Up today in the company where I work we are using the F1 Score for evaluating the performance of our model, also our competitor's using the same metric.
I would like to understand what's the difference between F1,F2 and mAP?(Please do not explain me how to calculate them, also I know that F measure gives the same weight to the precision and recall while mAP choose the best precision from all recalls)
Why in competitions (e.g. PASCAL VOC) and articles for object detection I am reading it is always preferred to use mAP instead of F1 or F2 scores ?