What Is Bounding Box Annotation?

What Is Bounding Box Annotation?

Bounding Box is one of the most widely used techniques to annotate objects in images or videos by drawing a rectangular box around the object of interest. It is used in computer vision and ML applications to train algorithms to recognize and detect objects.

Use Cases

Use Cases

Object Detection

Object Detection





Bounding box is used to train object detection models to identify and locate objects in images or videos. This application is used in Autonomous Driving, Surveillance, and Robotics.




Object-Detection-Before-Image Object-Detection-After-Image
Object-Detection-Before-Image

Image Classification

Image Classification

Image-Classification-Before Image-Classification-After
Image-Classification-Before




Bounding box can be used to classify images based on the objects they contain. This application is used in E-commerce, Medical Imaging, and Agriculture.





Face Recognition

Face Recognition





Bounding box is also used to identify and locate faces. This application is used in Security, Entertainment, and Marketing.




Face-Recognition-Before Face-Recognition-After
Face-Recognition-Before

Image Segmenting

Image Segmenting

Image-Segmenting-Before Image-Segmenting-After
Image-Segmenting-Before




Bounding box is used to label parts of an image or video frame based on their semantic meaning. This application is used in medical imaging, satellite imagery, and NLP.




Object Tracking

Object Tracking




Bounding box is applied to track the movement of objects in videos over time. This application is used in sports analysis, traffic monitoring, and animal behavior research.





Object-Tracking-Before Object-Tracking-After
Object-Tracking-Before

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