Getting the votes from the Hough transform

In the Hough transform, the votes give a good indication of how likely a certain pair of r and θ represent a line. But depending on the thickness and straightness of the lines in the image, the Hough transform can return multiple pairs of r and θ that represent lines that are very similar to each (i.e. colinear lines). We can then cluster the r and θ pairs into groups (especially useful when we know how many lines there are in the image), and use the centers of each group to get a mean line. But it would be even better to have the votes per pair of r and θ so that we can weigh the r and θ estimates accordingly when calculating the mean per group (and/or even before, during the clustering).

Start by locating the Hough transform implementation and the point where r and θ pairs are produced. Determine how the associated votes can be exposed; the work is done when callers can obtain votes per pair for weighted clustering or mean-line estimation.