Developing an object detection application
Object detection generally includes object localization and classification. Specifically, deep learning models for this task predict where objects of interest are in an image by giving the bounding boxes around these objects (localization). The following sections detail the steps to develop an object detection application using Detectron2 pre-trained models.
Getting the configuration file
Various pre-trained models for object detection tasks are available on the Detectron2 Model Zoo. These models are listed under the COCO Object Detection Baselines header. Specifically, there are three main categories of these baselines, namely the Faster Region-based Convolution Neural Network (R-CNN) subheader, the RetinaNet subheader, and the Region Proposal Network (RPN) and Fast R-CNN subheader. Figure 2.1 shows the available pre-trained models currently listed under the Faster R-CNN subheader.
Figure 2.1: Pre-trained...