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#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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enum { TYPE_5_8 =FastFeatureDetector::TYPE_5_8, TYPE_7_12 = FastFeatureDetector::TYPE_7_12, TYPE_9_16 = FastFeatureDetector::TYPE_9_16 };
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CV_ENUM(FastType, TYPE_5_8, TYPE_7_12, TYPE_9_16)
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typedef std::tr1::tuple<string, FastType> File_Type_t;
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typedef perf::TestBaseWithParam<File_Type_t> fast;
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#define FAST_IMAGES \
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"cv/detectors_descriptors_evaluation/images_datasets/leuven/img1.png",\
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"stitching/a3.png"
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PERF_TEST_P(fast, detect, testing::Combine(
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testing::Values(FAST_IMAGES),
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FastType::all()
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))
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{
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string filename = getDataPath(get<0>(GetParam()));
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int type = get<1>(GetParam());
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Mat frame = imread(filename, IMREAD_GRAYSCALE);
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if (frame.empty())
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FAIL() << "Unable to load source image " << filename;
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declare.in(frame);
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Ptr<FeatureDetector> fd = Algorithm::create<FeatureDetector>("Feature2D.FAST");
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ASSERT_FALSE( fd.empty() );
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fd->set("threshold", 20);
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fd->set("nonmaxSuppression", true);
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fd->set("type", type);
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vector<KeyPoint> points;
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TEST_CYCLE() fd->detect(frame, points);
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SANITY_CHECK_KEYPOINTS(points);
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}
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