Misc. modules/ typos

Found via `codespell`

modules/core/include/opencv2/core/core_c.h

@@ -1788,7 +1788,7 @@ CVAPI(int)  cvGraphRemoveVtx( CvGraph* graph, int index );
 CVAPI(int)  cvGraphRemoveVtxByPtr( CvGraph* graph, CvGraphVtx* vtx );
 
 
-/** Link two vertices specifed by indices or pointers if they
+/** Link two vertices specified by indices or pointers if they
    are not connected or return pointer to already existing edge
    connecting the vertices.
    Functions return 1 if a new edge was created, 0 otherwise */
@@ -2648,7 +2648,7 @@ CVAPI(void) cvSetErrStatus( int status );
 #define CV_ErrModeParent   1   /* Print error and continue */
 #define CV_ErrModeSilent   2   /* Don't print and continue */
 
-/** Retrives current error processing mode */
+/** Retrieves current error processing mode */
 CVAPI(int)  cvGetErrMode( void );
 
 /** Sets error processing mode, returns previously used mode */
@@ -2738,7 +2738,7 @@ static char cvFuncName[] = Name
 /**
  CV_CALL macro calls CV (or IPL) function, checks error status and
  signals a error if the function failed. Useful in "parent node"
- error procesing mode
+ error processing mode
  */
 #define CV_CALL( Func )                                             \
 {                                                                   \

modules/core/include/opencv2/core/cuda.hpp

@@ -56,7 +56,7 @@
   @{
     @defgroup cudacore Core part
     @{
-      @defgroup cudacore_init Initalization and Information
+      @defgroup cudacore_init Initialization and Information
       @defgroup cudacore_struct Data Structures
     @}
   @}

modules/core/include/opencv2/core/mat.hpp

@@ -2184,7 +2184,7 @@ template<typename _Tp> class Mat_ : public Mat
     Mat_(int _ndims, const int* _sizes);
     //! n-dim array constructor that sets each matrix element to specified value
     Mat_(int _ndims, const int* _sizes, const _Tp& value);
-    //! copy/conversion contructor. If m is of different type, it's converted
+    //! copy/conversion constructor. If m is of different type, it's converted
     Mat_(const Mat& m);
     //! copy constructor
     Mat_(const Mat_& m);
@@ -2275,7 +2275,7 @@ template<typename _Tp> class Mat_ : public Mat
     static MatExpr eye(int rows, int cols);
     static MatExpr eye(Size size);
 
-    //! some more overriden methods
+    //! some more overridden methods
     Mat_& adjustROI( int dtop, int dbottom, int dleft, int dright );
     Mat_ operator()( const Range& rowRange, const Range& colRange ) const;
     Mat_ operator()( const Rect& roi ) const;
@@ -2943,7 +2943,7 @@ template<typename _Tp> class SparseMat_ : public SparseMat
 
     //! the default constructor
     SparseMat_();
-    //! the full constructor equivelent to SparseMat(dims, _sizes, DataType<_Tp>::type)
+    //! the full constructor equivalent to SparseMat(dims, _sizes, DataType<_Tp>::type)
     SparseMat_(int dims, const int* _sizes);
     //! the copy constructor. If DataType<_Tp>.type != m.type(), the m elements are converted
     SparseMat_(const SparseMat& m);

modules/core/include/opencv2/core/matx.hpp

@@ -92,7 +92,7 @@ Except of the plain constructor which takes a list of elements, Matx can be init
     float values[] = { 1, 2, 3};
     Matx31f m(values);
 @endcode
-In case if C++11 features are avaliable, std::initializer_list can be also used to initialize Matx:
+In case if C++11 features are available, std::initializer_list can be also used to initialize Matx:
 @code{.cpp}
     Matx31f m = { 1, 2, 3};
 @endcode

modules/core/include/opencv2/core/opengl.hpp

@@ -245,7 +245,7 @@ class CV_EXPORTS Buffer
 
     /** @brief Maps OpenGL buffer to CUDA device memory.
 
-    This operatation doesn't copy data. Several buffer objects can be mapped to CUDA memory at a time.
+    This operation doesn't copy data. Several buffer objects can be mapped to CUDA memory at a time.
 
     A mapped data store must be unmapped with ogl::Buffer::unmapDevice before its buffer object is used.
      */

modules/core/include/opencv2/core/optim.hpp

@@ -115,7 +115,7 @@ class CV_EXPORTS MinProblemSolver : public Algorithm
     always sensible) will be used.
 
     @param x The initial point, that will become a centroid of an initial simplex. After the algorithm
-    will terminate, it will be setted to the point where the algorithm stops, the point of possible
+    will terminate, it will be set to the point where the algorithm stops, the point of possible
     minimum.
     @return The value of a function at the point found.
      */
@@ -288,7 +288,7 @@ Bland's rule <http://en.wikipedia.org/wiki/Bland%27s_rule> is used to prevent cy
 contain 32- or 64-bit floating point numbers. As a convenience, column-vector may be also submitted,
 in the latter case it is understood to correspond to \f$c^T\f$.
 @param Constr `m`-by-`n+1` matrix, whose rightmost column corresponds to \f$b\f$ in formulation above
-and the remaining to \f$A\f$. It should containt 32- or 64-bit floating point numbers.
+and the remaining to \f$A\f$. It should contain 32- or 64-bit floating point numbers.
 @param z The solution will be returned here as a column-vector - it corresponds to \f$c\f$ in the
 formulation above. It will contain 64-bit floating point numbers.
 @return One of cv::SolveLPResult

modules/core/include/opencv2/core/softfloat.hpp

@@ -82,7 +82,7 @@ namespace cv
   Both types support the following:
   - Construction from signed and unsigned 32-bit and 64 integers,
   float/double or raw binary representation
-  - Conversions betweeen each other, to float or double and to int
+  - Conversions between each other, to float or double and to int
   using @ref cvRound, @ref cvTrunc, @ref cvFloor, @ref cvCeil or a bunch of
   saturate_cast functions
   - Add, subtract, multiply, divide, remainder, square root, FMA with absolute precision

modules/core/include/opencv2/core/vsx_utils.hpp

@@ -555,7 +555,7 @@ VSX_IMPL_CONV_EVEN_2_4(vec_uint4,  vec_double2, vec_ctu, vec_ctuo)
 // vector population count
 #define vec_popcntu vec_popcnt
 
-// overload and redirect wih setting second arg to zero
+// overload and redirect with setting second arg to zero
 // since we only support conversions without the second arg
 #define VSX_IMPL_OVERLOAD_Z2(rt, rg, fnm) \
 VSX_FINLINE(rt) fnm(const rg& a) { return fnm(a, 0); }
@@ -610,7 +610,7 @@ VSX_IMPL_CONV_ODD_2_4(vec_uint4,  vec_double2, vec_ctuo, vec_ctu)
 
 #endif // XLC VSX compatibility
 
-// ignore GCC warning that casued by -Wunused-but-set-variable in rare cases
+// ignore GCC warning that caused by -Wunused-but-set-variable in rare cases
 #if defined(__GNUG__) && !defined(__clang__)
 #   define VSX_UNUSED(Tvec) Tvec __attribute__((__unused__))
 #else // CLANG, XLC
@@ -736,7 +736,7 @@ VSX_IMPL_LOAD_L8(vec_double2, double)
 #   define vec_cmpne(a, b) vec_not(vec_cmpeq(a, b))
 #endif
 
-// absoulte difference
+// absolute difference
 #ifndef vec_absd
 #   define vec_absd(a, b) vec_sub(vec_max(a, b), vec_min(a, b))
 #endif

modules/core/include/opencv2/core/wimage.hpp

@@ -289,7 +289,7 @@ class WImageC : public WImage<T>
 };
 
 /** Image class which owns the data, so it can be allocated and is always
-freed.  It cannot be copied but can be explicity cloned.
+freed.  It cannot be copied but can be explicitly cloned.
 */
 template<typename T>
 class WImageBuffer : public WImage<T>

modules/core/src/array.cpp

@@ -1914,7 +1914,7 @@ cvPtrND( const CvArr* arr, const int* idx, int* _type,
 }
 
 
-// Returns specifed element of n-D array given linear index
+// Returns specified element of n-D array given linear index
 CV_IMPL  CvScalar
 cvGet1D( const CvArr* arr, int idx )
 {
@@ -1949,7 +1949,7 @@ cvGet1D( const CvArr* arr, int idx )
 }
 
 
-// Returns specifed element of 2D array
+// Returns specified element of 2D array
 CV_IMPL  CvScalar
 cvGet2D( const CvArr* arr, int y, int x )
 {
@@ -1983,7 +1983,7 @@ cvGet2D( const CvArr* arr, int y, int x )
 }
 
 
-// Returns specifed element of 3D array
+// Returns specified element of 3D array
 CV_IMPL  CvScalar
 cvGet3D( const CvArr* arr, int z, int y, int x )
 {
@@ -2005,7 +2005,7 @@ cvGet3D( const CvArr* arr, int z, int y, int x )
 }
 
 
-// Returns specifed element of nD array
+// Returns specified element of nD array
 CV_IMPL  CvScalar
 cvGetND( const CvArr* arr, const int* idx )
 {
@@ -2025,7 +2025,7 @@ cvGetND( const CvArr* arr, const int* idx )
 }
 
 
-// Returns specifed element of n-D array given linear index
+// Returns specified element of n-D array given linear index
 CV_IMPL  double
 cvGetReal1D( const CvArr* arr, int idx )
 {
@@ -2064,7 +2064,7 @@ cvGetReal1D( const CvArr* arr, int idx )
 }
 
 
-// Returns specifed element of 2D array
+// Returns specified element of 2D array
 CV_IMPL  double
 cvGetReal2D( const CvArr* arr, int y, int x )
 {
@@ -2103,7 +2103,7 @@ cvGetReal2D( const CvArr* arr, int y, int x )
 }
 
 
-// Returns specifed element of 3D array
+// Returns specified element of 3D array
 CV_IMPL  double
 cvGetReal3D( const CvArr* arr, int z, int y, int x )
 {
@@ -2131,7 +2131,7 @@ cvGetReal3D( const CvArr* arr, int z, int y, int x )
 }
 
 
-// Returns specifed element of nD array
+// Returns specified element of nD array
 CV_IMPL  double
 cvGetRealND( const CvArr* arr, const int* idx )
 {
@@ -2156,7 +2156,7 @@ cvGetRealND( const CvArr* arr, const int* idx )
 }
 
 
-// Assigns new value to specifed element of nD array given linear index
+// Assigns new value to specified element of nD array given linear index
 CV_IMPL  void
 cvSet1D( CvArr* arr, int idx, CvScalar scalar )
 {
@@ -2187,7 +2187,7 @@ cvSet1D( CvArr* arr, int idx, CvScalar scalar )
 }
 
 
-// Assigns new value to specifed element of 2D array
+// Assigns new value to specified element of 2D array
 CV_IMPL  void
 cvSet2D( CvArr* arr, int y, int x, CvScalar scalar )
 {
@@ -2216,7 +2216,7 @@ cvSet2D( CvArr* arr, int y, int x, CvScalar scalar )
 }
 
 
-// Assigns new value to specifed element of 3D array
+// Assigns new value to specified element of 3D array
 CV_IMPL  void
 cvSet3D( CvArr* arr, int z, int y, int x, CvScalar scalar )
 {
@@ -2234,7 +2234,7 @@ cvSet3D( CvArr* arr, int z, int y, int x, CvScalar scalar )
 }
 
 
-// Assigns new value to specifed element of nD array
+// Assigns new value to specified element of nD array
 CV_IMPL  void
 cvSetND( CvArr* arr, const int* idx, CvScalar scalar )
 {

modules/core/src/conjugate_gradient.cpp

@@ -150,7 +150,7 @@ namespace cv
         d*=-1.0;
         d.copyTo(r);
 
-        //here everything goes. check that everything is setted properly
+        //here everything goes. check that everything is set properly
         dprintf(("proxy_x\n"));print_matrix(proxy_x);
         dprintf(("d first time\n"));print_matrix(d);
         dprintf(("r\n"));print_matrix(r);

modules/core/src/cuda_info.cpp

@@ -932,7 +932,7 @@ namespace
     {
         // Defines for GPU Architecture types (using the SM version to determine the # of cores per SM
         typedef struct {
-            int SM; // 0xMm (hexidecimal notation), M = SM Major version, and m = SM minor version
+            int SM; // 0xMm (hexadecimal notation), M = SM Major version, and m = SM minor version
             int Cores;
         } SMtoCores;
 

modules/core/src/downhill_simplex.cpp

@@ -129,7 +129,7 @@ system("pause");
 return 0;
 }
 
-****Suggesttion for imporving Simplex implentation***************************************************************************************
+****Suggestion for improving Simplex implementation***************************************************************************************
 
 Currently the downhilll simplex method outputs the function value that is minimized. It should also return the coordinate points where the
 function is minimized. This is very useful in many applications such as using back projection methods to find a point of intersection of

modules/core/src/opengl.cpp

@@ -1630,7 +1630,7 @@ Context& initializeContextFromGL()
 
     for (int i = 0; i < (int)numPlatforms; i++)
     {
-        // query platform extension: presence of "cl_khr_gl_sharing" extension is requred
+        // query platform extension: presence of "cl_khr_gl_sharing" extension is required
         {
             AutoBuffer<char> extensionStr;
 

modules/core/src/parallel_impl.cpp

@@ -730,7 +730,7 @@ void ThreadPool::setNumOfThreads(unsigned n)
     {
         num_threads = n;
         if (n == 1)
-           if (job == NULL) reconfigure(0);  // stop worker threads immediatelly
+           if (job == NULL) reconfigure(0);  // stop worker threads immediately
     }
 }
 

modules/core/src/persistence_base64.cpp

@@ -470,7 +470,7 @@ class Base64ContextEmitter
 
     /*
      * a convertor must provide :
-     * - `operator >> (uchar * & dst)` for writting current binary data to `dst` and moving to next data.
+     * - `operator >> (uchar * & dst)` for writing current binary data to `dst` and moving to next data.
      * - `operator bool` for checking if current loaction is valid and not the end.
      */
     template<typename _to_binary_convertor_t> inline
@@ -493,7 +493,7 @@ class Base64ContextEmitter
 
     bool flush()
     {
-        /* controll line width, so on. */
+        /* control line width, so on. */
         size_t len = base64_encode(src_beg, base64_buffer.data(), 0U, src_cur - src_beg);
         if (len == 0U)
             return false;

modules/core/src/persistence_c.cpp

@@ -259,7 +259,7 @@ cvOpenFileStorage( const char* query, CvMemStorage* dststorage, int flags, const
                 xml_buf_size = MIN(xml_buf_size, int(file_size));
                 fseek( fs->file, -xml_buf_size, SEEK_END );
                 char* xml_buf = (char*)cvAlloc( xml_buf_size+2 );
-                // find the last occurence of </opencv_storage>
+                // find the last occurrence of </opencv_storage>
                 for(;;)
                 {
                     int line_offset = (int)ftell( fs->file );

modules/core/src/persistence_types.cpp

@@ -1230,7 +1230,7 @@ static void* icvReadGraph( CvFileStorage* fs, CvFileNode* node )
                     vtx_buf[vtx1], vtx_buf[vtx2], 0, &edge );
 
                 if( result == 0 )
-                    CV_Error( CV_StsBadArg, "Duplicated edge has occured" );
+                    CV_Error( CV_StsBadArg, "Duplicated edge has occurred" );
 
                 edge->weight = *(float*)(dst_ptr + sizeof(int)*2);
                 if( elem_size > (int)sizeof(CvGraphEdge) )

modules/core/src/system.cpp

@@ -481,7 +481,7 @@ struct HWFeatures
         have[CV_CPU_NEON] = (features & ANDROID_CPU_ARM_FEATURE_NEON) != 0;
         have[CV_CPU_FP16] = (features & ANDROID_CPU_ARM_FEATURE_VFP_FP16) != 0;
       #else
-        __android_log_print(ANDROID_LOG_INFO, "OpenCV", "cpufeatures library is not avaialble for CPU detection");
+        __android_log_print(ANDROID_LOG_INFO, "OpenCV", "cpufeatures library is not available for CPU detection");
         #if CV_NEON
         __android_log_print(ANDROID_LOG_INFO, "OpenCV", "- NEON instructions is enabled via build flags");
         have[CV_CPU_NEON] = true;

modules/core/test/ocl/test_dft.cpp

@@ -112,7 +112,7 @@ OCL_TEST_P(Dft, Mat)
     OCL_OFF(cv::dft(src, dst, dft_flags, nonzero_rows));
     OCL_ON(cv::dft(usrc, udst, dft_flags, nonzero_rows));
 
-    // In case forward R2C 1d tranform dst contains only half of output
+    // In case forward R2C 1d transform dst contains only half of output
     // without complex conjugate
     if (dft_type == R2C && is1d && (dft_flags & cv::DFT_INVERSE) == 0)
     {

modules/core/test/test_downhill_simplex.cpp

@@ -51,7 +51,7 @@ static void mytest(cv::Ptr<cv::DownhillSolver> solver,cv::Ptr<cv::MinProblemSolv
     solver->getInitStep(settedStep);
     ASSERT_TRUE(settedStep.rows==1 && settedStep.cols==ndim);
     ASSERT_TRUE(std::equal(step.begin<double>(),step.end<double>(),settedStep.begin<double>()));
-    std::cout<<"step setted:\n\t"<<step<<std::endl;
+    std::cout<<"step set:\n\t"<<step<<std::endl;
     double res=solver->minimize(x);
     std::cout<<"res:\n\t"<<res<<std::endl;
     std::cout<<"x:\n\t"<<x<<std::endl;

modules/core/test/test_operations.cpp

@@ -466,7 +466,7 @@ bool CV_OperationsTest::TestSubMatAccess()
         Vec3f ydir(1.f, 0.f, 1.f);
         Vec3f fpt(0.1f, 0.7f, 0.2f);
         T_bs.setTo(0);
-        T_bs(Range(0,3),Range(2,3)) = 1.0*Mat(cdir); // wierd OpenCV stuff, need to do multiply
+        T_bs(Range(0,3),Range(2,3)) = 1.0*Mat(cdir); // weird OpenCV stuff, need to do multiply
         T_bs(Range(0,3),Range(1,2)) = 1.0*Mat(ydir);
         T_bs(Range(0,3),Range(0,1)) = 1.0*Mat(cdir.cross(ydir));
         T_bs(Range(0,3),Range(3,4)) = 1.0*Mat(fpt);

modules/core/test/test_umat.cpp

@@ -1192,7 +1192,7 @@ OCL_TEST(UMat, DISABLED_OCL_ThreadSafe_CleanupCallback_1_VeryLongTest)
     }
 }
 
-// Case 2: concurent deallocation of UMatData between UMat and Mat deallocators. Hard to catch!
+// Case 2: concurrent deallocation of UMatData between UMat and Mat deallocators. Hard to catch!
 OCL_TEST(UMat, DISABLED_OCL_ThreadSafe_CleanupCallback_2_VeryLongTest)
 {
     if (!cv::ocl::useOpenCL())

modules/dnn/CMakeLists.txt

@@ -41,7 +41,7 @@ endif()
 
 add_definitions(-DHAVE_PROTOBUF=1)
 
-#supress warnings in autogenerated caffe.pb.* files
+#suppress warnings in autogenerated caffe.pb.* files
 ocv_warnings_disable(CMAKE_CXX_FLAGS
     -Wunused-parameter -Wundef -Wignored-qualifiers -Wno-enum-compare
     -Wdeprecated-declarations

modules/dnn/include/opencv2/dnn.hpp

@@ -53,7 +53,7 @@
         - API for new layers creation, layers are building bricks of neural networks;
         - set of built-in most-useful Layers;
         - API to constuct and modify comprehensive neural networks from layers;
-        - functionality for loading serialized networks models from differnet frameworks.
+        - functionality for loading serialized networks models from different frameworks.
 
     Functionality of this module is designed only for forward pass computations (i. e. network testing).
     A network training is in principle not supported.