Introduction to the application architecture

As discussed in Chapter 1 and shown in Figure 4.1, Detectron2 has the architecture with the backbone network, the region proposal network, and the region of interest heads.

Figure 4.1: The main components of Detectron2

The backbone network includes several convolutional layers that help to perform feature extraction from the input image. The region proposal network is another neural network that predicts the proposals with objectness and locations of the objects before feeding to the next stage. The region of interest heads have neural networks for object localization and classification. However, the implementation details of Detectron2 are more involved. We should understand this architecture in depth to know what Detectron2 configurations to set and how to fine-tune its model.

Figure 4.2: Architecture of Detectron2’s implementation of Faster R-CNN

Detectron2’s architecture...