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added 3-channels support to cv::medianBlur

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This commit is contained in:
Ilya Lavrenov 2014-03-19 01:26:38 +04:00
parent a51ab99a79
commit b6833fdde7
3 changed files with 67 additions and 86 deletions
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123
modules/imgproc/src/opencl/medianFilter.cl
View File

@ -29,52 +29,52 @@
// 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.
#define DATA_TYPE type
#if cn != 3
#define loadpix(addr) *(__global const T *)(addr)
#define storepix(val, addr) *(__global T *)(addr) = val
#define TSIZE (int)sizeof(T)
#else
#define loadpix(addr) vload3(0, (__global const T1 *)(addr))
#define storepix(val, addr) vstore3(val, 0, (__global T1 *)(addr))
#define TSIZE (int)sizeof(T1) * cn
#endif
#define scnbytes ((int)sizeof(type))
#define op(a, b) { mid = a; a = min(a, b); b = max(mid, b); }
#define op(a,b) { mid=a; a=min(a,b); b=max(mid,b);}
__kernel void medianFilter3(__global const uchar* srcptr, int srcStep, int srcOffset,
__global uchar* dstptr, int dstStep, int dstOffset,
int rows, int cols)
__kernel void medianFilter3(__global const uchar * srcptr, int src_step, int src_offset,
__global uchar * dstptr, int dst_step, int dst_offset, int dst_rows, int dst_cols)
{
__local DATA_TYPE data[18][18];
__local T data[18][18];
int x = get_local_id(0);
int y = get_local_id(1);
int gx= get_global_id(0);
int gy= get_global_id(1);
int gx = get_global_id(0);
int gy = get_global_id(1);
int dx = gx - x - 1;
int dy = gy - y - 1;
const int id = min((int)(x*16+y), 9*18-1);
int id = min(mad24(x, 16, y), 9*18-1);
int dr = id / 18;
int dc = id % 18;
int c = clamp(dx+dc, 0, cols-1);
int c = clamp(dx + dc, 0, dst_cols - 1);
int r = clamp(dy+dr, 0, rows-1);
int index1 = mad24(r, srcStep, srcOffset + c*scnbytes);
r = clamp(dy+dr+9, 0, rows-1);
int index9 = mad24(r, srcStep, srcOffset + c*scnbytes);
__global DATA_TYPE * src = (__global DATA_TYPE *)(srcptr + index1);
data[dr][dc] = src[0];
src = (__global DATA_TYPE *)(srcptr + index9);
data[dr+9][dc] = src[0];
int r = clamp(dy + dr, 0, dst_rows - 1);
int index1 = mad24(r, src_step, mad24(c, TSIZE, src_offset));
r = clamp(dy + dr + 9, 0, dst_rows - 1);
int index9 = mad24(r, src_step, mad24(c, TSIZE, src_offset));
data[dr][dc] = loadpix(srcptr + index1);
data[dr+9][dc] = loadpix(srcptr + index9);
barrier(CLK_LOCAL_MEM_FENCE);
DATA_TYPE p0=data[y][x], p1=data[y][(x+1)], p2=data[y][(x+2)];
DATA_TYPE p3=data[y+1][x], p4=data[y+1][(x+1)], p5=data[y+1][(x+2)];
DATA_TYPE p6=data[y+2][x], p7=data[y+2][(x+1)], p8=data[y+2][(x+2)];
DATA_TYPE mid;
T p0 = data[y][x], p1 = data[y][(x+1)], p2 = data[y][(x+2)];
T p3 = data[y+1][x], p4 = data[y+1][(x+1)], p5 = data[y+1][(x+2)];
T p6 = data[y+2][x], p7 = data[y+2][(x+1)], p8 = data[y+2][(x+2)];
T mid;
op(p1, p2); op(p4, p5); op(p7, p8); op(p0, p1);
op(p3, p4); op(p6, p7); op(p1, p2); op(p4, p5);
@ -82,56 +82,48 @@ __kernel void medianFilter3(__global const uchar* srcptr, int srcStep, int srcOf
op(p3, p6); op(p1, p4); op(p2, p5); op(p4, p7);
op(p4, p2); op(p6, p4); op(p4, p2);
int dst_index = mad24( gy, dstStep, dstOffset + gx * scnbytes);
int dst_index = mad24( gy, dst_step, mad24(gx, TSIZE, dst_offset));
if( gy < rows && gx < cols)
{
__global DATA_TYPE* dst = (__global DATA_TYPE *)(dstptr + dst_index);
dst[0] = p4;
}
if (gy < dst_rows && gx < dst_cols)
storepix(p4, dstptr + dst_index);
}
__kernel void medianFilter5(__global const uchar* srcptr, int srcStep, int srcOffset,
__global uchar* dstptr, int dstStep, int dstOffset,
int rows, int cols)
__kernel void medianFilter5(__global const uchar * srcptr, int src_step, int src_offset,
__global uchar * dstptr, int dst_step, int dst_offset, int dst_rows, int dst_cols)
{
__local DATA_TYPE data[20][20];
__local T data[20][20];
int x =get_local_id(0);
int y =get_local_id(1);
int x = get_local_id(0);
int y = get_local_id(1);
int gx=get_global_id(0);
int gy=get_global_id(1);
int gx = get_global_id(0);
int gy = get_global_id(1);
int dx = gx - x - 2;
int dy = gy - y - 2;
const int id = min((int)(x*16+y), 10*20-1);
int id = min(mad24(x, 16, y), 10*20-1);
int dr=id/20;
int dc=id%20;
int dr = id / 20;
int dc = id % 20;
int c=clamp(dx+dc, 0, cols-1);
int c = clamp(dx + dc, 0, dst_cols - 1);
int r = clamp(dy + dr, 0, dst_rows - 1);
int index1 = mad24(r, src_step, mad24(c, TSIZE, src_offset));
int r = clamp(dy+dr, 0, rows-1);
int index1 = mad24(r, srcStep, srcOffset + c*scnbytes);
r = clamp(dy+dr+10, 0, rows-1);
int index10 = mad24(r, srcStep, srcOffset + c*scnbytes);
__global DATA_TYPE * src = (__global DATA_TYPE *)(srcptr + index1);
data[dr][dc] = src[0];
src = (__global DATA_TYPE *)(srcptr + index10);
data[dr+10][dc] = src[0];
r = clamp(dy + dr + 10, 0, dst_rows - 1);
int index10 = mad24(r, src_step, mad24(c, TSIZE, src_offset));
data[dr][dc] = loadpix(srcptr + index1);
data[dr+10][dc] = loadpix(srcptr + index10);
barrier(CLK_LOCAL_MEM_FENCE);
DATA_TYPE p0=data[y][x], p1=data[y][x+1], p2=data[y][x+2], p3=data[y][x+3], p4=data[y][x+4];
DATA_TYPE p5=data[y+1][x], p6=data[y+1][x+1], p7=data[y+1][x+2], p8=data[y+1][x+3], p9=data[y+1][x+4];
DATA_TYPE p10=data[y+2][x], p11=data[y+2][x+1], p12=data[y+2][x+2], p13=data[y+2][x+3], p14=data[y+2][x+4];
DATA_TYPE p15=data[y+3][x], p16=data[y+3][x+1], p17=data[y+3][x+2], p18=data[y+3][x+3], p19=data[y+3][x+4];
DATA_TYPE p20=data[y+4][x], p21=data[y+4][x+1], p22=data[y+4][x+2], p23=data[y+4][x+3], p24=data[y+4][x+4];
DATA_TYPE mid;
T p0 = data[y][x], p1 = data[y][x+1], p2 = data[y][x+2], p3 = data[y][x+3], p4 = data[y][x+4];
T p5 = data[y+1][x], p6 = data[y+1][x+1], p7 = data[y+1][x+2], p8 = data[y+1][x+3], p9 = data[y+1][x+4];
T p10 = data[y+2][x], p11 = data[y+2][x+1], p12 = data[y+2][x+2], p13 = data[y+2][x+3], p14 = data[y+2][x+4];
T p15 = data[y+3][x], p16 = data[y+3][x+1], p17 = data[y+3][x+2], p18 = data[y+3][x+3], p19 = data[y+3][x+4];
T p20 = data[y+4][x], p21 = data[y+4][x+1], p22 = data[y+4][x+2], p23 = data[y+4][x+3], p24 = data[y+4][x+4];
T mid;
op(p1, p2); op(p0, p1); op(p1, p2); op(p4, p5); op(p3, p4);
op(p4, p5); op(p0, p3); op(p2, p5); op(p2, p3); op(p1, p4);
@ -157,11 +149,8 @@ __kernel void medianFilter5(__global const uchar* srcptr, int srcStep, int srcOf
op(p13, p17); op(p3, p15); op(p11, p23); op(p11, p15); op(p7, p19);
op(p7, p11); op(p11, p13); op(p11, p12);
int dst_index = mad24( gy, dstStep, dstOffset + gx * scnbytes);
int dst_index = mad24(gy, dst_step, mad24(gx, TSIZE, dst_offset));
if( gy < rows && gx < cols)
{
__global DATA_TYPE* dst = (__global DATA_TYPE *)(dstptr + dst_index);
dst[0] = p12;
}
if (gy < dst_rows && gx < dst_cols)
storepix(p12, dstptr + dst_index);
}

28
modules/imgproc/src/smooth.cpp
View File

@ -1904,35 +1904,27 @@ medianBlur_SortNet( const Mat& _src, Mat& _dst, int m )
#ifdef HAVE_OPENCL
static bool ocl_medianFilter ( InputArray _src, OutputArray _dst, int m)
static bool ocl_medianFilter(InputArray _src, OutputArray _dst, int m)
{
int type = _src.type();
int depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
int type = _src.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
if (!((depth == CV_8U || depth == CV_16U || depth == CV_16S || depth == CV_32F) && (cn != 3 && cn <= 4)))
if ( !((depth == CV_8U || depth == CV_16U || depth == CV_16S || depth == CV_32F) && cn <= 4 && (m == 3 || m == 5)) )
return false;
const char * kernelName;
if (m == 3)
kernelName = "medianFilter3";
else if (m == 5)
kernelName = "medianFilter5";
else
return false;
ocl::Kernel k(kernelName,ocl::imgproc::medianFilter_oclsrc,format("-D type=%s",ocl::typeToStr(type)));
ocl::Kernel k(format("medianFilter%d", m).c_str(), ocl::imgproc::medianFilter_oclsrc,
format("-D T=%s -D T1=%s -D cn=%d", ocl::typeToStr(type),
ocl::typeToStr(depth), cn));
if (k.empty())
return false;
UMat src = _src.getUMat();
_dst.create(_src.size(),type);
_dst.create(src.size(), type);
UMat dst = _dst.getUMat();
size_t globalsize[2] = {(src.cols + 18) / 16 * 16, (src.rows + 15) / 16 * 16};
size_t localsize[2] = {16, 16};
k.args(ocl::KernelArg::ReadOnlyNoSize(src), ocl::KernelArg::WriteOnly(dst));
return k.args(ocl::KernelArg::ReadOnlyNoSize(src), ocl::KernelArg::WriteOnly(dst)).run(2,globalsize,localsize,false);
size_t globalsize[2] = { (src.cols + 18) / 16 * 16, (src.rows + 15) / 16 * 16}, localsize[2] = { 16, 16 };
return k.run(2, globalsize, localsize, false);
}
#endif

2
modules/imgproc/test/ocl/test_medianfilter.cpp
View File

@ -102,7 +102,7 @@ OCL_TEST_P(MedianFilter, Mat)
OCL_INSTANTIATE_TEST_CASE_P(ImageProc, MedianFilter, Combine(
Values(CV_8U, CV_16U, CV_16S, CV_32F),
Values(1, 2, 4),
OCL_ALL_CHANNELS,
Values(3, 5),
Bool())
);