core.hpp 文件参考

#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 的包含依赖关系图

命名空间
命名空间	cv
命名空间	cv::gapi
命名空间	cv::gapi::core
	此命名空间包含用于 OpenCV 核心模块功能的 G-API 操作类型。
命名空间	cv::gapi::streaming
	此命名空间包含与流式执行模式相关的 G-API 函数、结构和符号。

类型定义
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

函数
GMat	cv::gapi::absDiff (const GMat &src1, const GMat &src2)
	计算两个矩阵的逐元素绝对差。
GMat	cv::gapi::absDiffC (const GMat &src, const GScalar &c)
	计算矩阵元素的绝对值。
GMat	cv::gapi::add (const GMat &src1, const GMat &src2, int ddepth=-1)
	计算两个矩阵的逐元素和。
GMat	cv::gapi::addC (const GMat &src1, const GScalar &c, int ddepth=-1)
	计算矩阵和给定标量的逐元素和。
GMat	cv::gapi::addC (const GScalar &c, const GMat &src1, int ddepth=-1)
	这是一个重载成员函数，为方便起见提供。它与上面的函数仅在接受的参数上有所不同。
GMat	cv::gapi::addWeighted (const GMat &src1, double alpha, const GMat &src2, double beta, double gamma, int ddepth=-1)
	计算两个矩阵的加权和。
GMat	cv::gapi::bitwise_and (const GMat &src1, const GMat &src2)
	计算两个矩阵（src1 & src2）的按位合取。计算两个相同大小矩阵的逐元素按位逻辑合取。
GMat	cv::gapi::bitwise_and (const GMat &src1, const GScalar &src2)
GMat	cv::gapi::bitwise_not (const GMat &src)
	反转数组的每个位。
GMat	cv::gapi::bitwise_or (const GMat &src1, const GMat &src2)
	计算两个矩阵（src1 | src2）的按位析取。计算两个相同大小矩阵的逐元素按位逻辑析取。
GMat	cv::gapi::bitwise_or (const GMat &src1, const GScalar &src2)
GMat	cv::gapi::bitwise_xor (const GMat &src1, const GMat &src2)
	计算两个矩阵（src1 ^ src2）的按位逻辑“异或”。计算两个相同大小矩阵的逐元素按位逻辑“异或”。
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)
	对两个矩阵执行逐元素比较，检查第一个矩阵的元素是否等于第二个矩阵的元素。
GMat	cv::gapi::cmpEQ (const GMat &src1, const GScalar &src2)
GMat	cv::gapi::cmpGE (const GMat &src1, const GMat &src2)
	对两个矩阵执行逐元素比较，检查第一个矩阵的元素是否大于或等于第二个矩阵的元素。
GMat	cv::gapi::cmpGE (const GMat &src1, const GScalar &src2)
GMat	cv::gapi::cmpGT (const GMat &src1, const GMat &src2)
	对两个矩阵执行逐元素比较，检查第一个矩阵的元素是否大于第二个矩阵的元素。
GMat	cv::gapi::cmpGT (const GMat &src1, const GScalar &src2)
GMat	cv::gapi::cmpLE (const GMat &src1, const GMat &src2)
	对两个矩阵执行逐元素比较，检查第一个矩阵的元素是否小于或等于第二个矩阵的元素。
GMat	cv::gapi::cmpLE (const GMat &src1, const GScalar &src2)
GMat	cv::gapi::cmpLT (const GMat &src1, const GMat &src2)
	对两个矩阵执行逐元素比较，检查第一个矩阵的元素是否小于第二个矩阵的元素。
GMat	cv::gapi::cmpLT (const GMat &src1, const GScalar &src2)
GMat	cv::gapi::cmpNE (const GMat &src1, const GMat &src2)
	对两个矩阵执行逐元素比较，检查第一个矩阵的元素是否不等于第二个矩阵的元素。
GMat	cv::gapi::cmpNE (const GMat &src1, const GScalar &src2)
GMat	cv::gapi::concatHor (const GMat &src1, const GMat &src2)
	对给定矩阵进行水平连接。
GMat	cv::gapi::concatHor (const std::vector< GMat > &v)
GMat	cv::gapi::concatVert (const GMat &src1, const GMat &src2)
	对给定矩阵执行垂直连接。
GMat	cv::gapi::concatVert (const std::vector< GMat > &v)
GMat	cv::gapi::convertTo (const GMat &src, int rdepth, double alpha=1, double beta=0)
	将矩阵转换为另一种数据深度，并可选择缩放。
GOpaque< int >	cv::gapi::countNonZero (const GMat &src)
	Counts non-zero array elements.
GMat	cv::gapi::crop (const GMat &src, const Rect &rect)
	裁剪二维矩阵。
GMat	cv::gapi::div (const GMat &src1, const GMat &src2, double scale, int ddepth=-1)
	执行两个矩阵的逐元素除法。
GMat	cv::gapi::divC (const GMat &src, const GScalar &divisor, double scale, int ddepth=-1)
	矩阵除以标量。
GMat	cv::gapi::divRC (const GScalar &divident, const GMat &src, double scale, int ddepth=-1)
	标量除以矩阵。
GMat	cv::gapi::flip (const GMat &src, int flipCode)
	围绕垂直、水平或两个轴翻转二维矩阵。
	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)
	对每个矩阵元素应用范围阈值。
std::tuple< GMat, GMat >	cv::gapi::integral (const GMat &src, int sdepth=-1, int sqdepth=-1)
	计算图像的积分。
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)
	寻找聚类中心，并将输入样本按聚类分组。
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)
	对矩阵执行查找表转换。
GMat	cv::gapi::mask (const GMat &src, const GMat &mask)
	将掩码应用于矩阵。
GMat	cv::gapi::max (const GMat &src1, const GMat &src2)
	计算两个矩阵的逐元素最大值。
GScalar	cv::gapi::mean (const GMat &src)
	计算矩阵元素的平均值。
GMat	cv::gapi::merge3 (const GMat &src1, const GMat &src2, const GMat &src3)
	从3个单通道矩阵创建一个3通道矩阵。
GMat	cv::gapi::merge4 (const GMat &src1, const GMat &src2, const GMat &src3, const GMat &src4)
	将 4 个单通道矩阵合并为一个 4 通道矩阵。
GMat	cv::gapi::min (const GMat &src1, const GMat &src2)
	计算两个矩阵的逐元素最小值。
GMat	cv::gapi::mul (const GMat &src1, const GMat &src2, double scale=1.0, int ddepth=-1)
	计算两个矩阵的逐元素缩放积。
GMat	cv::gapi::mulC (const GMat &src, const GScalar &multiplier, int ddepth=-1)
	这是一个重载成员函数，为方便起见提供。它与上面的函数仅在接受的参数上有所不同。
GMat	cv::gapi::mulC (const GMat &src, double multiplier, int ddepth=-1)
	矩阵乘以标量。
GMat	cv::gapi::mulC (const GScalar &multiplier, const GMat &src, int ddepth=-1)
	这是一个重载成员函数，为方便起见提供。它与上面的函数仅在接受的参数上有所不同。
GMat	cv::gapi::normalize (const GMat &src, double alpha, double beta, int norm_type, int ddepth=-1)
	对数组的范数或值范围进行归一化。
GScalar	cv::gapi::normInf (const GMat &src)
	计算矩阵的绝对无穷范数。
GScalar	cv::gapi::normL1 (const GMat &src)
	计算矩阵的绝对 L1 范数。
GScalar	cv::gapi::normL2 (const GMat &src)
	计算矩阵的绝对 L2 范数。
GMat	cv::gapi::phase (const GMat &x, const GMat &y, bool angleInDegrees=false)
	计算二维向量的旋转角度。
std::tuple< GMat, GMat >	cv::gapi::polarToCart (const GMat &magnitude, const GMat &angle, bool angleInDegrees=false)
	根据二维向量的幅度和角度计算其 x 和 y 坐标。
GMat	cv::gapi::remap (const GMat &src, const Mat &map1, const Mat &map2, int interpolation, int borderMode=BORDER_CONSTANT, const Scalar &borderValue=Scalar())
	对图像应用通用几何变换。
GMat	cv::gapi::select (const GMat &src1, const GMat &src2, const GMat &mask)
	根据给定掩码从输入矩阵的第一或第二项中选择值。如果掩码矩阵的相应值为 255，则该函数将输出矩阵设置为第一个输入矩阵的值；如果掩码矩阵的值设置为 0，则设置为第二个输入矩阵的值。
GOpaque< Size >	cv::gapi::streaming::size (const GFrame &src)
	从 MediaFrame 获取尺寸。
GOpaque< Size >	cv::gapi::streaming::size (const GMat &src)
	从 Mat 获取尺寸。
GOpaque< Size >	cv::gapi::streaming::size (const GOpaque< Rect > &r)
std::tuple< GMat, GMat, GMat >	cv::gapi::split3 (const GMat &src)
	将3通道矩阵分成3个单通道矩阵。
std::tuple< GMat, GMat, GMat, GMat >	cv::gapi::split4 (const GMat &src)
	将一个4通道矩阵分割成4个单通道矩阵。
GMat	cv::gapi::sqrt (const GMat &src)
	计算数组元素的平方根。
GMat	cv::gapi::sub (const GMat &src1, const GMat &src2, int ddepth=-1)
	计算两个矩阵的逐元素差值。
GMat	cv::gapi::subC (const GMat &src, const GScalar &c, int ddepth=-1)
	计算矩阵与给定标量之间的逐元素差。
GMat	cv::gapi::subRC (const GScalar &c, const GMat &src, int ddepth=-1)
	计算给定标量与矩阵之间的逐元素差。
GScalar	cv::gapi::sum (const GMat &src)
	计算所有矩阵元素的总和。
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)
	对每个矩阵元素应用固定级别的阈值。
GMat	cv::gapi::transpose (const GMat &src)
	转置矩阵。
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())
	对图像应用仿射变换。
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())
	对图像应用透视变换。