Try these questions to test your knowledge from this chapter:
- When we trained the cascade classifier for the faces of the Boston Bulls, we annotated the dog faces on each image by ourselves. The annotation process cost us much time. There is a tarball of annotation data for that dataset at this website: http://vision.stanford.edu/aditya86/ImageNetDogs/annotation.tar. Could we generate the info.txt file from this annotation data via a piece of code? How would we do that?
- Try to find a pretrained (fast/faster) R-CNN model and a pretrained SSD model. Run them and compare their performance to YOLOv3.
- Could we use YOLOv3 to detect a certain kind of object, but not all the 80 classes of objects?
