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Merge pull request #26260 from sturkmen72:upd_doc_4_x
Update Documentation #26260 ### Pull Request Readiness Checklist See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [x] I agree to contribute to the project under Apache 2 License. - [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [x] The PR is proposed to the proper branch - [ ] There is a reference to the original bug report and related work - [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [ ] The feature is well documented and sample code can be built with the project CMake
This commit is contained in:
Suleyman TURKMEN
GitHub
@@ -60,11 +60,16 @@
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/**
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@defgroup core Core functionality
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The Core module is the backbone of OpenCV, offering fundamental data structures, matrix operations,
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and utility functions that other modules depend on. It’s essential for handling image data,
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performing mathematical computations, and managing memory efficiently within the OpenCV ecosystem.
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@{
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@defgroup core_basic Basic structures
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@defgroup core_array Operations on arrays
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@defgroup core_async Asynchronous API
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@defgroup core_xml XML/YAML Persistence
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@defgroup core_xml XML/YAML/JSON Persistence
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@defgroup core_cluster Clustering
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@defgroup core_utils Utility and system functions and macros
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@{
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@@ -76,7 +81,6 @@
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@defgroup core_utils_samples Utility functions for OpenCV samples
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@}
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@defgroup core_opengl OpenGL interoperability
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@defgroup core_ipp Intel IPP Asynchronous C/C++ Converters
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@defgroup core_optim Optimization Algorithms
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@defgroup core_directx DirectX interoperability
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@defgroup core_eigen Eigen support
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@@ -96,6 +100,7 @@
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@{
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@defgroup core_parallel_backend Parallel backends API
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@}
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@defgroup core_quaternion Quaternion
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@}
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*/
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@@ -163,7 +168,7 @@ enum SortFlags { SORT_EVERY_ROW = 0, //!< each matrix row is sorted independe
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//! @} core_utils
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//! @addtogroup core
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//! @addtogroup core_array
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//! @{
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//! Covariation flags
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@@ -202,27 +207,6 @@ enum CovarFlags {
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COVAR_COLS = 16
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};
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//! @addtogroup core_cluster
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//! @{
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//! k-Means flags
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enum KmeansFlags {
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/** Select random initial centers in each attempt.*/
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KMEANS_RANDOM_CENTERS = 0,
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/** Use kmeans++ center initialization by Arthur and Vassilvitskii [Arthur2007].*/
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KMEANS_PP_CENTERS = 2,
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/** During the first (and possibly the only) attempt, use the
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user-supplied labels instead of computing them from the initial centers. For the second and
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further attempts, use the random or semi-random centers. Use one of KMEANS_\*_CENTERS flag
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to specify the exact method.*/
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KMEANS_USE_INITIAL_LABELS = 1
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};
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//! @} core_cluster
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//! @addtogroup core_array
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//! @{
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enum ReduceTypes { REDUCE_SUM = 0, //!< the output is the sum of all rows/columns of the matrix.
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REDUCE_AVG = 1, //!< the output is the mean vector of all rows/columns of the matrix.
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REDUCE_MAX = 2, //!< the output is the maximum (column/row-wise) of all rows/columns of the matrix.
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@@ -230,19 +214,12 @@ enum ReduceTypes { REDUCE_SUM = 0, //!< the output is the sum of all rows/column
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REDUCE_SUM2 = 4 //!< the output is the sum of all squared rows/columns of the matrix.
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};
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//! @} core_array
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/** @brief Swaps two matrices
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*/
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CV_EXPORTS void swap(Mat& a, Mat& b);
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/** @overload */
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CV_EXPORTS void swap( UMat& a, UMat& b );
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//! @} core
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//! @addtogroup core_array
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//! @{
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/** @brief Computes the source location of an extrapolated pixel.
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The function computes and returns the coordinate of a donor pixel corresponding to the specified
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@@ -557,6 +534,10 @@ The format of half precision floating point is defined in IEEE 754-2008.
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*/
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CV_EXPORTS_W void convertFp16(InputArray src, OutputArray dst);
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/** @example samples/cpp/tutorial_code/core/how_to_scan_images/how_to_scan_images.cpp
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Check @ref tutorial_how_to_scan_images "the corresponding tutorial" for more details
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*/
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/** @brief Performs a look-up table transform of an array.
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The function LUT fills the output array with values from the look-up table. Indices of the entries
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@@ -3085,8 +3066,21 @@ private:
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//! @addtogroup core_cluster
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//! @{
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//! k-means flags
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enum KmeansFlags {
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/** Select random initial centers in each attempt.*/
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KMEANS_RANDOM_CENTERS = 0,
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/** Use kmeans++ center initialization by Arthur and Vassilvitskii [Arthur2007].*/
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KMEANS_PP_CENTERS = 2,
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/** During the first (and possibly the only) attempt, use the
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user-supplied labels instead of computing them from the initial centers. For the second and
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further attempts, use the random or semi-random centers. Use one of KMEANS_\*_CENTERS flag
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to specify the exact method.*/
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KMEANS_USE_INITIAL_LABELS = 1
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};
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/** @example samples/cpp/kmeans.cpp
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An example on K-means clustering
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An example on k-means clustering
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*/
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/** @brief Finds centers of clusters and groups input samples around the clusters.
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@@ -3096,7 +3090,7 @@ and groups the input samples around the clusters. As an output, \f$\texttt{bestL
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0-based cluster index for the sample stored in the \f$i^{th}\f$ row of the samples matrix.
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@note
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- (Python) An example on K-means clustering can be found at
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- (Python) An example on k-means clustering can be found at
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opencv_source_code/samples/python/kmeans.py
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@param data Data for clustering. An array of N-Dimensional points with float coordinates is needed.
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Examples of this array can be:
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@@ -51,7 +51,7 @@
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namespace cv
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{
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//! @addtogroup core
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//! @addtogroup core_eigen
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//! @{
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/** @brief Affine transform
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@@ -288,28 +288,28 @@ enum BorderTypes {
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By default the function prints information about the error to stderr,
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then it either stops if setBreakOnError() had been called before or raises the exception.
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It is possible to alternate error processing by using redirectError().
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@param _code - error code (Error::Code)
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@param _err - error description
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@param _func - function name. Available only when the compiler supports getting it
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@param _file - source file name where the error has occurred
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@param _line - line number in the source file where the error has occurred
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@param code - error code (Error::Code)
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@param err - error description
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@param func - function name. Available only when the compiler supports getting it
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@param file - source file name where the error has occurred
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@param line - line number in the source file where the error has occurred
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@see CV_Error, CV_Error_, CV_Assert, CV_DbgAssert
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*/
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CV_EXPORTS CV_NORETURN void error(int _code, const String& _err, const char* _func, const char* _file, int _line);
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CV_EXPORTS CV_NORETURN void error(int code, const String& err, const char* func, const char* file, int line);
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/*! @brief Signals an error and terminate application.
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By default the function prints information about the error to stderr, then it terminates application
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with std::terminate. The function is designed for invariants check in functions and methods with
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noexcept attribute.
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@param _code - error code (Error::Code)
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@param _err - error description
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@param _func - function name. Available only when the compiler supports getting it
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@param _file - source file name where the error has occurred
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@param _line - line number in the source file where the error has occurred
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@param code - error code (Error::Code)
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@param err - error description
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@param func - function name. Available only when the compiler supports getting it
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@param file - source file name where the error has occurred
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@param line - line number in the source file where the error has occurred
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@see CV_AssertTerminate
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*/
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CV_EXPORTS CV_NORETURN void terminate(int _code, const String& _err, const char* _func, const char* _file, int _line) CV_NOEXCEPT;
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CV_EXPORTS CV_NORETURN void terminate(int code, const String& err, const char* func, const char* file, int line) CV_NOEXCEPT;
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#ifdef CV_STATIC_ANALYSIS
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@@ -15,7 +15,7 @@
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namespace cv
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{
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//! @addtogroup core
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//! @addtogroup core_opencl
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//! @{
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class BufferPoolController
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@@ -30,7 +30,7 @@
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#include <opencv2/core/affine.hpp>
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namespace cv{
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//! @addtogroup core
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//! @addtogroup core_quaternion
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//! @{
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template <typename _Tp> class DualQuat;
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@@ -446,6 +446,22 @@ typedef OutputArray OutputArrayOfArrays;
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typedef const _InputOutputArray& InputOutputArray;
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typedef InputOutputArray InputOutputArrayOfArrays;
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/** @brief Returns an empty InputArray or OutputArray.
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This function is used to provide an "empty" or "null" array when certain functions
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take optional input or output arrays that you don't want to provide.
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Many OpenCV functions accept optional arguments as `cv::InputArray` or `cv::OutputArray`.
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When you don't want to pass any data for these optional parameters, you can use `cv::noArray()`
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to indicate that you are omitting them.
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@return An empty `cv::InputArray` or `cv::OutputArray` that can be used as a placeholder.
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@note This is often used when a function has optional arrays, and you do not want to
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provide a specific input or output array.
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@see cv::InputArray, cv::OutputArray
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*/
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CV_EXPORTS InputOutputArray noArray();
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/////////////////////////////////// MatAllocator //////////////////////////////////////
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@@ -508,7 +508,7 @@ The generic function partition implements an \f$O(N^2)\f$ algorithm for splittin
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into one or more equivalency classes, as described in
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<http://en.wikipedia.org/wiki/Disjoint-set_data_structure> . The function returns the number of
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equivalency classes.
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@param _vec Set of elements stored as a vector.
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@param vec Set of elements stored as a vector.
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@param labels Output vector of labels. It contains as many elements as vec. Each label labels[i] is
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a 0-based cluster index of `vec[i]`.
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@param predicate Equivalence predicate (pointer to a boolean function of two arguments or an
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@@ -518,11 +518,11 @@ may or may not be in the same class.
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@ingroup core_cluster
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*/
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template<typename _Tp, class _EqPredicate> int
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partition( const std::vector<_Tp>& _vec, std::vector<int>& labels,
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partition( const std::vector<_Tp>& vec, std::vector<int>& labels,
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_EqPredicate predicate=_EqPredicate())
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{
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int i, j, N = (int)_vec.size();
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const _Tp* vec = &_vec[0];
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int i, j, N = (int)vec.size();
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const _Tp* _vec = &vec[0];
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const int PARENT=0;
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const int RANK=1;
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@@ -548,7 +548,7 @@ partition( const std::vector<_Tp>& _vec, std::vector<int>& labels,
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for( j = 0; j < N; j++ )
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{
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if( i == j || !predicate(vec[i], vec[j]))
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if( i == j || !predicate(_vec[i], _vec[j]))
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continue;
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int root2 = j;
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@@ -53,50 +53,6 @@
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# error persistence.hpp header must be compiled as C++
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#endif
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//! @addtogroup core_c
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//! @{
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/** @brief "black box" representation of the file storage associated with a file on disk.
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Several functions that are described below take CvFileStorage\* as inputs and allow the user to
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save or to load hierarchical collections that consist of scalar values, standard CXCore objects
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(such as matrices, sequences, graphs), and user-defined objects.
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OpenCV can read and write data in XML (<http://www.w3c.org/XML>), YAML (<http://www.yaml.org>) or
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JSON (<http://www.json.org/>) formats. Below is an example of 3x3 floating-point identity matrix A,
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stored in XML and YAML files
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using CXCore functions:
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XML:
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@code{.xml}
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<?xml version="1.0">
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<opencv_storage>
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<A type_id="opencv-matrix">
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<rows>3</rows>
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<cols>3</cols>
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<dt>f</dt>
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<data>1. 0. 0. 0. 1. 0. 0. 0. 1.</data>
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</A>
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</opencv_storage>
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@endcode
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YAML:
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@code{.yaml}
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%YAML:1.0
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A: !!opencv-matrix
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rows: 3
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cols: 3
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dt: f
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data: [ 1., 0., 0., 0., 1., 0., 0., 0., 1.]
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@endcode
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As it can be seen from the examples, XML uses nested tags to represent hierarchy, while YAML uses
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indentation for that purpose (similar to the Python programming language).
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The same functions can read and write data in both formats; the particular format is determined by
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the extension of the opened file, ".xml" for XML files, ".yml" or ".yaml" for YAML and ".json" for
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JSON.
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*/
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//! @} core_c
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#include "opencv2/core/types.hpp"
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#include "opencv2/core/mat.hpp"
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@@ -283,13 +239,14 @@ element is a structure of 2 integers, followed by a single-precision floating-po
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equivalent notations of the above specification are `iif`, `2i1f` and so forth. Other examples: `u`
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means that the array consists of bytes, and `2d` means the array consists of pairs of doubles.
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@see @ref samples/cpp/filestorage.cpp
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@see @ref samples/cpp/tutorial_code/core/file_input_output/file_input_output.cpp
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*/
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//! @{
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/** @example samples/cpp/filestorage.cpp
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/** @example samples/cpp/tutorial_code/core/file_input_output/file_input_output.cpp
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A complete example using the FileStorage interface
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Check @ref tutorial_file_input_output_with_xml_yml "the corresponding tutorial" for more details
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*/
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////////////////////////// XML & YAML I/O //////////////////////////
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@@ -322,10 +279,10 @@ public:
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};
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enum State
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{
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UNDEFINED = 0,
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VALUE_EXPECTED = 1,
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NAME_EXPECTED = 2,
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INSIDE_MAP = 4
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UNDEFINED = 0, //!< Initial or uninitialized state.
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VALUE_EXPECTED = 1, //!< Expecting a value in the current position.
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NAME_EXPECTED = 2, //!< Expecting a key/name in the current position.
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INSIDE_MAP = 4 //!< Indicates being inside a map (a set of key-value pairs).
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};
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/** @brief The constructors.
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@@ -31,7 +31,7 @@
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#include <iostream>
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namespace cv
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{
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//! @addtogroup core
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//! @addtogroup core_quaternion
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//! @{
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//! Unit quaternion flag
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@@ -176,7 +176,38 @@ extern "C" typedef int (*ErrorCallback)( int status, const char* func_name,
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*/
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CV_EXPORTS ErrorCallback redirectError( ErrorCallback errCallback, void* userdata=0, void** prevUserdata=0);
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/** @brief Generates a unique temporary file name.
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This function generates a full, unique file path for a temporary file,
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which can be used to create temporary files for various purposes.
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@param suffix (optional) The desired file extension or suffix for the temporary file (e.g., ".png", ".txt").
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If no suffix is provided (suffix = 0), the file will not have a specific extension.
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@return cv::String A full unique path for the temporary file.
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@note
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- The function does not create the file, it only generates the name.
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- The file name is unique for the system session.
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- Works cross-platform (Windows, Linux, macOS).
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*/
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CV_EXPORTS String tempfile( const char* suffix = 0);
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/** @brief Searches for files matching the specified pattern in a directory.
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This function searches for files that match a given pattern (e.g., `*.jpg`)
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in the specified directory. The search can be limited to the directory itself
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or be recursive, including subdirectories.
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@param pattern The file search pattern, which can include wildcards like `*`
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(for matching multiple characters) or `?` (for matching a single character).
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@param result Output vector where the file paths matching the search
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pattern will be stored.
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@param recursive (optional) Boolean flag indicating whether to search
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subdirectories recursively. If true, the search will include all subdirectories.
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The default value is `false`.
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*/
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CV_EXPORTS void glob(String pattern, std::vector<String>& result, bool recursive = false);
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/** @brief OpenCV will try to set the number of threads for subsequent parallel regions.
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