Precision, Recall,IoU

From : https://github.com/AlexeyAB/darknet#how-to-train-to-detect-your-custom-objects

• IoU (intersect of union) - average instersect of union of objects and detections for a certain threshold = 0.24

• mAP (mean average precision) - mean value of average precisions for each class, where average precision is average value of 11 points on PR-curve for each possible threshold (each probability of detection) for the same class (Precision-Recall in terms of PascalVOC, where Precision=TP/(TP+FP) and Recall=TP/(TP+FN) ), page-11: http://homepages.inf.ed.ac.uk/ckiw/postscript/ijcv_voc09.pdf

In terms of Wiki, indicators Precision and Recall have a slightly different meaning than in the PascalVOC competition, but IoU always has the same meaning.