# 06 - Image Augmentation: Techniques to Prevent Overfitting

Complete guide to Image Augmentation: Techniques to Prevent Overfitting: architecture, practical implementation and best practices for developers and technical teams.

## What you'll learn

- 1.1 Mapping Invariances to Transformations by Domain
- 2.1 Albumentations vs torchvision.transforms: Choosing the Right Tool
- 3.1 MixUp: Interpolating Between Images
- 3.2 AutoAugment, RandAugment, and TrivialAugment
- 3.3 Test-Time Augmentation (TTA)

*This article is part of the **Computer Vision** series on federicocalo.dev.*

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## Read the full article

The complete article (14 min read) with code examples, diagrams, and practical exercises is available here:

**➡️ [06 - Image Augmentation: Techniques to Prevent Overfitting](https://federicocalo.dev/en/blog/image-augmentation-techniques-prevent-overfitting)**

`https://federicocalo.dev/en/blog/image-augmentation-techniques-prevent-overfitting`

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*By [Federico Calò](https://federicocalo.dev) — Software Developer & Technical Writer*