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OpenCV 4.10.0
开源计算机视觉
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OpenCV 4.10.0
开源计算机视觉
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#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>命名空间 | |
| 命名空间 | cv |
| 硬盘上与文件关联的文件存储“黑盒”表示。 | |
| 命名空间 | cv::gapi |
| 命名空间 | cv::gapi::core |
| 此命名空间包含 OpenCV Core 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执行模式相关的 G-API 函数、结构和符号。 | |
类型定义 | |
| 使用 | cv::gapi::core::GMat2 = std::tuple< GMat, GMat > |
| 使用 | cv::gapi::core::GMat3 = std::tuple< GMat, GMat, GMat > |
| 使用 | cv::gapi::core::GMat4 = std::tuple< GMat, GMat, GMat, GMat > |
| 使用 | cv::gapi::core::GMatScalar = std::tuple< GMat, GScalar > |
| 使用 | cv::gapi::core::GResize = cv::gapi::imgproc::GResize |
| 使用 | cv::gapi::core::GResizeP = cv::gapi::imgproc::GResizeP |
函数 | |
| GMat | cv::gapi::absDiff (const GMat &src1, const GMat &src2) |
| 计算两个矩阵中每个元素的绝对差。 | |
| 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) |
| 计算两个矩阵的元素级和。 | |
| GMat | cv::gapi::addC (const GMat &src1, const GScalar &c, int ddepth=-1) |
| 计算矩阵和给定标量的元素级和。 | |
| GMat | cv::gapi::addC (const GScalar &c, const GMat &src1, int ddepth=-1) |
| 这是一个提供方便的重载成员函数。它与上述函数的区别仅在于它接受的参数。 | |
| 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总和。 | |
| GMat | cv::gapi::bitwise_and (const GMat &src1, const GMat &src2) |
| 计算两个矩阵 (src1 & src2) 的按位与。计算相同大小的两个矩阵的每个元素按位逻辑与。 | |
| GMat | cv::gapi::bitwise_and (const GMat &src1, const GScalar &src2) |
| GMat | cv::gapi::bitwise_not (const GMat &src) |
| 反转数组中的每个位。 | |
| GMat | cv::gapi::bitwise_or (const GMat &src1, const GMat &src2) |
| 计算两个矩阵 (src1 | src2) 的按位或。计算相同大小的两个矩阵的每个元素按位逻辑或。 | |
| GMat | cv::gapi::bitwise_or (const GMat &src1, const GScalar &src2) |
| GMat | cv::gapi::bitwise_xor (const GMat &src1, const GMat &src2) |
| 计算两个矩阵的按位逻辑"异或" (src1 ^ src2)。计算相同大小的两个矩阵的每个元素按位逻辑"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) |
| 计算二维向量的幅值和角度。 | |
| GMat | cv::gapi::cmpEQ (const GMat &src1, const GMat &src2) |
| 执行两个矩阵的每个元素比较，检查第一个矩阵的元素是否等于第二个矩阵中的元素。 | |
| GMat | cv::gapi::cmpEQ (const GMat &src1, const GScalar &src2) |
| GMat | cv::gapi::cmpGE (const GMat &src1, const GMat &src2) |
| 执行两个矩阵的每个元素比较，检查第一个矩阵的元素是否大于或等于第二个矩阵中的元素。 | |
| GMat | cv::gapi::cmpGE (const GMat &src1, const GScalar &src2) |
| GMat | cv::gapi::cmpGT (const GMat &src1, const GMat &src2) |
| 执行两个矩阵的每个元素比较，检查第一个矩阵的元素是否大于第二个矩阵中的元素。 | |
| GMat | cv::gapi::cmpGT (const GMat &src1, const GScalar &src2) |
| GMat | cv::gapi::cmpLE (const GMat &src1, const GMat &src2) |
| 对所有矩阵元素进行逐元素比较，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) |
| 对所有矩阵元素进行逐元素比较，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) |
| 对所有矩阵元素进行逐元素比较，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) |
| 对给定矩阵应用水平连接。 | |
| GMat | cv::gapi::concatHor (const std::vector< GMat > &v) |
| GMat | cv::gapi::concatVert (const GMat &src1, const GMat &src2) |
| 对给定矩阵应用垂直连接。 | |
| GMat | cv::gapi::concatVert (const std::vector< GMat > &v) |
| GMat | cv::gapi::convertTo (const GMat &src, int rdepth, double alpha=1, double beta=0) |
| 将矩阵转换到另一种数据深度，可选比例缩放。 | |
| GOpaque< int > | cv::gapi::countNonZero (const GMat &src) |
| 计算非零数组元素的数量。 | |
| GMat | cv::gapi::crop (const GMat &src, const Rect &rect) |
| 裁剪2D矩阵。 | |
| GMat | cv::gapi::div (const GMat &src1, const GMat &src2, double scale, int ddepth=-1) |
| 对两个矩阵执行逐元素除法。 | |
| GMat | cv::gapi::divC (const GMat &src, const GScalar &divisor, double scale, int ddepth=-1) |
| 用矩阵除以标量。 | |
| GMat | cv::gapi::divRC (const GScalar ÷nt, const GMat &src, double scale, int ddepth=-1) |
| 用标量除以矩阵。 | |
| GMat | cv::gapi::flip (const GMat &src, int flipCode) |
| 沿垂直、水平或同时沿两个轴翻转2D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_TYPEDKERNEL: (GAnd,< GMat(GMat, GMat)>, "org.opencv.core.pixelwise.bitwise_and") | |
| cv::gapi::core::G_TYPEDKERNEL: (GAndS,< GMat(GMat, GScalar)>, "org.opencv.core.pixelwise.bitwise_andS") | |
| cv::gapi::core::G_TYPEDKERNEL: (GCmpEQ,< GMat(GMat, GScalar)>, "org.opencv.core.pixelwise.compare.cmpEQ") | |
| cv::gapi::core::G_TYPEDKERNEL: (GCmpEQScalar,< GMat(GMat, GScalar)>, "org.opencv.core.pixelwise.compare.cmpEQScalar") | |
| cv::gapi::core::G_TYPEDKERNEL: (GCmpGE,< GMat(GMat, GScalar)>, "org.opencv.core.pixelwise.compare.cmpGE") | |
| cv::gapi::core::G_TYPEDKERNEL: (GCmpGEScalar,< GMat(GMat, GScalar)>, "org.opencv.core.pixelwise.compare.cmpGEScalar") | |
| cv::gapi::core::G_TYPEDKERNEL: (GCmpGT,< GMat(GMat, GScalar)>, "org.opencv.core.pixelwise.compare.cmpGT") | |
| cv::gapi::core::G_TYPEDKERNEL: (GCmpGTScalar,< GMat(GMat, GScalar)>, "org.opencv.core.pixelwise.compare.cmpGTScalar") | |
| cv::gapi::core::G_TYPEDKERNEL: (GCmpLE,< GMat(GMat, GScalar)>, "org.opencv.core.pixelwise.compare.cmpLE") | |
| cv::gapi::core::G_TYPEDKERNEL: (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(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, 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, < interviewing GMat(GMat, GMat) >, "org.opencv.core.matrixop.min") | |
| cv::gapi::core::G_TYPED KERNEL (GMul, < interviewing GMat(GMat, GMat, double, int) >, "org.opencv.core.math.mul") | |
| cv::gapi::core::G_TYPED KERNEL (GMulC, < interviewing GMat(GMat, GScalar, int) >, "org.opencv.core.math.mulC") | |
| cv::gapi::core::G_TYPED KERNEL (GMulCOld, < interviewing GMat(GMat, double, int) >, "org.opencv.core.math.mulCOld") | |
| cv::gapi::core::G_TYPED KERNEL (GMulS, < interviewing GMat(GMat, GScalar) >, "org.opencv.core.math.muls") | |
| cv::gapi::core::G_TYPED KERNEL (GNormalize, < interviewing GMat(GMat, double, double, int, int) >, "org.opencv.core.normalize") | |
| cv::gapi::core::G_TYPED KERNEL (GNormInf, < interviewing GScalar(GMat) >, "org.opencv.core.matrixop.norminf") | |
| cv::gapi::core::G_TYPED KERNEL (GNormL1, < interviewing GScalar(GMat) >, "org.opencv.core.matrixop.norml1") | |
| cv::gapi::core::G_TYPED KERNEL (GNormL2, < interviewing GScalar(GMat) >, "org.opencv.core.matrixop.norml2") | |
| cv::gapi::core::G_TYPED KERNEL (GNot, < interviewing GMat(GMat) >, "org.opencv.core.pixelwise.bitwise_not") | |
| cv::gapi::core::G_TYPED KERNEL (GOr, < interviewing GMat(GMat, GMat) >, "org.opencv.core.pixelwise.bitwise_or") | |
| cv::gapi::core::G_TYPED KERNEL (GOrS, < interviewing GMat(GMat, GScalar) >, "org.opencv.core.pixelwise.bitwise_orS") | |
| cv::gapi::core::G_TYPED KERNEL (GPhase, < interviewing GMat(GMat, GMat, bool) >, "org.opencv.core.math.phase") | |
| cv::gapi::core::G_TYPED KERNEL (GRemap, < interviewing GMat(GMat, Mat, Mat, int, int, Scalar) >, "org.opencv.core.transform.remap") | |
| cv::gapi::core::G_TYPED KERNEL (GSelect, < interviewing GMat(GMat, GMat, GMat) >, "org.opencv.core.pixelwise.select") | |
| 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< Rect >)>, "org.opencv.streaming.sizeR") | |
| 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, | |
| cv::gapi::core::G_TYPED KERNEL (GSum,< GScalar( | |
| cv::gapi::core::G_TYPED KERNEL (GThreshold,< | |
| cv::gapi::core::G_TYPED KERNEL (GTranspose,< | |
| cv::gapi::core::G_TYPED KERNEL (GWarpAffine,< | |
| cv::gapi::core::G_TYPED KERNEL (GWarpPerspective,< | |
| cv::gapi::core::G_TYPED KERNEL (GXor,< | |
| cv::gapi::core::G_TYPED KERNEL (GXorS,< | |
| 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) |
| 将阈值范围应用于每个矩阵元素。 | |
| 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分组到聚类周围。 | |
| 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) |
| 执行矩阵的查找表转换。 | |
| 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) |
| 计算两矩阵的每个元素的取最大值的操作。 | |
| GScalar | cv::gapi::mean (const GMat &src) |
| 计算矩阵元素的平均值（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) |
| 从4个单通道矩阵创建一个4通道矩阵。 | |
| GMat | cv::gapi::min (const GMat &src1, const GMat &src2) |
| 计算两矩阵的每个元素的取最小值的操作。 | |
| GMat | cv::gapi::mul (const GMat &src1, const GMat &src2, double scale=1.0, int ddepth=-1) |
| 计算两矩阵的每个元素的缩放乘积。 | |
| GMat | cv::gapi::mulC (const GMat &src, const GScalar &multiplier, int ddepth=-1) |
| 这是一个提供方便的重载成员函数。它与上述函数的区别仅在于它接受的参数。 | |
| GMat | cv::gapi::mulC (const GMat &src, double multiplier, int ddepth=-1) |
| 将矩阵乘以标量。 | |
| GMat | cv::gapi::mulC (const GScalar &multiplier, const GMat &src, int ddepth=-1) |
| 这是一个提供方便的重载成员函数。它与上述函数的区别仅在于它接受的参数。 | |
| GMat | cv::gapi::normalize (const GMat &src, double alpha, double beta, int norm_type, int ddepth=-1) |
| 归一化数组的标准或值范围。 | |
| GScalar | cv::gapi::normInf (const GMat &src) |
| 计算矩阵的绝对无限范数。 | |
| 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2D向量的旋转角度。 | |
| std::tuple< GMat, GMat > | cv::gapi::polarToCart (const magnitude, const GMat &angle, bool angleInDegrees=false) |
| 根据向量的大小和角度计算2D向量的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()) |
| 对一个图像应用通用的几何变换。 | |
| GMat | cv::gapi::select (const GMat &src1, const GMat &src2, const GMat &mask) |
| 根据给定的掩码从输入矩阵的第一个或第二个中选择值。如果掩码矩阵的对应值是255，则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中获取尺寸。 | |
| GOpaque< Size > | cv::gapi::streaming::size (const GMat &src) |
| 从Mat中获取尺寸。 | |
| GOpaque< Size > | cv::gapi::streaming::size (const GOpaque< Rect > &r) |
| std::tuple< GMat, GMat, GMat > | cv::gapi::split3 (const GMat &src) |
| 将3通道矩阵分割为3个单通道矩阵。 | |
| std::tuple< GMat, GMat, GMat, GMat > | cv::gapi::split4 (const GMat &src) |
| 将4通道矩阵分割为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) |
| 计算两个矩阵每个元素的差值。 | |
| GMat | cv::gapi::subC (const GMat &src, const GScalar &c, int ddepth=-1) |
| 计算矩阵与给定标量的每个元素差值。 | |
| GMat | cv::gapi::subRC (const GScalar &c, const GMat &src, int ddepth=-1) |
| 计算给定标量与矩阵的每个元素差值。 | |
| GScalar | cv::gapi::sum (const GMat &src) |
| 计算矩阵所有元素的总和。 | |
| 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。 | |
1.9.8