-//This sample is inherited from facedetect.cpp in smaple/c
-
#include "opencv2/objdetect/objdetect.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
using namespace std;
using namespace cv;
+#define LOOP_NUM 10
+
+const static Scalar colors[] = { CV_RGB(0,0,255),
+ CV_RGB(0,128,255),
+ CV_RGB(0,255,255),
+ CV_RGB(0,255,0),
+ CV_RGB(255,128,0),
+ CV_RGB(255,255,0),
+ CV_RGB(255,0,0),
+ CV_RGB(255,0,255)} ;
-static void help()
+int64 work_begin = 0;
+int64 work_end = 0;
+
+static void workBegin()
+{
+ work_begin = getTickCount();
+}
+static void workEnd()
{
- cout << "\nThis program demonstrates the cascade recognizer.\n"
- "This classifier can recognize many ~rigid objects, it's most known use is for faces.\n"
- "Usage:\n"
- "./facedetect [--cascade=<cascade_path> this is the primary trained classifier such as frontal face]\n"
- " [--scale=<image scale greater or equal to 1, try 1.3 for example>\n"
- " [filename|camera_index]\n\n"
- "see facedetect.cmd for one call:\n"
- "./facedetect --cascade=\"../../data/haarcascades/haarcascade_frontalface_alt.xml\" --scale=1.3 \n"
- "Hit any key to quit.\n"
- "Using OpenCV version " << CV_VERSION << "\n" << endl;
+ work_end += (getTickCount() - work_begin);
}
-struct getRect { Rect operator ()(const CvAvgComp& e) const { return e.rect; } };
-void detectAndDraw( Mat& img,
- cv::ocl::OclCascadeClassifier& cascade, CascadeClassifier& nestedCascade,
- double scale);
+static double getTime(){
+ return work_end /((double)cvGetTickFrequency() * 1000.);
+}
+
+void detect( Mat& img, vector<Rect>& faces,
+ cv::ocl::OclCascadeClassifierBuf& cascade,
+ double scale, bool calTime);
-String cascadeName = "../../../data/haarcascades/haarcascade_frontalface_alt.xml";
+void detectCPU( Mat& img, vector<Rect>& faces,
+ CascadeClassifier& cascade,
+ double scale, bool calTime);
+
+void Draw(Mat& img, vector<Rect>& faces, double scale);
+
+// 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);
int main( int argc, const char** argv )
{
- CvCapture* capture = 0;
- Mat frame, frameCopy, image;
- const String scaleOpt = "--scale=";
- size_t scaleOptLen = scaleOpt.length();
- const String cascadeOpt = "--cascade=";
- size_t cascadeOptLen = cascadeOpt.length();
- String inputName;
-
- help();
- cv::ocl::OclCascadeClassifier cascade;
- CascadeClassifier nestedCascade;
- double scale = 1;
-
- for( int i = 1; i < argc; i++ )
+ const char* keys =
+ "{ h | help | false | print help message }"
+ "{ i | input | | specify input image }"
+ "{ t | template | ../../../data/haarcascades/haarcascade_frontalface_alt.xml | specify template file }"
+ "{ c | scale | 1.0 | scale image }"
+ "{ s | use_cpu | false | use cpu or gpu to process the image }";
+
+ CommandLineParser cmd(argc, argv, keys);
+ if (cmd.get<bool>("help"))
{
- cout << "Processing " << i << " " << argv[i] << endl;
- if( cascadeOpt.compare( 0, cascadeOptLen, argv[i], cascadeOptLen ) == 0 )
- {
- cascadeName.assign( argv[i] + cascadeOptLen );
- cout << " from which we have cascadeName= " << cascadeName << endl;
- }
- else if( scaleOpt.compare( 0, scaleOptLen, argv[i], scaleOptLen ) == 0 )
- {
- if( !sscanf( argv[i] + scaleOpt.length(), "%lf", &scale ) || scale < 1 )
- scale = 1;
- cout << " from which we read scale = " << scale << endl;
- }
- else if( argv[i][0] == '-' )
- {
- cerr << "WARNING: Unknown option %s" << argv[i] << endl;
- }
- else
- inputName.assign( argv[i] );
+ cout << "Avaible options:" << endl;
+ cmd.printParams();
+ return 0;
}
+ CvCapture* capture = 0;
+ Mat frame, frameCopy, image;
- if( !cascade.load( cascadeName ) )
+ bool useCPU = cmd.get<bool>("s");
+ string inputName = cmd.get<string>("i");
+ string cascadeName = cmd.get<string>("t");
+ double scale = cmd.get<double>("c");
+ cv::ocl::OclCascadeClassifierBuf cascade;
+ CascadeClassifier cpu_cascade;
+
+ if( !cascade.load( cascadeName ) || !cpu_cascade.load(cascadeName) )
{
cerr << "ERROR: Could not load classifier cascade" << endl;
- cerr << "Usage: facedetect [--cascade=<cascade_path>]\n"
- " [--scale[=<image scale>\n"
- " [filename|camera_index]\n" << endl ;
return -1;
}
- if( inputName.empty() || (isdigit(inputName.c_str()[0]) && inputName.c_str()[1] == '\0') )
+ if( inputName.empty() )
{
- capture = cvCaptureFromCAM( inputName.empty() ? 0 : inputName.c_str()[0] - '0' );
- int c = inputName.empty() ? 0 : inputName.c_str()[0] - '0' ;
- if(!capture) cout << "Capture from CAM " << c << " didn't work" << endl;
+ capture = cvCaptureFromCAM(0);
+ if(!capture)
+ cout << "Capture from CAM 0 didn't work" << endl;
}
else if( inputName.size() )
{
if( image.empty() )
{
capture = cvCaptureFromAVI( inputName.c_str() );
- if(!capture) cout << "Capture from AVI didn't work" << endl;
+ if(!capture)
+ cout << "Capture from AVI didn't work" << endl;
+ return -1;
}
}
else
{
image = imread( "lena.jpg", 1 );
- if(image.empty()) cout << "Couldn't read lena.jpg" << endl;
+ if(image.empty())
+ cout << "Couldn't read lena.jpg" << endl;
+ return -1;
}
cvNamedWindow( "result", 1 );
std::vector<cv::ocl::Info> oclinfo;
int devnums = cv::ocl::getDevice(oclinfo);
- if(devnums<1)
+ if( devnums < 1 )
{
std::cout << "no device found\n";
return -1;
}
//if you want to use undefault device, set it here
//setDevice(oclinfo[0]);
- //setBinpath(CLBINPATH);
+ ocl::setBinpath("./");
if( capture )
{
cout << "In capture ..." << endl;
{
IplImage* iplImg = cvQueryFrame( capture );
frame = iplImg;
+ vector<Rect> faces;
if( frame.empty() )
break;
if( iplImg->origin == IPL_ORIGIN_TL )
frame.copyTo( frameCopy );
else
flip( frame, frameCopy, 0 );
-
- detectAndDraw( frameCopy, cascade, nestedCascade, scale );
-
+ if(useCPU){
+ detectCPU(frameCopy, faces, cpu_cascade, scale, false);
+ }
+ else{
+ detect(frameCopy, faces, cascade, scale, false);
+ }
+ Draw(frameCopy, faces, scale);
if( waitKey( 10 ) >= 0 )
goto _cleanup_;
}
else
{
cout << "In image read" << endl;
- if( !image.empty() )
- {
- detectAndDraw( image, cascade, nestedCascade, scale );
- waitKey(0);
- }
- else if( !inputName.empty() )
+ vector<Rect> faces;
+ vector<Rect> ref_rst;
+ double accuracy = 0.;
+ for(int i = 0; i <= LOOP_NUM;i ++)
{
- /* assume it is a text file containing the
- list of the image filenames to be processed - one per line */
- FILE* f = fopen( inputName.c_str(), "rt" );
- if( f )
+ cout << "loop" << i << endl;
+ if(useCPU){
+ detectCPU(image, faces, cpu_cascade, scale, i==0?false:true);
+ }
+ else{
+ detect(image, faces, cascade, scale, i==0?false:true);
+ if(i == 0){
+ detectCPU(image, ref_rst, cpu_cascade, scale, false);
+ accuracy = checkRectSimilarity(image.size(), ref_rst, faces);
+ }
+ }
+ if (i == LOOP_NUM)
{
- char buf[1000+1];
- while( fgets( buf, 1000, f ) )
- {
- int len = (int)strlen(buf), c;
- while( len > 0 && isspace(buf[len-1]) )
- len--;
- buf[len] = '\0';
- cout << "file " << buf << endl;
- image = imread( buf, 1 );
- if( !image.empty() )
- {
- detectAndDraw( image, cascade, nestedCascade, scale );
- c = waitKey(0);
- if( c == 27 || c == 'q' || c == 'Q' )
- break;
- }
- else
- {
- cerr << "Aw snap, couldn't read image " << buf << endl;
- }
- }
- fclose(f);
+ if (useCPU)
+ cout << "average CPU time (noCamera) : ";
+ else
+ cout << "average GPU time (noCamera) : ";
+ cout << getTime() / LOOP_NUM << " ms" << endl;
+ cout << "accuracy value: " << accuracy <<endl;
}
}
+ Draw(image, faces, scale);
+ waitKey(0);
}
cvDestroyWindow("result");
return 0;
}
-void detectAndDraw( Mat& img,
- cv::ocl::OclCascadeClassifier& cascade, CascadeClassifier&,
- double scale)
+void detect( Mat& img, vector<Rect>& faces,
+ cv::ocl::OclCascadeClassifierBuf& cascade,
+ double scale, bool calTime)
{
- int i = 0;
- double t = 0;
- vector<Rect> faces;
- const static Scalar colors[] = { CV_RGB(0,0,255),
- CV_RGB(0,128,255),
- CV_RGB(0,255,255),
- CV_RGB(0,255,0),
- CV_RGB(255,128,0),
- CV_RGB(255,255,0),
- CV_RGB(255,0,0),
- CV_RGB(255,0,255)} ;
cv::ocl::oclMat image(img);
cv::ocl::oclMat gray, smallImg( cvRound (img.rows/scale), cvRound(img.cols/scale), CV_8UC1 );
-
+ if(calTime) workBegin();
cv::ocl::cvtColor( image, gray, CV_BGR2GRAY );
cv::ocl::resize( gray, smallImg, smallImg.size(), 0, 0, INTER_LINEAR );
cv::ocl::equalizeHist( smallImg, smallImg );
- CvSeq* _objects;
- MemStorage storage(cvCreateMemStorage(0));
- t = (double)cvGetTickCount();
- _objects = cascade.oclHaarDetectObjects( smallImg, storage, 1.1,
+ cascade.detectMultiScale( smallImg, faces, 1.1,
3, 0
|CV_HAAR_SCALE_IMAGE
, Size(30,30), Size(0, 0) );
- vector<CvAvgComp> vecAvgComp;
- Seq<CvAvgComp>(_objects).copyTo(vecAvgComp);
- faces.resize(vecAvgComp.size());
- std::transform(vecAvgComp.begin(), vecAvgComp.end(), faces.begin(), getRect());
- t = (double)cvGetTickCount() - t;
- printf( "detection time = %g ms\n", t/((double)cvGetTickFrequency()*1000.) );
+ if(calTime) workEnd();
+}
+
+void detectCPU( Mat& img, vector<Rect>& faces,
+ CascadeClassifier& cascade,
+ double scale, bool calTime)
+{
+ if(calTime) workBegin();
+ Mat cpu_gray, cpu_smallImg( cvRound (img.rows/scale), cvRound(img.cols/scale), CV_8UC1 );
+ cvtColor(img, cpu_gray, CV_BGR2GRAY);
+ resize(cpu_gray, cpu_smallImg, cpu_smallImg.size(), 0, 0, INTER_LINEAR);
+ equalizeHist(cpu_smallImg, cpu_smallImg);
+ cascade.detectMultiScale(cpu_smallImg, faces, 1.1,
+ 3, 0 | CV_HAAR_SCALE_IMAGE,
+ Size(30, 30), Size(0, 0));
+ if(calTime) workEnd();
+}
+
+void Draw(Mat& img, vector<Rect>& faces, double scale)
+{
+ int i = 0;
for( vector<Rect>::const_iterator r = faces.begin(); r != faces.end(); r++, i++ )
{
- Mat smallImgROI;
Point center;
Scalar color = colors[i%8];
int radius;
}
cv::imshow( "result", img );
}
+
+double 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;
+}
bool gamma_corr;
};
-
class App
{
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&);
ocl::oclMat gpu_img;
// Iterate over all frames
+ bool verify = false;
while (running && !frame.empty())
{
workBegin();
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();
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;
+
+}
+
projects / platform / upstream / opencv.git / commitdiff