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Boring changes - features2d.

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This commit is contained in:
Roman Donchenko 2013-08-13 17:30:14 +04:00
parent bd70a033fc
commit 1eacb485c5
11 changed files with 55 additions and 55 deletions
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6
modules/features2d/include/opencv2/features2d.hpp
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@ -646,7 +646,7 @@ public:
* gridRows Grid rows count.
* gridCols Grid column count.
*/
CV_WRAP GridAdaptedFeatureDetector( const Ptr<FeatureDetector>& detector=0,
CV_WRAP GridAdaptedFeatureDetector( const Ptr<FeatureDetector>& detector=Ptr<FeatureDetector>(),
int maxTotalKeypoints=1000,
int gridRows=4, int gridCols=4 );
@ -1143,8 +1143,8 @@ protected:
class CV_EXPORTS_W FlannBasedMatcher : public DescriptorMatcher
{
public:
CV_WRAP FlannBasedMatcher( const Ptr<flann::IndexParams>& indexParams=new flann::KDTreeIndexParams(),
const Ptr<flann::SearchParams>& searchParams=new flann::SearchParams() );
CV_WRAP FlannBasedMatcher( const Ptr<flann::IndexParams>& indexParams=makePtr<flann::KDTreeIndexParams>(),
const Ptr<flann::SearchParams>& searchParams=makePtr<flann::SearchParams>() );
virtual void add( const std::vector<Mat>& descriptors );
virtual void clear();

4
modules/features2d/src/brisk.cpp
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@ -2003,7 +2003,7 @@ BriskLayer::BriskLayer(const cv::Mat& img_in, float scale_in, float offset_in)
scale_ = scale_in;
offset_ = offset_in;
// create an agast detector
fast_9_16_ = new FastFeatureDetector(1, true, FastFeatureDetector::TYPE_9_16);
fast_9_16_ = makePtr<FastFeatureDetector>(1, true, FastFeatureDetector::TYPE_9_16);
makeOffsets(pixel_5_8_, (int)img_.step, 8);
makeOffsets(pixel_9_16_, (int)img_.step, 16);
}
@ -2025,7 +2025,7 @@ BriskLayer::BriskLayer(const BriskLayer& layer, int mode)
offset_ = 0.5f * scale_ - 0.5f;
}
scores_ = cv::Mat::zeros(img_.rows, img_.cols, CV_8U);
fast_9_16_ = new FastFeatureDetector(1, false, FastFeatureDetector::TYPE_9_16);
fast_9_16_ = makePtr<FastFeatureDetector>(1, false, FastFeatureDetector::TYPE_9_16);
makeOffsets(pixel_5_8_, (int)img_.step, 8);
makeOffsets(pixel_9_16_, (int)img_.step, 16);
}

6
modules/features2d/src/descriptors.cpp
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@ -99,7 +99,7 @@ Ptr<DescriptorExtractor> DescriptorExtractor::create(const String& descriptorExt
{
size_t pos = String("Opponent").size();
String type = descriptorExtractorType.substr(pos);
return new OpponentColorDescriptorExtractor(DescriptorExtractor::create(type));
return makePtr<OpponentColorDescriptorExtractor>(DescriptorExtractor::create(type));
}
return Algorithm::create<DescriptorExtractor>("Feature2D." + descriptorExtractorType);
@ -119,7 +119,7 @@ CV_WRAP void Feature2D::compute( const Mat& image, CV_OUT CV_IN_OUT std::vector<
OpponentColorDescriptorExtractor::OpponentColorDescriptorExtractor( const Ptr<DescriptorExtractor>& _descriptorExtractor ) :
descriptorExtractor(_descriptorExtractor)
{
CV_Assert( !descriptorExtractor.empty() );
CV_Assert( descriptorExtractor );
}
static void convertBGRImageToOpponentColorSpace( const Mat& bgrImage, std::vector<Mat>& opponentChannels )
@ -249,7 +249,7 @@ int OpponentColorDescriptorExtractor::descriptorType() const
bool OpponentColorDescriptorExtractor::empty() const
{
return descriptorExtractor.empty() || (DescriptorExtractor*)(descriptorExtractor)->empty();
return !descriptorExtractor || descriptorExtractor->empty();
}
}

10
modules/features2d/src/detectors.cpp
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@ -90,19 +90,19 @@ Ptr<FeatureDetector> FeatureDetector::create( const String& detectorType )
{
if( detectorType.find("Grid") == 0 )
{
return new GridAdaptedFeatureDetector(FeatureDetector::create(
return makePtr<GridAdaptedFeatureDetector>(FeatureDetector::create(
detectorType.substr(strlen("Grid"))));
}
if( detectorType.find("Pyramid") == 0 )
{
return new PyramidAdaptedFeatureDetector(FeatureDetector::create(
return makePtr<PyramidAdaptedFeatureDetector>(FeatureDetector::create(
detectorType.substr(strlen("Pyramid"))));
}
if( detectorType.find("Dynamic") == 0 )
{
return new DynamicAdaptedFeatureDetector(AdjusterAdapter::create(
return makePtr<DynamicAdaptedFeatureDetector>(AdjusterAdapter::create(
detectorType.substr(strlen("Dynamic"))));
}
@ -190,7 +190,7 @@ GridAdaptedFeatureDetector::GridAdaptedFeatureDetector( const Ptr<FeatureDetecto
bool GridAdaptedFeatureDetector::empty() const
{
return detector.empty() || (FeatureDetector*)detector->empty();
return !detector || detector->empty();
}
struct ResponseComparator
@ -295,7 +295,7 @@ PyramidAdaptedFeatureDetector::PyramidAdaptedFeatureDetector( const Ptr<FeatureD
bool PyramidAdaptedFeatureDetector::empty() const
{
return detector.empty() || (FeatureDetector*)detector->empty();
return !detector || detector->empty();
}
void PyramidAdaptedFeatureDetector::detectImpl( const Mat& image, std::vector<KeyPoint>& keypoints, const Mat& mask ) const

14
modules/features2d/src/dynamic.cpp
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@ -51,7 +51,7 @@ DynamicAdaptedFeatureDetector::DynamicAdaptedFeatureDetector(const Ptr<AdjusterA
bool DynamicAdaptedFeatureDetector::empty() const
{
return adjuster_.empty() || adjuster_->empty();
return !adjuster_ || adjuster_->empty();
}
void DynamicAdaptedFeatureDetector::detectImpl(const Mat& image, std::vector<KeyPoint>& keypoints, const Mat& mask) const
@ -124,7 +124,7 @@ bool FastAdjuster::good() const
Ptr<AdjusterAdapter> FastAdjuster::clone() const
{
Ptr<AdjusterAdapter> cloned_obj = new FastAdjuster( init_thresh_, nonmax_, min_thresh_, max_thresh_ );
Ptr<AdjusterAdapter> cloned_obj(new FastAdjuster( init_thresh_, nonmax_, min_thresh_, max_thresh_ ));
return cloned_obj;
}
@ -158,7 +158,7 @@ bool StarAdjuster::good() const
Ptr<AdjusterAdapter> StarAdjuster::clone() const
{
Ptr<AdjusterAdapter> cloned_obj = new StarAdjuster( init_thresh_, min_thresh_, max_thresh_ );
Ptr<AdjusterAdapter> cloned_obj(new StarAdjuster( init_thresh_, min_thresh_, max_thresh_ ));
return cloned_obj;
}
@ -195,7 +195,7 @@ bool SurfAdjuster::good() const
Ptr<AdjusterAdapter> SurfAdjuster::clone() const
{
Ptr<AdjusterAdapter> cloned_obj = new SurfAdjuster( init_thresh_, min_thresh_, max_thresh_ );
Ptr<AdjusterAdapter> cloned_obj(new SurfAdjuster( init_thresh_, min_thresh_, max_thresh_ ));
return cloned_obj;
}
@ -205,15 +205,15 @@ Ptr<AdjusterAdapter> AdjusterAdapter::create( const String& detectorType )
if( !detectorType.compare( "FAST" ) )
{
adapter = new FastAdjuster();
adapter = makePtr<FastAdjuster>();
}
else if( !detectorType.compare( "STAR" ) )
{
adapter = new StarAdjuster();
adapter = makePtr<StarAdjuster>();
}
else if( !detectorType.compare( "SURF" ) )
{
adapter = new SurfAdjuster();
adapter = makePtr<SurfAdjuster>();
}
return adapter;

4
modules/features2d/src/evaluation.cpp
View File

@ -461,7 +461,7 @@ void cv::evaluateFeatureDetector( const Mat& img1, const Mat& img2, const Mat& H
keypoints1 = _keypoints1 != 0 ? _keypoints1 : &buf1;
keypoints2 = _keypoints2 != 0 ? _keypoints2 : &buf2;
if( (keypoints1->empty() || keypoints2->empty()) && fdetector.empty() )
if( (keypoints1->empty() || keypoints2->empty()) && !fdetector )
CV_Error( Error::StsBadArg, "fdetector must not be empty when keypoints1 or keypoints2 is empty" );
if( keypoints1->empty() )
@ -575,7 +575,7 @@ void cv::evaluateGenericDescriptorMatcher( const Mat& img1, const Mat& img2, con
if( keypoints1.empty() )
CV_Error( Error::StsBadArg, "keypoints1 must not be empty" );
if( matches1to2->empty() && dmatcher.empty() )
if( matches1to2->empty() && !dmatcher )
CV_Error( Error::StsBadArg, "dmatch must not be empty when matches1to2 is empty" );
bool computeKeypoints2ByPrj = keypoints2.empty();

44
modules/features2d/src/matchers.cpp
View File

@ -326,7 +326,7 @@ BFMatcher::BFMatcher( int _normType, bool _crossCheck )
Ptr<DescriptorMatcher> BFMatcher::clone( bool emptyTrainData ) const
{
BFMatcher* matcher = new BFMatcher(normType, crossCheck);
Ptr<BFMatcher> matcher = makePtr<BFMatcher>(normType, crossCheck);
if( !emptyTrainData )
{
matcher->trainDescCollection.resize(trainDescCollection.size());
@ -458,31 +458,31 @@ void BFMatcher::radiusMatchImpl( const Mat& queryDescriptors, std::vector<std::v
*/
Ptr<DescriptorMatcher> DescriptorMatcher::create( const String& descriptorMatcherType )
{
DescriptorMatcher* dm = 0;
Ptr<DescriptorMatcher> dm;
if( !descriptorMatcherType.compare( "FlannBased" ) )
{
dm = new FlannBasedMatcher();
dm = makePtr<FlannBasedMatcher>();
}
else if( !descriptorMatcherType.compare( "BruteForce" ) ) // L2
{
dm = new BFMatcher(NORM_L2);
dm = makePtr<BFMatcher>(int(NORM_L2)); // anonymous enums can't be template parameters
}
else if( !descriptorMatcherType.compare( "BruteForce-SL2" ) ) // Squared L2
{
dm = new BFMatcher(NORM_L2SQR);
dm = makePtr<BFMatcher>(int(NORM_L2SQR));
}
else if( !descriptorMatcherType.compare( "BruteForce-L1" ) )
{
dm = new BFMatcher(NORM_L1);
dm = makePtr<BFMatcher>(int(NORM_L1));
}
else if( !descriptorMatcherType.compare("BruteForce-Hamming") ||
!descriptorMatcherType.compare("BruteForce-HammingLUT") )
{
dm = new BFMatcher(NORM_HAMMING);
dm = makePtr<BFMatcher>(int(NORM_HAMMING));
}
else if( !descriptorMatcherType.compare("BruteForce-Hamming(2)") )
{
dm = new BFMatcher(NORM_HAMMING2);
dm = makePtr<BFMatcher>(int(NORM_HAMMING2));
}
else
CV_Error( Error::StsBadArg, "Unknown matcher name" );
@ -497,8 +497,8 @@ Ptr<DescriptorMatcher> DescriptorMatcher::create( const String& descriptorMatche
FlannBasedMatcher::FlannBasedMatcher( const Ptr<flann::IndexParams>& _indexParams, const Ptr<flann::SearchParams>& _searchParams )
: indexParams(_indexParams), searchParams(_searchParams), addedDescCount(0)
{
CV_Assert( !_indexParams.empty() );
CV_Assert( !_searchParams.empty() );
CV_Assert( _indexParams );
CV_Assert( _searchParams );
}
void FlannBasedMatcher::add( const std::vector<Mat>& descriptors )
@ -522,17 +522,17 @@ void FlannBasedMatcher::clear()
void FlannBasedMatcher::train()
{
if( flannIndex.empty() || mergedDescriptors.size() < addedDescCount )
if( !flannIndex || mergedDescriptors.size() < addedDescCount )
{
mergedDescriptors.set( trainDescCollection );
flannIndex = new flann::Index( mergedDescriptors.getDescriptors(), *indexParams );
flannIndex = makePtr<flann::Index>( mergedDescriptors.getDescriptors(), *indexParams );
}
}
void FlannBasedMatcher::read( const FileNode& fn)
{
if (indexParams.empty())
indexParams = new flann::IndexParams();
if (!indexParams)
indexParams = makePtr<flann::IndexParams>();
FileNode ip = fn["indexParams"];
CV_Assert(ip.type() == FileNode::SEQ);
@ -570,8 +570,8 @@ void FlannBasedMatcher::read( const FileNode& fn)
};
}
if (searchParams.empty())
searchParams = new flann::SearchParams();
if (!searchParams)
searchParams = makePtr<flann::SearchParams>();
FileNode sp = fn["searchParams"];
CV_Assert(sp.type() == FileNode::SEQ);
@ -725,7 +725,7 @@ bool FlannBasedMatcher::isMaskSupported() const
Ptr<DescriptorMatcher> FlannBasedMatcher::clone( bool emptyTrainData ) const
{
FlannBasedMatcher* matcher = new FlannBasedMatcher(indexParams, searchParams);
Ptr<FlannBasedMatcher> matcher = makePtr<FlannBasedMatcher>(indexParams, searchParams);
if( !emptyTrainData )
{
CV_Error( Error::StsNotImplemented, "deep clone functionality is not implemented, because "
@ -1066,7 +1066,7 @@ Ptr<GenericDescriptorMatcher> GenericDescriptorMatcher::create( const String& ge
Ptr<GenericDescriptorMatcher> descriptorMatcher =
Algorithm::create<GenericDescriptorMatcher>("DescriptorMatcher." + genericDescritptorMatcherType);
if( !paramsFilename.empty() && !descriptorMatcher.empty() )
if( !paramsFilename.empty() && descriptorMatcher )
{
FileStorage fs = FileStorage( paramsFilename, FileStorage::READ );
if( fs.isOpened() )
@ -1086,7 +1086,7 @@ VectorDescriptorMatcher::VectorDescriptorMatcher( const Ptr<DescriptorExtractor>
const Ptr<DescriptorMatcher>& _matcher )
: extractor( _extractor ), matcher( _matcher )
{
CV_Assert( !extractor.empty() && !matcher.empty() );
CV_Assert( extractor && matcher );
}
VectorDescriptorMatcher::~VectorDescriptorMatcher()
@ -1152,14 +1152,14 @@ void VectorDescriptorMatcher::write (FileStorage& fs) const
bool VectorDescriptorMatcher::empty() const
{
return extractor.empty() || extractor->empty() ||
matcher.empty() || matcher->empty();
return !extractor || extractor->empty() ||
!matcher || matcher->empty();
}
Ptr<GenericDescriptorMatcher> VectorDescriptorMatcher::clone( bool emptyTrainData ) const
{
// TODO clone extractor
return new VectorDescriptorMatcher( extractor, matcher->clone(emptyTrainData) );
return makePtr<VectorDescriptorMatcher>( extractor, matcher->clone(emptyTrainData) );
}
}

6
modules/features2d/test/test_descriptors_regression.cpp
View File

@ -141,7 +141,7 @@ protected:
void emptyDataTest()
{
assert( !dextractor.empty() );
assert( dextractor );
// One image.
Mat image;
@ -186,7 +186,7 @@ protected:
void regressionTest()
{
assert( !dextractor.empty() );
assert( dextractor );
// Read the test image.
string imgFilename = string(ts->get_data_path()) + FEATURES2D_DIR + "/" + IMAGE_FILENAME;
@ -267,7 +267,7 @@ protected:
void run(int)
{
createDescriptorExtractor();
if( dextractor.empty() )
if( !dextractor )
{
ts->printf(cvtest::TS::LOG, "Descriptor extractor is empty.\n");
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_TEST_DATA );

2
modules/features2d/test/test_detectors_regression.cpp
View File

@ -230,7 +230,7 @@ void CV_FeatureDetectorTest::regressionTest()
void CV_FeatureDetectorTest::run( int /*start_from*/ )
{
if( fdetector.empty() )
if( !fdetector )
{
ts->printf( cvtest::TS::LOG, "Feature detector is empty.\n" );
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_TEST_DATA );

2
modules/features2d/test/test_keypoints.cpp
View File

@ -62,7 +62,7 @@ protected:
virtual void run(int)
{
cv::initModule_features2d();
CV_Assert(!detector.empty());
CV_Assert(detector);
string imgFilename = string(ts->get_data_path()) + FEATURES2D_DIR + "/" + IMAGE_FILENAME;
// Read the test image.

12
modules/features2d/test/test_rotation_and_scale_invariance.cpp
View File

@ -196,7 +196,7 @@ public:
minKeyPointMatchesRatio(_minKeyPointMatchesRatio),
minAngleInliersRatio(_minAngleInliersRatio)
{
CV_Assert(!featureDetector.empty());
CV_Assert(featureDetector);
}
protected:
@ -307,8 +307,8 @@ public:
normType(_normType),
minDescInliersRatio(_minDescInliersRatio)
{
CV_Assert(!featureDetector.empty());
CV_Assert(!descriptorExtractor.empty());
CV_Assert(featureDetector);
CV_Assert(descriptorExtractor);
}
protected:
@ -392,7 +392,7 @@ public:
minKeyPointMatchesRatio(_minKeyPointMatchesRatio),
minScaleInliersRatio(_minScaleInliersRatio)
{
CV_Assert(!featureDetector.empty());
CV_Assert(featureDetector);
}
protected:
@ -510,8 +510,8 @@ public:
normType(_normType),
minDescInliersRatio(_minDescInliersRatio)
{
CV_Assert(!featureDetector.empty());
CV_Assert(!descriptorExtractor.empty());
CV_Assert(featureDetector);
CV_Assert(descriptorExtractor);
}
protected: