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https://github.com/opencv/opencv.git
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Andrei Fedorov
96ec0c97df
Extend core performance tests - #29922 Added more cases for performance tests. It's a part of a bigger PR https://github.com/opencv/opencv/pull/29631 execution time increased by <18% per my measurements. Duplication of https://github.com/opencv/opencv/pull/29900, but from a different fork. `opencv_extra` PR is https://github.com/opencv/opencv_extra/pull/1410 Following was added: | File | Test | Added | |------|------|-------| | `perf_arithm.cpp` | `BinaryOpTest.*` (add/subtract/multiply/absdiff/min/max/transpose2d) | types `CV_16UC1`, `CV_64FC1` | | `perf_compare.cpp` | `compareScalar` | types `CV_16UC1`, `CV_16SC1` | | `perf_dot.cpp` | `dot` | type `CV_64FC1` | | `perf_flip.cpp` | `flip` (`FLIP_TYPES`) | types `CV_32FC3`, `CV_32FC4` | | `perf_mat.cpp` | `Mat_CopyToWithMask` | types `CV_32FC3` | | `perf_mat.cpp` | `Mat_SetToWithMask` | types `CV_8UC3, CV_8UC4, CV_16UC3, CV_16UC4, CV_32FC3, CV_32FC4` | | `perf_norm.cpp` | `norm` | norm type `NORM_L2SQR` | | `perf_norm.cpp` | `norm_mask` | types `CV_8UC3`, `CV_16UC3`, `CV_32FC3`; norm type `NORM_L2SQR` | | `perf_norm.cpp` | `norm2` | norm types `NORM_L2SQR`, `NORM_RELATIVE+NORM_L2SQR` | | `perf_norm.cpp` | `norm2_mask` | types `CV_8UC3`, `CV_16UC3`, `CV_32FC3`; norm types `NORM_L2SQR`, `NORM_RELATIVE\|NORM_L2SQR` | | `perf_sort.cpp` | `sort`, `sorIdx` (`TYPICAL_MAT_TYPES_SORT`) | types `CV_16SC1`, `CV_32SC1`, `CV_64FC1` | | `perf_stat.cpp` | `sum`, `mean` | types widened `{8UC1,8UC4,32FC1}` → `8U/16U/16S/32F × C1/C3/C4` | | `perf_stat.cpp` | `mean_mask`, `meanStdDev`, `meanStdDev_mask` | types widened `{8UC1,8UC4,32FC1}` → `8U/16U/32F × C1/C3/C4` | ### Pull Request Readiness Checklist See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [x] I agree to contribute to the project under Apache 2 License. - [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [ ] 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. - [ ] The feature is well documented and sample code can be built with the project CMake
131 lines
3.4 KiB
C++
131 lines
3.4 KiB
C++
#include "perf_precomp.hpp"
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namespace opencv_test
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{
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using namespace perf;
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// Masked variants: 8U/16U/32F x C1/C3/C4.
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#define TYPICAL_MAT_TYPES_STAT_MASK CV_8UC1, CV_8UC3, CV_8UC4, CV_16UC1, CV_16UC3, CV_16UC4, CV_32FC1, CV_32FC3, CV_32FC4
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// sum/mean/meanStdDev additionally cover 16S.
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#define TYPICAL_MAT_TYPES_STAT TYPICAL_MAT_TYPES_STAT_MASK, CV_16SC1, CV_16SC3, CV_16SC4
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PERF_TEST_P(Size_MatType, sum, testing::Combine( testing::Values( TYPICAL_MAT_SIZES ),
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testing::Values( TYPICAL_MAT_TYPES_STAT ) ))
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{
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Size sz = get<0>(GetParam());
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int type = get<1>(GetParam());
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Mat arr(sz, type);
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Scalar s;
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declare.in(arr, WARMUP_RNG).out(s);
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TEST_CYCLE() s = sum(arr);
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SANITY_CHECK(s, 1e-6, ERROR_RELATIVE);
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}
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PERF_TEST_P(Size_MatType, mean, testing::Combine( testing::Values( TYPICAL_MAT_SIZES ),
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testing::Values( TYPICAL_MAT_TYPES_STAT ) ))
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{
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Size sz = get<0>(GetParam());
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int type = get<1>(GetParam());
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Mat src(sz, type);
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Scalar s;
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declare.in(src, WARMUP_RNG).out(s);
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TEST_CYCLE() s = cv::mean(src);
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SANITY_CHECK(s, 1e-5);
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}
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PERF_TEST_P(Size_MatType, mean_mask, testing::Combine( testing::Values( TYPICAL_MAT_SIZES ),
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testing::Values( TYPICAL_MAT_TYPES_STAT_MASK ) ))
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{
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Size sz = get<0>(GetParam());
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int type = get<1>(GetParam());
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Mat src(sz, type);
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Mat mask = Mat::ones(src.size(), CV_8U);
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Scalar s;
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declare.in(src, WARMUP_RNG).in(mask).out(s);
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TEST_CYCLE() s = cv::mean(src, mask);
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SANITY_CHECK(s, 5e-5);
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}
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PERF_TEST_P(Size_MatType, meanStdDev, testing::Combine( testing::Values( TYPICAL_MAT_SIZES ),
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testing::Values( TYPICAL_MAT_TYPES_STAT_MASK ) ))
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{
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Size sz = get<0>(GetParam());
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int matType = get<1>(GetParam());
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Mat src(sz, matType);
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Scalar mean;
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Scalar dev;
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declare.in(src, WARMUP_RNG).out(mean, dev);
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TEST_CYCLE() meanStdDev(src, mean, dev);
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SANITY_CHECK(mean, 1e-5, ERROR_RELATIVE);
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SANITY_CHECK(dev, 1e-5, ERROR_RELATIVE);
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}
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PERF_TEST_P(Size_MatType, meanStdDev_mask, testing::Combine( testing::Values( TYPICAL_MAT_SIZES ),
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testing::Values( TYPICAL_MAT_TYPES_STAT_MASK ) ))
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{
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Size sz = get<0>(GetParam());
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int matType = get<1>(GetParam());
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Mat src(sz, matType);
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Mat mask = Mat::ones(sz, CV_8U);
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Scalar mean;
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Scalar dev;
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declare.in(src, WARMUP_RNG).in(mask).out(mean, dev);
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TEST_CYCLE() meanStdDev(src, mean, dev, mask);
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SANITY_CHECK(mean, 1e-5);
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SANITY_CHECK(dev, 1e-5);
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}
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PERF_TEST_P(Size_MatType, countNonZero, testing::Combine( testing::Values( TYPICAL_MAT_SIZES ), testing::Values( CV_8UC1, CV_8SC1, CV_16UC1, CV_16SC1, CV_32SC1, CV_32FC1, CV_64FC1 ) ))
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{
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Size sz = get<0>(GetParam());
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int matType = get<1>(GetParam());
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Mat src(sz, matType);
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int cnt = 0;
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declare.in(src, WARMUP_RNG);
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int runs = (sz.width <= 640) ? 8 : 1;
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TEST_CYCLE_MULTIRUN(runs) cnt = countNonZero(src);
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SANITY_CHECK(cnt);
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}
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PERF_TEST_P(Size_MatType, hasNonZero, testing::Combine( testing::Values( TYPICAL_MAT_SIZES ), testing::Values( CV_8UC1, CV_8SC1, CV_16UC1, CV_16SC1, CV_32SC1, CV_32FC1, CV_64FC1 ) ))
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{
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Size sz = get<0>(GetParam());
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int matType = get<1>(GetParam());
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Mat src(sz, matType);
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/*bool hnz = false;*/
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declare.in(src, WARMUP_RNG);
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int runs = (sz.width <= 640) ? 8 : 1;
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TEST_CYCLE_MULTIRUN(runs) /*hnz =*/ hasNonZero(src);
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SANITY_CHECK_NOTHING();
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}
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} // namespace
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