refactored OpticalFlowDual_TVL1:
* added DenseOpticalFlow interface * moved OpticalFlowDual_TVL1 to src folder
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2181a41a07
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modules
gpu
video
doc
include/opencv2/video
perf
src
test
samples/cpp
@ -431,13 +431,13 @@ PERF_TEST_P(ImagePair, Video_OpticalFlowDual_TVL1,
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{
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cv::Mat flow;
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cv::OpticalFlowDual_TVL1 alg;
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cv::Ptr<cv::DenseOpticalFlow> alg = cv::createOptFlow_DualTVL1();
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alg(frame0, frame1, flow);
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alg->calc(frame0, frame1, flow);
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TEST_CYCLE()
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{
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alg(frame0, frame1, flow);
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alg->calc(frame0, frame1, flow);
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}
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CPU_SANITY_CHECK(flow);
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@ -431,9 +431,9 @@ GPU_TEST_P(OpticalFlowDual_TVL1, Accuracy)
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cv::gpu::GpuMat d_flowy = createMat(frame0.size(), CV_32FC1, useRoi);
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d_alg(loadMat(frame0, useRoi), loadMat(frame1, useRoi), d_flowx, d_flowy);
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cv::OpticalFlowDual_TVL1 alg;
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cv::Ptr<cv::DenseOpticalFlow> alg = cv::createOptFlow_DualTVL1();
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cv::Mat flow;
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alg(frame0, frame1, flow);
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alg->calc(frame0, frame1, flow);
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cv::Mat gold[2];
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cv::split(flow, gold);
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@ -643,11 +643,11 @@ See [Tao2012]_. And site of project - http://graphics.berkeley.edu/papers/Tao-SA
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OpticalFlowDual_TVL1
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--------------------
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createOptFlow_DualTVL1
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----------------------
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"Dual TV L1" Optical Flow Algorithm.
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.. ocv:class:: OpticalFlowDual_TVL12
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.. ocv:function:: Ptr<DenseOpticalFlow> createOptFlow_DualTVL1()
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The class implements the "Dual TV L1" optical flow algorithm described in [Zach2007]_ and [Javier2012]_ .
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@ -685,11 +685,11 @@ Here are important members of the class that control the algorithm, which you ca
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OpticalFlowDual_TVL1::operator()
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--------------------------------
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DenseOpticalFlow::calc
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--------------------------
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Calculates an optical flow.
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.. ocv:function:: void OpticalFlowDual_TVL1::operator ()(InputArray I0, InputArray I1, InputOutputArray flow)
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.. ocv:function:: void DenseOpticalFlow::calc(InputArray I0, InputArray I1, InputOutputArray flow)
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:param prev: first 8-bit single-channel input image.
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@ -699,11 +699,11 @@ Calculates an optical flow.
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OpticalFlowDual_TVL1::collectGarbage
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------------------------------------
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DenseOpticalFlow::collectGarbage
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--------------------------------
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Releases all inner buffers.
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.. ocv:function:: void OpticalFlowDual_TVL1::collectGarbage()
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.. ocv:function:: void DenseOpticalFlow::collectGarbage()
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@ -352,104 +352,19 @@ CV_EXPORTS_W void calcOpticalFlowSF(Mat& from,
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double upscale_sigma_color,
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double speed_up_thr);
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class CV_EXPORTS DenseOpticalFlow : public Algorithm
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{
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public:
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virtual void calc(InputArray I0, InputArray I1, InputOutputArray flow) = 0;
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virtual void collectGarbage() = 0;
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};
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// Implementation of the Zach, Pock and Bischof Dual TV-L1 Optical Flow method
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//
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// see reference:
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// [1] C. Zach, T. Pock and H. Bischof, "A Duality Based Approach for Realtime TV-L1 Optical Flow".
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// [2] Javier Sanchez, Enric Meinhardt-Llopis and Gabriele Facciolo. "TV-L1 Optical Flow Estimation".
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class CV_EXPORTS OpticalFlowDual_TVL1
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{
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public:
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OpticalFlowDual_TVL1();
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void operator ()(InputArray I0, InputArray I1, InputOutputArray flow);
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void collectGarbage();
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/**
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* Time step of the numerical scheme.
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*/
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double tau;
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/**
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* Weight parameter for the data term, attachment parameter.
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* This is the most relevant parameter, which determines the smoothness of the output.
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* The smaller this parameter is, the smoother the solutions we obtain.
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* It depends on the range of motions of the images, so its value should be adapted to each image sequence.
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*/
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double lambda;
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/**
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* Weight parameter for (u - v)^2, tightness parameter.
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* It serves as a link between the attachment and the regularization terms.
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* In theory, it should have a small value in order to maintain both parts in correspondence.
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* The method is stable for a large range of values of this parameter.
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*/
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double theta;
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/**
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* Number of scales used to create the pyramid of images.
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*/
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int nscales;
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/**
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* Number of warpings per scale.
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* Represents the number of times that I1(x+u0) and grad( I1(x+u0) ) are computed per scale.
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* This is a parameter that assures the stability of the method.
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* It also affects the running time, so it is a compromise between speed and accuracy.
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*/
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int warps;
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/**
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* Stopping criterion threshold used in the numerical scheme, which is a trade-off between precision and running time.
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* A small value will yield more accurate solutions at the expense of a slower convergence.
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*/
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double epsilon;
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/**
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* Stopping criterion iterations number used in the numerical scheme.
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*/
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int iterations;
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bool useInitialFlow;
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private:
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void procOneScale(const Mat_<float>& I0, const Mat_<float>& I1, Mat_<float>& u1, Mat_<float>& u2);
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std::vector<Mat_<float> > I0s;
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std::vector<Mat_<float> > I1s;
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std::vector<Mat_<float> > u1s;
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std::vector<Mat_<float> > u2s;
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Mat_<float> I1x_buf;
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Mat_<float> I1y_buf;
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Mat_<float> flowMap1_buf;
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Mat_<float> flowMap2_buf;
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Mat_<float> I1w_buf;
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Mat_<float> I1wx_buf;
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Mat_<float> I1wy_buf;
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Mat_<float> grad_buf;
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Mat_<float> rho_c_buf;
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Mat_<float> v1_buf;
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Mat_<float> v2_buf;
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Mat_<float> p11_buf;
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Mat_<float> p12_buf;
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Mat_<float> p21_buf;
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Mat_<float> p22_buf;
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Mat_<float> div_p1_buf;
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Mat_<float> div_p2_buf;
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Mat_<float> u1x_buf;
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Mat_<float> u1y_buf;
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Mat_<float> u2x_buf;
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Mat_<float> u2y_buf;
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};
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CV_EXPORTS Ptr<DenseOpticalFlow> createOptFlow_DualTVL1();
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}
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@ -22,12 +22,9 @@ PERF_TEST_P(ImagePair, OpticalFlowDual_TVL1, testing::Values(impair("cv/optflow/
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Mat flow;
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OpticalFlowDual_TVL1 tvl1;
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Ptr<DenseOpticalFlow> tvl1 = createOptFlow_DualTVL1();
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TEST_CYCLE()
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{
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tvl1(frame1, frame2, flow);
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}
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TEST_CYCLE_N(10) tvl1->calc(frame1, frame2, flow);
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SANITY_CHECK(flow, 0.5);
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}
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File diff suppressed because it is too large
Load Diff
@ -152,9 +152,9 @@ TEST(Video_calcOpticalFlowDual_TVL1, Regression)
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ASSERT_FALSE(frame2.empty());
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Mat_<Point2f> flow;
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OpticalFlowDual_TVL1 tvl1;
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Ptr<DenseOpticalFlow> tvl1 = createOptFlow_DualTVL1();
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tvl1(frame1, frame2, flow);
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tvl1->calc(frame1, frame2, flow);
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#ifdef DUMP
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writeOpticalFlowToFile(flow, gold_flow_path);
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@ -173,10 +173,10 @@ int main(int argc, const char* argv[])
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}
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Mat_<Point2f> flow;
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OpticalFlowDual_TVL1 tvl1;
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Ptr<DenseOpticalFlow> tvl1 = createOptFlow_DualTVL1();
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const double start = (double)getTickCount();
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tvl1(frame0, frame1, flow);
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tvl1->calc(frame0, frame1, flow);
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const double timeSec = (getTickCount() - start) / getTickFrequency();
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cout << "calcOpticalFlowDual_TVL1 : " << timeSec << " sec" << endl;
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