The Jaccard index, also known as Intersection over Union and the Jaccard similarity coefficient (originally coined coefficient de communauté by Paul Jaccard), is a statistic used for comparing the similarity and diversity of sample sets. The Jaccard coefficient measures similarity between finite sample sets, and is defined as the size of the intersection divided by the size of the union of the sample sets:
(source: Wikipedia https://en.wikipedia.org/wiki/Jaccard_index)
Below a clear blog post about it:
https://www.pyimagesearch.com/2016/11/07/intersection-over-union-iou-for-object-detection/
I am using Intersection Over Union for testing solution to this kind of pcomputer vision problem for instance
https://www.kaggle.com/vanausloos/keras-linknet-with-intersection-over-union/edit?unified=1
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