# wyharveychen/CloserLookFewShot

source code to ICLR'19, 'A Closer Look at Few-shot Classification'

Repository: https://github.com/wyharveychen/CloserLookFewShot
Canonical: https://ross.abutalabs.com/products/closerlookfewshot
Language: Python
License: NOASSERTION
License Family: other
Last push: 2021-12-14T23:56:23+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2788, "days_push": 1723, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1159, forks 268 (observed 2026-08-28T04:03:48.664497+00:00)

## What it is
Reference PyTorch implementation of the ICLR 2019 paper 'A Closer Look at Few-shot Classification', providing a testbed for empirical evaluation of few-shot image classification methods. It includes training, feature extraction, and testing pipelines across datasets like mini-ImageNet, CUB, and Omniglot.

## Use cases
- reproduce few-shot classification baselines
- benchmark meta-learning methods on mini-ImageNet
- evaluate few-shot learning on CUB and Omniglot
- compare baseline vs meta-learning approaches
- run cross-domain few-shot experiments
- extract and save backbone features for fast testing

## When to choose
- you need a standard testbed for few-shot classification research
- you want to reproduce or compare against the paper's published results
- you need ready-made data pipelines for mini-ImageNet, CUB, or Omniglot

## When to avoid
- you need modern PyTorch support (the code targets PyTorch < 0.4)
- you want a production-ready or maintained library
- you need few-shot learning for non-image modalities

## Facets
- artifact type: library
- maturity: maintenance
- function: machine-learning, deep-learning, benchmarking
- domain: machine-learning, deep-learning, computer-vision
- platform: python
- tags: few-shot-learning, meta-learning, pytorch, iclr-2019, image-classification, research-code, benchmark, research, linux, macos

## Member repositories
- wyharveychen/CloserLookFewShot (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:48.664497+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:31:55.275377+00:00, confidence not recorded.
  - readme: https://github.com/wyharveychen/CloserLookFewShot (fetched 2026-08-28T04:03:48.664497+00:00, sha b1390bb0f898)
  - registry_pypi: https://pypi.org/pypi/closerlookfewshot/json (fetched 2026-08-29T12:36:38.448741+00:00, sha bcc65d563ef9)
- Data as of 2026-08-30T08:39:29.467469+00:00.