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:[64 x 64] type:2 continuous = true iterations:1000 nz=false pos=none
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size:[128 x 128] type:5 continuous = false iterations:1000 nz=false pos=none
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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=true pos=end
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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=true pos=begin
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size:[320 x 240] type:0 continuous = false iterations:1000 nz=true pos=middle
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size:[320 x 240] type:0 continuous = false iterations:1000 nz=true pos=end
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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 = false iterations:1000 nz=true pos=end
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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
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size:[640 x 480] type:2 continuous = true iterations:1000 nz=true pos=middle
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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=begin
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size:[640 x 480] type:2 continuous = false iterations:1000 nz=true pos=middle
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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
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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
============================================================
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
...
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
...
* Fix warnings for clang15
* Fix warnings: Remove unnecessary code
* Fix warnings: Remove unnecessary code
2022-05-13 17:32:05 +00:00
Dale Phurrough
c2ce3d927a
UMat usageFlags fixes opencv/opencv#19807
...
- 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
Aaron Greig
f3f46096d6
Relax accuracy requirements in the OpenCL sqrt perf arithmetic test.
...
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
Alexander Alekhin
54063c40de
core(ocl): options to control buffer access flags
...
- control using of clEnqueueMapBuffer or clEnqueueReadBuffer[Rect]
- added benchmarks with OpenCL buffer access use cases
2020-04-02 11:11:06 +00:00
Vadim Pisarevsky
54279523a3
Merge pull request #12437 from vpisarev:avx2_fixes
...
* 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
Alexander Alekhin
4a297a2443
ts: refactor OpenCV tests
...
- 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
Tomoaki Teshima
3cbe60cca2
Merge pull request #9753 from tomoaki0705:universalMatmul
...
* 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
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
thebucc
421e1b237c
Fix for bug #5007 : moved definition of Size_MatDepth_t and Size_MatDepth from ts_perf.hpp to perf_channels.cpp. This way they are closer to where they are needed and live in a different namespace (possibly the reason why the fix works).
2015-08-17 16:09:00 +01:00
Elena Gvozdeva
46b6a095a2
changed perf test for ocl_gemm
2014-08-26 15:05:36 +04:00
Alexander Karsakov
f3dfdfef8a
Fixed warning with "uninitialized local variable"
2014-08-12 10:35:15 +04:00
Alexander Alekhin
55188fe991
world fix
2014-08-05 20:12:35 +04:00
Alexander Karsakov
e51c0810b6
Added accuracy and performance tests for DFT all modes.
2014-07-24 15:17:31 +04:00
Ilya Lavrenov
c949845a6b
fixed perf test
2014-07-10 16:03:31 +04:00
Ilya Lavrenov
978f7eb44a
added perf test for transpose inplace
2014-06-30 18:33:26 +04:00
Ilya Lavrenov
9edd24fe51
changed power in cv::pow test to test actual kernel
2014-06-10 17:41:43 +04:00
Ilya Lavrenov
80470f9cf6
added performance test
2014-05-30 18:34:04 +04:00
Ilya Lavrenov
d156f5af6d
added missed tests for cv::norm, cv::normalize
2014-05-29 16:00:38 +04:00
Alexander Alekhin
cf5dd88cf2
Merge pull request #2776 from ilya-lavrenov:tapi_meanstddev
2014-05-21 17:43:29 +04:00
Ilya Lavrenov
0e1b37675c
added performance test for cv::meanStdDev with mask
2014-05-21 11:50:31 +04:00
Ilya Lavrenov
1e46a99d9f
added performance test for cv::norm with NORM_RELATIVE
2014-05-16 14:15:31 +04:00
Ilya Lavrenov
9cc80a68db
fixed warnings
2014-04-21 13:14:55 +04:00
Alexander Alekhin
af062b7c42
ocl: compare: remove useless perf tests
2014-03-17 12:33:12 +04:00
Alexander Alekhin
755ca4b7cf
ocl: compare with scalar
2014-03-14 19:51:19 +04:00
Andrey Pavlenko
c5bf1c108c
Merge pull request #2470 from ilya-lavrenov:tapi_reduction
2014-03-13 18:42:01 +04:00
Ilya Lavrenov
9932cf41a4
3-channel reduction operations
2014-03-12 15:07:39 +04:00
Ilya Lavrenov
89b7c0dd93
3 channel support to cv::transpose
2014-03-12 00:17:11 +04:00
Ilya Lavrenov
68957b2757
added some new performance tests
2014-03-02 10:29:50 +04:00
Roman Donchenko
48432502b6
Merge remote-tracking branch 'origin/2.4' into merge-2.4
...
Conflicts:
cmake/OpenCVDetectCUDA.cmake
doc/tutorials/introduction/linux_gcc_cmake/linux_gcc_cmake.rst
modules/core/CMakeLists.txt
modules/features2d/perf/opencl/perf_brute_force_matcher.cpp
modules/highgui/src/grfmt_tiff.cpp
modules/imgproc/src/clahe.cpp
modules/imgproc/src/moments.cpp
modules/nonfree/CMakeLists.txt
modules/ocl/perf/perf_ml.cpp
modules/superres/CMakeLists.txt
2014-02-25 15:02:24 +04:00
Alexander Alekhin
79eba54a4f
some fixes in perf tests
2014-02-20 13:29:11 +04:00
Andrey Pavlenko
47d9b933f6
Merge pull request #2345 from ilya-lavrenov:tapi_3cn_perf
2014-02-17 17:38:26 +04:00
Ilya Lavrenov
7629bb78a4
extended performance tests to test 3 channels
2014-02-16 01:31:33 +04:00
Alexander Alekhin
95e38e457f
core/umat: usage flags (with proposals from PR #2195 )
2014-02-14 15:40:16 +04:00
Ilya Lavrenov
e190d3fd36
added perf test
2014-02-05 20:24:30 +04:00
Alexander Alekhin
485635310c
core/ocl: OpenCLBufferPool
2014-02-04 16:48:35 +04:00
Andrey Pavlenko
5d818c010e
Merge pull request #2156 from ilya-lavrenov:tapi_reduce
2014-01-22 10:12:08 +04:00
Ilya Lavrenov
ae4be413c3
added perf tests for cv::reduce
2014-01-21 14:18:38 +04:00
Ilya Lavrenov
5d18cf9989
added cv::[extract|insert]Channel to T-API
2014-01-20 13:52:07 +04:00
Ilya Lavrenov
da2790249e
added NORM_L2SQR type to cv::norm
2014-01-10 18:45:52 +04:00
Ilya Lavrenov
2e5e278271
added cv::PSNR performance test
2014-01-10 18:45:40 +04:00
Ilya Lavrenov
a01e81c8f7
added some performance tests
2014-01-10 18:45:40 +04:00
Roman Donchenko
5a9900481a
Merge pull request #2105 from ilya-lavrenov:norm
2014-01-10 18:12:08 +04:00
Ilya Lavrenov
9899cf7519
fixed cv::mixChannels perf test
2014-01-09 14:26:44 +04:00
Ilya Lavrenov
3a4d4080f4
fixed overflow for cv::norm NORM_L2
2014-01-04 15:20:50 +04:00
Ilya Lavrenov
bb7e96311e
disabled cv::split perf test
2013-12-27 21:57:20 +04:00
Ilya Lavrenov
31e6251793
added new perf tests to core
2013-12-27 20:02:12 +04:00