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Undocumented flags in cv::detectMultiScale #4387
Transferred from http://code.opencv.org/issues/2142
Undocumented flags in cv::detectMultiScale
This is indeed still the case for the old cascades, but not for the cascades generated by the newer train_cascade interface. Since we were told that the haartraining interface will no longer be developed and actually be removed in the OpenCV3 interface, we should close down this bug, because fixing deprecated software is just not manageable.
Going back to the flags in cv::detectMultiScale apols as I am an OpenCV noob but why is there a lack of flags in the detect method so devs have more control over processing power vs accuracy?
I have been playing with a Raspberry Pi 3 which copes but does provide high latency via cv::detectMultiScale CV_HAAR_SCALE_IMAGE.
I managed to route out some code for cv.HaarDetectObjects which uses the flag
Is cv.HaarDetectObjects going to receive support as it is so much faster and also those flags do actually make much difference?
@StuartIanNaylor let me give you some answers
I guess not. The cv interface is the C-based API and is only still there because it is legacy code. However, it will be gone some day, so no support will be given for it.
If the flags do make so much difference, then maybe you should provide a PR that integrates the flags and accompanied code into the current detectMultiScale functionality. I guess that is the only way you are getting it in.
Actually, there is nothing holding you back to run do this technique yourself. Why should the actual detector do this for you? You can basically make a mask and run the detector only there. I do it all the time in my research.
Most of them are actually there, but not as flags but as actual parameters to be set. Scaling can be influenced. Getting largest object is simply looping over your returned data.
The only one seeming to be missing is the rough search now.
Actually it works on cv::detectMultiScale and its a choice of SCALE_IMAGE alone or if not included any of the other flags.
FIND_BIGGEST_OBJECT and FIND_BIGGEST_OBJECT are part of the function and can not be done before and as said
Doing this after will not be any faster.