metadata

dataset_info:
  features:
    - name: image
      dtype: image
    - name: label
      dtype:
        class_label:
          names:
            '0': abyssinian
            '1': american_bulldog
            '2': american_pit_bull_terrier
            '3': basset_hound
            '4': beagle
            '5': bengal
            '6': birman
            '7': bombay
            '8': boxer
            '9': british_shorthair
            '10': chihuahua
            '11': egyptian_mau
            '12': english_cocker_spaniel
            '13': english_setter
            '14': german_shorthaired
            '15': great_pyrenees
            '16': havanese
            '17': japanese_chin
            '18': keeshond
            '19': leonberger
            '20': maine_coon
            '21': miniature_pinscher
            '22': newfoundland
            '23': persian
            '24': pomeranian
            '25': pug
            '26': ragdoll
            '27': russian_blue
            '28': saint_bernard
            '29': samoyed
            '30': scottish_terrier
            '31': shiba_inu
            '32': siamese
            '33': sphynx
            '34': staffordshire_bull_terrier
            '35': wheaten_terrier
            '36': yorkshire_terrier
    - name: image_id
      dtype: string
    - name: label_cat_dog
      dtype:
        class_label:
          names:
            '0': cat
            '1': dog
  splits:
    - name: train
      num_bytes: 376746044.08
      num_examples: 3680
    - name: test
      num_bytes: 426902517.206
      num_examples: 3669
  download_size: 790265316
  dataset_size: 803648561.286
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: test
        path: data/test-*
license: cc-by-sa-4.0
size_categories:
  - 1K<n<10K
task_categories:
  - image-classification

The Oxford-IIIT Pet Dataset

Description

A 37 category pet dataset with roughly 200 images for each class. The images have a large variations in scale, pose and lighting.

This instance of the dataset uses standard label ordering and includes the standard train/test splits. Trimaps and bbox are not included, but there is an image_id field that can be used to reference those annotations from official metadata.

Website: https://www.robots.ox.ac.uk/~vgg/data/pets/

Citation

@InProceedings{parkhi12a,
  author       = "Omkar M. Parkhi and Andrea Vedaldi and Andrew Zisserman and C. V. Jawahar",
  title        = "Cats and Dogs",
  booktitle    = "IEEE Conference on Computer Vision and Pattern Recognition",
  year         = "2012",
}