Basic Usage Guides 🔗

This section provides guides for common augmentation tasks, data types, and optimization strategies.

• Optimizing Pipelines for Speed: Strategies to make your augmentation pipelines run faster and avoid CPU bottlenecks.

• Choosing Augmentations for Generalization: How to select augmentations that help improve your model's performance on unseen data.

• Image Classification: Augmenting images for classification tasks.

• Semantic Segmentation: Augmenting images and corresponding segmentation masks.

• Object Detection (Bounding Boxes): Augmenting images and bounding boxes, including format handling.

• Keypoint Augmentation: Augmenting images and associated keypoints.

• Video Augmentation: Applying consistent augmentations across sequences of images (video frames).

• Volumetric Augmentation: Working with 3D data like CT or MRI scans and corresponding 3D masks.

Where to Go Next? 🔗

After exploring the basic usage examples relevant to your task, you might want to:

• Dive into Advanced Guides: Explore topics like creating custom transforms, serialization, or using additional targets.
• Revisit Core Concepts: Solidify your understanding of transforms, pipelines, targets, and probabilities.
• Visually Explore Transforms: Experiment with the full range of available augmentations.