OpenCV  4.1.1-pre
Open Source Computer Vision
Looking for a C++ dev who knows OpenCV?
I'm looking for work. Hire me!
cv::gapi::core Namespace Reference

Namespaces

 cpu
 
 fluid
 
 gpu
 
 ocl
 

Typedefs

using GMat2 = std::tuple< GMat, GMat >
 
using GMat3 = std::tuple< GMat, GMat, GMat >
 
using GMat4 = std::tuple< GMat, GMat, GMat, GMat >
 
using GMatScalar = std::tuple< GMat, GScalar >
 

Functions

 G_TYPED_KERNEL (GAdd,< GMat(GMat, GMat, int)>, "org.opencv.core.math.add")
 
 G_TYPED_KERNEL (GAddC,< GMat(GMat, GScalar, int)>, "org.opencv.core.math.addC")
 
 G_TYPED_KERNEL (GSub,< GMat(GMat, GMat, int)>, "org.opencv.core.math.sub")
 
 G_TYPED_KERNEL (GSubC,< GMat(GMat, GScalar, int)>, "org.opencv.core.math.subC")
 
 G_TYPED_KERNEL (GSubRC,< GMat(GScalar, GMat, int)>, "org.opencv.core.math.subRC")
 
 G_TYPED_KERNEL (GMul,< GMat(GMat, GMat, double, int)>, "org.opencv.core.math.mul")
 
 G_TYPED_KERNEL (GMulCOld,< GMat(GMat, double, int)>, "org.opencv.core.math.mulCOld")
 
 G_TYPED_KERNEL (GMulC,< GMat(GMat, GScalar, int)>, "org.opencv.core.math.mulC")
 
 G_TYPED_KERNEL (GMulS,< GMat(GMat, GScalar)>, "org.opencv.core.math.muls")
 
 G_TYPED_KERNEL (GDiv,< GMat(GMat, GMat, double, int)>, "org.opencv.core.math.div")
 
 G_TYPED_KERNEL (GDivC,< GMat(GMat, GScalar, double, int)>, "org.opencv.core.math.divC")
 
 G_TYPED_KERNEL (GDivRC,< GMat(GScalar, GMat, double, int)>, "org.opencv.core.math.divRC")
 
 G_TYPED_KERNEL (GMean,< GScalar(GMat)>, "org.opencv.core.math.mean")
 
 G_TYPED_KERNEL (GPhase,< GMat(GMat, GMat, bool)>, "org.opencv.core.math.phase")
 
 G_TYPED_KERNEL (GMask,< GMat(GMat, GMat)>, "org.opencv.core.pixelwise.mask")
 
 G_TYPED_KERNEL (GCmpGT,< GMat(GMat, GMat)>, "org.opencv.core.pixelwise.compare.cmpGT")
 
 G_TYPED_KERNEL (GCmpGE,< GMat(GMat, GMat)>, "org.opencv.core.pixelwise.compare.cmpGE")
 
 G_TYPED_KERNEL (GCmpLE,< GMat(GMat, GMat)>, "org.opencv.core.pixelwise.compare.cmpLE")
 
 G_TYPED_KERNEL (GCmpLT,< GMat(GMat, GMat)>, "org.opencv.core.pixelwise.compare.cmpLT")
 
 G_TYPED_KERNEL (GCmpEQ,< GMat(GMat, GMat)>, "org.opencv.core.pixelwise.compare.cmpEQ")
 
 G_TYPED_KERNEL (GCmpNE,< GMat(GMat, GMat)>, "org.opencv.core.pixelwise.compare.cmpNE")
 
 G_TYPED_KERNEL (GCmpGTScalar,< GMat(GMat, GScalar)>, "org.opencv.core.pixelwise.compare.cmpGTScalar")
 
 G_TYPED_KERNEL (GCmpGEScalar,< GMat(GMat, GScalar)>, "org.opencv.core.pixelwise.compare.cmpGEScalar")
 
 G_TYPED_KERNEL (GCmpLEScalar,< GMat(GMat, GScalar)>, "org.opencv.core.pixelwise.compare.cmpLEScalar")
 
 G_TYPED_KERNEL (GCmpLTScalar,< GMat(GMat, GScalar)>, "org.opencv.core.pixelwise.compare.cmpLTScalar")
 
 G_TYPED_KERNEL (GCmpEQScalar,< GMat(GMat, GScalar)>, "org.opencv.core.pixelwise.compare.cmpEQScalar")
 
 G_TYPED_KERNEL (GCmpNEScalar,< GMat(GMat, GScalar)>, "org.opencv.core.pixelwise.compare.cmpNEScalar")
 
 G_TYPED_KERNEL (GAnd,< GMat(GMat, GMat)>, "org.opencv.core.pixelwise.bitwise_and")
 
 G_TYPED_KERNEL (GAndS,< GMat(GMat, GScalar)>, "org.opencv.core.pixelwise.bitwise_andS")
 
 G_TYPED_KERNEL (GOr,< GMat(GMat, GMat)>, "org.opencv.core.pixelwise.bitwise_or")
 
 G_TYPED_KERNEL (GOrS,< GMat(GMat, GScalar)>, "org.opencv.core.pixelwise.bitwise_orS")
 
 G_TYPED_KERNEL (GXor,< GMat(GMat, GMat)>, "org.opencv.core.pixelwise.bitwise_xor")
 
 G_TYPED_KERNEL (GXorS,< GMat(GMat, GScalar)>, "org.opencv.core.pixelwise.bitwise_xorS")
 
 G_TYPED_KERNEL (GNot,< GMat(GMat)>, "org.opencv.core.pixelwise.bitwise_not")
 
 G_TYPED_KERNEL (GSelect,< GMat(GMat, GMat, GMat)>, "org.opencv.core.pixelwise.select")
 
 G_TYPED_KERNEL (GMin,< GMat(GMat, GMat)>, "org.opencv.core.matrixop.min")
 
 G_TYPED_KERNEL (GMax,< GMat(GMat, GMat)>, "org.opencv.core.matrixop.max")
 
 G_TYPED_KERNEL (GAbsDiff,< GMat(GMat, GMat)>, "org.opencv.core.matrixop.absdiff")
 
 G_TYPED_KERNEL (GAbsDiffC,< GMat(GMat, GScalar)>, "org.opencv.core.matrixop.absdiffC")
 
 G_TYPED_KERNEL (GSum,< GScalar(GMat)>, "org.opencv.core.matrixop.sum")
 
 G_TYPED_KERNEL (GAddW,< GMat(GMat, double, GMat, double, double, int)>, "org.opencv.core.matrixop.addweighted")
 
 G_TYPED_KERNEL (GNormL1,< GScalar(GMat)>, "org.opencv.core.matrixop.norml1")
 
 G_TYPED_KERNEL (GNormL2,< GScalar(GMat)>, "org.opencv.core.matrixop.norml2")
 
 G_TYPED_KERNEL (GNormInf,< GScalar(GMat)>, "org.opencv.core.matrixop.norminf")
 
 G_TYPED_KERNEL (GThreshold,< GMat(GMat, GScalar, GScalar, int)>, "org.opencv.core.matrixop.threshold")
 
 G_TYPED_KERNEL (GInRange,< GMat(GMat, GScalar, GScalar)>, "org.opencv.core.matrixop.inrange")
 
 G_TYPED_KERNEL (GResize,< GMat(GMat, Size, double, double, int)>, "org.opencv.core.transform.resize")
 
 G_TYPED_KERNEL (GResizeP,< GMatP(GMatP, Size, int)>, "org.opencv.core.transform.resizeP")
 
 G_TYPED_KERNEL (GMerge3,< GMat(GMat, GMat, GMat)>, "org.opencv.core.transform.merge3")
 
 G_TYPED_KERNEL (GMerge4,< GMat(GMat, GMat, GMat, GMat)>, "org.opencv.core.transform.merge4")
 
 G_TYPED_KERNEL (GRemap,< GMat(GMat, Mat, Mat, int, int, Scalar)>, "org.opencv.core.transform.remap")
 
 G_TYPED_KERNEL (GFlip,< GMat(GMat, int)>, "org.opencv.core.transform.flip")
 
 G_TYPED_KERNEL (GCrop,< GMat(GMat, Rect)>, "org.opencv.core.transform.crop")
 
 G_TYPED_KERNEL (GConcatHor,< GMat(GMat, GMat)>, "org.opencv.imgproc.transform.concatHor")
 
 G_TYPED_KERNEL (GConcatVert,< GMat(GMat, GMat)>, "org.opencv.imgproc.transform.concatVert")
 
 G_TYPED_KERNEL (GLUT,< GMat(GMat, Mat)>, "org.opencv.core.transform.LUT")
 
 G_TYPED_KERNEL (GConvertTo,< GMat(GMat, int, double, double)>, "org.opencv.core.transform.convertTo")
 
 G_TYPED_KERNEL (GSqrt,< GMat(GMat)>, "org.opencv.core.math.sqrt")
 
 G_TYPED_KERNEL (GNormalize,< GMat(GMat, double, double, int, int)>, "org.opencv.core.normalize")
 
 G_TYPED_KERNEL_M (GPolarToCart,< GMat2(GMat, GMat, bool)>, "org.opencv.core.math.polarToCart")
 
 G_TYPED_KERNEL_M (GCartToPolar,< GMat2(GMat, GMat, bool)>, "org.opencv.core.math.cartToPolar")
 
 G_TYPED_KERNEL_M (GIntegral,< GMat2(GMat, int, int)>, "org.opencv.core.matrixop.integral")
 
 G_TYPED_KERNEL_M (GThresholdOT,< GMatScalar(GMat, GScalar, int)>, "org.opencv.core.matrixop.thresholdOT")
 
 G_TYPED_KERNEL_M (GSplit3,< GMat3(GMat)>, "org.opencv.core.transform.split3")
 
 G_TYPED_KERNEL_M (GSplit4,< GMat4(GMat)>,"org.opencv.core.transform.split4")
 

Typedef Documentation

◆ GMat2

using cv::gapi::core::GMat2 = typedef std::tuple<GMat,GMat>

◆ GMat3

using cv::gapi::core::GMat3 = typedef std::tuple<GMat,GMat,GMat>

◆ GMat4

using cv::gapi::core::GMat4 = typedef std::tuple<GMat,GMat,GMat,GMat>

◆ GMatScalar

using cv::gapi::core::GMatScalar = typedef std::tuple<GMat, GScalar>

Function Documentation

◆ G_TYPED_KERNEL() [1/59]

cv::gapi::core::G_TYPED_KERNEL ( GAdd  ,
< GMat(GMat, GMat, int)>  ,
"org.opencv.core.math.add"   
)

References cv::GMatDesc::chan, cv::GMatDesc::depth, and cv::GMatDesc::withDepth().

Here is the call graph for this function:

◆ G_TYPED_KERNEL() [2/59]

cv::gapi::core::G_TYPED_KERNEL ( GAddC  ,
< GMat(GMat, GScalar, int)>  ,
"org.opencv.core.math.addC"   
)

References cv::GMatDesc::withDepth().

Here is the call graph for this function:

◆ G_TYPED_KERNEL() [3/59]

cv::gapi::core::G_TYPED_KERNEL ( GSub  ,
< GMat(GMat, GMat, int)>  ,
"org.opencv.core.math.sub"   
)

References cv::GMatDesc::chan, cv::GMatDesc::depth, cv::gapi::max(), and cv::GMatDesc::withDepth().

Here is the call graph for this function:

◆ G_TYPED_KERNEL() [4/59]

cv::gapi::core::G_TYPED_KERNEL ( GSubC  ,
< GMat(GMat, GScalar, int)>  ,
"org.opencv.core.math.subC"   
)

References cv::GMatDesc::withDepth().

Here is the call graph for this function:

◆ G_TYPED_KERNEL() [5/59]

cv::gapi::core::G_TYPED_KERNEL ( GSubRC  ,
< GMat(GScalar, GMat, int)>  ,
"org.opencv.core.math.subRC"   
)

References cv::GMatDesc::withDepth().

Here is the call graph for this function:

◆ G_TYPED_KERNEL() [6/59]

cv::gapi::core::G_TYPED_KERNEL ( GMul  ,
< GMat(GMat, GMat, double, int)>  ,
"org.opencv.core.math.mul"   
)

References cv::GMatDesc::withDepth().

Here is the call graph for this function:

◆ G_TYPED_KERNEL() [7/59]

cv::gapi::core::G_TYPED_KERNEL ( GMulCOld  ,
< GMat(GMat, double, int)>  ,
"org.opencv.core.math.mulCOld"   
)

References cv::GMatDesc::withDepth().

Here is the call graph for this function:

◆ G_TYPED_KERNEL() [8/59]

cv::gapi::core::G_TYPED_KERNEL ( GMulC  ,
< GMat(GMat, GScalar, int)>  ,
"org.opencv.core.math.mulC"   
)

References cv::GMatDesc::withDepth().

Here is the call graph for this function:

◆ G_TYPED_KERNEL() [9/59]

cv::gapi::core::G_TYPED_KERNEL ( GMulS  ,
< GMat(GMat, GScalar)>  ,
"org.opencv.core.math.muls"   
)

◆ G_TYPED_KERNEL() [10/59]

cv::gapi::core::G_TYPED_KERNEL ( GDiv  ,
< GMat(GMat, GMat, double, int)>  ,
"org.opencv.core.math.div"   
)

References cv::GMatDesc::depth, and cv::GMatDesc::withDepth().

Here is the call graph for this function:

◆ G_TYPED_KERNEL() [11/59]

cv::gapi::core::G_TYPED_KERNEL ( GDivC  ,
< GMat(GMat, GScalar, double, int)>  ,
"org.opencv.core.math.divC"   
)

References cv::GMatDesc::withDepth().

Here is the call graph for this function:

◆ G_TYPED_KERNEL() [12/59]

cv::gapi::core::G_TYPED_KERNEL ( GDivRC  ,
< GMat(GScalar, GMat, double, int)>  ,
"org.opencv.core.math.divRC"   
)

References cv::GMatDesc::withDepth().

Here is the call graph for this function:

◆ G_TYPED_KERNEL() [13/59]

cv::gapi::core::G_TYPED_KERNEL ( GMean  ,
< GScalar(GMat)>  ,
"org.opencv.core.math.mean"   
)

References cv::empty_scalar_desc().

Here is the call graph for this function:

◆ G_TYPED_KERNEL() [14/59]

cv::gapi::core::G_TYPED_KERNEL ( GPhase  ,
< GMat(GMat, GMat, bool)>  ,
"org.opencv.core.math.phase"   
)

◆ G_TYPED_KERNEL() [15/59]

cv::gapi::core::G_TYPED_KERNEL ( GMask  ,
< GMat(GMat, GMat)>  ,
"org.opencv.core.pixelwise.mask"   
)

◆ G_TYPED_KERNEL() [16/59]

cv::gapi::core::G_TYPED_KERNEL ( GCmpGT  ,
< GMat(GMat, GMat)>  ,
"org.opencv.core.pixelwise.compare.cmpGT"   
)

References CV_8U, and cv::GMatDesc::withDepth().

Here is the call graph for this function:

◆ G_TYPED_KERNEL() [17/59]

cv::gapi::core::G_TYPED_KERNEL ( GCmpGE  ,
< GMat(GMat, GMat)>  ,
"org.opencv.core.pixelwise.compare.cmpGE"   
)

References CV_8U, and cv::GMatDesc::withDepth().

Here is the call graph for this function:

◆ G_TYPED_KERNEL() [18/59]

cv::gapi::core::G_TYPED_KERNEL ( GCmpLE  ,
< GMat(GMat, GMat)>  ,
"org.opencv.core.pixelwise.compare.cmpLE"   
)

References CV_8U, and cv::GMatDesc::withDepth().

Here is the call graph for this function:

◆ G_TYPED_KERNEL() [19/59]

cv::gapi::core::G_TYPED_KERNEL ( GCmpLT  ,
< GMat(GMat, GMat)>  ,
"org.opencv.core.pixelwise.compare.cmpLT"   
)

References CV_8U, and cv::GMatDesc::withDepth().

Here is the call graph for this function:

◆ G_TYPED_KERNEL() [20/59]

cv::gapi::core::G_TYPED_KERNEL ( GCmpEQ  ,
< GMat(GMat, GMat)>  ,
"org.opencv.core.pixelwise.compare.cmpEQ"   
)

References CV_8U, and cv::GMatDesc::withDepth().

Here is the call graph for this function:

◆ G_TYPED_KERNEL() [21/59]

cv::gapi::core::G_TYPED_KERNEL ( GCmpNE  ,
< GMat(GMat, GMat)>  ,
"org.opencv.core.pixelwise.compare.cmpNE"   
)

References CV_8U, and cv::GMatDesc::withDepth().

Here is the call graph for this function:

◆ G_TYPED_KERNEL() [22/59]

cv::gapi::core::G_TYPED_KERNEL ( GCmpGTScalar  ,
< GMat(GMat, GScalar)>  ,
"org.opencv.core.pixelwise.compare.cmpGTScalar"   
)

References CV_8U, and cv::GMatDesc::withDepth().

Here is the call graph for this function:

◆ G_TYPED_KERNEL() [23/59]

cv::gapi::core::G_TYPED_KERNEL ( GCmpGEScalar  ,
< GMat(GMat, GScalar)>  ,
"org.opencv.core.pixelwise.compare.cmpGEScalar"   
)

References CV_8U, and cv::GMatDesc::withDepth().

Here is the call graph for this function:

◆ G_TYPED_KERNEL() [24/59]

cv::gapi::core::G_TYPED_KERNEL ( GCmpLEScalar  ,
< GMat(GMat, GScalar)>  ,
"org.opencv.core.pixelwise.compare.cmpLEScalar"   
)

References CV_8U, and cv::GMatDesc::withDepth().

Here is the call graph for this function:

◆ G_TYPED_KERNEL() [25/59]

cv::gapi::core::G_TYPED_KERNEL ( GCmpLTScalar  ,
< GMat(GMat, GScalar)>  ,
"org.opencv.core.pixelwise.compare.cmpLTScalar"   
)

References CV_8U, and cv::GMatDesc::withDepth().

Here is the call graph for this function:

◆ G_TYPED_KERNEL() [26/59]

cv::gapi::core::G_TYPED_KERNEL ( GCmpEQScalar  ,
< GMat(GMat, GScalar)>  ,
"org.opencv.core.pixelwise.compare.cmpEQScalar"   
)

References CV_8U, and cv::GMatDesc::withDepth().

Here is the call graph for this function:

◆ G_TYPED_KERNEL() [27/59]

cv::gapi::core::G_TYPED_KERNEL ( GCmpNEScalar  ,
< GMat(GMat, GScalar)>  ,
"org.opencv.core.pixelwise.compare.cmpNEScalar"   
)

References CV_8U, and cv::GMatDesc::withDepth().

Here is the call graph for this function:

◆ G_TYPED_KERNEL() [28/59]

cv::gapi::core::G_TYPED_KERNEL ( GAnd  ,
< GMat(GMat, GMat)>  ,
"org.opencv.core.pixelwise.bitwise_and"   
)

◆ G_TYPED_KERNEL() [29/59]

cv::gapi::core::G_TYPED_KERNEL ( GAndS  ,
< GMat(GMat, GScalar)>  ,
"org.opencv.core.pixelwise.bitwise_andS"   
)

◆ G_TYPED_KERNEL() [30/59]

cv::gapi::core::G_TYPED_KERNEL ( GOr  ,
< GMat(GMat, GMat)>  ,
"org.opencv.core.pixelwise.bitwise_or"   
)

◆ G_TYPED_KERNEL() [31/59]

cv::gapi::core::G_TYPED_KERNEL ( GOrS  ,
< GMat(GMat, GScalar)>  ,
"org.opencv.core.pixelwise.bitwise_orS"   
)

◆ G_TYPED_KERNEL() [32/59]

cv::gapi::core::G_TYPED_KERNEL ( GXor  ,
< GMat(GMat, GMat)>  ,
"org.opencv.core.pixelwise.bitwise_xor"   
)

◆ G_TYPED_KERNEL() [33/59]

cv::gapi::core::G_TYPED_KERNEL ( GXorS  ,
< GMat(GMat, GScalar)>  ,
"org.opencv.core.pixelwise.bitwise_xorS"   
)

◆ G_TYPED_KERNEL() [34/59]

cv::gapi::core::G_TYPED_KERNEL ( GNot  ,
< GMat(GMat)>  ,
"org.opencv.core.pixelwise.bitwise_not"   
)

◆ G_TYPED_KERNEL() [35/59]

cv::gapi::core::G_TYPED_KERNEL ( GSelect  ,
< GMat(GMat, GMat, GMat)>  ,
"org.opencv.core.pixelwise.select"   
)

◆ G_TYPED_KERNEL() [36/59]

cv::gapi::core::G_TYPED_KERNEL ( GMin  ,
< GMat(GMat, GMat)>  ,
"org.opencv.core.matrixop.min"   
)

◆ G_TYPED_KERNEL() [37/59]

cv::gapi::core::G_TYPED_KERNEL ( GMax  ,
< GMat(GMat, GMat)>  ,
"org.opencv.core.matrixop.max"   
)

◆ G_TYPED_KERNEL() [38/59]

cv::gapi::core::G_TYPED_KERNEL ( GAbsDiff  ,
< GMat(GMat, GMat)>  ,
"org.opencv.core.matrixop.absdiff"   
)

◆ G_TYPED_KERNEL() [39/59]

cv::gapi::core::G_TYPED_KERNEL ( GAbsDiffC  ,
< GMat(GMat, GScalar)>  ,
"org.opencv.core.matrixop.absdiffC"   
)

◆ G_TYPED_KERNEL() [40/59]

cv::gapi::core::G_TYPED_KERNEL ( GSum  ,
< GScalar(GMat)>  ,
"org.opencv.core.matrixop.sum"   
)

References cv::empty_scalar_desc().

Here is the call graph for this function:

◆ G_TYPED_KERNEL() [41/59]

cv::gapi::core::G_TYPED_KERNEL ( GAddW  ,
< GMat(GMat, double, GMat, double, double, int)>  ,
"org.opencv.core.matrixop.addweighted"   
)

References cv::GMatDesc::chan, cv::GMatDesc::depth, and cv::GMatDesc::withDepth().

Here is the call graph for this function:

◆ G_TYPED_KERNEL() [42/59]

cv::gapi::core::G_TYPED_KERNEL ( GNormL1  ,
< GScalar(GMat)>  ,
"org.opencv.core.matrixop.norml1"   
)

References cv::empty_scalar_desc().

Here is the call graph for this function:

◆ G_TYPED_KERNEL() [43/59]

cv::gapi::core::G_TYPED_KERNEL ( GNormL2  ,
< GScalar(GMat)>  ,
"org.opencv.core.matrixop.norml2"   
)

References cv::empty_scalar_desc().

Here is the call graph for this function:

◆ G_TYPED_KERNEL() [44/59]

cv::gapi::core::G_TYPED_KERNEL ( GNormInf  ,
< GScalar(GMat)>  ,
"org.opencv.core.matrixop.norminf"   
)

References cv::empty_scalar_desc().

Here is the call graph for this function:

◆ G_TYPED_KERNEL() [45/59]

cv::gapi::core::G_TYPED_KERNEL ( GThreshold  ,
< GMat(GMat, GScalar, GScalar, int)>  ,
"org.opencv.core.matrixop.threshold"   
)

◆ G_TYPED_KERNEL() [46/59]

cv::gapi::core::G_TYPED_KERNEL ( GInRange  ,
< GMat(GMat, GScalar, GScalar)>  ,
"org.opencv.core.matrixop.inrange"   
)

References CV_8U, and cv::GMatDesc::withType().

Here is the call graph for this function:

◆ G_TYPED_KERNEL() [47/59]

cv::gapi::core::G_TYPED_KERNEL ( GResize  ,
< GMat(GMat, Size, double, double, int)>  ,
"org.opencv.core.transform.resize"   
)

◆ G_TYPED_KERNEL() [48/59]

cv::gapi::core::G_TYPED_KERNEL ( GResizeP  ,
< GMatP(GMatP, Size, int)>  ,
"org.opencv.core.transform.resizeP"   
)

References cv::GMatDesc::chan, CV_8U, cv::GMatDesc::depth, cv::INTER_LINEAR, cv::GMatDesc::planar, and cv::GMatDesc::withSize().

Here is the call graph for this function:

◆ G_TYPED_KERNEL() [49/59]

cv::gapi::core::G_TYPED_KERNEL ( GMerge3  ,
< GMat(GMat, GMat, GMat)>  ,
"org.opencv.core.transform.merge3"   
)

References cv::GMatDesc::depth, and cv::GMatDesc::withType().

Here is the call graph for this function:

◆ G_TYPED_KERNEL() [50/59]

cv::gapi::core::G_TYPED_KERNEL ( GMerge4  ,
< GMat(GMat, GMat, GMat, GMat)>  ,
"org.opencv.core.transform.merge4"   
)

References cv::GMatDesc::depth, and cv::GMatDesc::withType().

Here is the call graph for this function:

◆ G_TYPED_KERNEL() [51/59]

cv::gapi::core::G_TYPED_KERNEL ( GRemap  ,
< GMat(GMat, Mat, Mat, int, int, Scalar)>  ,
"org.opencv.core.transform.remap"   
)

References cv::Mat::size, and cv::GMatDesc::withSize().

Here is the call graph for this function:

◆ G_TYPED_KERNEL() [52/59]

cv::gapi::core::G_TYPED_KERNEL ( GFlip  ,
< GMat(GMat, int)>  ,
"org.opencv.core.transform.flip"   
)

◆ G_TYPED_KERNEL() [53/59]

cv::gapi::core::G_TYPED_KERNEL ( GCrop  ,
< GMat(GMat, Rect)>  ,
"org.opencv.core.transform.crop"   
)

References cv::Rect_< _Tp >::height, cv::Rect_< _Tp >::width, and cv::GMatDesc::withSize().

Here is the call graph for this function:

◆ G_TYPED_KERNEL() [54/59]

cv::gapi::core::G_TYPED_KERNEL ( GConcatHor  ,
< GMat(GMat, GMat)>  ,
"org.opencv.imgproc.transform.concatHor"   
)

References cv::GMatDesc::size, cv::gapi::own::Size::width, and cv::GMatDesc::withSizeDelta().

Here is the call graph for this function:

◆ G_TYPED_KERNEL() [55/59]

cv::gapi::core::G_TYPED_KERNEL ( GConcatVert  ,
< GMat(GMat, GMat)>  ,
"org.opencv.imgproc.transform.concatVert"   
)

References cv::gapi::own::Size::height, cv::GMatDesc::size, and cv::GMatDesc::withSizeDelta().

Here is the call graph for this function:

◆ G_TYPED_KERNEL() [56/59]

cv::gapi::core::G_TYPED_KERNEL ( GLUT  ,
< GMat(GMat, Mat)>  ,
"org.opencv.core.transform.LUT"   
)

◆ G_TYPED_KERNEL() [57/59]

cv::gapi::core::G_TYPED_KERNEL ( GConvertTo  ,
< GMat(GMat, int, double, double)>  ,
"org.opencv.core.transform.convertTo"   
)

References cv::GMatDesc::withDepth().

Here is the call graph for this function:

◆ G_TYPED_KERNEL() [58/59]

cv::gapi::core::G_TYPED_KERNEL ( GSqrt  ,
< GMat(GMat)>  ,
"org.opencv.core.math.sqrt"   
)

◆ G_TYPED_KERNEL() [59/59]

◆ G_TYPED_KERNEL_M() [1/6]

cv::gapi::core::G_TYPED_KERNEL_M ( GPolarToCart  ,
< GMat2(GMat, GMat, bool)>  ,
"org.opencv.core.math.polarToCart"   
)

◆ G_TYPED_KERNEL_M() [2/6]

cv::gapi::core::G_TYPED_KERNEL_M ( GCartToPolar  ,
< GMat2(GMat, GMat, bool)>  ,
"org.opencv.core.math.cartToPolar"   
)

◆ G_TYPED_KERNEL_M() [3/6]

cv::gapi::core::G_TYPED_KERNEL_M ( GIntegral  ,
< GMat2(GMat, int, int)>  ,
"org.opencv.core.matrixop.integral"   
)

References cv::GMatDesc::withDepth(), and cv::GMatDesc::withSizeDelta().

Here is the call graph for this function:

◆ G_TYPED_KERNEL_M() [4/6]

cv::gapi::core::G_TYPED_KERNEL_M ( GThresholdOT  ,
< GMatScalar(GMat, GScalar, int)>  ,
"org.opencv.core.matrixop.thresholdOT"   
)

References cv::empty_scalar_desc().

Here is the call graph for this function:

◆ G_TYPED_KERNEL_M() [5/6]

cv::gapi::core::G_TYPED_KERNEL_M ( GSplit3  ,
< GMat3(GMat)>  ,
"org.opencv.core.transform.split3"   
)

References cv::GMatDesc::depth, and cv::GMatDesc::withType().

Here is the call graph for this function:

◆ G_TYPED_KERNEL_M() [6/6]

cv::gapi::core::G_TYPED_KERNEL_M ( GSplit4  ,
< GMat4(GMat)>  ,
"org.opencv.core.transform.split4"   
)

References cv::GMatDesc::depth, and cv::GMatDesc::withType().

Here is the call graph for this function: