What is albumentations?

79/100
Trust Score (B+)
✅ Safe

albumentations is a pypi that 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, key. It has a Nerq Trust Score of 79/100 (B+). 0 GitHub stars. Published by Vladimir Iglovikov. Last analyzed October 2026.

Why This Score

Trust & Safety Overview

79
TRUST SCORE
B+
GRADE
0
STARS
0
DOWNLOADS

What albumentations Does

albumentations is a pypi in the pypi category. 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.. It is published by Vladimir Iglovikov and has no specified license. With 0 GitHub stars and 0 downloads, it has a small community of users and contributors.

Who Should Use albumentations

albumentations is well-suited for production use given its strong trust score and active community.

Details

AuthorVladimir Iglovikov
Categorypypi
LicenseNot specified
Typepypi
SourceView on GitHub
Security Score0/100
Activity Score0/100

How to Get Started

Check the trust score before installing:

curl nerq.ai/v1/preflight?target=albumentations

Setup guide · Full safety report · Production review · Is it safe?

Frequently Asked Questions

What is albumentations used for?
albumentations is a pypi tool. 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, key.
Is albumentations free?
License: Check project page. albumentations has 0 GitHub stars.
Is albumentations safe?
albumentations has a Nerq Trust Score of 79/100 (B+). Safe for production use.
What are alternatives to albumentations?
Top alternatives: . See full comparison.

Last updated October 2026. Trust scores based on automated analysis of public data.

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