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---

# Dataset Card for dSprites

<!-- Provide a quick summary of the dataset. -->

## Dataset Details

### Dataset Description

<!-- Provide a longer summary of what this dataset is. -->
dSprites is a dataset of 2D shapes procedurally generated from 6 ground truth independent latent factors. These factors are color, shape, scale, rotation, x-position, and y-position of a sprite. All possible combinations of these latents are present exactly once, generating 737,280 total images. The dataset is widely used for studying disentangled representations in machine learning.

### Dataset Sources

<!-- Provide the basic links for the dataset. -->

- **Homepage:** https://github.com/google-deepmind/dsprites-dataset
- **Paper:** Matthey, L., Higgins, I., Hassabis, D., & Lerchner, A. (2017, May). dsprites: Disentanglement testing sprites dataset.

## Dataset Structure

<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->

Each sample in the dataset contains:

- **image:** A 64×64 grayscale image

- **orientation:** A float representing the rotation angle of the shape

- **shape:** A categorical label representing the shape type (square, ellipse, heart)

- **scale:** A float representing the size of the shape

- **color:** A categorical label representing the color (only 'white' in this dataset)

- **position_x:** A float representing the x-position of the shape

- **position_y:** A float representing the y-position of the shape

Total images: 737,280

Classes: 3 (square, ellipse, heart)

Splits:

- **Train:** 70% of total dataset

- **Test:** 30% of total dataset

Image specs: PNG format, 64×64 pixels, grayscale

## Example Usage
Below is a quick example of how to load this dataset via the Hugging Face Datasets library.
```
from datasets import load_dataset  

# Load the dataset  
dataset = load_dataset("../../aidatasets/images/dsprites.py", split="train", trust_remote_code=True)
# dataset = load_dataset("../../aidatasets/images/dsprites.py", split="test", trust_remote_code=True)  

# Access a sample from the dataset  
example = dataset[0]  
image = example["image"]  
shape = example["shape"]  

image.show()  # Display the image  
print(f"Shape: {shape}")
```

## Citation

<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->

**BibTeX:**

@misc{matthey2017dsprites,
  title={dsprites: Disentanglement testing sprites dataset},
  author={Matthey, Loic and Higgins, Irina and Hassabis, Demis and Lerchner, Alexander},
  year={2017}
}