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visual_domain_decathlon

This contains the 10 datasets used in the Visual Domain Decathlon, part of the PASCAL in Detail Workshop Challenge (CVPR 2017). The goal of this challenge is to solve simultaneously ten image classification problems representative of very different visual domains.

Some of the datasets included here are also available as separate datasets in TFDS. However, notice that images were preprocessed for the Visual Domain Decathlon (resized isotropically to have a shorter size of 72 pixels) and might have different train/validation/test splits. Here we use the official splits for the competition.

visual_domain_decathlon is configured with tfds.image.visual_domain_decathlon.VisualDomainDecathlonConfig and has the following configurations predefined (defaults to the first one):

  • aircraft (v1.1.0) (Size: 1.04 GiB): Data based on "Aircraft", with images resized isotropically to have a shorter size of 72 pixels.

  • cifar100 (v1.1.0) (Size: 1.04 GiB): Data based on "CIFAR-100", with images resized isotropically to have a shorter size of 72 pixels.

  • daimlerpedcls (v1.1.0) (Size: 1.04 GiB): Data based on "Daimler Pedestrian Classification", with images resized isotropically to have a shorter size of 72 pixels.

  • dtd (v1.1.0) (Size: 1.04 GiB): Data based on "Describable Textures", with images resized isotropically to have a shorter size of 72 pixels.

  • gtsrb (v1.1.0) (Size: 1.04 GiB): Data based on "German Traffic Signs", with images resized isotropically to have a shorter size of 72 pixels.

  • imagenet12 (v1.1.0) (Size: 6.40 GiB): Data based on "Imagenet", with images resized isotropically to have a shorter size of 72 pixels.

  • omniglot (v1.1.0) (Size: 1.04 GiB): Data based on "Omniglot", with images resized isotropically to have a shorter size of 72 pixels.

  • svhn (v1.1.0) (Size: 1.04 GiB): Data based on "Street View House Numbers", with images resized isotropically to have a shorter size of 72 pixels.

  • ucf101 (v1.1.0) (Size: 1.04 GiB): Data based on "UCF101 Dynamic Images", with images resized isotropically to have a shorter size of 72 pixels.

  • vgg-flowers (v1.1.0) (Size: 1.04 GiB): Data based on "VGG-Flowers", with images resized isotropically to have a shorter size of 72 pixels.

visual_domain_decathlon/aircraft

FeaturesDict({
    'image': Image(shape=(None, None, 3), dtype=tf.uint8),
    'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=100),
    'name': Text(shape=(), dtype=tf.string),
})

visual_domain_decathlon/cifar100

FeaturesDict({
    'image': Image(shape=(None, None, 3), dtype=tf.uint8),
    'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=100),
    'name': Text(shape=(), dtype=tf.string),
})

visual_domain_decathlon/daimlerpedcls

FeaturesDict({
    'image': Image(shape=(None, None, 3), dtype=tf.uint8),
    'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    'name': Text(shape=(), dtype=tf.string),
})

visual_domain_decathlon/dtd

FeaturesDict({
    'image': Image(shape=(None, None, 3), dtype=tf.uint8),
    'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=47),
    'name': Text(shape=(), dtype=tf.string),
})

visual_domain_decathlon/gtsrb

FeaturesDict({
    'image': Image(shape=(None, None, 3), dtype=tf.uint8),
    'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=43),
    'name': Text(shape=(), dtype=tf.string),
})

visual_domain_decathlon/imagenet12

FeaturesDict({
    'image': Image(shape=(None, None, 3), dtype=tf.uint8),
    'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=1000),
    'name': Text(shape=(), dtype=tf.string),
})

visual_domain_decathlon/omniglot

FeaturesDict({
    'image': Image(shape=(None, None, 3), dtype=tf.uint8),
    'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=1623),
    'name': Text(shape=(), dtype=tf.string),
})

visual_domain_decathlon/svhn

FeaturesDict({
    'image': Image(shape=(None, None, 3), dtype=tf.uint8),
    'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=10),
    'name': Text(shape=(), dtype=tf.string),
})

visual_domain_decathlon/ucf101

FeaturesDict({
    'image': Image(shape=(None, None, 3), dtype=tf.uint8),
    'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=101),
    'name': Text(shape=(), dtype=tf.string),
})

visual_domain_decathlon/vgg-flowers

FeaturesDict({
    'image': Image(shape=(None, None, 3), dtype=tf.uint8),
    'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=102),
    'name': Text(shape=(), dtype=tf.string),
})

Statistics

Split Examples
ALL 8,189
TEST 6,149
VALIDATION 1,020
TRAIN 1,020

Urls

Supervised keys (for as_supervised=True)

(u'image', u'label')

Citation

@ONLINE{hakanbilensylvestrerebuffitomasjakab2017,
    author = "Hakan Bilen, Sylvestre Rebuffi, Tomas Jakab",
    title  = "Visual Domain Decathlon",
    year   = "2017",
    url    = "https://www.robots.ox.ac.uk/~vgg/decathlon/"
}