PERF_TEST_P( Img_Aperture_L2_thresholds, canny,
testing::Combine(
- testing::Values( "cv/shared/lena.jpg", "stitching/b1.jpg" ),
+ testing::Values( "cv/shared/lena.jpg", "stitching/b1.jpg", "cv/detectors_descriptors_evaluation/images_datasets/leuven/img1.png" ),
testing::Values( 3, 5 ),
testing::Bool(),
- testing::Values( make_tuple(50.0, 100.0), make_tuple(0.0, 50.0) )
+ testing::Values( make_tuple(50.0, 100.0), make_tuple(0.0, 50.0), make_tuple(100.0, 120.0) )
)
)
{
double low_thresh, double high_thresh,
int aperture_size )
{
+#ifdef HAVE_TEGRA_OPTIMIZATION
+ if (tegra::canny(cv::cvarrToMat(srcarr), cv::cvarrToMat(dstarr), low_thresh, high_thresh,
+ aperture_size & ~CV_CANNY_L2_GRADIENT, (aperture_size & CV_CANNY_L2_GRADIENT) == CV_CANNY_L2_GRADIENT))
+ return;
+#endif
cv::Ptr<CvMat> dx, dy;
cv::AutoBuffer<char> buffer;
std::vector<uchar*> stack;
from optparse import OptionParser
-import glob, sys, os
+import glob, sys, os, re
if __name__ == "__main__":
parser = OptionParser()
continue
idx1 = text.find("<tbody>") + len("<tbody>")
idx2 = html.rfind("</tbody>")
- html = html[:idx2] + text[idx1:]
+ html = html[:idx2] + re.sub(r"[ \t\n\r]+", " ", text[idx1:])
except:
pass