datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
geometric-shapes
Dataset Card for Geometric Shapes Dataset
Dataset Description
Dataset Summary
The Geometric Shapes Dataset is a synthetic dataset containing images of various geometric shapes with superimposed random text. Each image features a polygon (or just text) on a randomly colored background, with a short string of random characters partially obscuring the shape. This dataset is designed for tasks such as shape classification, image recognition, and… See the full description on the dataset page: https://huggingface.co/datasets/0-ma/geometric-shapes.texture-shape-cue-conflictThis dataset contains the stimuli for ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness by Robert Geirhos, Patricia Rubisch, Claudio Michaelis, Matthias Bethge, Felix A. Wichmann, and Wieland Brendel.
The stimuli allow testing of the texture/shape bias in an observer model (human or artificial) by containing two conflicting cues per image (shape and texture). The images generated using iterative style transfer (Gatys et al., 2016) between… See the full description on the dataset page: https://huggingface.co/datasets/rgeirhos/texture-shape-cue-conflict.shape-counting-dataset
Shape Counting Dataset
A dataset for evaluating shape counting abilities in vision models and humans.
Dataset Description
This dataset contains images with varying numbers of squares, triangles, and stars on a white background. Each image is provided in multiple versions: the original clean image plus several noisy variants.
Image Specifications
Size: 256×256 pixels
Format: Grayscale PNG
Shape size: 18 pixels
Background: White (255)
Shapes: Black (0)… See the full description on the dataset page: https://huggingface.co/datasets/nooranis/shape-counting-dataset.synthetic-shapes-3x6x7
Synthetic Shapes 3×6×7
A fully deterministic synthetic dataset of simple geometric shapes rendered as SVG images, with precomputed CLIP (ViT-B-32) embeddings for both text and images.
Purpose
This dataset is designed for controlled experiments in representation alignment and steering vector evaluation. Because images are generated deterministically from a known combinatorial space, it provides a clean testbed where ground-truth structure is fully known.… See the full description on the dataset page: https://huggingface.co/datasets/amirali1985/synthetic-shapes-3x6x7.colored-shapesThis dataset is generated as a part of a tutorial on fitting PyTorch models. The tutorial is at github.com/sdtemple/zootopia3.
You can generate your own data with answers/simulation-exercise.ipynb at the repo.
Treat this as held-out test data, with 20 examples for each shape (4) and color (8) combo.