mAP is commonly used to evaluate the performance of object detection models. However, there are two variables that need to be set when calculating mAP:
- confidence threshold
- IoU threshold
Just to clarify, confidence threshold is the minimum score that the model will consider the prediction to be a true prediction (otherwise it will ignore this prediction entirely). IoU threshold is the minimum overlap between ground truth and prediction boxes for the prediction to be considered a true positive.
Setting both of these thresholds to be low would result in a greater mAP. However, the low thresholds would most likely be inconsistent with the mAP scores from other studies. How does one select, and justify, these threshold values?