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Merge pull request #2027 from AD-530:brief_cl

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pull/2203/merge
Andrey Pavlenko 11 years ago committed by OpenCV Buildbot
parent a64d3c1744 d270c9e8b6
commit 06acf7090c
8 changed files with 596 additions and 32 deletions
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  1. 32
      modules/features2d/doc/common_interfaces_of_descriptor_extractors.rst
  2. 31
      modules/features2d/doc/feature_detection_and_description.rst
  3. 52
      modules/ocl/doc/feature_detection_and_description.rst
  4. 20
      modules/ocl/include/opencv2/ocl.hpp
  5. 114
      modules/ocl/perf/perf_brief.cpp
  6. 91
      modules/ocl/src/brief.cpp
  7. 173
      modules/ocl/src/opencl/brief.cl
  8. 115
      modules/ocl/test/test_brief.cpp

32
modules/features2d/doc/common_interfaces_of_descriptor_extractors.rst
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@ -119,35 +119,3 @@ them into a single color descriptor. ::
protected:
...
};
BriefDescriptorExtractor
------------------------
.. ocv:class:: BriefDescriptorExtractor : public DescriptorExtractor
Class for computing BRIEF descriptors described in a paper of Calonder M., Lepetit V.,
Strecha C., Fua P. *BRIEF: Binary Robust Independent Elementary Features* ,
11th European Conference on Computer Vision (ECCV), Heraklion, Crete. LNCS Springer, September 2010. ::
class BriefDescriptorExtractor : public DescriptorExtractor
{
public:
static const int PATCH_SIZE = 48;
static const int KERNEL_SIZE = 9;
// bytes is a length of descriptor in bytes. It can be equal 16, 32 or 64 bytes.
BriefDescriptorExtractor( int bytes = 32 );
virtual void read( const FileNode& );
virtual void write( FileStorage& ) const;
virtual int descriptorSize() const;
virtual int descriptorType() const;
virtual int defaultNorm() const;
protected:
...
};
.. note::
* A complete BRIEF extractor sample can be found at opencv_source_code/samples/cpp/brief_match_test.cpp

31
modules/features2d/doc/feature_detection_and_description.rst
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@ -37,6 +37,37 @@ Detects corners using the FAST algorithm by [Rosten06]_.
.. [Rosten06] E. Rosten. Machine Learning for High-speed Corner Detection, 2006.
BriefDescriptorExtractor
------------------------
.. ocv:class:: BriefDescriptorExtractor : public DescriptorExtractor
Class for computing BRIEF descriptors described in a paper of Calonder M., Lepetit V.,
Strecha C., Fua P. *BRIEF: Binary Robust Independent Elementary Features* ,
11th European Conference on Computer Vision (ECCV), Heraklion, Crete. LNCS Springer, September 2010. ::
class BriefDescriptorExtractor : public DescriptorExtractor
{
public:
static const int PATCH_SIZE = 48;
static const int KERNEL_SIZE = 9;
// bytes is a length of descriptor in bytes. It can be equal 16, 32 or 64 bytes.
BriefDescriptorExtractor( int bytes = 32 );
virtual void read( const FileNode& );
virtual void write( FileStorage& ) const;
virtual int descriptorSize() const;
virtual int descriptorType() const;
virtual int defaultNorm() const;
protected:
...
};
.. note::
* A complete BRIEF extractor sample can be found at opencv_source_code/samples/cpp/brief_match_test.cpp
MSER
----
.. ocv:class:: MSER : public FeatureDetector

52
modules/ocl/doc/feature_detection_and_description.rst
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@ -450,7 +450,59 @@ Gets final array of keypoints.
The function performs non-max suppression if needed and returns the final amount of keypoints.
ocl::BRIEF_OCL
------------------
.. ocv:class:: ocl::BRIEF_OCL
Class for computing BRIEF descriptors described in a paper of Calonder M., Lepetit V.,
Strecha C., Fua P. *BRIEF: Binary Robust Independent Elementary Features* ,
11th European Conference on Computer Vision (ECCV), Heraklion, Crete. LNCS Springer, September 2010. ::
class CV_EXPORTS BRIEF_OCL
{
public:
static const int PATCH_SIZE = 48;
static const int KERNEL_SIZE = 9;
explicit BRIEF_OCL(int _bytes = 32);
//!computes the brief descriptor for a set of given keypoints
//! supports only CV_8UC1 images
void compute(const oclMat& image, const oclMat& keypoints, oclMat& mask, oclMat& descriptors) const;
static int getBorderSize();
protected:
...
};
ocl::BRIEF_OCL::BRIEF_OCL
--------------------------
Constructor.
.. ocv:function:: ocl::BRIEF_OCL::BRIEF_OCL(int _bytes = 32)
:param bytes: The length of the descriptor in bytes. Supported values are 16, 32 or 64 bytes.
ocl::BRIEF_OCL::compute
------------------------
Computes BRIEF descriptors.
.. ocv:function:: void ocl::BRIEF_OCL::compute(const oclMat& image, const oclMat& keypoints, oclMat& mask, oclMat& descriptors) const
:param image: Image The input 8-bit grayscale image.
:param keypoints: The keypoints.
:param mask: In and output mask. If mask has same cols as keypoints, descriptors are computed for keypoints with non-zero mask element.
On return it indicates for what keypoints a descriptor was computed or not(if a keypoint is near the image border).
:param descriptors: The computed descriptors. It has size keypoints.cols x bytes.
ocl::BRIEF_OCL::getBorderSize
-----------------------------
Returns the size of the image border where descriptors cannot be computed
.. ocv:function:: static int ocl::BRIEF_OCL::getBorderSize() const
ocl::HOGDescriptor
----------------------

20
modules/ocl/include/opencv2/ocl.hpp
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@ -1515,6 +1515,26 @@ namespace cv
int nonmaxSupressionOCL(oclMat& keypoints);
};
////////////////////////////////// BRIEF Feature Descriptor //////////////////////////////////
class CV_EXPORTS BRIEF_OCL
{
public:
static const int PATCH_SIZE = 48;
static const int KERNEL_SIZE = 9;
explicit BRIEF_OCL(int _bytes = 32);
//!computes the brief descriptor for a set of given keypoints
//! supports only CV_8UC1 images
void compute(const oclMat& image, const oclMat& keypoints, oclMat& mask, oclMat& descriptors) const;
static int getBorderSize();
protected:
int bytes;
};
////////////////////////////////// ORB Descriptor Extractor //////////////////////////////////
class CV_EXPORTS ORB_OCL
{

114
modules/ocl/perf/perf_brief.cpp
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@ -0,0 +1,114 @@
/*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) 2013, OpenCV Foundation, 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.
//
// Authors:
// * Matthias Bady, aegirxx ==> gmail.com
//
//M*/
#include "perf_precomp.hpp"
using namespace std;
using namespace cv;
using namespace ocl;
using namespace perf;
///////////// BRIEF ////////////////////////
typedef TestBaseWithParam<std::tr1::tuple<std::string, int, size_t> > OCL_BRIEF;
PERF_TEST_P( OCL_BRIEF, extract, testing::Combine(
testing::Values( string( "gpu/opticalflow/rubberwhale1.png" ),
string( "gpu/stereobm/aloe-L.png" )
), testing::Values( 16, 32, 64 ), testing::Values( 250, 500, 1000, 2500, 3000 ) ) )
{
const std::string filename = std::tr1::get<0>(GetParam( ));
const int bytes = std::tr1::get<1>(GetParam( ));
const size_t numKp = std::tr1::get<2>(GetParam( ));
Mat img = imread( getDataPath( filename ), IMREAD_GRAYSCALE );
ASSERT_TRUE( !img.empty( ) ) << "no input image";
int threshold = 15;
std::vector<KeyPoint> keypoints;
while (threshold > 0 && keypoints.size( ) < numKp)
{
FastFeatureDetector fast( threshold );
fast.detect( img, keypoints, Mat( ) );
threshold -= 5;
KeyPointsFilter::runByImageBorder( keypoints, img.size( ), BRIEF_OCL::getBorderSize( ) );
}
ASSERT_TRUE( keypoints.size( ) >= numKp ) << "not enough keypoints";
keypoints.resize( numKp );
if ( RUN_OCL_IMPL )
{
Mat kpMat( 2, int( keypoints.size() ), CV_32FC1 );
for ( size_t i = 0; i < keypoints.size( ); ++i )
{
kpMat.col( int( i ) ).row( 0 ) = keypoints[i].pt.x;
kpMat.col( int( i ) ).row( 1 ) = keypoints[i].pt.y;
}
BRIEF_OCL brief( bytes );
oclMat imgCL( img ), keypointsCL(kpMat), mask;
while (next( ))
{
startTimer( );
oclMat descriptorsCL;
brief.compute( imgCL, keypointsCL, mask, descriptorsCL );
cv::ocl::finish( );
stopTimer( );
}
SANITY_CHECK_NOTHING( )
}
else if ( RUN_PLAIN_IMPL )
{
BriefDescriptorExtractor brief( bytes );
while (next( ))
{
startTimer( );
Mat descriptors;
brief.compute( img, keypoints, descriptors );
stopTimer( );
}
SANITY_CHECK_NOTHING( )
}
else
OCL_PERF_ELSE;
}

91
modules/ocl/src/brief.cpp
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@ -0,0 +1,91 @@
/*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.
//
// @Authors
// Matthias Bady aegirxx ==> gmail.com
//
// 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 "precomp.hpp"
#include "opencl_kernels.hpp"
using namespace cv;
using namespace cv::ocl;
BRIEF_OCL::BRIEF_OCL( int _bytes ) : bytes( _bytes )
{
}
void BRIEF_OCL::compute( const oclMat& image, const oclMat& keypoints, oclMat& mask, oclMat& descriptors ) const
{
CV_Assert( image.type( ) == CV_8UC1 );
if ( keypoints.size( ).area( ) == 0 ) return;
descriptors = oclMat( Mat( keypoints.cols, bytes, CV_8UC1 ) );
if( mask.cols != keypoints.cols )
{
mask = oclMat( Mat::ones( 1, keypoints.cols, CV_8UC1 ) );
}
oclMat sum;
integral( image, sum, CV_32S );
cl_mem sumTexture = bindTexture( sum );
std::stringstream build_opt;
build_opt
<< " -D BYTES=" << bytes
<< " -D KERNEL_SIZE=" << KERNEL_SIZE
<< " -D BORDER=" << getBorderSize();
const String kernelname = "extractBriefDescriptors";
size_t localThreads[3] = {bytes, 1, 1};
size_t globalThreads[3] = {keypoints.cols * bytes, 1, 1};
Context* ctx = Context::getContext( );
std::vector< std::pair<size_t, const void *> > args;
args.push_back( std::make_pair( sizeof (cl_mem), (void *) &sumTexture ) );
args.push_back( std::make_pair( sizeof (cl_mem), (void *) &keypoints.data ) );
args.push_back( std::make_pair( sizeof (cl_int), (void *) &keypoints.step ) );
args.push_back( std::make_pair( sizeof (cl_mem), (void *) &descriptors.data ) );
args.push_back( std::make_pair( sizeof (cl_int), (void *) &descriptors.step ) );
args.push_back( std::make_pair( sizeof (cl_mem), (void *) &mask.data ) );
openCLExecuteKernel( ctx, &brief, kernelname, globalThreads, localThreads, args, -1, -1, build_opt.str( ).c_str( ) );
openCLFree( sumTexture );
}
int BRIEF_OCL::getBorderSize( )
{
return PATCH_SIZE / 2 + KERNEL_SIZE / 2;
}

173
modules/ocl/src/opencl/brief.cl
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@ -0,0 +1,173 @@
/*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
//
// Third party copyrights are property of their respective owners.
//
// @Authors
// Matthias Bady, aegirxx ==> gmail.com
//
// 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*/
#ifndef BYTES
#define BYTES 16
#endif
#ifndef KERNEL_SIZE
#define KERNEL_SIZE 9
#endif
#ifndef BORDER
#define BORDER 0
#endif
#define HALF_KERNEL (KERNEL_SIZE/2)
__constant sampler_t sampler = CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_NONE | CLK_FILTER_NEAREST;
__constant char tests[32 * BYTES] =
{
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#if BYTES > 16
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#endif
#if BYTES > 32
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24,3,2,-2,-8,17,-14,-10,6,5,-13,7,11,10,0,-1,4,6,-10,6,-12,-2,5,6,3,-1,8,-15,1,-4,-7,11,
1,11,5,0,6,-12,10,1,-3,-2,-1,4,-2,-11,-1,12,7,-8,-20,-18,2,0,-9,2,-13,-1,-16,2,3,-1,-5,-17,
15,8,3,-14,-13,-12,6,15,2,-8,2,6,6,22,-3,-23,-2,-7,-6,0,13,-10,-6,6,6,7,-10,12,-6,7,-2,11,
0,-22,-2,-17,-4,-1,-11,-14,-2,-8,7,12,12,-5,7,-13,2,-2,-7,6,0,8,-3,23,6,12,13,-11,-21,-10,10,8,
-3,0,7,15,7,-6,-5,-12,-21,-10,12,-11,-5,-11,8,-11,5,0,-11,-1,8,-9,7,-1,11,-23,21,-5,0,-5,-8,6,
-6,8,8,12,-7,5,3,-2,-5,-20,-12,9,-6,12,-11,3,4,5,13,11,2,12,13,-12,-4,-13,4,7,0,15,-3,-16,
-3,2,-2,14,4,-14,16,-11,-13,3,23,10,9,-19,2,5,5,3,14,-7,19,-13,-11,15,14,0,-2,-5,11,-4,0,-6,
-2,5,-13,-8,-11,-15,-7,-17,1,3,-10,-8,-13,-10,7,-12,0,-13,23,-6,2,-17,-7,-3,1,3,4,-10,13,4,14,-6,
-19,-2,-1,5,9,-8,10,-5,7,-1,5,7,9,-10,19,0,7,5,-4,-7,-11,1,-1,-11,2,-1,-4,11,-1,7,2,-2,
1,-20,-9,-6,-4,-18,8,-18,-16,-2,7,-6,-3,-6,-1,-4,0,-16,24,-5,-4,-2,-1,9,-8,2,-6,15,11,4,0,-3,
7,6,2,-10,-7,-9,12,-6,24,15,-8,-1,15,-9,-3,-15,17,-5,11,-10,-2,13,-15,4,-2,-1,4,-23,-16,3,-7,-14,
-3,-5,-10,-9,-5,3,-2,-1,-1,4,1,8,12,9,9,-14,-9,17,-3,0,5,4,13,-6,-1,-8,19,10,8,-5,-15,2,
-12,-9,-4,-5,12,0,24,4,8,-2,14,4,8,-4,-7,16,5,-1,-8,-4,-2,18,-5,17,8,-2,-9,-2,3,-7,1,-6,
-5,-22,-5,-2,-8,-10,14,1,-3,-13,3,9,-4,-1,-1,0,-7,-21,12,-19,-8,8,24,8,12,-6,-2,3,-5,-11,-22,-4,
-3,5,-4,4,-16,24,7,-9,-10,23,-9,18,1,12,17,21,24,-6,-3,-11,-7,17,1,-6,4,4,2,-7,14,6,-12,3,
-6,0,-16,13,-10,5,7,12,5,2,6,-3,7,0,-23,1,15,-5,1,14,-3,-1,6,6,6,-9,-9,12,4,-2,-4,7,
-4,-5,4,4,-13,0,6,-10,2,-12,-6,-3,16,0,-3,3,5,-14,6,11,5,11,0,-13,7,5,-1,-5,12,4,6,10,
-10,4,-1,-11,4,10,-14,5,11,-14,-13,0,2,8,12,24,-1,3,-1,2,9,-14,-23,3,-8,-6,0,9,-15,14,10,-10,
-10,-6,-7,-5,11,5,-3,-15,1,0,1,8,-11,-6,-4,-18,9,0,22,-4,-5,-1,-9,4,-20,2,1,6,1,2,-9,-12,
5,15,4,-6,19,4,4,11,17,-4,-8,-1,-8,-12,7,-3,11,9,8,1,9,22,-15,15,-7,-7,1,-23,-5,13,-8,2,
3,-5,11,-11,3,-18,14,-5,-20,7,-10,-23,-2,-5,6,0,-17,-13,-3,2,-6,-1,14,-2,-12,-16,15,6,-12,-2,3,-19
#endif
};
inline int smoothedSum(__read_only image2d_t sum, const int2 kpPos, const int2 pt)
{
return ( read_imagei( sum, sampler, kpPos + pt + (int2)( HALF_KERNEL + 1, HALF_KERNEL + 1 ))
- read_imagei( sum, sampler, kpPos + pt + (int2)( -HALF_KERNEL, HALF_KERNEL + 1 ))
- read_imagei( sum, sampler, kpPos + pt + (int2)( HALF_KERNEL + 1, -HALF_KERNEL ))
+ read_imagei( sum, sampler, kpPos + pt + (int2)( -HALF_KERNEL, -HALF_KERNEL ))).x;
}
__kernel void extractBriefDescriptors(
__read_only image2d_t sumImg,
__global float* keypoints, int kpRowStep,
__global uchar* descriptors, int dscRowStep,
__global uchar* mask)
{
const int byte = get_local_id(0);
const int kpId = get_group_id(0);
if( !mask[kpId])
{
return;
}
const float2 kpPos = (float2)(keypoints[kpId], keypoints[kpRowStep/4 + kpId]);
if( kpPos.x < BORDER
|| kpPos.y < BORDER
|| kpPos.x >= (get_image_width( sumImg ) - BORDER)
|| kpPos.y >= (get_image_height( sumImg ) - BORDER) )
{
if( byte == 0) mask[kpId] = 0;
return;
}
uchar descByte = 0;
const int2 pt = (int2)( kpPos.x + 0.5f, kpPos.y + 0.5f );
for(int i = 0; i<8; ++i)
{
descByte |= (
smoothedSum(sumImg, pt, (int2)( tests[byte * 32 + (i * 4) + 1], tests[byte * 32 + (i * 4) + 0] ))
< smoothedSum(sumImg, pt, (int2)( tests[byte * 32 + (i * 4) + 3], tests[byte * 32 + (i * 4) + 2] ))
) << (7-i);
}
descriptors[kpId * dscRowStep + byte] = descByte;
if( byte == 0) mask[kpId] = 1;
}

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modules/ocl/test/test_brief.cpp
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/*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.
//
// @Authors
// Matthias Bady aegirxx ==> gmail.com
//
// 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 std;
using namespace cv;
using namespace ocl;
#ifdef HAVE_OPENCL
namespace
{
IMPLEMENT_PARAM_CLASS( BRIEF_Bytes, int )
}
PARAM_TEST_CASE( BRIEF, BRIEF_Bytes )
{
int bytes;
virtual void SetUp( )
{
bytes = GET_PARAM( 0 );
}
};
OCL_TEST_P( BRIEF, Accuracy )
{
Mat img = readImage( "gpu/opticalflow/rubberwhale1.png", IMREAD_GRAYSCALE );
ASSERT_TRUE( !img.empty( ) ) << "no input image";
FastFeatureDetector fast( 20 );
std::vector<KeyPoint> keypoints;
fast.detect( img, keypoints, Mat( ) );
Mat descriptorsGold;
BriefDescriptorExtractor brief( bytes );
brief.compute( img, keypoints, descriptorsGold );
Mat kpMat( 2, int( keypoints.size() ), CV_32FC1 );
for ( size_t i = 0; i < keypoints.size( ); ++i )
{
kpMat.col( i ).row( 0 ) = int( keypoints[i].pt.x );
kpMat.col( i ).row( 1 ) = int( keypoints[i].pt.y );
}
oclMat imgOcl( img ), keypointsOcl( kpMat ), descriptorsOcl, maskOcl;
BRIEF_OCL briefOcl( bytes );
briefOcl.compute( imgOcl, keypointsOcl, maskOcl, descriptorsOcl );
Mat mask, descriptors;
maskOcl.download( mask );
descriptorsOcl.download( descriptors );
const int numDesc = cv::countNonZero( mask );
if ( numDesc != descriptors.cols )
{
int idx = 0;
Mat tmp( numDesc, bytes, CV_8UC1 );
for ( int i = 0; i < descriptors.rows; ++i )
{
if ( mask.at<uchar>(i) )
{
descriptors.row( i ).copyTo( tmp.row( idx++ ) );
}
}
descriptors = tmp;
}
ASSERT_TRUE( descriptors.size( ) == descriptorsGold.size( ) ) << "Different number of descriptors";
ASSERT_TRUE( 0 == norm( descriptors, descriptorsGold, NORM_HAMMING ) ) << "Descriptors different";
}
INSTANTIATE_TEST_CASE_P( OCL_Features2D, BRIEF, testing::Values( 16, 32, 64 ) );
#endif
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