Giters

qubvel / segmentation_models

Segmentation models with pretrained backbones. Keras and TensorFlow Keras.

Geek Repo:Geek Repo

Github PK Tool:Github PK Tool

mIoU with background in semantic segmentaion

Gil-TakKong opened this issue · comments

commented

Hi!

I have a question about background in the calculation of the mIoU.

When we calculate the mIoU of the segmentaion, usually IoU of the background is included.

In that case, mIoU is at least 0.45 even the model didn't catch anything because of the IoU(background).

I wondering about
Is the calculation(mIoU with background) correct or reasonable?
If the calculation is not reasonable, then how can we measure the performance of the segmentation model?

Thank you.

commented

Hi @Gil-TakKong

I think, background can ignored by passing class_indexes argument to the sm.metrics.IOUScore() function.

For example, to ignore background during IoU evaluation (for 3 classes CLASSES = ['sky', 'building', 'pole', 'unlabelled/background']), sm.metrics.IOUScore() function can be modified as follows:

metrics = [sm.metrics.IOUScore(threshold=0.5,class_indexes=[0,1,2]), sm.metrics.FScore(threshold=0.5,class_indexes=[0,1,2])]

Cheers