Object detection
Object detection is the process of finding object instances of a certain class, such as people, cars, and trees, in images or videos. Unlike classification, object detection can detect multiple objects as well as their location in the image.
An object detector would return a list of detected objects with the following information for each object:
- The class of the object (person, car, tree, and so on).
- A probability (or objectness score) in the [0, 1] range, which conveys how confident the detector is that the object exists in that location. This is similar to the output of a regular binary classifier.
- The coordinates of the rectangular region of the image where the object is located. This rectangle is called a bounding box.
We can see the typical output of an object-detection algorithm in the following figure. The object type and objectness score are above each bounding box:
Figure 5.2 – The output of an object...