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1.x related fixes

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This commit is contained in:
marina.kolpakova 2012-08-09 18:48:25 +04:00
parent 3f68e5bb0e
commit 40c76b9de2
6 changed files with 594 additions and 415 deletions

4
modules/gpu/perf/perf_labeling.cpp

@ -48,7 +48,9 @@ GPU_PERF_TEST(ConnectedComponents, cv::gpu::DeviceInfo, cv::Size)
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::gpu::setDevice(devInfo.deviceID());
cv::Mat image = readImage("gpu/labeling/label.png", cv::IMREAD_GRAYSCALE);
cv::Mat image = readImage("gpu/labeling/aloe-disp.png", cv::IMREAD_GRAYSCALE);
cv::threshold(image, image, 150, 255, CV_THRESH_BINARY);
cv::gpu::GpuMat mask;
mask.create(image.rows, image.cols, CV_8UC1);

157
modules/gpu/perf_cpu/perf_labeling.cpp Normal file

@ -0,0 +1,157 @@
/*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) 2008-2011, 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:
//
// * Redistributions of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistributions 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*/
#include "perf_precomp.hpp"
#ifdef HAVE_CUDA
namespace {
struct GreedyLabeling
{
struct dot
{
int x;
int y;
static dot make(int i, int j)
{
dot d; d.x = i; d.y = j;
return d;
}
};
struct InInterval
{
InInterval(const int& _lo, const int& _hi) : lo(-_lo), hi(_hi) {};
const int lo, hi;
bool operator() (const unsigned char a, const unsigned char b) const
{
int d = a - b;
return lo <= d && d <= hi;
}
};
GreedyLabeling(cv::Mat img)
: image(img), _labels(image.size(), CV_32SC1, cv::Scalar::all(-1)) {stack = new dot[image.cols * image.rows];}
~GreedyLabeling(){delete[] stack;}
void operator() (cv::Mat labels) const
{
InInterval inInt(0, 2);
int cc = -1;
int* dist_labels = (int*)labels.data;
int pitch = labels.step1();
unsigned char* source = (unsigned char*)image.data;
int width = image.cols;
int height = image.rows;
for (int j = 0; j < image.rows; ++j)
for (int i = 0; i < image.cols; ++i)
{
if (dist_labels[j * pitch + i] != -1) continue;
dot* top = stack;
dot p = dot::make(i, j);
cc++;
dist_labels[j * pitch + i] = cc;
while (top >= stack)
{
int* dl = &dist_labels[p.y * pitch + p.x];
unsigned char* sp = &source[p.y * image.step1() + p.x];
dl[0] = cc;
//right
if( p.x < (width - 1) && dl[ +1] == -1 && inInt(sp[0], sp[+1]))
*top++ = dot::make(p.x + 1, p.y);
//left
if( p.x > 0 && dl[-1] == -1 && inInt(sp[0], sp[-1]))
*top++ = dot::make(p.x - 1, p.y);
//bottom
if( p.y < (height - 1) && dl[+pitch] == -1 && inInt(sp[0], sp[+image.step1()]))
*top++ = dot::make(p.x, p.y + 1);
//top
if( p.y > 0 && dl[-pitch] == -1 && inInt(sp[0], sp[-image.step1()]))
*top++ = dot::make(p.x, p.y - 1);
p = *--top;
}
}
}
cv::Mat image;
cv::Mat _labels;
dot* stack;
};
}
GPU_PERF_TEST(ConnectedComponents, cv::gpu::DeviceInfo, cv::Size)
{
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::gpu::setDevice(devInfo.deviceID());
cv::Mat image = readImage("gpu/labeling/aloe-disp.png", cv::IMREAD_GRAYSCALE);
GreedyLabeling host(image);
host(host._labels);
declare.time(1.0);
TEST_CYCLE()
{
host(host._labels);
}
}
INSTANTIATE_TEST_CASE_P(Labeling, ConnectedComponents, testing::Combine(ALL_DEVICES, testing::Values(cv::Size(261, 262))));
#endif

9
modules/gpu/src/cuda/ccomponetns.cu

@ -42,6 +42,7 @@
#include <opencv2/gpu/device/common.hpp>
#include <opencv2/gpu/device/vec_traits.hpp>
#include <opencv2/gpu/device/vec_math.hpp>
#include <opencv2/gpu/device/emulation.hpp>
#include <iostream>
#include <stdio.h>
@ -255,8 +256,7 @@ namespace cv { namespace gpu { namespace device
edgesTile[yloc][xloc] = c;
}
for (int i = 0; ; ++i)
for (int k = 0; ;++k)
{
//1. backup
#pragma unroll
@ -312,11 +312,12 @@ namespace cv { namespace gpu { namespace device
if (new_labels[i][j] < old_labels[i][j])
{
changed = 1;
atomicMin(&labelsTile[0][0] + old_labels[i][j], new_labels[i][j]);
Emulation::smem::atomicMin(&labelsTile[0][0] + old_labels[i][j], new_labels[i][j]);
}
}
changed = __syncthreads_or(changed);
changed = Emulation::sycthOr(changed);
if (!changed)
break;

570
modules/gpu/src/graphcuts.cpp

@ -1,284 +1,286 @@
/*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 GpuMaterials 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 bpied warranties, including, but not limited to, the bpied
// 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*/
#include "precomp.hpp"
#if !defined (HAVE_CUDA)
void cv::gpu::graphcut(GpuMat&, GpuMat&, GpuMat&, GpuMat&, GpuMat&, GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
void cv::gpu::graphcut(GpuMat&, GpuMat&, GpuMat&, GpuMat&, GpuMat&, GpuMat&, GpuMat&, GpuMat&, GpuMat&, GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
void cv::gpu::connectivityMask(const GpuMat&, GpuMat&, const cv::Scalar&, const cv::Scalar&, Stream&) { throw_nogpu(); }
void cv::gpu::labelComponents(const GpuMat& mask, GpuMat& components, int, Stream& stream) { throw_nogpu(); }
#else /* !defined (HAVE_CUDA) */
namespace cv { namespace gpu { namespace device
{
namespace ccl
{
void labelComponents(const DevMem2D& edges, DevMem2Di comps, int flags, cudaStream_t stream);
template<typename T>
void computeEdges(const DevMem2D& image, DevMem2D edges, const float4& lo, const float4& hi, cudaStream_t stream);
}
}}}
float4 scalarToCudaType(const cv::Scalar& in)
{
float4 res;
res.x = in[0]; res.y = in[1]; res.z = in[2]; res.w = in[3];
return res;
}
void cv::gpu::connectivityMask(const GpuMat& image, GpuMat& mask, const cv::Scalar& lo, const cv::Scalar& hi, Stream& s)
{
CV_Assert(!image.empty());
int ch = image.channels();
CV_Assert(ch <= 4);
int depth = image.depth();
typedef void (*func_t)(const DevMem2D& image, DevMem2D edges, const float4& lo, const float4& hi, cudaStream_t stream);
static const func_t suppotLookup[8][4] =
{ // 1, 2, 3, 4
{ device::ccl::computeEdges<uchar>, 0, device::ccl::computeEdges<uchar3>, device::ccl::computeEdges<uchar4> },// CV_8U
{ 0, 0, 0, 0 },// CV_16U
{ device::ccl::computeEdges<ushort>, 0, device::ccl::computeEdges<ushort3>, device::ccl::computeEdges<ushort4> },// CV_8S
{ 0, 0, 0, 0 },// CV_16S
{ device::ccl::computeEdges<int>, 0, 0, 0 },// CV_32S
{ device::ccl::computeEdges<float>, 0, 0, 0 },// CV_32F
{ 0, 0, 0, 0 },// CV_64F
{ 0, 0, 0, 0 } // CV_USRTYPE1
};
func_t f = suppotLookup[depth][ch - 1];
CV_Assert(f);
if (image.size() != mask.size() || mask.type() != CV_8UC1)
mask.create(image.size(), CV_8UC1);
cudaStream_t stream = StreamAccessor::getStream(s);
float4 culo = scalarToCudaType(lo), cuhi = scalarToCudaType(hi);
f(image, mask, culo, cuhi, stream);
}
void cv::gpu::labelComponents(const GpuMat& mask, GpuMat& components, int flags, Stream& s)
{
CV_Assert(!mask.empty() && mask.type() == CV_8U);
if (mask.size() != components.size() || components.type() != CV_32SC1)
components.create(mask.size(), CV_32SC1);
cudaStream_t stream = StreamAccessor::getStream(s);
device::ccl::labelComponents(mask, components, flags, stream);
}
namespace
{
typedef NppStatus (*init_func_t)(NppiSize oSize, NppiGraphcutState** ppState, Npp8u* pDeviceMem);
class NppiGraphcutStateHandler
{
public:
NppiGraphcutStateHandler(NppiSize sznpp, Npp8u* pDeviceMem, const init_func_t func)
{
nppSafeCall( func(sznpp, &pState, pDeviceMem) );
}
~NppiGraphcutStateHandler()
{
nppSafeCall( nppiGraphcutFree(pState) );
}
operator NppiGraphcutState*()
{
return pState;
}
private:
NppiGraphcutState* pState;
};
}
void cv::gpu::graphcut(GpuMat& terminals, GpuMat& leftTransp, GpuMat& rightTransp, GpuMat& top, GpuMat& bottom, GpuMat& labels, GpuMat& buf, Stream& s)
{
#if (CUDA_VERSION < 5000)
CV_Assert(terminals.type() == CV_32S);
#else
CV_Assert(terminals.type() == CV_32S || terminals.type() == CV_32F);
#endif
Size src_size = terminals.size();
CV_Assert(leftTransp.size() == Size(src_size.height, src_size.width));
CV_Assert(leftTransp.type() == terminals.type());
CV_Assert(rightTransp.size() == Size(src_size.height, src_size.width));
CV_Assert(rightTransp.type() == terminals.type());
CV_Assert(top.size() == src_size);
CV_Assert(top.type() == terminals.type());
CV_Assert(bottom.size() == src_size);
CV_Assert(bottom.type() == terminals.type());
labels.create(src_size, CV_8U);
NppiSize sznpp;
sznpp.width = src_size.width;
sznpp.height = src_size.height;
int bufsz;
nppSafeCall( nppiGraphcutGetSize(sznpp, &bufsz) );
ensureSizeIsEnough(1, bufsz, CV_8U, buf);
cudaStream_t stream = StreamAccessor::getStream(s);
NppStreamHandler h(stream);
NppiGraphcutStateHandler state(sznpp, buf.ptr<Npp8u>(), nppiGraphcutInitAlloc);
#if (CUDA_VERSION < 5000)
nppSafeCall( nppiGraphcut_32s8u(terminals.ptr<Npp32s>(), leftTransp.ptr<Npp32s>(), rightTransp.ptr<Npp32s>(), top.ptr<Npp32s>(), bottom.ptr<Npp32s>(),
static_cast<int>(terminals.step), static_cast<int>(leftTransp.step), sznpp, labels.ptr<Npp8u>(), static_cast<int>(labels.step), state) );
#else
if (terminals.type() == CV_32S)
{
nppSafeCall( nppiGraphcut_32s8u(terminals.ptr<Npp32s>(), leftTransp.ptr<Npp32s>(), rightTransp.ptr<Npp32s>(), top.ptr<Npp32s>(), bottom.ptr<Npp32s>(),
static_cast<int>(terminals.step), static_cast<int>(leftTransp.step), sznpp, labels.ptr<Npp8u>(), static_cast<int>(labels.step), state) );
}
else
{
nppSafeCall( nppiGraphcut_32f8u(terminals.ptr<Npp32f>(), leftTransp.ptr<Npp32f>(), rightTransp.ptr<Npp32f>(), top.ptr<Npp32f>(), bottom.ptr<Npp32f>(),
static_cast<int>(terminals.step), static_cast<int>(leftTransp.step), sznpp, labels.ptr<Npp8u>(), static_cast<int>(labels.step), state) );
}
#endif
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
void cv::gpu::graphcut(GpuMat& terminals, GpuMat& leftTransp, GpuMat& rightTransp, GpuMat& top, GpuMat& topLeft, GpuMat& topRight,
GpuMat& bottom, GpuMat& bottomLeft, GpuMat& bottomRight, GpuMat& labels, GpuMat& buf, Stream& s)
{
#if (CUDA_VERSION < 5000)
CV_Assert(terminals.type() == CV_32S);
#else
CV_Assert(terminals.type() == CV_32S || terminals.type() == CV_32F);
#endif
Size src_size = terminals.size();
CV_Assert(leftTransp.size() == Size(src_size.height, src_size.width));
CV_Assert(leftTransp.type() == terminals.type());
CV_Assert(rightTransp.size() == Size(src_size.height, src_size.width));
CV_Assert(rightTransp.type() == terminals.type());
CV_Assert(top.size() == src_size);
CV_Assert(top.type() == terminals.type());
CV_Assert(topLeft.size() == src_size);
CV_Assert(topLeft.type() == terminals.type());
CV_Assert(topRight.size() == src_size);
CV_Assert(topRight.type() == terminals.type());
CV_Assert(bottom.size() == src_size);
CV_Assert(bottom.type() == terminals.type());
CV_Assert(bottomLeft.size() == src_size);
CV_Assert(bottomLeft.type() == terminals.type());
CV_Assert(bottomRight.size() == src_size);
CV_Assert(bottomRight.type() == terminals.type());
labels.create(src_size, CV_8U);
NppiSize sznpp;
sznpp.width = src_size.width;
sznpp.height = src_size.height;
int bufsz;
nppSafeCall( nppiGraphcut8GetSize(sznpp, &bufsz) );
ensureSizeIsEnough(1, bufsz, CV_8U, buf);
cudaStream_t stream = StreamAccessor::getStream(s);
NppStreamHandler h(stream);
NppiGraphcutStateHandler state(sznpp, buf.ptr<Npp8u>(), nppiGraphcut8InitAlloc);
#if (CUDA_VERSION < 5000)
nppSafeCall( nppiGraphcut8_32s8u(terminals.ptr<Npp32s>(), leftTransp.ptr<Npp32s>(), rightTransp.ptr<Npp32s>(),
top.ptr<Npp32s>(), topLeft.ptr<Npp32s>(), topRight.ptr<Npp32s>(),
bottom.ptr<Npp32s>(), bottomLeft.ptr<Npp32s>(), bottomRight.ptr<Npp32s>(),
static_cast<int>(terminals.step), static_cast<int>(leftTransp.step), sznpp, labels.ptr<Npp8u>(), static_cast<int>(labels.step), state) );
#else
if (terminals.type() == CV_32S)
{
nppSafeCall( nppiGraphcut8_32s8u(terminals.ptr<Npp32s>(), leftTransp.ptr<Npp32s>(), rightTransp.ptr<Npp32s>(),
top.ptr<Npp32s>(), topLeft.ptr<Npp32s>(), topRight.ptr<Npp32s>(),
bottom.ptr<Npp32s>(), bottomLeft.ptr<Npp32s>(), bottomRight.ptr<Npp32s>(),
static_cast<int>(terminals.step), static_cast<int>(leftTransp.step), sznpp, labels.ptr<Npp8u>(), static_cast<int>(labels.step), state) );
}
else
{
nppSafeCall( nppiGraphcut8_32f8u(terminals.ptr<Npp32f>(), leftTransp.ptr<Npp32f>(), rightTransp.ptr<Npp32f>(),
top.ptr<Npp32f>(), topLeft.ptr<Npp32f>(), topRight.ptr<Npp32f>(),
bottom.ptr<Npp32f>(), bottomLeft.ptr<Npp32f>(), bottomRight.ptr<Npp32f>(),
static_cast<int>(terminals.step), static_cast<int>(leftTransp.step), sznpp, labels.ptr<Npp8u>(), static_cast<int>(labels.step), state) );
}
#endif
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
#endif /* !defined (HAVE_CUDA) */
/*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 GpuMaterials 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 bpied warranties, including, but not limited to, the bpied
// 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*/
#include "precomp.hpp"
#if !defined (HAVE_CUDA)
void cv::gpu::graphcut(GpuMat&, GpuMat&, GpuMat&, GpuMat&, GpuMat&, GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
void cv::gpu::graphcut(GpuMat&, GpuMat&, GpuMat&, GpuMat&, GpuMat&, GpuMat&, GpuMat&, GpuMat&, GpuMat&, GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
void cv::gpu::connectivityMask(const GpuMat&, GpuMat&, const cv::Scalar&, const cv::Scalar&, Stream&) { throw_nogpu(); }
void cv::gpu::labelComponents(const GpuMat& mask, GpuMat& components, int, Stream& stream) { throw_nogpu(); }
#else /* !defined (HAVE_CUDA) */
namespace cv { namespace gpu { namespace device
{
namespace ccl
{
void labelComponents(const DevMem2D& edges, DevMem2Di comps, int flags, cudaStream_t stream);
template<typename T>
void computeEdges(const DevMem2D& image, DevMem2D edges, const float4& lo, const float4& hi, cudaStream_t stream);
}
}}}
float4 scalarToCudaType(const cv::Scalar& in)
{
float4 res;
res.x = in[0]; res.y = in[1]; res.z = in[2]; res.w = in[3];
return res;
}
void cv::gpu::connectivityMask(const GpuMat& image, GpuMat& mask, const cv::Scalar& lo, const cv::Scalar& hi, Stream& s)
{
CV_Assert(!image.empty());
int ch = image.channels();
CV_Assert(ch <= 4);
int depth = image.depth();
typedef void (*func_t)(const DevMem2D& image, DevMem2D edges, const float4& lo, const float4& hi, cudaStream_t stream);
static const func_t suppotLookup[8][4] =
{ // 1, 2, 3, 4
{ device::ccl::computeEdges<uchar>, 0, device::ccl::computeEdges<uchar3>, device::ccl::computeEdges<uchar4> },// CV_8U
{ 0, 0, 0, 0 },// CV_16U
{ device::ccl::computeEdges<ushort>, 0, device::ccl::computeEdges<ushort3>, device::ccl::computeEdges<ushort4> },// CV_8S
{ 0, 0, 0, 0 },// CV_16S
{ device::ccl::computeEdges<int>, 0, 0, 0 },// CV_32S
{ device::ccl::computeEdges<float>, 0, 0, 0 },// CV_32F
{ 0, 0, 0, 0 },// CV_64F
{ 0, 0, 0, 0 } // CV_USRTYPE1
};
func_t f = suppotLookup[depth][ch - 1];
CV_Assert(f);
if (image.size() != mask.size() || mask.type() != CV_8UC1)
mask.create(image.size(), CV_8UC1);
cudaStream_t stream = StreamAccessor::getStream(s);
float4 culo = scalarToCudaType(lo), cuhi = scalarToCudaType(hi);
f(image, mask, culo, cuhi, stream);
}
void cv::gpu::labelComponents(const GpuMat& mask, GpuMat& components, int flags, Stream& s)
{
if (!TargetArchs::builtWith(SHARED_ATOMICS) || !DeviceInfo().supports(SHARED_ATOMICS))
CV_Error(CV_StsNotImplemented, "The device doesn't support shared atomics and communicative synchronization!");
CV_Assert(!mask.empty() && mask.type() == CV_8U);
if (mask.size() != components.size() || components.type() != CV_32SC1)
components.create(mask.size(), CV_32SC1);
cudaStream_t stream = StreamAccessor::getStream(s);
device::ccl::labelComponents(mask, components, flags, stream);
}
namespace
{
typedef NppStatus (*init_func_t)(NppiSize oSize, NppiGraphcutState** ppState, Npp8u* pDeviceMem);
class NppiGraphcutStateHandler
{
public:
NppiGraphcutStateHandler(NppiSize sznpp, Npp8u* pDeviceMem, const init_func_t func)
{
nppSafeCall( func(sznpp, &pState, pDeviceMem) );
}
~NppiGraphcutStateHandler()
{
nppSafeCall( nppiGraphcutFree(pState) );
}
operator NppiGraphcutState*()
{
return pState;
}
private:
NppiGraphcutState* pState;
};
}
void cv::gpu::graphcut(GpuMat& terminals, GpuMat& leftTransp, GpuMat& rightTransp, GpuMat& top, GpuMat& bottom, GpuMat& labels, GpuMat& buf, Stream& s)
{
#if (CUDA_VERSION < 5000)
CV_Assert(terminals.type() == CV_32S);
#else
CV_Assert(terminals.type() == CV_32S || terminals.type() == CV_32F);
#endif
Size src_size = terminals.size();
CV_Assert(leftTransp.size() == Size(src_size.height, src_size.width));
CV_Assert(leftTransp.type() == terminals.type());
CV_Assert(rightTransp.size() == Size(src_size.height, src_size.width));
CV_Assert(rightTransp.type() == terminals.type());
CV_Assert(top.size() == src_size);
CV_Assert(top.type() == terminals.type());
CV_Assert(bottom.size() == src_size);
CV_Assert(bottom.type() == terminals.type());
labels.create(src_size, CV_8U);
NppiSize sznpp;
sznpp.width = src_size.width;
sznpp.height = src_size.height;
int bufsz;
nppSafeCall( nppiGraphcutGetSize(sznpp, &bufsz) );
ensureSizeIsEnough(1, bufsz, CV_8U, buf);
cudaStream_t stream = StreamAccessor::getStream(s);
NppStreamHandler h(stream);
NppiGraphcutStateHandler state(sznpp, buf.ptr<Npp8u>(), nppiGraphcutInitAlloc);
#if (CUDA_VERSION < 5000)
nppSafeCall( nppiGraphcut_32s8u(terminals.ptr<Npp32s>(), leftTransp.ptr<Npp32s>(), rightTransp.ptr<Npp32s>(), top.ptr<Npp32s>(), bottom.ptr<Npp32s>(),
static_cast<int>(terminals.step), static_cast<int>(leftTransp.step), sznpp, labels.ptr<Npp8u>(), static_cast<int>(labels.step), state) );
#else
if (terminals.type() == CV_32S)
{
nppSafeCall( nppiGraphcut_32s8u(terminals.ptr<Npp32s>(), leftTransp.ptr<Npp32s>(), rightTransp.ptr<Npp32s>(), top.ptr<Npp32s>(), bottom.ptr<Npp32s>(),
static_cast<int>(terminals.step), static_cast<int>(leftTransp.step), sznpp, labels.ptr<Npp8u>(), static_cast<int>(labels.step), state) );
}
else
{
nppSafeCall( nppiGraphcut_32f8u(terminals.ptr<Npp32f>(), leftTransp.ptr<Npp32f>(), rightTransp.ptr<Npp32f>(), top.ptr<Npp32f>(), bottom.ptr<Npp32f>(),
static_cast<int>(terminals.step), static_cast<int>(leftTransp.step), sznpp, labels.ptr<Npp8u>(), static_cast<int>(labels.step), state) );
}
#endif
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
void cv::gpu::graphcut(GpuMat& terminals, GpuMat& leftTransp, GpuMat& rightTransp, GpuMat& top, GpuMat& topLeft, GpuMat& topRight,
GpuMat& bottom, GpuMat& bottomLeft, GpuMat& bottomRight, GpuMat& labels, GpuMat& buf, Stream& s)
{
#if (CUDA_VERSION < 5000)
CV_Assert(terminals.type() == CV_32S);
#else
CV_Assert(terminals.type() == CV_32S || terminals.type() == CV_32F);
#endif
Size src_size = terminals.size();
CV_Assert(leftTransp.size() == Size(src_size.height, src_size.width));
CV_Assert(leftTransp.type() == terminals.type());
CV_Assert(rightTransp.size() == Size(src_size.height, src_size.width));
CV_Assert(rightTransp.type() == terminals.type());
CV_Assert(top.size() == src_size);
CV_Assert(top.type() == terminals.type());
CV_Assert(topLeft.size() == src_size);
CV_Assert(topLeft.type() == terminals.type());
CV_Assert(topRight.size() == src_size);
CV_Assert(topRight.type() == terminals.type());
CV_Assert(bottom.size() == src_size);
CV_Assert(bottom.type() == terminals.type());
CV_Assert(bottomLeft.size() == src_size);
CV_Assert(bottomLeft.type() == terminals.type());
CV_Assert(bottomRight.size() == src_size);
CV_Assert(bottomRight.type() == terminals.type());
labels.create(src_size, CV_8U);
NppiSize sznpp;
sznpp.width = src_size.width;
sznpp.height = src_size.height;
int bufsz;
nppSafeCall( nppiGraphcut8GetSize(sznpp, &bufsz) );
ensureSizeIsEnough(1, bufsz, CV_8U, buf);
cudaStream_t stream = StreamAccessor::getStream(s);
NppStreamHandler h(stream);
NppiGraphcutStateHandler state(sznpp, buf.ptr<Npp8u>(), nppiGraphcut8InitAlloc);
#if (CUDA_VERSION < 5000)
nppSafeCall( nppiGraphcut8_32s8u(terminals.ptr<Npp32s>(), leftTransp.ptr<Npp32s>(), rightTransp.ptr<Npp32s>(),
top.ptr<Npp32s>(), topLeft.ptr<Npp32s>(), topRight.ptr<Npp32s>(),
bottom.ptr<Npp32s>(), bottomLeft.ptr<Npp32s>(), bottomRight.ptr<Npp32s>(),
static_cast<int>(terminals.step), static_cast<int>(leftTransp.step), sznpp, labels.ptr<Npp8u>(), static_cast<int>(labels.step), state) );
#else
if (terminals.type() == CV_32S)
{
nppSafeCall( nppiGraphcut8_32s8u(terminals.ptr<Npp32s>(), leftTransp.ptr<Npp32s>(), rightTransp.ptr<Npp32s>(),
top.ptr<Npp32s>(), topLeft.ptr<Npp32s>(), topRight.ptr<Npp32s>(),
bottom.ptr<Npp32s>(), bottomLeft.ptr<Npp32s>(), bottomRight.ptr<Npp32s>(),
static_cast<int>(terminals.step), static_cast<int>(leftTransp.step), sznpp, labels.ptr<Npp8u>(), static_cast<int>(labels.step), state) );
}
else
{
nppSafeCall( nppiGraphcut8_32f8u(terminals.ptr<Npp32f>(), leftTransp.ptr<Npp32f>(), rightTransp.ptr<Npp32f>(),
top.ptr<Npp32f>(), topLeft.ptr<Npp32f>(), topRight.ptr<Npp32f>(),
bottom.ptr<Npp32f>(), bottomLeft.ptr<Npp32f>(), bottomRight.ptr<Npp32f>(),
static_cast<int>(terminals.step), static_cast<int>(leftTransp.step), sznpp, labels.ptr<Npp8u>(), static_cast<int>(labels.step), state) );
}
#endif
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
#endif /* !defined (HAVE_CUDA) */

261
modules/gpu/src/opencv2/gpu/device/emulation.hpp

@ -1,126 +1,137 @@
/*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 bpied warranties, including, but not limited to, the bpied
// 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*/
#ifndef OPENCV_GPU_EMULATION_HPP_
#define OPENCV_GPU_EMULATION_HPP_
#include "warp_reduce.hpp"
#include <stdio.h>
namespace cv { namespace gpu { namespace device
{
struct Emulation
{
template<int CTA_SIZE>
static __forceinline__ __device__ int Ballot(int predicate)
{
#if defined (__CUDA_ARCH__) && (__CUDA_ARCH__ >= 200)
return __ballot(predicate);
#else
__shared__ volatile int cta_buffer[CTA_SIZE];
int tid = threadIdx.x;
cta_buffer[tid] = predicate ? (1 << (tid & 31)) : 0;
return warp_reduce(cta_buffer);
#endif
}
struct smem
{
enum { TAG_MASK = (1U << ( (sizeof(unsigned int) << 3) - 5U)) - 1U };
template<typename T>
static __device__ __forceinline__ T atomicInc(T* address, T val)
{
#if defined (__CUDA_ARCH__) && (__CUDA_ARCH__ < 120)
T count;
unsigned int tag = threadIdx.x << ( (sizeof(unsigned int) << 3) - 5U);
do
{
count = *address & TAG_MASK;
count = tag | (count + 1);
*address = count;
} while (*address != count);
return (count & TAG_MASK) - 1;
#else
return ::atomicInc(address, val);
#endif
}
template<typename T>
static __device__ __forceinline__ void atomicAdd(T* address, T val)
{
#if defined (__CUDA_ARCH__) && (__CUDA_ARCH__ < 120)
T count;
unsigned int tag = threadIdx.x << ( (sizeof(unsigned int) << 3) - 5U);
do
{
count = *address & TAG_MASK;
count = tag | (count + val);
*address = count;
} while (*address != count);
#else
::atomicAdd(address, val);
#endif
}
template<typename T>
static __device__ __forceinline__ T atomicMin(T* address, T val)
{
#if defined (__CUDA_ARCH__) && (__CUDA_ARCH__ < 120)
T count = min(*address, val);
do
{
*address = count;
} while (*address > count);
return count;
#else
return ::atomicMin(address, val);
#endif
}
};
};
}}} // namespace cv { namespace gpu { namespace device
/*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 bpied warranties, including, but not limited to, the bpied
// 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*/
#ifndef OPENCV_GPU_EMULATION_HPP_
#define OPENCV_GPU_EMULATION_HPP_
#include "warp_reduce.hpp"
#include <stdio.h>
namespace cv { namespace gpu { namespace device
{
struct Emulation
{
static __device__ __forceinline__ int sycthOr(int pred)
{
#if defined (__CUDA_ARCH__) && (__CUDA_ARCH__ < 120)
// just campilation stab
return false;
#else
return __syncthreads_or(pred);
#endif
}
template<int CTA_SIZE>
static __forceinline__ __device__ int Ballot(int predicate)
{
#if defined (__CUDA_ARCH__) && (__CUDA_ARCH__ >= 200)
return __ballot(predicate);
#else
__shared__ volatile int cta_buffer[CTA_SIZE];
int tid = threadIdx.x;
cta_buffer[tid] = predicate ? (1 << (tid & 31)) : 0;
return warp_reduce(cta_buffer);
#endif
}
struct smem
{
enum { TAG_MASK = (1U << ( (sizeof(unsigned int) << 3) - 5U)) - 1U };
template<typename T>
static __device__ __forceinline__ T atomicInc(T* address, T val)
{
#if defined (__CUDA_ARCH__) && (__CUDA_ARCH__ < 120)
T count;
unsigned int tag = threadIdx.x << ( (sizeof(unsigned int) << 3) - 5U);
do
{
count = *address & TAG_MASK;
count = tag | (count + 1);
*address = count;
} while (*address != count);
return (count & TAG_MASK) - 1;
#else
return ::atomicInc(address, val);
#endif
}
template<typename T>
static __device__ __forceinline__ void atomicAdd(T* address, T val)
{
#if defined (__CUDA_ARCH__) && (__CUDA_ARCH__ < 120)
T count;
unsigned int tag = threadIdx.x << ( (sizeof(unsigned int) << 3) - 5U);
do
{
count = *address & TAG_MASK;
count = tag | (count + val);
*address = count;
} while (*address != count);
#else
::atomicAdd(address, val);
#endif
}
template<typename T>
static __device__ __forceinline__ T atomicMin(T* address, T val)
{
#if defined (__CUDA_ARCH__) && (__CUDA_ARCH__ < 120)
T count = min(*address, val);
do
{
*address = count;
} while (*address > count);
return count;
#else
return ::atomicMin(address, val);
#endif
}
};
};
}}} // namespace cv { namespace gpu { namespace device
#endif /* OPENCV_GPU_EMULATION_HPP_ */

8
modules/gpu/test/test_labeling.cpp

@ -164,7 +164,7 @@ struct Labeling : testing::TestWithParam<cv::gpu::DeviceInfo>
cv::Mat loat_image()
{
return cv::imread(std::string( cvtest::TS::ptr()->get_data_path() ) + "labeling/label.png");
return cv::imread(std::string( cvtest::TS::ptr()->get_data_path() ) + "labeling/IMG_0727.JPG");
}
};
@ -173,6 +173,8 @@ TEST_P(Labeling, ConnectedComponents)
cv::Mat image;
cvtColor(loat_image(), image, CV_BGR2GRAY);
cv::threshold(image, image, 150, 255, CV_THRESH_BINARY);
ASSERT_TRUE(image.type() == CV_8UC1);
GreedyLabeling host(image);
@ -189,6 +191,10 @@ TEST_P(Labeling, ConnectedComponents)
ASSERT_NO_THROW(cv::gpu::labelComponents(mask, components));
host.checkCorrectness(cv::Mat(components));
cv::imshow("test", image);
cv::waitKey(0);
cv::imshow("test", host._labels);
cv::waitKey(0);
}
INSTANTIATE_TEST_CASE_P(ConnectedComponents, Labeling, ALL_DEVICES);