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What steps will reproduce the problem?
1. use method predict() in ml.CvBoost when _missing matrix is null or ommited
(Mat())
predict( (CvBoost)inst, (Mat)_sample [, (Mat)_missing=Mat() [,
(Range)slice=Range(start=0, end=1073741823) [, (bool)raw_mode=False [,
(bool)return_sum=False]]]]) -> tuple :
What is the expected output? What do you see instead?
Expected output -> Tuple
we get -> OpenCV Error: Bad argument (the missing data mask must be 8-bit
vector of the same size as input sample) in CvBoost::predict, file
/home/eloi/Escriptori/OpenCV-2.1.0/src/ml/mlboost.cpp, line 1627
Traceback (most recent call last):
RuntimeError: OpenCV-2.1.0/src/ml/mlboost.cpp:1627: error: (-5) the missing
data mask must be 8-bit vector of the same size as input sample in function
CvBoost::predict
What version of the product are you using? On what operating system?
pyopencv-2.1.0.wr1.2.0, UBUNTU 9.10
Please provide any additional information below.
It seems that if _missing is missed then it creates a void Mat() and OpenCV
fails because the dimensions of the input sample and the void missing matrix
doesn't match.
Original issue reported on code.google.com by espavi...@gmail.com on 17 Nov 2010 at 10:41
The text was updated successfully, but these errors were encountered:
Original issue reported on code.google.com by
espavi...@gmail.com
on 17 Nov 2010 at 10:41The text was updated successfully, but these errors were encountered: