chore: import upstream snapshot with attribution
This commit is contained in:
wehub-resource-sync
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// This file is part of OpenCV project.
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// It is subject to the license terms in the LICENSE file found in the top-level directory
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// of this distribution and at http://opencv.org/license.html.
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//
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// Copyright (C) 2020 Intel Corporation
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#include "precomp.hpp"
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#include <opencv2/gapi/video.hpp>
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#include <opencv2/gapi/cpu/video.hpp>
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#include <opencv2/gapi/cpu/gcpukernel.hpp>
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#ifdef HAVE_OPENCV_VIDEO
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#include <opencv2/video.hpp>
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#endif // HAVE_OPENCV_VIDEO
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#ifdef HAVE_OPENCV_VIDEO
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GAPI_OCV_KERNEL(GCPUBuildOptFlowPyramid, cv::gapi::video::GBuildOptFlowPyramid)
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{
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static void run(const cv::Mat &img,
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const cv::Size &winSize,
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const cv::Scalar &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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std::vector<cv::Mat> &outPyr,
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cv::Scalar &outMaxLevel)
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{
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outMaxLevel = cv::buildOpticalFlowPyramid(img, outPyr, winSize,
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static_cast<int>(maxLevel[0]),
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withDerivatives, pyrBorder,
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derivBorder, tryReuseInputImage);
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}
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};
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GAPI_OCV_KERNEL(GCPUCalcOptFlowLK, cv::gapi::video::GCalcOptFlowLK)
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{
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static void run(const cv::Mat &prevImg,
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const cv::Mat &nextImg,
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const std::vector<cv::Point2f> &prevPts,
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const std::vector<cv::Point2f> &predPts,
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const cv::Size &winSize,
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const cv::Scalar &maxLevel,
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const cv::TermCriteria &criteria,
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int flags,
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double minEigThresh,
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std::vector<cv::Point2f> &outPts,
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std::vector<uchar> &status,
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std::vector<float> &err)
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{
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if (flags & cv::OPTFLOW_USE_INITIAL_FLOW)
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outPts = predPts;
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cv::calcOpticalFlowPyrLK(prevImg, nextImg, prevPts, outPts, status, err, winSize,
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static_cast<int>(maxLevel[0]), criteria, flags, minEigThresh);
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}
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};
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GAPI_OCV_KERNEL(GCPUCalcOptFlowLKForPyr, cv::gapi::video::GCalcOptFlowLKForPyr)
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{
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static void run(const std::vector<cv::Mat> &prevPyr,
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const std::vector<cv::Mat> &nextPyr,
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const std::vector<cv::Point2f> &prevPts,
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const std::vector<cv::Point2f> &predPts,
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const cv::Size &winSize,
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const cv::Scalar &maxLevel,
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const cv::TermCriteria &criteria,
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int flags,
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double minEigThresh,
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std::vector<cv::Point2f> &outPts,
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std::vector<uchar> &status,
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std::vector<float> &err)
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{
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if (flags & cv::OPTFLOW_USE_INITIAL_FLOW)
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outPts = predPts;
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cv::calcOpticalFlowPyrLK(prevPyr, nextPyr, prevPts, outPts, status, err, winSize,
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static_cast<int>(maxLevel[0]), criteria, flags, minEigThresh);
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}
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};
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GAPI_OCV_KERNEL_ST(GCPUBackgroundSubtractor,
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cv::gapi::video::GBackgroundSubtractor,
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cv::BackgroundSubtractor)
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{
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static void setup(const cv::GMatDesc&, const cv::gapi::video::BackgroundSubtractorParams& bsParams,
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std::shared_ptr<cv::BackgroundSubtractor>& state,
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const cv::GCompileArgs&)
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{
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if (bsParams.operation == cv::gapi::video::TYPE_BS_MOG2)
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state = cv::createBackgroundSubtractorMOG2(bsParams.history,
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bsParams.threshold,
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bsParams.detectShadows);
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else if (bsParams.operation == cv::gapi::video::TYPE_BS_KNN)
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state = cv::createBackgroundSubtractorKNN(bsParams.history,
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bsParams.threshold,
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bsParams.detectShadows);
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GAPI_Assert(state);
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}
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static void run(const cv::Mat& in, const cv::gapi::video::BackgroundSubtractorParams& bsParams,
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cv::Mat &out, cv::BackgroundSubtractor& state)
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{
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state.apply(in, out, bsParams.learningRate);
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}
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};
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GAPI_OCV_KERNEL_ST(GCPUKalmanFilter, cv::gapi::video::GKalmanFilter, cv::KalmanFilter)
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{
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static void setup(const cv::GMatDesc&, const cv::GOpaqueDesc&,
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const cv::GMatDesc&, const cv::gapi::KalmanParams& kfParams,
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std::shared_ptr<cv::KalmanFilter> &state, const cv::GCompileArgs&)
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{
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state = std::make_shared<cv::KalmanFilter>(kfParams.transitionMatrix.rows, kfParams.measurementMatrix.rows,
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kfParams.controlMatrix.cols, kfParams.transitionMatrix.type());
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// initial state
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kfParams.state.copyTo(state->statePost);
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kfParams.errorCov.copyTo(state->errorCovPost);
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// dynamic system initialization
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kfParams.controlMatrix.copyTo(state->controlMatrix);
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kfParams.measurementMatrix.copyTo(state->measurementMatrix);
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kfParams.transitionMatrix.copyTo(state->transitionMatrix);
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kfParams.processNoiseCov.copyTo(state->processNoiseCov);
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kfParams.measurementNoiseCov.copyTo(state->measurementNoiseCov);
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}
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static void run(const cv::Mat& measurements, bool haveMeasurement,
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const cv::Mat& control, const cv::gapi::KalmanParams&,
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cv::Mat &out, cv::KalmanFilter& state)
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{
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cv::Mat pre = state.predict(control);
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if (haveMeasurement)
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state.correct(measurements).copyTo(out);
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else
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pre.copyTo(out);
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}
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};
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GAPI_OCV_KERNEL_ST(GCPUKalmanFilterNoControl, cv::gapi::video::GKalmanFilterNoControl, cv::KalmanFilter)
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{
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static void setup(const cv::GMatDesc&, const cv::GOpaqueDesc&,
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const cv::gapi::KalmanParams& kfParams,
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std::shared_ptr<cv::KalmanFilter> &state,
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const cv::GCompileArgs&)
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{
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state = std::make_shared<cv::KalmanFilter>(kfParams.transitionMatrix.rows, kfParams.measurementMatrix.rows,
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0, kfParams.transitionMatrix.type());
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// initial state
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kfParams.state.copyTo(state->statePost);
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kfParams.errorCov.copyTo(state->errorCovPost);
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// dynamic system initialization
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kfParams.measurementMatrix.copyTo(state->measurementMatrix);
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kfParams.transitionMatrix.copyTo(state->transitionMatrix);
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kfParams.processNoiseCov.copyTo(state->processNoiseCov);
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kfParams.measurementNoiseCov.copyTo(state->measurementNoiseCov);
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}
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static void run(const cv::Mat& measurements, bool haveMeasurement,
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const cv::gapi::KalmanParams&, cv::Mat &out,
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cv::KalmanFilter& state)
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{
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cv::Mat pre = state.predict();
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if (haveMeasurement)
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state.correct(measurements).copyTo(out);
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else
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pre.copyTo(out);
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}
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};
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cv::GKernelPackage cv::gapi::video::cpu::kernels()
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{
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static auto pkg = cv::gapi::kernels
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< GCPUBuildOptFlowPyramid
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, GCPUCalcOptFlowLK
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, GCPUCalcOptFlowLKForPyr
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, GCPUBackgroundSubtractor
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, GCPUKalmanFilter
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, GCPUKalmanFilterNoControl
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>();
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return pkg;
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}
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#else
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cv::GKernelPackage cv::gapi::video::cpu::kernels()
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{
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return GKernelPackage();
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}
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#endif // HAVE_OPENCV_VIDEO
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