Normalize line endings and whitespace
This commit is contained in:
OpenCV Buildbot
committed by
Andrey Kamaev
Andrey Kamaev
parent
69020da607
commit
04384a71e4
@@ -42,152 +42,152 @@
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void CvAdaptiveSkinDetector::initData(IplImage *src, int widthDivider, int heightDivider)
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{
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CvSize imageSize = cvSize(src->width/widthDivider, src->height/heightDivider);
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CvSize imageSize = cvSize(src->width/widthDivider, src->height/heightDivider);
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imgHueFrame = cvCreateImage(imageSize, IPL_DEPTH_8U, 1);
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imgShrinked = cvCreateImage(imageSize, IPL_DEPTH_8U, src->nChannels);
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imgSaturationFrame = cvCreateImage(imageSize, IPL_DEPTH_8U, 1);
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imgMotionFrame = cvCreateImage(imageSize, IPL_DEPTH_8U, 1);
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imgTemp = cvCreateImage(imageSize, IPL_DEPTH_8U, 1);
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imgFilteredFrame = cvCreateImage(imageSize, IPL_DEPTH_8U, 1);
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imgGrayFrame = cvCreateImage(imageSize, IPL_DEPTH_8U, 1);
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imgLastGrayFrame = cvCreateImage(imageSize, IPL_DEPTH_8U, 1);
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imgHSVFrame = cvCreateImage(imageSize, IPL_DEPTH_8U, 3);
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imgHueFrame = cvCreateImage(imageSize, IPL_DEPTH_8U, 1);
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imgShrinked = cvCreateImage(imageSize, IPL_DEPTH_8U, src->nChannels);
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imgSaturationFrame = cvCreateImage(imageSize, IPL_DEPTH_8U, 1);
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imgMotionFrame = cvCreateImage(imageSize, IPL_DEPTH_8U, 1);
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imgTemp = cvCreateImage(imageSize, IPL_DEPTH_8U, 1);
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imgFilteredFrame = cvCreateImage(imageSize, IPL_DEPTH_8U, 1);
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imgGrayFrame = cvCreateImage(imageSize, IPL_DEPTH_8U, 1);
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imgLastGrayFrame = cvCreateImage(imageSize, IPL_DEPTH_8U, 1);
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imgHSVFrame = cvCreateImage(imageSize, IPL_DEPTH_8U, 3);
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};
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CvAdaptiveSkinDetector::CvAdaptiveSkinDetector(int samplingDivider, int morphingMethod)
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{
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nSkinHueLowerBound = GSD_HUE_LT;
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nSkinHueUpperBound = GSD_HUE_UT;
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nSkinHueLowerBound = GSD_HUE_LT;
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nSkinHueUpperBound = GSD_HUE_UT;
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fHistogramMergeFactor = 0.05; // empirical result
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fHuePercentCovered = 0.95; // empirical result
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fHistogramMergeFactor = 0.05; // empirical result
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fHuePercentCovered = 0.95; // empirical result
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nMorphingMethod = morphingMethod;
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nSamplingDivider = samplingDivider;
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nMorphingMethod = morphingMethod;
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nSamplingDivider = samplingDivider;
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nFrameCount = 0;
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nStartCounter = 0;
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nFrameCount = 0;
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nStartCounter = 0;
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imgHueFrame = NULL;
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imgMotionFrame = NULL;
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imgTemp = NULL;
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imgFilteredFrame = NULL;
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imgShrinked = NULL;
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imgGrayFrame = NULL;
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imgLastGrayFrame = NULL;
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imgSaturationFrame = NULL;
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imgHSVFrame = NULL;
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imgHueFrame = NULL;
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imgMotionFrame = NULL;
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imgTemp = NULL;
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imgFilteredFrame = NULL;
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imgShrinked = NULL;
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imgGrayFrame = NULL;
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imgLastGrayFrame = NULL;
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imgSaturationFrame = NULL;
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imgHSVFrame = NULL;
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};
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CvAdaptiveSkinDetector::~CvAdaptiveSkinDetector()
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{
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cvReleaseImage(&imgHueFrame);
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cvReleaseImage(&imgSaturationFrame);
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cvReleaseImage(&imgMotionFrame);
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cvReleaseImage(&imgTemp);
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cvReleaseImage(&imgFilteredFrame);
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cvReleaseImage(&imgShrinked);
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cvReleaseImage(&imgGrayFrame);
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cvReleaseImage(&imgLastGrayFrame);
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cvReleaseImage(&imgHSVFrame);
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cvReleaseImage(&imgHueFrame);
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cvReleaseImage(&imgSaturationFrame);
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cvReleaseImage(&imgMotionFrame);
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cvReleaseImage(&imgTemp);
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cvReleaseImage(&imgFilteredFrame);
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cvReleaseImage(&imgShrinked);
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cvReleaseImage(&imgGrayFrame);
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cvReleaseImage(&imgLastGrayFrame);
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cvReleaseImage(&imgHSVFrame);
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};
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void CvAdaptiveSkinDetector::process(IplImage *inputBGRImage, IplImage *outputHueMask)
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{
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IplImage *src = inputBGRImage;
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IplImage *src = inputBGRImage;
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int h, v, i, l;
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bool isInit = false;
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int h, v, i, l;
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bool isInit = false;
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nFrameCount++;
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nFrameCount++;
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if (imgHueFrame == NULL)
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{
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isInit = true;
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initData(src, nSamplingDivider, nSamplingDivider);
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}
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if (imgHueFrame == NULL)
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{
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isInit = true;
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initData(src, nSamplingDivider, nSamplingDivider);
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}
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unsigned char *pShrinked, *pHueFrame, *pMotionFrame, *pLastGrayFrame, *pFilteredFrame, *pGrayFrame;
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pShrinked = (unsigned char *)imgShrinked->imageData;
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pHueFrame = (unsigned char *)imgHueFrame->imageData;
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pMotionFrame = (unsigned char *)imgMotionFrame->imageData;
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pLastGrayFrame = (unsigned char *)imgLastGrayFrame->imageData;
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pFilteredFrame = (unsigned char *)imgFilteredFrame->imageData;
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pGrayFrame = (unsigned char *)imgGrayFrame->imageData;
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unsigned char *pShrinked, *pHueFrame, *pMotionFrame, *pLastGrayFrame, *pFilteredFrame, *pGrayFrame;
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pShrinked = (unsigned char *)imgShrinked->imageData;
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pHueFrame = (unsigned char *)imgHueFrame->imageData;
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pMotionFrame = (unsigned char *)imgMotionFrame->imageData;
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pLastGrayFrame = (unsigned char *)imgLastGrayFrame->imageData;
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pFilteredFrame = (unsigned char *)imgFilteredFrame->imageData;
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pGrayFrame = (unsigned char *)imgGrayFrame->imageData;
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if ((src->width != imgHueFrame->width) || (src->height != imgHueFrame->height))
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{
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cvResize(src, imgShrinked);
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cvCvtColor(imgShrinked, imgHSVFrame, CV_BGR2HSV);
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}
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else
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{
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cvCvtColor(src, imgHSVFrame, CV_BGR2HSV);
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}
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if ((src->width != imgHueFrame->width) || (src->height != imgHueFrame->height))
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{
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cvResize(src, imgShrinked);
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cvCvtColor(imgShrinked, imgHSVFrame, CV_BGR2HSV);
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}
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else
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{
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cvCvtColor(src, imgHSVFrame, CV_BGR2HSV);
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}
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cvSplit(imgHSVFrame, imgHueFrame, imgSaturationFrame, imgGrayFrame, 0);
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cvSplit(imgHSVFrame, imgHueFrame, imgSaturationFrame, imgGrayFrame, 0);
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cvSetZero(imgMotionFrame);
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cvSetZero(imgFilteredFrame);
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cvSetZero(imgMotionFrame);
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cvSetZero(imgFilteredFrame);
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l = imgHueFrame->height * imgHueFrame->width;
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l = imgHueFrame->height * imgHueFrame->width;
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for (i = 0; i < l; i++)
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{
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v = (*pGrayFrame);
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if ((v >= GSD_INTENSITY_LT) && (v <= GSD_INTENSITY_UT))
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{
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h = (*pHueFrame);
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if ((h >= GSD_HUE_LT) && (h <= GSD_HUE_UT))
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{
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if ((h >= nSkinHueLowerBound) && (h <= nSkinHueUpperBound))
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ASD_INTENSITY_SET_PIXEL(pFilteredFrame, h);
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for (i = 0; i < l; i++)
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{
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v = (*pGrayFrame);
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if ((v >= GSD_INTENSITY_LT) && (v <= GSD_INTENSITY_UT))
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{
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h = (*pHueFrame);
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if ((h >= GSD_HUE_LT) && (h <= GSD_HUE_UT))
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{
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if ((h >= nSkinHueLowerBound) && (h <= nSkinHueUpperBound))
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ASD_INTENSITY_SET_PIXEL(pFilteredFrame, h);
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if (ASD_IS_IN_MOTION(pLastGrayFrame, v, 7))
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ASD_INTENSITY_SET_PIXEL(pMotionFrame, h);
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}
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}
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pShrinked += 3;
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pGrayFrame++;
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pLastGrayFrame++;
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pMotionFrame++;
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pHueFrame++;
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pFilteredFrame++;
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}
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if (ASD_IS_IN_MOTION(pLastGrayFrame, v, 7))
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ASD_INTENSITY_SET_PIXEL(pMotionFrame, h);
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}
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}
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pShrinked += 3;
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pGrayFrame++;
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pLastGrayFrame++;
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pMotionFrame++;
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pHueFrame++;
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pFilteredFrame++;
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}
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if (isInit)
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cvCalcHist(&imgHueFrame, skinHueHistogram.fHistogram);
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if (isInit)
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cvCalcHist(&imgHueFrame, skinHueHistogram.fHistogram);
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cvCopy(imgGrayFrame, imgLastGrayFrame);
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cvCopy(imgGrayFrame, imgLastGrayFrame);
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cvErode(imgMotionFrame, imgTemp); // eliminate disperse pixels, which occur because of the camera noise
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cvDilate(imgTemp, imgMotionFrame);
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cvErode(imgMotionFrame, imgTemp); // eliminate disperse pixels, which occur because of the camera noise
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cvDilate(imgTemp, imgMotionFrame);
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cvCalcHist(&imgMotionFrame, histogramHueMotion.fHistogram);
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cvCalcHist(&imgMotionFrame, histogramHueMotion.fHistogram);
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skinHueHistogram.mergeWith(&histogramHueMotion, fHistogramMergeFactor);
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skinHueHistogram.mergeWith(&histogramHueMotion, fHistogramMergeFactor);
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skinHueHistogram.findCurveThresholds(nSkinHueLowerBound, nSkinHueUpperBound, 1 - fHuePercentCovered);
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skinHueHistogram.findCurveThresholds(nSkinHueLowerBound, nSkinHueUpperBound, 1 - fHuePercentCovered);
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switch (nMorphingMethod)
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{
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case MORPHING_METHOD_ERODE :
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cvErode(imgFilteredFrame, imgTemp);
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cvCopy(imgTemp, imgFilteredFrame);
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break;
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case MORPHING_METHOD_ERODE_ERODE :
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cvErode(imgFilteredFrame, imgTemp);
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cvErode(imgTemp, imgFilteredFrame);
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break;
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case MORPHING_METHOD_ERODE_DILATE :
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cvErode(imgFilteredFrame, imgTemp);
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cvDilate(imgTemp, imgFilteredFrame);
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break;
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}
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switch (nMorphingMethod)
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{
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case MORPHING_METHOD_ERODE :
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cvErode(imgFilteredFrame, imgTemp);
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cvCopy(imgTemp, imgFilteredFrame);
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break;
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case MORPHING_METHOD_ERODE_ERODE :
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cvErode(imgFilteredFrame, imgTemp);
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cvErode(imgTemp, imgFilteredFrame);
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break;
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case MORPHING_METHOD_ERODE_DILATE :
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cvErode(imgFilteredFrame, imgTemp);
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cvDilate(imgTemp, imgFilteredFrame);
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break;
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}
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if (outputHueMask != NULL)
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cvCopy(imgFilteredFrame, outputHueMask);
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if (outputHueMask != NULL)
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cvCopy(imgFilteredFrame, outputHueMask);
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};
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@@ -195,94 +195,94 @@ void CvAdaptiveSkinDetector::process(IplImage *inputBGRImage, IplImage *outputHu
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CvAdaptiveSkinDetector::Histogram::Histogram()
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{
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int histogramSize[] = { HistogramSize };
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float range[] = { GSD_HUE_LT, GSD_HUE_UT };
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float *ranges[] = { range };
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fHistogram = cvCreateHist(1, histogramSize, CV_HIST_ARRAY, ranges, 1);
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cvClearHist(fHistogram);
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int histogramSize[] = { HistogramSize };
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float range[] = { GSD_HUE_LT, GSD_HUE_UT };
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float *ranges[] = { range };
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fHistogram = cvCreateHist(1, histogramSize, CV_HIST_ARRAY, ranges, 1);
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cvClearHist(fHistogram);
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};
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CvAdaptiveSkinDetector::Histogram::~Histogram()
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{
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cvReleaseHist(&fHistogram);
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cvReleaseHist(&fHistogram);
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};
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int CvAdaptiveSkinDetector::Histogram::findCoverageIndex(double surfaceToCover, int defaultValue)
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{
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double s = 0;
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for (int i = 0; i < HistogramSize; i++)
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{
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s += cvGetReal1D( fHistogram->bins, i );
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if (s >= surfaceToCover)
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{
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return i;
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}
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}
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return defaultValue;
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double s = 0;
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for (int i = 0; i < HistogramSize; i++)
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{
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s += cvGetReal1D( fHistogram->bins, i );
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if (s >= surfaceToCover)
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{
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return i;
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}
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}
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return defaultValue;
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};
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void CvAdaptiveSkinDetector::Histogram::findCurveThresholds(int &x1, int &x2, double percent)
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{
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double sum = 0;
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double sum = 0;
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for (int i = 0; i < HistogramSize; i++)
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{
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sum += cvGetReal1D( fHistogram->bins, i );
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}
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for (int i = 0; i < HistogramSize; i++)
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{
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sum += cvGetReal1D( fHistogram->bins, i );
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}
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x1 = findCoverageIndex(sum * percent, -1);
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x2 = findCoverageIndex(sum * (1-percent), -1);
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x1 = findCoverageIndex(sum * percent, -1);
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x2 = findCoverageIndex(sum * (1-percent), -1);
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if (x1 == -1)
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x1 = GSD_HUE_LT;
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else
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x1 += GSD_HUE_LT;
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if (x1 == -1)
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x1 = GSD_HUE_LT;
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else
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x1 += GSD_HUE_LT;
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if (x2 == -1)
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x2 = GSD_HUE_UT;
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else
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x2 += GSD_HUE_LT;
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if (x2 == -1)
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x2 = GSD_HUE_UT;
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else
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x2 += GSD_HUE_LT;
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};
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void CvAdaptiveSkinDetector::Histogram::mergeWith(CvAdaptiveSkinDetector::Histogram *source, double weight)
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{
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float myweight = (float)(1-weight);
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float maxVal1 = 0, maxVal2 = 0, *f1, *f2, ff1, ff2;
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float myweight = (float)(1-weight);
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float maxVal1 = 0, maxVal2 = 0, *f1, *f2, ff1, ff2;
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cvGetMinMaxHistValue(source->fHistogram, NULL, &maxVal2);
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cvGetMinMaxHistValue(source->fHistogram, NULL, &maxVal2);
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if (maxVal2 > 0 )
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{
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cvGetMinMaxHistValue(fHistogram, NULL, &maxVal1);
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if (maxVal1 <= 0)
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{
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for (int i = 0; i < HistogramSize; i++)
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{
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f1 = (float*)cvPtr1D(fHistogram->bins, i);
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f2 = (float*)cvPtr1D(source->fHistogram->bins, i);
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(*f1) = (*f2);
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}
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}
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else
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{
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for (int i = 0; i < HistogramSize; i++)
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{
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f1 = (float*)cvPtr1D(fHistogram->bins, i);
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f2 = (float*)cvPtr1D(source->fHistogram->bins, i);
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if (maxVal2 > 0 )
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{
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cvGetMinMaxHistValue(fHistogram, NULL, &maxVal1);
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if (maxVal1 <= 0)
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{
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for (int i = 0; i < HistogramSize; i++)
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{
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f1 = (float*)cvPtr1D(fHistogram->bins, i);
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f2 = (float*)cvPtr1D(source->fHistogram->bins, i);
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(*f1) = (*f2);
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}
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}
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else
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{
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for (int i = 0; i < HistogramSize; i++)
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{
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f1 = (float*)cvPtr1D(fHistogram->bins, i);
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f2 = (float*)cvPtr1D(source->fHistogram->bins, i);
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ff1 = ((*f1)/maxVal1)*myweight;
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if (ff1 < 0)
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ff1 = -ff1;
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ff1 = ((*f1)/maxVal1)*myweight;
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if (ff1 < 0)
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ff1 = -ff1;
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ff2 = (float)(((*f2)/maxVal2)*weight);
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if (ff2 < 0)
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ff2 = -ff2;
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ff2 = (float)(((*f2)/maxVal2)*weight);
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if (ff2 < 0)
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ff2 = -ff2;
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(*f1) = (ff1 + ff2);
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(*f1) = (ff1 + ff2);
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}
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}
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}
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}
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}
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}
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};
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