oxford_iiit_pet

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.

• URL: http://www.robots.ox.ac.uk/~vgg/data/pets/
• DatasetBuilder: tfds.image.oxford_iiit_pet.OxfordIIITPet
• Version: v1.1.0

• Versions:

  • 1.1.0 (default):
  • 3.0.0: New split API (https://tensorflow.org/datasets/splits);additon of segmentation_mask feature.

• Size: 801.24 MiB

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),
})

Statistics

Homepage

• http://www.robots.ox.ac.uk/~vgg/data/pets/

Supervised keys (for as_supervised=True)

(u'image', u'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",
}