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Merge pull request #918 from bitwangyaoyao:2.4_samples
This commit is contained in:
Vadim Pisarevsky
OpenCV Buildbot
commit
6bb9342a5f
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@ -1,5 +1,3 @@
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//This sample is inherited from facedetect.cpp in smaple/c
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#include "opencv2/objdetect/objdetect.hpp"
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#include "opencv2/highgui/highgui.hpp"
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#include "opencv2/imgproc/imgproc.hpp"
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@ -9,78 +7,84 @@
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using namespace std;
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using namespace cv;
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#define LOOP_NUM 10
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static void help()
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const static Scalar colors[] = { CV_RGB(0,0,255),
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CV_RGB(0,128,255),
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CV_RGB(0,255,255),
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CV_RGB(0,255,0),
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CV_RGB(255,128,0),
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CV_RGB(255,255,0),
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CV_RGB(255,0,0),
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CV_RGB(255,0,255)} ;
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int64 work_begin = 0;
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int64 work_end = 0;
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static void workBegin()
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{
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cout << "\nThis program demonstrates the cascade recognizer.\n"
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"This classifier can recognize many ~rigid objects, it's most known use is for faces.\n"
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"Usage:\n"
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"./facedetect [--cascade=<cascade_path> this is the primary trained classifier such as frontal face]\n"
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" [--scale=<image scale greater or equal to 1, try 1.3 for example>\n"
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" [filename|camera_index]\n\n"
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"see facedetect.cmd for one call:\n"
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"./facedetect --cascade=\"../../data/haarcascades/haarcascade_frontalface_alt.xml\" --scale=1.3 \n"
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"Hit any key to quit.\n"
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"Using OpenCV version " << CV_VERSION << "\n" << endl;
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work_begin = getTickCount();
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}
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static void workEnd()
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{
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work_end += (getTickCount() - work_begin);
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}
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static double getTime(){
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return work_end /((double)cvGetTickFrequency() * 1000.);
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}
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struct getRect { Rect operator ()(const CvAvgComp& e) const { return e.rect; } };
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void detectAndDraw( Mat& img,
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cv::ocl::OclCascadeClassifier& cascade, CascadeClassifier& nestedCascade,
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double scale);
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String cascadeName = "../../../data/haarcascades/haarcascade_frontalface_alt.xml";
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void detect( Mat& img, vector<Rect>& faces,
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cv::ocl::OclCascadeClassifierBuf& cascade,
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double scale, bool calTime);
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void detectCPU( Mat& img, vector<Rect>& faces,
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CascadeClassifier& cascade,
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double scale, bool calTime);
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void Draw(Mat& img, vector<Rect>& faces, double scale);
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// This function test if gpu_rst matches cpu_rst.
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// If the two vectors are not equal, it will return the difference in vector size
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// Else if will return (total diff of each cpu and gpu rects covered pixels)/(total cpu rects covered pixels)
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double checkRectSimilarity(Size sz, std::vector<Rect>& cpu_rst, std::vector<Rect>& gpu_rst);
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int main( int argc, const char** argv )
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{
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const char* keys =
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"{ h | help | false | print help message }"
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"{ i | input | | specify input image }"
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"{ t | template | ../../../data/haarcascades/haarcascade_frontalface_alt.xml | specify template file }"
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"{ c | scale | 1.0 | scale image }"
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"{ s | use_cpu | false | use cpu or gpu to process the image }";
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CommandLineParser cmd(argc, argv, keys);
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if (cmd.get<bool>("help"))
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{
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cout << "Avaible options:" << endl;
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cmd.printParams();
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return 0;
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}
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CvCapture* capture = 0;
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Mat frame, frameCopy, image;
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const String scaleOpt = "--scale=";
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size_t scaleOptLen = scaleOpt.length();
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const String cascadeOpt = "--cascade=";
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size_t cascadeOptLen = cascadeOpt.length();
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String inputName;
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help();
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cv::ocl::OclCascadeClassifier cascade;
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CascadeClassifier nestedCascade;
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double scale = 1;
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bool useCPU = cmd.get<bool>("s");
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string inputName = cmd.get<string>("i");
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string cascadeName = cmd.get<string>("t");
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double scale = cmd.get<double>("c");
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cv::ocl::OclCascadeClassifierBuf cascade;
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CascadeClassifier cpu_cascade;
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for( int i = 1; i < argc; i++ )
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{
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cout << "Processing " << i << " " << argv[i] << endl;
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if( cascadeOpt.compare( 0, cascadeOptLen, argv[i], cascadeOptLen ) == 0 )
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{
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cascadeName.assign( argv[i] + cascadeOptLen );
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cout << " from which we have cascadeName= " << cascadeName << endl;
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}
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else if( scaleOpt.compare( 0, scaleOptLen, argv[i], scaleOptLen ) == 0 )
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{
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if( !sscanf( argv[i] + scaleOpt.length(), "%lf", &scale ) || scale < 1 )
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scale = 1;
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cout << " from which we read scale = " << scale << endl;
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}
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else if( argv[i][0] == '-' )
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{
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cerr << "WARNING: Unknown option %s" << argv[i] << endl;
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}
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else
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inputName.assign( argv[i] );
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}
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if( !cascade.load( cascadeName ) )
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if( !cascade.load( cascadeName ) || !cpu_cascade.load(cascadeName) )
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{
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cerr << "ERROR: Could not load classifier cascade" << endl;
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cerr << "Usage: facedetect [--cascade=<cascade_path>]\n"
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" [--scale[=<image scale>\n"
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" [filename|camera_index]\n" << endl ;
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return -1;
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}
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if( inputName.empty() || (isdigit(inputName.c_str()[0]) && inputName.c_str()[1] == '\0') )
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if( inputName.empty() )
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{
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capture = cvCaptureFromCAM( inputName.empty() ? 0 : inputName.c_str()[0] - '0' );
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int c = inputName.empty() ? 0 : inputName.c_str()[0] - '0' ;
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if(!capture) cout << "Capture from CAM " << c << " didn't work" << endl;
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capture = cvCaptureFromCAM(0);
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if(!capture)
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cout << "Capture from CAM 0 didn't work" << endl;
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}
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else if( inputName.size() )
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{
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@ -88,26 +92,30 @@ int main( int argc, const char** argv )
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if( image.empty() )
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{
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capture = cvCaptureFromAVI( inputName.c_str() );
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if(!capture) cout << "Capture from AVI didn't work" << endl;
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if(!capture)
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cout << "Capture from AVI didn't work" << endl;
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return -1;
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}
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}
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else
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{
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image = imread( "lena.jpg", 1 );
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if(image.empty()) cout << "Couldn't read lena.jpg" << endl;
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if(image.empty())
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cout << "Couldn't read lena.jpg" << endl;
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return -1;
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}
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cvNamedWindow( "result", 1 );
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std::vector<cv::ocl::Info> oclinfo;
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int devnums = cv::ocl::getDevice(oclinfo);
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if(devnums<1)
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if( devnums < 1 )
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{
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std::cout << "no device found\n";
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return -1;
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}
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//if you want to use undefault device, set it here
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//setDevice(oclinfo[0]);
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//setBinpath(CLBINPATH);
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ocl::setBinpath("./");
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if( capture )
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{
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cout << "In capture ..." << endl;
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@ -115,15 +123,20 @@ int main( int argc, const char** argv )
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{
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IplImage* iplImg = cvQueryFrame( capture );
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frame = iplImg;
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vector<Rect> faces;
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if( frame.empty() )
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break;
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if( iplImg->origin == IPL_ORIGIN_TL )
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frame.copyTo( frameCopy );
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else
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flip( frame, frameCopy, 0 );
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detectAndDraw( frameCopy, cascade, nestedCascade, scale );
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if(useCPU){
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detectCPU(frameCopy, faces, cpu_cascade, scale, false);
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}
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else{
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detect(frameCopy, faces, cascade, scale, false);
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}
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Draw(frameCopy, faces, scale);
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if( waitKey( 10 ) >= 0 )
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goto _cleanup_;
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}
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@ -136,42 +149,34 @@ _cleanup_:
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else
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{
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cout << "In image read" << endl;
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if( !image.empty() )
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vector<Rect> faces;
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vector<Rect> ref_rst;
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double accuracy = 0.;
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for(int i = 0; i <= LOOP_NUM;i ++)
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{
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detectAndDraw( image, cascade, nestedCascade, scale );
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waitKey(0);
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}
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else if( !inputName.empty() )
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{
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/* assume it is a text file containing the
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list of the image filenames to be processed - one per line */
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FILE* f = fopen( inputName.c_str(), "rt" );
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if( f )
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{
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char buf[1000+1];
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while( fgets( buf, 1000, f ) )
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{
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int len = (int)strlen(buf), c;
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while( len > 0 && isspace(buf[len-1]) )
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len--;
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buf[len] = '\0';
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cout << "file " << buf << endl;
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image = imread( buf, 1 );
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if( !image.empty() )
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{
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detectAndDraw( image, cascade, nestedCascade, scale );
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c = waitKey(0);
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if( c == 27 || c == 'q' || c == 'Q' )
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break;
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}
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else
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{
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cerr << "Aw snap, couldn't read image " << buf << endl;
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}
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cout << "loop" << i << endl;
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if(useCPU){
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detectCPU(image, faces, cpu_cascade, scale, i==0?false:true);
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}
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else{
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detect(image, faces, cascade, scale, i==0?false:true);
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if(i == 0){
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detectCPU(image, ref_rst, cpu_cascade, scale, false);
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accuracy = checkRectSimilarity(image.size(), ref_rst, faces);
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}
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fclose(f);
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}
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if (i == LOOP_NUM)
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{
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if (useCPU)
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cout << "average CPU time (noCamera) : ";
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else
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cout << "average GPU time (noCamera) : ";
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cout << getTime() / LOOP_NUM << " ms" << endl;
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cout << "accuracy value: " << accuracy <<endl;
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}
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}
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Draw(image, faces, scale);
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waitKey(0);
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}
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cvDestroyWindow("result");
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@ -179,44 +184,44 @@ _cleanup_:
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return 0;
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}
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void detectAndDraw( Mat& img,
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cv::ocl::OclCascadeClassifier& cascade, CascadeClassifier&,
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double scale)
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void detect( Mat& img, vector<Rect>& faces,
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cv::ocl::OclCascadeClassifierBuf& cascade,
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double scale, bool calTime)
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{
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int i = 0;
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double t = 0;
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vector<Rect> faces;
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const static Scalar colors[] = { CV_RGB(0,0,255),
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CV_RGB(0,128,255),
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CV_RGB(0,255,255),
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CV_RGB(0,255,0),
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CV_RGB(255,128,0),
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CV_RGB(255,255,0),
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CV_RGB(255,0,0),
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CV_RGB(255,0,255)} ;
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cv::ocl::oclMat image(img);
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cv::ocl::oclMat gray, smallImg( cvRound (img.rows/scale), cvRound(img.cols/scale), CV_8UC1 );
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if(calTime) workBegin();
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cv::ocl::cvtColor( image, gray, CV_BGR2GRAY );
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cv::ocl::resize( gray, smallImg, smallImg.size(), 0, 0, INTER_LINEAR );
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cv::ocl::equalizeHist( smallImg, smallImg );
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CvSeq* _objects;
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MemStorage storage(cvCreateMemStorage(0));
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t = (double)cvGetTickCount();
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_objects = cascade.oclHaarDetectObjects( smallImg, storage, 1.1,
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cascade.detectMultiScale( smallImg, faces, 1.1,
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3, 0
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|CV_HAAR_SCALE_IMAGE
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, Size(30,30), Size(0, 0) );
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vector<CvAvgComp> vecAvgComp;
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Seq<CvAvgComp>(_objects).copyTo(vecAvgComp);
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faces.resize(vecAvgComp.size());
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std::transform(vecAvgComp.begin(), vecAvgComp.end(), faces.begin(), getRect());
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t = (double)cvGetTickCount() - t;
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printf( "detection time = %g ms\n", t/((double)cvGetTickFrequency()*1000.) );
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if(calTime) workEnd();
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}
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void detectCPU( Mat& img, vector<Rect>& faces,
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CascadeClassifier& cascade,
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double scale, bool calTime)
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{
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if(calTime) workBegin();
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Mat cpu_gray, cpu_smallImg( cvRound (img.rows/scale), cvRound(img.cols/scale), CV_8UC1 );
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cvtColor(img, cpu_gray, CV_BGR2GRAY);
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resize(cpu_gray, cpu_smallImg, cpu_smallImg.size(), 0, 0, INTER_LINEAR);
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equalizeHist(cpu_smallImg, cpu_smallImg);
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cascade.detectMultiScale(cpu_smallImg, faces, 1.1,
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3, 0 | CV_HAAR_SCALE_IMAGE,
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Size(30, 30), Size(0, 0));
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if(calTime) workEnd();
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}
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void Draw(Mat& img, vector<Rect>& faces, double scale)
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{
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int i = 0;
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for( vector<Rect>::const_iterator r = faces.begin(); r != faces.end(); r++, i++ )
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{
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Mat smallImgROI;
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Point center;
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Scalar color = colors[i%8];
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int radius;
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@ -227,3 +232,42 @@ void detectAndDraw( Mat& img,
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}
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cv::imshow( "result", img );
|
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}
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double checkRectSimilarity(Size sz, std::vector<Rect>& ob1, std::vector<Rect>& ob2)
|
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{
|
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double final_test_result = 0.0;
|
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size_t sz1 = ob1.size();
|
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size_t sz2 = ob2.size();
|
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|
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if(sz1 != sz2)
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return sz1 > sz2 ? (double)(sz1 - sz2) : (double)(sz2 - sz1);
|
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else
|
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{
|
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cv::Mat cpu_result(sz, CV_8UC1);
|
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cpu_result.setTo(0);
|
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|
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for(vector<Rect>::const_iterator r = ob1.begin(); r != ob1.end(); r++)
|
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{
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cv::Mat cpu_result_roi(cpu_result, *r);
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cpu_result_roi.setTo(1);
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cpu_result.copyTo(cpu_result);
|
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}
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int cpu_area = cv::countNonZero(cpu_result > 0);
|
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cv::Mat gpu_result(sz, CV_8UC1);
|
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gpu_result.setTo(0);
|
||||
for(vector<Rect>::const_iterator r2 = ob2.begin(); r2 != ob2.end(); r2++)
|
||||
{
|
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cv::Mat gpu_result_roi(gpu_result, *r2);
|
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gpu_result_roi.setTo(1);
|
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gpu_result.copyTo(gpu_result);
|
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}
|
||||
|
||||
cv::Mat result_;
|
||||
multiply(cpu_result, gpu_result, result_);
|
||||
int result = cv::countNonZero(result_ > 0);
|
||||
|
||||
final_test_result = 1.0 - (double)result/(double)cpu_area;
|
||||
}
|
||||
return final_test_result;
|
||||
}
|
||||
|
||||
@ -45,7 +45,6 @@ public:
|
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bool gamma_corr;
|
||||
};
|
||||
|
||||
|
||||
class App
|
||||
{
|
||||
public:
|
||||
@ -64,6 +63,13 @@ public:
|
||||
|
||||
string message() const;
|
||||
|
||||
// This function test if gpu_rst matches cpu_rst.
|
||||
// If the two vectors are not equal, it will return the difference in vector size
|
||||
// Else if will return
|
||||
// (total diff of each cpu and gpu rects covered pixels)/(total cpu rects covered pixels)
|
||||
double checkRectSimilarity(Size sz,
|
||||
std::vector<Rect>& cpu_rst,
|
||||
std::vector<Rect>& gpu_rst);
|
||||
private:
|
||||
App operator=(App&);
|
||||
|
||||
@ -290,6 +296,7 @@ void App::run()
|
||||
ocl::oclMat gpu_img;
|
||||
|
||||
// Iterate over all frames
|
||||
bool verify = false;
|
||||
while (running && !frame.empty())
|
||||
{
|
||||
workBegin();
|
||||
@ -316,7 +323,18 @@ void App::run()
|
||||
gpu_img.upload(img);
|
||||
gpu_hog.detectMultiScale(gpu_img, found, hit_threshold, win_stride,
|
||||
Size(0, 0), scale, gr_threshold);
|
||||
}
|
||||
if (!verify)
|
||||
{
|
||||
// verify if GPU output same objects with CPU at 1st run
|
||||
verify = true;
|
||||
vector<Rect> ref_rst;
|
||||
cvtColor(img, img, CV_BGRA2BGR);
|
||||
cpu_hog.detectMultiScale(img, ref_rst, hit_threshold, win_stride,
|
||||
Size(0, 0), scale, gr_threshold-2);
|
||||
double accuracy = checkRectSimilarity(img.size(), ref_rst, found);
|
||||
cout << "\naccuracy value: " << accuracy << endl;
|
||||
}
|
||||
}
|
||||
else cpu_hog.detectMultiScale(img, found, hit_threshold, win_stride,
|
||||
Size(0, 0), scale, gr_threshold);
|
||||
hogWorkEnd();
|
||||
@ -457,3 +475,45 @@ inline string App::workFps() const
|
||||
return ss.str();
|
||||
}
|
||||
|
||||
double App::checkRectSimilarity(Size sz,
|
||||
std::vector<Rect>& ob1,
|
||||
std::vector<Rect>& ob2)
|
||||
{
|
||||
double final_test_result = 0.0;
|
||||
size_t sz1 = ob1.size();
|
||||
size_t sz2 = ob2.size();
|
||||
|
||||
if(sz1 != sz2)
|
||||
return sz1 > sz2 ? (double)(sz1 - sz2) : (double)(sz2 - sz1);
|
||||
else
|
||||
{
|
||||
cv::Mat cpu_result(sz, CV_8UC1);
|
||||
cpu_result.setTo(0);
|
||||
|
||||
for(vector<Rect>::const_iterator r = ob1.begin(); r != ob1.end(); r++)
|
||||
{
|
||||
cv::Mat cpu_result_roi(cpu_result, *r);
|
||||
cpu_result_roi.setTo(1);
|
||||
cpu_result.copyTo(cpu_result);
|
||||
}
|
||||
int cpu_area = cv::countNonZero(cpu_result > 0);
|
||||
|
||||
cv::Mat gpu_result(sz, CV_8UC1);
|
||||
gpu_result.setTo(0);
|
||||
for(vector<Rect>::const_iterator r2 = ob2.begin(); r2 != ob2.end(); r2++)
|
||||
{
|
||||
cv::Mat gpu_result_roi(gpu_result, *r2);
|
||||
gpu_result_roi.setTo(1);
|
||||
gpu_result.copyTo(gpu_result);
|
||||
}
|
||||
|
||||
cv::Mat result_;
|
||||
multiply(cpu_result, gpu_result, result_);
|
||||
int result = cv::countNonZero(result_ > 0);
|
||||
|
||||
final_test_result = 1.0 - (double)result/(double)cpu_area;
|
||||
}
|
||||
return final_test_result;
|
||||
|
||||
}
|
||||
|
||||
|
||||
290
samples/ocl/pyrlk_optical_flow.cpp
Normal file
290
samples/ocl/pyrlk_optical_flow.cpp
Normal file
@ -0,0 +1,290 @@
|
||||
#include <iostream>
|
||||
#include <vector>
|
||||
#include <iomanip>
|
||||
|
||||
#include "opencv2/highgui/highgui.hpp"
|
||||
#include "opencv2/ocl/ocl.hpp"
|
||||
#include "opencv2/video/video.hpp"
|
||||
|
||||
using namespace std;
|
||||
using namespace cv;
|
||||
using namespace cv::ocl;
|
||||
|
||||
typedef unsigned char uchar;
|
||||
#define LOOP_NUM 10
|
||||
int64 work_begin = 0;
|
||||
int64 work_end = 0;
|
||||
|
||||
static void workBegin()
|
||||
{
|
||||
work_begin = getTickCount();
|
||||
}
|
||||
static void workEnd()
|
||||
{
|
||||
work_end += (getTickCount() - work_begin);
|
||||
}
|
||||
static double getTime(){
|
||||
return work_end * 1000. / getTickFrequency();
|
||||
}
|
||||
|
||||
static void download(const oclMat& d_mat, vector<Point2f>& vec)
|
||||
{
|
||||
vec.resize(d_mat.cols);
|
||||
Mat mat(1, d_mat.cols, CV_32FC2, (void*)&vec[0]);
|
||||
d_mat.download(mat);
|
||||
}
|
||||
|
||||
static void download(const oclMat& d_mat, vector<uchar>& vec)
|
||||
{
|
||||
vec.resize(d_mat.cols);
|
||||
Mat mat(1, d_mat.cols, CV_8UC1, (void*)&vec[0]);
|
||||
d_mat.download(mat);
|
||||
}
|
||||
|
||||
static void drawArrows(Mat& frame, const vector<Point2f>& prevPts, const vector<Point2f>& nextPts, const vector<uchar>& status, Scalar line_color = Scalar(0, 0, 255))
|
||||
{
|
||||
for (size_t i = 0; i < prevPts.size(); ++i)
|
||||
{
|
||||
if (status[i])
|
||||
{
|
||||
int line_thickness = 1;
|
||||
|
||||
Point p = prevPts[i];
|
||||
Point q = nextPts[i];
|
||||
|
||||
double angle = atan2((double) p.y - q.y, (double) p.x - q.x);
|
||||
|
||||
double hypotenuse = sqrt( (double)(p.y - q.y)*(p.y - q.y) + (double)(p.x - q.x)*(p.x - q.x) );
|
||||
|
||||
if (hypotenuse < 1.0)
|
||||
continue;
|
||||
|
||||
// Here we lengthen the arrow by a factor of three.
|
||||
q.x = (int) (p.x - 3 * hypotenuse * cos(angle));
|
||||
q.y = (int) (p.y - 3 * hypotenuse * sin(angle));
|
||||
|
||||
// Now we draw the main line of the arrow.
|
||||
line(frame, p, q, line_color, line_thickness);
|
||||
|
||||
// Now draw the tips of the arrow. I do some scaling so that the
|
||||
// tips look proportional to the main line of the arrow.
|
||||
|
||||
p.x = (int) (q.x + 9 * cos(angle + CV_PI / 4));
|
||||
p.y = (int) (q.y + 9 * sin(angle + CV_PI / 4));
|
||||
line(frame, p, q, line_color, line_thickness);
|
||||
|
||||
p.x = (int) (q.x + 9 * cos(angle - CV_PI / 4));
|
||||
p.y = (int) (q.y + 9 * sin(angle - CV_PI / 4));
|
||||
line(frame, p, q, line_color, line_thickness);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
int main(int argc, const char* argv[])
|
||||
{
|
||||
static std::vector<Info> ocl_info;
|
||||
ocl::getDevice(ocl_info);
|
||||
//if you want to use undefault device, set it here
|
||||
setDevice(ocl_info[0]);
|
||||
|
||||
//set this to save kernel compile time from second time you run
|
||||
ocl::setBinpath("./");
|
||||
const char* keys =
|
||||
"{ h | help | false | print help message }"
|
||||
"{ l | left | | specify left image }"
|
||||
"{ r | right | | specify right image }"
|
||||
"{ c | camera | 0 | enable camera capturing }"
|
||||
"{ s | use_cpu | false | use cpu or gpu to process the image }"
|
||||
"{ v | video | | use video as input }"
|
||||
"{ points | points | 1000 | specify points count [GoodFeatureToTrack] }"
|
||||
"{ min_dist | min_dist | 0 | specify minimal distance between points [GoodFeatureToTrack] }";
|
||||
|
||||
CommandLineParser cmd(argc, argv, keys);
|
||||
|
||||
if (cmd.get<bool>("help"))
|
||||
{
|
||||
cout << "Usage: pyrlk_optical_flow [options]" << endl;
|
||||
cout << "Avaible options:" << endl;
|
||||
cmd.printParams();
|
||||
return 0;
|
||||
}
|
||||
|
||||
bool defaultPicturesFail = false;
|
||||
string fname0 = cmd.get<string>("left");
|
||||
string fname1 = cmd.get<string>("right");
|
||||
string vdofile = cmd.get<string>("video");
|
||||
int points = cmd.get<int>("points");
|
||||
double minDist = cmd.get<double>("min_dist");
|
||||
bool useCPU = cmd.get<bool>("s");
|
||||
bool useCamera = cmd.get<bool>("c");
|
||||
int inputName = cmd.get<int>("c");
|
||||
oclMat d_nextPts, d_status;
|
||||
|
||||
Mat frame0 = imread(fname0, cv::IMREAD_GRAYSCALE);
|
||||
Mat frame1 = imread(fname1, cv::IMREAD_GRAYSCALE);
|
||||
PyrLKOpticalFlow d_pyrLK;
|
||||
vector<cv::Point2f> pts;
|
||||
vector<cv::Point2f> nextPts;
|
||||
vector<unsigned char> status;
|
||||
vector<float> err;
|
||||
|
||||
if (frame0.empty() || frame1.empty())
|
||||
{
|
||||
useCamera = true;
|
||||
defaultPicturesFail = true;
|
||||
CvCapture* capture = 0;
|
||||
capture = cvCaptureFromCAM( inputName );
|
||||
if (!capture)
|
||||
{
|
||||
cout << "Can't load input images" << endl;
|
||||
return -1;
|
||||
}
|
||||
}
|
||||
|
||||
cout << "Points count : " << points << endl << endl;
|
||||
|
||||
if (useCamera)
|
||||
{
|
||||
CvCapture* capture = 0;
|
||||
Mat frame, frameCopy;
|
||||
Mat frame0Gray, frame1Gray;
|
||||
Mat ptr0, ptr1;
|
||||
|
||||
if(vdofile == "")
|
||||
capture = cvCaptureFromCAM( inputName );
|
||||
else
|
||||
capture = cvCreateFileCapture(vdofile.c_str());
|
||||
|
||||
int c = inputName ;
|
||||
if(!capture)
|
||||
{
|
||||
if(vdofile == "")
|
||||
cout << "Capture from CAM " << c << " didn't work" << endl;
|
||||
else
|
||||
cout << "Capture from file " << vdofile << " failed" <<endl;
|
||||
if (defaultPicturesFail)
|
||||
{
|
||||
return -1;
|
||||
}
|
||||
goto nocamera;
|
||||
}
|
||||
|
||||
cout << "In capture ..." << endl;
|
||||
for(int i = 0;; i++)
|
||||
{
|
||||
frame = cvQueryFrame( capture );
|
||||
if( frame.empty() )
|
||||
break;
|
||||
|
||||
if (i == 0)
|
||||
{
|
||||
frame.copyTo( frame0 );
|
||||
cvtColor(frame0, frame0Gray, COLOR_BGR2GRAY);
|
||||
}
|
||||
else
|
||||
{
|
||||
if (i%2 == 1)
|
||||
{
|
||||
frame.copyTo(frame1);
|
||||
cvtColor(frame1, frame1Gray, COLOR_BGR2GRAY);
|
||||
ptr0 = frame0Gray;
|
||||
ptr1 = frame1Gray;
|
||||
}
|
||||
else
|
||||
{
|
||||
frame.copyTo(frame0);
|
||||
cvtColor(frame0, frame0Gray, COLOR_BGR2GRAY);
|
||||
ptr0 = frame1Gray;
|
||||
ptr1 = frame0Gray;
|
||||
}
|
||||
|
||||
pts.clear();
|
||||
|
||||
cv::goodFeaturesToTrack(ptr0, pts, points, 0.01, 0.0);
|
||||
|
||||
if (pts.size() == 0)
|
||||
{
|
||||
continue;
|
||||
}
|
||||
|
||||
if (useCPU)
|
||||
{
|
||||
cv::calcOpticalFlowPyrLK(ptr0, ptr1, pts, nextPts, status, err);
|
||||
}
|
||||
else
|
||||
{
|
||||
oclMat d_prevPts(1, points, CV_32FC2, (void*)&pts[0]);
|
||||
|
||||
d_pyrLK.sparse(oclMat(ptr0), oclMat(ptr1), d_prevPts, d_nextPts, d_status);
|
||||
|
||||
download(d_prevPts, pts);
|
||||
download(d_nextPts, nextPts);
|
||||
download(d_status, status);
|
||||
|
||||
}
|
||||
if (i%2 == 1)
|
||||
frame1.copyTo(frameCopy);
|
||||
else
|
||||
frame0.copyTo(frameCopy);
|
||||
drawArrows(frameCopy, pts, nextPts, status, Scalar(255, 0, 0));
|
||||
imshow("PyrLK [Sparse]", frameCopy);
|
||||
}
|
||||
|
||||
if( waitKey( 10 ) >= 0 )
|
||||
goto _cleanup_;
|
||||
}
|
||||
|
||||
waitKey(0);
|
||||
|
||||
_cleanup_:
|
||||
cvReleaseCapture( &capture );
|
||||
}
|
||||
else
|
||||
{
|
||||
nocamera:
|
||||
for(int i = 0; i <= LOOP_NUM;i ++)
|
||||
{
|
||||
cout << "loop" << i << endl;
|
||||
if (i > 0) workBegin();
|
||||
|
||||
cv::goodFeaturesToTrack(frame0, pts, points, 0.01, minDist);
|
||||
|
||||
if (useCPU)
|
||||
{
|
||||
cv::calcOpticalFlowPyrLK(frame0, frame1, pts, nextPts, status, err);
|
||||
}
|
||||
else
|
||||
{
|
||||
oclMat d_prevPts(1, points, CV_32FC2, (void*)&pts[0]);
|
||||
|
||||
d_pyrLK.sparse(oclMat(frame0), oclMat(frame1), d_prevPts, d_nextPts, d_status);
|
||||
|
||||
download(d_prevPts, pts);
|
||||
download(d_nextPts, nextPts);
|
||||
download(d_status, status);
|
||||
}
|
||||
|
||||
if (i > 0 && i <= LOOP_NUM)
|
||||
workEnd();
|
||||
|
||||
if (i == LOOP_NUM)
|
||||
{
|
||||
if (useCPU)
|
||||
cout << "average CPU time (noCamera) : ";
|
||||
else
|
||||
cout << "average GPU time (noCamera) : ";
|
||||
|
||||
cout << getTime() / LOOP_NUM << " ms" << endl;
|
||||
|
||||
drawArrows(frame0, pts, nextPts, status, Scalar(255, 0, 0));
|
||||
|
||||
imshow("PyrLK [Sparse]", frame0);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
waitKey();
|
||||
|
||||
return 0;
|
||||
}
|
||||
419
samples/ocl/stereo_match.cpp
Normal file
419
samples/ocl/stereo_match.cpp
Normal file
@ -0,0 +1,419 @@
|
||||
#include <iostream>
|
||||
#include <string>
|
||||
#include <sstream>
|
||||
#include <iomanip>
|
||||
#include <stdexcept>
|
||||
#include "opencv2/ocl/ocl.hpp"
|
||||
#include "opencv2/highgui/highgui.hpp"
|
||||
|
||||
using namespace cv;
|
||||
using namespace std;
|
||||
using namespace ocl;
|
||||
|
||||
bool help_showed = false;
|
||||
|
||||
struct Params
|
||||
{
|
||||
Params();
|
||||
static Params read(int argc, char** argv);
|
||||
|
||||
string left;
|
||||
string right;
|
||||
|
||||
string method_str() const
|
||||
{
|
||||
switch (method)
|
||||
{
|
||||
case BM: return "BM";
|
||||
case BP: return "BP";
|
||||
case CSBP: return "CSBP";
|
||||
}
|
||||
return "";
|
||||
}
|
||||
enum {BM, BP, CSBP} method;
|
||||
int ndisp; // Max disparity + 1
|
||||
enum {GPU, CPU} type;
|
||||
};
|
||||
|
||||
|
||||
struct App
|
||||
{
|
||||
App(const Params& p);
|
||||
void run();
|
||||
void handleKey(char key);
|
||||
void printParams() const;
|
||||
|
||||
void workBegin() { work_begin = getTickCount(); }
|
||||
void workEnd()
|
||||
{
|
||||
int64 d = getTickCount() - work_begin;
|
||||
double f = getTickFrequency();
|
||||
work_fps = f / d;
|
||||
}
|
||||
|
||||
string text() const
|
||||
{
|
||||
stringstream ss;
|
||||
ss << "(" << p.method_str() << ") FPS: " << setiosflags(ios::left)
|
||||
<< setprecision(4) << work_fps;
|
||||
return ss.str();
|
||||
}
|
||||
private:
|
||||
Params p;
|
||||
bool running;
|
||||
|
||||
Mat left_src, right_src;
|
||||
Mat left, right;
|
||||
oclMat d_left, d_right;
|
||||
|
||||
StereoBM_OCL bm;
|
||||
StereoBeliefPropagation bp;
|
||||
StereoConstantSpaceBP csbp;
|
||||
|
||||
int64 work_begin;
|
||||
double work_fps;
|
||||
};
|
||||
|
||||
static void printHelp()
|
||||
{
|
||||
cout << "Usage: stereo_match_gpu\n"
|
||||
<< "\t--left <left_view> --right <right_view> # must be rectified\n"
|
||||
<< "\t--method <stereo_match_method> # BM | BP | CSBP\n"
|
||||
<< "\t--ndisp <number> # number of disparity levels\n"
|
||||
<< "\t--type <device_type> # cpu | CPU | gpu | GPU\n";
|
||||
help_showed = true;
|
||||
}
|
||||
|
||||
int main(int argc, char** argv)
|
||||
{
|
||||
try
|
||||
{
|
||||
if (argc < 2)
|
||||
{
|
||||
printHelp();
|
||||
return 1;
|
||||
}
|
||||
|
||||
Params args = Params::read(argc, argv);
|
||||
if (help_showed)
|
||||
return -1;
|
||||
|
||||
int flags[2] = { CVCL_DEVICE_TYPE_GPU, CVCL_DEVICE_TYPE_CPU };
|
||||
vector<Info> info;
|
||||
|
||||
if(getDevice(info, flags[args.type]) == 0)
|
||||
{
|
||||
throw runtime_error("Error: Did not find a valid OpenCL device!");
|
||||
}
|
||||
cout << "Device name:" << info[0].DeviceName[0] << endl;
|
||||
|
||||
App app(args);
|
||||
app.run();
|
||||
}
|
||||
catch (const exception& e)
|
||||
{
|
||||
cout << "error: " << e.what() << endl;
|
||||
}
|
||||
return 0;
|
||||
}
|
||||
|
||||
|
||||
Params::Params()
|
||||
{
|
||||
method = BM;
|
||||
ndisp = 64;
|
||||
type = GPU;
|
||||
}
|
||||
|
||||
|
||||
Params Params::read(int argc, char** argv)
|
||||
{
|
||||
Params p;
|
||||
|
||||
for (int i = 1; i < argc; i++)
|
||||
{
|
||||
if (string(argv[i]) == "--left") p.left = argv[++i];
|
||||
else if (string(argv[i]) == "--right") p.right = argv[++i];
|
||||
else if (string(argv[i]) == "--method")
|
||||
{
|
||||
if (string(argv[i + 1]) == "BM") p.method = BM;
|
||||
else if (string(argv[i + 1]) == "BP") p.method = BP;
|
||||
else if (string(argv[i + 1]) == "CSBP") p.method = CSBP;
|
||||
else throw runtime_error("unknown stereo match method: " + string(argv[i + 1]));
|
||||
i++;
|
||||
}
|
||||
else if (string(argv[i]) == "--ndisp") p.ndisp = atoi(argv[++i]);
|
||||
else if (string(argv[i]) == "--type")
|
||||
{
|
||||
string t(argv[++i]);
|
||||
if (t == "cpu" || t == "CPU")
|
||||
{
|
||||
p.type = CPU;
|
||||
}
|
||||
else if (t == "gpu" || t == "GPU")
|
||||
{
|
||||
p.type = GPU;
|
||||
}
|
||||
else throw runtime_error("unknown device type: " + t);
|
||||
}
|
||||
else if (string(argv[i]) == "--help") printHelp();
|
||||
else throw runtime_error("unknown key: " + string(argv[i]));
|
||||
}
|
||||
|
||||
return p;
|
||||
}
|
||||
|
||||
|
||||
App::App(const Params& params)
|
||||
: p(params), running(false)
|
||||
{
|
||||
cout << "stereo_match_ocl sample\n";
|
||||
cout << "\nControls:\n"
|
||||
<< "\tesc - exit\n"
|
||||
<< "\tp - print current parameters\n"
|
||||
<< "\tg - convert source images into gray\n"
|
||||
<< "\tm - change stereo match method\n"
|
||||
<< "\ts - change Sobel prefiltering flag (for BM only)\n"
|
||||
<< "\t1/q - increase/decrease maximum disparity\n"
|
||||
<< "\t2/w - increase/decrease window size (for BM only)\n"
|
||||
<< "\t3/e - increase/decrease iteration count (for BP and CSBP only)\n"
|
||||
<< "\t4/r - increase/decrease level count (for BP and CSBP only)\n";
|
||||
}
|
||||
|
||||
|
||||
void App::run()
|
||||
{
|
||||
// Load images
|
||||
left_src = imread(p.left);
|
||||
right_src = imread(p.right);
|
||||
if (left_src.empty()) throw runtime_error("can't open file \"" + p.left + "\"");
|
||||
if (right_src.empty()) throw runtime_error("can't open file \"" + p.right + "\"");
|
||||
|
||||
cvtColor(left_src, left, CV_BGR2GRAY);
|
||||
cvtColor(right_src, right, CV_BGR2GRAY);
|
||||
|
||||
d_left.upload(left);
|
||||
d_right.upload(right);
|
||||
|
||||
imshow("left", left);
|
||||
imshow("right", right);
|
||||
|
||||
// Set common parameters
|
||||
bm.ndisp = p.ndisp;
|
||||
bp.ndisp = p.ndisp;
|
||||
csbp.ndisp = p.ndisp;
|
||||
|
||||
cout << endl;
|
||||
printParams();
|
||||
|
||||
running = true;
|
||||
while (running)
|
||||
{
|
||||
|
||||
// Prepare disparity map of specified type
|
||||
Mat disp;
|
||||
oclMat d_disp;
|
||||
workBegin();
|
||||
switch (p.method)
|
||||
{
|
||||
case Params::BM:
|
||||
if (d_left.channels() > 1 || d_right.channels() > 1)
|
||||
{
|
||||
cout << "BM doesn't support color images\n";
|
||||
cvtColor(left_src, left, CV_BGR2GRAY);
|
||||
cvtColor(right_src, right, CV_BGR2GRAY);
|
||||
cout << "image_channels: " << left.channels() << endl;
|
||||
d_left.upload(left);
|
||||
d_right.upload(right);
|
||||
imshow("left", left);
|
||||
imshow("right", right);
|
||||
}
|
||||
bm(d_left, d_right, d_disp);
|
||||
break;
|
||||
case Params::BP:
|
||||
bp(d_left, d_right, d_disp);
|
||||
break;
|
||||
case Params::CSBP:
|
||||
csbp(d_left, d_right, d_disp);
|
||||
break;
|
||||
}
|
||||
ocl::finish();
|
||||
workEnd();
|
||||
|
||||
// Show results
|
||||
d_disp.download(disp);
|
||||
if (p.method != Params::BM)
|
||||
{
|
||||
disp.convertTo(disp, 0);
|
||||
}
|
||||
putText(disp, text(), Point(5, 25), FONT_HERSHEY_SIMPLEX, 1.0, Scalar::all(255));
|
||||
imshow("disparity", disp);
|
||||
|
||||
handleKey((char)waitKey(3));
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
void App::printParams() const
|
||||
{
|
||||
cout << "--- Parameters ---\n";
|
||||
cout << "image_size: (" << left.cols << ", " << left.rows << ")\n";
|
||||
cout << "image_channels: " << left.channels() << endl;
|
||||
cout << "method: " << p.method_str() << endl
|
||||
<< "ndisp: " << p.ndisp << endl;
|
||||
switch (p.method)
|
||||
{
|
||||
case Params::BM:
|
||||
cout << "win_size: " << bm.winSize << endl;
|
||||
cout << "prefilter_sobel: " << bm.preset << endl;
|
||||
break;
|
||||
case Params::BP:
|
||||
cout << "iter_count: " << bp.iters << endl;
|
||||
cout << "level_count: " << bp.levels << endl;
|
||||
break;
|
||||
case Params::CSBP:
|
||||
cout << "iter_count: " << csbp.iters << endl;
|
||||
cout << "level_count: " << csbp.levels << endl;
|
||||
break;
|
||||
}
|
||||
cout << endl;
|
||||
}
|
||||
|
||||
|
||||
void App::handleKey(char key)
|
||||
{
|
||||
switch (key)
|
||||
{
|
||||
case 27:
|
||||
running = false;
|
||||
break;
|
||||
case 'p': case 'P':
|
||||
printParams();
|
||||
break;
|
||||
case 'g': case 'G':
|
||||
if (left.channels() == 1 && p.method != Params::BM)
|
||||
{
|
||||
left = left_src;
|
||||
right = right_src;
|
||||
}
|
||||
else
|
||||
{
|
||||
cvtColor(left_src, left, CV_BGR2GRAY);
|
||||
cvtColor(right_src, right, CV_BGR2GRAY);
|
||||
}
|
||||
d_left.upload(left);
|
||||
d_right.upload(right);
|
||||
cout << "image_channels: " << left.channels() << endl;
|
||||
imshow("left", left);
|
||||
imshow("right", right);
|
||||
break;
|
||||
case 'm': case 'M':
|
||||
switch (p.method)
|
||||
{
|
||||
case Params::BM:
|
||||
p.method = Params::BP;
|
||||
break;
|
||||
case Params::BP:
|
||||
p.method = Params::CSBP;
|
||||
break;
|
||||
case Params::CSBP:
|
||||
p.method = Params::BM;
|
||||
break;
|
||||
}
|
||||
cout << "method: " << p.method_str() << endl;
|
||||
break;
|
||||
case 's': case 'S':
|
||||
if (p.method == Params::BM)
|
||||
{
|
||||
switch (bm.preset)
|
||||
{
|
||||
case StereoBM_OCL::BASIC_PRESET:
|
||||
bm.preset = StereoBM_OCL::PREFILTER_XSOBEL;
|
||||
break;
|
||||
case StereoBM_OCL::PREFILTER_XSOBEL:
|
||||
bm.preset = StereoBM_OCL::BASIC_PRESET;
|
||||
break;
|
||||
}
|
||||
cout << "prefilter_sobel: " << bm.preset << endl;
|
||||
}
|
||||
break;
|
||||
case '1':
|
||||
p.ndisp = p.ndisp == 1 ? 8 : p.ndisp + 8;
|
||||
cout << "ndisp: " << p.ndisp << endl;
|
||||
bm.ndisp = p.ndisp;
|
||||
bp.ndisp = p.ndisp;
|
||||
csbp.ndisp = p.ndisp;
|
||||
break;
|
||||
case 'q': case 'Q':
|
||||
p.ndisp = max(p.ndisp - 8, 1);
|
||||
cout << "ndisp: " << p.ndisp << endl;
|
||||
bm.ndisp = p.ndisp;
|
||||
bp.ndisp = p.ndisp;
|
||||
csbp.ndisp = p.ndisp;
|
||||
break;
|
||||
case '2':
|
||||
if (p.method == Params::BM)
|
||||
{
|
||||
bm.winSize = min(bm.winSize + 1, 51);
|
||||
cout << "win_size: " << bm.winSize << endl;
|
||||
}
|
||||
break;
|
||||
case 'w': case 'W':
|
||||
if (p.method == Params::BM)
|
||||
{
|
||||
bm.winSize = max(bm.winSize - 1, 2);
|
||||
cout << "win_size: " << bm.winSize << endl;
|
||||
}
|
||||
break;
|
||||
case '3':
|
||||
if (p.method == Params::BP)
|
||||
{
|
||||
bp.iters += 1;
|
||||
cout << "iter_count: " << bp.iters << endl;
|
||||
}
|
||||
else if (p.method == Params::CSBP)
|
||||
{
|
||||
csbp.iters += 1;
|
||||
cout << "iter_count: " << csbp.iters << endl;
|
||||
}
|
||||
break;
|
||||
case 'e': case 'E':
|
||||
if (p.method == Params::BP)
|
||||
{
|
||||
bp.iters = max(bp.iters - 1, 1);
|
||||
cout << "iter_count: " << bp.iters << endl;
|
||||
}
|
||||
else if (p.method == Params::CSBP)
|
||||
{
|
||||
csbp.iters = max(csbp.iters - 1, 1);
|
||||
cout << "iter_count: " << csbp.iters << endl;
|
||||
}
|
||||
break;
|
||||
case '4':
|
||||
if (p.method == Params::BP)
|
||||
{
|
||||
bp.levels += 1;
|
||||
cout << "level_count: " << bp.levels << endl;
|
||||
}
|
||||
else if (p.method == Params::CSBP)
|
||||
{
|
||||
csbp.levels += 1;
|
||||
cout << "level_count: " << csbp.levels << endl;
|
||||
}
|
||||
break;
|
||||
case 'r': case 'R':
|
||||
if (p.method == Params::BP)
|
||||
{
|
||||
bp.levels = max(bp.levels - 1, 1);
|
||||
cout << "level_count: " << bp.levels << endl;
|
||||
}
|
||||
else if (p.method == Params::CSBP)
|
||||
{
|
||||
csbp.levels = max(csbp.levels - 1, 1);
|
||||
cout << "level_count: " << csbp.levels << endl;
|
||||
}
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
Loading…
Reference in New Issue
Block a user