diff --git a/apps/createsamples/utility.cpp b/apps/createsamples/utility.cpp index 919ad2dcc4..5176f14836 100644 --- a/apps/createsamples/utility.cpp +++ b/apps/createsamples/utility.cpp @@ -1078,8 +1078,8 @@ void cvCreateTrainingSamples( const char* filename, icvPlaceDistortedSample( sample, inverse, maxintensitydev, maxxangle, maxyangle, maxzangle, 0 /* nonzero means placing image without cut offs */, - 0.0 /* nozero adds random shifting */, - 0.0 /* nozero adds random scaling */, + 0.0 /* nonzero adds random shifting */, + 0.0 /* nonzero adds random scaling */, &data ); if( showsamples ) diff --git a/apps/traincascade/HOGfeatures.h b/apps/traincascade/HOGfeatures.h index cdf758777d..3d4092eab9 100644 --- a/apps/traincascade/HOGfeatures.h +++ b/apps/traincascade/HOGfeatures.h @@ -45,7 +45,7 @@ protected: }; std::vector features; - cv::Mat normSum; //for nomalization calculation (L1 or L2) + cv::Mat normSum; //for normalization calculation (L1 or L2) std::vector hist; }; @@ -70,7 +70,7 @@ inline float CvHOGEvaluator::Feature::calc( const std::vector& _hists, const float *pnormSum = _normSum.ptr((int)y); normFactor = (float)(pnormSum[fastRect[0].p0] - pnormSum[fastRect[1].p1] - pnormSum[fastRect[2].p2] + pnormSum[fastRect[3].p3]); - res = (res > 0.001f) ? ( res / (normFactor + 0.001f) ) : 0.f; //for cutting negative values, which apper due to floating precision + res = (res > 0.001f) ? ( res / (normFactor + 0.001f) ) : 0.f; //for cutting negative values, which appear due to floating precision return res; } diff --git a/doc/js_tutorials/js_imgproc/js_contours/js_contours_hierarchy/js_contours_hierarchy.markdown b/doc/js_tutorials/js_imgproc/js_contours/js_contours_hierarchy/js_contours_hierarchy.markdown index 5dc807742b..c98628e486 100644 --- a/doc/js_tutorials/js_imgproc/js_contours/js_contours_hierarchy/js_contours_hierarchy.markdown +++ b/doc/js_tutorials/js_imgproc/js_contours/js_contours_hierarchy/js_contours_hierarchy.markdown @@ -145,7 +145,7 @@ no child, parent is contour-3. So array is [-1,-1,-1,3]. And this is the final guy, Mr.Perfect. It retrieves all the contours and creates a full family hierarchy list. **It even tells, who is the grandpa, father, son, grandson and even beyond... :)**. -For examle, I took above image, rewrite the code for cv.RETR_TREE, reorder the contours as per the +For example, I took above image, rewrite the code for cv.RETR_TREE, reorder the contours as per the result given by OpenCV and analyze it. Again, red letters give the contour number and green letters give the hierarchy order. diff --git a/doc/py_tutorials/py_feature2d/py_feature_homography/py_feature_homography.markdown b/doc/py_tutorials/py_feature2d/py_feature_homography/py_feature_homography.markdown index f2c0cdddb5..ed76d638f5 100644 --- a/doc/py_tutorials/py_feature2d/py_feature_homography/py_feature_homography.markdown +++ b/doc/py_tutorials/py_feature2d/py_feature_homography/py_feature_homography.markdown @@ -17,7 +17,7 @@ In short, we found locations of some parts of an object in another cluttered ima is sufficient to find the object exactly on the trainImage. For that, we can use a function from calib3d module, ie **cv.findHomography()**. If we pass the set -of points from both the images, it will find the perpective transformation of that object. Then we +of points from both the images, it will find the perspective transformation of that object. Then we can use **cv.perspectiveTransform()** to find the object. It needs atleast four correct points to find the transformation. @@ -68,7 +68,7 @@ Now we set a condition that atleast 10 matches (defined by MIN_MATCH_COUNT) are find the object. Otherwise simply show a message saying not enough matches are present. If enough matches are found, we extract the locations of matched keypoints in both the images. They -are passed to find the perpective transformation. Once we get this 3x3 transformation matrix, we use +are passed to find the perspective transformation. Once we get this 3x3 transformation matrix, we use it to transform the corners of queryImage to corresponding points in trainImage. Then we draw it. @code{.py} if len(good)>MIN_MATCH_COUNT: diff --git a/doc/py_tutorials/py_feature2d/py_shi_tomasi/py_shi_tomasi.markdown b/doc/py_tutorials/py_feature2d/py_shi_tomasi/py_shi_tomasi.markdown index b440f46338..1229581ce6 100644 --- a/doc/py_tutorials/py_feature2d/py_shi_tomasi/py_shi_tomasi.markdown +++ b/doc/py_tutorials/py_feature2d/py_shi_tomasi/py_shi_tomasi.markdown @@ -28,7 +28,7 @@ If it is a greater than a threshold value, it is considered as a corner. If we p ![image](images/shitomasi_space.png) From the figure, you can see that only when \f$\lambda_1\f$ and \f$\lambda_2\f$ are above a minimum value, -\f$\lambda_{min}\f$, it is conidered as a corner(green region). +\f$\lambda_{min}\f$, it is considered as a corner(green region). Code ---- diff --git a/doc/py_tutorials/py_imgproc/py_contours/py_contour_features/py_contour_features.markdown b/doc/py_tutorials/py_imgproc/py_contours/py_contour_features/py_contour_features.markdown index f018e111bb..ecd0e97af2 100644 --- a/doc/py_tutorials/py_imgproc/py_contours/py_contour_features/py_contour_features.markdown +++ b/doc/py_tutorials/py_imgproc/py_contours/py_contour_features/py_contour_features.markdown @@ -144,7 +144,7 @@ cv.rectangle(img,(x,y),(x+w,y+h),(0,255,0),2) ### 7.b. Rotated Rectangle Here, bounding rectangle is drawn with minimum area, so it considers the rotation also. The function -used is **cv.minAreaRect()**. It returns a Box2D structure which contains following detals - ( +used is **cv.minAreaRect()**. It returns a Box2D structure which contains following details - ( center (x,y), (width, height), angle of rotation ). But to draw this rectangle, we need 4 corners of the rectangle. It is obtained by the function **cv.boxPoints()** @code{.py} diff --git a/doc/py_tutorials/py_imgproc/py_contours/py_contours_hierarchy/py_contours_hierarchy.markdown b/doc/py_tutorials/py_imgproc/py_contours/py_contours_hierarchy/py_contours_hierarchy.markdown index 831754d212..2619ea2a70 100644 --- a/doc/py_tutorials/py_imgproc/py_contours/py_contours_hierarchy/py_contours_hierarchy.markdown +++ b/doc/py_tutorials/py_imgproc/py_contours/py_contours_hierarchy/py_contours_hierarchy.markdown @@ -185,7 +185,7 @@ array([[[ 3, -1, 1, -1], And this is the final guy, Mr.Perfect. It retrieves all the contours and creates a full family hierarchy list. **It even tells, who is the grandpa, father, son, grandson and even beyond... :)**. -For examle, I took above image, rewrite the code for cv.RETR_TREE, reorder the contours as per the +For example, I took above image, rewrite the code for cv.RETR_TREE, reorder the contours as per the result given by OpenCV and analyze it. Again, red letters give the contour number and green letters give the hierarchy order. 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 e05e6e11ac..f61fa7a8b4 100644 --- a/doc/tutorials/calib3d/real_time_pose/real_time_pose.markdown +++ b/doc/tutorials/calib3d/real_time_pose/real_time_pose.markdown @@ -381,7 +381,7 @@ Here is explained in detail the code for the real time application: as not, there are false correspondences or also called *outliers*. The [Random Sample Consensus](http://en.wikipedia.org/wiki/RANSAC) or *Ransac* is a non-deterministic iterative method which estimate parameters of a mathematical model from observed data producing an - approximate result as the number of iterations increase. After appyling *Ransac* all the *outliers* + approximate result as the number of iterations increase. After applying *Ransac* all the *outliers* will be eliminated to then estimate the camera pose with a certain probability to obtain a good solution. diff --git a/doc/tutorials/introduction/clojure_dev_intro/clojure_dev_intro.markdown b/doc/tutorials/introduction/clojure_dev_intro/clojure_dev_intro.markdown index 2cd8c74a07..1dd440cb47 100644 --- a/doc/tutorials/introduction/clojure_dev_intro/clojure_dev_intro.markdown +++ b/doc/tutorials/introduction/clojure_dev_intro/clojure_dev_intro.markdown @@ -499,7 +499,7 @@ using the following OpenCV methods: - the imwrite static method from the Highgui class to write an image to a file - the GaussianBlur static method from the Imgproc class to apply to blur the original image -We're also going to use the Mat class which is returned from the imread method and accpeted as the +We're also going to use the Mat class which is returned from the imread method and accepted as the main argument to both the GaussianBlur and the imwrite methods. ### Add an image to the project diff --git a/doc/tutorials/objdetect/cascade_classifier/cascade_classifier.markdown b/doc/tutorials/objdetect/cascade_classifier/cascade_classifier.markdown index 936b6c31b9..138f43bb8e 100644 --- a/doc/tutorials/objdetect/cascade_classifier/cascade_classifier.markdown +++ b/doc/tutorials/objdetect/cascade_classifier/cascade_classifier.markdown @@ -10,7 +10,7 @@ In this tutorial, - We will see the basics of face detection and eye detection using the Haar Feature-based Cascade Classifiers - We will use the @ref cv::CascadeClassifier class to detect objects in a video stream. Particularly, we will use the functions: - - @ref cv::CascadeClassifier::load to load a .xml classifier file. It can be either a Haar or a LBP classifer + - @ref cv::CascadeClassifier::load to load a .xml classifier file. It can be either a Haar or a LBP classifier - @ref cv::CascadeClassifier::detectMultiScale to perform the detection. Theory diff --git a/doc/tutorials/objdetect/traincascade.markdown b/doc/tutorials/objdetect/traincascade.markdown index 167e34fe60..2a0b1ae276 100644 --- a/doc/tutorials/objdetect/traincascade.markdown +++ b/doc/tutorials/objdetect/traincascade.markdown @@ -168,7 +168,7 @@ Command line arguments of opencv_traincascade application grouped by purposes: - `-w ` : Width of training samples (in pixels). Must have exactly the same value as used during training samples creation (opencv_createsamples utility). - `-h ` : Height of training samples (in pixels). Must have exactly the same value as used during training samples creation (opencv_createsamples utility). -- Boosted classifer parameters: +- Boosted classifier parameters: - `-bt <{DAB, RAB, LB, GAB(default)}>` : Type of boosted classifiers: DAB - Discrete AdaBoost, RAB - Real AdaBoost, LB - LogitBoost, GAB - Gentle AdaBoost. - `-minHitRate ` : Minimal desired hit rate for each stage of the classifier. Overall hit rate may be estimated as (min_hit_rate ^ number_of_stages), @cite Viola04 §4.1. - `-maxFalseAlarmRate ` : Maximal desired false alarm rate for each stage of the classifier. Overall false alarm rate may be estimated as (max_false_alarm_rate ^ number_of_stages), @cite Viola04 §4.1. diff --git a/doc/tutorials/videoio/kinect_openni.markdown b/doc/tutorials/videoio/kinect_openni.markdown index 32cc99533b..8e28286a92 100644 --- a/doc/tutorials/videoio/kinect_openni.markdown +++ b/doc/tutorials/videoio/kinect_openni.markdown @@ -43,7 +43,7 @@ VideoCapture can retrieve the following data: - CAP_OPENNI_POINT_CLOUD_MAP - XYZ in meters (CV_32FC3) - CAP_OPENNI_DISPARITY_MAP - disparity in pixels (CV_8UC1) - CAP_OPENNI_DISPARITY_MAP_32F - disparity in pixels (CV_32FC1) - - CAP_OPENNI_VALID_DEPTH_MASK - mask of valid pixels (not ocluded, not shaded etc.) + - CAP_OPENNI_VALID_DEPTH_MASK - mask of valid pixels (not occluded, not shaded etc.) (CV_8UC1) -# data given from BGR image generator: diff --git a/modules/calib3d/include/opencv2/calib3d.hpp b/modules/calib3d/include/opencv2/calib3d.hpp index f78902eed2..a2ee47f730 100644 --- a/modules/calib3d/include/opencv2/calib3d.hpp +++ b/modules/calib3d/include/opencv2/calib3d.hpp @@ -1218,7 +1218,7 @@ struct CV_EXPORTS_W_SIMPLE CirclesGridFinderParameters2 : public CirclesGridFind CV_WRAP CirclesGridFinderParameters2(); CV_PROP_RW float squareSize; //!< Distance between two adjacent points. Used by CALIB_CB_CLUSTERING. - CV_PROP_RW float maxRectifiedDistance; //!< Max deviation from predicion. Used by CALIB_CB_CLUSTERING. + CV_PROP_RW float maxRectifiedDistance; //!< Max deviation from prediction. Used by CALIB_CB_CLUSTERING. }; /** @brief Finds centers in the grid of circles. diff --git a/modules/calib3d/src/calibration.cpp b/modules/calib3d/src/calibration.cpp index 9c640540f7..ecf46d1f41 100644 --- a/modules/calib3d/src/calibration.cpp +++ b/modules/calib3d/src/calibration.cpp @@ -48,7 +48,7 @@ #include /* - This is stright-forward port v3 of Matlab calibration engine by Jean-Yves Bouguet + This is straight-forward port v3 of Matlab calibration engine by Jean-Yves Bouguet that is (in a large extent) based on the paper: Z. Zhang. "A flexible new technique for camera calibration". IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(11):1330-1334, 2000. diff --git a/modules/calib3d/test/test_chesscorners_badarg.cpp b/modules/calib3d/test/test_chesscorners_badarg.cpp index 422e364d46..2676a1bff1 100644 --- a/modules/calib3d/test/test_chesscorners_badarg.cpp +++ b/modules/calib3d/test/test_chesscorners_badarg.cpp @@ -115,7 +115,7 @@ void CV_ChessboardDetectorBadArgTest::run( int /*start_from */) img = cb.clone(); pattern_size = Size(2,2); - errors += run_test_case( CV_StsOutOfRange, "Invlid pattern size" ); + errors += run_test_case( CV_StsOutOfRange, "Invalid pattern size" ); pattern_size = cbg.cornersSize(); cb.convertTo(img, CV_32F); diff --git a/modules/core/include/opencv2/core/core_c.h b/modules/core/include/opencv2/core/core_c.h index fa8f1509a0..95a98cfcd0 100644 --- a/modules/core/include/opencv2/core/core_c.h +++ b/modules/core/include/opencv2/core/core_c.h @@ -1309,7 +1309,7 @@ CVAPI(void) cvMulTransposed( const CvArr* src, CvArr* dst, int order, const CvArr* delta CV_DEFAULT(NULL), double scale CV_DEFAULT(1.) ); -/** Tranposes matrix. Square matrices can be transposed in-place */ +/** Transposes matrix. Square matrices can be transposed in-place */ CVAPI(void) cvTranspose( const CvArr* src, CvArr* dst ); #define cvT cvTranspose diff --git a/modules/core/include/opencv2/core/hal/intrin_avx.hpp b/modules/core/include/opencv2/core/hal/intrin_avx.hpp index 6fc03b7274..ca315ae284 100644 --- a/modules/core/include/opencv2/core/hal/intrin_avx.hpp +++ b/modules/core/include/opencv2/core/hal/intrin_avx.hpp @@ -569,7 +569,7 @@ inline v_int64x4 v256_blend(const v_int64x4& a, const v_int64x4& b) { return v_int64x4(v256_blend(v_uint64x4(a.val), v_uint64x4(b.val)).val); } // shuffle -// todo: emluate 64bit +// todo: emulate 64bit #define OPENCV_HAL_IMPL_AVX_SHUFFLE(_Tpvec, intrin) \ template \ inline _Tpvec v256_shuffle(const _Tpvec& a) \ diff --git a/modules/core/include/opencv2/core/hal/intrin_cpp.hpp b/modules/core/include/opencv2/core/hal/intrin_cpp.hpp index 67d3155f00..15ae380e65 100644 --- a/modules/core/include/opencv2/core/hal/intrin_cpp.hpp +++ b/modules/core/include/opencv2/core/hal/intrin_cpp.hpp @@ -73,7 +73,7 @@ implemented as a structure based on a one SIMD register. - cv::v_uint8x16 and cv::v_int8x16: sixteen 8-bit integer values (unsigned/signed) - char - cv::v_uint16x8 and cv::v_int16x8: eight 16-bit integer values (unsigned/signed) - short -- cv::v_uint32x4 and cv::v_int32x4: four 32-bit integer values (unsgined/signed) - int +- cv::v_uint32x4 and cv::v_int32x4: four 32-bit integer values (unsigned/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 values (signed) - double diff --git a/modules/core/include/opencv2/core/hal/intrin_msa.hpp b/modules/core/include/opencv2/core/hal/intrin_msa.hpp index 0db137b032..76e6bed200 100755 --- a/modules/core/include/opencv2/core/hal/intrin_msa.hpp +++ b/modules/core/include/opencv2/core/hal/intrin_msa.hpp @@ -1805,7 +1805,7 @@ inline v_float32x4 v_broadcast_element(const v_float32x4& a) return v_setall_f32(v_extract_n(a)); } -////// FP16 suport /////// +////// FP16 support /////// #if CV_FP16 inline v_float32x4 v_load_expand(const float16_t* ptr) { diff --git a/modules/core/include/opencv2/core/hal/intrin_wasm.hpp b/modules/core/include/opencv2/core/hal/intrin_wasm.hpp index 7b3259f4c0..b8c250fcc2 100644 --- a/modules/core/include/opencv2/core/hal/intrin_wasm.hpp +++ b/modules/core/include/opencv2/core/hal/intrin_wasm.hpp @@ -94,7 +94,7 @@ struct v_uint16x8 } ushort get0() const { - return (ushort)wasm_i16x8_extract_lane(val, 0); // wasm_u16x8_extract_lane() unimplemeted yet + return (ushort)wasm_i16x8_extract_lane(val, 0); // wasm_u16x8_extract_lane() unimplemented yet } v128_t val; diff --git a/modules/core/include/opencv2/core/hal/msa_macros.h b/modules/core/include/opencv2/core/hal/msa_macros.h index 3ed6e58d3c..bd6ddb127a 100755 --- a/modules/core/include/opencv2/core/hal/msa_macros.h +++ b/modules/core/include/opencv2/core/hal/msa_macros.h @@ -50,7 +50,7 @@ typedef double v1f64 __attribute__ ((vector_size(8), aligned(8))); #define msa_ld1q_f32(__a) ((v4f32)__builtin_msa_ld_w(__a, 0)) #define msa_ld1q_f64(__a) ((v2f64)__builtin_msa_ld_d(__a, 0)) -/* Store 64bits vector elments values to the given memory address. */ +/* Store 64bits vector elements values to the given memory address. */ #define msa_st1_s8(__a, __b) (*((v8i8*)(__a)) = __b) #define msa_st1_s16(__a, __b) (*((v4i16*)(__a)) = __b) #define msa_st1_s32(__a, __b) (*((v2i32*)(__a)) = __b) @@ -377,7 +377,7 @@ typedef double v1f64 __attribute__ ((vector_size(8), aligned(8))); }) /* Right shift elements in a 128 bits vector by an immediate value, saturate the results and them in a 64 bits vector. - Input is signed and outpus is unsigned. */ + Input is signed and output is unsigned. */ #define msa_qrshrun_n_s16(__a, __b) \ ({ \ v8i16 __d = __builtin_msa_srlri_h(__builtin_msa_max_s_h(__builtin_msa_fill_h(0), (v8i16)(__a)), (int)(__b)); \ diff --git a/modules/core/include/opencv2/core/opencl/opencl_info.hpp b/modules/core/include/opencv2/core/opencl/opencl_info.hpp index 21b3672925..5e5c846ad0 100644 --- a/modules/core/include/opencv2/core/opencl/opencl_info.hpp +++ b/modules/core/include/opencv2/core/opencl/opencl_info.hpp @@ -62,7 +62,7 @@ static String getDeviceTypeString(const cv::ocl::Device& device) } } - return "unkown"; + return "unknown"; } } // namespace diff --git a/modules/core/include/opencv2/core/optim.hpp b/modules/core/include/opencv2/core/optim.hpp index 66e81ae741..5a0940037d 100644 --- a/modules/core/include/opencv2/core/optim.hpp +++ b/modules/core/include/opencv2/core/optim.hpp @@ -165,7 +165,7 @@ public: /** @brief Sets the initial step that will be used in downhill simplex algorithm. - Step, together with initial point (givin in DownhillSolver::minimize) are two `n`-dimensional + Step, together with initial point (given in DownhillSolver::minimize) are two `n`-dimensional vectors that are used to determine the shape of initial simplex. Roughly said, initial point determines the position of a simplex (it will become simplex's centroid), while step determines the spread (size in each dimension) of a simplex. To be more precise, if \f$s,x_0\in\mathbb{R}^n\f$ are diff --git a/modules/core/include/opencv2/core/vsx_utils.hpp b/modules/core/include/opencv2/core/vsx_utils.hpp index 91669bff31..d7c7140607 100644 --- a/modules/core/include/opencv2/core/vsx_utils.hpp +++ b/modules/core/include/opencv2/core/vsx_utils.hpp @@ -317,7 +317,7 @@ VSX_IMPL_1RG(vec_udword2, wi, vec_float4, wf, xvcvspuxds, vec_ctulo) * Also there's already an open bug https://bugs.llvm.org/show_bug.cgi?id=31837 * * So we're not able to use inline asm and only use built-in functions that CLANG supports - * and use __builtin_convertvector if clang missng any of vector conversions built-in functions + * and use __builtin_convertvector if clang missing any of vector conversions built-in functions * * todo: clang asm template bug is fixed, need to reconsider the current workarounds. */ @@ -491,7 +491,7 @@ VSX_IMPL_CONV_EVEN_2_4(vec_uint4, vec_double2, vec_ctu, vec_ctuo) // Only for Eigen! /* * changing behavior of conversion intrinsics for gcc has effect on Eigen - * so we redfine old behavior again only on gcc, clang + * so we redefine old behavior again only on gcc, clang */ #if !defined(__clang__) || __clang_major__ > 4 // ignoring second arg since Eigen only truncates toward zero diff --git a/modules/core/src/array.cpp b/modules/core/src/array.cpp index 4c0d3eb433..f2a79b5a69 100644 --- a/modules/core/src/array.cpp +++ b/modules/core/src/array.cpp @@ -250,7 +250,7 @@ cvInitMatNDHeader( CvMatND* mat, int dims, const int* sizes, for( int i = dims - 1; i >= 0; i-- ) { if( sizes[i] < 0 ) - CV_Error( CV_StsBadSize, "one of dimesion sizes is non-positive" ); + CV_Error( CV_StsBadSize, "one of dimension sizes is non-positive" ); mat->dim[i].size = sizes[i]; if( step > INT_MAX ) CV_Error( CV_StsOutOfRange, "The array is too big" ); @@ -545,7 +545,7 @@ cvCreateSparseMat( int dims, const int* sizes, int type ) for( i = 0; i < dims; i++ ) { if( sizes[i] <= 0 ) - CV_Error( CV_StsBadSize, "one of dimesion sizes is non-positive" ); + CV_Error( CV_StsBadSize, "one of dimension sizes is non-positive" ); } CvSparseMat* arr = (CvSparseMat*)cvAlloc(sizeof(*arr)+MAX(0,dims-CV_MAX_DIM)*sizeof(arr->size[0])); diff --git a/modules/core/src/convert_scale.simd.hpp b/modules/core/src/convert_scale.simd.hpp index 878e39329c..98703c16e9 100644 --- a/modules/core/src/convert_scale.simd.hpp +++ b/modules/core/src/convert_scale.simd.hpp @@ -53,7 +53,7 @@ cvtabs_32f( const _Ts* src, size_t sstep, _Td* dst, size_t dstep, } } -// variant for convrsions 16f <-> ... w/o unrolling +// variant for conversions 16f <-> ... w/o unrolling template inline void cvtabs1_32f( const _Ts* src, size_t sstep, _Td* dst, size_t dstep, Size size, float a, float b ) @@ -123,7 +123,7 @@ cvt_32f( const _Ts* src, size_t sstep, _Td* dst, size_t dstep, } } -// variant for convrsions 16f <-> ... w/o unrolling +// variant for conversions 16f <-> ... w/o unrolling template inline void cvt1_32f( const _Ts* src, size_t sstep, _Td* dst, size_t dstep, Size size, float a, float b ) diff --git a/modules/core/src/downhill_simplex.cpp b/modules/core/src/downhill_simplex.cpp index 15d6469465..5013d4c506 100644 --- a/modules/core/src/downhill_simplex.cpp +++ b/modules/core/src/downhill_simplex.cpp @@ -77,7 +77,7 @@ Replaced y(1,ndim,0.0) ------> y(1,ndim+1,0.0) *********************************************************************************************************************************** -The code below was used in tesing the source code. +The code below was used in testing the source code. Created by @SareeAlnaghy #include diff --git a/modules/core/src/system.cpp b/modules/core/src/system.cpp index 2ed05f12ee..3c0588c355 100644 --- a/modules/core/src/system.cpp +++ b/modules/core/src/system.cpp @@ -1592,7 +1592,7 @@ public: { TlsAbstraction* tls = getTlsAbstraction(); if (NULL == tls) - return; // TLS signleton is not available (terminated) + return; // TLS singleton is not available (terminated) ThreadData *pTD = tlsValue == NULL ? (ThreadData*)tls->getData() : (ThreadData*)tlsValue; if (pTD == NULL) return; // no OpenCV TLS data for this thread @@ -1683,7 +1683,7 @@ public: TlsAbstraction* tls = getTlsAbstraction(); if (NULL == tls) - return NULL; // TLS signleton is not available (terminated) + return NULL; // TLS singleton is not available (terminated) ThreadData* threadData = (ThreadData*)tls->getData(); if(threadData && threadData->slots.size() > slotIdx) @@ -1719,7 +1719,7 @@ public: TlsAbstraction* tls = getTlsAbstraction(); if (NULL == tls) - return; // TLS signleton is not available (terminated) + return; // TLS singleton is not available (terminated) ThreadData* threadData = (ThreadData*)tls->getData(); if(!threadData) diff --git a/modules/dnn/include/opencv2/dnn/all_layers.hpp b/modules/dnn/include/opencv2/dnn/all_layers.hpp index b251b4adb3..710de82539 100644 --- a/modules/dnn/include/opencv2/dnn/all_layers.hpp +++ b/modules/dnn/include/opencv2/dnn/all_layers.hpp @@ -134,7 +134,7 @@ CV__DNN_EXPERIMENTAL_NS_BEGIN virtual void setOutShape(const MatShape &outTailShape = MatShape()) = 0; /** @deprecated Use flag `produce_cell_output` in LayerParams. - * @brief Specifies either interpret first dimension of input blob as timestamp dimenion either as sample. + * @brief Specifies either interpret first dimension of input blob as timestamp dimension either as sample. * * 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. diff --git a/modules/dnn/src/ie_ngraph.cpp b/modules/dnn/src/ie_ngraph.cpp index 6b5c611c9a..2688428dc3 100644 --- a/modules/dnn/src/ie_ngraph.cpp +++ b/modules/dnn/src/ie_ngraph.cpp @@ -622,7 +622,7 @@ void InfEngineNgraphNet::forward(const std::vector >& outBlo 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"); } } } @@ -635,7 +635,7 @@ void InfEngineNgraphNet::forward(const std::vector >& outBlo 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"); } } } diff --git a/modules/dnn/src/onnx/opencv-onnx.proto b/modules/dnn/src/onnx/opencv-onnx.proto index b8b616a0d8..b24220adb9 100644 --- a/modules/dnn/src/onnx/opencv-onnx.proto +++ b/modules/dnn/src/onnx/opencv-onnx.proto @@ -116,7 +116,7 @@ message AttributeProto { // The type field MUST be present for this version of the IR. // For 0.0.1 versions of the IR, this field was not defined, and - // implementations needed to use has_field hueristics to determine + // implementations needed to use has_field heuristics 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 accommodate proto3 implementations. @@ -323,7 +323,7 @@ message TensorProto { // For float and complex64 values // Complex64 tensors are encoded as a single array of floats, // with the real components appearing in odd numbered positions, - // and the corresponding imaginary component apparing in the + // and the corresponding imaginary component appearing in the // subsequent even numbered position. (e.g., [1.0 + 2.0i, 3.0 + 4.0i] // is encoded as [1.0, 2.0 ,3.0 ,4.0] // When this field is present, the data_type field MUST be FLOAT or COMPLEX64. @@ -373,7 +373,7 @@ message TensorProto { // For double // Complex64 tensors are encoded as a single array of doubles, // with the real components appearing in odd numbered positions, - // and the corresponding imaginary component apparing in the + // and the corresponding imaginary component appearing in the // subsequent even numbered position. (e.g., [1.0 + 2.0i, 3.0 + 4.0i] // is encoded as [1.0, 2.0 ,3.0 ,4.0] // When this field is present, the data_type field MUST be DOUBLE or COMPLEX128 diff --git a/modules/features2d/include/opencv2/features2d.hpp b/modules/features2d/include/opencv2/features2d.hpp index 867e89e5af..217cfc0c26 100644 --- a/modules/features2d/include/opencv2/features2d.hpp +++ b/modules/features2d/include/opencv2/features2d.hpp @@ -385,7 +385,7 @@ code which is distributed under GPL. class CV_EXPORTS_W MSER : public Feature2D { public: - /** @brief Full consturctor for %MSER detector + /** @brief Full constructor for %MSER detector @param _delta it compares \f$(size_{i}-size_{i-delta})/size_{i-delta}\f$ @param _min_area prune the area which smaller than minArea diff --git a/modules/features2d/src/kaze/nldiffusion_functions.h b/modules/features2d/src/kaze/nldiffusion_functions.h index 97c36a2094..4254edc6a0 100644 --- a/modules/features2d/src/kaze/nldiffusion_functions.h +++ b/modules/features2d/src/kaze/nldiffusion_functions.h @@ -36,7 +36,7 @@ void image_derivatives_scharr(const cv::Mat& src, cv::Mat& dst, int xorder, int // Nonlinear diffusion filtering scalar step void nld_step_scalar(cv::Mat& Ld, const cv::Mat& c, cv::Mat& Lstep, float stepsize); -// For non-maxima suppresion +// For non-maxima suppression bool check_maximum_neighbourhood(const cv::Mat& img, int dsize, float value, int row, int col, bool same_img); // Image downsampling diff --git a/modules/features2d/src/mser.cpp b/modules/features2d/src/mser.cpp index 85187f7c81..a37b4ea482 100755 --- a/modules/features2d/src/mser.cpp +++ b/modules/features2d/src/mser.cpp @@ -983,7 +983,7 @@ extractMSER_8uC3( const Mat& src, double s = (double)(lr->size-lr->sizei)/(lr->dt-lr->di); if ( s < lr->s ) { - // skip the first one and check stablity + // skip the first one and check stability if ( i > lr->reinit+1 && MSCRStableCheck( lr, params ) ) { if ( lr->tmsr == NULL ) diff --git a/modules/flann/include/opencv2/flann/simplex_downhill.h b/modules/flann/include/opencv2/flann/simplex_downhill.h index 9fd84f488c..20b7e03c92 100644 --- a/modules/flann/include/opencv2/flann/simplex_downhill.h +++ b/modules/flann/include/opencv2/flann/simplex_downhill.h @@ -131,7 +131,7 @@ float optimizeSimplexDownhill(T* points, int n, F func, float* vals = NULL ) } if (val_r* src_contour, int count0, Point_* dst_contour, WRITE_PT( src_contour[count-1] ); // last stage: do final clean-up of the approximated contour - - // remove extra points on the [almost] stright lines. + // remove extra points on the [almost] straight lines. is_closed = is_closed0; count = new_count; pos = is_closed ? count - 1 : 0; diff --git a/modules/imgproc/src/shapedescr.cpp b/modules/imgproc/src/shapedescr.cpp index 8ba4b41424..a8c64d4789 100644 --- a/modules/imgproc/src/shapedescr.cpp +++ b/modules/imgproc/src/shapedescr.cpp @@ -776,7 +776,7 @@ cv::RotatedRect cv::fitEllipseDirect( InputArray _points ) namespace cv { -// Calculates bounding rectagnle of a point set or retrieves already calculated +// Calculates bounding rectangle of a point set or retrieves already calculated static Rect pointSetBoundingRect( const Mat& points ) { int npoints = points.checkVector(2); @@ -1392,7 +1392,7 @@ cvFitEllipse2( const CvArr* array ) return cvBox2D(cv::fitEllipse(points)); } -/* Calculates bounding rectagnle of a point set or retrieves already calculated */ +/* Calculates bounding rectangle of a point set or retrieves already calculated */ CV_IMPL CvRect cvBoundingRect( CvArr* array, int update ) { diff --git a/modules/imgproc/test/test_approxpoly.cpp b/modules/imgproc/test/test_approxpoly.cpp index 845d7bb4ea..81a9772bb1 100644 --- a/modules/imgproc/test/test_approxpoly.cpp +++ b/modules/imgproc/test/test_approxpoly.cpp @@ -325,7 +325,7 @@ void CV_ApproxPolyTest::run( int /*start_from*/ ) if( DstSeq == NULL ) { ts->printf( cvtest::TS::LOG, - "cvApproxPoly returned NULL for contour #%d, espilon = %g\n", i, Eps ); + "cvApproxPoly returned NULL for contour #%d, epsilon = %g\n", i, Eps ); code = cvtest::TS::FAIL_INVALID_OUTPUT; goto _exit_; } // if( DstSeq == NULL ) diff --git a/modules/imgproc/test/test_intersection.cpp b/modules/imgproc/test/test_intersection.cpp index 0e419c4702..93909b3a9e 100644 --- a/modules/imgproc/test/test_intersection.cpp +++ b/modules/imgproc/test/test_intersection.cpp @@ -60,7 +60,7 @@ namespace opencv_test { namespace { // 6 - partial intersection, rectangle on top of different size // 7 - full intersection, rectangle fully enclosed in the other // 8 - partial intersection, rectangle corner just touching. point contact -// 9 - partial intersetion. rectangle side by side, line contact +// 9 - partial intersection. rectangle side by side, line contact static void compare(const std::vector& test, const std::vector& target) { diff --git a/modules/java/android_sdk/CMakeLists.txt b/modules/java/android_sdk/CMakeLists.txt index e57b0394a3..2eb63e1dd6 100644 --- a/modules/java/android_sdk/CMakeLists.txt +++ b/modules/java/android_sdk/CMakeLists.txt @@ -40,7 +40,7 @@ foreach(file ${seed_project_files_rel}) endforeach() list(APPEND depends gen_opencv_java_source "${OPENCV_DEPHELPER}/gen_opencv_java_source") -ocv_copyfiles_add_target(${the_module}_android_source_copy JAVA_SRC_COPY "Copy Java(Andoid SDK) source files" ${depends}) +ocv_copyfiles_add_target(${the_module}_android_source_copy JAVA_SRC_COPY "Copy Java(Android SDK) source files" ${depends}) file(REMOVE "${OPENCV_DEPHELPER}/${the_module}_android_source_copy") # force rebuild after CMake run set(depends ${the_module}_android_source_copy "${OPENCV_DEPHELPER}/${the_module}_android_source_copy") diff --git a/modules/java/generator/android/java/org/opencv/android/CameraBridgeViewBase.java b/modules/java/generator/android/java/org/opencv/android/CameraBridgeViewBase.java index 681b7ab974..bc6f9423f1 100644 --- a/modules/java/generator/android/java/org/opencv/android/CameraBridgeViewBase.java +++ b/modules/java/generator/android/java/org/opencv/android/CameraBridgeViewBase.java @@ -232,7 +232,7 @@ public abstract class CameraBridgeViewBase extends SurfaceView implements Surfac /** * This method is provided for clients, so they can disable camera connection and stop - * the delivery of frames even though the surface view itself is not destroyed and still stays on the scren + * the delivery of frames even though the surface view itself is not destroyed and still stays on the screen */ public void disableView() { synchronized(mSyncObject) { diff --git a/modules/js/perf/README.md b/modules/js/perf/README.md index c851bd51dd..2389aab2c6 100644 --- a/modules/js/perf/README.md +++ b/modules/js/perf/README.md @@ -32,4 +32,4 @@ To run performance tests, please launch a local web server in /bin fo Navigate the web browser to the kernel page you want to test, like http://localhost:8080/perf/imgproc/cvtcolor.html. -You can input the paramater, and then click the `Run` button to run the specific case, or it will run all the cases. +You can input the parameter, and then click the `Run` button to run the specific case, or it will run all the cases. diff --git a/modules/ml/include/opencv2/ml.hpp b/modules/ml/include/opencv2/ml.hpp index 506fd3ebcb..adbd84682e 100644 --- a/modules/ml/include/opencv2/ml.hpp +++ b/modules/ml/include/opencv2/ml.hpp @@ -1679,7 +1679,7 @@ public: /** @brief This function returns the trained parameters arranged across rows. - For a two class classifcation problem, it returns a row matrix. It returns learnt parameters of + For a two class classification problem, it returns a row matrix. It returns learnt parameters of the Logistic Regression as a matrix of type CV_32F. */ CV_WRAP virtual Mat get_learnt_thetas() const = 0; diff --git a/modules/python/test/test_algorithm_rw.py b/modules/python/test/test_algorithm_rw.py index c925a99e7b..29351869be 100644 --- a/modules/python/test/test_algorithm_rw.py +++ b/modules/python/test/test_algorithm_rw.py @@ -1,5 +1,5 @@ #!/usr/bin/env python -"""Algorithm serializaion test.""" +"""Algorithm serialization test.""" import tempfile import os import cv2 as cv diff --git a/modules/python/test/test_persistence.py b/modules/python/test/test_persistence.py index dcfce6e975..f15f521e3f 100644 --- a/modules/python/test/test_persistence.py +++ b/modules/python/test/test_persistence.py @@ -1,5 +1,5 @@ #!/usr/bin/env python -""""Core serializaion tests.""" +""""Core serialization tests.""" import tempfile import os import cv2 as cv diff --git a/modules/stitching/include/opencv2/stitching/detail/matchers.hpp b/modules/stitching/include/opencv2/stitching/detail/matchers.hpp index 25c0f2ab1e..560af28dc0 100644 --- a/modules/stitching/include/opencv2/stitching/detail/matchers.hpp +++ b/modules/stitching/include/opencv2/stitching/detail/matchers.hpp @@ -332,14 +332,14 @@ finds two best matches for each feature and leaves the best one only if the ratio between descriptor distances is greater than the threshold match_conf. Unlike cv::detail::BestOf2NearestMatcher this matcher uses affine -transformation (affine trasformation estimate will be placed in matches_info). +transformation (affine transformation estimate will be placed in matches_info). @sa cv::detail::FeaturesMatcher cv::detail::BestOf2NearestMatcher */ class CV_EXPORTS AffineBestOf2NearestMatcher : public BestOf2NearestMatcher { public: - /** @brief Constructs a "best of 2 nearest" matcher that expects affine trasformation + /** @brief Constructs a "best of 2 nearest" matcher that expects affine transformation between images @param full_affine whether to use full affine transformation with 6 degress of freedom or reduced diff --git a/modules/ts/include/opencv2/ts/ts_gtest.h b/modules/ts/include/opencv2/ts/ts_gtest.h index cd62024d58..0cffe61fea 100644 --- a/modules/ts/include/opencv2/ts/ts_gtest.h +++ b/modules/ts/include/opencv2/ts/ts_gtest.h @@ -11367,7 +11367,7 @@ void UniversalTersePrint(const T& value, ::std::ostream* os) { // NUL-terminated string. template void UniversalPrint(const T& value, ::std::ostream* os) { - // A workarond for the bug in VC++ 7.1 that prevents us from instantiating + // A workaround for the bug in VC++ 7.1 that prevents us from instantiating // UniversalPrinter with T directly. typedef T T1; UniversalPrinter::Print(value, os); diff --git a/modules/ts/misc/run_android.py b/modules/ts/misc/run_android.py index 84f2907288..4aa2b0dd78 100644 --- a/modules/ts/misc/run_android.py +++ b/modules/ts/misc/run_android.py @@ -94,11 +94,11 @@ class Aapt(Tool): # get test instrumentation info instrumentation_tag = [t for t in tags if t.startswith("instrumentation ")] if not instrumentation_tag: - raise Err("Can not find instrumentation detials in: %s", exe) + raise Err("Can not find instrumentation details in: %s", exe) res.pkg_runner = re.search(r"^[ ]+A: android:name\(0x[0-9a-f]{8}\)=\"(?P.*?)\" \(Raw: \"(?P=runner)\"\)\r?$", instrumentation_tag[0], flags=re.MULTILINE).group("runner") res.pkg_target = re.search(r"^[ ]+A: android:targetPackage\(0x[0-9a-f]{8}\)=\"(?P.*?)\" \(Raw: \"(?P=pkg)\"\)\r?$", instrumentation_tag[0], flags=re.MULTILINE).group("pkg") if not res.pkg_name or not res.pkg_runner or not res.pkg_target: - raise Err("Can not find instrumentation detials in: %s", exe) + raise Err("Can not find instrumentation details in: %s", exe) return res diff --git a/modules/ts/src/ts.cpp b/modules/ts/src/ts.cpp index 406ee1f3be..99f684d054 100644 --- a/modules/ts/src/ts.cpp +++ b/modules/ts/src/ts.cpp @@ -452,7 +452,7 @@ int BadArgTest::run_test_case( int expected_code, const string& _descr ) { thrown = true; if (e.code != expected_code && - e.code != cv::Error::StsError && e.code != cv::Error::StsAssert // Exact error codes support will be dropped. Checks should provide proper text messages intead. + e.code != cv::Error::StsError && e.code != cv::Error::StsAssert // Exact error codes support will be dropped. Checks should provide proper text messages instead. ) { ts->printf(TS::LOG, "%s (test case #%d): the error code %d is different from the expected %d\n", diff --git a/modules/video/src/bgfg_KNN.cpp b/modules/video/src/bgfg_KNN.cpp index 39cd6457e9..1ddf1b7d51 100755 --- a/modules/video/src/bgfg_KNN.cpp +++ b/modules/video/src/bgfg_KNN.cpp @@ -110,7 +110,7 @@ public: //set parameters // N - the number of samples stored in memory per model nN = defaultNsamples; - //kNN - k nearest neighbour - number on NN for detcting background - default K=[0.1*nN] + //kNN - k nearest neighbour - number on NN for detecting background - default K=[0.1*nN] nkNN=MAX(1,cvRound(0.1*nN*3+0.40)); //Tb - Threshold Tb*kernelwidth @@ -292,7 +292,7 @@ protected: //less important parameters - things you might change but be careful //////////////////////// int nN;//totlal number of samples - int nkNN;//number on NN for detcting background - default K=[0.1*nN] + int nkNN;//number on NN for detecting background - default K=[0.1*nN] //shadow detection parameters bool bShadowDetection;//default 1 - do shadow detection diff --git a/modules/video/src/bgfg_gaussmix2.cpp b/modules/video/src/bgfg_gaussmix2.cpp index 4241670f1c..69e4baf657 100644 --- a/modules/video/src/bgfg_gaussmix2.cpp +++ b/modules/video/src/bgfg_gaussmix2.cpp @@ -181,7 +181,7 @@ public: //! computes a background image which are the mean of all background gaussians virtual void getBackgroundImage(OutputArray backgroundImage) const CV_OVERRIDE; - //! re-initiaization method + //! re-initialization method void initialize(Size _frameSize, int _frameType) { frameSize = _frameSize; diff --git a/modules/videoio/include/opencv2/videoio/videoio_c.h b/modules/videoio/include/opencv2/videoio/videoio_c.h index 32f6ec7eaf..5167c77ace 100644 --- a/modules/videoio/include/opencv2/videoio/videoio_c.h +++ b/modules/videoio/include/opencv2/videoio/videoio_c.h @@ -319,8 +319,8 @@ enum CV_CAP_PROP_XI_COOLING = 466, // Start camera cooling. CV_CAP_PROP_XI_TARGET_TEMP = 467, // Set sensor target temperature for cooling. CV_CAP_PROP_XI_CHIP_TEMP = 468, // Camera sensor temperature - CV_CAP_PROP_XI_HOUS_TEMP = 469, // Camera housing tepmerature - CV_CAP_PROP_XI_HOUS_BACK_SIDE_TEMP = 590, // Camera housing back side tepmerature + CV_CAP_PROP_XI_HOUS_TEMP = 469, // Camera housing temperature + CV_CAP_PROP_XI_HOUS_BACK_SIDE_TEMP = 590, // Camera housing back side temperature CV_CAP_PROP_XI_SENSOR_BOARD_TEMP = 596, // Camera sensor board temperature CV_CAP_PROP_XI_CMS = 470, // Mode of color management system. CV_CAP_PROP_XI_APPLY_CMS = 471, // Enable applying of CMS profiles to xiGetImage (see XI_PRM_INPUT_CMS_PROFILE, XI_PRM_OUTPUT_CMS_PROFILE). diff --git a/modules/videoio/src/cap_aravis.cpp b/modules/videoio/src/cap_aravis.cpp index ef291b5905..b406adbb83 100644 --- a/modules/videoio/src/cap_aravis.cpp +++ b/modules/videoio/src/cap_aravis.cpp @@ -299,7 +299,7 @@ bool CvCaptureCAM_Aravis::grabFrame() size_t buffer_size; framebuffer = (void*)arv_buffer_get_data (arv_buffer, &buffer_size); - // retrieve image size properites + // retrieve image size properties arv_buffer_get_image_region (arv_buffer, &xoffset, &yoffset, &width, &height); // retrieve image ID set by camera diff --git a/modules/videoio/src/cap_avfoundation.mm b/modules/videoio/src/cap_avfoundation.mm index 4a27f6673a..2547a46966 100644 --- a/modules/videoio/src/cap_avfoundation.mm +++ b/modules/videoio/src/cap_avfoundation.mm @@ -1293,7 +1293,7 @@ bool CvVideoWriter_AVFoundation::writeFrame(const IplImage* iplimage) { colorSpace, kCGImageAlphaLast|kCGBitmapByteOrderDefault, provider, NULL, false, kCGRenderingIntentDefault); - //CGImage -> CVPixelBufferRef coversion + //CGImage -> CVPixelBufferRef conversion CVPixelBufferRef pixelBuffer = NULL; CFDataRef cfData = CGDataProviderCopyData(CGImageGetDataProvider(cgImage)); int status = CVPixelBufferCreateWithBytes(NULL, diff --git a/modules/videoio/src/cap_avfoundation_mac.mm b/modules/videoio/src/cap_avfoundation_mac.mm index 75af8a0090..6a52727d27 100644 --- a/modules/videoio/src/cap_avfoundation_mac.mm +++ b/modules/videoio/src/cap_avfoundation_mac.mm @@ -805,7 +805,7 @@ bool CvCaptureFile::setupReadingAt(CMTime position) { if (mMode == CV_CAP_MODE_BGR || mMode == CV_CAP_MODE_RGB) { // For CV_CAP_MODE_BGR, read frames as BGRA (AV Foundation's YUV->RGB conversion is slightly faster than OpenCV's CV_YUV2BGR_YV12) // kCVPixelFormatType_32ABGR is reportedly faster on OS X, but OpenCV doesn't have a CV_ABGR2BGR conversion. - // kCVPixelFormatType_24RGB is significanly slower than kCVPixelFormatType_32BGRA. + // kCVPixelFormatType_24RGB is significantly slower than kCVPixelFormatType_32BGRA. pixelFormat = kCVPixelFormatType_32BGRA; mFormat = CV_8UC3; } else if (mMode == CV_CAP_MODE_GRAY) { @@ -1323,7 +1323,7 @@ bool CvVideoWriter_AVFoundation::writeFrame(const IplImage* iplimage) { colorSpace, kCGImageAlphaLast|kCGBitmapByteOrderDefault, provider, NULL, false, kCGRenderingIntentDefault); - //CGImage -> CVPixelBufferRef coversion + //CGImage -> CVPixelBufferRef conversion CVPixelBufferRef pixelBuffer = NULL; CFDataRef cfData = CGDataProviderCopyData(CGImageGetDataProvider(cgImage)); int status = CVPixelBufferCreateWithBytes(NULL, diff --git a/modules/videoio/src/cap_gstreamer.cpp b/modules/videoio/src/cap_gstreamer.cpp index f0a4f8eddb..5821fb0180 100644 --- a/modules/videoio/src/cap_gstreamer.cpp +++ b/modules/videoio/src/cap_gstreamer.cpp @@ -1045,7 +1045,7 @@ bool GStreamerCapture::open(const String &filename_) * \return property value * * There are two ways the properties can be retrieved. For seek-based properties we can query the pipeline. - * For frame-based properties, we use the caps of the lasst receivef sample. This means that some properties + * For frame-based properties, we use the caps of the last receivef sample. This means that some properties * are not available until a first frame was received */ double GStreamerCapture::getProperty(int propId) const diff --git a/platforms/ios/cmake/Modules/Platform/iOS.cmake b/platforms/ios/cmake/Modules/Platform/iOS.cmake index 5e2bbc5672..207f41f455 100644 --- a/platforms/ios/cmake/Modules/Platform/iOS.cmake +++ b/platforms/ios/cmake/Modules/Platform/iOS.cmake @@ -46,7 +46,7 @@ if (APPLE_FRAMEWORK AND BUILD_SHARED_LIBS) set (CMAKE_INSTALL_NAME_DIR "@rpath") endif() -# Hidden visibilty is required for cxx on iOS +# Hidden visibility is required for cxx on iOS set (no_warn "-Wno-unused-function -Wno-overloaded-virtual") set (CMAKE_C_FLAGS "${CMAKE_C_FLAGS} ${no_warn}") set (CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -stdlib=libc++ -fvisibility=hidden -fvisibility-inlines-hidden ${no_warn}") diff --git a/platforms/linux/mips.toolchain.cmake b/platforms/linux/mips.toolchain.cmake index 425d5dfcf9..b6b4609050 100755 --- a/platforms/linux/mips.toolchain.cmake +++ b/platforms/linux/mips.toolchain.cmake @@ -4,7 +4,7 @@ # Toolchains with 'img' in the name are for MIPS R6 instruction sets. # It is recommended to use cmake-gui application for build scripts configuration and generation: # 1. Run cmake-gui -# 2. Specifiy toolchain file for cross-compiling, mips32r5el-gnu.toolchian.cmake or mips64r6el-gnu.toolchain.cmake +# 2. Specify toolchain file for cross-compiling, mips32r5el-gnu.toolchian.cmake or mips64r6el-gnu.toolchain.cmake # can be selected. # 3. Configure and Generate makefiles. # 4. make -j4 & make install diff --git a/platforms/linux/mips32r5el-gnu.toolchain.cmake b/platforms/linux/mips32r5el-gnu.toolchain.cmake index 1937270f82..d93d4f2c94 100755 --- a/platforms/linux/mips32r5el-gnu.toolchain.cmake +++ b/platforms/linux/mips32r5el-gnu.toolchain.cmake @@ -4,7 +4,7 @@ # Toolchains with 'img' in the name are for MIPS R6 instruction sets. # It is recommended to use cmake-gui for build scripts configuration and generation: # 1. Run cmake-gui -# 2. Specifiy toolchain file mips32r5el-gnu.toolchian.cmake for cross-compiling. +# 2. Specify toolchain file mips32r5el-gnu.toolchian.cmake for cross-compiling. # 3. Configure and Generate makefiles. # 4. make -j4 & make install # ---------------------------------------------------------------------------------------------- diff --git a/platforms/linux/mips64r6el-gnu.toolchain.cmake b/platforms/linux/mips64r6el-gnu.toolchain.cmake index b022240a72..ce63668665 100755 --- a/platforms/linux/mips64r6el-gnu.toolchain.cmake +++ b/platforms/linux/mips64r6el-gnu.toolchain.cmake @@ -4,7 +4,7 @@ # Toolchains with 'img' in the name are for MIPS R6 instruction sets. # It is recommended to use cmake-gui for build scripts configuration and generation: # 1. Run cmake-gui -# 2. Specifiy toolchain file mips64r6el-gnu.toolchain.cmake for cross-compiling. +# 2. Specify toolchain file mips64r6el-gnu.toolchain.cmake for cross-compiling. # 3. Configure and Generate makefiles. # 4. make -j4 & make install # ---------------------------------------------------------------------------------------------- diff --git a/samples/cpp/CMakeLists.txt b/samples/cpp/CMakeLists.txt index ad251748c4..db16785dcc 100644 --- a/samples/cpp/CMakeLists.txt +++ b/samples/cpp/CMakeLists.txt @@ -58,7 +58,7 @@ foreach(sample_filename ${cpp_samples}) target_compile_definitions(${tgt} PRIVATE HAVE_OPENGL) endif() if(sample_filename MATCHES "simd_") - # disabled intentionally - demonstation purposes only + # disabled intentionally - demonstration purposes only #target_include_directories(${tgt} PRIVATE "${CMAKE_CURRENT_LIST_DIR}") #target_compile_definitions(${tgt} PRIVATE OPENCV_SIMD_CONFIG_HEADER=opencv_simd_config_custom.hpp) #target_compile_definitions(${tgt} PRIVATE OPENCV_SIMD_CONFIG_INCLUDE_DIR=1) diff --git a/samples/cpp/delaunay2.cpp b/samples/cpp/delaunay2.cpp index 925477b4a0..26f10bd668 100644 --- a/samples/cpp/delaunay2.cpp +++ b/samples/cpp/delaunay2.cpp @@ -12,7 +12,7 @@ static void help() "It draws a random set of points in an image and then delaunay triangulates them.\n" "Usage: \n" "./delaunay \n" - "\nThis program builds the traingulation interactively, you may stop this process by\n" + "\nThis program builds the triangulation interactively, you may stop this process by\n" "hitting any key.\n"; } diff --git a/samples/cpp/logistic_regression.cpp b/samples/cpp/logistic_regression.cpp index 365b32e523..4338b61f7b 100644 --- a/samples/cpp/logistic_regression.cpp +++ b/samples/cpp/logistic_regression.cpp @@ -157,7 +157,7 @@ int main() cout << responses.t() << endl; cout << "accuracy: " << calculateAccuracyPercent(labels_test, responses) << "%" << endl; - // save the classfier + // save the classifier const String saveFilename = "NewLR_Trained.xml"; cout << "saving the classifier to " << saveFilename << endl; lr1->save(saveFilename); @@ -167,7 +167,7 @@ int main() Ptr lr2 = StatModel::load(saveFilename); // predict using loaded classifier - cout << "predicting the dataset using the loaded classfier..."; + cout << "predicting the dataset using the loaded classifier..."; Mat responses2; lr2->predict(data_test, responses2); cout << "done!" << endl; diff --git a/samples/cpp/pca.cpp b/samples/cpp/pca.cpp index ba42700f18..a5a1c54a92 100644 --- a/samples/cpp/pca.cpp +++ b/samples/cpp/pca.cpp @@ -10,7 +10,7 @@ * This program demonstrates how to use OpenCV PCA with a * specified amount of variance to retain. The effect * is illustrated further by using a trackbar to -* change the value for retained varaince. +* change the value for retained variance. * * The program takes as input a text file with each line * begin the full path to an image. PCA will be performed diff --git a/samples/cpp/tutorial_code/calib3d/real_time_pose_estimation/src/Model.h b/samples/cpp/tutorial_code/calib3d/real_time_pose_estimation/src/Model.h index 7380af5d0e..92f004d4d9 100644 --- a/samples/cpp/tutorial_code/calib3d/real_time_pose_estimation/src/Model.h +++ b/samples/cpp/tutorial_code/calib3d/real_time_pose_estimation/src/Model.h @@ -36,7 +36,7 @@ public: void load(const std::string &path); private: - /** The current number of correspondecnes */ + /** The current number of correspondences */ int n_correspondences_; /** The list of 2D points on the model surface */ std::vector list_keypoints_; diff --git a/samples/cpp/videocapture_openni.cpp b/samples/cpp/videocapture_openni.cpp index e8a87193e1..0b67d92f61 100644 --- a/samples/cpp/videocapture_openni.cpp +++ b/samples/cpp/videocapture_openni.cpp @@ -17,7 +17,7 @@ static void help() " CAP_OPENNI_POINT_CLOUD_MAP - XYZ in meters (CV_32FC3)\n" " CAP_OPENNI_DISPARITY_MAP - disparity in pixels (CV_8UC1)\n" " CAP_OPENNI_DISPARITY_MAP_32F - disparity in pixels (CV_32FC1)\n" - " CAP_OPENNI_VALID_DEPTH_MASK - mask of valid pixels (not ocluded, not shaded etc.) (CV_8UC1)\n" + " CAP_OPENNI_VALID_DEPTH_MASK - mask of valid pixels (not occluded, not shaded etc.) (CV_8UC1)\n" "2.) Data given from RGB image generator\n" " CAP_OPENNI_BGR_IMAGE - color image (CV_8UC3)\n" " CAP_OPENNI_GRAY_IMAGE - gray image (CV_8UC1)\n" diff --git a/samples/opencl/opencl-opencv-interop.cpp b/samples/opencl/opencl-opencv-interop.cpp index f648f78bf8..e889623463 100644 --- a/samples/opencl/opencl-opencv-interop.cpp +++ b/samples/opencl/opencl-opencv-interop.cpp @@ -3,7 +3,7 @@ // This will loop through frames of video either from input media file // or camera device and do processing of these data in OpenCL and then // in OpenCV. In OpenCL it does inversion of pixels in left half of frame and -// in OpenCV it does bluring in the right half of frame. +// in OpenCV it does blurring in the right half of frame. */ #include #include diff --git a/samples/python/deconvolution.py b/samples/python/deconvolution.py index bf136c522f..b276ca8cfb 100755 --- a/samples/python/deconvolution.py +++ b/samples/python/deconvolution.py @@ -15,7 +15,7 @@ Usage: Use sliders to adjust PSF paramitiers. Keys: - SPACE - switch btw linear/cirular PSF + SPACE - switch btw linear/circular PSF ESC - exit Examples: diff --git a/samples/winrt/ImageManipulations/Constants.cpp b/samples/winrt/ImageManipulations/Constants.cpp index a26634272b..c819b76809 100644 --- a/samples/winrt/ImageManipulations/Constants.cpp +++ b/samples/winrt/ImageManipulations/Constants.cpp @@ -17,6 +17,6 @@ using namespace SDKSample; Platform::Array^ MainPage::scenariosInner = ref new Platform::Array { // The format here is the following: - // { "Description for the sample", "Fully quaified name for the class that implements the scenario" } + // { "Description for the sample", "Fully qualified name for the class that implements the scenario" } { "Enumerate cameras and add a video effect", "SDKSample.MediaCapture.AdvancedCapture" }, };