Object detection is the process of finding instances of real-world objects such as persons, cars, vehicle, animals, bicycles and buildings in images or videos.
Object detection algorithms typically use deep learning algorithms to recognize instances of an object category.
Given an image or a video stream, an object detection model can identify which of a known set of objects might be present and provide information about their positions within the image. It will output a list of the objects it detects, the location of a bounding box that contains each object, and a score that indicates the confidence that detection was correct.
An object detection model is trained to detect the presence and location of multiple classes of objects.
Software has been trained to detect more than 1000 objects.