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opencv/modules/ocl/src/pyrlk.cpp
Andrey Kamaev 877dfae044 Fix build of ocl module
2013-03-22 22:14:57 +04:00

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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) 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
// Dachuan Zhao, dachuan@multicorewareinc.com
// Yao Wang, yao@multicorewareinc.com
// Nathan, liujun@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"
using namespace cv;
using namespace cv::ocl;
namespace cv
{
namespace ocl
{
///////////////////////////OpenCL kernel strings///////////////////////////
extern const char *pyrlk;
extern const char *pyrlk_no_image;
extern const char *operator_setTo;
extern const char *operator_convertTo;
extern const char *operator_copyToM;
extern const char *arithm_mul;
extern const char *pyr_down;
}
}
struct dim3
{
unsigned int x, y, z;
};
struct float2
{
float x, y;
};
struct int2
{
int x, y;
};
namespace
{
void calcPatchSize(cv::Size winSize, int cn, dim3 &block, dim3 &patch, bool isDeviceArch11)
{
winSize.width *= cn;
if (winSize.width > 32 && winSize.width > 2 * winSize.height)
{
block.x = isDeviceArch11 ? 16 : 32;
block.y = 8;
}
else
{
block.x = 16;
block.y = isDeviceArch11 ? 8 : 16;
}
patch.x = (winSize.width + block.x - 1) / block.x;
patch.y = (winSize.height + block.y - 1) / block.y;
block.z = patch.z = 1;
}
}
inline int divUp(int total, int grain)
{
return (total + grain - 1) / grain;
}
///////////////////////////////////////////////////////////////////////////
//////////////////////////////// ConvertTo ////////////////////////////////
///////////////////////////////////////////////////////////////////////////
static void convert_run_cus(const oclMat &src, oclMat &dst, double alpha, double beta)
{
String kernelName = "convert_to_S";
std::stringstream idxStr;
idxStr << src.depth();
kernelName = kernelName + idxStr.str().c_str();
float alpha_f = (float)alpha, beta_f = (float)beta;
CV_DbgAssert(src.rows == dst.rows && src.cols == dst.cols);
std::vector<std::pair<size_t , const void *> > args;
size_t localThreads[3] = {16, 16, 1};
size_t globalThreads[3];
globalThreads[0] = (dst.cols + localThreads[0] - 1) / localThreads[0] * localThreads[0];
globalThreads[1] = (dst.rows + localThreads[1] - 1) / localThreads[1] * localThreads[1];
globalThreads[2] = 1;
int dststep_in_pixel = dst.step / dst.elemSize(), dstoffset_in_pixel = dst.offset / dst.elemSize();
int srcstep_in_pixel = src.step / src.elemSize(), srcoffset_in_pixel = src.offset / src.elemSize();
if(dst.type() == CV_8UC1)
{
globalThreads[0] = ((dst.cols + 4) / 4 + localThreads[0]) / localThreads[0] * localThreads[0];
}
args.push_back( std::make_pair( sizeof(cl_mem) , (void *)&src.data ));
args.push_back( std::make_pair( sizeof(cl_mem) , (void *)&dst.data ));
args.push_back( std::make_pair( sizeof(cl_int) , (void *)&src.cols ));
args.push_back( std::make_pair( sizeof(cl_int) , (void *)&src.rows ));
args.push_back( std::make_pair( sizeof(cl_int) , (void *)&srcstep_in_pixel ));
args.push_back( std::make_pair( sizeof(cl_int) , (void *)&srcoffset_in_pixel ));
args.push_back( std::make_pair( sizeof(cl_int) , (void *)&dststep_in_pixel ));
args.push_back( std::make_pair( sizeof(cl_int) , (void *)&dstoffset_in_pixel ));
args.push_back( std::make_pair( sizeof(cl_float) , (void *)&alpha_f ));
args.push_back( std::make_pair( sizeof(cl_float) , (void *)&beta_f ));
openCLExecuteKernel2(dst.clCxt , &operator_convertTo, kernelName, globalThreads,
localThreads, args, dst.oclchannels(), dst.depth(), CLFLUSH);
}
void convertTo( const oclMat &src, oclMat &m, int rtype, double alpha = 1, double beta = 0 );
void convertTo( const oclMat &src, oclMat &dst, int rtype, double alpha, double beta )
{
//cout << "cv::ocl::oclMat::convertTo()" << endl;
bool noScale = fabs(alpha - 1) < std::numeric_limits<double>::epsilon()
&& fabs(beta) < std::numeric_limits<double>::epsilon();
if( rtype < 0 )
rtype = src.type();
else
rtype = CV_MAKETYPE(CV_MAT_DEPTH(rtype), src.oclchannels());
int sdepth = src.depth(), ddepth = CV_MAT_DEPTH(rtype);
if( sdepth == ddepth && noScale )
{
src.copyTo(dst);
return;
}
oclMat temp;
const oclMat *psrc = &src;
if( sdepth != ddepth && psrc == &dst )
psrc = &(temp = src);
dst.create( src.size(), rtype );
convert_run_cus(*psrc, dst, alpha, beta);
}
///////////////////////////////////////////////////////////////////////////
//////////////////////////////// setTo ////////////////////////////////////
///////////////////////////////////////////////////////////////////////////
//oclMat &operator = (const Scalar &s)
//{
// //cout << "cv::ocl::oclMat::=" << endl;
// setTo(s);
// return *this;
//}
static void set_to_withoutmask_run_cus(const oclMat &dst, const Scalar &scalar, String kernelName)
{
std::vector<std::pair<size_t , const void *> > args;
size_t localThreads[3] = {16, 16, 1};
size_t globalThreads[3];
globalThreads[0] = (dst.cols + localThreads[0] - 1) / localThreads[0] * localThreads[0];
globalThreads[1] = (dst.rows + localThreads[1] - 1) / localThreads[1] * localThreads[1];
globalThreads[2] = 1;
int step_in_pixel = dst.step / dst.elemSize(), offset_in_pixel = dst.offset / dst.elemSize();
if(dst.type() == CV_8UC1)
{
globalThreads[0] = ((dst.cols + 4) / 4 + localThreads[0] - 1) / localThreads[0] * localThreads[0];
}
char compile_option[32];
union sc
{
cl_uchar4 uval;
cl_char4 cval;
cl_ushort4 usval;
cl_short4 shval;
cl_int4 ival;
cl_float4 fval;
cl_double4 dval;
} val;
switch(dst.depth())
{
case 0:
val.uval.s[0] = saturate_cast<uchar>(scalar.val[0]);
val.uval.s[1] = saturate_cast<uchar>(scalar.val[1]);
val.uval.s[2] = saturate_cast<uchar>(scalar.val[2]);
val.uval.s[3] = saturate_cast<uchar>(scalar.val[3]);
switch(dst.oclchannels())
{
case 1:
sprintf(compile_option, "-D GENTYPE=uchar");
args.push_back( std::make_pair( sizeof(cl_uchar) , (void *)&val.uval.s[0] ));
break;
case 4:
sprintf(compile_option, "-D GENTYPE=uchar4");
args.push_back( std::make_pair( sizeof(cl_uchar4) , (void *)&val.uval ));
break;
default:
CV_Error(CV_StsUnsupportedFormat, "unsupported channels");
}
break;
case 1:
val.cval.s[0] = saturate_cast<char>(scalar.val[0]);
val.cval.s[1] = saturate_cast<char>(scalar.val[1]);
val.cval.s[2] = saturate_cast<char>(scalar.val[2]);
val.cval.s[3] = saturate_cast<char>(scalar.val[3]);
switch(dst.oclchannels())
{
case 1:
sprintf(compile_option, "-D GENTYPE=char");
args.push_back( std::make_pair( sizeof(cl_char) , (void *)&val.cval.s[0] ));
break;
case 4:
sprintf(compile_option, "-D GENTYPE=char4");
args.push_back( std::make_pair( sizeof(cl_char4) , (void *)&val.cval ));
break;
default:
CV_Error(CV_StsUnsupportedFormat, "unsupported channels");
}
break;
case 2:
val.usval.s[0] = saturate_cast<ushort>(scalar.val[0]);
val.usval.s[1] = saturate_cast<ushort>(scalar.val[1]);
val.usval.s[2] = saturate_cast<ushort>(scalar.val[2]);
val.usval.s[3] = saturate_cast<ushort>(scalar.val[3]);
switch(dst.oclchannels())
{
case 1:
sprintf(compile_option, "-D GENTYPE=ushort");
args.push_back( std::make_pair( sizeof(cl_ushort) , (void *)&val.usval.s[0] ));
break;
case 4:
sprintf(compile_option, "-D GENTYPE=ushort4");
args.push_back( std::make_pair( sizeof(cl_ushort4) , (void *)&val.usval ));
break;
default:
CV_Error(CV_StsUnsupportedFormat, "unsupported channels");
}
break;
case 3:
val.shval.s[0] = saturate_cast<short>(scalar.val[0]);
val.shval.s[1] = saturate_cast<short>(scalar.val[1]);
val.shval.s[2] = saturate_cast<short>(scalar.val[2]);
val.shval.s[3] = saturate_cast<short>(scalar.val[3]);
switch(dst.oclchannels())
{
case 1:
sprintf(compile_option, "-D GENTYPE=short");
args.push_back( std::make_pair( sizeof(cl_short) , (void *)&val.shval.s[0] ));
break;
case 4:
sprintf(compile_option, "-D GENTYPE=short4");
args.push_back( std::make_pair( sizeof(cl_short4) , (void *)&val.shval ));
break;
default:
CV_Error(CV_StsUnsupportedFormat, "unsupported channels");
}
break;
case 4:
val.ival.s[0] = saturate_cast<int>(scalar.val[0]);
val.ival.s[1] = saturate_cast<int>(scalar.val[1]);
val.ival.s[2] = saturate_cast<int>(scalar.val[2]);
val.ival.s[3] = saturate_cast<int>(scalar.val[3]);
switch(dst.oclchannels())
{
case 1:
sprintf(compile_option, "-D GENTYPE=int");
args.push_back( std::make_pair( sizeof(cl_int) , (void *)&val.ival.s[0] ));
break;
case 2:
sprintf(compile_option, "-D GENTYPE=int2");
cl_int2 i2val;
i2val.s[0] = val.ival.s[0];
i2val.s[1] = val.ival.s[1];
args.push_back( std::make_pair( sizeof(cl_int2) , (void *)&i2val ));
break;
case 4:
sprintf(compile_option, "-D GENTYPE=int4");
args.push_back( std::make_pair( sizeof(cl_int4) , (void *)&val.ival ));
break;
default:
CV_Error(CV_StsUnsupportedFormat, "unsupported channels");
}
break;
case 5:
val.fval.s[0] = (float)scalar.val[0];
val.fval.s[1] = (float)scalar.val[1];
val.fval.s[2] = (float)scalar.val[2];
val.fval.s[3] = (float)scalar.val[3];
switch(dst.oclchannels())
{
case 1:
sprintf(compile_option, "-D GENTYPE=float");
args.push_back( std::make_pair( sizeof(cl_float) , (void *)&val.fval.s[0] ));
break;
case 4:
sprintf(compile_option, "-D GENTYPE=float4");
args.push_back( std::make_pair( sizeof(cl_float4) , (void *)&val.fval ));
break;
default:
CV_Error(CV_StsUnsupportedFormat, "unsupported channels");
}
break;
case 6:
val.dval.s[0] = scalar.val[0];
val.dval.s[1] = scalar.val[1];
val.dval.s[2] = scalar.val[2];
val.dval.s[3] = scalar.val[3];
switch(dst.oclchannels())
{
case 1:
sprintf(compile_option, "-D GENTYPE=double");
args.push_back( std::make_pair( sizeof(cl_double) , (void *)&val.dval.s[0] ));
break;
case 4:
sprintf(compile_option, "-D GENTYPE=double4");
args.push_back( std::make_pair( sizeof(cl_double4) , (void *)&val.dval ));
break;
default:
CV_Error(CV_StsUnsupportedFormat, "unsupported channels");
}
break;
default:
CV_Error(CV_StsUnsupportedFormat, "unknown depth");
}
#ifdef CL_VERSION_1_2
if(dst.offset == 0 && dst.cols == dst.wholecols)
{
clEnqueueFillBuffer((cl_command_queue)dst.clCxt->oclCommandQueue(), (cl_mem)dst.data, args[0].second, args[0].first, 0, dst.step * dst.rows, 0, NULL, NULL);
}
else
{
args.push_back( std::make_pair( sizeof(cl_mem) , (void *)&dst.data ));
args.push_back( std::make_pair( sizeof(cl_int) , (void *)&dst.cols ));
args.push_back( std::make_pair( sizeof(cl_int) , (void *)&dst.rows ));
args.push_back( std::make_pair( sizeof(cl_int) , (void *)&step_in_pixel ));
args.push_back( std::make_pair( sizeof(cl_int) , (void *)&offset_in_pixel));
openCLExecuteKernel2(dst.clCxt , &operator_setTo, kernelName, globalThreads,
localThreads, args, -1, -1, compile_option, CLFLUSH);
}
#else
args.push_back( std::make_pair( sizeof(cl_mem) , (void *)&dst.data ));
args.push_back( std::make_pair( sizeof(cl_int) , (void *)&dst.cols ));
args.push_back( std::make_pair( sizeof(cl_int) , (void *)&dst.rows ));
args.push_back( std::make_pair( sizeof(cl_int) , (void *)&step_in_pixel ));
args.push_back( std::make_pair( sizeof(cl_int) , (void *)&offset_in_pixel));
openCLExecuteKernel2(dst.clCxt , &operator_setTo, kernelName, globalThreads,
localThreads, args, -1, -1, compile_option, CLFLUSH);
#endif
}
static oclMat &setTo(oclMat &src, const Scalar &scalar)
{
CV_Assert( src.depth() >= 0 && src.depth() <= 6 );
CV_DbgAssert( !src.empty());
if(src.type() == CV_8UC1)
{
set_to_withoutmask_run_cus(src, scalar, "set_to_without_mask_C1_D0");
}
else
{
set_to_withoutmask_run_cus(src, scalar, "set_to_without_mask");
}
return src;
}
///////////////////////////////////////////////////////////////////////////
////////////////////////////////// CopyTo /////////////////////////////////
///////////////////////////////////////////////////////////////////////////
// static void copy_to_with_mask_cus(const oclMat &src, oclMat &dst, const oclMat &mask, String kernelName)
// {
// CV_DbgAssert( dst.rows == mask.rows && dst.cols == mask.cols &&
// src.rows == dst.rows && src.cols == dst.cols
// && mask.type() == CV_8UC1);
// std::vector<std::pair<size_t , const void *> > args;
// String string_types[4][7] = {{"uchar", "char", "ushort", "short", "int", "float", "double"},
// {"uchar2", "char2", "ushort2", "short2", "int2", "float2", "double2"},
// {"uchar3", "char3", "ushort3", "short3", "int3", "float3", "double3"},
// {"uchar4", "char4", "ushort4", "short4", "int4", "float4", "double4"}
// };
// char compile_option[32];
// sprintf(compile_option, "-D GENTYPE=%s", string_types[dst.oclchannels() - 1][dst.depth()].c_str());
// size_t localThreads[3] = {16, 16, 1};
// size_t globalThreads[3];
// globalThreads[0] = divUp(dst.cols, localThreads[0]) * localThreads[0];
// globalThreads[1] = divUp(dst.rows, localThreads[1]) * localThreads[1];
// globalThreads[2] = 1;
// int dststep_in_pixel = dst.step / dst.elemSize(), dstoffset_in_pixel = dst.offset / dst.elemSize();
// int srcstep_in_pixel = src.step / src.elemSize(), srcoffset_in_pixel = src.offset / src.elemSize();
// args.push_back( std::make_pair( sizeof(cl_mem) , (void *)&src.data ));
// args.push_back( std::make_pair( sizeof(cl_mem) , (void *)&dst.data ));
// args.push_back( std::make_pair( sizeof(cl_mem) , (void *)&mask.data ));
// args.push_back( std::make_pair( sizeof(cl_int) , (void *)&src.cols ));
// args.push_back( std::make_pair( sizeof(cl_int) , (void *)&src.rows ));
// args.push_back( std::make_pair( sizeof(cl_int) , (void *)&srcstep_in_pixel ));
// args.push_back( std::make_pair( sizeof(cl_int) , (void *)&srcoffset_in_pixel ));
// args.push_back( std::make_pair( sizeof(cl_int) , (void *)&dststep_in_pixel ));
// args.push_back( std::make_pair( sizeof(cl_int) , (void *)&dstoffset_in_pixel ));
// args.push_back( std::make_pair( sizeof(cl_int) , (void *)&mask.step ));
// args.push_back( std::make_pair( sizeof(cl_int) , (void *)&mask.offset ));
// openCLExecuteKernel2(dst.clCxt , &operator_copyToM, kernelName, globalThreads,
// localThreads, args, -1, -1, compile_option, CLFLUSH);
// }
static void copyTo(const oclMat &src, oclMat &m )
{
CV_DbgAssert(!src.empty());
m.create(src.size(), src.type());
openCLCopyBuffer2D(src.clCxt, m.data, m.step, m.offset,
src.data, src.step, src.cols * src.elemSize(), src.rows, src.offset);
}
// static void copyTo(const oclMat &src, oclMat &mat, const oclMat &mask)
// {
// if (mask.empty())
// {
// copyTo(src, mat);
// }
// else
// {
// mat.create(src.size(), src.type());
// copy_to_with_mask_cus(src, mat, mask, "copy_to_with_mask");
// }
// }
static void arithmetic_run(const oclMat &src1, oclMat &dst, String kernelName, const char **kernelString, void *_scalar)
{
if(!src1.clCxt->supportsFeature(Context::CL_DOUBLE) && src1.type() == CV_64F)
{
CV_Error(CV_GpuNotSupported, "Selected device don't support double\r\n");
return;
}
//dst.create(src1.size(), src1.type());
//CV_Assert(src1.cols == src2.cols && src2.cols == dst.cols &&
// src1.rows == src2.rows && src2.rows == dst.rows);
CV_Assert(src1.cols == dst.cols &&
src1.rows == dst.rows);
CV_Assert(src1.type() == dst.type());
CV_Assert(src1.depth() != CV_8S);
Context *clCxt = src1.clCxt;
//int channels = dst.channels();
//int depth = dst.depth();
//int vector_lengths[4][7] = {{4, 0, 4, 4, 1, 1, 1},
// {4, 0, 4, 4, 1, 1, 1},
// {4, 0, 4, 4, 1, 1, 1},
// {4, 0, 4, 4, 1, 1, 1}
//};
//size_t vector_length = vector_lengths[channels-1][depth];
//int offset_cols = (dst.offset / dst.elemSize1()) & (vector_length - 1);
//int cols = divUp(dst.cols * channels + offset_cols, vector_length);
size_t localThreads[3] = { 16, 16, 1 };
//size_t globalThreads[3] = { divUp(cols, localThreads[0]) * localThreads[0],
// divUp(dst.rows, localThreads[1]) * localThreads[1],
// 1
// };
size_t globalThreads[3] = { src1.cols,
src1.rows,
1
};
int dst_step1 = dst.cols * dst.elemSize();
std::vector<std::pair<size_t , const void *> > args;
args.push_back( std::make_pair( sizeof(cl_mem), (void *)&src1.data ));
args.push_back( std::make_pair( sizeof(cl_int), (void *)&src1.step ));
args.push_back( std::make_pair( sizeof(cl_int), (void *)&src1.offset ));
//args.push_back( std::make_pair( sizeof(cl_mem), (void *)&src2.data ));
//args.push_back( std::make_pair( sizeof(cl_int), (void *)&src2.step ));
//args.push_back( std::make_pair( sizeof(cl_int), (void *)&src2.offset ));
args.push_back( std::make_pair( sizeof(cl_mem), (void *)&dst.data ));
args.push_back( std::make_pair( sizeof(cl_int), (void *)&dst.step ));
args.push_back( std::make_pair( sizeof(cl_int), (void *)&dst.offset ));
args.push_back( std::make_pair( sizeof(cl_int), (void *)&src1.rows ));
args.push_back( std::make_pair( sizeof(cl_int), (void *)&src1.cols ));
args.push_back( std::make_pair( sizeof(cl_int), (void *)&dst_step1 ));
//if(_scalar != NULL)
//{
float scalar1 = *((float *)_scalar);
args.push_back( std::make_pair( sizeof(float), (float *)&scalar1 ));
//}
openCLExecuteKernel2(clCxt, kernelString, kernelName, globalThreads, localThreads, args, -1, src1.depth(), CLFLUSH);
}
static void multiply_cus(const oclMat &src1, oclMat &dst, float scalar)
{
arithmetic_run(src1, dst, "arithm_muls", &arithm_mul, (void *)(&scalar));
}
static void pyrdown_run_cus(const oclMat &src, const oclMat &dst)
{
CV_Assert(src.type() == dst.type());
CV_Assert(src.depth() != CV_8S);
Context *clCxt = src.clCxt;
String kernelName = "pyrDown";
size_t localThreads[3] = { 256, 1, 1 };
size_t globalThreads[3] = { src.cols, dst.rows, 1};
std::vector<std::pair<size_t , const void *> > args;
args.push_back( std::make_pair( sizeof(cl_mem), (void *)&src.data ));
args.push_back( std::make_pair( sizeof(cl_int), (void *)&src.step ));
args.push_back( std::make_pair( sizeof(cl_int), (void *)&src.rows));
args.push_back( std::make_pair( sizeof(cl_int), (void *)&src.cols));
args.push_back( std::make_pair( sizeof(cl_mem), (void *)&dst.data ));
args.push_back( std::make_pair( sizeof(cl_int), (void *)&dst.step ));
args.push_back( std::make_pair( sizeof(cl_int), (void *)&dst.cols));
openCLExecuteKernel2(clCxt, &pyr_down, kernelName, globalThreads, localThreads, args, src.oclchannels(), src.depth(), CLFLUSH);
}
static void pyrDown_cus(const oclMat &src, oclMat &dst)
{
CV_Assert(src.depth() <= CV_32F && src.channels() <= 4);
dst.create((src.rows + 1) / 2, (src.cols + 1) / 2, src.type());
pyrdown_run_cus(src, dst);
}
static void lkSparse_run(oclMat &I, oclMat &J,
const oclMat &prevPts, oclMat &nextPts, oclMat &status, oclMat& err, bool /*GET_MIN_EIGENVALS*/, int ptcount,
int level, /*dim3 block, */dim3 patch, Size winSize, int iters)
{
Context *clCxt = I.clCxt;
int elemCntPerRow = I.step / I.elemSize();
String kernelName = "lkSparse";
bool isImageSupported = support_image2d();
size_t localThreads[3] = { 8, isImageSupported ? 8 : 32, 1 };
size_t globalThreads[3] = { 8 * ptcount, isImageSupported ? 8 : 32, 1};
int cn = I.oclchannels();
char calcErr;
if (level == 0)
{
calcErr = 1;
}
else
{
calcErr = 0;
}
std::vector<std::pair<size_t , const void *> > args;
cl_mem ITex = isImageSupported ? bindTexture(I) : (cl_mem)I.data;
cl_mem JTex = isImageSupported ? bindTexture(J) : (cl_mem)J.data;
args.push_back( std::make_pair( sizeof(cl_mem), (void *)&ITex ));
args.push_back( std::make_pair( sizeof(cl_mem), (void *)&JTex ));
args.push_back( std::make_pair( sizeof(cl_mem), (void *)&prevPts.data ));
args.push_back( std::make_pair( sizeof(cl_int), (void *)&prevPts.step ));
args.push_back( std::make_pair( sizeof(cl_mem), (void *)&nextPts.data ));
args.push_back( std::make_pair( sizeof(cl_int), (void *)&nextPts.step ));
args.push_back( std::make_pair( sizeof(cl_mem), (void *)&status.data ));
args.push_back( std::make_pair( sizeof(cl_mem), (void *)&err.data ));
args.push_back( std::make_pair( sizeof(cl_int), (void *)&level ));
args.push_back( std::make_pair( sizeof(cl_int), (void *)&I.rows ));
args.push_back( std::make_pair( sizeof(cl_int), (void *)&I.cols ));
if (!isImageSupported)
args.push_back( std::make_pair( sizeof(cl_int), (void *)&elemCntPerRow ) );
args.push_back( std::make_pair( sizeof(cl_int), (void *)&patch.x ));
args.push_back( std::make_pair( sizeof(cl_int), (void *)&patch.y ));
args.push_back( std::make_pair( sizeof(cl_int), (void *)&cn ));
args.push_back( std::make_pair( sizeof(cl_int), (void *)&winSize.width ));
args.push_back( std::make_pair( sizeof(cl_int), (void *)&winSize.height ));
args.push_back( std::make_pair( sizeof(cl_int), (void *)&iters ));
args.push_back( std::make_pair( sizeof(cl_char), (void *)&calcErr ));
if(isImageSupported)
{
openCLExecuteKernel2(clCxt, &pyrlk, kernelName, globalThreads, localThreads, args, I.oclchannels(), I.depth(), CLFLUSH);
releaseTexture(ITex);
releaseTexture(JTex);
}
else
{
openCLExecuteKernel2(clCxt, &pyrlk_no_image, kernelName, globalThreads, localThreads, args, I.oclchannels(), I.depth(), CLFLUSH);
}
}
void cv::ocl::PyrLKOpticalFlow::sparse(const oclMat &prevImg, const oclMat &nextImg, const oclMat &prevPts, oclMat &nextPts, oclMat &status, oclMat *err)
{
if (prevPts.empty())
{
nextPts.release();
status.release();
//if (err) err->release();
return;
}
derivLambda = std::min(std::max(derivLambda, 0.0), 1.0);
iters = std::min(std::max(iters, 0), 100);
const int cn = prevImg.oclchannels();
dim3 block, patch;
calcPatchSize(winSize, cn, block, patch, isDeviceArch11_);
CV_Assert(derivLambda >= 0);
CV_Assert(maxLevel >= 0 && winSize.width > 2 && winSize.height > 2);
CV_Assert(prevImg.size() == nextImg.size() && prevImg.type() == nextImg.type());
CV_Assert(patch.x > 0 && patch.x < 6 && patch.y > 0 && patch.y < 6);
CV_Assert(prevPts.rows == 1 && prevPts.type() == CV_32FC2);
if (useInitialFlow)
CV_Assert(nextPts.size() == prevPts.size() && nextPts.type() == CV_32FC2);
else
ensureSizeIsEnough(1, prevPts.cols, prevPts.type(), nextPts);
oclMat temp1 = (useInitialFlow ? nextPts : prevPts).reshape(1);
oclMat temp2 = nextPts.reshape(1);
//oclMat scalar(temp1.rows, temp1.cols, temp1.type(), Scalar(1.0f / (1 << maxLevel) / 2.0f));
multiply_cus(temp1, temp2, 1.0f / (1 << maxLevel) / 2.0f);
//::multiply(temp1, 1.0f / (1 << maxLevel) / 2.0f, temp2);
ensureSizeIsEnough(1, prevPts.cols, CV_8UC1, status);
//status.setTo(Scalar::all(1));
setTo(status, Scalar::all(1));
bool errMat = false;
if (!err)
{
err = new oclMat(1, prevPts.cols, CV_32FC1);
errMat = true;
}
else
ensureSizeIsEnough(1, prevPts.cols, CV_32FC1, *err);
//ensureSizeIsEnough(1, prevPts.cols, CV_32FC1, err);
// build the image pyramids.
prevPyr_.resize(maxLevel + 1);
nextPyr_.resize(maxLevel + 1);
if (cn == 1 || cn == 4)
{
//prevImg.convertTo(prevPyr_[0], CV_32F);
//nextImg.convertTo(nextPyr_[0], CV_32F);
convertTo(prevImg, prevPyr_[0], CV_32F);
convertTo(nextImg, nextPyr_[0], CV_32F);
}
else
{
//oclMat buf_;
// cvtColor(prevImg, buf_, COLOR_BGR2BGRA);
// buf_.convertTo(prevPyr_[0], CV_32F);
// cvtColor(nextImg, buf_, COLOR_BGR2BGRA);
// buf_.convertTo(nextPyr_[0], CV_32F);
}
for (int level = 1; level <= maxLevel; ++level)
{
pyrDown_cus(prevPyr_[level - 1], prevPyr_[level]);
pyrDown_cus(nextPyr_[level - 1], nextPyr_[level]);
}
// dI/dx ~ Ix, dI/dy ~ Iy
for (int level = maxLevel; level >= 0; level--)
{
lkSparse_run(prevPyr_[level], nextPyr_[level],
prevPts, nextPts, status, *err, getMinEigenVals, prevPts.cols,
level, /*block, */patch, winSize, iters);
}
clFinish((cl_command_queue)prevImg.clCxt->oclCommandQueue());
if(errMat)
delete err;
}
static void lkDense_run(oclMat &I, oclMat &J, oclMat &u, oclMat &v,
oclMat &prevU, oclMat &prevV, oclMat *err, Size winSize, int iters)
{
Context *clCxt = I.clCxt;
bool isImageSupported = support_image2d();
int elemCntPerRow = I.step / I.elemSize();
String kernelName = "lkDense";
size_t localThreads[3] = { 16, 16, 1 };
size_t globalThreads[3] = { I.cols, I.rows, 1};
bool calcErr;
if (err)
{
calcErr = true;
}
else
{
calcErr = false;
}
cl_mem ITex;
cl_mem JTex;
if (isImageSupported)
{
ITex = bindTexture(I);
JTex = bindTexture(J);
}
else
{
ITex = (cl_mem)I.data;
JTex = (cl_mem)J.data;
}
//int2 halfWin = {(winSize.width - 1) / 2, (winSize.height - 1) / 2};
//const int patchWidth = 16 + 2 * halfWin.x;
//const int patchHeight = 16 + 2 * halfWin.y;
//size_t smem_size = 3 * patchWidth * patchHeight * sizeof(int);
std::vector<std::pair<size_t , const void *> > args;
args.push_back( std::make_pair( sizeof(cl_mem), (void *)&ITex ));
args.push_back( std::make_pair( sizeof(cl_mem), (void *)&JTex ));
args.push_back( std::make_pair( sizeof(cl_mem), (void *)&u.data ));
args.push_back( std::make_pair( sizeof(cl_int), (void *)&u.step ));
args.push_back( std::make_pair( sizeof(cl_mem), (void *)&v.data ));
args.push_back( std::make_pair( sizeof(cl_int), (void *)&v.step ));
args.push_back( std::make_pair( sizeof(cl_mem), (void *)&prevU.data ));
args.push_back( std::make_pair( sizeof(cl_int), (void *)&prevU.step ));
args.push_back( std::make_pair( sizeof(cl_mem), (void *)&prevV.data ));
args.push_back( std::make_pair( sizeof(cl_int), (void *)&prevV.step ));
args.push_back( std::make_pair( sizeof(cl_int), (void *)&I.rows ));
args.push_back( std::make_pair( sizeof(cl_int), (void *)&I.cols ));
//args.push_back( std::make_pair( sizeof(cl_mem), (void *)&(*err).data ));
//args.push_back( std::make_pair( sizeof(cl_int), (void *)&(*err).step ));
if (!isImageSupported)
{
args.push_back( std::make_pair( sizeof(cl_int), (void *)&elemCntPerRow ) );
}
args.push_back( std::make_pair( sizeof(cl_int), (void *)&winSize.width ));
args.push_back( std::make_pair( sizeof(cl_int), (void *)&winSize.height ));
args.push_back( std::make_pair( sizeof(cl_int), (void *)&iters ));
args.push_back( std::make_pair( sizeof(cl_char), (void *)&calcErr ));
if (isImageSupported)
{
openCLExecuteKernel2(clCxt, &pyrlk, kernelName, globalThreads, localThreads, args, I.oclchannels(), I.depth(), CLFLUSH);
releaseTexture(ITex);
releaseTexture(JTex);
}
else
{
//printf("Warning: The image2d_t is not supported by the device. Using alternative method!\n");
openCLExecuteKernel2(clCxt, &pyrlk_no_image, kernelName, globalThreads, localThreads, args, I.oclchannels(), I.depth(), CLFLUSH);
}
}
void cv::ocl::PyrLKOpticalFlow::dense(const oclMat &prevImg, const oclMat &nextImg, oclMat &u, oclMat &v, oclMat *err)
{
CV_Assert(prevImg.type() == CV_8UC1);
CV_Assert(prevImg.size() == nextImg.size() && prevImg.type() == nextImg.type());
CV_Assert(maxLevel >= 0);
CV_Assert(winSize.width > 2 && winSize.height > 2);
if (err)
err->create(prevImg.size(), CV_32FC1);
prevPyr_.resize(maxLevel + 1);
nextPyr_.resize(maxLevel + 1);
prevPyr_[0] = prevImg;
//nextImg.convertTo(nextPyr_[0], CV_32F);
convertTo(nextImg, nextPyr_[0], CV_32F);
for (int level = 1; level <= maxLevel; ++level)
{
pyrDown_cus(prevPyr_[level - 1], prevPyr_[level]);
pyrDown_cus(nextPyr_[level - 1], nextPyr_[level]);
}
ensureSizeIsEnough(prevImg.size(), CV_32FC1, uPyr_[0]);
ensureSizeIsEnough(prevImg.size(), CV_32FC1, vPyr_[0]);
ensureSizeIsEnough(prevImg.size(), CV_32FC1, uPyr_[1]);
ensureSizeIsEnough(prevImg.size(), CV_32FC1, vPyr_[1]);
//uPyr_[1].setTo(Scalar::all(0));
//vPyr_[1].setTo(Scalar::all(0));
setTo(uPyr_[1], Scalar::all(0));
setTo(vPyr_[1], Scalar::all(0));
Size winSize2i(winSize.width, winSize.height);
int idx = 0;
for (int level = maxLevel; level >= 0; level--)
{
int idx2 = (idx + 1) & 1;
lkDense_run(prevPyr_[level], nextPyr_[level], uPyr_[idx], vPyr_[idx], uPyr_[idx2], vPyr_[idx2],
level == 0 ? err : 0, winSize2i, iters);
if (level > 0)
idx = idx2;
}
//uPyr_[idx].copyTo(u);
//vPyr_[idx].copyTo(v);
copyTo(uPyr_[idx], u);
copyTo(vPyr_[idx], v);
clFinish((cl_command_queue)prevImg.clCxt->oclCommandQueue());
}
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