diff --git a/apps/interactive-calibration/rotationConverters.cpp b/apps/interactive-calibration/rotationConverters.cpp index ff31c9e380ca..421d15a924d2 100644 --- a/apps/interactive-calibration/rotationConverters.cpp +++ b/apps/interactive-calibration/rotationConverters.cpp @@ -16,7 +16,7 @@ void calib::Euler(const cv::Mat& src, cv::Mat& dst, int argType) { if((src.rows == 3) && (src.cols == 3)) { - //convert rotaion matrix to 3 angles (pitch, yaw, roll) + //convert rotation matrix to 3 angles (pitch, yaw, roll) dst = cv::Mat(3, 1, CV_64F); double pitch, yaw, roll; @@ -55,7 +55,7 @@ void calib::Euler(const cv::Mat& src, cv::Mat& dst, int argType) else if( (src.cols == 1 && src.rows == 3) || (src.cols == 3 && src.rows == 1 ) ) { - //convert vector which contains 3 angles (pitch, yaw, roll) to rotaion matrix + //convert vector which contains 3 angles (pitch, yaw, roll) to rotation matrix double pitch, yaw, roll; if(src.cols == 1 && src.rows == 3) { diff --git a/cmake/FindCUDA.cmake b/cmake/FindCUDA.cmake index 632b8c828510..37d557a792e1 100644 --- a/cmake/FindCUDA.cmake +++ b/cmake/FindCUDA.cmake @@ -141,7 +141,7 @@ # -- Same as CUDA_ADD_EXECUTABLE except that a library is created. # # CUDA_BUILD_CLEAN_TARGET() -# -- Creates a convience target that deletes all the dependency files +# -- Creates a convenience target that deletes all the dependency files # generated. You should make clean after running this target to ensure the # dependency files get regenerated. # @@ -473,7 +473,7 @@ else() endif() # Propagate the host flags to the host compiler via -Xcompiler -option(CUDA_PROPAGATE_HOST_FLAGS "Propage C/CXX_FLAGS and friends to the host compiler via -Xcompile" ON) +option(CUDA_PROPAGATE_HOST_FLAGS "Propagate C/CXX_FLAGS and friends to the host compiler via -Xcompile" ON) # Enable CUDA_SEPARABLE_COMPILATION option(CUDA_SEPARABLE_COMPILATION "Compile CUDA objects with separable compilation enabled. Requires CUDA 5.0+" OFF) diff --git a/cmake/OpenCVPCHSupport.cmake b/cmake/OpenCVPCHSupport.cmake index b4658c604bc6..f9b1b48b658a 100644 --- a/cmake/OpenCVPCHSupport.cmake +++ b/cmake/OpenCVPCHSupport.cmake @@ -362,7 +362,7 @@ MACRO(ADD_NATIVE_PRECOMPILED_HEADER _targetName _input) endif() endforeach() - #also inlude ${oldProps} to have the same compile options + #also include ${oldProps} to have the same compile options GET_TARGET_PROPERTY(oldProps ${_targetName} COMPILE_FLAGS) if (oldProps MATCHES NOTFOUND) SET(oldProps "") diff --git a/cmake/templates/OpenCVConfig.cmake.in b/cmake/templates/OpenCVConfig.cmake.in index 84262a87b30f..fefa359e0a9d 100644 --- a/cmake/templates/OpenCVConfig.cmake.in +++ b/cmake/templates/OpenCVConfig.cmake.in @@ -260,7 +260,7 @@ endif() set(OpenCV_LIBRARIES ${OpenCV_LIBS}) # -# Some macroses for samples +# Some macros for samples # macro(ocv_check_dependencies) set(OCV_DEPENDENCIES_FOUND TRUE) diff --git a/doc/js_tutorials/js_imgproc/js_grabcut/js_grabcut.markdown b/doc/js_tutorials/js_imgproc/js_grabcut/js_grabcut.markdown index 570a490fea21..ef71d07aa5e0 100644 --- a/doc/js_tutorials/js_imgproc/js_grabcut/js_grabcut.markdown +++ b/doc/js_tutorials/js_imgproc/js_grabcut/js_grabcut.markdown @@ -29,7 +29,7 @@ What happens in background ? objects). Everything inside rectangle is unknown. Similarly any user input specifying foreground and background are considered as hard-labelling which means they won't change in the process. -- Computer does an initial labelling depeding on the data we gave. It labels the foreground and +- Computer does an initial labelling depending on the data we gave. It labels the foreground and background pixels (or it hard-labels) - Now a Gaussian Mixture Model(GMM) is used to model the foreground and background. - Depending on the data we gave, GMM learns and create new pixel distribution. That is, the diff --git a/doc/js_tutorials/js_setup/js_usage/js_usage.markdown b/doc/js_tutorials/js_setup/js_usage/js_usage.markdown index 72f481df7a90..88aba1afd552 100644 --- a/doc/js_tutorials/js_setup/js_usage/js_usage.markdown +++ b/doc/js_tutorials/js_setup/js_usage/js_usage.markdown @@ -129,7 +129,7 @@ function onOpenCvReady() { </html> @endcode -@note You have to call delete method of cv.Mat to free memory allocated in Emscripten's heap. Please refer to [Memeory management of Emscripten](https://kripken.github.io/emscripten-site/docs/porting/connecting_cpp_and_javascript/embind.html#memory-management) for details. +@note You have to call delete method of cv.Mat to free memory allocated in Emscripten's heap. Please refer to [Memory management of Emscripten](https://kripken.github.io/emscripten-site/docs/porting/connecting_cpp_and_javascript/embind.html#memory-management) for details. Try it ------ diff --git a/doc/py_tutorials/py_imgproc/py_grabcut/py_grabcut.markdown b/doc/py_tutorials/py_imgproc/py_grabcut/py_grabcut.markdown index 2c489e2453a5..7dc22d37aad5 100644 --- a/doc/py_tutorials/py_imgproc/py_grabcut/py_grabcut.markdown +++ b/doc/py_tutorials/py_imgproc/py_grabcut/py_grabcut.markdown @@ -37,7 +37,7 @@ So what happens in background ? objects). Everything inside rectangle is unknown. Similarly any user input specifying foreground and background are considered as hard-labelling which means they won't change in the process. -- Computer does an initial labelling depeding on the data we gave. It labels the foreground and +- Computer does an initial labelling depending on the data we gave. It labels the foreground and background pixels (or it hard-labels) - Now a Gaussian Mixture Model(GMM) is used to model the foreground and background. - Depending on the data we gave, GMM learns and create new pixel distribution. That is, the diff --git a/doc/tutorials/calib3d/real_time_pose/real_time_pose.markdown b/doc/tutorials/calib3d/real_time_pose/real_time_pose.markdown index b974b8bc6327..4347d116510b 100644 --- a/doc/tutorials/calib3d/real_time_pose/real_time_pose.markdown +++ b/doc/tutorials/calib3d/real_time_pose/real_time_pose.markdown @@ -16,7 +16,7 @@ In this tutorial is explained how to build a real time application to estimate t order to track a textured object with six degrees of freedom given a 2D image and its 3D textured model. -The application will have the followings parts: +The application will have the following parts: - Read 3D textured object model and object mesh. - Take input from Camera or Video. @@ -426,16 +426,16 @@ Here is explained in detail the code for the real time application: @endcode OpenCV provides four PnP methods: ITERATIVE, EPNP, P3P and DLS. Depending on the application type, the estimation method will be different. In the case that we want to make a real time application, - the more suitable methods are EPNP and P3P due to that are faster than ITERATIVE and DLS at + the more suitable methods are EPNP and P3P since they are faster than ITERATIVE and DLS at finding an optimal solution. However, EPNP and P3P are not especially robust in front of planar - surfaces and sometimes the pose estimation seems to have a mirror effect. Therefore, in this this - tutorial is used ITERATIVE method due to the object to be detected has planar surfaces. + surfaces and sometimes the pose estimation seems to have a mirror effect. Therefore, in this + tutorial an ITERATIVE method is used due to the object to be detected has planar surfaces. - The OpenCV RANSAC implementation wants you to provide three parameters: the maximum number of - iterations until stop the algorithm, the maximum allowed distance between the observed and - computed point projections to consider it an inlier and the confidence to obtain a good result. + The OpenCV RANSAC implementation wants you to provide three parameters: 1) the maximum number of + iterations until the algorithm stops, 2) the maximum allowed distance between the observed and + computed point projections to consider it an inlier and 3) the confidence to obtain a good result. You can tune these parameters in order to improve your algorithm performance. Increasing the - number of iterations you will have a more accurate solution, but will take more time to find a + number of iterations will have a more accurate solution, but will take more time to find a solution. Increasing the reprojection error will reduce the computation time, but your solution will be unaccurate. Decreasing the confidence your algorithm will be faster, but the obtained solution will be unaccurate. diff --git a/doc/tutorials/introduction/windows_install/windows_install.markdown b/doc/tutorials/introduction/windows_install/windows_install.markdown index e60c846b12e8..7f491d8fdd7d 100644 --- a/doc/tutorials/introduction/windows_install/windows_install.markdown +++ b/doc/tutorials/introduction/windows_install/windows_install.markdown @@ -46,7 +46,7 @@ cd /c/lib myRepo=$(pwd) CMAKE_CONFIG_GENERATOR="Visual Studio 14 2015 Win64" if [ ! -d "$myRepo/opencv" ]; then - echo "clonning opencv" + echo "cloning opencv" git clone https://github.com/opencv/opencv.git mkdir Build mkdir Build/opencv @@ -58,7 +58,7 @@ else cd .. fi if [ ! -d "$myRepo/opencv_contrib" ]; then - echo "clonning opencv_contrib" + echo "cloning opencv_contrib" git clone https://github.com/opencv/opencv_contrib.git mkdir Build mkdir Build/opencv_contrib diff --git a/modules/calib3d/test/test_chesscorners.cpp b/modules/calib3d/test/test_chesscorners.cpp index 8303a8dcd424..e55d069de059 100644 --- a/modules/calib3d/test/test_chesscorners.cpp +++ b/modules/calib3d/test/test_chesscorners.cpp @@ -198,7 +198,7 @@ void CV_ChessboardDetectorTest::run_batch( const string& filename ) if( !fs.isOpened() || board_list.empty() || !board_list.isSeq() || board_list.size() % 2 != 0 ) { - ts->printf( cvtest::TS::LOG, "%s can not be readed or is not valid\n", (folder + filename).c_str() ); + ts->printf( cvtest::TS::LOG, "%s can not be read or is not valid\n", (folder + filename).c_str() ); ts->printf( cvtest::TS::LOG, "fs.isOpened=%d, board_list.empty=%d, board_list.isSeq=%d,board_list.size()%2=%d\n", fs.isOpened(), (int)board_list.empty(), board_list.isSeq(), board_list.size()%2); ts->set_failed_test_info( cvtest::TS::FAIL_MISSING_TEST_DATA ); diff --git a/modules/calib3d/test/test_chesscorners_timing.cpp b/modules/calib3d/test/test_chesscorners_timing.cpp index 4d643a1d4514..b89d2e014785 100644 --- a/modules/calib3d/test/test_chesscorners_timing.cpp +++ b/modules/calib3d/test/test_chesscorners_timing.cpp @@ -85,7 +85,7 @@ void CV_ChessboardDetectorTimingTest::run( int start_from ) if( !fs || !board_list || !CV_NODE_IS_SEQ(board_list->tag) || board_list->data.seq->total % 4 != 0 ) { - ts->printf( cvtest::TS::LOG, "chessboard_timing_list.dat can not be readed or is not valid" ); + ts->printf( cvtest::TS::LOG, "chessboard_timing_list.dat can not be read or is not valid" ); code = cvtest::TS::FAIL_MISSING_TEST_DATA; goto _exit_; } diff --git a/modules/core/include/opencv2/core/types_c.h b/modules/core/include/opencv2/core/types_c.h index 7e384a5c6f7d..81e986fcd15c 100644 --- a/modules/core/include/opencv2/core/types_c.h +++ b/modules/core/include/opencv2/core/types_c.h @@ -1764,7 +1764,7 @@ typedef struct CvString } CvString; -/** All the keys (names) of elements in the readed file storage +/** All the keys (names) of elements in the read file storage are stored in the hash to speed up the lookup operations: */ typedef struct CvStringHashNode { diff --git a/modules/core/src/datastructs.cpp b/modules/core/src/datastructs.cpp index 56528fcf699a..83c11c18555d 100644 --- a/modules/core/src/datastructs.cpp +++ b/modules/core/src/datastructs.cpp @@ -2779,7 +2779,7 @@ cvGraphAddEdgeByPtr( CvGraph* graph, if( start_vtx == end_vtx ) CV_Error( start_vtx ? CV_StsBadArg : CV_StsNullPtr, - "vertex pointers coinside (or set to NULL)" ); + "vertex pointers coincide (or set to NULL)" ); edge = (CvGraphEdge*)cvSetNew( (CvSet*)(graph->edges) ); assert( edge->flags >= 0 ); diff --git a/modules/core/src/persistence_c.cpp b/modules/core/src/persistence_c.cpp index ed315d0971bf..ed349cc15052 100644 --- a/modules/core/src/persistence_c.cpp +++ b/modules/core/src/persistence_c.cpp @@ -1063,7 +1063,7 @@ cvReadRawDataSlice( const CvFileStorage* fs, CvSeqReader* reader, CV_Error( CV_StsNullPtr, "Null pointer to reader or destination array" ); if( !reader->seq && len != 1 ) - CV_Error( CV_StsBadSize, "The readed sequence is a scalar, thus len must be 1" ); + CV_Error( CV_StsBadSize, "The read sequence is a scalar, thus len must be 1" ); fmt_pair_count = icvDecodeFormat( dt, fmt_pairs, CV_FS_MAX_FMT_PAIRS ); size_t step = ::icvCalcStructSize(dt, 0); diff --git a/modules/cudafilters/src/cuda/median_filter.cu b/modules/cudafilters/src/cuda/median_filter.cu index f8e02cb03907..fe26c7be0e33 100644 --- a/modules/cudafilters/src/cuda/median_filter.cu +++ b/modules/cudafilters/src/cuda/median_filter.cu @@ -246,7 +246,7 @@ namespace cv { namespace cuda { namespace device } __syncthreads(); - // Fot all remaining rows in the median filter, add the values to the the histogram + // For all remaining rows in the median filter, add the values to the the histogram for (int j=threadIdx.x; j<cols; j+=blockDim.x){ for(int i=initStartRow; i<initStopRow; i++){ int pos=::min(i,rows-1); diff --git a/modules/cudaimgproc/src/mssegmentation.cpp b/modules/cudaimgproc/src/mssegmentation.cpp index ee9ce5ac0a3b..2bc071813e8e 100644 --- a/modules/cudaimgproc/src/mssegmentation.cpp +++ b/modules/cudaimgproc/src/mssegmentation.cpp @@ -342,7 +342,7 @@ void cv::cuda::meanShiftSegmentation(InputArray _src, OutputArray _dst, int sp, } } - // Sort all graph's edges connecting different components (in asceding order) + // Sort all graph's edges connecting different components (in ascending order) std::sort(edges.begin(), edges.end()); // Exclude small components (starting from the nearest couple) diff --git a/modules/features2d/doc/read_file_nondiff32.pl b/modules/features2d/doc/read_file_nondiff32.pl index 6f1b420ecbee..2ada4c9ea212 100644 --- a/modules/features2d/doc/read_file_nondiff32.pl +++ b/modules/features2d/doc/read_file_nondiff32.pl @@ -131,7 +131,7 @@ } close $in2 or die "Can't close $filein: $!"; } - #find next else and interprete it + #find next else and interpret it open(my $in3, "<", $filein) or die "Can't open $filein: $!"; $i3=1; $ifcount3=0; diff --git a/modules/features2d/doc/read_file_score32.pl b/modules/features2d/doc/read_file_score32.pl index c1adedac203a..10cb77d0809c 100644 --- a/modules/features2d/doc/read_file_score32.pl +++ b/modules/features2d/doc/read_file_score32.pl @@ -119,7 +119,7 @@ } close $in2 or die "Can't close $filein: $!"; } - #find next else and interprete it + #find next else and interpret it open(my $in3, "<", $filein) or die "Can't open $filein: $!"; $i3=1; $ifcount3=0; diff --git a/modules/ml/src/svm.cpp b/modules/ml/src/svm.cpp index 330831c0dc31..6aff6ff7d829 100644 --- a/modules/ml/src/svm.cpp +++ b/modules/ml/src/svm.cpp @@ -2048,7 +2048,7 @@ class SVMImpl CV_FINAL : public SVM svmType == NU_SVC ? "NU_SVC" : svmType == ONE_CLASS ? "ONE_CLASS" : svmType == EPS_SVR ? "EPS_SVR" : - svmType == NU_SVR ? "NU_SVR" : format("Uknown_%d", svmType); + svmType == NU_SVR ? "NU_SVR" : format("Unknown_%d", svmType); String kernel_type_str = kernelType == LINEAR ? "LINEAR" : kernelType == POLY ? "POLY" : diff --git a/modules/ts/include/opencv2/ts/ts_gtest.h b/modules/ts/include/opencv2/ts/ts_gtest.h index 2b1299c3bf7a..b687a5722e28 100644 --- a/modules/ts/include/opencv2/ts/ts_gtest.h +++ b/modules/ts/include/opencv2/ts/ts_gtest.h @@ -9013,7 +9013,7 @@ class NativeArray { // Implements Boolean test assertions such as EXPECT_TRUE. expression can be // either a boolean expression or an AssertionResult. text is a textual -// represenation of expression as it was passed into the EXPECT_TRUE. +// representation of expression as it was passed into the EXPECT_TRUE. #define GTEST_TEST_BOOLEAN_(expression, text, actual, expected, fail) \ GTEST_AMBIGUOUS_ELSE_BLOCKER_ \ if (const ::testing::AssertionResult gtest_ar_ = \ diff --git a/samples/cpp/train_HOG.cpp b/samples/cpp/train_HOG.cpp index 1c6c81481c86..3a1527d8f422 100644 --- a/samples/cpp/train_HOG.cpp +++ b/samples/cpp/train_HOG.cpp @@ -204,7 +204,7 @@ int main( int argc, char** argv ) const char* keys = { "{help h| | show help message}" - "{pd | | path of directory contains possitive images}" + "{pd | | path of directory contains positive images}" "{nd | | path of directory contains negative images}" "{td | | path of directory contains test images}" "{tv | | test video file name}" diff --git a/samples/cpp/tutorial_code/ml/introduction_to_pca/introduction_to_pca.cpp b/samples/cpp/tutorial_code/ml/introduction_to_pca/introduction_to_pca.cpp index c194e82f24cd..aa6107c120cd 100644 --- a/samples/cpp/tutorial_code/ml/introduction_to_pca/introduction_to_pca.cpp +++ b/samples/cpp/tutorial_code/ml/introduction_to_pca/introduction_to_pca.cpp @@ -1,6 +1,6 @@ /** * @file introduction_to_pca.cpp - * @brief This program demonstrates how to use OpenCV PCA to extract the orienation of an object + * @brief This program demonstrates how to use OpenCV PCA to extract the orientation of an object * @author OpenCV team */ diff --git a/samples/cpp/warpPerspective_demo.cpp b/samples/cpp/warpPerspective_demo.cpp index 35bf87dfd9de..591e03d59b76 100644 --- a/samples/cpp/warpPerspective_demo.cpp +++ b/samples/cpp/warpPerspective_demo.cpp @@ -26,7 +26,7 @@ static void help(char** argv) "\tESC, q - quit the program\n" "\tr - change order of points to rotate transformation\n" "\tc - delete selected points\n" - "\ti - change order of points to invers transformation \n" + "\ti - change order of points to inverse transformation \n" "\nUse your mouse to select a point and move it to see transformation changes" << endl; } diff --git a/samples/dnn/custom_layers.hpp b/samples/dnn/custom_layers.hpp index 918cc8ae4676..a18bb9a5cfe6 100644 --- a/samples/dnn/custom_layers.hpp +++ b/samples/dnn/custom_layers.hpp @@ -198,7 +198,7 @@ class ResizeBilinearLayer CV_FINAL : public cv::dnn::Layer //! [ResizeBilinearLayer] // -// The folowing code is used only to generate tutorials documentation. +// The following code is used only to generate tutorials documentation. // //! [A custom layer interface] diff --git a/samples/winrt/OcvImageProcessing/OcvImageProcessing/Common/StandardStyles.xaml b/samples/winrt/OcvImageProcessing/OcvImageProcessing/Common/StandardStyles.xaml index 4def039e591b..c8f8500db2b7 100644 --- a/samples/winrt/OcvImageProcessing/OcvImageProcessing/Common/StandardStyles.xaml +++ b/samples/winrt/OcvImageProcessing/OcvImageProcessing/Common/StandardStyles.xaml @@ -1091,7 +1091,7 @@ Style x:Key="SkipBackAppBarButtonStyle" TargetType="ButtonBase" BasedOn="{Static </Style> <Style x:Key="PermissionsAppBarButtonStyle" TargetType="ButtonBase" BasedOn="{StaticResource AppBarButtonStyle}"> <Setter Property="AutomationProperties.AutomationId" Value="PermissionsAppBarButton"/> - <Setter Property="AutomationProperties.Name" Value="Permisions"/> + <Setter Property="AutomationProperties.Name" Value="Permissions"/> <Setter Property="Content" Value=""/> </Style> <Style x:Key="HighlightAppBarButtonStyle" TargetType="ButtonBase" BasedOn="{StaticResource AppBarButtonStyle}">