Description: Anchor boxes are fundamental tools in the field of computer vision, used for object detection in images and videos. These boxes are rectangular delimitations placed around objects of interest in an image, providing a framework that helps machine learning models identify and predict the location of those objects. Each anchor box is defined by its coordinates, indicating its position and size, and is associated with a label that identifies the type of object it contains. The use of anchor boxes allows object detection algorithms to learn to recognize specific patterns and characteristics of objects, facilitating their identification in different contexts and conditions. Furthermore, anchor boxes play a crucial role in training convolutional neural network (CNN) models, which are widely used in various computer vision tasks. Their implementation has revolutionized the way machines interpret images, enabling advanced applications in areas such as security, automotive, and robotics.
