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#include "precomp.hpp"
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#include <opencv2/gapi/video.hpp>
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namespace cv { namespace gapi {
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using namespace video;
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GBuildPyrOutput buildOpticalFlowPyramid(const GMat &img,
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const Size &winSize,
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const GScalar &maxLevel,
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bool withDerivatives,
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int pyrBorder,
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int derivBorder,
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bool tryReuseInputImage)
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{
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return GBuildOptFlowPyramid::on(img, winSize, maxLevel, withDerivatives, pyrBorder,
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derivBorder, tryReuseInputImage);
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}
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GOptFlowLKOutput calcOpticalFlowPyrLK(const GMat &prevImg,
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const GMat &nextImg,
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const cv::GArray<cv::Point2f> &prevPts,
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const cv::GArray<cv::Point2f> &predPts,
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const Size &winSize,
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const GScalar &maxLevel,
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const TermCriteria &criteria,
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int flags,
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double minEigThresh)
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{
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return GCalcOptFlowLK::on(prevImg, nextImg, prevPts, predPts, winSize, maxLevel,
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criteria, flags, minEigThresh);
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}
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GOptFlowLKOutput calcOpticalFlowPyrLK(const cv::GArray<cv::GMat> &prevPyr,
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const cv::GArray<cv::GMat> &nextPyr,
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const cv::GArray<cv::Point2f> &prevPts,
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const cv::GArray<cv::Point2f> &predPts,
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const Size &winSize,
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const GScalar &maxLevel,
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const TermCriteria &criteria,
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int flags,
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double minEigThresh)
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{
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return GCalcOptFlowLKForPyr::on(prevPyr, nextPyr, prevPts, predPts, winSize, maxLevel,
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criteria, flags, minEigThresh);
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}
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GMat BackgroundSubtractor(const GMat& src, const BackgroundSubtractorParams& bsp)
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{
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return GBackgroundSubtractor::on(src, bsp);
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}
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GMat KalmanFilter(const GMat& m, const cv::GOpaque<bool>& have_m, const GMat& c, const KalmanParams& kp)
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{
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return GKalmanFilter::on(m, have_m, c, kp);
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}
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GMat KalmanFilter(const GMat& m, const cv::GOpaque<bool>& have_m, const KalmanParams& kp)
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{
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return GKalmanFilterNoControl::on(m, have_m, kp);
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}
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namespace video {
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void checkParams(const cv::gapi::KalmanParams& kfParams,
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const cv::GMatDesc& measurement, const cv::GMatDesc& control)
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{
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int type = kfParams.transitionMatrix.type();
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GAPI_Assert(type == CV_32FC1 || type == CV_64FC1);
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int depth = CV_MAT_DEPTH(type);
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bool controlCapable = !(control == GMatDesc{});
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if (controlCapable)
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{
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GAPI_Assert(!kfParams.controlMatrix.empty());
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GAPI_Assert(control.depth == depth && control.chan == 1 &&
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control.size.height == kfParams.controlMatrix.cols &&
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control.size.width == 1);
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}
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else
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GAPI_Assert(kfParams.controlMatrix.empty());
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GAPI_Assert(!kfParams.state.empty() && kfParams.state.type() == type);
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GAPI_Assert(!kfParams.errorCov.empty() && kfParams.errorCov.type() == type);
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GAPI_Assert(!kfParams.transitionMatrix.empty() && kfParams.transitionMatrix.type() == type);
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GAPI_Assert(!kfParams.processNoiseCov.empty() && kfParams.processNoiseCov.type() == type);
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GAPI_Assert(!kfParams.measurementNoiseCov.empty() && kfParams.measurementNoiseCov.type() == type);
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GAPI_Assert(!kfParams.measurementMatrix.empty() && kfParams.measurementMatrix.type() == type);
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GAPI_Assert(measurement.depth == depth && measurement.chan == 1);
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int dDim = kfParams.transitionMatrix.cols;
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GAPI_Assert(kfParams.transitionMatrix.rows == dDim);
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GAPI_Assert(kfParams.processNoiseCov.cols == dDim &&
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kfParams.processNoiseCov.rows == dDim);
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GAPI_Assert(kfParams.errorCov.cols == dDim && kfParams.errorCov.rows == dDim);
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GAPI_Assert(kfParams.state.rows == dDim && kfParams.state.cols == 1);
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GAPI_Assert(kfParams.measurementMatrix.cols == dDim);
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int mDim = kfParams.measurementMatrix.rows;
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GAPI_Assert(kfParams.measurementNoiseCov.cols == mDim &&
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kfParams.measurementNoiseCov.rows == mDim);
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if (controlCapable)
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GAPI_Assert(kfParams.controlMatrix.rows == dDim);
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GAPI_Assert(measurement.size.height == mDim &&
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measurement.size.width == 1);
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}
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}
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}
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}
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