How to get the confidence of HaarDetection in python openCV 2.0 -

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the old version of opencv returned number of neighbors detected, , used measure of confidence.

for example:

cv.haardetectobjects(grayscale, cascade, storage, 1.2, 2, cv.cv_haar_do_canny_pruning, (50,50)) [((174, 54, 114, 114), 53)]

the new version of opencv changed signature used, either

detectmultiscale(image[, scalefactor[, minneighbors[, flags[, minsize[, maxsize]]]]]) -> objects

or 

detectmultiscale(image, rejectlevels, levelweights[,  scalefactor[, minneighbors[,  flags[, minsize[, maxsize[, outputrejectlevels]]]]]]) -> objects

the second signature has rejectlevels , levelweights which, understanding, can used confidence.

this reflection of c++ version of functions. but, unclear me how pass parameters changed in python. i've tried, example, following, not change r , w:

r = list() w = list() res = cascade2.detectmultiscale(image=img, rejectlevels=r, levelweights=w) print res print r, w  [[ 82 158  53  53]  [175 157  52  52]  [103 266 112 112]] [] []

can explain how pass r , w updated?


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