Commit 9f1c10e1 authored by Alexandre Benoit's avatar Alexandre Benoit

Merge branch 'master' of git://code.opencv.org/opencv

parents 52b4b5b0 01410678
......@@ -267,6 +267,97 @@ public:
static Ptr<Feature2D> create( const string& name );
};
/*!
BRISK implementation
*/
class CV_EXPORTS_W BRISK : public Feature2D
{
public:
CV_WRAP explicit BRISK(int thresh=30, int octaves=3, float patternScale=1.0f);
virtual ~BRISK();
// returns the descriptor size in bytes
int descriptorSize() const;
// returns the descriptor type
int descriptorType() const;
// Compute the BRISK features on an image
void operator()(InputArray image, InputArray mask, vector<KeyPoint>& keypoints) const;
// Compute the BRISK features and descriptors on an image
void operator()( InputArray image, InputArray mask, vector<KeyPoint>& keypoints,
OutputArray descriptors, bool useProvidedKeypoints=false ) const;
AlgorithmInfo* info() const;
// custom setup
CV_WRAP explicit BRISK(std::vector<float> &radiusList, std::vector<int> &numberList,
float dMax=5.85f, float dMin=8.2f, std::vector<int> indexChange=std::vector<int>());
// call this to generate the kernel:
// circle of radius r (pixels), with n points;
// short pairings with dMax, long pairings with dMin
CV_WRAP void generateKernel(std::vector<float> &radiusList,
std::vector<int> &numberList, float dMax=5.85f, float dMin=8.2f,
std::vector<int> indexChange=std::vector<int>());
protected:
void computeImpl( const Mat& image, vector<KeyPoint>& keypoints, Mat& descriptors ) const;
void detectImpl( const Mat& image, vector<KeyPoint>& keypoints, const Mat& mask=Mat() ) const;
void computeKeypointsNoOrientation(InputArray image, InputArray mask, vector<KeyPoint>& keypoints) const;
void computeDescriptorsAndOrOrientation(InputArray image, InputArray mask, vector<KeyPoint>& keypoints,
OutputArray descriptors, bool doDescriptors, bool doOrientation,
bool useProvidedKeypoints) const;
// Feature parameters
CV_PROP_RW int threshold;
CV_PROP_RW int octaves;
// some helper structures for the Brisk pattern representation
struct BriskPatternPoint{
float x; // x coordinate relative to center
float y; // x coordinate relative to center
float sigma; // Gaussian smoothing sigma
};
struct BriskShortPair{
unsigned int i; // index of the first pattern point
unsigned int j; // index of other pattern point
};
struct BriskLongPair{
unsigned int i; // index of the first pattern point
unsigned int j; // index of other pattern point
int weighted_dx; // 1024.0/dx
int weighted_dy; // 1024.0/dy
};
inline int smoothedIntensity(const cv::Mat& image,
const cv::Mat& integral,const float key_x,
const float key_y, const unsigned int scale,
const unsigned int rot, const unsigned int point) const;
// pattern properties
BriskPatternPoint* patternPoints_; //[i][rotation][scale]
unsigned int points_; // total number of collocation points
float* scaleList_; // lists the scaling per scale index [scale]
unsigned int* sizeList_; // lists the total pattern size per scale index [scale]
static const unsigned int scales_; // scales discretization
static const float scalerange_; // span of sizes 40->4 Octaves - else, this needs to be adjusted...
static const unsigned int n_rot_; // discretization of the rotation look-up
// pairs
int strings_; // number of uchars the descriptor consists of
float dMax_; // short pair maximum distance
float dMin_; // long pair maximum distance
BriskShortPair* shortPairs_; // d<_dMax
BriskLongPair* longPairs_; // d>_dMin
unsigned int noShortPairs_; // number of shortParis
unsigned int noLongPairs_; // number of longParis
// general
static const float basicSize_;
};
/*!
ORB implementation.
......
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/* This is FAST corner detector, contributed to OpenCV by the author, Edward Rosten.
Below is the original copyright and the references */
/*
Copyright (c) 2006, 2008 Edward Rosten
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions
are met:
*Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
*Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.
*Neither the name of the University of Cambridge nor the names of
its contributors may be used to endorse or promote products derived
from this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
/*
The references are:
* Machine learning for high-speed corner detection,
E. Rosten and T. Drummond, ECCV 2006
* Faster and better: A machine learning approach to corner detection
E. Rosten, R. Porter and T. Drummond, PAMI, 2009
*/
#ifndef __OPENCV_FEATURES_2D_FAST_HPP__
#define __OPENCV_FEATURES_2D_FAST_HPP__
#ifdef __cplusplus
#include "precomp.hpp"
namespace cv
{
void makeOffsets(int pixel[25], int row_stride, int patternSize);
//static void testCorner(const uchar* ptr, const int pixel[], int K, int N, int threshold);
template<int patternSize>
int cornerScore(const uchar* ptr, const int pixel[], int threshold);
}
#endif
#endif
......@@ -51,6 +51,12 @@ using namespace cv;
Otherwise, linker may throw away some seemingly unused stuff.
*/
CV_INIT_ALGORITHM(BRISK, "Feature2D.BRISK",
obj.info()->addParam(obj, "thres", obj.threshold);
obj.info()->addParam(obj, "octaves", obj.octaves));
///////////////////////////////////////////////////////////////////////////////////////////////////////////
CV_INIT_ALGORITHM(BriefDescriptorExtractor, "Feature2D.BRIEF",
obj.info()->addParam(obj, "bytes", obj.bytes_));
......@@ -154,6 +160,7 @@ bool cv::initModule_features2d(void)
{
bool all = true;
all &= !BriefDescriptorExtractor_info_auto.name().empty();
all &= !BRISK_info_auto.name().empty();
all &= !FastFeatureDetector_info_auto.name().empty();
all &= !StarDetector_info_auto.name().empty();
all &= !MSER_info_auto.name().empty();
......
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "test_precomp.hpp"
using namespace cv;
class CV_BRISKTest : public cvtest::BaseTest
{
public:
CV_BRISKTest();
~CV_BRISKTest();
protected:
void run(int);
};
CV_BRISKTest::CV_BRISKTest() {}
CV_BRISKTest::~CV_BRISKTest() {}
void CV_BRISKTest::run( int )
{
Mat image1 = imread(string(ts->get_data_path()) + "inpaint/orig.jpg");
Mat image2 = imread(string(ts->get_data_path()) + "cameracalibration/chess9.jpg");
if (image1.empty() || image2.empty())
{
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_TEST_DATA );
return;
}
Mat gray1, gray2;
cvtColor(image1, gray1, CV_BGR2GRAY);
cvtColor(image2, gray2, CV_BGR2GRAY);
Ptr<FeatureDetector> detector = Algorithm::create<FeatureDetector>("Feature2D.BRISK");
vector<KeyPoint> keypoints1;
vector<KeyPoint> keypoints2;
detector->detect(image1, keypoints1);
detector->detect(image2, keypoints2);
for(size_t i = 0; i < keypoints1.size(); ++i)
{
const KeyPoint& kp = keypoints1[i];
ASSERT_NE(kp.angle, -1);
}
for(size_t i = 0; i < keypoints2.size(); ++i)
{
const KeyPoint& kp = keypoints2[i];
ASSERT_NE(kp.angle, -1);
}
}
TEST(Features2d_BRISK, regression) { CV_BRISKTest test; test.safe_run(); }
......@@ -301,6 +301,13 @@ private:
* Tests registrations *
\****************************************************************************************/
TEST( Features2d_DescriptorExtractor_BRISK, regression )
{
CV_DescriptorExtractorTest<Hamming> test( "descriptor-brisk", (CV_DescriptorExtractorTest<Hamming>::DistanceType)2.f,
DescriptorExtractor::create("BRISK") );
test.safe_run();
}
TEST( Features2d_DescriptorExtractor_ORB, regression )
{
// TODO adjust the parameters below
......
......@@ -247,6 +247,12 @@ void CV_FeatureDetectorTest::run( int /*start_from*/ )
* Tests registrations *
\****************************************************************************************/
TEST( Features2d_Detector_BRISK, regression )
{
CV_FeatureDetectorTest test( "detector-brisk", FeatureDetector::create("BRISK") );
test.safe_run();
}
TEST( Features2d_Detector_FAST, regression )
{
CV_FeatureDetectorTest test( "detector-fast", FeatureDetector::create("FAST") );
......
......@@ -119,6 +119,12 @@ protected:
// Registration of tests
TEST(Features2d_Detector_Keypoints_BRISK, validation)
{
CV_FeatureDetectorKeypointsTest test(Algorithm::create<FeatureDetector>("Feature2D.BRISK"));
test.safe_run();
}
TEST(Features2d_Detector_Keypoints_FAST, validation)
{
CV_FeatureDetectorKeypointsTest test(Algorithm::create<FeatureDetector>("Feature2D.FAST"));
......
......@@ -592,6 +592,15 @@ protected:
/*
* Detector's rotation invariance check
*/
TEST(Features2d_RotationInvariance_Detector_BRISK, regression)
{
DetectorRotationInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.BRISK"),
0.32f,
0.81f);
test.safe_run();
}
TEST(Features2d_RotationInvariance_Detector_ORB, regression)
{
DetectorRotationInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.ORB"),
......@@ -603,6 +612,16 @@ TEST(Features2d_RotationInvariance_Detector_ORB, regression)
/*
* Descriptors's rotation invariance check
*/
TEST(Features2d_RotationInvariance_Descriptor_BRISK, regression)
{
DescriptorRotationInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.BRISK"),
Algorithm::create<DescriptorExtractor>("Feature2D.BRISK"),
NORM_HAMMING,
0.99f);
test.safe_run();
}
TEST(Features2d_RotationInvariance_Descriptor_ORB, regression)
{
DescriptorRotationInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.ORB"),
......@@ -625,6 +644,14 @@ TEST(Features2d_RotationInvariance_Descriptor_ORB, regression)
* Detector's scale invariance check
*/
TEST(Features2d_ScaleInvariance_Detector_BRISK, regression)
{
DetectorScaleInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.BRISK"),
0.08f,
0.54f);
test.safe_run();
}
//TEST(Features2d_ScaleInvariance_Detector_ORB, regression)
//{
// DetectorScaleInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.ORB"),
......@@ -637,6 +664,15 @@ TEST(Features2d_RotationInvariance_Descriptor_ORB, regression)
* Descriptor's scale invariance check
*/
//TEST(Features2d_ScaleInvariance_Descriptor_BRISK, regression)
//{
// DescriptorScaleInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.BRISK"),
// Algorithm::create<DescriptorExtractor>("Feature2D.BRISK"),
// NORM_HAMMING,
// 0.99f);
// test.safe_run();
//}
//TEST(Features2d_ScaleInvariance_Descriptor_ORB, regression)
//{
// DescriptorScaleInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.ORB"),
......
......@@ -1314,7 +1314,7 @@ public:
ssize.width *= cn;
int dy, dx, k = 0;
VecOp vop(scale_x, scale_y, src.channels(), src.step/*, area_ofs*/);
VecOp vop(scale_x, scale_y, src.channels(), (int)src.step/*, area_ofs*/);
for( dy = range.start; dy < range.end; dy++ )
{
......
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