What is 2D image annotation? What is the use of 2D bounding box annotation?

Image annotation is the technique of making the objects in the images recognizable to machine through computer vision. And there are different types of annotation techniques used in image annotation. 2D bounding box annotation is one the very popular among all types of data annotation.

In 2D Image annotation a rectangular or square line is drawn around the object of interest with motive to make it only recognizable that there is some kind of object visible in the environment. The two dimensions of the object is captured to make it recognizable for machine learning training.

And while drawing the 2D image annotation, either shades or without shaded boxes are drawn as per the requirements. It is very simple to draw the 2D bounding box annotation and there are various tools or software available making the bounding box annotation easier for the annotators.

Use of 2D Bounding Box Annotation

To make all types of objects visible in their natural environment, 2D bounding box annotation is used. From self-driving cars to drones and robotics, this technique of image annotation is used to create the huge amount of training data for machine learning into different fields.

In autonomous driving 2D bounding box annotation is used to train autonomous vehicles to detect the various objects on the streets like lanes, traffic, potholes, signals, and other objects. AI models developed for different sectors like retail, automotive, healthcare and agriculture, 2D bounding box annotation is used to simply make objects recognizable or detectable through computer vision.

Anolytics provides the 2D Bounding Box Annotation with extra level of precision creating the huge amount of training datasets for machine learning algorithms. Using the most advance tools and techniques, Anolytics is working with well-trained and highly skilled annotators to produce the high-quality training data for machine and deep learning based visual perception AI models.