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Author SHA1 Message Date
Sean McBride
e64857c561
Merge pull request #23736 from seanm:c++11-simplifications 
Removed all pre-C++11 code, workarounds, and branches #23736

This removes a bunch of pre-C++11 workrarounds that are no longer necessary as C++11 is now required.
It is a nice clean up and simplification.

* No longer unconditionally #include <array> in cvdef.h, include explicitly where needed
* Removed deprecated CV_NODISCARD, already unused in the codebase
* Removed some pre-C++11 workarounds, and simplified some backwards compat defines
* Removed CV_CXX_STD_ARRAY
* Removed CV_CXX_MOVE_SEMANTICS and CV_CXX_MOVE
* Removed all tests of CV_CXX11, now assume it's always true. This allowed removing a lot of dead code.
* Updated some documentation consequently.
* Removed all tests of CV_CXX11, now assume it's always true
* Fixed links.

---------

Co-authored-by: Maksim Shabunin <maksim.shabunin@gmail.com>
Co-authored-by: Alexander Smorkalov <alexander.smorkalov@xperience.ai>
 2024-01-19 16:53:08 +03:00
Maksim Shabunin
6b77f50269 RISC-V: use non-saturating 64-bit add in intrin_rvv071.hpp 2024-01-17 20:34:12 +03:00
Maksim Shabunin
224b9ee33f RISC-V: updated intrin_rvv071.hpp to work with modern toolchain 2.8.0 
- intrinsics implementation (071) reworked to use modern RVV intrinsics syntax
- cmake toolchain file (071) now allows selecting from predefined configurations

Co-authored-by: Fang Sun <fangsun@linux.alibaba.com>
 2024-01-17 20:34:12 +03:00
Stefan Dragnev
2791bb7062
Merge pull request #24773 from tailsu:sd/pathlike 
python: accept path-like objects wherever file names are expected #24773

Merry Christmas, all 🎄

Implements #15731

Support is enabled for all arguments named `filename` or `filepath` (case-insensitive), or annotated with `CV_WRAP_FILE_PATH`.

Support is based on `PyOS_FSPath`, which is available in Python 3.6+. When running on older Python versions the arguments must have a `str` value as before.

### 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
- [ ] 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
 2024-01-12 16:23:05 +03:00
Aryan
9b402cfa59 Resolved issue number #22177 2024-01-09 01:23:26 +05:30
Alexander Smorkalov
22a8fa0730
Merge pull request #24798 from Rageking8:correct-invalid-error-directive 
Correct invalid error directive
 2024-01-06 12:05:07 +03:00
cudawarped
19527d79d6 core: address clang warnings 2024-01-02 08:33:55 +02:00
Rageking8
7f2c14fc4f
Correct invalid error directive 2023-12-29 21:34:16 +08:00
Alexander Alekhin
2e3ccb4e8e Merge tag '4.9.0' 2023-12-28 09:29:33 +00:00
Alexander Smorkalov
dad8af6b17 Release 4.9.0. 2023-12-27 19:46:55 +03:00
Alexander Alekhin
49a0877b8c docs: exclude test entites from bindings utils 2023-12-27 06:46:20 +00:00
Alexander Smorkalov
b407c58b96 pre: OpenCV 4.9.0 (version++). 2023-12-25 15:20:10 +03:00
Kumataro
dba7186378
Merge pull request #24271 from Kumataro:fix24163 
Fix to convert float32 to int32/uint32 with rounding to nearest (ties to even). #24271

Fix https://github.com/opencv/opencv/issues/24163

### 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

(carotene is BSD)
 2023-12-25 12:17:17 +03:00
Alexander Smorkalov
3893936243
Merge pull request #24565 from CNClareChen:4.x 
Change the lsx to baseline features.
 2023-11-30 15:27:49 +03:00
Alexander Smorkalov
e20250139a
Merge pull request #24582 from hanliutong:rvv-lut 
Optimize the v_lut* functions for RISC-V Vector(RVV).
 2023-11-30 10:59:51 +03:00
Philip Allgaier
9bb0a8d9e9
Fix comment typo in matx.hpp 2023-11-28 08:26:40 +01:00
Liutong HAN
ce0516282a Optimize the v_lut for RVV. 2023-11-23 15:06:04 +08:00
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
zihaomu
b913e73d04
DNN: add the Winograd fp16 support (#23654) 
* add Winograd FP16 implementation

* fixed dispatching of FP16 code paths in dnn; use dynamic dispatcher only when NEON_FP16 is enabled in the build and the feature is present in the host CPU at runtime

* fixed some warnings

* hopefully fixed winograd on x64 (and maybe other platforms)

---------

Co-authored-by: Vadim Pisarevsky <vadim.pisarevsky@gmail.com>
 2023-11-20 13:45:37 +03:00
Alexander Smorkalov
8df76fe0cb Exclude RVV UI internals from Doxygen documentation. 2023-11-08 14:22:05 +03:00
Vincent Rabaud
832f738db0
Merge pull request #24495 from vrabaud:fast_math_compile 
Get the SSE2 condition match the emmintrin.h inclusion condition. #24495

### 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
 2023-11-07 09:06:28 +03:00
Alexander Smorkalov
fe4d518d85
Merge pull request #24485 from hanliutong:rvv-opt 
Optimize the Implementation of RVV Universal Intrinsic.
 2023-11-03 12:31:10 +03:00
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
Liutong HAN
451ee3991e Use local variable. 2023-11-03 10:21:13 +08:00
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
Alexander Smorkalov
7e17f01b7b
Merge pull request #24368 from mshabunin:rvv-clang-17 
RISC-V: added v0.12 intrinsics compatibility header
 2023-10-12 10:28:54 +03:00
Maksim Shabunin
8edf37903d RISC-V: added v0.12 intrinsics compatibility header 2023-10-06 20:16:57 +03:00
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
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
Kumataro
b870ad46bf
Merge pull request #24074 from Kumataro/fix24057 
Python: support tuple src for cv::add()/subtract()/... #24074

fix https://github.com/opencv/opencv/issues/24057

### 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
 2023-09-19 10:32:47 +03:00
HAN Liutong
f617fbe166
Merge pull request #24132 from hanliutong:rewrite-imgproc2 
Rewrite Universal Intrinsic code by using new API: ImgProc module Part 2 #24132

The goal of this series of PRs is to modify the SIMD code blocks guarded by CV_SIMD macro in the opencv/modules/imgproc folder: rewrite them by using the new Universal Intrinsic API.

This is the second part of the modification to the Imgproc module ( Part 1: #24058 ), And I tested this patch on RVV (QEMU) and AVX devices, `opencv_test_imgproc` is passed.

The patch is partially auto-generated by using the [rewriter](https://github.com/hanliutong/rewriter).

### 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
 2023-09-19 08:52:42 +03:00
Alexander Smorkalov
8f2e6640e3
Merge pull request #24288 from tailsu:sd/emscripten-3.1.45-fixes 
build fixes for emscripten 3.1.45
 2023-09-19 08:09:18 +03:00
Stefan Dragnev
9b5a719d80 build fixes for emscripten 3.1.45 2023-09-18 15:38:31 +02:00
Yuriy Chernyshov
494d201fda Add missing <sstream> includes 2023-09-05 22:04:26 +03:00
Kumataro
72bb8bb73c core: arm64: v_round() works with round to nearest, ties to even. 2023-09-04 10:27:55 +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
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
cudawarped
bea0c1b660 cuda: Fix GpuMat::copyTo and GpuMat::converTo python bindings 2023-08-01 15:09:37 +03:00
Alexander Smorkalov
b22c2505a8 Disable warning C5054 in VS 2022 C++20 2023-07-26 09:23:32 +03:00
Alexander Smorkalov
12acf5603a
Merge pull request #24001 from legrosbuffle:legrosbuffle-cvround-intrinsic 
Use intrinsics for `cvRound` on x86_64 `__GNUC__` (clang/gcc linux) too.
 2023-07-23 09:53:18 +03:00
Clement Courbet
3cce299a78 Use intrinsics for cvRound on x86 and x86_64 __GNUC__ (clang/gcc linux) too. 
We've measured a 7x improvement in speed for `cvRound` using the intrinsic.
 2023-07-21 10:57:54 +03:00
Alexander Smorkalov
1f7025f028
Merge pull request #23920 from loongson-zn:4.x 
Fix LoongArch Macro Definition
 2023-07-14 15:00:41 +03:00
Alexander Smorkalov
bd2695f01b
Merge pull request #23966 from hanliutong:popcount 
Add missing ”v_popcount“ for RVV and enable tests.
 2023-07-13 12:22:46 +03:00
Liutong HAN
a00818047f Add missing ”v_popcount“ for RVV and enable tests. 2023-07-11 16:10:27 +08:00
Zhang Na
10294a84fa Fix LoongArch Macro Definition 2023-07-05 17:42:39 +08:00
Berke
71796edf95
removed trailing semicolon after function 
It gives error when building projects with -Wpedantic -Werror

error: extra ‘;’ [-Werror=pedantic]

Issue ##23916
 2023-07-04 21:18:30 +03:00
Alexander Smorkalov
131dab774c Merge branch 'release_4.8.0' into 4.x 2023-06-28 15:22:43 +03:00
Alexander Smorkalov
f9a59f2592 Release OpenCV 4.8.0 2023-06-28 14:53:33 +03:00
Alexander Smorkalov
bf06bc92aa Merge branch '3.4' into merge-3.4 2023-06-23 20:12:58 +03:00
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
65b957a5b3
Merge pull request #23832 from asmorkalov:as/reshape_docs 
Document parameters of multi-dimentional reshape
 2023-06-21 09:04:17 +03:00
Alexander Smorkalov
9eaa7bd566 Document parameters of multi-dimentional reshape. 2023-06-20 21:54:49 +03:00
Alexander Smorkalov
51702ffd92 pre: OpenCV 4.8.0 (version++) 2023-06-20 15:52:57 +03:00
Alexander Smorkalov
805946baaf pre: OpenCV 3.4.20 (version++) 2023-06-20 14:10:08 +03:00
Alexander Smorkalov
004801f1c5 Merge remote-tracking branch 'origin/3.4' into merge-3.4 2023-06-20 09:56:57 +03:00
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(2*size.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
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 Smorkalov
4eec739624 Build warning fix on Windows for Eigen wrapper. 2023-05-17 10:12:02 +03:00
n0099
868787c364
Merge pull request #23342 from n0099:#23335 
Improve document of cv::RotatedRect for #23335 #23342

fix #23335

### 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
 2023-05-03 14:15:53 +03:00
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
Laurent Berger
23b819efb8
Merge pull request #23555 from LaurentBerger:doc_format 
don't ignore documentation for cv::format in doxygen #23555 

Issue https://github.com/opencv/opencv/issues/23553

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 issue
- [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
 2023-04-28 15:24:07 +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
Alexander Smorkalov
e4a29d93fe Merge remote-tracking branch 'origin/3.4' into merge-3.4 2023-04-21 10:55:04 +03:00
Alexander Smorkalov
3f02c9d5b9
Merge pull request #23310 from hanliutong:fix_hal_compatibility 
Fix HAL compatibility layer
 2023-04-11 12:43:54 +03:00
Alexander Alekhin
daf9de7463 Merge pull request #23383 from mshabunin:rvv-scalable-gcc 2023-04-10 13:35:43 +00:00
Alexander Smorkalov
f5a92cb43f
Merge pull request #22889 from D-Alex:patch-1 
core: improve doc for setNumThreads
 2023-04-07 16:37:40 +03:00
Alexander Smorkalov
3bcc3e70f1 Extended setNumThreads documentation according to code review. 2023-04-07 13:56:57 +03:00
Maksim Shabunin
b12c14514a RISC-V: allow building scalable RVV support with GCC, LLVM 16 support 2023-04-05 14:18:58 +03:00
HAN Liutong
a809ae4e88 Fix HAL compatibility layer and modify use cases. 2023-03-27 21:30:47 +08:00
unknown
ee302b063f Typo in enum cv::QuatEnum::EulerAnglesType 2023-03-24 14:03:14 +01:00
Alexey Shtern
c6e5f60525
Merge pull request #23301 from shtern:fix_quaternion 
Fixed strict type in slerp and spline; Fixed nlerp usage condition

Fixes #23293

The PR is fixing the issue described in [Issue #23293 ](https://github.com/opencv/opencv/issues/23293)

- [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
 2023-03-10 11:37:43 +03:00
Alexander Alekhin
fe59a5695f core(simd): 64-bit integer EQ/NE without misused 64F guard 2023-02-27 19:51:55 +00:00
Maksim Shabunin
903ec0ec60 RISC-V: support RVV 0.7 in mainline RVV intrinsics 2023-02-17 18:17:11 +03:00
Alexander Alekhin
47293f28cf Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2023-02-11 18:35:00 +00:00
Yannis Guyon
56102737d7
Merge pull request #23131 from y-guyon:align_ptr_intrin_sse 
Fix misaligned-pointer-use in intrin_sse.hpp

* Fix misaligned-pointer-use in intrin_sse.hpp

* Use _mm_loadu_si32() instead of memcpy()

* Use CV_DECL_ALIGNED instead of _mm_loadu_si32()
 2023-02-10 22:46:21 +00:00
Alexander Alekhin
44290af516 Merge pull request #23224 from VadimLevin:dev/vlevin/cxx-named-arguments 2023-02-08 17:31:30 +00:00
Maksim Shabunin
e4acd74e87 Fix some clang 14 warnings 2023-02-07 01:19:00 +03:00
Vadim Levin
b07031b594 feat: named arguments handling in Python interface 2023-02-06 22:14:58 +03:00
Maksim Shabunin
9efaa3cce7 RISC-V/RVV 0.7: v_add/v_sub saturation and avoiding 64-bit register in v_check_ 2023-01-30 23:25:53 +03:00
Alexander Alekhin
18cbfa4a4f Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2023-01-23 00:11:12 +00:00
Rostislav Vasilikhin
f3a03aefad cvIsInf(double) fix + regression test 2023-01-17 23:06:39 +01:00
Maksim Shabunin
c1e5c16ff3 Backport C-API cleanup (imgproc) from 5.x 2023-01-16 23:29:50 +03:00
Xxfore
ef0fcb9238
Merge pull request #22938 from Xxfore:4.x 
Use reinterpret instead of c-style casting for GCC

Co-authored-by: Xu Zhang <xu.zhang@hexintek.com>
Co-authored-by: Maksim Shabunin <maksim.shabunin@gmail.com>
 2023-01-11 14:11:16 +00:00
Alexander Alekhin
9208dcb07c Merge tag '4.7.0' 2022-12-28 15:23:46 +00:00
Alexander Smorkalov
725e440d27 release: OpenCV 4.7.0 2022-12-28 17:31:52 +03:00
Alexander Alekhin
eab7faf536 Merge tag '3.4.19' 2022-12-27 08:41:49 +00:00
Alexander Alekhin
83391ac59d release: OpenCV 3.4.19 2022-12-27 03:50:12 +00:00
cudawarped
692d6168b3 cuda: fix CUDA 12.0 build errors 2022-12-26 15:25:29 +02:00
Alexander Alekhin
b42c11de82 pre: OpenCV 4.7.0 (version++) 2022-12-25 17:00:22 +00:00
Alexander Alekhin
a494c75bfe pre: OpenCV 3.4.19 (version++) 2022-12-25 16:59:47 +00:00
fengyuentau
34a0897f90 add cv::flipND; support onnx slice with negative steps via cv::flipND 2022-12-23 16:39:53 +08:00
cudawarped
9aa5ab7557 cv::cuda: Replace all instances of texture references/objects with texture objects using the existing updated cv::cudev::Texture class. 
Fixes bugs in cv::cuda::demosaicing, cv::cuda::resize and cv::cuda::HoughSegmentDetector.
 2022-12-19 19:28:15 +02:00
Alexander Alekhin
420db56ffd Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2022-12-18 02:17:17 +00:00