Skip to content

O
opencv
Commit a55cc601 authored by Andrey Pavlenko's avatar Andrey Pavlenko Committed by OpenCV Buildbot
Browse files
Options

Merge pull request #1606 from ilya-lavrenov:ocl_imgproc

parents 9f5cda79 dfbea351
Hide whitespace changes
Inline Side-by-side
Showing with 184 additions and 356 deletions
modules/ocl/src/imgproc.cpp
View file @ a55cc601
......@@ -102,12 +102,8 @@ namespace cv
static void threshold_8u(const oclMat &src, oclMat &dst, double thresh, double maxVal, int type)
{
CV_Assert( (src.cols == dst.cols) && (src.rows == dst.rows) );
Context *clCxt = src.clCxt;
uchar thresh_uchar = cvFloor(thresh);
uchar max_val = cvRound(maxVal);
string kernelName = "threshold";
size_t cols = (dst.cols + (dst.offset % 16) + 15) / 16;
size_t bSizeX = 16, bSizeY = 16;
......@@ -128,14 +124,11 @@ namespace cv
args.push_back( make_pair(sizeof(cl_uchar), (void *)&thresh_uchar));
args.push_back( make_pair(sizeof(cl_uchar), (void *)&max_val));
args.push_back( make_pair(sizeof(cl_int), (void *)&type));
openCLExecuteKernel(clCxt, &imgproc_threshold, kernelName, globalThreads, localThreads, args, src.oclchannels(), src.depth());
openCLExecuteKernel(src.clCxt, &imgproc_threshold, "threshold", globalThreads, localThreads, args, src.oclchannels(), src.depth());
}
static void threshold_32f(const oclMat &src, oclMat &dst, double thresh, double maxVal, int type)
{
CV_Assert( (src.cols == dst.cols) && (src.rows == dst.rows) );
Context *clCxt = src.clCxt;
float thresh_f = thresh;
float max_val = maxVal;
int dst_offset = (dst.offset >> 2);
......@@ -143,10 +136,7 @@ namespace cv
int src_offset = (src.offset >> 2);
int src_step = (src.step >> 2);
string kernelName = "threshold";
size_t cols = (dst.cols + (dst_offset & 3) + 3) / 4;
//size_t cols = dst.cols;
size_t bSizeX = 16, bSizeY = 16;
size_t gSizeX = cols % bSizeX == 0 ? cols : (cols + bSizeX - 1) / bSizeX * bSizeX;
size_t gSizeY = dst.rows;
......@@ -165,11 +155,12 @@ namespace cv
args.push_back( make_pair(sizeof(cl_float), (void *)&thresh_f));
args.push_back( make_pair(sizeof(cl_float), (void *)&max_val));
args.push_back( make_pair(sizeof(cl_int), (void *)&type));
openCLExecuteKernel(clCxt, &imgproc_threshold, kernelName, globalThreads, localThreads, args, src.oclchannels(), src.depth());
openCLExecuteKernel(src.clCxt, &imgproc_threshold, "threshold", globalThreads, localThreads, args, src.oclchannels(), src.depth());
}
//threshold: support 8UC1 and 32FC1 data type and five threshold type
// threshold: support 8UC1 and 32FC1 data type and five threshold type
double threshold(const oclMat &src, oclMat &dst, double thresh, double maxVal, int type)
{
//TODO: These limitations shall be removed later.
......@@ -184,6 +175,7 @@ namespace cv
return thresh;
}
////////////////////////////////////////////////////////////////////////////////////////////
/////////////////////////////// remap //////////////////////////////////////////////////
////////////////////////////////////////////////////////////////////////////////////////////
......@@ -199,27 +191,26 @@ namespace cv
dst.create(map1.size(), src.type());
string kernelName;
if( map1.type() == CV_32FC2 && !map2.data )
if ( map1.type() == CV_32FC2 && !map2.data )
{
if(interpolation == INTER_LINEAR && borderType == BORDER_CONSTANT)
if (interpolation == INTER_LINEAR && borderType == BORDER_CONSTANT)
kernelName = "remapLNFConstant";
else if(interpolation == INTER_NEAREST && borderType == BORDER_CONSTANT)
else if (interpolation == INTER_NEAREST && borderType == BORDER_CONSTANT)
kernelName = "remapNNFConstant";
}
else if(map1.type() == CV_16SC2 && !map2.data)
else if (map1.type() == CV_16SC2 && !map2.data)
{
if(interpolation == INTER_LINEAR && borderType == BORDER_CONSTANT)
if (interpolation == INTER_LINEAR && borderType == BORDER_CONSTANT)
kernelName = "remapLNSConstant";
else if(interpolation == INTER_NEAREST && borderType == BORDER_CONSTANT)
else if (interpolation == INTER_NEAREST && borderType == BORDER_CONSTANT)
kernelName = "remapNNSConstant";
}
else if(map1.type() == CV_32FC1 && map2.type() == CV_32FC1)
else if (map1.type() == CV_32FC1 && map2.type() == CV_32FC1)
{
if(interpolation == INTER_LINEAR && borderType == BORDER_CONSTANT)
if (interpolation == INTER_LINEAR && borderType == BORDER_CONSTANT)
kernelName = "remapLNF1Constant";
else if (interpolation == INTER_NEAREST && borderType == BORDER_CONSTANT)
kernelName = "remapNNF1Constant";
......@@ -228,30 +219,27 @@ namespace cv
size_t blkSizeX = 16, blkSizeY = 16;
size_t glbSizeX;
int cols = dst.cols;
if(src.type() == CV_8UC1)
if (src.type() == CV_8UC1)
{
cols = (dst.cols + dst.offset % 4 + 3) / 4;
glbSizeX = cols % blkSizeX == 0 ? cols : (cols / blkSizeX + 1) * blkSizeX;
}
else if(src.type() == CV_32FC1 && interpolation == INTER_LINEAR)
else if (src.type() == CV_32FC1 && interpolation == INTER_LINEAR)
{
cols = (dst.cols + (dst.offset >> 2) % 4 + 3) / 4;
glbSizeX = cols % blkSizeX == 0 ? cols : (cols / blkSizeX + 1) * blkSizeX;
}
else
{
glbSizeX = dst.cols % blkSizeX == 0 ? dst.cols : (dst.cols / blkSizeX + 1) * blkSizeX;
}
size_t glbSizeY = dst.rows % blkSizeY == 0 ? dst.rows : (dst.rows / blkSizeY + 1) * blkSizeY;
size_t globalThreads[3] = {glbSizeX, glbSizeY, 1};
size_t localThreads[3] = {blkSizeX, blkSizeY, 1};
float borderFloat[4] = {(float)borderValue[0], (float)borderValue[1], (float)borderValue[2], (float)borderValue[3]};
vector< pair<size_t, const void *> > args;
if(map1.channels() == 2)
if (map1.channels() == 2)
{
args.push_back( make_pair(sizeof(cl_mem), (void *)&dst.data));
args.push_back( make_pair(sizeof(cl_mem), (void *)&src.data));
......@@ -270,16 +258,12 @@ namespace cv
args.push_back( make_pair(sizeof(cl_int), (void *)&map1.rows));
args.push_back( make_pair(sizeof(cl_int), (void *)&cols));
if(src.clCxt->supportsFeature(FEATURE_CL_DOUBLE))
{
if (src.clCxt->supportsFeature(FEATURE_CL_DOUBLE))
args.push_back( make_pair(sizeof(cl_double4), (void *)&borderValue));
}
else
{
args.push_back( make_pair(sizeof(cl_float4), (void *)&borderFloat));
}
}
if(map1.channels() == 1)
if (map1.channels() == 1)
{
args.push_back( make_pair(sizeof(cl_mem), (void *)&dst.data));
args.push_back( make_pair(sizeof(cl_mem), (void *)&src.data));
......@@ -298,14 +282,10 @@ namespace cv
args.push_back( make_pair(sizeof(cl_int), (void *)&map1.cols));
args.push_back( make_pair(sizeof(cl_int), (void *)&map1.rows));
args.push_back( make_pair(sizeof(cl_int), (void *)&cols));
if(src.clCxt->supportsFeature(FEATURE_CL_DOUBLE))
{
if (src.clCxt->supportsFeature(FEATURE_CL_DOUBLE))
args.push_back( make_pair(sizeof(cl_double4), (void *)&borderValue));
}
else
{
args.push_back( make_pair(sizeof(cl_float4), (void *)&borderFloat));
}
}
openCLExecuteKernel(clCxt, &imgproc_remap, kernelName, globalThreads, localThreads, args, src.oclchannels(), src.depth());
}
......@@ -325,31 +305,30 @@ namespace cv
int srcoffset_in_pixel = src.offset / src.elemSize();
int dstStep_in_pixel = dst.step1() / dst.oclchannels();
int dstoffset_in_pixel = dst.offset / dst.elemSize();
//printf("%d %d\n",src.step1() , dst.elemSize());
string kernelName;
if(interpolation == INTER_LINEAR)
if (interpolation == INTER_LINEAR)
kernelName = "resizeLN";
else if(interpolation == INTER_NEAREST)
else if (interpolation == INTER_NEAREST)
kernelName = "resizeNN";
//TODO: improve this kernel
size_t blkSizeX = 16, blkSizeY = 16;
size_t glbSizeX;
if(src.type() == CV_8UC1)
if (src.type() == CV_8UC1)
{
size_t cols = (dst.cols + dst.offset % 4 + 3) / 4;
glbSizeX = cols % blkSizeX == 0 && cols != 0 ? cols : (cols / blkSizeX + 1) * blkSizeX;
}
else
{
glbSizeX = dst.cols % blkSizeX == 0 && dst.cols != 0 ? dst.cols : (dst.cols / blkSizeX + 1) * blkSizeX;
}
size_t glbSizeY = dst.rows % blkSizeY == 0 && dst.rows != 0 ? dst.rows : (dst.rows / blkSizeY + 1) * blkSizeY;
size_t globalThreads[3] = {glbSizeX, glbSizeY, 1};
size_t localThreads[3] = {blkSizeX, blkSizeY, 1};
vector< pair<size_t, const void *> > args;
if(interpolation == INTER_NEAREST)
if (interpolation == INTER_NEAREST)
{
args.push_back( make_pair(sizeof(cl_mem), (void *)&dst.data));
args.push_back( make_pair(sizeof(cl_mem), (void *)&src.data));
......@@ -361,7 +340,7 @@ namespace cv
args.push_back( make_pair(sizeof(cl_int), (void *)&src.rows));
args.push_back( make_pair(sizeof(cl_int), (void *)&dst.cols));
args.push_back( make_pair(sizeof(cl_int), (void *)&dst.rows));
if(src.clCxt->supportsFeature(FEATURE_CL_DOUBLE))
if (src.clCxt->supportsFeature(FEATURE_CL_DOUBLE))
{
args.push_back( make_pair(sizeof(cl_double), (void *)&ifx_d));
args.push_back( make_pair(sizeof(cl_double), (void *)&ify_d));
......@@ -391,7 +370,6 @@ namespace cv
openCLExecuteKernel(clCxt, &imgproc_resize, kernelName, globalThreads, localThreads, args, src.oclchannels(), src.depth());
}
void resize(const oclMat &src, oclMat &dst, Size dsize,
double fx, double fy, int interpolation)
{
......@@ -401,17 +379,12 @@ namespace cv
CV_Assert( src.size().area() > 0 );
CV_Assert( !(dsize == Size()) || (fx > 0 && fy > 0) );
if(!(dsize == Size()) && (fx > 0 && fy > 0))
{
if(dsize.width != (int)(src.cols * fx) || dsize.height != (int)(src.rows * fy))
{
if (!(dsize == Size()) && (fx > 0 && fy > 0))
if (dsize.width != (int)(src.cols * fx) || dsize.height != (int)(src.rows * fy))
CV_Error(CV_StsUnmatchedSizes, "invalid dsize and fx, fy!");
}
}
if( dsize == Size() )
{
if ( dsize == Size() )
dsize = Size(saturate_cast<int>(src.cols * fx), saturate_cast<int>(src.rows * fy));
}
else
{
fx = (double)dsize.width / src.cols;
......@@ -420,24 +393,25 @@ namespace cv
dst.create(dsize, src.type());
if( interpolation == INTER_NEAREST || interpolation == INTER_LINEAR )
if ( interpolation == INTER_NEAREST || interpolation == INTER_LINEAR )
{
resize_gpu( src, dst, fx, fy, interpolation);
return;
}
CV_Error(CV_StsUnsupportedFormat, "Non-supported interpolation method");
}
////////////////////////////////////////////////////////////////////////
// medianFilter
void medianFilter(const oclMat &src, oclMat &dst, int m)
{
CV_Assert( m % 2 == 1 && m > 1 );
CV_Assert( m <= 5 || src.depth() == CV_8U );
CV_Assert( src.cols <= dst.cols && src.rows <= dst.rows );
if(src.data == dst.data)
if (src.data == dst.data)
{
oclMat src1;
src.copyTo(src1);
......@@ -450,8 +424,6 @@ namespace cv
int dstOffset = dst.offset / dst.oclchannels() / dst.elemSize1();
Context *clCxt = src.clCxt;
string kernelName = "medianFilter";
vector< pair<size_t, const void *> > args;
args.push_back( make_pair( sizeof(cl_mem), (void *)&src.data));
......@@ -466,67 +438,65 @@ namespace cv
size_t globalThreads[3] = {(src.cols + 18) / 16 * 16, (src.rows + 15) / 16 * 16, 1};
size_t localThreads[3] = {16, 16, 1};
if(m == 3)
if (m == 3)
{
string kernelName = "medianFilter3";
openCLExecuteKernel(clCxt, &imgproc_median, kernelName, globalThreads, localThreads, args, src.oclchannels(), src.depth());
}
else if(m == 5)
else if (m == 5)
{
string kernelName = "medianFilter5";
openCLExecuteKernel(clCxt, &imgproc_median, kernelName, globalThreads, localThreads, args, src.oclchannels(), src.depth());
}
else
CV_Error(CV_StsUnsupportedFormat, "Non-supported filter length");
CV_Error(CV_StsBadArg, "Non-supported filter length");
}
////////////////////////////////////////////////////////////////////////
// copyMakeBorder
void copyMakeBorder(const oclMat &src, oclMat &dst, int top, int bottom, int left, int right, int bordertype, const Scalar &scalar)
{
CV_Assert(top >= 0 && bottom >= 0 && left >= 0 && right >= 0);
if((dst.cols != dst.wholecols) || (dst.rows != dst.wholerows)) //has roi
if ((dst.cols != dst.wholecols) || (dst.rows != dst.wholerows)) //has roi
{
if(((bordertype & cv::BORDER_ISOLATED) == 0) &&
if (((bordertype & cv::BORDER_ISOLATED) == 0) &&
(bordertype != cv::BORDER_CONSTANT) &&
(bordertype != cv::BORDER_REPLICATE))
{
CV_Error(CV_StsBadArg, "unsupported border type");
CV_Error(CV_StsBadArg, "Unsupported border type");
}
}
bordertype &= ~cv::BORDER_ISOLATED;
if((bordertype == cv::BORDER_REFLECT) || (bordertype == cv::BORDER_WRAP))
if (bordertype == cv::BORDER_REFLECT || bordertype == cv::BORDER_WRAP)
{
CV_Assert((src.cols >= left) && (src.cols >= right) && (src.rows >= top) && (src.rows >= bottom));
}
if(bordertype == cv::BORDER_REFLECT_101)
else if (bordertype == cv::BORDER_REFLECT_101)
{
CV_Assert((src.cols > left) && (src.cols > right) && (src.rows > top) && (src.rows > bottom));
}
dst.create(src.rows + top + bottom, src.cols + left + right, src.type());
int srcStep = src.step1() / src.oclchannels();
int dstStep = dst.step1() / dst.oclchannels();
int srcOffset = src.offset / src.elemSize();
int dstOffset = dst.offset / dst.elemSize();
int srcStep = src.step1() / src.oclchannels(), dstStep = dst.step1() / dst.oclchannels();
int srcOffset = src.offset / src.elemSize(), dstOffset = dst.offset / dst.elemSize();
int depth = src.depth(), ochannels = src.oclchannels();
int __bordertype[] = {cv::BORDER_CONSTANT, cv::BORDER_REPLICATE, BORDER_REFLECT, BORDER_WRAP, BORDER_REFLECT_101};
const char *borderstr[] = {"BORDER_CONSTANT", "BORDER_REPLICATE", "BORDER_REFLECT", "BORDER_WRAP", "BORDER_REFLECT_101"};
size_t bordertype_index;
for(bordertype_index = 0; bordertype_index < sizeof(__bordertype) / sizeof(int); bordertype_index++)
{
if(__bordertype[bordertype_index] == bordertype)
if (__bordertype[bordertype_index] == bordertype)
break;
}
if(bordertype_index == sizeof(__bordertype) / sizeof(int))
{
if (bordertype_index == sizeof(__bordertype) / sizeof(int))
CV_Error(CV_StsBadArg, "unsupported border type");
}
string kernelName = "copymakeborder";
size_t localThreads[3] = {16, 16, 1};
size_t globalThreads[3] = {(dst.cols + localThreads[0] - 1) / localThreads[0] *localThreads[0],
(dst.rows + localThreads[1] - 1) / localThreads[1] *localThreads[1], 1
};
size_t globalThreads[3] = { dst.cols, dst.rows, 1 };
vector< pair<size_t, const void *> > args;
args.push_back( make_pair( sizeof(cl_mem), (void *)&src.data));
......@@ -541,169 +511,30 @@ namespace cv
args.push_back( make_pair( sizeof(cl_int), (void *)&dstOffset));
args.push_back( make_pair( sizeof(cl_int), (void *)&top));
args.push_back( make_pair( sizeof(cl_int), (void *)&left));
char compile_option[64];
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())
const char * const typeMap[] = { "uchar", "char", "ushort", "short", "int", "float", "double" };
const char * const channelMap[] = { "", "", "2", "4", "4" };
std::string buildOptions = format("-D GENTYPE=%s%s -D %s",
typeMap[depth], channelMap[ochannels],
borderstr[bordertype_index]);
if (src.type() == CV_8UC1 && (dst.offset & 3) == 0 && (dst.cols & 3) == 0)
{
case CV_8U:
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 -D %s", borderstr[bordertype_index]);
args.push_back( make_pair( sizeof(cl_uchar) , (void *)&val.uval.s[0] ));
if(((dst.offset & 3) == 0) && ((dst.cols & 3) == 0))
{
kernelName = "copymakeborder_C1_D0";
globalThreads[0] = (dst.cols / 4 + localThreads[0] - 1) / localThreads[0] * localThreads[0];
}
break;
case 4:
sprintf(compile_option, "-D GENTYPE=uchar4 -D %s", borderstr[bordertype_index]);
args.push_back( make_pair( sizeof(cl_uchar4) , (void *)&val.uval ));
break;
default:
CV_Error(CV_StsUnsupportedFormat, "unsupported channels");
}
break;
case CV_8S:
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 -D %s", borderstr[bordertype_index]);
args.push_back( make_pair( sizeof(cl_char) , (void *)&val.cval.s[0] ));
break;
case 4:
sprintf(compile_option, "-D GENTYPE=char4 -D %s", borderstr[bordertype_index]);
args.push_back( make_pair( sizeof(cl_char4) , (void *)&val.cval ));
break;
default:
CV_Error(CV_StsUnsupportedFormat, "unsupported channels");
}
break;
case CV_16U:
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 -D %s", borderstr[bordertype_index]);
args.push_back( make_pair( sizeof(cl_ushort) , (void *)&val.usval.s[0] ));
break;
case 4:
sprintf(compile_option, "-D GENTYPE=ushort4 -D %s", borderstr[bordertype_index]);
args.push_back( make_pair( sizeof(cl_ushort4) , (void *)&val.usval ));
break;
default:
CV_Error(CV_StsUnsupportedFormat, "unsupported channels");
}
break;
case CV_16S:
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 -D %s", borderstr[bordertype_index]);
args.push_back( make_pair( sizeof(cl_short) , (void *)&val.shval.s[0] ));
break;
case 4:
sprintf(compile_option, "-D GENTYPE=short4 -D %s", borderstr[bordertype_index]);
args.push_back( make_pair( sizeof(cl_short4) , (void *)&val.shval ));
break;
default:
CV_Error(CV_StsUnsupportedFormat, "unsupported channels");
}
break;
case CV_32S:
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 -D %s", borderstr[bordertype_index]);
args.push_back( make_pair( sizeof(cl_int) , (void *)&val.ival.s[0] ));
break;
case 2:
sprintf(compile_option, "-D GENTYPE=int2 -D %s", borderstr[bordertype_index]);
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 -D %s", borderstr[bordertype_index]);
args.push_back( make_pair( sizeof(cl_int4) , (void *)&val.ival ));
break;
default:
CV_Error(CV_StsUnsupportedFormat, "unsupported channels");
}
break;
case CV_32F:
val.fval.s[0] = scalar.val[0];
val.fval.s[1] = scalar.val[1];
val.fval.s[2] = scalar.val[2];
val.fval.s[3] = scalar.val[3];
switch(dst.oclchannels())
{
case 1:
sprintf(compile_option, "-D GENTYPE=float -D %s", borderstr[bordertype_index]);
args.push_back( make_pair( sizeof(cl_float) , (void *)&val.fval.s[0] ));
break;
case 4:
sprintf(compile_option, "-D GENTYPE=float4 -D %s", borderstr[bordertype_index]);
args.push_back( make_pair( sizeof(cl_float4) , (void *)&val.fval ));
break;
default:
CV_Error(CV_StsUnsupportedFormat, "unsupported channels");
}
break;
case CV_64F:
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 -D %s", borderstr[bordertype_index]);
args.push_back( make_pair( sizeof(cl_double) , (void *)&val.dval.s[0] ));
break;
case 4:
sprintf(compile_option, "-D GENTYPE=double4 -D %s", borderstr[bordertype_index]);
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");
kernelName = "copymakeborder_C1_D0";
globalThreads[0] = dst.cols >> 2;
}
openCLExecuteKernel(src.clCxt, &imgproc_copymakeboder, kernelName, globalThreads, localThreads, args, -1, -1, compile_option);
int cn = src.channels(), ocn = src.oclchannels();
int bufSize = src.elemSize1() * ocn;
AutoBuffer<uchar> _buf(bufSize);
uchar * buf = (uchar *)_buf;
scalarToRawData(scalar, buf, dst.type());
memset(buf + src.elemSize1() * cn, 0, (ocn - cn) * src.elemSize1());
args.push_back( make_pair( bufSize , (void *)buf ));
openCLExecuteKernel(src.clCxt, &imgproc_copymakeboder, kernelName, globalThreads,
localThreads, args, -1, -1, buildOptions.c_str());
}
////////////////////////////////////////////////////////////////////////
......@@ -739,7 +570,7 @@ namespace cv
double *Dd = M;
double d = det3(Sd);
double result = 0;
if( d != 0)
if ( d != 0)
{
double t[9];
result = d;
......@@ -782,32 +613,32 @@ namespace cv
string s[3] = {"NN", "Linear", "Cubic"};
string kernelName = "warpAffine" + s[interpolation];
if(src.clCxt->supportsFeature(FEATURE_CL_DOUBLE))
if (src.clCxt->supportsFeature(FEATURE_CL_DOUBLE))
{
cl_int st;
coeffs_cm = clCreateBuffer(*(cl_context*)clCxt->getOpenCLContextPtr(), CL_MEM_READ_WRITE, sizeof(F) * 2 * 3, NULL, &st );
openCLVerifyCall(st);
openCLSafeCall(clEnqueueWriteBuffer(*(cl_command_queue*)clCxt->getOpenCLCommandQueuePtr(), (cl_mem)coeffs_cm, 1, 0, sizeof(F) * 2 * 3, coeffs, 0, 0, 0));
openCLSafeCall(clEnqueueWriteBuffer(*(cl_command_queue*)clCxt->getOpenCLCommandQueuePtr(), (cl_mem)coeffs_cm, 1, 0,
sizeof(F) * 2 * 3, coeffs, 0, 0, 0));
}
else
{
cl_int st;
for(int m = 0; m < 2; m++)
for(int n = 0; n < 3; n++)
{
float_coeffs[m][n] = coeffs[m][n];
}
coeffs_cm = clCreateBuffer(*(cl_context*)clCxt->getOpenCLContextPtr(), CL_MEM_READ_WRITE, sizeof(float) * 2 * 3, NULL, &st );
openCLSafeCall(clEnqueueWriteBuffer(*(cl_command_queue*)clCxt->getOpenCLCommandQueuePtr(), (cl_mem)coeffs_cm, 1, 0, sizeof(float) * 2 * 3, float_coeffs, 0, 0, 0));
coeffs_cm = clCreateBuffer(*(cl_context*)clCxt->getOpenCLContextPtr(), CL_MEM_READ_WRITE, sizeof(float) * 2 * 3, NULL, &st );
openCLSafeCall(clEnqueueWriteBuffer(*(cl_command_queue*)clCxt->getOpenCLCommandQueuePtr(), (cl_mem)coeffs_cm,
1, 0, sizeof(float) * 2 * 3, float_coeffs, 0, 0, 0));
}
//TODO: improve this kernel
size_t blkSizeX = 16, blkSizeY = 16;
size_t glbSizeX;
size_t cols;
//if(src.type() == CV_8UC1 && interpolation != 2)
if(src.type() == CV_8UC1 && interpolation != 2)
if (src.type() == CV_8UC1 && interpolation != 2)
{
cols = (dst.cols + dst.offset % 4 + 3) / 4;
glbSizeX = cols % blkSizeX == 0 ? cols : (cols / blkSizeX + 1) * blkSizeX;
......@@ -817,6 +648,7 @@ namespace cv
cols = dst.cols;
glbSizeX = dst.cols % blkSizeX == 0 ? dst.cols : (dst.cols / blkSizeX + 1) * blkSizeX;
}
size_t glbSizeY = dst.rows % blkSizeY == 0 ? dst.rows : (dst.rows / blkSizeY + 1) * blkSizeY;
size_t globalThreads[3] = {glbSizeX, glbSizeY, 1};
size_t localThreads[3] = {blkSizeX, blkSizeY, 1};
......@@ -840,7 +672,6 @@ namespace cv
openCLSafeCall(clReleaseMemObject(coeffs_cm));
}
void warpPerspective_gpu(const oclMat &src, oclMat &dst, double coeffs[3][3], int interpolation)
{
CV_Assert( (src.oclchannels() == dst.oclchannels()) );
......@@ -853,12 +684,13 @@ namespace cv
string s[3] = {"NN", "Linear", "Cubic"};
string kernelName = "warpPerspective" + s[interpolation];
if(src.clCxt->supportsFeature(FEATURE_CL_DOUBLE))
if (src.clCxt->supportsFeature(FEATURE_CL_DOUBLE))
{
cl_int st;
coeffs_cm = clCreateBuffer(*(cl_context*)clCxt->getOpenCLContextPtr(), CL_MEM_READ_WRITE, sizeof(double) * 3 * 3, NULL, &st );
openCLVerifyCall(st);
openCLSafeCall(clEnqueueWriteBuffer(*(cl_command_queue*)clCxt->getOpenCLCommandQueuePtr(), (cl_mem)coeffs_cm, 1, 0, sizeof(double) * 3 * 3, coeffs, 0, 0, 0));
openCLSafeCall(clEnqueueWriteBuffer(*(cl_command_queue*)clCxt->getOpenCLCommandQueuePtr(), (cl_mem)coeffs_cm, 1, 0,
sizeof(double) * 3 * 3, coeffs, 0, 0, 0));
}
else
{
......@@ -869,24 +701,25 @@ namespace cv
coeffs_cm = clCreateBuffer(*(cl_context*)clCxt->getOpenCLContextPtr(), CL_MEM_READ_WRITE, sizeof(float) * 3 * 3, NULL, &st );
openCLVerifyCall(st);
openCLSafeCall(clEnqueueWriteBuffer(*(cl_command_queue*)clCxt->getOpenCLCommandQueuePtr(), (cl_mem)coeffs_cm, 1, 0, sizeof(float) * 3 * 3, float_coeffs, 0, 0, 0));
openCLSafeCall(clEnqueueWriteBuffer(*(cl_command_queue*)clCxt->getOpenCLCommandQueuePtr(), (cl_mem)coeffs_cm, 1, 0,
sizeof(float) * 3 * 3, float_coeffs, 0, 0, 0));
}
//TODO: improve this kernel
size_t blkSizeX = 16, blkSizeY = 16;
size_t glbSizeX;
size_t cols;
if(src.type() == CV_8UC1 && interpolation == 0)
if (src.type() == CV_8UC1 && interpolation == 0)
{
cols = (dst.cols + dst.offset % 4 + 3) / 4;
glbSizeX = cols % blkSizeX == 0 ? cols : (cols / blkSizeX + 1) * blkSizeX;
}
else
/*
*/
{
cols = dst.cols;
glbSizeX = dst.cols % blkSizeX == 0 ? dst.cols : (dst.cols / blkSizeX + 1) * blkSizeX;
}
size_t glbSizeY = dst.rows % blkSizeY == 0 ? dst.rows : (dst.rows / blkSizeY + 1) * blkSizeY;
size_t globalThreads[3] = {glbSizeX, glbSizeY, 1};
size_t localThreads[3] = {blkSizeX, blkSizeY, 1};
......@@ -928,10 +761,8 @@ namespace cv
double coeffsM[2*3];
Mat coeffsMat(2, 3, CV_64F, (void *)coeffsM);
M.convertTo(coeffsMat, coeffsMat.type());
if(!warpInd)
{
if (!warpInd)
convert_coeffs(coeffsM);
}
for(int i = 0; i < 2; ++i)
for(int j = 0; j < 3; ++j)
......@@ -958,10 +789,8 @@ namespace cv
double coeffsM[3*3];
Mat coeffsMat(3, 3, CV_64F, (void *)coeffsM);
M.convertTo(coeffsMat, coeffsMat.type());
if(!warpInd)
{
if (!warpInd)
invert(coeffsM);
}
for(int i = 0; i < 3; ++i)
for(int j = 0; j < 3; ++j)
......@@ -972,12 +801,13 @@ namespace cv
////////////////////////////////////////////////////////////////////////
// integral
void integral(const oclMat &src, oclMat &sum, oclMat &sqsum)
{
CV_Assert(src.type() == CV_8UC1);
if(!src.clCxt->supportsFeature(ocl::FEATURE_CL_DOUBLE) && src.depth() == CV_64F)
if (!src.clCxt->supportsFeature(ocl::FEATURE_CL_DOUBLE) && src.depth() == CV_64F)
{
CV_Error(CV_OpenCLDoubleNotSupported, "select device don't support double");
CV_Error(CV_OpenCLDoubleNotSupported, "Select device doesn't support double");
return;
}
......@@ -1071,6 +901,7 @@ namespace cv
}
/////////////////////// corner //////////////////////////////
static void extractCovData(const oclMat &src, oclMat &Dx, oclMat &Dy,
int blockSize, int ksize, int borderType)
{
......@@ -1085,9 +916,8 @@ namespace cv
scale = 1. / scale;
}
else
{
scale = 1. / scale;
}
if (ksize > 0)
{
Sobel(src, Dx, CV_32F, 1, 0, ksize, scale, 0, borderType);
......@@ -1120,10 +950,10 @@ namespace cv
sprintf(borderType, "BORDER_REPLICATE");
break;
default:
cout << "BORDER type is not supported!" << endl;
CV_Error(CV_StsBadFlag, "BORDER type is not supported!");
}
char build_options[150];
sprintf(build_options, "-D anX=%d -D anY=%d -D ksX=%d -D ksY=%d -D %s",
std::string buildOptions = format("-D anX=%d -D anY=%d -D ksX=%d -D ksY=%d -D %s",
block_size / 2, block_size / 2, block_size, block_size, borderType);
size_t blockSizeX = 256, blockSizeY = 1;
......@@ -1153,7 +983,7 @@ namespace cv
args.push_back( make_pair(sizeof(cl_int), (void *)&dst.cols));
args.push_back( make_pair(sizeof(cl_int), (void *)&dst.step));
args.push_back( make_pair( sizeof(cl_float) , (void *)&k));
openCLExecuteKernel(dst.clCxt, source, kernelName, gt, lt, args, -1, -1, build_options);
openCLExecuteKernel(dst.clCxt, source, kernelName, gt, lt, args, -1, -1, buildOptions.c_str());
}
void cornerHarris(const oclMat &src, oclMat &dst, int blockSize, int ksize,
......@@ -1166,12 +996,15 @@ namespace cv
void cornerHarris_dxdy(const oclMat &src, oclMat &dst, oclMat &dx, oclMat &dy, int blockSize, int ksize,
double k, int borderType)
{
if(!src.clCxt->supportsFeature(FEATURE_CL_DOUBLE) && src.depth() == CV_64F)
if (!src.clCxt->supportsFeature(FEATURE_CL_DOUBLE) && src.depth() == CV_64F)
{
CV_Error(CV_OpenCLDoubleNotSupported, "select device don't support double");
CV_Error(CV_OpenCLDoubleNotSupported, "Select device doesn't support double");
return;
}
CV_Assert(src.cols >= blockSize / 2 && src.rows >= blockSize / 2);
CV_Assert(borderType == cv::BORDER_CONSTANT || borderType == cv::BORDER_REFLECT101 || borderType == cv::BORDER_REPLICATE || borderType == cv::BORDER_REFLECT);
CV_Assert(borderType == cv::BORDER_CONSTANT || borderType == cv::BORDER_REFLECT101 || borderType == cv::BORDER_REPLICATE
|| borderType == cv::BORDER_REFLECT);
extractCovData(src, dx, dy, blockSize, ksize, borderType);
dst.create(src.size(), CV_32F);
corner_ocl(&imgproc_calcHarris, "calcHarris", blockSize, static_cast<float>(k), dx, dy, dst, borderType);
......@@ -1185,29 +1018,33 @@ namespace cv
void cornerMinEigenVal_dxdy(const oclMat &src, oclMat &dst, oclMat &dx, oclMat &dy, int blockSize, int ksize, int borderType)
{
if(!src.clCxt->supportsFeature(FEATURE_CL_DOUBLE) && src.depth() == CV_64F)
if (!src.clCxt->supportsFeature(FEATURE_CL_DOUBLE) && src.depth() == CV_64F)
{
CV_Error(CV_OpenCLDoubleNotSupported, "select device don't support double");
return;
}
CV_Assert(src.cols >= blockSize / 2 && src.rows >= blockSize / 2);
CV_Assert(borderType == cv::BORDER_CONSTANT || borderType == cv::BORDER_REFLECT101 || borderType == cv::BORDER_REPLICATE || borderType == cv::BORDER_REFLECT);
extractCovData(src, dx, dy, blockSize, ksize, borderType);
dst.create(src.size(), CV_32F);
corner_ocl(&imgproc_calcMinEigenVal, "calcMinEigenVal", blockSize, 0, dx, dy, dst, borderType);
}
/////////////////////////////////// MeanShiftfiltering ///////////////////////////////////////////////
static void meanShiftFiltering_gpu(const oclMat &src, oclMat dst, int sp, int sr, int maxIter, float eps)
{
CV_Assert( (src.cols == dst.cols) && (src.rows == dst.rows) );
CV_Assert( !(dst.step & 0x3) );
Context *clCxt = src.clCxt;
//Arrange the NDRange
int col = src.cols, row = src.rows;
int ltx = 16, lty = 8;
if(src.cols % ltx != 0)
if (src.cols % ltx != 0)
col = (col / ltx + 1) * ltx;
if(src.rows % lty != 0)
if (src.rows % lty != 0)
row = (row / lty + 1) * lty;
size_t globalThreads[3] = {col, row, 1};
......@@ -1227,31 +1064,31 @@ namespace cv
args.push_back( make_pair( sizeof(cl_int) , (void *)&sr ));
args.push_back( make_pair( sizeof(cl_int) , (void *)&maxIter ));
args.push_back( make_pair( sizeof(cl_float) , (void *)&eps ));
openCLExecuteKernel(clCxt, &meanShift, "meanshift_kernel", globalThreads, localThreads, args, -1, -1);
openCLExecuteKernel(src.clCxt, &meanShift, "meanshift_kernel", globalThreads, localThreads, args, -1, -1);
}
void meanShiftFiltering(const oclMat &src, oclMat &dst, int sp, int sr, TermCriteria criteria)
{
if( src.empty() )
if ( src.empty() )
CV_Error( CV_StsBadArg, "The input image is empty" );
if( src.depth() != CV_8U || src.oclchannels() != 4 )
if ( src.depth() != CV_8U || src.oclchannels() != 4 )
CV_Error( CV_StsUnsupportedFormat, "Only 8-bit, 4-channel images are supported" );
dst.create( src.size(), CV_8UC4 );
if( !(criteria.type & TermCriteria::MAX_ITER) )
if ( !(criteria.type & TermCriteria::MAX_ITER) )
criteria.maxCount = 5;
int maxIter = std::min(std::max(criteria.maxCount, 1), 100);
float eps;
if( !(criteria.type & TermCriteria::EPS) )
if ( !(criteria.type & TermCriteria::EPS) )
eps = 1.f;
eps = (float)std::max(criteria.epsilon, 0.0);
meanShiftFiltering_gpu(src, dst, sp, sr, maxIter, eps);
}
static void meanShiftProc_gpu(const oclMat &src, oclMat dstr, oclMat dstsp, int sp, int sr, int maxIter, float eps)
......@@ -1260,14 +1097,13 @@ namespace cv
CV_Assert( (src.cols == dstr.cols) && (src.rows == dstr.rows) &&
(src.rows == dstsp.rows) && (src.cols == dstsp.cols));
CV_Assert( !(dstsp.step & 0x3) );
Context *clCxt = src.clCxt;
//Arrange the NDRange
int col = src.cols, row = src.rows;
int ltx = 16, lty = 8;
if(src.cols % ltx != 0)
if (src.cols % ltx != 0)
col = (col / ltx + 1) * ltx;
if(src.rows % lty != 0)
if (src.rows % lty != 0)
row = (row / lty + 1) * lty;
size_t globalThreads[3] = {col, row, 1};
......@@ -1290,18 +1126,19 @@ namespace cv
args.push_back( make_pair( sizeof(cl_int) , (void *)&sr ));
args.push_back( make_pair( sizeof(cl_int) , (void *)&maxIter ));
args.push_back( make_pair( sizeof(cl_float) , (void *)&eps ));
openCLExecuteKernel(clCxt, &meanShift, "meanshiftproc_kernel", globalThreads, localThreads, args, -1, -1);
openCLExecuteKernel(src.clCxt, &meanShift, "meanshiftproc_kernel", globalThreads, localThreads, args, -1, -1);
}
void meanShiftProc(const oclMat &src, oclMat &dstr, oclMat &dstsp, int sp, int sr, TermCriteria criteria)
{
if( src.empty() )
if ( src.empty() )
CV_Error( CV_StsBadArg, "The input image is empty" );
if( src.depth() != CV_8U || src.oclchannels() != 4 )
if ( src.depth() != CV_8U || src.oclchannels() != 4 )
CV_Error( CV_StsUnsupportedFormat, "Only 8-bit, 4-channel images are supported" );
// if(!src.clCxt->supportsFeature(FEATURE_CL_DOUBLE))
// if (!src.clCxt->supportsFeature(FEATURE_CL_DOUBLE))
// {
// CV_Error( CV_OpenCLDoubleNotSupportedNotSupported, "Selected device doesn't support double, so a deviation exists.\nIf the accuracy is acceptable, the error can be ignored.\n");
// return;
......@@ -1310,13 +1147,13 @@ namespace cv
dstr.create( src.size(), CV_8UC4 );
dstsp.create( src.size(), CV_16SC2 );
if( !(criteria.type & TermCriteria::MAX_ITER) )
if ( !(criteria.type & TermCriteria::MAX_ITER) )
criteria.maxCount = 5;
int maxIter = std::min(std::max(criteria.maxCount, 1), 100);
float eps;
if( !(criteria.type & TermCriteria::EPS) )
if ( !(criteria.type & TermCriteria::EPS) )
eps = 1.f;
eps = (float)std::max(criteria.epsilon, 0.0);
......@@ -1326,6 +1163,7 @@ namespace cv
///////////////////////////////////////////////////////////////////////////////////////////////////
////////////////////////////////////////////////////hist///////////////////////////////////////////////
/////////////////////////////////////////////////////////////////////////////////////////////////////
namespace histograms
{
const int PARTIAL_HISTOGRAM256_COUNT = 256;
......@@ -1336,11 +1174,8 @@ namespace cv
{
using namespace histograms;
Context *clCxt = mat_src.clCxt;
int depth = mat_src.depth();
string kernelName = "calc_sub_hist";
size_t localThreads[3] = { HISTOGRAM256_BIN_COUNT, 1, 1 };
size_t globalThreads[3] = { PARTIAL_HISTOGRAM256_COUNT *localThreads[0], 1, 1};
......@@ -1353,7 +1188,7 @@ namespace cv
int hist_step = mat_sub_hist.step >> 2;
int left_col = 0, right_col = 0;
if(cols >= dataWidth * 2 - 1)
if (cols >= dataWidth * 2 - 1)
{
left_col = dataWidth - (src_offset & mask);
left_col &= mask;
......@@ -1371,7 +1206,7 @@ namespace cv
}
vector<pair<size_t , const void *> > args;
if(globalThreads[0] != 0)
if (globalThreads[0] != 0)
{
int tempcols = cols >> dataWidth_bits;
int inc_x = globalThreads[0] % tempcols;
......@@ -1379,6 +1214,7 @@ namespace cv
src_offset >>= dataWidth_bits;
int src_step = mat_src.step >> dataWidth_bits;
int datacount = tempcols * mat_src.rows;
args.push_back( make_pair( sizeof(cl_mem), (void *)&mat_src.data));
args.push_back( make_pair( sizeof(cl_int), (void *)&src_step));
args.push_back( make_pair( sizeof(cl_int), (void *)&src_offset));
......@@ -1388,16 +1224,17 @@ namespace cv
args.push_back( make_pair( sizeof(cl_int), (void *)&inc_x));
args.push_back( make_pair( sizeof(cl_int), (void *)&inc_y));
args.push_back( make_pair( sizeof(cl_int), (void *)&hist_step));
openCLExecuteKernel(clCxt, &imgproc_histogram, kernelName, globalThreads, localThreads, args, -1, depth);
openCLExecuteKernel(mat_src.clCxt, &imgproc_histogram, "calc_sub_hist", globalThreads, localThreads, args, -1, depth);
}
if(left_col != 0 || right_col != 0)
if (left_col != 0 || right_col != 0)
{
kernelName = "calc_sub_hist_border";
src_offset = mat_src.offset;
localThreads[0] = 1;
localThreads[1] = 256;
globalThreads[0] = left_col + right_col;
globalThreads[1] = (mat_src.rows + localThreads[1] - 1) / localThreads[1] * localThreads[1];
globalThreads[1] = mat_src.rows;
args.clear();
args.push_back( make_pair( sizeof(cl_mem), (void *)&mat_src.data));
......@@ -1408,25 +1245,27 @@ namespace cv
args.push_back( make_pair( sizeof(cl_int), (void *)&cols));
args.push_back( make_pair( sizeof(cl_int), (void *)&mat_src.rows));
args.push_back( make_pair( sizeof(cl_int), (void *)&hist_step));
openCLExecuteKernel(clCxt, &imgproc_histogram, kernelName, globalThreads, localThreads, args, -1, depth);
openCLExecuteKernel(mat_src.clCxt, &imgproc_histogram, "calc_sub_hist_border", globalThreads, localThreads, args, -1, depth);
}
}
static void merge_sub_hist(const oclMat &sub_hist, oclMat &mat_hist)
{
using namespace histograms;
Context *clCxt = sub_hist.clCxt;
string kernelName = "merge_hist";
size_t localThreads[3] = { 256, 1, 1 };
size_t globalThreads[3] = { HISTOGRAM256_BIN_COUNT *localThreads[0], 1, 1};
int src_step = sub_hist.step >> 2;
vector<pair<size_t , const void *> > args;
args.push_back( make_pair( sizeof(cl_mem), (void *)&sub_hist.data));
args.push_back( make_pair( sizeof(cl_mem), (void *)&mat_hist.data));
args.push_back( make_pair( sizeof(cl_int), (void *)&src_step));
openCLExecuteKernel(clCxt, &imgproc_histogram, kernelName, globalThreads, localThreads, args, -1, -1);
openCLExecuteKernel(sub_hist.clCxt, &imgproc_histogram, "merge_hist", globalThreads, localThreads, args, -1, -1);
}
void calcHist(const oclMat &mat_src, oclMat &mat_hist)
{
using namespace histograms;
......@@ -1439,6 +1278,7 @@ namespace cv
calc_sub_hist(mat_src, buf);
merge_sub_hist(buf, mat_hist);
}
///////////////////////////////////equalizeHist/////////////////////////////////////////////////////
void equalizeHist(const oclMat &mat_src, oclMat &mat_dst)
{
......@@ -1448,17 +1288,17 @@ namespace cv
calcHist(mat_src, mat_hist);
Context *clCxt = mat_src.clCxt;
string kernelName = "calLUT";
size_t localThreads[3] = { 256, 1, 1};
size_t globalThreads[3] = { 256, 1, 1};
oclMat lut(1, 256, CV_8UC1);
vector<pair<size_t , const void *> > args;
int total = mat_src.rows * mat_src.cols;
vector<pair<size_t , const void *> > args;
args.push_back( make_pair( sizeof(cl_mem), (void *)&lut.data));
args.push_back( make_pair( sizeof(cl_mem), (void *)&mat_hist.data));
args.push_back( make_pair( sizeof(int), (void *)&total));
openCLExecuteKernel(clCxt, &imgproc_histogram, kernelName, globalThreads, localThreads, args, -1, -1);
openCLExecuteKernel(mat_src.clCxt, &imgproc_histogram, "calLUT", globalThreads, localThreads, args, -1, -1);
LUT(mat_src, lut, mat_dst);
}
......@@ -1489,16 +1329,15 @@ namespace cv
size_t globalThreads[3] = { tilesX * localThreads[0], tilesY * localThreads[1], 1 };
bool is_cpu = isCpuDevice();
if (is_cpu)
openCLExecuteKernel(Context::getContext(), &imgproc_clahe, kernelName, globalThreads, localThreads, args, -1, -1, (char*)" -D CPU");
openCLExecuteKernel(Context::getContext(), &imgproc_clahe, kernelName, globalThreads, localThreads, args, -1, -1, (char*)"-D CPU");
else
{
cl_kernel kernel = openCLGetKernelFromSource(Context::getContext(), &imgproc_clahe, kernelName);
size_t wave_size = queryWaveFrontSize(kernel);
int wave_size = (int)queryWaveFrontSize(kernel);
openCLSafeCall(clReleaseKernel(kernel));
static char opt[20] = {0};
sprintf(opt, "-D WAVE_SIZE=%d", (int)wave_size);
openCLExecuteKernel(Context::getContext(), &imgproc_clahe, kernelName, globalThreads, localThreads, args, -1, -1, opt);
std::string opt = format("-D WAVE_SIZE=%d", wave_size);
openCLExecuteKernel(Context::getContext(), &imgproc_clahe, kernelName, globalThreads, localThreads, args, -1, -1, opt.c_str());
}
}
......@@ -1522,11 +1361,10 @@ namespace cv
args.push_back( std::make_pair( sizeof(cl_int), (void *)&tilesX ));
args.push_back( std::make_pair( sizeof(cl_int), (void *)&tilesY ));
String kernelName = "transform";
size_t localThreads[3] = { 32, 8, 1 };
size_t globalThreads[3] = { src.cols, src.rows, 1 };
openCLExecuteKernel(Context::getContext(), &imgproc_clahe, kernelName, globalThreads, localThreads, args, -1, -1);
openCLExecuteKernel(Context::getContext(), &imgproc_clahe, "transform", globalThreads, localThreads, args, -1, -1);
}
}
......@@ -1557,8 +1395,9 @@ namespace cv
oclMat srcExt_;
oclMat lut_;
};
CLAHE_Impl::CLAHE_Impl(double clipLimit, int tilesX, int tilesY) :
clipLimit_(clipLimit), tilesX_(tilesX), tilesY_(tilesY)
clipLimit_(clipLimit), tilesX_(tilesX), tilesY_(tilesY)
{
}
......@@ -1566,6 +1405,7 @@ namespace cv
obj.info()->addParam(obj, "clipLimit", obj.clipLimit_);
obj.info()->addParam(obj, "tilesX", obj.tilesX_);
obj.info()->addParam(obj, "tilesY", obj.tilesY_))
void CLAHE_Impl::apply(cv::InputArray src_raw, cv::OutputArray dst_raw)
{
oclMat& src = getOclMatRef(src_raw);
......@@ -1605,7 +1445,6 @@ namespace cv
}
clahe::calcLut(srcForLut, lut_, tilesX_, tilesY_, tileSize, clipLimit, lutScale);
//finish();
clahe::transform(src, dst, lut_, tilesX_, tilesY_, tileSize);
}
......@@ -1643,8 +1482,8 @@ namespace cv
}
//////////////////////////////////bilateralFilter////////////////////////////////////////////////////
static void
oclbilateralFilter_8u( const oclMat &src, oclMat &dst, int d,
static void oclbilateralFilter_8u( const oclMat &src, oclMat &dst, int d,
double sigma_color, double sigma_space,
int borderType )
{
......@@ -1655,15 +1494,15 @@ namespace cv
src.type() == dst.type() && src.size() == dst.size() &&
src.data != dst.data );
if( sigma_color <= 0 )
if ( sigma_color <= 0 )
sigma_color = 1;
if( sigma_space <= 0 )
if ( sigma_space <= 0 )
sigma_space = 1;
double gauss_color_coeff = -0.5 / (sigma_color * sigma_color);
double gauss_space_coeff = -0.5 / (sigma_space * sigma_space);
if( d <= 0 )
if ( d <= 0 )
radius = cvRound(sigma_space * 1.5);
else
radius = d / 2;
......@@ -1682,6 +1521,7 @@ namespace cv
int dst_step_in_pixel = dst.step / dst.elemSize();
int dst_offset_in_pixel = dst.offset / dst.elemSize();
int temp_step_in_pixel = temp.step / temp.elemSize();
// initialize color-related bilateral filter coefficients
for( i = 0; i < 256 * cn; i++ )
color_weight[i] = (float)std::exp(i * i * gauss_color_coeff);
......@@ -1691,26 +1531,26 @@ namespace cv
for( j = -radius; j <= radius; j++ )
{
double r = std::sqrt((double)i * i + (double)j * j);
if( r > radius )
if ( r > radius )
continue;
space_weight[maxk] = (float)std::exp(r * r * gauss_space_coeff);
space_ofs[maxk++] = (int)(i * temp_step_in_pixel + j);
}
oclMat oclcolor_weight(1, cn * 256, CV_32FC1, color_weight);
oclMat oclspace_weight(1, d * d, CV_32FC1, space_weight);
oclMat oclspace_ofs(1, d * d, CV_32SC1, space_ofs);
string kernelName = "bilateral";
size_t localThreads[3] = { 16, 16, 1 };
size_t globalThreads[3] = { (dst.cols + localThreads[0] - 1) / localThreads[0] *localThreads[0],
(dst.rows + localThreads[1] - 1) / localThreads[1] *localThreads[1],
1
};
if((dst.type() == CV_8UC1) && ((dst.offset & 3) == 0) && ((dst.cols & 3) == 0))
size_t globalThreads[3] = { dst.cols, dst.rows, 1 };
if ((dst.type() == CV_8UC1) && ((dst.offset & 3) == 0) && ((dst.cols & 3) == 0))
{
kernelName = "bilateral2";
globalThreads[0] = (dst.cols / 4 + localThreads[0] - 1) / localThreads[0] * localThreads[0];
globalThreads[0] = dst.cols / 4;
}
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 *)&temp.data ));
......@@ -1730,13 +1570,11 @@ namespace cv
}
void bilateralFilter(const oclMat &src, oclMat &dst, int radius, double sigmaclr, double sigmaspc, int borderType)
{
dst.create( src.size(), src.type() );
if( src.depth() == CV_8U )
if ( src.depth() == CV_8U )
oclbilateralFilter_8u( src, dst, radius, sigmaclr, sigmaspc, borderType );
else
CV_Error( CV_StsUnsupportedFormat,
"Bilateral filtering is only implemented for 8uimages" );
CV_Error( CV_StsUnsupportedFormat, "Bilateral filtering is only implemented for 8uimages" );
}
}
......@@ -1745,18 +1583,9 @@ namespace cv
static void convolve_run(const oclMat &src, const oclMat &temp1, oclMat &dst, string kernelName, const cv::ocl::ProgramEntry* source)
{
CV_Assert(src.depth() == CV_32FC1);
CV_Assert(temp1.depth() == CV_32F);
CV_Assert(temp1.cols <= 17 && temp1.rows <= 17);
dst.create(src.size(), src.type());
CV_Assert(src.cols == dst.cols && src.rows == dst.rows);
CV_Assert(src.type() == dst.type());
Context *clCxt = src.clCxt;
int channels = dst.oclchannels();
int depth = dst.depth();
int channels = dst.oclchannels(), depth = dst.depth();
size_t vector_length = 1;
int offset_cols = ((dst.offset % dst.step) / dst.elemSize1()) & (vector_length - 1);
......@@ -1778,15 +1607,14 @@ static void convolve_run(const oclMat &src, const oclMat &temp1, oclMat &dst, st
args.push_back( make_pair( sizeof(cl_int), (void *)&temp1.rows ));
args.push_back( make_pair( sizeof(cl_int), (void *)&temp1.cols ));
openCLExecuteKernel(clCxt, source, kernelName, globalThreads, localThreads, args, -1, depth);
openCLExecuteKernel(src.clCxt, source, kernelName, globalThreads, localThreads, args, -1, depth);
}
void cv::ocl::convolve(const oclMat &x, const oclMat &t, oclMat &y)
{
CV_Assert(x.depth() == CV_32F);
CV_Assert(t.depth() == CV_32F);
CV_Assert(x.type() == y.type() && x.size() == y.size());
CV_Assert(x.depth() == CV_32F && t.depth() == CV_32F);
CV_Assert(t.cols <= 17 && t.rows <= 17);
y.create(x.size(), x.type());
string kernelName = "convolve";
convolve_run(x, t, y, kernelName, &imgproc_convolve);
convolve_run(x, t, y, "convolve", &imgproc_convolve);
}
Markdown is supported
0% or
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment