Pick centers in KMeans++ with a probability proportional to their distance^2, instead of simple distance, to previous centers
Apply to KMeansIndex KMeanspp the same modification as in HierarchicalClusteringIndex
As some processed distances are already ^2, use template to select whether or not we have to ^2 in KMeanspp
Move templates in dist.h in order to share them between KMeansIndex and HierarchicalClusteringIndex classes.
Optimizations to OpenCL bilateral filter.
perf report: summary.py: added custom --regressions map
Optimizations to OpenCL bilateral filter.
Resolving conflicts after rebasing from public
TAPI: added perf test for stitching
TAPI: stitching, replaced Mat->UMat/_Array
features2d: workaround for 'utrainDescCollection' issue (PR #2142)
TAPI: stitching: improve warpers
TAPI: stitching: workaround for problem getUMat() call
TAPI: stitching: optimize exposure
TAPI: stitching: optimize compare operation
stitching: use BORDER_CONSTANT in warp
stitching: extend logging
TAPI: stiching: add custom OpenCL kernels for MultiBandBlender
stitching: allow to use dynamic DescriptorMatcher
TAPI: stitching: blender: fix OpenCL path & adjust test condition