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Merge pull request #742 from bitwangyaoyao:2.4_fix

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pull/792/merge
Andrey Kamaev 12 years ago committed by OpenCV Buildbot
parent 0c64fc61dc 8cc5b98051
commit 9ba25e9d09
9 changed files with 541 additions and 628 deletions
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  1. 5
      modules/ocl/include/opencv2/ocl/private/util.hpp
  2. 61
      modules/ocl/src/hog.cpp
  3. 9
      modules/ocl/src/initialization.cpp
  4. 2
      modules/ocl/src/matrix_operations.cpp
  5. 207
      modules/ocl/src/opencl/objdetect_hog.cl
  6. 278
      modules/ocl/src/opencl/pyrlk.cl
  7. 78
      modules/ocl/src/opencl/stereobm.cl
  8. 520
      modules/ocl/src/pyrlk.cpp
  9. 7
      modules/ocl/test/main.cpp

5
modules/ocl/include/opencv2/ocl/private/util.hpp
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@ -127,8 +127,9 @@ namespace cv
// currently only support wavefront size queries
enum DEVICE_INFO
{
WAVEFRONT_SIZE, //in AMD speak
WARP_SIZE = WAVEFRONT_SIZE //in nvidia speak
WAVEFRONT_SIZE, //in AMD speak
WARP_SIZE = WAVEFRONT_SIZE, //in nvidia speak
IS_CPU_DEVICE //check if the device is CPU
};
//info should have been pre-allocated
void CV_EXPORTS queryDeviceInfo(DEVICE_INFO info_type, void* info);

61
modules/ocl/src/hog.cpp
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@ -44,7 +44,6 @@
//M*/
#include "precomp.hpp"
using namespace cv;
using namespace cv::ocl;
using namespace std;
@ -230,7 +229,6 @@ void cv::ocl::HOGDescriptor::computeGradient(const oclMat &img, oclMat &grad, oc
}
}
void cv::ocl::HOGDescriptor::computeBlockHistograms(const oclMat &img)
{
computeGradient(img, grad, qangle);
@ -1571,6 +1569,27 @@ void cv::ocl::device::hog::set_up_constants(int nbins, int block_stride_x, int b
cdescr_size = descr_size;
}
static inline int divUp(int total, int grain)
{
return (total + grain - 1) / grain;
}
static void openCLExecuteKernel_hog(Context *clCxt , const char **source, string kernelName,
size_t globalThreads[3], size_t localThreads[3],
vector< pair<size_t, const void *> > &args)
{
size_t wave_size = 0;
queryDeviceInfo(WAVEFRONT_SIZE, &wave_size);
if (wave_size <= 16)
{
char build_options[64];
sprintf(build_options, (wave_size == 16) ? "-D WAVE_SIZE_16" : "-D WAVE_SIZE_1");
openCLExecuteKernel(clCxt, source, kernelName, globalThreads, localThreads, args, -1, -1, build_options);
}
else
openCLExecuteKernel(clCxt, source, kernelName, globalThreads, localThreads, args, -1, -1);
}
void cv::ocl::device::hog::compute_hists(int nbins, int block_stride_x, int block_stride_y,
int height, int width, const cv::ocl::oclMat &grad,
const cv::ocl::oclMat &qangle, float sigma, cv::ocl::oclMat &block_hists)
@ -1582,8 +1601,10 @@ void cv::ocl::device::hog::compute_hists(int nbins, int block_stride_x, int bloc
int img_block_width = (width - CELLS_PER_BLOCK_X * CELL_WIDTH + block_stride_x) / block_stride_x;
int img_block_height = (height - CELLS_PER_BLOCK_Y * CELL_HEIGHT + block_stride_y) / block_stride_y;
size_t globalThreads[3] = { img_block_width * 32, img_block_height * 2, 1 };
size_t localThreads[3] = { 32, 2, 1 };
int blocks_total = img_block_width * img_block_height;
int blocks_in_group = 4;
size_t localThreads[3] = { blocks_in_group * 24, 2, 1 };
size_t globalThreads[3] = { divUp(blocks_total, blocks_in_group) * localThreads[0], 2, 1 };
int grad_quadstep = grad.step >> 2;
int qangle_step = qangle.step;
@ -1593,14 +1614,15 @@ void cv::ocl::device::hog::compute_hists(int nbins, int block_stride_x, int bloc
int hists_size = (nbins * CELLS_PER_BLOCK_X * CELLS_PER_BLOCK_Y * 12) * sizeof(float);
int final_hists_size = (nbins * CELLS_PER_BLOCK_X * CELLS_PER_BLOCK_Y) * sizeof(float);
int smem = hists_size + final_hists_size;
int smem = (hists_size + final_hists_size) * blocks_in_group;
args.push_back( make_pair( sizeof(cl_int), (void *)&width));
args.push_back( make_pair( sizeof(cl_int), (void *)&cblock_stride_x));
args.push_back( make_pair( sizeof(cl_int), (void *)&cblock_stride_y));
args.push_back( make_pair( sizeof(cl_int), (void *)&cnbins));
args.push_back( make_pair( sizeof(cl_int), (void *)&cblock_hist_size));
args.push_back( make_pair( sizeof(cl_int), (void *)&img_block_width));
args.push_back( make_pair( sizeof(cl_int), (void *)&blocks_in_group));
args.push_back( make_pair( sizeof(cl_int), (void *)&blocks_total));
args.push_back( make_pair( sizeof(cl_int), (void *)&grad_quadstep));
args.push_back( make_pair( sizeof(cl_int), (void *)&qangle_step));
args.push_back( make_pair( sizeof(cl_mem), (void *)&grad.data));
@ -1609,7 +1631,7 @@ void cv::ocl::device::hog::compute_hists(int nbins, int block_stride_x, int bloc
args.push_back( make_pair( sizeof(cl_mem), (void *)&block_hists.data));
args.push_back( make_pair( smem, (void *)NULL));
openCLExecuteKernel2(clCxt, &objdetect_hog, kernelName, globalThreads, localThreads, args, -1, -1);
openCLExecuteKernel_hog(clCxt, &objdetect_hog, kernelName, globalThreads, localThreads, args);
}
void cv::ocl::device::hog::normalize_hists(int nbins, int block_stride_x, int block_stride_y,
@ -1637,7 +1659,7 @@ void cv::ocl::device::hog::normalize_hists(int nbins, int block_stride_x, int bl
args.push_back( make_pair( sizeof(cl_float), (void *)&threshold));
args.push_back( make_pair( nthreads * sizeof(float), (void *)NULL));
openCLExecuteKernel2(clCxt, &objdetect_hog, kernelName, globalThreads, localThreads, args, -1, -1);
openCLExecuteKernel_hog(clCxt, &objdetect_hog, kernelName, globalThreads, localThreads, args);
}
void cv::ocl::device::hog::classify_hists(int win_height, int win_width, int block_stride_y,
@ -1671,7 +1693,7 @@ void cv::ocl::device::hog::classify_hists(int win_height, int win_width, int blo
args.push_back( make_pair( sizeof(cl_float), (void *)&threshold));
args.push_back( make_pair( sizeof(cl_mem), (void *)&labels.data));
openCLExecuteKernel2(clCxt, &objdetect_hog, kernelName, globalThreads, localThreads, args, -1, -1);
openCLExecuteKernel_hog(clCxt, &objdetect_hog, kernelName, globalThreads, localThreads, args);
}
void cv::ocl::device::hog::extract_descrs_by_rows(int win_height, int win_width, int block_stride_y, int block_stride_x,
@ -1702,7 +1724,7 @@ void cv::ocl::device::hog::extract_descrs_by_rows(int win_height, int win_width,
args.push_back( make_pair( sizeof(cl_mem), (void *)&block_hists.data));
args.push_back( make_pair( sizeof(cl_mem), (void *)&descriptors.data));
openCLExecuteKernel2(clCxt, &objdetect_hog, kernelName, globalThreads, localThreads, args, -1, -1);
openCLExecuteKernel(clCxt, &objdetect_hog, kernelName, globalThreads, localThreads, args, -1, -1);
}
void cv::ocl::device::hog::extract_descrs_by_cols(int win_height, int win_width, int block_stride_y, int block_stride_x,
@ -1734,12 +1756,7 @@ void cv::ocl::device::hog::extract_descrs_by_cols(int win_height, int win_width,
args.push_back( make_pair( sizeof(cl_mem), (void *)&block_hists.data));
args.push_back( make_pair( sizeof(cl_mem), (void *)&descriptors.data));
openCLExecuteKernel2(clCxt, &objdetect_hog, kernelName, globalThreads, localThreads, args, -1, -1);
}
static inline int divUp(int total, int grain)
{
return (total + grain - 1) / grain;
openCLExecuteKernel(clCxt, &objdetect_hog, kernelName, globalThreads, localThreads, args, -1, -1);
}
void cv::ocl::device::hog::compute_gradients_8UC1(int height, int width, const cv::ocl::oclMat &img,
@ -1768,7 +1785,7 @@ void cv::ocl::device::hog::compute_gradients_8UC1(int height, int width, const c
args.push_back( make_pair( sizeof(cl_char), (void *)&correctGamma));
args.push_back( make_pair( sizeof(cl_int), (void *)&cnbins));
openCLExecuteKernel2(clCxt, &objdetect_hog, kernelName, globalThreads, localThreads, args, -1, -1);
openCLExecuteKernel(clCxt, &objdetect_hog, kernelName, globalThreads, localThreads, args, -1, -1);
}
void cv::ocl::device::hog::compute_gradients_8UC4(int height, int width, const cv::ocl::oclMat &img,
@ -1798,7 +1815,7 @@ void cv::ocl::device::hog::compute_gradients_8UC4(int height, int width, const c
args.push_back( make_pair( sizeof(cl_char), (void *)&correctGamma));
args.push_back( make_pair( sizeof(cl_int), (void *)&cnbins));
openCLExecuteKernel2(clCxt, &objdetect_hog, kernelName, globalThreads, localThreads, args, -1, -1);
openCLExecuteKernel(clCxt, &objdetect_hog, kernelName, globalThreads, localThreads, args, -1, -1);
}
void cv::ocl::device::hog::resize( const oclMat &src, oclMat &dst, const Size sz)
@ -1815,14 +1832,16 @@ void cv::ocl::device::hog::resize( const oclMat &src, oclMat &dst, const Size sz
float ifx = (float)src.cols / sz.width;
float ify = (float)src.rows / sz.height;
int src_step = static_cast<int>(src.step);
int dst_step = static_cast<int>(dst.step);
vector< pair<size_t, const void *> > args;
args.push_back( make_pair(sizeof(cl_mem), (void *)&dst.data));
args.push_back( make_pair(sizeof(cl_mem), (void *)&src.data));
args.push_back( make_pair(sizeof(cl_int), (void *)&dst.offset));
args.push_back( make_pair(sizeof(cl_int), (void *)&src.offset));
args.push_back( make_pair(sizeof(cl_int), (void *)&dst.step));
args.push_back( make_pair(sizeof(cl_int), (void *)&src.step));
args.push_back( make_pair(sizeof(cl_int), (void *)&dst_step));
args.push_back( make_pair(sizeof(cl_int), (void *)&src_step));
args.push_back( make_pair(sizeof(cl_int), (void *)&src.cols));
args.push_back( make_pair(sizeof(cl_int), (void *)&src.rows));
args.push_back( make_pair(sizeof(cl_int), (void *)&sz.width));
@ -1830,5 +1849,5 @@ void cv::ocl::device::hog::resize( const oclMat &src, oclMat &dst, const Size sz
args.push_back( make_pair(sizeof(cl_float), (void *)&ifx));
args.push_back( make_pair(sizeof(cl_float), (void *)&ify));
openCLExecuteKernel2(clCxt, &objdetect_hog, kernelName, globalThreads, localThreads, args, -1, -1);
openCLExecuteKernel(clCxt, &objdetect_hog, kernelName, globalThreads, localThreads, args, -1, -1);
}

9
modules/ocl/src/initialization.cpp
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@ -397,6 +397,15 @@ namespace cv
}
break;
case IS_CPU_DEVICE:
{
cl_device_type devicetype;
openCLSafeCall(clGetDeviceInfo(impl->devices[impl->devnum],
CL_DEVICE_TYPE, sizeof(cl_device_type),
&devicetype, NULL));
*(bool*)info = (devicetype == CVCL_DEVICE_TYPE_CPU);
}
break;
default:
CV_Error(-1, "Invalid device info type");
break;

2
modules/ocl/src/matrix_operations.cpp
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@ -394,7 +394,7 @@ void cv::ocl::oclMat::convertTo( oclMat &dst, int rtype, double alpha, double be
if( rtype < 0 )
rtype = type();
else
rtype = CV_MAKETYPE(CV_MAT_DEPTH(rtype), channels());
rtype = CV_MAKETYPE(CV_MAT_DEPTH(rtype), oclchannels());
//int scn = channels();
int sdepth = depth(), ddepth = CV_MAT_DEPTH(rtype);

207
modules/ocl/src/opencl/objdetect_hog.cl
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@ -53,76 +53,96 @@
//----------------------------------------------------------------------------
// Histogram computation
__kernel void compute_hists_kernel(const int width, const int cblock_stride_x, const int cblock_stride_y,
const int cnbins, const int cblock_hist_size, const int img_block_width,
const int grad_quadstep, const int qangle_step,
__global const float* grad, __global const uchar* qangle,
const float scale, __global float* block_hists, __local float* smem)
// 12 threads for a cell, 12x4 threads per block
__kernel void compute_hists_kernel(
const int cblock_stride_x, const int cblock_stride_y,
const int cnbins, const int cblock_hist_size, const int img_block_width,
const int blocks_in_group, const int blocks_total,
const int grad_quadstep, const int qangle_step,
__global const float* grad, __global const uchar* qangle,
const float scale, __global float* block_hists, __local float* smem)
{
const int lidX = get_local_id(0);
const int lx = get_local_id(0);
const int lp = lx / 24; /* local group id */
const int gid = get_group_id(0) * blocks_in_group + lp;/* global group id */
const int gidY = gid / img_block_width;
const int gidX = gid - gidY * img_block_width;
const int lidX = lx - lp * 24;
const int lidY = get_local_id(1);
const int gidX = get_group_id(0);
const int gidY = get_group_id(1);
const int cell_x = lidX / 16;
const int cell_x = lidX / 12;
const int cell_y = lidY;
const int cell_thread_x = lidX & 0xF;
const int cell_thread_x = lidX - cell_x * 12;
__local float* hists = smem;
__local float* final_hist = smem + cnbins * 48;
__local float* hists = smem + lp * cnbins * (CELLS_PER_BLOCK_X *
CELLS_PER_BLOCK_Y * 12 + CELLS_PER_BLOCK_X * CELLS_PER_BLOCK_Y);
__local float* final_hist = hists + cnbins *
(CELLS_PER_BLOCK_X * CELLS_PER_BLOCK_Y * 12);
const int offset_x = gidX * cblock_stride_x + (cell_x << 2) + cell_thread_x;
const int offset_y = gidY * cblock_stride_y + (cell_y << 2);
__global const float* grad_ptr = grad + offset_y * grad_quadstep + (offset_x << 1);
__global const uchar* qangle_ptr = qangle + offset_y * qangle_step + (offset_x << 1);
// 12 means that 12 pixels affect on block's cell (in one row)
if (cell_thread_x < 12)
{
__local float* hist = hists + 12 * (cell_y * CELLS_PER_BLOCK_Y + cell_x) + cell_thread_x;
for (int bin_id = 0; bin_id < cnbins; ++bin_id)
hist[bin_id * 48] = 0.f;
__global const float* grad_ptr = (gid < blocks_total) ?
grad + offset_y * grad_quadstep + (offset_x << 1) : grad;
__global const uchar* qangle_ptr = (gid < blocks_total) ?
qangle + offset_y * qangle_step + (offset_x << 1) : qangle;
const int dist_x = -4 + cell_thread_x - 4 * cell_x;
__local float* hist = hists + 12 * (cell_y * CELLS_PER_BLOCK_Y + cell_x) +
cell_thread_x;
for (int bin_id = 0; bin_id < cnbins; ++bin_id)
hist[bin_id * 48] = 0.f;
const int dist_y_begin = -4 - 4 * lidY;
for (int dist_y = dist_y_begin; dist_y < dist_y_begin + 12; ++dist_y)
{
float2 vote = (float2) (grad_ptr[0], grad_ptr[1]);
uchar2 bin = (uchar2) (qangle_ptr[0], qangle_ptr[1]);
const int dist_x = -4 + cell_thread_x - 4 * cell_x;
const int dist_center_x = dist_x - 4 * (1 - 2 * cell_x);
grad_ptr += grad_quadstep;
qangle_ptr += qangle_step;
const int dist_y_begin = -4 - 4 * lidY;
for (int dist_y = dist_y_begin; dist_y < dist_y_begin + 12; ++dist_y)
{
float2 vote = (float2) (grad_ptr[0], grad_ptr[1]);
uchar2 bin = (uchar2) (qangle_ptr[0], qangle_ptr[1]);
int dist_center_y = dist_y - 4 * (1 - 2 * cell_y);
int dist_center_x = dist_x - 4 * (1 - 2 * cell_x);
grad_ptr += grad_quadstep;
qangle_ptr += qangle_step;
float gaussian = exp(-(dist_center_y * dist_center_y + dist_center_x * dist_center_x) * scale);
float interp_weight = (8.f - fabs(dist_y + 0.5f)) * (8.f - fabs(dist_x + 0.5f)) / 64.f;
int dist_center_y = dist_y - 4 * (1 - 2 * cell_y);
hist[bin.x * 48] += gaussian * interp_weight * vote.x;
hist[bin.y * 48] += gaussian * interp_weight * vote.y;
}
float gaussian = exp(-(dist_center_y * dist_center_y + dist_center_x *
dist_center_x) * scale);
float interp_weight = (8.f - fabs(dist_y + 0.5f)) *
(8.f - fabs(dist_x + 0.5f)) / 64.f;
volatile __local float* hist_ = hist;
for (int bin_id = 0; bin_id < cnbins; ++bin_id, hist_ += 48)
{
if (cell_thread_x < 6) hist_[0] += hist_[6];
if (cell_thread_x < 3) hist_[0] += hist_[3];
if (cell_thread_x == 0)
final_hist[(cell_x * 2 + cell_y) * cnbins + bin_id] = hist_[0] + hist_[1] + hist_[2];
}
hist[bin.x * 48] += gaussian * interp_weight * vote.x;
hist[bin.y * 48] += gaussian * interp_weight * vote.y;
}
barrier(CLK_LOCAL_MEM_FENCE);
__global float* block_hist = block_hists + (gidY * img_block_width + gidX) * cblock_hist_size;
volatile __local float* hist_ = hist;
for (int bin_id = 0; bin_id < cnbins; ++bin_id, hist_ += 48)
{
if (cell_thread_x < 6)
hist_[0] += hist_[6];
barrier(CLK_LOCAL_MEM_FENCE);
if (cell_thread_x < 3)
hist_[0] += hist_[3];
#ifdef WAVE_SIZE_1
barrier(CLK_LOCAL_MEM_FENCE);
#endif
if (cell_thread_x == 0)
final_hist[(cell_x * 2 + cell_y) * cnbins + bin_id] =
hist_[0] + hist_[1] + hist_[2];
}
#ifdef WAVE_SIZE_1
barrier(CLK_LOCAL_MEM_FENCE);
#endif
int tid = (cell_y * CELLS_PER_BLOCK_Y + cell_x) * 16 + cell_thread_x;
if (tid < cblock_hist_size)
int tid = (cell_y * CELLS_PER_BLOCK_Y + cell_x) * 12 + cell_thread_x;
if ((tid < cblock_hist_size) && (gid < blocks_total))
{
__global float* block_hist = block_hists +
(gidY * img_block_width + gidX) * cblock_hist_size;
block_hist[tid] = final_hist[tid];
}
}
//-------------------------------------------------------------
@ -133,21 +153,59 @@ float reduce_smem(volatile __local float* smem, int size)
unsigned int tid = get_local_id(0);
float sum = smem[tid];
if (size >= 512) { if (tid < 256) smem[tid] = sum = sum + smem[tid + 256]; barrier(CLK_LOCAL_MEM_FENCE); }
if (size >= 256) { if (tid < 128) smem[tid] = sum = sum + smem[tid + 128]; barrier(CLK_LOCAL_MEM_FENCE); }
if (size >= 128) { if (tid < 64) smem[tid] = sum = sum + smem[tid + 64]; barrier(CLK_LOCAL_MEM_FENCE); }
if (size >= 512)
{
if (tid < 256) smem[tid] = sum = sum + smem[tid + 256];
barrier(CLK_LOCAL_MEM_FENCE);
}
if (size >= 256)
{
if (tid < 128) smem[tid] = sum = sum + smem[tid + 128];
barrier(CLK_LOCAL_MEM_FENCE);
}
if (size >= 128)
{
if (tid < 64) smem[tid] = sum = sum + smem[tid + 64];
barrier(CLK_LOCAL_MEM_FENCE);
}
if (tid < 32)
{
if (size >= 64) smem[tid] = sum = sum + smem[tid + 32];
#if defined(WAVE_SIZE_16) || defined(WAVE_SIZE_1)
}
barrier(CLK_LOCAL_MEM_FENCE);
if (tid < 16)
{
#endif
if (size >= 32) smem[tid] = sum = sum + smem[tid + 16];
#ifdef WAVE_SIZE_1
}
barrier(CLK_LOCAL_MEM_FENCE);
if (tid < 8)
{
#endif
if (size >= 16) smem[tid] = sum = sum + smem[tid + 8];
#ifdef WAVE_SIZE_1
}
barrier(CLK_LOCAL_MEM_FENCE);
if (tid < 4)
{
#endif
if (size >= 8) smem[tid] = sum = sum + smem[tid + 4];
#ifdef WAVE_SIZE_1
}
barrier(CLK_LOCAL_MEM_FENCE);
if (tid < 2)
{
#endif
if (size >= 4) smem[tid] = sum = sum + smem[tid + 2];
#ifdef WAVE_SIZE_1
}
barrier(CLK_LOCAL_MEM_FENCE);
if (tid < 1)
{
#endif
if (size >= 2) smem[tid] = sum = sum + smem[tid + 1];
}
@ -224,19 +282,44 @@ __kernel void classify_hists_kernel(const int cblock_hist_size, const int cdescr
if (tid < 64) products[tid] = product = product + products[tid + 64];
barrier(CLK_LOCAL_MEM_FENCE);
volatile __local float* smem = products;
if (tid < 32)
{
volatile __local float* smem = products;
smem[tid] = product = product + smem[tid + 32];
#if defined(WAVE_SIZE_16) || defined(WAVE_SIZE_1)
}
barrier(CLK_LOCAL_MEM_FENCE);
if (tid < 16)
{
volatile __local float* smem = products;
#endif
smem[tid] = product = product + smem[tid + 16];
#ifdef WAVE_SIZE_1
}
barrier(CLK_LOCAL_MEM_FENCE);
if (tid < 8)
{
#endif
smem[tid] = product = product + smem[tid + 8];
#ifdef WAVE_SIZE_1
}
barrier(CLK_LOCAL_MEM_FENCE);
if (tid < 4)
{
#endif
smem[tid] = product = product + smem[tid + 4];
#ifdef WAVE_SIZE_1
}
barrier(CLK_LOCAL_MEM_FENCE);
if (tid < 2)
{
#endif
smem[tid] = product = product + smem[tid + 2];
#ifdef WAVE_SIZE_1
}
barrier(CLK_LOCAL_MEM_FENCE);
if (tid < 1)
{
#endif
smem[tid] = product = product + smem[tid + 1];
}
@ -248,8 +331,8 @@ __kernel void classify_hists_kernel(const int cblock_hist_size, const int cdescr
// Extract descriptors
__kernel void extract_descrs_by_rows_kernel(const int cblock_hist_size, const int descriptors_quadstep, const int cdescr_size, const int cdescr_width,
const int img_block_width, const int win_block_stride_x, const int win_block_stride_y,
__global const float* block_hists, __global float* descriptors)
const int img_block_width, const int win_block_stride_x, const int win_block_stride_y,
__global const float* block_hists, __global float* descriptors)
{
int tid = get_local_id(0);
int gidX = get_group_id(0);
@ -271,8 +354,8 @@ __kernel void extract_descrs_by_rows_kernel(const int cblock_hist_size, const in
}
__kernel void extract_descrs_by_cols_kernel(const int cblock_hist_size, const int descriptors_quadstep, const int cdescr_size,
const int cnblocks_win_x, const int cnblocks_win_y, const int img_block_width, const int win_block_stride_x,
const int win_block_stride_y, __global const float* block_hists, __global float* descriptors)
const int cnblocks_win_x, const int cnblocks_win_y, const int img_block_width, const int win_block_stride_x,
const int win_block_stride_y, __global const float* block_hists, __global float* descriptors)
{
int tid = get_local_id(0);
int gidX = get_group_id(0);
@ -301,8 +384,8 @@ __kernel void extract_descrs_by_cols_kernel(const int cblock_hist_size, const in
// Gradients computation
__kernel void compute_gradients_8UC4_kernel(const int height, const int width, const int img_step, const int grad_quadstep, const int qangle_step,
const __global uchar4 * img, __global float * grad, __global uchar * qangle,
const float angle_scale, const char correct_gamma, const int cnbins)
const __global uchar4 * img, __global float * grad, __global uchar * qangle,
const float angle_scale, const char correct_gamma, const int cnbins)
{
const int x = get_global_id(0);
const int tid = get_local_id(0);
@ -400,8 +483,8 @@ __kernel void compute_gradients_8UC4_kernel(const int height, const int width, c
}
__kernel void compute_gradients_8UC1_kernel(const int height, const int width, const int img_step, const int grad_quadstep, const int qangle_step,
__global const uchar * img, __global float * grad, __global uchar * qangle,
const float angle_scale, const char correct_gamma, const int cnbins)
__global const uchar * img, __global float * grad, __global uchar * qangle,
const float angle_scale, const char correct_gamma, const int cnbins)
{
const int x = get_global_id(0);
const int tid = get_local_id(0);

278
modules/ocl/src/opencl/pyrlk.cl
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@ -184,6 +184,209 @@ float linearFilter_float(__global const float* src, int srcStep, int cn, float2
}
#define BUFFER 64
#ifdef CPU
void reduce3(float val1, float val2, float val3, __local float* smem1, __local float* smem2, __local float* smem3, int tid)
{
smem1[tid] = val1;
smem2[tid] = val2;
smem3[tid] = val3;
barrier(CLK_LOCAL_MEM_FENCE);
#if BUFFER > 128
if (tid < 128)
{
smem1[tid] = val1 += smem1[tid + 128];
smem2[tid] = val2 += smem2[tid + 128];
smem3[tid] = val3 += smem3[tid + 128];
}
barrier(CLK_LOCAL_MEM_FENCE);
#endif
#if BUFFER > 64
if (tid < 64)
{
smem1[tid] = val1 += smem1[tid + 64];
smem2[tid] = val2 += smem2[tid + 64];
smem3[tid] = val3 += smem3[tid + 64];
}
barrier(CLK_LOCAL_MEM_FENCE);
#endif
if (tid < 32)
{
smem1[tid] = val1 += smem1[tid + 32];
smem2[tid] = val2 += smem2[tid + 32];
smem3[tid] = val3 += smem3[tid + 32];
}
barrier(CLK_LOCAL_MEM_FENCE);
if (tid < 16)
{
smem1[tid] = val1 += smem1[tid + 16];
smem2[tid] = val2 += smem2[tid + 16];
smem3[tid] = val3 += smem3[tid + 16];
}
barrier(CLK_LOCAL_MEM_FENCE);
if (tid < 8)
{
smem1[tid] = val1 += smem1[tid + 8];
smem2[tid] = val2 += smem2[tid + 8];
smem3[tid] = val3 += smem3[tid + 8];
}
barrier(CLK_LOCAL_MEM_FENCE);
if (tid < 4)
{
smem1[tid] = val1 += smem1[tid + 4];
smem2[tid] = val2 += smem2[tid + 4];
smem3[tid] = val3 += smem3[tid + 4];
}
barrier(CLK_LOCAL_MEM_FENCE);
if (tid < 2)
{
smem1[tid] = val1 += smem1[tid + 2];
smem2[tid] = val2 += smem2[tid + 2];
smem3[tid] = val3 += smem3[tid + 2];
}
barrier(CLK_LOCAL_MEM_FENCE);
if (tid < 1)
{
smem1[BUFFER] = val1 += smem1[tid + 1];
smem2[BUFFER] = val2 += smem2[tid + 1];
smem3[BUFFER] = val3 += smem3[tid + 1];
}
barrier(CLK_LOCAL_MEM_FENCE);
}
void reduce2(float val1, float val2, volatile __local float* smem1, volatile __local float* smem2, int tid)
{
smem1[tid] = val1;
smem2[tid] = val2;
barrier(CLK_LOCAL_MEM_FENCE);
#if BUFFER > 128
if (tid < 128)
{
smem1[tid] = (val1 += smem1[tid + 128]);
smem2[tid] = (val2 += smem2[tid + 128]);
}
barrier(CLK_LOCAL_MEM_FENCE);
#endif
#if BUFFER > 64
if (tid < 64)
{
smem1[tid] = (val1 += smem1[tid + 64]);
smem2[tid] = (val2 += smem2[tid + 64]);
}
barrier(CLK_LOCAL_MEM_FENCE);
#endif
if (tid < 32)
{
smem1[tid] = (val1 += smem1[tid + 32]);
smem2[tid] = (val2 += smem2[tid + 32]);
}
barrier(CLK_LOCAL_MEM_FENCE);
if (tid < 16)
{
smem1[tid] = (val1 += smem1[tid + 16]);
smem2[tid] = (val2 += smem2[tid + 16]);
}
barrier(CLK_LOCAL_MEM_FENCE);
if (tid < 8)
{
smem1[tid] = (val1 += smem1[tid + 8]);
smem2[tid] = (val2 += smem2[tid + 8]);
}
barrier(CLK_LOCAL_MEM_FENCE);
if (tid < 4)
{
smem1[tid] = (val1 += smem1[tid + 4]);
smem2[tid] = (val2 += smem2[tid + 4]);
}
barrier(CLK_LOCAL_MEM_FENCE);
if (tid < 2)
{
smem1[tid] = (val1 += smem1[tid + 2]);
smem2[tid] = (val2 += smem2[tid + 2]);
}
barrier(CLK_LOCAL_MEM_FENCE);
if (tid < 1)
{
smem1[BUFFER] = (val1 += smem1[tid + 1]);
smem2[BUFFER] = (val2 += smem2[tid + 1]);
}
barrier(CLK_LOCAL_MEM_FENCE);
}
void reduce1(float val1, volatile __local float* smem1, int tid)
{
smem1[tid] = val1;
barrier(CLK_LOCAL_MEM_FENCE);
#if BUFFER > 128
if (tid < 128)
{
smem1[tid] = (val1 += smem1[tid + 128]);
}
barrier(CLK_LOCAL_MEM_FENCE);
#endif
#if BUFFER > 64
if (tid < 64)
{
smem1[tid] = (val1 += smem1[tid + 64]);
}
barrier(CLK_LOCAL_MEM_FENCE);
#endif
if (tid < 32)
{
smem1[tid] = (val1 += smem1[tid + 32]);
}
barrier(CLK_LOCAL_MEM_FENCE);
if (tid < 16)
{
smem1[tid] = (val1 += smem1[tid + 16]);
}
barrier(CLK_LOCAL_MEM_FENCE);
if (tid < 8)
{
smem1[tid] = (val1 += smem1[tid + 8]);
}
barrier(CLK_LOCAL_MEM_FENCE);
if (tid < 4)
{
smem1[tid] = (val1 += smem1[tid + 4]);
}
barrier(CLK_LOCAL_MEM_FENCE);
if (tid < 2)
{
smem1[tid] = (val1 += smem1[tid + 2]);
}
barrier(CLK_LOCAL_MEM_FENCE);
if (tid < 1)
{
smem1[BUFFER] = (val1 += smem1[tid + 1]);
}
barrier(CLK_LOCAL_MEM_FENCE);
}
#else
void reduce3(float val1, float val2, float val3, __local float* smem1, __local float* smem2, __local float* smem3, int tid)
{
smem1[tid] = val1;
@ -325,6 +528,7 @@ void reduce1(float val1, __local float* smem1, int tid)
vmem1[tid] = val1 += vmem1[tid + 1];
}
}
#endif
#define SCALE (1.0f / (1 << 20))
#define THRESHOLD 0.01f
@ -411,14 +615,20 @@ void GetError4(image2d_t J, const float x, const float y, const float4* Pch, flo
*errval += fabs(diff.x) + fabs(diff.y) + fabs(diff.z);
}
#define GRIDSIZE 3
__kernel void lkSparse_C1_D5(image2d_t I, image2d_t J,
__global const float2* prevPts, int prevPtsStep, __global float2* nextPts, int nextPtsStep, __global uchar* status, __global float* err,
const int level, const int rows, const int cols, int PATCH_X, int PATCH_Y, int cn, int c_winSize_x, int c_winSize_y, int c_iters, char calcErr)
{
#ifdef CPU
__local float smem1[BUFFER+1];
__local float smem2[BUFFER+1];
__local float smem3[BUFFER+1];
#else
__local float smem1[BUFFER];
__local float smem2[BUFFER];
__local float smem3[BUFFER];
#endif
unsigned int xid=get_local_id(0);
unsigned int yid=get_local_id(1);
@ -431,7 +641,7 @@ __kernel void lkSparse_C1_D5(image2d_t I, image2d_t J,
const int tid = mad24(yid, xsize, xid);
float2 prevPt = prevPts[gid] / (1 << level);
float2 prevPt = prevPts[gid] / (float2)(1 << level);
if (prevPt.x < 0 || prevPt.x >= cols || prevPt.y < 0 || prevPt.y >= rows)
{
@ -450,9 +660,9 @@ __kernel void lkSparse_C1_D5(image2d_t I, image2d_t J,
float A12 = 0;
float A22 = 0;
float I_patch[3][3];
float dIdx_patch[3][3];
float dIdy_patch[3][3];
float I_patch[GRIDSIZE][GRIDSIZE];
float dIdx_patch[GRIDSIZE][GRIDSIZE];
float dIdy_patch[GRIDSIZE][GRIDSIZE];
yBase=yid;
{
@ -512,12 +722,19 @@ __kernel void lkSparse_C1_D5(image2d_t I, image2d_t J,
&I_patch[2][2], &dIdx_patch[2][2], &dIdy_patch[2][2],
&A11, &A12, &A22);
}
reduce3(A11, A12, A22, smem1, smem2, smem3, tid);
barrier(CLK_LOCAL_MEM_FENCE);
#ifdef CPU
A11 = smem1[BUFFER];
A12 = smem2[BUFFER];
A22 = smem3[BUFFER];
#else
A11 = smem1[0];
A12 = smem2[0];
A22 = smem3[0];
#endif
float D = A11 * A22 - A12 * A12;
@ -609,8 +826,13 @@ __kernel void lkSparse_C1_D5(image2d_t I, image2d_t J,
reduce2(b1, b2, smem1, smem2, tid);
barrier(CLK_LOCAL_MEM_FENCE);
#ifdef CPU
b1 = smem1[BUFFER];
b2 = smem2[BUFFER];
#else
b1 = smem1[0];
b2 = smem2[0];
#endif
float2 delta;
delta.x = A12 * b2 - A22 * b1;
@ -685,18 +907,28 @@ __kernel void lkSparse_C1_D5(image2d_t I, image2d_t J,
nextPts[gid] = prevPt;
if (calcErr)
err[gid] = smem1[0] / (c_winSize_x * c_winSize_y);
#ifdef CPU
err[gid] = smem1[BUFFER] / (float)(c_winSize_x * c_winSize_y);
#else
err[gid] = smem1[0] / (float)(c_winSize_x * c_winSize_y);
#endif
}
}
__kernel void lkSparse_C4_D5(image2d_t I, image2d_t J,
__global const float2* prevPts, int prevPtsStep, __global float2* nextPts, int nextPtsStep, __global uchar* status, __global float* err,
const int level, const int rows, const int cols, int PATCH_X, int PATCH_Y, int cn, int c_winSize_x, int c_winSize_y, int c_iters, char calcErr)
{
__local float smem1[BUFFER];
__local float smem2[BUFFER];
__local float smem3[BUFFER];
#ifdef CPU
__local float smem1[BUFFER+1];
__local float smem2[BUFFER+1];
__local float smem3[BUFFER+1];
#else
__local float smem1[BUFFER];
__local float smem2[BUFFER];
__local float smem3[BUFFER];
#endif
unsigned int xid=get_local_id(0);
unsigned int yid=get_local_id(1);
@ -709,7 +941,7 @@ __kernel void lkSparse_C4_D5(image2d_t I, image2d_t J,
const int tid = mad24(yid, xsize, xid);
float2 nextPt = prevPts[gid]/(1<<level);
float2 nextPt = prevPts[gid]/(float2)(1<<level);
if (nextPt.x < 0 || nextPt.x >= cols || nextPt.y < 0 || nextPt.y >= rows)
{
@ -725,9 +957,9 @@ __kernel void lkSparse_C4_D5(image2d_t I, image2d_t J,
// extract the patch from the first image, compute covariation matrix of derivatives
float A11 = 0;
float A12 = 0;
float A22 = 0;
float A11 = 0.0f;
float A12 = 0.0f;
float A22 = 0.0f;
float4 I_patch[8];
float4 dIdx_patch[8];
@ -797,9 +1029,15 @@ __kernel void lkSparse_C4_D5(image2d_t I, image2d_t J,
reduce3(A11, A12, A22, smem1, smem2, smem3, tid);
barrier(CLK_LOCAL_MEM_FENCE);
#ifdef CPU
A11 = smem1[BUFFER];
A12 = smem2[BUFFER];
A22 = smem3[BUFFER];
#else
A11 = smem1[0];
A12 = smem2[0];
A22 = smem3[0];
#endif
float D = A11 * A22 - A12 * A12;
@ -888,12 +1126,16 @@ __kernel void lkSparse_C4_D5(image2d_t I, image2d_t J,
&b1, &b2);
}
reduce2(b1, b2, smem1, smem2, tid);
barrier(CLK_LOCAL_MEM_FENCE);
#ifdef CPU
b1 = smem1[BUFFER];
b2 = smem2[BUFFER];
#else
b1 = smem1[0];
b2 = smem2[0];
#endif
float2 delta;
delta.x = A12 * b2 - A22 * b1;
@ -967,7 +1209,11 @@ __kernel void lkSparse_C4_D5(image2d_t I, image2d_t J,
nextPts[gid] = nextPt;
if (calcErr)
err[gid] = smem1[0] / (3 * c_winSize_x * c_winSize_y);
#ifdef CPU
err[gid] = smem1[BUFFER] / (float)(3 * c_winSize_x * c_winSize_y);
#else
err[gid] = smem1[0] / (float)(3 * c_winSize_x * c_winSize_y);
#endif
}
}

78
modules/ocl/src/opencl/stereobm.cl
Unescape View File

@ -226,9 +226,9 @@ __kernel void stereoKernel(__global unsigned char *left, __global unsigned char
volatile __local unsigned int *col_ssd_extra = get_local_id(0) < (2 * radius) ? col_ssd + BLOCK_W : 0;
int X = get_group_id(0) * BLOCK_W + get_local_id(0) + maxdisp + radius;
// int Y = get_group_id(1) * ROWSperTHREAD + radius;
// int Y = get_group_id(1) * ROWSperTHREAD + radius;
#define Y (get_group_id(1) * ROWSperTHREAD + radius)
#define Y (get_group_id(1) * ROWSperTHREAD + radius)
volatile __global unsigned int* minSSDImage = cminSSDImage + X + Y * cminSSD_step;
__global unsigned char* disparImage = disp + X + Y * disp_step;
@ -251,9 +251,9 @@ __kernel void stereoKernel(__global unsigned char *left, __global unsigned char
barrier(CLK_LOCAL_MEM_FENCE); //before MinSSD function
uint2 minSSD = MinSSD(col_ssd_cache + get_local_id(0), col_ssd, radius);
if (X < cwidth - radius && Y < cheight - radius)
{
uint2 minSSD = MinSSD(col_ssd_cache + get_local_id(0), col_ssd, radius);
if (minSSD.x < minSSDImage[0])
{
disparImage[0] = (unsigned char)(d + minSSD.y);
@ -264,7 +264,7 @@ __kernel void stereoKernel(__global unsigned char *left, __global unsigned char
for(int row = 1; row < end_row; row++)
{
int idx1 = y_tex * img_step + x_tex;
int idx2 = (y_tex + (2 * radius + 1)) * img_step + x_tex;
int idx2 = min(y_tex + (2 * radius + 1), cheight - 1) * img_step + x_tex;
barrier(CLK_GLOBAL_MEM_FENCE);
barrier(CLK_LOCAL_MEM_FENCE);
@ -278,10 +278,10 @@ __kernel void stereoKernel(__global unsigned char *left, __global unsigned char
barrier(CLK_LOCAL_MEM_FENCE);
uint2 minSSD = MinSSD(col_ssd_cache + get_local_id(0), col_ssd, radius);
if (X < cwidth - radius && row < cheight - radius - Y)
{
int idx = row * cminSSD_step;
uint2 minSSD = MinSSD(col_ssd_cache + get_local_id(0), col_ssd, radius);
if (minSSD.x < minSSDImage[idx])
{
disparImage[disp_step * row] = (unsigned char)(d + minSSD.y);
@ -378,50 +378,50 @@ __kernel void textureness_kernel(__global unsigned char *disp, int disp_rows, in
int beg_row = group_id_y * RpT;
int end_row = min(beg_row + RpT, disp_rows);
// if (x < disp_cols)
// {
int y = beg_row;
// if (x < disp_cols)
// {
int y = beg_row;
float sum = 0;
float sum_extra = 0;
float sum = 0;
float sum_extra = 0;
for(int i = y - winsz2; i <= y + winsz2; ++i)
{
sum += sobel(input, x - winsz2, i, input_rows, input_cols);
if (cols_extra)
sum_extra += sobel(input, x + group_size_x - winsz2, i, input_rows, input_cols);
}
for(int i = y - winsz2; i <= y + winsz2; ++i)
{
sum += sobel(input, x - winsz2, i, input_rows, input_cols);
if (cols_extra)
sum_extra += sobel(input, x + group_size_x - winsz2, i, input_rows, input_cols);
}
*cols = sum;
if (cols_extra)
*cols_extra = sum_extra;
barrier(CLK_LOCAL_MEM_FENCE);
float sum_win = CalcSums(cols, cols_cache + local_id_x, winsz) * 255;
if (sum_win < threshold)
disp[y * disp_step + x] = 0;
barrier(CLK_LOCAL_MEM_FENCE);
for(int y = beg_row + 1; y < end_row; ++y)
{
sum = sum - sobel(input, x - winsz2, y - winsz2 - 1, input_rows, input_cols) +
sobel(input, x - winsz2, y + winsz2, input_rows, input_cols);
*cols = sum;
if (cols_extra)
{
sum_extra = sum_extra - sobel(input, x + group_size_x - winsz2, y - winsz2 - 1,input_rows, input_cols)
+ sobel(input, x + group_size_x - winsz2, y + winsz2, input_rows, input_cols);
*cols_extra = sum_extra;
}
barrier(CLK_LOCAL_MEM_FENCE);
float sum_win = CalcSums(cols, cols_cache + local_id_x, winsz) * 255;
if (sum_win < threshold)
disp[y * disp_step + x] = 0;
barrier(CLK_LOCAL_MEM_FENCE);
for(int y = beg_row + 1; y < end_row; ++y)
{
sum = sum - sobel(input, x - winsz2, y - winsz2 - 1, input_rows, input_cols) +
sobel(input, x - winsz2, y + winsz2, input_rows, input_cols);
*cols = sum;
if (cols_extra)
{
sum_extra = sum_extra - sobel(input, x + group_size_x - winsz2, y - winsz2 - 1,input_rows, input_cols)
+ sobel(input, x + group_size_x - winsz2, y + winsz2, input_rows, input_cols);
*cols_extra = sum_extra;
}
barrier(CLK_LOCAL_MEM_FENCE);
float sum_win = CalcSums(cols, cols_cache + local_id_x, winsz) * 255;
if (sum_win < threshold)
disp[y * disp_step + x] = 0;
barrier(CLK_LOCAL_MEM_FENCE);
}
// }
}
// }
}

520
modules/ocl/src/pyrlk.cpp
Unescape View File

@ -16,7 +16,7 @@
//
// @Authors
// Dachuan Zhao, dachuan@multicorewareinc.com
// Yao Wang, yao@multicorewareinc.com
// Yao Wang, bitwangyaoyao@gmail.com
// Nathan, liujun@multicorewareinc.com
//
// Redistribution and use in source and binary forms, with or without modification,
@ -47,6 +47,7 @@
#include "precomp.hpp"
using namespace std;
using namespace cv;
using namespace cv::ocl;
@ -58,11 +59,7 @@ 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;
}
}
@ -105,364 +102,7 @@ void calcPatchSize(cv::Size winSize, int cn, dim3 &block, dim3 &patch, bool isDe
}
}
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";
stringstream idxStr;
idxStr << src.depth();
kernelName += idxStr.str();
float alpha_f = (float)alpha, beta_f = (float)beta;
CV_DbgAssert(src.rows == dst.rows && src.cols == dst.cols);
vector<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( make_pair( sizeof(cl_mem) , (void *)&src.data ));
args.push_back( make_pair( sizeof(cl_mem) , (void *)&dst.data ));
args.push_back( make_pair( sizeof(cl_int) , (void *)&src.cols ));
args.push_back( make_pair( sizeof(cl_int) , (void *)&src.rows ));
args.push_back( make_pair( sizeof(cl_int) , (void *)&srcstep_in_pixel ));
args.push_back( make_pair( sizeof(cl_int) , (void *)&srcoffset_in_pixel ));
args.push_back( make_pair( sizeof(cl_int) , (void *)&dststep_in_pixel ));
args.push_back( make_pair( sizeof(cl_int) , (void *)&dstoffset_in_pixel ));
args.push_back( make_pair( sizeof(cl_float) , (void *)&alpha_f ));
args.push_back( 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)
{
vector<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( make_pair( sizeof(cl_uchar) , (void *)&val.uval.s[0] ));
break;
case 4:
sprintf(compile_option, "-D GENTYPE=uchar4");
args.push_back( 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( make_pair( sizeof(cl_char) , (void *)&val.cval.s[0] ));
break;
case 4:
sprintf(compile_option, "-D GENTYPE=char4");
args.push_back( 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( make_pair( sizeof(cl_ushort) , (void *)&val.usval.s[0] ));
break;
case 4:
sprintf(compile_option, "-D GENTYPE=ushort4");
args.push_back( 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( make_pair( sizeof(cl_short) , (void *)&val.shval.s[0] ));
break;
case 4:
sprintf(compile_option, "-D GENTYPE=short4");
args.push_back( 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( 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( make_pair( sizeof(cl_int2) , (void *)&i2val ));
break;
case 4:
sprintf(compile_option, "-D GENTYPE=int4");
args.push_back( 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( make_pair( sizeof(cl_float) , (void *)&val.fval.s[0] ));
break;
case 4:
sprintf(compile_option, "-D GENTYPE=float4");
args.push_back( 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( make_pair( sizeof(cl_double) , (void *)&val.dval.s[0] ));
break;
case 4:
sprintf(compile_option, "-D GENTYPE=double4");
args.push_back( 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( make_pair( sizeof(cl_mem) , (void *)&dst.data ));
args.push_back( make_pair( sizeof(cl_int) , (void *)&dst.cols ));
args.push_back( make_pair( sizeof(cl_int) , (void *)&dst.rows ));
args.push_back( make_pair( sizeof(cl_int) , (void *)&step_in_pixel ));
args.push_back( 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( make_pair( sizeof(cl_mem) , (void *)&dst.data ));
args.push_back( make_pair( sizeof(cl_int) , (void *)&dst.cols ));
args.push_back( make_pair( sizeof(cl_int) , (void *)&dst.rows ));
args.push_back( make_pair( sizeof(cl_int) , (void *)&step_in_pixel ));
args.push_back( 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);
// vector<pair<size_t , const void *> > args;
// std::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( make_pair( sizeof(cl_mem) , (void *)&src.data ));
// args.push_back( make_pair( sizeof(cl_mem) , (void *)&dst.data ));
// args.push_back( make_pair( sizeof(cl_mem) , (void *)&mask.data ));
// args.push_back( make_pair( sizeof(cl_int) , (void *)&src.cols ));
// args.push_back( make_pair( sizeof(cl_int) , (void *)&src.rows ));
// args.push_back( make_pair( sizeof(cl_int) , (void *)&srcstep_in_pixel ));
// args.push_back( make_pair( sizeof(cl_int) , (void *)&srcoffset_in_pixel ));
// args.push_back( make_pair( sizeof(cl_int) , (void *)&dststep_in_pixel ));
// args.push_back( make_pair( sizeof(cl_int) , (void *)&dstoffset_in_pixel ));
// args.push_back( make_pair( sizeof(cl_int) , (void *)&mask.step ));
// args.push_back( 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)
static void multiply_cus(const oclMat &src1, oclMat &dst, float scalar)
{
if(!src1.clCxt->supportsFeature(Context::CL_DOUBLE) && src1.type() == CV_64F)
{
@ -470,9 +110,6 @@ static void arithmetic_run(const oclMat &src1, oclMat &dst, string kernelName, c
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);
@ -480,24 +117,8 @@ static void arithmetic_run(const oclMat &src1, oclMat &dst, string kernelName, c
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
@ -508,67 +129,20 @@ static void arithmetic_run(const oclMat &src1, oclMat &dst, string kernelName, c
args.push_back( make_pair( sizeof(cl_mem), (void *)&src1.data ));
args.push_back( make_pair( sizeof(cl_int), (void *)&src1.step ));
args.push_back( make_pair( sizeof(cl_int), (void *)&src1.offset ));
//args.push_back( make_pair( sizeof(cl_mem), (void *)&src2.data ));
//args.push_back( make_pair( sizeof(cl_int), (void *)&src2.step ));
//args.push_back( make_pair( sizeof(cl_int), (void *)&src2.offset ));
args.push_back( make_pair( sizeof(cl_mem), (void *)&dst.data ));
args.push_back( make_pair( sizeof(cl_int), (void *)&dst.step ));
args.push_back( make_pair( sizeof(cl_int), (void *)&dst.offset ));
args.push_back( make_pair( sizeof(cl_int), (void *)&src1.rows ));
args.push_back( make_pair( sizeof(cl_int), (void *)&src1.cols ));
args.push_back( make_pair( sizeof(cl_int), (void *)&dst_step1 ));
args.push_back( make_pair( sizeof(float), (float *)&scalar ));
//if(_scalar != NULL)
//{
float scalar1 = *((float *)_scalar);
args.push_back( 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};
vector<pair<size_t , const void *> > args;
args.push_back( make_pair( sizeof(cl_mem), (void *)&src.data ));
args.push_back( make_pair( sizeof(cl_int), (void *)&src.step ));
args.push_back( make_pair( sizeof(cl_int), (void *)&src.rows));
args.push_back( make_pair( sizeof(cl_int), (void *)&src.cols));
args.push_back( make_pair( sizeof(cl_mem), (void *)&dst.data ));
args.push_back( make_pair( sizeof(cl_int), (void *)&dst.step ));
args.push_back( 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);
openCLExecuteKernel(clCxt, &arithm_mul, "arithm_muls", globalThreads, localThreads, args, -1, src1.depth());
}
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)
const oclMat &prevPts, oclMat &nextPts, oclMat &status, oclMat& err, bool /*GET_MIN_EIGENVALS*/, int ptcount,
int level, dim3 patch, Size winSize, int iters)
{
Context *clCxt = I.clCxt;
int elemCntPerRow = I.step / I.elemSize();
@ -613,15 +187,26 @@ static void lkSparse_run(oclMat &I, oclMat &J,
args.push_back( make_pair( sizeof(cl_int), (void *)&iters ));
args.push_back( make_pair( sizeof(cl_char), (void *)&calcErr ));
if(isImageSupported)
bool is_cpu;
queryDeviceInfo(IS_CPU_DEVICE, &is_cpu);
if (is_cpu)
{
openCLExecuteKernel2(clCxt, &pyrlk, kernelName, globalThreads, localThreads, args, I.oclchannels(), I.depth(), CLFLUSH);
openCLExecuteKernel(clCxt, &pyrlk, kernelName, globalThreads, localThreads, args, I.oclchannels(), I.depth(), (char*)" -D CPU");
releaseTexture(ITex);
releaseTexture(JTex);
}
else
{
openCLExecuteKernel2(clCxt, &pyrlk_no_image, kernelName, globalThreads, localThreads, args, I.oclchannels(), I.depth(), CLFLUSH);
if(isImageSupported)
{
openCLExecuteKernel(clCxt, &pyrlk, kernelName, globalThreads, localThreads, args, I.oclchannels(), I.depth());
releaseTexture(ITex);
releaseTexture(JTex);
}
else
{
openCLExecuteKernel(clCxt, &pyrlk_no_image, kernelName, globalThreads, localThreads, args, I.oclchannels(), I.depth());
}
}
}
@ -631,7 +216,7 @@ void cv::ocl::PyrLKOpticalFlow::sparse(const oclMat &prevImg, const oclMat &next
{
nextPts.release();
status.release();
//if (err) err->release();
if (err) err->release();
return;
}
@ -657,13 +242,11 @@ void cv::ocl::PyrLKOpticalFlow::sparse(const oclMat &prevImg, const oclMat &next
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));
status.setTo(Scalar::all(1));
bool errMat = false;
if (!err)
@ -673,7 +256,6 @@ void cv::ocl::PyrLKOpticalFlow::sparse(const oclMat &prevImg, const oclMat &next
}
else
ensureSizeIsEnough(1, prevPts.cols, CV_32FC1, *err);
//ensureSizeIsEnough(1, prevPts.cols, CV_32FC1, err);
// build the image pyramids.
@ -682,25 +264,14 @@ void cv::ocl::PyrLKOpticalFlow::sparse(const oclMat &prevImg, const oclMat &next
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);
prevImg.convertTo(prevPyr_[0], CV_32F);
nextImg.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]);
pyrDown(prevPyr_[level - 1], prevPyr_[level]);
pyrDown(nextPyr_[level - 1], nextPyr_[level]);
}
// dI/dx ~ Ix, dI/dy ~ Iy
@ -709,17 +280,15 @@ void cv::ocl::PyrLKOpticalFlow::sparse(const oclMat &prevImg, const oclMat &next
{
lkSparse_run(prevPyr_[level], nextPyr_[level],
prevPts, nextPts, status, *err, getMinEigenVals, prevPts.cols,
level, /*block, */patch, winSize, iters);
level, 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)
oclMat &prevU, oclMat &prevV, oclMat *err, Size winSize, int iters)
{
Context *clCxt = I.clCxt;
bool isImageSupported = support_image2d();
@ -754,11 +323,6 @@ static void lkDense_run(oclMat &I, oclMat &J, oclMat &u, oclMat &v,
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);
vector<pair<size_t , const void *> > args;
args.push_back( make_pair( sizeof(cl_mem), (void *)&ITex ));
@ -787,15 +351,14 @@ static void lkDense_run(oclMat &I, oclMat &J, oclMat &u, oclMat &v,
if (isImageSupported)
{
openCLExecuteKernel2(clCxt, &pyrlk, kernelName, globalThreads, localThreads, args, I.oclchannels(), I.depth(), CLFLUSH);
openCLExecuteKernel(clCxt, &pyrlk, kernelName, globalThreads, localThreads, args, I.oclchannels(), I.depth());
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);
openCLExecuteKernel(clCxt, &pyrlk_no_image, kernelName, globalThreads, localThreads, args, I.oclchannels(), I.depth());
}
}
@ -813,23 +376,20 @@ void cv::ocl::PyrLKOpticalFlow::dense(const oclMat &prevImg, const oclMat &nextI
nextPyr_.resize(maxLevel + 1);
prevPyr_[0] = prevImg;
//nextImg.convertTo(nextPyr_[0], CV_32F);
convertTo(nextImg, nextPyr_[0], CV_32F);
nextImg.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]);
pyrDown(prevPyr_[level - 1], prevPyr_[level]);
pyrDown(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));
uPyr_[1].setTo(Scalar::all(0));
vPyr_[1].setTo(Scalar::all(0));
Size winSize2i(winSize.width, winSize.height);
@ -846,10 +406,6 @@ void cv::ocl::PyrLKOpticalFlow::dense(const oclMat &prevImg, const oclMat &nextI
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());
uPyr_[idx].copyTo(u);
vPyr_[idx].copyTo(v);
}

7
modules/ocl/test/main.cpp
Unescape View File

@ -115,10 +115,9 @@ int main(int argc, char **argv)
std::cout << "platform invalid\n";
return -1;
}
if(pid != 0 || device != 0)
{
setDevice(oclinfo[pid], device);
}
setDevice(oclinfo[pid], device);
cout << "Device type:" << type << endl << "Device name:" << oclinfo[pid].DeviceName[device] << endl;
return RUN_ALL_TESTS();
}

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