My assumption was correct: the ground truth bounding box is aligned with an anchor box such that they share the same center In other words, only the widths and heights are used to calculate the ground truth IOU.


A bounding box is a rectangle superimposed over an image within which all important features of a particular object is expected to reside. It's purpose is to reduce the range of search for those object features and thereby conserve computing resources: Allocation of memory, processors, cores, processing time, some other resource, or a combination of them. ...


There are some special architectures of CNNs which are designed exactly for the task you mention. The Detector library includes a collection of these architectures, this paper describes the Mask R-CNN network in detail, which is designed for image segmentation tasks.

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