We use visual tool to mark the boundary of objects in the training data (like https://github.com/puzzledqs/BBox-Label-Tool)and have program to convert them into the labels we want. We find the center of the bounding box and assign to the corresponding grid with prob=1.0. Often, we use Amazon Mechanical Turk to outsource the task. It is expensive and therefore they use public dataset like COCO. The confidence score (and objectness) is more like a probability rather than an unlimited range number.