Commit 1a617614 authored by cbalint13's avatar cbalint13

Merge branch 'master' of https://github.com/Itseez/opencv_contrib into daisy

parents 1a9eee39 7b6fe5cd
...@@ -351,7 +351,7 @@ void RetinaOCLImpl::setupIPLMagnoChannel(const bool normaliseOutput, const float ...@@ -351,7 +351,7 @@ void RetinaOCLImpl::setupIPLMagnoChannel(const bool normaliseOutput, const float
_retinaParameters.IplMagno.localAdaptintegration_k = localAdaptintegration_k; _retinaParameters.IplMagno.localAdaptintegration_k = localAdaptintegration_k;
} }
void RetinaOCLImpl::run(const InputArray input) void RetinaOCLImpl::run(InputArray input)
{ {
oclMat &inputMatToConvert = getOclMatRef(input); oclMat &inputMatToConvert = getOclMatRef(input);
bool colorMode = convertToColorPlanes(inputMatToConvert, _inputBuffer); bool colorMode = convertToColorPlanes(inputMatToConvert, _inputBuffer);
......
...@@ -78,7 +78,7 @@ class CV_EXPORTS Saliency : public virtual Algorithm ...@@ -78,7 +78,7 @@ class CV_EXPORTS Saliency : public virtual Algorithm
* \param saliencyMap The computed saliency map. * \param saliencyMap The computed saliency map.
* \return true if the saliency map is computed, false otherwise * \return true if the saliency map is computed, false otherwise
*/ */
bool computeSaliency( const InputArray image, OutputArray saliencyMap ); bool computeSaliency( InputArray image, OutputArray saliencyMap );
/** /**
* \brief Get the name of the specific saliency type * \brief Get the name of the specific saliency type
...@@ -88,7 +88,7 @@ class CV_EXPORTS Saliency : public virtual Algorithm ...@@ -88,7 +88,7 @@ class CV_EXPORTS Saliency : public virtual Algorithm
protected: protected:
virtual bool computeSaliencyImpl( const InputArray image, OutputArray saliencyMap ) = 0; virtual bool computeSaliencyImpl( InputArray image, OutputArray saliencyMap ) = 0;
String className; String className;
}; };
...@@ -114,7 +114,7 @@ class CV_EXPORTS StaticSaliency : public virtual Saliency ...@@ -114,7 +114,7 @@ class CV_EXPORTS StaticSaliency : public virtual Saliency
*/ */
bool computeBinaryMap( const Mat& saliencyMap, Mat& binaryMap ); bool computeBinaryMap( const Mat& saliencyMap, Mat& binaryMap );
protected: protected:
virtual bool computeSaliencyImpl( const InputArray image, OutputArray saliencyMap )=0; virtual bool computeSaliencyImpl( InputArray image, OutputArray saliencyMap )=0;
}; };
...@@ -123,7 +123,7 @@ class CV_EXPORTS MotionSaliency : public virtual Saliency ...@@ -123,7 +123,7 @@ class CV_EXPORTS MotionSaliency : public virtual Saliency
{ {
protected: protected:
virtual bool computeSaliencyImpl( const InputArray image, OutputArray saliencyMap )=0; virtual bool computeSaliencyImpl( InputArray image, OutputArray saliencyMap )=0;
}; };
...@@ -132,7 +132,7 @@ class CV_EXPORTS Objectness : public virtual Saliency ...@@ -132,7 +132,7 @@ class CV_EXPORTS Objectness : public virtual Saliency
{ {
protected: protected:
virtual bool computeSaliencyImpl( const InputArray image, OutputArray saliencyMap )=0; virtual bool computeSaliencyImpl( InputArray image, OutputArray saliencyMap )=0;
}; };
......
...@@ -94,7 +94,7 @@ public: ...@@ -94,7 +94,7 @@ public:
} }
protected: protected:
bool computeSaliencyImpl( const InputArray image, OutputArray saliencyMap ); bool computeSaliencyImpl( InputArray image, OutputArray saliencyMap );
int resImWidth; int resImWidth;
int resImHeight; int resImHeight;
...@@ -154,7 +154,7 @@ protected: ...@@ -154,7 +154,7 @@ protected:
The saliency map is given by a single *Mat* (one for each frame of an hypothetical video The saliency map is given by a single *Mat* (one for each frame of an hypothetical video
stream). stream).
*/ */
bool computeSaliencyImpl( const InputArray image, OutputArray saliencyMap ); bool computeSaliencyImpl( InputArray image, OutputArray saliencyMap );
private: private:
...@@ -268,7 +268,7 @@ protected: ...@@ -268,7 +268,7 @@ protected:
specialized algorithm, the objectnessBoundingBox is a *vector\<Vec4i\>*. Each bounding box is specialized algorithm, the objectnessBoundingBox is a *vector\<Vec4i\>*. Each bounding box is
represented by a *Vec4i* for (minX, minY, maxX, maxY). represented by a *Vec4i* for (minX, minY, maxX, maxY).
*/ */
bool computeSaliencyImpl( const InputArray image, OutputArray objectnessBoundingBox ); bool computeSaliencyImpl( InputArray image, OutputArray objectnessBoundingBox );
private: private:
......
...@@ -460,7 +460,7 @@ void ObjectnessBING::write() const ...@@ -460,7 +460,7 @@ void ObjectnessBING::write() const
} }
bool ObjectnessBING::computeSaliencyImpl( const InputArray image, OutputArray objectnessBoundingBox ) bool ObjectnessBING::computeSaliencyImpl( InputArray image, OutputArray objectnessBoundingBox )
{ {
ValStructVec<float, Vec4i> finalBoxes; ValStructVec<float, Vec4i> finalBoxes;
getObjBndBoxesForSingleImage( image.getMat(), finalBoxes, 250 ); getObjBndBoxesForSingleImage( image.getMat(), finalBoxes, 250 );
......
...@@ -501,7 +501,7 @@ bool MotionSaliencyBinWangApr2014::templateReplacement( const Mat& finalBFMask, ...@@ -501,7 +501,7 @@ bool MotionSaliencyBinWangApr2014::templateReplacement( const Mat& finalBFMask,
return true; return true;
} }
bool MotionSaliencyBinWangApr2014::computeSaliencyImpl( const InputArray image, OutputArray saliencyMap ) bool MotionSaliencyBinWangApr2014::computeSaliencyImpl( InputArray image, OutputArray saliencyMap )
{ {
Mat highResBFMask; Mat highResBFMask;
Mat lowResBFMask; Mat lowResBFMask;
......
...@@ -62,7 +62,7 @@ Ptr<Saliency> Saliency::create( const String& saliencyType ) ...@@ -62,7 +62,7 @@ Ptr<Saliency> Saliency::create( const String& saliencyType )
return Ptr<Saliency>(); return Ptr<Saliency>();
} }
bool Saliency::computeSaliency( const InputArray image, OutputArray saliencyMap ) bool Saliency::computeSaliency( InputArray image, OutputArray saliencyMap )
{ {
if( image.empty() ) if( image.empty() )
return false; return false;
......
...@@ -73,7 +73,7 @@ void StaticSaliencySpectralResidual::write( cv::FileStorage& /*fs*/) const ...@@ -73,7 +73,7 @@ void StaticSaliencySpectralResidual::write( cv::FileStorage& /*fs*/) const
//params.write( fs ); //params.write( fs );
} }
bool StaticSaliencySpectralResidual::computeSaliencyImpl( const InputArray image, OutputArray saliencyMap ) bool StaticSaliencySpectralResidual::computeSaliencyImpl( InputArray image, OutputArray saliencyMap )
{ {
Mat grayTemp, grayDown; Mat grayTemp, grayDown;
std::vector<Mat> mv; std::vector<Mat> mv;
......
...@@ -76,7 +76,7 @@ They are competitive alternatives to existing keypoints in particular for embedd ...@@ -76,7 +76,7 @@ They are competitive alternatives to existing keypoints in particular for embedd
- An example on how to use the FREAK descriptor can be found at - An example on how to use the FREAK descriptor can be found at
opencv_source_code/samples/cpp/freak_demo.cpp opencv_source_code/samples/cpp/freak_demo.cpp
*/ */
class CV_EXPORTS FREAK : public Feature2D class CV_EXPORTS_W FREAK : public Feature2D
{ {
public: public:
...@@ -92,7 +92,7 @@ public: ...@@ -92,7 +92,7 @@ public:
@param nOctaves Number of octaves covered by the detected keypoints. @param nOctaves Number of octaves covered by the detected keypoints.
@param selectedPairs (Optional) user defined selected pairs indexes, @param selectedPairs (Optional) user defined selected pairs indexes,
*/ */
static Ptr<FREAK> create(bool orientationNormalized = true, CV_WRAP static Ptr<FREAK> create(bool orientationNormalized = true,
bool scaleNormalized = true, bool scaleNormalized = true,
float patternScale = 22.0f, float patternScale = 22.0f,
int nOctaves = 4, int nOctaves = 4,
...@@ -102,11 +102,11 @@ public: ...@@ -102,11 +102,11 @@ public:
/** @brief The class implements the keypoint detector introduced by @cite Agrawal08, synonym of StarDetector. : /** @brief The class implements the keypoint detector introduced by @cite Agrawal08, synonym of StarDetector. :
*/ */
class CV_EXPORTS StarDetector : public FeatureDetector class CV_EXPORTS_W StarDetector : public Feature2D
{ {
public: public:
//! the full constructor //! the full constructor
static Ptr<StarDetector> create(int maxSize=45, int responseThreshold=30, CV_WRAP static Ptr<StarDetector> create(int maxSize=45, int responseThreshold=30,
int lineThresholdProjected=10, int lineThresholdProjected=10,
int lineThresholdBinarized=8, int lineThresholdBinarized=8,
int suppressNonmaxSize=5); int suppressNonmaxSize=5);
...@@ -123,10 +123,10 @@ public: ...@@ -123,10 +123,10 @@ public:
opencv_source_code/samples/cpp/brief_match_test.cpp opencv_source_code/samples/cpp/brief_match_test.cpp
*/ */
class CV_EXPORTS BriefDescriptorExtractor : public DescriptorExtractor class CV_EXPORTS_W BriefDescriptorExtractor : public Feature2D
{ {
public: public:
static Ptr<BriefDescriptorExtractor> create( int bytes = 32 ); CV_WRAP static Ptr<BriefDescriptorExtractor> create( int bytes = 32 );
}; };
/** @brief Class implementing the locally uniform comparison image descriptor, described in @cite LUCID /** @brief Class implementing the locally uniform comparison image descriptor, described in @cite LUCID
...@@ -134,14 +134,42 @@ public: ...@@ -134,14 +134,42 @@ public:
An image descriptor that can be computed very fast, while being An image descriptor that can be computed very fast, while being
about as robust as, for example, SURF or BRIEF. about as robust as, for example, SURF or BRIEF.
*/ */
class CV_EXPORTS LUCID : public DescriptorExtractor class CV_EXPORTS_W LUCID : public Feature2D
{ {
public: public:
/** /**
* @param lucid_kernel kernel for descriptor construction, where 1=3x3, 2=5x5, 3=7x7 and so forth * @param lucid_kernel kernel for descriptor construction, where 1=3x3, 2=5x5, 3=7x7 and so forth
* @param blur_kernel kernel for blurring image prior to descriptor construction, where 1=3x3, 2=5x5, 3=7x7 and so forth * @param blur_kernel kernel for blurring image prior to descriptor construction, where 1=3x3, 2=5x5, 3=7x7 and so forth
*/ */
static Ptr<LUCID> create(const int lucid_kernel, const int blur_kernel); CV_WRAP static Ptr<LUCID> create(const int lucid_kernel, const int blur_kernel);
};
/*
* LATCH Descriptor
*/
/** latch Class for computing the LATCH descriptor.
If you find this code useful, please add a reference to the following paper in your work:
Gil Levi and Tal Hassner, "LATCH: Learned Arrangements of Three Patch Codes", arXiv preprint arXiv:1501.03719, 15 Jan. 2015
LATCH is a binary descriptor based on learned comparisons of triplets of image patches.
* bytes is the size of the descriptor - can be 64, 32, 16, 8, 4, 2 or 1
* rotationInvariance - whether or not the descriptor should compansate for orientation changes.
* half_ssd_size - the size of half of the mini-patches size. For example, if we would like to compare triplets of patches of size 7x7x
then the half_ssd_size should be (7-1)/2 = 3.
Note: the descriptor can be coupled with any keypoint extractor. The only demand is that if you use set rotationInvariance = True then
you will have to use an extractor which estimates the patch orientation (in degrees). Examples for such extractors are ORB and SIFT.
Note: a complete example can be found under /samples/cpp/tutorial_code/xfeatures2D/latch_match.cpp
*/
class CV_EXPORTS LATCH : public DescriptorExtractor
{
public:
static Ptr<LATCH> create(int bytes = 32, bool rotationInvariance = true, int half_ssd_size=3);
}; };
/** @brief Class implementing DAISY descriptor, described in @cite Tola10 /** @brief Class implementing DAISY descriptor, described in @cite Tola10
......
#include "perf_precomp.hpp"
using namespace std;
using namespace cv;
using namespace cv::xfeatures2d;
using namespace perf;
using std::tr1::make_tuple;
using std::tr1::get;
typedef perf::TestBaseWithParam<std::string> latch;
#define LATCH_IMAGES \
"cv/detectors_descriptors_evaluation/images_datasets/leuven/img1.png",\
"stitching/a3.png"
PERF_TEST_P(latch, extract, testing::Values(LATCH_IMAGES))
{
string filename = getDataPath(GetParam());
Mat frame = imread(filename, IMREAD_GRAYSCALE);
ASSERT_FALSE(frame.empty()) << "Unable to load source image " << filename;
Mat mask;
declare.in(frame).time(90);
Ptr<SURF> detector = SURF::create();
vector<KeyPoint> points;
detector->detect(frame, points, mask);
Ptr<LATCH> descriptor = LATCH::create();
vector<uchar> descriptors;
TEST_CYCLE() descriptor->compute(frame, points, descriptors);
SANITY_CHECK(descriptors, 1e-4);
}
/*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) 2009-2010, 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.
//
// If you find this code useful, please add a reference to the following paper in your work:
// Gil Levi and Tal Hassner, "LATCH: Learned Arrangements of Three Patch Codes", arXiv preprint arXiv:1501.03719, 15 Jan. 2015
//M*/
#include "precomp.hpp"
#include <algorithm>
#include <vector>
#include <iostream>
#include <iomanip>
namespace cv
{
namespace xfeatures2d
{
/*
* LATCH Descriptor
*/
class LATCHDescriptorExtractorImpl : public LATCH
{
public:
enum { PATCH_SIZE = 48 };
LATCHDescriptorExtractorImpl(int bytes = 32, bool rotationInvariance = true, int half_ssd_size = 3);
virtual void read( const FileNode& );
virtual void write( FileStorage& ) const;
virtual int descriptorSize() const;
virtual int descriptorType() const;
virtual int defaultNorm() const;
virtual void compute(InputArray image, std::vector<KeyPoint>& keypoints, OutputArray descriptors);
protected:
typedef void(*PixelTestFn)(const Mat& input_image, const std::vector<KeyPoint>& keypoints, OutputArray, const std::vector<int> &points, bool rotationInvariance, int half_ssd_size);
void setSamplingPoints();
int bytes_;
PixelTestFn test_fn_;
bool rotationInvariance_;
int half_ssd_size_;
std::vector<int> sampling_points_ ;
};
Ptr<LATCH> LATCH::create(int bytes, bool rotationInvariance, int half_ssd_size)
{
return makePtr<LATCHDescriptorExtractorImpl>(bytes, rotationInvariance, half_ssd_size);
}
void CalcuateSums(int count, const std::vector<int> &points, bool rotationInvariance, const Mat &grayImage, const KeyPoint &pt, int &suma, int &sumc, float cos_theta, float sin_theta, int half_ssd_size);
static void pixelTests1(const Mat& grayImage, const std::vector<KeyPoint>& keypoints, OutputArray _descriptors, const std::vector<int> &points, bool rotationInvariance, int half_ssd_size)
{
Mat descriptors = _descriptors.getMat();
for (int i = 0; i < (int)keypoints.size(); ++i)
{
uchar* desc = descriptors.ptr(i);
const KeyPoint& pt = keypoints[i];
int count = 0;
//handling keypoint orientation
float angle = pt.angle;
angle *= (float)(CV_PI / 180.f);
float cos_theta = cos(angle);
float sin_theta = sin(angle);
for (int ix = 0; ix < 1; ix++){
desc[ix] = 0;
for (int j = 7; j >= 0; j--){
int suma = 0;
int sumc = 0;
CalcuateSums(count, points, rotationInvariance, grayImage, pt, suma, sumc, cos_theta, sin_theta, half_ssd_size);
desc[ix] += (uchar)((suma < sumc) << j);
count += 6;
}
}
}
}
static void pixelTests2(const Mat& grayImage, const std::vector<KeyPoint>& keypoints, OutputArray _descriptors, const std::vector<int> &points, bool rotationInvariance, int half_ssd_size)
{
Mat descriptors = _descriptors.getMat();
for (int i = 0; i < (int)keypoints.size(); ++i)
{
uchar* desc = descriptors.ptr(i);
const KeyPoint& pt = keypoints[i];
int count = 0;
//handling keypoint orientation
float angle = pt.angle;
angle *= (float)(CV_PI / 180.f);
float cos_theta = cos(angle);
float sin_theta = sin(angle);
for (int ix = 0; ix < 2; ix++){
desc[ix] = 0;
for (int j = 7; j >= 0; j--){
int suma = 0;
int sumc = 0;
CalcuateSums(count, points, rotationInvariance, grayImage, pt, suma, sumc, cos_theta, sin_theta, half_ssd_size);
desc[ix] += (uchar)((suma < sumc) << j);
count += 6;
}
}
}
}
static void pixelTests4(const Mat& grayImage, const std::vector<KeyPoint>& keypoints, OutputArray _descriptors, const std::vector<int> &points, bool rotationInvariance, int half_ssd_size)
{
Mat descriptors = _descriptors.getMat();
for (int i = 0; i < (int)keypoints.size(); ++i)
{
uchar* desc = descriptors.ptr(i);
const KeyPoint& pt = keypoints[i];
int count = 0;
//handling keypoint orientation
float angle = pt.angle;
angle *= (float)(CV_PI / 180.f);
float cos_theta = cos(angle);
float sin_theta = sin(angle);
for (int ix = 0; ix < 4; ix++){
desc[ix] = 0;
for (int j = 7; j >= 0; j--){
int suma = 0;
int sumc = 0;
CalcuateSums(count, points, rotationInvariance, grayImage, pt, suma, sumc, cos_theta, sin_theta, half_ssd_size);
desc[ix] += (uchar)((suma < sumc) << j);
count += 6;
}
}
}
}
static void pixelTests8(const Mat& grayImage, const std::vector<KeyPoint>& keypoints, OutputArray _descriptors, const std::vector<int> &points, bool rotationInvariance, int half_ssd_size)
{
Mat descriptors = _descriptors.getMat();
for (int i = 0; i < (int)keypoints.size(); ++i)
{
uchar* desc = descriptors.ptr(i);
const KeyPoint& pt = keypoints[i];
int count = 0;
//handling keypoint orientation
float angle = pt.angle;
angle *= (float)(CV_PI / 180.f);
float cos_theta = cos(angle);
float sin_theta = sin(angle);
for (int ix = 0; ix < 8; ix++){
desc[ix] = 0;
for (int j = 7; j >= 0; j--){
int suma = 0;
int sumc = 0;
CalcuateSums(count, points, rotationInvariance, grayImage, pt, suma, sumc, cos_theta, sin_theta, half_ssd_size);
desc[ix] += (uchar)((suma < sumc) << j);
count += 6;
}
}
}
}
static void pixelTests16(const Mat& grayImage, const std::vector<KeyPoint>& keypoints, OutputArray _descriptors, const std::vector<int> &points, bool rotationInvariance, int half_ssd_size)
{
Mat descriptors = _descriptors.getMat();
for (int i = 0; i < (int)keypoints.size(); ++i)
{
uchar* desc = descriptors.ptr(i);
const KeyPoint& pt = keypoints[i];
int count = 0;
//handling keypoint orientation
float angle = pt.angle;
angle *= (float)(CV_PI / 180.f);
float cos_theta = cos(angle);
float sin_theta = sin(angle);
for (int ix = 0; ix < 16; ix++){
desc[ix] = 0;
for (int j = 7; j >= 0; j--){
int suma = 0;
int sumc = 0;
CalcuateSums(count, points, rotationInvariance, grayImage, pt, suma, sumc, cos_theta, sin_theta, half_ssd_size);
desc[ix] += (uchar)((suma < sumc) << j);
count += 6;
}
}
}
}
static void pixelTests32(const Mat& grayImage, const std::vector<KeyPoint>& keypoints, OutputArray _descriptors, const std::vector<int> &points, bool rotationInvariance, int half_ssd_size)
{
Mat descriptors = _descriptors.getMat();
for (int i = 0; i < (int)keypoints.size(); ++i)
{
uchar* desc = descriptors.ptr(i);
const KeyPoint& pt = keypoints[i];
int count = 0;
float angle = pt.angle;
angle *= (float)(CV_PI / 180.f);
float cos_theta = cos(angle);
float sin_theta = sin(angle);
for (int ix = 0; ix < 32; ix++){
desc[ix] = 0;
for (int j = 7; j >= 0; j--){
int suma = 0;
int sumc = 0;
CalcuateSums(count, points, rotationInvariance, grayImage, pt, suma, sumc, cos_theta, sin_theta, half_ssd_size);
desc[ix] += (uchar)((suma < sumc) << j);
count += 6;
}
}
}
}
static void pixelTests64(const Mat& grayImage, const std::vector<KeyPoint>& keypoints, OutputArray _descriptors, const std::vector<int> &points, bool rotationInvariance, int half_ssd_size)
{
Mat descriptors = _descriptors.getMat();
for (int i = 0; i < (int)keypoints.size(); ++i)
{
uchar* desc = descriptors.ptr(i);
const KeyPoint& pt = keypoints[i];
int count = 0;
//handling keypoint orientation
float angle = pt.angle;
angle *= (float)(CV_PI / 180.f);
float cos_theta = cos(angle);
float sin_theta = sin(angle);
for (int ix = 0; ix < 64; ix++){
desc[ix] = 0;
for (int j = 7; j >= 0; j--){
int suma = 0;
int sumc = 0;
CalcuateSums(count, points, rotationInvariance, grayImage, pt, suma, sumc, cos_theta, sin_theta, half_ssd_size);
desc[ix] += (uchar)((suma < sumc) << j);
count += 6;
}
}
}
}
void CalcuateSums(int count, const std::vector<int> &points, bool rotationInvariance, const Mat &grayImage, const KeyPoint &pt, int &suma, int &sumc, float cos_theta, float sin_theta, int half_ssd_size)
{
int ax = points[count];
int ay = points[count + 1];
int bx = points[count + 2];
int by = points[count + 3];
int cx = points[count + 4];
int cy = points[count + 5];
int ax2 = ax;
int ay2 = ay;
int bx2 = bx;
int by2 = by;
int cx2 = cx;
int cy2 = cy;
if (rotationInvariance){
ax2 =(int)(((float)ax)*cos_theta - ((float)ay)*sin_theta);
ay2 = (int)(((float)ax)*sin_theta + ((float)ay)*cos_theta);
bx2 = (int)(((float)bx)*cos_theta - ((float)by)*sin_theta);
by2 = (int)(((float)bx)*sin_theta + ((float)by)*cos_theta);
cx2 = (int)(((float)cx)*cos_theta - ((float)cy)*sin_theta);
cy2 = (int)(((float)cx)*sin_theta + ((float)cy)*cos_theta);
if (ax2 > 24)
ax2 = 24;
if (ax2<-24)
ax2 = -24;
if (ay2>24)
ay2 = 24;
if (ay2<-24)
ay2 = -24;
if (bx2>24)
bx2 = 24;
if (bx2<-24)
bx2 = -24;
if (by2>24)
by2 = 24;
if (by2<-24)
by2 = -24;
if (cx2>24)
cx2 = 24;
if (cx2<-24)
cx2 = -24;
if (cy2>24)
cy2 = 24;
if (cy2 < -24)
cy2 = -24;
}
ax2 += (int)(pt.pt.x + 0.5);
ay2 += (int)(pt.pt.y + 0.5);
bx2 += (int)(pt.pt.x + 0.5);
by2 += (int)(pt.pt.y + 0.5);
cx2 += (int)(pt.pt.x + 0.5);
cy2 += (int)(pt.pt.y + 0.5);
int K = half_ssd_size;
for (int iy = -K; iy <= K; iy++)
{
const uchar * Mi_a = grayImage.ptr<uchar>(ay2 + iy);
const uchar * Mi_b = grayImage.ptr<uchar>(by2 + iy);
const uchar * Mi_c = grayImage.ptr<uchar>(cy2 + iy);
for (int ix = -K; ix <= K; ix++)
{
double difa = Mi_a[ax2 + ix] - Mi_b[bx2 + ix];
suma += (int)((difa)*(difa));
double difc = Mi_c[cx2 + ix] - Mi_b[bx2 + ix];
sumc += (int)((difc)*(difc));
}
}
}
LATCHDescriptorExtractorImpl::LATCHDescriptorExtractorImpl(int bytes, bool rotationInvariance, int half_ssd_size) :
bytes_(bytes), test_fn_(NULL), rotationInvariance_(rotationInvariance), half_ssd_size_(half_ssd_size)
{
switch (bytes)
{
case 1:
test_fn_ = pixelTests1;
break;
case 2:
test_fn_ = pixelTests2;
break;
case 4:
test_fn_ = pixelTests4;
break;
case 8:
test_fn_ = pixelTests8;
break;
case 16:
test_fn_ = pixelTests16;
break;
case 32:
test_fn_ = pixelTests32;
break;
case 64:
test_fn_ = pixelTests64;
break;
default:
CV_Error(Error::StsBadArg, "descriptorSize must be 1,2, 4, 8, 16, 32, or 64");
}
setSamplingPoints();
}
int LATCHDescriptorExtractorImpl::descriptorSize() const
{
return bytes_;
}
int LATCHDescriptorExtractorImpl::descriptorType() const
{
return CV_8UC1;
}
int LATCHDescriptorExtractorImpl::defaultNorm() const
{
return NORM_HAMMING;
}
void LATCHDescriptorExtractorImpl::read(const FileNode& fn)
{
int dSize = fn["descriptorSize"];
switch (dSize)
{
case 1:
test_fn_ = pixelTests1;
break;
case 2:
test_fn_ = pixelTests2;
break;
case 4:
test_fn_ = pixelTests4;
break;
case 8:
test_fn_ = pixelTests8;
break;
case 16:
test_fn_ = pixelTests16;
break;
case 32:
test_fn_ = pixelTests32;
break;
case 64:
test_fn_ = pixelTests64;
break;
default:
CV_Error(Error::StsBadArg, "descriptorSize must be 1,2, 4, 8, 16, 32, or 64");
}
bytes_ = dSize;
}
void LATCHDescriptorExtractorImpl::write(FileStorage& fs) const
{
fs << "descriptorSize" << bytes_;
}
void LATCHDescriptorExtractorImpl::compute(InputArray _image,
std::vector<KeyPoint>& keypoints,
OutputArray _descriptors)
{
Mat image = _image.getMat();
if ( image.empty() )
return;
if ( keypoints.empty() )
return;
Mat grayImage;
GaussianBlur(image, grayImage, cv::Size(3, 3), 2, 2);
if (image.type() != CV_8U) cvtColor(image, grayImage, COLOR_BGR2GRAY);
//Remove keypoints very close to the border
KeyPointsFilter::runByImageBorder(keypoints, image.size(), PATCH_SIZE / 2 + half_ssd_size_);
bool _1d = false;
Mat descriptors;
_1d = _descriptors.kind() == _InputArray::STD_VECTOR && _descriptors.type() == CV_8U;
if( _1d )
{
_descriptors.create((int)keypoints.size()*bytes_, 1, CV_8U);
descriptors = _descriptors.getMat().reshape(1, (int)keypoints.size());
}
else
{
_descriptors.create((int)keypoints.size(), bytes_, CV_8U);
descriptors = _descriptors.getMat();
}
//_descriptors.create((int)keypoints.size(), bytes_, CV_8U);
// prepare descriptors as mat
//Mat descriptors = _descriptors.getMat();
test_fn_(grayImage, keypoints, descriptors, sampling_points_, rotationInvariance_, half_ssd_size_);
}
void LATCHDescriptorExtractorImpl::setSamplingPoints(){
int sampling_points_arr[]= { 13, -6, 19, 19, 23, -4,
4, 16, 24, -11, 4, -21,
22, -14, -2, -20, 23, 5,
17, -10, 2, 10, 14, -18,
-22, 2, -12, 12, -22, 21,
11, 6, 7, 15, 3, -11,
-7, 16, -10, -14, -3, 9,
-5, 1, -16, 16, -9, -21,
-19, 2, -2, -9, -22, 24,
19, 12, -1, -19, 15, -9,
7, -2, 22, -23, 13, 20,
-3, 9, -17, -1, -5, -19,
-3, -14, 5, -21, 10, 19,
12, -9, 24, 20, 20, -20,
-5, 18, 19, 11, -6, -16,
22, 7, 1, -8, -10, 6,
19, -4, 3, 8, -2, 19,
-17, 10, -11, -12, -21, -17,
24, -13, 18, -14, 14, -19,
-24, -15, 15, -14, -23, -11,
-6, 22, -1, -11, 6, -14,
16, 18, 10, -23, 20, 4,
23, 8, 4, 7, 17, -19,
-2, -21, -11, -18, -3, 7,
-23, 10, -11, 5, -16, 19,
-24, 4, 15, -16, -19, -5,
-19, -4, -1, 5, -20, 2,
20, 12, 11, -24, 9, 22,
9, 13, -6, -23, 10, 15,
-22, -8, -4, -5, -15, 20,
-6, -13, 1, 16, -6, 23,
-18, -3, -8, -15, -18, 5,
14, -12, 9, 13, 19, 12,
-22, 16, -1, 19, 16, -12,
1, 8, -1, -4, -3, 7,
3, 15, 23, -23, 5, -9,
2, -7, 14, -13, 6, 20,
-18, 11, 16, -10, -12, 4,
-15, 2, -9, 21, -21, 20,
-3, 5, -22, 23, -7, -22,
-17, 13, 24, -14, -24, -24,
24, 15, 3, -22, -16, 7,
-14, -20, 1, -7, -12, -2,
19, 17, 0, 18, -12, -7,
-12, 10, 8, 5, -21, -18,
-15, 9, 13, 3, -18, -17,
0, 5, 11, -22, 8, 18,
21, 2, -22, -17, 15, 3,
-22, -15, 18, 23, -23, 21,
-24, 16, 10, -3, -8, -1,
-19, 19, 22, 23, -14, -2,
20, 15, -2, -19, 19, -15,
-10, 12, 0, -9, -9, -16,
13, -22, 16, 16, 0, -14,
-8, -13, -1, 20, -5, -22,
-7, -23, -4, 10, -1, 20,
16, -1, -13, -16, 24, -18,
-18, 12, 8, 19, -24, -14,
-15, 24, 6, 2, -21, -22,
20, -2, 8, 0, 17, -10,
-19, 21, -7, 20, -14, 3,
19, 17, 0, -16, -18, -19,
-17, -19, 12, -23, -12, -8,
9, 10, 9, -23, 21, -24,
9, 19, -15, -18, 7, -19,
5, 3, -3, -16, 4, -2,
15, -10, -24, 16, 24, 11,
17, 16, -9, 1, 18, -15,
11, -5, 0, 24, -20, -12,
-14, -19, 24, -16, -9, -6,
22, -14, 2, -22, 16, 11,
23, -1, 4, -10, 20, 22,
-10, -9, 17, 13, -13, -13,
-15, 13, 11, 9, -13, 9,
22, 15, 2, 18, -12, -10,
3, 23, 18, 15, 20, -24,
7, -6, 16, 11, 8, 1,
13, 16, 24, -20, 9, -4,
-8, -3, 17, 24, -19, 17,
11, 6, -5, 22, 14, -10,
-5, -11, -15, -10, -22, 9,
7, 18, -12, 8, 13, -24,
9, 0, 2, 3, 7, 12,
21, 14, 0, -8, -17, 2,
22, 20, -5, 16, 19, -23,
22, -18, -19, -3, 24, -15,
18, 0, -11, 16, 17, 11,
22, 15, -11, 7, 20, -9,
-16, 10, 2, 1, -19, 20,
-19, -4, 2, -3, -24, 17,
-3, 21, 22, -12, -1, 3,
-3, -20, -7, 23, -1, -9,
-11, 3, -20, -5, -9, -8,
19, -17, 21, 21, 21, -13,
-10, 6, 2, -2, -17, -21,
19, 24, 20, 6, 24, -11,
10, -23, -1, -9, 8, -5,
22, -20, -3, 24, 19, 5,
-24, 6, 0, -13, -23, -15,
10, 20, -22, -4, 9, -20,
-24, 10, 5, -15, -24, -20,
22, 6, 8, -7, 11, 22,
-18, 7, -9, 19, -12, -5,
-9, 21, -20, -17, -17, 22,
-23, 6, -22, -12, -17, 7,
-18, 3, 1, 24, -24, 20,
-10, -9, 2, 15, 18, 18,
16, -13, -18, 11, 9, -6,
24, 24, -24, 22, 12, -12,
20, 7, -21, 15, 22, -5,
-9, -7, 23, -13, -17, -20,
-9, -6, 23, 0, -22, 13,
-15, -18, 1, -22, -17, 10,
0, 4, 4, -8, 18, -8,
-7, -6, -20, 18, -20, -3,
-20, -14, 4, -9, -17, -8,
-18, -7, 3, 8, -16, 5,
7, -12, 10, 19, 20, 21,
-22, 24, 4, 8, -22, 2,
-19, -18, -18, 22, -2, 13,
10, 9, -15, 15, 21, 16,
16, 11, -24, -2, 24, 21,
-7, -12, 1, 14, 9, 17,
20, 17, 7, 7, 5, -24,
-13, -8, 21, 18, -15, 11,
-22, 8, 12, -8, -18, 23,
14, 10, 6, -24, 17, -10,
8, 13, 21, 17, 24, -3,
-21, -24, 18, 11, -8, 5,
-10, -23, -2, 23, -13, 5,
11, 7, -1, -21, -10, -4,
21, -22, -15, 6, 6, -4,
16, -7, -7, -23, 19, 6,
-1, 21, 23, -14, -2, -17,
22, -13, -22, 4, 14, 3,
-10, 3, 14, -11, -22, 8,
11, 13, -24, 10, 24, 21,
12, 2, 13, -16, 15, 1,
-1, -4, 20, -22, -6, -19,
-14, -20, 2, -11, -20, 24,
-23, -10, 12, 1, -24, 2,
-24, -23, -16, 13, -1, -11,
-8, 6, 19, -13, -23, 23,
-18, -24, 23, -16, -21, 16,
-12, 19, -10, 6, -6, -16,
0, -15, -13, 24, -2, 9,
19, -4, 0, 21, 21, 16,
-10, -24, -24, -20, -13, -5,
24, 7, -13, 7, 18, 19,
0, 22, -21, 20, 0, 18,
23, 10, -13, -14, 16, 10,
-10, -12, 8, 10, -13, 24,
-22, -6, -17, 14, -6, 11,
17, 17, -7, 17, 17, -12,
22, -1, -2, -3, -24, 22,
12, 0, 1, -11, 12, -16,
-20, -6, -11, 17, -5, -19,
18, 7, -8, 3, 23, -11,
24, -7, -18, 24, 20, -1,
-10, 4, -4, -22, -14, -8,
15, -8, -16, 20, 17, 23,
12, 15, 15, -19, 5, 4,
-16, 21, 3, -3, -17, -15,
-18, 14, -20, -22, -18, 12,
21, 13, -18, 0, 12, -12,
-20, 23, 15, -10, -14, -16,
-24, 16, 12, -5, -16, 13,
-11, -13, -4, -9, -2, -18,
3, -12, -24, 0, -2, -3,
-14, -14, 22, 9, -21, 17,
18, 10, 2, 23, 15, 6,
-8, -18, 15, 23, -11, 23,
-24, 13, 4, 16, -24, -13,
9, 0, 21, -23, 6, -24,
-22, 13, 21, 19, -21, -10,
-21, 19, 7, -2, -7, 1,
2, -21, 8, 20, 11, -12,
19, -19, -2, 24, 17, 1,
-3, -7, 3, 17, -4, -13,
-23, -5, -15, -14, -7, 11,
-15, -23, 24, 22, -17, 18,
5, -7, 11, -22, 18, -5,
20, -11, -20, 0, 11, 4,
18, 18, -9, 7, 19, 17,
1, -17, 24, -24, 4, 3,
-19, -23, 9, 23, -10, 9,
7, -2, -13, 5, 16, -5,
8, -13, -9, -23, 12, 13,
6, -21, -1, 0, -4, 18,
9, -17, -24, -22, 9, 17,
-19, 2, 20, -14, -22, 23,
22, 11, -9, -14, 8, -4,
12, -22, -2, 13, 8, 21,
9, -8, 14, 18, 5, -9,
16, -13, -7, -7, 21, -12,
13, -12, -10, 11, 7, 11,
3, 8, 5, -6, 2, 14,
24, -22, 8, 23, -7, -10,
22, 11, 6, 20, -6, -9,
10, -5, -2, -1, 12, 15,
-14, 14, -23, 6, -13, -3,
-9, 2, 22, -1, -24, -10,
-17, 22, 6, -9, -12, -13,
-12, 1, -4, 9, -14, -2,
13, 2, 23, -2, 12, 5,
16, -14, -4, -22, 18, 17,
-13, -8, 7, -5, -21, -17,
3, -1, -3, -2, -10, 19,
18, 6, -14, 24, 20, 10,
-7, -20, -23, 10, -4, -8,
-20, -9, -10, 16, -14, -21,
9, 17, -12, 21, 16, 24,
19, -22, -11, -12, 24, -20,
5, -15, 14, 12, 3, -13,
-6, 20, 4, 22, 3, -20,
-23, -12, 7, 12, -23, 16,
22, 3, -4, 18, 22, 8,
1, 1, 16, 9, -5, 18,
21, -7, -5, -15, 24, -6,
-13, 14, -12, 23, -17, 18,
12, 18, -1, 0, 20, 7,
14, -7, -15, -17, 18, -2,
-18, -12, -11, 14, -15, -21,
-2, -21, 4, -16, 10, -2,
22, -23, -19, -17, 19, 16,
8, 22, 7, -22, 22, -22,
8, -17, -17, 0, 12, 22,
13, 8, -6, 19, 19, -6,
19, -4, -23, -10, 23, -13,
-16, -19, -6, 18, -19, 23,
5, -18, -4, -12, -18, -24,
-10, 9, 6, 4, -16, -24,
-7, -15, 0, 3, -1, 24,
-5, 12, 10, -24, 24, 22,
-13, 9, 1, 18, 15, 7,
-18, -3, -11, -22, -18, -5,
-9, 7, 14, 24, -6, -1,
-1, -24, 22, 19, -1, 13,
-19, 3, -15, -16, -12, 1,
0, 12, 21, 21, 13, -22,
-19, -9, 14, 12, -23, 17,
13, -11, 22, 3, 24, -14,
-19, 5, -1, 20, 18, 15,
19, -19, -16, 24, 23, 7,
-20, -13, 22, 21, -23, -3,
-20, 19, 16, -2, -20, -19,
18, 18, -12, -16, 14, -5,
21, -16, -23, -5, 19, 8,
-12, 12, -20, -5, -7, -6,
-10, -24, -3, 18, -11, -5,
8, 14, 2, -3, 9, 6,
24, 2, -2, -6, 24, -12,
7, -8, 0, 8, -3, 21,
22, 1, 17, -12, 14, -23,
19, -18, -1, 23, -21, -10,
-6, -1, 14, -22, -9, -9,
20, -24, -16, -11, 21, 19,
-24, 9, -8, 17, -19, -7,
-12, -3, 19, -24, -15, 0,
-1, -21, -9, 22, -21, -4,
23, 4, -3, 11, 9, 4,
-10, 10, 10, 4, -8, 7,
5, -15, 21, -23, 9, -12,
-17, -21, -2, -15, -17, -15,
21, 12, 9, 23, 1, -9,
21, 20, 19, -6, 5, -1,
-16, -21, 19, -3, -12, 15,
14, 3, -2, 2, -20, -17,
-3, -16, -15, -13, -21, 11,
-18, 21, -5, -17, 5, 11,
23, 7, -9, 17, 20, -6,
11, -14, -21, 23, 19, -21,
-9, -6, 23, -24, -16, 7,
-22, 21, 7, 12, -19, -12,
-3, 19, 23, 10, -3, -18,
-2, 22, -8, -16, -5, 23,
14, 21, 22, -19, 6, -9,
-6, -24, -12, -13, -23, 9,
4, -21, 14, -4, 23, 18,
9, 7, -6, 6, 22, 0,
14, -13, 8, 24, 16, -14,
2, -20, 4, -13, 11, -11,
14, -12, 23, 7, 10, 21,
14, -4, 14, 22, 13, -14,
11, -12, 21, 19, 20, -8,
3, -20, 23, -13, 23, 23,
4, 18, -2, 10, -11, 20,
1, 21, 6, 15, 14, -3,
16, 24, 8, -11, 18, 23,
21, -3, 15, -23, 5, -5,
7, 9, -12, -4, 14, 18,
1, -24, 11, -9, -1, 10,
-16, -10, -7, 22, -14, 5,
-22, 18, -15, -24, -1, 8,
-17, 16, 4, 0, -17, 24,
-9, -8, 17, -3, -13, 21,
24, 10, 12, 12, 3, -15,
21, 6, -1, -5, 19, 19,
-21, -15, 12, 14, -24, -15,
-24, 10, 5, -11, -16, -6,
16, -8, -5, -20, 15, -7,
-4, 20, -5, 12, -9, 20,
-18, 12, 10, -14, -14, 24,
17, -12, -1, 13, 18, 19,
-13, 22, 2, 9, -14, 19,
13, -12, 5, 18, 4, -24,
-23, -5, -1, -11, 19, 13,
14, -11, -21, -8, 22, -22,
-24, 21, -8, -21, 5, 14,
11, -4, -9, -10, 16, 2,
19, -12, -8, 14, 22, -23,
-22, -13, 1, -4, -17, 4,
-21, 10, 5, 3, -19, 18,
-3, -18, 13, 15, 19, -23,
-2, 12, 23, -19, -1, -10,
15, -7, 0, -20, 7, 0,
-17, -1, -5, 15, -16, -20,
11, -21, 2, -15, 4, 2,
-3, 5, 4, -2, -3, -14,
13, 22, -15, 19, 9, -17,
-4, 18, 21, 7, -2, 5,
15, 22, 7, -23, 19, 14,
11, 14, 24, -23, 11, 6,
17, 21, -8, -13, 15, 11,
-12, -23, 10, 8, -8, -11,
12, -5, -16, -19, 18, -6,
-20, -24, -1, -22, -24, -9,
-17, -12, 9, 19, -16, 24,
14, -9, -6, 7, 20, -23,
7, 19, 24, 0, 9, 23,
-23, 22, 11, 7, -24, 22,
-21, 0, -8, 14, -20, 23,
14, -8, -16, -15, 18, 11,
2, -6, 24, 7, 6, 24,
-14, 24, -4, 3, -21, 2,
23, 10, 24, -24, 10, 10,
11, 5, -2, 15, 12, 7,
24, 11, -5, 6, 21, 12,
12, 22, -1, 13, -15, -18,
14, -23, 20, 1, 19, 23,
-19, -22, 4, -2, -19, 20,
8, 2, -9, 10, 23, 21,
-11, -11, -1, 15, 9, 23,
20, 1, 9, 9, 13, 21,
9, -22, -5, -16, 5, -11,
-17, -23, -7, 9, -24, 23,
7, -9, 23, 2, 20, -16,
15, -18, -22, 18, 16, 14,
-13, -18, -23, -8, -22, 13,
12, -9, 12, 20, 14, -12,
-18, -5, -15, 3, -19, 8,
-16, -13, 10, 10, -15, 17,
-9, 5, -23, 16, -9, 3,
-16, -19, 14, 21, -19, -22,
-1, 5, 23, 13, 1, -24,
-10, 19, -1, -23, -19, -23,
4, -19, 8, 4, 7, 18,
17, 12, 1, 7, -6, 18,
11, -24, 8, 18, 16, -14,
-22, 11, -11, -2, -20, 14,
-5, 9, 9, -23, 16, 24,
-12, -8, 14, -6, -11, 5,
23, -6, -16, -5, 21, -15,
21, -22, -24, -2, 13, -8,
17, 19, 24, -4, 10, 6,
-14, -21, -8, 13, -5, -1,
-21, -12, 23, -24, -21, -17,
12, 11, 21, 15, 13, 23,
-9, 16, -23, -2, -6, 2,
19, 4, 18, -24, 23, 6,
8, -23, 15, -2, 7, 20,
24, 10, 8, 24, 4, -3,
-23, 5, 19, -3, -23, 23,
-19, -20, 3, 15, -12, 6,
-10, 23, 0, 3, 18, -22,
12, 8, -24, 19, 22, 2,
12, 0, -4, -24, 21, 16,
-9, -3, 14, 14, -14, 4,
18, 11, -9, -14, 21, -23,
11, 22, 1, 4, 17, -3,
13, -22, -17, 23, 11, 15,
11, -14, 3, 9, -4, -12,
-6, 16, 2, 5, 20, 6,
10, -1, 7, 21, 12, 7,
-21, 12, -14, -21, -23, 13,
16, 24, 0, -10, -14, -16,
-12, -6, 23, 8, -10, 9,
14, -18, 2, 24, -9, -5,
16, 17, 0, -1, 10, 21,
7, 0, -12, -15, 13, -11,
14, -20, -22, -13, 0, 1,
-21, -15, 6, -23, -16, -20,
-9, 24, 2, -17, -5, 4,
-21, 18, 18, -22, -21, -6,
8, -3, 5, 17, 18, 10,
3, 0, 11, 22, -4, -12,
-24, 10, 18, 20, -21, -24,
-8, -19, 6, -24, 17, 7,
1, 8, 19, 8, 13, -23,
-21, -24, 21, 2, -21, -15,
20, 17, 21, -3, 21, 18,
-18, -10, 17, -18, -18, 10,
5, -6, 19, 10, 11, 22,
6, 24, 8, 13, 3, -8,
-3, -12, -13, 4, -21, 23,
-10, 5, -2, -22, 5, -9,
20, -17, -24, 16, 5, -3,
2, 5, 6, -24, 5, 21,
-15, 22, 1, 7, -16, 0,
-19, -21, -7, 10, 0, -23,
-15, -6, -2, -18, -20, -8,
-16, 19, 1, 15, 18, 4,
5, 4, -21, -14, 4, 2,
2, 19, 0, -8, 5, 7,
-16, -18, 22, 2, -18, 22,
-23, 2, 15, -21, -19, -10,
-15, 12, -8, -14, -20, -11,
-11, 3, 1, 20, -24, 20,
2, 3, -1, 24, 17, 19,
-22, 2, 9, -23, -20, -3,
-11, -11, 11, -20, -13, -23,
5, -1, 16, -7, 3, 9,
23, -2, 14, 23, 13, -2,
20, -12, 12, 18, 22, 1,
16, -19, 11, 8, 7, 23,
9, 9, 2, -20, 15, -23,
10, 0, -10, 23, 9, 4,
-24, -18, 3, 15, -16, -7,
19, -17, -17, 1, 23, 11,
22, -7, 0, 24, 0, -3,
-24, -22, 15, 9, -8, -4,
20, -14, -8, -14, 19, 9,
24, -2, -8, -4, 24, 14,
17, -1, 10, -23, 1, 15,
9, -1, 0, -24, 13, -12,
-5, 10, -18, -6, -23, 11,
-20, 21, 18, 4, -9, -7,
24, 15, 7, -3, -2, 11,
-10, -24, 11, 2, -10, 13,
17, -17, -14, -18, 21, -14,
-9, -17, -4, -9, -10, -2,
22, -21, 8, -11, 1, 23,
-3, -15, -21, -20, -14, 19,
3, -10, -11, 22, 3, -21,
-23, -15, 0, 9, -19, 12,
-24, -3, -5, 22, -23, 15,
16, -9, -19, -18, 11, -1,
-18, 6, 0, -24, 18, -23,
15, -11, -24, 4, 16, 1,
10, -21, 23, 1, 2, -10,
18, -2, 1, 5, -7, -23,
24, -16, -11, -22, 24, -19,
19, 12, -23, 2, 12, 0,
17, 9, 12, -12, 8, 11,
-16, -16, 19, 0, -19, -21,
15, 20, 20, -24, 9, 3,
24, 1, 6, 21, 18, -19,
-22, 21, -2, -14, 19, 22,
0, -17, 18, -12, -2, 10,
-21, -8, -9, -7, -18, -15,
-19, -1, -7, -21, -23, -15,
-23, -5, 13, 21, -18, 1,
12, 6, 15, -12, 10, -20,
16, -13, -20, -6, 14, 13,
-9, -2, 11, -14, -13, -5,
15, -4, 13, 17, 22, -3,
19, -17, -2, 11, -23, 22,
12, 16, 12, -4, 18, 9,
0, 9, 11, -20, 11, 1,
12, -11, 22, -9, 24, -23,
-14, -13, -3, 5, 4, 12,
14, 12, -14, 3, 15, 17,
-11, -24, 18, -23, -5, 3,
18, 9, 9, 20, 9, 3,
-21, -10, 8, -1, -24, -23,
13, 4, -3, -19, 19, 1,
18, -18, 2, -21, 10, 13,
-10, -17, 0, 12, 8, 19,
21, 8, 2, -23, -19, 8,
5, -4, -12, 18, 14, -12,
19, -19, 14, 5, 9, 21,
-21, -21, -8, 1, -1, 14,
13, 6, 16, -24, 15, 14,
-5, 21, -14, -8, -2, 11,
-14, -21, -23, 19, -6, -6,
10, -10, -23, -2, 16, 16,
13, -14, 3, -15, 13, -23,
-15, -13, 17, 12, -19, 19,
-5, 18, -12, 10, -4, -16,
-22, -15, -9, -18, -10, 16,
-7, -5, 13, -18, -18, -23,
-23, 22, -3, -24, 14, 20,
12, 16, 21, -11, 19, 19,
12, -18, -3, -17, 9, -14,
-19, -11, 14, -13, -21, 23,
8, -6, -18, 12, 17, 1,
-4, -1, 4, 19, -12, -7,
21, 3, -24, 21, 13, 8,
17, 23, 2, 15, 21, -4,
4, 16, -15, -20, 1, 6,
16, -22, 6, 11, 18, -12,
-24, -1, -18, 8, -13, -2,
16, -6, -1, -7, -20, -20,
9, -10, -15, 6, 17, 16,
-19, 17, 19, 0, -18, -8,
15, -23, 12, -6, 1, 11,
21, -15, 6, 19, 10, -24,
-16, 23, -1, -8, -17, -14,
11, 2, -1, 7, 14, -2,
11, 20, -1, -4, -3, -23,
-19, 20, -11, -2, -20, -24,
11, -12, 5, -21, -2, -13};
sampling_points_.assign(&sampling_points_arr[0],&sampling_points_arr[0]+sizeof(sampling_points_arr)/4); }
}
} // namespace cv
...@@ -1039,6 +1039,13 @@ TEST( Features2d_DescriptorExtractor_LUCID, regression ) ...@@ -1039,6 +1039,13 @@ TEST( Features2d_DescriptorExtractor_LUCID, regression )
test.safe_run(); test.safe_run();
} }
TEST( Features2d_DescriptorExtractor_LATCH, regression )
{
CV_DescriptorExtractorTest<Hamming> test( "descriptor-latch", 1,
LATCH::create() );
test.safe_run();
}
/*#if CV_SSE2 /*#if CV_SSE2
...@@ -1247,3 +1254,31 @@ TEST(DISABLED_Features2d_SURF_using_mask, regression) ...@@ -1247,3 +1254,31 @@ TEST(DISABLED_Features2d_SURF_using_mask, regression)
FeatureDetectorUsingMaskTest test(SURF::create()); FeatureDetectorUsingMaskTest test(SURF::create());
test.safe_run(); test.safe_run();
} }
TEST( XFeatures2d_DescriptorExtractor, batch )
{
string path = string(cvtest::TS::ptr()->get_data_path() + "detectors_descriptors_evaluation/images_datasets/graf");
vector<Mat> imgs, descriptors;
vector<vector<KeyPoint> > keypoints;
int i, n = 6;
Ptr<SIFT> sift = SIFT::create();
for( i = 0; i < n; i++ )
{
string imgname = format("%s/img%d.png", path.c_str(), i+1);
Mat img = imread(imgname, 0);
imgs.push_back(img);
}
sift->detect(imgs, keypoints);
sift->compute(imgs, keypoints, descriptors);
ASSERT_EQ((int)keypoints.size(), n);
ASSERT_EQ((int)descriptors.size(), n);
for( i = 0; i < n; i++ )
{
EXPECT_GT((int)keypoints[i].size(), 100);
EXPECT_GT(descriptors[i].rows, 100);
}
}
...@@ -651,15 +651,16 @@ TEST(Features2d_RotationInvariance_Descriptor_SIFT, regression) ...@@ -651,15 +651,16 @@ TEST(Features2d_RotationInvariance_Descriptor_SIFT, regression)
test.safe_run(); test.safe_run();
} }
TEST(Features2d_RotationInvariance_Descriptor_DAISY, regression) TEST(Features2d_RotationInvariance_Descriptor_LATCH, regression)
{ {
DescriptorRotationInvarianceTest test(BRISK::create(), DescriptorRotationInvarianceTest test(SIFT::create(),
DAISY::create(15, 3, 8, 8, DAISY::NRM_NONE, noArray(), true, true), LATCH::create(),
NORM_L1, NORM_HAMMING,
0.79f); 0.9999f);
test.safe_run(); test.safe_run();
} }
/* /*
* Detector's scale invariance check * Detector's scale invariance check
*/ */
......
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