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gpuimgproc module fixes

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This commit is contained in:
Vladislav Vinogradov
2013-04-18 10:46:28 +04:00
parent b4f3d08725
commit c0b3424a23
40 changed files with 4364 additions and 3263 deletions
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138
modules/gpuimgproc/src/cuda/imgproc.cu → modules/gpuimgproc/src/cuda/corners.cu
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@@ -52,137 +52,6 @@ namespace cv { namespace gpu { namespace cudev
{
namespace imgproc
{
/////////////////////////////////// MeanShiftfiltering ///////////////////////////////////////////////
texture<uchar4, 2> tex_meanshift;
__device__ short2 do_mean_shift(int x0, int y0, unsigned char* out,
size_t out_step, int cols, int rows,
int sp, int sr, int maxIter, float eps)
{
int isr2 = sr*sr;
uchar4 c = tex2D(tex_meanshift, x0, y0 );
// iterate meanshift procedure
for( int iter = 0; iter < maxIter; iter++ )
{
int count = 0;
int s0 = 0, s1 = 0, s2 = 0, sx = 0, sy = 0;
float icount;
//mean shift: process pixels in window (p-sigmaSp)x(p+sigmaSp)
int minx = x0-sp;
int miny = y0-sp;
int maxx = x0+sp;
int maxy = y0+sp;
for( int y = miny; y <= maxy; y++)
{
int rowCount = 0;
for( int x = minx; x <= maxx; x++ )
{
uchar4 t = tex2D( tex_meanshift, x, y );
int norm2 = (t.x - c.x) * (t.x - c.x) + (t.y - c.y) * (t.y - c.y) + (t.z - c.z) * (t.z - c.z);
if( norm2 <= isr2 )
{
s0 += t.x; s1 += t.y; s2 += t.z;
sx += x; rowCount++;
}
}
count += rowCount;
sy += y*rowCount;
}
if( count == 0 )
break;
icount = 1.f/count;
int x1 = __float2int_rz(sx*icount);
int y1 = __float2int_rz(sy*icount);
s0 = __float2int_rz(s0*icount);
s1 = __float2int_rz(s1*icount);
s2 = __float2int_rz(s2*icount);
int norm2 = (s0 - c.x) * (s0 - c.x) + (s1 - c.y) * (s1 - c.y) + (s2 - c.z) * (s2 - c.z);
bool stopFlag = (x0 == x1 && y0 == y1) || (::abs(x1-x0) + ::abs(y1-y0) + norm2 <= eps);
x0 = x1; y0 = y1;
c.x = s0; c.y = s1; c.z = s2;
if( stopFlag )
break;
}
int base = (blockIdx.y * blockDim.y + threadIdx.y) * out_step + (blockIdx.x * blockDim.x + threadIdx.x) * 4 * sizeof(uchar);
*(uchar4*)(out + base) = c;
return make_short2((short)x0, (short)y0);
}
__global__ void meanshift_kernel(unsigned char* out, size_t out_step, int cols, int rows, int sp, int sr, int maxIter, float eps )
{
int x0 = blockIdx.x * blockDim.x + threadIdx.x;
int y0 = blockIdx.y * blockDim.y + threadIdx.y;
if( x0 < cols && y0 < rows )
do_mean_shift(x0, y0, out, out_step, cols, rows, sp, sr, maxIter, eps);
}
__global__ void meanshiftproc_kernel(unsigned char* outr, size_t outrstep,
unsigned char* outsp, size_t outspstep,
int cols, int rows,
int sp, int sr, int maxIter, float eps)
{
int x0 = blockIdx.x * blockDim.x + threadIdx.x;
int y0 = blockIdx.y * blockDim.y + threadIdx.y;
if( x0 < cols && y0 < rows )
{
int basesp = (blockIdx.y * blockDim.y + threadIdx.y) * outspstep + (blockIdx.x * blockDim.x + threadIdx.x) * 2 * sizeof(short);
*(short2*)(outsp + basesp) = do_mean_shift(x0, y0, outr, outrstep, cols, rows, sp, sr, maxIter, eps);
}
}
void meanShiftFiltering_gpu(const PtrStepSzb& src, PtrStepSzb dst, int sp, int sr, int maxIter, float eps, cudaStream_t stream)
{
dim3 grid(1, 1, 1);
dim3 threads(32, 8, 1);
grid.x = divUp(src.cols, threads.x);
grid.y = divUp(src.rows, threads.y);
cudaChannelFormatDesc desc = cudaCreateChannelDesc<uchar4>();
cudaSafeCall( cudaBindTexture2D( 0, tex_meanshift, src.data, desc, src.cols, src.rows, src.step ) );
meanshift_kernel<<< grid, threads, 0, stream >>>( dst.data, dst.step, dst.cols, dst.rows, sp, sr, maxIter, eps );
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
//cudaSafeCall( cudaUnbindTexture( tex_meanshift ) );
}
void meanShiftProc_gpu(const PtrStepSzb& src, PtrStepSzb dstr, PtrStepSzb dstsp, int sp, int sr, int maxIter, float eps, cudaStream_t stream)
{
dim3 grid(1, 1, 1);
dim3 threads(32, 8, 1);
grid.x = divUp(src.cols, threads.x);
grid.y = divUp(src.rows, threads.y);
cudaChannelFormatDesc desc = cudaCreateChannelDesc<uchar4>();
cudaSafeCall( cudaBindTexture2D( 0, tex_meanshift, src.data, desc, src.cols, src.rows, src.step ) );
meanshiftproc_kernel<<< grid, threads, 0, stream >>>( dstr.data, dstr.step, dstsp.data, dstsp.step, dstr.cols, dstr.rows, sp, sr, maxIter, eps );
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
//cudaSafeCall( cudaUnbindTexture( tex_meanshift ) );
}
/////////////////////////////////////////// Corner Harris /////////////////////////////////////////////////
texture<float, cudaTextureType2D, cudaReadModeElementType> harrisDxTex(0, cudaFilterModePoint, cudaAddressModeClamp);
@@ -399,8 +268,7 @@ namespace cv { namespace gpu { namespace cudev
if (stream == 0)
cudaSafeCall(cudaDeviceSynchronize());
}
} // namespace imgproc
}}} // namespace cv { namespace gpu { namespace cudev {
}
}}}
#endif /* CUDA_DISABLER */
#endif

182
modules/gpuimgproc/src/cuda/mean_shift.cu Normal file
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@@ -0,0 +1,182 @@
/*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) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// 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 materials 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*/
#if !defined CUDA_DISABLER
#include "opencv2/core/cuda/common.hpp"
#include "opencv2/core/cuda/vec_traits.hpp"
#include "opencv2/core/cuda/vec_math.hpp"
#include "opencv2/core/cuda/saturate_cast.hpp"
#include "opencv2/core/cuda/border_interpolate.hpp"
namespace cv { namespace gpu { namespace cudev
{
namespace imgproc
{
texture<uchar4, 2> tex_meanshift;
__device__ short2 do_mean_shift(int x0, int y0, unsigned char* out,
size_t out_step, int cols, int rows,
int sp, int sr, int maxIter, float eps)
{
int isr2 = sr*sr;
uchar4 c = tex2D(tex_meanshift, x0, y0 );
// iterate meanshift procedure
for( int iter = 0; iter < maxIter; iter++ )
{
int count = 0;
int s0 = 0, s1 = 0, s2 = 0, sx = 0, sy = 0;
float icount;
//mean shift: process pixels in window (p-sigmaSp)x(p+sigmaSp)
int minx = x0-sp;
int miny = y0-sp;
int maxx = x0+sp;
int maxy = y0+sp;
for( int y = miny; y <= maxy; y++)
{
int rowCount = 0;
for( int x = minx; x <= maxx; x++ )
{
uchar4 t = tex2D( tex_meanshift, x, y );
int norm2 = (t.x - c.x) * (t.x - c.x) + (t.y - c.y) * (t.y - c.y) + (t.z - c.z) * (t.z - c.z);
if( norm2 <= isr2 )
{
s0 += t.x; s1 += t.y; s2 += t.z;
sx += x; rowCount++;
}
}
count += rowCount;
sy += y*rowCount;
}
if( count == 0 )
break;
icount = 1.f/count;
int x1 = __float2int_rz(sx*icount);
int y1 = __float2int_rz(sy*icount);
s0 = __float2int_rz(s0*icount);
s1 = __float2int_rz(s1*icount);
s2 = __float2int_rz(s2*icount);
int norm2 = (s0 - c.x) * (s0 - c.x) + (s1 - c.y) * (s1 - c.y) + (s2 - c.z) * (s2 - c.z);
bool stopFlag = (x0 == x1 && y0 == y1) || (::abs(x1-x0) + ::abs(y1-y0) + norm2 <= eps);
x0 = x1; y0 = y1;
c.x = s0; c.y = s1; c.z = s2;
if( stopFlag )
break;
}
int base = (blockIdx.y * blockDim.y + threadIdx.y) * out_step + (blockIdx.x * blockDim.x + threadIdx.x) * 4 * sizeof(uchar);
*(uchar4*)(out + base) = c;
return make_short2((short)x0, (short)y0);
}
__global__ void meanshift_kernel(unsigned char* out, size_t out_step, int cols, int rows, int sp, int sr, int maxIter, float eps )
{
int x0 = blockIdx.x * blockDim.x + threadIdx.x;
int y0 = blockIdx.y * blockDim.y + threadIdx.y;
if( x0 < cols && y0 < rows )
do_mean_shift(x0, y0, out, out_step, cols, rows, sp, sr, maxIter, eps);
}
void meanShiftFiltering_gpu(const PtrStepSzb& src, PtrStepSzb dst, int sp, int sr, int maxIter, float eps, cudaStream_t stream)
{
dim3 grid(1, 1, 1);
dim3 threads(32, 8, 1);
grid.x = divUp(src.cols, threads.x);
grid.y = divUp(src.rows, threads.y);
cudaChannelFormatDesc desc = cudaCreateChannelDesc<uchar4>();
cudaSafeCall( cudaBindTexture2D( 0, tex_meanshift, src.data, desc, src.cols, src.rows, src.step ) );
meanshift_kernel<<< grid, threads, 0, stream >>>( dst.data, dst.step, dst.cols, dst.rows, sp, sr, maxIter, eps );
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
__global__ void meanshiftproc_kernel(unsigned char* outr, size_t outrstep,
unsigned char* outsp, size_t outspstep,
int cols, int rows,
int sp, int sr, int maxIter, float eps)
{
int x0 = blockIdx.x * blockDim.x + threadIdx.x;
int y0 = blockIdx.y * blockDim.y + threadIdx.y;
if( x0 < cols && y0 < rows )
{
int basesp = (blockIdx.y * blockDim.y + threadIdx.y) * outspstep + (blockIdx.x * blockDim.x + threadIdx.x) * 2 * sizeof(short);
*(short2*)(outsp + basesp) = do_mean_shift(x0, y0, outr, outrstep, cols, rows, sp, sr, maxIter, eps);
}
}
void meanShiftProc_gpu(const PtrStepSzb& src, PtrStepSzb dstr, PtrStepSzb dstsp, int sp, int sr, int maxIter, float eps, cudaStream_t stream)
{
dim3 grid(1, 1, 1);
dim3 threads(32, 8, 1);
grid.x = divUp(src.cols, threads.x);
grid.y = divUp(src.rows, threads.y);
cudaChannelFormatDesc desc = cudaCreateChannelDesc<uchar4>();
cudaSafeCall( cudaBindTexture2D( 0, tex_meanshift, src.data, desc, src.cols, src.rows, src.step ) );
meanshiftproc_kernel<<< grid, threads, 0, stream >>>( dstr.data, dstr.step, dstsp.data, dstsp.step, dstr.cols, dstr.rows, sp, sr, maxIter, eps );
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
}
}}}
#endif