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Merge pull request #28298 from raimbekovm:fix-spelling-errors

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docs: fix spelling errors in documentation
This commit is contained in:
Alexander Smorkalov
2025-12-25 08:33:50 +03:00
committed by GitHub
parent 3e89c3e26f 17a01d687c
commit ec4889b7ae
6 changed files with 13 additions and 13 deletions
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6
modules/core/include/opencv2/core/mat.hpp
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@@ -1366,15 +1366,15 @@ public:
/** @overload
* @param cn New number of channels. If the parameter is 0, the number of channels remains the same.
* @param newndims New number of dimentions.
* @param newsz Array with new matrix size by all dimentions. If some sizes are zero,
* @param newndims New number of dimensions.
* @param newsz Array with new matrix size by all dimensions. If some sizes are zero,
* the original sizes in those dimensions are presumed.
*/
Mat reshape(int cn, int newndims, const int* newsz) const;
/** @overload
* @param cn New number of channels. If the parameter is 0, the number of channels remains the same.
* @param newshape Vector with new matrix size by all dimentions. If some sizes are zero,
* @param newshape Vector with new matrix size by all dimensions. If some sizes are zero,
* the original sizes in those dimensions are presumed.
*/
Mat reshape(int cn, const std::vector<int>& newshape) const;

2
modules/dnn/src/layers/recurrent_layers.cpp
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@@ -416,7 +416,7 @@ public:
if (layout == BATCH_SEQ_HID){
//swap axis 0 and 1 input x
cv::Mat tmp;
// Since python input is 4 dimentional and C++ input 3 dimentinal
// Since python input is 4 dimensional and C++ input 3 dimensional
// we need to process each differently
if (input[0].dims == 4){
// here !!!

2
modules/gapi/include/opencv2/gapi/gmat.hpp
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@@ -245,7 +245,7 @@ struct GAPI_EXPORTS_W_SIMPLE GMatDesc
static inline GMatDesc empty_gmat_desc() { return GMatDesc{-1,-1,{-1,-1}}; }
namespace gapi { namespace detail {
/** Checks GMatDesc fields if the passed matrix is a set of n-dimentional points.
/** Checks GMatDesc fields if the passed matrix is a set of n-dimensional points.
@param in GMatDesc to check.
@param n expected dimensionality.
@return the amount of points. In case input matrix can't be described as vector of points

10
modules/gapi/include/opencv2/gapi/imgproc.hpp
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@@ -217,7 +217,7 @@ namespace imgproc {
GAPI_Assert (in.depth == CV_32S || in.depth == CV_32F);
int amount = detail::checkVector(in, 2u);
GAPI_Assert(amount != -1 &&
"Input Mat can't be described as vector of 2-dimentional points");
"Input Mat can't be described as vector of 2-dimensional points");
}
return empty_gopaque_desc();
}
@@ -242,7 +242,7 @@ namespace imgproc {
static GOpaqueDesc outMeta(GMatDesc in,DistanceTypes,double,double,double) {
int amount = detail::checkVector(in, 2u);
GAPI_Assert(amount != -1 &&
"Input Mat can't be described as vector of 2-dimentional points");
"Input Mat can't be described as vector of 2-dimensional points");
return empty_gopaque_desc();
}
};
@@ -276,7 +276,7 @@ namespace imgproc {
static GOpaqueDesc outMeta(GMatDesc in,int,double,double,double) {
int amount = detail::checkVector(in, 3u);
GAPI_Assert(amount != -1 &&
"Input Mat can't be described as vector of 3-dimentional points");
"Input Mat can't be described as vector of 3-dimensional points");
return empty_gopaque_desc();
}
};
@@ -1235,7 +1235,7 @@ weights \f$w_i\f$ are adjusted to be inversely proportional to \f$\rho(r_i)\f$ .
@note
- Function textual ID is "org.opencv.imgproc.shape.fitLine2DMat"
- In case of an N-dimentional points' set given, Mat should be 2-dimensional, have a single row
- In case of an N-dimensional points' set given, Mat should be 2-dimensional, have a single row
or column if there are N channels, or have N columns if there is a single channel.
@param src Input set of 2D points stored in one of possible containers: Mat,
@@ -1307,7 +1307,7 @@ weights \f$w_i\f$ are adjusted to be inversely proportional to \f$\rho(r_i)\f$ .
@note
- Function textual ID is "org.opencv.imgproc.shape.fitLine3DMat"
- In case of an N-dimentional points' set given, Mat should be 2-dimensional, have a single row
- In case of an N-dimensional points' set given, Mat should be 2-dimensional, have a single row
or column if there are N channels, or have N columns if there is a single channel.
@param src Input set of 3D points stored in one of possible containers: Mat,

2
modules/objdetect/src/aruco/aruco_detector.cpp
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@@ -125,7 +125,7 @@ static void _threshold(InputArray _in, OutputArray _out, int winSize, double con
/**
* @brief Given a tresholded image, find the contours, calculate their polygonal approximation
* @brief Given a thresholded image, find the contours, calculate their polygonal approximation
* and take those that accomplish some conditions
*/
static void _findMarkerContours(const Mat &in, vector<vector<Point2f> > &candidates,

4
modules/video/include/opencv2/video/background_segm.hpp
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@@ -117,7 +117,7 @@ public:
CV_WRAP virtual int getNMixtures() const = 0;
/** @brief Sets the number of gaussian components in the background model.
The model needs to be reinitalized to reserve memory.
The model needs to be reinitialized to reserve memory.
*/
CV_WRAP virtual void setNMixtures(int nmixtures) = 0;//needs reinitialization!
@@ -268,7 +268,7 @@ public:
CV_WRAP virtual int getNSamples() const = 0;
/** @brief Sets the number of data samples in the background model.
The model needs to be reinitalized to reserve memory.
The model needs to be reinitialized to reserve memory.
*/
CV_WRAP virtual void setNSamples(int _nN) = 0;//needs reinitialization!