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SVjd bmf! {URI` Aik!b ZNL(Z ck!A 9H@N Wf!  <# 1D Re s      + 9L Zm x    huu q~O!U MaX iahA}~~ ~~`~qymm@ u8 0 (  T}   s  Q(AA:BAbvirtual void cv::BackgroundSubtractorKNNImpl::apply(cv::InputArray, cv::OutputArray, double)/Users/build/buildAgent/work/b5d3ba53e49a4b81/build-victor-deps/build-opencv/opencv/modules/video/src/bgfg_KNN.cpplearningRate >= 0applyvirtual void cv::BackgroundSubtractorKNNImpl::getBackgroundImage(cv::OutputArray) constgetBackgroundImagenchannels <= 512initializenamehistorynsamplesnKNNdist2ThresholddetectShadowsshadowValueshadowThresholdNo element name has been givenoperator<</Users/build/buildAgent/work/b5d3ba53e49a4b81/build-victor-deps/build-opencv/opencv/modules/core/include/opencv2/core/persistence.hpp(String)fn["name"] == name_readBackgroundSubtractor.KNNN2cv27BackgroundSubtractorKNNImplEN2cv23BackgroundSubtractorKNNEN2cv20BackgroundSubtractorEN2cv6detail12PtrOwnerImplINS_27BackgroundSubtractorKNNImplENS_14DefaultDeleterIS2_EEEEN2cv6detail8PtrOwnerEXA8XA9@UXA: 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M` n      (; LDhuu ~O!f ^ri zrIA!  ww$D#Rf}k@ <bK}u!d \!F >I Tg xp''^h )$.1s0a(4?4?4?4??4learningRate >= 0ocl_apply/Users/build/buildAgent/work/b5d3ba53e49a4b81/build-victor-deps/build-opencv/opencv/modules/video/src/bgfg_gaussmix2.cpp-D CN=%d -D FL=%d -D NMIXTURES=%d%s -D SHADOW_DETECTmog2_kernelvirtual void cv::BackgroundSubtractorMOG2Impl::apply(cv::InputArray, cv::OutputArray, double)applyframeType == (((0) & ((1 << 3) - 1)) + (((1)-1) << 3)) || frameType == (((0) & ((1 << 3) - 1)) + (((3)-1) << 3)) || frameType == (((5) & ((1 << 3) - 1)) + (((1)-1) << 3)) || frameType == (((5) & ((1 << 3) - 1)) + (((3)-1) << 3))getBackgroundImagenchannels <= 512initializenmixtures <= 255getBackgroundImage2_kernel-D CN=%d -D FL=%d -D NMIXTURES=%dtotal() == 0 || data != __nullMat/Users/build/buildAgent/work/b5d3ba53e49a4b81/build-victor-deps/build-opencv/opencv/modules/core/include/opencv2/core/mat.inl.hppStep must be a multiple of esz1namehistorynmixturesbackgroundRatiovarThresholdvarThresholdGenvarInitvarMinvarMaxcomplexityReductionThresholddetectShadowsshadowValueshadowThresholdNo element name has been givenoperator<</Users/build/buildAgent/work/b5d3ba53e49a4b81/build-victor-deps/build-opencv/opencv/modules/core/include/opencv2/core/persistence.hpp(String)fn["name"] == name_read!kernel_apply.empty()setDetectShadowsvoid cv::BackgroundSubtractorMOG2Impl::getBackgroundImage_intern(cv::OutputArray) const [T = unsigned char, CN = 1]void cv::BackgroundSubtractorMOG2Impl::getBackgroundImage_intern(cv::OutputArray) const [T = unsigned char, CN = 3]void cv::BackgroundSubtractorMOG2Impl::getBackgroundImage_intern(cv::OutputArray) const [T = float, CN = 1]void cv::BackgroundSubtractorMOG2Impl::getBackgroundImage_intern(cv::OutputArray) const [T = float, CN = 3]BackgroundSubtractor.MOG2oLnJN2cv28BackgroundSubtractorMOG2ImplEN2cv24BackgroundSubtractorMOG2EN2cv20BackgroundSubtractorEN2cv11MOG2InvokerEN2cv6detail12PtrOwnerImplINS_28BackgroundSubtractorMOG2ImplENS_14DefaultDeleterIS2_EEEEN2cv6detail8PtrOwnerE,sLnrsLnrtLnrtLnrXA_   A`@A >@>`>>>> >!Al? ? ?@0@P@9XAPlTXAlWA`mXXAm^^ ^'zPLRx 4$?AC P4\ 'AC N,kAC E,iAC L4POAC MzRx $ AC ,l6AC I4X/AC N4wAC P4 AC N4DP&AC N4|HOAC K$ AC $AC B$AC 4,TAC K,dAC L$lAC $ AC $ AC $ȹ AC $  AC $4AC $\AC $AC $pAC $XAC $PAC $$HAC $L@AC $t8AC $0AC $(AC $ AC $AC $<AC $d AC ,AC G$ AC $ AC $ AC $4xAC $\AC B4x9gAC P4AC M,AC B4LH AC M$\AC $ AC $'AC B^-u^]-m^]-e^]-]^^-U^-M^-]a-]-b]a->]s-6]s-.]s-&]s-]o-\o-\~-\-\~-p\7\[n-[n-XSX-X]-X]-X]-X-X-8Xa-X-Wa-sWs-gWs-[Ws-OWs-CWo-7Wo-+W~-WS W]-W^-V~-V]-V]-V~-V]-vV~-mVx-ZVSVV-U~-Ux-UxU:U-T^-dT-DT]-:T-Sa-S]-zS-Sa-R]-R]-R-R=R-OFEEEEzE-DDDDDa-DwDoDbDZD-CCCCCa-CzCqCRC?C-:CC,-Bd-AAAA@-j@=H@-:@`-'@-"@-?]-?^-?~-?]-?~-}?x-j?c?3?-?-? -?-<]-<]-<^-<~-<]-<v-s<-d<B<w-4<-%<<w-<-;;v-;-;;v-;-;;v-w;-e;T;v-E;-3;";v-;-;:u-:-::v-:-::w-}:-k:Z:w-L:-::3:~-*:x-::9-9~-9-9~9t-h9-Y909]-(9^- 9~-9]- 9]-9~-8]-8]-8~-8]-8]-8~-8]-8]-8~-8]-8]-8~-{8]-s8]-f8~-Z8]-R8]-E8~-98]-18]-$8~-8]-8]-8~-7]-7]-7~-7]-7]-7~-7]-7]-7~-7]-7]-7~-s7]-k7]-^7~-R7]-J7]-=7~-17]-)7]-7~-7]-7]-6~-6]-6]-6~-6]-6]-6~-6]-6]-6~-6]-6]-w6~-k6]-c6]-V6~-J6]-B6]-56~-)6]-!6]-6~-6]-5|-5~-5x-55m5->5~-25- 5-4}-4~-4x-44t4-=4~-14-4-3}-3~-3x-33w3-@3~-43-3-2|-2~-2x-22p2-A2~-52-1-1|-1~-1x-11\1--1~-!1- 1-0|-0~-0x-00l0-=0~-10-0-/|-/~-/x-//|/-M/~-A/-&/-/|-.~-.x-...-Y.~-M.-1.- .{--~--x-----d-~-X--9---|-,~-,x-,,,-l,~-`,-:,-,}-+~-+x-+++-o+~-c+-G+-"+}- +~-+x-***-|*~-p*-U*-:*-+*~-*-*-)-)-)*-)*-)^-)-)]-F)T8)-.)'-)-(]-(^-(y-(]-(-Q(a-*(]-"(]-(-'='y-'-'a-^'-& &&%e-%b-$z-$W$=$]-$^-$y-$]-$-!$a-#]-#]-#-#=#y-#-N#a-*#-+"#""!e-!b-!z- !U = ]- ^- y- ]- -3 a- ]- ]--=y--Za-6-g^Ue-b-Gz-;[-=]-^-y-]--qa-J]-B]-:-=y--a-~-kc[e-b-Uz-IY;=]-^-~-]->-=-y@-i~-`x-MF?-2+-?-<-f-`-m]-e^-]~-Q]-I]-?~-3]-+]-!~-]- ^--q--r-Lq-=-r-q--lr-q--r-)="e- b-b-?-3-&~-m---i= -f-~-x-rkI-#~-x--=e]-]^-Uy-;]-1-a-]--Ya-2`-#]-]-]-]-~-]-y--[a-:- a- `- _-  y ! 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§HfW@ujf)pHpHHontinuouHHHsrc5.isCH@)f@s()AHH`H KHHX@ DZHHH@HHXZLHxXLpLHLLDž BH$@8H@0H@(H@ H@H@H@HH(H`HpHhH@HHpHLH PLLH@HHHLXLHxH@HHLDžBH@4H@,H@$H@H@H@ H@H@HHHH@HH@HHHPHLHHDžDžL LLHHHDžDžHHHHHHeHLHHHDž8DHHߡH bHfW!ȃf)p7HH) << 3))HH/H(((1)-1)HH(H- 1)) + HH H1 << 3) HHH(5) & ((HHH() == ((HHHdst.typeH)A?HH&H HfW@ucf)pHHontinuouHHHsrc5.isCH@)f@s()AAHHH 9HH0@4@ <@@@@8@DHX@ZHHZLHxH@HHLH?HHH@HH@LpLHHDžBH@8H@0H@(H@ H@H@H@HH HXHhH`H@HHpHLHLMPLL@LLHHHHLH0ZLH4ZL LHxHHLL8ZHH@H@HLHHDžBH@8H@0H@(H@ H@H@H@HHHLLIGIH@HLLLPLLLL LHHLLHDžDžLHDžDžHHHDžDžLMLHLI~LHLHL<ZLL@ZHHHxLLLHDZHH@H@HHHLHDžBH@8H@0H@(H@ H@H@H@HHHHHH@HHHHLLLHPHHHLLLLL LHDžDžLHDžDžLLHDž0Dž L(MHLL6|DžBH@4H@,H@$H@H@H@ H@H@HHHH@HDžBH@4H@,H@$H@H@H@ H@H@HHHH@HHDžDžHHHDžDžLHDž0Dž HH(HLLzHDžDžHHHDžDžLHDž0Dž HH(HMLLQzLHLHDžDžHHHHLzHH DžHXH8HHLLLHHHHPHpHLXtHuHHDžpHHH@H@H@H<~,Hx1ffff.HHcLH) << 3))HH6H((1)-1) HH0H 1)) + (HH(H << 3) -HH H5) & ((1HHH) == (((HHHix.type(HHHmap_matrH)ALLH xL!ȃW)p:LH-1) << 3HH0H + (((1)HH(H3) - 1))HH H ((1 << HHH (((5) &HHHype() ==HHHupdate.tHf@8)))ALLH LWDrS)pLHH5)ALLH gLWD‹f(@f(%~du l)p(LHows == 8HH Hupdate.rHHH== 3 && HHHix.rows HHHmap_matrH)ALLH ~Lf(@f(%cu )p(LHows == 6HH Hupdate.rHHH== 2 && HHHix.rows HHHmap_matrH)ALLH ~L&u ")p(LHows == 3HH Hupdate.rHHH== 2 && HHHix.rows HHHmap_matrH)ALLH f}Lu )p(LHows == 2HH Hupdate.rHHH== 2 && HHHix.rows HHHmap_matrH)A LLH |Lf(@f(%bW탽tg)pLHols == 1HHHupdate.cH)A LLH e|Lf(@f(%aW@uy)pLHtinuous(HHHix.isConHHHmap_matrH@))A LLH {Lf(@f(%aW@uu)pLHinuous()HH HsContinuHHHupdate.iH)ALLH e{Lf(@f(%`WDHLDLcAXAFXC C AFXCCAF XCCAFXCCAFXCCAZC ZXANXKKANXKKDWf(%_f(@ZK ZC fW_CH;|@HL f(pLHhwAXCCAFXCCLAXAFXC C AFXCCAF XCCAFXCCAFXCCAFXCCAFXCC}^HHht#HuHhHDžHDžHDžHDžHDž~*H1ff.HHcH9|HHH9t hHHt#HuHhHDžHDžHDžHDžHDž~!H1fHHcH9|HH H9t hHhHt#HuH0hHDžhHDžXHDžPHDžHHDž@4~!Hp1fHHc4H9|HxHH9t hHHt#HuHhHDžHDžHDžHDžHDž~!H1fHHcH9|HH H9t hHHt#HuHPhHDžHDžxHDžpHDžhHDž`T~!H1fHHcTH9|HHH9t hHHt#HuHphHDžHDžHDžHDžHDžt~!H1fHHctH9|HHH9t hHHt#HuHhHDžHDžHDžHDžHDž~!H1fHHcH9|HL9t hHHt#HuHhHDžHDžHDžHDžHDžH~!H1fHHcH9|HH9t hH0Ht#HuHhHDž0HDž HDžHDžHDž~(H81fHHcH9|H@L9t hHHHt#HuHhHDžHDžHDžHDžHDž~!H1fHHcH9|H H(H9t hHHt#HuHhHDžHDžHDžHDžHDž~!H 1fHHcH9|H(H0H9t hHHt#HuHhHDžHDžHDžHDžHDž~!H1fHHcH9|HHH9t hHpHt#HuH8hHDžpHDž`HDžXHDžPHDžH<~!Hx1fHHc3T3HHH33HHHHp"HHHp"HHHHHHHHHHHHLHtHu HHDžHH@H@H@H~H 1HHcH9|H(H0H9}HqlHHHHp\!HHHHLMLHtHu HHDžHH@H@H@H~H 1HHcH9|H(H0H9H~HHHLMLHtHu HHDžHH@H@H@H~H1HHcH9|H H(H9HHHHHLMLHtHu HxHDžHH@H@H@H|~H1HHc|H9|HHH9HHHMH8HHHPHLMLHtHu HHDžPH(H@H@H@H~HX1HHcH9|H`HhH9HHHLMLHH8HHHHLMLHtHu HHDžHH@H@H@H~H1HHcH9|HHH9t#HHLMLHHH8HtHu HHDž8HH@$H@H@H@ ~H@1HHcH9|HHHPH9tHHHHH8HCYHH8HtHu HHDž8HH@$H@H@H@ ~H@1HHcH9|HHHPH9tH HHH HHHH%HHpLHHHHtHu HXHDžHhH@H@H@H\~H1HHc\H9|HHH9HHKHHHHpHtHu H8HDžpHHH@H@H@H<~Hx1HHcB*>k>!2>>+?!L?}?"ѳ?-@Q5@y2@/A VYAA@BBB B}aC C i Dm@D~tD/EdEFNFN|FIGKG!УlGtGG!G:HTH!uHHI!ל5IRII!mIII/J+JJoK:K2K֬KӫL4[L%ǩLܨL$$L?MMڤNHN'N J,O?uOy P`PX?Q {Q!QQ Q!XR2:R tR!RR -S!NSkS S!QS =T\T1kT TfPUUU :UU4VVWWIW WOW¤9XXOYZ/v[,[\#%4\hh\F ]So]N]]Zm^"y^%b^It__ `';`o`—$aYIbʗbbbؖcc'dBd| d8e beLefOfGff\g Tggxh)iiyijq kika4lPlkllljWmm!Ҵmʴm+mhmf/n d^nbn Ŵnn!no `&o.Bogo ooo bpԱp^p q:8qRq _qsqqq *r~Grqr rnr^"s tsEs!s t)"tMt uttt tu?u uuuu^wtxlaydz\zTq{L!|D|<z}41~,~$A QQ܋ԋa̋ċq!uQ , =U f~  Ό  8 If woW h #ǐ, =H YƓLq ?{JЖ/"}~w~A >}T ep  Ϝڜ  [/'7d  *5 Fvm~ # 4? P[ ll   ȣӣ    +6 G7n  -8 IT e} 3~ c) ˫~k i%د~g~*= Nױ o- մ ".ɶ&i I~"»i IuY9~yvnufIu^uVNtt! }l !. :p!a Yo Fnq !Q 1 ~ ZQ} o d u  wg  I t d  p x '+~g^!src.empty()findTransformECC/Users/build/buildAgent/work/b5d3ba53e49a4b81/build-victor-deps/build-opencv/opencv/modules/video/src/ecc.cpp!dst.empty()Both input images must have the same data typeImages must have 8uC1 or 32fC1 typewarpMatrix must be single-channel floating-point matrixmap.cols == 3map.rows == 2 || map.rows ==3motionType == MOTION_AFFINE || motionType == MOTION_HOMOGRAPHY || motionType == MOTION_EUCLIDEAN || motionType == MOTION_TRANSLATIONmap.rows ==3criteria.type & TermCriteria::COUNT || criteria.type & TermCriteria::EPSNaN encountered.The algorithm stopped before its convergence. The correlation is going to be minimized. Images may be uncorrelated or non-overlappedsrc1.size() == src2.size()image_jacobian_affine_ECCsrc1.size() == src3.size()src1.size() == src4.size()src1.rows == dst.rowsdst.cols == (6*src1.cols)dst.type() == (((5) & ((1 << 3) - 1)) + (((1)-1) << 3))image_jacobian_homo_ECCdst.cols == (src1.cols*8)src5.isContinuous()src1.size()==src2.size()image_jacobian_translation_ECCdst.cols == (src1.cols*2)image_jacobian_euclidean_ECCsrc1.size()==src3.size()src1.size()==src4.size()dst.cols == (src1.cols*3)src1.rows == src2.rowsproject_onto_jacobian_ECC(src1.cols % src2.cols) == 0dst.cols == dst.rowsmap_matrix.type() == (((5) & ((1 << 3) - 1)) + (((1)-1) << 3))update_warping_matrix_ECCupdate.type() == (((5) & ((1 << 3) - 1)) + (((1)-1) << 3))motionType == MOTION_TRANSLATION || motionType == MOTION_EUCLIDEAN || motionType == MOTION_AFFINE || motionType == MOTION_HOMOGRAPHYmap_matrix.rows == 3 && update.rows == 8map_matrix.rows == 2 && update.rows == 6map_matrix.rows == 2 && update.rows == 3map_matrix.rows == 2 && update.rows == 2update.cols == 1map_matrix.isContinuous()update.isContinuous()6XAP XA$AzPLRx 4$6AC P4\ AC P,(AC B----X -7- -- -3-4----` -9-1-$- --- ----C ------------t- -.--4- -J- -.-a-----4 - -#----z-g`)----2-*-"--- ------------------z-r-j-b-Z-R-J- --Q -*- --! -- -Z- --A -- -z- --a -:- --! -- -j- -ʾ-Q -*- -- --q -J-ʻ --* -- -j- -ʹ-Q -*- -- --q -J-Ѷ --* --w-G-(- --ݴ-δ------ ---5 ----w -)--߱----b-R-E-6-.-$-- -k-^-R- ---- ----q -- ---s -L-!---Ь-----|- -ϫ-«---1 ---k -+-- ---é---; -----~-e-@- --- -i-\-M-@-1-$-----v -;-.- --|-t-l-d-Z-K->-/-"-----Ԥ------- --ۣ-̣------x-p-c- ------x-p-c-T-G-8-+------u -F->-6-.---~ -J-=-.-!------l -;-3-+-- -z- -ڝ-c -+-#--- ----Ӝ-Ɯ-----x-i-\-M-0-!--- -- -d-\-J-B-5- ---u-^-T-E-;-/- -{-^- -Ř---* -Ɨ---7 -ܖ-Ԗ-ǖ-R - --- -C-6- --y-j-b-P-C-Γ -----}-u-m-e-]-P-A-4-%----- -ː---+ ----y-l-_-P-)-- - -{-n-_-M-@-1-$-----ߌ-Ҍ-Ō----x-p-h-`-X-P-H-@-8-0-(- ---------؋-Ћ-ȋ--------w-j-]-N-A-4-%-7- -ي8=ʊ-Y -*- --) --y -J-ɇ -- --i -:- -- -ڄ-Y -*- -z- -ʂ-Y -*- 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E  7p u R    ~ "  x&  pc v ~wwB }u!h  `!J BM Xk |t}u!d \!F >I Tg xpOOKV=6|9:79j(9t|9=V=X!|9yl9d9\9T9L98t9'" 9'95D9} 9#=<j %< < B>= ;\ %; ; >= = #= = < i<M %M<r E< %< <@<Q%$<v <%;<<7;]:wH:%,: $:*k=n:%9 9^::%: :A)k=9%9 9|:: %:2 :2:52:< x@+?q>>%>1 ?(>>v>?"6!>W>@!@@ @!c@! ;l"i;F" <\#i+F$z~:$bv:%kn:%up<& :l& 8x& ?9'8^'!8'l8E)8)!8)l8+=+=`,}=H.=}.=.=Z0#80#8F1=1=2/%=.3(;C3 ;3 :3 <3,<4i:O4%M:t4 :4<4<4,x<5En<E5E<5E2;5C-;6:K6:}6 :696969%79O79v797 97+97 ;89 99 :/: @:P: a:: :: :; ;U;o;; ;'< 8<P< a<< <(= 6=> >?v??p@@ @@jFAFLBi3FCi#FCz FVDbFDkEYEuEE EE`[ n0 f> q |z)')'{)'''y''virtual void cv::detail::LKTrackerInvoker::operator()(const cv::Range &) const/Users/build/buildAgent/work/b5d3ba53e49a4b81/build-victor-deps/build-opencv/opencv/modules/video/src/lkpyramid.cppstatus != __nulloperator()int cv::buildOpticalFlowPyramid(cv::InputArray, cv::OutputArrayOfArrays, cv::Size, int, bool, int, int, bool)img.depth() == 0 && winSize.width > 2 && winSize.height > 2buildOpticalFlowPyramidcv::Mat cv::estimateRigidTransform(cv::InputArray, cv::InputArray, bool)Both input images must have the same sizeestimateRigidTransformBoth input images must have the same data typecn == 1 || cn == 3 || cn == 4Both input images must have either 8uC1 or 8uC3 typetotal() == 0 || data != __nullMat/Users/build/buildAgent/work/b5d3ba53e49a4b81/build-victor-deps/build-opencv/opencv/modules/core/include/opencv2/core/mat.inl.hppStep must be a multiple of esz1depth == 0calcSharrDerivM.isContinuous()getRTMatrixvirtual void cv::(anonymous namespace)::SparsePyrLKOpticalFlowImpl::calc(cv::InputArray, cv::InputArray, cv::InputArray, cv::InputOutputArray, cv::OutputArray, cv::OutputArray)maxLevel >= 0 && winSize.width > 2 && winSize.height > 2calc(npoints = prevPtsMat.checkVector(2, 5, true)) >= 0nextPtsMat.checkVector(2, 5, true) == npointsstatusMat.isContinuous()errMat.isContinuous()levels1 >= 0ofs.x >= winSize.width && ofs.y >= winSize.height && ofs.x + prevPyr[lvlStep1].cols + winSize.width <= fullSize.width && ofs.y + prevPyr[lvlStep1].rows + winSize.height <= fullSize.heightlevels2 >= 0ofs.x >= winSize.width && ofs.y >= winSize.height && ofs.x + nextPyr[lvlStep2].cols + winSize.width <= fullSize.width && ofs.y + nextPyr[lvlStep2].rows + winSize.height <= fullSize.heightprevPyr[level * lvlStep1].size() == nextPyr[level * lvlStep2].size()prevPyr[level * lvlStep1].type() == nextPyr[level * lvlStep2].type()lkSparseallocator::allocate(size_t n) 'n' exceeds maximum supported size -D CPU-D WAVE_SIZE=%d -D WSX=%d -D WSY=%dI.depth() == 5 && J.depth() == 5lkSparse_runN2cv6detail16LKTrackerInvokerEN2cv12_GLOBAL__N_126SparsePyrLKOpticalFlowImplEN2cv22SparsePyrLKOpticalFlowEN2cv17SparseOpticalFlowEN2cv6detail12PtrOwnerImplINS_12_GLOBAL__N_126SparsePyrLKOpticalFlowImplENS_14DefaultDeleterIS3_EEEEN2cv6detail8PtrOwnerE  @XA[XAp2? 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namespace)::FarnebackOpticalFlowImpl::calc(cv::InputArray, cv::InputArray, cv::InputOutputArray)prev0.size() == next0.size() && prev0.channels() == next0.channels() && prev0.channels() == 1 && pyrScale_ < 1calcframe0.channels() == 1 && frame1.channels() == 1operator()frame0.size() == frame1.size()polyN_ == 5 || polyN_ == 7!fastPyramids_ || std::abs(pyrScale_ - 0.5) < 1e-6total() == 0 || data != __nullMat/Users/build/buildAgent/work/b5d3ba53e49a4b81/build-victor-deps/build-opencv/opencv/modules/core/include/opencv2/core/mat.inl.hppStep must be a multiple of esz1-D polyN=%dpolynomialExpansiongaussianBlurdst.size() == src.size()gaussianBlurOclupdateMatricesgaussianBlur5updateFlowboxFilter5src.type() == (((5) & ((1 << 3) - 1)) + (((1)-1) << 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#1/36 1548786668 501 20 100644 36092 ` opencl_kernels_video.cpp.o 8__text__TEXT__cstring__TEXT__data__DATAЊp$ 0 Pvideobgfg_mog2#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 inline float sum(float val) { return val; } #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; inline float sum(const float4 val) { return (val.x + val.y + val.z); } #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]; T_MEAN pix_mean = pix * c_mean; float numerator = sum(pix_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 } } a502386253c964907c0593109986217doptical_flow_farneback#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; } } 529300e6242f574f83d11a089cc120c0optical_flow_tvl1__kernel void centeredGradientKernel(__global const float* src_ptr, int src_col, int src_row, int src_step, __global float* dx, __global float* dy, int d_step) { int x = get_global_id(0); int y = get_global_id(1); if((x < src_col)&&(y < src_row)) { int src_x1 = (x + 1) < (src_col -1)? (x + 1) : (src_col - 1); int src_x2 = (x - 1) > 0 ? (x -1) : 0; dx[y * d_step+ x] = 0.5f * (src_ptr[y * src_step + src_x1] - src_ptr[y * src_step+ src_x2]); int src_y1 = (y+1) < (src_row - 1) ? (y + 1) : (src_row - 1); int src_y2 = (y - 1) > 0 ? (y - 1) : 0; dy[y * d_step+ x] = 0.5f * (src_ptr[src_y1 * src_step + x] - src_ptr[src_y2 * src_step+ x]); } } inline float bicubicCoeff(float x_) { float x = fabs(x_); if (x <= 1.0f) return x * x * (1.5f * x - 2.5f) + 1.0f; else if (x < 2.0f) return x * (x * (-0.5f * x + 2.5f) - 4.0f) + 2.0f; else return 0.0f; } __kernel void warpBackwardKernel(__global const float* I0, int I0_step, int I0_col, int I0_row, image2d_t tex_I1, image2d_t tex_I1x, image2d_t tex_I1y, __global const float* u1, int u1_step, __global const float* u2, __global float* I1w, __global float* I1wx, __global float* I1wy, __global float* grad, __global float* rho, int I1w_step, int u2_step, int u1_offset_x, int u1_offset_y, int u2_offset_x, int u2_offset_y) { int x = get_global_id(0); int y = get_global_id(1); if(x < I0_col&&y < I0_row) { float u1Val = u1[(y + u1_offset_y) * u1_step + x + u1_offset_x]; float u2Val = u2[(y + u2_offset_y) * u2_step + x + u2_offset_x]; float wx = x + u1Val; float wy = y + u2Val; int xmin = ceil(wx - 2.0f); int xmax = floor(wx + 2.0f); int ymin = ceil(wy - 2.0f); int ymax = floor(wy + 2.0f); float sum = 0.0f; float sumx = 0.0f; float sumy = 0.0f; float wsum = 0.0f; sampler_t sampleri = CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP_TO_EDGE | CLK_FILTER_NEAREST; for (int cy = ymin; cy <= ymax; ++cy) { for (int cx = xmin; cx <= xmax; ++cx) { float w = bicubicCoeff(wx - cx) * bicubicCoeff(wy - cy); int2 cood = (int2)(cx, cy); sum += w * read_imagef(tex_I1, sampleri, cood).x; sumx += w * read_imagef(tex_I1x, sampleri, cood).x; sumy += w * read_imagef(tex_I1y, sampleri, cood).x; wsum += w; } } float coeff = 1.0f / wsum; float I1wVal = sum * coeff; float I1wxVal = sumx * coeff; float I1wyVal = sumy * coeff; I1w[y * I1w_step + x] = I1wVal; I1wx[y * I1w_step + x] = I1wxVal; I1wy[y * I1w_step + x] = I1wyVal; float Ix2 = I1wxVal * I1wxVal; float Iy2 = I1wyVal * I1wyVal; grad[y * I1w_step + x] = Ix2 + Iy2; float I0Val = I0[y * I0_step + x]; rho[y * I1w_step + x] = I1wVal - I1wxVal * u1Val - I1wyVal * u2Val - I0Val; } } inline float readImage(__global const float *image, int x, int y, int rows, int cols, int elemCntPerRow) { int i0 = clamp(x, 0, cols - 1); int j0 = clamp(y, 0, rows - 1); return image[j0 * elemCntPerRow + i0]; } __kernel void warpBackwardKernelNoImage2d(__global const float* I0, int I0_step, int I0_col, int I0_row, __global const float* tex_I1, __global const float* tex_I1x, __global const float* tex_I1y, __global const float* u1, int u1_step, __global const float* u2, __global float* I1w, __global float* I1wx, __global float* I1wy, __global float* grad, __global float* rho, int I1w_step, int u2_step, int I1_step, int I1x_step) { int x = get_global_id(0); int y = get_global_id(1); if(x < I0_col&&y < I0_row) { float u1Val = u1[y * u1_step + x]; float u2Val = u2[y * u2_step + x]; float wx = x + u1Val; float wy = y + u2Val; int xmin = ceil(wx - 2.0f); int xmax = floor(wx + 2.0f); int ymin = ceil(wy - 2.0f); int ymax = floor(wy + 2.0f); float sum = 0.0f; float sumx = 0.0f; float sumy = 0.0f; float wsum = 0.0f; for (int cy = ymin; cy <= ymax; ++cy) { for (int cx = xmin; cx <= xmax; ++cx) { float w = bicubicCoeff(wx - cx) * bicubicCoeff(wy - cy); int2 cood = (int2)(cx, cy); sum += w * readImage(tex_I1, cood.x, cood.y, I0_col, I0_row, I1_step); sumx += w * readImage(tex_I1x, cood.x, cood.y, I0_col, I0_row, I1x_step); sumy += w * readImage(tex_I1y, cood.x, cood.y, I0_col, I0_row, I1x_step); wsum += w; } } float coeff = 1.0f / wsum; float I1wVal = sum * coeff; float I1wxVal = sumx * coeff; float I1wyVal = sumy * coeff; I1w[y * I1w_step + x] = I1wVal; I1wx[y * I1w_step + x] = I1wxVal; I1wy[y * I1w_step + x] = I1wyVal; float Ix2 = I1wxVal * I1wxVal; float Iy2 = I1wyVal * I1wyVal; grad[y * I1w_step + x] = Ix2 + Iy2; float I0Val = I0[y * I0_step + x]; rho[y * I1w_step + x] = I1wVal - I1wxVal * u1Val - I1wyVal * u2Val - I0Val; } } __kernel void estimateDualVariablesKernel(__global const float* u1, int u1_col, int u1_row, int u1_step, __global const float* u2, __global float* p11, int p11_step, __global float* p12, __global float* p21, __global float* p22, float taut, int u2_step, int u1_offset_x, int u1_offset_y, int u2_offset_x, int u2_offset_y) { int x = get_global_id(0); int y = get_global_id(1); if(x < u1_col && y < u1_row) { int src_x1 = (x + 1) < (u1_col - 1) ? (x + 1) : (u1_col - 1); float u1x = u1[(y + u1_offset_y) * u1_step + src_x1 + u1_offset_x] - u1[(y + u1_offset_y) * u1_step + x + u1_offset_x]; int src_y1 = (y + 1) < (u1_row - 1) ? (y + 1) : (u1_row - 1); float u1y = u1[(src_y1 + u1_offset_y) * u1_step + x + u1_offset_x] - u1[(y + u1_offset_y) * u1_step + x + u1_offset_x]; int src_x2 = (x + 1) < (u1_col - 1) ? (x + 1) : (u1_col - 1); float u2x = u2[(y + u2_offset_y) * u2_step + src_x2 + u2_offset_x] - u2[(y + u2_offset_y) * u2_step + x + u2_offset_x]; int src_y2 = (y + 1) < (u1_row - 1) ? (y + 1) : (u1_row - 1); float u2y = u2[(src_y2 + u2_offset_y) * u2_step + x + u2_offset_x] - u2[(y + u2_offset_y) * u2_step + x + u2_offset_x]; float g1 = hypot(u1x, u1y); float g2 = hypot(u2x, u2y); float ng1 = 1.0f + taut * g1; float ng2 = 1.0f + taut * g2; p11[y * p11_step + x] = (p11[y * p11_step + x] + taut * u1x) / ng1; p12[y * p11_step + x] = (p12[y * p11_step + x] + taut * u1y) / ng1; p21[y * p11_step + x] = (p21[y * p11_step + x] + taut * u2x) / ng2; p22[y * p11_step + x] = (p22[y * p11_step + x] + taut * u2y) / ng2; } } inline float divergence(__global const float* v1, __global const float* v2, int y, int x, int v1_step, int v2_step) { if (x > 0 && y > 0) { float v1x = v1[y * v1_step + x] - v1[y * v1_step + x - 1]; float v2y = v2[y * v2_step + x] - v2[(y - 1) * v2_step + x]; return v1x + v2y; } else { if (y > 0) return v1[y * v1_step + 0] + v2[y * v2_step + 0] - v2[(y - 1) * v2_step + 0]; else { if (x > 0) return v1[0 * v1_step + x] - v1[0 * v1_step + x - 1] + v2[0 * v2_step + x]; else return v1[0 * v1_step + 0] + v2[0 * v2_step + 0]; } } } __kernel void estimateUKernel(__global const float* I1wx, int I1wx_col, int I1wx_row, int I1wx_step, __global const float* I1wy, __global const float* grad, __global const float* rho_c, __global const float* p11, __global const float* p12, __global const float* p21, __global const float* p22, __global float* u1, int u1_step, __global float* u2, __global float* error, float l_t, float theta, int u2_step, int u1_offset_x, int u1_offset_y, int u2_offset_x, int u2_offset_y, char calc_error) { int x = get_global_id(0); int y = get_global_id(1); if(x < I1wx_col && y < I1wx_row) { float I1wxVal = I1wx[y * I1wx_step + x]; float I1wyVal = I1wy[y * I1wx_step + x]; float gradVal = grad[y * I1wx_step + x]; float u1OldVal = u1[(y + u1_offset_y) * u1_step + x + u1_offset_x]; float u2OldVal = u2[(y + u2_offset_y) * u2_step + x + u2_offset_x]; float rho = rho_c[y * I1wx_step + x] + (I1wxVal * u1OldVal + I1wyVal * u2OldVal); float d1 = 0.0f; float d2 = 0.0f; if (rho < -l_t * gradVal) { d1 = l_t * I1wxVal; d2 = l_t * I1wyVal; } else if (rho > l_t * gradVal) { d1 = -l_t * I1wxVal; d2 = -l_t * I1wyVal; } else if (gradVal > 1.192092896e-07f) { float fi = -rho / gradVal; d1 = fi * I1wxVal; d2 = fi * I1wyVal; } float v1 = u1OldVal + d1; float v2 = u2OldVal + d2; float div_p1 = divergence(p11, p12, y, x, I1wx_step, I1wx_step); float div_p2 = divergence(p21, p22, y, x, I1wx_step, I1wx_step); float u1NewVal = v1 + theta * div_p1; float u2NewVal = v2 + theta * div_p2; u1[(y + u1_offset_y) * u1_step + x + u1_offset_x] = u1NewVal; u2[(y + u2_offset_y) * u2_step + x + u2_offset_x] = u2NewVal; if(calc_error) { float n1 = (u1OldVal - u1NewVal) * (u1OldVal - u1NewVal); float n2 = (u2OldVal - u2NewVal) * (u2OldVal - u2NewVal); error[y * I1wx_step + x] = n1 + n2; } } } 9474ca90cbcc7660f6c47b8a45d6730dpyrlk#define GRIDSIZE 3 #define LSx 8 #define LSy 8 #define LM_W (LSx*GRIDSIZE+2) #define LM_H (LSy*GRIDSIZE+2) #define BUFFER (LSx*LSy) #define BUFFER2 BUFFER>>1 #ifndef WAVE_SIZE #define WAVE_SIZE 1 #endif #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; smem2[tid] = val2; smem3[tid] = val3; 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]; smem3[tid] += smem3[tid + i]; } barrier(CLK_LOCAL_MEM_FENCE); } } inline void reduce2(float val1, float val2, volatile __local float* smem1, volatile __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]; smem2[tid] += smem2[tid + i]; } barrier(CLK_LOCAL_MEM_FENCE); } } inline void reduce1(float val1, volatile __local float* smem1, int tid) { smem1[tid] = val1; barrier(CLK_LOCAL_MEM_FENCE); for(int i = BUFFER2; i > 0; i >>= 1) { if(tid < i) { smem1[tid] += smem1[tid + i]; } barrier(CLK_LOCAL_MEM_FENCE); } } #else inline void reduce3(float val1, float val2, float val3, __local volatile float* smem1, __local volatile float* smem2, __local volatile float* smem3, int tid) { smem1[tid] = val1; smem2[tid] = val2; smem3[tid] = val3; barrier(CLK_LOCAL_MEM_FENCE); if (tid < 32) { smem1[tid] += smem1[tid + 32]; smem2[tid] += smem2[tid + 32]; smem3[tid] += smem3[tid + 32]; #if WAVE_SIZE < 32 } barrier(CLK_LOCAL_MEM_FENCE); if (tid < 16) { #endif smem1[tid] += smem1[tid + 16]; smem2[tid] += smem2[tid + 16]; smem3[tid] += smem3[tid + 16]; #if WAVE_SIZE <16 } barrier(CLK_LOCAL_MEM_FENCE); if (tid<1) { #endif local float8* m1 = (local float8*)smem1; local float8* m2 = (local float8*)smem2; local float8* m3 = (local float8*)smem3; float8 t1 = m1[0]+m1[1]; float8 t2 = m2[0]+m2[1]; float8 t3 = m3[0]+m3[1]; float4 t14 = t1.lo + t1.hi; float4 t24 = t2.lo + t2.hi; float4 t34 = t3.lo + t3.hi; smem1[0] = t14.x+t14.y+t14.z+t14.w; smem2[0] = t24.x+t24.y+t24.z+t24.w; smem3[0] = t34.x+t34.y+t34.z+t34.w; } barrier(CLK_LOCAL_MEM_FENCE); } inline void reduce2(float val1, float val2, __local volatile float* smem1, __local volatile 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]; #if WAVE_SIZE < 32 } barrier(CLK_LOCAL_MEM_FENCE); if (tid < 16) { #endif smem1[tid] += smem1[tid + 16]; smem2[tid] += smem2[tid + 16]; #if WAVE_SIZE <16 } barrier(CLK_LOCAL_MEM_FENCE); if (tid<1) { #endif local float8* m1 = (local float8*)smem1; local float8* m2 = (local float8*)smem2; float8 t1 = m1[0]+m1[1]; float8 t2 = m2[0]+m2[1]; float4 t14 = t1.lo + t1.hi; float4 t24 = t2.lo + t2.hi; smem1[0] = t14.x+t14.y+t14.z+t14.w; smem2[0] = t24.x+t24.y+t24.z+t24.w; } barrier(CLK_LOCAL_MEM_FENCE); } inline void reduce1(float val1, __local volatile float* smem1, int tid) { smem1[tid] = val1; barrier(CLK_LOCAL_MEM_FENCE); if (tid < 32) { smem1[tid] += smem1[tid + 32]; #if WAVE_SIZE < 32 } barrier(CLK_LOCAL_MEM_FENCE); if (tid < 16) { #endif smem1[tid] += smem1[tid + 16]; #if WAVE_SIZE <16 } barrier(CLK_LOCAL_MEM_FENCE); if (tid<1) { #endif local float8* m1 = (local float8*)smem1; float8 t1 = m1[0]+m1[1]; float4 t14 = t1.lo + t1.hi; smem1[0] = t14.x+t14.y+t14.z+t14.w; } 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); } } bb795566482a0fd9c80aabca645bf9ee< =2=]]]ވxh`XP@80(xTyP"(__ZN2cv3ocl5video12pyrlk_oclsrcE__ZN2cv3ocl5video29optical_flow_farneback_oclsrcE__ZN2cv3ocl5video16bgfg_mog2_oclsrcE__ZN2cv3ocl5video24optical_flow_tvl1_oclsrcE