Merge pull request #13794 from alalek:backport_13786

apps/traincascade/old_ml.hpp

@@ -88,7 +88,7 @@ struct CvVectors
 #if 0
 /* A structure, representing the lattice range of statmodel parameters.
    It is used for optimizing statmodel parameters by cross-validation method.
-   The lattice is logarithmic, so <step> must be greater then 1. */
+   The lattice is logarithmic, so <step> must be greater than 1. */
 typedef struct CvParamLattice
 {
     double min_val;
@@ -158,7 +158,7 @@ protected:
 /* The structure, representing the grid range of statmodel parameters.
    It is used for optimizing statmodel accuracy by varying model parameters,
    the accuracy estimate being computed by cross-validation.
-   The grid is logarithmic, so <step> must be greater then 1. */
+   The grid is logarithmic, so <step> must be greater than 1. */
 
 class CvMLData;
 

doc/pattern_tools/gen_pattern.py

@@ -12,7 +12,7 @@ python gen_pattern.py -o out.svg -r 11 -c 8 -T circles -s 20.0 -R 5.0 -u mm -w 2
 -u, --units - mm, inches, px, m (default mm)
 -w, --page_width - page width in units (default 216)
 -h, --page_height - page height in units (default 279)
--a, --page_size - page size (default A4), supercedes -h -w arguments
+-a, --page_size - page size (default A4), supersedes -h -w arguments
 -H, --help - show help
 """
 

doc/py_tutorials/py_feature2d/py_brief/py_brief.markdown

@@ -12,7 +12,7 @@ Theory
 
 We know SIFT uses 128-dim vector for descriptors. Since it is using floating point numbers, it takes
 basically 512 bytes. Similarly SURF also takes minimum of 256 bytes (for 64-dim). Creating such a
-vector for thousands of features takes a lot of memory which are not feasible for resouce-constraint
+vector for thousands of features takes a lot of memory which are not feasible for resource-constraint
 applications especially for embedded systems. Larger the memory, longer the time it takes for
 matching.
 

modules/calib3d/src/rho.cpp

@@ -2164,7 +2164,7 @@ inline void   RHO_HEST_REFC::refine(void){
          * order to compute a candidate homography (newH).
          *
          * The system above is solved by Cholesky decomposition of a
-         * sufficently-damped JtJ into a lower-triangular matrix (and its
+         * sufficiently-damped JtJ into a lower-triangular matrix (and its
          * transpose), whose inverse is then computed. This inverse (and its
          * transpose) then multiply Jte in order to find dH.
          */

modules/core/include/opencv2/core/cvstd.hpp

@@ -103,7 +103,7 @@ double memory deallocation.
 CV_EXPORTS void fastFree(void* ptr);
 
 /*!
-  The STL-compilant memory Allocator based on cv::fastMalloc() and cv::fastFree()
+  The STL-compliant memory Allocator based on cv::fastMalloc() and cv::fastFree()
 */
 template<typename _Tp> class Allocator
 {

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

@@ -2266,7 +2266,7 @@ inline v_float32x4 v_matmuladd(const v_float32x4& v, const v_float32x4& m0,
                        v.s[0]*m0.s[3] + v.s[1]*m1.s[3] + v.s[2]*m2.s[3] + m3.s[3]);
 }
 
-////// FP16 suport ///////
+////// FP16 support ///////
 
 inline v_reg<float, V_TypeTraits<float>::nlanes128>
 v_load_expand(const float16_t* ptr)

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

@@ -1635,7 +1635,7 @@ inline void v_lut_deinterleave(const double* tab, const v_int32x4& idxvec, v_flo
 }
 #endif
 
-////// FP16 suport ///////
+////// FP16 support ///////
 #if CV_FP16
 inline v_float32x4 v_load_expand(const float16_t* ptr)
 {

modules/core/src/bindings_utils.cpp

@@ -33,7 +33,7 @@ String dumpInputArray(InputArray argument)
     }
     catch (...)
     {
-        ss << " ERROR: exception occured, dump is non-complete";  // need to properly support different kinds
+        ss << " ERROR: exception occurred, dump is non-complete";  // need to properly support different kinds
     }
     return ss.str();
 }
@@ -70,7 +70,7 @@ CV_EXPORTS_W String dumpInputArrayOfArrays(InputArrayOfArrays argument)
     }
     catch (...)
     {
-        ss << " ERROR: exception occured, dump is non-complete";  // need to properly support different kinds
+        ss << " ERROR: exception occurred, dump is non-complete";  // need to properly support different kinds
     }
     return ss.str();
 }
@@ -100,7 +100,7 @@ CV_EXPORTS_W String dumpInputOutputArray(InputOutputArray argument)
     }
     catch (...)
     {
-        ss << " ERROR: exception occured, dump is non-complete";  // need to properly support different kinds
+        ss << " ERROR: exception occurred, dump is non-complete";  // need to properly support different kinds
     }
     return ss.str();
 }
@@ -137,7 +137,7 @@ CV_EXPORTS_W String dumpInputOutputArrayOfArrays(InputOutputArrayOfArrays argume
     }
     catch (...)
     {
-        ss << " ERROR: exception occured, dump is non-complete";  // need to properly support different kinds
+        ss << " ERROR: exception occurred, dump is non-complete";  // need to properly support different kinds
     }
     return ss.str();
 }

modules/core/src/precomp.hpp

@@ -250,7 +250,7 @@ BinaryFunc getCopyMaskFunc(size_t esz);
 
 // There is some mess in code with vectors representation.
 // Both vector-column / vector-rows are used with dims=2 (as Mat2D always).
-// Reshape matrices if neccessary (in case of vectors) and returns size with scaled width.
+// Reshape matrices if necessary (in case of vectors) and returns size with scaled width.
 Size getContinuousSize2D(Mat& m1, int widthScale=1);
 Size getContinuousSize2D(Mat& m1, Mat& m2, int widthScale=1);
 Size getContinuousSize2D(Mat& m1, Mat& m2, Mat& m3, int widthScale=1);

modules/core/src/utils/datafile.cpp

@@ -344,7 +344,7 @@ cv::String findDataFile(const cv::String& relative_path,
 #if defined OPENCV_INSTALL_PREFIX && defined OPENCV_DATA_INSTALL_PATH
     cv::String install_dir(OPENCV_INSTALL_PREFIX);
     // use core/world module path and verify that library is running from installation directory
-    // It is neccessary to avoid touching of unrelated common /usr/local path
+    // It is necessary to avoid touching of unrelated common /usr/local path
     if (module_path.empty()) // can't determine
         module_path = install_dir;
     if (isSubDirectory(install_dir, module_path) || isSubDirectory(utils::fs::canonical(install_dir), utils::fs::canonical(module_path)))

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

@@ -119,7 +119,7 @@ message AttributeProto {
   // implementations needed to use has_field hueristics to determine
   // which value field was in use.  For IR_VERSION 0.0.2 or later, this
   // field MUST be set and match the f|i|s|t|... field in use.  This
-  // change was made to accomodate proto3 implementations.
+  // change was made to accommodate proto3 implementations.
   optional AttributeType type = 20;   // discriminator that indicates which field below is in use
 
   // Exactly ONE of the following fields must be present for this version of the IR

modules/ml/include/opencv2/ml.hpp

@@ -120,7 +120,7 @@ public:
     \f[(minVal, minVal*step, minVal*{step}^2, \dots,  minVal*{logStep}^n),\f]
     where \f$n\f$ is the maximal index satisfying
     \f[\texttt{minVal} * \texttt{logStep} ^n <  \texttt{maxVal}\f]
-    The grid is logarithmic, so logStep must always be greater then 1. Default value is 1.
+    The grid is logarithmic, so logStep must always be greater than 1. Default value is 1.
     */
     CV_PROP_RW double logStep;
 

modules/ml/src/svm.cpp

@@ -99,7 +99,7 @@ static void checkParamGrid(const ParamGrid& pg)
     if( pg.minVal < DBL_EPSILON )
         CV_Error( CV_StsBadArg, "Lower bound of the grid must be positive" );
     if( pg.logStep < 1. + FLT_EPSILON )
-        CV_Error( CV_StsBadArg, "Grid step must greater then 1" );
+        CV_Error( CV_StsBadArg, "Grid step must greater than 1" );
 }
 
 // SVM training parameters

modules/videoio/src/cap_dshow.cpp

@@ -2171,7 +2171,7 @@ void videoInput::setPhyCon(int id, int conn){
 
 
 // ----------------------------------------------------------------------
-// Check that we are not trying to setup a non-existant device
+// Check that we are not trying to setup a non-existent device
 // Then start the graph building!
 // ----------------------------------------------------------------------