A dataset consisting of images from two classes A and B (For example: horses/zebras, apple/orange,...)
- URL: https://people.eecs.berkeley.edu/~taesung_park/CycleGAN/datasets/
DatasetBuilder
:tfds.image.cycle_gan.CycleGAN
cycle_gan
is configured with tfds.image.cycle_gan.CycleGANConfig
and has the
following configurations predefined (defaults to the first one):
apple2orange
(v0.1.0
) (Size: 74.82 MiB
): A dataset consisting of images from two classes A and B (For example: horses/zebras, apple/orange,...)summer2winter_yosemite
(v0.1.0
) (Size: 126.50 MiB
): A dataset consisting of images from two classes A and B (For example: horses/zebras, apple/orange,...)horse2zebra
(v0.1.0
) (Size: 111.45 MiB
): A dataset consisting of images from two classes A and B (For example: horses/zebras, apple/orange,...)monet2photo
(v0.1.0
) (Size: 291.09 MiB
): A dataset consisting of images from two classes A and B (For example: horses/zebras, apple/orange,...)cezanne2photo
(v0.1.0
) (Size: 266.92 MiB
): A dataset consisting of images from two classes A and B (For example: horses/zebras, apple/orange,...)ukiyoe2photo
(v0.1.0
) (Size: 279.38 MiB
): A dataset consisting of images from two classes A and B (For example: horses/zebras, apple/orange,...)vangogh2photo
(v0.1.0
) (Size: 292.39 MiB
): A dataset consisting of images from two classes A and B (For example: horses/zebras, apple/orange,...)maps
(v0.1.0
) (Size: 1.38 GiB
): A dataset consisting of images from two classes A and B (For example: horses/zebras, apple/orange,...)cityscapes
(v0.1.0
) (Size: 266.65 MiB
): A dataset consisting of images from two classes A and B (For example: horses/zebras, apple/orange,...)facades
(v0.1.0
) (Size: 33.51 MiB
): A dataset consisting of images from two classes A and B (For example: horses/zebras, apple/orange,...)iphone2dslr_flower
(v0.1.0
) (Size: 324.22 MiB
): A dataset consisting of images from two classes A and B (For example: horses/zebras, apple/orange,...)
cycle_gan/apple2orange
A dataset consisting of images from two classes A and B (For example: horses/zebras, apple/orange,...)
Versions:
0.1.0
(default):2.0.0
: New split API (https://tensorflow.org/datasets/splits)
Statistics
Split | Examples |
---|---|
ALL | 2,528 |
TRAINB | 1,019 |
TRAINA | 995 |
TESTA | 266 |
TESTB | 248 |
Features
FeaturesDict({
'image': Image(shape=(None, None, 3), dtype=tf.uint8),
'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
})
Homepage
Supervised keys (for as_supervised=True
)
(u'image', u'label')
cycle_gan/summer2winter_yosemite
A dataset consisting of images from two classes A and B (For example: horses/zebras, apple/orange,...)
Versions:
0.1.0
(default):2.0.0
: New split API (https://tensorflow.org/datasets/splits)
Statistics
Split | Examples |
---|---|
ALL | 2,740 |
TRAINA | 1,231 |
TRAINB | 962 |
TESTA | 309 |
TESTB | 238 |
Features
FeaturesDict({
'image': Image(shape=(None, None, 3), dtype=tf.uint8),
'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
})
Homepage
Supervised keys (for as_supervised=True
)
(u'image', u'label')
cycle_gan/horse2zebra
A dataset consisting of images from two classes A and B (For example: horses/zebras, apple/orange,...)
Versions:
0.1.0
(default):2.0.0
: New split API (https://tensorflow.org/datasets/splits)
Statistics
Split | Examples |
---|---|
ALL | 2,661 |
TRAINB | 1,334 |
TRAINA | 1,067 |
TESTB | 140 |
TESTA | 120 |
Features
FeaturesDict({
'image': Image(shape=(None, None, 3), dtype=tf.uint8),
'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
})
Homepage
Supervised keys (for as_supervised=True
)
(u'image', u'label')
cycle_gan/monet2photo
A dataset consisting of images from two classes A and B (For example: horses/zebras, apple/orange,...)
Versions:
0.1.0
(default):2.0.0
: New split API (https://tensorflow.org/datasets/splits)
Statistics
Split | Examples |
---|---|
ALL | 8,231 |
TRAINB | 6,287 |
TRAINA | 1,072 |
TESTB | 751 |
TESTA | 121 |
Features
FeaturesDict({
'image': Image(shape=(None, None, 3), dtype=tf.uint8),
'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
})
Homepage
Supervised keys (for as_supervised=True
)
(u'image', u'label')
cycle_gan/cezanne2photo
A dataset consisting of images from two classes A and B (For example: horses/zebras, apple/orange,...)
Versions:
0.1.0
(default):2.0.0
: New split API (https://tensorflow.org/datasets/splits)
Statistics
Split | Examples |
---|---|
ALL | 7,621 |
TRAINB | 6,287 |
TESTB | 751 |
TRAINA | 525 |
TESTA | 58 |
Features
FeaturesDict({
'image': Image(shape=(None, None, 3), dtype=tf.uint8),
'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
})
Homepage
Supervised keys (for as_supervised=True
)
(u'image', u'label')
cycle_gan/ukiyoe2photo
A dataset consisting of images from two classes A and B (For example: horses/zebras, apple/orange,...)
Versions:
0.1.0
(default):2.0.0
: New split API (https://tensorflow.org/datasets/splits)
Statistics
Split | Examples |
---|---|
ALL | 7,863 |
TRAINB | 6,287 |
TESTB | 751 |
TRAINA | 562 |
TESTA | 263 |
Features
FeaturesDict({
'image': Image(shape=(None, None, 3), dtype=tf.uint8),
'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
})
Homepage
Supervised keys (for as_supervised=True
)
(u'image', u'label')
cycle_gan/vangogh2photo
A dataset consisting of images from two classes A and B (For example: horses/zebras, apple/orange,...)
Versions:
0.1.0
(default):2.0.0
: New split API (https://tensorflow.org/datasets/splits)
Statistics
Split | Examples |
---|---|
ALL | 7,838 |
TRAINB | 6,287 |
TESTB | 751 |
TESTA | 400 |
TRAINA | 400 |
Features
FeaturesDict({
'image': Image(shape=(None, None, 3), dtype=tf.uint8),
'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
})
Homepage
Supervised keys (for as_supervised=True
)
(u'image', u'label')
cycle_gan/maps
A dataset consisting of images from two classes A and B (For example: horses/zebras, apple/orange,...)
Versions:
0.1.0
(default):2.0.0
: New split API (https://tensorflow.org/datasets/splits)
Statistics
Split | Examples |
---|---|
ALL | 4,388 |
TESTA | 1,098 |
TESTB | 1,098 |
TRAINA | 1,096 |
TRAINB | 1,096 |
Features
FeaturesDict({
'image': Image(shape=(None, None, 3), dtype=tf.uint8),
'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
})
Homepage
Supervised keys (for as_supervised=True
)
(u'image', u'label')
cycle_gan/cityscapes
A dataset consisting of images from two classes A and B (For example: horses/zebras, apple/orange,...)
Versions:
0.1.0
(default):2.0.0
: New split API (https://tensorflow.org/datasets/splits)
Statistics
Split | Examples |
---|---|
ALL | 6,950 |
TRAINA | 2,975 |
TRAINB | 2,975 |
TESTA | 500 |
TESTB | 500 |
Features
FeaturesDict({
'image': Image(shape=(None, None, 3), dtype=tf.uint8),
'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
})
Homepage
Supervised keys (for as_supervised=True
)
(u'image', u'label')
cycle_gan/facades
A dataset consisting of images from two classes A and B (For example: horses/zebras, apple/orange,...)
Versions:
0.1.0
(default):2.0.0
: New split API (https://tensorflow.org/datasets/splits)
Statistics
Split | Examples |
---|---|
ALL | 1,012 |
TRAINA | 400 |
TRAINB | 400 |
TESTA | 106 |
TESTB | 106 |
Features
FeaturesDict({
'image': Image(shape=(None, None, 3), dtype=tf.uint8),
'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
})
Homepage
Supervised keys (for as_supervised=True
)
(u'image', u'label')
cycle_gan/iphone2dslr_flower
A dataset consisting of images from two classes A and B (For example: horses/zebras, apple/orange,...)
Versions:
0.1.0
(default):2.0.0
: New split API (https://tensorflow.org/datasets/splits)
Statistics
Split | Examples |
---|---|
ALL | 6,186 |
TRAINB | 3,325 |
TRAINA | 1,812 |
TESTA | 569 |
TESTB | 480 |
Features
FeaturesDict({
'image': Image(shape=(None, None, 3), dtype=tf.uint8),
'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
})
Homepage
Supervised keys (for as_supervised=True
)
(u'image', u'label')
Citation
@article{DBLP:journals/corr/ZhuPIE17,
author = {Jun{-}Yan Zhu and
Taesung Park and
Phillip Isola and
Alexei A. Efros},
title = {Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial
Networks},
journal = {CoRR},
volume = {abs/1703.10593},
year = {2017},
url = {http://arxiv.org/abs/1703.10593},
archivePrefix = {arXiv},
eprint = {1703.10593},
timestamp = {Mon, 13 Aug 2018 16:48:06 +0200},
biburl = {https://dblp.org/rec/bib/journals/corr/ZhuPIE17},
bibsource = {dblp computer science bibliography, https://dblp.org}
}