Summary
This chapter described the common places to acquire data for object instance segmentation tasks, and the steps to extract data from a non-standard annotation format and create a custom dataset in the format supported by Detectron2. Furthermore, it utilized the code and visualizations approach to illustrate the architecture of the object instance segmentation application implemented in Detectron2 as an extension of the architecture of an object detection application. Finally, it provided the steps to train a custom model for object instance segmentation tasks and visualize the prediction results for qualitative evaluations.
The next chapter describes techniques for fine-tuning the object instance segmentation application and improving segmentation quality using Detectron2.
