Merge pull request #724 from jet47:tvl1-updates
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commit
54511b4198
@ -1810,6 +1810,8 @@ public:
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*/
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*/
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int iterations;
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int iterations;
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double scaleStep;
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bool useInitialFlow;
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bool useInitialFlow;
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private:
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private:
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@ -434,6 +434,9 @@ PERF_TEST_P(ImagePair, Video_OpticalFlowDual_TVL1,
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cv::Mat flow;
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cv::Mat flow;
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cv::Ptr<cv::DenseOpticalFlow> alg = cv::createOptFlow_DualTVL1();
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cv::Ptr<cv::DenseOpticalFlow> alg = cv::createOptFlow_DualTVL1();
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alg->set("medianFiltering", 1);
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alg->set("innerIterations", 1);
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alg->set("outerIterations", 300);
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TEST_CYCLE() alg->calc(frame0, frame1, flow);
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TEST_CYCLE() alg->calc(frame0, frame1, flow);
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@ -63,6 +63,7 @@ cv::gpu::OpticalFlowDual_TVL1_GPU::OpticalFlowDual_TVL1_GPU()
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warps = 5;
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warps = 5;
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epsilon = 0.01;
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epsilon = 0.01;
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iterations = 300;
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iterations = 300;
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scaleStep = 0.8;
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useInitialFlow = false;
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useInitialFlow = false;
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}
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}
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@ -112,8 +113,8 @@ void cv::gpu::OpticalFlowDual_TVL1_GPU::operator ()(const GpuMat& I0, const GpuM
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// create the scales
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// create the scales
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for (int s = 1; s < nscales; ++s)
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for (int s = 1; s < nscales; ++s)
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{
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{
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gpu::pyrDown(I0s[s - 1], I0s[s]);
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gpu::resize(I0s[s-1], I0s[s], Size(), scaleStep, scaleStep);
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gpu::pyrDown(I1s[s - 1], I1s[s]);
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gpu::resize(I1s[s-1], I1s[s], Size(), scaleStep, scaleStep);
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if (I0s[s].cols < 16 || I0s[s].rows < 16)
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if (I0s[s].cols < 16 || I0s[s].rows < 16)
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{
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{
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@ -123,11 +124,11 @@ void cv::gpu::OpticalFlowDual_TVL1_GPU::operator ()(const GpuMat& I0, const GpuM
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if (useInitialFlow)
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if (useInitialFlow)
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{
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{
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gpu::pyrDown(u1s[s - 1], u1s[s]);
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gpu::resize(u1s[s-1], u1s[s], Size(), scaleStep, scaleStep);
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gpu::pyrDown(u2s[s - 1], u2s[s]);
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gpu::resize(u2s[s-1], u2s[s], Size(), scaleStep, scaleStep);
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gpu::multiply(u1s[s], Scalar::all(0.5), u1s[s]);
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gpu::multiply(u1s[s], Scalar::all(scaleStep), u1s[s]);
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gpu::multiply(u2s[s], Scalar::all(0.5), u2s[s]);
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gpu::multiply(u2s[s], Scalar::all(scaleStep), u2s[s]);
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}
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}
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else
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else
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{
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{
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@ -159,8 +160,8 @@ void cv::gpu::OpticalFlowDual_TVL1_GPU::operator ()(const GpuMat& I0, const GpuM
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gpu::resize(u2s[s], u2s[s - 1], I0s[s - 1].size());
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gpu::resize(u2s[s], u2s[s - 1], I0s[s - 1].size());
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// scale the optical flow with the appropriate zoom factor
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// scale the optical flow with the appropriate zoom factor
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gpu::multiply(u1s[s - 1], Scalar::all(2), u1s[s - 1]);
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gpu::multiply(u1s[s - 1], Scalar::all(1/scaleStep), u1s[s - 1]);
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gpu::multiply(u2s[s - 1], Scalar::all(2), u2s[s - 1]);
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gpu::multiply(u2s[s - 1], Scalar::all(1/scaleStep), u2s[s - 1]);
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}
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}
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}
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}
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@ -435,13 +435,16 @@ GPU_TEST_P(OpticalFlowDual_TVL1, Accuracy)
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d_alg(loadMat(frame0, useRoi), loadMat(frame1, useRoi), d_flowx, d_flowy);
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d_alg(loadMat(frame0, useRoi), loadMat(frame1, useRoi), d_flowx, d_flowy);
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cv::Ptr<cv::DenseOpticalFlow> alg = cv::createOptFlow_DualTVL1();
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cv::Ptr<cv::DenseOpticalFlow> alg = cv::createOptFlow_DualTVL1();
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alg->set("medianFiltering", 1);
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alg->set("innerIterations", 1);
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alg->set("outerIterations", d_alg.iterations);
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cv::Mat flow;
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cv::Mat flow;
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alg->calc(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::Mat gold[2];
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cv::split(flow, gold);
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cv::split(flow, gold);
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EXPECT_MAT_SIMILAR(gold[0], d_flowx, 3e-3);
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EXPECT_MAT_SIMILAR(gold[0], d_flowx, 4e-3);
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EXPECT_MAT_SIMILAR(gold[1], d_flowy, 3e-3);
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EXPECT_MAT_SIMILAR(gold[1], d_flowy, 4e-3);
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}
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}
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INSTANTIATE_TEST_CASE_P(GPU_Video, OpticalFlowDual_TVL1, testing::Combine(
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INSTANTIATE_TEST_CASE_P(GPU_Video, OpticalFlowDual_TVL1, testing::Combine(
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@ -26,5 +26,5 @@ PERF_TEST_P(ImagePair, OpticalFlowDual_TVL1, testing::Values(impair("cv/optflow/
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TEST_CYCLE_N(10) tvl1->calc(frame1, frame2, flow);
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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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SANITY_CHECK(flow, 0.8);
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}
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}
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@ -95,8 +95,11 @@ protected:
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int nscales;
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int nscales;
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int warps;
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int warps;
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double epsilon;
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double epsilon;
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int iterations;
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int innerIterations;
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int outerIterations;
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bool useInitialFlow;
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bool useInitialFlow;
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double scaleStep;
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int medianFiltering;
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private:
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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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void procOneScale(const Mat_<float>& I0, const Mat_<float>& I1, Mat_<float>& u1, Mat_<float>& u2);
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@ -144,8 +147,11 @@ OpticalFlowDual_TVL1::OpticalFlowDual_TVL1()
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nscales = 5;
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nscales = 5;
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warps = 5;
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warps = 5;
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epsilon = 0.01;
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epsilon = 0.01;
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iterations = 300;
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innerIterations = 30;
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outerIterations = 10;
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useInitialFlow = false;
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useInitialFlow = false;
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medianFiltering = 5;
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scaleStep = 0.8;
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}
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}
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void OpticalFlowDual_TVL1::calc(InputArray _I0, InputArray _I1, InputOutputArray _flow)
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void OpticalFlowDual_TVL1::calc(InputArray _I0, InputArray _I1, InputOutputArray _flow)
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@ -209,8 +215,8 @@ void OpticalFlowDual_TVL1::calc(InputArray _I0, InputArray _I1, InputOutputArray
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// create the scales
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// create the scales
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for (int s = 1; s < nscales; ++s)
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for (int s = 1; s < nscales; ++s)
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{
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{
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pyrDown(I0s[s - 1], I0s[s]);
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resize(I0s[s-1], I0s[s], Size(), scaleStep, scaleStep);
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pyrDown(I1s[s - 1], I1s[s]);
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resize(I1s[s-1], I1s[s], Size(), scaleStep, scaleStep);
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if (I0s[s].cols < 16 || I0s[s].rows < 16)
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if (I0s[s].cols < 16 || I0s[s].rows < 16)
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{
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{
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@ -220,11 +226,11 @@ void OpticalFlowDual_TVL1::calc(InputArray _I0, InputArray _I1, InputOutputArray
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if (useInitialFlow)
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if (useInitialFlow)
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{
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{
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pyrDown(u1s[s - 1], u1s[s]);
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resize(u1s[s-1], u1s[s], Size(), scaleStep, scaleStep);
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pyrDown(u2s[s - 1], u2s[s]);
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resize(u2s[s-1], u2s[s], Size(), scaleStep, scaleStep);
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multiply(u1s[s], Scalar::all(0.5), u1s[s]);
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multiply(u1s[s], Scalar::all(scaleStep), u1s[s]);
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multiply(u2s[s], Scalar::all(0.5), u2s[s]);
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multiply(u2s[s], Scalar::all(scaleStep), u2s[s]);
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}
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}
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else
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else
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{
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{
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@ -256,8 +262,8 @@ void OpticalFlowDual_TVL1::calc(InputArray _I0, InputArray _I1, InputOutputArray
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resize(u2s[s], u2s[s - 1], I0s[s - 1].size());
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resize(u2s[s], u2s[s - 1], I0s[s - 1].size());
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// scale the optical flow with the appropriate zoom factor
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// scale the optical flow with the appropriate zoom factor
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multiply(u1s[s - 1], Scalar::all(2), u1s[s - 1]);
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multiply(u1s[s - 1], Scalar::all(1/scaleStep), u1s[s - 1]);
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multiply(u2s[s - 1], Scalar::all(2), u2s[s - 1]);
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multiply(u2s[s - 1], Scalar::all(1/scaleStep), u2s[s - 1]);
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}
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}
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Mat uxy[] = {u1s[0], u2s[0]};
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Mat uxy[] = {u1s[0], u2s[0]};
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@ -853,24 +859,31 @@ void OpticalFlowDual_TVL1::procOneScale(const Mat_<float>& I0, const Mat_<float>
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calcGradRho(I0, I1w, I1wx, I1wy, u1, u2, grad, rho_c);
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calcGradRho(I0, I1w, I1wx, I1wy, u1, u2, grad, rho_c);
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float error = std::numeric_limits<float>::max();
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float error = std::numeric_limits<float>::max();
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for (int n = 0; error > scaledEpsilon && n < iterations; ++n)
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for (int n_outer = 0; error > scaledEpsilon && n_outer < outerIterations; ++n_outer)
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{
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{
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// estimate the values of the variable (v1, v2) (thresholding operator TH)
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if (medianFiltering > 1) {
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estimateV(I1wx, I1wy, u1, u2, grad, rho_c, v1, v2, l_t);
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cv::medianBlur(u1, u1, medianFiltering);
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cv::medianBlur(u2, u2, medianFiltering);
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}
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for (int n_inner = 0; error > scaledEpsilon && n_inner < innerIterations; ++n_inner)
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{
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// estimate the values of the variable (v1, v2) (thresholding operator TH)
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estimateV(I1wx, I1wy, u1, u2, grad, rho_c, v1, v2, l_t);
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// compute the divergence of the dual variable (p1, p2)
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// compute the divergence of the dual variable (p1, p2)
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divergence(p11, p12, div_p1);
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divergence(p11, p12, div_p1);
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divergence(p21, p22, div_p2);
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divergence(p21, p22, div_p2);
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// estimate the values of the optical flow (u1, u2)
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// estimate the values of the optical flow (u1, u2)
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error = estimateU(v1, v2, div_p1, div_p2, u1, u2, static_cast<float>(theta));
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error = estimateU(v1, v2, div_p1, div_p2, u1, u2, static_cast<float>(theta));
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// compute the gradient of the optical flow (Du1, Du2)
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// compute the gradient of the optical flow (Du1, Du2)
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forwardGradient(u1, u1x, u1y);
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forwardGradient(u1, u1x, u1y);
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forwardGradient(u2, u2x, u2y);
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forwardGradient(u2, u2x, u2y);
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// estimate the values of the dual variable (p1, p2)
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// estimate the values of the dual variable (p1, p2)
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estimateDualVariables(u1x, u1y, u2x, u2y, p11, p12, p21, p22, taut);
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estimateDualVariables(u1x, u1y, u2x, u2y, p11, p12, p21, p22, taut);
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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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@ -923,10 +936,16 @@ CV_INIT_ALGORITHM(OpticalFlowDual_TVL1, "DenseOpticalFlow.DualTVL1",
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"Number of scales used to create the pyramid of images");
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"Number of scales used to create the pyramid of images");
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obj.info()->addParam(obj, "warps", obj.warps, false, 0, 0,
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obj.info()->addParam(obj, "warps", obj.warps, false, 0, 0,
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"Number of warpings per scale");
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"Number of warpings per scale");
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obj.info()->addParam(obj, "medianFiltering", obj.medianFiltering, false, 0, 0,
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"Median filter kernel size (1 = no filter) (3 or 5)");
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obj.info()->addParam(obj, "scaleStep", obj.scaleStep, false, 0, 0,
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"Step between scales (<1)");
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obj.info()->addParam(obj, "epsilon", obj.epsilon, false, 0, 0,
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obj.info()->addParam(obj, "epsilon", obj.epsilon, false, 0, 0,
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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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"Stopping criterion threshold used in the numerical scheme, which is a trade-off between precision and running time");
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obj.info()->addParam(obj, "iterations", obj.iterations, false, 0, 0,
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obj.info()->addParam(obj, "innerIterations", obj.innerIterations, false, 0, 0,
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"Stopping criterion iterations number used in the numerical scheme");
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"inner iterations (between outlier filtering) used in the numerical scheme");
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obj.info()->addParam(obj, "outerIterations", obj.outerIterations, false, 0, 0,
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"outer iterations (number of inner loops) used in the numerical scheme");
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obj.info()->addParam(obj, "useInitialFlow", obj.useInitialFlow));
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obj.info()->addParam(obj, "useInitialFlow", obj.useInitialFlow));
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} // namespace
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} // namespace
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