Liutong HAN
ce0516282a
Optimize the v_lut for RVV.
2023-11-23 15:06:04 +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
