Alexander Smorkalov
004801f1c5
Merge remote-tracking branch 'origin/3.4' into merge-3.4
2023-06-20 09:56:57 +03:00
dizcza
e625b32841
[opencv 3.x] back-ported tbb support ubuntu 22.04
2023-06-15 19:30:40 +03:00
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
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size:[32 x 32] type:6 continuous = true iterations:1000 nz=true pos=middle
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size:[32 x 32] type:6 continuous = true iterations:1000 nz=true pos=end
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size:[32 x 32] type:6 continuous = true iterations:1000 nz=false pos=none
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size:[32 x 32] type:6 continuous = false iterations:1000 nz=true pos=begin
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size:[32 x 32] type:6 continuous = false iterations:1000 nz=true pos=middle
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size:[32 x 32] type:6 continuous = false iterations:1000 nz=false pos=none
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size:[64 x 64] type:0 continuous = true iterations:1000 nz=true pos=begin
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size:[128 x 128] type:6 continuous = true iterations:1000 nz=true pos=middle
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size:[128 x 128] type:6 continuous = true iterations:1000 nz=false pos=none
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size:[128 x 128] type:6 continuous = false iterations:1000 nz=true pos=begin
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size:[128 x 128] type:6 continuous = false iterations:1000 nz=true pos=middle
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size:[128 x 128] type:6 continuous = false iterations:1000 nz=true pos=end
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size:[128 x 128] type:6 continuous = false iterations:1000 nz=false pos=none
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size:[320 x 240] type:0 continuous = true iterations:1000 nz=true pos=begin
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size:[320 x 240] type:0 continuous = true iterations:1000 nz=true pos=middle
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size:[320 x 240] type:0 continuous = true iterations:1000 nz=false pos=none
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size:[320 x 240] type:0 continuous = false iterations:1000 nz=false pos=none
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size:[320 x 240] type:2 continuous = true iterations:1000 nz=true pos=begin
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size:[320 x 240] type:2 continuous = true iterations:1000 nz=true pos=middle
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size:[320 x 240] type:2 continuous = true iterations:1000 nz=true pos=end
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size:[320 x 240] type:2 continuous = true iterations:1000 nz=false pos=none
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size:[320 x 240] type:2 continuous = false iterations:1000 nz=true pos=begin
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size:[320 x 240] type:2 continuous = false iterations:1000 nz=true pos=middle
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size:[320 x 240] type:2 continuous = false iterations:1000 nz=true pos=end
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size:[320 x 240] type:2 continuous = false iterations:1000 nz=false pos=none
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size:[320 x 240] type:4 continuous = true iterations:1000 nz=true pos=begin
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size:[320 x 240] type:4 continuous = true iterations:1000 nz=true pos=end
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size:[320 x 240] type:4 continuous = true iterations:1000 nz=false pos=none
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size:[320 x 240] type:4 continuous = false iterations:1000 nz=true pos=begin
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size:[320 x 240] type:4 continuous = false iterations:1000 nz=true pos=end
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size:[320 x 240] type:4 continuous = false iterations:1000 nz=false pos=none
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size:[640 x 480] type:0 continuous = true iterations:1000 nz=false pos=none
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size:[640 x 480] type:2 continuous = true iterations:1000 nz=true pos=end
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size:[640 x 480] type:2 continuous = true iterations:1000 nz=false pos=none
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size:[640 x 480] type:2 continuous = false iterations:1000 nz=true pos=end
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size:[640 x 480] type:2 continuous = false iterations:1000 nz=false pos=none
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size:[640 x 480] type:4 continuous = true iterations:1000 nz=true pos=begin
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size:[640 x 480] type:4 continuous = true iterations:1000 nz=true pos=middle
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size:[640 x 480] type:4 continuous = true iterations:1000 nz=true pos=end
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size:[640 x 480] type:4 continuous = true iterations:1000 nz=false pos=none
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size:[640 x 480] type:4 continuous = false iterations:1000 nz=true pos=begin
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size:[640 x 480] type:4 continuous = false iterations:1000 nz=true pos=middle
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size:[640 x 480] type:4 continuous = false iterations:1000 nz=true pos=end
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size:[640 x 480] type:4 continuous = false iterations:1000 nz=false pos=none
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size:[640 x 480] type:5 continuous = true iterations:1000 nz=true pos=begin
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size:[640 x 480] type:5 continuous = true iterations:1000 nz=true pos=middle
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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
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size:[640 x 480] type:5 continuous = false iterations:1000 nz=true pos=begin
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size:[640 x 480] type:5 continuous = false iterations:1000 nz=true pos=middle
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size:[640 x 480] type:5 continuous = false iterations:1000 nz=true pos=end
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size:[640 x 480] type:5 continuous = false iterations:1000 nz=false pos=none
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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
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size:[640 x 480] type:6 continuous = true iterations:1000 nz=true pos=end
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size:[640 x 480] type:6 continuous = true iterations:1000 nz=false pos=none
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size:[640 x 480] type:6 continuous = false iterations:1000 nz=true pos=begin
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size:[640 x 480] type:6 continuous = false iterations:1000 nz=true pos=middle
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size:[640 x 480] type:6 continuous = false iterations:1000 nz=true pos=end
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size:[640 x 480] type:6 continuous = false iterations:1000 nz=false pos=none
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size:[1024 x 768] type:0 continuous = true iterations:1000 nz=true pos=begin
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size:[1024 x 768] type:0 continuous = true iterations:1000 nz=true pos=middle
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size:[1024 x 768] type:0 continuous = true iterations:1000 nz=true pos=end
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size:[1024 x 768] type:0 continuous = true iterations:1000 nz=false pos=none
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size:[1024 x 768] type:0 continuous = false iterations:1000 nz=true pos=begin
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size:[1024 x 768] type:0 continuous = false iterations:1000 nz=true pos=middle
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size:[1024 x 768] type:0 continuous = false iterations:1000 nz=true pos=end
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size:[1024 x 768] type:0 continuous = false iterations:1000 nz=false pos=none
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size:[1024 x 768] type:2 continuous = true iterations:1000 nz=true pos=begin
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size:[1024 x 768] type:2 continuous = true iterations:1000 nz=true pos=middle
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size:[1024 x 768] type:2 continuous = true iterations:1000 nz=true pos=end
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size:[1024 x 768] type:2 continuous = true iterations:1000 nz=false pos=none
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size:[1024 x 768] type:2 continuous = false iterations:1000 nz=true pos=begin
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size:[1024 x 768] type:2 continuous = false iterations:1000 nz=true pos=middle
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size:[1024 x 768] type:2 continuous = false iterations:1000 nz=true pos=end
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size:[1024 x 768] type:2 continuous = false iterations:1000 nz=false pos=none
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size:[1024 x 768] type:4 continuous = true iterations:1000 nz=true pos=begin
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size:[1024 x 768] type:4 continuous = true iterations:1000 nz=true pos=middle
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size:[1024 x 768] type:4 continuous = true iterations:1000 nz=true pos=end
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size:[1024 x 768] type:4 continuous = true iterations:1000 nz=false pos=none
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size:[1024 x 768] type:4 continuous = false iterations:1000 nz=true pos=begin
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size:[1024 x 768] type:4 continuous = false iterations:1000 nz=true pos=middle
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size:[1024 x 768] type:4 continuous = false iterations:1000 nz=true pos=end
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size:[1024 x 768] type:4 continuous = false iterations:1000 nz=false pos=none
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size:[1024 x 768] type:5 continuous = true iterations:1000 nz=true pos=begin
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size:[1024 x 768] type:5 continuous = true iterations:1000 nz=true pos=middle
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size:[1024 x 768] type:5 continuous = true iterations:1000 nz=true pos=end
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size:[1024 x 768] type:5 continuous = true iterations:1000 nz=false pos=none
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size:[1024 x 768] type:5 continuous = false iterations:1000 nz=true pos=begin
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size:[1024 x 768] type:5 continuous = false iterations:1000 nz=true pos=middle
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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
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size:[1024 x 768] type:6 continuous = true iterations:1000 nz=true pos=begin
============================================================
size:[1024 x 768] type:6 continuous = true iterations:1000 nz=true pos=middle
============================================================
size:[1024 x 768] type:6 continuous = true iterations:1000 nz=true pos=end
============================================================
size:[1024 x 768] type:6 continuous = true iterations:1000 nz=false pos=none
============================================================
size:[1024 x 768] type:6 continuous = false iterations:1000 nz=true pos=begin
============================================================
size:[1024 x 768] type:6 continuous = false iterations:1000 nz=true pos=middle
============================================================
size:[1024 x 768] type:6 continuous = false iterations:1000 nz=true pos=end
============================================================
size:[1024 x 768] type:6 continuous = false iterations:1000 nz=false pos=none
============================================================
size:[2048 x 2048] type:0 continuous = true iterations:1000 nz=true pos=begin
============================================================
size:[2048 x 2048] type:0 continuous = true iterations:1000 nz=true pos=middle
============================================================
size:[2048 x 2048] type:0 continuous = true iterations:1000 nz=true pos=end
============================================================
size:[2048 x 2048] type:0 continuous = true iterations:1000 nz=false pos=none
============================================================
size:[2048 x 2048] type:0 continuous = false iterations:1000 nz=true pos=begin
============================================================
size:[2048 x 2048] type:0 continuous = false iterations:1000 nz=true pos=middle
============================================================
size:[2048 x 2048] type:0 continuous = false iterations:1000 nz=true pos=end
============================================================
size:[2048 x 2048] type:0 continuous = false iterations:1000 nz=false pos=none
============================================================
size:[2048 x 2048] type:2 continuous = true iterations:1000 nz=true pos=begin
============================================================
size:[2048 x 2048] type:2 continuous = true iterations:1000 nz=true pos=middle
============================================================
size:[2048 x 2048] type:2 continuous = true iterations:1000 nz=true pos=end
============================================================
size:[2048 x 2048] type:2 continuous = true iterations:1000 nz=false pos=none
============================================================
size:[2048 x 2048] type:2 continuous = false iterations:1000 nz=true pos=begin
============================================================
size:[2048 x 2048] type:2 continuous = false iterations:1000 nz=true pos=middle
============================================================
size:[2048 x 2048] type:2 continuous = false iterations:1000 nz=true pos=end
============================================================
size:[2048 x 2048] type:2 continuous = false iterations:1000 nz=false pos=none
============================================================
size:[2048 x 2048] type:4 continuous = true iterations:1000 nz=true pos=begin
============================================================
size:[2048 x 2048] type:4 continuous = true iterations:1000 nz=true pos=middle
============================================================
size:[2048 x 2048] type:4 continuous = true iterations:1000 nz=true pos=end
cv::hasNonZero =>1 perf:895.381ms => 1116.84 im/s
cv::countNonZero =>1 perf:882.569ms => 1133.06 im/s *
============================================================
size:[2048 x 2048] type:4 continuous = true iterations:1000 nz=false pos=none
cv::hasNonZero =>0 perf:899.53ms => 1111.69 im/s
cv::countNonZero =>0 perf:870.894ms => 1148.24 im/s *
============================================================
size:[2048 x 2048] type:4 continuous = false iterations:1000 nz=true pos=begin
============================================================
size:[2048 x 2048] type:4 continuous = false iterations:1000 nz=true pos=middle
============================================================
size:[2048 x 2048] type:4 continuous = false iterations:1000 nz=true pos=end
============================================================
size:[2048 x 2048] type:4 continuous = false iterations:1000 nz=false pos=none
============================================================
size:[2048 x 2048] type:5 continuous = true iterations:1000 nz=true pos=begin
============================================================
size:[2048 x 2048] type:5 continuous = true iterations:1000 nz=true pos=middle
============================================================
size:[2048 x 2048] type:5 continuous = true iterations:1000 nz=true pos=end
============================================================
size:[2048 x 2048] type:5 continuous = true iterations:1000 nz=false pos=none
============================================================
size:[2048 x 2048] type:5 continuous = false iterations:1000 nz=true pos=begin
============================================================
size:[2048 x 2048] type:5 continuous = false iterations:1000 nz=true pos=middle
============================================================
size:[2048 x 2048] type:5 continuous = false iterations:1000 nz=true pos=end
============================================================
size:[2048 x 2048] type:5 continuous = false iterations:1000 nz=false pos=none
============================================================
size:[2048 x 2048] type:6 continuous = true iterations:1000 nz=true pos=begin
============================================================
size:[2048 x 2048] type:6 continuous = true iterations:1000 nz=true pos=middle
============================================================
size:[2048 x 2048] type:6 continuous = true iterations:1000 nz=true pos=end
cv::hasNonZero =>1 perf:2018.92ms => 495.313 im/s
cv::countNonZero =>1 perf:1966.37ms => 508.552 im/s *
============================================================
size:[2048 x 2048] type:6 continuous = true iterations:1000 nz=false pos=none
cv::hasNonZero =>0 perf:2005.87ms => 498.537 im/s
cv::countNonZero =>0 perf:1992.78ms => 501.812 im/s *
============================================================
size:[2048 x 2048] type:6 continuous = false iterations:1000 nz=true pos=begin
============================================================
size:[2048 x 2048] type:6 continuous = false iterations:1000 nz=true pos=middle
============================================================
size:[2048 x 2048] type:6 continuous = false iterations:1000 nz=true pos=end
============================================================
size:[2048 x 2048] type:6 continuous = false iterations:1000 nz=false pos=none
============================================================
size:[1031 x 1000] type:0 continuous = true iterations:1000 nz=true pos=begin
============================================================
size:[1031 x 1000] type:0 continuous = true iterations:1000 nz=true pos=middle
============================================================
size:[1031 x 1000] type:0 continuous = true iterations:1000 nz=true pos=end
============================================================
size:[1031 x 1000] type:0 continuous = true iterations:1000 nz=false pos=none
============================================================
size:[1031 x 1000] type:0 continuous = false iterations:1000 nz=true pos=begin
============================================================
size:[1031 x 1000] type:0 continuous = false iterations:1000 nz=true pos=middle
============================================================
size:[1031 x 1000] type:0 continuous = false iterations:1000 nz=true pos=end
============================================================
size:[1031 x 1000] type:0 continuous = false iterations:1000 nz=false pos=none
============================================================
size:[1031 x 1000] type:2 continuous = true iterations:1000 nz=true pos=begin
============================================================
size:[1031 x 1000] type:2 continuous = true iterations:1000 nz=true pos=middle
============================================================
size:[1031 x 1000] type:2 continuous = true iterations:1000 nz=true pos=end
============================================================
size:[1031 x 1000] type:2 continuous = true iterations:1000 nz=false pos=none
============================================================
size:[1031 x 1000] type:2 continuous = false iterations:1000 nz=true pos=begin
============================================================
size:[1031 x 1000] type:2 continuous = false iterations:1000 nz=true pos=middle
============================================================
size:[1031 x 1000] type:2 continuous = false iterations:1000 nz=true pos=end
============================================================
size:[1031 x 1000] type:2 continuous = false iterations:1000 nz=false pos=none
============================================================
size:[1031 x 1000] type:4 continuous = true iterations:1000 nz=true pos=begin
============================================================
size:[1031 x 1000] type:4 continuous = true iterations:1000 nz=true pos=middle
============================================================
size:[1031 x 1000] type:4 continuous = true iterations:1000 nz=true pos=end
============================================================
size:[1031 x 1000] type:4 continuous = true iterations:1000 nz=false pos=none
============================================================
size:[1031 x 1000] type:4 continuous = false iterations:1000 nz=true pos=begin
============================================================
size:[1031 x 1000] type:4 continuous = false iterations:1000 nz=true pos=middle
============================================================
size:[1031 x 1000] type:4 continuous = false iterations:1000 nz=true pos=end
============================================================
size:[1031 x 1000] type:4 continuous = false iterations:1000 nz=false pos=none
============================================================
size:[1031 x 1000] type:5 continuous = true iterations:1000 nz=true pos=begin
============================================================
size:[1031 x 1000] type:5 continuous = true iterations:1000 nz=true pos=middle
============================================================
size:[1031 x 1000] type:5 continuous = true iterations:1000 nz=true pos=end
============================================================
size:[1031 x 1000] type:5 continuous = true iterations:1000 nz=false pos=none
============================================================
size:[1031 x 1000] type:5 continuous = false iterations:1000 nz=true pos=begin
============================================================
size:[1031 x 1000] type:5 continuous = false iterations:1000 nz=true pos=middle
============================================================
size:[1031 x 1000] type:5 continuous = false iterations:1000 nz=true pos=end
============================================================
size:[1031 x 1000] type:5 continuous = false iterations:1000 nz=false pos=none
============================================================
size:[1031 x 1000] type:6 continuous = true iterations:1000 nz=true pos=begin
============================================================
size:[1031 x 1000] type:6 continuous = true iterations:1000 nz=true pos=middle
============================================================
size:[1031 x 1000] type:6 continuous = true iterations:1000 nz=true pos=end
============================================================
size:[1031 x 1000] type:6 continuous = true iterations:1000 nz=false pos=none
============================================================
size:[1031 x 1000] type:6 continuous = false iterations:1000 nz=true pos=begin
============================================================
size:[1031 x 1000] type:6 continuous = false iterations:1000 nz=true pos=middle
============================================================
size:[1031 x 1000] type:6 continuous = false iterations:1000 nz=true pos=end
============================================================
size:[1031 x 1000] type:6 continuous = false iterations:1000 nz=false pos=none
done
```
2023-06-09 13:37:20 +03:00
Dmitry Kurtaev
380caa1a87
Merge pull request #23691 from dkurt:pycv_float16_fixes
...
Import and export np.float16 in Python #23691
### Pull Request Readiness Checklist
* Also, fixes `cv::norm` with `NORM_INF` and `CV_16F`
resolves https://github.com/opencv/opencv/issues/23687
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2023-05-26 18:56:21 +03:00
Alexander Smorkalov
65487946cc
Added final constrants check to solveLP to filter out flating-point numeric issues.
2023-05-25 17:29:01 +03:00
Alexander Smorkalov
d4861bfd1f
Merge remote-tracking branch 'origin/3.4' into merge-3.4
2023-05-24 14:37:48 +03:00
cudawarped
7539abecdb
cuda: add python bindings to allow GpuMat and Stream objects to be initialized from raw pointers
2023-05-22 11:02:04 +03:00
Alexander Alekhin
04d71da6e7
Merge pull request #23566 from seanm:atomic-bool
2023-05-16 10:46:59 +00:00
Sean McBride
27e10efa66
Use std::atomic<bool> as it's necessary for correct thread safety
...
Now that C++11 is required, we can unconditionally use std::atomic in this case, which is more correct.
2023-05-01 16:44:34 -04:00
Pierre Chatelier
6dd8a9b6ad
Merge pull request #13879 from chacha21:REDUCE_SUM2
...
add REDUCE_SUM2 #13879
proposal to add REDUCE_SUM2 to cv::reduce, an operation that sums up the square of elements
2023-04-28 20:42:52 +03:00
Sean McBride
58e4a880a2
Deprecated convertTypeStr and made new variant that also takes the buffer size
...
This allows removing the unsafe sprintf.
2023-04-26 09:48:15 -04:00
Giles Payne
38e35d5137
Fix ocl::device::isIntel implementation
2023-04-24 22:01:53 +09:00
Alexander Smorkalov
e4a29d93fe
Merge remote-tracking branch 'origin/3.4' into merge-3.4
2023-04-21 10:55:04 +03:00
Sean McBride
47bea69322
Merge pull request #23055 from seanm:sprintf2
...
* Replaced most remaining sprintf with snprintf
* Deprecated encodeFormat and introduced new method that takes the buffer length
* Also increased buffer size at call sites to be a little bigger, in case int is 64 bit
2023-04-18 09:22:59 +03:00
eplankin
fd8b346c3e
Merge pull request #23443 from eplankin:3.4
...
* Update IPPICV binaries (20230330)
* Revert "core(IPP): disable some ippsMagnitude_32f calls"
This reverts commit 8069a6b4f8
.
* Reverted changes in norm() and count_non_zero()
2023-04-07 09:14:42 +00:00
Christian Henkel
c9e42c5050
two typos
2023-03-22 09:17:41 +03:00
Alexander Alekhin
d3ae175bca
Merge remote-tracking branch 'upstream/3.4' into merge-3.4
2023-01-28 10:01:23 +00:00
Yannis Guyon
bf29a4d746
Avoid double-checked locking with TSAN in parallel
...
Omit the first check of the double-checked locking pattern in
recordException() in parallel.cpp when CV_THREAD_SANITIZER is defined.
This should only slow recordException() down when the thread sanitizer
is used, and avoids the TSAN data race warning.
2023-01-27 13:36:33 +01:00
Alexander Alekhin
18cbfa4a4f
Merge remote-tracking branch 'upstream/3.4' into merge-3.4
2023-01-23 00:11:12 +00:00
Yang Chao
e0aa677388
Open CV_CPU_NEON_DOTPROD on Apple silicon devices
2023-01-09 19:27:35 +08:00
Alexander Alekhin
bc8c912c7a
Merge remote-tracking branch 'upstream/3.4' into merge-3.4
2022-12-24 13:54:58 +00:00
fengyuentau
34a0897f90
add cv::flipND; support onnx slice with negative steps via cv::flipND
2022-12-23 16:39:53 +08:00
Alexander Alekhin
da43778c1f
Merge pull request #22981 from alalek:core_freeze_cache_dir_prefix_4.x
2022-12-19 17:29:57 +00:00
Vincent Rabaud
7463e9b8bb
Even faster CV_PAUSE on SkyLake and above.
...
No need to loop as RDTSC is 3/4 times faster than _mm_pause.
2022-12-19 14:15:34 +01:00
Alexander Alekhin
420db56ffd
Merge remote-tracking branch 'upstream/3.4' into merge-3.4
2022-12-18 02:17:17 +00:00
Alexander Alekhin
4824ce300f
core: freeze cache directory prefix - "4.x"
2022-12-18 00:24:52 +00:00
Alexander Alekhin
eace6adb6d
Merge pull request #22934 from alalek:fix_filestorage_binding
2022-12-17 03:28:13 +00:00
Alexander Alekhin
6e3700593f
compatibility: keep Ptr<FileStorage> stubs till OpenCV 5.0
2022-12-16 00:47:44 +00:00
Alexander Alekhin
6a8c5a1d27
python: resolve Ptr<FileStorage> requirement issue
2022-12-16 00:47:44 +00:00
Vincent Rabaud
b7b08fa0c3
Fix slower CV_PAUSE on SkyLake and above.
...
This is fixing https://github.com/opencv/opencv/issues/22852
2022-12-15 14:18:57 +01:00
Alexander Alekhin
7e3c53b9d3
core(logger): strip path prefix
2022-12-07 23:58:36 +00:00
Alexander Alekhin
b16f76eede
Merge remote-tracking branch 'upstream/3.4' into merge-3.4
2022-12-03 12:39:41 +00:00
Christine Poerschke
4792837f2e
Merge pull request #22865 from cpoerschke:3.4-issue-22860
...
ocl_minMaxIdx to call minmaxloc.cl for OpenCL 1.2+ only
2022-12-03 05:29:04 +00:00
Alexander Smorkalov
1c3e287d32
More fixes for OpenCL error reporting.
2022-11-28 09:47:51 +03:00
Alexander Smorkalov
7622fbf895
Fixed OpenGL errors formatting.
2022-11-25 16:46:12 +03:00
Amir Hassan
3f371fe2dd
Merge pull request #22855 from kallaballa:print_cl_status_on_fail
...
Print CL status code on error in opengl interop functions
2022-11-25 09:13:57 +03:00
Alexander Alekhin
5d14cc68b7
Merge remote-tracking branch 'upstream/3.4' into merge-3.4
2022-11-16 16:54:11 +00:00
Alexander Alekhin
54531f8e3b
core: support CV_Check*() macros with 'bool' parameters
2022-11-15 11:47:16 +00:00
Alexander Alekhin
762481411d
Merge remote-tracking branch 'upstream/3.4' into merge-3.4
2022-10-15 16:44:47 +00:00
Vincent Rabaud
38c9c20a35
Move marking memory as initialized earlier.
2022-09-28 21:58:17 +02:00
Sean McBride
1829eba584
Fixed most clang -Wextra-semi warnings
2022-09-27 18:06:46 -04:00
wxsheng
4154bd0667
Add Loongson Advanced SIMD Extension support: -DCPU_BASELINE=LASX
...
* Add Loongson Advanced SIMD Extension support: -DCPU_BASELINE=LASX
* Add resize.lasx.cpp for Loongson SIMD acceleration
* Add imgwarp.lasx.cpp for Loongson SIMD acceleration
* Add LASX acceleration support for dnn/conv
* Add CV_PAUSE(v) for Loongarch
* Set LASX by default on Loongarch64
* LoongArch: tune test threshold for Core/HAL.mat_decomp/15
Co-authored-by: shengwenxue <shengwenxue@loongson.cn>
2022-09-10 09:39:43 +03:00
Yuantao Feng
9dc844a6e1
Merge pull request #22346 from fengyuentau:mat1d_part1
...
Changes separated from Mat 1D support in core #18594 (#22346 )
2022-09-09 12:56:30 +03:00
Alexander Alekhin
2ebdc04787
Merge remote-tracking branch 'upstream/3.4' into merge-3.4
2022-08-14 15:50:42 +00:00
Alexander Smorkalov
2ffa7ac0da
Merge pull request #22217 from CSharperMantle:CSharperMantle-patch-steady-clock
...
Use `std::chrono::steady_clock` in `getTickCount`
2022-08-03 14:09:45 +03:00
Alexander Alekhin
0862d69a6e
Merge pull request #22271 from tomoaki0705:dotprod_neon
2022-07-25 15:00:32 +00:00
Maksim Shabunin
f729202272
core: remove unnecessary pointer cleanup in BufferArea
2022-07-24 11:58:17 +03:00
Tomoaki Teshima
b3269b08a1
neon: add dotprod dispatch implementation
...
* read vector at runtime
* add enum
2022-07-20 19:25:39 +09:00
HAN Liutong
0ef803950b
Merge pull request #22179 from hanliutong:new-rvv
...
[GSoC] New universal intrinsic backend for RVV
* Add new rvv backend (partially implemented).
* Modify the framework of Universal Intrinsic.
* Add CV_SIMD macro guards to current UI code.
* Use vlanes() instead of nlanes.
* Modify the UI test.
* Enable the new RVV (scalable) backend.
* Remove whitespace.
* Rename and some others modify.
* Update intrin.hpp but still not work on AVX/SSE
* Update conditional compilation macros.
* Use static variable for vlanes.
* Use max_nlanes for array defining.
2022-07-19 20:02:00 +03:00
Rong Mantle Bao
fa613e393f
Read CV_CXX11 for C++11 detection
2022-07-10 19:21:17 +08:00