albumentations
Fast, flexible, and advanced augmentation library for deep learning, computer vision, and medical imaging. Albumentations offers a wide range of transformations for both 2D (images, masks, bboxes, keypoints) and 3D (volumes, volumetric masks, keypoints) data, with optimized performance and seamless integration into ML workflows.
Decision gist · record as of 2026-08-14
Yes. Albumentations is a mature, permissively licensed library with low install friction and no known vulnerabilities. The aging maintenance status (444 days since release) is a minor concern but does not block use for stable augmentation pipelines. Install it if you need a unified, production-grade augmentation API for computer vision tasks.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.9 or higher.
- Low friction install with 8 runtime dependencies including numpy, scipy, and opencv-python-headless.
- Maintenance status is aging (444 days since last release), though the package is marked Production/Stable and supports Python 3.9, 3.10, 3.11, 3.12, 3.13.
License · maintenance · safety
permissive license (permissive) — MIT License permits unrestricted use, modification, and distribution with minimal restrictions—suitable for both open-source and commercial projects.
last release 2025-05-27 (444 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 5,497,903 downloads/mo, #2,087 on PyPI
Alternatives
Verify before relying
pip install albumentations
import albumentations as A
transform = A.Compose([
A.RandomCrop(width=256, height=256),
A.HorizontalFlip(p=0.5),
])
transformed = transform(image=image)
transformed_image = transformed["image"]- Exact number of augmentation transforms available (description mentions '70+' but version-specific count unknown)
- Performance benchmarking details and comparison methodology against other libraries
- Whether all advertised framework integrations are actively maintained in version 2.0.8
What it is and what it does
Albumentations is a Python library for augmenting training data in computer vision and deep learning tasks. It provides a unified API to apply transformations to images, masks, bounding boxes, and keypoints—supporting classification, semantic and instance segmentation, object detection, and pose estimation. The library separates pixel-level transforms from spatial transforms and applies them consistently across all data types in a single pipeline.
The package depends on numpy, scipy, PyYAML, pydantic, albucore, opencv-python-headless, typing-extensions, and eval-type-backport. It is classified as Production/Stable and requires Python 3.9 or higher. The last release was 444 days ago.
Use it for
- Augment training datasets for image classification to improve model generalization without collecting new labeled data.
- Apply consistent transformations to images and bounding boxes for object detection model training.
- Generate varied training samples for semantic segmentation by transforming both images and pixel-level masks.
- Augment keypoint annotations alongside images for pose estimation and human pose recognition tasks.
- Preprocess medical imaging data with specialized augmentations for anomaly detection and diagnostic tasks.
- Create synthetic training variations for autonomous driving datasets with coordinated image and bounding-box transforms.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
Albumentations is a mature, permissively licensed library with low install friction and no known vulnerabilities. The aging maintenance status (444 days since release) is a minor concern but does not block use for stable augmentation pipelines. Install it if you need a unified, production-grade augmentation API for computer vision tasks.
Install
albumentations on PyPI
Before you install
Low friction install with 8 runtime dependencies including numpy, scipy, and opencv-python-headless. Maintenance status is aging (444 days since last release), though the package is marked Production/Stable and supports Python 3.9, 3.10, 3.11, 3.12, 3.13.
Requires Python 3.9 or higher.
License in practice
MIT License permits unrestricted use, modification, and distribution with minimal restrictions—suitable for both open-source and commercial projects.
Quickstart
pip install albumentations
import albumentations as A
transform = A.Compose([
A.RandomCrop(width=256, height=256),
A.HorizontalFlip(p=0.5),
])
transformed = transform(image=image)
transformed_image = transformed["image"]Verify before relying
- Exact number of augmentation transforms available (description mentions '70+' but version-specific count unknown)
- Performance benchmarking details and comparison methodology against other libraries
- Whether all advertised framework integrations are actively maintained in version 2.0.8
Package facts
| License | permissive license permissive |
| Python support | Supports the current Python release >=3.9 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 8 packagesnumpyscipyPyYAMLtyping-extensionspydanticalbucoreeval-type-backportopencv-python-headless |
| Maintenance | Aging 444 days since the last release |
| First released | |
| Downloads | 5,497,903 / month, #2,087 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersIntended Audience :: Healthcare IndustryIntended Audience :: Information TechnologyIntended Audience :: Science/ResearchLicense :: OSI Approved :: MIT LicenseOperating System :: OS IndependentProgramming Language :: PythonProgramming Language :: Python :: 3 :: OnlyProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.9Topic :: Scientific/EngineeringTopic :: Scientific/Engineering :: Artificial IntelligenceTopic :: Scientific/Engineering :: AstronomyTopic :: Scientific/Engineering :: Atmospheric ScienceTopic :: Scientific/Engineering :: Bio-InformaticsTopic :: Scientific/Engineering :: Image ProcessingTopic :: Scientific/Engineering :: PhysicsTopic :: Scientific/Engineering :: VisualizationTopic :: Software Development :: LibrariesTopic :: Software Development :: Libraries :: Python ModulesTyping :: Typed |
Evidence: albumentations-2.0.8-py3-none-any.whl
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See also batchgenerators · imgaug · pybboxes · batchgeneratorsv2 · ultralytics · audiomentations · ttach · cellpose · controlnet-aux · imgviz