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opencv_contrib/modules/fastcv/perf/perf_bilateral.cpp
adsha-quic a00b3f3296 Merge pull request #3845 from CodeLinaro:adsha_2ndPost
FastCV Extension code for OpenCV 2ndpost-2 #3845

### Description:
- Add support for cv::fastcv::calcHist

Depends on: [opencv/opencv_contrib#3844](https://github.com/opencv/opencv_contrib/pull/3844)
Depends on: [opencv/opencv#26619](https://github.com/opencv/opencv/pull/26619)
Requires binary from: [opencv/opencv_3rdparty#90](https://github.com/opencv/opencv_3rdparty/pull/90)

### 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
- [ ] 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
2024-12-23 10:11:45 +03:00

69 lines
1.9 KiB
C++

/*
* Copyright (c) 2024 Qualcomm Innovation Center, Inc. All rights reserved.
* SPDX-License-Identifier: Apache-2.0
*/
#include "perf_precomp.hpp"
namespace opencv_test {
typedef std::tuple<float /*sigmaColor*/, float /*sigmaSpace*/> BilateralRecursivePerfParams;
typedef perf::TestBaseWithParam<BilateralRecursivePerfParams> BilateralRecursivePerfTest;
PERF_TEST_P(BilateralRecursivePerfTest, run,
::testing::Combine(::testing::Values(0.01f, 0.03f, 0.1f, 1.f, 5.f),
::testing::Values(0.01f, 0.05f, 0.1f, 1.f, 5.f))
)
{
auto p = GetParam();
float sigmaColor = std::get<0>(p);
float sigmaSpace = std::get<1>(p);
cv::Mat src = imread(cvtest::findDataFile("cv/shared/baboon.png"), cv::IMREAD_GRAYSCALE);
Mat dst;
while(next())
{
startTimer();
cv::fastcv::bilateralRecursive(src, dst, sigmaColor, sigmaSpace);
stopTimer();
}
SANITY_CHECK_NOTHING();
}
typedef std::tuple<float /*sigmaColor*/, float /*sigmaSpace*/, cv::Size, int > BilateralPerfParams;
typedef perf::TestBaseWithParam<BilateralPerfParams> BilateralPerfTest;
PERF_TEST_P(BilateralPerfTest, run,
::testing::Combine(::testing::Values(0.01f, 0.03f, 0.1f, 1.f, 5.f),
::testing::Values(0.01f, 0.05f, 0.1f, 1.f, 5.f),
::testing::Values(Size(8, 8), Size(640, 480), Size(800, 600)),
::testing::Values(5, 7, 9))
)
{
auto p = GetParam();
float sigmaColor = std::get<0>(p);
float sigmaSpace = std::get<1>(p);
cv::Size size = std::get<2>(p);
int d = get<3>(p);
RNG& rng = cv::theRNG();
Mat src(size, CV_8UC1);
cvtest::randUni(rng, src, Scalar::all(0), Scalar::all(255));
Mat dst;
while (next())
{
startTimer();
cv::fastcv::bilateralFilter(src, dst, d, sigmaColor, sigmaSpace);
stopTimer();
}
SANITY_CHECK_NOTHING();
}
} // namespace