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#include "perf_precomp.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/core/internal.hpp"
#include "opencv2/flann/flann.hpp"
#include "opencv2/opencv_modules.hpp"
using namespace std;
using namespace cv;
using namespace perf;
using std::tr1::make_tuple;
using std::tr1::get;
#define SURF_MATCH_CONFIDENCE 0.65f
#define ORB_MATCH_CONFIDENCE 0.3f
#define WORK_MEGAPIX 0.6
typedef TestBaseWithParam<String> stitch;
typedef TestBaseWithParam<String> match;
typedef std::tr1::tuple<String, int> matchVector_t;
typedef TestBaseWithParam<matchVector_t> matchVector;
#ifdef HAVE_OPENCV_NONFREE_TODO_FIND_WHY_SURF_IS_NOT_ABLE_TO_STITCH_PANOS
#define TEST_DETECTORS testing::Values("surf", "orb")
#else
#define TEST_DETECTORS testing::Values<String>("orb")
#endif
PERF_TEST_P(stitch, a123, TEST_DETECTORS)
{
Mat pano;
vector<Mat> imgs;
imgs.push_back( imread( getDataPath("stitching/a1.png") ) );
imgs.push_back( imread( getDataPath("stitching/a2.png") ) );
imgs.push_back( imread( getDataPath("stitching/a3.png") ) );
Ptr<detail::FeaturesFinder> featuresFinder = GetParam() == "orb"
? (detail::FeaturesFinder*)new detail::OrbFeaturesFinder()
: (detail::FeaturesFinder*)new detail::SurfFeaturesFinder();
Ptr<detail::FeaturesMatcher> featuresMatcher = GetParam() == "orb"
? new detail::BestOf2NearestMatcher(false, ORB_MATCH_CONFIDENCE)
: new detail::BestOf2NearestMatcher(false, SURF_MATCH_CONFIDENCE);
declare.time(30 * 20).iterations(20);
while(next())
{
Stitcher stitcher = Stitcher::createDefault();
stitcher.setFeaturesFinder(featuresFinder);
stitcher.setFeaturesMatcher(featuresMatcher);
stitcher.setWarper(new SphericalWarper());
stitcher.setRegistrationResol(WORK_MEGAPIX);
startTimer();
stitcher.stitch(imgs, pano);
stopTimer();
}
Mat pano_small;
if (!pano.empty())
resize(pano, pano_small, Size(320, 240), 0, 0, INTER_AREA);
SANITY_CHECK(pano_small, 5);
}
PERF_TEST_P(stitch, b12, TEST_DETECTORS)
{
Mat pano;
vector<Mat> imgs;
imgs.push_back( imread( getDataPath("stitching/b1.png") ) );
imgs.push_back( imread( getDataPath("stitching/b2.png") ) );
Ptr<detail::FeaturesFinder> featuresFinder = GetParam() == "orb"
? (detail::FeaturesFinder*)new detail::OrbFeaturesFinder()
: (detail::FeaturesFinder*)new detail::SurfFeaturesFinder();
Ptr<detail::FeaturesMatcher> featuresMatcher = GetParam() == "orb"
? new detail::BestOf2NearestMatcher(false, ORB_MATCH_CONFIDENCE)
: new detail::BestOf2NearestMatcher(false, SURF_MATCH_CONFIDENCE);
declare.time(30 * 20).iterations(20);
while(next())
{
Stitcher stitcher = Stitcher::createDefault();
stitcher.setFeaturesFinder(featuresFinder);
stitcher.setFeaturesMatcher(featuresMatcher);
stitcher.setWarper(new SphericalWarper());
stitcher.setRegistrationResol(WORK_MEGAPIX);
startTimer();
stitcher.stitch(imgs, pano);
stopTimer();
}
Mat pano_small;
if (!pano.empty())
resize(pano, pano_small, Size(320, 240), 0, 0, INTER_AREA);
SANITY_CHECK(pano_small, 5);
}
PERF_TEST_P( match, bestOf2Nearest, TEST_DETECTORS)
{
Mat img1, img1_full = imread( getDataPath("stitching/b1.png") );
Mat img2, img2_full = imread( getDataPath("stitching/b2.png") );
float scale1 = (float)std::min(1.0, sqrt(WORK_MEGAPIX * 1e6 / img1_full.total()));
float scale2 = (float)std::min(1.0, sqrt(WORK_MEGAPIX * 1e6 / img2_full.total()));
resize(img1_full, img1, Size(), scale1, scale1);
resize(img2_full, img2, Size(), scale2, scale2);
Ptr<detail::FeaturesFinder> finder;
Ptr<detail::FeaturesMatcher> matcher;
if (GetParam() == "surf")
{
finder = new detail::SurfFeaturesFinder();
matcher = new detail::BestOf2NearestMatcher(false, SURF_MATCH_CONFIDENCE);
}
else if (GetParam() == "orb")
{
finder = new detail::OrbFeaturesFinder();
matcher = new detail::BestOf2NearestMatcher(false, ORB_MATCH_CONFIDENCE);
}
else
{
FAIL() << "Unknown 2D features type: " << GetParam();
}
detail::ImageFeatures features1, features2;
(*finder)(img1, features1);
(*finder)(img2, features2);
detail::MatchesInfo pairwise_matches;
declare.in(features1.descriptors, features2.descriptors);
while(next())
{
cvflann::seed_random(42);//for predictive FlannBasedMatcher
startTimer();
(*matcher)(features1, features2, pairwise_matches);
stopTimer();
matcher->collectGarbage();
}
std::vector<DMatch>& matches = pairwise_matches.matches;
if (GetParam() == "orb") matches.resize(0);
for(size_t q = 0; q < matches.size(); ++q)
if (matches[q].imgIdx < 0) { matches.resize(q); break;}
SANITY_CHECK_MATCHES(matches);
}
PERF_TEST_P( matchVector, bestOf2NearestVectorFeatures, testing::Combine(
TEST_DETECTORS,
testing::Values(2, 4, 8))
)
{
Mat img1, img1_full = imread( getDataPath("stitching/b1.png") );
Mat img2, img2_full = imread( getDataPath("stitching/b2.png") );
float scale1 = (float)std::min(1.0, sqrt(WORK_MEGAPIX * 1e6 / img1_full.total()));
float scale2 = (float)std::min(1.0, sqrt(WORK_MEGAPIX * 1e6 / img2_full.total()));
resize(img1_full, img1, Size(), scale1, scale1);
resize(img2_full, img2, Size(), scale2, scale2);
Ptr<detail::FeaturesFinder> finder;
Ptr<detail::FeaturesMatcher> matcher;
String detectorName = get<0>(GetParam());
int featuresVectorSize = get<1>(GetParam());
if (detectorName == "surf")
{
finder = new detail::SurfFeaturesFinder();
matcher = new detail::BestOf2NearestMatcher(false, SURF_MATCH_CONFIDENCE);
}
else if (detectorName == "orb")
{
finder = new detail::OrbFeaturesFinder();
matcher = new detail::BestOf2NearestMatcher(false, ORB_MATCH_CONFIDENCE);
}
else
{
FAIL() << "Unknown 2D features type: " << get<0>(GetParam());
}
detail::ImageFeatures features1, features2;
(*finder)(img1, features1);
(*finder)(img2, features2);
vector<detail::ImageFeatures> features;
vector<detail::MatchesInfo> pairwise_matches;
for(int i = 0; i < featuresVectorSize/2; i++)
{
features.push_back(features1);
features.push_back(features2);
}
declare.time(200);
while(next())
{
cvflann::seed_random(42);//for predictive FlannBasedMatcher
startTimer();
(*matcher)(features, pairwise_matches);
stopTimer();
matcher->collectGarbage();
}
std::vector<DMatch>& matches = pairwise_matches[detectorName == "surf" ? 1 : 0].matches;
for(size_t q = 0; q < matches.size(); ++q)
if (matches[q].imgIdx < 0) { matches.resize(q); break;}
SANITY_CHECK_MATCHES(matches);
}
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