Applications of Image Annotation
Image annotation is a process of adding labels or tags to an image to identify the content of the image. Image annotation can be used to train machine learning models for various applications, such as object detection, image classification, and activity recognition. There are many different ways to annotate images, such as bounding boxes, polygons, lines, and points. The type of annotation will depend on the application for which the image is being annotated. For example, bounding boxes are typically used for object detection, while polygons are more commonly used for image segmentation. Image annotation is a time-consuming process, but it is essential for training high-quality machine learning models. In this article, we will discuss the different applications of image annotation and some tips on how to do it effectively. Detection of Object of Interest One of the most imperative uses of image annotation is detecting objects within pictures. In an image, there are various things, or o...