- Description:
The Oxford-IIIT pet dataset is a 37 category pet image dataset with roughly 200 images for each class. The images have large variations in scale, pose and lighting. All images have an associated ground truth annotation of breed.
Additional Documentation: Explore on Papers With Code
Source code:
tfds.datasets.oxford_iiit_pet.Builder
Versions:
3.2.0
(default): No release notes.
Download size:
773.52 MiB
Dataset size:
774.69 MiB
Auto-cached (documentation): No
Splits:
Split | Examples |
---|---|
'test' |
3,669 |
'train' |
3,680 |
- Feature structure:
FeaturesDict({
'file_name': Text(shape=(), dtype=string),
'image': Image(shape=(None, None, 3), dtype=uint8),
'label': ClassLabel(shape=(), dtype=int64, num_classes=37),
'segmentation_mask': Image(shape=(None, None, 1), dtype=uint8),
'species': ClassLabel(shape=(), dtype=int64, num_classes=2),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
file_name | Text | string | ||
image | Image | (None, None, 3) | uint8 | |
label | ClassLabel | int64 | ||
segmentation_mask | Image | (None, None, 1) | uint8 | |
species | ClassLabel | int64 |
Supervised keys (See
as_supervised
doc):('image', 'label')
Figure (tfds.show_examples): Not supported.
Examples (tfds.as_dataframe):
- Citation:
@InProceedings{parkhi12a,
author = "Parkhi, O. M. and Vedaldi, A. and Zisserman, A. and Jawahar, C.~V.",
title = "Cats and Dogs",
booktitle = "IEEE Conference on Computer Vision and Pattern Recognition",
year = "2012",
}