# Image Augmentation

> Image Augmentation - Describes the settings available from the Image Augmentation advanced option
> tab, where you can create new training images by randomly transforming existing images, thereby
> increasing the size of the training data.

This Markdown file sits beside the HTML page at the same path (with a `.md` suffix). It summarizes the topic and lists links for tools and LLM context.

Companion generated at `2026-04-24T16:03:56.597979+00:00` (UTC).

## Primary page

- [Image Augmentation](https://docs.datarobot.com/en/docs/classic-ui/modeling/build-models/adv-opt/ttia.html): Full documentation for this topic (HTML).

## Sections on this page

- [Set transformations prior to modeling](https://docs.datarobot.com/en/docs/classic-ui/modeling/build-models/adv-opt/ttia.html#set-transformations-prior-to-modeling): In-page section heading.

## Related documentation

- [Classic UI documentation](https://docs.datarobot.com/en/docs/classic-ui/index.html): Linked from this page.
- [Modeling](https://docs.datarobot.com/en/docs/classic-ui/modeling/index.html): Linked from this page.
- [Build models](https://docs.datarobot.com/en/docs/classic-ui/modeling/build-models/index.html): Linked from this page.
- [Advanced options](https://docs.datarobot.com/en/docs/classic-ui/modeling/build-models/adv-opt/index.html): Linked from this page.
- [secondary dataset](https://docs.datarobot.com/en/docs/classic-ui/data/transform-data/feature-discovery/fd-overview.html): Linked from this page.
- [modify each needed blueprint](https://docs.datarobot.com/en/docs/classic-ui/modeling/special-workflows/cml/cml-blueprint-edit.html): Linked from this page.
- [here](https://docs.datarobot.com/en/docs/classic-ui/modeling/special-workflows/visual-ai/tti-augment/ttia-lists.html#augmentation-lists): Linked from this page.
- [Advanced Tuning](https://docs.datarobot.com/en/docs/classic-ui/modeling/analyze-models/evaluate/adv-tuning.html): Linked from this page.

## Documentation content

# Image Augmentation

Train-time image augmentation creates new training images by randomly transforming existing images, thereby increasing the size of (i.e., “augmenting”) the training data. This allows projects to be built with datasets that might otherwise be too small. In addition, all image projects that use augmentation have the potential for smaller overall loss by improving the generalization of models on unseen data.

> [!NOTE] Note
> If you add a [secondary dataset](https://docs.datarobot.com/en/docs/classic-ui/data/transform-data/feature-discovery/fd-overview.html) with images to a primary tabular dataset, the augmentation options described above are not available. Instead, if you have access to Composable ML, you can [modify each needed blueprint](https://docs.datarobot.com/en/docs/classic-ui/modeling/special-workflows/cml/cml-blueprint-edit.html) by adding an image augmentation vertex directly after the raw image input (as the first vertex in the image branch) and configure augmentation from there.

## Set transformations prior to modeling

After selecting your target, toggle on the Image Augmentation tab in Advanced options.

From there, begin selecting transformation settings, described [here](https://docs.datarobot.com/en/docs/classic-ui/modeling/special-workflows/visual-ai/tti-augment/ttia-lists.html#augmentation-lists). These settings will be applied to all models when running Autopilot or using the Repository.

You can continue to modify settings, clicking Preview augmentation to view a sample of results:

The settings you choose are automatically saved as a list named Initial Augmentation List. If you do not set transformations through Advanced options, you can later create augmentation lists using the [Advanced Tuning](https://docs.datarobot.com/en/docs/classic-ui/modeling/analyze-models/evaluate/adv-tuning.html) tab.