Vadim Pisarevsky
518486ed3d
Added new data types to cv::Mat & UMat ( #23865 )
...
* started working on adding 32u, 64u, 64s, bool and 16bf types to OpenCV
* core & imgproc tests seem to pass
* fixed a few compile errors and test failures on macOS x86
* hopefully fixed some compile problems and test failures
* fixed some more warnings and test failures
* trying to fix small deviations in perf_core & perf_imgproc by revering randf_64f to exact version used before
* trying to fix behavior of the new OpenCV with old plugins; there is (quite strong) assumption that video capture would give us frames with depth == CV_8U (0) or CV_16U (2). If depth is > 7 then it means that the plugin is built with the old OpenCV. It needs to be recompiled, of course and then this hack can be removed.
* try to repair the case when target arch does not have FP64 SIMD
* 1. fixed bug in itoa() found by alalek
2. restored ==, !=, > and < univ. intrinsics on ARM32/ARM64.
2 years ago
Liutong HAN
a00818047f
Add missing ”v_popcount“ for RVV and enable tests.
2 years ago
Maksim Shabunin
09944a83d9
build: w/a compiler warnings for GCC 11-12 and Clang 13, reduce build output
2 years ago
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=middle
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size:[64 x 64] type:2 continuous = true iterations:1000 nz=false pos=none
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size:[64 x 64] type:4 continuous = true iterations:1000 nz=false pos=none
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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=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: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=false pos=none
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size:[320 x 240] type:4 continuous = true iterations:1000 nz=false pos=none
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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
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size:[640 x 480] type:0 continuous = true iterations:1000 nz=true pos=end
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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:0 continuous = false iterations:1000 nz=true pos=begin
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size:[640 x 480] type:0 continuous = false iterations:1000 nz=true pos=middle
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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
```
2 years ago
Alexander Smorkalov
65487946cc
Added final constrants check to solveLP to filter out flating-point numeric issues.
2 years ago
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
2 years ago
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
2 years ago
Alexander Alekhin
fe59a5695f
core(simd): 64-bit integer EQ/NE without misused 64F guard
2 years ago
Alexander Alekhin
1d530eb2e2
core(test_math): replace the_rng() => cv::theRNG()
2 years ago
Rostislav Vasilikhin
f3a03aefad
cvIsInf(double) fix + regression test
2 years ago
fengyuentau
34a0897f90
add cv::flipND; support onnx slice with negative steps via cv::flipND
2 years ago
Alexander Alekhin
be326ff752
build: fix/eliminate MSVC warnings
2 years ago
HAN Liutong
df24bd295d
Fix v_signmask for RISC-V Vector.
2 years ago
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>
2 years ago
Yuantao Feng
9dc844a6e1
Merge pull request #22346 from fengyuentau:mat1d_part1
...
Changes separated from Mat 1D support in core #18594 (#22346 )
2 years ago
HAN Liutong
7e2c8cc9f4
Add remaining intrinsics.
2 years ago
HAN Liutong
b9a1039566
Remove the test log in test_interleave_pq.
3 years ago
HAN Liutong
8dc332721f
Add testcases for interleave_p&q and enable others testcases.
3 years ago
HAN Liutong
f572ae3474
add missing test cases(v_abs)
3 years ago
HAN Liutong
2fb652ce09
Add testcase for continuous mul and add.
3 years ago
HAN Liutong
f0d29cd33c
Add more universal intrinsic implementations for RVV.
3 years ago
HAN Liutong
2bd72af2ef
Merge pull request #22292 from hanliutong:fix
...
[GSoC] Fix compilation errors and warnings when using MSVC on Windows.
* Pass reference of the argument.
* Add some cast to suppress warnings.
3 years ago
Maksim Shabunin
f729202272
core: remove unnecessary pointer cleanup in BufferArea
3 years ago
HAN Liutong
3e3b53f815
Fix compile errors when all SIMD is disabled.
3 years ago
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.
3 years ago
Sean McBride
35f1a90df7
Merge pull request #22149 from seanm:sprintf
...
Replaced sprintf with safer snprintf
* Straightforward replacement of sprintf with safer snprintf
* Trickier replacement of sprintf with safer snprintf
Some functions were changed to take another parameter: the size of the buffer, so that they can pass that size on to snprintf.
3 years ago
rogday
7daf84fb44
address security concerns in persistence
3 years ago
Anatoliy Talamanov
9390c56831
Merge pull request #21782 from TolyaTalamanov:at/fix-1d-mat-problems
...
[G-API] Fix problems with 1D cv::Mat as graph output
* Fix issues with 1D cv::Mat
* Fix cv::Mat::create
* Fix standalone build
* Add test on 1d mat
* Fix warning
* Add additional condition
* Add more tests
3 years ago
Maksim Shabunin
593996216f
cartToPolar/polarToCart: disable inplace mode
3 years ago
rogday
e16cb8b4a2
Merge pull request #21703 from rogday:transpose
...
Add n-dimensional transpose to core
* add n-dimensional transpose to core
* add performance test, write sequentially and address review comments
3 years ago
Vincent Rabaud
057c3da82a
Allow Matx static function to work with Vec.
3 years ago
Alexander Alekhin
123519165d
core: FP denormals hints support
3 years ago
Alexander Alekhin
5ba9a089e1
core(persistence): avoid NULL pointer dereference
3 years ago
Suleyman TURKMEN
0e6a2c0491
fix legacy constants
3 years ago
rogday
692059e899
initialize members
3 years ago
Vincent Rabaud
6b4ea68bc7
Solve Rect overflow issues.
...
Fow now, it is possible to define valid rectangle for which some
functions overflow (e.g. br(), ares() ...).
This patch fixes the intersection operator so that it works with
any rectangle.
3 years ago
rogday
f044037ec5
Merge pull request #20733 from rogday:argmaxnd
...
Implement ArgMax and ArgMin
* add reduceArgMax and reduceArgMin
* fix review comments
* address review concerns
3 years ago
yuki takehara
a6277370ca
Merge pull request #21107 from take1014:remove_assert_21038
...
resolves #21038
* remove C assert
* revert C header
* fix several points in review
* fix test_ds.cpp
3 years ago
Alexander Alekhin
b5fcb06a76
core(SIMD): update int64 SSE constructor
3 years ago
Alexander Alekhin
8c7dc1f6b7
core: OPENCV_ABI_COMPATIBILITY=500
3 years ago
Alexander Alekhin
eab2b9dc09
core: ensure is_trivially_copyable for simple types
3 years ago
Alexander Alekhin
e3f4f874c5
Merge pull request #20670 from alalek:core_ocl_fix_intel_gpu_gemm_requirements
...
core(OpenCL): fix intel_gpu_gemm kernel requirements
* core(ocl): fix intel_gpu_gemm integration
- allow bailout to generic OpenCL kernel
* core(ocl): avoid failures of generic OpenCL gemm kernel
* core(ocl): define alignment requirements of intel_gpu_gemm kernels
3 years ago
Dale Phurrough
9bda96d39e
add test case
4 years ago
Francesco Petrogalli
b928ebdd53
Merge pull request #19985 from fpetrogalli:disable_threads
...
* [build][option] Introduce `OPENCV_DISABLE_THREAD_SUPPORT` option.
The option forces the library to build without thread support.
* update handling of OPENCV_DISABLE_THREAD_SUPPORT
- reduce amount of #if conditions
* [to squash] cmake: apply mode vars in toolchains too
Co-authored-by: Alexander Alekhin <alexander.a.alekhin@gmail.com>
4 years ago
Smirnov Egor
b42623ff9d
port base64 encoding from 3.4
4 years ago
Alexander Alekhin
4eac198270
core(persistence): fix types format handling, fix 16F support
4 years ago
Dale Phurrough
8be86cbdfd
add usageFlags to UMat static factories
...
- add abi compatible overloads
- add test case
4 years ago
Vincent Rabaud
c8268e65fd
Fix potential NaN in cv::norm.
...
There can be an int overflow.
cv::norm( InputArray _src, int normType, InputArray _mask ) is fine,
not cv::norm( InputArray _src1, InputArray _src2, int normType, InputArray _mask ).
4 years ago
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
4 years ago
Developer-Ecosystem-Engineering
814550d2a6
Merge pull request #20011 from Developer-Ecosystem-Engineering:3.4
...
Improve performance on Arm64
* Improve performance on Apple silicon
This patch will
- Enable dot product intrinsics for macOS arm64 builds
- Enable for macOS arm64 builds
- Improve HAL primitives
- reduction (sum, min, max, sad)
- signmask
- mul_expand
- check_any / check_all
Results on a M1 Macbook Pro
* Updates to #20011 based on feedback
- Removes Apple Silicon specific workarounds
- Makes #ifdef sections smaller for v_mul_expand cases
- Moves dot product optimization to compiler optimization check
- Adds 4x4 matrix transpose optimization
* Remove dotprod and fix v_transpose
Based on the latest, we've removed dotprod entirely and will revisit in a future PR.
Added explicit cats with v_transpose4x4()
This should resolve all opens with this PR
* Remove commented out lines
Remove two extraneous comments
4 years ago