Rostislav Vasilikhin
a7e53aa184
Merge pull request #25671 from savuor:rv/arithm_extend_tests
...
Tests added for mixed type arithmetic operations #25671
### Changes
* added accuracy tests for mixed type arithmetic operations
_Note: div-by-zero values are removed from checking since the result is implementation-defined in common case_
* added perf tests for the same cases
* fixed a typo in `getMulExtTab()` function that lead to dead code
### 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
2024-06-02 14:28:06 +03:00
Rostislav Vasilikhin
b267f1791c
Merge pull request #25633 from savuor:rv/rotate_tests
...
Tests for cv::rotate() added #25633
fixes #25449
### 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
2024-05-25 11:23:31 +03:00
Rostislav Vasilikhin
357b9abaef
Merge pull request #25450 from savuor:rv/svd_perf
...
Perf tests for SVD and solve() created #25450
fixes #25336
### 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
2024-04-27 14:33:13 +03:00
Alexander Alekhin
40533dbf69
Merge pull request #24918 from opencv-pushbot:gitee/alalek/core_convertfp16_replacement
...
core(OpenCL): optimize convertTo() with CV_16F (convertFp16() replacement) #24918
relates #24909
relates #24917
relates #24892
Performance changes:
- [x] 12700K (1 thread) + Intel iGPU
|Name of Test|noOCL|convertFp16|convertTo BASE|convertTo PATCH|
|---|:-:|:-:|:-:|:-:|
|ConvertFP16FP32MatMat::OCL_Core|3.130|3.152|3.127|3.136|
|ConvertFP16FP32MatUMat::OCL_Core|3.030|3.996|3.007|2.671|
|ConvertFP16FP32UMatMat::OCL_Core|3.010|3.101|3.056|2.854|
|ConvertFP16FP32UMatUMat::OCL_Core|3.016|3.298|2.072|2.061|
|ConvertFP32FP16MatMat::OCL_Core|2.697|2.652|2.723|2.721|
|ConvertFP32FP16MatUMat::OCL_Core|2.752|4.268|2.662|2.947|
|ConvertFP32FP16UMatMat::OCL_Core|2.706|2.601|2.603|2.528|
|ConvertFP32FP16UMatUMat::OCL_Core|2.704|3.215|1.999|1.988|
Patched version is not worse than convertFp16 and convertTo baseline (except MatUMat 32->16, baseline uses CPU code+dst buffer map).
There are still gaps against noOpenCL(CPU only) mode due to T-API implementation issues (unnecessary synchronization).
- [x] 12700K + AMD dGPU
|Name of Test|noOCL|convertFp16 dGPU|convertTo BASE dGPU|convertTo PATCH dGPU|
|---|:-:|:-:|:-:|:-:|
|ConvertFP16FP32MatMat::OCL_Core|3.130|3.133|3.172|3.087|
|ConvertFP16FP32MatUMat::OCL_Core|3.030|1.713|9.559|1.729|
|ConvertFP16FP32UMatMat::OCL_Core|3.010|6.515|6.309|4.452|
|ConvertFP16FP32UMatUMat::OCL_Core|3.016|0.242|23.597|0.170|
|ConvertFP32FP16MatMat::OCL_Core|2.697|2.641|2.713|2.689|
|ConvertFP32FP16MatUMat::OCL_Core|2.752|4.076|6.483|4.191|
|ConvertFP32FP16UMatMat::OCL_Core|2.706|9.042|16.481|1.834|
|ConvertFP32FP16UMatUMat::OCL_Core|2.704|0.229|15.730|0.176|
convertTo-baseline can't compile OpenCL kernel for FP16 properly - FIXED.
dGPU has much more power, so results are x16-17 better than single cpu core.
Patched version is not worse than convertFp16 and convertTo baseline.
There are still gaps against noOpenCL(CPU only) mode due to T-API implementation issues (unnecessary synchronization) and required memory transfers.
Co-authored-by: Alexander Alekhin <alexander.a.alekhin@gmail.com>
2024-01-26 12:56:52 +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
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
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
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
Pierre Chatelier
6dd8a9b6ad
Merge pull request #13879 from chacha21:REDUCE_SUM2
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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
Kumataro
602caa9cd6
Merge pull request #21937 from Kumataro:4.x-fix-21911
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* Fix warnings for clang15
* Fix warnings: Remove unnecessary code
* Fix warnings: Remove unnecessary code
2022-05-13 17:32:05 +00:00
rogday
e16cb8b4a2
Merge pull request #21703 from rogday:transpose
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Add n-dimensional transpose to core
* add n-dimensional transpose to core
* add performance test, write sequentially and address review comments
2022-03-14 13:10:04 +00:00
Suleyman TURKMEN
0e6a2c0491
fix legacy constants
2022-01-03 15:08:10 +03:00
rogday
f044037ec5
Merge pull request #20733 from rogday:argmaxnd
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Implement ArgMax and ArgMin
* add reduceArgMax and reduceArgMin
* fix review comments
* address review concerns
2021-11-28 16:17:46 +00:00
Dale Phurrough
c2ce3d927a
UMat usageFlags fixes opencv/opencv#19807
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- corrects code to support non- USAGE_DEFAULT settings
- accuracy, regression, perf test cases
- not tested on the 3.x branch
2021-06-03 16:33:03 +02:00
Alexander Alekhin
68d15fc62e
Merge remote-tracking branch 'upstream/3.4' into merge-3.4
2021-04-08 11:23:24 +00:00
Aaron Greig
f3f46096d6
Relax accuracy requirements in the OpenCL sqrt perf arithmetic test.
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Also bring perf_imgproc CornerMinEigenVal accuracy requirements in line with
the test_imgproc accuracy requirements on that test and fix indentation on
the latter.
Partially addresses issue #9821
2021-04-06 17:32:48 +01:00
Dale Phurrough
ad94d8cc4f
Merge pull request #19029 from diablodale:fix19004-memthreadstart
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add thread-safe startup of fastMalloc and fastFree
* add perf test core memory allocation
* fix threading in isAlignedAllocationEnabled()
* tweaks requested by maintainer
2020-12-08 10:05:14 +00:00
Alexander Alekhin
cf2a3c8e74
Merge remote-tracking branch 'upstream/3.4' into merge-3.4
2020-04-02 21:52:32 +00:00
Alexander Alekhin
54063c40de
core(ocl): options to control buffer access flags
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- control using of clEnqueueMapBuffer or clEnqueueReadBuffer[Rect]
- added benchmarks with OpenCL buffer access use cases
2020-04-02 11:11:06 +00:00
Alexander Alekhin
65573784c4
Merge remote-tracking branch 'upstream/3.4' into merge-3.4
2019-10-09 19:46:18 +00:00
Sayed Adel
f2fe6f40c2
Merge pull request #15510 from seiko2plus:issue15506
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* core: rework and optimize SIMD implementation of dotProd
- add new universal intrinsics v_dotprod[int32], v_dotprod_expand[u&int8, u&int16, int32], v_cvt_f64(int64)
- add a boolean param for all v_dotprod&_expand intrinsics that change the behavior of addition order between
pairs in some platforms in order to reach the maximum optimization when the sum among all lanes is what only matters
- fix clang build on ppc64le
- support wide universal intrinsics for dotProd_32s
- remove raw SIMD and activate universal intrinsics for dotProd_8
- implement SIMD optimization for dotProd_s16&u16
- extend performance test data types of dotprod
- fix GCC VSX workaround of vec_mule and vec_mulo (in little-endian it must be swapped)
- optimize v_mul_expand(int32) on VSX
* core: remove boolean param from v_dotprod&_expand and implement v_dotprod_fast&v_dotprod_expand_fast
this changes made depend on "terfendail" review
2019-10-07 22:01:35 +03:00
Alexander Alekhin
19a4b51371
Merge remote-tracking branch 'upstream/3.4' into merge-3.4
2019-08-16 18:48:08 +03:00
Paul E. Murphy
b2135be594
fast_math: add extra perf/unit tests
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Add a basic sanity test to verify the rounding functions
work as expected.
Likewise, extend the rounding performance test to cover the
additional float -> int fast math functions.
2019-08-07 14:59:46 -05:00
Alexander Alekhin
332c37f332
Merge remote-tracking branch 'upstream/3.4' into merge-3.4
2019-03-06 11:43:16 +03:00
Alexander Alekhin
f1f0f630c7
core: disable I/O perf test
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- can be enable separately if needed
- not stable (due storage I/O processing)
2019-02-27 18:07:45 +03:00
Alexander Alekhin
2e0150e601
Merge remote-tracking branch 'upstream/3.4' into merge-3.4
2018-12-03 18:38:27 +03:00
Vitaly Tuzov
00c9ab8c23
Merge pull request #13317 from terfendail:norm_wintr
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* Added performance tests for hal::norm functions
* Added sum of absolute differences intrinsic
* norm implementation updated to use wide universal intrinsics
* improve and fix v_reduce_sad on VSX
2018-11-29 19:34:14 +03:00
Alexander Alekhin
dca657a2fd
Merge remote-tracking branch 'upstream/3.4' into merge-3.4
2018-09-10 00:10:21 +03:00
Hamdi Sahloul
a39e0daacf
Utilize CV_UNUSED macro
2018-09-07 20:33:52 +09:00
Alexander Alekhin
73bfe68821
Merge remote-tracking branch 'upstream/3.4' into merge-3.4
2018-09-07 12:40:27 +03:00
Vadim Pisarevsky
80b62a41c6
Merge pull request #12411 from vpisarev:wide_convert
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* rewrote Mat::convertTo() and convertScaleAbs() to wide universal intrinsics; added always-available and SIMD-optimized FP16<=>FP32 conversion
* fixed compile warnings
* fix some more compile errors
* slightly relaxed accuracy threshold for int->float conversion (since we now do it using single-precision arithmetics, not double-precision)
* fixed compile errors on iOS, Android and in the baseline C++ version (intrin_cpp.hpp)
* trying to fix ARM-neon builds
* trying to fix ARM-neon builds
* trying to fix ARM-neon builds
* trying to fix ARM-neon builds
2018-09-06 19:36:59 +03:00
Vadim Pisarevsky
54279523a3
Merge pull request #12437 from vpisarev:avx2_fixes
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* trying to fix the custom AVX2 builder test failures (false alarms)
* fixed compile error with CPU_BASELINE=AVX2 on x86; raised tolerance thresholds in a couple of tests
* fixed compile error with CPU_BASELINE=AVX2 on x86; raised tolerance thresholds in a couple of tests
* fixed compile error with CPU_BASELINE=AVX2 on x86; raised tolerance thresholds in a couple of tests
* seemingly disabled false alarm warning in surf.cpp; increased tolerance thresholds in the tests for SolvePnP and in DNN/ENet
2018-09-06 18:56:55 +03:00
Jakub Golinowski
9f1218b00b
Merge pull request #11897 from Jakub-Golinowski:hpx_backend
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* Add HPX backend for OpenCV implementation
Adds hpx backend for cv::parallel_for_() calls respecting the nstripes chunking parameter. C++ code for the backend is added to modules/core/parallel.cpp. Also, the necessary changes to cmake files are introduced.
Backend can operate in 2 versions (selectable by cmake build option WITH_HPX_STARTSTOP): hpx (runtime always on) and hpx_startstop (start and stop the backend for each cv::parallel_for_() call)
* WIP: Conditionally include hpx_main.hpp to tests in core module
Header hpx_main.hpp is included to both core/perf/perf_main.cpp and core/test/test_main.cpp.
The changes to cmake files for linking hpx library to above mentioned test executalbles are proposed but have issues.
* Add coditional iclusion of hpx_main.hpp to cpp cpu modules
* Remove start/stop version of hpx backend
2018-08-31 16:23:26 +03:00
Alexander Alekhin
b24fc6954d
core(perf): fix addScalar test
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keep the same type for passed Scalar values
2018-08-16 19:36:28 +03:00
Alexander Alekhin
b0ee5d9023
core: CV_NODISCARD macro with semantic of [[nodiscard]] attr
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[[nodiscard]] is defined in C++17.
There is fallback alias for modern GCC / Clang compilers.
2018-07-16 18:03:32 +03:00
Alexander Alekhin
65726e4244
core(hal): improve v_select() SSE4.1+
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v_select 'mask' is restricted to these values only: 0 or ~0 (0xff/0xffff/etc)
mask in accuracy test is updated.
2018-04-23 13:17:53 +03:00
Vadim Pisarevsky
53661d55ae
Merge pull request #10406 from seiko2plus:coreUnvintrinCopy
2018-02-20 14:50:17 +00:00
Alexander Alekhin
4a297a2443
ts: refactor OpenCV tests
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- removed tr1 usage (dropped in C++17)
- moved includes of vector/map/iostream/limits into ts.hpp
- require opencv_test + anonymous namespace (added compile check)
- fixed norm() usage (must be from cvtest::norm for checks) and other conflict functions
- added missing license headers
2018-02-03 19:39:47 +00:00
Alexander Alekhin
a5cd62f7bf
core(perf): refactor kmeans test
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- don't use RNG for "task size" parameters (N, K, dims)
- add "good" kmeans test data (without singularities: K > unique points)
2018-01-22 14:25:29 +03:00
Sayed Adel
fd0ac962fb
core: replace raw intrinsics with universal intrinsics in copy.cpp
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- use universal intrinsic instead of raw intrinsic
- add performance check for Mat::copyTo/setTo with mask
2017-12-26 05:30:32 +02:00
Tomoaki Teshima
ca1a0a1108
core: remove raw SSE2/NEON implementation from convert.cpp ( #9831 )
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* remove raw SSE2/NEON implementation from convert.cpp
* remove raw implementation from Cvt_SIMD
* remove raw implementation from cvtScale_SIMD
* remove raw implementation from cvtScaleAbs_SIMD
* remove duplicated implementation cvt_<float, short>
* remove duplicated implementation cvtScale_<short, short, float>
* add "from double" version of Cvt_SIMD
* modify the condition of test ConvertScaleAbs
* Update convert.cpp
fixed crash in cvtScaleAbs(8s=>8u)
* fixed compile error on Win32
* fixed several test failures because of accuracy loss in cvtScale(int=>int)
* fixed NEON implementation of v_cvt_f64(int=>double) intrinsic
* another attempt to fix test failures
* keep trying to fix the test failures and just introduced compile warnings
* fixed one remaining test (subtractScalar)
2017-12-15 00:00:35 +03:00
Tomoaki Teshima
3cbe60cca2
Merge pull request #9753 from tomoaki0705:universalMatmul
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* add accuracy test and performance check for matmul
* add performance tests for transform and dotProduct
* add test Core_TransformLargeTest for 8u version of transform
* remove raw SSE2/NEON implementation from matmul.cpp
* use universal intrinsic instead of raw intrinsic
* remove unused templated function
* add v_matmuladd which multiply 3x3 matrix and add 3x1 vector
* add v_rotate_left/right in universal intrinsic
* suppress intrinsic on some function and platform
* add pure SW implementation of new universal intrinsics
* add test for new universal intrinsics
* core: prevent memory access after the end of buffer
* fix perf tests
2017-11-20 15:56:53 +03:00
Alexander Alekhin
582bb3c311
core(perf): added Hamming tests
2017-07-01 00:49:18 +00:00
Vitaly Tuzov
2492c299f3
Extended set of existing performance test to OpenVX HAL suitable execution modes
2017-04-27 12:32:29 +03:00
Pavel Vlasov
35c7216846
IPP for OpenCV 2017u2 initial enabling patch;
2017-04-20 20:26:30 +03:00
Alexander Alekhin
a901cc542b
test: fix tolerance perf check for Exp/Log/Sqrt
2016-10-20 16:54:48 +03:00
Alexander Alekhin
43c48e2ed1
test: update Div and ConvertScaleAbs perf tests
2016-10-20 16:54:46 +03:00
Alexander Alekhin
5bafc1db75
test: fix tolerance
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cv::rand result is not bitexact for floating-point numbers
2016-10-20 16:54:33 +03:00
Alexander Alekhin
abad2ca76c
test: fix tolerance
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cv::rand result is not bitexact for floating-point numbers
2016-10-20 16:54:30 +03:00
Maksim Shabunin
dc704d77ac
Fixed several GCC 5.x warnings
2016-09-01 15:44:01 +03:00
