Commit 63bb7c16 authored by Alexander Alekhin's avatar Alexander Alekhin

Merge pull request #1208 from Bleach665:fix_VS2010

parents 38dd47cf 41559d74
...@@ -92,12 +92,12 @@ void MakeArtificialExample(UMat &dst_frame1, UMat &dst_frame2) ...@@ -92,12 +92,12 @@ void MakeArtificialExample(UMat &dst_frame1, UMat &dst_frame2)
int OF_scale = 6; int OF_scale = 6;
double sigma = dst_frame1.cols / 300; double sigma = dst_frame1.cols / 300;
UMat tmp(Size(dst_frame1.cols / (int)pow(2, src_scale), dst_frame1.rows / (int)pow(2, src_scale)), CV_8U); UMat tmp(Size(dst_frame1.cols / (1 << src_scale), dst_frame1.rows / (1 << src_scale)), CV_8U);
randu(tmp, 0, 255); randu(tmp, 0, 255);
resize(tmp, dst_frame1, dst_frame1.size(), 0.0, 0.0, INTER_LINEAR); resize(tmp, dst_frame1, dst_frame1.size(), 0.0, 0.0, INTER_LINEAR);
resize(tmp, dst_frame2, dst_frame2.size(), 0.0, 0.0, INTER_LINEAR); resize(tmp, dst_frame2, dst_frame2.size(), 0.0, 0.0, INTER_LINEAR);
Mat displacement_field(Size(dst_frame1.cols / (int)pow(2, OF_scale), dst_frame1.rows / (int)pow(2, OF_scale)), Mat displacement_field(Size(dst_frame1.cols / (1 << OF_scale), dst_frame1.rows / (1 << OF_scale)),
CV_32FC2); CV_32FC2);
randn(displacement_field, 0.0, sigma); randn(displacement_field, 0.0, sigma);
resize(displacement_field, displacement_field, dst_frame2.size(), 0.0, 0.0, INTER_CUBIC); resize(displacement_field, displacement_field, dst_frame2.size(), 0.0, 0.0, INTER_CUBIC);
......
...@@ -86,12 +86,12 @@ void MakeArtificialExample(Mat &dst_frame1, Mat &dst_frame2) ...@@ -86,12 +86,12 @@ void MakeArtificialExample(Mat &dst_frame1, Mat &dst_frame2)
int OF_scale = 6; int OF_scale = 6;
double sigma = dst_frame1.cols / 300; double sigma = dst_frame1.cols / 300;
Mat tmp(Size(dst_frame1.cols / (int)pow(2, src_scale), dst_frame1.rows / (int)pow(2, src_scale)), CV_8U); Mat tmp(Size(dst_frame1.cols / (1 << src_scale), dst_frame1.rows / (1 << src_scale)), CV_8U);
randu(tmp, 0, 255); randu(tmp, 0, 255);
resize(tmp, dst_frame1, dst_frame1.size(), 0.0, 0.0, INTER_LINEAR); resize(tmp, dst_frame1, dst_frame1.size(), 0.0, 0.0, INTER_LINEAR);
resize(tmp, dst_frame2, dst_frame2.size(), 0.0, 0.0, INTER_LINEAR); resize(tmp, dst_frame2, dst_frame2.size(), 0.0, 0.0, INTER_LINEAR);
Mat displacement_field(Size(dst_frame1.cols / (int)pow(2, OF_scale), dst_frame1.rows / (int)pow(2, OF_scale)), Mat displacement_field(Size(dst_frame1.cols / (1 << OF_scale), dst_frame1.rows / (1 << OF_scale)),
CV_32FC2); CV_32FC2);
randn(displacement_field, 0.0, sigma); randn(displacement_field, 0.0, sigma);
resize(displacement_field, displacement_field, dst_frame2.size(), 0.0, 0.0, INTER_CUBIC); resize(displacement_field, displacement_field, dst_frame2.size(), 0.0, 0.0, INTER_CUBIC);
......
...@@ -570,7 +570,7 @@ bool GPCTree::trainNode( size_t nodeId, SIter begin, SIter end, unsigned depth ) ...@@ -570,7 +570,7 @@ bool GPCTree::trainNode( size_t nodeId, SIter begin, SIter end, unsigned depth )
localBestScore = score; localBestScore = score;
else else
{ {
const double beta = simulatedAnnealingTemperatureCoef * std::sqrt( i ) / ( nSamples * ( scoreGainPos + scoreGainNeg ) ); const double beta = simulatedAnnealingTemperatureCoef * std::sqrt( static_cast<float>(i) ) / ( nSamples * ( scoreGainPos + scoreGainNeg ) );
if ( rng.uniform( 0.0, 1.0 ) > std::exp( -beta * ( localBestScore - score) ) ) if ( rng.uniform( 0.0, 1.0 ) > std::exp( -beta * ( localBestScore - score) ) )
coef[pos] = randomModification; coef[pos] = randomModification;
} }
......
...@@ -100,8 +100,8 @@ TEST_P(DenseOpticalFlow_DIS, MultithreadReproducibility) ...@@ -100,8 +100,8 @@ TEST_P(DenseOpticalFlow_DIS, MultithreadReproducibility)
// resulting flow should be within the frame bounds: // resulting flow should be within the frame bounds:
double min_val, max_val; double min_val, max_val;
minMaxLoc(resMultiThread, &min_val, &max_val); minMaxLoc(resMultiThread, &min_val, &max_val);
EXPECT_LE(abs(min_val), sqrt(size.height * size.height + size.width * size.width)); EXPECT_LE(abs(min_val), sqrt( static_cast<double>(size.height * size.height + size.width * size.width)) );
EXPECT_LE(abs(max_val), sqrt(size.height * size.height + size.width * size.width)); EXPECT_LE(abs(max_val), sqrt( static_cast<double>(size.height * size.height + size.width * size.width)) );
} }
} }
...@@ -151,8 +151,8 @@ TEST_P(DenseOpticalFlow_VariationalRefinement, MultithreadReproducibility) ...@@ -151,8 +151,8 @@ TEST_P(DenseOpticalFlow_VariationalRefinement, MultithreadReproducibility)
// resulting flow should be within the frame bounds: // resulting flow should be within the frame bounds:
double min_val, max_val; double min_val, max_val;
minMaxLoc(resMultiThread, &min_val, &max_val); minMaxLoc(resMultiThread, &min_val, &max_val);
EXPECT_LE(abs(min_val), sqrt(size.height * size.height + size.width * size.width)); EXPECT_LE(abs(min_val), sqrt( static_cast<double>(size.height * size.height + size.width * size.width)) );
EXPECT_LE(abs(max_val), sqrt(size.height * size.height + size.width * size.width)); EXPECT_LE(abs(max_val), sqrt( static_cast<double>(size.height * size.height + size.width * size.width)) );
} }
} }
......
...@@ -477,7 +477,7 @@ void normalize( const Mat &pts, const int& dim, Mat& normpts, Mat &T ) ...@@ -477,7 +477,7 @@ void normalize( const Mat &pts, const int& dim, Mat& normpts, Mat &T )
averagedist = averagedist+(float)norm(ptstmp); averagedist = averagedist+(float)norm(ptstmp);
} }
averagedist = averagedist / normpts.cols; averagedist = averagedist / normpts.cols;
scale = (float)(sqrt(dim) / averagedist); scale = (float)(sqrt(static_cast<float>(dim)) / averagedist);
normpts = normpts * scale; normpts = normpts * scale;
......
...@@ -200,12 +200,12 @@ bool SinusoidalPatternProfilometry_Impl::generate( OutputArrayOfArrays pattern ) ...@@ -200,12 +200,12 @@ bool SinusoidalPatternProfilometry_Impl::generate( OutputArrayOfArrays pattern )
if( params.horizontal ) if( params.horizontal )
{ {
period = params.height / params.nbrOfPeriods; period = params.height / params.nbrOfPeriods;
nbrOfMarkersOnOneRow = (int)floor((params.width - firstMarkerOffset) / m); nbrOfMarkersOnOneRow = (int)floor(static_cast<float>((params.width - firstMarkerOffset) / m));
} }
else else
{ {
period = params.width / params.nbrOfPeriods; period = params.width / params.nbrOfPeriods;
nbrOfMarkersOnOneRow = (int)floor((params.height - firstMarkerOffset) / m); nbrOfMarkersOnOneRow = (int)floor(static_cast<float>((params.height - firstMarkerOffset) / m));
} }
frequency = (float) 1 / period; frequency = (float) 1 / period;
......
...@@ -117,7 +117,7 @@ int main(int argc, char** argv) ...@@ -117,7 +117,7 @@ int main(int argc, char** argv)
cerr << "Sample count have to be a positive integer: " << argv[1] << endl; cerr << "Sample count have to be a positive integer: " << argv[1] << endl;
return 1; return 1;
} }
initSeedCount = (int)floor(initSampleCount / 4); initSeedCount = (int)floor(static_cast<float>(initSampleCount / 4));
initSeedCount = std::max(1, initSeedCount); // fallback if sample count == 1 initSeedCount = std::max(1, initSeedCount); // fallback if sample count == 1
} }
if (argc > 2) // seed count if (argc > 2) // seed count
......
...@@ -63,7 +63,7 @@ namespace ximgproc ...@@ -63,7 +63,7 @@ namespace ximgproc
if (sigmaAlpha < 0) if (sigmaAlpha < 0)
sigmaAlpha = 5. * fr; sigmaAlpha = 5. * fr;
if (sigmaAvg < 0) if (sigmaAvg < 0)
sigmaAvg = 0.05 * sqrt(src.channels()); sigmaAvg = 0.05 * sqrt(static_cast<float>(src.channels()));
Mat I; Mat I;
src.copyTo(I); src.copyTo(I);
......
Markdown is supported
0% or
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment