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metadata
license: apache-2.0
dataset_info:
  features:
    - name: id
      dtype: int32
    - name: x
      sequence: image
    - name: color
      dtype:
        class_label:
          names:
            '0': DarkSlateGray
            '1': OrangeRed
            '2': Yellow
            '3': SpringGreen
            '4': Cyan
            '5': Purple
            '6': DodgerBlue
            '7': DeepPink
            '8': NavajoWhite
    - name: shape
      dtype:
        class_label:
          names:
            '0': square
            '1': ellipse
            '2': heart
    - name: posX
      dtype:
        class_label:
          names:
            '0': '0.06452'
            '1': '0.19355'
            '2': '0.32258'
            '3': '0.45161'
            '4': '0.58065'
            '5': '0.70968'
            '6': '0.83871'
            '7': '0.96774'
    - name: posY
      dtype:
        class_label:
          names:
            '0': '0.06452'
            '1': '0.19355'
            '2': '0.32258'
            '3': '0.45161'
            '4': '0.58065'
            '5': '0.70968'
            '6': '0.83871'
            '7': '0.96774'
    - name: scale_dynamic
      dtype:
        class_label:
          names:
            '0': increasing_1x
            '1': decreasing_1x
            '2': increasing_2x
            '3': decreasing_2x
            '4': increasing_3x
            '5': decreasing_3x
    - name: orientation_dynamic
      dtype:
        class_label:
          names:
            '0': counterclockwise
            '1': static
            '2': clockwise
  splits:
    - name: train
      num_bytes: 36447828.056
      num_examples: 21772
    - name: val
      num_bytes: 13035775.304
      num_examples: 4666
    - name: test
      num_bytes: 13064702.304
      num_examples: 4666
  download_size: 53718665
  dataset_size: 62548305.664
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: val
        path: data/val-*
      - split: test
        path: data/test-*

MSD dSprites-Static Dataset Attribution

The Multi-factor Sequential Disentanglement benchmark includes a modified variant of the dSprites dataset, adapted to support sequential multi-factor disentanglement.

In this modified sequential version, the object's color, shape, and position are fixed, while its scale and orientation change over time.

@misc{dsprites17,
author = {Loic Matthey and Irina Higgins and Demis Hassabis and Alexander Lerchner},
title = {dSprites: Disentanglement testing Sprites dataset},
howpublished= {https://github.com/deepmind/dsprites-dataset/},
year = "2017",
}

Note: The dSprites dataset is licensed under the Apache License 2.0. We redistribute it here solely for non-commercial research purposes, following the original license terms. Please cite the above when using this dataset in your work.