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https://github.com/opencv/opencv.git
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Anand Mahesh
ad50964f78
Feat: Add OpenCL support for AKAZE features #28879 Implement OpenCL-accelerated AKAZE feature detection and descriptor extraction Benchmarked on RTX 5060 Ti: 1.2x to 3.31x faster for image sizes from 640x480 to 3840x2160 - Added 8 OpenCL kernels for feature detection and descriptor extraction - Refactored compute_kcontrast to use OpenCV magnitude() for consistency - Added comprehensive tests with >95% accuracy vs CPU baseline ### 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 - [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. - [x] The feature is well documented and sample code can be built with the project CMake
128 lines
3.9 KiB
C++
128 lines
3.9 KiB
C++
// This file is part of OpenCV project.
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// It is subject to the license terms in the LICENSE file found in the top-level directory
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// of this distribution and at http://opencv.org/license.html
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#include "../perf_precomp.hpp"
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#include "opencv2/ts/ocl_perf.hpp"
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#ifdef HAVE_OPENCL
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namespace opencv_test {
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namespace ocl {
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typedef Size_MatType AKAZEFixture;
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OCL_PERF_TEST_P(AKAZEFixture, detectAndCompute, ::testing::Combine(OCL_PERF_ENUM(OCL_SIZE_1, OCL_SIZE_2, OCL_SIZE_3), OCL_PERF_ENUM((MatType)CV_8UC1)))
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{
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const Size_MatType_t params = GetParam();
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const Size srcSize = get<0>(params);
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const int type = get<1>(params);
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checkDeviceMaxMemoryAllocSize(srcSize, type);
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UMat img(srcSize, type), mask;
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declare.in(img, WARMUP_RNG);
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Ptr<AKAZE> akaze = AKAZE::create(AKAZE::DESCRIPTOR_MLDB_UPRIGHT, 0, 3, 0.001f, 1, 1, KAZE::DIFF_PM_G2);
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vector<KeyPoint> points;
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UMat descriptors;
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OCL_TEST_CYCLE() akaze->detectAndCompute(img, mask, points, descriptors, false);
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EXPECT_GT(points.size(), 20u);
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EXPECT_EQ((size_t)descriptors.rows, points.size());
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SANITY_CHECK_NOTHING();
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}
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typedef Size_MatType AKAZEOclMldbUprightFixture;
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OCL_PERF_TEST_P(AKAZEOclMldbUprightFixture, detectAndComputeMLDB,
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::testing::Combine(
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::testing::Values(
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cv::Size(320, 240), cv::Size(640, 480), cv::Size(960, 540),
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cv::Size(1280, 720), cv::Size(1920, 1080), cv::Size(2560, 1440), cv::Size(3840, 2160)
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),
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OCL_PERF_ENUM((MatType)CV_8UC1)
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))
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{
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const Size_MatType_t params = GetParam();
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const cv::Size srcSize = get<0>(params);
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UMat img(srcSize, CV_8U);
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declare.in(img, WARMUP_RNG);
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Ptr<Feature2D> det = AKAZE::create(AKAZE::DESCRIPTOR_MLDB_UPRIGHT, 0, 3, 0.001f, 4, 4, KAZE::DIFF_PM_G2);
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vector<KeyPoint> kps;
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UMat descriptors;
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OCL_TEST_CYCLE() det->detectAndCompute(img, noArray(), kps, descriptors, false);
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EXPECT_GT(kps.size(), 0u);
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SANITY_CHECK_NOTHING();
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}
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typedef tuple<std::string, int> AKAZEOclRealImagesParams;
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typedef TestBaseWithParam<AKAZEOclRealImagesParams> AKAZEOclRealImagesFixture;
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OCL_PERF_TEST_P(AKAZEOclRealImagesFixture, detectAndComputeMLDBRealImages,
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::testing::Combine(
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::testing::Values(
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std::string("stitching/boat1.jpg"),
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std::string("stitching/boat2.jpg"),
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std::string("stitching/boat3.jpg"),
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std::string("stitching/boat4.jpg"),
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std::string("stitching/boat5.jpg"),
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std::string("stitching/boat6.jpg")
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),
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::testing::Values(0)
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))
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{
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const std::string imgName = get<0>(GetParam());
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Mat img_mat = imread(getDataPath(imgName), IMREAD_GRAYSCALE);
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if (img_mat.empty())
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throw cvtest::SkipTestException("Image not found: " + imgName);
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UMat img;
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img_mat.copyTo(img);
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declare.in(img);
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Ptr<Feature2D> det = AKAZE::create(AKAZE::DESCRIPTOR_MLDB_UPRIGHT, 0, 3, 0.001f, 4, 4, KAZE::DIFF_PM_G2);
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vector<KeyPoint> kps;
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UMat descriptors;
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OCL_TEST_CYCLE() det->detectAndCompute(img, noArray(), kps, descriptors, false);
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EXPECT_GT(kps.size(), 0u);
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SANITY_CHECK_NOTHING();
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}
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typedef Size_MatType AKAZEOclKazeUprightFixture;
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OCL_PERF_TEST_P(AKAZEOclKazeUprightFixture, detectAndComputeKAZEUpright,
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::testing::Combine(
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::testing::Values(cv::Size(320, 240), cv::Size(640, 480), cv::Size(1280, 720)),
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OCL_PERF_ENUM((MatType)CV_8UC1)
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))
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{
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const Size_MatType_t params = GetParam();
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const cv::Size srcSize = get<0>(params);
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UMat img(srcSize, CV_8U);
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declare.in(img, WARMUP_RNG);
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Ptr<Feature2D> det = AKAZE::create(AKAZE::DESCRIPTOR_KAZE_UPRIGHT, 0, 3, 0.001f, 4, 4, KAZE::DIFF_PM_G2);
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vector<KeyPoint> kps;
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UMat descriptors;
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OCL_TEST_CYCLE() det->detectAndCompute(img, noArray(), kps, descriptors, false);
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EXPECT_GT(kps.size(), 0u);
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SANITY_CHECK_NOTHING();
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}
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} // ocl
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} // opencv_test
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#endif // HAVE_OPENCL
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