👉 The term "IoU" stands for Intersection over Union, a metric used primarily in computer vision and machine learning to measure the overlap between two overlapping bounding boxes that are attempting to label the same object in an image. Specifically, IoU calculates the ratio of the area where the boxes intersect (the intersection area) to the total area of the bounding boxes (the union area). A higher IoU value indicates better overlap and, consequently, a more accurate prediction. For example, if two bounding boxes have an intersection area of 10 pixels out of a total union area of 100 pixels, the IoU is 0.1, or 10%. This metric is crucial for evaluating the performance of object detection models, as it helps quantify how well the model's predictions align with ground truth annotations.
