Albumentations.AI
- 175 followers
- United States of America
- https://albumentations.ai/
- @albumentations
- company/albumentations
- https://discord.gg/e6zHCXTvaN
Albumentations is a widely adopted open-source image-augmentation ecosystem for computer vision. It helps engineers and researchers create valid training variation while keeping images, masks, bounding boxes, keypoints, volumes, and video frames synchronized.
AlbumentationsX is the actively developed library in the ecosystem. Install it with OpenCV for headless servers and training environments:
pip install "albumentationsx[headless]"The package preserves the familiar albumentations import path:
import albumentations as A
transform = A.Compose(
[
A.RandomCrop(height=256, width=256),
A.HorizontalFlip(p=0.5),
A.RandomBrightnessContrast(p=0.2),
]
)
augmented = transform(image=image, mask=mask)Use the documentation for guides and API details, or open Explore to test transforms in the browser.
| Component | What it provides |
|---|---|
| AlbumentationsX | Actively developed augmentation pipelines for images and synchronized annotations. |
| Website and documentation | Project homepage, guides, API documentation, blog, benchmarks, and transform reference. |
| Explore | Interactive browser playground for trying every transform on user-uploaded images. |
| Albucore | Optimized atomic image-processing functions with workload-aware backend selection. |
| albu-spec | Structured, typed metadata extracted from AlbumentationsX transforms. |
| Benchmark suite | Reproducible image, multichannel, video, and DataLoader comparisons. |
| Examples | Runnable notebooks for classification, segmentation, detection, keypoints, replay, serialization, and integrations. |
| Albumentations | The MIT-licensed legacy library, preserved for reproducibility, continued use, and forks. |
| 160.7M PyPI downloads |
15.3k GitHub stars |
40k+ GitHub-reported public dependents |
2,270 citing research works |
These figures describe public ecosystem adoption, not paid customers or endorsements. Downloads were checked on pepy.tech, stars and public dependents on GitHub, and research works in the deduplicated adoption snapshot on 22 July 2026. Browse the wider public adoption evidence. Albumentations is a NumFOCUS Affiliated Project.
Components of the ecosystem use different licenses. The legacy albumentations package and repository remain available under the MIT License. The current albumentationsx package and repository are available under AGPL-3.0-only.
The AGPL permits commercial use subject to its terms. Albumentations, LLC also offers separately negotiated commercial licenses for AlbumentationsX, with alternative rights defined by the applicable agreement. Whether a particular use complies with the AGPL depends on the deployment facts.
- Read the contribution guide and help improve AlbumentationsX.
- Ask usage questions and meet other practitioners on Discord.
- Follow releases and tutorials through the newsletter.
- Support long-term maintenance through GitHub Sponsors.
Code · Docs · Explore · Benchmarks · Sponsor
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Repositories
- AlbumentationsX Public
Next-generation Albumentations: dual-licensed for open-source and commercial use
- albucore Public
A high-performance image processing library designed to optimize and extend the Albumentations library with specialized functions for advanced image transformations. Perfect for developers working in computer vision who require efficient and scalable image augmentation.
- voxel51-plugin Public
- albu-spec Public
- benchmark Public
- albumentations Public archive
Fast and flexible image augmentation library. Paper about the library: https://www.mdpi.com/2078-2489/11/2/125
- albumentations-demo Public archive
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