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icv_ipp_is_sse41_extension icv_ipp_is_sse42_extension icv_ipp_is_movbe icv_ipp_is_avx_extension icv_ipp_is_avx512_extension icv_ipp_get_cores_on_die icv_ipp_get_pentium_ident icv_ipp_get_pentium_counter icv_ippStartTscp icv_ippStopTscp icv_ippStartTsc icv_ippStopTsc icv_ipp_clear_ssx icv_ps_set_cw_fpu icv_ps_get_cw_fpu icv_ps_get_sw_fpu icv_ps_clear_fpu icv_ps_set_ssx icv_ps_get_ssx icv_ipp_isnan icv_ipp_finite icv_ipp_set_rc_ssx icv_ipp_set_cw_ssx icv_ipp_tst_daz_ssx icv_ipp_control87 icv_ipp_status87 icv_ipp_clear87 icv_ipp_set_rcpc_fpu icv_ipp_set_cw_fpu icv_ownGetCacheSize icv_ownGetReg icv_ownSetFeatureMask icv_ownGetFeature ippicvGetEnabledCpuFeatures libopencv_imgproc.so.4.0 libopencv_core.so.4.0 libstdc++.so.6 libm.so.6 libgcc_s.so.1 libc.so.6 _edata __bss_start _end libopencv_video.so.4.0 /usr/local/lib GCC_3.0 GLIBC_2.4 GLIBC_2.14 GLIBC_2.2.5 CXXABI_1.3.8 GLIBCXX_3.4.21 CXXABI_1.3 GLIBCXX_3.4
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Ç f! à SHcöHcÒHðHÑ1Û1Ò¢_OW [ÃHìHÄà basic_string::_M_construct null not valid /tmp/opencv/opencv-4.0.1/modules/video/src/bgfg_KNN.cpp No element name has been given /tmp/opencv/opencv-4.0.1/modules/core/include/opencv2/core/persistence.hpp name (String)fn["name"] == name_ history nsamples nKNN dist2Threshold detectShadows shadowValue shadowThreshold -D SHADOW_DETECT -D CN=%d -D NSAMPLES=%d%s knn_kernel !kernel_apply.empty() -D CN=%d -D NSAMPLES=%d getBackgroundImage2_kernel learningRate >= 0 BackgroundSubtractor.KNN operator<< operator<< read setDetectShadows virtual void cv::BackgroundSubtractorKNNImpl::getBackgroundImage(cv::OutputArray) const getBackgroundImage virtual void cv::BackgroundSubtractorKNNImpl::apply(cv::InputArray, cv::OutputArray, double) apply ocl_apply St11_Mutex_baseILN9__gnu_cxx12_Lock_policyE2EE St16_Sp_counted_baseILN9__gnu_cxx12_Lock_policyE2EE N2cv20BackgroundSubtractorE N2cv23BackgroundSubtractorKNNE N2cv27BackgroundSubtractorKNNImplE N2cv10KNNInvokerE St19_Sp_make_shared_tag St23_Sp_counted_ptr_inplaceIN2cv27BackgroundSubtractorKNNImplESaIS1_ELN9__gnu_cxx12_Lock_policyE2EE ð?P?á$ÃÓÖ¿wààð@Rí¿Uµ»±kÀ ð> @ ÿB ÈC /tmp/opencv/opencv-4.0.1/modules/video/src/bgfg_gaussmix2.cpp /tmp/opencv/opencv-4.0.1/modules/core/include/opencv2/core/mat.inl.hpp -D CN=%d -D FL=%d -D NMIXTURES=%d%s -D CN=%d -D FL=%d -D NMIXTURES=%d frameType == CV_8UC1 || frameType == CV_8UC3 || frameType == CV_32FC1 || frameType == CV_32FC3 nmixtures backgroundRatio varThreshold varThresholdGen varInit varMin varMax complexityReductionThreshold total() == 0 || data != NULL mog2_kernel nmixtures <= 255 BackgroundSubtractor.MOG2 operator<< operator<< operator<< read setDetectShadows void cv::BackgroundSubtractorMOG2Impl::getBackgroundImage_intern(cv::OutputArray) const [with T = float; int CN = 3; cv::OutputArray = const cv::_OutputArray&] void cv::BackgroundSubtractorMOG2Impl::getBackgroundImage_intern(cv::OutputArray) const [with T = float; int CN = 1; cv::OutputArray = const cv::_OutputArray&] void cv::BackgroundSubtractorMOG2Impl::getBackgroundImage_intern(cv::OutputArray) const [with T = unsigned char; int CN = 3; cv::OutputArray = const cv::_OutputArray&] void cv::BackgroundSubtractorMOG2Impl::getBackgroundImage_intern(cv::OutputArray) const [with T = unsigned char; int CN = 1; cv::OutputArray = const cv::_OutputArray&] getBackgroundImage Mat virtual void cv::BackgroundSubtractorMOG2Impl::apply(cv::InputArray, cv::OutputArray, double) apply initialize ocl_apply N2cv24BackgroundSubtractorMOG2E N2cv28BackgroundSubtractorMOG2ImplE N2cv11MOG2InvokerE St23_Sp_counted_ptr_inplaceIN2cv28BackgroundSubtractorMOG2ImplESaIS1_ELN9__gnu_cxx12_Lock_policyE2EE ? 4 0@ ÿÿÿ /tmp/opencv/opencv-4.0.1/modules/video/src/camshift.cpp Input window has non-positive sizes cn == 1 cv::RotatedRect cv::CamShift(cv::InputArray, cv::Rect&, cv::TermCriteria) int cv::meanShift(cv::InputArray, cv::Rect&, cv::TermCriteria) meanShift °< à? @-DTû!ù? f@-DTû! @ÿÿÿÿÿÿÿ ´C 4C ? dis_patch_inverse_search_fwd_1 dis_patch_inverse_search_fwd_2 dis_patch_inverse_search_bwd_1 dis_patch_inverse_search_bwd_2 dis_precomputeStructureTensor_hor dis_precomputeStructureTensor_ver /tmp/opencv/opencv-4.0.1/modules/video/src/dis_flow.cpp !I0.empty() && I0.depth() == CV_8U && I0.channels() == 1 !I1.empty() && I1.depth() == CV_8U && I1.channels() == 1 dis_densification vector::_M_default_append I0.sameSize(I1) I0.isContinuous() I1.isContinuous() calc N2cv16DenseOpticalFlowE N2cv14DISOpticalFlowE N2cv18DISOpticalFlowImpl26PatchInverseSearch_ParBodyE N2cv18DISOpticalFlowImpl21Densification_ParBodyE N2cv18DISOpticalFlowImplE St23_Sp_counted_ptr_inplaceIN2cv18DISOpticalFlowImplESaIS1_ELN9__gnu_cxx12_Lock_policyE2EE o:ùP ï9úþB.æ? @ À? ð¿/tmp/opencv/opencv-4.0.1/modules/video/src/ecc.cpp Both input images must have the same data type warpMatrix must be single-channel floating-point matrix motionType == MOTION_AFFINE || motionType == MOTION_HOMOGRAPHY || motionType == MOTION_EUCLIDEAN || motionType == MOTION_TRANSLATION criteria.type & TermCriteria::COUNT || criteria.type & TermCriteria::EPS The algorithm stopped before its convergence. The correlation is going to be minimized. Images may be uncorrelated or non-overlapped map_matrix.rows == 3 && update.rows == 8 map_matrix.rows == 2 && update.rows == 6 map_matrix.rows == 2 && update.rows == 3 map_matrix.rows == 2 && update.rows == 2 Images must have 8uC1 or 32fC1 type src1.rows == src2.rows (src1.cols % src2.cols) == 0 dst.cols == dst.rows src1.rows == dst.rows dst.cols == (src1.cols*8) dst.type() == CV_32FC1 src5.isContinuous() src1.size() == src2.size() src1.size() == src3.size() src1.size() == src4.size() map.cols == 3 map.rows == 2 || map.rows ==3 dst.cols == (6*src1.cols) dst.cols == (src1.cols*2) dst.cols == (src1.cols*3) NaN encountered. map_matrix.type() == CV_32FC1 update.type() == CV_32FC1 update.cols == 1 map_matrix.isContinuous() update.isContinuous() !src.empty() !dst.empty() src1.size()==src2.size() src1.size()==src3.size() src1.size()==src4.size() update_warping_matrix_ECC project_onto_jacobian_ECC image_jacobian_euclidean_ECC image_jacobian_translation_ECC image_jacobian_homo_ECC image_jacobian_affine_ECC findTransformECC y å5×à?/tmp/opencv/opencv-4.0.1/modules/video/src/kalman.cpp type == CV_32F || type == CV_64F DP > 0 && MP > 0 const cv::Mat& cv::KalmanFilter::correct(const cv::Mat&) const cv::Mat& cv::KalmanFilter::predict(const cv::Mat&) init /tmp/opencv/opencv-4.0.1/modules/video/src/lkpyramid.cpp img.depth() == CV_8U && winSize.width > 2 && winSize.height > 2 maxLevel >= 0 && winSize.width > 2 && winSize.height > 2 (npoints = prevPtsMat.checkVector(2, CV_32F, true)) >= 0 nextPtsMat.checkVector(2, CV_32F, true) == npoints I.depth() == CV_32F && J.depth() == CV_32F ofs.x >= winSize.width && ofs.y >= winSize.height && ofs.x + prevPyr[lvlStep1].cols + winSize.width <= fullSize.width && ofs.y + prevPyr[lvlStep1].rows + winSize.height <= fullSize.height ofs.x >= winSize.width && ofs.y >= winSize.height && ofs.x + nextPyr[lvlStep2].cols + winSize.width <= fullSize.width && ofs.y + nextPyr[lvlStep2].rows + winSize.height <= fullSize.height Both input images must have either 8uC1 or 8uC3 type Both input images must have the same size depth == CV_8U status != NULL -D CPU -D WSX=%d -D WSY=%d lkSparse statusMat.isContinuous() errMat.isContinuous() levels1 >= 0 levels2 >= 0 cn == 1 || cn == 3 || cn == 4 cv::Mat cv::estimateRigidTransform(cv::InputArray, cv::InputArray, bool) estimateRigidTransform Mat lkSparse_run virtual void cv::{anonymous}::SparsePyrLKOpticalFlowImpl::calc(cv::InputArray, cv::InputArray, cv::InputArray, cv::InputOutputArray, cv::OutputArray, cv::OutputArray) calc calcSharrDeriv int cv::buildOpticalFlowPyramid(cv::InputArray, cv::OutputArrayOfArrays, cv::Size, int, bool, int, int, bool) buildOpticalFlowPyramid Mat virtual void cv::detail::LKTrackerInvoker::operator()(const cv::Range&) const operator() N2cv17SparseOpticalFlowE N2cv22SparsePyrLKOpticalFlowE N2cv6detail16LKTrackerInvokerE *N2cv12_GLOBAL__N_126SparsePyrLKOpticalFlowImplE *St23_Sp_counted_ptr_inplaceIN2cv12_GLOBAL__N_126SparsePyrLKOpticalFlowImplESaIS2_ELN9__gnu_cxx12_Lock_policyE2EE {®Gáz? Y@-C ëâ6? $@ ^@ d@ .@®Gáz®ï? @
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ð? ð? ? ? ? ? F 5 @ pAStep must be a multiple of esz1 /tmp/opencv/opencv-4.0.1/modules/video/src/optflowgf.cpp frame0.channels() == 1 && frame1.channels() == 1 frame0.size() == frame1.size() !fastPyramids_ || std::abs(pyrScale_ - 0.5) < 1e-6 prev0.size() == next0.size() && prev0.channels() == next0.channels() && prev0.channels() == 1 && pyrScale_ < 1 updateMatrices updateFlow -D polyN=%d polynomialExpansion polyN_ == 5 || polyN_ == 7 gaussianBlur gaussianBlur5 boxFilter5 dst.size() == src.size() src.type() == CV_32FC1 )\>)\>f÷ä>f÷ä>f÷ä> FarnebackPolyExp gaussianBlurOcl Mat operator() virtual void cv::{anonymous}::FarnebackOpticalFlowImpl::calc(cv::InputArray, cv::InputArray, cv::InputOutputArray) calc void cv::calcOpticalFlowFarneback(cv::InputArray, cv::InputArray, cv::InputOutputArray, double, int, int, int, int, double, int) N2cv20FarnebackOpticalFlowE *N2cv12_GLOBAL__N_124FarnebackOpticalFlowImplE *St23_Sp_counted_ptr_inplaceIN2cv12_GLOBAL__N_124FarnebackOpticalFlowImplESaIS2_ELN9__gnu_cxx12_Lock_policyE2EE >> >333333Ó?íµ ÷Æ°> @@ @ü©ñÒMbP?PIEH ÿB PIEH /tmp/opencv/opencv-4.0.1/modules/video/src/variational_refinement.cpp !flow_v.empty() && flow_v.depth() == CV_32F && flow_v.channels() == 1 !I0.empty() && I0.channels() == 1 !I1.empty() && I1.channels() == 1 (I0.depth() == CV_8U && I1.depth() == CV_8U) || (I0.depth() == CV_32F && I1.depth() == CV_32F) !flow_u.empty() && flow_u.depth() == CV_32F && flow_u.channels() == 1 !flow.empty() && flow.depth() == CV_32F && flow.channels() == 2 I0.sameSize(flow_u) flow_u.sameSize(flow_v) I0.sameSize(flow) calcUV calc N2cv21VariationalRefinementE N2cv25VariationalRefinementImpl18ParallelOp_ParBodyE N2cv25VariationalRefinementImpl23ComputeDataTerm_ParBodyE N2cv25VariationalRefinementImpl36ComputeSmoothnessTermHorPass_ParBodyE N2cv25VariationalRefinementImpl37ComputeSmoothnessTermVertPass_ParBodyE N2cv25VariationalRefinementImpl19RedBlackSOR_ParBodyE N2cv25VariationalRefinementImplE St23_Sp_counted_ptr_inplaceIN2cv25VariationalRefinementImplESaIS1_ELN9__gnu_cxx12_Lock_policyE2EE @video pyrlk optical_flow_farneback dis_flow bgfg_mog2 bgfg_knn #define GRIDSIZE 3
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#define LSx 8
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#define LSy 8
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#define LM_W (LSx*GRIDSIZE+2)
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#define LM_H (LSy*GRIDSIZE+2)
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#define BUFFER (LSx*LSy)
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#define BUFFER2 BUFFER>>1
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#ifdef CPU
|
inline void reduce3(float val1, float val2, float val3, __local float* smem1, __local float* smem2, __local float* smem3, int tid)
|
{
|
smem1[tid] = val1;
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smem2[tid] = val2;
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smem3[tid] = val3;
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barrier(CLK_LOCAL_MEM_FENCE);
|
for(int i = BUFFER2; i > 0; i >>= 1)
|
{
|
if(tid < i)
|
{
|
smem1[tid] += smem1[tid + i];
|
smem2[tid] += smem2[tid + i];
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smem3[tid] += smem3[tid + i];
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}
|
barrier(CLK_LOCAL_MEM_FENCE);
|
}
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}
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inline void reduce2(float val1, float val2, __local float* smem1, __local float* smem2, int tid)
|
{
|
smem1[tid] = val1;
|
smem2[tid] = val2;
|
barrier(CLK_LOCAL_MEM_FENCE);
|
for(int i = BUFFER2; i > 0; i >>= 1)
|
{
|
if(tid < i)
|
{
|
smem1[tid] += smem1[tid + i];
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smem2[tid] += smem2[tid + i];
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}
|
barrier(CLK_LOCAL_MEM_FENCE);
|
}
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}
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inline void reduce1(float val1, __local float* smem1, int tid)
|
{
|
smem1[tid] = val1;
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barrier(CLK_LOCAL_MEM_FENCE);
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for(int i = BUFFER2; i > 0; i >>= 1)
|
{
|
if(tid < i)
|
{
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smem1[tid] += smem1[tid + i];
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}
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barrier(CLK_LOCAL_MEM_FENCE);
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}
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}
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#else
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inline void reduce3(float val1, float val2, float val3,
|
__local float* smem1, __local float* smem2, __local float* smem3, int tid)
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{
|
smem1[tid] = val1;
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smem2[tid] = val2;
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smem3[tid] = val3;
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barrier(CLK_LOCAL_MEM_FENCE);
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if (tid < 32)
|
{
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smem1[tid] += smem1[tid + 32];
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smem2[tid] += smem2[tid + 32];
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smem3[tid] += smem3[tid + 32];
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}
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barrier(CLK_LOCAL_MEM_FENCE);
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if (tid < 16)
|
{
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smem1[tid] += smem1[tid + 16];
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smem2[tid] += smem2[tid + 16];
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smem3[tid] += smem3[tid + 16];
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}
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barrier(CLK_LOCAL_MEM_FENCE);
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if (tid < 8)
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{
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smem1[tid] += smem1[tid + 8];
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smem2[tid] += smem2[tid + 8];
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smem3[tid] += smem3[tid + 8];
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}
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barrier(CLK_LOCAL_MEM_FENCE);
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if (tid < 4)
|
{
|
smem1[tid] += smem1[tid + 4];
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smem2[tid] += smem2[tid + 4];
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smem3[tid] += smem3[tid + 4];
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}
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barrier(CLK_LOCAL_MEM_FENCE);
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if (tid == 0)
|
{
|
smem1[0] = (smem1[0] + smem1[1]) + (smem1[2] + smem1[3]);
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smem2[0] = (smem2[0] + smem2[1]) + (smem2[2] + smem2[3]);
|
smem3[0] = (smem3[0] + smem3[1]) + (smem3[2] + smem3[3]);
|
}
|
barrier(CLK_LOCAL_MEM_FENCE);
|
}
|
inline void reduce2(float val1, float val2, __local float* smem1, __local float* smem2, int tid)
|
{
|
smem1[tid] = val1;
|
smem2[tid] = val2;
|
barrier(CLK_LOCAL_MEM_FENCE);
|
if (tid < 32)
|
{
|
smem1[tid] += smem1[tid + 32];
|
smem2[tid] += smem2[tid + 32];
|
}
|
barrier(CLK_LOCAL_MEM_FENCE);
|
if (tid < 16)
|
{
|
smem1[tid] += smem1[tid + 16];
|
smem2[tid] += smem2[tid + 16];
|
}
|
barrier(CLK_LOCAL_MEM_FENCE);
|
if (tid < 8)
|
{
|
smem1[tid] += smem1[tid + 8];
|
smem2[tid] += smem2[tid + 8];
|
}
|
barrier(CLK_LOCAL_MEM_FENCE);
|
if (tid < 4)
|
{
|
smem1[tid] += smem1[tid + 4];
|
smem2[tid] += smem2[tid + 4];
|
}
|
barrier(CLK_LOCAL_MEM_FENCE);
|
if (tid == 0)
|
{
|
smem1[0] = (smem1[0] + smem1[1]) + (smem1[2] + smem1[3]);
|
smem2[0] = (smem2[0] + smem2[1]) + (smem2[2] + smem2[3]);
|
}
|
barrier(CLK_LOCAL_MEM_FENCE);
|
}
|
inline void reduce1(float val1, __local float* smem1, int tid)
|
{
|
smem1[tid] = val1;
|
barrier(CLK_LOCAL_MEM_FENCE);
|
if (tid < 32)
|
{
|
smem1[tid] += smem1[tid + 32];
|
}
|
barrier(CLK_LOCAL_MEM_FENCE);
|
if (tid < 16)
|
{
|
smem1[tid] += smem1[tid + 16];
|
}
|
barrier(CLK_LOCAL_MEM_FENCE);
|
if (tid < 8)
|
{
|
smem1[tid] += smem1[tid + 8];
|
}
|
barrier(CLK_LOCAL_MEM_FENCE);
|
if (tid < 4)
|
{
|
smem1[tid] += smem1[tid + 4];
|
}
|
barrier(CLK_LOCAL_MEM_FENCE);
|
if (tid == 0)
|
{
|
smem1[0] = (smem1[0] + smem1[1]) + (smem1[2] + smem1[3]);
|
}
|
barrier(CLK_LOCAL_MEM_FENCE);
|
}
|
#endif
|
#define SCALE (1.0f / (1 << 20))
|
#define THRESHOLD 0.01f
|
__constant sampler_t sampler = CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP_TO_EDGE | CLK_FILTER_LINEAR;
|
#define VAL(_y,_x,_yy,_xx) (IPatchLocal[mad24(((_y) + (_yy)), LM_W, ((_x) + (_xx)))])
|
inline void SetPatch(local float* IPatchLocal, int TileY, int TileX,
|
float* Pch, float* Dx, float* Dy,
|
float* A11, float* A12, float* A22, float w)
|
{
|
int xid=get_local_id(0);
|
int yid=get_local_id(1);
|
int xBase = mad24(TileX, LSx, (xid + 1));
|
int yBase = mad24(TileY, LSy, (yid + 1));
|
*Pch = VAL(yBase,xBase,0,0);
|
*Dx = mad((VAL(yBase,xBase,-1,1) + VAL(yBase,xBase,+1,1) - VAL(yBase,xBase,-1,-1) - VAL(yBase,xBase,+1,-1)), 3.0f, (VAL(yBase,xBase,0,1) - VAL(yBase,xBase,0,-1)) * 10.0f) * w;
|
*Dy = mad((VAL(yBase,xBase,1,-1) + VAL(yBase,xBase,1,+1) - VAL(yBase,xBase,-1,-1) - VAL(yBase,xBase,-1,+1)), 3.0f, (VAL(yBase,xBase,1,0) - VAL(yBase,xBase,-1,0)) * 10.0f) * w;
|
*A11 = mad(*Dx, *Dx, *A11);
|
*A12 = mad(*Dx, *Dy, *A12);
|
*A22 = mad(*Dy, *Dy, *A22);
|
}
|
#undef VAL
|
inline void GetPatch(image2d_t J, float x, float y,
|
float* Pch, float* Dx, float* Dy,
|
float* b1, float* b2)
|
{
|
float diff = read_imagef(J, sampler, (float2)(x,y)).x-*Pch;
|
*b1 = mad(diff, *Dx, *b1);
|
*b2 = mad(diff, *Dy, *b2);
|
}
|
inline void GetError(image2d_t J, const float x, const float y, const float* Pch, float* errval, float w)
|
{
|
float diff = ((((read_imagef(J, sampler, (float2)(x,y)).x * 16384) + 256) / 512) - (((*Pch * 16384) + 256) /512)) * w;
|
*errval += fabs(diff);
|
}
|
#define READI(_y,_x) IPatchLocal[mad24(mad24((_y), LSy, yid), LM_W, mad24((_x), LSx, xid))] = read_imagef(I, sampler, (float2)(mad((float)(_x), (float)LSx, Point.x + xid - 0.5f), mad((float)(_y), (float)LSy, Point.y + yid - 0.5f))).x;
|
void ReadPatchIToLocalMem(image2d_t I, float2 Point, local float* IPatchLocal)
|
{
|
int xid=get_local_id(0);
|
int yid=get_local_id(1);
|
READI(0,0);READI(0,1);READI(0,2);
|
READI(1,0);READI(1,1);READI(1,2);
|
READI(2,0);READI(2,1);READI(2,2);
|
if(xid<2)
|
{
|
READI(0,3);
|
READI(1,3);
|
READI(2,3);
|
}
|
if(yid<2)
|
{
|
READI(3,0);READI(3,1);READI(3,2);
|
}
|
if(yid<2 && xid<2)
|
{
|
READI(3,3);
|
}
|
barrier(CLK_LOCAL_MEM_FENCE);
|
}
|
#undef READI
|
__attribute__((reqd_work_group_size(LSx, LSy, 1)))
|
__kernel void lkSparse(image2d_t I, image2d_t J,
|
__global const float2* prevPts, __global float2* nextPts, __global uchar* status, __global float* err,
|
const int level, const int rows, const int cols, int PATCH_X, int PATCH_Y, int c_winSize_x, int c_winSize_y, int c_iters, char calcErr)
|
{
|
__local float smem1[BUFFER];
|
__local float smem2[BUFFER];
|
__local float smem3[BUFFER];
|
int xid=get_local_id(0);
|
int yid=get_local_id(1);
|
int gid=get_group_id(0);
|
int xsize=get_local_size(0);
|
int ysize=get_local_size(1);
|
int k;
|
#ifdef CPU
|
float wx0 = 1.0f;
|
float wy0 = 1.0f;
|
int xBase = mad24(xsize, 2, xid);
|
int yBase = mad24(ysize, 2, yid);
|
float wx1 = (xBase < c_winSize_x) ? 1 : 0;
|
float wy1 = (yBase < c_winSize_y) ? 1 : 0;
|
#else
|
#if WSX == 1
|
float wx0 = 1.0f;
|
int xBase = mad24(xsize, 2, xid);
|
float wx1 = (xBase < c_winSize_x) ? 1 : 0;
|
#else
|
int xBase = mad24(xsize, 1, xid);
|
float wx0 = (xBase < c_winSize_x) ? 1 : 0;
|
float wx1 = 0.0f;
|
#endif
|
#if WSY == 1
|
float wy0 = 1.0f;
|
int yBase = mad24(ysize, 2, yid);
|
float wy1 = (yBase < c_winSize_y) ? 1 : 0;
|
#else
|
int yBase = mad24(ysize, 1, yid);
|
float wy0 = (yBase < c_winSize_y) ? 1 : 0;
|
float wy1 = 0.0f;
|
#endif
|
#endif
|
float2 c_halfWin = (float2)((c_winSize_x - 1)>>1, (c_winSize_y - 1)>>1);
|
const int tid = mad24(yid, xsize, xid);
|
float2 prevPt = prevPts[gid] / (float2)(1 << level);
|
if (prevPt.x < 0 || prevPt.x >= cols || prevPt.y < 0 || prevPt.y >= rows)
|
{
|
if (tid == 0 && level == 0)
|
{
|
status[gid] = 0;
|
}
|
return;
|
}
|
prevPt -= c_halfWin;
|
float A11 = 0;
|
float A12 = 0;
|
float A22 = 0;
|
float I_patch[GRIDSIZE][GRIDSIZE];
|
float dIdx_patch[GRIDSIZE][GRIDSIZE];
|
float dIdy_patch[GRIDSIZE][GRIDSIZE];
|
local float IPatchLocal[LM_W*LM_H];
|
ReadPatchIToLocalMem(I,prevPt,IPatchLocal);
|
{
|
SetPatch(IPatchLocal, 0, 0,
|
&I_patch[0][0], &dIdx_patch[0][0], &dIdy_patch[0][0],
|
&A11, &A12, &A22,1);
|
SetPatch(IPatchLocal, 0, 1,
|
&I_patch[0][1], &dIdx_patch[0][1], &dIdy_patch[0][1],
|
&A11, &A12, &A22,wx0);
|
SetPatch(IPatchLocal, 0, 2,
|
&I_patch[0][2], &dIdx_patch[0][2], &dIdy_patch[0][2],
|
&A11, &A12, &A22,wx1);
|
}
|
{
|
SetPatch(IPatchLocal, 1, 0,
|
&I_patch[1][0], &dIdx_patch[1][0], &dIdy_patch[1][0],
|
&A11, &A12, &A22,wy0);
|
SetPatch(IPatchLocal, 1,1,
|
&I_patch[1][1], &dIdx_patch[1][1], &dIdy_patch[1][1],
|
&A11, &A12, &A22,wx0*wy0);
|
SetPatch(IPatchLocal, 1,2,
|
&I_patch[1][2], &dIdx_patch[1][2], &dIdy_patch[1][2],
|
&A11, &A12, &A22,wx1*wy0);
|
}
|
{
|
SetPatch(IPatchLocal, 2,0,
|
&I_patch[2][0], &dIdx_patch[2][0], &dIdy_patch[2][0],
|
&A11, &A12, &A22,wy1);
|
SetPatch(IPatchLocal, 2,1,
|
&I_patch[2][1], &dIdx_patch[2][1], &dIdy_patch[2][1],
|
&A11, &A12, &A22,wx0*wy1);
|
SetPatch(IPatchLocal, 2,2,
|
&I_patch[2][2], &dIdx_patch[2][2], &dIdy_patch[2][2],
|
&A11, &A12, &A22,wx1*wy1);
|
}
|
reduce3(A11, A12, A22, smem1, smem2, smem3, tid);
|
A11 = smem1[0];
|
A12 = smem2[0];
|
A22 = smem3[0];
|
barrier(CLK_LOCAL_MEM_FENCE);
|
float D = mad(A11, A22, - A12 * A12);
|
if (D < 1.192092896e-07f)
|
{
|
if (tid == 0 && level == 0)
|
status[gid] = 0;
|
return;
|
}
|
A11 /= D;
|
A12 /= D;
|
A22 /= D;
|
prevPt = mad(nextPts[gid], 2.0f, - c_halfWin);
|
float2 offset0 = (float2)(xid + 0.5f, yid + 0.5f);
|
float2 offset1 = (float2)(xsize, ysize);
|
float2 loc0 = prevPt + offset0;
|
float2 loc1 = loc0 + offset1;
|
float2 loc2 = loc1 + offset1;
|
for (k = 0; k < c_iters; ++k)
|
{
|
if (prevPt.x < -c_halfWin.x || prevPt.x >= cols || prevPt.y < -c_halfWin.y || prevPt.y >= rows)
|
{
|
if (tid == 0 && level == 0)
|
status[gid] = 0;
|
break;
|
}
|
float b1 = 0;
|
float b2 = 0;
|
{
|
GetPatch(J, loc0.x, loc0.y,
|
&I_patch[0][0], &dIdx_patch[0][0], &dIdy_patch[0][0],
|
&b1, &b2);
|
GetPatch(J, loc1.x, loc0.y,
|
&I_patch[0][1], &dIdx_patch[0][1], &dIdy_patch[0][1],
|
&b1, &b2);
|
GetPatch(J, loc2.x, loc0.y,
|
&I_patch[0][2], &dIdx_patch[0][2], &dIdy_patch[0][2],
|
&b1, &b2);
|
}
|
{
|
GetPatch(J, loc0.x, loc1.y,
|
&I_patch[1][0], &dIdx_patch[1][0], &dIdy_patch[1][0],
|
&b1, &b2);
|
GetPatch(J, loc1.x, loc1.y,
|
&I_patch[1][1], &dIdx_patch[1][1], &dIdy_patch[1][1],
|
&b1, &b2);
|
GetPatch(J, loc2.x, loc1.y,
|
&I_patch[1][2], &dIdx_patch[1][2], &dIdy_patch[1][2],
|
&b1, &b2);
|
}
|
{
|
GetPatch(J, loc0.x, loc2.y,
|
&I_patch[2][0], &dIdx_patch[2][0], &dIdy_patch[2][0],
|
&b1, &b2);
|
GetPatch(J, loc1.x, loc2.y,
|
&I_patch[2][1], &dIdx_patch[2][1], &dIdy_patch[2][1],
|
&b1, &b2);
|
GetPatch(J, loc2.x, loc2.y,
|
&I_patch[2][2], &dIdx_patch[2][2], &dIdy_patch[2][2],
|
&b1, &b2);
|
}
|
reduce2(b1, b2, smem1, smem2, tid);
|
b1 = smem1[0];
|
b2 = smem2[0];
|
barrier(CLK_LOCAL_MEM_FENCE);
|
float2 delta;
|
delta.x = mad(A12, b2, - A22 * b1) * 32.0f;
|
delta.y = mad(A12, b1, - A11 * b2) * 32.0f;
|
prevPt += delta;
|
loc0 += delta;
|
loc1 += delta;
|
loc2 += delta;
|
if (fabs(delta.x) < THRESHOLD && fabs(delta.y) < THRESHOLD)
|
break;
|
}
|
D = 0.0f;
|
if (calcErr)
|
{
|
{
|
GetError(J, loc0.x, loc0.y, &I_patch[0][0], &D, 1);
|
GetError(J, loc1.x, loc0.y, &I_patch[0][1], &D, wx0);
|
}
|
{
|
GetError(J, loc0.x, loc1.y, &I_patch[1][0], &D, wy0);
|
GetError(J, loc1.x, loc1.y, &I_patch[1][1], &D, wx0*wy0);
|
}
|
if(xBase < c_winSize_x)
|
{
|
GetError(J, loc2.x, loc0.y, &I_patch[0][2], &D, wx1);
|
GetError(J, loc2.x, loc1.y, &I_patch[1][2], &D, wx1*wy0);
|
}
|
if(yBase < c_winSize_y)
|
{
|
GetError(J, loc0.x, loc2.y, &I_patch[2][0], &D, wy1);
|
GetError(J, loc1.x, loc2.y, &I_patch[2][1], &D, wx0*wy1);
|
if(xBase < c_winSize_x)
|
GetError(J, loc2.x, loc2.y, &I_patch[2][2], &D, wx1*wy1);
|
}
|
reduce1(D, smem1, tid);
|
}
|
if (tid == 0)
|
{
|
prevPt += c_halfWin;
|
nextPts[gid] = prevPt;
|
if (calcErr)
|
err[gid] = smem1[0] / (float)(32 * c_winSize_x * c_winSize_y);
|
}
|
}
|
fa578a4fdcd31c3e32eedab3e323ac05 #define tx (int)get_local_id(0)
|
#define ty get_local_id(1)
|
#define bx get_group_id(0)
|
#define bdx (int)get_local_size(0)
|
#define BORDER_SIZE 5
|
#define MAX_KSIZE_HALF 100
|
#ifndef polyN
|
#define polyN 5
|
#endif
|
#if USE_DOUBLE
|
#ifdef cl_amd_fp64
|
#pragma OPENCL EXTENSION cl_amd_fp64:enable
|
#elif defined (cl_khr_fp64)
|
#pragma OPENCL EXTENSION cl_khr_fp64:enable
|
#endif
|
#define TYPE double
|
#define VECTYPE double4
|
#else
|
#define TYPE float
|
#define VECTYPE float4
|
#endif
|
__kernel void polynomialExpansion(__global __const float * src, int srcStep,
|
__global float * dst, int dstStep,
|
const int rows, const int cols,
|
__global __const float * c_g,
|
__global __const float * c_xg,
|
__global __const float * c_xxg,
|
__local float * smem,
|
const VECTYPE ig)
|
{
|
const int y = get_global_id(1);
|
const int x = bx * (bdx - 2*polyN) + tx - polyN;
|
int xWarped;
|
__local float *row = smem + tx;
|
if (y < rows && y >= 0)
|
{
|
xWarped = min(max(x, 0), cols - 1);
|
row[0] = src[mad24(y, srcStep, xWarped)] * c_g[0];
|
row[bdx] = 0.f;
|
row[2*bdx] = 0.f;
|
#pragma unroll
|
for (int k = 1; k <= polyN; ++k)
|
{
|
float t0 = src[mad24(max(y - k, 0), srcStep, xWarped)];
|
float t1 = src[mad24(min(y + k, rows - 1), srcStep, xWarped)];
|
row[0] += c_g[k] * (t0 + t1);
|
row[bdx] += c_xg[k] * (t1 - t0);
|
row[2*bdx] += c_xxg[k] * (t0 + t1);
|
}
|
}
|
barrier(CLK_LOCAL_MEM_FENCE);
|
if (y < rows && y >= 0 && tx >= polyN && tx + polyN < bdx && x < cols)
|
{
|
TYPE b1 = c_g[0] * row[0];
|
TYPE b3 = c_g[0] * row[bdx];
|
TYPE b5 = c_g[0] * row[2*bdx];
|
TYPE b2 = 0, b4 = 0, b6 = 0;
|
#pragma unroll
|
for (int k = 1; k <= polyN; ++k)
|
{
|
b1 += (row[k] + row[-k]) * c_g[k];
|
b4 += (row[k] + row[-k]) * c_xxg[k];
|
b2 += (row[k] - row[-k]) * c_xg[k];
|
b3 += (row[k + bdx] + row[-k + bdx]) * c_g[k];
|
b6 += (row[k + bdx] - row[-k + bdx]) * c_xg[k];
|
b5 += (row[k + 2*bdx] + row[-k + 2*bdx]) * c_g[k];
|
}
|
dst[mad24(y, dstStep, xWarped)] = (float)(b3*ig.s0);
|
dst[mad24(rows + y, dstStep, xWarped)] = (float)(b2*ig.s0);
|
dst[mad24(2*rows + y, dstStep, xWarped)] = (float)(b1*ig.s1 + b5*ig.s2);
|
dst[mad24(3*rows + y, dstStep, xWarped)] = (float)(b1*ig.s1 + b4*ig.s2);
|
dst[mad24(4*rows + y, dstStep, xWarped)] = (float)(b6*ig.s3);
|
}
|
}
|
inline int idx_row_low(const int y, const int last_row)
|
{
|
return abs(y) % (last_row + 1);
|
}
|
inline int idx_row_high(const int y, const int last_row)
|
{
|
return abs(last_row - abs(last_row - y)) % (last_row + 1);
|
}
|
inline int idx_col_low(const int x, const int last_col)
|
{
|
return abs(x) % (last_col + 1);
|
}
|
inline int idx_col_high(const int x, const int last_col)
|
{
|
return abs(last_col - abs(last_col - x)) % (last_col + 1);
|
}
|
inline int idx_col(const int x, const int last_col)
|
{
|
return idx_col_low(idx_col_high(x, last_col), last_col);
|
}
|
__kernel void gaussianBlur(__global const float * src, int srcStep,
|
__global float * dst, int dstStep, const int rows, const int cols,
|
__global const float * c_gKer, const int ksizeHalf,
|
__local float * smem)
|
{
|
const int y = get_global_id(1);
|
const int x = get_global_id(0);
|
__local float *row = smem + ty * (bdx + 2*ksizeHalf);
|
if (y < rows)
|
{
|
for (int i = tx; i < bdx + 2*ksizeHalf; i += bdx)
|
{
|
int xExt = (int)(bx * bdx) + i - ksizeHalf;
|
xExt = idx_col(xExt, cols - 1);
|
row[i] = src[mad24(y, srcStep, xExt)] * c_gKer[0];
|
for (int j = 1; j <= ksizeHalf; ++j)
|
row[i] += (src[mad24(idx_row_low(y - j, rows - 1), srcStep, xExt)]
|
+ src[mad24(idx_row_high(y + j, rows - 1), srcStep, xExt)]) * c_gKer[j];
|
}
|
}
|
barrier(CLK_LOCAL_MEM_FENCE);
|
if (y < rows && y >= 0 && x < cols && x >= 0)
|
{
|
row += tx + ksizeHalf;
|
float res = row[0] * c_gKer[0];
|
for (int i = 1; i <= ksizeHalf; ++i)
|
res += (row[-i] + row[i]) * c_gKer[i];
|
dst[mad24(y, dstStep, x)] = res;
|
}
|
}
|
__kernel void gaussianBlur5(__global const float * src, int srcStep,
|
__global float * dst, int dstStep,
|
const int rows, const int cols,
|
__global const float * c_gKer, const int ksizeHalf,
|
__local float * smem)
|
{
|
const int y = get_global_id(1);
|
const int x = get_global_id(0);
|
const int smw = bdx + 2*ksizeHalf;
|
__local volatile float *row = smem + 5 * ty * smw;
|
if (y < rows)
|
{
|
for (int i = tx; i < bdx + 2*ksizeHalf; i += bdx)
|
{
|
int xExt = (int)(bx * bdx) + i - ksizeHalf;
|
xExt = idx_col(xExt, cols - 1);
|
#pragma unroll
|
for (int k = 0; k < 5; ++k)
|
row[k*smw + i] = src[mad24(k*rows + y, srcStep, xExt)] * c_gKer[0];
|
for (int j = 1; j <= ksizeHalf; ++j)
|
#pragma unroll
|
for (int k = 0; k < 5; ++k)
|
row[k*smw + i] +=
|
(src[mad24(k*rows + idx_row_low(y - j, rows - 1), srcStep, xExt)] +
|
src[mad24(k*rows + idx_row_high(y + j, rows - 1), srcStep, xExt)]) * c_gKer[j];
|
}
|
}
|
barrier(CLK_LOCAL_MEM_FENCE);
|
if (y < rows && y >= 0 && x < cols && x >= 0)
|
{
|
row += tx + ksizeHalf;
|
float res[5];
|
#pragma unroll
|
for (int k = 0; k < 5; ++k)
|
res[k] = row[k*smw] * c_gKer[0];
|
for (int i = 1; i <= ksizeHalf; ++i)
|
#pragma unroll
|
for (int k = 0; k < 5; ++k)
|
res[k] += (row[k*smw - i] + row[k*smw + i]) * c_gKer[i];
|
#pragma unroll
|
for (int k = 0; k < 5; ++k)
|
dst[mad24(k*rows + y, dstStep, x)] = res[k];
|
}
|
}
|
__constant float c_border[BORDER_SIZE + 1] = { 0.14f, 0.14f, 0.4472f, 0.4472f, 0.4472f, 1.f };
|
__kernel void updateMatrices(__global const float * flowx, int xStep,
|
__global const float * flowy, int yStep,
|
const int rows, const int cols,
|
__global const float * R0, int R0Step,
|
__global const float * R1, int R1Step,
|
__global float * M, int mStep)
|
{
|
const int y = get_global_id(1);
|
const int x = get_global_id(0);
|
if (y < rows && y >= 0 && x < cols && x >= 0)
|
{
|
float dx = flowx[mad24(y, xStep, x)];
|
float dy = flowy[mad24(y, yStep, x)];
|
float fx = x + dx;
|
float fy = y + dy;
|
int x1 = convert_int(floor(fx));
|
int y1 = convert_int(floor(fy));
|
fx -= x1;
|
fy -= y1;
|
float r2, r3, r4, r5, r6;
|
if (x1 >= 0 && y1 >= 0 && x1 < cols - 1 && y1 < rows - 1)
|
{
|
float a00 = (1.f - fx) * (1.f - fy);
|
float a01 = fx * (1.f - fy);
|
float a10 = (1.f - fx) * fy;
|
float a11 = fx * fy;
|
r2 = a00 * R1[mad24(y1, R1Step, x1)] +
|
a01 * R1[mad24(y1, R1Step, x1 + 1)] +
|
a10 * R1[mad24(y1 + 1, R1Step, x1)] +
|
a11 * R1[mad24(y1 + 1, R1Step, x1 + 1)];
|
r3 = a00 * R1[mad24(rows + y1, R1Step, x1)] +
|
a01 * R1[mad24(rows + y1, R1Step, x1 + 1)] +
|
a10 * R1[mad24(rows + y1 + 1, R1Step, x1)] +
|
a11 * R1[mad24(rows + y1 + 1, R1Step, x1 + 1)];
|
r4 = a00 * R1[mad24(2*rows + y1, R1Step, x1)] +
|
a01 * R1[mad24(2*rows + y1, R1Step, x1 + 1)] +
|
a10 * R1[mad24(2*rows + y1 + 1, R1Step, x1)] +
|
a11 * R1[mad24(2*rows + y1 + 1, R1Step, x1 + 1)];
|
r5 = a00 * R1[mad24(3*rows + y1, R1Step, x1)] +
|
a01 * R1[mad24(3*rows + y1, R1Step, x1 + 1)] +
|
a10 * R1[mad24(3*rows + y1 + 1, R1Step, x1)] +
|
a11 * R1[mad24(3*rows + y1 + 1, R1Step, x1 + 1)];
|
r6 = a00 * R1[mad24(4*rows + y1, R1Step, x1)] +
|
a01 * R1[mad24(4*rows + y1, R1Step, x1 + 1)] +
|
a10 * R1[mad24(4*rows + y1 + 1, R1Step, x1)] +
|
a11 * R1[mad24(4*rows + y1 + 1, R1Step, x1 + 1)];
|
r4 = (R0[mad24(2*rows + y, R0Step, x)] + r4) * 0.5f;
|
r5 = (R0[mad24(3*rows + y, R0Step, x)] + r5) * 0.5f;
|
r6 = (R0[mad24(4*rows + y, R0Step, x)] + r6) * 0.25f;
|
}
|
else
|
{
|
r2 = r3 = 0.f;
|
r4 = R0[mad24(2*rows + y, R0Step, x)];
|
r5 = R0[mad24(3*rows + y, R0Step, x)];
|
r6 = R0[mad24(4*rows + y, R0Step, x)] * 0.5f;
|
}
|
r2 = (R0[mad24(y, R0Step, x)] - r2) * 0.5f;
|
r3 = (R0[mad24(rows + y, R0Step, x)] - r3) * 0.5f;
|
r2 += r4*dy + r6*dx;
|
r3 += r6*dy + r5*dx;
|
float scale =
|
c_border[min(x, BORDER_SIZE)] *
|
c_border[min(y, BORDER_SIZE)] *
|
c_border[min(cols - x - 1, BORDER_SIZE)] *
|
c_border[min(rows - y - 1, BORDER_SIZE)];
|
r2 *= scale;
|
r3 *= scale;
|
r4 *= scale;
|
r5 *= scale;
|
r6 *= scale;
|
M[mad24(y, mStep, x)] = r4*r4 + r6*r6;
|
M[mad24(rows + y, mStep, x)] = (r4 + r5)*r6;
|
M[mad24(2*rows + y, mStep, x)] = r5*r5 + r6*r6;
|
M[mad24(3*rows + y, mStep, x)] = r4*r2 + r6*r3;
|
M[mad24(4*rows + y, mStep, x)] = r6*r2 + r5*r3;
|
}
|
}
|
__kernel void boxFilter5(__global const float * src, int srcStep,
|
__global float * dst, int dstStep,
|
const int rows, const int cols,
|
const int ksizeHalf,
|
__local float * smem)
|
{
|
const int y = get_global_id(1);
|
const int x = get_global_id(0);
|
const float boxAreaInv = 1.f / ((1 + 2*ksizeHalf) * (1 + 2*ksizeHalf));
|
const int smw = bdx + 2*ksizeHalf;
|
__local float *row = smem + 5 * ty * smw;
|
if (y < rows)
|
{
|
for (int i = tx; i < bdx + 2*ksizeHalf; i += bdx)
|
{
|
int xExt = (int)(bx * bdx) + i - ksizeHalf;
|
xExt = min(max(xExt, 0), cols - 1);
|
#pragma unroll
|
for (int k = 0; k < 5; ++k)
|
row[k*smw + i] = src[mad24(k*rows + y, srcStep, xExt)];
|
for (int j = 1; j <= ksizeHalf; ++j)
|
#pragma unroll
|
for (int k = 0; k < 5; ++k)
|
row[k*smw + i] +=
|
src[mad24(k*rows + max(y - j, 0), srcStep, xExt)] +
|
src[mad24(k*rows + min(y + j, rows - 1), srcStep, xExt)];
|
}
|
}
|
barrier(CLK_LOCAL_MEM_FENCE);
|
if (y < rows && y >= 0 && x < cols && x >= 0)
|
{
|
row += tx + ksizeHalf;
|
float res[5];
|
#pragma unroll
|
for (int k = 0; k < 5; ++k)
|
res[k] = row[k*smw];
|
for (int i = 1; i <= ksizeHalf; ++i)
|
#pragma unroll
|
for (int k = 0; k < 5; ++k)
|
res[k] += row[k*smw - i] + row[k*smw + i];
|
#pragma unroll
|
for (int k = 0; k < 5; ++k)
|
dst[mad24(k*rows + y, dstStep, x)] = res[k] * boxAreaInv;
|
}
|
}
|
__kernel void updateFlow(__global const float * M, int mStep,
|
__global float * flowx, int xStep,
|
__global float * flowy, int yStep,
|
const int rows, const int cols)
|
{
|
const int y = get_global_id(1);
|
const int x = get_global_id(0);
|
if (y < rows && y >= 0 && x < cols && x >= 0)
|
{
|
float g11 = M[mad24(y, mStep, x)];
|
float g12 = M[mad24(rows + y, mStep, x)];
|
float g22 = M[mad24(2*rows + y, mStep, x)];
|
float h1 = M[mad24(3*rows + y, mStep, x)];
|
float h2 = M[mad24(4*rows + y, mStep, x)];
|
float detInv = 1.f / (g11*g22 - g12*g12 + 1e-3f);
|
flowx[mad24(y, xStep, x)] = (g11*h2 - g12*h1) * detInv;
|
flowy[mad24(y, yStep, x)] = (g22*h1 - g12*h2) * detInv;
|
}
|
}
|
529300e6242f574f83d11a089cc120c0 #define EPS 0.001f
|
#define INF 1E+10F
|
__kernel void dis_precomputeStructureTensor_hor(__global const short *I0x,
|
__global const short *I0y,
|
int patch_size, int patch_stride,
|
int w, int h, int ws,
|
__global float *I0xx_aux_ptr,
|
__global float *I0yy_aux_ptr,
|
__global float *I0xy_aux_ptr,
|
__global float *I0x_aux_ptr,
|
__global float *I0y_aux_ptr)
|
{
|
int i = get_global_id(0);
|
if (i >= h) return;
|
const __global short *x_row = I0x + i * w;
|
const __global short *y_row = I0y + i * w;
|
float sum_xx = 0.0f, sum_yy = 0.0f, sum_xy = 0.0f, sum_x = 0.0f, sum_y = 0.0f;
|
float8 x_vec = convert_float8(vload8(0, x_row));
|
float8 y_vec = convert_float8(vload8(0, y_row));
|
sum_xx = dot(x_vec.lo, x_vec.lo) + dot(x_vec.hi, x_vec.hi);
|
sum_yy = dot(y_vec.lo, y_vec.lo) + dot(y_vec.hi, y_vec.hi);
|
sum_xy = dot(x_vec.lo, y_vec.lo) + dot(x_vec.hi, y_vec.hi);
|
sum_x = dot(x_vec.lo, 1.0f) + dot(x_vec.hi, 1.0f);
|
sum_y = dot(y_vec.lo, 1.0f) + dot(y_vec.hi, 1.0f);
|
I0xx_aux_ptr[i * ws] = sum_xx;
|
I0yy_aux_ptr[i * ws] = sum_yy;
|
I0xy_aux_ptr[i * ws] = sum_xy;
|
I0x_aux_ptr[i * ws] = sum_x;
|
I0y_aux_ptr[i * ws] = sum_y;
|
int js = 1;
|
for (int j = patch_size; j < w; j++)
|
{
|
short x_val1 = x_row[j];
|
short x_val2 = x_row[j - patch_size];
|
short y_val1 = y_row[j];
|
short y_val2 = y_row[j - patch_size];
|
sum_xx += (x_val1 * x_val1 - x_val2 * x_val2);
|
sum_yy += (y_val1 * y_val1 - y_val2 * y_val2);
|
sum_xy += (x_val1 * y_val1 - x_val2 * y_val2);
|
sum_x += (x_val1 - x_val2);
|
sum_y += (y_val1 - y_val2);
|
if ((j - patch_size + 1) % patch_stride == 0)
|
{
|
int index = i * ws + js;
|
I0xx_aux_ptr[index] = sum_xx;
|
I0yy_aux_ptr[index] = sum_yy;
|
I0xy_aux_ptr[index] = sum_xy;
|
I0x_aux_ptr[index] = sum_x;
|
I0y_aux_ptr[index] = sum_y;
|
js++;
|
}
|
}
|
}
|
__kernel void dis_precomputeStructureTensor_ver(__global const float *I0xx_aux_ptr,
|
__global const float *I0yy_aux_ptr,
|
__global const float *I0xy_aux_ptr,
|
__global const float *I0x_aux_ptr,
|
__global const float *I0y_aux_ptr,
|
int patch_size, int patch_stride,
|
int w, int h, int ws,
|
__global float *I0xx_ptr,
|
__global float *I0yy_ptr,
|
__global float *I0xy_ptr,
|
__global float *I0x_ptr,
|
__global float *I0y_ptr)
|
{
|
int j = get_global_id(0);
|
if (j >= ws) return;
|
float sum_xx, sum_yy, sum_xy, sum_x, sum_y;
|
sum_xx = sum_yy = sum_xy = sum_x = sum_y = 0.0f;
|
for (int i = 0; i < patch_size; i++)
|
{
|
sum_xx += I0xx_aux_ptr[i * ws + j];
|
sum_yy += I0yy_aux_ptr[i * ws + j];
|
sum_xy += I0xy_aux_ptr[i * ws + j];
|
sum_x += I0x_aux_ptr[i * ws + j];
|
sum_y += I0y_aux_ptr[i * ws + j];
|
}
|
I0xx_ptr[j] = sum_xx;
|
I0yy_ptr[j] = sum_yy;
|
I0xy_ptr[j] = sum_xy;
|
I0x_ptr[j] = sum_x;
|
I0y_ptr[j] = sum_y;
|
int is = 1;
|
for (int i = patch_size; i < h; i++)
|
{
|
sum_xx += (I0xx_aux_ptr[i * ws + j] - I0xx_aux_ptr[(i - patch_size) * ws + j]);
|
sum_yy += (I0yy_aux_ptr[i * ws + j] - I0yy_aux_ptr[(i - patch_size) * ws + j]);
|
sum_xy += (I0xy_aux_ptr[i * ws + j] - I0xy_aux_ptr[(i - patch_size) * ws + j]);
|
sum_x += (I0x_aux_ptr[i * ws + j] - I0x_aux_ptr[(i - patch_size) * ws + j]);
|
sum_y += (I0y_aux_ptr[i * ws + j] - I0y_aux_ptr[(i - patch_size) * ws + j]);
|
if ((i - patch_size + 1) % patch_stride == 0)
|
{
|
I0xx_ptr[is * ws + j] = sum_xx;
|
I0yy_ptr[is * ws + j] = sum_yy;
|
I0xy_ptr[is * ws + j] = sum_xy;
|
I0x_ptr[is * ws + j] = sum_x;
|
I0y_ptr[is * ws + j] = sum_y;
|
is++;
|
}
|
}
|
}
|
__kernel void dis_densification(__global const float *sx, __global const float *sy,
|
__global const uchar *i0, __global const uchar *i1,
|
int psz, int pstr,
|
int w, int h, int ws,
|
__global float *ux, __global float *uy)
|
{
|
int x = get_global_id(0);
|
int y = get_global_id(1);
|
int i, j;
|
if (x >= w || y >= h) return;
|
int start_is, end_is;
|
int start_js, end_js;
|
end_is = min(y / pstr, (h - psz) / pstr);
|
start_is = max(0, y - psz + pstr) / pstr;
|
start_is = min(start_is, end_is);
|
end_js = min(x / pstr, (w - psz) / pstr);
|
start_js = max(0, x - psz + pstr) / pstr;
|
start_js = min(start_js, end_js);
|
float coef, sum_coef = 0.0f;
|
float sum_Ux = 0.0f;
|
float sum_Uy = 0.0f;
|
int i_l, i_u;
|
int j_l, j_u;
|
float i_m, j_m, diff;
|
i = y;
|
j = x;
|
for (int is = start_is; is <= end_is; is++)
|
for (int js = start_js; js <= end_js; js++)
|
{
|
float sx_val = sx[is * ws + js];
|
float sy_val = sy[is * ws + js];
|
uchar2 i1_vec1, i1_vec2;
|
j_m = min(max(j + sx_val, 0.0f), w - 1.0f - EPS);
|
i_m = min(max(i + sy_val, 0.0f), h - 1.0f - EPS);
|
j_l = (int)j_m;
|
j_u = j_l + 1;
|
i_l = (int)i_m;
|
i_u = i_l + 1;
|
i1_vec1 = vload2(0, i1 + i_u * w + j_l);
|
i1_vec2 = vload2(0, i1 + i_l * w + j_l);
|
diff = (j_m - j_l) * (i_m - i_l) * i1_vec1.y +
|
(j_u - j_m) * (i_m - i_l) * i1_vec1.x +
|
(j_m - j_l) * (i_u - i_m) * i1_vec2.y +
|
(j_u - j_m) * (i_u - i_m) * i1_vec2.x - i0[i * w + j];
|
coef = 1 / max(1.0f, fabs(diff));
|
sum_Ux += coef * sx_val;
|
sum_Uy += coef * sy_val;
|
sum_coef += coef;
|
}
|
ux[i * w + j] = sum_Ux / sum_coef;
|
uy[i * w + j] = sum_Uy / sum_coef;
|
}
|
#define INIT_BILINEAR_WEIGHTS(Ux, Uy) \
|
i_I1 = min(max(i + Uy + bsz, i_lower_limit), i_upper_limit); \
|
j_I1 = min(max(j + Ux + bsz, j_lower_limit), j_upper_limit); \
|
\
|
w11 = (i_I1 - floor(i_I1)) * (j_I1 - floor(j_I1)); \
|
w10 = (i_I1 - floor(i_I1)) * (floor(j_I1) + 1 - j_I1); \
|
w01 = (floor(i_I1) + 1 - i_I1) * (j_I1 - floor(j_I1)); \
|
w00 = (floor(i_I1) + 1 - i_I1) * (floor(j_I1) + 1 - j_I1);
|
float computeSSDMeanNorm(const __global uchar *I0_ptr, const __global uchar *I1_ptr,
|
int I0_stride, int I1_stride,
|
float w00, float w01, float w10, float w11, int patch_sz, int i)
|
{
|
float sum_diff = 0.0f, sum_diff_sq = 0.0f;
|
int n = patch_sz * patch_sz;
|
uchar8 I1_vec1, I1_vec2, I0_vec;
|
uchar I1_val1, I1_val2;
|
I0_vec = vload8(0, I0_ptr + i * I0_stride);
|
I1_vec1 = vload8(0, I1_ptr + i * I1_stride);
|
I1_vec2 = vload8(0, I1_ptr + (i + 1) * I1_stride);
|
I1_val1 = I1_ptr[i * I1_stride + 8];
|
I1_val2 = I1_ptr[(i + 1) * I1_stride + 8];
|
float8 vec = w00 * convert_float8(I1_vec1) + w01 * convert_float8((uchar8)(I1_vec1.s123, I1_vec1.s4567, I1_val1)) +
|
w10 * convert_float8(I1_vec2) + w11 * convert_float8((uchar8)(I1_vec2.s123, I1_vec2.s4567, I1_val2)) -
|
convert_float8(I0_vec);
|
sum_diff = (dot(vec.lo, 1.0) + dot(vec.hi, 1.0));
|
sum_diff_sq = (dot(vec.lo, vec.lo) + dot(vec.hi, vec.hi));
|
sum_diff = sub_group_reduce_add(sum_diff);
|
sum_diff_sq = sub_group_reduce_add(sum_diff_sq);
|
return sum_diff_sq - sum_diff * sum_diff / n;
|
}
|
__kernel void dis_patch_inverse_search_fwd_1(__global const float *Ux_ptr, __global const float *Uy_ptr,
|
__global const uchar *I0_ptr, __global const uchar *I1_ptr,
|
int border_size, int patch_size, int patch_stride,
|
int w, int h, int ws, int hs, int pyr_level,
|
__global float *Sx_ptr, __global float *Sy_ptr)
|
{
|
int id = get_global_id(0);
|
int is = id / 8;
|
if (id >= (hs * 8)) return;
|
int i = is * patch_stride;
|
int j = 0;
|
int psz = patch_size;
|
int psz2 = psz / 2;
|
int w_ext = w + 2 * border_size;
|
int bsz = border_size;
|
float i_lower_limit = bsz - psz + 1.0f;
|
float i_upper_limit = bsz + h - 1.0f;
|
float j_lower_limit = bsz - psz + 1.0f;
|
float j_upper_limit = bsz + w - 1.0f;
|
float i_I1, j_I1, w00, w01, w10, w11;
|
float prev_Ux = Ux_ptr[(i + psz2) * w + j + psz2];
|
float prev_Uy = Uy_ptr[(i + psz2) * w + j + psz2];
|
Sx_ptr[is * ws] = prev_Ux;
|
Sy_ptr[is * ws] = prev_Uy;
|
j += patch_stride;
|
int sid = get_sub_group_local_id();
|
for (int js = 1; js < ws; js++, j += patch_stride)
|
{
|
float min_SSD, cur_SSD;
|
float Ux = Ux_ptr[(i + psz2) * w + j + psz2];
|
float Uy = Uy_ptr[(i + psz2) * w + j + psz2];
|
INIT_BILINEAR_WEIGHTS(Ux, Uy);
|
min_SSD = computeSSDMeanNorm(I0_ptr + i * w + j, I1_ptr + (int)i_I1 * w_ext + (int)j_I1,
|
w, w_ext, w00, w01, w10, w11, psz, sid);
|
INIT_BILINEAR_WEIGHTS(prev_Ux, prev_Uy);
|
cur_SSD = computeSSDMeanNorm(I0_ptr + i * w + j, I1_ptr + (int)i_I1 * w_ext + (int)j_I1,
|
w, w_ext, w00, w01, w10, w11, psz, sid);
|
if (cur_SSD < min_SSD)
|
{
|
Ux = prev_Ux;
|
Uy = prev_Uy;
|
}
|
prev_Ux = Ux;
|
prev_Uy = Uy;
|
Sx_ptr[is * ws + js] = Ux;
|
Sy_ptr[is * ws + js] = Uy;
|
}
|
}
|
float3 processPatchMeanNorm(const __global uchar *I0_ptr, const __global uchar *I1_ptr,
|
const __global short *I0x_ptr, const __global short *I0y_ptr,
|
int I0_stride, int I1_stride, float w00, float w01, float w10,
|
float w11, int patch_sz, float x_grad_sum, float y_grad_sum)
|
{
|
float sum_diff = 0.0, sum_diff_sq = 0.0;
|
float sum_I0x_mul = 0.0, sum_I0y_mul = 0.0;
|
int n = patch_sz * patch_sz;
|
uchar8 I1_vec1, I1_vec2;
|
uchar I1_val1, I1_val2;
|
for (int i = 0; i < 8; i++)
|
{
|
uchar8 I0_vec = vload8(0, I0_ptr + i * I0_stride);
|
I1_vec1 = (i == 0) ? vload8(0, I1_ptr + i * I1_stride) : I1_vec2;
|
I1_vec2 = vload8(0, I1_ptr + (i + 1) * I1_stride);
|
I1_val1 = (i == 0) ? I1_ptr[i * I1_stride + patch_sz] : I1_val2;
|
I1_val2 = I1_ptr[(i + 1) * I1_stride + patch_sz];
|
float8 vec = w00 * convert_float8(I1_vec1) + w01 * convert_float8((uchar8)(I1_vec1.s123, I1_vec1.s4567, I1_val1)) +
|
w10 * convert_float8(I1_vec2) + w11 * convert_float8((uchar8)(I1_vec2.s123, I1_vec2.s4567, I1_val2)) -
|
convert_float8(I0_vec);
|
sum_diff += (dot(vec.lo, 1.0) + dot(vec.hi, 1.0));
|
sum_diff_sq += (dot(vec.lo, vec.lo) + dot(vec.hi, vec.hi));
|
short8 I0x_vec = vload8(0, I0x_ptr + i * I0_stride);
|
short8 I0y_vec = vload8(0, I0y_ptr + i * I0_stride);
|
sum_I0x_mul += dot(vec.lo, convert_float4(I0x_vec.lo));
|
sum_I0x_mul += dot(vec.hi, convert_float4(I0x_vec.hi));
|
sum_I0y_mul += dot(vec.lo, convert_float4(I0y_vec.lo));
|
sum_I0y_mul += dot(vec.hi, convert_float4(I0y_vec.hi));
|
}
|
float dst_dUx = sum_I0x_mul - sum_diff * x_grad_sum / n;
|
float dst_dUy = sum_I0y_mul - sum_diff * y_grad_sum / n;
|
float SSD = sum_diff_sq - sum_diff * sum_diff / n;
|
return (float3)(SSD, dst_dUx, dst_dUy);
|
}
|
__kernel void dis_patch_inverse_search_fwd_2(__global const float *Ux_ptr, __global const float *Uy_ptr,
|
__global const uchar *I0_ptr, __global const uchar *I1_ptr,
|
__global const short *I0x_ptr, __global const short *I0y_ptr,
|
__global const float *xx_ptr, __global const float *yy_ptr,
|
__global const float *xy_ptr,
|
__global const float *x_ptr, __global const float *y_ptr,
|
int border_size, int patch_size, int patch_stride,
|
int w, int h, int ws, int hs, int num_inner_iter, int pyr_level,
|
__global float *Sx_ptr, __global float *Sy_ptr)
|
{
|
int js = get_global_id(0);
|
int is = get_global_id(1);
|
int i = is * patch_stride;
|
int j = js * patch_stride;
|
int psz = patch_size;
|
int psz2 = psz / 2;
|
int w_ext = w + 2 * border_size;
|
int bsz = border_size;
|
int index = is * ws + js;
|
if (js >= ws || is >= hs) return;
|
float Ux = Sx_ptr[index];
|
float Uy = Sy_ptr[index];
|
float cur_Ux = Ux;
|
float cur_Uy = Uy;
|
float cur_xx = xx_ptr[index];
|
float cur_yy = yy_ptr[index];
|
float cur_xy = xy_ptr[index];
|
float detH = cur_xx * cur_yy - cur_xy * cur_xy;
|
if (fabs(detH) < EPS) detH = EPS;
|
float invH11 = cur_yy / detH;
|
float invH12 = -cur_xy / detH;
|
float invH22 = cur_xx / detH;
|
float prev_SSD = INF, SSD;
|
float x_grad_sum = x_ptr[index];
|
float y_grad_sum = y_ptr[index];
|
float i_lower_limit = bsz - psz + 1.0f;
|
float i_upper_limit = bsz + h - 1.0f;
|
float j_lower_limit = bsz - psz + 1.0f;
|
float j_upper_limit = bsz + w - 1.0f;
|
float dUx, dUy, i_I1, j_I1, w00, w01, w10, w11, dx, dy;
|
float3 res;
|
for (int t = 0; t < num_inner_iter; t++)
|
{
|
INIT_BILINEAR_WEIGHTS(cur_Ux, cur_Uy);
|
res = processPatchMeanNorm(I0_ptr + i * w + j,
|
I1_ptr + (int)i_I1 * w_ext + (int)j_I1, I0x_ptr + i * w + j,
|
I0y_ptr + i * w + j, w, w_ext, w00, w01, w10, w11, psz,
|
x_grad_sum, y_grad_sum);
|
SSD = res.x;
|
dUx = res.y;
|
dUy = res.z;
|
dx = invH11 * dUx + invH12 * dUy;
|
dy = invH12 * dUx + invH22 * dUy;
|
cur_Ux -= dx;
|
cur_Uy -= dy;
|
if (SSD >= prev_SSD)
|
break;
|
prev_SSD = SSD;
|
}
|
float2 vec = (float2)(cur_Ux - Ux, cur_Uy - Uy);
|
if (dot(vec, vec) <= (float)(psz * psz))
|
{
|
Sx_ptr[index] = cur_Ux;
|
Sy_ptr[index] = cur_Uy;
|
}
|
}
|
__kernel void dis_patch_inverse_search_bwd_1(__global const uchar *I0_ptr, __global const uchar *I1_ptr,
|
int border_size, int patch_size, int patch_stride,
|
int w, int h, int ws, int hs, int pyr_level,
|
__global float *Sx_ptr, __global float *Sy_ptr)
|
{
|
int id = get_global_id(0);
|
int is = id / 8;
|
if (id >= (hs * 8)) return;
|
is = (hs - 1 - is);
|
int i = is * patch_stride;
|
int j = (ws - 2) * patch_stride;
|
int psz = patch_size;
|
int psz2 = psz / 2;
|
int w_ext = w + 2 * border_size;
|
int bsz = border_size;
|
float i_lower_limit = bsz - psz + 1.0f;
|
float i_upper_limit = bsz + h - 1.0f;
|
float j_lower_limit = bsz - psz + 1.0f;
|
float j_upper_limit = bsz + w - 1.0f;
|
float i_I1, j_I1, w00, w01, w10, w11;
|
int sid = get_sub_group_local_id();
|
for (int js = (ws - 2); js > -1; js--, j -= patch_stride)
|
{
|
float min_SSD, cur_SSD;
|
float2 Ux = vload2(0, Sx_ptr + is * ws + js);
|
float2 Uy = vload2(0, Sy_ptr + is * ws + js);
|
INIT_BILINEAR_WEIGHTS(Ux.x, Uy.x);
|
min_SSD = computeSSDMeanNorm(I0_ptr + i * w + j, I1_ptr + (int)i_I1 * w_ext + (int)j_I1,
|
w, w_ext, w00, w01, w10, w11, psz, sid);
|
INIT_BILINEAR_WEIGHTS(Ux.y, Uy.y);
|
cur_SSD = computeSSDMeanNorm(I0_ptr + i * w + j, I1_ptr + (int)i_I1 * w_ext + (int)j_I1,
|
w, w_ext, w00, w01, w10, w11, psz, sid);
|
if (cur_SSD < min_SSD)
|
{
|
Sx_ptr[is * ws + js] = Ux.y;
|
Sy_ptr[is * ws + js] = Uy.y;
|
}
|
}
|
}
|
__kernel void dis_patch_inverse_search_bwd_2(__global const uchar *I0_ptr, __global const uchar *I1_ptr,
|
__global const short *I0x_ptr, __global const short *I0y_ptr,
|
__global const float *xx_ptr, __global const float *yy_ptr,
|
__global const float *xy_ptr,
|
__global const float *x_ptr, __global const float *y_ptr,
|
int border_size, int patch_size, int patch_stride,
|
int w, int h, int ws, int hs, int num_inner_iter,
|
__global float *Sx_ptr, __global float *Sy_ptr)
|
{
|
int js = get_global_id(0);
|
int is = get_global_id(1);
|
if (js >= ws || is >= hs) return;
|
js = (ws - 1 - js);
|
is = (hs - 1 - is);
|
int j = js * patch_stride;
|
int i = is * patch_stride;
|
int psz = patch_size;
|
int psz2 = psz / 2;
|
int w_ext = w + 2 * border_size;
|
int bsz = border_size;
|
int index = is * ws + js;
|
float Ux = Sx_ptr[index];
|
float Uy = Sy_ptr[index];
|
float cur_Ux = Ux;
|
float cur_Uy = Uy;
|
float cur_xx = xx_ptr[index];
|
float cur_yy = yy_ptr[index];
|
float cur_xy = xy_ptr[index];
|
float detH = cur_xx * cur_yy - cur_xy * cur_xy;
|
if (fabs(detH) < EPS) detH = EPS;
|
float invH11 = cur_yy / detH;
|
float invH12 = -cur_xy / detH;
|
float invH22 = cur_xx / detH;
|
float prev_SSD = INF, SSD;
|
float x_grad_sum = x_ptr[index];
|
float y_grad_sum = y_ptr[index];
|
float i_lower_limit = bsz - psz + 1.0f;
|
float i_upper_limit = bsz + h - 1.0f;
|
float j_lower_limit = bsz - psz + 1.0f;
|
float j_upper_limit = bsz + w - 1.0f;
|
float dUx, dUy, i_I1, j_I1, w00, w01, w10, w11, dx, dy;
|
float3 res;
|
for (int t = 0; t < num_inner_iter; t++)
|
{
|
INIT_BILINEAR_WEIGHTS(cur_Ux, cur_Uy);
|
res = processPatchMeanNorm(I0_ptr + i * w + j,
|
I1_ptr + (int)i_I1 * w_ext + (int)j_I1, I0x_ptr + i * w + j,
|
I0y_ptr + i * w + j, w, w_ext, w00, w01, w10, w11, psz,
|
x_grad_sum, y_grad_sum);
|
SSD = res.x;
|
dUx = res.y;
|
dUy = res.z;
|
dx = invH11 * dUx + invH12 * dUy;
|
dy = invH12 * dUx + invH22 * dUy;
|
cur_Ux -= dx;
|
cur_Uy -= dy;
|
if (SSD >= prev_SSD)
|
break;
|
prev_SSD = SSD;
|
}
|
float2 vec = (float2)(cur_Ux - Ux, cur_Uy - Uy);
|
if ((dot(vec, vec)) <= (float)(psz * psz))
|
{
|
Sx_ptr[index] = cur_Ux;
|
Sy_ptr[index] = cur_Uy;
|
}
|
}
|
b4a43889f4f3346e29ae36e2502b2821 #if CN==1
|
#define T_MEAN float
|
#define F_ZERO (0.0f)
|
#define cnMode 1
|
#define frameToMean(a, b) (b) = *(a);
|
#if FL==0
|
#define meanToFrame(a, b) *b = convert_uchar_sat(a);
|
#else
|
#define meanToFrame(a, b) *b = (float)a;
|
#endif
|
#else
|
#define T_MEAN float4
|
#define F_ZERO (0.0f, 0.0f, 0.0f, 0.0f)
|
#define cnMode 4
|
#if FL == 0
|
#define meanToFrame(a, b)\
|
b[0] = convert_uchar_sat(a.x); \
|
b[1] = convert_uchar_sat(a.y); \
|
b[2] = convert_uchar_sat(a.z);
|
#else
|
#define meanToFrame(a, b)\
|
b[0] = a.x; \
|
b[1] = a.y; \
|
b[2] = a.z;
|
#endif
|
#define frameToMean(a, b)\
|
b.x = a[0]; \
|
b.y = a[1]; \
|
b.z = a[2]; \
|
b.w = 0.0f;
|
#endif
|
__kernel void mog2_kernel(__global const uchar* frame, int frame_step, int frame_offset, int frame_row, int frame_col,
|
__global uchar* modesUsed,
|
__global uchar* weight,
|
__global uchar* mean,
|
__global uchar* variance,
|
__global uchar* fgmask, int fgmask_step, int fgmask_offset,
|
float alphaT, float alpha1, float prune,
|
float c_Tb, float c_TB, float c_Tg, float c_varMin,
|
float c_varMax, float c_varInit, float c_tau
|
#ifdef SHADOW_DETECT
|
, uchar c_shadowVal
|
#endif
|
)
|
{
|
int x = get_global_id(0);
|
int y = get_global_id(1);
|
if( x < frame_col && y < frame_row)
|
{
|
#if FL==0
|
__global const uchar* _frame = (frame + mad24(y, frame_step, mad24(x, CN, frame_offset)));
|
#else
|
__global const float* _frame = ((__global const float*)( frame + mad24(y, frame_step, frame_offset)) + mad24(x, CN, 0));
|
#endif
|
T_MEAN pix;
|
frameToMean(_frame, pix);
|
uchar foreground = 255;
|
bool fitsPDF = false;
|
int pt_idx = mad24(y, frame_col, x);
|
int idx_step = frame_row * frame_col;
|
__global uchar* _modesUsed = modesUsed + pt_idx;
|
uchar nmodes = _modesUsed[0];
|
float totalWeight = 0.0f;
|
__global float* _weight = (__global float*)(weight);
|
__global float* _variance = (__global float*)(variance);
|
__global T_MEAN* _mean = (__global T_MEAN*)(mean);
|
uchar mode = 0;
|
for (; mode < nmodes; ++mode)
|
{
|
int mode_idx = mad24(mode, idx_step, pt_idx);
|
float c_weight = mad(alpha1, _weight[mode_idx], prune);
|
float c_var = _variance[mode_idx];
|
T_MEAN c_mean = _mean[mode_idx];
|
T_MEAN diff = c_mean - pix;
|
float dist2 = dot(diff, diff);
|
if (totalWeight < c_TB && dist2 < c_Tb * c_var)
|
foreground = 0;
|
if (dist2 < c_Tg * c_var)
|
{
|
fitsPDF = true;
|
c_weight += alphaT;
|
float k = alphaT / c_weight;
|
T_MEAN mean_new = mad((T_MEAN)-k, diff, c_mean);
|
float variance_new = clamp(mad(k, (dist2 - c_var), c_var), c_varMin, c_varMax);
|
for (int i = mode; i > 0; --i)
|
{
|
int prev_idx = mode_idx - idx_step;
|
if (c_weight < _weight[prev_idx])
|
break;
|
_weight[mode_idx] = _weight[prev_idx];
|
_variance[mode_idx] = _variance[prev_idx];
|
_mean[mode_idx] = _mean[prev_idx];
|
mode_idx = prev_idx;
|
}
|
_mean[mode_idx] = mean_new;
|
_variance[mode_idx] = variance_new;
|
_weight[mode_idx] = c_weight;
|
totalWeight += c_weight;
|
mode ++;
|
break;
|
}
|
if (c_weight < -prune)
|
c_weight = 0.0f;
|
_weight[mode_idx] = c_weight;
|
totalWeight += c_weight;
|
}
|
for (; mode < nmodes; ++mode)
|
{
|
int mode_idx = mad24(mode, idx_step, pt_idx);
|
float c_weight = mad(alpha1, _weight[mode_idx], prune);
|
if (c_weight < -prune)
|
{
|
c_weight = 0.0f;
|
nmodes = mode;
|
break;
|
}
|
_weight[mode_idx] = c_weight;
|
totalWeight += c_weight;
|
}
|
if (0.f < totalWeight)
|
{
|
totalWeight = 1.f / totalWeight;
|
for (int mode = 0; mode < nmodes; ++mode)
|
_weight[mad24(mode, idx_step, pt_idx)] *= totalWeight;
|
}
|
if (!fitsPDF)
|
{
|
uchar mode = nmodes == (NMIXTURES) ? (NMIXTURES) - 1 : nmodes++;
|
int mode_idx = mad24(mode, idx_step, pt_idx);
|
if (nmodes == 1)
|
_weight[mode_idx] = 1.f;
|
else
|
{
|
_weight[mode_idx] = alphaT;
|
for (int i = pt_idx; i < mode_idx; i += idx_step)
|
_weight[i] *= alpha1;
|
}
|
for (int i = nmodes - 1; i > 0; --i)
|
{
|
int prev_idx = mode_idx - idx_step;
|
if (alphaT < _weight[prev_idx])
|
break;
|
_weight[mode_idx] = _weight[prev_idx];
|
_variance[mode_idx] = _variance[prev_idx];
|
_mean[mode_idx] = _mean[prev_idx];
|
mode_idx = prev_idx;
|
}
|
_mean[mode_idx] = pix;
|
_variance[mode_idx] = c_varInit;
|
}
|
_modesUsed[0] = nmodes;
|
#ifdef SHADOW_DETECT
|
if (foreground)
|
{
|
float tWeight = 0.0f;
|
for (uchar mode = 0; mode < nmodes; ++mode)
|
{
|
int mode_idx = mad24(mode, idx_step, pt_idx);
|
T_MEAN c_mean = _mean[mode_idx];
|
float numerator = dot(pix, c_mean);
|
float denominator = dot(c_mean, c_mean);
|
if (denominator == 0)
|
break;
|
if (numerator <= denominator && numerator >= c_tau * denominator)
|
{
|
float a = numerator / denominator;
|
T_MEAN dD = mad(a, c_mean, -pix);
|
if (dot(dD, dD) < c_Tb * _variance[mode_idx] * a * a)
|
{
|
foreground = c_shadowVal;
|
break;
|
}
|
}
|
tWeight += _weight[mode_idx];
|
if (tWeight > c_TB)
|
break;
|
}
|
}
|
#endif
|
__global uchar* _fgmask = fgmask + mad24(y, fgmask_step, x + fgmask_offset);
|
*_fgmask = (uchar)foreground;
|
}
|
}
|
__kernel void getBackgroundImage2_kernel(__global const uchar* modesUsed,
|
__global const uchar* weight,
|
__global const uchar* mean,
|
__global uchar* dst, int dst_step, int dst_offset, int dst_row, int dst_col,
|
float c_TB)
|
{
|
int x = get_global_id(0);
|
int y = get_global_id(1);
|
if(x < dst_col && y < dst_row)
|
{
|
int pt_idx = mad24(y, dst_col, x);
|
__global const uchar* _modesUsed = modesUsed + pt_idx;
|
uchar nmodes = _modesUsed[0];
|
T_MEAN meanVal = (T_MEAN)F_ZERO;
|
float totalWeight = 0.0f;
|
__global const float* _weight = (__global const float*)weight;
|
__global const T_MEAN* _mean = (__global const T_MEAN*)(mean);
|
int idx_step = dst_row * dst_col;
|
for (uchar mode = 0; mode < nmodes; ++mode)
|
{
|
int mode_idx = mad24(mode, idx_step, pt_idx);
|
float c_weight = _weight[mode_idx];
|
T_MEAN c_mean = _mean[mode_idx];
|
meanVal = mad(c_weight, c_mean, meanVal);
|
totalWeight += c_weight;
|
if (totalWeight > c_TB)
|
break;
|
}
|
if (0.f < totalWeight)
|
meanVal = meanVal / totalWeight;
|
else
|
meanVal = (T_MEAN)(0.f);
|
#if FL==0
|
__global uchar* _dst = dst + mad24(y, dst_step, mad24(x, CN, dst_offset));
|
meanToFrame(meanVal, _dst);
|
#else
|
__global float* _dst = ((__global float*)( dst + mad24(y, dst_step, dst_offset)) + mad24(x, CN, 0));
|
meanToFrame(meanVal, _dst);
|
#endif
|
}
|
}
|
39b7e7b52e8eb53029cf2337ae3d904f #if CN==1
|
#define T_MEAN float
|
#define F_ZERO (0.0f)
|
#define frameToMean(a, b) (b) = *(a);
|
#define meanToFrame(a, b) *b = convert_uchar_sat(a);
|
#else
|
#define T_MEAN float4
|
#define F_ZERO (0.0f, 0.0f, 0.0f, 0.0f)
|
#define meanToFrame(a, b)\
|
b[0] = convert_uchar_sat(a.x); \
|
b[1] = convert_uchar_sat(a.y); \
|
b[2] = convert_uchar_sat(a.z);
|
#define frameToMean(a, b)\
|
b.x = a[0]; \
|
b.y = a[1]; \
|
b.z = a[2]; \
|
b.w = 0.0f;
|
#endif
|
__kernel void knn_kernel(__global const uchar* frame, int frame_step, int frame_offset, int frame_row, int frame_col,
|
__global const uchar* nNextLongUpdate,
|
__global const uchar* nNextMidUpdate,
|
__global const uchar* nNextShortUpdate,
|
__global uchar* aModelIndexLong,
|
__global uchar* aModelIndexMid,
|
__global uchar* aModelIndexShort,
|
__global uchar* flag,
|
__global uchar* sample,
|
__global uchar* fgmask, int fgmask_step, int fgmask_offset,
|
int nLongCounter, int nMidCounter, int nShortCounter,
|
float c_Tb, int c_nkNN, float c_tau
|
#ifdef SHADOW_DETECT
|
, uchar c_shadowVal
|
#endif
|
)
|
{
|
int x = get_global_id(0);
|
int y = get_global_id(1);
|
if( x < frame_col && y < frame_row)
|
{
|
__global const uchar* _frame = (frame + mad24(y, frame_step, mad24(x, CN, frame_offset)));
|
T_MEAN pix;
|
frameToMean(_frame, pix);
|
uchar foreground = 255;
|
int Pbf = 0;
|
int Pb = 0;
|
uchar include = 0;
|
int pt_idx = mad24(y, frame_col, x);
|
int idx_step = frame_row * frame_col;
|
__global T_MEAN* _sample = (__global T_MEAN*)(sample);
|
for (uchar n = 0; n < (NSAMPLES) * 3 ; ++n)
|
{
|
int n_idx = mad24(n, idx_step, pt_idx);
|
T_MEAN c_mean = _sample[n_idx];
|
uchar c_flag = flag[n_idx];
|
T_MEAN diff = c_mean - pix;
|
float dist2 = dot(diff, diff);
|
if (dist2 < c_Tb)
|
{
|
Pbf++;
|
if (c_flag)
|
{
|
Pb++;
|
if (Pb >= c_nkNN)
|
{
|
include = 1;
|
foreground = 0;
|
break;
|
}
|
}
|
}
|
}
|
if (Pbf >= c_nkNN)
|
{
|
include = 1;
|
}
|
#ifdef SHADOW_DETECT
|
if (foreground)
|
{
|
int Ps = 0;
|
for (uchar n = 0; n < (NSAMPLES) * 3 ; ++n)
|
{
|
int n_idx = mad24(n, idx_step, pt_idx);
|
uchar c_flag = flag[n_idx];
|
if (c_flag)
|
{
|
T_MEAN c_mean = _sample[n_idx];
|
float numerator = dot(pix, c_mean);
|
float denominator = dot(c_mean, c_mean);
|
if (denominator == 0)
|
break;
|
if (numerator <= denominator && numerator >= c_tau * denominator)
|
{
|
float a = numerator / denominator;
|
T_MEAN dD = mad(a, c_mean, -pix);
|
if (dot(dD, dD) < c_Tb * a * a)
|
{
|
Ps++;
|
if (Ps >= c_nkNN)
|
{
|
foreground = c_shadowVal;
|
break;
|
}
|
}
|
}
|
}
|
}
|
}
|
#endif
|
__global uchar* _fgmask = fgmask + mad24(y, fgmask_step, x + fgmask_offset);
|
*_fgmask = (uchar)foreground;
|
__global const uchar* _nNextLongUpdate = nNextLongUpdate + pt_idx;
|
__global const uchar* _nNextMidUpdate = nNextMidUpdate + pt_idx;
|
__global const uchar* _nNextShortUpdate = nNextShortUpdate + pt_idx;
|
__global uchar* _aModelIndexLong = aModelIndexLong + pt_idx;
|
__global uchar* _aModelIndexMid = aModelIndexMid + pt_idx;
|
__global uchar* _aModelIndexShort = aModelIndexShort + pt_idx;
|
uchar nextLongUpdate = _nNextLongUpdate[0];
|
uchar nextMidUpdate = _nNextMidUpdate[0];
|
uchar nextShortUpdate = _nNextShortUpdate[0];
|
uchar modelIndexLong = _aModelIndexLong[0];
|
uchar modelIndexMid = _aModelIndexMid[0];
|
uchar modelIndexShort = _aModelIndexShort[0];
|
int offsetLong = mad24(mad24(2, (NSAMPLES), modelIndexLong), idx_step, pt_idx);
|
int offsetMid = mad24((NSAMPLES)+modelIndexMid, idx_step, pt_idx);
|
int offsetShort = mad24(modelIndexShort, idx_step, pt_idx);
|
if (nextLongUpdate == nLongCounter)
|
{
|
_sample[offsetLong] = _sample[offsetMid];
|
flag[offsetLong] = flag[offsetMid];
|
_aModelIndexLong[0] = (modelIndexLong >= ((NSAMPLES)-1)) ? 0 : (modelIndexLong + 1);
|
}
|
if (nextMidUpdate == nMidCounter)
|
{
|
_sample[offsetMid] = _sample[offsetShort];
|
flag[offsetMid] = flag[offsetShort];
|
_aModelIndexMid[0] = (modelIndexMid >= ((NSAMPLES)-1)) ? 0 : (modelIndexMid + 1);
|
}
|
if (nextShortUpdate == nShortCounter)
|
{
|
_sample[offsetShort] = pix;
|
flag[offsetShort] = include;
|
_aModelIndexShort[0] = (modelIndexShort >= ((NSAMPLES)-1)) ? 0 : (modelIndexShort + 1);
|
}
|
}
|
}
|
__kernel void getBackgroundImage2_kernel(__global const uchar* flag,
|
__global const uchar* sample,
|
__global uchar* dst, int dst_step, int dst_offset, int dst_row, int dst_col)
|
{
|
int x = get_global_id(0);
|
int y = get_global_id(1);
|
if(x < dst_col && y < dst_row)
|
{
|
int pt_idx = mad24(y, dst_col, x);
|
T_MEAN meanVal = (T_MEAN)F_ZERO;
|
__global T_MEAN* _sample = (__global T_MEAN*)(sample);
|
int idx_step = dst_row * dst_col;
|
for (uchar n = 0; n < (NSAMPLES) * 3 ; ++n)
|
{
|
int n_idx = mad24(n, idx_step, pt_idx);
|
uchar c_flag = flag[n_idx];
|
if(c_flag)
|
{
|
meanVal = _sample[n_idx];
|
break;
|
}
|
}
|
__global uchar* _dst = dst + mad24(y, dst_step, mad24(x, CN, dst_offset));
|
meanToFrame(meanVal, _dst);
|
}
|
}
|
a192721ae727b25afde8d854a0679ee4 ;ä ; àéùÿ
|
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þùÿð1 úÿH2 úÿ2 Àúÿ`4 ¶ úÿ5 Ê úÿ`6 º+úÿ< ,úÿ(8 °-úÿ(
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_ZZN2cv28BackgroundSubtractorMOG2Impl10initializeENS_5Size_IiEEiE8__func__ _ZZN2cv28BackgroundSubtractorMOG2Impl9ocl_applyERKNS_11_InputArrayERKNS_12_OutputArrayEdE8__func__ _ZZN2cv28BackgroundSubtractorMOG2Impl5applyERKNS_11_InputArrayERKNS_12_OutputArrayEdE25__cv_trace_location_fn847 _ZZN2cv28BackgroundSubtractorMOG2Impl5applyERKNS_11_InputArrayERKNS_12_OutputArrayEdE8__func__ _ZZNK2cv28BackgroundSubtractorMOG2Impl18getBackgroundImageERKNS_12_OutputArrayEE8__func__ _ZZNK2cv28BackgroundSubtractorMOG2Impl25getBackgroundImage_internIfLi3EEEvRKNS_12_OutputArrayEE19__PRETTY_FUNCTION__ _ZZNK2cv28BackgroundSubtractorMOG2Impl25getBackgroundImage_internIfLi1EEEvRKNS_12_OutputArrayEE19__PRETTY_FUNCTION__ _ZZNK2cv28BackgroundSubtractorMOG2Impl25getBackgroundImage_internIhLi3EEEvRKNS_12_OutputArrayEE19__PRETTY_FUNCTION__ _ZZNK2cv28BackgroundSubtractorMOG2Impl25getBackgroundImage_internIhLi1EEEvRKNS_12_OutputArrayEE19__PRETTY_FUNCTION__ _ZZN2cv28BackgroundSubtractorMOG2Impl5applyERKNS_11_InputArrayERKNS_12_OutputArrayEdE31__cv_trace_location_extra_fn847 _ZZN2cv28BackgroundSubtractorMOG2Impl5applyERKNS_11_InputArrayERKNS_12_OutputArrayEdE19__PRETTY_FUNCTION__ camshift.cpp _ZNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEC2EPKcRKS3_.isra.21 _ZZN2cv9meanShiftERKNS_11_InputArrayERNS_5Rect_IiEENS_12TermCriteriaEE24__cv_trace_location_fn46 _ZZN2cv9meanShiftERKNS_11_InputArrayERNS_5Rect_IiEENS_12TermCriteriaEE8__func__ _ZZN2cv8CamShiftERKNS_11_InputArrayERNS_5Rect_IiEENS_12TermCriteriaEE25__cv_trace_location_fn113 _ZZN2cv8CamShiftERKNS_11_InputArrayERNS_5Rect_IiEENS_12TermCriteriaEE31__cv_trace_location_extra_fn113 _ZZN2cv8CamShiftERKNS_11_InputArrayERNS_5Rect_IiEENS_12TermCriteriaEE19__PRETTY_FUNCTION__ _ZZN2cv9meanShiftERKNS_11_InputArrayERNS_5Rect_IiEENS_12TermCriteriaEE30__cv_trace_location_extra_fn46 _ZZN2cv9meanShiftERKNS_11_InputArrayERNS_5Rect_IiEENS_12TermCriteriaEE19__PRETTY_FUNCTION__ dis_flow.cpp 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_ZNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEC2EPKcRKS3_.isra.18 _ZZN2cv12KalmanFilter4initEiiiiE8__func__ _ZZN2cv12KalmanFilter7predictERKNS_3MatEE24__cv_trace_location_fn84 _ZZN2cv12KalmanFilter7correctERKNS_3MatEE25__cv_trace_location_fn108 _ZZN2cv12KalmanFilter7correctERKNS_3MatEE31__cv_trace_location_extra_fn108 _ZZN2cv12KalmanFilter7correctERKNS_3MatEE19__PRETTY_FUNCTION__ _ZZN2cv12KalmanFilter7predictERKNS_3MatEE30__cv_trace_location_extra_fn84 _ZZN2cv12KalmanFilter7predictERKNS_3MatEE19__PRETTY_FUNCTION__ lkpyramid.cpp _ZNK2cv12_GLOBAL__N_126SparsePyrLKOpticalFlowImpl10getWinSizeEv _ZN2cv12_GLOBAL__N_126SparsePyrLKOpticalFlowImpl10setWinSizeENS_5Size_IiEE _ZNK2cv12_GLOBAL__N_126SparsePyrLKOpticalFlowImpl11getMaxLevelEv _ZN2cv12_GLOBAL__N_126SparsePyrLKOpticalFlowImpl11setMaxLevelEi _ZNK2cv12_GLOBAL__N_126SparsePyrLKOpticalFlowImpl15getTermCriteriaEv _ZN2cv12_GLOBAL__N_126SparsePyrLKOpticalFlowImpl15setTermCriteriaERNS_12TermCriteriaE 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_ZTISt23_Sp_counted_ptr_inplaceIN2cv12_GLOBAL__N_126SparsePyrLKOpticalFlowImplESaIS2_ELN9__gnu_cxx12_Lock_policyE2EE _ZTSSt23_Sp_counted_ptr_inplaceIN2cv12_GLOBAL__N_126SparsePyrLKOpticalFlowImplESaIS2_ELN9__gnu_cxx12_Lock_policyE2EE optflowgf.cpp _ZNK2cv12_GLOBAL__N_124FarnebackOpticalFlowImpl12getNumLevelsEv _ZN2cv12_GLOBAL__N_124FarnebackOpticalFlowImpl12setNumLevelsEi _ZNK2cv12_GLOBAL__N_124FarnebackOpticalFlowImpl11getPyrScaleEv _ZN2cv12_GLOBAL__N_124FarnebackOpticalFlowImpl11setPyrScaleEd _ZNK2cv12_GLOBAL__N_124FarnebackOpticalFlowImpl15getFastPyramidsEv _ZN2cv12_GLOBAL__N_124FarnebackOpticalFlowImpl15setFastPyramidsEb _ZNK2cv12_GLOBAL__N_124FarnebackOpticalFlowImpl10getWinSizeEv _ZN2cv12_GLOBAL__N_124FarnebackOpticalFlowImpl10setWinSizeEi _ZNK2cv12_GLOBAL__N_124FarnebackOpticalFlowImpl11getNumItersEv _ZN2cv12_GLOBAL__N_124FarnebackOpticalFlowImpl11setNumItersEi _ZNK2cv12_GLOBAL__N_124FarnebackOpticalFlowImpl8getPolyNEv _ZN2cv12_GLOBAL__N_124FarnebackOpticalFlowImpl8setPolyNEi 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_ZN2cv4UMatC1ERKS0_RKNS_5RangeES5_ memset@@GLIBC_2.2.5 _ZN2cv22SparsePyrLKOpticalFlow6createENS_5Size_IiEEiNS_12TermCriteriaEid _ZN2cv20calcOpticalFlowPyrLKERKNS_11_InputArrayES2_S2_RKNS_17_InputOutputArrayERKNS_12_OutputArrayES8_NS_5Size_IiEEiNS_12TermCriteriaEid _ZN2cv3ocl6KernelD1Ev icv_ownMaskIsFeatures _ZTIN2cv16DenseOpticalFlowE icv_ipp_is_mmx_extension _ZN2cv14DISOpticalFlow6createEi _ZNK2cv3Mat3dotERKNS_11_InputArrayE _ZTISt16_Sp_counted_baseILN9__gnu_cxx12_Lock_policyE2EE _ZNK2cv11_InputArray7getMat_Ei icv_ipp_set_cw_fpu icv_ps_set_ssx sincos@@GLIBC_2.2.5 _ZN2cv4UMat5setToERKNS_11_InputArrayES3_ _ZN2cvmiERKNS_7MatExprERKNS_7Scalar_IdEE _ZN2cv3ocl7Image2D17isFormatSupportedEiib _ZNK2cv3Mat1tEv _ZTVSt15basic_streambufIcSt11char_traitsIcEE@@GLIBCXX_3.4 _ZN2cv5splitERKNS_3MatEPS0_ _ZTSN2cv16DenseOpticalFlowE _ZN2cv3ocl17isOpenCLActivatedEv _ZN2cv3ocl6KernelC1Ev _ZNK2cv11_InputArray8sameSizeERKS0_ _ZTVN2cv17SparseOpticalFlowE _ZN2cv3ocl7Image2DD1Ev _ZN2cv5remapERKNS_11_InputArrayERKNS_12_OutputArrayES2_S2_iiRKNS_7Scalar_IdEE _ZN2cv6formatB5cxx11EPKcz icv_ps_get_sw_fpu icv_ipp_is_avx_extension _ZN2cv4UMatC2ERKS0_ _ZN2cv5splitERKNS_11_InputArrayERKNS_12_OutputArrayE _ZTVN10__cxxabiv117__class_type_infoE@@CXXABI_1.3 _ZSt19__throw_logic_errorPKc@@GLIBCXX_3.4 _ZNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEE4swapERS4_@@GLIBCXX_3.4.21 _fini _ZNSt6vectorIPvSaIS0_EE19_M_emplace_back_auxIIS0_EEEvDpOT_ _ZTTSt14basic_ofstreamIcSt11char_traitsIcEE@@GLIBCXX_3.4 _ZN2cv21VariationalRefinement6createEv _ZTIN2cv20BackgroundSubtractorE _ZTSN2cv20FarnebackOpticalFlowE _ZN2cv10warpAffineERKNS_11_InputArrayERKNS_12_OutputArrayES2_NS_5Size_IiEEiiRKNS_7Scalar_IdEE icv_ipp_get_cores_on_die _ZN2cv9meanShiftERKNS_11_InputArrayERNS_5Rect_IiEENS_12TermCriteriaE _ZN2cvngERKNS_7MatExprE _ZN2cv3MatC1EiiiPvm icv_ownSetCpuFeaturesAndIdx _ZNK2cv8FileNodeixEPKc sqrt@@GLIBC_2.2.5 _ZN2cv4UMat10deallocateEv _ZTSN2cv24BackgroundSubtractorMOG2E _ZN2cv3Mat6createEiPKii _ZNSt16_Sp_counted_baseILN9__gnu_cxx12_Lock_policyE2EE10_M_releaseEv _ZN2cv4UMat8copySizeERKS0_ memcpy@@GLIBC_2.14 _ZNK2cv3ocl6Device19imagePitchAlignmentEv _ZN2cv23estimateAffinePartial2DERKNS_11_InputArrayES2_RKNS_12_OutputArrayEidmdm _ZN2cv12GaussianBlurERKNS_11_InputArrayERKNS_12_OutputArrayENS_5Size_IiEEddi _ZN2cv16estimateAffine2DERKNS_11_InputArrayES2_RKNS_12_OutputArrayEidmdm _ZN2cv8filter2DERKNS_11_InputArrayERKNS_12_OutputArrayEiS2_NS_6Point_IiEEdi _ZN2cvmiERKNS_7MatExprES2_ _ZN2cv3ocl5QueueC1Ev _ZN2cv6divideERKNS_11_InputArrayES2_RKNS_12_OutputArrayEdi _ZN2cv15spatialGradientERKNS_11_InputArrayERKNS_12_OutputArrayES5_ii __cxa_atexit@@GLIBC_2.2.5 _ZNSt6vectorIN2cv4UMatESaIS1_EE19_M_emplace_back_auxIIS1_EEEvDpOT_ _ZN2cvplERKNS_7MatExprES2_ icv_ippJumpIndexForMergedLibs _ZNSt13basic_filebufIcSt11char_traitsIcEE4openEPKcSt13_Ios_Openmode@@GLIBCXX_3.4 _ZN2cv7momentsERKNS_11_InputArrayEb __pthread_key_create ippicvGetEnabledCpuFeatures icv_ownGetFeature _ZN2cv3ocl6Kernel3setEiRKNS0_9KernelArgE _ZNK2cv11_InputArray4sizeEi _ZTSN2cv17SparseOpticalFlowE _ZdlPv@@GLIBCXX_3.4 _ZNK2cv3Mat7reshapeEii icv_ps_clear_fpu _ZN2cv22estimateRigidTransformERKNS_11_InputArrayES2_b icv_ipp_has_cpuid _ZNK2cv12_OutputArray10getUMatRefEi _ZTVSt14basic_ifstreamIcSt11char_traitsIcEE@@GLIBCXX_3.4 icv_ipp_is_em64t_extension _Znwm@@GLIBCXX_3.4 _ZN2cv6resizeERKNS_11_InputArrayERKNS_12_OutputArrayENS_5Size_IiEEddi _ZNSt13basic_filebufIcSt11char_traitsIcEEC1Ev@@GLIBCXX_3.4 _ZNK2cv11_InputArray8channelsEi _ZN2cv3MatC2EiiiPvm _ZNK2cv3ocl8internal12ProgramEntrycvRNS0_13ProgramSourceEEv icv_ipp_control87 _ZTSSt19_Sp_make_shared_tag icv_ipp_is_sse42_extension icv_ipp_set_cw_ssx _ZN2cv3Mat7releaseEv _ZNK2cv3Mat9convertToERKNS_12_OutputArrayEidd _ZN2cv3ocl6Kernel3runEiPmS2_bRKNS0_5QueueE _ZN2cv4gemmERKNS_11_InputArrayES2_dS2_dRKNS_12_OutputArrayEi __stack_chk_fail@@GLIBC_2.4 _init _ZNSt6vectorIN2cv4UMatESaIS1_EE19_M_emplace_back_auxIJS1_EEEvDpOT_ icv_ipp_has_rdtsc _ZNK2cv9Algorithm11writeFormatERNS_11FileStorageE _ZN2cv20checkHardwareSupportEi _Jv_RegisterClasses _ZN2cv11addWeightedERKNS_11_InputArrayEdS2_ddRKNS_12_OutputArrayEi _ZN2cv5solveERKNS_11_InputArrayES2_RKNS_12_OutputArrayEi icv_ps_get_cw_fpu _ZTISt11_Mutex_baseILN9__gnu_cxx12_Lock_policyE2EE _ZN2cvplERKNS_3MatERKNS_7MatExprE _ZNK2cv3ocl6Device4typeEv _ZN2cv20FarnebackOpticalFlow6createEidbiiidi _ZN2cv3MatC1ERKS0_RKNS_5Rect_IiEE _ZNSi4readEPcl@@GLIBCXX_3.4 _ZN2cv5utils5trace7details6RegionC1ERKNS3_21LocationStaticStorageE _ZTIN2cv17SparseOpticalFlowE _ZNK2cv3ocl6Device12imageSupportEv _ZNK2cv3Mat9locateROIERNS_5Size_IiEERNS_6Point_IiEE _ZNK2cv12_OutputArray6neededEv _ZdaPv@@GLIBCXX_3.4 _ZTVN10__cxxabiv120__si_class_type_infoE@@CXXABI_1.3 icv_ps_set_cw_fpu _ZN2cv29createBackgroundSubtractorKNNEidb _ZNSo5writeEPKcl@@GLIBCXX_3.4 _ZTSSt11_Mutex_baseILN9__gnu_cxx12_Lock_policyE2EE icv_ipp_finite _ZTIN2cv16ParallelLoopBodyE _ZN2cv3ocl9KernelArgC1EiPNS_4UMatEiiPKvm icv_ippStopTscp exp@@GLIBC_2.2.5 _ZNK2cv11_InputArray5totalEi icv_ipp_get_pentium_counter _ZNK2cv12_OutputArray6createENS_5Size_IiEEiibNS0_9DepthMaskE _ZNK2cv11_InputArray4kindEv _ZTISt19_Sp_make_shared_tag ippicvSetCpuFeaturesMask _ZNSt9basic_iosIcSt11char_traitsIcEE4initEPSt15basic_streambufIcS1_E@@GLIBCXX_3.4 _ZN2cv13getNumThreadsEv _ZNK2cv9Algorithm14getDefaultNameB5cxx11Ev _ZTIN2cv9AlgorithmE _ZN2cv3ocl6Kernel6createEPKcRKNS0_13ProgramSourceERKNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEEPSC_ icv_ownSetFeatureMask _end _ZN2cv16findTransformECCERKNS_11_InputArrayES2_RKNS_17_InputOutputArrayEiNS_12TermCriteriaES2_ _ZN2cv3Mat9adjustROIEiiii icv_ippStopTsc _ZNSt6localeD1Ev@@GLIBCXX_3.4 icv_ipp_is_pni_extension __cxa_throw_bad_array_new_length@@CXXABI_1.3.8 icv_ipp_clear87 icv_ipp_get_pentium_ident _ZN2cv8cvtColorERKNS_11_InputArrayERKNS_12_OutputArrayEii _ZN2cv15readOpticalFlowERKNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEE _ZTVN2cv16DenseOpticalFlowE _ZNSt6vectorIhSaIhEE17_M_default_appendEm _ZN2cv12KalmanFilterC1Ev _ZN2cvmlERKNS_7MatExprEd __cxa_rethrow@@CXXABI_1.3 _ZN2cv5writeERNS_11FileStorageERKNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEEi _ZN2cv8CamShiftERKNS_11_InputArrayERNS_5Rect_IiEENS_12TermCriteriaE _ZNSt14basic_ofstreamIcSt11char_traitsIcEED1Ev@@GLIBCXX_3.4 _ZTSN2cv20BackgroundSubtractorE _ZNK2cv12_OutputArray7releaseEv _ZN2cv5SobelERKNS_11_InputArrayERKNS_12_OutputArrayEiiiiddi __bss_start _ZN2cv16writeOpticalFlowERKNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEERKNS_11_InputArrayE _ZTVSt13basic_filebufIcSt11char_traitsIcEE@@GLIBCXX_3.4 _ZN2cv12countNonZeroERKNS_11_InputArrayE _ZN2cvmiERKNS_3MatERKNS_7MatExprE _ZNSt6vectorIPvSaIS0_EE19_M_emplace_back_auxIJS0_EEEvDpOT_ _ZNK2cv8FileNodecviEv _ZNSt8ios_base4InitC1Ev@@GLIBCXX_3.4 _ZNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEE10_M_replaceEmmPKcm@@GLIBCXX_3.4.21 _ZNK2cv3Mat11checkVectorEiib _ZTIN2cv22SparsePyrLKOpticalFlowE _ZTVSt14basic_ofstreamIcSt11char_traitsIcEE@@GLIBCXX_3.4 _ZN2cv30createBackgroundSubtractorMOG2Eidb _ZNSt13basic_filebufIcSt11char_traitsIcEED1Ev@@GLIBCXX_3.4 _ZTIN2cv14DISOpticalFlowE icv_ipp_set_rc_ssx _ZN2cvmlERKNS_3MatEd icv_ipp_set_rcpc_fpu _ZNSt6vectorIN2cv3MatESaIS1_EED1Ev _ZNK2cv11_InputArray5depthEi _ZN2cv4normERKNS_11_InputArrayEiS2_ _ZN2cv9AlgorithmC2Ev _ZN2cv3ocl6KernelC1EPKcRKNS0_13ProgramSourceERKNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEEPSC_ _ZN2cvmlEdRKNS_3MatE _ZN2cv3Mat4onesEiii _ZN2cv5mergeERKNS_11_InputArrayERKNS_12_OutputArrayE _ZN2cv3Mat20updateContinuityFlagEv _ZN2cv12KalmanFilterC2Eiiii _ZNK2cv3Mat7reshapeEiiPKi memmove@@GLIBC_2.2.5 __cxa_end_catch@@CXXABI_1.3 icv_ownGetCacheSize _ZTIN2cv20FarnebackOpticalFlowE _ZNK2cv12_OutputArray6createEiiiibNS0_9DepthMaskE __gxx_personality_v0@@CXXABI_1.3 _ZN2cv12KalmanFilter7correctERKNS_3MatE asin@@GLIBC_2.2.5 _ZN2cv3MataSERKNS_7Scalar_IdEE _ZNK2cv11_InputArray5emptyEv _ZN2cv15warpPerspectiveERKNS_11_InputArrayERKNS_12_OutputArrayES2_NS_5Size_IiEEiiRKNS_7Scalar_IdEE icv_ipp_tst_daz_ssx _ZN2cv3ocl7Image2DC1ERKNS_4UMatEbb _ZN2cv5errorEiRKNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEEPKcS9_i _ZN2cv5writeERNS_11FileStorageERKNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEEd _ZN2cv3Mat5zerosEiii _ZN2cvplERKNS_7MatExprERKNS_7Scalar_IdEE _ZN2cv4UMatC1ERKS0_ _ZN2cv16ParallelLoopBodyD2Ev _ZN2cv4UMat6createEiiiNS_14UMatUsageFlagsE icv_ipp_is_ssx_extension _ZNSt6vectorIN2cv4UMatESaIS1_EE6resizeEm _ZNSt9basic_iosIcSt11char_traitsIcEE5clearESt12_Ios_Iostate@@GLIBCXX_3.4 icv_ipp_is_avx512_extension _ZN2cv24calcOpticalFlowFarnebackERKNS_11_InputArrayES2_RKNS_17_InputOutputArrayEdiiiidi _ZTVN2cv20BackgroundSubtractorE _ITM_deregisterTMCloneTable _Unwind_Resume@@GCC_3.0 _ZN2cv3MatD2Ev _ZN2cv3ocl7Image2D14canCreateAliasERKNS_4UMatE _ZNSt6vectorIN2cv4UMatESaIS1_EE12emplace_backIJS1_EEEvDpOT_ _ZNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEE9_M_createERmm@@GLIBCXX_3.4.21 sqrtf@@GLIBC_2.2.5 _ZN2cv3ocl6Kernel3setEiPKvm _ZNK2cv8FileNodecvfEv _ZNK2cv11_InputArray12getMatVectorERSt6vectorINS_3MatESaIS2_EE _ZNSt12__basic_fileIcED1Ev@@GLIBCXX_3.4 _ZN2cv12KalmanFilter4initEiiii icv_ipp_is_GenuineIntel icv_ownGetMaskFeatures _ZN2cv5mergeEPKNS_3MatEmRKNS_12_OutputArrayE _ZNK2cv8FileNode6stringB5cxx11Ev icv_ps_get_ssx _ZN2cv3Mat8copySizeERKS0_ __gmon_start__ _ZTSN2cv21VariationalRefinementE _ZNSt6vectorIN2cv4UMatESaIS1_EE17_M_default_appendEm _ZNSt6vectorIN2cv4UMatESaIS1_EE12emplace_backIIS1_EEEvDpOT_ _ZNK2cv3Mat3invEi __cxa_pure_virtual@@CXXABI_1.3 icv_ownGetReg _ITM_registerTMCloneTable _ZNK2cv3Mat6copyToERKNS_12_OutputArrayE _ZN2cv3MatC1ERKS0_RKNS_5RangeES5_ _ZNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEE6assignEPKc@@GLIBCXX_3.4.21 _ZNK2cv8FileNodecvdEv _ZN2cv3Mat10deallocateEv _ZN2cv13parallel_for_ERKNS_5RangeERKNS_16ParallelLoopBodyEd _ZTTSt14basic_ifstreamIcSt11char_traitsIcEE@@GLIBCXX_3.4 _ZN2cv17getGaussianKernelEidi _ZN2cv9AlgorithmD2Ev _ZNK2cv9Algorithm4saveERKNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEE _ZN2cv3ocl5QueueD1Ev _ZNSt8ios_base4InitD1Ev@@GLIBCXX_3.4 _ZN2cv4UMataSEOS0_ .symtab .strtab .shstrtab .note.gnu.build-id .gnu.hash .dynsym .dynstr .gnu.version .gnu.version_r .rela.dyn .rela.plt .init .plt.got .text .fini .rodata .eh_frame_hdr .eh_frame .gcc_except_table .init_array .fini_array .jcr .data.rel.ro .dynamic .got.plt .data .bss .comment È È $ . öÿÿo ð ð ¸ 8 ¨ ¨ ¸ @ `' `' Ð0 H ÿÿÿo 0X 0X º U þÿÿo ðZ ðZ Ð d À[ À[ P+ n B H x X X s @ ~ Àª Àª ઠઠ`( @Ó @Ó `Ó `Ó @ß ² ² ä © ¼ ¼ d: ³ ìö ìö ¡ Å ` ' ` Ñ p ' p Ý x ' x â ' ï -' - @ P/' P/ ø 0' 0 0 @7' @7 X 8' 8 ¨ 0 8 5 ÑD Ð8 øR È ¹
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