generic-library/opencv
1
0
Fork 0
Code Issues Pull Requests Releases Wiki Activity

Merged the trunk 8892,8894,8898

Browse Source
This commit is contained in:
Andrey Kamaev 2012-07-02 13:06:28 +00:00
parent cf97209f95
commit a66cd5698a
3 changed files with 9 additions and 10 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
modules/core/doc/operations_on_arrays.rst
View File

@ -1820,7 +1820,7 @@ Finds the global minimum and maximum in an array
.. note:: .. note::
When ``minIdx`` is not NULL, it must have at least 2 elements (as well as ``maxIdx``), even if ``src`` is a single-row or single-column matrix. In OpenCV (following MATLAB) each array has at least 2 dimensions, i.e. single-row matrix is ``Mx1`` matrix (and therefore ``minIdx``/``maxIdx`` will be ``(i1,0)``/``(i2,0)``) and single-column matrix is ``1xN`` matrix (and therefore ``minIdx``/``maxIdx`` will be ``(0,j1)``/``(0,j2)``). When ``minIdx`` is not NULL, it must have at least 2 elements (as well as ``maxIdx``), even if ``src`` is a single-row or single-column matrix. In OpenCV (following MATLAB) each array has at least 2 dimensions, i.e. single-column matrix is ``Mx1`` matrix (and therefore ``minIdx``/``maxIdx`` will be ``(i1,0)``/``(i2,0)``) and single-row matrix is ``1xN`` matrix (and therefore ``minIdx``/``maxIdx`` will be ``(0,j1)``/``(0,j2)``).
:param maxIdx: Pointer to the returned maximum location (in nD case). ``NULL`` is used if not required. :param maxIdx: Pointer to the returned maximum location (in nD case). ``NULL`` is used if not required.

2
modules/nonfree/src/surf.cpp
View File

@ -667,7 +667,7 @@ struct SURFInvoker
besty = sumy; besty = sumy;
} }
} }
descriptor_dir = fastAtan2( besty, bestx ); descriptor_dir = fastAtan2( -besty, bestx );
} }
kp.angle = descriptor_dir; kp.angle = descriptor_dir;
if( !descriptors || !descriptors->data ) if( !descriptors || !descriptors->data )

15
modules/nonfree/test/test_features2d.cpp
View File

@ -291,9 +291,9 @@ public:
typedef typename Distance::ValueType ValueType; typedef typename Distance::ValueType ValueType;
typedef typename Distance::ResultType DistanceType; typedef typename Distance::ResultType DistanceType;
CV_DescriptorExtractorTest( const string _name, DistanceType _maxDist, const Ptr<DescriptorExtractor>& _dextractor, float _prevTime, CV_DescriptorExtractorTest( const string _name, DistanceType _maxDist, const Ptr<DescriptorExtractor>& _dextractor,
Distance d = Distance() ): Distance d = Distance() ):
name(_name), maxDist(_maxDist), prevTime(_prevTime), dextractor(_dextractor), distance(d) {} name(_name), maxDist(_maxDist), dextractor(_dextractor), distance(d) {}
protected: protected:
virtual void createDescriptorExtractor() {} virtual void createDescriptorExtractor() {}
@ -401,7 +401,7 @@ protected:
double t = (double)getTickCount(); double t = (double)getTickCount();
dextractor->compute( img, keypoints, calcDescriptors ); dextractor->compute( img, keypoints, calcDescriptors );
t = getTickCount() - t; t = getTickCount() - t;
ts->printf(cvtest::TS::LOG, "\nAverage time of computing one descriptor = %g ms (previous time = %g ms).\n", t/((double)cvGetTickFrequency()*1000.)/calcDescriptors.rows, prevTime ); ts->printf(cvtest::TS::LOG, "\nAverage time of computing one descriptor = %g ms.\n", t/((double)cvGetTickFrequency()*1000.)/calcDescriptors.rows );
if( calcDescriptors.rows != (int)keypoints.size() ) if( calcDescriptors.rows != (int)keypoints.size() )
{ {
@ -486,7 +486,6 @@ protected:
string name; string name;
const DistanceType maxDist; const DistanceType maxDist;
const float prevTime;
Ptr<DescriptorExtractor> dextractor; Ptr<DescriptorExtractor> dextractor;
Distance distance; Distance distance;
@ -988,28 +987,28 @@ TEST( Features2d_Detector_SURF, regression )
TEST( Features2d_DescriptorExtractor_SIFT, regression ) TEST( Features2d_DescriptorExtractor_SIFT, regression )
{ {
CV_DescriptorExtractorTest<L2<float> > test( "descriptor-sift", 0.03f, CV_DescriptorExtractorTest<L2<float> > test( "descriptor-sift", 0.03f,
DescriptorExtractor::create("SIFT"), 8.06652f ); DescriptorExtractor::create("SIFT") );
test.safe_run(); test.safe_run();
} }
TEST( Features2d_DescriptorExtractor_SURF, regression ) TEST( Features2d_DescriptorExtractor_SURF, regression )
{ {
CV_DescriptorExtractorTest<L2<float> > test( "descriptor-surf", 0.05f, CV_DescriptorExtractorTest<L2<float> > test( "descriptor-surf", 0.05f,
DescriptorExtractor::create("SURF"), 0.147372f ); DescriptorExtractor::create("SURF") );
test.safe_run(); test.safe_run();
} }
TEST( Features2d_DescriptorExtractor_OpponentSIFT, regression ) TEST( Features2d_DescriptorExtractor_OpponentSIFT, regression )
{ {
CV_DescriptorExtractorTest<L2<float> > test( "descriptor-opponent-sift", 0.18f, CV_DescriptorExtractorTest<L2<float> > test( "descriptor-opponent-sift", 0.18f,
DescriptorExtractor::create("OpponentSIFT"), 8.06652f ); DescriptorExtractor::create("OpponentSIFT") );
test.safe_run(); test.safe_run();
} }
TEST( Features2d_DescriptorExtractor_OpponentSURF, regression ) TEST( Features2d_DescriptorExtractor_OpponentSURF, regression )
{ {
CV_DescriptorExtractorTest<L2<float> > test( "descriptor-opponent-surf", 0.3f, CV_DescriptorExtractorTest<L2<float> > test( "descriptor-opponent-surf", 0.3f,
DescriptorExtractor::create("OpponentSURF"), 0.147372f ); DescriptorExtractor::create("OpponentSURF") );
test.safe_run(); test.safe_run();
} }