core.hpp 檔案參考

#include <math.h>
#include <utility>
#include <opencv2/imgproc.hpp>
#include <opencv2/gapi/imgproc.hpp>
#include <opencv2/gapi/gmat.hpp>
#include <opencv2/gapi/gscalar.hpp>
#include <opencv2/gapi/gkernel.hpp>
#include <opencv2/gapi/streaming/format.hpp>

core.hpp 的包含依賴關係圖

名稱空間
名稱空間	cv
名稱空間	cv::gapi
名稱空間	cv::gapi::core
	此名稱空間包含用於 OpenCV 核心模組功能的 G-API 操作型別。
名稱空間	cv::gapi::streaming
	此名稱空間包含與流式執行模式相關的 G-API 函式、結構和符號。

型別定義
using	cv::gapi::core::GMat2 = std::tuple<GMat,GMat>
using	cv::gapi::core::GMat3 = std::tuple<GMat,GMat,GMat>
using	cv::gapi::core::GMat4 = std::tuple<GMat,GMat,GMat,GMat>
using	cv::gapi::core::GMatScalar = std::tuple<GMat, GScalar>
using	cv::gapi::core::GResize = cv::gapi::imgproc::GResize
using	cv::gapi::core::GResizeP = cv::gapi::imgproc::GResizeP

函式
GMat	cv::gapi::absDiff (const GMat &src1, const GMat &src2)
	計算兩個矩陣的逐元素絕對差。
GMat	cv::gapi::absDiffC (const GMat &src, const GScalar &c)
	計算矩陣元素的絕對值。
GMat	cv::gapi::add (const GMat &src1, const GMat &src2, int ddepth=-1)
	計算兩個矩陣的逐元素和。
GMat	cv::gapi::addC (const GMat &src1, const GScalar &c, int ddepth=-1)
	計算矩陣和給定標量的逐元素和。
GMat	cv::gapi::addC (const GScalar &c, const GMat &src1, int ddepth=-1)
	這是一個過載成員函式，為方便起見提供。它與上面的函式僅在接受的引數上有所不同。
GMat	cv::gapi::addWeighted (const GMat &src1, double alpha, const GMat &src2, double beta, double gamma, int ddepth=-1)
	計算兩個矩陣的加權和。
GMat	cv::gapi::bitwise_and (const GMat &src1, const GMat &src2)
	計算兩個矩陣（src1 & src2）的按位合取。計算兩個相同大小矩陣的逐元素按位邏輯合取。
GMat	cv::gapi::bitwise_and (const GMat &src1, const GScalar &src2)
GMat	cv::gapi::bitwise_not (const GMat &src)
	反轉陣列的每個位。
GMat	cv::gapi::bitwise_or (const GMat &src1, const GMat &src2)
	計算兩個矩陣（src1 | src2）的按位析取。計算兩個相同大小矩陣的逐元素按位邏輯析取。
GMat	cv::gapi::bitwise_or (const GMat &src1, const GScalar &src2)
GMat	cv::gapi::bitwise_xor (const GMat &src1, const GMat &src2)
	計算兩個矩陣（src1 ^ src2）的按位邏輯“異或”。計算兩個相同大小矩陣的逐元素按位邏輯“異或”。
GMat	cv::gapi::bitwise_xor (const GMat &src1, const GScalar &src2)
std::tuple< GMat, GMat >	cv::gapi::cartToPolar (const GMat &x, const GMat &y, bool angleInDegrees=false)
	Calculates the magnitude and angle of 2D vectors.
GMat	cv::gapi::cmpEQ (const GMat &src1, const GMat &src2)
	對兩個矩陣執行逐元素比較，檢查第一個矩陣的元素是否等於第二個矩陣的元素。
GMat	cv::gapi::cmpEQ (const GMat &src1, const GScalar &src2)
GMat	cv::gapi::cmpGE (const GMat &src1, const GMat &src2)
	對兩個矩陣執行逐元素比較，檢查第一個矩陣的元素是否大於或等於第二個矩陣的元素。
GMat	cv::gapi::cmpGE (const GMat &src1, const GScalar &src2)
GMat	cv::gapi::cmpGT (const GMat &src1, const GMat &src2)
	對兩個矩陣執行逐元素比較，檢查第一個矩陣的元素是否大於第二個矩陣的元素。
GMat	cv::gapi::cmpGT (const GMat &src1, const GScalar &src2)
GMat	cv::gapi::cmpLE (const GMat &src1, const GMat &src2)
	對兩個矩陣執行逐元素比較，檢查第一個矩陣的元素是否小於或等於第二個矩陣的元素。
GMat	cv::gapi::cmpLE (const GMat &src1, const GScalar &src2)
GMat	cv::gapi::cmpLT (const GMat &src1, const GMat &src2)
	對兩個矩陣執行逐元素比較，檢查第一個矩陣的元素是否小於第二個矩陣的元素。
GMat	cv::gapi::cmpLT (const GMat &src1, const GScalar &src2)
GMat	cv::gapi::cmpNE (const GMat &src1, const GMat &src2)
	對兩個矩陣執行逐元素比較，檢查第一個矩陣的元素是否不等於第二個矩陣的元素。
GMat	cv::gapi::cmpNE (const GMat &src1, const GScalar &src2)
GMat	cv::gapi::concatHor (const GMat &src1, const GMat &src2)
	對給定矩陣進行水平連線。
GMat	cv::gapi::concatHor (const std::vector< GMat > &v)
GMat	cv::gapi::concatVert (const GMat &src1, const GMat &src2)
	對給定矩陣執行垂直連線。
GMat	cv::gapi::concatVert (const std::vector< GMat > &v)
GMat	cv::gapi::convertTo (const GMat &src, int rdepth, double alpha=1, double beta=0)
	將矩陣轉換為另一種資料深度，並可選擇縮放。
GOpaque< int >	cv::gapi::countNonZero (const GMat &src)
	Counts non-zero array elements.
GMat	cv::gapi::crop (const GMat &src, const Rect &rect)
	裁剪二維矩陣。
GMat	cv::gapi::div (const GMat &src1, const GMat &src2, double scale, int ddepth=-1)
	執行兩個矩陣的逐元素除法。
GMat	cv::gapi::divC (const GMat &src, const GScalar &divisor, double scale, int ddepth=-1)
	矩陣除以標量。
GMat	cv::gapi::divRC (const GScalar &divident, const GMat &src, double scale, int ddepth=-1)
	標量除以矩陣。
GMat	cv::gapi::flip (const GMat &src, int flipCode)
	圍繞垂直、水平或兩個軸翻轉二維矩陣。
	cv::gapi::core::G_TYPED_KERNEL (GAbsDiff,< GMat(GMat, GMat)>, "org.opencv.core.matrixop.absdiff")
	cv::gapi::core::G_TYPED_KERNEL (GAbsDiffC,< GMat(GMat, GScalar)>, "org.opencv.core.matrixop.absdiffC")
	cv::gapi::core::G_TYPED_KERNEL (GAdd,< GMat(GMat, GMat, int)>, "org.opencv.core.math.add")
	cv::gapi::core::G_TYPED_KERNEL (GAddC,< GMat(GMat, GScalar, int)>, "org.opencv.core.math.addC")
	cv::gapi::core::G_TYPED_KERNEL (GAddW,< GMat(GMat, double, GMat, double, double, int)>, "org.opencv.core.matrixop.addweighted")
	cv::gapi::core::G_TYPED_KERNEL (GAnd,< GMat(GMat, GMat)>, "org.opencv.core.pixelwise.bitwise_and")
	cv::gapi::core::G_TYPED_KERNEL (GAndS,< GMat(GMat, GScalar)>, "org.opencv.core.pixelwise.bitwise_andS")
	cv::gapi::core::G_TYPED_KERNEL (GCmpEQ,< GMat(GMat, GMat)>, "org.opencv.core.pixelwise.compare.cmpEQ")
	cv::gapi::core::G_TYPED_KERNEL (GCmpEQScalar,< GMat(GMat, GScalar)>, "org.opencv.core.pixelwise.compare.cmpEQScalar")
	cv::gapi::core::G_TYPED_KERNEL (GCmpGE,< GMat(GMat, GMat)>, "org.opencv.core.pixelwise.compare.cmpGE")
	cv::gapi::core::G_TYPED_KERNEL (GCmpGEScalar,< GMat(GMat, GScalar)>, "org.opencv.core.pixelwise.compare.cmpGEScalar")
	cv::gapi::core::G_TYPED_KERNEL (GCmpGT,< GMat(GMat, GMat)>, "org.opencv.core.pixelwise.compare.cmpGT")
	cv::gapi::core::G_TYPED_KERNEL (GCmpGTScalar,< GMat(GMat, GScalar)>, "org.opencv.core.pixelwise.compare.cmpGTScalar")
	cv::gapi::core::G_TYPED_KERNEL (GCmpLE,< GMat(GMat, GMat)>, "org.opencv.core.pixelwise.compare.cmpLE")
	cv::gapi::core::G_TYPED_KERNEL (GCmpLEScalar,< GMat(GMat, GScalar)>, "org.opencv.core.pixelwise.compare.cmpLEScalar")
	cv::gapi::core::G_TYPED_KERNEL (GCmpLT,< GMat(GMat, GMat)>, "org.opencv.core.pixelwise.compare.cmpLT")
	cv::gapi::core::G_TYPED_KERNEL (GCmpLTScalar,< GMat(GMat, GScalar)>, "org.opencv.core.pixelwise.compare.cmpLTScalar")
	cv::gapi::core::G_TYPED_KERNEL (GCmpNE,< GMat(GMat, GMat)>, "org.opencv.core.pixelwise.compare.cmpNE")
	cv::gapi::core::G_TYPED_KERNEL (GCmpNEScalar,< GMat(GMat, GScalar)>, "org.opencv.core.pixelwise.compare.cmpNEScalar")
	cv::gapi::core::G_TYPED_KERNEL (GConcatHor,< GMat(GMat, GMat)>, "org.opencv.imgproc.transform.concatHor")
	cv::gapi::core::G_TYPED_KERNEL (GConcatVert,< GMat(GMat, GMat)>, "org.opencv.imgproc.transform.concatVert")
	cv::gapi::core::G_TYPED_KERNEL (GConvertTo,< GMat(GMat, int, double, double)>, "org.opencv.core.transform.convertTo")
	cv::gapi::core::G_TYPED_KERNEL (GCountNonZero,< GOpaque< int >(GMat)>, "org.opencv.core.matrixop.countNonZero")
	cv::gapi::core::G_TYPED_KERNEL (GCrop,< GMat(GMat, Rect)>, "org.opencv.core.transform.crop")
	cv::gapi::core::G_TYPED_KERNEL (GDiv,< GMat(GMat, GMat, double, int)>, "org.opencv.core.math.div")
	cv::gapi::core::G_TYPED_KERNEL (GDivC,< GMat(GMat, GScalar, double, int)>, "org.opencv.core.math.divC")
	cv::gapi::core::G_TYPED_KERNEL (GDivRC,< GMat(GScalar, GMat, double, int)>, "org.opencv.core.math.divRC")
	cv::gapi::core::G_TYPED_KERNEL (GFlip,< GMat(GMat, int)>, "org.opencv.core.transform.flip")
	cv::gapi::core::G_TYPED_KERNEL (GInRange,< GMat(GMat, GScalar, GScalar)>, "org.opencv.core.matrixop.inrange")
	cv::gapi::core::G_TYPED_KERNEL (GKMeans2D,< std::tuple< GOpaque< double >, GArray< int >, GArray< Point2f > >(GArray< Point2f >, int, GArray< int >, TermCriteria, int, KmeansFlags)>, "org.opencv.core.kmeans2D")
	cv::gapi::core::G_TYPED_KERNEL (GKMeans3D,< std::tuple< GOpaque< double >, GArray< int >, GArray< Point3f > >(GArray< Point3f >, int, GArray< int >, TermCriteria, int, KmeansFlags)>, "org.opencv.core.kmeans3D")
	cv::gapi::core::G_TYPED_KERNEL (GKMeansND,< std::tuple< GOpaque< double >, GMat, GMat >(GMat, int, GMat, TermCriteria, int, KmeansFlags)>, "org.opencv.core.kmeansND")
	cv::gapi::core::G_TYPED_KERNEL (GKMeansNDNoInit,< std::tuple< GOpaque< double >, GMat, GMat >(GMat, int, TermCriteria, int, KmeansFlags)>, "org.opencv.core.kmeansNDNoInit")
	cv::gapi::core::G_TYPED_KERNEL (GLUT,< GMat(GMat, Mat)>, "org.opencv.core.transform.LUT")
	cv::gapi::core::G_TYPED_KERNEL (GMask,< GMat(GMat, GMat)>, "org.opencv.core.pixelwise.mask")
	cv::gapi::core::G_TYPED_KERNEL (GMax,< GMat(GMat, GMat)>, "org.opencv.core.matrixop.max")
	cv::gapi::core::G_TYPED_KERNEL (GMean,< GScalar(GMat)>, "org.opencv.core.math.mean")
	cv::gapi::core::G_TYPED_KERNEL (GMerge3,< GMat(GMat, GMat, GMat)>, "org.opencv.core.transform.merge3")
	cv::gapi::core::G_TYPED_KERNEL (GMerge4,< GMat(GMat, GMat, GMat, GMat)>, "org.opencv.core.transform.merge4")
	cv::gapi::core::G_TYPED_KERNEL (GMin,< GMat(GMat, GMat)>, "org.opencv.core.matrixop.min")
	cv::gapi::core::G_TYPED_KERNEL (GMul,< GMat(GMat, GMat, double, int)>, "org.opencv.core.math.mul")
	cv::gapi::core::G_TYPED_KERNEL (GMulC,< GMat(GMat, GScalar, int)>, "org.opencv.core.math.mulC")
	cv::gapi::core::G_TYPED_KERNEL (GMulCOld,< GMat(GMat, double, int)>, "org.opencv.core.math.mulCOld")
	cv::gapi::core::G_TYPED_KERNEL (GMulS,< GMat(GMat, GScalar)>, "org.opencv.core.math.muls")
	cv::gapi::core::G_TYPED_KERNEL (GNormalize,< GMat(GMat, double, double, int, int)>, "org.opencv.core.normalize")
	cv::gapi::core::G_TYPED_KERNEL (GNormInf,< GScalar(GMat)>, "org.opencv.core.matrixop.norminf")
	cv::gapi::core::G_TYPED_KERNEL (GNormL1,< GScalar(GMat)>, "org.opencv.core.matrixop.norml1")
	cv::gapi::core::G_TYPED_KERNEL (GNormL2,< GMat(GMat)>, "org.opencv.core.matrixop.norml2")
	cv::gapi::core::G_TYPED_KERNEL (GNot,< GMat(GMat)>, "org.opencv.core.pixelwise.bitwise_not")
	cv::gapi::core::G_TYPED_KERNEL (GOr,< GMat(GMat, GMat)>, "org.opencv.core.pixelwise.bitwise_or")
	cv::gapi::core::G_TYPED_KERNEL (GOrS,< GMat(GMat, GScalar)>, "org.opencv.core.pixelwise.bitwise_orS")
	cv::gapi::core::G_TYPED_KERNEL (GPhase,< GMat(GMat, GMat, bool)>, "org.opencv.core.math.phase")
	cv::gapi::core::G_TYPED_KERNEL (GRemap,< GMat(GMat, Mat, Mat, int, int, Scalar)>, "org.opencv.core.transform.remap")
	cv::gapi::core::G_TYPED_KERNEL (GSelect,< GMat(GMat, GMat, GMat)>, "org.opencv.core.pixelwise.select")
	cv::gapi::core::G_TYPED_KERNEL (GSqrt,< GMat(GMat)>, "org.opencv.core.math.sqrt")
	cv::gapi::core::G_TYPED_KERNEL (GSub,< GMat(GMat, GMat, int)>, "org.opencv.core.math.sub")
	cv::gapi::core::G_TYPED_KERNEL (GSubC,< GMat(GMat, GScalar, int)>, "org.opencv.core.math.subC")
	cv::gapi::core::G_TYPED_KERNEL (GSubRC,< GMat(GScalar, GMat, int)>, "org.opencv.core.math.subRC")
	cv::gapi::core::G_TYPED_KERNEL (GSum,< GScalar(GMat)>, "org.opencv.core.matrixop.sum")
	cv::gapi::core::G_TYPED_KERNEL (GThreshold,< GMat(GMat, GScalar, GScalar, int)>, "org.opencv.core.matrixop.threshold")
	cv::gapi::core::G_TYPED_KERNEL (GTranspose,< GMat(GMat)>, "org.opencv.core.transpose")
	cv::gapi::core::G_TYPED_KERNEL (GWarpAffine,< GMat(GMat, const Mat &, Size, int, int, const cv::Scalar &)>, "org.opencv.core.warpAffine")
	cv::gapi::core::G_TYPED_KERNEL (GWarpPerspective,< GMat(GMat, const Mat &, Size, int, int, const cv::Scalar &)>, "org.opencv.core.warpPerspective")
	cv::gapi::core::G_TYPED_KERNEL (GXor,< GMat(GMat, GMat)>, "org.opencv.core.pixelwise.bitwise_xor")
	cv::gapi::core::G_TYPED_KERNEL (GXorS,< GMat(GMat, GScalar)>, "org.opencv.core.pixelwise.bitwise_xorS")
	cv::gapi::streaming::G_TYPED_KERNEL (GSize,< GOpaque< Size >(GMat)>, "org.opencv.streaming.size")
	cv::gapi::streaming::G_TYPED_KERNEL (GSizeMF,< GOpaque< Size >(GFrame)>, "org.opencv.streaming.sizeMF")
	cv::gapi::streaming::G_TYPED_KERNEL (GSizeR,< GOpaque< Size >(GOpaque< Rect >)>, "org.opencv.streaming.sizeR")
	cv::gapi::core::G_TYPED_KERNEL_M (GCartToPolar,< GMat2(GMat, GMat, bool)>, "org.opencv.core.math.cartToPolar")
	cv::gapi::core::G_TYPED_KERNEL_M (GIntegral,< GMat2(GMat, int, int)>, "org.opencv.core.matrixop.integral")
	cv::gapi::core::G_TYPED_KERNEL_M (GPolarToCart,< GMat2(GMat, GMat, bool)>, "org.opencv.core.math.polarToCart")
	cv::gapi::core::G_TYPED_KERNEL_M (GSplit3,< GMat3(GMat)>, "org.opencv.core.transform.split3")
	cv::gapi::core::G_TYPED_KERNEL_M (GSplit4,< GMat4(GMat)>,"org.opencv.core.transform.split4")
	cv::gapi::core::G_TYPED_KERNEL_M (GThresholdOT,< GMatScalar(GMat, GScalar, int)>, "org.opencv.core.matrixop.thresholdOT")
GMat	cv::gapi::inRange (const GMat &src, const GScalar &threshLow, const GScalar &threshUp)
	對每個矩陣元素應用範圍閾值。
std::tuple< GMat, GMat >	cv::gapi::integral (const GMat &src, int sdepth=-1, int sqdepth=-1)
	計算影像的積分。
std::tuple< GOpaque< double >, GArray< int >, GArray< Point2f > >	cv::gapi::kmeans (const GArray< Point2f > &data, const int K, const GArray< int > &bestLabels, const TermCriteria &criteria, const int attempts, const KmeansFlags flags)
std::tuple< GOpaque< double >, GArray< int >, GArray< Point3f > >	cv::gapi::kmeans (const GArray< Point3f > &data, const int K, const GArray< int > &bestLabels, const TermCriteria &criteria, const int attempts, const KmeansFlags flags)
std::tuple< GOpaque< double >, GMat, GMat >	cv::gapi::kmeans (const GMat &data, const int K, const GMat &bestLabels, const TermCriteria &criteria, const int attempts, const KmeansFlags flags)
	尋找聚類中心，並將輸入樣本按聚類分組。
std::tuple< GOpaque< double >, GMat, GMat >	cv::gapi::kmeans (const GMat &data, const int K, const TermCriteria &criteria, const int attempts, const KmeansFlags flags)
GMat	cv::gapi::LUT (const GMat &src, const Mat &lut)
	對矩陣執行查詢錶轉換。
GMat	cv::gapi::mask (const GMat &src, const GMat &mask)
	將掩碼應用於矩陣。
GMat	cv::gapi::max (const GMat &src1, const GMat &src2)
	計算兩個矩陣的逐元素最大值。
GScalar	cv::gapi::mean (const GMat &src)
	計算矩陣元素的平均值。
GMat	cv::gapi::merge3 (const GMat &src1, const GMat &src2, const GMat &src3)
	從3個單通道矩陣建立一個3通道矩陣。
GMat	cv::gapi::merge4 (const GMat &src1, const GMat &src2, const GMat &src3, const GMat &src4)
	將 4 個單通道矩陣合併為一個 4 通道矩陣。
GMat	cv::gapi::min (const GMat &src1, const GMat &src2)
	計算兩個矩陣的逐元素最小值。
GMat	cv::gapi::mul (const GMat &src1, const GMat &src2, double scale=1.0, int ddepth=-1)
	計算兩個矩陣的逐元素縮放積。
GMat	cv::gapi::mulC (const GMat &src, const GScalar &multiplier, int ddepth=-1)
	這是一個過載成員函式，為方便起見提供。它與上面的函式僅在接受的引數上有所不同。
GMat	cv::gapi::mulC (const GMat &src, double multiplier, int ddepth=-1)
	矩陣乘以標量。
GMat	cv::gapi::mulC (const GScalar &multiplier, const GMat &src, int ddepth=-1)
	這是一個過載成員函式，為方便起見提供。它與上面的函式僅在接受的引數上有所不同。
GMat	cv::gapi::normalize (const GMat &src, double alpha, double beta, int norm_type, int ddepth=-1)
	對陣列的範數或值範圍進行歸一化。
GScalar	cv::gapi::normInf (const GMat &src)
	計算矩陣的絕對無窮範數。
GScalar	cv::gapi::normL1 (const GMat &src)
	計算矩陣的絕對 L1 範數。
GScalar	cv::gapi::normL2 (const GMat &src)
	計算矩陣的絕對 L2 範數。
GMat	cv::gapi::phase (const GMat &x, const GMat &y, bool angleInDegrees=false)
	計算二維向量的旋轉角度。
std::tuple< GMat, GMat >	cv::gapi::polarToCart (const GMat &magnitude, const GMat &angle, bool angleInDegrees=false)
	根據二維向量的幅度和角度計算其 x 和 y 座標。
GMat	cv::gapi::remap (const GMat &src, const Mat &map1, const Mat &map2, int interpolation, int borderMode=BORDER_CONSTANT, const Scalar &borderValue=Scalar())
	對影像應用通用幾何變換。
GMat	cv::gapi::select (const GMat &src1, const GMat &src2, const GMat &mask)
	根據給定掩碼從輸入矩陣的第一或第二項中選擇值。如果掩碼矩陣的相應值為 255，則該函式將輸出矩陣設定為第一個輸入矩陣的值；如果掩碼矩陣的值設定為 0，則設定為第二個輸入矩陣的值。
GOpaque< Size >	cv::gapi::streaming::size (const GFrame &src)
	從 MediaFrame 獲取尺寸。
GOpaque< Size >	cv::gapi::streaming::size (const GMat &src)
	從 Mat 獲取尺寸。
GOpaque< Size >	cv::gapi::streaming::size (const GOpaque< Rect > &r)
std::tuple< GMat, GMat, GMat >	cv::gapi::split3 (const GMat &src)
	將3通道矩陣分成3個單通道矩陣。
std::tuple< GMat, GMat, GMat, GMat >	cv::gapi::split4 (const GMat &src)
	將一個4通道矩陣分割成4個單通道矩陣。
GMat	cv::gapi::sqrt (const GMat &src)
	計算陣列元素的平方根。
GMat	cv::gapi::sub (const GMat &src1, const GMat &src2, int ddepth=-1)
	計算兩個矩陣的逐元素差值。
GMat	cv::gapi::subC (const GMat &src, const GScalar &c, int ddepth=-1)
	計算矩陣與給定標量之間的逐元素差。
GMat	cv::gapi::subRC (const GScalar &c, const GMat &src, int ddepth=-1)
	計算給定標量與矩陣之間的逐元素差。
GScalar	cv::gapi::sum (const GMat &src)
	計算所有矩陣元素的總和。
std::tuple< GMat, GScalar >	cv::gapi::threshold (const GMat &src, const GScalar &maxval, int type)
GMat	cv::gapi::threshold (const GMat &src, const GScalar &thresh, const GScalar &maxval, int type)
	對每個矩陣元素應用固定級別的閾值。
GMat	cv::gapi::transpose (const GMat &src)
	轉置矩陣。
GMat	cv::gapi::warpAffine (const GMat &src, const Mat &M, const Size &dsize, int flags=cv::INTER_LINEAR, int borderMode=cv::BORDER_CONSTANT, const Scalar &borderValue=Scalar())
	對影像應用仿射變換。
GMat	cv::gapi::warpPerspective (const GMat &src, const Mat &M, const Size &dsize, int flags=cv::INTER_LINEAR, int borderMode=cv::BORDER_CONSTANT, const Scalar &borderValue=Scalar())
	對影像應用透視變換。