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