499 lines
14 KiB
C++
499 lines
14 KiB
C++
|
// This sample demonstrates working on one piece of data using two GPUs.
|
||
|
|
// It splits input into two parts and processes them separately on different GPUs.
|
||
|
|
|
||
|
|
#ifdef _WIN32
|
||
|
|
#define NOMINMAX
|
||
|
|
#include <windows.h>
|
||
|
|
#else
|
||
|
|
#include <pthread.h>
|
||
|
|
#include <unistd.h>
|
||
|
|
#endif
|
||
|
|
|
||
|
|
#include <iostream>
|
||
|
|
#include <iomanip>
|
||
|
|
|
||
|
|
#include "opencv2/core.hpp"
|
||
|
|
#include "opencv2/highgui.hpp"
|
||
|
|
#include "opencv2/imgproc.hpp"
|
||
|
|
#include "opencv2/cudastereo.hpp"
|
||
|
|
|
||
|
|
using namespace std;
|
||
|
|
using namespace cv;
|
||
|
|
using namespace cv::cuda;
|
||
|
|
|
||
|
|
///////////////////////////////////////////////////////////
|
||
|
|
// Thread
|
||
|
|
// OS-specific wrappers for multi-threading
|
||
|
|
|
||
|
|
#ifdef _WIN32
|
||
|
|
class Thread
|
||
|
|
{
|
||
|
|
struct UserData
|
||
|
|
{
|
||
|
|
void (*func)(void* userData);
|
||
|
|
void* param;
|
||
|
|
};
|
||
|
|
|
||
|
|
static DWORD WINAPI WinThreadFunction(LPVOID lpParam)
|
||
|
|
{
|
||
|
|
UserData* userData = static_cast<UserData*>(lpParam);
|
||
|
|
|
||
|
|
userData->func(userData->param);
|
||
|
|
|
||
|
|
return 0;
|
||
|
|
}
|
||
|
|
|
||
|
|
UserData userData_;
|
||
|
|
HANDLE thread_;
|
||
|
|
DWORD threadId_;
|
||
|
|
|
||
|
|
public:
|
||
|
|
Thread(void (*func)(void* userData), void* userData)
|
||
|
|
{
|
||
|
|
userData_.func = func;
|
||
|
|
userData_.param = userData;
|
||
|
|
|
||
|
|
thread_ = CreateThread(
|
||
|
|
NULL, // default security attributes
|
||
|
|
0, // use default stack size
|
||
|
|
WinThreadFunction, // thread function name
|
||
|
|
&userData_, // argument to thread function
|
||
|
|
0, // use default creation flags
|
||
|
|
&threadId_); // returns the thread identifier
|
||
|
|
}
|
||
|
|
|
||
|
|
~Thread()
|
||
|
|
{
|
||
|
|
CloseHandle(thread_);
|
||
|
|
}
|
||
|
|
|
||
|
|
void wait()
|
||
|
|
{
|
||
|
|
WaitForSingleObject(thread_, INFINITE);
|
||
|
|
}
|
||
|
|
};
|
||
|
|
#else
|
||
|
|
class Thread
|
||
|
|
{
|
||
|
|
struct UserData
|
||
|
|
{
|
||
|
|
void (*func)(void* userData);
|
||
|
|
void* param;
|
||
|
|
};
|
||
|
|
|
||
|
|
static void* PThreadFunction(void* lpParam)
|
||
|
|
{
|
||
|
|
UserData* userData = static_cast<UserData*>(lpParam);
|
||
|
|
|
||
|
|
userData->func(userData->param);
|
||
|
|
|
||
|
|
return 0;
|
||
|
|
}
|
||
|
|
|
||
|
|
pthread_t thread_;
|
||
|
|
UserData userData_;
|
||
|
|
|
||
|
|
public:
|
||
|
|
Thread(void (*func)(void* userData), void* userData)
|
||
|
|
{
|
||
|
|
userData_.func = func;
|
||
|
|
userData_.param = userData;
|
||
|
|
|
||
|
|
pthread_create(&thread_, NULL, PThreadFunction, &userData_);
|
||
|
|
}
|
||
|
|
|
||
|
|
~Thread()
|
||
|
|
{
|
||
|
|
pthread_detach(thread_);
|
||
|
|
}
|
||
|
|
|
||
|
|
void wait()
|
||
|
|
{
|
||
|
|
pthread_join(thread_, NULL);
|
||
|
|
}
|
||
|
|
};
|
||
|
|
#endif
|
||
|
|
|
||
|
|
///////////////////////////////////////////////////////////
|
||
|
|
// StereoSingleGpu
|
||
|
|
// Run Stereo algorithm on single GPU
|
||
|
|
|
||
|
|
class StereoSingleGpu
|
||
|
|
{
|
||
|
|
public:
|
||
|
|
explicit StereoSingleGpu(int deviceId = 0);
|
||
|
|
~StereoSingleGpu();
|
||
|
|
|
||
|
|
void compute(const Mat& leftFrame, const Mat& rightFrame, Mat& disparity);
|
||
|
|
|
||
|
|
private:
|
||
|
|
int deviceId_;
|
||
|
|
GpuMat d_leftFrame;
|
||
|
|
GpuMat d_rightFrame;
|
||
|
|
GpuMat d_disparity;
|
||
|
|
Ptr<cuda::StereoBM> d_alg;
|
||
|
|
};
|
||
|
|
|
||
|
|
StereoSingleGpu::StereoSingleGpu(int deviceId) : deviceId_(deviceId)
|
||
|
|
{
|
||
|
|
cuda::setDevice(deviceId_);
|
||
|
|
d_alg = cuda::createStereoBM(256);
|
||
|
|
}
|
||
|
|
|
||
|
|
StereoSingleGpu::~StereoSingleGpu()
|
||
|
|
{
|
||
|
|
cuda::setDevice(deviceId_);
|
||
|
|
d_leftFrame.release();
|
||
|
|
d_rightFrame.release();
|
||
|
|
d_disparity.release();
|
||
|
|
d_alg.release();
|
||
|
|
}
|
||
|
|
|
||
|
|
void StereoSingleGpu::compute(const Mat& leftFrame, const Mat& rightFrame, Mat& disparity)
|
||
|
|
{
|
||
|
|
cuda::setDevice(deviceId_);
|
||
|
|
d_leftFrame.upload(leftFrame);
|
||
|
|
d_rightFrame.upload(rightFrame);
|
||
|
|
d_alg->compute(d_leftFrame, d_rightFrame, d_disparity);
|
||
|
|
d_disparity.download(disparity);
|
||
|
|
}
|
||
|
|
|
||
|
|
///////////////////////////////////////////////////////////
|
||
|
|
// StereoMultiGpuThread
|
||
|
|
// Run Stereo algorithm on two GPUs using different host threads
|
||
|
|
|
||
|
|
class StereoMultiGpuThread
|
||
|
|
{
|
||
|
|
public:
|
||
|
|
StereoMultiGpuThread();
|
||
|
|
~StereoMultiGpuThread();
|
||
|
|
|
||
|
|
void compute(const Mat& leftFrame, const Mat& rightFrame, Mat& disparity);
|
||
|
|
|
||
|
|
private:
|
||
|
|
GpuMat d_leftFrames[2];
|
||
|
|
GpuMat d_rightFrames[2];
|
||
|
|
GpuMat d_disparities[2];
|
||
|
|
Ptr<cuda::StereoBM> d_algs[2];
|
||
|
|
|
||
|
|
struct StereoLaunchData
|
||
|
|
{
|
||
|
|
int deviceId;
|
||
|
|
Mat leftFrame;
|
||
|
|
Mat rightFrame;
|
||
|
|
Mat disparity;
|
||
|
|
GpuMat* d_leftFrame;
|
||
|
|
GpuMat* d_rightFrame;
|
||
|
|
GpuMat* d_disparity;
|
||
|
|
Ptr<cuda::StereoBM> d_alg;
|
||
|
|
};
|
||
|
|
|
||
|
|
static void launchGpuStereoAlg(void* userData);
|
||
|
|
};
|
||
|
|
|
||
|
|
StereoMultiGpuThread::StereoMultiGpuThread()
|
||
|
|
{
|
||
|
|
cuda::setDevice(0);
|
||
|
|
d_algs[0] = cuda::createStereoBM(256);
|
||
|
|
|
||
|
|
cuda::setDevice(1);
|
||
|
|
d_algs[1] = cuda::createStereoBM(256);
|
||
|
|
}
|
||
|
|
|
||
|
|
StereoMultiGpuThread::~StereoMultiGpuThread()
|
||
|
|
{
|
||
|
|
cuda::setDevice(0);
|
||
|
|
d_leftFrames[0].release();
|
||
|
|
d_rightFrames[0].release();
|
||
|
|
d_disparities[0].release();
|
||
|
|
d_algs[0].release();
|
||
|
|
|
||
|
|
cuda::setDevice(1);
|
||
|
|
d_leftFrames[1].release();
|
||
|
|
d_rightFrames[1].release();
|
||
|
|
d_disparities[1].release();
|
||
|
|
d_algs[1].release();
|
||
|
|
}
|
||
|
|
|
||
|
|
void StereoMultiGpuThread::compute(const Mat& leftFrame, const Mat& rightFrame, Mat& disparity)
|
||
|
|
{
|
||
|
|
disparity.create(leftFrame.size(), CV_8UC1);
|
||
|
|
|
||
|
|
// Split input data onto two parts for each GPUs.
|
||
|
|
// We add small border for each part,
|
||
|
|
// because original algorithm doesn't calculate disparity on image borders.
|
||
|
|
// With such padding we will get output in the middle of final result.
|
||
|
|
|
||
|
|
StereoLaunchData launchDatas[2];
|
||
|
|
|
||
|
|
launchDatas[0].deviceId = 0;
|
||
|
|
launchDatas[0].leftFrame = leftFrame.rowRange(0, leftFrame.rows / 2 + 32);
|
||
|
|
launchDatas[0].rightFrame = rightFrame.rowRange(0, rightFrame.rows / 2 + 32);
|
||
|
|
launchDatas[0].disparity = disparity.rowRange(0, leftFrame.rows / 2);
|
||
|
|
launchDatas[0].d_leftFrame = &d_leftFrames[0];
|
||
|
|
launchDatas[0].d_rightFrame = &d_rightFrames[0];
|
||
|
|
launchDatas[0].d_disparity = &d_disparities[0];
|
||
|
|
launchDatas[0].d_alg = d_algs[0];
|
||
|
|
|
||
|
|
launchDatas[1].deviceId = 1;
|
||
|
|
launchDatas[1].leftFrame = leftFrame.rowRange(leftFrame.rows / 2 - 32, leftFrame.rows);
|
||
|
|
launchDatas[1].rightFrame = rightFrame.rowRange(leftFrame.rows / 2 - 32, leftFrame.rows);
|
||
|
|
launchDatas[1].disparity = disparity.rowRange(leftFrame.rows / 2, leftFrame.rows);
|
||
|
|
launchDatas[1].d_leftFrame = &d_leftFrames[1];
|
||
|
|
launchDatas[1].d_rightFrame = &d_rightFrames[1];
|
||
|
|
launchDatas[1].d_disparity = &d_disparities[1];
|
||
|
|
launchDatas[1].d_alg = d_algs[1];
|
||
|
|
|
||
|
|
Thread thread0(launchGpuStereoAlg, &launchDatas[0]);
|
||
|
|
Thread thread1(launchGpuStereoAlg, &launchDatas[1]);
|
||
|
|
|
||
|
|
thread0.wait();
|
||
|
|
thread1.wait();
|
||
|
|
}
|
||
|
|
|
||
|
|
void StereoMultiGpuThread::launchGpuStereoAlg(void* userData)
|
||
|
|
{
|
||
|
|
StereoLaunchData* data = static_cast<StereoLaunchData*>(userData);
|
||
|
|
|
||
|
|
cuda::setDevice(data->deviceId);
|
||
|
|
data->d_leftFrame->upload(data->leftFrame);
|
||
|
|
data->d_rightFrame->upload(data->rightFrame);
|
||
|
|
data->d_alg->compute(*data->d_leftFrame, *data->d_rightFrame, *data->d_disparity);
|
||
|
|
|
||
|
|
if (data->deviceId == 0)
|
||
|
|
data->d_disparity->rowRange(0, data->d_disparity->rows - 32).download(data->disparity);
|
||
|
|
else
|
||
|
|
data->d_disparity->rowRange(32, data->d_disparity->rows).download(data->disparity);
|
||
|
|
}
|
||
|
|
|
||
|
|
///////////////////////////////////////////////////////////
|
||
|
|
// StereoMultiGpuStream
|
||
|
|
// Run Stereo algorithm on two GPUs from single host thread using async API
|
||
|
|
|
||
|
|
class StereoMultiGpuStream
|
||
|
|
{
|
||
|
|
public:
|
||
|
|
StereoMultiGpuStream();
|
||
|
|
~StereoMultiGpuStream();
|
||
|
|
|
||
|
|
void compute(const HostMem& leftFrame, const HostMem& rightFrame, HostMem& disparity);
|
||
|
|
|
||
|
|
private:
|
||
|
|
GpuMat d_leftFrames[2];
|
||
|
|
GpuMat d_rightFrames[2];
|
||
|
|
GpuMat d_disparities[2];
|
||
|
|
Ptr<cuda::StereoBM> d_algs[2];
|
||
|
|
Ptr<Stream> streams[2];
|
||
|
|
};
|
||
|
|
|
||
|
|
StereoMultiGpuStream::StereoMultiGpuStream()
|
||
|
|
{
|
||
|
|
cuda::setDevice(0);
|
||
|
|
d_algs[0] = cuda::createStereoBM(256);
|
||
|
|
streams[0] = makePtr<Stream>();
|
||
|
|
|
||
|
|
cuda::setDevice(1);
|
||
|
|
d_algs[1] = cuda::createStereoBM(256);
|
||
|
|
streams[1] = makePtr<Stream>();
|
||
|
|
}
|
||
|
|
|
||
|
|
StereoMultiGpuStream::~StereoMultiGpuStream()
|
||
|
|
{
|
||
|
|
cuda::setDevice(0);
|
||
|
|
d_leftFrames[0].release();
|
||
|
|
d_rightFrames[0].release();
|
||
|
|
d_disparities[0].release();
|
||
|
|
d_algs[0].release();
|
||
|
|
streams[0].release();
|
||
|
|
|
||
|
|
cuda::setDevice(1);
|
||
|
|
d_leftFrames[1].release();
|
||
|
|
d_rightFrames[1].release();
|
||
|
|
d_disparities[1].release();
|
||
|
|
d_algs[1].release();
|
||
|
|
streams[1].release();
|
||
|
|
}
|
||
|
|
|
||
|
|
void StereoMultiGpuStream::compute(const HostMem& leftFrame, const HostMem& rightFrame, HostMem& disparity)
|
||
|
|
{
|
||
|
|
disparity.create(leftFrame.size(), CV_8UC1);
|
||
|
|
|
||
|
|
// Split input data onto two parts for each GPUs.
|
||
|
|
// We add small border for each part,
|
||
|
|
// because original algorithm doesn't calculate disparity on image borders.
|
||
|
|
// With such padding we will get output in the middle of final result.
|
||
|
|
|
||
|
|
Mat leftFrameHdr = leftFrame.createMatHeader();
|
||
|
|
Mat rightFrameHdr = rightFrame.createMatHeader();
|
||
|
|
Mat disparityHdr = disparity.createMatHeader();
|
||
|
|
Mat disparityPart0 = disparityHdr.rowRange(0, leftFrame.rows / 2);
|
||
|
|
Mat disparityPart1 = disparityHdr.rowRange(leftFrame.rows / 2, leftFrame.rows);
|
||
|
|
|
||
|
|
cuda::setDevice(0);
|
||
|
|
d_leftFrames[0].upload(leftFrameHdr.rowRange(0, leftFrame.rows / 2 + 32), *streams[0]);
|
||
|
|
d_rightFrames[0].upload(rightFrameHdr.rowRange(0, leftFrame.rows / 2 + 32), *streams[0]);
|
||
|
|
d_algs[0]->compute(d_leftFrames[0], d_rightFrames[0], d_disparities[0], *streams[0]);
|
||
|
|
d_disparities[0].rowRange(0, leftFrame.rows / 2).download(disparityPart0, *streams[0]);
|
||
|
|
|
||
|
|
cuda::setDevice(1);
|
||
|
|
d_leftFrames[1].upload(leftFrameHdr.rowRange(leftFrame.rows / 2 - 32, leftFrame.rows), *streams[1]);
|
||
|
|
d_rightFrames[1].upload(rightFrameHdr.rowRange(leftFrame.rows / 2 - 32, leftFrame.rows), *streams[1]);
|
||
|
|
d_algs[1]->compute(d_leftFrames[1], d_rightFrames[1], d_disparities[1], *streams[1]);
|
||
|
|
d_disparities[1].rowRange(32, d_disparities[1].rows).download(disparityPart1, *streams[1]);
|
||
|
|
|
||
|
|
cuda::setDevice(0);
|
||
|
|
streams[0]->waitForCompletion();
|
||
|
|
|
||
|
|
cuda::setDevice(1);
|
||
|
|
streams[1]->waitForCompletion();
|
||
|
|
}
|
||
|
|
|
||
|
|
///////////////////////////////////////////////////////////
|
||
|
|
// main
|
||
|
|
|
||
|
|
int main(int argc, char** argv)
|
||
|
|
{
|
||
|
|
if (argc != 3)
|
||
|
|
{
|
||
|
|
cerr << "Usage: stereo_multi <left_video> <right_video>" << endl;
|
||
|
|
return -1;
|
||
|
|
}
|
||
|
|
|
||
|
|
const int numDevices = getCudaEnabledDeviceCount();
|
||
|
|
if (numDevices != 2)
|
||
|
|
{
|
||
|
|
cerr << "Two GPUs are required" << endl;
|
||
|
|
return -1;
|
||
|
|
}
|
||
|
|
|
||
|
|
for (int i = 0; i < numDevices; ++i)
|
||
|
|
{
|
||
|
|
DeviceInfo devInfo(i);
|
||
|
|
if (!devInfo.isCompatible())
|
||
|
|
{
|
||
|
|
cerr << "CUDA module wasn't built for GPU #" << i << " ("
|
||
|
|
<< devInfo.name() << ", CC " << devInfo.majorVersion()
|
||
|
|
<< devInfo.minorVersion() << endl;
|
||
|
|
return -1;
|
||
|
|
}
|
||
|
|
|
||
|
|
printShortCudaDeviceInfo(i);
|
||
|
|
}
|
||
|
|
|
||
|
|
VideoCapture leftVideo(argv[1]);
|
||
|
|
VideoCapture rightVideo(argv[2]);
|
||
|
|
|
||
|
|
if (!leftVideo.isOpened())
|
||
|
|
{
|
||
|
|
cerr << "Can't open " << argv[1] << " video file" << endl;
|
||
|
|
return -1;
|
||
|
|
}
|
||
|
|
|
||
|
|
if (!rightVideo.isOpened())
|
||
|
|
{
|
||
|
|
cerr << "Can't open " << argv[2] << " video file" << endl;
|
||
|
|
return -1;
|
||
|
|
}
|
||
|
|
|
||
|
|
cout << endl;
|
||
|
|
cout << "This sample demonstrates working on one piece of data using two GPUs." << endl;
|
||
|
|
cout << "It splits input into two parts and processes them separately on different GPUs." << endl;
|
||
|
|
cout << endl;
|
||
|
|
|
||
|
|
Mat leftFrame, rightFrame;
|
||
|
|
HostMem leftGrayFrame, rightGrayFrame;
|
||
|
|
|
||
|
|
StereoSingleGpu gpu0Alg(0);
|
||
|
|
StereoSingleGpu gpu1Alg(1);
|
||
|
|
StereoMultiGpuThread multiThreadAlg;
|
||
|
|
StereoMultiGpuStream multiStreamAlg;
|
||
|
|
|
||
|
|
Mat disparityGpu0;
|
||
|
|
Mat disparityGpu1;
|
||
|
|
Mat disparityMultiThread;
|
||
|
|
HostMem disparityMultiStream;
|
||
|
|
|
||
|
|
Mat disparityGpu0Show;
|
||
|
|
Mat disparityGpu1Show;
|
||
|
|
Mat disparityMultiThreadShow;
|
||
|
|
Mat disparityMultiStreamShow;
|
||
|
|
|
||
|
|
TickMeter tm;
|
||
|
|
|
||
|
|
cout << "-------------------------------------------------------------------" << endl;
|
||
|
|
cout << "| Frame | GPU 0 ms | GPU 1 ms | Multi Thread ms | Multi Stream ms |" << endl;
|
||
|
|
cout << "-------------------------------------------------------------------" << endl;
|
||
|
|
|
||
|
|
for (int i = 0;; ++i)
|
||
|
|
{
|
||
|
|
leftVideo >> leftFrame;
|
||
|
|
rightVideo >> rightFrame;
|
||
|
|
|
||
|
|
if (leftFrame.empty() || rightFrame.empty())
|
||
|
|
break;
|
||
|
|
|
||
|
|
if (leftFrame.size() != rightFrame.size())
|
||
|
|
{
|
||
|
|
cerr << "Frames have different sizes" << endl;
|
||
|
|
return -1;
|
||
|
|
}
|
||
|
|
|
||
|
|
leftGrayFrame.create(leftFrame.size(), CV_8UC1);
|
||
|
|
rightGrayFrame.create(leftFrame.size(), CV_8UC1);
|
||
|
|
|
||
|
|
cvtColor(leftFrame, leftGrayFrame.createMatHeader(), COLOR_BGR2GRAY);
|
||
|
|
cvtColor(rightFrame, rightGrayFrame.createMatHeader(), COLOR_BGR2GRAY);
|
||
|
|
|
||
|
|
tm.reset(); tm.start();
|
||
|
|
gpu0Alg.compute(leftGrayFrame.createMatHeader(), rightGrayFrame.createMatHeader(),
|
||
|
|
disparityGpu0);
|
||
|
|
tm.stop();
|
||
|
|
|
||
|
|
const double gpu0Time = tm.getTimeMilli();
|
||
|
|
|
||
|
|
tm.reset(); tm.start();
|
||
|
|
gpu1Alg.compute(leftGrayFrame.createMatHeader(), rightGrayFrame.createMatHeader(),
|
||
|
|
disparityGpu1);
|
||
|
|
tm.stop();
|
||
|
|
|
||
|
|
const double gpu1Time = tm.getTimeMilli();
|
||
|
|
|
||
|
|
tm.reset(); tm.start();
|
||
|
|
multiThreadAlg.compute(leftGrayFrame.createMatHeader(), rightGrayFrame.createMatHeader(),
|
||
|
|
disparityMultiThread);
|
||
|
|
tm.stop();
|
||
|
|
|
||
|
|
const double multiThreadTime = tm.getTimeMilli();
|
||
|
|
|
||
|
|
tm.reset(); tm.start();
|
||
|
|
multiStreamAlg.compute(leftGrayFrame, rightGrayFrame, disparityMultiStream);
|
||
|
|
tm.stop();
|
||
|
|
|
||
|
|
const double multiStreamTime = tm.getTimeMilli();
|
||
|
|
|
||
|
|
cout << "| " << setw(5) << i << " | "
|
||
|
|
<< setw(8) << setprecision(1) << fixed << gpu0Time << " | "
|
||
|
|
<< setw(8) << setprecision(1) << fixed << gpu1Time << " | "
|
||
|
|
<< setw(15) << setprecision(1) << fixed << multiThreadTime << " | "
|
||
|
|
<< setw(15) << setprecision(1) << fixed << multiStreamTime << " |" << endl;
|
||
|
|
|
||
|
|
resize(disparityGpu0, disparityGpu0Show, Size(1024, 768), 0, 0, INTER_AREA);
|
||
|
|
resize(disparityGpu1, disparityGpu1Show, Size(1024, 768), 0, 0, INTER_AREA);
|
||
|
|
resize(disparityMultiThread, disparityMultiThreadShow, Size(1024, 768), 0, 0, INTER_AREA);
|
||
|
|
resize(disparityMultiStream.createMatHeader(), disparityMultiStreamShow, Size(1024, 768), 0, 0, INTER_AREA);
|
||
|
|
|
||
|
|
imshow("disparityGpu0", disparityGpu0Show);
|
||
|
|
imshow("disparityGpu1", disparityGpu1Show);
|
||
|
|
imshow("disparityMultiThread", disparityMultiThreadShow);
|
||
|
|
imshow("disparityMultiStream", disparityMultiStreamShow);
|
||
|
|
|
||
|
|
const int key = waitKey(30) & 0xff;
|
||
|
|
if (key == 27)
|
||
|
|
break;
|
||
|
|
}
|
||
|
|
|
||
|
|
cout << "-------------------------------------------------------------------" << endl;
|
||
|
|
|
||
|
|
return 0;
|
||
|
|
}
|