Evaluation of semantic segmentation network with mAP I am interested in evaluating a semantic segmentation network. I've seen lots of challenges such as PASCAL VOC use the mean average precision metric(mAP). I understand how this would work with an instance detection approach, however I am unsure how it works for networks which just provide a  class label to each pixel. Should I treat each image as a single instance of each class?

Thanks
Here is a great post which explains the evaluation methods for semantic segmentation: https://www.jeremyjordan.me/evaluating-image-segmentation-models/

It also describes the mean average precision at the end.