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add results verification to facedetect and hog samples
This commit is contained in:
yao
parent
036b0579f1
commit
fad96b95ad
@ -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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{
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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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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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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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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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}
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if (i == LOOP_NUM)
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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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}
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fclose(f);
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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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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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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);
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for(vector<Rect>::const_iterator r2 = ob2.begin(); r2 != ob2.end(); r2++)
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{
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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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}
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cv::Mat result_;
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multiply(cpu_result, gpu_result, result_);
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int result = cv::countNonZero(result_ > 0);
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final_test_result = 1.0 - (double)result/(double)cpu_area;
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}
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return final_test_result;
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}
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@ -45,7 +45,6 @@ public:
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bool gamma_corr;
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};
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class App
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{
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public:
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@ -64,6 +63,13 @@ public:
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string message() const;
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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
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// (total diff of each cpu and gpu rects covered pixels)/(total cpu rects covered pixels)
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double checkRectSimilarity(Size sz,
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std::vector<Rect>& cpu_rst,
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std::vector<Rect>& gpu_rst);
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private:
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App operator=(App&);
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@ -290,6 +296,7 @@ void App::run()
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ocl::oclMat gpu_img;
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// Iterate over all frames
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bool verify = false;
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while (running && !frame.empty())
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{
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workBegin();
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@ -316,7 +323,18 @@ void App::run()
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gpu_img.upload(img);
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gpu_hog.detectMultiScale(gpu_img, found, hit_threshold, win_stride,
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Size(0, 0), scale, gr_threshold);
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}
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if (!verify)
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{
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// verify if GPU output same objects with CPU at 1st run
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verify = true;
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vector<Rect> ref_rst;
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cvtColor(img, img, CV_BGRA2BGR);
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cpu_hog.detectMultiScale(img, ref_rst, hit_threshold, win_stride,
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Size(0, 0), scale, gr_threshold-2);
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double accuracy = checkRectSimilarity(img.size(), ref_rst, found);
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cout << "\naccuracy value: " << accuracy << endl;
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}
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}
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else cpu_hog.detectMultiScale(img, found, hit_threshold, win_stride,
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Size(0, 0), scale, gr_threshold);
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hogWorkEnd();
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@ -457,3 +475,45 @@ inline string App::workFps() const
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return ss.str();
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}
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double App::checkRectSimilarity(Size sz,
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std::vector<Rect>& ob1,
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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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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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{
|
||||
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;
|
||||
|
||||
}
|
||||
|
||||
|
||||
Loading…
Reference in New Issue
Block a user