# mdbloice/Augmentor

Image augmentation library in Python for machine learning.

Repository: https://github.com/mdbloice/Augmentor
Canonical: https://ross.abutalabs.com/products/augmentor
Homepage: https://augmentor.readthedocs.io/en/stable
Language: Python
License: MIT
License Family: permissive
Topics: augmentation, machine-learning, deep-learning, neural-networks
Last push: 2024-03-21T14:27:34+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": 3837, "days_push": 895, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 5133, forks 870 (observed 2026-08-28T04:09:11.053799+00:00)

## What it is
Augmentor is a standalone Python library for image augmentation in machine learning, providing a pipeline of stochastic operations like rotations and transforms to artificially expand image datasets. It is platform and framework independent, allowing fine-grained control over augmentation techniques.

## Use cases
- augment image datasets for training neural networks
- generate artificial training images for deep learning
- build a pipeline of image transformations like rotations and flips
- expand a small image dataset for machine learning
- apply stochastic image augmentations framework-independently

## When to choose
- you need a simple, framework-independent image augmentation library in Python
- you want fine-grained control over augmentation operations via a pipeline
- you need to expand image datasets for deep learning models

## When to avoid
- you need GPU-accelerated or real-time augmentation integrated into a deep learning framework
- you need augmentation for non-image data types
- you require very recent features or active development

## Facets
- artifact type: library
- maturity: maintenance
- function: image-processing, machine-learning, data-generation
- domain: machine-learning, deep-learning, image-processing, data-science
- platform: python, cross-platform
- tags: image-augmentation, data-augmentation, pipeline, computer-vision, dataset-expansion

## Member repositories
- mdbloice/Augmentor (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:11.053799+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 2026-08-29T18:02:02.023755+00:00, confidence not recorded.
  - readme: https://github.com/mdbloice/Augmentor (fetched 2026-08-28T04:09:11.053799+00:00, sha 9a9278a16c98)
  - registry_pypi: https://pypi.org/pypi/augmentor/json (fetched 2026-08-29T08:57:01.835502+00:00, sha cbb8662d4b49)
- Data as of 2026-08-30T08:39:29.467469+00:00.