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提交 b5bd2cde 编写于 作者: Y yao 提交者： Andrey Kamaev
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A few optimizations to ocl::pyrLK::sparse, make it running on more OCL platforms

上级 02c9e0a3
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Showing with 1469 addition and 347 deletion
modules/ocl/src/kernels/arithm_mul.cl
浏览文件 @ b5bd2cde
......@@ -16,6 +16,7 @@
//
// @Authors
// Jia Haipeng, jiahaipeng95@gmail.com
// Dachuan Zhao, dachuan@multicorewareinc.com
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
......@@ -260,3 +261,22 @@ __kernel void arithm_mul_D6 (__global double *src1, int src1_step, int src1_offs
}
}
#endif
__kernel void arithm_muls_D5 (__global float *src1, int src1_step, int src1_offset,
__global float *dst, int dst_step, int dst_offset,
int rows, int cols, int dst_step1, float scalar)
{
int x = get_global_id(0);
int y = get_global_id(1);
if (x < cols && y < rows)
{
int src1_index = mad24(y, src1_step, (x << 2) + src1_offset);
int dst_index = mad24(y, dst_step, (x << 2) + dst_offset);
float data1 = *((__global float *)((__global char *)src1 + src1_index));
float tmp = data1 * scalar;
*((__global float *)((__global char *)dst + dst_index)) = tmp;
}
}
\ No newline at end of file
modules/ocl/src/kernels/pyrlk.cl
浏览文件 @ b5bd2cde
此差异已折叠。
modules/ocl/src/kernels/pyrlk_no_image.cl 0 → 100644
浏览文件 @ b5bd2cde
此差异已折叠。
modules/ocl/src/pyrlk.cpp
浏览文件 @ b5bd2cde
......@@ -48,23 +48,24 @@ using namespace cv::ocl;
#if !defined (HAVE_OPENCL)
void cv::ocl::PyrLKOpticalFlow::sparse(const oclMat &, const oclMat &, const oclMat &, oclMat &, oclMat &, oclMat *) { }
void cv::ocl::PyrLKOpticalFlow::sparse(const oclMat &, const oclMat &, const oclMat &, oclMat &, oclMat &, oclMat &) { }
void cv::ocl::PyrLKOpticalFlow::dense(const oclMat &, const oclMat &, oclMat &, oclMat &, oclMat *) { }
#else /* !defined (HAVE_OPENCL) */
namespace cv
{
namespace ocl
{
///////////////////////////OpenCL kernel strings///////////////////////////
extern const char *pyrlk;
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;
}
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
......@@ -84,26 +85,26 @@ struct int2
namespace
{
void calcPatchSize(cv::Size winSize, int cn, dim3 &block, dim3 &patch, bool isDeviceArch11)
{
winSize.width *= cn;
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;
}
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;
patch.x = (winSize.width + block.x - 1) / block.x;
patch.y = (winSize.height + block.y - 1) / block.y;
block.z = patch.z = 1;
}
block.z = patch.z = 1;
}
}
inline int divUp(int total, int grain)
......@@ -530,7 +531,7 @@ void arithmetic_run(const oclMat &src1, oclMat &dst, string kernelName, const ch
void multiply_cus(const oclMat &src1, oclMat &dst, float scalar)
{
arithmetic_run(src1, dst, "arithm_muls", &pyrlk, (void *)(&scalar));
arithmetic_run(src1, dst, "arithm_muls", &arithm_mul, (void *)(&scalar));
}
void pyrdown_run_cus(const oclMat &src, const oclMat &dst)
......@@ -581,26 +582,26 @@ void pyrDown_cus(const oclMat &src, oclMat &dst)
//
//void callF(const oclMat& src, oclMat& dst, MultiplyScalar op, int mask)
//{
// Mat srcTemp;
// Mat dstTemp;
// src.download(srcTemp);
// dst.download(dstTemp);
// Mat srcTemp;
// Mat dstTemp;
// src.download(srcTemp);
// dst.download(dstTemp);
//
// int i;
// int j;
// int k;
// for(i = 0; i < srcTemp.rows; i++)
// {
// for(j = 0; j < srcTemp.cols; j++)
// {
// for(k = 0; k < srcTemp.channels(); k++)
// {
// ((float*)dstTemp.data)[srcTemp.channels() * (i * srcTemp.rows + j) + k] = (float)op(((float*)srcTemp.data)[srcTemp.channels() * (i * srcTemp.rows + j) + k]);
// }
// }
// }
// int i;
// int j;
// int k;
// for(i = 0; i < srcTemp.rows; i++)
// {
// for(j = 0; j < srcTemp.cols; j++)
// {
// for(k = 0; k < srcTemp.channels(); k++)
// {
// ((float*)dstTemp.data)[srcTemp.channels() * (i * srcTemp.rows + j) + k] = (float)op(((float*)srcTemp.data)[srcTemp.channels() * (i * srcTemp.rows + j) + k]);
// }
// }
// }
//
// dst = dstTemp;
// dst = dstTemp;
//}
//
//static inline bool isAligned(const unsigned char* ptr, size_t size)
......@@ -622,54 +623,54 @@ void pyrDown_cus(const oclMat &src, oclMat &dst)
// return;
// }
//
// Mat srcTemp;
// Mat dstTemp;
// src.download(srcTemp);
// dst.download(dstTemp);
// Mat srcTemp;
// Mat dstTemp;
// src.download(srcTemp);
// dst.download(dstTemp);
//
// int x_shifted;
// int x_shifted;
//
// int i;
// int j;
// for(i = 0; i < srcTemp.rows; i++)
// {
// const double* srcRow = (const double*)srcTemp.data + i * srcTemp.rows;
// int i;
// int j;
// for(i = 0; i < srcTemp.rows; i++)
// {
// const double* srcRow = (const double*)srcTemp.data + i * srcTemp.rows;
// double* dstRow = (double*)dstTemp.data + i * dstTemp.rows;;
//
// for(j = 0; j < srcTemp.cols; j++)
// {
// x_shifted = j * 4;
// for(j = 0; j < srcTemp.cols; j++)
// {
// x_shifted = j * 4;
//
// if(x_shifted + 4 - 1 < srcTemp.cols)
// {
// dstRow[x_shifted ] = op(srcRow[x_shifted ]);
// dstRow[x_shifted + 1] = op(srcRow[x_shifted + 1]);
// dstRow[x_shifted + 2] = op(srcRow[x_shifted + 2]);
// dstRow[x_shifted + 3] = op(srcRow[x_shifted + 3]);
// }
// else
// {
// for (int real_x = x_shifted; real_x < srcTemp.cols; ++real_x)
// {
// ((float*)dstTemp.data)[i * srcTemp.rows + real_x] = op(((float*)srcTemp.data)[i * srcTemp.rows + real_x]);
// }
// }
// }
// }
// if(x_shifted + 4 - 1 < srcTemp.cols)
// {
// dstRow[x_shifted ] = op(srcRow[x_shifted ]);
// dstRow[x_shifted + 1] = op(srcRow[x_shifted + 1]);
// dstRow[x_shifted + 2] = op(srcRow[x_shifted + 2]);
// dstRow[x_shifted + 3] = op(srcRow[x_shifted + 3]);
// }
// else
// {
// for (int real_x = x_shifted; real_x < srcTemp.cols; ++real_x)
// {
// ((float*)dstTemp.data)[i * srcTemp.rows + real_x] = op(((float*)srcTemp.data)[i * srcTemp.rows + real_x]);
// }
// }
// }
// }
//}
//
//void multiply(const oclMat& src1, double val, oclMat& dst, double scale = 1.0f);
//void multiply(const oclMat& src1, double val, oclMat& dst, double scale)
//{
// MultiplyScalar op(val, scale);
// //if(src1.channels() == 1 && dst.channels() == 1)
// //{
// // callT(src1, dst, op, 0);
// //}
// //else
// //{
// callF(src1, dst, op, 0);
// //}
// //if(src1.channels() == 1 && dst.channels() == 1)
// //{
// // callT(src1, dst, op, 0);
// //}
// //else
// //{
// callF(src1, dst, op, 0);
// //}
//}
cl_mem bindTexture(const oclMat &mat, int depth, int channels)
......@@ -735,46 +736,69 @@ void releaseTexture(cl_mem texture)
}
void lkSparse_run(oclMat &I, oclMat &J,
const oclMat &prevPts, oclMat &nextPts, oclMat &status, oclMat *err, bool GET_MIN_EIGENVALS, int ptcount,
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;
char platform[256] = {0};
cl_platform_id pid;
clGetDeviceInfo(*clCxt->impl->devices, CL_DEVICE_PLATFORM, sizeof(pid), &pid, NULL);
clGetPlatformInfo(pid, CL_PLATFORM_NAME, 256, platform, NULL);
std::string namestr = platform;
bool isImageSupported = true;
if(namestr.find("NVIDIA")!=string::npos || namestr.find("Intel")!=string::npos)
isImageSupported = false;
int elemCntPerRow = I.step / I.elemSize();
string kernelName = "lkSparse";
size_t localThreads[3] = { 8, 32, 1 };
size_t globalThreads[3] = { 8 * ptcount, 32, 1};
size_t localThreads[3] = { 8, isImageSupported?8:32, 1 };
size_t globalThreads[3] = { 8 * ptcount, isImageSupported?8:32, 1};
int cn = I.oclchannels();
bool calcErr;
if (err)
char calcErr;
if (level == 0)
{
calcErr = true;
calcErr = 1;
}
else
{
calcErr = false;
calcErr = 0;
}
calcErr = true;
cl_mem ITex = bindTexture(I, I.depth(), cn);
cl_mem JTex = bindTexture(J, J.depth(), cn);
vector<pair<size_t , const void *> > args;
cl_mem ITex;
cl_mem JTex;
if (isImageSupported)
{
ITex = bindTexture(I, I.depth(), cn);
JTex = bindTexture(J, J.depth(), cn);
}
else
{
ITex = (cl_mem)I.data;
JTex = (cl_mem)J.data;
}
args.push_back( make_pair( sizeof(cl_mem), (void *)&ITex ));
args.push_back( make_pair( sizeof(cl_mem), (void *)&JTex ));
//cl_mem clmD = clCreateBuffer(clCxt, CL_MEM_READ_WRITE, ptcount * sizeof(float), NULL, NULL);
args.push_back( make_pair( sizeof(cl_mem), (void *)&prevPts.data ));
args.push_back( make_pair( sizeof(cl_int), (void *)&prevPts.step ));
args.push_back( make_pair( sizeof(cl_mem), (void *)&nextPts.data ));
args.push_back( make_pair( sizeof(cl_int), (void *)&nextPts.step ));
args.push_back( make_pair( sizeof(cl_mem), (void *)&status.data ));
//args.push_back( make_pair( sizeof(cl_mem), (void *)&(err->data) ));
args.push_back( make_pair( sizeof(cl_mem), (void *)&err.data ));
args.push_back( make_pair( sizeof(cl_int), (void *)&level ));
args.push_back( make_pair( sizeof(cl_int), (void *)&I.rows ));
args.push_back( make_pair( sizeof(cl_int), (void *)&I.cols ));
if (!isImageSupported)
{
args.push_back( make_pair( sizeof(cl_int), (void *)&elemCntPerRow ) );
}
args.push_back( make_pair( sizeof(cl_int), (void *)&patch.x ));
args.push_back( make_pair( sizeof(cl_int), (void *)&patch.y ));
args.push_back( make_pair( sizeof(cl_int), (void *)&cn ));
......@@ -782,27 +806,29 @@ void lkSparse_run(oclMat &I, oclMat &J,
args.push_back( make_pair( sizeof(cl_int), (void *)&winSize.height ));
args.push_back( make_pair( sizeof(cl_int), (void *)&iters ));
args.push_back( make_pair( sizeof(cl_char), (void *)&calcErr ));
args.push_back( make_pair( sizeof(cl_char), (void *)&GET_MIN_EIGENVALS ));
//args.push_back( make_pair( sizeof(cl_char), (void *)&GET_MIN_EIGENVALS ));
openCLExecuteKernel2(clCxt, &pyrlk, kernelName, globalThreads, localThreads, args, I.oclchannels(), I.depth(), CLFLUSH);
if (isImageSupported)
{
openCLExecuteKernel2(clCxt, &pyrlk, kernelName, globalThreads, localThreads, args, I.oclchannels(), I.depth(), CLFLUSH);
releaseTexture(ITex);
releaseTexture(JTex);
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::sparse(const oclMat &prevImg, const oclMat &nextImg, const oclMat &prevPts, oclMat &nextPts, oclMat &status, oclMat *err)
{
if (prevImg.clCxt->impl->devName.find("Intel(R) HD Graphics") != string::npos)
{
cout << " Intel HD GPU device unsupported " << endl;
return;
}
if (prevPts.empty())
{
nextPts.release();
status.release();
if (err) err->release();
//if (err) err->release();
return;
}
......@@ -836,8 +862,15 @@ void cv::ocl::PyrLKOpticalFlow::sparse(const oclMat &prevImg, const oclMat &next
//status.setTo(Scalar::all(1));
setTo(status, Scalar::all(1));
//if (err)
// ensureSizeIsEnough(1, prevPts.cols, CV_32FC1, *err);
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.
......@@ -872,17 +905,22 @@ void cv::ocl::PyrLKOpticalFlow::sparse(const oclMat &prevImg, const oclMat &next
for (int level = maxLevel; level >= 0; level--)
{
lkSparse_run(prevPyr_[level], nextPyr_[level],
prevPts, nextPts, status, level == 0 && err ? err : 0, getMinEigenVals, prevPts.cols,
prevPts, nextPts, status, *err, getMinEigenVals, prevPts.cols,
level, /*block, */patch, winSize, iters);
}
clFinish(prevImg.clCxt->impl->clCmdQueue);
if(errMat)
delete err;
}
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 = clCxt->impl->devName.find("Intel(R) HD Graphics") == string::npos;
int elemCntPerRow = I.step / I.elemSize();
string kernelName = "lkDense";
......@@ -901,8 +939,19 @@ void lkDense_run(oclMat &I, oclMat &J, oclMat &u, oclMat &v,
calcErr = false;
}
cl_mem ITex = bindTexture(I, I.depth(), cn);
cl_mem JTex = bindTexture(J, J.depth(), cn);
cl_mem ITex;
cl_mem JTex;
if (isImageSupported)
{
ITex = bindTexture(I, I.depth(), cn);
JTex = bindTexture(J, J.depth(), cn);
}
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;
......@@ -926,15 +975,27 @@ void lkDense_run(oclMat &I, oclMat &J, oclMat &u, oclMat &v,
args.push_back( make_pair( sizeof(cl_int), (void *)&I.cols ));
//args.push_back( make_pair( sizeof(cl_mem), (void *)&(*err).data ));
//args.push_back( make_pair( sizeof(cl_int), (void *)&(*err).step ));
if (!isImageSupported)
{
args.push_back( make_pair( sizeof(cl_int), (void *)&elemCntPerRow ) );
}
args.push_back( make_pair( sizeof(cl_int), (void *)&winSize.width ));
args.push_back( make_pair( sizeof(cl_int), (void *)&winSize.height ));
args.push_back( make_pair( sizeof(cl_int), (void *)&iters ));
args.push_back( make_pair( sizeof(cl_char), (void *)&calcErr ));
openCLExecuteKernel2(clCxt, &pyrlk, kernelName, globalThreads, localThreads, args, I.oclchannels(), I.depth(), CLFLUSH);
if (isImageSupported)
{
openCLExecuteKernel2(clCxt, &pyrlk, kernelName, globalThreads, localThreads, args, I.oclchannels(), I.depth(), CLFLUSH);
releaseTexture(ITex);
releaseTexture(JTex);
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)
......
modules/ocl/test/test_pyrlk.cpp
浏览文件 @ b5bd2cde
......@@ -118,9 +118,9 @@ TEST_P(Sparse, Mat)
cv::Mat status_mat(1, d_status.cols, CV_8UC1, (void *)&status[0]);
d_status.download(status_mat);
//std::vector<float> err(d_err.cols);
//cv::Mat err_mat(1, d_err.cols, CV_32FC1, (void*)&err[0]);
//d_err.download(err_mat);
std::vector<float> err(d_err.cols);
cv::Mat err_mat(1, d_err.cols, CV_32FC1, (void*)&err[0]);
d_err.download(err_mat);
std::vector<cv::Point2f> nextPts_gold;
std::vector<unsigned char> status_gold;
......@@ -153,9 +153,9 @@ TEST_P(Sparse, Mat)
}
}
double bad_ratio = static_cast<double>(mistmatch) / (nextPts.size() * 2);
double bad_ratio = static_cast<double>(mistmatch) / (nextPts.size());
ASSERT_LE(bad_ratio, 0.05f);
ASSERT_LE(bad_ratio, 0.02f);
}
......
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