Help protect the Great Barrier Reef with TensorFlow on Kaggle Join Challenge


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.

Split Examples
'test' 3,669
'train' 3,680
  • Features:
    '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),
  • Citation:
  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",