dsprites

• Description:

dSprites is a dataset of 2D shapes procedurally generated from 6 ground truth independent latent factors. These factors are color, shape, scale, rotation, x and y positions of a sprite.

All possible combinations of these latents are present exactly once, generating N = 737280 total images.

Latent factor values

• Color: white
• Shape: square, ellipse, heart
• Scale: 6 values linearly spaced in [0.5, 1]
• Orientation: 40 values in [0, 2 pi]
• Position X: 32 values in [0, 1]
• Position Y: 32 values in [0, 1]

We varied one latent at a time (starting from Position Y, then Position X, etc), and sequentially stored the images in fixed order. Hence the order along the first dimension is fixed and allows you to map back to the value of the latents corresponding to that image.

We chose the latents values deliberately to have the smallest step changes while ensuring that all pixel outputs were different. No noise was added.

• Additional Documentation: Explore on Papers With Code

• Homepage: https://github.com/deepmind/dsprites-dataset

• Source code: tfds.datasets.dsprites.Builder

• Versions:

  • 2.0.0 (default): New split API (https://tensorflow.org/datasets/splits)
  • 2.1.0: No release notes.

• Download size: 26.73 MiB

• Dataset size: Unknown size

• Auto-cached (documentation): Unknown

• Splits:

Split	Examples
'train'	737,280

• Feature structure:

FeaturesDict({
    'image': Image(shape=(64, 64, 1), dtype=uint8),
    'label_orientation': ClassLabel(shape=(), dtype=int64, num_classes=40),
    'label_scale': ClassLabel(shape=(), dtype=int64, num_classes=6),
    'label_shape': ClassLabel(shape=(), dtype=int64, num_classes=3),
    'label_x_position': ClassLabel(shape=(), dtype=int64, num_classes=32),
    'label_y_position': ClassLabel(shape=(), dtype=int64, num_classes=32),
    'value_orientation': float32,
    'value_scale': float32,
    'value_shape': float32,
    'value_x_position': float32,
    'value_y_position': float32,
})

• Feature documentation:

Feature	Class	Shape	Dtype	Description
	FeaturesDict
image	Image	(64, 64, 1)	uint8
label_orientation	ClassLabel		int64
label_scale	ClassLabel		int64
label_shape	ClassLabel		int64
label_x_position	ClassLabel		int64
label_y_position	ClassLabel		int64
value_orientation	Tensor		float32
value_scale	Tensor		float32
value_shape	Tensor		float32
value_x_position	Tensor		float32
value_y_position	Tensor		float32

• Supervised keys (See as_supervised doc): None

• Figure (tfds.show_examples):

• Examples (tfds.as_dataframe):

• Citation:

@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",
}