#include "perf_precomp.hpp" #include using namespace std; using namespace cv; using namespace perf; using std::tr1::make_tuple; using std::tr1::get; typedef std::tr1::tuple ImageName_MinSize_t; typedef perf::TestBaseWithParam ImageName_MinSize; PERF_TEST_P(ImageName_MinSize, CascadeClassifierLBPFrontalFace, testing::Combine(testing::Values( std::string("cv/shared/lena.png"), std::string("cv/shared/1_itseez-0000289.png"), std::string("cv/shared/1_itseez-0000492.png"), std::string("cv/shared/1_itseez-0000573.png")), testing::Values(24, 30, 40, 50, 60, 70, 80, 90) ) ) { const string filename = get<0>(GetParam()); int min_size = get<1>(GetParam()); Size minSize(min_size, min_size); CascadeClassifier cc(getDataPath("cv/cascadeandhog/cascades/lbpcascade_frontalface.xml")); if (cc.empty()) FAIL() << "Can't load cascade file"; Mat img = imread(getDataPath(filename), 0); if (img.empty()) FAIL() << "Can't load source image"; vector faces; equalizeHist(img, img); declare.in(img); while(next()) { faces.clear(); startTimer(); cc.detectMultiScale(img, faces, 1.1, 3, 0, minSize); stopTimer(); } std::sort(faces.begin(), faces.end(), comparators::RectLess()); SANITY_CHECK(faces, 3.001 * faces.size()); } typedef std::tr1::tuple fixture; typedef perf::TestBaseWithParam detect; namespace { typedef cv::SCascade::Detection detection_t; void extractRacts(std::vector objectBoxes, vector rects) { rects.clear(); for (int i = 0; i < (int)objectBoxes.size(); ++i) rects.push_back(objectBoxes[i].bb); } } PERF_TEST_P(detect, SCascade, testing::Combine(testing::Values(std::string("cv/cascadeandhog/sc_cvpr_2012_to_opencv.xml")), testing::Values(std::string("cv/cascadeandhog/bahnhof/image_00000000_0.png")))) { typedef cv::SCascade::Detection Detection; cv::Mat colored = imread(getDataPath(get<1>(GetParam()))); ASSERT_FALSE(colored.empty()); cv::SCascade cascade; cv::FileStorage fs(getDataPath(get<0>(GetParam())), cv::FileStorage::READ); ASSERT_TRUE(fs.isOpened()); ASSERT_TRUE(cascade.load(fs.getFirstTopLevelNode())); std::vector objectBoxes; cascade.detect(colored, cv::noArray(), objectBoxes); TEST_CYCLE() { cascade.detect(colored, cv::noArray(), objectBoxes); } vector rects; extractRacts(objectBoxes, rects); std::sort(rects.begin(), rects.end(), comparators::RectLess()); SANITY_CHECK(rects); }