mAP(mean average precision) is an important parameter to tell whether an object detection model is good. Here I represent a python code to calculate mAP with given boxes edge from your prediction and data. The prediction should be in shape=(-1,5) [probability, xmin, ymin, xmax, ymax]and data in shape=(-1,4) [xmin, ymin, xmax, ymax]. If there is any bug inside, please contact me. Thanks! I didn't include probability(That a box is a real box) into account for now. Coming soon. Remember the data I include in our toy model is not accurate since I use a pre-trained yolov2 model which has different classes from the validation set. This is just a formula to calculate mAP.