|
| template<class Feature > |
| void | _writeFeatures (const std::vector< Feature > features, FileStorage &fs, const Mat &featureMap) |
| |
| WaveCorrectKind | autoDetectWaveCorrectKind (const std::vector< Mat > &rmats) |
| | 尝试根据全景图是水平还是垂直展开来检测波浪校正类型。
|
| |
| float | calcNormFactor (const Mat &sum, const Mat &sqSum) |
| |
| bool | calibrateRotatingCamera (const std::vector< Mat > &Hs, Mat &K) |
| |
| void | computeImageFeatures (const Ptr< Feature2D > &featuresFinder, InputArray image, ImageFeatures &features, InputArray mask=noArray()) |
| |
| void | computeImageFeatures (const Ptr< Feature2D > &featuresFinder, InputArrayOfArrays images, std::vector< ImageFeatures > &features, InputArrayOfArrays masks=noArray()) |
| |
| void | computeInteractionMatrix (const cv::Mat &uv, const cv::Mat &depths, const cv::Mat &K, cv::Mat &J) |
| | 计算一组 2D 像素的交互矩阵（[134] [54] [55]）。这通常用于视觉伺服应用中，以指令机器人移动到所需的像素位置/速度。通过反转此矩阵，可以估计相机的空间速度，即扭转。
|
| |
| cv::Vec6d | computeTwist (const cv::Mat &uv, const cv::Mat &duv, const cv::Mat &depths, const cv::Mat &K) |
| | 根据一组 2D 像素位置、它们的速度、深度值和相机内在参数计算相机扭转。像素速度通常从光流算法获得，密集流和稀疏流都可用于计算图像之间的流，并且通过将流除以图像之间的时间间隔来计算 duv。
|
| |
| void | constructGraphOutputs (const cv::GTypesInfo &out_info, cv::GRunArgs &args, cv::GRunArgsP &outs) |
| |
| Ptr< UnscentedKalmanFilter > | createAugmentedUnscentedKalmanFilter (const AugmentedUnscentedKalmanFilterParams ¶ms) |
| | 增广无迹卡尔曼滤波工厂方法。
|
| |
| void | createLaplacePyr (InputArray img, int num_levels, std::vector< UMat > &pyr) |
| |
| void | createLaplacePyrGpu (InputArray img, int num_levels, std::vector< UMat > &pyr) |
| |
| Ptr< UnscentedKalmanFilter > | createUnscentedKalmanFilter (const UnscentedKalmanFilterParams ¶ms) |
| | 无迹卡尔曼滤波工厂方法。
|
| |
| void | createWeightMap (InputArray mask, float sharpness, InputOutputArray weight) |
| |
| void | estimateFocal (const std::vector< ImageFeatures > &features, const std::vector< MatchesInfo > &pairwise_matches, std::vector< double > &focals) |
| | 估计每个给定相机的焦距。
|
| |
| void | findMaxSpanningTree (int num_images, const std::vector< MatchesInfo > &pairwise_matches, Graph &span_tree, std::vector< int > ¢ers) |
| |
| void | focalsFromHomography (const Mat &H, double &f0, double &f1, bool &f0_ok, bool &f1_ok) |
| | 假设相机仅绕其中心旋转，尝试从给定单应性估计焦距。
|
| |
| template<typename T > |
| std::enable_if< is_nongapi_type< T >::value, T >::type | get_in_meta (const GMetaArgs &, const GArgs &in_args, int idx) |
| |
| template<typename T > |
| std::enable_if<!is_nongapi_type< T >::value, typenameMetaType< T >::type >::type | get_in_meta (const GMetaArgs &in_meta, const GArgs &, int idx) |
| |
| template<typename... Ts, int... Indexes> |
| static GProtoOutputArgs | getGOut_impl (const std::tuple< Ts... > &ts, detail::Seq< Indexes... >) |
| |
| template<typename InferType > |
| InferROITraits< InferType >::outType | inferGenericROI (const std::string &tag, const typename InferROITraits< InferType >::inType &in, const cv::GInferInputs &inputs) |
| |
| std::vector< int > | leaveBiggestComponent (std::vector< ImageFeatures > &features, std::vector< MatchesInfo > &pairwise_matches, float conf_threshold) |
| |
| template<typename T > |
| auto | make_default () -> decltype(T{}) |
| |
| template<typename InferT > |
| std::shared_ptr< cv::GCall > | makeCall (const std::string &tag, std::vector< cv::GArg > &&args, std::vector< std::string > &&names, cv::GKinds &&kinds) |
| |
| String | matchesGraphAsString (std::vector< String > &paths, std::vector< MatchesInfo > &pairwise_matches, float conf_threshold) |
| |
| void | normalizeUsingWeightMap (InputArray weight, InputOutputArray src) |
| |
| bool | overlapRoi (Point tl1, Point tl2, Size sz1, Size sz2, Rect &roi) |
| |
| template<typename... Ts> |
| GProtoArgs | packArgs (Ts... args) |
| |
| template<typename... Outputs> |
| void | postprocess (Outputs &... outs) |
| |
| template<typename... Outputs> |
| void | postprocess_ocl (Outputs &... outs) |
| |
| void | restoreImageFromLaplacePyr (std::vector< UMat > &pyr) |
| |
| void | restoreImageFromLaplacePyrGpu (std::vector< UMat > &pyr) |
| |
| Rect | resultRoi (const std::vector< Point > &corners, const std::vector< Size > &sizes) |
| |
| Rect | resultRoi (const std::vector< Point > &corners, const std::vector< UMat > &images) |
| |
| Rect | resultRoiIntersection (const std::vector< Point > &corners, const std::vector< Size > &sizes) |
| |
| Point | resultTl (const std::vector< Point > &corners) |
| |
| void | selectRandomSubset (int count, int size, std::vector< int > &subset) |
| |
| int & | stitchingLogLevel () |
| |
| template<typename T > |
| gapi::GNetParam | strip (T &&t) |
| |
| void | unpackBlobs (const cv::GInferInputs::Map &blobs, std::vector< cv::GArg > &args, std::vector< std::string > &names, cv::GKinds &kinds) |
| |
| void | waveCorrect (std::vector< Mat > &rmats, WaveCorrectKind kind) |
| | 尝试使全景图更水平（或垂直）。
|
| |
| template<> |
| GOptRunArgP | wrap_opt_arg (optional< cv::Mat > &m) |
| |
| template<> |
| GOptRunArgP | wrap_opt_arg (optional< cv::MediaFrame > &f) |
| |
| template<> |
| GOptRunArgP | wrap_opt_arg (optional< cv::RMat > &m) |
| |
| template<> |
| GOptRunArgP | wrap_opt_arg (optional< cv::Scalar > &s) |
| |
| template<typename T > |
| GOptRunArgP | wrap_opt_arg (optional< std::vector< T > > &arg) |
| |
| template<typename T > |
| GOptRunArgP | wrap_opt_arg (optional< T > &arg) |
| |
1.12.0 版 Doxygen 生成。