added VIBE_GPU (background subtraction) to gpu module
This commit is contained in:
Vladislav Vinogradov
@@ -48,11 +48,13 @@ cv::gpu::MOG_GPU::MOG_GPU(int) { throw_nogpu(); }
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void cv::gpu::MOG_GPU::initialize(cv::Size, int) { throw_nogpu(); }
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void cv::gpu::MOG_GPU::operator()(const cv::gpu::GpuMat&, cv::gpu::GpuMat&, float, Stream&) { throw_nogpu(); }
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void cv::gpu::MOG_GPU::getBackgroundImage(GpuMat&, Stream&) const { throw_nogpu(); }
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void cv::gpu::MOG_GPU::release() {}
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cv::gpu::MOG2_GPU::MOG2_GPU(int) { throw_nogpu(); }
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void cv::gpu::MOG2_GPU::initialize(cv::Size, int) { throw_nogpu(); }
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void cv::gpu::MOG2_GPU::operator()(const GpuMat&, GpuMat&, float, Stream&) { throw_nogpu(); }
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void cv::gpu::MOG2_GPU::getBackgroundImage(GpuMat&, Stream&) const { throw_nogpu(); }
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void cv::gpu::MOG2_GPU::release() {}
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#else
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@@ -151,6 +153,18 @@ void cv::gpu::MOG_GPU::getBackgroundImage(GpuMat& backgroundImage, Stream& strea
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getBackgroundImage_gpu(backgroundImage.channels(), weight_, mean_, backgroundImage, nmixtures_, backgroundRatio, StreamAccessor::getStream(stream));
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}
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void cv::gpu::MOG_GPU::release()
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{
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frameSize_ = Size(0, 0);
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frameType_ = 0;
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nframes_ = 0;
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weight_.release();
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sortKey_.release();
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mean_.release();
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var_.release();
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}
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/////////////////////////////////////////////////////////////////
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// MOG2
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@@ -250,4 +264,17 @@ void cv::gpu::MOG2_GPU::getBackgroundImage(GpuMat& backgroundImage, Stream& stre
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getBackgroundImage2_gpu(backgroundImage.channels(), bgmodelUsedModes_, weight_, mean_, backgroundImage, StreamAccessor::getStream(stream));
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}
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void cv::gpu::MOG2_GPU::release()
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{
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frameSize_ = Size(0, 0);
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frameType_ = 0;
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nframes_ = 0;
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weight_.release();
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variance_.release();
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mean_.release();
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bgmodelUsedModes_.release();
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}
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#endif
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137
modules/gpu/src/bgfg_vibe.cpp
Normal file
137
modules/gpu/src/bgfg_vibe.cpp
Normal file
@@ -0,0 +1,137 @@
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/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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||||
// If you do not agree to this license, do not download, install,
|
||||
// copy or use the software.
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||||
//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
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// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
|
||||
// this list of conditions and the following disclaimer.
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||||
//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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||||
// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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||||
// 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
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// and on any theory of liability, whether in contract, strict liability,
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||||
// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#include "precomp.hpp"
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#ifndef HAVE_CUDA
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cv::gpu::VIBE_GPU::VIBE_GPU(unsigned long) { throw_nogpu(); }
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void cv::gpu::VIBE_GPU::initialize(const GpuMat&, Stream&) { throw_nogpu(); }
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void cv::gpu::VIBE_GPU::operator()(const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
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void cv::gpu::VIBE_GPU::release() {}
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#else
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namespace cv { namespace gpu { namespace device
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{
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namespace vibe
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{
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void loadConstants(int nbSamples, int reqMatches, int radius, int subsamplingFactor);
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void init_gpu(DevMem2Db frame, int cn, DevMem2Db samples, DevMem2D_<unsigned int> randStates, cudaStream_t stream);
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void update_gpu(DevMem2Db frame, int cn, DevMem2Db fgmask, DevMem2Db samples, DevMem2D_<unsigned int> randStates, cudaStream_t stream);
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}
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}}}
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namespace
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{
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const int defaultNbSamples = 20;
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const int defaultReqMatches = 2;
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const int defaultRadius = 20;
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const int defaultSubsamplingFactor = 16;
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}
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cv::gpu::VIBE_GPU::VIBE_GPU(unsigned long rngSeed) :
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frameSize_(0, 0), rngSeed_(rngSeed)
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{
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nbSamples = defaultNbSamples;
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reqMatches = defaultReqMatches;
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radius = defaultRadius;
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subsamplingFactor = defaultSubsamplingFactor;
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}
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void cv::gpu::VIBE_GPU::initialize(const GpuMat& firstFrame, Stream& s)
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{
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using namespace cv::gpu::device::vibe;
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CV_Assert(firstFrame.type() == CV_8UC1 || firstFrame.type() == CV_8UC3 || firstFrame.type() == CV_8UC4);
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cudaStream_t stream = StreamAccessor::getStream(s);
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loadConstants(nbSamples, reqMatches, radius, subsamplingFactor);
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frameSize_ = firstFrame.size();
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if (randStates_.size() != frameSize_)
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{
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cv::RNG rng(rngSeed_);
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cv::Mat h_randStates(frameSize_, CV_8UC4);
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rng.fill(h_randStates, cv::RNG::UNIFORM, 0, 255);
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randStates_.upload(h_randStates);
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}
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int ch = firstFrame.channels();
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int sample_ch = ch == 1 ? 1 : 4;
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samples_.create(nbSamples * frameSize_.height, frameSize_.width, CV_8UC(sample_ch));
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init_gpu(firstFrame, ch, samples_, randStates_, stream);
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}
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void cv::gpu::VIBE_GPU::operator()(const GpuMat& frame, GpuMat& fgmask, Stream& s)
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{
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using namespace cv::gpu::device::vibe;
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CV_Assert(frame.depth() == CV_8U);
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int ch = frame.channels();
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int sample_ch = ch == 1 ? 1 : 4;
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if (frame.size() != frameSize_ || sample_ch != samples_.channels())
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initialize(frame);
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fgmask.create(frameSize_, CV_8UC1);
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update_gpu(frame, ch, fgmask, samples_, randStates_, StreamAccessor::getStream(s));
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}
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void cv::gpu::VIBE_GPU::release()
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{
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frameSize_ = Size(0, 0);
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randStates_.release();
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samples_.release();
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}
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#endif
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@@ -40,7 +40,6 @@
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//
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//M*/
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#include <stdio.h>
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#include "opencv2/gpu/device/common.hpp"
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#include "opencv2/gpu/device/vec_traits.hpp"
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#include "opencv2/gpu/device/vec_math.hpp"
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253
modules/gpu/src/cuda/bgfg_vibe.cu
Normal file
253
modules/gpu/src/cuda/bgfg_vibe.cu
Normal file
@@ -0,0 +1,253 @@
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/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// 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.
|
||||
//
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//M*/
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#include "opencv2/gpu/device/common.hpp"
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namespace cv { namespace gpu { namespace device
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{
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namespace vibe
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{
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__constant__ int c_nbSamples;
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__constant__ int c_reqMatches;
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__constant__ int c_radius;
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__constant__ int c_subsamplingFactor;
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void loadConstants(int nbSamples, int reqMatches, int radius, int subsamplingFactor)
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{
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cudaSafeCall( cudaMemcpyToSymbol(c_nbSamples, &nbSamples, sizeof(int)) );
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cudaSafeCall( cudaMemcpyToSymbol(c_reqMatches, &reqMatches, sizeof(int)) );
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cudaSafeCall( cudaMemcpyToSymbol(c_radius, &radius, sizeof(int)) );
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cudaSafeCall( cudaMemcpyToSymbol(c_subsamplingFactor, &subsamplingFactor, sizeof(int)) );
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}
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__device__ __forceinline__ uint nextRand(uint& state)
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{
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const unsigned int CV_RNG_COEFF = 4164903690U;
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state = state * CV_RNG_COEFF + (state >> 16);
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return state;
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}
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__constant__ int c_xoff[9] = {-1, 0, 1, -1, 1, -1, 0, 1, 0};
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__constant__ int c_yoff[9] = {-1, -1, -1, 0, 0, 1, 1, 1, 0};
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__device__ __forceinline__ int2 chooseRandomNeighbor(int x, int y, uint& randState, int count = 8)
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{
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int idx = nextRand(randState) % count;
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return make_int2(x + c_xoff[idx], y + c_yoff[idx]);
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}
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__device__ __forceinline__ uchar cvt(uchar val)
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{
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return val;
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}
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__device__ __forceinline__ uchar4 cvt(const uchar3& val)
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{
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return make_uchar4(val.x, val.y, val.z, 0);
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}
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__device__ __forceinline__ uchar4 cvt(const uchar4& val)
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{
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return val;
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}
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template <typename SrcT, typename SampleT>
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__global__ void init(const DevMem2D_<SrcT> frame, PtrStep_<SampleT> samples, PtrStep_<uint> randStates)
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{
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const int x = blockIdx.x * blockDim.x + threadIdx.x;
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const int y = blockIdx.y * blockDim.y + threadIdx.y;
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if (x >= frame.cols || y >= frame.rows)
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return;
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uint localState = randStates(y, x);
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for (int k = 0; k < c_nbSamples; ++k)
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{
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int2 np = chooseRandomNeighbor(x, y, localState, 9);
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np.x = ::max(0, ::min(np.x, frame.cols - 1));
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np.y = ::max(0, ::min(np.y, frame.rows - 1));
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SrcT pix = frame(np.y, np.x);
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samples(k * frame.rows + y, x) = cvt(pix);
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}
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randStates(y, x) = localState;
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}
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template <typename SrcT, typename SampleT>
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void init_caller(DevMem2Db frame, DevMem2Db samples, DevMem2D_<uint> randStates, cudaStream_t stream)
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{
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dim3 block(32, 8);
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dim3 grid(divUp(frame.cols, block.x), divUp(frame.rows, block.y));
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cudaSafeCall( cudaFuncSetCacheConfig(init<SrcT, SampleT>, cudaFuncCachePreferL1) );
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init<SrcT, SampleT><<<grid, block, 0, stream>>>((DevMem2D_<SrcT>) frame, (DevMem2D_<SampleT>) samples, randStates);
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cudaSafeCall( cudaGetLastError() );
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if (stream == 0)
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cudaSafeCall( cudaDeviceSynchronize() );
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}
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void init_gpu(DevMem2Db frame, int cn, DevMem2Db samples, DevMem2D_<uint> randStates, cudaStream_t stream)
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{
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typedef void (*func_t)(DevMem2Db frame, DevMem2Db samples, DevMem2D_<uint> randStates, cudaStream_t stream);
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static const func_t funcs[] =
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{
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0, init_caller<uchar, uchar>, 0, init_caller<uchar3, uchar4>, init_caller<uchar4, uchar4>
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};
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funcs[cn](frame, samples, randStates, stream);
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}
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__device__ __forceinline__ int calcDist(uchar a, uchar b)
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{
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return ::abs(a - b);
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}
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__device__ __forceinline__ int calcDist(const uchar3& a, const uchar4& b)
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{
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return (::abs(a.x - b.x) + ::abs(a.y - b.y) + ::abs(a.z - b.z)) / 3;
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}
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__device__ __forceinline__ int calcDist(const uchar4& a, const uchar4& b)
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{
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return (::abs(a.x - b.x) + ::abs(a.y - b.y) + ::abs(a.z - b.z)) / 3;
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}
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template <typename SrcT, typename SampleT>
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__global__ void update(const DevMem2D_<SrcT> frame, PtrStepb fgmask, PtrStep_<SampleT> samples, PtrStep_<uint> randStates)
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{
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const int x = blockIdx.x * blockDim.x + threadIdx.x;
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const int y = blockIdx.y * blockDim.y + threadIdx.y;
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if (x >= frame.cols || y >= frame.rows)
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return;
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uint localState = randStates(y, x);
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SrcT imgPix = frame(y, x);
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// comparison with the model
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int count = 0;
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for (int k = 0; (count < c_reqMatches) && (k < c_nbSamples); ++k)
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{
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SampleT samplePix = samples(k * frame.rows + y, x);
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int distance = calcDist(imgPix, samplePix);
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if (distance < c_radius)
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++count;
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}
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// pixel classification according to reqMatches
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fgmask(y, x) = (uchar) (-(count < c_reqMatches));
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if (count >= c_reqMatches)
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{
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// the pixel belongs to the background
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// gets a random number between 0 and subsamplingFactor-1
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int randomNumber = nextRand(localState) % c_subsamplingFactor;
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// update of the current pixel model
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if (randomNumber == 0)
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{
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// random subsampling
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int k = nextRand(localState) % c_nbSamples;
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samples(k * frame.rows + y, x) = cvt(imgPix);
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}
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// update of a neighboring pixel model
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randomNumber = nextRand(localState) % c_subsamplingFactor;
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if (randomNumber == 0)
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{
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// random subsampling
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// chooses a neighboring pixel randomly
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int2 np = chooseRandomNeighbor(x, y, localState);
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np.x = ::max(0, ::min(np.x, frame.cols - 1));
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np.y = ::max(0, ::min(np.y, frame.rows - 1));
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// chooses the value to be replaced randomly
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int k = nextRand(localState) % c_nbSamples;
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samples(k * frame.rows + np.y, np.x) = cvt(imgPix);
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}
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}
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randStates(y, x) = localState;
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}
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template <typename SrcT, typename SampleT>
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void update_caller(DevMem2Db frame, DevMem2Db fgmask, DevMem2Db samples, DevMem2D_<uint> randStates, cudaStream_t stream)
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{
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dim3 block(32, 8);
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dim3 grid(divUp(frame.cols, block.x), divUp(frame.rows, block.y));
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cudaSafeCall( cudaFuncSetCacheConfig(update<SrcT, SampleT>, cudaFuncCachePreferL1) );
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update<SrcT, SampleT><<<grid, block, 0, stream>>>((DevMem2D_<SrcT>) frame, fgmask, (DevMem2D_<SampleT>) samples, randStates);
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cudaSafeCall( cudaGetLastError() );
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if (stream == 0)
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cudaSafeCall( cudaDeviceSynchronize() );
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}
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void update_gpu(DevMem2Db frame, int cn, DevMem2Db fgmask, DevMem2Db samples, DevMem2D_<uint> randStates, cudaStream_t stream)
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{
|
||||
typedef void (*func_t)(DevMem2Db frame, DevMem2Db fgmask, DevMem2Db samples, DevMem2D_<uint> randStates, cudaStream_t stream);
|
||||
static const func_t funcs[] =
|
||||
{
|
||||
0, update_caller<uchar, uchar>, 0, update_caller<uchar3, uchar4>, update_caller<uchar4, uchar4>
|
||||
};
|
||||
|
||||
funcs[cn](frame, fgmask, samples, randStates, stream);
|
||||
}
|
||||
}
|
||||
}}}
|
||||
Reference in New Issue
Block a user