- 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.
Source code:
tfds.image_classification.OxfordIIITPet
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 |
- Features:
FeaturesDict({
'file_name': Text(shape=(), dtype=tf.string),
'image': Image(shape=(None, None, 3), dtype=tf.uint8),
'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=37),
'segmentation_mask': Image(shape=(None, None, 1), dtype=tf.uint8),
'species': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
})
Supervised keys (See
as_supervised
doc):('image', 'label')
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",
}
Figure (tfds.show_examples): Not supported.
Examples (tfds.as_dataframe):