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Commit 57120c1a authored by Alexander Alekhin's avatar Alexander Alekhin
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ocl: remove support_image2d(): we target on OpenCL 1.1 (with image2d support by default)

parent c0265c60
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Showing with 44 additions and 898 deletions
modules/nonfree/src/surf.ocl.cpp
View file @ 57120c1a
......@@ -55,20 +55,11 @@ namespace cv
{
namespace ocl
{
static const char noImage2dOption[] = "-D DISABLE_IMAGE2D";
static bool use_image2d = false;
static void openCLExecuteKernelSURF(Context *clCxt, const cv::ocl::ProgramEntry* source, string kernelName, size_t globalThreads[3],
size_t localThreads[3], std::vector< std::pair<size_t, const void *> > &args, int channels, int depth)
{
char optBuf [100] = {0};
char * optBufPtr = optBuf;
if( !use_image2d )
{
strcat(optBufPtr, noImage2dOption);
optBufPtr += strlen(noImage2dOption);
}
cl_kernel kernel;
kernel = openCLGetKernelFromSource(clCxt, source, kernelName, optBufPtr);
size_t wave_size = queryWaveFrontSize(kernel);
......@@ -149,13 +140,10 @@ public:
counters.setTo(Scalar::all(0));
integral(img, surf_.sum);
use_image2d = support_image2d();
if(use_image2d)
{
bindImgTex(img, imgTex);
bindImgTex(surf_.sum, sumTex);
finish();
}
bindImgTex(img, imgTex);
bindImgTex(surf_.sum, sumTex);
finish();
maskSumTex = 0;
......
modules/ocl/include/opencv2/ocl/private/util.hpp
View file @ 57120c1a
......@@ -165,15 +165,11 @@ private:
// for faster clamping, there is no buffer padding for the constructed texture
Ptr<TextureCL> CV_EXPORTS bindTexturePtr(const oclMat &mat);
// returns whether the current context supports image2d_t format or not
bool CV_EXPORTS support_image2d(Context *clCxt = Context::getContext());
bool CV_EXPORTS isCpuDevice();
size_t CV_EXPORTS queryWaveFrontSize(cl_kernel kernel);
inline size_t divUp(size_t total, size_t grain)
{
return (total + grain - 1) / grain;
......
modules/ocl/src/cl_programcache.cpp
View file @ 57120c1a
......@@ -448,26 +448,30 @@ cl_program ProgramCache::getProgram(const Context *ctx, const cv::ocl::ProgramEn
{
stringstream src_sign;
src_sign << source->name;
src_sign << getClContext(ctx);
if (NULL != build_options)
if (source->name)
{
src_sign << "_" << build_options;
}
src_sign << source->name;
src_sign << getClContext(ctx);
if (NULL != build_options)
{
src_sign << "_" << build_options;
}
{
cv::AutoLock lockCache(mutexCache);
cl_program program = ProgramCache::getProgramCache()->progLookup(src_sign.str());
if (!!program)
{
clRetainProgram(program);
return program;
cv::AutoLock lockCache(mutexCache);
cl_program program = ProgramCache::getProgramCache()->progLookup(src_sign.str());
if (!!program)
{
clRetainProgram(program);
return program;
}
}
}
cv::AutoLock lockCache(mutexFiles);
// second check
if (source->name)
{
cv::AutoLock lockCache(mutexCache);
cl_program program = ProgramCache::getProgramCache()->progLookup(src_sign.str());
......@@ -493,6 +497,7 @@ cl_program ProgramCache::getProgram(const Context *ctx, const cv::ocl::ProgramEn
cl_program program = programFileCache.getOrBuildProgram(ctx, source, all_build_options);
//Cache the binary for future use if build_options is null
if (source->name)
{
cv::AutoLock lockCache(mutexCache);
this->addProgram(src_sign.str(), program);
......
modules/ocl/src/gftt.cpp
View file @ 57120c1a
......@@ -202,8 +202,6 @@ void cv::ocl::GoodFeaturesToTrackDetector_OCL::operator ()(const oclMat& image,
CV_Assert(qualityLevel > 0 && minDistance >= 0 && maxCorners >= 0);
CV_Assert(mask.empty() || (mask.type() == CV_8UC1 && mask.size() == image.size()));
CV_DbgAssert(support_image2d());
ensureSizeIsEnough(image.size(), CV_32F, eig_);
if (useHarrisDetector)
......
modules/ocl/src/mcwutil.cpp
View file @ 57120c1a
......@@ -216,41 +216,11 @@ namespace cv
{
return Ptr<TextureCL>(new TextureCL(bindTexture(mat), mat.rows, mat.cols, mat.type()));
}
void releaseTexture(cl_mem& texture)
{
openCLFree(texture);
}
bool support_image2d(Context *clCxt)
{
const cv::ocl::ProgramEntry _kernel = {"test_func", "__kernel void test_func(image2d_t img) {}", NULL};
static bool _isTested = false;
static bool _support = false;
if(_isTested)
{
return _support;
}
try
{
cv::ocl::openCLGetKernelFromSource(clCxt, &_kernel, "test_func");
cv::ocl::finish();
_support = true;
}
catch (const cv::Exception& e)
{
if(e.code == -217)
{
_support = false;
}
else
{
// throw e once again
throw e;
}
}
_isTested = true;
return _support;
}
}//namespace ocl
}//namespace cv
modules/ocl/src/opencl/pyrlk_no_image.cl deleted 100644 → 0
View file @ c0265c60
/*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
// Sen Liu, sen@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*/
#define BUFFER 256
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)
{
volatile __local float *vmem1 = smem1;
volatile __local float *vmem2 = smem2;
volatile __local float *vmem3 = smem3;
vmem1[tid] = val1 += vmem1[tid + 8];
vmem2[tid] = val2 += vmem2[tid + 8];
vmem3[tid] = val3 += vmem3[tid + 8];
vmem1[tid] = val1 += vmem1[tid + 4];
vmem2[tid] = val2 += vmem2[tid + 4];
vmem3[tid] = val3 += vmem3[tid + 4];
vmem1[tid] = val1 += vmem1[tid + 2];
vmem2[tid] = val2 += vmem2[tid + 2];
vmem3[tid] = val3 += vmem3[tid + 2];
vmem1[tid] = val1 += vmem1[tid + 1];
vmem2[tid] = val2 += vmem2[tid + 1];
vmem3[tid] = val3 += vmem3[tid + 1];
}
}
void reduce2(float val1, float val2, __local float *smem1, __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)
{
volatile __local float *vmem1 = smem1;
volatile __local float *vmem2 = smem2;
vmem1[tid] = val1 += vmem1[tid + 8];
vmem2[tid] = val2 += vmem2[tid + 8];
vmem1[tid] = val1 += vmem1[tid + 4];
vmem2[tid] = val2 += vmem2[tid + 4];
vmem1[tid] = val1 += vmem1[tid + 2];
vmem2[tid] = val2 += vmem2[tid + 2];
vmem1[tid] = val1 += vmem1[tid + 1];
vmem2[tid] = val2 += vmem2[tid + 1];
}
}
void reduce1(float val1, __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)
{
volatile __local float *vmem1 = smem1;
vmem1[tid] = val1 += vmem1[tid + 16];
}
barrier(CLK_LOCAL_MEM_FENCE);
if (tid < 8)
{
volatile __local float *vmem1 = smem1;
vmem1[tid] = val1 += vmem1[tid + 8];
vmem1[tid] = val1 += vmem1[tid + 4];
vmem1[tid] = val1 += vmem1[tid + 2];
vmem1[tid] = val1 += vmem1[tid + 1];
}
}
#define SCALE (1.0f / (1 << 20))
#define THRESHOLD 0.01f
#define DIMENSION 21
float readImage2Df_C1(__global const float *image, const float x, const float y, const int rows, const int cols, const int elemCntPerRow)
{
float2 coor = (float2)(x, y);
int i0 = clamp((int)floor(coor.x), 0, cols - 1);
int j0 = clamp((int)floor(coor.y), 0, rows - 1);
int i1 = clamp((int)floor(coor.x) + 1, 0, cols - 1);
int j1 = clamp((int)floor(coor.y) + 1, 0, rows - 1);
float a = coor.x - floor(coor.x);
float b = coor.y - floor(coor.y);
return (1 - a) * (1 - b) * image[mad24(j0, elemCntPerRow, i0)]
+ a * (1 - b) * image[mad24(j0, elemCntPerRow, i1)]
+ (1 - a) * b * image[mad24(j1, elemCntPerRow, i0)]
+ a * b * image[mad24(j1, elemCntPerRow, i1)];
}
__kernel void lkSparse_C1_D5(__global const float *I, __global const float *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, const int elemCntPerRow,
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];
float2 c_halfWin = (float2)((c_winSize_x - 1) >> 1, (c_winSize_y - 1) >> 1);
const int tid = mad24(get_local_id(1), get_local_size(0), get_local_id(0));
float2 prevPt = prevPts[get_group_id(0)] * (1.0f / (1 << level));
if (prevPt.x < 0 || prevPt.x >= cols || prevPt.y < 0 || prevPt.y >= rows)
{
if (tid == 0 && level == 0)
{
status[get_group_id(0)] = 0;
}
return;
}
prevPt -= c_halfWin;
// extract the patch from the first image, compute covariation matrix of derivatives
float A11 = 0;
float A12 = 0;
float A22 = 0;
float I_patch[1][3];
float dIdx_patch[1][3];
float dIdy_patch[1][3];
for (int yBase = get_local_id(1), i = 0; yBase < c_winSize_y; yBase += get_local_size(1), ++i)
{
for (int xBase = get_local_id(0), j = 0; xBase < c_winSize_x; xBase += get_local_size(0), ++j)
{
float x = (prevPt.x + xBase);
float y = (prevPt.y + yBase);
I_patch[i][j] = readImage2Df_C1(I, x, y, rows, cols, elemCntPerRow);
float dIdx = 3.0f * readImage2Df_C1(I, x + 1, y - 1, rows, cols, elemCntPerRow) + 10.0f * readImage2Df_C1(I, x + 1, y, rows, cols, elemCntPerRow) + 3.0f * readImage2Df_C1(I, x + 1, y + 1, rows, cols, elemCntPerRow) -
(3.0f * readImage2Df_C1(I, x - 1, y - 1, rows, cols, elemCntPerRow) + 10.0f * readImage2Df_C1(I, x - 1, y, rows, cols, elemCntPerRow) + 3.0f * readImage2Df_C1(I, x - 1, y + 1, rows, cols, elemCntPerRow));
float dIdy = 3.0f * readImage2Df_C1(I, x - 1, y + 1, rows, cols, elemCntPerRow) + 10.0f * readImage2Df_C1(I, x, y + 1, rows, cols, elemCntPerRow) + 3.0f * readImage2Df_C1(I, x + 1, y + 1, rows, cols, elemCntPerRow) -
(3.0f * readImage2Df_C1(I, x - 1, y - 1, rows, cols, elemCntPerRow) + 10.0f * readImage2Df_C1(I, x, y - 1, rows, cols, elemCntPerRow) + 3.0f * readImage2Df_C1(I, x + 1, y - 1, rows, cols, elemCntPerRow));
dIdx_patch[i][j] = dIdx;
dIdy_patch[i][j] = dIdy;
A11 += dIdx * dIdx;
A12 += dIdx * dIdy;
A22 += dIdy * dIdy;
}
}
reduce3(A11, A12, A22, smem1, smem2, smem3, tid);
barrier(CLK_LOCAL_MEM_FENCE);
A11 = smem1[0];
A12 = smem2[0];
A22 = smem3[0];
float D = A11 * A22 - A12 * A12;
if (D < 1.192092896e-07f)
{
if (tid == 0 && level == 0)
{
status[get_group_id(0)] = 0;
}
return;
}
D = 1.f / D;
A11 *= D;
A12 *= D;
A22 *= D;
float2 nextPt = nextPts[get_group_id(0)];
nextPt = nextPt * 2.0f - c_halfWin;
for (int k = 0; k < c_iters; ++k)
{
if (nextPt.x < -c_halfWin.x || nextPt.x >= cols || nextPt.y < -c_halfWin.y || nextPt.y >= rows)
{
if (tid == 0 && level == 0)
{
status[get_group_id(0)] = 0;
}
return;
}
float b1 = 0;
float b2 = 0;
for (int y = get_local_id(1), i = 0; y < c_winSize_y; y += get_local_size(1), ++i)
{
for (int x = get_local_id(0), j = 0; x < c_winSize_x; x += get_local_size(0), ++j)
{
float diff = (readImage2Df_C1(J, nextPt.x + x, nextPt.y + y, rows, cols, elemCntPerRow) - I_patch[i][j]) * 32.0f;
b1 += diff * dIdx_patch[i][j];
b2 += diff * dIdy_patch[i][j];
}
}
reduce2(b1, b2, smem1, smem2, tid);
barrier(CLK_LOCAL_MEM_FENCE);
b1 = smem1[0];
b2 = smem2[0];
float2 delta;
delta.x = A12 * b2 - A22 * b1;
delta.y = A12 * b1 - A11 * b2;
nextPt += delta;
//if (fabs(delta.x) < THRESHOLD && fabs(delta.y) < THRESHOLD)
// break;
}
float errval = 0.0f;
if (calcErr)
{
for (int y = get_local_id(1), i = 0; y < c_winSize_y; y += get_local_size(1), ++i)
{
for (int x = get_local_id(0), j = 0; x < c_winSize_x; x += get_local_size(0), ++j)
{
float diff = readImage2Df_C1(J, nextPt.x + x, nextPt.y + y, rows, cols, elemCntPerRow) - I_patch[i][j];
errval += fabs(diff);
}
}
reduce1(errval, smem1, tid);
}
if (tid == 0)
{
nextPt += c_halfWin;
nextPts[get_group_id(0)] = nextPt;
if (calcErr)
{
err[get_group_id(0)] = smem1[0] / (c_winSize_x * c_winSize_y);
}
}
}
float4 readImage2Df_C4(__global const float4 *image, const float x, const float y, const int rows, const int cols, const int elemCntPerRow)
{
float2 coor = (float2)(x, y);
int i0 = clamp((int)floor(coor.x), 0, cols - 1);
int j0 = clamp((int)floor(coor.y), 0, rows - 1);
int i1 = clamp((int)floor(coor.x) + 1, 0, cols - 1);
int j1 = clamp((int)floor(coor.y) + 1, 0, rows - 1);
float a = coor.x - floor(coor.x);
float b = coor.y - floor(coor.y);
return (1 - a) * (1 - b) * image[mad24(j0, elemCntPerRow, i0)]
+ a * (1 - b) * image[mad24(j0, elemCntPerRow, i1)]
+ (1 - a) * b * image[mad24(j1, elemCntPerRow, i0)]
+ a * b * image[mad24(j1, elemCntPerRow, i1)];
}
__kernel void lkSparse_C4_D5(__global const float *I, __global const float *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, const int elemCntPerRow,
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];
float2 c_halfWin = (float2)((c_winSize_x - 1) >> 1, (c_winSize_y - 1) >> 1);
const int tid = mad24(get_local_id(1), get_local_size(0), get_local_id(0));
float2 prevPt = prevPts[get_group_id(0)] * (1.0f / (1 << level));
if (prevPt.x < 0 || prevPt.x >= cols || prevPt.y < 0 || prevPt.y >= rows)
{
if (tid == 0 && level == 0)
{
status[get_group_id(0)] = 0;
}
return;
}
prevPt -= c_halfWin;
// extract the patch from the first image, compute covariation matrix of derivatives
float A11 = 0;
float A12 = 0;
float A22 = 0;
float4 I_patch[1][3];
float4 dIdx_patch[1][3];
float4 dIdy_patch[1][3];
__global float4 *ptrI = (__global float4 *)I;
for (int yBase = get_local_id(1), i = 0; yBase < c_winSize_y; yBase += get_local_size(1), ++i)
{
for (int xBase = get_local_id(0), j = 0; xBase < c_winSize_x; xBase += get_local_size(0), ++j)
{
float x = (prevPt.x + xBase);
float y = (prevPt.y + yBase);
I_patch[i][j] = readImage2Df_C4(ptrI, x, y, rows, cols, elemCntPerRow);
float4 dIdx = 3.0f * readImage2Df_C4(ptrI, x + 1, y - 1, rows, cols, elemCntPerRow) + 10.0f * readImage2Df_C4(ptrI, x + 1, y, rows, cols, elemCntPerRow) + 3.0f * readImage2Df_C4(ptrI, x + 1, y + 1, rows, cols, elemCntPerRow) -
(3.0f * readImage2Df_C4(ptrI, x - 1, y - 1, rows, cols, elemCntPerRow) + 10.0f * readImage2Df_C4(ptrI, x - 1, y, rows, cols, elemCntPerRow) + 3.0f * readImage2Df_C4(ptrI, x - 1, y + 1, rows, cols, elemCntPerRow));
float4 dIdy = 3.0f * readImage2Df_C4(ptrI, x - 1, y + 1, rows, cols, elemCntPerRow) + 10.0f * readImage2Df_C4(ptrI, x, y + 1, rows, cols, elemCntPerRow) + 3.0f * readImage2Df_C4(ptrI, x + 1, y + 1, rows, cols, elemCntPerRow) -
(3.0f * readImage2Df_C4(ptrI, x - 1, y - 1, rows, cols, elemCntPerRow) + 10.0f * readImage2Df_C4(ptrI, x, y - 1, rows, cols, elemCntPerRow) + 3.0f * readImage2Df_C4(ptrI, x + 1, y - 1, rows, cols, elemCntPerRow));
dIdx_patch[i][j] = dIdx;
dIdy_patch[i][j] = dIdy;
A11 += (dIdx * dIdx).x + (dIdx * dIdx).y + (dIdx * dIdx).z;
A12 += (dIdx * dIdy).x + (dIdx * dIdy).y + (dIdx * dIdy).z;
A22 += (dIdy * dIdy).x + (dIdy * dIdy).y + (dIdy * dIdy).z;
}
}
reduce3(A11, A12, A22, smem1, smem2, smem3, tid);
barrier(CLK_LOCAL_MEM_FENCE);
A11 = smem1[0];
A12 = smem2[0];
A22 = smem3[0];
float D = A11 * A22 - A12 * A12;
//pD[get_group_id(0)] = D;
if (D < 1.192092896e-07f)
{
if (tid == 0 && level == 0)
{
status[get_group_id(0)] = 0;
}
return;
}
D = 1.f / D;
A11 *= D;
A12 *= D;
A22 *= D;
float2 nextPt = nextPts[get_group_id(0)];
nextPt = nextPt * 2.0f - c_halfWin;
__global float4 *ptrJ = (__global float4 *)J;
for (int k = 0; k < c_iters; ++k)
{
if (nextPt.x < -c_halfWin.x || nextPt.x >= cols || nextPt.y < -c_halfWin.y || nextPt.y >= rows)
{
if (tid == 0 && level == 0)
{
status[get_group_id(0)] = 0;
}
return;
}
float b1 = 0;
float b2 = 0;
for (int y = get_local_id(1), i = 0; y < c_winSize_y; y += get_local_size(1), ++i)
{
for (int x = get_local_id(0), j = 0; x < c_winSize_x; x += get_local_size(0), ++j)
{
float4 diff = (readImage2Df_C4(ptrJ, nextPt.x + x, nextPt.y + y, rows, cols, elemCntPerRow) - I_patch[i][j]) * 32.0f;
b1 += (diff * dIdx_patch[i][j]).x + (diff * dIdx_patch[i][j]).y + (diff * dIdx_patch[i][j]).z;
b2 += (diff * dIdy_patch[i][j]).x + (diff * dIdy_patch[i][j]).y + (diff * dIdy_patch[i][j]).z;
}
}
reduce2(b1, b2, smem1, smem2, tid);
barrier(CLK_LOCAL_MEM_FENCE);
b1 = smem1[0];
b2 = smem2[0];
float2 delta;
delta.x = A12 * b2 - A22 * b1;
delta.y = A12 * b1 - A11 * b2;
nextPt += delta;
//if (fabs(delta.x) < THRESHOLD && fabs(delta.y) < THRESHOLD)
// break;
}
float errval = 0.0f;
if (calcErr)
{
for (int y = get_local_id(1), i = 0; y < c_winSize_y; y += get_local_size(1), ++i)
{
for (int x = get_local_id(0), j = 0; x < c_winSize_x; x += get_local_size(0), ++j)
{
float4 diff = readImage2Df_C4(ptrJ, nextPt.x + x, nextPt.y + y, rows, cols, elemCntPerRow) - I_patch[i][j];
errval += fabs(diff.x) + fabs(diff.y) + fabs(diff.z);
}
}
reduce1(errval, smem1, tid);
}
if (tid == 0)
{
nextPt += c_halfWin;
nextPts[get_group_id(0)] = nextPt;
if (calcErr)
{
err[get_group_id(0)] = smem1[0] / (3 * c_winSize_x * c_winSize_y);
}
}
}
int readImage2Di_C1(__global const int *image, float2 coor, int2 size, const int elemCntPerRow)
{
int i = clamp((int)floor(coor.x), 0, size.x - 1);
int j = clamp((int)floor(coor.y), 0, size.y - 1);
return image[mad24(j, elemCntPerRow, i)];
}
__kernel void lkDense_C1_D0(__global const int *I, __global const int *J, __global float *u, int uStep, __global float *v, int vStep, __global const float *prevU, int prevUStep, __global const float *prevV, int prevVStep,
const int rows, const int cols, /*__global float* err, int errStep, int cn,*/
const int elemCntPerRow, int c_winSize_x, int c_winSize_y, int c_iters, char calcErr)
{
int c_halfWin_x = (c_winSize_x - 1) / 2;
int c_halfWin_y = (c_winSize_y - 1) / 2;
const int patchWidth = get_local_size(0) + 2 * c_halfWin_x;
const int patchHeight = get_local_size(1) + 2 * c_halfWin_y;
__local int smem[8192];
__local int *I_patch = smem;
__local int *dIdx_patch = I_patch + patchWidth * patchHeight;
__local int *dIdy_patch = dIdx_patch + patchWidth * patchHeight;
const int xBase = get_group_id(0) * get_local_size(0);
const int yBase = get_group_id(1) * get_local_size(1);
int2 size = (int2)(cols, rows);
for (int i = get_local_id(1); i < patchHeight; i += get_local_size(1))
{
for (int j = get_local_id(0); j < patchWidth; j += get_local_size(0))
{
float x = xBase - c_halfWin_x + j + 0.5f;
float y = yBase - c_halfWin_y + i + 0.5f;
I_patch[i * patchWidth + j] = readImage2Di_C1(I, (float2)(x, y), size, elemCntPerRow);
// Sharr Deriv
dIdx_patch[i * patchWidth + j] = 3 * readImage2Di_C1(I, (float2)(x + 1, y - 1), size, elemCntPerRow) + 10 * readImage2Di_C1(I, (float2)(x + 1, y), size, elemCntPerRow) + 3 * readImage2Di_C1(I, (float2)(x + 1, y + 1), size, elemCntPerRow) -
(3 * readImage2Di_C1(I, (float2)(x - 1, y - 1), size, elemCntPerRow) + 10 * readImage2Di_C1(I, (float2)(x - 1, y), size, elemCntPerRow) + 3 * readImage2Di_C1(I, (float2)(x - 1, y + 1), size, elemCntPerRow));
dIdy_patch[i * patchWidth + j] = 3 * readImage2Di_C1(I, (float2)(x - 1, y + 1), size, elemCntPerRow) + 10 * readImage2Di_C1(I, (float2)(x, y + 1), size, elemCntPerRow) + 3 * readImage2Di_C1(I, (float2)(x + 1, y + 1), size, elemCntPerRow) -
(3 * readImage2Di_C1(I, (float2)(x - 1, y - 1), size, elemCntPerRow) + 10 * readImage2Di_C1(I, (float2)(x, y - 1), size, elemCntPerRow) + 3 * readImage2Di_C1(I, (float2)(x + 1, y - 1), size, elemCntPerRow));
}
}
barrier(CLK_LOCAL_MEM_FENCE);
// extract the patch from the first image, compute covariation matrix of derivatives
const int x = get_global_id(0);
const int y = get_global_id(1);
if (x >= cols || y >= rows)
{
return;
}
int A11i = 0;
int A12i = 0;
int A22i = 0;
for (int i = 0; i < c_winSize_y; ++i)
{
for (int j = 0; j < c_winSize_x; ++j)
{
int dIdx = dIdx_patch[(get_local_id(1) + i) * patchWidth + (get_local_id(0) + j)];
int dIdy = dIdy_patch[(get_local_id(1) + i) * patchWidth + (get_local_id(0) + j)];
A11i += dIdx * dIdx;
A12i += dIdx * dIdy;
A22i += dIdy * dIdy;
}
}
float A11 = A11i;
float A12 = A12i;
float A22 = A22i;
float D = A11 * A22 - A12 * A12;
//if (calcErr && GET_MIN_EIGENVALS)
// (err + y * errStep)[x] = minEig;
if (D < 1.192092896e-07f)
{
//if (calcErr)
// err(y, x) = 3.402823466e+38f;
return;
}
D = 1.f / D;
A11 *= D;
A12 *= D;
A22 *= D;
float2 nextPt;
nextPt.x = x + prevU[y / 2 * prevUStep / 4 + x / 2] * 2.0f;
nextPt.y = y + prevV[y / 2 * prevVStep / 4 + x / 2] * 2.0f;
for (int k = 0; k < c_iters; ++k)
{
if (nextPt.x < 0 || nextPt.x >= cols || nextPt.y < 0 || nextPt.y >= rows)
{
//if (calcErr)
// err(y, x) = 3.402823466e+38f;
return;
}
int b1 = 0;
int b2 = 0;
for (int i = 0; i < c_winSize_y; ++i)
{
for (int j = 0; j < c_winSize_x; ++j)
{
int iI = I_patch[(get_local_id(1) + i) * patchWidth + get_local_id(0) + j];
int iJ = readImage2Di_C1(J, (float2)(nextPt.x - c_halfWin_x + j + 0.5f, nextPt.y - c_halfWin_y + i + 0.5f), size, elemCntPerRow);
int diff = (iJ - iI) * 32;
int dIdx = dIdx_patch[(get_local_id(1) + i) * patchWidth + (get_local_id(0) + j)];
int dIdy = dIdy_patch[(get_local_id(1) + i) * patchWidth + (get_local_id(0) + j)];
b1 += diff * dIdx;
b2 += diff * dIdy;
}
}
float2 delta;
delta.x = A12 * b2 - A22 * b1;
delta.y = A12 * b1 - A11 * b2;
nextPt.x += delta.x;
nextPt.y += delta.y;
if (fabs(delta.x) < 0.01f && fabs(delta.y) < 0.01f)
{
break;
}
}
u[y * uStep / 4 + x] = nextPt.x - x;
v[y * vStep / 4 + x] = nextPt.y - y;
if (calcErr)
{
int errval = 0;
for (int i = 0; i < c_winSize_y; ++i)
{
for (int j = 0; j < c_winSize_x; ++j)
{
int iI = I_patch[(get_local_id(1) + i) * patchWidth + get_local_id(0) + j];
int iJ = readImage2Di_C1(J, (float2)(nextPt.x - c_halfWin_x + j + 0.5f, nextPt.y - c_halfWin_y + i + 0.5f), size, elemCntPerRow);
errval += abs(iJ - iI);
}
}
//err[y * errStep / 4 + x] = static_cast<float>(errval) / (c_winSize_x * c_winSize_y);
}
}
modules/ocl/src/pyrlk.cpp
View file @ 57120c1a
......@@ -82,18 +82,16 @@ static void lkSparse_run(oclMat &I, oclMat &J,
int level, 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};
size_t localThreads[3] = { 8, 8, 1 };
size_t globalThreads[3] = { 8 * ptcount, 8, 1};
int cn = I.oclchannels();
char calcErr = level==0?1:0;
vector<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;
cl_mem ITex = bindTexture(I);
cl_mem JTex = bindTexture(J);
args.push_back( make_pair( sizeof(cl_mem), (void *)&ITex ));
args.push_back( make_pair( sizeof(cl_mem), (void *)&JTex ));
......@@ -106,8 +104,6 @@ static void lkSparse_run(oclMat &I, oclMat &J,
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 ));
......@@ -120,32 +116,23 @@ static void lkSparse_run(oclMat &I, oclMat &J,
if (is_cpu)
{
openCLExecuteKernel(clCxt, &pyrlk, kernelName, globalThreads, localThreads, args, I.oclchannels(), I.depth(), (char*)" -D CPU");
releaseTexture(ITex);
releaseTexture(JTex);
}
else
{
if(isImageSupported)
{
stringstream idxStr;
idxStr << kernelName << "_C" << I.oclchannels() << "_D" << I.depth();
cl_kernel kernel = openCLGetKernelFromSource(clCxt, &pyrlk, idxStr.str());
int wave_size = (int)queryWaveFrontSize(kernel);
openCLSafeCall(clReleaseKernel(kernel));
static char opt[32] = {0};
sprintf(opt, "-D WAVE_SIZE=%d", wave_size);
openCLExecuteKernel(clCxt, &pyrlk, kernelName, globalThreads, localThreads,
args, I.oclchannels(), I.depth(), opt);
releaseTexture(ITex);
releaseTexture(JTex);
}
else
{
openCLExecuteKernel(clCxt, &pyrlk_no_image, kernelName, globalThreads, localThreads, args, I.oclchannels(), I.depth());
}
stringstream idxStr;
idxStr << kernelName << "_C" << I.oclchannels() << "_D" << I.depth();
cl_kernel kernel = openCLGetKernelFromSource(clCxt, &pyrlk, idxStr.str());
int wave_size = (int)queryWaveFrontSize(kernel);
openCLSafeCall(clReleaseKernel(kernel));
static char opt[32] = {0};
sprintf(opt, "-D WAVE_SIZE=%d", wave_size);
openCLExecuteKernel(clCxt, &pyrlk, kernelName, globalThreads, localThreads,
args, I.oclchannels(), I.depth(), opt);
}
releaseTexture(ITex);
releaseTexture(JTex);
}
void cv::ocl::PyrLKOpticalFlow::sparse(const oclMat &prevImg, const oclMat &nextImg, const oclMat &prevPts, oclMat &nextPts, oclMat &status, oclMat *err)
......@@ -226,37 +213,19 @@ 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_char calcErr = err ? 1 : 0;
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;
}
ITex = bindTexture(I);
JTex = bindTexture(J);
vector<pair<size_t , const void *> > args;
......@@ -273,28 +242,15 @@ static void lkDense_run(oclMat &I, oclMat &J, oclMat &u, oclMat &v,
args.push_back( make_pair( sizeof(cl_int), (void *)&prevV.step ));
args.push_back( make_pair( sizeof(cl_int), (void *)&I.rows ));
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 ));
if (isImageSupported)
{
openCLExecuteKernel(clCxt, &pyrlk, kernelName, globalThreads, localThreads, args, I.oclchannels(), I.depth());
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());
}
releaseTexture(ITex);
releaseTexture(JTex);
}
void cv::ocl::PyrLKOpticalFlow::dense(const oclMat &prevImg, const oclMat &nextImg, oclMat &u, oclMat &v, oclMat *err)
......
modules/ocl/src/tvl1flow.cpp
View file @ 57120c1a
......@@ -411,9 +411,6 @@ void ocl_tvl1flow::estimateU(oclMat &I1wx, oclMat &I1wy, oclMat &grad,
void ocl_tvl1flow::warpBackward(const oclMat &I0, const oclMat &I1, oclMat &I1x, oclMat &I1y, oclMat &u1, oclMat &u2, oclMat &I1w, oclMat &I1wx, oclMat &I1wy, oclMat &grad, oclMat &rho)
{
Context* clCxt = I0.clCxt;
const bool isImgSupported = support_image2d(clCxt);
CV_Assert(isImgSupported);
int u1ElementSize = u1.elemSize();
int u1Step = u1.step/u1ElementSize;
......
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