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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: scale
      dtype:
        class_label:
          names:
            '0': '0.5'
            '1': '0.6'
            '2': '0.7'
            '3': '0.8'
            '4': '0.9'
            '5': '1.0'
    - name: orientation
      dtype:
        class_label:
          names:
            '0': '0.0'
            '1': '0.32221'
            '2': '0.64443'
            '3': '0.96664'
            '4': '1.28886'
    - name: posX_dynamic
      dtype:
        class_label:
          names:
            '0': right_1x
            '1': left_1x
            '2': right_2x
            '3': left_2x
            '4': mid_right
            '5': mid_left
    - name: posY_dynamic
      dtype:
        class_label:
          names:
            '0': down_1x
            '1': up_1x
            '2': down_2x
            '3': up_2x
            '4': mid_down
            '5': mid_up
  splits:
    - name: train
      num_bytes: 29330065.672
      num_examples: 20412
    - name: val
      num_bytes: 9822019.138
      num_examples: 4374
    - name: test
      num_bytes: 9787552.138
      num_examples: 4374
  download_size: 49141904
  dataset_size: 48939636.948
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: val
        path: data/val-*
      - split: test
        path: data/test-*

MSD dSprites-Dynamic 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, scale, and orientation are fixed, while its spatial position may 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.