mIoU of semantic segmentation for incorrect Prediction.

[Gil-TakKong]

Hi!

I am wondering about mIoU method.
When I calculate mIoU of an image with incorrect prediction, if there are wrong label region, the IoU of the label is nan, not 0.

Here is the example.

Class in Ground Truth : Background, L1, L2
Class in Prediction : Background, L1, L2, L3

(1) mIoU = {IoU(BG) + IoU(L1) + IoU(L2)} / 3
Is it right?

I think, the formular should be
(2) mIoU = {IoU(BG) + IoU(L1) + IoU(L2) + IoU(L3)} / 4

If (1) is right, could you explain about why the IoU of L3 is not included?

Thank you.