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Object Detection is crucial for applications like Autonomous Driving and Surveillance. To evaluate the quality of bounding boxes post-detection, Intersection over Union (IoU) is used, calculated as the Area of Intersection divided by the Area of Union. Using a bird image as an example, three detection models (A, B, and C) are compared, with the Ground Truth marked in red and predictions in cyan. Model A shows a higher overlap with the Ground Truth than Model B, suggesting better performance. However, Model C, which exhibits an even higher overlap than Model B, has an issue with the localization of its predictions. Thus, while overlap is important, localization quality must also be considered in evaluating model performance.
