http://feelmare.blogspot.kr/2014/04/opencv-study-calcopticalflowfarneback.html
In the GPU mode, the return value of the function is two vector direction, that is x direction and y direction.
In the GPU mode, functions of resize, cvtColor cannot copy to same variable of gpumat.
And gputmat cannot access to the pixel point using at
GPU is more fast about 10 times than cpu mode in my computer environment.
refer to this example source code and video.
#include < stdio.h> #include < iostream> #include < opencv2\opencv.hpp> #include < opencv2/core/core.hpp> #include < opencv2/highgui/highgui.hpp> #include < opencv2/video/background_segm.hpp> #include < opencv2\gpu\gpu.hpp> #ifdef _DEBUG #pragma comment(lib, "opencv_core247d.lib") #pragma comment(lib, "opencv_imgproc247d.lib") //MAT processing #pragma comment(lib, "opencv_objdetect247d.lib") //HOGDescriptor #pragma comment(lib, "opencv_gpu247d.lib") //#pragma comment(lib, "opencv_features2d247d.lib") #pragma comment(lib, "opencv_highgui247d.lib") #pragma comment(lib, "opencv_ml247d.lib") //#pragma comment(lib, "opencv_stitching247d.lib"); //#pragma comment(lib, "opencv_nonfree247d.lib"); #pragma comment(lib, "opencv_video247d.lib") #else #pragma comment(lib, "opencv_core247.lib") #pragma comment(lib, "opencv_imgproc247.lib") #pragma comment(lib, "opencv_objdetect247.lib") #pragma comment(lib, "opencv_gpu247.lib") //#pragma comment(lib, "opencv_features2d247.lib") #pragma comment(lib, "opencv_highgui247.lib") #pragma comment(lib, "opencv_ml247.lib") //#pragma comment(lib, "opencv_stitching247.lib"); //#pragma comment(lib, "opencv_nonfree247.lib"); #pragma comment(lib, "opencv_video247d.lib") #endif using namespace cv; using namespace std; void drawOptFlowMap_gpu (const Mat& flow_x, const Mat& flow_y, Mat& cflowmap, int step, const Scalar& color) { for(int y = 0; y < cflowmap.rows; y += step) for(int x = 0; x < cflowmap.cols; x += step) { Point2f fxy; fxy.x = cvRound( flow_x.at< float >(y, x) + x ); fxy.y = cvRound( flow_y.at< float >(y, x) + y ); line(cflowmap, Point(x,y), Point(fxy.x, fxy.y), color); circle(cflowmap, Point(fxy.x, fxy.y), 1, color, -1); } } int main() { //resize scale int s=4; unsigned long AAtime=0, BBtime=0; //variables Mat GetImg, flow_x, flow_y, next, prvs; //gpu variable gpu::GpuMat prvs_gpu, next_gpu, flow_x_gpu, flow_y_gpu; gpu::GpuMat prvs_gpu_o, next_gpu_o; gpu::GpuMat prvs_gpu_c, next_gpu_c; //file name char fileName[100] = ".\\mm2.avi"; //Gate1_175_p1.avi"; //video\\mm2.avi"; //mm2.avi"; //cctv 2.mov"; //mm2.avi"; //";//_p1.avi"; //video file open VideoCapture stream1(fileName); //0 is the id of video device.0 if you have only one camera if(!(stream1.read(GetImg))) //get one frame form video return 0; ////////////////////////////////////////////////////////////////////////////////////////////// //resize(GetImg, prvs, Size(GetImg.size().width/s, GetImg.size().height/s) ); //cvtColor(prvs, prvs, CV_BGR2GRAY); //prvs_gpu.upload(prvs); ////////////////////////////////////////////////////////////////////////////////////////////// //gpu upload, resize, color convert prvs_gpu_o.upload(GetImg); gpu::resize(prvs_gpu_o, prvs_gpu_c, Size(GetImg.size().width/s, GetImg.size().height/s) ); gpu::cvtColor(prvs_gpu_c, prvs_gpu, CV_BGR2GRAY); ///////////////////////////////////////////////////////////////////////////////////////////// //dense optical flow gpu::FarnebackOpticalFlow fbOF; //unconditional loop while (true) { if(!(stream1.read(GetImg))) //get one frame form video break; /////////////////////////////////////////////////////////////////// //resize(GetImg, next, Size(GetImg.size().width/s, GetImg.size().height/s) ); //cvtColor(next, next, CV_BGR2GRAY); //next_gpu.upload(next); /////////////////////////////////////////////////////////////////// //gpu upload, resize, color convert next_gpu_o.upload(GetImg); gpu::resize(next_gpu_o, next_gpu_c, Size(GetImg.size().width/s, GetImg.size().height/s) ); gpu::cvtColor(next_gpu_c, next_gpu, CV_BGR2GRAY); /////////////////////////////////////////////////////////////////// AAtime = getTickCount(); //dense optical flow fbOF.operator()(prvs_gpu, next_gpu, flow_x_gpu, flow_y_gpu); //fbOF(prvs_gpu, next_gpu, flow_x_gpu, flow_y_gpu); BBtime = getTickCount(); float pt = (BBtime - AAtime)/getTickFrequency(); float fpt = 1/pt; printf("%.2lf / %.2lf \n", pt, fpt ); //copy for vector flow drawing Mat cflow; resize(GetImg, cflow, Size(GetImg.size().width/s, GetImg.size().height/s) ); flow_x_gpu.download( flow_x ); flow_y_gpu.download( flow_y ); drawOptFlowMap_gpu(flow_x, flow_y, cflow, 10 , CV_RGB(0, 255, 0)); imshow("OpticalFlowFarneback", cflow); /////////////////////////////////////////////////////////////////// //Display gpumat next_gpu.download( next ); prvs_gpu.download( prvs ); imshow("next", next ); imshow("prvs", prvs ); //prvs mat update prvs_gpu = next_gpu.clone(); if (waitKey(5) >= 0) break; } }
Hello,
ReplyDeleteThank you very much for sharing your job.
I would like to know which pc did you need to obtain this result ?
(RAM, processor,graphics board)
Thank you very much !
Camille
Thank you for visiting my blog.
ReplyDeleteMy computer spec is
xeon cpu e5-2609
ram 16gb
quadro k2000
but
i7, 8ram, geforce graphic spec is enough to obtain that performance.
Hi there! nice setup. You know, i'm probably gonna have to work with optical flow and cnn really soon, and I have access to a server with 6 core xeon cpu, and a quadro k4200.
ReplyDeleteI'd like to know, did you do any benchmarks? how many fps did you got?
Nice blog btw :)