• niko's avatar
    use mutex provided by opencv itself · 6f6e9909
    niko authored
    add getoclcontext and getoclcommandqueue so that other opencl program can interactive with opencv ocl module
    correct haar test cases
    add face detection sample
    6f6e9909
facedetect.cpp 6.31 KB
//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"
#include "opencv2/ocl/ocl.hpp"
#include <iostream>
#include <stdio.h>

using namespace std;
using namespace cv;

void help()
{
	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;
}
struct getRect { Rect operator ()(const CvAvgComp& e) const { return e.rect; } };
void detectAndDraw( Mat& img,
	cv::ocl::OclCascadeClassifier& cascade, CascadeClassifier& nestedCascade,
	double scale);

String cascadeName = "../../../data/haarcascades/haarcascade_frontalface_alt.xml";

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++ )
	{
		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] );
	}

	if( !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') )
	{
		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;
	}
	else if( inputName.size() )
	{
		image = imread( inputName, 1 );
		if( image.empty() )
		{
			capture = cvCaptureFromAVI( inputName.c_str() );
			if(!capture) cout << "Capture from AVI didn't work" << endl;
		}
	}
	else
	{
		image = imread( "lena.jpg", 1 );
		if(image.empty()) cout << "Couldn't read lena.jpg" << endl;
	}

	cvNamedWindow( "result", 1 );
	std::vector<cv::ocl::Info> oclinfo;
	int devnums = cv::ocl::getDevice(oclinfo);
	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);
	if( capture )
	{
		cout << "In capture ..." << endl;
		for(;;)
		{
			IplImage* iplImg = cvQueryFrame( capture );
			frame = iplImg;
			if( frame.empty() )
				break;
			if( iplImg->origin == IPL_ORIGIN_TL )
				frame.copyTo( frameCopy );
			else
				flip( frame, frameCopy, 0 );

			detectAndDraw( frameCopy, cascade, nestedCascade, scale );

			if( waitKey( 10 ) >= 0 )
				goto _cleanup_;
		}

		waitKey(0);

_cleanup_:
		cvReleaseCapture( &capture );
	}
	else
	{
		cout << "In image read" << endl;
		if( !image.empty() )
		{
			detectAndDraw( image, cascade, nestedCascade, scale );
			waitKey(0);
		}
		else if( !inputName.empty() )
		{
			/* 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 )
			{
				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);
			}
		}
	}

	cvDestroyWindow("result");

	return 0;
}

void detectAndDraw( Mat& img,
	cv::ocl::OclCascadeClassifier& cascade, CascadeClassifier& nestedCascade,
	double scale)
{
	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 );

	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,
		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.) );
	for( vector<Rect>::const_iterator r = faces.begin(); r != faces.end(); r++, i++ )
	{
		Mat smallImgROI;
		Point center;
		Scalar color = colors[i%8];
		int radius;
		center.x = cvRound((r->x + r->width*0.5)*scale);
		center.y = cvRound((r->y + r->height*0.5)*scale);
		radius = cvRound((r->width + r->height)*0.25*scale);
		circle( img, center, radius, color, 3, 8, 0 );
	}
	cv::imshow( "result", img );
}