[FIXED] How to find IoU from segmentation masks?

Issue

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

Solution

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

Answered By - Farshid Rayhan