在CUDA平台上对图像算法进行并行加速是目前并行计算方面比较简单易行的一种方式，而同时利用OpenCV提供的一些库函数的话，那么事情将会变得更加easy。以下是我个人采用的一种模板，这个模板是从OpenCV里的算法CUDA源码挖掘出来的，我感觉这个用起来比较傲方便，所以经常采用。首先大牛们写的源码都很鲁棒，考虑的比较全面（如大部分算法将1,3,4通道的图像同时搞定），感觉还有一个比较神奇的地方在于CPU端GpuMat和GPU端PtrStepSzb的转换，让我欲罢不能，一个不太理想的地方在于第一帧的初始化时间比较长，应该是CPU到GPU的数据传输。代码中有考虑流，但貌似没有使用。
代码如下：
sample.cu
/********************************************************************* sample.cu* This is a example of the CUDA program.*********************************************************************/#include <stdio.h>#include <stdlib.h>#include <cutil_inline.h>#include <iostream>#include <string>#include "opencv2/core/core.hpp"#include "opencv2/gpu/gpu.hpp"#include "opencv2/highgui/highgui.hpp"#include "Vibe_M_kernel.cu"#include "Vibe_M.h"using namespace std;using namespace cv;using namespace cv::gpu;enum Method{FGD_STAT,MOG,MOG2,VIBE,GMG};int main(int argc, const char** argv){cv::CommandLineParser cmd(argc, argv,"{ c | camera | flase| use camera }""{ f | file | 768×576.avi | input video file }""{ m | method | vibe| method (fgd, mog, mog2, vibe, gmg) }""{ h | help | false| print help message }");if (cmd.get<bool>("help")){cout << "Usage : bgfg_segm [options]" << endl;cout << "Avaible options:" << endl;cmd.printParams();return 0;}bool useCamera = cmd.get<bool>("camera");string file = cmd.get<string>("file");string method = cmd.get<string>("method");if (method != "fgd" && method != "mog" && method != "mog2" && method != "vibe" && method != "gmg"){cerr << "Incorrect method" << endl;return -1;}Method m = method == "fgd" ? FGD_STAT : method == "mog" ? MOG : method == "mog2" ? MOG2 : method == "vibe" ? VIBE : GMG;VideoCapture cap;if (useCamera)cap.open(0);elsecap.open(file);if (!cap.isOpened()){cerr << "can not open camera or video file" << endl;return -1;}Mat origin, frame;cap >> origin;cvtColor(origin,frame,CV_BGR2GRAY);GpuMat d_frame(frame);Vibe_M vibe;GpuMat d_fgmask;Mat fgmask;Mat fgimg;Mat bgimg;switch (m){case VIBE:vibe.initialize(d_frame);break;}namedWindow("image", WINDOW_NORMAL);namedWindow("foreground mask", WINDOW_NORMAL);for(;;){cap >> origin;if (origin.empty())break;cvtColor(origin,frame,CV_BGR2GRAY);d_frame.upload(frame);//update the modelswitch (m){case VIBE:vibe(d_frame, d_fgmask);break;}d_fgmask.download(fgmask);imshow("image", frame);imshow("foreground mask", fgmask);int key = waitKey(30);if (key == 27)break;else if(key == ‘ ‘){cvWaitKey(0);}}exit(0);}Vibe_M.cpp#include "Vibe_M.h"namespace cv { namespace gpu { namespace device{namespace vibe_m{void loadConstants(int nbSamples, int reqMatches, int radius, int subsamplingFactor);void init_gpu(PtrStepSzb frame, int cn, PtrStepSzb samples, PtrStepSz<unsigned int> randStates, cudaStream_t stream);void update_gpu(PtrStepSzb frame, int cn, PtrStepSzb fgmask, PtrStepSzb samples, PtrStepSz<unsigned int> randStates, cudaStream_t stream);}}}}namespace{const int defaultNbSamples = 20;const int defaultReqMatches = 2;const int defaultRadius = 20;const int defaultSubsamplingFactor = 16;}Vibe_M::Vibe_M(unsigned long rngSeed) :frameSize_(0, 0), rngSeed_(rngSeed){nbSamples = defaultNbSamples;reqMatches = defaultReqMatches;radius = defaultRadius;subsamplingFactor = defaultSubsamplingFactor;}void Vibe_M::initialize(const GpuMat& firstFrame, Stream& s){using namespace cv::gpu::device::vibe_m;CV_Assert(firstFrame.type() == CV_8UC1 || firstFrame.type() == CV_8UC3 || firstFrame.type() == CV_8UC4);//cudaStream_t stream = StreamAccessor::getStream(s);loadConstants(nbSamples, reqMatches, radius, subsamplingFactor);frameSize_ = firstFrame.size();if (randStates_.size() != frameSize_){cv::RNG rng(rngSeed_);cv::Mat h_randStates(frameSize_, CV_8UC4);rng.fill(h_randStates, cv::RNG::UNIFORM, 0, 255);randStates_.upload(h_randStates);}int ch = firstFrame.channels();int sample_ch = ch == 1 ? 1 : 4;samples_.create(nbSamples * frameSize_.height, frameSize_.width, CV_8UC(sample_ch));init_gpu(firstFrame, ch, samples_, randStates_, 0);}void Vibe_M::operator()(const GpuMat& frame, GpuMat& fgmask, Stream& s){using namespace cv::gpu::device::vibe_m;CV_Assert(frame.depth() == CV_8U);int ch = frame.channels();int sample_ch = ch == 1 ? 1 : 4;if (frame.size() != frameSize_ || sample_ch != samples_.channels())initialize(frame);fgmask.create(frameSize_, CV_8UC1);update_gpu(frame, ch, fgmask, samples_, randStates_, StreamAccessor::getStream(s));}void Vibe_M::release(){frameSize_ = Size(0, 0);randStates_.release();samples_.release();}Vibe_M.h#ifndef _VIBE_M_H_#define _VIBE_M_H_#ifndef SKIP_INCLUDES#include <vector>#include <memory>#include <iosfwd>#endif#include "opencv2/core/core.hpp"#include "opencv2/core/gpumat.hpp"#include "opencv2/gpu/gpu.hpp"#include "opencv2/imgproc/imgproc.hpp"#include "opencv2/objdetect/objdetect.hpp"#include "opencv2/features2d/features2d.hpp"using namespace std;using namespace cv;using namespace cv::gpu;class Vibe_M{public://! the default constructorexplicit Vibe_M(unsigned long rngSeed = 1234567);//! re-initiaization methodvoid initialize(const GpuMat& firstFrame, Stream& stream = Stream::Null());//! the update operatorvoid operator()(const GpuMat& frame, GpuMat& fgmask, Stream& stream = Stream::Null());//! releases all inner buffersvoid release();int nbSamples;// number of samples per pixelint reqMatches;// #_minint radius;// Rint subsamplingFactor; // amount of random subsamplingprivate:Size frameSize_;unsigned long rngSeed_;GpuMat randStates_;GpuMat samples_;};#endifVibe_M.cu#include "Vibe_M.h"#include "opencv2/gpu/stream_accessor.hpp"namespace cv { namespace gpu { namespace device{namespace vibe_m{void loadConstants(int nbSamples, int reqMatches, int radius, int subsamplingFactor);void init_gpu(PtrStepSzb frame, int cn, PtrStepSzb samples, PtrStepSz<unsigned int> randStates, cudaStream_t stream);void update_gpu(PtrStepSzb frame, int cn, PtrStepSzb fgmask, PtrStepSzb samples, PtrStepSz<unsigned int> randStates, cudaStream_t stream);}}}}namespace{const int defaultNbSamples = 20;const int defaultReqMatches = 2;const int defaultRadius = 20;const int defaultSubsamplingFactor = 16;}Vibe_M::Vibe_M(unsigned long rngSeed) :frameSize_(0, 0), rngSeed_(rngSeed){nbSamples = defaultNbSamples;reqMatches = defaultReqMatches;radius = defaultRadius;subsamplingFactor = defaultSubsamplingFactor;}void Vibe_M::initialize(const GpuMat& firstFrame, Stream& s){using namespace cv::gpu::device::vibe_m;CV_Assert(firstFrame.type() == CV_8UC1 || firstFrame.type() == CV_8UC3 || firstFrame.type() == CV_8UC4);cudaStream_t stream = cv::gpu::StreamAccessor::getStream(s);loadConstants(nbSamples, reqMatches, radius, subsamplingFactor);frameSize_ = firstFrame.size();if (randStates_.size() != frameSize_){cv::RNG rng(rngSeed_);cv::Mat h_randStates(frameSize_, CV_8UC4);rng.fill(h_randStates, cv::RNG::UNIFORM, 0, 255);randStates_.upload(h_randStates);}int ch = firstFrame.channels();int sample_ch = ch == 1 ? 1 : 4;samples_.create(nbSamples * frameSize_.height, frameSize_.width, CV_8UC(sample_ch));init_gpu(firstFrame, ch, samples_, randStates_, stream);}void Vibe_M::operator()(const GpuMat& frame, GpuMat& fgmask, Stream& s){using namespace cv::gpu::device::vibe_m;CV_Assert(frame.depth() == CV_8U);int ch = frame.channels();int sample_ch = ch == 1 ? 1 : 4;if (frame.size() != frameSize_ || sample_ch != samples_.channels())initialize(frame);fgmask.create(frameSize_, CV_8UC1);update_gpu(frame, ch, fgmask, samples_, randStates_, cv::gpu::StreamAccessor::getStream(s));}void Vibe_M::release(){frameSize_ = Size(0, 0);randStates_.release();samples_.release();}Vibe_M_kernel.cu那段岁月，无论从何种角度读你，你都完美无缺，
