starcraft_video

This data set contains videos generated from Starcraft.

starcraft_video is configured with tfds.video.starcraft.StarcraftVideoConfig and has the following configurations predefined (defaults to the first one):

  • brawl_64 (v0.1.2) (Size: 6.40 GiB): Brawl map with 64x64 resolution.

  • brawl_128 (v0.1.2) (Size: 20.76 GiB): Brawl map with 128x128 resolution.

  • collect_mineral_shards_64 (v0.1.2) (Size: 7.83 GiB): CollectMineralShards map with 64x64 resolution.

  • collect_mineral_shards_128 (v0.1.2) (Size: 24.83 GiB): CollectMineralShards map with 128x128 resolution.

  • move_unit_to_border_64 (v0.1.2) (Size: 1.77 GiB): MoveUnitToBorder map with 64x64 resolution.

  • move_unit_to_border_128 (v0.1.2) (Size: 5.75 GiB): MoveUnitToBorder map with 128x128 resolution.

  • road_trip_with_medivac_64 (v0.1.2) (Size: 2.48 GiB): RoadTripWithMedivac map with 64x64 resolution.

  • road_trip_with_medivac_128 (v0.1.2) (Size: 7.80 GiB): RoadTripWithMedivac map with 128x128 resolution.

starcraft_video/brawl_64

Brawl map with 64x64 resolution.

Versions:

  • 0.1.2 (default):
  • 1.0.0: New split API (https://tensorflow.org/datasets/splits)

Statistics

Split Examples
ALL 14,000
TRAIN 10,000
TEST 2,000
VALIDATION 2,000

Features

FeaturesDict({
    'rgb_screen': Video(Image(shape=(64, 64, 3), dtype=tf.uint8)),
})

Homepage

starcraft_video/brawl_128

Brawl map with 128x128 resolution.

Versions:

  • 0.1.2 (default):
  • 1.0.0: New split API (https://tensorflow.org/datasets/splits)

Statistics

Split Examples
ALL 14,000
TRAIN 10,000
TEST 2,000
VALIDATION 2,000

Features

FeaturesDict({
    'rgb_screen': Video(Image(shape=(128, 128, 3), dtype=tf.uint8)),
})

Homepage

starcraft_video/collect_mineral_shards_64

CollectMineralShards map with 64x64 resolution.

Versions:

  • 0.1.2 (default):
  • 1.0.0: New split API (https://tensorflow.org/datasets/splits)

Statistics

Split Examples
ALL 14,000
TRAIN 10,000
TEST 2,000
VALIDATION 2,000

Features

FeaturesDict({
    'rgb_screen': Video(Image(shape=(64, 64, 3), dtype=tf.uint8)),
})

Homepage

starcraft_video/collect_mineral_shards_128

CollectMineralShards map with 128x128 resolution.

Versions:

  • 0.1.2 (default):
  • 1.0.0: New split API (https://tensorflow.org/datasets/splits)

Statistics

Split Examples
ALL 14,000
TRAIN 10,000
TEST 2,000
VALIDATION 2,000

Features

FeaturesDict({
    'rgb_screen': Video(Image(shape=(128, 128, 3), dtype=tf.uint8)),
})

Homepage

starcraft_video/move_unit_to_border_64

MoveUnitToBorder map with 64x64 resolution.

Versions:

  • 0.1.2 (default):
  • 1.0.0: New split API (https://tensorflow.org/datasets/splits)

Statistics

Split Examples
ALL 14,000
TRAIN 10,000
TEST 2,000
VALIDATION 2,000

Features

FeaturesDict({
    'rgb_screen': Video(Image(shape=(64, 64, 3), dtype=tf.uint8)),
})

Homepage

starcraft_video/move_unit_to_border_128

MoveUnitToBorder map with 128x128 resolution.

Versions:

  • 0.1.2 (default):
  • 1.0.0: New split API (https://tensorflow.org/datasets/splits)

Statistics

Split Examples
ALL 14,000
TRAIN 10,000
TEST 2,000
VALIDATION 2,000

Features

FeaturesDict({
    'rgb_screen': Video(Image(shape=(128, 128, 3), dtype=tf.uint8)),
})

Homepage

starcraft_video/road_trip_with_medivac_64

RoadTripWithMedivac map with 64x64 resolution.

Versions:

  • 0.1.2 (default):
  • 1.0.0: New split API (https://tensorflow.org/datasets/splits)

Statistics

Split Examples
ALL 14,000
TRAIN 10,000
TEST 2,000
VALIDATION 2,000

Features

FeaturesDict({
    'rgb_screen': Video(Image(shape=(64, 64, 3), dtype=tf.uint8)),
})

Homepage

starcraft_video/road_trip_with_medivac_128

RoadTripWithMedivac map with 128x128 resolution.

Versions:

  • 0.1.2 (default):
  • 1.0.0: New split API (https://tensorflow.org/datasets/splits)

Statistics

Split Examples
ALL 14,000
TRAIN 10,000
TEST 2,000
VALIDATION 2,000

Features

FeaturesDict({
    'rgb_screen': Video(Image(shape=(128, 128, 3), dtype=tf.uint8)),
})

Homepage

Citation

@article{DBLP:journals/corr/abs-1812-01717,
  author    = {Thomas Unterthiner and
               Sjoerd van Steenkiste and
               Karol Kurach and
               Rapha{"{e}}l Marinier and
               Marcin Michalski and
               Sylvain Gelly},
  title     = {Towards Accurate Generative Models of Video: {A} New Metric and
               Challenges},
  journal   = {CoRR},
  volume    = {abs/1812.01717},
  year      = {2018},
  url       = {http://arxiv.org/abs/1812.01717},
  archivePrefix = {arXiv},
  eprint    = {1812.01717},
  timestamp = {Tue, 01 Jan 2019 15:01:25 +0100},
  biburl    = {https://dblp.org/rec/bib/journals/corr/abs-1812-01717},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}