datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
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.simple-shapes-256x256
simple-shapes-256x256
6 diffrent simple shapes. Use for benchmarking, and simple shape recognission.
Teachable machine link: https://teachablemachine.withgoogle.com/models/AQwwPGTH1/
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Splits
Split
Count
train
85
Usage
from datasets import load_dataset
ds =… See the full description on the dataset page: https://huggingface.co/datasets/simonko912/simple-shapes-256x256.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.Water-Heater-Shape-Classification-Dataset
Water Heater Shape Classification Dataset
The retail e-commerce industry is rapidly evolving, facing challenges in accurately categorizing diverse product shapes to enhance customer experience. Existing solutions often struggle with inconsistent labeling and insufficient datasets, leading to poor classification performance. This dataset aims to tackle the specific need for robust image classification of water heater shapes, addressing the gap in reliable training data for machine… See the full description on the dataset page: https://huggingface.co/datasets/Mobiusi/Water-Heater-Shape-Classification-Dataset.