Bounding boxes are a fundamental component of object detection, providing a rectangular region around objects of interest in an image. They are used to indicate the spatial location and size of an object, making it easier for the model to understand where the object is within the image. During training, bounding boxes, along with labels, serve as ground truth data, enabling the model to learn how to localize and classify objects. In practical applications, bounding boxes are used in tasks such as tracking objects in video feeds, autonomous vehicle navigation, and retail analytics.
What's the role of bounding boxes in object detection?
Keep Reading
How do you create a temporary table in SQL?
Creating a temporary table in SQL is a straightforward process that allows you to hold data temporarily during a databas
How does PCA relate to embeddings?
Principal Component Analysis (PCA) and embeddings are both techniques used to represent high-dimensional data in a lower
How do you handle out-of-vocabulary images in search?
Handling out-of-vocabulary images in search involves developing techniques to process and index images that do not have