How to find IoU from segmentation masks?
I am doing an image segmentation task and I am using a dataset that only has ground truths but no bounding boxes or polygons.

I have 2 classes( ignoring 0 for background) and the outputs and ground truth labels are in an array like 

Predicted--/---Labels 

0|0|0|1|2   0|0|0|1|2 
 0|2|1|0|0   0|2|1|0|0
 0|0|1|1|1   0|0|1|1|1
 0|0|0|0|1   0|0|0|0|1

How do I calculate IoU from these ? 

PS: I am using python3 with pytorch api

So I just found out that jaccard_similarity_score is regarded as IoU.

So the solution is very simple,

from sklearn.metrics import jaccard_similarity_score
 jac = jaccard_similarity_score(predictions, label, Normalize = True/False)

Source link: https://scikit-learn.org/stable/modules/generated/sklearn.metrics.jaccard_score.html#sklearn.metrics.jaccard_score  
