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Hi,
I'm having difficulity using the IPP5.1 Mixed (Tilted and Non-tilted) classifier API with a tilted classifier trained using OpenCV. Non-tilted classifiers appear to work equivalently.
I am initializing the tilted integral images as such:
ret = ippiTiltedSqrIntegral_8u32s64f_C1R((const Ipp8u*)resizedSrc8u.imageData,resizedSrc8u.widthStep,
(Ipp32s*)resizedTiltedSrc.imageData,resizedTiltedSrc.widthStep,
(Ipp64f*)resizedTiltedSqr.imageData,resizedTiltedSqr.widthStep,
roi,(Ipp32f)(-(1<<24)),0.0);
ret = ippiTiltedRectStdDev_32s32f_C1R((const Ipp32s*)resizedTiltedSrc.imageData,resizedTiltedSrc.widthStep, (Ipp64f*)resizedTiltedSqr.imageData,resizedTiltedSqr.widthStep,
(Ipp32f*)resizedTiltedNorm.imageData,resizedTiltedNorm.widthStep,
roi1,rect);
Where the structures are IplImage stubs and the tilted integral destination images are of width/height = (resizedSrc8u.width+resizedSrc8u.height)/sqrt(2).
The call to apply the mixed Classifier is:
ret = ippiApplyMixedHaarClassifier_32s32f_C1R( (const Ipp32s*)resizedSrc.imageData,resizedSrc.widthStep,
(const Ipp32s*)resizedTiltedSrc.imageData,resizedTiltedSrc.widthStep, (Ipp32f*)resizedTiltedNorm.imageData,resizedTiltedNorm.widthStep, // ????
(Ipp8u*)resizedMask.imageData, resizedMask.widthStep,
roi1,&positive,sThreshold,pHaar);
Note my confusion as to which normalized image to use (from the ippiTiltedRectStdDev_32s32f_C1R or from the non-tilted call (not shown) to ippiRectStdDev_32s32f_C1R(). Use of the non-tilted normalized image appears to provide better results, but begs the question as to why we calculated the TiltedNorm image in the first place.
Is there any secret XY offset value to ROI that we should apply when passing in the tilted integral images? Is there any example code similar to that provided for non-tilted classifiers available for 5.1?
Thanks,
Randy
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Hello Randy,
could you please provide simple test case (it is not obvious what is your ROI size, how many stages you use and so on).
Regards,
Vladimir
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