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Hands-On Computer Vision with Detectron2
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Applying augmentations in Detectron2 can be straightforward and complicated at the same time. It is relatively easy to use the declarative approach and apply existing transformations and augmentations provided by Detectron2, which should meet the most common needs. However, adding custom augmentations that require multiple data samples (e.g., MixUp and Mosaic) is a little complicated. This section describes how Detectron2 loads data and how to incorporate existing and custom data augmentations into training Detectron2 models. Figure 9.1 illustrates the steps and main components of the Detectron2 data loading system.
Figure 9.1: Loading data and data augmentations in Detectron2
There are classes for Dataset, Sampler, Mapper, and Loader. The Dataset component normally stores a list of data items in JSON format. The Sampler component helps to randomly select one data item (dataset_dict) from the dataset. The selected data item has...