--- # For reference on dataset card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/datasetcard.md?plain=1 # Doc / guide: https://huggingface.co/docs/hub/datasets-cards {} --- # Dataset Card for dSprites ## Dataset Details ### Dataset 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-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 - **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 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 **BibTeX:** @misc{matthey2017dsprites, title={dsprites: Disentanglement testing sprites dataset}, author={Matthey, Loic and Higgins, Irina and Hassabis, Demis and Lerchner, Alexander}, year={2017} }