Mahotas – Weight of Labeled Region
In this article we will see how we can obtain weights of labeled region in mahotas. Labeled images are integer images where the values correspond to different regions. I.e., region 1 is all of the pixels which have value 1, region two is the pixels with value 2, and so on. By convention, region 0 is the background and often handled differently. We can create a labelled region with the help of mahotas.label method.
We can get the size of each region with the help of mahotas.label_size method, this size is measured simply as the number of pixels in each region. We can instead measure the total weight in each area.
In order to do this we will use mahotas.label_size method
Syntax : mahotas.labeled_sum(array, labeled_region)
Argument : It takes two numpy.ndarray object as argument i.e random array of region shape and labeled region
Return : It returns list of numpy.float64 values
Sum of region 0 : 38.81707025816505 Sum of region 1 : 5.627375253802732 Sum of region 2 : 8.224633573583985
Sum of region 0 : 47.05475409838963 Sum of region 1 : 0.07129110100184632 Sum of region 2 : 0.9333006775043519 Sum of region 3 : 0.8322767370999588 Sum of region 4 : 0.1700224211466459