TEST_P(InterpolatorTest, MultiThreadReproducibility)
{
if (cv::getNumberOfCPUs() == 1)
return;
double MAX_DIF = 1.0;
double MAX_MEAN_DIF = 1.0 / 256.0;
int loopsCount = 2;
RNG rng(0);
InterpolatorParams params = GetParam();
Size size = get<0>(params);
int guideType = get<1>(params);
Mat from(size, guideType);
randu(from, 0, 255);
int num_matches = rng.uniform(5,SHRT_MAX-1);
vector<Point2f> from_points;
vector<Point2f> to_points;
for(int i=0;i<num_matches;i++)
{
from_points.push_back(Point2f(rng.uniform(0.01f,(float)size.width-1.01f),rng.uniform(0.01f,(float)size.height-1.01f)));
to_points.push_back(Point2f(rng.uniform(0.01f,(float)size.width-1.01f),rng.uniform(0.01f,(float)size.height-1.01f)));
}
int nThreads = cv::getNumThreads();
if (nThreads == 1)
throw SkipTestException("Single thread environment");
for (int iter = 0; iter <= loopsCount; iter++)
{
int K = rng.uniform(4,512);
float sigma = rng.uniform(0.01f,0.5f);
float FGSlambda = rng.uniform(100.0f, 10000.0f);
float FGSsigma = rng.uniform(0.5f, 100.0f);
Ptr<EdgeAwareInterpolator> interpolator = createEdgeAwareInterpolator();
interpolator->setK(K);
interpolator->setSigma(sigma);
interpolator->setUsePostProcessing(true);
interpolator->setFGSLambda(FGSlambda);
interpolator->setFGSSigma(FGSsigma);
cv::setNumThreads(nThreads);
Mat resMultiThread;
interpolator->interpolate(from,from_points,Mat(),to_points,resMultiThread);
cv::setNumThreads(1);
Mat resSingleThread;
interpolator->interpolate(from,from_points,Mat(),to_points,resSingleThread);
EXPECT_LE(cv::norm(resSingleThread, resMultiThread, NORM_INF), MAX_DIF);
EXPECT_LE(cv::norm(resSingleThread, resMultiThread, NORM_L1) , MAX_MEAN_DIF*resMultiThread.total());
}
}
TEST(InterpolatorTest, ReferenceAccuracy)
{
double MAX_DIF = 1.0;
double MAX_MEAN_DIF = 1.0 / 256.0;
string dir = getDataDir() + "cv/sparse_match_interpolator";
Mat src = imread(getDataDir() + "cv/optflow/RubberWhale1.png",IMREAD_COLOR);
ASSERT_FALSE(src.empty());
Mat ref_flow = readOpticalFlow(dir + "/RubberWhale_reference_result.flo");
ASSERT_FALSE(ref_flow.empty());
ifstream file((dir + "/RubberWhale_sparse_matches.txt").c_str());
float from_x,from_y,to_x,to_y;
vector<Point2f> from_points;
vector<Point2f> to_points;
while(file >> from_x >> from_y >> to_x >> to_y)
{
from_points.push_back(Point2f(from_x,from_y));
to_points.push_back(Point2f(to_x,to_y));
}
cv::setNumThreads(cv::getNumberOfCPUs());
Mat res_flow;
Ptr<EdgeAwareInterpolator> interpolator = createEdgeAwareInterpolator();
interpolator->setK(128);
interpolator->setSigma(0.05f);
interpolator->setUsePostProcessing(true);
interpolator->setFGSLambda(500.0f);
interpolator->setFGSSigma(1.5f);
interpolator->interpolate(src,from_points,Mat(),to_points,res_flow);
EXPECT_LE(cv::norm(res_flow, ref_flow, NORM_INF), MAX_DIF);
EXPECT_LE(cv::norm(res_flow, ref_flow, NORM_L1) , MAX_MEAN_DIF*res_flow.total());
}