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胡晨宇
5137676ea7
Fast-path transposeND for identity and 2D transpose orders #29172 ### Pull Request Readiness Checklist See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [x] I agree to contribute to the project under Apache 2 License. - [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [x] The PR is proposed to the proper branch - [ ] 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. - [x] The feature is well documented and sample code can be built with the project CMake <!-- Note!!! If you are an automated agent, we have a special process for you: add 🤖🤖🤖 to the end of the PR title. --> This PR adds fast paths to cv::transposeND() for two common cases: - identity permutation: dispatch to copyTo() - 2D permutation {1, 0}: dispatch to transpose() All other permutations continue to use the existing generic ND implementation. Why: transposeND() currently falls back to the generic memcpy/index-update loop even for the common 2D transpose case, while OpenCV already has an optimized transpose() path. Reusing that path avoids unnecessary index arithmetic and improves performance for 2D inputs passed through transposeND(). Performance: [BinaryOpTest.transposeND/21 (1920x1080, 8UC3): 28.21 ms -> 0.66 ms (-97.7%)] [BinaryOpTest.transposeND/22 (1920x1080, 8UC4): 37.61 ms -> 0.88 ms (-97.7%)] [BinaryOpTest.transposeND/29 (1920x1080, 32FC1): 10.26 ms -> 0.75 ms (-92.7%)] Full transposeND perf subset: 6760 ms -> 592 ms (-91.2%)
952 lines
22 KiB
C++
952 lines
22 KiB
C++
#include "perf_precomp.hpp"
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#include <numeric>
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#include "opencv2/core/softfloat.hpp"
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namespace opencv_test
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{
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using namespace perf;
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using BroadcastTest = perf::TestBaseWithParam<std::tuple<std::vector<int>, perf::MatType, std::vector<int>>>;
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typedef Size_MatType BinaryOpTest;
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PERF_TEST_P_(BroadcastTest, basic)
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{
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std::vector<int> shape_src = get<0>(GetParam());
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int dt_type = get<1>(GetParam());
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std::vector<int> shape_dst = get<2>(GetParam());
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cv::Mat src(static_cast<int>(shape_src.size()), shape_src.data(), dt_type);
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cv::Mat dst(static_cast<int>(shape_dst.size()), shape_dst.data(), dt_type);
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cv::randu(src, -1.f, 1.f);
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TEST_CYCLE() cv::broadcast(src, shape_dst, dst);
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SANITY_CHECK_NOTHING();
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}
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INSTANTIATE_TEST_CASE_P(/*nothing*/ , BroadcastTest,
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testing::Combine(
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testing::Values(std::vector<int>{1, 100, 800},
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std::vector<int>{10, 1, 800},
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std::vector<int>{10, 100, 1}),
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testing::Values(CV_32FC1),
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testing::Values(std::vector<int>{10, 100, 800})
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)
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);
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PERF_TEST_P_(BinaryOpTest, min)
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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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cv::Mat a = Mat(sz, type);
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cv::Mat b = Mat(sz, type);
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cv::Mat c = Mat(sz, type);
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declare.in(a, b, WARMUP_RNG).out(c);
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TEST_CYCLE() cv::min(a, b, c);
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SANITY_CHECK_NOTHING();
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}
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PERF_TEST_P_(BinaryOpTest, minScalarDouble)
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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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cv::Mat a = Mat(sz, type);
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cv::Scalar b;
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cv::Mat c = Mat(sz, type);
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declare.in(a, b, WARMUP_RNG).out(c);
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TEST_CYCLE() cv::min(a, b, c);
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SANITY_CHECK_NOTHING();
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}
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PERF_TEST_P_(BinaryOpTest, minScalarSameType)
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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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cv::Mat a = Mat(sz, type);
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cv::Scalar b;
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cv::Mat c = Mat(sz, type);
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declare.in(a, b, WARMUP_RNG).out(c);
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if (CV_MAT_DEPTH(type) < CV_32S)
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{
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b = Scalar(1, 0, 3, 4); // don't pass non-integer values for 8U/8S/16U/16S processing
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}
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else if (CV_MAT_DEPTH(type) == CV_32S)
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{
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b = Scalar(1, 0, -3, 4); // don't pass non-integer values for 32S processing
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}
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TEST_CYCLE() cv::min(a, b, c);
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SANITY_CHECK_NOTHING();
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}
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PERF_TEST_P_(BinaryOpTest, max)
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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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cv::Mat a = Mat(sz, type);
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cv::Mat b = Mat(sz, type);
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cv::Mat c = Mat(sz, type);
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declare.in(a, b, WARMUP_RNG).out(c);
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TEST_CYCLE() cv::max(a, b, c);
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SANITY_CHECK_NOTHING();
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}
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PERF_TEST_P_(BinaryOpTest, maxScalarDouble)
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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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cv::Mat a = Mat(sz, type);
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cv::Scalar b;
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cv::Mat c = Mat(sz, type);
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declare.in(a, b, WARMUP_RNG).out(c);
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TEST_CYCLE() cv::max(a, b, c);
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SANITY_CHECK_NOTHING();
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}
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PERF_TEST_P_(BinaryOpTest, maxScalarSameType)
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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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cv::Mat a = Mat(sz, type);
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cv::Scalar b;
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cv::Mat c = Mat(sz, type);
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declare.in(a, b, WARMUP_RNG).out(c);
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if (CV_MAT_DEPTH(type) < CV_32S)
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{
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b = Scalar(1, 0, 3, 4); // don't pass non-integer values for 8U/8S/16U/16S processing
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}
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else if (CV_MAT_DEPTH(type) == CV_32S)
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{
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b = Scalar(1, 0, -3, 4); // don't pass non-integer values for 32S processing
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}
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TEST_CYCLE() cv::max(a, b, c);
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SANITY_CHECK_NOTHING();
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}
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PERF_TEST_P_(BinaryOpTest, absdiff)
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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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cv::Mat a = Mat(sz, type);
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cv::Mat b = Mat(sz, type);
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cv::Mat c = Mat(sz, type);
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declare.in(a, b, WARMUP_RNG).out(c);
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if (CV_MAT_DEPTH(type) == CV_32S)
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{
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//see ticket 1529: absdiff can be without saturation on 32S
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a /= 2;
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b /= 2;
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}
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TEST_CYCLE() cv::absdiff(a, b, c);
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SANITY_CHECK_NOTHING();
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}
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PERF_TEST_P_(BinaryOpTest, absdiffScalarDouble)
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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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cv::Mat a = Mat(sz, type);
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cv::Scalar b;
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cv::Mat c = Mat(sz, type);
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declare.in(a, b, WARMUP_RNG).out(c);
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if (CV_MAT_DEPTH(type) == CV_32S)
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{
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//see ticket 1529: absdiff can be without saturation on 32S
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a /= 2;
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b /= 2;
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}
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TEST_CYCLE() cv::absdiff(a, b, c);
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SANITY_CHECK_NOTHING();
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}
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PERF_TEST_P_(BinaryOpTest, absdiffScalarSameType)
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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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cv::Mat a = Mat(sz, type);
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cv::Scalar b;
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cv::Mat c = Mat(sz, type);
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declare.in(a, b, WARMUP_RNG).out(c);
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if (CV_MAT_DEPTH(type) < CV_32S)
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{
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b = Scalar(1, 0, 3, 4); // don't pass non-integer values for 8U/8S/16U/16S processing
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}
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else if (CV_MAT_DEPTH(type) == CV_32S)
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{
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//see ticket 1529: absdiff can be without saturation on 32S
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a /= 2;
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b = Scalar(1, 0, -3, 4); // don't pass non-integer values for 32S processing
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}
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TEST_CYCLE() cv::absdiff(a, b, c);
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SANITY_CHECK_NOTHING();
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}
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PERF_TEST_P_(BinaryOpTest, add)
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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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cv::Mat a = Mat(sz, type);
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cv::Mat b = Mat(sz, type);
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cv::Mat c = Mat(sz, type);
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declare.in(a, b, WARMUP_RNG).out(c);
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declare.time(50);
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if (CV_MAT_DEPTH(type) == CV_32S)
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{
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//see ticket 1529: add can be without saturation on 32S
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a /= 2;
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b /= 2;
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}
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TEST_CYCLE() cv::add(a, b, c);
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SANITY_CHECK_NOTHING();
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}
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PERF_TEST_P_(BinaryOpTest, addScalarDouble)
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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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cv::Mat a = Mat(sz, type);
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cv::Scalar b;
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cv::Mat c = Mat(sz, type);
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declare.in(a, b, WARMUP_RNG).out(c);
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if (CV_MAT_DEPTH(type) == CV_32S)
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{
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//see ticket 1529: add can be without saturation on 32S
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a /= 2;
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b /= 2;
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}
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TEST_CYCLE() cv::add(a, b, c);
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SANITY_CHECK_NOTHING();
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}
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PERF_TEST_P_(BinaryOpTest, addScalarSameType)
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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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cv::Mat a = Mat(sz, type);
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cv::Scalar b;
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cv::Mat c = Mat(sz, type);
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declare.in(a, b, WARMUP_RNG).out(c);
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if (CV_MAT_DEPTH(type) < CV_32S)
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{
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b = Scalar(1, 0, 3, 4); // don't pass non-integer values for 8U/8S/16U/16S processing
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}
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else if (CV_MAT_DEPTH(type) == CV_32S)
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{
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//see ticket 1529: add can be without saturation on 32S
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a /= 2;
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b = Scalar(1, 0, -3, 4); // don't pass non-integer values for 32S processing
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}
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TEST_CYCLE() cv::add(a, b, c, noArray(), type);
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SANITY_CHECK_NOTHING();
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}
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PERF_TEST_P_(BinaryOpTest, subtract)
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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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cv::Mat a = Mat(sz, type);
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cv::Mat b = Mat(sz, type);
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cv::Mat c = Mat(sz, type);
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declare.in(a, b, WARMUP_RNG).out(c);
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if (CV_MAT_DEPTH(type) == CV_32S)
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{
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//see ticket 1529: subtract can be without saturation on 32S
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a /= 2;
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b /= 2;
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}
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TEST_CYCLE() cv::subtract(a, b, c);
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SANITY_CHECK_NOTHING();
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}
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PERF_TEST_P_(BinaryOpTest, subtractScalarDouble)
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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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cv::Mat a = Mat(sz, type);
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cv::Scalar b;
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cv::Mat c = Mat(sz, type);
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declare.in(a, b, WARMUP_RNG).out(c);
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if (CV_MAT_DEPTH(type) == CV_32S)
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{
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//see ticket 1529: subtract can be without saturation on 32S
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a /= 2;
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b /= 2;
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}
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TEST_CYCLE() cv::subtract(a, b, c);
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SANITY_CHECK_NOTHING();
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}
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PERF_TEST_P_(BinaryOpTest, subtractScalarSameType)
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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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cv::Mat a = Mat(sz, type);
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cv::Scalar b;
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cv::Mat c = Mat(sz, type);
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declare.in(a, b, WARMUP_RNG).out(c);
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if (CV_MAT_DEPTH(type) < CV_32S)
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{
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b = Scalar(1, 0, 3, 4); // don't pass non-integer values for 8U/8S/16U/16S processing
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}
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else if (CV_MAT_DEPTH(type) == CV_32S)
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{
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//see ticket 1529: subtract can be without saturation on 32S
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a /= 2;
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b = Scalar(1, 0, -3, 4); // don't pass non-integer values for 32S processing
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}
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TEST_CYCLE() cv::subtract(a, b, c, noArray(), type);
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SANITY_CHECK_NOTHING();
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}
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PERF_TEST_P_(BinaryOpTest, multiply)
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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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cv::Mat a(sz, type), b(sz, type), c(sz, type);
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declare.in(a, b, WARMUP_RNG).out(c);
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if (CV_MAT_DEPTH(type) == CV_32S)
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{
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//According to docs, saturation is not applied when result is 32bit integer
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a /= (2 << 16);
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b /= (2 << 16);
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}
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TEST_CYCLE() cv::multiply(a, b, c);
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SANITY_CHECK_NOTHING();
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}
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PERF_TEST_P_(BinaryOpTest, multiplyScale)
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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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cv::Mat a(sz, type), b(sz, type), c(sz, type);
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double scale = 0.5;
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declare.in(a, b, WARMUP_RNG).out(c);
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if (CV_MAT_DEPTH(type) == CV_32S)
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{
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//According to docs, saturation is not applied when result is 32bit integer
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a /= (2 << 16);
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b /= (2 << 16);
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}
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TEST_CYCLE() cv::multiply(a, b, c, scale);
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SANITY_CHECK_NOTHING();
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}
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PERF_TEST_P_(BinaryOpTest, divide)
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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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cv::Mat a(sz, type), b(sz, type), c(sz, type);
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double scale = 0.5;
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declare.in(a, b, WARMUP_RNG).out(c);
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TEST_CYCLE() cv::divide(a, b, c, scale);
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SANITY_CHECK_NOTHING();
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}
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PERF_TEST_P_(BinaryOpTest, reciprocal)
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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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cv::Mat b(sz, type), c(sz, type);
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double scale = 0.5;
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declare.in(b, WARMUP_RNG).out(c);
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TEST_CYCLE() cv::divide(scale, b, c);
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SANITY_CHECK_NOTHING();
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}
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PERF_TEST_P_(BinaryOpTest, transpose2d)
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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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Size tsz = Size(sz.height, sz.width);
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cv::Mat a(sz, type), b(tsz, type);;
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declare.in(a, WARMUP_RNG).out(b);
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TEST_CYCLE() cv::transpose(a, b);
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SANITY_CHECK_NOTHING();
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}
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static cv::Mat makeTransposeNDOutput(const cv::Mat& src, const std::vector<int>& order)
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{
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std::vector<int> new_sz(order.size());
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for (size_t i = 0; i < order.size(); ++i)
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new_sz[i] = src.size[order[i]];
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return Mat(static_cast<int>(new_sz.size()), new_sz.data(), src.type());
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}
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static cv::Mat makeTransposeNDInput3D(Size sz, int type)
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{
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const int channels = CV_MAT_CN(type);
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int dims[] = { sz.height, sz.width, channels };
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return Mat(3, dims, CV_MAKETYPE(CV_MAT_DEPTH(type), 1));
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}
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PERF_TEST_P_(BinaryOpTest, transposeND_identity_order)
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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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cv::Mat a = Mat(sz, type).reshape(1);
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std::vector<int> order(a.dims);
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std::iota(order.begin(), order.end(), 0);
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cv::Mat b = makeTransposeNDOutput(a, order);
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declare.in(a, WARMUP_RNG).out(b);
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TEST_CYCLE() cv::transposeND(a, order, b);
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SANITY_CHECK_NOTHING();
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}
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PERF_TEST_P_(BinaryOpTest, transposeND_2d_swap_order)
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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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cv::Mat a = Mat(sz, type).reshape(1);
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std::vector<int> order{1, 0};
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cv::Mat b = makeTransposeNDOutput(a, order);
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declare.in(a, WARMUP_RNG).out(b);
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TEST_CYCLE() cv::transposeND(a, order, b);
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SANITY_CHECK_NOTHING();
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}
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PERF_TEST_P_(BinaryOpTest, transposeND_generic_keep_tail_order)
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{
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Size sz = get<0>(GetParam());
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int type = get<1>(GetParam());
|
|
cv::Mat a = makeTransposeNDInput3D(sz, type);
|
|
|
|
std::vector<int> order{1, 0, 2};
|
|
|
|
cv::Mat b = makeTransposeNDOutput(a, order);
|
|
|
|
randu(a, 0, 255);
|
|
declare.in(a).out(b);
|
|
|
|
TEST_CYCLE() cv::transposeND(a, order, b);
|
|
|
|
SANITY_CHECK_NOTHING();
|
|
}
|
|
|
|
PERF_TEST_P_(BinaryOpTest, transposeND_generic_move_tail_order)
|
|
{
|
|
Size sz = get<0>(GetParam());
|
|
int type = get<1>(GetParam());
|
|
cv::Mat a = makeTransposeNDInput3D(sz, type);
|
|
|
|
std::vector<int> order{2, 0, 1};
|
|
|
|
cv::Mat b = makeTransposeNDOutput(a, order);
|
|
|
|
randu(a, 0, 255);
|
|
declare.in(a).out(b);
|
|
|
|
TEST_CYCLE() cv::transposeND(a, order, b);
|
|
|
|
SANITY_CHECK_NOTHING();
|
|
}
|
|
|
|
INSTANTIATE_TEST_CASE_P(/*nothing*/ , BinaryOpTest,
|
|
testing::Combine(
|
|
testing::Values(szVGA, sz720p, sz1080p),
|
|
testing::Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_8SC1, CV_16SC1, CV_16SC2, CV_16SC3, CV_16SC4, CV_32SC1, CV_32FC1)
|
|
)
|
|
);
|
|
|
|
///////////// Mixed type arithmetics ////////
|
|
|
|
typedef perf::TestBaseWithParam<std::tuple<cv::Size, std::tuple<perf::MatType, perf::MatType>>> ArithmMixedTest;
|
|
|
|
PERF_TEST_P_(ArithmMixedTest, add)
|
|
{
|
|
auto p = GetParam();
|
|
Size sz = get<0>(p);
|
|
int srcType = get<0>(get<1>(p));
|
|
int dstType = get<1>(get<1>(p));
|
|
|
|
cv::Mat a = Mat(sz, srcType);
|
|
cv::Mat b = Mat(sz, srcType);
|
|
cv::Mat c = Mat(sz, dstType);
|
|
|
|
declare.in(a, b, WARMUP_RNG).out(c);
|
|
declare.time(50);
|
|
|
|
if (CV_MAT_DEPTH(dstType) == CV_32S)
|
|
{
|
|
//see ticket 1529: add can be without saturation on 32S
|
|
a /= 2;
|
|
b /= 2;
|
|
}
|
|
|
|
TEST_CYCLE() cv::add(a, b, c, /* mask */ noArray(), dstType);
|
|
|
|
SANITY_CHECK_NOTHING();
|
|
}
|
|
|
|
PERF_TEST_P_(ArithmMixedTest, addScalarDouble)
|
|
{
|
|
auto p = GetParam();
|
|
Size sz = get<0>(p);
|
|
int srcType = get<0>(get<1>(p));
|
|
int dstType = get<1>(get<1>(p));
|
|
|
|
cv::Mat a = Mat(sz, srcType);
|
|
cv::Scalar b;
|
|
cv::Mat c = Mat(sz, dstType);
|
|
|
|
declare.in(a, b, WARMUP_RNG).out(c);
|
|
|
|
if (CV_MAT_DEPTH(dstType) == CV_32S)
|
|
{
|
|
//see ticket 1529: add can be without saturation on 32S
|
|
a /= 2;
|
|
b /= 2;
|
|
}
|
|
|
|
TEST_CYCLE() cv::add(a, b, c, /* mask */ noArray(), dstType);
|
|
|
|
SANITY_CHECK_NOTHING();
|
|
}
|
|
|
|
PERF_TEST_P_(ArithmMixedTest, addScalarSameType)
|
|
{
|
|
auto p = GetParam();
|
|
Size sz = get<0>(p);
|
|
int srcType = get<0>(get<1>(p));
|
|
int dstType = get<1>(get<1>(p));
|
|
|
|
cv::Mat a = Mat(sz, srcType);
|
|
cv::Scalar b;
|
|
cv::Mat c = Mat(sz, dstType);
|
|
|
|
declare.in(a, b, WARMUP_RNG).out(c);
|
|
|
|
if (CV_MAT_DEPTH(dstType) < CV_32S)
|
|
{
|
|
b = Scalar(1, 0, 3, 4); // don't pass non-integer values for 8U/8S/16U/16S processing
|
|
}
|
|
else if (CV_MAT_DEPTH(dstType) == CV_32S)
|
|
{
|
|
//see ticket 1529: add can be without saturation on 32S
|
|
a /= 2;
|
|
b = Scalar(1, 0, -3, 4); // don't pass non-integer values for 32S processing
|
|
}
|
|
|
|
TEST_CYCLE() cv::add(a, b, c, /* mask */ noArray(), dstType);
|
|
|
|
SANITY_CHECK_NOTHING();
|
|
}
|
|
|
|
PERF_TEST_P_(ArithmMixedTest, subtract)
|
|
{
|
|
auto p = GetParam();
|
|
Size sz = get<0>(p);
|
|
int srcType = get<0>(get<1>(p));
|
|
int dstType = get<1>(get<1>(p));
|
|
|
|
cv::Mat a = Mat(sz, srcType);
|
|
cv::Mat b = Mat(sz, srcType);
|
|
cv::Mat c = Mat(sz, dstType);
|
|
|
|
declare.in(a, b, WARMUP_RNG).out(c);
|
|
|
|
if (CV_MAT_DEPTH(dstType) == CV_32S)
|
|
{
|
|
//see ticket 1529: subtract can be without saturation on 32S
|
|
a /= 2;
|
|
b /= 2;
|
|
}
|
|
|
|
TEST_CYCLE() cv::subtract(a, b, c, /* mask */ noArray(), dstType);
|
|
|
|
SANITY_CHECK_NOTHING();
|
|
}
|
|
|
|
PERF_TEST_P_(ArithmMixedTest, subtractScalarDouble)
|
|
{
|
|
auto p = GetParam();
|
|
Size sz = get<0>(p);
|
|
int srcType = get<0>(get<1>(p));
|
|
int dstType = get<1>(get<1>(p));
|
|
|
|
cv::Mat a = Mat(sz, srcType);
|
|
cv::Scalar b;
|
|
cv::Mat c = Mat(sz, dstType);
|
|
|
|
declare.in(a, b, WARMUP_RNG).out(c);
|
|
|
|
if (CV_MAT_DEPTH(dstType) == CV_32S)
|
|
{
|
|
//see ticket 1529: subtract can be without saturation on 32S
|
|
a /= 2;
|
|
b /= 2;
|
|
}
|
|
|
|
TEST_CYCLE() cv::subtract(a, b, c, /* mask */ noArray(), dstType);
|
|
|
|
SANITY_CHECK_NOTHING();
|
|
}
|
|
|
|
PERF_TEST_P_(ArithmMixedTest, subtractScalarSameType)
|
|
{
|
|
auto p = GetParam();
|
|
Size sz = get<0>(p);
|
|
int srcType = get<0>(get<1>(p));
|
|
int dstType = get<1>(get<1>(p));
|
|
|
|
cv::Mat a = Mat(sz, srcType);
|
|
cv::Scalar b;
|
|
cv::Mat c = Mat(sz, dstType);
|
|
|
|
declare.in(a, b, WARMUP_RNG).out(c);
|
|
|
|
if (CV_MAT_DEPTH(dstType) < CV_32S)
|
|
{
|
|
b = Scalar(1, 0, 3, 4); // don't pass non-integer values for 8U/8S/16U/16S processing
|
|
}
|
|
else if (CV_MAT_DEPTH(dstType) == CV_32S)
|
|
{
|
|
//see ticket 1529: subtract can be without saturation on 32S
|
|
a /= 2;
|
|
b = Scalar(1, 0, -3, 4); // don't pass non-integer values for 32S processing
|
|
}
|
|
|
|
TEST_CYCLE() cv::subtract(a, b, c, /* mask */ noArray(), dstType);
|
|
|
|
SANITY_CHECK_NOTHING();
|
|
}
|
|
|
|
PERF_TEST_P_(ArithmMixedTest, multiply)
|
|
{
|
|
auto p = GetParam();
|
|
Size sz = get<0>(p);
|
|
int srcType = get<0>(get<1>(p));
|
|
int dstType = get<1>(get<1>(p));
|
|
|
|
cv::Mat a(sz, srcType), b(sz, srcType), c(sz, dstType);
|
|
|
|
declare.in(a, b, WARMUP_RNG).out(c);
|
|
if (CV_MAT_DEPTH(dstType) == CV_32S)
|
|
{
|
|
//According to docs, saturation is not applied when result is 32bit integer
|
|
a /= (2 << 16);
|
|
b /= (2 << 16);
|
|
}
|
|
|
|
TEST_CYCLE() cv::multiply(a, b, c, /* scale */ 1.0, dstType);
|
|
|
|
SANITY_CHECK_NOTHING();
|
|
}
|
|
|
|
PERF_TEST_P_(ArithmMixedTest, multiplyScale)
|
|
{
|
|
auto p = GetParam();
|
|
Size sz = get<0>(p);
|
|
int srcType = get<0>(get<1>(p));
|
|
int dstType = get<1>(get<1>(p));
|
|
|
|
cv::Mat a(sz, srcType), b(sz, srcType), c(sz, dstType);
|
|
double scale = 0.5;
|
|
|
|
declare.in(a, b, WARMUP_RNG).out(c);
|
|
|
|
if (CV_MAT_DEPTH(dstType) == CV_32S)
|
|
{
|
|
//According to docs, saturation is not applied when result is 32bit integer
|
|
a /= (2 << 16);
|
|
b /= (2 << 16);
|
|
}
|
|
|
|
TEST_CYCLE() cv::multiply(a, b, c, scale, dstType);
|
|
|
|
SANITY_CHECK_NOTHING();
|
|
}
|
|
|
|
PERF_TEST_P_(ArithmMixedTest, divide)
|
|
{
|
|
auto p = GetParam();
|
|
Size sz = get<0>(p);
|
|
int srcType = get<0>(get<1>(p));
|
|
int dstType = get<1>(get<1>(p));
|
|
|
|
cv::Mat a(sz, srcType), b(sz, srcType), c(sz, dstType);
|
|
double scale = 0.5;
|
|
|
|
declare.in(a, b, WARMUP_RNG).out(c);
|
|
|
|
TEST_CYCLE() cv::divide(a, b, c, scale, dstType);
|
|
|
|
SANITY_CHECK_NOTHING();
|
|
}
|
|
|
|
PERF_TEST_P_(ArithmMixedTest, reciprocal)
|
|
{
|
|
auto p = GetParam();
|
|
Size sz = get<0>(p);
|
|
int srcType = get<0>(get<1>(p));
|
|
int dstType = get<1>(get<1>(p));
|
|
|
|
cv::Mat b(sz, srcType), c(sz, dstType);
|
|
double scale = 0.5;
|
|
|
|
declare.in(b, WARMUP_RNG).out(c);
|
|
|
|
TEST_CYCLE() cv::divide(scale, b, c, dstType);
|
|
|
|
SANITY_CHECK_NOTHING();
|
|
}
|
|
|
|
INSTANTIATE_TEST_CASE_P(/*nothing*/ , ArithmMixedTest,
|
|
testing::Combine(
|
|
testing::Values(szVGA, sz720p, sz1080p),
|
|
testing::Values(std::tuple<perf::MatType, perf::MatType>{CV_8U, CV_16U},
|
|
std::tuple<perf::MatType, perf::MatType>{CV_8S, CV_16S},
|
|
std::tuple<perf::MatType, perf::MatType>{CV_8U, CV_32F},
|
|
std::tuple<perf::MatType, perf::MatType>{CV_8S, CV_32F}
|
|
)
|
|
)
|
|
);
|
|
|
|
typedef perf::TestBaseWithParam<std::tuple<cv::Size, int, bool>> SqrtFixture;
|
|
PERF_TEST_P_(SqrtFixture, Sqrt) {
|
|
Size sz = get<0>(GetParam());
|
|
int type = get<1>(GetParam());
|
|
bool inverse = get<2>(GetParam());
|
|
|
|
Mat src(sz, type), dst(sz, type);
|
|
randu(src, FLT_EPSILON, 1000);
|
|
declare.in(src).out(dst);
|
|
|
|
TEST_CYCLE() cv::pow(src, inverse ? -0.5 : 0.5, dst);
|
|
|
|
SANITY_CHECK_NOTHING();
|
|
}
|
|
INSTANTIATE_TEST_CASE_P(/*nothing*/ , SqrtFixture,
|
|
testing::Combine(
|
|
testing::Values(TYPICAL_MAT_SIZES),
|
|
testing::Values(CV_32FC1, CV_64FC1),
|
|
testing::Bool()
|
|
)
|
|
);
|
|
|
|
///////////// Rotate ////////////////////////
|
|
|
|
typedef perf::TestBaseWithParam<std::tuple<cv::Size, int, perf::MatType>> RotateTest;
|
|
|
|
PERF_TEST_P_(RotateTest, rotate)
|
|
{
|
|
Size sz = get<0>(GetParam());
|
|
int rotatecode = get<1>(GetParam());
|
|
int type = get<2>(GetParam());
|
|
cv::Mat a(sz, type), b(sz, type);
|
|
|
|
declare.in(a, WARMUP_RNG).out(b);
|
|
|
|
TEST_CYCLE() cv::rotate(a, b, rotatecode);
|
|
|
|
SANITY_CHECK_NOTHING();
|
|
}
|
|
|
|
INSTANTIATE_TEST_CASE_P(/*nothing*/ , RotateTest,
|
|
testing::Combine(
|
|
testing::Values(szVGA, sz720p, sz1080p),
|
|
testing::Values(ROTATE_180, ROTATE_90_CLOCKWISE, ROTATE_90_COUNTERCLOCKWISE),
|
|
testing::Values(CV_8UC1, CV_8UC2, CV_8UC3, CV_8UC4, CV_8SC1, CV_16SC1, CV_16SC2, CV_16SC3, CV_16SC4, CV_32SC1, CV_32FC1)
|
|
)
|
|
);
|
|
|
|
|
|
///////////// PatchNaNs ////////////////////////
|
|
|
|
template<typename _Tp>
|
|
_Tp randomNan(RNG& rng);
|
|
|
|
template<>
|
|
float randomNan(RNG& rng)
|
|
{
|
|
uint32_t r = rng.next();
|
|
Cv32suf v;
|
|
v.u = r;
|
|
// exp & set a bit to avoid zero mantissa
|
|
v.u = v.u | 0x7f800001;
|
|
return v.f;
|
|
}
|
|
|
|
template<>
|
|
double randomNan(RNG& rng)
|
|
{
|
|
uint32_t r0 = rng.next();
|
|
uint32_t r1 = rng.next();
|
|
Cv64suf v;
|
|
v.u = (uint64_t(r0) << 32) | uint64_t(r1);
|
|
// exp &set a bit to avoid zero mantissa
|
|
v.u = v.u | 0x7ff0000000000001;
|
|
return v.f;
|
|
}
|
|
|
|
typedef Size_MatType PatchNaNsFixture;
|
|
|
|
PERF_TEST_P_(PatchNaNsFixture, PatchNaNs)
|
|
{
|
|
const Size_MatType_t params = GetParam();
|
|
Size srcSize = get<0>(params);
|
|
const int type = get<1>(params), cn = CV_MAT_CN(type);
|
|
|
|
Mat src(srcSize, type);
|
|
declare.in(src, WARMUP_RNG).out(src);
|
|
|
|
// generating NaNs
|
|
{
|
|
srcSize.width *= cn;
|
|
RNG& rng = theRNG();
|
|
for (int y = 0; y < srcSize.height; ++y)
|
|
{
|
|
float *const ptrf = src.ptr<float>(y);
|
|
for (int x = 0; x < srcSize.width; ++x)
|
|
{
|
|
ptrf[x] = (x + y) % 2 == 0 ? randomNan<float >(rng) : ptrf[x];
|
|
}
|
|
}
|
|
}
|
|
|
|
TEST_CYCLE() cv::patchNaNs(src, 17.7);
|
|
|
|
SANITY_CHECK(src);
|
|
}
|
|
|
|
INSTANTIATE_TEST_CASE_P(/*nothing*/ , PatchNaNsFixture,
|
|
testing::Combine(
|
|
testing::Values(szVGA, sz720p, sz1080p, sz2160p),
|
|
testing::Values(CV_32FC1, CV_32FC2, CV_32FC3, CV_32FC4)
|
|
)
|
|
);
|
|
|
|
//////////////EXP////////////
|
|
|
|
typedef Size_MatType ExpFixture;
|
|
|
|
PERF_TEST_P(ExpFixture, Exp,
|
|
testing::Combine(testing::Values(TYPICAL_MAT_SIZES), testing::Values(CV_32F, CV_64F)))
|
|
{
|
|
cv::Size size = std::get<0>(GetParam());
|
|
int type = std::get<1>(GetParam());
|
|
|
|
cv::Mat src(size, type);
|
|
cv::Mat dst(size, type);
|
|
|
|
declare.in(src).out(dst);
|
|
|
|
cv::randu(src, -5.0, 5.0);
|
|
|
|
TEST_CYCLE()
|
|
{
|
|
cv::exp(src, dst);
|
|
}
|
|
|
|
SANITY_CHECK_NOTHING();
|
|
}
|
|
|
|
//////////////LOG////////////
|
|
|
|
typedef Size_MatType LogFixture;
|
|
|
|
PERF_TEST_P(LogFixture, Log,
|
|
testing::Combine(testing::Values(TYPICAL_MAT_SIZES), testing::Values(CV_32F, CV_64F)))
|
|
{
|
|
cv::Size size = std::get<0>(GetParam());
|
|
int type = std::get<1>(GetParam());
|
|
|
|
cv::Mat src(size, type);
|
|
cv::Mat dst(size, type);
|
|
|
|
declare.in(src).out(dst);
|
|
|
|
cv::randu(src, 1e-5, 1e5);
|
|
|
|
TEST_CYCLE()
|
|
{
|
|
cv::log(src, dst);
|
|
}
|
|
|
|
SANITY_CHECK_NOTHING();
|
|
}
|
|
|
|
} // namespace
|