Added option to pass pre-computed pyramid to piramidal LK optical flow #1321
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@ -203,9 +203,6 @@ void cv::copyMakeBorder( InputArray _src, OutputArray _dst, int top, int bottom,
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Mat src = _src.getMat();
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CV_Assert( top >= 0 && bottom >= 0 && left >= 0 && right >= 0 );
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_dst.create( src.rows + top + bottom, src.cols + left + right, src.type() );
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Mat dst = _dst.getMat();
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if( src.isSubmatrix() && (borderType & BORDER_ISOLATED) == 0 )
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{
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Size wholeSize;
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@ -221,6 +218,16 @@ void cv::copyMakeBorder( InputArray _src, OutputArray _dst, int top, int bottom,
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bottom -= dbottom;
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right -= dright;
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}
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_dst.create( src.rows + top + bottom, src.cols + left + right, src.type() );
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Mat dst = _dst.getMat();
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if(top == 0 && left == 0 && bottom == 0 && right == 0)
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{
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if(src.data != dst.data)
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src.copyTo(dst);
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return;
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}
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borderType &= ~BORDER_ISOLATED;
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@ -33,7 +33,7 @@ PERF_TEST_P(Path_Idx_Cn_NPoints_WSize, OpticalFlowPyrLK, testing::Combine(
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testing::Range(0, 3),
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testing::Values(1, 3, 4),
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testing::Values(make_tuple(9, 9), make_tuple(15, 15)),
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testing::Values(11, 21, 25)
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testing::Values(7, 11, 21, 25)
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)
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)
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{
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@ -49,7 +49,7 @@ PERF_TEST_P(Path_Idx_Cn_NPoints_WSize, OpticalFlowPyrLK, testing::Combine(
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int nPointsY = min(get<1>(get<3>(GetParam())), img1.rows);
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int winSize = get<4>(GetParam());
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int maxLevel = 2;
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TermCriteria criteria(CV_TERMCRIT_ITER|CV_TERMCRIT_EPS, 5, 0.01);
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TermCriteria criteria(CV_TERMCRIT_ITER|CV_TERMCRIT_EPS, 7, 0.001);
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int flags = 0;
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double minEigThreshold = 1e-4;
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@ -493,6 +493,106 @@ struct LKTrackerInvoker
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}
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namespace cv {
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int buildOpticalFlowPyramid(InputArray _img, OutputArrayOfArrays pyramid, Size winSize, int maxLevel, bool withDerivatives = true,
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int pyrBorder = BORDER_REFLECT_101, int derivBorder=BORDER_CONSTANT, bool tryReuseInputImage = true)
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{
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Mat img = _img.getMat();
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CV_Assert(img.depth() == CV_8U && winSize.width > 2 && winSize.height > 2 );
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int pyrstep = withDerivatives ? 2 : 1;
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pyramid.create(1, (maxLevel + 1) * pyrstep, 0 /*type*/, -1, true, 0);
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//int cn = img.channels();
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int derivType = CV_MAKETYPE(DataType<deriv_type>::depth, img.channels() * 2);
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//level 0
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bool lvl0IsSet = false;
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if(tryReuseInputImage && img.isSubmatrix() && (pyrBorder & BORDER_ISOLATED) == 0)
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{
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Size wholeSize;
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Point ofs;
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img.locateROI(wholeSize, ofs);
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if (ofs.x >= winSize.width && ofs.y >= winSize.height
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&& ofs.x + img.cols + winSize.width <= wholeSize.width
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&& ofs.y + img.rows + winSize.height <= wholeSize.height)
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{
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pyramid.getMatRef(0) = img;
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lvl0IsSet = true;
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}
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}
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if(!lvl0IsSet)
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{
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Mat& temp = pyramid.getMatRef(0);
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if(!temp.empty())
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temp.adjustROI(winSize.height, winSize.height, winSize.width, winSize.width);
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if(temp.type() != img.type() || temp.cols != winSize.width*2 + img.cols || temp.rows != winSize.height * 2 + img.rows)
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temp.create(img.rows + winSize.height*2, img.cols + winSize.width*2, img.type());
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if(pyrBorder == BORDER_TRANSPARENT)
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img.copyTo(temp(Rect(winSize.width, winSize.height, img.cols, img.rows)));
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else
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copyMakeBorder(img, temp, winSize.height, winSize.height, winSize.width, winSize.width, pyrBorder);
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temp.adjustROI(-winSize.height, -winSize.height, -winSize.width, -winSize.width);
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}
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Size sz = img.size();
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Mat prevLevel = pyramid.getMatRef(0);
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Mat thisLevel = prevLevel;
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for(int level = 0; level <= maxLevel; ++level)
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{
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if (level != 0)
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{
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Mat& temp = pyramid.getMatRef(level * pyrstep);
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if(!temp.empty())
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temp.adjustROI(winSize.height, winSize.height, winSize.width, winSize.width);
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if(temp.type() != img.type() || temp.cols != winSize.width*2 + sz.width || temp.rows != winSize.height * 2 + sz.height)
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temp.create(sz.height + winSize.height*2, sz.width + winSize.width*2, img.type());
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thisLevel = temp(Rect(winSize.width, winSize.height, sz.width, sz.height));
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pyrDown(prevLevel, thisLevel, sz);
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if(pyrBorder != BORDER_TRANSPARENT)
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copyMakeBorder(thisLevel, temp, winSize.height, winSize.height, winSize.width, winSize.width, pyrBorder|BORDER_ISOLATED);
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temp.adjustROI(-winSize.height, -winSize.height, -winSize.width, -winSize.width);
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}
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if(withDerivatives)
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{
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Mat& deriv = pyramid.getMatRef(level * pyrstep + 1);
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if(!deriv.empty())
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deriv.adjustROI(winSize.height, winSize.height, winSize.width, winSize.width);
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if(deriv.type() != derivType || deriv.cols != winSize.width*2 + sz.width || deriv.rows != winSize.height * 2 + sz.height)
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deriv.create(sz.height + winSize.height*2, sz.width + winSize.width*2, derivType);
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Mat derivI = deriv(Rect(winSize.width, winSize.height, sz.width, sz.height));
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calcSharrDeriv(thisLevel, derivI);
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if(derivBorder != BORDER_TRANSPARENT)
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copyMakeBorder(derivI, deriv, winSize.height, winSize.height, winSize.width, winSize.width, derivBorder|BORDER_ISOLATED);
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deriv.adjustROI(-winSize.height, -winSize.height, -winSize.width, -winSize.width);
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}
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sz = Size((sz.width+1)/2, (sz.height+1)/2);
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if( sz.width <= winSize.width || sz.height <= winSize.height )
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{
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pyramid.create(1, (level + 1) * pyrstep, 0 /*type*/, -1, true, 0);//check this
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return level;
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}
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prevLevel = thisLevel;
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}
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return maxLevel;
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}
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}
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void cv::calcOpticalFlowPyrLK( InputArray _prevImg, InputArray _nextImg,
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InputArray _prevPts, InputOutputArray _nextPts,
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OutputArray _status, OutputArray _err,
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@ -504,14 +604,14 @@ void cv::calcOpticalFlowPyrLK( InputArray _prevImg, InputArray _nextImg,
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if (tegra::calcOpticalFlowPyrLK(_prevImg, _nextImg, _prevPts, _nextPts, _status, _err, winSize, maxLevel, criteria, flags, minEigThreshold))
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return;
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#endif
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Mat prevImg = _prevImg.getMat(), nextImg = _nextImg.getMat(), prevPtsMat = _prevPts.getMat();
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Mat /*prevImg = _prevImg.getMat(), nextImg = _nextImg.getMat(),*/ prevPtsMat = _prevPts.getMat();
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const int derivDepth = DataType<deriv_type>::depth;
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CV_Assert( maxLevel >= 0 && winSize.width > 2 && winSize.height > 2 );
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CV_Assert( prevImg.size() == nextImg.size() &&
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prevImg.type() == nextImg.type() );
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//CV_Assert( prevImg.size() == nextImg.size() &&
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// prevImg.type() == nextImg.type() );
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int level=0, i, k, npoints, cn = prevImg.channels(), cn2 = cn*2;
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int level=0, i, npoints;//, cn = prevImg.channels(), cn2 = cn*2;
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CV_Assert( (npoints = prevPtsMat.checkVector(2, CV_32F, true)) >= 0 );
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if( npoints == 0 )
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@ -548,43 +648,47 @@ void cv::calcOpticalFlowPyrLK( InputArray _prevImg, InputArray _nextImg,
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err = (float*)errMat.data;
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}
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vector<Mat> prevPyr(maxLevel+1), nextPyr(maxLevel+1);
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// build the image pyramids.
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// we pad each level with +/-winSize.{width|height}
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// pixels to simplify the further patch extraction.
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// Thanks to the reference counting, "temp" mat (the pyramid layer + border)
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// will not be deallocated, since {prevPyr|nextPyr}[level] will be a ROI in "temp".
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for( k = 0; k < 2; k++ )
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vector<Mat> prevPyr, nextPyr;
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int levels1 = 0;
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int lvlStep1 = 1;
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int levels2 = 0;
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int lvlStep2 = 1;
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if(_prevImg.kind() == _InputArray::STD_VECTOR_MAT)
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{
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Size sz = prevImg.size();
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vector<Mat>& pyr = k == 0 ? prevPyr : nextPyr;
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Mat& img0 = k == 0 ? prevImg : nextImg;
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for( level = 0; level <= maxLevel; level++ )
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_prevImg.getMatVector(prevPyr);
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levels1 = (int)prevPyr.size();
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if (levels1 % 2 == 0 && levels1 > 1 && prevPyr[0].channels() * 2 == prevPyr[1].channels() && prevPyr[1].depth() == derivDepth)
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{
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Mat temp(sz.height + winSize.height*2,
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sz.width + winSize.width*2,
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img0.type());
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pyr[level] = temp(Rect(winSize.width, winSize.height, sz.width, sz.height));
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if( level == 0 )
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img0.copyTo(pyr[level]);
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else
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pyrDown(pyr[level-1], pyr[level], pyr[level].size());
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copyMakeBorder(pyr[level], temp, winSize.height, winSize.height,
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winSize.width, winSize.width, BORDER_REFLECT_101|BORDER_ISOLATED);
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sz = Size((sz.width+1)/2, (sz.height+1)/2);
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if( sz.width <= winSize.width || sz.height <= winSize.height )
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{
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maxLevel = level;
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break;
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}
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lvlStep1 = 2;
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levels1 /= 2;
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}
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}
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// dI/dx ~ Ix, dI/dy ~ Iy
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Mat derivIBuf((prevImg.rows + winSize.height*2),
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(prevImg.cols + winSize.width*2),
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CV_MAKETYPE(derivDepth, cn2));
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if(_nextImg.kind() == _InputArray::STD_VECTOR_MAT)
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{
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_nextImg.getMatVector(nextPyr);
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levels2 = (int)nextPyr.size();
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if (levels2 % 2 == 0 && levels2 > 1 && nextPyr[0].channels() * 2 == nextPyr[1].channels() && nextPyr[1].depth() == derivDepth)
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{
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lvlStep2 = 2;
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levels2 /= 2;
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}
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}
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if(levels1 != 0 || levels2 != 0)
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maxLevel = std::max(levels1, levels2);
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if (levels1 == 0)
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maxLevel = levels1 = buildOpticalFlowPyramid(_prevImg, prevPyr, winSize, maxLevel, false);
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if (levels2 == 0)
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levels2 = buildOpticalFlowPyramid(_nextImg, nextPyr, winSize, maxLevel, false);
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CV_Assert(levels1 == levels2);
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if( (criteria.type & TermCriteria::COUNT) == 0 )
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criteria.maxCount = 30;
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@ -596,20 +700,43 @@ void cv::calcOpticalFlowPyrLK( InputArray _prevImg, InputArray _nextImg,
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criteria.epsilon = std::min(std::max(criteria.epsilon, 0.), 10.);
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criteria.epsilon *= criteria.epsilon;
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for( level = maxLevel; level >= 0; level-- )
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if(lvlStep1 == 1)
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{
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Size imgSize = prevPyr[level].size();
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Mat _derivI( imgSize.height + winSize.height*2,
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imgSize.width + winSize.width*2, derivIBuf.type(), derivIBuf.data );
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Mat derivI = _derivI(Rect(winSize.width, winSize.height, imgSize.width, imgSize.height));
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calcSharrDeriv(prevPyr[level], derivI);
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copyMakeBorder(derivI, _derivI, winSize.height, winSize.height, winSize.width, winSize.width, BORDER_CONSTANT|BORDER_ISOLATED);
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parallel_for(BlockedRange(0, npoints), LKTrackerInvoker(prevPyr[level], derivI,
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nextPyr[level], prevPts, nextPts,
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status, err,
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winSize, criteria, level, maxLevel,
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flags, (float)minEigThreshold));
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// dI/dx ~ Ix, dI/dy ~ Iy
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Mat derivIBuf((prevPyr[0].rows + winSize.height*2),
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(prevPyr[0].cols + winSize.width*2),
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CV_MAKETYPE(derivDepth, prevPyr[0].channels() * 2));
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for( level = maxLevel; level >= 0; level-- )
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{
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Size imgSize = prevPyr[level * lvlStep1].size();
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Mat _derivI( imgSize.height + winSize.height*2,
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imgSize.width + winSize.width*2, derivIBuf.type(), derivIBuf.data );
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Mat derivI = _derivI(Rect(winSize.width, winSize.height, imgSize.width, imgSize.height));
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calcSharrDeriv(prevPyr[level * lvlStep1], derivI);
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copyMakeBorder(derivI, _derivI, winSize.height, winSize.height, winSize.width, winSize.width, BORDER_CONSTANT|BORDER_ISOLATED);
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CV_Assert(prevPyr[level * lvlStep1].size() == nextPyr[level * lvlStep2].size());
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CV_Assert(prevPyr[level * lvlStep1].type() == nextPyr[level * lvlStep2].type());
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parallel_for(BlockedRange(0, npoints), LKTrackerInvoker(prevPyr[level * lvlStep1], derivI,
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nextPyr[level * lvlStep2], prevPts, nextPts,
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status, err,
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winSize, criteria, level, maxLevel,
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flags, (float)minEigThreshold));
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}
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}
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else
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{
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for( level = levels1; level >= 0; level-- )
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{
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CV_Assert(prevPyr[level * lvlStep1].size() == nextPyr[level * lvlStep2].size());
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CV_Assert(prevPyr[level * lvlStep1].type() == nextPyr[level * lvlStep2].type());
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parallel_for(BlockedRange(0, npoints), LKTrackerInvoker(prevPyr[level * lvlStep1], prevPyr[level * lvlStep1 + 1],
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nextPyr[level * lvlStep2], prevPts, nextPts,
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status, err,
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winSize, criteria, level, maxLevel,
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flags, (float)minEigThreshold));
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}
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}
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}
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