opencv

mirror of https://github.com/opencv/opencv.git synced 2025-01-11 23:18:11 +08:00

Author	SHA1	Message	Date
Brad Smith	34a871c855	Fix building on OpenBSD X86	2024-01-06 01:41:02 -05:00
Maksim Shabunin	adde942e34	OCL: fix incompatibility with Mali ruintime	2023-12-21 00:30:44 +03:00
Alexander Smorkalov	408730b7ab	Merge pull request #24618 from vrabaud:compilation Fix compilation on some 32-bit windows	2023-12-01 09:10:30 +03:00
Vincent Rabaud	0812659e92	Fix compilation on some 32-bit windows I do not have more info on the platform as it is internal. Without this fix, the error is: core/src/arithm.simd.hpp:868:1: error: too few arguments provided to function-like macro invocation 868 \| DEFINE_SIMD_ALL(cmp) \| ^ ./third_party/OpenCV/public/modules/./core/src/arithm.simd.hpp:93:5: note: expanded from macro 'DEFINE_SIMD_ALL' 93 \| DEFINE_SIMD_NSAT(fun, __VA_ARGS__) \| ^ ./third_party/OpenCV/public/modules/./core/src/arithm.simd.hpp:89:5: note: expanded from macro 'DEFINE_SIMD_NSAT' 89 \| DEFINE_SIMD_F64(fun, __VA_ARGS__) \| ^ ./third_party/OpenCV/public/modules/./core/src/arithm.simd.hpp:77:9: note: expanded from macro 'DEFINE_SIMD_F64' 77 \| DEFINE_NOSIMD(__CV_CAT(fun, 64f), double, __VA_ARGS__) \| ^ ./third_party/OpenCV/public/modules/./core/src/arithm.simd.hpp:47:56: note: expanded from macro 'DEFINE_NOSIMD' 47 \| DEFINE_NOSIMD_FUN(fun_name, c_type, __VA_ARGS__) \| ^ ./third_party/OpenCV/public/modules/./core/src/arithm.simd.hpp:860:9: note: macro 'DEFINE_NOSIMD_FUN' defined here 860 \| #define DEFINE_NOSIMD_FUN(fun, _T1, _Tvec, ...) \	2023-11-29 16:27:11 +01:00
Hao Chen	c19adb4953	Change the lsx to baseline features. This patch change lsx to baseline feature, and lasx to dispatch feature. Additionally, the runtime detection methods for lasx and lsx have been modified.	2023-11-21 11:51:22 +08:00
Rostislav Vasilikhin	ea47cb3ffe	Merge pull request #24480 from savuor:backport_patch_nans Backport to 4.x: patchNaNs() SIMD acceleration #24480 backport from #23098 connected PR in extra: [#1118@extra](https://github.com/opencv/opencv_extra/pull/1118) ### This PR contains: * new SIMD code for `patchNaNs()` * CPU perf test <details> <summary>Performance comparison</summary> Geometric mean (ms) \|Name of Test\|noopt\|sse2\|avx2\|sse2 vs noopt (x-factor)\|avx2 vs noopt (x-factor)\| \|---\|:-:\|:-:\|:-:\|:-:\|:-:\| \|PatchNaNs::OCL_PatchNaNsFixture::(640x480, 32FC1)\|0.019\|0.017\|0.018\|1.11\|1.07\| \|PatchNaNs::OCL_PatchNaNsFixture::(640x480, 32FC4)\|0.037\|0.037\|0.033\|1.00\|1.10\| \|PatchNaNs::OCL_PatchNaNsFixture::(1280x720, 32FC1)\|0.032\|0.032\|0.033\|0.99\|0.98\| \|PatchNaNs::OCL_PatchNaNsFixture::(1280x720, 32FC4)\|0.072\|0.072\|0.070\|1.00\|1.03\| \|PatchNaNs::OCL_PatchNaNsFixture::(1920x1080, 32FC1)\|0.051\|0.051\|0.050\|1.00\|1.01\| \|PatchNaNs::OCL_PatchNaNsFixture::(1920x1080, 32FC4)\|0.137\|0.138\|0.128\|0.99\|1.06\| \|PatchNaNs::OCL_PatchNaNsFixture::(3840x2160, 32FC1)\|0.137\|0.128\|0.129\|1.07\|1.06\| \|PatchNaNs::OCL_PatchNaNsFixture::(3840x2160, 32FC4)\|0.450\|0.450\|0.448\|1.00\|1.01\| \|PatchNaNs::PatchNaNsFixture::(640x480, 32FC1)\|0.149\|0.029\|0.020\|5.13\|7.44\| \|PatchNaNs::PatchNaNsFixture::(640x480, 32FC2)\|0.304\|0.058\|0.040\|5.25\|7.65\| \|PatchNaNs::PatchNaNsFixture::(640x480, 32FC3)\|0.448\|0.086\|0.059\|5.22\|7.55\| \|PatchNaNs::PatchNaNsFixture::(640x480, 32FC4)\|0.601\|0.133\|0.083\|4.51\|7.23\| \|PatchNaNs::PatchNaNsFixture::(1280x720, 32FC1)\|0.451\|0.093\|0.060\|4.83\|7.52\| \|PatchNaNs::PatchNaNsFixture::(1280x720, 32FC2)\|0.892\|0.184\|0.126\|4.85\|7.06\| \|PatchNaNs::PatchNaNsFixture::(1280x720, 32FC3)\|1.345\|0.311\|0.230\|4.32\|5.84\| \|PatchNaNs::PatchNaNsFixture::(1280x720, 32FC4)\|1.831\|0.546\|0.436\|3.35\|4.20\| \|PatchNaNs::PatchNaNsFixture::(1920x1080, 32FC1)\|1.017\|0.250\|0.160\|4.06\|6.35\| \|PatchNaNs::PatchNaNsFixture::(1920x1080, 32FC2)\|2.077\|0.646\|0.605\|3.21\|3.43\| \|PatchNaNs::PatchNaNsFixture::(1920x1080, 32FC3)\|3.134\|1.053\|0.961\|2.97\|3.26\| \|PatchNaNs::PatchNaNsFixture::(1920x1080, 32FC4)\|4.222\|1.436\|1.288\|2.94\|3.28\| \|PatchNaNs::PatchNaNsFixture::(3840x2160, 32FC1)\|4.225\|1.401\|1.277\|3.01\|3.31\| \|PatchNaNs::PatchNaNsFixture::(3840x2160, 32FC2)\|8.310\|2.953\|2.635\|2.81\|3.15\| \|PatchNaNs::PatchNaNsFixture::(3840x2160, 32FC3)\|12.396\|4.455\|4.252\|2.78\|2.92\| \|PatchNaNs::PatchNaNsFixture::(3840x2160, 32FC4)\|17.174\|5.831\|5.824\|2.95\|2.95\| </details> ### Pull Request Readiness Checklist See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [x] I agree to contribute to the project under Apache 2 License. - [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [x] The PR is proposed to the proper branch - [x] There is a reference to the original bug report and related work - [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [x] The feature is well documented and sample code can be built with the project CMake	2023-11-03 08:58:07 +03:00
CNClareChen	d142a796d8	Merge pull request #23929 from CNClareChen:4.x * Optimize some function with lasx. Optimize some function with lasx. #23929 This patch optimizes some lasx functions and reduces the runtime of opencv_test_core from 662,238ms to 633603ms on the 3A5000 platform. ### Pull Request Readiness Checklist See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [x] I agree to contribute to the project under Apache 2 License. - [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [x] The PR is proposed to the proper branch - [x] There is a reference to the original bug report and related work - [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [x] The feature is well documented and sample code can be built with the project CMake	2023-10-20 14:20:09 +03:00
Alexander Smorkalov	1c0ca41b6e	Merge pull request #24371 from hanliutong:clean-up Clean up the obsolete API of Universal Intrinsic	2023-10-20 12:50:26 +03:00
Vadim Pisarevsky	ba4d6c859d	added detection & dispatching of some modern NEON instructions (NEON_FP16, NEON_BF16) (#24420 ) * added more or less cross-platform (based on POSIX signal() semantics) method to detect various NEON extensions, such as FP16 SIMD arithmetics, BF16 SIMD arithmetics, SIMD dotprod etc. It could be propagated to other instruction sets if necessary. * hopefully fixed compile errors * continue to fix CI * another attempt to fix build on Linux aarch64 * * reverted to the original method to detect special arm neon instructions without signal() * renamed FP16_SIMD & BF16_SIMD to NEON_FP16 and NEON_BF16, respectively * removed extra whitespaces	2023-10-18 22:06:20 +03:00
Liutong HAN	a287605c3e	Clean up the Universal Intrinsic API.	2023-10-13 19:23:30 +08:00
Sean McBride	5fb3869775	Merge pull request #23109 from seanm:misc-warnings * Fixed clang -Wnewline-eof warnings * Fixed all trivial clang -Wextra-semi and -Wc++98-compat-extra-semi warnings * Removed trailing semi from various macros * Fixed various -Wunused-macros warnings * Fixed some trivial -Wdocumentation warnings * Fixed some -Wdocumentation-deprecated-sync warnings * Fixed incorrect indentation * Suppressed some clang warnings in 3rd party code * Fixed QRCodeEncoder::Params documentation. --------- Co-authored-by: Alexander Smorkalov <alexander.smorkalov@xperience.ai>	2023-10-06 13:33:21 +03:00
jvuillaumier	24fd39538e	Merge pull request #24233 from jvuillaumier:rotate_flip_hal_hooks Add HAL implementation hooks to cv::flip() and cv::rotate() functions from core module #24233 Hello, This change proposes the addition of HAL hooks for cv::flip() and cv::rotate() functions from OpenCV core module. Flip and rotation are functions commonly available from 2D hardware accelerators. This is convenient provision to enable custom optimized implementation of image flip/rotation on systems embedding such accelerator. Thank you ### Pull Request Readiness Checklist See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [x] I agree to contribute to the project under Apache 2 License. - [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [x] The PR is proposed to the proper branch - [ ] There is a reference to the original bug report and related work - [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [ ] The feature is well documented and sample code can be built with the project CMake	2023-10-06 12:31:53 +03:00
HAN Liutong	07bf9cb013	Merge pull request #24325 from hanliutong:rewrite Rewrite Universal Intrinsic code: float related part #24325 The goal of this series of PRs is to modify the SIMD code blocks guarded by CV_SIMD macro: rewrite them by using the new Universal Intrinsic API. The series of PRs is listed below: #23885 First patch, an example #23980 Core module #24058 ImgProc module, part 1 #24132 ImgProc module, part 2 #24166 ImgProc module, part 3 #24301 Features2d and calib3d module #24324 Gapi module This patch (hopefully) is the last one in the series. This patch mainly involves 3 parts 1. Add some modifications related to float (CV_SIMD_64F) 2. Use `#if (CV_SIMD \|\| CV_SIMD_SCALABLE)` instead of `#if CV_SIMD \|\| CV_SIMD_SCALABLE`, then we can get the `CV_SIMD` module that is not enabled for `CV_SIMD_SCALABLE` by looking for `if CV_SIMD` 3. Summary of `CV_SIMD` blocks that remains unmodified: Updated comments - Some blocks will cause test fail when enable for RVV, marked as `TODO: enable for CV_SIMD_SCALABLE, ....` - Some blocks can not be rewrited directly. (Not commented in the source code, just listed here) - ./modules/core/src/mathfuncs_core.simd.hpp (Vector type wrapped in class/struct) - ./modules/imgproc/src/color_lab.cpp (Array of vector type) - ./modules/imgproc/src/color_rgb.simd.hpp (Array of vector type) - ./modules/imgproc/src/sumpixels.simd.hpp (fixed length algorithm, strongly ralated with `CV_SIMD_WIDTH`) These algorithms will need to be redesigned to accommodate scalable backends. ### Pull Request Readiness Checklist See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [ ] I agree to contribute to the project under Apache 2 License. - [ ] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [ ] The PR is proposed to the proper branch - [ ] There is a reference to the original bug report and related work - [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [ ] The feature is well documented and sample code can be built with the project CMake	2023-10-05 17:57:25 +03:00
casualwinds	7b399c4248	Merge pull request #24280 from casualwind:parallel_opt Optimization for parallelization when large core number #24280 Problem description： When the number of cores is large, OpenCV’s thread library may reduce performance when processing parallel jobs. The reason for this problem: When the number of cores (the thread pool initialized the threads, whose number is as same as the number of cores) is large, the main thread will spend too much time on waking up unnecessary threads. When a parallel job needs to be executed, the main thread will wake up all threads in sequence, and then wait for the signal for the job completion after waking up all threads. When the number of threads is larger than the parallel number of a job slices, there will be a situation where the main thread wakes up the threads in sequence and the awakened threads have completed the job, but the main thread is still waking up the other threads. The threads woken up by the main thread after this have nothing to do, and the broadcasts made by the waking threads take a lot of time, which reduce the performance. Solution： Reduce the time for the process of main thread waking up the worker threads through the following two methods: • The number of threads awakened by the main thread should be adjusted according to the parallel number of a job slices. If the number of threads is greater than the number of the parallel number of job slices, the total number of threads awakened should be reduced. • In the process of waking up threads in sequence, if the main thread finds that all parallel job slices have been allocated, it will jump out of the loop in time and wait for the signal for the job completion. Performance Test: The tests were run in the manner described by https://github.com/opencv/opencv/wiki/HowToUsePerfTests. At core number = 160, There are big performance gain in some cases. Take the following cases in the video module as examples: OpticalFlowPyrLK_self::Path_Idx_Cn_NPoints_WSize_Deriv::("cv/optflow/frames/VGA_%02d.png", 2, 1, (9, 9), 11, true) Performance improves 191%:0.185405ms ->0.0636496ms perf::DenseOpticalFlow_VariationalRefinement::(320x240, 10, 10) Performance improves 112%:23.88938ms -> 11.2562ms Among all the modules, the performance improvement is greatest on module video, and there are also certain improvements on other modules. At core number = 160, the times labeled below are the geometric mean of the average time of all cases for one module. The optimization is available on each module. overall \| time(ms) \| \| \| \| \| \| \| -- \| -- \| -- \| -- \| -- \| -- \| -- \| -- \| -- module name \| gapi \| dnn \| features2d \| objdetect \| core \| imgproc \| stitching \| video original \| 0.185 \| 1.586 \| 9.998 \| 11.846 \| 0.205 \| 0.215 \| 164.409 \| 0.803 optimized \| 0.174 \| 1.353 \| 9.535 \| 11.105 \| 0.199 \| 0.185 \| 153.972 \| 0.489 Performance improves \| 6% \| 17% \| 5% \| 7% \| 3% \| 16% \| 7% \| 64% Meanwhile, It is found that adjusting the order of test cases will have an impact on some test cases. For example, we used option --gtest-shuffle to run opencv_perf_gapi, the performance of TestPerformance::CmpWithScalarPerfTestFluid/CmpWithScalarPerfTest::(compare_f, CMP_GE, 1920x1080, 32FC1, { gapi.kernel_package }) case had 30% changes compared to the case without shuffle. I would like to ask if you have also encountered such a situation and could you share your experience? ### Pull Request Readiness Checklist See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [x] I agree to contribute to the project under Apache 2 License. - [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [x] The PR is proposed to the proper branch - [ ] There is a reference to the original bug report and related work - [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [ ] The feature is well documented and sample code can be built with the project CMake	2023-09-27 16:21:20 +03:00
Vincent Rabaud	3880d059b3	Merge pull request #24260 from vrabaud:ubsan Fix undefined behavior arithmetic in copyMakeBorder and adjustROI. #24260 This is due to the undefined: negative int multiplied by size_t pointer increment. To test, compile with: ``` mkdir build cd build cmake ../ -DCMAKE_C_FLAGS_INIT="-fsanitize=undefined" -DCMAKE_CXX_FLAGS_INIT="-fsanitize=undefined" -DCMAKE_C_COMPILER="/usr/bin/clang" -DCMAKE_CXX_COMPILER="/usr/bin/clang++" -DCMAKE_SHARED_LINKER_FLAGS="-fsanitize=undefined -lubsan" ``` And run: ``` make -j opencv_test_core && ./bin/opencv_test_core --gtest_filter=UndefinedBehavior ``` ### Pull Request Readiness Checklist See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [x] I agree to contribute to the project under Apache 2 License. - [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [x] The PR is proposed to the proper branch - [x] There is a reference to the original bug report and related work - [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [x] The feature is well documented and sample code can be built with the project CMake	2023-09-14 15:16:28 +03:00
Yuriy Chernyshov	eb20bb3b23	Add missing sanitizer interface include	2023-09-13 12:15:34 +03:00
Alexander Smorkalov	0367a12b92	Check that cv::merge input matrices are not empty.	2023-09-08 12:36:46 +03:00
Yuriy Chernyshov	494d201fda	Add missing <sstream> includes	2023-09-05 22:04:26 +03:00
Yuantao Feng	a308dfca98	core: add broadcast (#23965 ) * add broadcast_to with tests * change name * fix test * fix implicit type conversion * replace type of shape with InputArray * add perf test * add perf tests which takes care of axis * v2 from ficus expand * rename to broadcast * use randu in place of declare * doc improvement; smaller scale in perf * capture get_index by reference	2023-08-30 09:53:59 +03:00
Kumataro	81cc89a3ce	Merge pull request #24179 from Kumataro:fix24145 * core:add OPENCV_IPP_MEAN/MINMAX/SUM option to enable IPP optimizations * fix: to use guard HAVE_IPP and ocv_append_source_file_compile_definitions() macro. * support OPENCV_IPP_ENABLE_ALL * add document for OPENCV_IPP_ENABLE_ALL * fix OPENCV_IPP_ENABLE_ALL comment	2023-08-23 22:53:11 +03:00
Sean McBride	d792ebc5d2	Fixed buffer overrun; removed the last two uses of sprintf Fixed an off-by-1 buffer resize, the space for the null termination was forgotten. Prefer snprintf, which can never overflow (if given the right size). In one case I cheated and used strcpy, because I cannot figure out the buffer size at that point in the code.	2023-08-16 20:04:17 -04:00
Alexander Smorkalov	747b7cab6c	Merge pull request #23734 from seanm:unaligned-copy Fixed invalid cast and unaligned memory access	2023-08-11 15:23:08 +03:00
Alexander Smorkalov	232c67bf76	Merge pull request #24140 from sthibaul:4.x Fix GNU/Hurd build	2023-08-11 12:32:22 +03:00
HAN Liutong	0dd7769bb1	Merge pull request #23980 from hanliutong:rewrite-core Rewrite Universal Intrinsic code by using new API: Core module. #23980 The goal of this PR is to match and modify all SIMD code blocks guarded by `CV_SIMD` macro in the `opencv/modules/core` folder and rewrite them by using the new Universal Intrinsic API. The patch is almost auto-generated by using the [rewriter](https://github.com/hanliutong/rewriter), related PR #23885. Most of the files have been rewritten, but I marked this PR as draft because, the `CV_SIMD` macro also exists in the following files, and the reasons why they are not rewrited are: 1. ~~code design for fixed-size SIMD (v_int16x8, v_float32x4, etc.), need to manually rewrite.~~ Rewrited - ./modules/core/src/stat.simd.hpp - ./modules/core/src/matrix_transform.cpp - ./modules/core/src/matmul.simd.hpp 2. Vector types are wrapped in other class/struct, that are not supported by the compiler in variable-length backends. Can not be rewrited directly. - ./modules/core/src/mathfuncs_core.simd.hpp ```cpp struct v_atan_f32 { explicit v_atan_f32(const float& scale) { ... } v_float32 compute(const v_float32& y, const v_float32& x) { ... } ... v_float32 val90; // sizeless type can not used in a class v_float32 val180; v_float32 val360; v_float32 s; }; ``` 3. The API interface does not support/does not match - ./modules/core/src/norm.cpp Use `v_popcount`, ~~waiting for #23966~~ Fixed - ./modules/core/src/has_non_zero.simd.hpp Use illegal Universal Intrinsic API: For float type, there is no logical operation `\|`. Further discussion needed ```cpp /** @brief Bitwise OR Only for integer types. / template<typename _Tp, int n> CV_INLINE v_reg<_Tp, n> operator\|(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b); template<typename _Tp, int n> CV_INLINE v_reg<_Tp, n>& operator\|=(v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b); ``` ```cpp #if CV_SIMD typedef v_float32 v_type; const v_type v_zero = vx_setzero_f32(); constexpr const int unrollCount = 8; int step = v_type::nlanes unrollCount; int len0 = len & -step; const float* srcSimdEnd = src+len0; int countSIMD = static_cast<int>((srcSimdEnd-src)/step); while(!res && countSIMD--) { v_type v0 = vx_load(src); src += v_type::nlanes; v_type v1 = vx_load(src); src += v_type::nlanes; .... src += v_type::nlanes; v0 \|= v1; //Illegal ? .... //res = v_check_any(((v0 \| v4) != v_zero));//beware : (NaN != 0) returns "false" since != is mapped to _CMP_NEQ_OQ and not _CMP_NEQ_UQ res = !v_check_all(((v0 \| v4) == v_zero)); } v_cleanup(); #endif ``` ### Pull Request Readiness Checklist See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [ ] I agree to contribute to the project under Apache 2 License. - [ ] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [ ] The PR is proposed to the proper branch - [ ] There is a reference to the original bug report and related work - [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [ ] The feature is well documented and sample code can be built with the project CMake	2023-08-11 08:33:33 +03:00
Samuel Thibault	82de5b3a67	Fix GNU/Hurd build It has the usual Unix filesystem operations.	2023-08-10 22:43:46 +02:00
Vincent Rabaud	423ab8ddb8	Use void*	2023-07-20 15:53:57 +02:00
Vincent Rabaud	20784d3da2	Fix undefined behavior with wrong function pointers called. Details here: https://bugs.chromium.org/p/oss-fuzz/issues/detail?id=58006 runtime error: call to function (unknown) through pointer to incorrect function type 'void ()(const unsigned char , const int , unsigned char *, const int , int, int)'	2023-07-20 15:32:05 +02:00
Alexander Smorkalov	23f27d8dbe	Use OpenCV logging instead of std::cerr.	2023-07-19 10:49:54 +03:00
Maksim Shabunin	3f0707234f	risc-v: fix unaligned loads and stores	2023-07-11 19:23:12 +03:00
Liutong HAN	d17507052e	Rewrite SIMD code by using new Universal Intrinsic API.	2023-06-28 17:12:37 +08:00
Alexander Smorkalov	bf06bc92aa	Merge branch '3.4' into merge-3.4	2023-06-23 20:12:58 +03:00
Paul Kim (김형준)	3b264d5877	Add `pthread.h` Inclusion if `HAVE_PTHREADS_PF` is defined Single-case tested with success on Windows 11 with MinGW-w64 Standalone GCC v13.1.0 while building OpenCV 4.7.0	2023-06-23 17:53:03 +09:00
Dmitry Kurtaev	22b747eae2	Merge pull request #23702 from dkurt:py_rotated_rect Python binding for RotatedRect #23702 ### Pull Request Readiness Checklist related: https://github.com/opencv/opencv/issues/23546#issuecomment-1562894602 See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [x] I agree to contribute to the project under Apache 2 License. - [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [x] The PR is proposed to the proper branch - [x] There is a reference to the original bug report and related work - [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [x] The feature is well documented and sample code can be built with the project CMake	2023-06-22 15:09:53 +03:00
Alexander Smorkalov	004801f1c5	Merge remote-tracking branch 'origin/3.4' into merge-3.4	2023-06-20 09:56:57 +03:00
dizcza	e625b32841	[opencv 3.x] back-ported tbb support ubuntu 22.04	2023-06-15 19:30:40 +03:00
Sean McBride	57da72d444	Fixed invalid cast and unaligned memory access Although acceptible to Intel CPUs, it's still undefined behaviour according to the C++ standard. It can be replaced with memcpy, which makes the code simpler, and it generates the same assembly code with gcc and clang with -O2 (verified with godbolt). Also expanded the test to include other little endian CPUs by testing for __LITTLE_ENDIAN__.	2023-06-09 18:56:49 -04:00
Pierre Chatelier	60b806f9b8	Merge pull request #22947 from chacha21:hasNonZero Added cv::hasNonZero() #22947 `cv::hasNonZero()` is semantically equivalent to (`cv::countNonZero()>0`) but stops parsing the image when a non-zero value is found, for a performance gain - [X] I agree to contribute to the project under Apache 2 License. - [X] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [X] The PR is proposed to the proper branch - [ ] There is a reference to the original bug report and related work - [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [ ] The feature is well documented and sample code can be built with the project CMake This pull request might be refused, but I submit it to know if further work is needed or if I just stop working on it. The idea is only a performance gain vs `countNonZero()>0` at the cost of more code. Reasons why it might be refused : - this is just more code - the execution time is "unfair"/"unpredictable" since it depends on the position of the first non-zero value - the user must be aware that default search is from first row/col to last row/col and has no way to customize that, even if his use case lets him know where a non zero could be found - the PR in its current state is using, for the ocl implementation, a mere `countNonZero()>0` ; there is not much sense in trying to break early the ocl kernel call when non-zero is encountered. So the ocl implementation does not bring any improvement. - there is no IPP function that can help (`countNonZero()` is based in `ippCountInRange`) - the PR in its current state might be slower than a call to `countNonZero()>0` in some cases (see "challenges" below) Reasons why it might be accepted : - the performance gain is huge on average, if we consider that "on average" means "non zero in the middle of the image" - the "missing" IPP implementation is replaced by an "Open-CV universal intrinsics" implementation - the PR in its current state is almost always faster than a call to `countNonZero()>0`, is only slightly slower in the worst cases, and not even for all matrices Challenges The worst case is either an all-zero matrix, or a non-zero at the very last position. In such a case, the `hasNonZero()` implementation will parse the whole matrix like `countNonZero()` would do. But we expect the performance to be the same in this case. And `ippCountInRange` is hard to beat ! There is also the case of very small matrices (<=32x32...) in 8b, where the SIMD can be hard to feed. For all cases but the worse, my custom `hasNonZero()` performs better than `ippCountInRange()` For the worst case, my custom `hasNonZero()` performs better than `ippCountInRange()` except for large matrices of type CV_32S or CV_64F (but surprisingly, not CV_32F). The difference is small, but it exists (and I don't understand why). For very small CV_8U matrices `ippCountInRange()` seems unbeatable. Here is the code that I use to check timings ``` //test cv::hasNonZero() vs (cv::countNonZero()>0) for different matrices sizes, types, strides... { cv::setRNGSeed(1234); const std::vector<cv::Size> sizes = {{32, 32}, {64, 64}, {128, 128}, {320, 240}, {512, 512}, {640, 480}, {1024, 768}, {2048, 2048}, {1031, 1000}}; const std::vector<int> types = {CV_8U, CV_16U, CV_32S, CV_32F, CV_64F}; const size_t iterations = 1000; for(const cv::Size& size : sizes) { for(const int type : types) { for(int c = 0 ; c<2 ; ++c) { const bool continuous = !c; for(int i = 0 ; i<4 ; ++i) { cv::Mat m = continuous ? cv::Mat::zeros(size, type) : cv::Mat(cv::Mat::zeros(cv::Size(2size.width, size.height), type), cv::Rect(cv::Point(0, 0), size)); const bool nz = (i <= 2); const unsigned int nzOffsetRange = 10; const unsigned int nzOffset = cv::randu<unsigned int>()%nzOffsetRange; const cv::Point pos = (i == 0) ? cv::Point(nzOffset, 0) : (i == 1) ? cv::Point(size.width/2-nzOffsetRange/2+nzOffset, size.height/2) : (i == 2) ? cv::Point(size.width-1-nzOffset, size.height-1) : cv::Point(0, 0); std::cout << "============================================================" << std::endl; std::cout << "size:" << size << " type:" << type << " continuous = " << (continuous ? "true" : "false") << " iterations:" << iterations << " nz=" << (nz ? "true" : "false"); std::cout << " pos=" << ((i == 0) ? "begin" : (i == 1) ? "middle" : (i == 2) ? "end" : "none"); std::cout << std::endl; cv::Mat mask = cv::Mat::zeros(size, CV_8UC1); mask.at<unsigned char>(pos) = 0xFF; m.setTo(cv::Scalar::all(0)); m.setTo(cv::Scalar::all(nz ? 1 : 0), mask); std::vector<bool> results; std::vector<double> timings; { bool res = false; auto ref = cv::getTickCount(); for(size_t k = 0 ; k<iterations ; ++k) res = cv::hasNonZero(m); auto now = cv::getTickCount(); const bool error = (res != nz); if (error) printf("!!ERROR!!\r\n"); results.push_back(res); timings.push_back(1000.(now-ref)/cv::getTickFrequency()); } { bool res = false; auto ref = cv::getTickCount(); for(size_t k = 0 ; k<iterations ; ++k) res = (cv::countNonZero(m)>0); auto now = cv::getTickCount(); const bool error = (res != nz); if (error) printf("!!ERROR!!\r\n"); results.push_back(res); timings.push_back(1000.(now-ref)/cv::getTickFrequency()); } const size_t bestTimingIndex = (std::min_element(timings.begin(), timings.end())-timings.begin()); if ((bestTimingIndex != 0) \|\| (std::find_if_not(results.begin(), results.end(), [&](bool r) {return (r == nz);}) != results.end())) { std::cout << "cv::hasNonZero\t\t=>" << results[0] << ((results[0] != nz) ? " ERROR" : "") << " perf:" << timings[0] << "ms => " << (iterations/timings[0]1000) << " im/s" << ((bestTimingIndex == 0) ? " * " : "") << std::endl; std::cout << "cv::countNonZero\t=>" << results[1] << ((results[1] != nz) ? " ERROR" : "") << " perf:" << timings[1] << "ms => " << (iterations/timings[1]1000) << " im/s" << ((bestTimingIndex == 1) ? " " : "") << std::endl; } } } } } } ``` Here is a report of this benchmark (it only reports timings when `cv::countNonZero()` is faster) My CPU is an Intel Core I7 4790 @ 3.60Ghz ``` ============================================================ size:[32 x 32] type:0 continuous = true iterations:1000 nz=true pos=begin ============================================================ size:[32 x 32] type:0 continuous = true iterations:1000 nz=true pos=middle ============================================================ size:[32 x 32] type:0 continuous = true iterations:1000 nz=true pos=end ============================================================ size:[32 x 32] type:0 continuous = true iterations:1000 nz=false pos=none ============================================================ size:[32 x 32] type:0 continuous = false iterations:1000 nz=true pos=begin ============================================================ size:[32 x 32] type:0 continuous = false iterations:1000 nz=true pos=middle cv::hasNonZero =>1 perf:0.353764ms => 2.82674e+06 im/s cv::countNonZero =>1 perf:0.282044ms => 3.54555e+06 im/s * ============================================================ size:[32 x 32] type:0 continuous = false iterations:1000 nz=true pos=end cv::hasNonZero =>1 perf:0.610478ms => 1.63806e+06 im/s cv::countNonZero =>1 perf:0.283182ms => 3.5313e+06 im/s * ============================================================ size:[32 x 32] type:0 continuous = false iterations:1000 nz=false pos=none cv::hasNonZero =>0 perf:0.630115ms => 1.58701e+06 im/s cv::countNonZero =>0 perf:0.282044ms => 3.54555e+06 im/s * ============================================================ size:[32 x 32] type:2 continuous = true iterations:1000 nz=true pos=begin ============================================================ size:[32 x 32] type:2 continuous = true iterations:1000 nz=true pos=middle ============================================================ size:[32 x 32] type:2 continuous = true iterations:1000 nz=true pos=end ============================================================ size:[32 x 32] type:2 continuous = true iterations:1000 nz=false pos=none ============================================================ size:[32 x 32] type:2 continuous = false iterations:1000 nz=true pos=begin ============================================================ size:[32 x 32] type:2 continuous = false iterations:1000 nz=true pos=middle ============================================================ size:[32 x 32] type:2 continuous = false iterations:1000 nz=true pos=end ============================================================ size:[32 x 32] type:2 continuous = false iterations:1000 nz=false pos=none ============================================================ size:[32 x 32] type:4 continuous = true iterations:1000 nz=true pos=begin ============================================================ size:[32 x 32] type:4 continuous = true iterations:1000 nz=true pos=middle ============================================================ size:[32 x 32] type:4 continuous = true iterations:1000 nz=true pos=end ============================================================ size:[32 x 32] type:4 continuous = true iterations:1000 nz=false pos=none ============================================================ size:[32 x 32] type:4 continuous = false iterations:1000 nz=true pos=begin ============================================================ size:[32 x 32] type:4 continuous = false iterations:1000 nz=true pos=middle ============================================================ size:[32 x 32] type:4 continuous = false iterations:1000 nz=true pos=end ============================================================ size:[32 x 32] type:4 continuous = false iterations:1000 nz=false pos=none ============================================================ size:[32 x 32] type:5 continuous = true iterations:1000 nz=true pos=begin ============================================================ size:[32 x 32] type:5 continuous = true iterations:1000 nz=true pos=middle ============================================================ size:[32 x 32] type:5 continuous = true iterations:1000 nz=true pos=end ============================================================ size:[32 x 32] type:5 continuous = true iterations:1000 nz=false pos=none ============================================================ size:[32 x 32] type:5 continuous = false iterations:1000 nz=true pos=begin ============================================================ size:[32 x 32] type:5 continuous = false iterations:1000 nz=true pos=middle ============================================================ size:[32 x 32] type:5 continuous = false iterations:1000 nz=true pos=end cv::hasNonZero =>1 perf:0.607347ms => 1.64651e+06 im/s cv::countNonZero =>1 perf:0.467037ms => 2.14116e+06 im/s * ============================================================ size:[32 x 32] type:5 continuous = false iterations:1000 nz=false pos=none cv::hasNonZero =>0 perf:0.618162ms => 1.6177e+06 im/s cv::countNonZero =>0 perf:0.468175ms => 2.13595e+06 im/s * ============================================================ size:[32 x 32] type:6 continuous = true iterations:1000 nz=true pos=begin ============================================================ size:[32 x 32] type:6 continuous = true iterations:1000 nz=true pos=middle ============================================================ size:[32 x 32] type:6 continuous = true iterations:1000 nz=true pos=end ============================================================ size:[32 x 32] type:6 continuous = true iterations:1000 nz=false pos=none ============================================================ size:[32 x 32] type:6 continuous = false iterations:1000 nz=true pos=begin ============================================================ size:[32 x 32] type:6 continuous = false iterations:1000 nz=true pos=middle ============================================================ size:[32 x 32] type:6 continuous = false iterations:1000 nz=true pos=end ============================================================ size:[32 x 32] type:6 continuous = false iterations:1000 nz=false pos=none ============================================================ size:[64 x 64] type:0 continuous = true iterations:1000 nz=true pos=begin ============================================================ size:[64 x 64] type:0 continuous = true iterations:1000 nz=true pos=middle ============================================================ size:[64 x 64] type:0 continuous = true iterations:1000 nz=true pos=end ============================================================ size:[64 x 64] type:0 continuous = true iterations:1000 nz=false pos=none ============================================================ size:[64 x 64] type:0 continuous = false iterations:1000 nz=true pos=begin ============================================================ size:[64 x 64] type:0 continuous = false iterations:1000 nz=true pos=middle ============================================================ size:[64 x 64] type:0 continuous = false iterations:1000 nz=true pos=end ============================================================ size:[64 x 64] type:0 continuous = false iterations:1000 nz=false pos=none ============================================================ size:[64 x 64] type:2 continuous = true iterations:1000 nz=true pos=begin ============================================================ size:[64 x 64] type:2 continuous = true iterations:1000 nz=true pos=middle ============================================================ size:[64 x 64] type:2 continuous = true iterations:1000 nz=true pos=end ============================================================ size:[64 x 64] type:2 continuous = true iterations:1000 nz=false pos=none ============================================================ size:[64 x 64] type:2 continuous = false iterations:1000 nz=true pos=begin ============================================================ size:[64 x 64] type:2 continuous = false iterations:1000 nz=true pos=middle ============================================================ size:[64 x 64] type:2 continuous = false iterations:1000 nz=true pos=end ============================================================ size:[64 x 64] type:2 continuous = false iterations:1000 nz=false pos=none ============================================================ size:[64 x 64] type:4 continuous = true iterations:1000 nz=true pos=begin ============================================================ size:[64 x 64] type:4 continuous = true iterations:1000 nz=true pos=middle ============================================================ size:[64 x 64] type:4 continuous = true iterations:1000 nz=true pos=end ============================================================ size:[64 x 64] type:4 continuous = true iterations:1000 nz=false pos=none ============================================================ size:[64 x 64] type:4 continuous = false iterations:1000 nz=true pos=begin ============================================================ size:[64 x 64] type:4 continuous = false iterations:1000 nz=true pos=middle ============================================================ size:[64 x 64] type:4 continuous = false iterations:1000 nz=true pos=end ============================================================ size:[64 x 64] type:4 continuous = false iterations:1000 nz=false pos=none ============================================================ size:[64 x 64] type:5 continuous = true iterations:1000 nz=true pos=begin ============================================================ size:[64 x 64] type:5 continuous = true iterations:1000 nz=true pos=middle ============================================================ size:[64 x 64] type:5 continuous = true iterations:1000 nz=true pos=end ============================================================ size:[64 x 64] type:5 continuous = true iterations:1000 nz=false pos=none ============================================================ size:[64 x 64] type:5 continuous = false iterations:1000 nz=true pos=begin ============================================================ size:[64 x 64] type:5 continuous = false iterations:1000 nz=true pos=middle ============================================================ size:[64 x 64] type:5 continuous = false iterations:1000 nz=true pos=end ============================================================ size:[64 x 64] type:5 continuous = false iterations:1000 nz=false pos=none ============================================================ size:[64 x 64] type:6 continuous = true iterations:1000 nz=true pos=begin ============================================================ size:[64 x 64] type:6 continuous = true iterations:1000 nz=true pos=middle ============================================================ size:[64 x 64] type:6 continuous = true iterations:1000 nz=true pos=end ============================================================ size:[64 x 64] type:6 continuous = true iterations:1000 nz=false pos=none ============================================================ size:[64 x 64] type:6 continuous = false iterations:1000 nz=true pos=begin ============================================================ size:[64 x 64] type:6 continuous = false iterations:1000 nz=true pos=middle ============================================================ size:[64 x 64] type:6 continuous = false iterations:1000 nz=true pos=end ============================================================ size:[64 x 64] type:6 continuous = false iterations:1000 nz=false pos=none ============================================================ size:[128 x 128] type:0 continuous = true iterations:1000 nz=true pos=begin ============================================================ size:[128 x 128] type:0 continuous = true iterations:1000 nz=true pos=middle ============================================================ size:[128 x 128] type:0 continuous = true iterations:1000 nz=true pos=end ============================================================ size:[128 x 128] type:0 continuous = true iterations:1000 nz=false pos=none ============================================================ size:[128 x 128] type:0 continuous = false iterations:1000 nz=true pos=begin ============================================================ size:[128 x 128] type:0 continuous = false iterations:1000 nz=true pos=middle ============================================================ size:[128 x 128] type:0 continuous = false iterations:1000 nz=true pos=end ============================================================ size:[128 x 128] type:0 continuous = false iterations:1000 nz=false pos=none ============================================================ size:[128 x 128] type:2 continuous = true iterations:1000 nz=true pos=begin ============================================================ size:[128 x 128] type:2 continuous = true iterations:1000 nz=true pos=middle ============================================================ size:[128 x 128] type:2 continuous = true iterations:1000 nz=true pos=end ============================================================ size:[128 x 128] type:2 continuous = true iterations:1000 nz=false pos=none ============================================================ size:[128 x 128] type:2 continuous = false iterations:1000 nz=true pos=begin ============================================================ size:[128 x 128] type:2 continuous = false iterations:1000 nz=true pos=middle ============================================================ size:[128 x 128] type:2 continuous = false iterations:1000 nz=true pos=end ============================================================ size:[128 x 128] type:2 continuous = false iterations:1000 nz=false pos=none ============================================================ size:[128 x 128] type:4 continuous = true iterations:1000 nz=true pos=begin ============================================================ size:[128 x 128] type:4 continuous = true iterations:1000 nz=true pos=middle ============================================================ size:[128 x 128] type:4 continuous = true iterations:1000 nz=true pos=end ============================================================ size:[128 x 128] type:4 continuous = true iterations:1000 nz=false pos=none ============================================================ size:[128 x 128] type:4 continuous = false iterations:1000 nz=true pos=begin ============================================================ size:[128 x 128] type:4 continuous = false iterations:1000 nz=true pos=middle ============================================================ size:[128 x 128] type:4 continuous = false iterations:1000 nz=true pos=end ============================================================ size:[128 x 128] type:4 continuous = false iterations:1000 nz=false pos=none ============================================================ size:[128 x 128] type:5 continuous = true iterations:1000 nz=true pos=begin ============================================================ size:[128 x 128] type:5 continuous = true iterations:1000 nz=true pos=middle ============================================================ size:[128 x 128] type:5 continuous = true iterations:1000 nz=true pos=end ============================================================ size:[128 x 128] type:5 continuous = true iterations:1000 nz=false pos=none ============================================================ size:[128 x 128] type:5 continuous = false iterations:1000 nz=true pos=begin ============================================================ size:[128 x 128] type:5 continuous = false iterations:1000 nz=true pos=middle ============================================================ size:[128 x 128] type:5 continuous = false iterations:1000 nz=true pos=end ============================================================ size:[128 x 128] type:5 continuous = false iterations:1000 nz=false pos=none ============================================================ size:[128 x 128] type:6 continuous = true iterations:1000 nz=true pos=begin ============================================================ size:[128 x 128] type:6 continuous = true iterations:1000 nz=true pos=middle ============================================================ size:[128 x 128] type:6 continuous = true iterations:1000 nz=true pos=end ============================================================ size:[128 x 128] type:6 continuous = true iterations:1000 nz=false pos=none ============================================================ size:[128 x 128] type:6 continuous = false iterations:1000 nz=true pos=begin ============================================================ size:[128 x 128] type:6 continuous = false iterations:1000 nz=true pos=middle ============================================================ size:[128 x 128] type:6 continuous = false iterations:1000 nz=true pos=end ============================================================ size:[128 x 128] type:6 continuous = false iterations:1000 nz=false pos=none ============================================================ size:[320 x 240] type:0 continuous = true iterations:1000 nz=true pos=begin ============================================================ size:[320 x 240] type:0 continuous = true iterations:1000 nz=true pos=middle ============================================================ size:[320 x 240] type:0 continuous = true iterations:1000 nz=true pos=end ============================================================ size:[320 x 240] type:0 continuous = true iterations:1000 nz=false pos=none ============================================================ size:[320 x 240] type:0 continuous = false iterations:1000 nz=true pos=begin ============================================================ size:[320 x 240] type:0 continuous = false iterations:1000 nz=true pos=middle ============================================================ size:[320 x 240] type:0 continuous = false iterations:1000 nz=true pos=end ============================================================ size:[320 x 240] type:0 continuous = false iterations:1000 nz=false pos=none ============================================================ size:[320 x 240] type:2 continuous = true iterations:1000 nz=true pos=begin ============================================================ size:[320 x 240] type:2 continuous = true iterations:1000 nz=true pos=middle ============================================================ size:[320 x 240] type:2 continuous = true iterations:1000 nz=true pos=end ============================================================ size:[320 x 240] type:2 continuous = true iterations:1000 nz=false pos=none ============================================================ size:[320 x 240] type:2 continuous = false iterations:1000 nz=true pos=begin ============================================================ size:[320 x 240] type:2 continuous = false iterations:1000 nz=true pos=middle ============================================================ size:[320 x 240] type:2 continuous = false iterations:1000 nz=true pos=end ============================================================ size:[320 x 240] type:2 continuous = false iterations:1000 nz=false pos=none ============================================================ size:[320 x 240] type:4 continuous = true iterations:1000 nz=true pos=begin ============================================================ size:[320 x 240] type:4 continuous = true iterations:1000 nz=true pos=middle ============================================================ size:[320 x 240] type:4 continuous = true iterations:1000 nz=true pos=end ============================================================ size:[320 x 240] type:4 continuous = true iterations:1000 nz=false pos=none ============================================================ size:[320 x 240] type:4 continuous = false iterations:1000 nz=true pos=begin ============================================================ size:[320 x 240] type:4 continuous = false iterations:1000 nz=true pos=middle ============================================================ size:[320 x 240] type:4 continuous = false iterations:1000 nz=true pos=end ============================================================ size:[320 x 240] type:4 continuous = false iterations:1000 nz=false pos=none ============================================================ size:[320 x 240] type:5 continuous = true iterations:1000 nz=true pos=begin ============================================================ size:[320 x 240] type:5 continuous = true iterations:1000 nz=true pos=middle ============================================================ size:[320 x 240] type:5 continuous = true iterations:1000 nz=true pos=end ============================================================ size:[320 x 240] type:5 continuous = true iterations:1000 nz=false pos=none ============================================================ size:[320 x 240] type:5 continuous = false iterations:1000 nz=true pos=begin ============================================================ size:[320 x 240] type:5 continuous = false iterations:1000 nz=true pos=middle ============================================================ size:[320 x 240] type:5 continuous = false iterations:1000 nz=true pos=end ============================================================ size:[320 x 240] type:5 continuous = false iterations:1000 nz=false pos=none ============================================================ size:[320 x 240] type:6 continuous = true iterations:1000 nz=true pos=begin ============================================================ size:[320 x 240] type:6 continuous = true iterations:1000 nz=true pos=middle ============================================================ size:[320 x 240] type:6 continuous = true iterations:1000 nz=true pos=end ============================================================ size:[320 x 240] type:6 continuous = true iterations:1000 nz=false pos=none ============================================================ size:[320 x 240] type:6 continuous = false iterations:1000 nz=true pos=begin ============================================================ size:[320 x 240] type:6 continuous = false iterations:1000 nz=true pos=middle ============================================================ size:[320 x 240] type:6 continuous = false iterations:1000 nz=true pos=end ============================================================ size:[320 x 240] type:6 continuous = false iterations:1000 nz=false pos=none ============================================================ size:[512 x 512] type:0 continuous = true iterations:1000 nz=true pos=begin ============================================================ size:[512 x 512] type:0 continuous = true iterations:1000 nz=true pos=middle ============================================================ size:[512 x 512] type:0 continuous = true iterations:1000 nz=true pos=end ============================================================ size:[512 x 512] type:0 continuous = true iterations:1000 nz=false pos=none ============================================================ size:[512 x 512] type:0 continuous = false iterations:1000 nz=true pos=begin ============================================================ size:[512 x 512] type:0 continuous = false iterations:1000 nz=true pos=middle ============================================================ size:[512 x 512] type:0 continuous = false iterations:1000 nz=true pos=end ============================================================ size:[512 x 512] type:0 continuous = false iterations:1000 nz=false pos=none ============================================================ size:[512 x 512] type:2 continuous = true iterations:1000 nz=true pos=begin ============================================================ size:[512 x 512] type:2 continuous = true iterations:1000 nz=true pos=middle ============================================================ size:[512 x 512] type:2 continuous = true iterations:1000 nz=true pos=end ============================================================ size:[512 x 512] type:2 continuous = true iterations:1000 nz=false pos=none ============================================================ size:[512 x 512] type:2 continuous = false iterations:1000 nz=true pos=begin ============================================================ size:[512 x 512] type:2 continuous = false iterations:1000 nz=true pos=middle ============================================================ size:[512 x 512] type:2 continuous = false iterations:1000 nz=true pos=end ============================================================ size:[512 x 512] type:2 continuous = false iterations:1000 nz=false pos=none ============================================================ size:[512 x 512] type:4 continuous = true iterations:1000 nz=true pos=begin ============================================================ size:[512 x 512] type:4 continuous = true iterations:1000 nz=true pos=middle ============================================================ size:[512 x 512] type:4 continuous = true iterations:1000 nz=true pos=end ============================================================ size:[512 x 512] type:4 continuous = true iterations:1000 nz=false pos=none ============================================================ size:[512 x 512] type:4 continuous = false iterations:1000 nz=true pos=begin ============================================================ size:[512 x 512] type:4 continuous = false iterations:1000 nz=true pos=middle ============================================================ size:[512 x 512] type:4 continuous = false iterations:1000 nz=true pos=end ============================================================ size:[512 x 512] type:4 continuous = false iterations:1000 nz=false pos=none ============================================================ size:[512 x 512] type:5 continuous = true iterations:1000 nz=true pos=begin ============================================================ size:[512 x 512] type:5 continuous = true iterations:1000 nz=true pos=middle ============================================================ size:[512 x 512] type:5 continuous = true iterations:1000 nz=true pos=end ============================================================ size:[512 x 512] type:5 continuous = true iterations:1000 nz=false pos=none ============================================================ size:[512 x 512] type:5 continuous = false iterations:1000 nz=true pos=begin ============================================================ size:[512 x 512] type:5 continuous = false iterations:1000 nz=true pos=middle ============================================================ size:[512 x 512] type:5 continuous = false iterations:1000 nz=true pos=end ============================================================ size:[512 x 512] type:5 continuous = false iterations:1000 nz=false pos=none ============================================================ size:[512 x 512] type:6 continuous = true iterations:1000 nz=true pos=begin ============================================================ size:[512 x 512] type:6 continuous = true iterations:1000 nz=true pos=middle ============================================================ size:[512 x 512] type:6 continuous = true iterations:1000 nz=true pos=end ============================================================ size:[512 x 512] type:6 continuous = true iterations:1000 nz=false pos=none ============================================================ size:[512 x 512] type:6 continuous = false iterations:1000 nz=true pos=begin ============================================================ size:[512 x 512] type:6 continuous = false iterations:1000 nz=true pos=middle ============================================================ size:[512 x 512] type:6 continuous = false iterations:1000 nz=true pos=end ============================================================ size:[512 x 512] type:6 continuous = false iterations:1000 nz=false pos=none ============================================================ size:[640 x 480] type:0 continuous = true iterations:1000 nz=true pos=begin ============================================================ size:[640 x 480] type:0 continuous = true iterations:1000 nz=true pos=middle ============================================================ size:[640 x 480] type:0 continuous = true iterations:1000 nz=true pos=end ============================================================ size:[640 x 480] type:0 continuous = true iterations:1000 nz=false pos=none ============================================================ size:[640 x 480] type:0 continuous = false iterations:1000 nz=true pos=begin ============================================================ size:[640 x 480] type:0 continuous = false iterations:1000 nz=true pos=middle ============================================================ size:[640 x 480] type:0 continuous = false iterations:1000 nz=true pos=end ============================================================ size:[640 x 480] type:0 continuous = false iterations:1000 nz=false pos=none ============================================================ size:[640 x 480] type:2 continuous = true iterations:1000 nz=true pos=begin ============================================================ size:[640 x 480] type:2 continuous = true iterations:1000 nz=true pos=middle ============================================================ size:[640 x 480] type:2 continuous = true iterations:1000 nz=true pos=end ============================================================ size:[640 x 480] type:2 continuous = true iterations:1000 nz=false pos=none ============================================================ size:[640 x 480] type:2 continuous = false iterations:1000 nz=true pos=begin ============================================================ size:[640 x 480] type:2 continuous = false iterations:1000 nz=true pos=middle ============================================================ size:[640 x 480] type:2 continuous = false iterations:1000 nz=true pos=end ============================================================ size:[640 x 480] type:2 continuous = false iterations:1000 nz=false pos=none ============================================================ size:[640 x 480] type:4 continuous = true iterations:1000 nz=true pos=begin ============================================================ size:[640 x 480] type:4 continuous = true iterations:1000 nz=true pos=middle ============================================================ size:[640 x 480] type:4 continuous = true iterations:1000 nz=true pos=end ============================================================ size:[640 x 480] type:4 continuous = true iterations:1000 nz=false pos=none ============================================================ size:[640 x 480] type:4 continuous = false iterations:1000 nz=true pos=begin ============================================================ size:[640 x 480] type:4 continuous = false iterations:1000 nz=true pos=middle ============================================================ size:[640 x 480] type:4 continuous = false iterations:1000 nz=true pos=end ============================================================ size:[640 x 480] type:4 continuous = false iterations:1000 nz=false pos=none ============================================================ size:[640 x 480] type:5 continuous = true iterations:1000 nz=true pos=begin ============================================================ size:[640 x 480] type:5 continuous = true iterations:1000 nz=true pos=middle ============================================================ size:[640 x 480] type:5 continuous = true iterations:1000 nz=true pos=end ============================================================ size:[640 x 480] type:5 continuous = true iterations:1000 nz=false pos=none ============================================================ size:[640 x 480] type:5 continuous = false iterations:1000 nz=true pos=begin ============================================================ size:[640 x 480] type:5 continuous = false iterations:1000 nz=true pos=middle ============================================================ size:[640 x 480] type:5 continuous = false iterations:1000 nz=true pos=end ============================================================ size:[640 x 480] type:5 continuous = false iterations:1000 nz=false pos=none ============================================================ size:[640 x 480] type:6 continuous = true iterations:1000 nz=true pos=begin ============================================================ size:[640 x 480] type:6 continuous = true iterations:1000 nz=true pos=middle ============================================================ size:[640 x 480] type:6 continuous = true iterations:1000 nz=true pos=end ============================================================ size:[640 x 480] type:6 continuous = true iterations:1000 nz=false pos=none ============================================================ size:[640 x 480] type:6 continuous = false iterations:1000 nz=true pos=begin ============================================================ size:[640 x 480] type:6 continuous = false iterations:1000 nz=true pos=middle ============================================================ size:[640 x 480] type:6 continuous = false iterations:1000 nz=true pos=end ============================================================ size:[640 x 480] type:6 continuous = false iterations:1000 nz=false pos=none ============================================================ size:[1024 x 768] type:0 continuous = true iterations:1000 nz=true pos=begin ============================================================ size:[1024 x 768] type:0 continuous = true iterations:1000 nz=true pos=middle ============================================================ size:[1024 x 768] type:0 continuous = true iterations:1000 nz=true pos=end ============================================================ size:[1024 x 768] type:0 continuous = true iterations:1000 nz=false pos=none ============================================================ size:[1024 x 768] type:0 continuous = false iterations:1000 nz=true pos=begin ============================================================ size:[1024 x 768] type:0 continuous = false iterations:1000 nz=true pos=middle ============================================================ size:[1024 x 768] type:0 continuous = false iterations:1000 nz=true pos=end ============================================================ size:[1024 x 768] type:0 continuous = false iterations:1000 nz=false pos=none ============================================================ size:[1024 x 768] type:2 continuous = true iterations:1000 nz=true pos=begin ============================================================ size:[1024 x 768] type:2 continuous = true iterations:1000 nz=true pos=middle ============================================================ size:[1024 x 768] type:2 continuous = true iterations:1000 nz=true pos=end ============================================================ size:[1024 x 768] type:2 continuous = true iterations:1000 nz=false pos=none ============================================================ size:[1024 x 768] type:2 continuous = false iterations:1000 nz=true pos=begin ============================================================ size:[1024 x 768] type:2 continuous = false iterations:1000 nz=true pos=middle ============================================================ size:[1024 x 768] type:2 continuous = false iterations:1000 nz=true pos=end ============================================================ size:[1024 x 768] type:2 continuous = false iterations:1000 nz=false pos=none ============================================================ size:[1024 x 768] type:4 continuous = true iterations:1000 nz=true pos=begin ============================================================ size:[1024 x 768] type:4 continuous = true iterations:1000 nz=true pos=middle ============================================================ size:[1024 x 768] type:4 continuous = true iterations:1000 nz=true pos=end ============================================================ size:[1024 x 768] type:4 continuous = true iterations:1000 nz=false pos=none ============================================================ size:[1024 x 768] type:4 continuous = false iterations:1000 nz=true pos=begin ============================================================ size:[1024 x 768] type:4 continuous = false iterations:1000 nz=true pos=middle ============================================================ size:[1024 x 768] type:4 continuous = false iterations:1000 nz=true pos=end ============================================================ size:[1024 x 768] type:4 continuous = false iterations:1000 nz=false pos=none ============================================================ size:[1024 x 768] type:5 continuous = true iterations:1000 nz=true pos=begin ============================================================ size:[1024 x 768] type:5 continuous = true iterations:1000 nz=true pos=middle ============================================================ size:[1024 x 768] type:5 continuous = true iterations:1000 nz=true pos=end ============================================================ size:[1024 x 768] type:5 continuous = true iterations:1000 nz=false pos=none ============================================================ size:[1024 x 768] type:5 continuous = false iterations:1000 nz=true pos=begin ============================================================ size:[1024 x 768] type:5 continuous = false iterations:1000 nz=true pos=middle ============================================================ size:[1024 x 768] type:5 continuous = false iterations:1000 nz=true pos=end ============================================================ size:[1024 x 768] type:5 continuous = false iterations:1000 nz=false pos=none ============================================================ size:[1024 x 768] type:6 continuous = true iterations:1000 nz=true pos=begin ============================================================ size:[1024 x 768] type:6 continuous = true iterations:1000 nz=true pos=middle ============================================================ size:[1024 x 768] type:6 continuous = true iterations:1000 nz=true pos=end ============================================================ size:[1024 x 768] type:6 continuous = true iterations:1000 nz=false pos=none ============================================================ size:[1024 x 768] type:6 continuous = false iterations:1000 nz=true pos=begin ============================================================ size:[1024 x 768] type:6 continuous = false iterations:1000 nz=true pos=middle ============================================================ size:[1024 x 768] type:6 continuous = false iterations:1000 nz=true pos=end ============================================================ size:[1024 x 768] type:6 continuous = false iterations:1000 nz=false pos=none ============================================================ size:[2048 x 2048] type:0 continuous = true iterations:1000 nz=true pos=begin ============================================================ size:[2048 x 2048] type:0 continuous = true iterations:1000 nz=true pos=middle ============================================================ size:[2048 x 2048] type:0 continuous = true iterations:1000 nz=true pos=end ============================================================ size:[2048 x 2048] type:0 continuous = true iterations:1000 nz=false pos=none ============================================================ size:[2048 x 2048] type:0 continuous = false iterations:1000 nz=true pos=begin ============================================================ size:[2048 x 2048] type:0 continuous = false iterations:1000 nz=true pos=middle ============================================================ size:[2048 x 2048] type:0 continuous = false iterations:1000 nz=true pos=end ============================================================ size:[2048 x 2048] type:0 continuous = false iterations:1000 nz=false pos=none ============================================================ size:[2048 x 2048] type:2 continuous = true iterations:1000 nz=true pos=begin ============================================================ size:[2048 x 2048] type:2 continuous = true iterations:1000 nz=true pos=middle ============================================================ size:[2048 x 2048] type:2 continuous = true iterations:1000 nz=true pos=end ============================================================ size:[2048 x 2048] type:2 continuous = true iterations:1000 nz=false pos=none ============================================================ size:[2048 x 2048] type:2 continuous = false iterations:1000 nz=true pos=begin ============================================================ size:[2048 x 2048] type:2 continuous = false iterations:1000 nz=true pos=middle ============================================================ size:[2048 x 2048] type:2 continuous = false iterations:1000 nz=true pos=end ============================================================ size:[2048 x 2048] type:2 continuous = false iterations:1000 nz=false pos=none ============================================================ size:[2048 x 2048] type:4 continuous = true iterations:1000 nz=true pos=begin ============================================================ size:[2048 x 2048] type:4 continuous = true iterations:1000 nz=true pos=middle ============================================================ size:[2048 x 2048] type:4 continuous = true iterations:1000 nz=true pos=end cv::hasNonZero =>1 perf:895.381ms => 1116.84 im/s cv::countNonZero =>1 perf:882.569ms => 1133.06 im/s * ============================================================ size:[2048 x 2048] type:4 continuous = true iterations:1000 nz=false pos=none cv::hasNonZero =>0 perf:899.53ms => 1111.69 im/s cv::countNonZero =>0 perf:870.894ms => 1148.24 im/s * ============================================================ size:[2048 x 2048] type:4 continuous = false iterations:1000 nz=true pos=begin ============================================================ size:[2048 x 2048] type:4 continuous = false iterations:1000 nz=true pos=middle ============================================================ size:[2048 x 2048] type:4 continuous = false iterations:1000 nz=true pos=end ============================================================ size:[2048 x 2048] type:4 continuous = false iterations:1000 nz=false pos=none ============================================================ size:[2048 x 2048] type:5 continuous = true iterations:1000 nz=true pos=begin ============================================================ size:[2048 x 2048] type:5 continuous = true iterations:1000 nz=true pos=middle ============================================================ size:[2048 x 2048] type:5 continuous = true iterations:1000 nz=true pos=end ============================================================ size:[2048 x 2048] type:5 continuous = true iterations:1000 nz=false pos=none ============================================================ size:[2048 x 2048] type:5 continuous = false iterations:1000 nz=true pos=begin ============================================================ size:[2048 x 2048] type:5 continuous = false iterations:1000 nz=true pos=middle ============================================================ size:[2048 x 2048] type:5 continuous = false iterations:1000 nz=true pos=end ============================================================ size:[2048 x 2048] type:5 continuous = false iterations:1000 nz=false pos=none ============================================================ size:[2048 x 2048] type:6 continuous = true iterations:1000 nz=true pos=begin ============================================================ size:[2048 x 2048] type:6 continuous = true iterations:1000 nz=true pos=middle ============================================================ size:[2048 x 2048] type:6 continuous = true iterations:1000 nz=true pos=end cv::hasNonZero =>1 perf:2018.92ms => 495.313 im/s cv::countNonZero =>1 perf:1966.37ms => 508.552 im/s * ============================================================ size:[2048 x 2048] type:6 continuous = true iterations:1000 nz=false pos=none cv::hasNonZero =>0 perf:2005.87ms => 498.537 im/s cv::countNonZero =>0 perf:1992.78ms => 501.812 im/s * ============================================================ size:[2048 x 2048] type:6 continuous = false iterations:1000 nz=true pos=begin ============================================================ size:[2048 x 2048] type:6 continuous = false iterations:1000 nz=true pos=middle ============================================================ size:[2048 x 2048] type:6 continuous = false iterations:1000 nz=true pos=end ============================================================ size:[2048 x 2048] type:6 continuous = false iterations:1000 nz=false pos=none ============================================================ size:[1031 x 1000] type:0 continuous = true iterations:1000 nz=true pos=begin ============================================================ size:[1031 x 1000] type:0 continuous = true iterations:1000 nz=true pos=middle ============================================================ size:[1031 x 1000] type:0 continuous = true iterations:1000 nz=true pos=end ============================================================ size:[1031 x 1000] type:0 continuous = true iterations:1000 nz=false pos=none ============================================================ size:[1031 x 1000] type:0 continuous = false iterations:1000 nz=true pos=begin ============================================================ size:[1031 x 1000] type:0 continuous = false iterations:1000 nz=true pos=middle ============================================================ size:[1031 x 1000] type:0 continuous = false iterations:1000 nz=true pos=end ============================================================ size:[1031 x 1000] type:0 continuous = false iterations:1000 nz=false pos=none ============================================================ size:[1031 x 1000] type:2 continuous = true iterations:1000 nz=true pos=begin ============================================================ size:[1031 x 1000] type:2 continuous = true iterations:1000 nz=true pos=middle ============================================================ size:[1031 x 1000] type:2 continuous = true iterations:1000 nz=true pos=end ============================================================ size:[1031 x 1000] type:2 continuous = true iterations:1000 nz=false pos=none ============================================================ size:[1031 x 1000] type:2 continuous = false iterations:1000 nz=true pos=begin ============================================================ size:[1031 x 1000] type:2 continuous = false iterations:1000 nz=true pos=middle ============================================================ size:[1031 x 1000] type:2 continuous = false iterations:1000 nz=true pos=end ============================================================ size:[1031 x 1000] type:2 continuous = false iterations:1000 nz=false pos=none ============================================================ size:[1031 x 1000] type:4 continuous = true iterations:1000 nz=true pos=begin ============================================================ size:[1031 x 1000] type:4 continuous = true iterations:1000 nz=true pos=middle ============================================================ size:[1031 x 1000] type:4 continuous = true iterations:1000 nz=true pos=end ============================================================ size:[1031 x 1000] type:4 continuous = true iterations:1000 nz=false pos=none ============================================================ size:[1031 x 1000] type:4 continuous = false iterations:1000 nz=true pos=begin ============================================================ size:[1031 x 1000] type:4 continuous = false iterations:1000 nz=true pos=middle ============================================================ size:[1031 x 1000] type:4 continuous = false iterations:1000 nz=true pos=end ============================================================ size:[1031 x 1000] type:4 continuous = false iterations:1000 nz=false pos=none ============================================================ size:[1031 x 1000] type:5 continuous = true iterations:1000 nz=true pos=begin ============================================================ size:[1031 x 1000] type:5 continuous = true iterations:1000 nz=true pos=middle ============================================================ size:[1031 x 1000] type:5 continuous = true iterations:1000 nz=true pos=end ============================================================ size:[1031 x 1000] type:5 continuous = true iterations:1000 nz=false pos=none ============================================================ size:[1031 x 1000] type:5 continuous = false iterations:1000 nz=true pos=begin ============================================================ size:[1031 x 1000] type:5 continuous = false iterations:1000 nz=true pos=middle ============================================================ size:[1031 x 1000] type:5 continuous = false iterations:1000 nz=true pos=end ============================================================ size:[1031 x 1000] type:5 continuous = false iterations:1000 nz=false pos=none ============================================================ size:[1031 x 1000] type:6 continuous = true iterations:1000 nz=true pos=begin ============================================================ size:[1031 x 1000] type:6 continuous = true iterations:1000 nz=true pos=middle ============================================================ size:[1031 x 1000] type:6 continuous = true iterations:1000 nz=true pos=end ============================================================ size:[1031 x 1000] type:6 continuous = true iterations:1000 nz=false pos=none ============================================================ size:[1031 x 1000] type:6 continuous = false iterations:1000 nz=true pos=begin ============================================================ size:[1031 x 1000] type:6 continuous = false iterations:1000 nz=true pos=middle ============================================================ size:[1031 x 1000] type:6 continuous = false iterations:1000 nz=true pos=end ============================================================ size:[1031 x 1000] type:6 continuous = false iterations:1000 nz=false pos=none done ```	2023-06-09 13:37:20 +03:00
Dmitry Kurtaev	380caa1a87	Merge pull request #23691 from dkurt:pycv_float16_fixes Import and export np.float16 in Python #23691 ### Pull Request Readiness Checklist * Also, fixes `cv::norm` with `NORM_INF` and `CV_16F` resolves https://github.com/opencv/opencv/issues/23687 See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [x] I agree to contribute to the project under Apache 2 License. - [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [x] The PR is proposed to the proper branch - [x] There is a reference to the original bug report and related work - [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [x] The feature is well documented and sample code can be built with the project CMake	2023-05-26 18:56:21 +03:00
Alexander Smorkalov	65487946cc	Added final constrants check to solveLP to filter out flating-point numeric issues.	2023-05-25 17:29:01 +03:00
Alexander Smorkalov	d4861bfd1f	Merge remote-tracking branch 'origin/3.4' into merge-3.4	2023-05-24 14:37:48 +03:00
cudawarped	7539abecdb	cuda: add python bindings to allow GpuMat and Stream objects to be initialized from raw pointers	2023-05-22 11:02:04 +03:00
Alexander Alekhin	04d71da6e7	Merge pull request #23566 from seanm:atomic-bool	2023-05-16 10:46:59 +00:00
Sean McBride	27e10efa66	Use std::atomic<bool> as it's necessary for correct thread safety Now that C++11 is required, we can unconditionally use std::atomic in this case, which is more correct.	2023-05-01 16:44:34 -04:00
Pierre Chatelier	6dd8a9b6ad	Merge pull request #13879 from chacha21:REDUCE_SUM2 add REDUCE_SUM2 #13879 proposal to add REDUCE_SUM2 to cv::reduce, an operation that sums up the square of elements	2023-04-28 20:42:52 +03:00
Sean McBride	58e4a880a2	Deprecated convertTypeStr and made new variant that also takes the buffer size This allows removing the unsafe sprintf.	2023-04-26 09:48:15 -04:00
Giles Payne	38e35d5137	Fix ocl::device::isIntel implementation	2023-04-24 22:01:53 +09:00
Alexander Smorkalov	e4a29d93fe	Merge remote-tracking branch 'origin/3.4' into merge-3.4	2023-04-21 10:55:04 +03:00
Sean McBride	47bea69322	Merge pull request #23055 from seanm:sprintf2 * Replaced most remaining sprintf with snprintf * Deprecated encodeFormat and introduced new method that takes the buffer length * Also increased buffer size at call sites to be a little bigger, in case int is 64 bit	2023-04-18 09:22:59 +03:00
eplankin	fd8b346c3e	Merge pull request #23443 from eplankin:3.4 * Update IPPICV binaries (20230330) * Revert "core(IPP): disable some ippsMagnitude_32f calls" This reverts commit `8069a6b4f8`. * Reverted changes in norm() and count_non_zero()	2023-04-07 09:14:42 +00:00
Christian Henkel	c9e42c5050	two typos	2023-03-22 09:17:41 +03:00
Alexander Alekhin	d3ae175bca	Merge remote-tracking branch 'upstream/3.4' into merge-3.4	2023-01-28 10:01:23 +00:00
Yannis Guyon	bf29a4d746	Avoid double-checked locking with TSAN in parallel Omit the first check of the double-checked locking pattern in recordException() in parallel.cpp when CV_THREAD_SANITIZER is defined. This should only slow recordException() down when the thread sanitizer is used, and avoids the TSAN data race warning.	2023-01-27 13:36:33 +01:00
Alexander Alekhin	18cbfa4a4f	Merge remote-tracking branch 'upstream/3.4' into merge-3.4	2023-01-23 00:11:12 +00:00
Yang Chao	e0aa677388	Open CV_CPU_NEON_DOTPROD on Apple silicon devices	2023-01-09 19:27:35 +08:00
Alexander Alekhin	bc8c912c7a	Merge remote-tracking branch 'upstream/3.4' into merge-3.4	2022-12-24 13:54:58 +00:00
fengyuentau	34a0897f90	add cv::flipND; support onnx slice with negative steps via cv::flipND	2022-12-23 16:39:53 +08:00
Alexander Alekhin	da43778c1f	Merge pull request #22981 from alalek:core_freeze_cache_dir_prefix_4.x	2022-12-19 17:29:57 +00:00
Vincent Rabaud	7463e9b8bb	Even faster CV_PAUSE on SkyLake and above. No need to loop as RDTSC is 3/4 times faster than _mm_pause.	2022-12-19 14:15:34 +01:00
Alexander Alekhin	420db56ffd	Merge remote-tracking branch 'upstream/3.4' into merge-3.4	2022-12-18 02:17:17 +00:00
Alexander Alekhin	4824ce300f	core: freeze cache directory prefix - "4.x"	2022-12-18 00:24:52 +00:00
Alexander Alekhin	eace6adb6d	Merge pull request #22934 from alalek:fix_filestorage_binding	2022-12-17 03:28:13 +00:00
Alexander Alekhin	6e3700593f	compatibility: keep Ptr<FileStorage> stubs till OpenCV 5.0	2022-12-16 00:47:44 +00:00
Alexander Alekhin	6a8c5a1d27	python: resolve Ptr<FileStorage> requirement issue	2022-12-16 00:47:44 +00:00
Vincent Rabaud	b7b08fa0c3	Fix slower CV_PAUSE on SkyLake and above. This is fixing https://github.com/opencv/opencv/issues/22852	2022-12-15 14:18:57 +01:00
Alexander Alekhin	7e3c53b9d3	core(logger): strip path prefix	2022-12-07 23:58:36 +00:00
Alexander Alekhin	b16f76eede	Merge remote-tracking branch 'upstream/3.4' into merge-3.4	2022-12-03 12:39:41 +00:00
Christine Poerschke	4792837f2e	Merge pull request #22865 from cpoerschke:3.4-issue-22860 ocl_minMaxIdx to call minmaxloc.cl for OpenCL 1.2+ only	2022-12-03 05:29:04 +00:00
Alexander Smorkalov	1c3e287d32	More fixes for OpenCL error reporting.	2022-11-28 09:47:51 +03:00
Alexander Smorkalov	7622fbf895	Fixed OpenGL errors formatting.	2022-11-25 16:46:12 +03:00
Amir Hassan	3f371fe2dd	Merge pull request #22855 from kallaballa:print_cl_status_on_fail Print CL status code on error in opengl interop functions	2022-11-25 09:13:57 +03:00
Alexander Alekhin	5d14cc68b7	Merge remote-tracking branch 'upstream/3.4' into merge-3.4	2022-11-16 16:54:11 +00:00
Alexander Alekhin	54531f8e3b	core: support CV_Check*() macros with 'bool' parameters	2022-11-15 11:47:16 +00:00
Alexander Alekhin	762481411d	Merge remote-tracking branch 'upstream/3.4' into merge-3.4	2022-10-15 16:44:47 +00:00
Vincent Rabaud	38c9c20a35	Move marking memory as initialized earlier.	2022-09-28 21:58:17 +02:00
Sean McBride	1829eba584	Fixed most clang -Wextra-semi warnings	2022-09-27 18:06:46 -04:00
wxsheng	4154bd0667	Add Loongson Advanced SIMD Extension support: -DCPU_BASELINE=LASX * Add Loongson Advanced SIMD Extension support: -DCPU_BASELINE=LASX * Add resize.lasx.cpp for Loongson SIMD acceleration * Add imgwarp.lasx.cpp for Loongson SIMD acceleration * Add LASX acceleration support for dnn/conv * Add CV_PAUSE(v) for Loongarch * Set LASX by default on Loongarch64 * LoongArch: tune test threshold for Core/HAL.mat_decomp/15 Co-authored-by: shengwenxue <shengwenxue@loongson.cn>	2022-09-10 09:39:43 +03:00
Yuantao Feng	9dc844a6e1	Merge pull request #22346 from fengyuentau:mat1d_part1 Changes separated from Mat 1D support in core #18594 (#22346)	2022-09-09 12:56:30 +03:00
Alexander Alekhin	2ebdc04787	Merge remote-tracking branch 'upstream/3.4' into merge-3.4	2022-08-14 15:50:42 +00:00
Alexander Smorkalov	2ffa7ac0da	Merge pull request #22217 from CSharperMantle:CSharperMantle-patch-steady-clock Use `std::chrono::steady_clock` in `getTickCount`	2022-08-03 14:09:45 +03:00
Alexander Alekhin	0862d69a6e	Merge pull request #22271 from tomoaki0705:dotprod_neon	2022-07-25 15:00:32 +00:00
Maksim Shabunin	f729202272	core: remove unnecessary pointer cleanup in BufferArea	2022-07-24 11:58:17 +03:00
Tomoaki Teshima	b3269b08a1	neon: add dotprod dispatch implementation * read vector at runtime * add enum	2022-07-20 19:25:39 +09:00
HAN Liutong	0ef803950b	Merge pull request #22179 from hanliutong:new-rvv [GSoC] New universal intrinsic backend for RVV * Add new rvv backend (partially implemented). * Modify the framework of Universal Intrinsic. * Add CV_SIMD macro guards to current UI code. * Use vlanes() instead of nlanes. * Modify the UI test. * Enable the new RVV (scalable) backend. * Remove whitespace. * Rename and some others modify. * Update intrin.hpp but still not work on AVX/SSE * Update conditional compilation macros. * Use static variable for vlanes. * Use max_nlanes for array defining.	2022-07-19 20:02:00 +03:00
Rong Mantle Bao	fa613e393f	Read CV_CXX11 for C++11 detection	2022-07-10 19:21:17 +08:00
Rong Mantle Bao	db70676933	Use cross-platform std::chrono in getTickCount() Add conditional compilation directives to enable uses of std::chrono on supported compilers. Use std::chrono::steady_clock as a source to retrieve current tick count and clock frequency. Fixes opencv/opencv#6902.	2022-07-09 10:42:29 +08:00
Alexander Alekhin	2a4926f417	Merge remote-tracking branch 'upstream/3.4' into merge-3.4	2022-06-26 14:22:24 +00:00
Sean McBride	35f1a90df7	Merge pull request #22149 from seanm:sprintf Replaced sprintf with safer snprintf * Straightforward replacement of sprintf with safer snprintf * Trickier replacement of sprintf with safer snprintf Some functions were changed to take another parameter: the size of the buffer, so that they can pass that size on to snprintf.	2022-06-25 06:48:22 +03:00
Vincent Rabaud	0d52c37e11	Fix typo that prevents compilation with sanitizer.	2022-06-17 11:40:22 +02:00
Alexander Alekhin	734e309b3e	Merge remote-tracking branch 'upstream/3.4' into merge-3.4	2022-06-16 11:04:50 +00:00
Vincent Rabaud	7a46d7efde	Fix compilation on some ARM architecture. This condition is the same as the line above.	2022-06-13 17:39:24 +02:00
Alexander Alekhin	583bd1a6e2	Merge remote-tracking branch 'upstream/3.4' into merge-3.4	2022-06-04 19:10:35 +00:00
Alexander Alekhin	65fcf22670	imgproc: use singleton in color_hsv.simd.hpp	2022-06-01 19:02:56 +00:00
Namgoo Lee	24547f40ff	remove const from functions returning by value	2022-05-26 21:30:41 +09:00
OpenCV Developers	d9a444ca1a	Merge remote-tracking branch 'upstream/3.4' into merge-3.4	2022-05-14 11:23:21 +00:00
Kumataro	602caa9cd6	Merge pull request #21937 from Kumataro:4.x-fix-21911 * Fix warnings for clang15 * Fix warnings: Remove unnecessary code * Fix warnings: Remove unnecessary code	2022-05-13 17:32:05 +00:00
Vincent Rabaud	667e5e4f89	Merge pull request #21943 from vrabaud:3.4_proc * Fix compilation with non glibc. _SC_NPROCESSORS_ONLN is non standard as defined on https://man7.org/linux/man-pages/man3/sysconf.3.html It seems to only be on glibc, cf https://www.gnu.org/software/libc/manual/html_node/Processor-Resources.html * Fix to defined(_SC_NPROCESSORS_ONLN)	2022-05-05 07:59:29 +00:00
rogday	7daf84fb44	address security concerns in persistence	2022-04-14 22:18:00 +03:00
Anatoliy Talamanov	9390c56831	Merge pull request #21782 from TolyaTalamanov:at/fix-1d-mat-problems [G-API] Fix problems with 1D cv::Mat as graph output * Fix issues with 1D cv::Mat * Fix cv::Mat::create * Fix standalone build * Add test on 1d mat * Fix warning * Add additional condition * Add more tests	2022-03-31 21:00:45 +00:00
Alexander Alekhin	1339ebaa84	Merge remote-tracking branch 'upstream/3.4' into merge-3.4	2022-03-26 16:00:28 +00:00
Maksim Shabunin	593996216f	cartToPolar/polarToCart: disable inplace mode	2022-03-21 16:06:12 +03:00

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3066 Commits