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Open Source Computer Vision Library
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43 lines
1.6 KiB
43 lines
1.6 KiB
#include "perf_precomp.hpp" |
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using namespace std; |
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using namespace cv; |
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using namespace perf; |
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using std::tr1::make_tuple; |
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using std::tr1::get; |
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typedef std::tr1::tuple<string, int, double, int, int, bool> Image_MaxCorners_QualityLevel_MinDistance_BlockSize_gradientSize_UseHarris_t; |
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typedef perf::TestBaseWithParam<Image_MaxCorners_QualityLevel_MinDistance_BlockSize_gradientSize_UseHarris_t> Image_MaxCorners_QualityLevel_MinDistance_BlockSize_gradientSize_UseHarris; |
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PERF_TEST_P(Image_MaxCorners_QualityLevel_MinDistance_BlockSize_gradientSize_UseHarris, goodFeaturesToTrack, |
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testing::Combine( |
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testing::Values( "stitching/a1.png", "cv/shared/pic5.png"), |
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testing::Values( 100, 500 ), |
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testing::Values( 0.1, 0.01 ), |
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testing::Values( 3, 5 ), |
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testing::Values( 3, 5 ), |
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testing::Bool() |
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) |
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) |
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{ |
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string filename = getDataPath(get<0>(GetParam())); |
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int maxCorners = get<1>(GetParam()); |
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double qualityLevel = get<2>(GetParam()); |
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int blockSize = get<3>(GetParam()); |
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int gradientSize = get<4>(GetParam()); |
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bool useHarrisDetector = get<5>(GetParam()); |
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Mat image = imread(filename, IMREAD_GRAYSCALE); |
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if (image.empty()) |
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FAIL() << "Unable to load source image" << filename; |
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std::vector<Point2f> corners; |
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double minDistance = 1; |
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TEST_CYCLE() goodFeaturesToTrack(image, corners, maxCorners, qualityLevel, minDistance, noArray(), blockSize, gradientSize, useHarrisDetector); |
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if (corners.size() > 50) |
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corners.erase(corners.begin() + 50, corners.end()); |
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SANITY_CHECK(corners); |
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}
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