brendenlake/omniglot resource

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1421 stars · 356 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

The Omniglot dataset for one-shot learning, containing 1,623 handwritten characters from 50 alphabets, each drawn by 20 people with paired stroke coordinate data. It includes background/evaluation splits and Python starter code for benchmarking human-like learning algorithms.

Use cases

• benchmark one-shot learning algorithms
• train few-shot image classification models
• research meta-learning with minimal training data
• model human-like concept learning from few examples
• work with handwritten character stroke data
• evaluate generative models of handwriting

When to choose

• you need a standard benchmark for one-shot or few-shot learning
• you want both raster images and stroke sequences for characters
• you are reproducing results from the Omniglot challenge papers

When to avoid

• you need large-scale training data with many examples per class
• you need production-ready code rather than a research dataset
• you need natural images rather than handwritten characters

Facets

dataset · maturity stable

machine-learning data-science computer-vision machine-learning deep-learning computer-vision python cross-platform one-shot-learning handwritten-characters benchmark-dataset few-shot-learning stroke-data meta-learning natural-language-processing

Member repositories

For agents

markdown · JSON · MCP: product_card(name="brendenlake/omniglot")