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In this video tutorial, the instructor addresses screen tearing issues before diving into the topic of evaluating bounding box predictions in object detection. The focus is on how to measure the effectiveness of a predicted bounding box against a target bounding box for an object. The key metric introduced is Intersection over Union (IoU), which quantifies the accuracy of bounding box predictions. The tutorial also includes an implementation of IoU in PyTorch. After an introductory segment, the video will explore the details of calculating IoU using an example involving an image of a car and its corresponding bounding boxes.