Fix modules/ typos

Found using `codespell -q 3 -S ./3rdparty -L activ,amin,ang,atleast,childs,dof,endwhile,halfs,hist,iff,nd,od,uint`

modules/calib3d/src/calibration.cpp

@@ -627,7 +627,7 @@ static void cvProjectPoints2Internal( const CvMat* objectPoints,
 
     if( (CV_MAT_TYPE(A->type) != CV_64FC1 && CV_MAT_TYPE(A->type) != CV_32FC1) ||
         A->rows != 3 || A->cols != 3 )
-        CV_Error( CV_StsBadArg, "Instrinsic parameters must be 3x3 floating-point matrix" );
+        CV_Error( CV_StsBadArg, "Intrinsic parameters must be 3x3 floating-point matrix" );
 
     cvConvert( A, &_a );
     fx = a[0]; fy = a[4];

modules/calib3d/src/chessboard.cpp

@@ -119,7 +119,7 @@ cv::Mat findHomography1D(cv::InputArray _src,cv::InputArray _dst)
     cv::Mat b = cv::Mat::zeros(count,1,CV_64FC1);
 
     // fill A;b and perform singular value decomposition
-    // it is assumed that w is one for both cooridnates
+    // it is assumed that w is one for both coordinates
     // h22 is kept to 1
     switch(src_n.type())
     {

modules/calib3d/src/chessboard.hpp

@@ -252,7 +252,7 @@ class Chessboard: public cv::Feature2D
                 /**
                  * \brief Estimates the search area for a specific point based on the given homography
                  *
-                 * \param[in] H homography descriping the transformation from ideal board to real one
+                 * \param[in] H homography describing the transformation from ideal board to real one
                  * \param[in] row Row of the point
                  * \param[in] col Col of the point
                  * \param[in] p Percentage [0..1]
@@ -562,8 +562,8 @@ class Chessboard: public cv::Feature2D
                 void flipHorizontal();
 
                 /**
-                 * \brief Flips and rotates the board so that the anlge of
-                 * either the black or white diagonale is bigger than the x
+                 * \brief Flips and rotates the board so that the angle of
+                 * either the black or white diagonal is bigger than the x
                  * and y axis of the board and from a right handed
                  * coordinate system
                  */
@@ -650,7 +650,7 @@ class Chessboard: public cv::Feature2D
                         bool right(bool check_empty=false);   // moves one corner to the right or returns false
                         bool bottom(bool check_empty=false);  // moves one corner to the bottom or returns false
                         bool top(bool check_empty=false);     // moves one corner to the top or returns false
-                        bool checkCorner()const;              // returns ture if the current corner belongs to at least one
+                        bool checkCorner()const;              // returns true if the current corner belongs to at least one
                                                               // none empty cell
                         bool isNaN()const;                    // returns true if the currnet corner is NaN
 

modules/calib3d/src/five-point.cpp

@@ -506,7 +506,7 @@ int cv::recoverPose( InputArray E, InputArray _points1, InputArray _points2,
     // Do the cheirality check.
     // Notice here a threshold dist is used to filter
     // out far away points (i.e. infinite points) since
-    // their depth may vary between positive and negtive.
+    // their depth may vary between positive and negative.
     std::vector<Mat> allTriangulations(4);
     Mat Q;
 

modules/calib3d/src/ippe.cpp

@@ -650,7 +650,7 @@ void PoseSolver::makeCanonicalObjectPoints(InputArray _objectPoints, OutputArray
 
         if (!computeObjextSpaceR3Pts(objectPoints,R))
         {
-            //we could not compute R, problably because there is a duplicate point in {objectPoints(0),objectPoints(1),objectPoints(2)}.
+            //we could not compute R, probably because there is a duplicate point in {objectPoints(0),objectPoints(1),objectPoints(2)}.
             //So we compute it with the SVD (which is slower):
             computeObjextSpaceRSvD(UZero,R);
         }

modules/calib3d/test/test_homography.cpp

@@ -191,7 +191,7 @@ void CV_HomographyTest::print_information_4(int _method, int j, int N, int k, in
     cout << "Number of point: " << k << endl;
     cout << "Norm type using in criteria: "; if (NORM_TYPE[l] == 1) cout << "INF"; else if (NORM_TYPE[l] == 2) cout << "L1"; else cout << "L2"; cout << endl;
     cout << "Difference with noise of point: " << diff << endl;
-    cout << "Maxumum allowed difference: " << max_2diff << endl; cout << endl;
+    cout << "Maximum allowed difference: " << max_2diff << endl; cout << endl;
 }
 
 void CV_HomographyTest::print_information_5(int _method, int j, int N, int l, double diff)
@@ -204,7 +204,7 @@ void CV_HomographyTest::print_information_5(int _method, int j, int N, int l, do
     cout << "Count of points: " << N << endl;
     cout << "Norm type using in criteria: "; if (NORM_TYPE[l] == 1) cout << "INF"; else if (NORM_TYPE[l] == 2) cout << "L1"; else cout << "L2"; cout << endl;
     cout << "Difference with noise of points: " << diff << endl;
-    cout << "Maxumum allowed difference: " << max_diff << endl; cout << endl;
+    cout << "Maximum allowed difference: " << max_diff << endl; cout << endl;
 }
 
 void CV_HomographyTest::print_information_6(int _method, int j, int N, int k, double diff, bool value)
@@ -244,7 +244,7 @@ void CV_HomographyTest::print_information_8(int _method, int j, int N, int k, in
     cout << "Number of point: " << k << "   " << endl;
     cout << "Norm type using in criteria: "; if (NORM_TYPE[l] == 1) cout << "INF"; else if (NORM_TYPE[l] == 2) cout << "L1"; else cout << "L2"; cout << endl;
     cout << "Difference with noise of point: " << diff << endl;
-    cout << "Maxumum allowed difference: " << max_2diff << endl; cout << endl;
+    cout << "Maximum allowed difference: " << max_2diff << endl; cout << endl;
 }
 
 void CV_HomographyTest::run(int)

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

@@ -53,7 +53,7 @@
                           which is incompatible with C
 
    It is OK to disable it because we only extend few plain structures with
-   C++ construrtors for simpler interoperability with C++ API of the library
+   C++ constructors for simpler interoperability with C++ API of the library
 */
 #    pragma warning(disable:4190)
 #  elif defined __clang__ && __clang_major__ >= 3

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

@@ -126,7 +126,7 @@ public:
     CV_WRAP GpuMat(int rows, int cols, int type, GpuMat::Allocator* allocator = GpuMat::defaultAllocator());
     CV_WRAP GpuMat(Size size, int type, GpuMat::Allocator* allocator = GpuMat::defaultAllocator());
 
-    //! constucts GpuMat and fills it with the specified value _s
+    //! constructs GpuMat and fills it with the specified value _s
     CV_WRAP GpuMat(int rows, int cols, int type, Scalar s, GpuMat::Allocator* allocator = GpuMat::defaultAllocator());
     CV_WRAP GpuMat(Size size, int type, Scalar s, GpuMat::Allocator* allocator = GpuMat::defaultAllocator());
 

modules/core/include/opencv2/core/hal/intrin_cpp.hpp

@@ -76,7 +76,7 @@ implemented as a structure based on a one SIMD register.
 - cv::v_uint32x4 and cv::v_int32x4: four 32-bit integer values (unsgined/signed) - int
 - cv::v_uint64x2 and cv::v_int64x2: two 64-bit integer values (unsigned/signed) - int64
 - cv::v_float32x4: four 32-bit floating point values (signed) - float
-- cv::v_float64x2: two 64-bit floating point valies (signed) - double
+- cv::v_float64x2: two 64-bit floating point values (signed) - double
 
 @note
 cv::v_float64x2 is not implemented in NEON variant, if you want to use this type, don't forget to

modules/core/include/opencv2/core/hal/intrin_vsx.hpp

@@ -1272,7 +1272,7 @@ inline v_float32x4 v_load_expand(const float16_t* ptr)
 
 inline void v_pack_store(float16_t* ptr, const v_float32x4& v)
 {
-// fixme: Is there any buitin op or intrinsic that cover "xvcvsphp"?
+// fixme: Is there any builtin op or intrinsic that cover "xvcvsphp"?
 #if CV_VSX3 && !defined(CV_COMPILER_VSX_BROKEN_ASM)
     vec_ushort8 vf16;
     __asm__ __volatile__ ("xvcvsphp %x0,%x1" : "=wa" (vf16) : "wf" (v.val));

modules/core/include/opencv2/core/llapi/llapi.h

@@ -29,7 +29,7 @@ Using this approach OpenCV provides some basic low level functionality for exter
 
 typedef enum cvResult
 {
-    CV_ERROR_FAIL = -1,                          //!< Some error occured (TODO Require to fill exception information)
+    CV_ERROR_FAIL = -1,                          //!< Some error occurred (TODO Require to fill exception information)
     CV_ERROR_OK = 0                              //!< No error
 } CvResult;
 

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

@@ -151,7 +151,7 @@ number of components (vectors/matrices) of the outer vector.
 
 In general, type support is limited to cv::Mat types. Other types are forbidden.
 But in some cases we need to support passing of custom non-general Mat types, like arrays of cv::KeyPoint, cv::DMatch, etc.
-This data is not intented to be interpreted as an image data, or processed somehow like regular cv::Mat.
+This data is not intended to be interpreted as an image data, or processed somehow like regular cv::Mat.
 To pass such custom type use rawIn() / rawOut() / rawInOut() wrappers.
 Custom type is wrapped as Mat-compatible `CV_8UC<N>` values (N = sizeof(T), N <= CV_CN_MAX).
  */
@@ -2380,7 +2380,7 @@ public:
     // (_type is CV_8UC1, CV_64FC3, CV_32SC(12) etc.)
     UMat(int rows, int cols, int type, UMatUsageFlags usageFlags = USAGE_DEFAULT);
     UMat(Size size, int type, UMatUsageFlags usageFlags = USAGE_DEFAULT);
-    //! constucts 2D matrix and fills it with the specified value _s.
+    //! constructs 2D matrix and fills it with the specified value _s.
     UMat(int rows, int cols, int type, const Scalar& s, UMatUsageFlags usageFlags = USAGE_DEFAULT);
     UMat(Size size, int type, const Scalar& s, UMatUsageFlags usageFlags = USAGE_DEFAULT);
 
@@ -2825,7 +2825,7 @@ public:
 
      `ref<_Tp>(i0,...[,hashval])` is equivalent to `*(_Tp*)ptr(i0,...,true[,hashval])`.
      The methods always return a valid reference.
-     If the element did not exist, it is created and initialiazed with 0.
+     If the element did not exist, it is created and initialized with 0.
     */
     //! returns reference to the specified element (1D case)
     template<typename _Tp> _Tp& ref(int i0, size_t* hashval=0);

modules/core/include/opencv2/core/simd_intrinsics.hpp

@@ -27,7 +27,7 @@ These files can be pre-generated for target configurations of your application
 or generated by CMake on the fly (use CMAKE_BINARY_DIR for that).
 
 Notes:
-- H/W capability checks are still responsibility of your applcation
+- H/W capability checks are still responsibility of your application
 - runtime dispatching is not covered by this helper header
 */
 

modules/core/include/opencv2/core/utils/filesystem.private.hpp

@@ -49,8 +49,8 @@ public:
     void lock(); //< acquire exclusive (writer) lock
     void unlock(); //< release exclusive (writer) lock
 
-    void lock_shared(); //< acquire sharable (reader) lock
-    void unlock_shared(); //< release sharable (reader) lock
+    void lock_shared(); //< acquire shareable (reader) lock
+    void unlock_shared(); //< release shareable (reader) lock
 
     struct Impl;
 protected:

modules/core/misc/python/shadow_umat.hpp

@@ -13,7 +13,7 @@ public:
     // (_type is CV_8UC1, CV_64FC3, CV_32SC(12) etc.)
     CV_WRAP UMat(int rows, int cols, int type, UMatUsageFlags usageFlags = USAGE_DEFAULT);
     CV_WRAP UMat(Size size, int type, UMatUsageFlags usageFlags = USAGE_DEFAULT);
-    //! constucts 2D matrix and fills it with the specified value _s.
+    //! constructs 2D matrix and fills it with the specified value _s.
     CV_WRAP UMat(int rows, int cols, int type, const Scalar& s, UMatUsageFlags usageFlags = USAGE_DEFAULT);
     CV_WRAP UMat(Size size, int type, const Scalar& s, UMatUsageFlags usageFlags = USAGE_DEFAULT);
 

modules/core/src/datastructs.cpp

@@ -1766,7 +1766,7 @@ cvSeqInsertSlice( CvSeq* seq, int index, const CvArr* from_arr )
             CV_Error( CV_StsBadArg, "Source is not a sequence nor matrix" );
 
         if( !CV_IS_MAT_CONT(mat->type) || (mat->rows != 1 && mat->cols != 1) )
-            CV_Error( CV_StsBadArg, "The source array must be 1d coninuous vector" );
+            CV_Error( CV_StsBadArg, "The source array must be 1d continuous vector" );
 
         from = cvMakeSeqHeaderForArray( CV_SEQ_KIND_GENERIC, sizeof(from_header),
                                                  CV_ELEM_SIZE(mat->type),

modules/core/src/hal_internal.cpp

@@ -63,7 +63,7 @@
 #define HAL_LU_SMALL_MATRIX_THRESH 100
 #define HAL_CHOLESKY_SMALL_MATRIX_THRESH 100
 
-//lapack stores matrices in column-major order so transposing is neded everywhere
+//lapack stores matrices in column-major order so transposing is needed everywhere
 template <typename fptype> static inline void
 transpose_square_inplace(fptype *src, size_t src_ld, size_t m)
 {

modules/core/src/ocl.cpp

@@ -5756,7 +5756,7 @@ public:
 
 static OpenCLAllocator* getOpenCLAllocator_() // call once guarantee
 {
-    static OpenCLAllocator* g_allocator = new OpenCLAllocator(); // avoid destrutor call (using of this object is too wide)
+    static OpenCLAllocator* g_allocator = new OpenCLAllocator(); // avoid destructor call (using of this object is too wide)
     g_isOpenCVActivated = true;
     return g_allocator;
 }

modules/core/test/test_eigen.cpp

@@ -73,7 +73,7 @@ public:
 protected:
 
     bool test_values(const cv::Mat& src);												// complex test for eigen without vectors
-    bool check_full(int type);													// compex test for symmetric matrix
+    bool check_full(int type);													// complex test for symmetric matrix
     virtual void run (int) = 0;													// main testing method
 
 protected:

modules/dnn/include/opencv2/dnn/all_layers.hpp

@@ -104,7 +104,7 @@ CV__DNN_INLINE_NS_BEGIN
         h_t &= o_t \odot tanh(c_t),               \\
         c_t &= f_t \odot c_{t-1} + i_t \odot g_t, \\
         @f}
-        where @f$\odot@f$ is per-element multiply operation and @f$i_t, f_t, o_t, g_t@f$ is internal gates that are computed using learned wights.
+        where @f$\odot@f$ is per-element multiply operation and @f$i_t, f_t, o_t, g_t@f$ is internal gates that are computed using learned weights.
 
         Gates are computed as follows:
         @f{eqnarray*}{

modules/dnn/include/opencv2/dnn/dnn.hpp

@@ -424,7 +424,7 @@ CV__DNN_INLINE_NS_BEGIN
          *  @param inpPin descriptor of the second layer input.
          *
          * Descriptors have the following template <DFN>&lt;layer_name&gt;[.input_number]</DFN>:
-         * - the first part of the template <DFN>layer_name</DFN> is sting name of the added layer.
+         * - the first part of the template <DFN>layer_name</DFN> is string name of the added layer.
          *   If this part is empty then the network input pseudo layer will be used;
          * - the second optional part of the template <DFN>input_number</DFN>
          *   is either number of the layer input, either label one.

modules/dnn/src/ocl4dnn/src/ocl4dnn_conv_spatial.cpp

@@ -618,7 +618,7 @@ void OCL4DNNConvSpatial<Dtype>::calculateBenchmark(const UMat &bottom, UMat &ver
 // For large enough input size, we do not need to tune kernels for different
 // size. The reason is with large input size, there will be enough work items
 // to feed al the EUs.
-// FIXME for the gemm like convolution, switch back to eaxct image size.
+// FIXME for the gemm like convolution, switch back to exact image size.
 
 #define TUNING_SIZE(x) ((x) > 256 ? 256 : (alignSize(x, 16)))
 

modules/dnn/src/onnx/opencv-onnx.proto

@@ -161,7 +161,7 @@ message NodeProto {
   repeated string output = 2;   // namespace Value
 
   // An optional identifier for this node in a graph.
-  // This field MAY be absent in ths version of the IR.
+  // This field MAY be absent in this version of the IR.
   optional string name = 3;     // namespace Node
 
   // The symbolic identifier of the Operator to execute.

modules/dnn/src/op_inf_engine.cpp

@@ -610,7 +610,7 @@ void InfEngineBackendNet::forward(const std::vector<Ptr<BackendWrapper> >& outBl
                             try {
                                 wrapper->outProms[processedOutputs].setException(std::current_exception());
                             } catch(...) {
-                                CV_LOG_ERROR(NULL, "DNN: Exception occured during async inference exception propagation");
+                                CV_LOG_ERROR(NULL, "DNN: Exception occurred during async inference exception propagation");
                             }
                         }
                     }
@@ -623,7 +623,7 @@ void InfEngineBackendNet::forward(const std::vector<Ptr<BackendWrapper> >& outBl
                         try {
                             wrapper->outProms[processedOutputs].setException(e);
                         } catch(...) {
-                            CV_LOG_ERROR(NULL, "DNN: Exception occured during async inference exception propagation");
+                            CV_LOG_ERROR(NULL, "DNN: Exception occurred during async inference exception propagation");
                         }
                     }
                 }

modules/dnn/src/op_inf_engine.hpp

@@ -40,7 +40,7 @@
 #endif
 
 //#define INFERENCE_ENGINE_DEPRECATED  // turn off deprecation warnings from IE
-//there is no way to suppress warnigns from IE only at this moment, so we are forced to suppress warnings globally
+//there is no way to suppress warnings from IE only at this moment, so we are forced to suppress warnings globally
 #if defined(__GNUC__)
 #pragma GCC diagnostic ignored "-Wdeprecated-declarations"
 #endif

modules/dnn/src/tensorflow/tf_importer.cpp

@@ -837,7 +837,7 @@ void TFImporter::populateNet(Net dstNet)
                 CV_Assert(paddings.type() == CV_32SC1);
                 if (paddings.total() == 8)
                 {
-                    // Perhabs, we have NHWC padding dimensions order.
+                    // Perhaps, we have NHWC padding dimensions order.
                     //  N    H    W    C
                     // 0 1  2 3  4 5  6 7
                     std::swap(paddings.at<int32_t>(2), paddings.at<int32_t>(6));

modules/dnn/src/torch/torch_importer.cpp

@@ -312,7 +312,7 @@ struct TorchImporter
             fpos = THFile_position(file);
             int ktype = readInt();
 
-            if (ktype != TYPE_STRING) //skip non-string fileds
+            if (ktype != TYPE_STRING) //skip non-string fields
             {
                 THFile_seek(file, fpos);
                 readObject(); //key

modules/dnn/src/vkcom/shader/softmax.comp

@@ -46,7 +46,7 @@ void main()
         }
     }
 
-    // substract, exp and accumulate along channel
+    // subtract, exp and accumulate along channel
     for (int i = 0; i < p.channel_size; ++i)
         sum_buffer[reduced_buffer_off + i] = 0.f;
 

modules/dnn/test/test_ie_models.cpp

@@ -14,7 +14,7 @@
 // Synchronize headers include statements with src/op_inf_engine.hpp
 //
 //#define INFERENCE_ENGINE_DEPRECATED  // turn off deprecation warnings from IE
-//there is no way to suppress warnigns from IE only at this moment, so we are forced to suppress warnings globally
+//there is no way to suppress warnings from IE only at this moment, so we are forced to suppress warnings globally
 #if defined(__GNUC__)
 #pragma GCC diagnostic ignored "-Wdeprecated-declarations"
 #endif

modules/features2d/perf/perf_feature2d.hpp

@@ -6,7 +6,7 @@
 namespace opencv_test
 {
 
-/* cofiguration for tests of detectors/descriptors. shared between ocl and cpu tests. */
+/* configuration for tests of detectors/descriptors. shared between ocl and cpu tests. */
 
 // detectors/descriptors configurations to test
 #define DETECTORS_ONLY                                                                  \

modules/flann/include/opencv2/flann/hierarchical_clustering_index.h

@@ -578,7 +578,7 @@ public:
 private:
 
     /**
-     * Struture representing a node in the hierarchical k-means tree.
+     * Structure representing a node in the hierarchical k-means tree.
      */
     struct Node
     {

modules/flann/include/opencv2/flann/kmeans_index.h

@@ -547,7 +547,7 @@ public:
 
 private:
     /**
-     * Struture representing a node in the hierarchical k-means tree.
+     * Structure representing a node in the hierarchical k-means tree.
      */
     struct KMeansNode
     {

modules/flann/include/opencv2/flann/result_set.h

@@ -301,7 +301,7 @@ public:
         unsigned int index_;
     };
 
-    /** Default cosntructor */
+    /** Default constructor */
     UniqueResultSet() :
         is_full_(false), worst_distance_(std::numeric_limits<DistanceType>::max())
     {

modules/gapi/doc/01-background.markdown

@@ -46,12 +46,12 @@ majority of the work by itself, keeping the algorithm code clean from
 device or optimization details. This approach has its own limitations,
 though, as graph model is a _constrained_ model and not every
 algorithm can be represented as a graph, so the G-API scope is limited
-only to regular image processing -- various filters, arithmentic,
+only to regular image processing -- various filters, arithmetic,
 binary operations, and well-defined geometrical transformations.
 
 ## Porting with Graph API {#gapi_intro_port}
 
-The essense of G-API is declaring a sequence of operations to run, and
+The essence of G-API is declaring a sequence of operations to run, and
 then executing that sequence. G-API is a constrained API, so it puts a
 number of limitations on which operations can form a pipeline and
 which data these operations may exchange each other.
@@ -67,7 +67,7 @@ interfaces, not implementations -- thus the same graph can be executed
 on different devices (and, of course, using different optimization
 techniques) with little-to-no changes in the graph itself.
 
-G-API supports plugins (_Backends_) which aggreate logic and
+G-API supports plugins (_Backends_) which aggregate logic and
 intelligence on what is the best way to execute on a particular
 platform. Once a pipeline is built with G-API, it can be parametrized
 to use either of the backends (or a combination of it) and so a graph

modules/gapi/include/opencv2/gapi/core.hpp

@@ -701,7 +701,7 @@ GAPI_EXPORTS GMat divRC(const GScalar& divident, const GMat& src, double scale,
 /** @brief Applies a mask to a matrix.
 
 The function mask set value from given matrix if the corresponding pixel value in mask matrix set to true,
-and set the matrix value to 0 overwise.
+and set the matrix value to 0 otherwise.
 
 Supported src matrix data types are @ref CV_8UC1, @ref CV_16SC1, @ref CV_16UC1. Supported mask data type is @ref CV_8UC1.
 
@@ -1293,7 +1293,7 @@ depths.
  */
 GAPI_EXPORTS GMat threshold(const GMat& src, const GScalar& thresh, const GScalar& maxval, int depth);
 /** @overload
-This function appicable for all threshold depths except CV_THRESH_OTSU and CV_THRESH_TRIANGLE
+This function applicable for all threshold depths except CV_THRESH_OTSU and CV_THRESH_TRIANGLE
 @note Function textual ID is "org.opencv.core.matrixop.thresholdOT"
 */
 GAPI_EXPORTS std::tuple<GMat, GScalar> threshold(const GMat& src, const GScalar& maxval, int depth);

modules/gapi/include/opencv2/gapi/cpu/gcpukernel.hpp

@@ -92,7 +92,7 @@ protected:
 
     std::vector<GArg> m_args;
 
-    //FIXME: avoid conversion of arguments from internal representaion to OpenCV one on each call
+    //FIXME: avoid conversion of arguments from internal representation to OpenCV one on each call
     //to OCV kernel. (This can be achieved by a two single time conversions in GCPUExecutable::run,
     //once on enter for input and output arguments, and once before return for output arguments only
     std::unordered_map<std::size_t, GRunArgP> m_results;
@@ -229,7 +229,7 @@ struct OCVCallHelper<Impl, std::tuple<Ins...>, std::tuple<Outs...> >
         static void call(Inputs&&... ins, Outputs&&... outs)
         {
             //not using a std::forward on outs is deliberate in order to
-            //cause compilation error, by tring to bind rvalue references to lvalue references
+            //cause compilation error, by trying to bind rvalue references to lvalue references
             Impl::run(std::forward<Inputs>(ins)..., outs...);
 
             postprocess(outs...);

modules/gapi/include/opencv2/gapi/garray.hpp

@@ -81,7 +81,7 @@ namespace detail
 
     protected:
         GArrayU();                                // Default constructor
-        template<class> friend class cv::GArray;  //  (avialable to GArray<T> only)
+        template<class> friend class cv::GArray;  //  (available to GArray<T> only)
 
         void setConstructFcn(ConstructVec &&cv);  // Store T-aware constructor
 

modules/gapi/include/opencv2/gapi/gcompiled_async.hpp

@@ -23,7 +23,7 @@ namespace wip {
     class GAsyncContext;
     //These functions asynchronously (i.e. probably on a separate thread of execution) call operator() member function of their first argument with copies of rest of arguments (except callback) passed in.
     //The difference between the function is the way to get the completion notification (via callback or a waiting on std::future object)
-    //If exception is occurred during execution of apply it is transfered to the callback (via function parameter) or passed to future (and will be thrown on call to std::future::get)
+    //If exception is occurred during execution of apply it is transferred to the callback (via function parameter) or passed to future (and will be thrown on call to std::future::get)
 
     //N.B. :
     //Input arguments are copied on call to async function (actually on call to cv::gin) and thus do not have to outlive the actual completion of asynchronous activity.

modules/gapi/include/opencv2/gapi/gcomputation.hpp

@@ -83,7 +83,7 @@ namespace detail
  * In the above example, sobelEdge expects one Mat on input and
  * produces one Mat; while sobelEdgeSub expects two Mats on input and
  * produces one Mat. GComputation's protocol defines how other
- * computaion methods should be used -- cv::GComputation::compile() and
+ * computation methods should be used -- cv::GComputation::compile() and
  * cv::GComputation::apply(). For example, if a graph is defined on
  * two GMat inputs, two cv::Mat objects have to be passed to apply()
  * for execution. GComputation checks protocol correctness in runtime

modules/gapi/include/opencv2/gapi/gcomputation_async.hpp

@@ -24,7 +24,7 @@ namespace wip  {
     class GAsyncContext;
     //These functions asynchronously (i.e. probably on a separate thread of execution) call apply member function of their first argument with copies of rest of arguments (except callback) passed in.
     //The difference between the function is the way to get the completion notification (via callback or a waiting on std::future object)
-    //If exception is occurred during execution of apply it is transfered to the callback (via function parameter) or passed to future (and will be thrown on call to std::future::get)
+    //If exception is occurred during execution of apply it is transferred to the callback (via function parameter) or passed to future (and will be thrown on call to std::future::get)
 
     //N.B. :
     //Input arguments are copied on call to async function (actually on call to cv::gin) and thus do not have to outlive the actual completion of asynchronous activity.

modules/gapi/include/opencv2/gapi/gkernel.hpp

@@ -323,7 +323,7 @@ namespace gapi {
      * implementations in form of type list (variadic template) and
      * generates a kernel package atop of that.
      *
-     * Kernel packages can be also generated programatically, starting
+     * Kernel packages can be also generated programmatically, starting
      * with an empty package (created with the default constructor)
      * and then by populating it with kernels via call to
      * GKernelPackage::include(). Note this method is also a template

modules/gapi/include/opencv2/gapi/infer.hpp

@@ -164,7 +164,7 @@ typename Net::ResultL infer(cv::GArray<cv::Rect> roi, Args&&... args) {
  * @param args network's input parameters as specified in G_API_NET() macro.
  * @return an object of return type as defined in G_API_NET().
  *   If a network has multiple return values (defined with a tuple), a tuple of
- *   objects of apprpriate type is returned.
+ *   objects of appropriate type is returned.
  * @sa  G_API_NET()
  */
 template<typename Net, typename... Args>

modules/gapi/include/opencv2/gapi/ocl/goclkernel.hpp

@@ -198,7 +198,7 @@ struct OCLCallHelper<Impl, std::tuple<Ins...>, std::tuple<Outs...> >
         static void call(Inputs&&... ins, Outputs&&... outs)
         {
             //not using a std::forward on outs is deliberate in order to
-            //cause compilation error, by tring to bind rvalue references to lvalue references
+            //cause compilation error, by trying to bind rvalue references to lvalue references
             Impl::run(std::forward<Inputs>(ins)..., outs...);
 
             postprocess_ocl(outs...);

modules/gapi/include/opencv2/gapi/own/saturate.hpp

@@ -66,7 +66,7 @@ static inline DST saturate(SRC x, R round)
         GAPI_DbgAssert(std::is_integral<DST>::value &&
                  std::is_floating_point<SRC>::value);
 #ifdef _WIN32
-// Suppress warning about convering x to floating-point
+// Suppress warning about converting x to floating-point
 // Note that x is already floating-point at this point
 #pragma warning(disable: 4244)
 #endif

modules/gapi/src/api/gbackend.cpp

@@ -239,7 +239,7 @@ void resetInternalData(Mag& mag, const Data &d)
         break;
 
     case GShape::GMAT:
-        // Do nothign here - FIXME unify with initInternalData?
+        // Do nothing here - FIXME unify with initInternalData?
         break;
 
     default:
@@ -281,7 +281,7 @@ cv::GRunArgP getObjPtr(Mag& mag, const RcDesc &rc, bool is_umat)
             return GRunArgP(&mag.template slot<cv::gapi::own::Mat>()[rc.id]);
     case GShape::GSCALAR: return GRunArgP(&mag.template slot<cv::gapi::own::Scalar>()[rc.id]);
     // Note: .at() is intentional for GArray as object MUST be already there
-    //   (and constructer by either bindIn/Out or resetInternal)
+    //   (and constructor by either bindIn/Out or resetInternal)
     case GShape::GARRAY:
         // FIXME(DM): For some absolutely unknown to me reason, move
         // semantics is involved here without const_cast to const (and

modules/gapi/src/backends/cpu/gcpucore.cpp

@@ -413,7 +413,7 @@ GAPI_OCV_KERNEL(GCPUSplit3, cv::gapi::core::GSplit3)
         std::vector<cv::Mat> outMats = {m1, m2, m3};
         cv::split(in, outMats);
 
-        // Write back FIXME: Write a helper or avoid this nonsence completely!
+        // Write back FIXME: Write a helper or avoid this nonsense completely!
         m1 = outMats[0];
         m2 = outMats[1];
         m3 = outMats[2];
@@ -427,7 +427,7 @@ GAPI_OCV_KERNEL(GCPUSplit4, cv::gapi::core::GSplit4)
         std::vector<cv::Mat> outMats = {m1, m2, m3, m4};
         cv::split(in, outMats);
 
-        // Write back FIXME: Write a helper or avoid this nonsence completely!
+        // Write back FIXME: Write a helper or avoid this nonsense completely!
         m1 = outMats[0];
         m2 = outMats[1];
         m3 = outMats[2];

modules/gapi/src/backends/ie/giebackend.cpp

@@ -204,7 +204,7 @@ struct IECallContext
     // Input parameters passed to an inference operation.
     std::vector<cv::GArg> args;
 
-    //FIXME: avoid conversion of arguments from internal representaion to OpenCV one on each call
+    //FIXME: avoid conversion of arguments from internal representation to OpenCV one on each call
     //to OCV kernel. (This can be achieved by a two single time conversions in GCPUExecutable::run,
     //once on enter for input and output arguments, and once before return for output arguments only
     //FIXME: check if the above applies to this backend (taken from CPU)

modules/gapi/src/backends/ocl/goclcore.cpp

@@ -410,7 +410,7 @@ GAPI_OCL_KERNEL(GOCLSplit3, cv::gapi::core::GSplit3)
         std::vector<cv::UMat> outMats = {m1, m2, m3};
         cv::split(in, outMats);
 
-        // Write back FIXME: Write a helper or avoid this nonsence completely!
+        // Write back FIXME: Write a helper or avoid this nonsense completely!
         m1 = outMats[0];
         m2 = outMats[1];
         m3 = outMats[2];
@@ -424,7 +424,7 @@ GAPI_OCL_KERNEL(GOCLSplit4, cv::gapi::core::GSplit4)
         std::vector<cv::UMat> outMats = {m1, m2, m3, m4};
         cv::split(in, outMats);
 
-        // Write back FIXME: Write a helper or avoid this nonsence completely!
+        // Write back FIXME: Write a helper or avoid this nonsense completely!
         m1 = outMats[0];
         m2 = outMats[1];
         m3 = outMats[2];

modules/gapi/src/compiler/gcompiler.cpp

@@ -297,7 +297,7 @@ void cv::gimpl::GCompiler::compileIslands(ade::Graph &g)
 cv::GCompiled cv::gimpl::GCompiler::produceCompiled(GPtr &&pg)
 {
     // This is the final compilation step. Here:
-    // - An instance of GExecutor is created. Depening on the platform,
+    // - An instance of GExecutor is created. Depending on the platform,
     //   build configuration, etc, a GExecutor may be:
     //   - a naive single-thread graph interpreter;
     //   - a std::thread-based thing

modules/gapi/src/compiler/gmodelbuilder.cpp

@@ -80,7 +80,7 @@ cv::gimpl::Unrolled cv::gimpl::unrollExpr(const GProtoArgs &ins,
     std::unordered_set<GObjId> in_objs_p;
     for (const auto& in_obj : ins)
     {
-        // Objects are guarnateed to remain alive while this method
+        // Objects are guaranteed to remain alive while this method
         // is working, so it is safe to keep pointers here and below
         in_objs_p.insert(&proto::origin_of(in_obj));
     }

modules/gapi/src/compiler/passes/exec.cpp

@@ -454,7 +454,7 @@ namespace
             m_changes.enqueue<Change::DropLink>(m_g, m_cons, out_edge);
         }
 
-        // D: Process the intermediate slots (betweed Prod n Cons).
+        // D: Process the intermediate slots (between Prod n Cons).
         // D/1 - Those which are optimized out are just removed from the model
         for (auto opt_slot_nh : mo.opt_interim_slots)
         {

modules/gapi/src/compiler/passes/kernels.cpp

@@ -32,7 +32,7 @@ namespace
         cv::GArgs       in_args;
     };
 
-    // Generaly the algorithm is following
+    // Generally the algorithm is following
     //
     // 1. Get GCompoundKernel implementation
     // 2. Create GCompoundContext

modules/gapi/src/compiler/passes/meta.cpp

@@ -113,7 +113,7 @@ void cv::gimpl::passes::inferMeta(ade::passes::PassContext &ctx, bool meta_is_in
     } // for(sorted)
 }
 
-// After all metadata in graph is infered, store a vector of inferred metas
+// After all metadata in graph is inferred, store a vector of inferred metas
 // for computation output values.
 void cv::gimpl::passes::storeResultingMeta(ade::passes::PassContext &ctx)
 {

modules/highgui/src/window_gtk.cpp

@@ -1806,7 +1806,7 @@ static gboolean icvOnMouse( GtkWidget *widget, GdkEvent *event, gpointer user_da
     else if( event->type == GDK_SCROLL )
     {
 #if defined(GTK_VERSION3_4)
-        // NOTE: in current implementation doesn't possible to put into callback function delta_x and delta_y separetely
+        // NOTE: in current implementation doesn't possible to put into callback function delta_x and delta_y separately
         double delta = (event->scroll.delta_x + event->scroll.delta_y);
         cv_event   = (event->scroll.delta_y!=0) ? CV_EVENT_MOUSEHWHEEL : CV_EVENT_MOUSEWHEEL;
 #else

modules/highgui/src/window_w32.cpp

@@ -1231,7 +1231,7 @@ cvShowImage( const char* name, const CvArr* arr )
         cv::flip(dst, dst, 0);
     }
 
-    // ony resize window if needed
+    // only resize window if needed
     if (changed_size)
         icvUpdateWindowPos(window);
     InvalidateRect(window->hwnd, 0, 0);

modules/imgcodecs/include/opencv2/imgcodecs/imgcodecs_c.h

@@ -1 +1 @@
-#error "This header with legacy C API declarations has been removed from OpenCV. Legacy contants are available from legacy/constants_c.h file."
+#error "This header with legacy C API declarations has been removed from OpenCV. Legacy constants are available from legacy/constants_c.h file."

modules/imgcodecs/src/grfmt_jpeg.cpp

@@ -52,7 +52,7 @@
 #include <stdio.h>
 #include <setjmp.h>
 
-// the following defines are a hack to avoid multiple problems with frame ponter handling and setjmp
+// the following defines are a hack to avoid multiple problems with frame pointer handling and setjmp
 // see http://gcc.gnu.org/ml/gcc/2011-10/msg00324.html for some details
 #define mingw_getsp(...) 0
 #define __builtin_frame_address(...) 0

modules/imgcodecs/src/grfmt_pam.cpp

@@ -62,7 +62,7 @@ namespace cv {
 #define MAX_PAM_HEADER_IDENITFIER_LENGTH 8
 #define MAX_PAM_HEADER_VALUE_LENGTH 255
 
-/* PAM header fileds */
+/* PAM header fields */
 typedef enum {
     PAM_HEADER_NONE,
     PAM_HEADER_COMMENT,

modules/imgcodecs/src/grfmt_pfm.cpp

@@ -47,7 +47,7 @@ template<> double atoT<double>(const std::string& s) { return std::atof(s.c_str(
 template<typename T>
 T read_number(cv::RLByteStream& strm)
 {
-  // should be enogh to take string representation of any number
+  // should be enough to take string representation of any number
   const size_t buffer_size = 2048;
 
   std::vector<char> buffer(buffer_size, 0);

modules/imgcodecs/src/grfmt_png.cpp

@@ -72,7 +72,7 @@
     #pragma warning( disable: 4611 )
 #endif
 
-// the following defines are a hack to avoid multiple problems with frame ponter handling and setjmp
+// the following defines are a hack to avoid multiple problems with frame pointer handling and setjmp
 // see http://gcc.gnu.org/ml/gcc/2011-10/msg00324.html for some details
 #define mingw_getsp(...) 0
 #define __builtin_frame_address(...) 0

modules/imgproc/perf/perf_houghlines.cpp

@@ -28,7 +28,7 @@ PERF_TEST_P(Image_RhoStep_ThetaStep_Threshold, HoughLines,
 
     Canny(image, image, 32, 128);
 
-    // add some syntetic lines:
+    // add some synthetic lines:
     line(image, Point(0, 0), Point(image.cols, image.rows), Scalar::all(255), 3);
     line(image, Point(image.cols, 0), Point(image.cols/2, image.rows), Scalar::all(255), 3);
 
@@ -89,7 +89,7 @@ PERF_TEST_P(Image_RhoStep_ThetaStep_Threshold, HoughLines3f,
 
     Canny(image, image, 32, 128);
 
-    // add some syntetic lines:
+    // add some synthetic lines:
     line(image, Point(0, 0), Point(image.cols, image.rows), Scalar::all(255), 3);
     line(image, Point(image.cols, 0), Point(image.cols/2, image.rows), Scalar::all(255), 3);
 

modules/imgproc/src/hough.cpp

@@ -603,7 +603,7 @@ HoughLinesProbabilistic( Mat& image,
             if( k > 0 )
                 dx = -dx, dy = -dy;
 
-            // walk along the line using fixed-point arithmetics,
+            // walk along the line using fixed-point arithmetic,
             // stop at the image border or in case of too big gap
             for( ;; x += dx, y += dy )
             {
@@ -651,7 +651,7 @@ HoughLinesProbabilistic( Mat& image,
             if( k > 0 )
                 dx = -dx, dy = -dy;
 
-            // walk along the line using fixed-point arithmetics,
+            // walk along the line using fixed-point arithmetic,
             // stop at the image border or in case of too big gap
             for( ;; x += dx, y += dy )
             {
@@ -968,7 +968,7 @@ void HoughLinesPointSet( InputArray _point, OutputArray _lines, int lines_max, i
     createTrigTable( numangle, min_theta, theta_step,
                      irho, tabSin, tabCos );
 
-    // stage 1. fill accumlator
+    // stage 1. fill accumulator
     for( i = 0; i < (int)point.size(); i++ )
         for(int n = 0; n < numangle; n++ )
         {

modules/imgproc/src/morph.dispatch.cpp

@@ -269,7 +269,7 @@ static bool ippMorph(int op, int src_type, int dst_type,
         return false;
 
     // Multiple iterations on small mask is not effective in current integration
-    // Implace imitation for 3x3 kernel is not efficient
+    // Inplace imitation for 3x3 kernel is not efficient
     // Advanced morphology for small mask introduces degradations
     if((iterations > 1 || src_data == dst_data || (op != MORPH_ERODE && op != MORPH_DILATE)) && kernel_width*kernel_height < 25)
         return false;

modules/imgproc/src/rotcalipers.cpp

@@ -104,7 +104,7 @@ static void rotatingCalipers( const Point2f* points, int n, int mode, float* out
     /* rotating calipers sides will always have coordinates
      (a,b) (-b,a) (-a,-b) (b, -a)
      */
-    /* this is a first base bector (a,b) initialized by (1,0) */
+    /* this is a first base vector (a,b) initialized by (1,0) */
     float orientation = 0;
     float base_a;
     float base_b = 0;

modules/imgproc/test/ocl/test_canny.cpp

@@ -77,7 +77,7 @@ PARAM_TEST_CASE(Canny, Channels, ApertureSize, L2gradient, UseRoi)
     void generateTestData()
     {
         Mat img = readImageType("shared/fruits.png", CV_8UC(cn));
-        ASSERT_FALSE(img.empty()) << "cann't load shared/fruits.png";
+        ASSERT_FALSE(img.empty()) << "can't load shared/fruits.png";
 
         Size roiSize = img.size();
         int type = img.type();

modules/imgproc/test/test_canny.cpp

@@ -357,7 +357,7 @@ PARAM_TEST_CASE(CannyVX, ImagePath, ApertureSize, L2gradient)
     void loadImage()
     {
         src = cv::imread(cvtest::TS::ptr()->get_data_path() + imgPath, IMREAD_GRAYSCALE);
-        ASSERT_FALSE(src.empty()) << "cann't load image: " << imgPath;
+        ASSERT_FALSE(src.empty()) << "can't load image: " << imgPath;
     }
 };
 

modules/java/generator/android/java/org/opencv/android/AsyncServiceHelper.java

@@ -268,7 +268,7 @@ class AsyncServiceHelper
                                         }
                                         else
                                         {
-                                            Log.d(TAG, "Wating for package installation");
+                                            Log.d(TAG, "Waiting for package installation");
                                         }
 
                                         Log.d(TAG, "Unbind from service");

modules/java/test/android_test/src/org/opencv/test/OpenCVTestCase.java

@@ -501,10 +501,10 @@ public class OpenCVTestCase extends TestCase {
         double maxDiff = Core.norm(diff, Core.NORM_INF);
 
         if (isEqualityMeasured)
-            assertTrue("Max difference between expected and actiual Mats is "+ maxDiff + ", that bigger than " + eps,
+            assertTrue("Max difference between expected and actual Mats is "+ maxDiff + ", that bigger than " + eps,
                     maxDiff <= eps);
         else
-            assertFalse("Max difference between expected and actiual Mats is "+ maxDiff + ", that less than " + eps,
+            assertFalse("Max difference between expected and actual Mats is "+ maxDiff + ", that less than " + eps,
                     maxDiff <= eps);
     }
 

modules/java/test/pure_test/src/org/opencv/test/OpenCVTestCase.java

@@ -527,10 +527,10 @@ public class OpenCVTestCase extends TestCase {
         double maxDiff = Core.norm(diff, Core.NORM_INF);
 
         if (isEqualityMeasured)
-            assertTrue("Max difference between expected and actiual Mats is "+ maxDiff + ", that bigger than " + eps,
+            assertTrue("Max difference between expected and actual Mats is "+ maxDiff + ", that bigger than " + eps,
                     maxDiff <= eps);
         else
-            assertFalse("Max difference between expected and actiual Mats is "+ maxDiff + ", that less than " + eps,
+            assertFalse("Max difference between expected and actual Mats is "+ maxDiff + ", that less than " + eps,
                     maxDiff <= eps);
     }
 

modules/js/test/test_calib3d.js

@@ -3,7 +3,7 @@
 // of this distribution and at http://opencv.org/license.html.
 
 if (typeof module !== 'undefined' && module.exports) {
-  // The envrionment is Node.js
+  // The environment is Node.js
   var cv = require('./opencv.js'); // eslint-disable-line no-var
 }
 

modules/js/test/test_features2d.js

@@ -3,7 +3,7 @@
 // of this distribution and at http://opencv.org/license.html.
 
 if (typeof module !== 'undefined' && module.exports) {
-    // The envrionment is Node.js
+    // The environment is Node.js
     var cv = require('./opencv.js'); // eslint-disable-line no-var
 }
 

modules/js/test/test_imgproc.js

@@ -69,7 +69,7 @@
 //
 
 if (typeof module !== 'undefined' && module.exports) {
-    // The envrionment is Node.js
+    // The environment is Node.js
     var cv = require('./opencv.js'); // eslint-disable-line no-var
 }
 
@@ -92,7 +92,7 @@ QUnit.test('test_imgProc', function(assert) {
         binView[0] = 10;
         cv.calcHist(source, channels, mask, hist, histSize, ranges, false);
 
-        // hist should contains a N X 1 arrary.
+        // hist should contains a N X 1 array.
         let size = hist.size();
         assert.equal(size.height, 256);
         assert.equal(size.width, 1);

modules/js/test/test_mat.js

@@ -69,7 +69,7 @@
 //
 
 if (typeof module !== 'undefined' && module.exports) {
-    // The envrionment is Node.js
+    // The environment is Node.js
     var cv = require('./opencv.js'); // eslint-disable-line no-var
 }
 

modules/js/test/test_objdetect.js

@@ -69,7 +69,7 @@
 //
 
 if (typeof module !== 'undefined' && module.exports) {
-    // The envrionment is Node.js
+    // The environment is Node.js
     var cv = require('./opencv.js'); // eslint-disable-line no-var
     cv.FS_createLazyFile('/', 'haarcascade_frontalface_default.xml', // eslint-disable-line new-cap
                          'haarcascade_frontalface_default.xml', true, false);

modules/js/test/test_photo.js

@@ -41,7 +41,7 @@
 // Author : Rijubrata Bhaumik, Intel Corporation. rijubrata.bhaumik[at]intel[dot]com
 
 if (typeof module !== 'undefined' && module.exports) {
-    // The envrionment is Node.js
+    // The environment is Node.js
     var cv = require('./opencv.js'); // eslint-disable-line no-var
 }
 

modules/js/test/test_utils.js

@@ -68,7 +68,7 @@
 //
 
 if (typeof module !== 'undefined' && module.exports) {
-    // The envrionment is Node.js
+    // The environment is Node.js
     var cv = require('./opencv.js'); // eslint-disable-line no-var
 }
 QUnit.module('Utils', {});

modules/js/test/test_video.js

@@ -68,7 +68,7 @@
 //
 
 if (typeof module !== 'undefined' && module.exports) {
-    // The envrionment is Node.js
+    // The environment is Node.js
     var cv = require('./opencv.js'); // eslint-disable-line no-var
 }
 

modules/ml/doc/ml_intro.markdown

@@ -433,7 +433,7 @@ Logistic Regression {#ml_intro_lr}
 ML implements logistic regression, which is a probabilistic classification technique. Logistic
 Regression is a binary classification algorithm which is closely related to Support Vector Machines
 (SVM). Like SVM, Logistic Regression can be extended to work on multi-class classification problems
-like digit recognition (i.e. recognizing digitis like 0,1 2, 3,... from the given images). This
+like digit recognition (i.e. recognizing digits like 0,1 2, 3,... from the given images). This
 version of Logistic Regression supports both binary and multi-class classifications (for multi-class
 it creates a multiple 2-class classifiers). In order to train the logistic regression classifier,
 Batch Gradient Descent and Mini-Batch Gradient Descent algorithms are used (see

modules/ml/include/opencv2/ml.hpp

@@ -1764,7 +1764,7 @@ Note that the parameters margin regularization, initial step size, and step decr
 
 To use SVMSGD algorithm do as follows:
 
-- first, create the SVMSGD object. The algoorithm will set optimal parameters by default, but you can set your own parameters via functions setSvmsgdType(),
+- first, create the SVMSGD object. The algorithm will set optimal parameters by default, but you can set your own parameters via functions setSvmsgdType(),
   setMarginType(), setMarginRegularization(), setInitialStepSize(), and setStepDecreasingPower().
 
 - then the SVM model can be trained using the train features and the correspondent labels by the method train().

modules/ml/test/test_emknearestkmeans.cpp

@@ -614,7 +614,7 @@ protected:
 
         if( data.empty() )
         {
-            ts->printf(cvtest::TS::LOG, "File with spambase dataset cann't be read.\n");
+            ts->printf(cvtest::TS::LOG, "File with spambase dataset can't be read.\n");
             ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA);
             return;
         }

modules/python/src2/gen2.py

@@ -721,7 +721,7 @@ class FuncInfo(object):
                     aname, argno = v.py_outlist[0]
                     code_ret = "return pyopencv_from(%s)" % (aname,)
             else:
-                # ther is more than 1 return parameter; form the tuple out of them
+                # there is more than 1 return parameter; form the tuple out of them
                 fmtspec = "N"*len(v.py_outlist)
                 backcvt_arg_list = []
                 for aname, argno in v.py_outlist:

modules/ts/misc/table_formatter.py

@@ -585,7 +585,7 @@ $(function(){
                $(tbl_row).remove()
          })
          if($("tbody tr", tbl).length == 0) {
-           $("<tr><td colspan='"+$("thead tr:first th", tbl).length+"'>No results mathing your search criteria</td></tr>")
+           $("<tr><td colspan='"+$("thead tr:first th", tbl).length+"'>No results matching your search criteria</td></tr>")
              .appendTo($("tbody", tbl))
          }
       }

modules/video/src/ecc.cpp

@@ -90,7 +90,7 @@ static void image_jacobian_homo_ECC(const Mat& src1, const Mat& src2,
 
 
     //instead of dividing each block with den,
-    //just pre-devide the block of gradients (it's more efficient)
+    //just pre-divide the block of gradients (it's more efficient)
 
     Mat src1Divided_;
     Mat src2Divided_;

modules/video/src/opencl/pyrlk.cl

@@ -48,7 +48,7 @@
 #define GRIDSIZE    3
 #define LSx 8
 #define LSy 8
-// defeine local memory sizes
+// define local memory sizes
 #define LM_W (LSx*GRIDSIZE+2)
 #define LM_H (LSy*GRIDSIZE+2)
 #define BUFFER  (LSx*LSy)

modules/videoio/include/opencv2/videoio/container_avi.private.hpp

@@ -58,7 +58,7 @@ RIFF ('AVI '
      {xxdb|xxdc|xxpc|xxwb}
      xx - stream number: 00, 01, 02, ...
      db - uncompressed video frame
-     dc - commpressed video frame
+     dc - compressed video frame
      pc - palette change
      wb - audio frame
 
@@ -139,7 +139,7 @@ class BitStream;
 // {xxdb|xxdc|xxpc|xxwb}
 // xx - stream number: 00, 01, 02, ...
 // db - uncompressed video frame
-// dc - commpressed video frame
+// dc - compressed video frame
 // pc - palette change
 // wb - audio frame
 

modules/videoio/src/cap_aravis.cpp

@@ -300,10 +300,10 @@ bool CvCaptureCAM_Aravis::grabFrame()
             size_t buffer_size;
             framebuffer = (void*)arv_buffer_get_data (arv_buffer, &buffer_size);
 
-            // retieve image size properites
+            // retrieve image size properites
             arv_buffer_get_image_region (arv_buffer, &xoffset, &yoffset, &width, &height);
 
-            // retieve image ID set by camera
+            // retrieve image ID set by camera
             frameID = arv_buffer_get_frame_id(arv_buffer);
 
             arv_stream_push_buffer(stream, arv_buffer);

modules/videoio/src/cap_avfoundation.mm

@@ -1196,7 +1196,7 @@ CvVideoWriter_AVFoundation::CvVideoWriter_AVFoundation(const char* filename, int
     NSError *error = nil;
 
 
-    // Make sure the file does not already exist. Necessary to overwirte??
+    // Make sure the file does not already exist. Necessary to overwrite??
     /*
     NSFileManager *fileManager = [NSFileManager defaultManager];
     if ([fileManager fileExistsAtPath:path]){
@@ -1238,7 +1238,7 @@ CvVideoWriter_AVFoundation::CvVideoWriter_AVFoundation(const char* filename, int
 
     if(mMovieWriter.status == AVAssetWriterStatusFailed){
         NSLog(@"%@", [mMovieWriter.error localizedDescription]);
-        // TODO: error handling, cleanup. Throw execption?
+        // TODO: error handling, cleanup. Throw exception?
         // return;
     }
 

modules/videoio/src/cap_avfoundation_mac.mm

@@ -1196,7 +1196,7 @@ CvVideoWriter_AVFoundation::CvVideoWriter_AVFoundation(const std::string &filena
         NSError *error = nil;
 
 
-        // Make sure the file does not already exist. Necessary to overwirte??
+        // Make sure the file does not already exist. Necessary to overwrite??
         /*
         NSFileManager *fileManager = [NSFileManager defaultManager];
         if ([fileManager fileExistsAtPath:path]){

modules/videoio/src/cap_dshow.cpp

@@ -481,7 +481,7 @@ class videoInput{
         bool setupDeviceFourcc(int deviceID, int w, int h,int fourcc);
 
         //These two are only for capture cards
-        //USB and Firewire cameras souldn't specify connection
+        //USB and Firewire cameras shouldn't specify connection
         bool setupDevice(int deviceID, int connection);
         bool setupDevice(int deviceID, int w, int h, int connection);
 

modules/videoio/src/cap_msmf.cpp

@@ -1199,7 +1199,7 @@ bool CvCapture_MSMF::grabFrame()
         {
             if (streamIndex != dwStreamIndex)
             {
-                CV_LOG_DEBUG(NULL, "videoio(MSMF): Wrong stream readed. Abort capturing");
+                CV_LOG_DEBUG(NULL, "videoio(MSMF): Wrong stream read. Abort capturing");
                 close();
             }
             else if (flags & MF_SOURCE_READERF_ERROR)

modules/videoio/src/container_avi.cpp

@@ -668,7 +668,7 @@ void BitStream::writeBlock()
 }
 
 size_t BitStream::getPos() const {
-    return safe_int_cast<size_t>(m_current - m_start, "Failed to determine AVI bufer position: value is out of range") + m_pos;
+    return safe_int_cast<size_t>(m_current - m_start, "Failed to determine AVI buffer position: value is out of range") + m_pos;
 }
 
 void BitStream::putByte(int val)

modules/videoio/src/wrl.h

@@ -49,8 +49,8 @@ private:
   unsigned char __k;
 };
 
-static_assert(sizeof(Guid) == sizeof(::_GUID), "Incorect size for Guid");
-static_assert(sizeof(__rcGUID_t) == sizeof(::_GUID), "Incorect size for __rcGUID_t");
+static_assert(sizeof(Guid) == sizeof(::_GUID), "Incorrect size for Guid");
+static_assert(sizeof(__rcGUID_t) == sizeof(::_GUID), "Incorrect size for __rcGUID_t");
 
 ////////////////////////////////////////////////////////////////////////////////
 inline Guid::Guid() : __a(0), __b(0), __c(0), __d(0), __e(0), __f(0), __g(0), __h(0), __i(0), __j(0), __k(0)

platforms/android/service/engine/src/org/opencv/engine/OpenCVEngineInterface.aidl

@@ -1,7 +1,7 @@
 package org.opencv.engine;
 
 /**
-* Class provides Java interface to OpenCV Engine Service. Is synchronious with native OpenCVEngine class.
+* Class provides Java interface to OpenCV Engine Service. Is synchronous with native OpenCVEngine class.
 */
 interface OpenCVEngineInterface
 {

platforms/ios/build_framework.py

@@ -31,7 +31,7 @@ from __future__ import print_function
 import glob, re, os, os.path, shutil, string, sys, argparse, traceback, multiprocessing
 from subprocess import check_call, check_output, CalledProcessError
 
-IPHONEOS_DEPLOYMENT_TARGET='8.0'  # default, can be changed via command line options or environemnt variable
+IPHONEOS_DEPLOYMENT_TARGET='8.0'  # default, can be changed via command line options or environment variable
 
 def execute(cmd, cwd = None):
     print("Executing: %s in %s" % (cmd, cwd), file=sys.stderr)