From 5718d09e392a79881ba723376ea9af211a3e7b3f Mon Sep 17 00:00:00 2001 From: "luz.paz" Date: Mon, 12 Feb 2018 07:07:39 -0500 Subject: [PATCH] Misc. modules/ typos Found via `codespell` --- modules/core/include/opencv2/core/core_c.h | 6 ++--- modules/core/include/opencv2/core/cuda.hpp | 2 +- modules/core/include/opencv2/core/mat.hpp | 6 ++--- modules/core/include/opencv2/core/matx.hpp | 2 +- modules/core/include/opencv2/core/opengl.hpp | 2 +- modules/core/include/opencv2/core/optim.hpp | 4 ++-- .../core/include/opencv2/core/softfloat.hpp | 2 +- .../core/include/opencv2/core/vsx_utils.hpp | 6 ++--- modules/core/include/opencv2/core/wimage.hpp | 2 +- modules/core/src/array.cpp | 24 +++++++++---------- modules/core/src/conjugate_gradient.cpp | 2 +- modules/core/src/cuda_info.cpp | 2 +- modules/core/src/downhill_simplex.cpp | 2 +- modules/core/src/opengl.cpp | 2 +- modules/core/src/parallel_impl.cpp | 2 +- modules/core/src/persistence_base64.cpp | 4 ++-- modules/core/src/persistence_c.cpp | 2 +- modules/core/src/persistence_types.cpp | 2 +- modules/core/src/system.cpp | 2 +- modules/core/test/ocl/test_dft.cpp | 2 +- modules/core/test/test_downhill_simplex.cpp | 2 +- modules/core/test/test_operations.cpp | 2 +- modules/core/test/test_umat.cpp | 2 +- modules/dnn/CMakeLists.txt | 2 +- modules/dnn/include/opencv2/dnn.hpp | 2 +- .../dnn/include/opencv2/dnn/all_layers.hpp | 18 +++++++------- modules/dnn/include/opencv2/dnn/dnn.hpp | 4 ++-- modules/dnn/src/caffe/opencv-caffe.proto | 2 +- modules/dnn/src/dnn.cpp | 6 ++--- modules/dnn/src/layers/concat_layer.cpp | 2 +- .../dnn/src/ocl4dnn/src/math_functions.cpp | 2 +- modules/dnn/src/opencl/conv_layer_spatial.cl | 4 ++-- modules/dnn/src/tensorflow/tf_importer.cpp | 4 ++-- .../dnn/test/cityscapes_semsegm_test_enet.py | 4 ++-- modules/dnn/test/imagenet_cls_test_alexnet.py | 4 ++-- .../dnn/test/imagenet_cls_test_googlenet.py | 4 ++-- .../dnn/test/imagenet_cls_test_inception.py | 4 ++-- modules/dnn/test/pascal_semsegm_test_fcn.py | 2 +- modules/viz/include/opencv2/viz/vizcore.hpp | 2 +- modules/viz/src/vtk/vtkCocoaInteractorFix.mm | 2 +- 40 files changed, 76 insertions(+), 76 deletions(-) diff --git a/modules/core/include/opencv2/core/core_c.h b/modules/core/include/opencv2/core/core_c.h index 754af2fc60..c8c9d2eb02 100644 --- a/modules/core/include/opencv2/core/core_c.h +++ b/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 ) \ { \ diff --git a/modules/core/include/opencv2/core/cuda.hpp b/modules/core/include/opencv2/core/cuda.hpp index ca6eb2cf86..42a3b2710c 100644 --- a/modules/core/include/opencv2/core/cuda.hpp +++ b/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 @} @} diff --git a/modules/core/include/opencv2/core/mat.hpp b/modules/core/include/opencv2/core/mat.hpp index 41652d28d5..ca1b3aa9b5 100644 --- a/modules/core/include/opencv2/core/mat.hpp +++ b/modules/core/include/opencv2/core/mat.hpp @@ -2184,7 +2184,7 @@ public: 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 @@ public: 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 @@ public: //! 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); diff --git a/modules/core/include/opencv2/core/matx.hpp b/modules/core/include/opencv2/core/matx.hpp index 048bf3b2c4..e664a3e84c 100644 --- a/modules/core/include/opencv2/core/matx.hpp +++ b/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 diff --git a/modules/core/include/opencv2/core/opengl.hpp b/modules/core/include/opencv2/core/opengl.hpp index 8b63d6c91f..5e88cb8ce4 100644 --- a/modules/core/include/opencv2/core/opengl.hpp +++ b/modules/core/include/opencv2/core/opengl.hpp @@ -245,7 +245,7 @@ public: /** @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. */ diff --git a/modules/core/include/opencv2/core/optim.hpp b/modules/core/include/opencv2/core/optim.hpp index 190d54310f..c4729a9c10 100644 --- a/modules/core/include/opencv2/core/optim.hpp +++ b/modules/core/include/opencv2/core/optim.hpp @@ -115,7 +115,7 @@ public: 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 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 diff --git a/modules/core/include/opencv2/core/softfloat.hpp b/modules/core/include/opencv2/core/softfloat.hpp index b640111b36..d773c3c778 100644 --- a/modules/core/include/opencv2/core/softfloat.hpp +++ b/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 diff --git a/modules/core/include/opencv2/core/vsx_utils.hpp b/modules/core/include/opencv2/core/vsx_utils.hpp index aca534a7c3..c377551364 100644 --- a/modules/core/include/opencv2/core/vsx_utils.hpp +++ b/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 diff --git a/modules/core/include/opencv2/core/wimage.hpp b/modules/core/include/opencv2/core/wimage.hpp index b246c89d34..c7b6efa06a 100644 --- a/modules/core/include/opencv2/core/wimage.hpp +++ b/modules/core/include/opencv2/core/wimage.hpp @@ -289,7 +289,7 @@ protected: }; /** 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 class WImageBuffer : public WImage diff --git a/modules/core/src/array.cpp b/modules/core/src/array.cpp index 0f50b75496..98306d35a6 100644 --- a/modules/core/src/array.cpp +++ b/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 ) { diff --git a/modules/core/src/conjugate_gradient.cpp b/modules/core/src/conjugate_gradient.cpp index 1259cc9756..3e6cffbbb2 100644 --- a/modules/core/src/conjugate_gradient.cpp +++ b/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); diff --git a/modules/core/src/cuda_info.cpp b/modules/core/src/cuda_info.cpp index b412438581..4bf3d8f78e 100644 --- a/modules/core/src/cuda_info.cpp +++ b/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; diff --git a/modules/core/src/downhill_simplex.cpp b/modules/core/src/downhill_simplex.cpp index a0cc1320b8..a830d02812 100644 --- a/modules/core/src/downhill_simplex.cpp +++ b/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 diff --git a/modules/core/src/opengl.cpp b/modules/core/src/opengl.cpp index 75ee5c75bc..e730261692 100644 --- a/modules/core/src/opengl.cpp +++ b/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 extensionStr; diff --git a/modules/core/src/parallel_impl.cpp b/modules/core/src/parallel_impl.cpp index 662db78e67..c270b94ba1 100644 --- a/modules/core/src/parallel_impl.cpp +++ b/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 } } diff --git a/modules/core/src/persistence_base64.cpp b/modules/core/src/persistence_base64.cpp index ce48c1ddea..90bb1f6312 100644 --- a/modules/core/src/persistence_base64.cpp +++ b/modules/core/src/persistence_base64.cpp @@ -470,7 +470,7 @@ public: /* * 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 inline @@ -493,7 +493,7 @@ public: 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; diff --git a/modules/core/src/persistence_c.cpp b/modules/core/src/persistence_c.cpp index 7c1e7d9433..d7542ce291 100644 --- a/modules/core/src/persistence_c.cpp +++ b/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 + // find the last occurrence of for(;;) { int line_offset = (int)ftell( fs->file ); diff --git a/modules/core/src/persistence_types.cpp b/modules/core/src/persistence_types.cpp index 879bd21cac..d5732a7793 100644 --- a/modules/core/src/persistence_types.cpp +++ b/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) ) diff --git a/modules/core/src/system.cpp b/modules/core/src/system.cpp index ac0bc16c71..5c2016ef7c 100644 --- a/modules/core/src/system.cpp +++ b/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; diff --git a/modules/core/test/ocl/test_dft.cpp b/modules/core/test/ocl/test_dft.cpp index de0eb301c0..8e920fb860 100644 --- a/modules/core/test/ocl/test_dft.cpp +++ b/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) { diff --git a/modules/core/test/test_downhill_simplex.cpp b/modules/core/test/test_downhill_simplex.cpp index a9cc3c5729..228b720084 100644 --- a/modules/core/test/test_downhill_simplex.cpp +++ b/modules/core/test/test_downhill_simplex.cpp @@ -51,7 +51,7 @@ static void mytest(cv::Ptr solver,cv::PtrgetInitStep(settedStep); ASSERT_TRUE(settedStep.rows==1 && settedStep.cols==ndim); ASSERT_TRUE(std::equal(step.begin(),step.end(),settedStep.begin())); - std::cout<<"step setted:\n\t"<minimize(x); std::cout<<"res:\n\t"<Caffe functionality: - Convolution - Deconvolution @@ -125,12 +125,12 @@ CV__DNN_EXPERIMENTAL_NS_BEGIN virtual void setOutShape(const MatShape &outTailShape = MatShape()) = 0; /** @deprecated Use flag `produce_cell_output` in LayerParams. - * @brief Specifies either interpet first dimension of input blob as timestamp dimenion either as sample. + * @brief Specifies either interpret first dimension of input blob as timestamp dimenion either as sample. * - * If flag is set to true then shape of input blob will be interpeted as [`T`, `N`, `[data dims]`] where `T` specifies number of timpestamps, `N` is number of independent streams. + * If flag is set to true then shape of input blob will be interpreted as [`T`, `N`, `[data dims]`] where `T` specifies number of timestamps, `N` is number of independent streams. * In this case each forward() call will iterate through `T` timestamps and update layer's state `T` times. * - * If flag is set to false then shape of input blob will be interpeted as [`N`, `[data dims]`]. + * If flag is set to false then shape of input blob will be interpreted as [`N`, `[data dims]`]. * In this case each forward() call will make one iteration and produce one timestamp with shape [`N`, `[out dims]`]. */ CV_DEPRECATED virtual void setUseTimstampsDim(bool use = true) = 0; @@ -146,7 +146,7 @@ CV__DNN_EXPERIMENTAL_NS_BEGIN * @param output contains computed outputs: @f$h_t@f$ (and @f$c_t@f$ if setProduceCellOutput() flag was set to true). * * If setUseTimstampsDim() is set to true then @p input[0] should has at least two dimensions with the following shape: [`T`, `N`, `[data dims]`], - * where `T` specifies number of timpestamps, `N` is number of independent streams (i.e. @f$ x_{t_0 + t}^{stream} @f$ is stored inside @p input[0][t, stream, ...]). + * where `T` specifies number of timestamps, `N` is number of independent streams (i.e. @f$ x_{t_0 + t}^{stream} @f$ is stored inside @p input[0][t, stream, ...]). * * If setUseTimstampsDim() is set to fase then @p input[0] should contain single timestamp, its shape should has form [`N`, `[data dims]`] with at least one dimension. * (i.e. @f$ x_{t}^{stream} @f$ is stored inside @p input[0][stream, ...]). @@ -328,7 +328,7 @@ CV__DNN_EXPERIMENTAL_NS_BEGIN * @param begin Vector of start indices * @param size Vector of sizes * - * More convinient numpy-like slice. One and only output blob + * More convenient numpy-like slice. One and only output blob * is a slice `input[begin[0]:begin[0]+size[0], begin[1]:begin[1]+size[1], ...]` * * 3. Torch mode diff --git a/modules/dnn/include/opencv2/dnn/dnn.hpp b/modules/dnn/include/opencv2/dnn/dnn.hpp index 15c41b3079..4ad303594e 100644 --- a/modules/dnn/include/opencv2/dnn/dnn.hpp +++ b/modules/dnn/include/opencv2/dnn/dnn.hpp @@ -691,7 +691,7 @@ CV__DNN_EXPERIMENTAL_NS_BEGIN * @param swapRB flag which indicates that swap first and last channels * in 3-channel image is necessary. * @param crop flag which indicates whether image will be cropped after resize or not - * @details if @p crop is true, input image is resized so one side after resize is equal to corresponing + * @details if @p crop is true, input image is resized so one side after resize is equal to corresponding * dimension in @p size and another one is equal or larger. Then, crop from the center is performed. * If @p crop is false, direct resize without cropping and preserving aspect ratio is performed. * @returns 4-dimansional Mat with NCHW dimensions order. @@ -719,7 +719,7 @@ CV__DNN_EXPERIMENTAL_NS_BEGIN * @param swapRB flag which indicates that swap first and last channels * in 3-channel image is necessary. * @param crop flag which indicates whether image will be cropped after resize or not - * @details if @p crop is true, input image is resized so one side after resize is equal to corresponing + * @details if @p crop is true, input image is resized so one side after resize is equal to corresponding * dimension in @p size and another one is equal or larger. Then, crop from the center is performed. * If @p crop is false, direct resize without cropping and preserving aspect ratio is performed. * @returns 4-dimansional Mat with NCHW dimensions order. diff --git a/modules/dnn/src/caffe/opencv-caffe.proto b/modules/dnn/src/caffe/opencv-caffe.proto index 88aaa86c22..41cd46bb1c 100644 --- a/modules/dnn/src/caffe/opencv-caffe.proto +++ b/modules/dnn/src/caffe/opencv-caffe.proto @@ -131,7 +131,7 @@ message PriorBoxParameter { // Variance for adjusting the prior bboxes. repeated float variance = 6; // By default, we calculate img_height, img_width, step_x, step_y based on - // bottom[0] (feat) and bottom[1] (img). Unless these values are explicitely + // bottom[0] (feat) and bottom[1] (img). Unless these values are explicitly // provided. // Explicitly provide the img_size. optional uint32 img_size = 7; diff --git a/modules/dnn/src/dnn.cpp b/modules/dnn/src/dnn.cpp index be4767b28a..b66fb4236d 100644 --- a/modules/dnn/src/dnn.cpp +++ b/modules/dnn/src/dnn.cpp @@ -58,7 +58,7 @@ namespace cv { namespace dnn { CV__DNN_EXPERIMENTAL_NS_BEGIN -// this option is usefull to run valgrind memory errors detection +// this option is useful to run valgrind memory errors detection static bool DNN_DISABLE_MEMORY_OPTIMIZATIONS = utils::getConfigurationParameterBool("OPENCV_DNN_DISABLE_MEMORY_OPTIMIZATIONS", false); using std::vector; @@ -911,7 +911,7 @@ struct Net::Impl int id = getLayerId(layerName); if (id < 0) - CV_Error(Error::StsError, "Requsted layer \"" + layerName + "\" not found"); + CV_Error(Error::StsError, "Requested layer \"" + layerName + "\" not found"); return getLayerData(id); } @@ -1897,7 +1897,7 @@ struct Net::Impl if ((size_t)pin.oid >= ld.outputBlobs.size()) { CV_Error(Error::StsOutOfRange, format("Layer \"%s\" produce only %d outputs, " - "the #%d was requsted", ld.name.c_str(), + "the #%d was requested", ld.name.c_str(), ld.outputBlobs.size(), pin.oid)); } if (preferableTarget != DNN_TARGET_CPU) diff --git a/modules/dnn/src/layers/concat_layer.cpp b/modules/dnn/src/layers/concat_layer.cpp index f8c0a27dbe..63b722ee9a 100644 --- a/modules/dnn/src/layers/concat_layer.cpp +++ b/modules/dnn/src/layers/concat_layer.cpp @@ -88,7 +88,7 @@ public: for (int curAxis = 0; curAxis < outputs[0].size(); curAxis++) { if (curAxis != cAxis && outputs[0][curAxis] != curShape[curAxis]) - CV_Error(Error::StsBadSize, "Inconsitent shape for ConcatLayer"); + CV_Error(Error::StsBadSize, "Inconsistent shape for ConcatLayer"); } } diff --git a/modules/dnn/src/ocl4dnn/src/math_functions.cpp b/modules/dnn/src/ocl4dnn/src/math_functions.cpp index c52a8a93c9..05cfd509b9 100644 --- a/modules/dnn/src/ocl4dnn/src/math_functions.cpp +++ b/modules/dnn/src/ocl4dnn/src/math_functions.cpp @@ -185,7 +185,7 @@ static bool ocl4dnnFastImageGEMM(const CBLAS_TRANSPOSE TransA, int blockC_height = blocksize; int use_buffer_indicator = 8; - // To fix the edge problem casued by the sub group block read. + // To fix the edge problem caused by the sub group block read. // we have to pad the image if it's not multiple of tile. // just padding one line is enough as the sub group block read // will clamp to edge according to the spec. diff --git a/modules/dnn/src/opencl/conv_layer_spatial.cl b/modules/dnn/src/opencl/conv_layer_spatial.cl index 3369c6c971..e31d173d75 100644 --- a/modules/dnn/src/opencl/conv_layer_spatial.cl +++ b/modules/dnn/src/opencl/conv_layer_spatial.cl @@ -188,7 +188,7 @@ __kernel void ConvolveBasic( #define VLOAD4(_v, _p) do { _v = vload4(0, _p); } while(0) // Each work-item computes a OUT_BLOCK_WIDTH * OUT_BLOCK_HEIGHT region of one output map. -// Each work-group (which will be mapped to 1 SIMD16/SIMD8 EU thread) will compute 16/8 different feature maps, but each feature map is for the same region of the imput image. +// Each work-group (which will be mapped to 1 SIMD16/SIMD8 EU thread) will compute 16/8 different feature maps, but each feature map is for the same region of the input image. // NDRange: (output_width+pad)/ OUT_BLOCK_WIDTH, (output_height+pad)/OUT_BLOCK_HEIGHT, NUM_FILTERS/OUT_BLOCK_DEPTH // NOTE: for beignet this reqd_work_group_size does not guarantee that SIMD16 mode will be used, the compiler could choose to use two SIMD8 threads, and if that happens the code will break. @@ -220,7 +220,7 @@ convolve_simd( int in_addr; - // find weights adress of given neuron (lid is index) + // find weights address of given neuron (lid is index) unsigned int weight_addr = (fmg % (ALIGNED_NUM_FILTERS/SIMD_SIZE)) * INPUT_DEPTH * KERNEL_WIDTH * KERNEL_HEIGHT * SIMD_SIZE + lid; for(int i=0;iSetRootWindow(NULL); } }