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changed nullptr to NULL to avoid c++11 (failed to build on linux)

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replaces tabs with spaces
This commit is contained in:
Ernest Galbrun 2014-07-07 09:32:48 +02:00
parent 062e1cbe06
commit eb6c598678
4 changed files with 47 additions and 47 deletions
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24
modules/cudaoptflow/include/opencv2/cudaoptflow.hpp
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@ -211,13 +211,13 @@ public:
* The method is stable for a large range of values of this parameter. * The method is stable for a large range of values of this parameter.
*/ */
double gamma; double gamma;
/** /**
* parameter used for motion estimation. It adds a variable allowing for illumination variations * parameter used for motion estimation. It adds a variable allowing for illumination variations
* Set this parameter to 1. if you have varying illumination. * Set this parameter to 1. if you have varying illumination.
* See: Chambolle et al, A First-Order Primal-Dual Algorithm for Convex Problems with Applications to Imaging * See: Chambolle et al, A First-Order Primal-Dual Algorithm for Convex Problems with Applications to Imaging
* Journal of Mathematical imaging and vision, may 2011 Vol 40 issue 1, pp 120-145 * Journal of Mathematical imaging and vision, may 2011 Vol 40 issue 1, pp 120-145
*/ */
double theta; double theta;
/** /**
@ -254,8 +254,8 @@ private:
std::vector<GpuMat> I0s; std::vector<GpuMat> I0s;
std::vector<GpuMat> I1s; std::vector<GpuMat> I1s;
std::vector<GpuMat> u1s; std::vector<GpuMat> u1s;
std::vector<GpuMat> u2s; std::vector<GpuMat> u2s;
std::vector<GpuMat> u3s; std::vector<GpuMat> u3s;
GpuMat I1x_buf; GpuMat I1x_buf;
GpuMat I1y_buf; GpuMat I1y_buf;
@ -270,9 +270,9 @@ private:
GpuMat p11_buf; GpuMat p11_buf;
GpuMat p12_buf; GpuMat p12_buf;
GpuMat p21_buf; GpuMat p21_buf;
GpuMat p22_buf; GpuMat p22_buf;
GpuMat p31_buf; GpuMat p31_buf;
GpuMat p32_buf; GpuMat p32_buf;
GpuMat diff_buf; GpuMat diff_buf;
GpuMat norm_buf; GpuMat norm_buf;

54
modules/cudaoptflow/src/tvl1flow.cpp
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@ -64,7 +64,7 @@ cv::cuda::OpticalFlowDual_TVL1_CUDA::OpticalFlowDual_TVL1_CUDA()
epsilon = 0.01; epsilon = 0.01;
iterations = 300; iterations = 300;
scaleStep = 0.8; scaleStep = 0.8;
gamma = 0.0; gamma = 0.0;
useInitialFlow = false; useInitialFlow = false;
} }
@ -81,7 +81,7 @@ void cv::cuda::OpticalFlowDual_TVL1_CUDA::operator ()(const GpuMat& I0, const Gp
I1s.resize(nscales); I1s.resize(nscales);
u1s.resize(nscales); u1s.resize(nscales);
u2s.resize(nscales); u2s.resize(nscales);
u3s.resize(nscales); u3s.resize(nscales);
I0.convertTo(I0s[0], CV_32F, I0.depth() == CV_8U ? 1.0 : 255.0); I0.convertTo(I0s[0], CV_32F, I0.depth() == CV_8U ? 1.0 : 255.0);
I1.convertTo(I1s[0], CV_32F, I1.depth() == CV_8U ? 1.0 : 255.0); I1.convertTo(I1s[0], CV_32F, I1.depth() == CV_8U ? 1.0 : 255.0);
@ -94,7 +94,7 @@ void cv::cuda::OpticalFlowDual_TVL1_CUDA::operator ()(const GpuMat& I0, const Gp
u1s[0] = flowx; u1s[0] = flowx;
u2s[0] = flowy; u2s[0] = flowy;
u3s[0].create(I0.size(), CV_32FC1); u3s[0].create(I0.size(), CV_32FC1);
I1x_buf.create(I0.size(), CV_32FC1); I1x_buf.create(I0.size(), CV_32FC1);
I1y_buf.create(I0.size(), CV_32FC1); I1y_buf.create(I0.size(), CV_32FC1);
@ -109,9 +109,9 @@ void cv::cuda::OpticalFlowDual_TVL1_CUDA::operator ()(const GpuMat& I0, const Gp
p11_buf.create(I0.size(), CV_32FC1); p11_buf.create(I0.size(), CV_32FC1);
p12_buf.create(I0.size(), CV_32FC1); p12_buf.create(I0.size(), CV_32FC1);
p21_buf.create(I0.size(), CV_32FC1); p21_buf.create(I0.size(), CV_32FC1);
p22_buf.create(I0.size(), CV_32FC1); p22_buf.create(I0.size(), CV_32FC1);
p31_buf.create(I0.size(), CV_32FC1); p31_buf.create(I0.size(), CV_32FC1);
p32_buf.create(I0.size(), CV_32FC1); p32_buf.create(I0.size(), CV_32FC1);
diff_buf.create(I0.size(), CV_32FC1); diff_buf.create(I0.size(), CV_32FC1);
@ -139,8 +139,8 @@ void cv::cuda::OpticalFlowDual_TVL1_CUDA::operator ()(const GpuMat& I0, const Gp
{ {
u1s[s].create(I0s[s].size(), CV_32FC1); u1s[s].create(I0s[s].size(), CV_32FC1);
u2s[s].create(I0s[s].size(), CV_32FC1); u2s[s].create(I0s[s].size(), CV_32FC1);
} }
u3s[s].create(I0s[s].size(), CV_32FC1); u3s[s].create(I0s[s].size(), CV_32FC1);
} }
if (!useInitialFlow) if (!useInitialFlow)
@ -148,7 +148,7 @@ void cv::cuda::OpticalFlowDual_TVL1_CUDA::operator ()(const GpuMat& I0, const Gp
u1s[nscales-1].setTo(Scalar::all(0)); u1s[nscales-1].setTo(Scalar::all(0));
u2s[nscales-1].setTo(Scalar::all(0)); u2s[nscales-1].setTo(Scalar::all(0));
} }
u3s[nscales - 1].setTo(Scalar::all(0)); u3s[nscales - 1].setTo(Scalar::all(0));
// pyramidal structure for computing the optical flow // pyramidal structure for computing the optical flow
for (int s = nscales - 1; s >= 0; --s) for (int s = nscales - 1; s >= 0; --s)
@ -164,8 +164,8 @@ void cv::cuda::OpticalFlowDual_TVL1_CUDA::operator ()(const GpuMat& I0, const Gp
// zoom the optical flow for the next finer scale // zoom the optical flow for the next finer scale
cuda::resize(u1s[s], u1s[s - 1], I0s[s - 1].size()); cuda::resize(u1s[s], u1s[s - 1], I0s[s - 1].size());
cuda::resize(u2s[s], u2s[s - 1], I0s[s - 1].size()); cuda::resize(u2s[s], u2s[s - 1], I0s[s - 1].size());
cuda::resize(u3s[s], u3s[s - 1], I0s[s - 1].size()); cuda::resize(u3s[s], u3s[s - 1], I0s[s - 1].size());
// scale the optical flow with the appropriate zoom factor // scale the optical flow with the appropriate zoom factor
cuda::multiply(u1s[s - 1], Scalar::all(1/scaleStep), u1s[s - 1]); cuda::multiply(u1s[s - 1], Scalar::all(1/scaleStep), u1s[s - 1]);
@ -179,10 +179,10 @@ namespace tvl1flow
void warpBackward(PtrStepSzf I0, PtrStepSzf I1, PtrStepSzf I1x, PtrStepSzf I1y, PtrStepSzf u1, PtrStepSzf u2, PtrStepSzf I1w, PtrStepSzf I1wx, PtrStepSzf I1wy, PtrStepSzf grad, PtrStepSzf rho); void warpBackward(PtrStepSzf I0, PtrStepSzf I1, PtrStepSzf I1x, PtrStepSzf I1y, PtrStepSzf u1, PtrStepSzf u2, PtrStepSzf I1w, PtrStepSzf I1wx, PtrStepSzf I1wy, PtrStepSzf grad, PtrStepSzf rho);
void estimateU(PtrStepSzf I1wx, PtrStepSzf I1wy, void estimateU(PtrStepSzf I1wx, PtrStepSzf I1wy,
PtrStepSzf grad, PtrStepSzf rho_c, PtrStepSzf grad, PtrStepSzf rho_c,
PtrStepSzf p11, PtrStepSzf p12, PtrStepSzf p21, PtrStepSzf p22, PtrStepSzf p31, PtrStepSzf p32, PtrStepSzf p11, PtrStepSzf p12, PtrStepSzf p21, PtrStepSzf p22, PtrStepSzf p31, PtrStepSzf p32,
PtrStepSzf u1, PtrStepSzf u2, PtrStepSzf u3, PtrStepSzf error, PtrStepSzf u1, PtrStepSzf u2, PtrStepSzf u3, PtrStepSzf error,
float l_t, float theta, float gamma, bool calcError); float l_t, float theta, float gamma, bool calcError);
void estimateDualVariables(PtrStepSzf u1, PtrStepSzf u2, PtrStepSzf u3, PtrStepSzf p11, PtrStepSzf p12, PtrStepSzf p21, PtrStepSzf p22, PtrStepSzf p31, PtrStepSzf p32, float taut); void estimateDualVariables(PtrStepSzf u1, PtrStepSzf u2, PtrStepSzf u3, PtrStepSzf p11, PtrStepSzf p12, PtrStepSzf p21, PtrStepSzf p22, PtrStepSzf p31, PtrStepSzf p32, float taut);
} }
void cv::cuda::OpticalFlowDual_TVL1_CUDA::procOneScale(const GpuMat& I0, const GpuMat& I1, GpuMat& u1, GpuMat& u2, GpuMat& u3) void cv::cuda::OpticalFlowDual_TVL1_CUDA::procOneScale(const GpuMat& I0, const GpuMat& I1, GpuMat& u1, GpuMat& u2, GpuMat& u3)
@ -210,15 +210,15 @@ void cv::cuda::OpticalFlowDual_TVL1_CUDA::procOneScale(const GpuMat& I0, const G
GpuMat p11 = p11_buf(Rect(0, 0, I0.cols, I0.rows)); GpuMat p11 = p11_buf(Rect(0, 0, I0.cols, I0.rows));
GpuMat p12 = p12_buf(Rect(0, 0, I0.cols, I0.rows)); GpuMat p12 = p12_buf(Rect(0, 0, I0.cols, I0.rows));
GpuMat p21 = p21_buf(Rect(0, 0, I0.cols, I0.rows)); GpuMat p21 = p21_buf(Rect(0, 0, I0.cols, I0.rows));
GpuMat p22 = p22_buf(Rect(0, 0, I0.cols, I0.rows)); GpuMat p22 = p22_buf(Rect(0, 0, I0.cols, I0.rows));
GpuMat p31 = p31_buf(Rect(0, 0, I0.cols, I0.rows)); GpuMat p31 = p31_buf(Rect(0, 0, I0.cols, I0.rows));
GpuMat p32 = p32_buf(Rect(0, 0, I0.cols, I0.rows)); GpuMat p32 = p32_buf(Rect(0, 0, I0.cols, I0.rows));
p11.setTo(Scalar::all(0)); p11.setTo(Scalar::all(0));
p12.setTo(Scalar::all(0)); p12.setTo(Scalar::all(0));
p21.setTo(Scalar::all(0)); p21.setTo(Scalar::all(0));
p22.setTo(Scalar::all(0)); p22.setTo(Scalar::all(0));
p31.setTo(Scalar::all(0)); p31.setTo(Scalar::all(0));
p32.setTo(Scalar::all(0)); p32.setTo(Scalar::all(0));
GpuMat diff = diff_buf(Rect(0, 0, I0.cols, I0.rows)); GpuMat diff = diff_buf(Rect(0, 0, I0.cols, I0.rows));
@ -235,8 +235,8 @@ void cv::cuda::OpticalFlowDual_TVL1_CUDA::procOneScale(const GpuMat& I0, const G
{ {
// some tweaks to make sum operation less frequently // some tweaks to make sum operation less frequently
bool calcError = (epsilon > 0) && (n & 0x1) && (prevError < scaledEpsilon); bool calcError = (epsilon > 0) && (n & 0x1) && (prevError < scaledEpsilon);
cv::Mat m1(u3); cv::Mat m1(u3);
estimateU(I1wx, I1wy, grad, rho_c, p11, p12, p21, p22, p31, p32, u1, u2, u3, diff, l_t, static_cast<float>(theta), gamma, calcError); estimateU(I1wx, I1wy, grad, rho_c, p11, p12, p21, p22, p31, p32, u1, u2, u3, diff, l_t, static_cast<float>(theta), gamma, calcError);
if (calcError) if (calcError)
{ {
error = cuda::sum(diff, norm_buf)[0]; error = cuda::sum(diff, norm_buf)[0];
@ -258,8 +258,8 @@ void cv::cuda::OpticalFlowDual_TVL1_CUDA::collectGarbage()
I0s.clear(); I0s.clear();
I1s.clear(); I1s.clear();
u1s.clear(); u1s.clear();
u2s.clear(); u2s.clear();
u3s.clear(); u3s.clear();
I1x_buf.release(); I1x_buf.release();
I1y_buf.release(); I1y_buf.release();
@ -274,9 +274,9 @@ void cv::cuda::OpticalFlowDual_TVL1_CUDA::collectGarbage()
p11_buf.release(); p11_buf.release();
p12_buf.release(); p12_buf.release();
p21_buf.release(); p21_buf.release();
p22_buf.release(); p22_buf.release();
p31_buf.release(); p31_buf.release();
p32_buf.release(); p32_buf.release();
diff_buf.release(); diff_buf.release();
norm_buf.release(); norm_buf.release();

2
modules/video/doc/motion_analysis_and_object_tracking.rst
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@ -1082,7 +1082,7 @@ createOptFlow_DualTVL1
.. ocv:member:: double gamma .. ocv:member:: double gamma
parameter used for motion estimation. It adds a variable allowing for illumination variations parameter used for motion estimation. It adds a variable allowing for illumination variations
Set this parameter to 1. if you have varying illumination. Set this parameter to 1 if you have varying illumination.
See: [Chambolle2011]_ See: [Chambolle2011]_

14
modules/video/src/tvl1flow.cpp
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@ -951,13 +951,13 @@ void EstimateVBody::operator() (const Range& range) const
const float* I1wyRow = I1wy[y]; const float* I1wyRow = I1wy[y];
const float* u1Row = u1[y]; const float* u1Row = u1[y];
const float* u2Row = u2[y]; const float* u2Row = u2[y];
const float* u3Row = use_gamma?u3[y]:nullptr; const float* u3Row = use_gamma?u3[y]:NULL;
const float* gradRow = grad[y]; const float* gradRow = grad[y];
const float* rhoRow = rho_c[y]; const float* rhoRow = rho_c[y];
float* v1Row = v1[y]; float* v1Row = v1[y];
float* v2Row = v2[y]; float* v2Row = v2[y];
float* v3Row = use_gamma ? v3[y]:nullptr; float* v3Row = use_gamma ? v3[y]:NULL;
for (int x = 0; x < I1wx.cols; ++x) for (int x = 0; x < I1wx.cols; ++x)
{ {
@ -1041,14 +1041,14 @@ float estimateU(const Mat_<float>& v1, const Mat_<float>& v2, const Mat_<float>&
{ {
const float* v1Row = v1[y]; const float* v1Row = v1[y];
const float* v2Row = v2[y]; const float* v2Row = v2[y];
const float* v3Row = use_gamma?v3[y]:nullptr; const float* v3Row = use_gamma?v3[y]:NULL;
const float* divP1Row = div_p1[y]; const float* divP1Row = div_p1[y];
const float* divP2Row = div_p2[y]; const float* divP2Row = div_p2[y];
const float* divP3Row = use_gamma?div_p3[y]:nullptr; const float* divP3Row = use_gamma?div_p3[y]:NULL;
float* u1Row = u1[y]; float* u1Row = u1[y];
float* u2Row = u2[y]; float* u2Row = u2[y];
float* u3Row = use_gamma?u3[y]:nullptr; float* u3Row = use_gamma?u3[y]:NULL;
for (int x = 0; x < v1.cols; ++x) for (int x = 0; x < v1.cols; ++x)
@ -1333,7 +1333,7 @@ void OpticalFlowDual_TVL1::procOneScale(const Mat_<float>& I0, const Mat_<float>
for (int n_inner = 0; error > scaledEpsilon && n_inner < innerIterations; ++n_inner) for (int n_inner = 0; error > scaledEpsilon && n_inner < innerIterations; ++n_inner)
{ {
// estimate the values of the variable (v1, v2) (thresholding operator TH) // estimate the values of the variable (v1, v2) (thresholding operator TH)
estimateV(I1wx, I1wy, u1, u2, u3, grad, rho_c, v1, v2, v3, l_t, gamma); estimateV(I1wx, I1wy, u1, u2, u3, grad, rho_c, v1, v2, v3, l_t, static_cast<float>(gamma));
// compute the divergence of the dual variable (p1, p2, p3) // compute the divergence of the dual variable (p1, p2, p3)
divergence(p11, p12, div_p1); divergence(p11, p12, div_p1);
@ -1341,7 +1341,7 @@ void OpticalFlowDual_TVL1::procOneScale(const Mat_<float>& I0, const Mat_<float>
if (use_gamma) divergence(p31, p32, div_p3); if (use_gamma) divergence(p31, p32, div_p3);
// estimate the values of the optical flow (u1, u2) // estimate the values of the optical flow (u1, u2)
error = estimateU(v1, v2, v3, div_p1, div_p2, div_p3, u1, u2, u3, static_cast<float>(theta), gamma); error = estimateU(v1, v2, v3, div_p1, div_p2, div_p3, u1, u2, u3, static_cast<float>(theta), static_cast<float>(gamma));
// compute the gradient of the optical flow (Du1, Du2) // compute the gradient of the optical flow (Du1, Du2)
forwardGradient(u1, u1x, u1y); forwardGradient(u1, u1x, u1y);