In the realm of computer vision, a label is a textual or numerical annotation assigned to an object or a region of interest in an image or video. Labels play a crucial role in supervised machine-learning applications, where they are utilized to train algorithms to recognize and classify objects in visual data. They serve to identify objects, demarcate their boundaries, and describe attributes like color, shape, or texture. Labels are generally assigned either manually by human annotators or generated automatically via computer-vision algorithms. The quality and precision of labels can notably influence the performance of computer-vision systems.
Currently, mainstream data labeling platforms include Roboflow, Labelbox, Label Studio, Makesense, T-Rex Label, and so on.