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Move OpenCL SURF to nonfree module

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This commit is contained in:
Andrey Kamaev
2013-03-16 15:47:40 +04:00
parent 91ac9688a8
commit 6846f881a2
16 changed files with 285 additions and 311 deletions
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2
modules/nonfree/CMakeLists.txt
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@@ -3,7 +3,7 @@ if(BUILD_ANDROID_PACKAGE)
endif()
set(the_description "Functionality with possible limitations on the use")
ocv_add_module(nonfree opencv_imgproc opencv_features2d opencv_calib3d OPTIONAL opencv_gpu)
ocv_add_module(nonfree opencv_imgproc opencv_features2d opencv_calib3d OPTIONAL opencv_gpu opencv_ocl)
ocv_module_include_directories()
if(HAVE_CUDA AND HAVE_opencv_gpu)

124
modules/nonfree/include/opencv2/nonfree/ocl.hpp Normal file
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@@ -0,0 +1,124 @@
/*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.
// 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.
//
//M*/
#ifndef __OPENCV_NONFREE_OCL_HPP__
#define __OPENCV_NONFREE_OCL_HPP__
#include "opencv2/ocl/ocl.hpp"
namespace cv
{
namespace ocl
{
//! Speeded up robust features, port from GPU module.
////////////////////////////////// SURF //////////////////////////////////////////
class CV_EXPORTS SURF_OCL
{
public:
enum KeypointLayout
{
X_ROW = 0,
Y_ROW,
LAPLACIAN_ROW,
OCTAVE_ROW,
SIZE_ROW,
ANGLE_ROW,
HESSIAN_ROW,
ROWS_COUNT
};
//! the default constructor
SURF_OCL();
//! the full constructor taking all the necessary parameters
explicit SURF_OCL(double _hessianThreshold, int _nOctaves = 4,
int _nOctaveLayers = 2, bool _extended = false, float _keypointsRatio = 0.01f, bool _upright = false);
//! returns the descriptor size in float's (64 or 128)
int descriptorSize() const;
//! upload host keypoints to device memory
void uploadKeypoints(const vector<cv::KeyPoint> &keypoints, oclMat &keypointsocl);
//! download keypoints from device to host memory
void downloadKeypoints(const oclMat &keypointsocl, vector<KeyPoint> &keypoints);
//! download descriptors from device to host memory
void downloadDescriptors(const oclMat &descriptorsocl, vector<float> &descriptors);
//! finds the keypoints using fast hessian detector used in SURF
//! supports CV_8UC1 images
//! keypoints will have nFeature cols and 6 rows
//! keypoints.ptr<float>(X_ROW)[i] will contain x coordinate of i'th feature
//! keypoints.ptr<float>(Y_ROW)[i] will contain y coordinate of i'th feature
//! keypoints.ptr<float>(LAPLACIAN_ROW)[i] will contain laplacian sign of i'th feature
//! keypoints.ptr<float>(OCTAVE_ROW)[i] will contain octave of i'th feature
//! keypoints.ptr<float>(SIZE_ROW)[i] will contain size of i'th feature
//! keypoints.ptr<float>(ANGLE_ROW)[i] will contain orientation of i'th feature
//! keypoints.ptr<float>(HESSIAN_ROW)[i] will contain response of i'th feature
void operator()(const oclMat &img, const oclMat &mask, oclMat &keypoints);
//! finds the keypoints and computes their descriptors.
//! Optionally it can compute descriptors for the user-provided keypoints and recompute keypoints direction
void operator()(const oclMat &img, const oclMat &mask, oclMat &keypoints, oclMat &descriptors,
bool useProvidedKeypoints = false);
void operator()(const oclMat &img, const oclMat &mask, std::vector<KeyPoint> &keypoints);
void operator()(const oclMat &img, const oclMat &mask, std::vector<KeyPoint> &keypoints, oclMat &descriptors,
bool useProvidedKeypoints = false);
void operator()(const oclMat &img, const oclMat &mask, std::vector<KeyPoint> &keypoints, std::vector<float> &descriptors,
bool useProvidedKeypoints = false);
void releaseMemory();
// SURF parameters
float hessianThreshold;
int nOctaves;
int nOctaveLayers;
bool extended;
bool upright;
//! max keypoints = min(keypointsRatio * img.size().area(), 65535)
float keypointsRatio;
oclMat sum, mask1, maskSum, intBuffer;
oclMat det, trace;
oclMat maxPosBuffer;
};
}
}
#endif __OPENCV_NONFREE_OCL_HPP__

1349
modules/nonfree/src/opencl/surf.cl Normal file
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5
modules/nonfree/src/precomp.hpp
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@@ -66,4 +66,9 @@
#endif
#endif
#ifdef HAVE_OPENCV_OCL
# include "opencv2/nonfree/ocl.hpp"
# include "opencv2/ocl/private/util.hpp"
#endif
#endif

728
modules/nonfree/src/surf.ocl.cpp Normal file
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@@ -0,0 +1,728 @@
/*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) 2010-2012, Multicoreware, Inc., all rights reserved.
// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// @Authors
// Peng Xiao, pengxiao@multicorewareinc.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 oclMaterials 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"
#ifdef HAVE_OPENCV_OCL
using namespace cv;
using namespace cv::ocl;
using namespace std;
namespace cv
{
namespace ocl
{
///////////////////////////OpenCL kernel strings///////////////////////////
extern const char *surf;
const char* noImage2dOption = "-D DISABLE_IMAGE2D";
static void openCLExecuteKernelSURF(Context *clCxt , const char **source, string kernelName, size_t globalThreads[3],
size_t localThreads[3], vector< pair<size_t, const void *> > &args, int channels, int depth)
{
if(support_image2d())
{
openCLExecuteKernel(clCxt, source, kernelName, globalThreads, localThreads, args, channels, depth);
}
else
{
openCLExecuteKernel(clCxt, source, kernelName, globalThreads, localThreads, args, channels, depth, noImage2dOption);
}
}
}
}
static inline int divUp(int total, int grain)
{
return (total + grain - 1) / grain;
}
static inline int calcSize(int octave, int layer)
{
/* Wavelet size at first layer of first octave. */
const int HAAR_SIZE0 = 9;
/* Wavelet size increment between layers. This should be an even number,
such that the wavelet sizes in an octave are either all even or all odd.
This ensures that when looking for the neighbors of a sample, the layers
above and below are aligned correctly. */
const int HAAR_SIZE_INC = 6;
return (HAAR_SIZE0 + HAAR_SIZE_INC * layer) << octave;
}
class SURF_OCL_Invoker
{
public:
// facilities
void bindImgTex(const oclMat &img, cl_mem &texture);
//void loadGlobalConstants(int maxCandidates, int maxFeatures, int img_rows, int img_cols, int nOctaveLayers, float hessianThreshold);
//void loadOctaveConstants(int octave, int layer_rows, int layer_cols);
// kernel callers declarations
void icvCalcLayerDetAndTrace_gpu(oclMat &det, oclMat &trace, int octave, int nOctaveLayers, int layer_rows);
void icvFindMaximaInLayer_gpu(const oclMat &det, const oclMat &trace, oclMat &maxPosBuffer, oclMat &maxCounter, int counterOffset,
int octave, bool use_mask, int nLayers, int layer_rows, int layer_cols);
void icvInterpolateKeypoint_gpu(const oclMat &det, const oclMat &maxPosBuffer, int maxCounter,
oclMat &keypoints, oclMat &counters, int octave, int layer_rows, int maxFeatures);
void icvCalcOrientation_gpu(const oclMat &keypoints, int nFeatures);
void icvSetUpright_gpu(const oclMat &keypoints, int nFeatures);
void compute_descriptors_gpu(const oclMat &descriptors, const oclMat &keypoints, int nFeatures);
// end of kernel callers declarations
SURF_OCL_Invoker(SURF_OCL &surf, const oclMat &img, const oclMat &mask) :
surf_(surf),
img_cols(img.cols), img_rows(img.rows),
use_mask(!mask.empty()), counters(oclMat()),
imgTex(NULL), sumTex(NULL), maskSumTex(NULL), _img(img)
{
CV_Assert(!img.empty() && img.type() == CV_8UC1);
CV_Assert(mask.empty() || (mask.size() == img.size() && mask.type() == CV_8UC1));
CV_Assert(surf_.nOctaves > 0 && surf_.nOctaveLayers > 0);
const int min_size = calcSize(surf_.nOctaves - 1, 0);
CV_Assert(img_rows - min_size >= 0);
CV_Assert(img_cols - min_size >= 0);
const int layer_rows = img_rows >> (surf_.nOctaves - 1);
const int layer_cols = img_cols >> (surf_.nOctaves - 1);
const int min_margin = ((calcSize((surf_.nOctaves - 1), 2) >> 1) >> (surf_.nOctaves - 1)) + 1;
CV_Assert(layer_rows - 2 * min_margin > 0);
CV_Assert(layer_cols - 2 * min_margin > 0);
maxFeatures = std::min(static_cast<int>(img.size().area() * surf.keypointsRatio), 65535);
maxCandidates = std::min(static_cast<int>(1.5 * maxFeatures), 65535);
CV_Assert(maxFeatures > 0);
counters.create(1, surf_.nOctaves + 1, CV_32SC1);
counters.setTo(Scalar::all(0));
integral(img, surf_.sum);
if(support_image2d())
{
bindImgTex(img, imgTex);
bindImgTex(surf_.sum, sumTex);
}
maskSumTex = 0;
if (use_mask)
{
CV_Error(CV_StsBadFunc, "Masked SURF detector is not implemented yet");
//!FIXME
// temp fix for missing min overload
//oclMat temp(mask.size(), mask.type());
//temp.setTo(Scalar::all(1.0));
////cv::ocl::min(mask, temp, surf_.mask1); ///////// disable this
//integral(surf_.mask1, surf_.maskSum);
//bindImgTex(surf_.maskSum, maskSumTex);
}
}
void detectKeypoints(oclMat &keypoints)
{
// create image pyramid buffers
// different layers have same sized buffers, but they are sampled from Gaussian kernel.
ensureSizeIsEnough(img_rows * (surf_.nOctaveLayers + 2), img_cols, CV_32FC1, surf_.det);
ensureSizeIsEnough(img_rows * (surf_.nOctaveLayers + 2), img_cols, CV_32FC1, surf_.trace);
ensureSizeIsEnough(1, maxCandidates, CV_32SC4, surf_.maxPosBuffer);
ensureSizeIsEnough(SURF_OCL::ROWS_COUNT, maxFeatures, CV_32FC1, keypoints);
keypoints.setTo(Scalar::all(0));
for (int octave = 0; octave < surf_.nOctaves; ++octave)
{
const int layer_rows = img_rows >> octave;
const int layer_cols = img_cols >> octave;
//loadOctaveConstants(octave, layer_rows, layer_cols);
icvCalcLayerDetAndTrace_gpu(surf_.det, surf_.trace, octave, surf_.nOctaveLayers, layer_rows);
icvFindMaximaInLayer_gpu(surf_.det, surf_.trace, surf_.maxPosBuffer, counters, 1 + octave,
octave, use_mask, surf_.nOctaveLayers, layer_rows, layer_cols);
int maxCounter = ((Mat)counters).at<int>(1 + octave);
maxCounter = std::min(maxCounter, static_cast<int>(maxCandidates));
if (maxCounter > 0)
{
icvInterpolateKeypoint_gpu(surf_.det, surf_.maxPosBuffer, maxCounter,
keypoints, counters, octave, layer_rows, maxFeatures);
}
}
int featureCounter = Mat(counters).at<int>(0);
featureCounter = std::min(featureCounter, static_cast<int>(maxFeatures));
keypoints.cols = featureCounter;
if (surf_.upright)
{
//keypoints.row(SURF_OCL::ANGLE_ROW).setTo(Scalar::all(90.0));
setUpright(keypoints);
}
else
{
findOrientation(keypoints);
}
}
void setUpright(oclMat &keypoints)
{
const int nFeatures = keypoints.cols;
if(nFeatures > 0)
{
icvSetUpright_gpu(keypoints, keypoints.cols);
}
}
void findOrientation(oclMat &keypoints)
{
const int nFeatures = keypoints.cols;
if (nFeatures > 0)
{
icvCalcOrientation_gpu(keypoints, nFeatures);
}
}
void computeDescriptors(const oclMat &keypoints, oclMat &descriptors, int descriptorSize)
{
const int nFeatures = keypoints.cols;
if (nFeatures > 0)
{
ensureSizeIsEnough(nFeatures, descriptorSize, CV_32F, descriptors);
compute_descriptors_gpu(descriptors, keypoints, nFeatures);
}
}
~SURF_OCL_Invoker()
{
if(imgTex)
openCLFree(imgTex);
if(sumTex)
openCLFree(sumTex);
if(maskSumTex)
openCLFree(maskSumTex);
}
private:
SURF_OCL &surf_;
int img_cols, img_rows;
bool use_mask;
int maxCandidates;
int maxFeatures;
oclMat counters;
// texture buffers
cl_mem imgTex;
cl_mem sumTex;
cl_mem maskSumTex;
const oclMat _img; // make a copy for non-image2d_t supported platform
SURF_OCL_Invoker &operator= (const SURF_OCL_Invoker &right)
{
(*this) = right;
return *this;
} // remove warning C4512
};
cv::ocl::SURF_OCL::SURF_OCL()
{
hessianThreshold = 100.0f;
extended = true;
nOctaves = 4;
nOctaveLayers = 2;
keypointsRatio = 0.01f;
upright = false;
}
cv::ocl::SURF_OCL::SURF_OCL(double _threshold, int _nOctaves, int _nOctaveLayers, bool _extended, float _keypointsRatio, bool _upright)
{
hessianThreshold = saturate_cast<float>(_threshold);
extended = _extended;
nOctaves = _nOctaves;
nOctaveLayers = _nOctaveLayers;
keypointsRatio = _keypointsRatio;
upright = _upright;
}
int cv::ocl::SURF_OCL::descriptorSize() const
{
return extended ? 128 : 64;
}
void cv::ocl::SURF_OCL::uploadKeypoints(const vector<KeyPoint> &keypoints, oclMat &keypointsGPU)
{
if (keypoints.empty())
keypointsGPU.release();
else
{
Mat keypointsCPU(SURF_OCL::ROWS_COUNT, static_cast<int>(keypoints.size()), CV_32FC1);
float *kp_x = keypointsCPU.ptr<float>(SURF_OCL::X_ROW);
float *kp_y = keypointsCPU.ptr<float>(SURF_OCL::Y_ROW);
int *kp_laplacian = keypointsCPU.ptr<int>(SURF_OCL::LAPLACIAN_ROW);
int *kp_octave = keypointsCPU.ptr<int>(SURF_OCL::OCTAVE_ROW);
float *kp_size = keypointsCPU.ptr<float>(SURF_OCL::SIZE_ROW);
float *kp_dir = keypointsCPU.ptr<float>(SURF_OCL::ANGLE_ROW);
float *kp_hessian = keypointsCPU.ptr<float>(SURF_OCL::HESSIAN_ROW);
for (size_t i = 0, size = keypoints.size(); i < size; ++i)
{
const KeyPoint &kp = keypoints[i];
kp_x[i] = kp.pt.x;
kp_y[i] = kp.pt.y;
kp_octave[i] = kp.octave;
kp_size[i] = kp.size;
kp_dir[i] = kp.angle;
kp_hessian[i] = kp.response;
kp_laplacian[i] = 1;
}
keypointsGPU.upload(keypointsCPU);
}
}
void cv::ocl::SURF_OCL::downloadKeypoints(const oclMat &keypointsGPU, vector<KeyPoint> &keypoints)
{
const int nFeatures = keypointsGPU.cols;
if (nFeatures == 0)
keypoints.clear();
else
{
CV_Assert(keypointsGPU.type() == CV_32FC1 && keypointsGPU.rows == ROWS_COUNT);
Mat keypointsCPU(keypointsGPU);
keypoints.resize(nFeatures);
float *kp_x = keypointsCPU.ptr<float>(SURF_OCL::X_ROW);
float *kp_y = keypointsCPU.ptr<float>(SURF_OCL::Y_ROW);
int *kp_laplacian = keypointsCPU.ptr<int>(SURF_OCL::LAPLACIAN_ROW);
int *kp_octave = keypointsCPU.ptr<int>(SURF_OCL::OCTAVE_ROW);
float *kp_size = keypointsCPU.ptr<float>(SURF_OCL::SIZE_ROW);
float *kp_dir = keypointsCPU.ptr<float>(SURF_OCL::ANGLE_ROW);
float *kp_hessian = keypointsCPU.ptr<float>(SURF_OCL::HESSIAN_ROW);
for (int i = 0; i < nFeatures; ++i)
{
KeyPoint &kp = keypoints[i];
kp.pt.x = kp_x[i];
kp.pt.y = kp_y[i];
kp.class_id = kp_laplacian[i];
kp.octave = kp_octave[i];
kp.size = kp_size[i];
kp.angle = kp_dir[i];
kp.response = kp_hessian[i];
}
}
}
void cv::ocl::SURF_OCL::downloadDescriptors(const oclMat &descriptorsGPU, vector<float> &descriptors)
{
if (descriptorsGPU.empty())
descriptors.clear();
else
{
CV_Assert(descriptorsGPU.type() == CV_32F);
descriptors.resize(descriptorsGPU.rows * descriptorsGPU.cols);
Mat descriptorsCPU(descriptorsGPU.size(), CV_32F, &descriptors[0]);
descriptorsGPU.download(descriptorsCPU);
}
}
void cv::ocl::SURF_OCL::operator()(const oclMat &img, const oclMat &mask, oclMat &keypoints)
{
if (!img.empty())
{
SURF_OCL_Invoker surf(*this, img, mask);
surf.detectKeypoints(keypoints);
}
}
void cv::ocl::SURF_OCL::operator()(const oclMat &img, const oclMat &mask, oclMat &keypoints, oclMat &descriptors,
bool useProvidedKeypoints)
{
if (!img.empty())
{
SURF_OCL_Invoker surf(*this, img, mask);
if (!useProvidedKeypoints)
surf.detectKeypoints(keypoints);
else if (!upright)
{
surf.findOrientation(keypoints);
}
surf.computeDescriptors(keypoints, descriptors, descriptorSize());
}
}
void cv::ocl::SURF_OCL::operator()(const oclMat &img, const oclMat &mask, vector<KeyPoint> &keypoints)
{
oclMat keypointsGPU;
(*this)(img, mask, keypointsGPU);
downloadKeypoints(keypointsGPU, keypoints);
}
void cv::ocl::SURF_OCL::operator()(const oclMat &img, const oclMat &mask, vector<KeyPoint> &keypoints,
oclMat &descriptors, bool useProvidedKeypoints)
{
oclMat keypointsGPU;
if (useProvidedKeypoints)
uploadKeypoints(keypoints, keypointsGPU);
(*this)(img, mask, keypointsGPU, descriptors, useProvidedKeypoints);
downloadKeypoints(keypointsGPU, keypoints);
}
void cv::ocl::SURF_OCL::operator()(const oclMat &img, const oclMat &mask, vector<KeyPoint> &keypoints,
vector<float> &descriptors, bool useProvidedKeypoints)
{
oclMat descriptorsGPU;
(*this)(img, mask, keypoints, descriptorsGPU, useProvidedKeypoints);
downloadDescriptors(descriptorsGPU, descriptors);
}
void cv::ocl::SURF_OCL::releaseMemory()
{
sum.release();
mask1.release();
maskSum.release();
intBuffer.release();
det.release();
trace.release();
maxPosBuffer.release();
}
// bind source buffer to image oject.
void SURF_OCL_Invoker::bindImgTex(const oclMat &img, cl_mem &texture)
{
if(texture)
{
openCLFree(texture);
}
texture = bindTexture(img);
}
////////////////////////////
// kernel caller definitions
void SURF_OCL_Invoker::icvCalcLayerDetAndTrace_gpu(oclMat &det, oclMat &trace, int octave, int nOctaveLayers, int c_layer_rows)
{
const int min_size = calcSize(octave, 0);
const int max_samples_i = 1 + ((img_rows - min_size) >> octave);
const int max_samples_j = 1 + ((img_cols - min_size) >> octave);
Context *clCxt = det.clCxt;
string kernelName = "icvCalcLayerDetAndTrace";
vector< pair<size_t, const void *> > args;
if(sumTex)
{
args.push_back( make_pair( sizeof(cl_mem), (void *)&sumTex));
}
else
{
args.push_back( make_pair( sizeof(cl_mem), (void *)&surf_.sum.data)); // if image2d is not supported
}
args.push_back( make_pair( sizeof(cl_mem), (void *)&det.data));
args.push_back( make_pair( sizeof(cl_mem), (void *)&trace.data));
args.push_back( make_pair( sizeof(cl_int), (void *)&det.step));
args.push_back( make_pair( sizeof(cl_int), (void *)&trace.step));
args.push_back( make_pair( sizeof(cl_int), (void *)&img_rows));
args.push_back( make_pair( sizeof(cl_int), (void *)&img_cols));
args.push_back( make_pair( sizeof(cl_int), (void *)&nOctaveLayers));
args.push_back( make_pair( sizeof(cl_int), (void *)&octave));
args.push_back( make_pair( sizeof(cl_int), (void *)&c_layer_rows));
args.push_back( make_pair( sizeof(cl_int), (void *)&surf_.sum.step));
size_t localThreads[3] = {16, 16, 1};
size_t globalThreads[3] =
{
divUp(max_samples_j, localThreads[0]) *localThreads[0],
divUp(max_samples_i, localThreads[1]) *localThreads[1] *(nOctaveLayers + 2),
1
};
openCLExecuteKernelSURF(clCxt, &surf, kernelName, globalThreads, localThreads, args, -1, -1);
}
void SURF_OCL_Invoker::icvFindMaximaInLayer_gpu(const oclMat &det, const oclMat &trace, oclMat &maxPosBuffer, oclMat &maxCounter, int counterOffset,
int octave, bool use_mask, int nLayers, int layer_rows, int layer_cols)
{
const int min_margin = ((calcSize(octave, 2) >> 1) >> octave) + 1;
Context *clCxt = det.clCxt;
string kernelName = use_mask ? "icvFindMaximaInLayer_withmask" : "icvFindMaximaInLayer";
vector< pair<size_t, const void *> > args;
args.push_back( make_pair( sizeof(cl_mem), (void *)&det.data));
args.push_back( make_pair( sizeof(cl_mem), (void *)&trace.data));
args.push_back( make_pair( sizeof(cl_mem), (void *)&maxPosBuffer.data));
args.push_back( make_pair( sizeof(cl_mem), (void *)&maxCounter.data));
args.push_back( make_pair( sizeof(cl_int), (void *)&counterOffset));
args.push_back( make_pair( sizeof(cl_int), (void *)&det.step));
args.push_back( make_pair( sizeof(cl_int), (void *)&trace.step));
args.push_back( make_pair( sizeof(cl_int), (void *)&img_rows));
args.push_back( make_pair( sizeof(cl_int), (void *)&img_cols));
args.push_back( make_pair( sizeof(cl_int), (void *)&nLayers));
args.push_back( make_pair( sizeof(cl_int), (void *)&octave));
args.push_back( make_pair( sizeof(cl_int), (void *)&layer_rows));
args.push_back( make_pair( sizeof(cl_int), (void *)&layer_cols));
args.push_back( make_pair( sizeof(cl_int), (void *)&maxCandidates));
args.push_back( make_pair( sizeof(cl_float), (void *)&surf_.hessianThreshold));
if(use_mask)
{
if(maskSumTex)
{
args.push_back( make_pair( sizeof(cl_mem), (void *)&maskSumTex));
}
else
{
args.push_back( make_pair( sizeof(cl_mem), (void *)&surf_.maskSum.data));
}
args.push_back( make_pair( sizeof(cl_mem), (void *)&surf_.maskSum.step));
}
size_t localThreads[3] = {16, 16, 1};
size_t globalThreads[3] = {divUp(layer_cols - 2 * min_margin, localThreads[0] - 2) *localThreads[0],
divUp(layer_rows - 2 * min_margin, localThreads[1] - 2) *nLayers *localThreads[1],
1
};
openCLExecuteKernelSURF(clCxt, &surf, kernelName, globalThreads, localThreads, args, -1, -1);
}
void SURF_OCL_Invoker::icvInterpolateKeypoint_gpu(const oclMat &det, const oclMat &maxPosBuffer, int maxCounter,
oclMat &keypoints, oclMat &counters, int octave, int layer_rows, int maxFeatures)
{
Context *clCxt = det.clCxt;
string kernelName = "icvInterpolateKeypoint";
vector< pair<size_t, const void *> > args;
args.push_back( make_pair( sizeof(cl_mem), (void *)&det.data));
args.push_back( make_pair( sizeof(cl_mem), (void *)&maxPosBuffer.data));
args.push_back( make_pair( sizeof(cl_mem), (void *)&keypoints.data));
args.push_back( make_pair( sizeof(cl_mem), (void *)&counters.data));
args.push_back( make_pair( sizeof(cl_int), (void *)&det.step));
args.push_back( make_pair( sizeof(cl_int), (void *)&keypoints.step));
args.push_back( make_pair( sizeof(cl_int), (void *)&img_rows));
args.push_back( make_pair( sizeof(cl_int), (void *)&img_cols));
args.push_back( make_pair( sizeof(cl_int), (void *)&octave));
args.push_back( make_pair( sizeof(cl_int), (void *)&layer_rows));
args.push_back( make_pair( sizeof(cl_int), (void *)&maxFeatures));
size_t localThreads[3] = {3, 3, 3};
size_t globalThreads[3] = {maxCounter *localThreads[0], localThreads[1], 1};
openCLExecuteKernelSURF(clCxt, &surf, kernelName, globalThreads, localThreads, args, -1, -1);
}
void SURF_OCL_Invoker::icvCalcOrientation_gpu(const oclMat &keypoints, int nFeatures)
{
Context *clCxt = counters.clCxt;
string kernelName = "icvCalcOrientation";
vector< pair<size_t, const void *> > args;
if(sumTex)
{
args.push_back( make_pair( sizeof(cl_mem), (void *)&sumTex));
}
else
{
args.push_back( make_pair( sizeof(cl_mem), (void *)&surf_.sum.data)); // if image2d is not supported
}
args.push_back( make_pair( sizeof(cl_mem), (void *)&keypoints.data));
args.push_back( make_pair( sizeof(cl_int), (void *)&keypoints.step));
args.push_back( make_pair( sizeof(cl_int), (void *)&img_rows));
args.push_back( make_pair( sizeof(cl_int), (void *)&img_cols));
args.push_back( make_pair( sizeof(cl_int), (void *)&surf_.sum.step));
size_t localThreads[3] = {32, 4, 1};
size_t globalThreads[3] = {nFeatures *localThreads[0], localThreads[1], 1};
openCLExecuteKernelSURF(clCxt, &surf, kernelName, globalThreads, localThreads, args, -1, -1);
}
void SURF_OCL_Invoker::icvSetUpright_gpu(const oclMat &keypoints, int nFeatures)
{
Context *clCxt = counters.clCxt;
string kernelName = "icvSetUpright";
vector< pair<size_t, const void *> > args;
args.push_back( make_pair( sizeof(cl_mem), (void *)&keypoints.data));
args.push_back( make_pair( sizeof(cl_int), (void *)&keypoints.step));
args.push_back( make_pair( sizeof(cl_int), (void *)&nFeatures));
size_t localThreads[3] = {256, 1, 1};
size_t globalThreads[3] = {saturate_cast<size_t>(nFeatures), 1, 1};
openCLExecuteKernelSURF(clCxt, &surf, kernelName, globalThreads, localThreads, args, -1, -1);
}
void SURF_OCL_Invoker::compute_descriptors_gpu(const oclMat &descriptors, const oclMat &keypoints, int nFeatures)
{
// compute unnormalized descriptors, then normalize them - odd indexing since grid must be 2D
Context *clCxt = descriptors.clCxt;
string kernelName = "";
vector< pair<size_t, const void *> > args;
size_t localThreads[3] = {1, 1, 1};
size_t globalThreads[3] = {1, 1, 1};
if(descriptors.cols == 64)
{
kernelName = "compute_descriptors64";
localThreads[0] = 6;
localThreads[1] = 6;
globalThreads[0] = nFeatures * localThreads[0];
globalThreads[1] = 16 * localThreads[1];
args.clear();
if(imgTex)
{
args.push_back( make_pair( sizeof(cl_mem), (void *)&imgTex));
}
else
{
args.push_back( make_pair( sizeof(cl_mem), (void *)&_img.data));
}
args.push_back( make_pair( sizeof(cl_mem), (void *)&descriptors.data));
args.push_back( make_pair( sizeof(cl_mem), (void *)&keypoints.data));
args.push_back( make_pair( sizeof(cl_int), (void *)&descriptors.step));
args.push_back( make_pair( sizeof(cl_int), (void *)&keypoints.step));
args.push_back( make_pair( sizeof(cl_int), (void *)&_img.rows));
args.push_back( make_pair( sizeof(cl_int), (void *)&_img.cols));
args.push_back( make_pair( sizeof(cl_int), (void *)&_img.step));
openCLExecuteKernelSURF(clCxt, &surf, kernelName, globalThreads, localThreads, args, -1, -1);
kernelName = "normalize_descriptors64";
localThreads[0] = 64;
localThreads[1] = 1;
globalThreads[0] = nFeatures * localThreads[0];
globalThreads[1] = localThreads[1];
args.clear();
args.push_back( make_pair( sizeof(cl_mem), (void *)&descriptors.data));
args.push_back( make_pair( sizeof(cl_int), (void *)&descriptors.step));
openCLExecuteKernelSURF(clCxt, &surf, kernelName, globalThreads, localThreads, args, -1, -1);
}
else
{
kernelName = "compute_descriptors128";
localThreads[0] = 6;
localThreads[1] = 6;
globalThreads[0] = nFeatures * localThreads[0];
globalThreads[1] = 16 * localThreads[1];
args.clear();
if(imgTex)
{
args.push_back( make_pair( sizeof(cl_mem), (void *)&imgTex));
}
else
{
args.push_back( make_pair( sizeof(cl_mem), (void *)&_img.data));
}
args.push_back( make_pair( sizeof(cl_mem), (void *)&descriptors.data));
args.push_back( make_pair( sizeof(cl_mem), (void *)&keypoints.data));
args.push_back( make_pair( sizeof(cl_int), (void *)&descriptors.step));
args.push_back( make_pair( sizeof(cl_int), (void *)&keypoints.step));
args.push_back( make_pair( sizeof(cl_int), (void *)&_img.rows));
args.push_back( make_pair( sizeof(cl_int), (void *)&_img.cols));
args.push_back( make_pair( sizeof(cl_int), (void *)&_img.step));
openCLExecuteKernelSURF(clCxt, &surf, kernelName, globalThreads, localThreads, args, -1, -1);
kernelName = "normalize_descriptors128";
localThreads[0] = 128;
localThreads[1] = 1;
globalThreads[0] = nFeatures * localThreads[0];
globalThreads[1] = localThreads[1];
args.clear();
args.push_back( make_pair( sizeof(cl_mem), (void *)&descriptors.data));
args.push_back( make_pair( sizeof(cl_int), (void *)&descriptors.step));
openCLExecuteKernelSURF(clCxt, &surf, kernelName, globalThreads, localThreads, args, -1, -1);
}
}
#endif //HAVE_OPENCV_OCL