Summary

This chapter described the steps to apply image augmentation techniques using Detectron2 at both train time and test time (inferencing time). Detectron2 provides a declarative approach to applying existing augmentations conveniently. However, the current system supports augmentations on a single input, while several modern image augmentations require data from different inputs. Therefore, this chapter described the Detectron2 data loader system and provided steps to modify several Detectron2 data loader components to enable applying modern image augmentation techniques such as MixUp and Mosaic that require multiple inputs. Lastly, this chapter also described the features in Detectron2 that allow for performing test-time augmentations.

Congratulations! You now understand the Detectron2 architecture for object detection models and should have mastered the steps to prepare data, train, and fine-tune Detectron2 object detection models. The following part of this book has a similar...