),
'label': ClassLabel(shape=(), dtype=int64, num_classes=10000),
'supercategory': ClassLabel(shape=(), dtype=int64, num_classes=11),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
file_id | Text | string | ||
id | Scalar | int64 | ||
image | Image | (None, None, 3) | uint8 | |
label | ClassLabel | int64 | ||
supercategory | ClassLabel | int64 |
Supervised keys (See
as_supervised
doc):('image', 'label')
Figure (tfds.show_examples):
- Examples (tfds.as_dataframe):
- Citation:
\
@misc{inaturalist21,
Howpublished = {~\url{https://github.com/visipedia/inat_comp/tree/master/2021} },
Title = { {iNaturalist} 2021 competition dataset.},
Year = {2021},
key = { {iNaturalist} 2021 competition dataset},
}