Merge branch 'master' of git://code.opencv.org/opencv
This commit is contained in:
@@ -107,7 +107,6 @@ endif()
|
||||
|
||||
if(WIN32)
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||||
list(APPEND highgui_srcs src/cap_vfw.cpp src/cap_cmu.cpp src/cap_dshow.cpp)
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list(APPEND HIGHGUI_LIBRARIES vfw32)
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||||
endif(WIN32)
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||||
|
||||
if(HAVE_XINE)
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||||
|
@@ -88,7 +88,10 @@ namespace cv
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//CV_EXPORTS void getComputeCapability(cl_device_id device, int &major, int &minor);
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//optional function, if you want save opencl binary kernel to the file, set its path
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CV_EXPORTS void setBinpath(const char *path);
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||||
|
||||
//The two functions below are used to get opencl runtime so that opencv can interactive with
|
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//other opencl program
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||||
CV_EXPORTS void* getoclContext();
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CV_EXPORTS void* getoclCommandQueue();
|
||||
//////////////////////////////// Error handling ////////////////////////
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||||
CV_EXPORTS void error(const char *error_string, const char *file, const int line, const char *func);
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||||
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||||
|
@@ -58,141 +58,113 @@ struct getRect { Rect operator ()(const CvAvgComp& e) const { return e.rect; } }
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PARAM_TEST_CASE(HaarTestBase, int, int)
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{
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||||
//std::vector<cv::ocl::Info> oclinfo;
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cv::ocl::OclCascadeClassifier cascade, nestedCascade;
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cv::ocl::OclCascadeClassifier cascade, nestedCascade;
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cv::CascadeClassifier cpucascade, cpunestedCascade;
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// Mat img;
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// Mat img;
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||||
double scale;
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||||
int index;
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double scale;
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int index;
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||||
|
||||
virtual void SetUp()
|
||||
{
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||||
scale = 1.1;
|
||||
virtual void SetUp()
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||||
{
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scale = 1.0;
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index=0;
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string cascadeName="../../../data/haarcascades/haarcascade_frontalface_alt.xml";
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||||
|
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#if WIN32
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string cascadeName="E:\\opencvbuffer\\trunk\\data\\haarcascades\\haarcascade_frontalface_alt.xml";
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#else
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string cascadeName="../data/haarcascades/haarcascade_frontalface_alt.xml";
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#endif
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|
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if( (!cascade.load( cascadeName )) || (!cpucascade.load(cascadeName)))
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||||
{
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cout << "ERROR: Could not load classifier cascade" << endl;
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cout << "Usage: facedetect [--cascade=<cascade_path>]\n"
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" [--nested-cascade[=nested_cascade_path]]\n"
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" [--scale[=<image scale>\n"
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" [filename|camera_index]\n" << endl ;
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|
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return;
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}
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||||
//int devnums = getDevice(oclinfo);
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//CV_Assert(devnums>0);
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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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//cv::ocl::setBinpath("E:\\");
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}
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if( (!cascade.load( cascadeName )) || (!cpucascade.load(cascadeName)))
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{
|
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cout << "ERROR: Could not load classifier cascade" << endl;
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cout << "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;
|
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}
|
||||
//int devnums = getDevice(oclinfo);
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||||
//CV_Assert(devnums>0);
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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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//cv::ocl::setBinpath("E:\\");
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}
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};
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////////////////////////////////faceDetect/////////////////////////////////////////////////
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struct Haar : HaarTestBase {};
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TEST_P(Haar, FaceDetect)
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TEST_F(Haar, FaceDetect)
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{
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for(int index = 1;index < 2; index++)
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{
|
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Mat img;
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char buff[256];
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||||
#if WIN32
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sprintf(buff,"E:\\myDataBase\\%d.jpg",index);
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img = imread( buff, 1 );
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#else
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sprintf(buff,"%d.jpg",index);
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img = imread( buff, 1 );
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std::cout << "Now test " << index << ".jpg" <<std::endl;
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#endif
|
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if(img.empty())
|
||||
{
|
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std::cout << "Couldn't read test" << index <<".jpg" << std::endl;
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continue;
|
||||
}
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string imgName = "../../../samples/c/lena.jpg";
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Mat img = imread( imgName, 1 );
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||||
|
||||
int i = 0;
|
||||
double t = 0;
|
||||
vector<Rect> faces;
|
||||
if(img.empty())
|
||||
{
|
||||
std::cout << "Couldn't read test" << index <<".jpg" << std::endl;
|
||||
return ;
|
||||
}
|
||||
|
||||
const static Scalar colors[] = { CV_RGB(0,0,255),
|
||||
CV_RGB(0,128,255),
|
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CV_RGB(0,255,255),
|
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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)} ;
|
||||
int i = 0;
|
||||
double t = 0;
|
||||
vector<Rect> faces, oclfaces;
|
||||
|
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Mat gray, smallImg(cvRound (img.rows/scale), cvRound(img.cols/scale), CV_8UC1 );
|
||||
MemStorage storage(cvCreateMemStorage(0));
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cvtColor( img, gray, CV_BGR2GRAY );
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resize( gray, smallImg, smallImg.size(), 0, 0, INTER_LINEAR );
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equalizeHist( smallImg, smallImg );
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CvMat _image = smallImg;
|
||||
const static Scalar colors[] = { CV_RGB(0,0,255),
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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)} ;
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||||
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||||
Mat tempimg(&_image, false);
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Mat gray, smallImg(cvRound (img.rows/scale), cvRound(img.cols/scale), CV_8UC1 );
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MemStorage storage(cvCreateMemStorage(0));
|
||||
cvtColor( img, gray, CV_BGR2GRAY );
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resize( gray, smallImg, smallImg.size(), 0, 0, INTER_LINEAR );
|
||||
equalizeHist( smallImg, smallImg );
|
||||
|
||||
cv::ocl::oclMat image(tempimg);
|
||||
CvSeq* _objects;
|
||||
t = (double)cvGetTickCount();
|
||||
for(int k= 0; k<LOOP_TIMES; k++)
|
||||
{
|
||||
cpucascade.detectMultiScale( smallImg, faces, 1.1,
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||||
3, 0
|
||||
|CV_HAAR_SCALE_IMAGE
|
||||
, Size(30,30), Size(0, 0) );
|
||||
}
|
||||
t = (double)cvGetTickCount() - t ;
|
||||
printf( "cpudetection time = %g ms\n", t/(LOOP_TIMES*(double)cvGetTickFrequency()*1000.) );
|
||||
|
||||
#if 1
|
||||
for(int k= 0; k<10; k++)
|
||||
{
|
||||
t = (double)cvGetTickCount();
|
||||
_objects = cascade.oclHaarDetectObjects( image, storage, 1.1,
|
||||
2, 0
|
||||
|CV_HAAR_SCALE_IMAGE
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||||
, Size(30,30), Size(0, 0) );
|
||||
cv::ocl::oclMat image;
|
||||
CvSeq* _objects;
|
||||
t = (double)cvGetTickCount();
|
||||
for(int k= 0; k<LOOP_TIMES; k++)
|
||||
{
|
||||
image.upload(smallImg);
|
||||
_objects = cascade.oclHaarDetectObjects( image, storage, 1.1,
|
||||
3, 0
|
||||
|CV_HAAR_SCALE_IMAGE
|
||||
, Size(30,30), Size(0, 0) );
|
||||
}
|
||||
t = (double)cvGetTickCount() - t ;
|
||||
printf( "ocldetection time = %g ms\n", t/(LOOP_TIMES*(double)cvGetTickFrequency()*1000.) );
|
||||
vector<CvAvgComp> vecAvgComp;
|
||||
Seq<CvAvgComp>(_objects).copyTo(vecAvgComp);
|
||||
oclfaces.resize(vecAvgComp.size());
|
||||
std::transform(vecAvgComp.begin(), vecAvgComp.end(), oclfaces.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;
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||||
// 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 );
|
||||
//}
|
||||
//namedWindow("result");
|
||||
//imshow("result",img);
|
||||
//waitKey(0);
|
||||
//destroyAllWindows();
|
||||
|
||||
#else
|
||||
cpucascade.detectMultiScale( image, faces, 1.1,
|
||||
2, 0
|
||||
|CV_HAAR_SCALE_IMAGE
|
||||
, Size(30,30), Size(0, 0) );
|
||||
|
||||
#endif
|
||||
vector<CvAvgComp> vecAvgComp;
|
||||
Seq<CvAvgComp>(_objects).copyTo(vecAvgComp);
|
||||
faces.resize(vecAvgComp.size());
|
||||
std::transform(vecAvgComp.begin(), vecAvgComp.end(), faces.begin(), getRect());
|
||||
|
||||
for( vector<Rect>::const_iterator r = faces.begin(); r != faces.end(); r++, i++ )
|
||||
{
|
||||
Mat smallImgROI;
|
||||
vector<Rect> nestedObjects;
|
||||
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 );
|
||||
}
|
||||
|
||||
#if WIN32
|
||||
sprintf(buff,"E:\\result1\\%d.jpg",index);
|
||||
imwrite(buff,img);
|
||||
#else
|
||||
sprintf(buff,"testdet_%d.jpg",index);
|
||||
imwrite(buff,img);
|
||||
#endif
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
//INSTANTIATE_TEST_CASE_P(HaarTestBase, Haar, Combine(Values(1),
|
||||
// Values(1)));
|
||||
|
||||
|
||||
#endif // HAVE_OPENCL
|
||||
|
@@ -45,10 +45,10 @@
|
||||
#ifdef PRINT_KERNEL_RUN_TIME
|
||||
#define LOOP_TIMES 1
|
||||
#else
|
||||
#define LOOP_TIMES 1
|
||||
#define LOOP_TIMES 100
|
||||
#endif
|
||||
#define MWIDTH 256
|
||||
#define MHEIGHT 256
|
||||
#define MWIDTH 1920
|
||||
#define MHEIGHT 1080
|
||||
#define CLBINPATH ".\\"
|
||||
#define LOOPROISTART 0
|
||||
#define LOOPROIEND 1
|
||||
|
@@ -44,7 +44,6 @@
|
||||
//M*/
|
||||
|
||||
#include "precomp.hpp"
|
||||
#include "threadsafe.h"
|
||||
#include <iomanip>
|
||||
#include "binarycaching.hpp"
|
||||
|
||||
@@ -348,7 +347,14 @@ namespace cv
|
||||
}
|
||||
Context::setContext(oclinfo);
|
||||
}
|
||||
|
||||
void* getoclContext()
|
||||
{
|
||||
return &(Context::getContext()->impl->clContext);
|
||||
}
|
||||
void* getoclCommandQueue()
|
||||
{
|
||||
return &(Context::getContext()->impl->clCmdQueue);
|
||||
}
|
||||
void openCLReadBuffer(Context *clCxt, cl_mem dst_buffer, void *host_buffer, size_t size)
|
||||
{
|
||||
cl_int status;
|
||||
@@ -772,12 +778,12 @@ namespace cv
|
||||
/////////////////////////////OpenCL initialization/////////////////
|
||||
auto_ptr<Context> Context::clCxt;
|
||||
int Context::val = 0;
|
||||
CriticalSection cs;
|
||||
Mutex cs;
|
||||
Context *Context::getContext()
|
||||
{
|
||||
if(val == 0)
|
||||
{
|
||||
myAutoLock al(&cs);
|
||||
AutoLock al(cs);
|
||||
if( NULL == clCxt.get())
|
||||
clCxt.reset(new Context);
|
||||
|
||||
|
@@ -1,83 +0,0 @@
|
||||
/*M///////////////////////////////////////////////////////////////////////////////////////
|
||||
//
|
||||
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
|
||||
//
|
||||
// By downloading, copying, installing or using the software you agree to this license.
|
||||
// If you do not agree to this license, do not download, install,
|
||||
// copy or use the software.
|
||||
//
|
||||
//
|
||||
// License Agreement
|
||||
// For Open Source Computer Vision Library
|
||||
//
|
||||
// Copyright (C) 2010-2012, Institute Of Software Chinese Academy Of Science, all rights reserved.
|
||||
// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
|
||||
// Third party copyrights are property of their respective owners.
|
||||
//
|
||||
// @Authors
|
||||
// Niko Li, newlife20080214@gmail.com
|
||||
//
|
||||
// Redistribution and use in source and binary forms, with or without modification,
|
||||
// are permitted provided that the following conditions are met:
|
||||
//
|
||||
// * Redistribution's of source code must retain the above copyright notice,
|
||||
// this list of conditions and the following disclaimer.
|
||||
//
|
||||
// * Redistribution's in binary form must reproduce the above copyright notice,
|
||||
// this list of conditions and the following disclaimer in the documentation
|
||||
// and/or other oclMaterials provided with the distribution.
|
||||
//
|
||||
// * The name of the copyright holders may not be used to endorse or promote products
|
||||
// derived from this software without specific prior written permission.
|
||||
//
|
||||
// This software is provided by the copyright holders and contributors "as is" and
|
||||
// any express or implied warranties, including, but not limited to, the implied
|
||||
// warranties of merchantability and fitness for a particular purpose are disclaimed.
|
||||
// In no event shall the Intel Corporation or contributors be liable for any direct,
|
||||
// indirect, incidental, special, exemplary, or consequential damages
|
||||
// (including, but not limited to, procurement of substitute goods or services;
|
||||
// loss of use, data, or profits; or business interruption) however caused
|
||||
// and on any theory of liability, whether in contract, strict liability,
|
||||
// or tort (including negligence or otherwise) arising in any way out of
|
||||
// the use of this software, even if advised of the possibility of such damage.
|
||||
//
|
||||
//M*/
|
||||
|
||||
//#include "precomp.hpp"
|
||||
#include "threadsafe.h"
|
||||
|
||||
CriticalSection::CriticalSection()
|
||||
{
|
||||
#if defined WIN32 || defined _WIN32
|
||||
InitializeCriticalSection(&m_CritSec);
|
||||
#else
|
||||
pthread_mutex_init(&m_CritSec, NULL);
|
||||
#endif
|
||||
}
|
||||
|
||||
CriticalSection::~CriticalSection()
|
||||
{
|
||||
#if defined WIN32 || defined _WIN32
|
||||
DeleteCriticalSection(&m_CritSec);
|
||||
#else
|
||||
pthread_mutex_destroy(&m_CritSec);
|
||||
#endif
|
||||
}
|
||||
|
||||
void CriticalSection::Lock()
|
||||
{
|
||||
#if defined WIN32 || defined _WIN32
|
||||
EnterCriticalSection(&m_CritSec);
|
||||
#else
|
||||
pthread_mutex_lock(&m_CritSec);
|
||||
#endif
|
||||
}
|
||||
|
||||
void CriticalSection::Unlock()
|
||||
{
|
||||
#if defined WIN32 || defined _WIN32
|
||||
LeaveCriticalSection(&m_CritSec);
|
||||
#else
|
||||
pthread_mutex_unlock(&m_CritSec);
|
||||
#endif
|
||||
}
|
@@ -1,92 +0,0 @@
|
||||
/*M///////////////////////////////////////////////////////////////////////////////////////
|
||||
//
|
||||
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
|
||||
//
|
||||
// By downloading, copying, installing or using the software you agree to this license.
|
||||
// If you do not agree to this license, do not download, install,
|
||||
// copy or use the software.
|
||||
//
|
||||
//
|
||||
// License Agreement
|
||||
// For Open Source Computer Vision Library
|
||||
//
|
||||
// Copyright (C) 2010-2012, Institute Of Software Chinese Academy Of Science, all rights reserved.
|
||||
// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
|
||||
// Third party copyrights are property of their respective owners.
|
||||
//
|
||||
//
|
||||
// Redistribution and use in source and binary forms, with or without modification,
|
||||
// are permitted provided that the following conditions are met:
|
||||
//
|
||||
// * Redistribution's of source code must retain the above copyright notice,
|
||||
// this list of conditions and the following disclaimer.
|
||||
//
|
||||
// * Redistribution's in binary form must reproduce the above copyright notice,
|
||||
// this list of conditions and the following disclaimer in the documentation
|
||||
// and/or other GpuMaterials provided with the distribution.
|
||||
//
|
||||
// * The name of the copyright holders may not be used to endorse or promote products
|
||||
// derived from this software without specific prior written permission.
|
||||
//
|
||||
// This software is provided by the copyright holders and contributors "as is" and
|
||||
// any express or implied warranties, including, but not limited to, the implied
|
||||
// warranties of merchantability and fitness for a particular purpose are disclaimed.
|
||||
// In no event shall the Intel Corporation or contributors be liable for any direct,
|
||||
// indirect, incidental, special, exemplary, or consequential damages
|
||||
// (including, but not limited to, procurement of substitute goods or services;
|
||||
// loss of use, data, or profits; or business interruption) however caused
|
||||
// and on any theory of liability, whether in contract, strict liability,
|
||||
// or tort (including negligence or otherwise) arising in any way out of
|
||||
// the use of this software, even if advised of the possibility of such damage.
|
||||
//
|
||||
//M*/
|
||||
|
||||
#if defined WIN32 || defined _WIN32
|
||||
#include <Windows.h>
|
||||
#undef min
|
||||
#undef max
|
||||
#else
|
||||
#include <pthread.h>
|
||||
#endif
|
||||
|
||||
class CriticalSection
|
||||
{
|
||||
public:
|
||||
CriticalSection();
|
||||
~CriticalSection();
|
||||
// Jia Haipeng, jiahaipeng95@gmail.com
|
||||
void Lock();
|
||||
void Unlock();
|
||||
protected:
|
||||
#if defined WIN32 || defined _WIN32
|
||||
CRITICAL_SECTION m_CritSec;
|
||||
#else
|
||||
pthread_mutex_t m_CritSec;
|
||||
#endif
|
||||
};
|
||||
|
||||
class myAutoLock
|
||||
{
|
||||
public:
|
||||
explicit myAutoLock(CriticalSection *lock)
|
||||
{
|
||||
m_lock = lock;
|
||||
m_lock->Lock();
|
||||
};
|
||||
~myAutoLock()
|
||||
{
|
||||
m_lock->Unlock();
|
||||
};
|
||||
protected:
|
||||
CriticalSection *m_lock;
|
||||
};
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
@@ -53,154 +53,107 @@ using namespace testing;
|
||||
using namespace std;
|
||||
using namespace cv;
|
||||
|
||||
struct getRect
|
||||
{
|
||||
Rect operator ()(const CvAvgComp &e) const
|
||||
{
|
||||
return e.rect;
|
||||
}
|
||||
};
|
||||
struct getRect { Rect operator ()(const CvAvgComp& e) const { return e.rect; } };
|
||||
|
||||
PARAM_TEST_CASE(HaarTestBase, int, int)
|
||||
{
|
||||
//std::vector<cv::ocl::Info> oclinfo;
|
||||
cv::ocl::OclCascadeClassifier cascade, nestedCascade;
|
||||
cv::CascadeClassifier cpucascade, cpunestedCascade;
|
||||
// Mat img;
|
||||
cv::ocl::OclCascadeClassifier cascade, nestedCascade;
|
||||
cv::CascadeClassifier cpucascade, cpunestedCascade;
|
||||
// Mat img;
|
||||
|
||||
double scale;
|
||||
int index;
|
||||
double scale;
|
||||
int index;
|
||||
|
||||
virtual void SetUp()
|
||||
{
|
||||
scale = 1.1;
|
||||
virtual void SetUp()
|
||||
{
|
||||
scale = 1.0;
|
||||
index=0;
|
||||
string cascadeName="../../../data/haarcascades/haarcascade_frontalface_alt.xml";
|
||||
|
||||
#if WIN32
|
||||
string cascadeName = "E:\\opencvbuffer\\trunk\\data\\haarcascades\\haarcascade_frontalface_alt.xml";
|
||||
#else
|
||||
string cascadeName = "../data/haarcascades/haarcascade_frontalface_alt.xml";
|
||||
#endif
|
||||
|
||||
if( (!cascade.load( cascadeName )) || (!cpucascade.load(cascadeName)))
|
||||
{
|
||||
cout << "ERROR: Could not load classifier cascade" << endl;
|
||||
cout << "Usage: facedetect [--cascade=<cascade_path>]\n"
|
||||
" [--nested-cascade[=nested_cascade_path]]\n"
|
||||
" [--scale[=<image scale>\n"
|
||||
" [filename|camera_index]\n" << endl ;
|
||||
|
||||
return;
|
||||
}
|
||||
//int devnums = getDevice(oclinfo, OPENCV_DEFAULT_OPENCL_DEVICE);
|
||||
//CV_Assert(devnums > 0);
|
||||
////if you want to use undefault device, set it here
|
||||
////setDevice(oclinfo[0]);
|
||||
//cv::ocl::setBinpath("E:\\");
|
||||
}
|
||||
if( (!cascade.load( cascadeName )) || (!cpucascade.load(cascadeName)))
|
||||
{
|
||||
cout << "ERROR: Could not load classifier cascade" << endl;
|
||||
cout << "Usage: facedetect [--cascade=<cascade_path>]\n"
|
||||
" [--scale[=<image scale>\n"
|
||||
" [filename|camera_index]\n" << endl ;
|
||||
return;
|
||||
}
|
||||
//int devnums = getDevice(oclinfo);
|
||||
//CV_Assert(devnums>0);
|
||||
////if you want to use undefault device, set it here
|
||||
////setDevice(oclinfo[0]);
|
||||
//cv::ocl::setBinpath("E:\\");
|
||||
}
|
||||
};
|
||||
|
||||
////////////////////////////////faceDetect/////////////////////////////////////////////////
|
||||
|
||||
struct Haar : HaarTestBase {};
|
||||
|
||||
TEST_P(Haar, FaceDetect)
|
||||
{
|
||||
|
||||
for(int index = 1; index < 2; index++)
|
||||
{
|
||||
Mat img;
|
||||
char buff[256];
|
||||
#if WIN32
|
||||
sprintf(buff, "E:\\myDataBase\\%d.jpg", index);
|
||||
img = imread( buff, 1 );
|
||||
#else
|
||||
sprintf(buff, "%d.jpg", index);
|
||||
img = imread( buff, 1 );
|
||||
std::cout << "Now test " << index << ".jpg" << std::endl;
|
||||
#endif
|
||||
if(img.empty())
|
||||
{
|
||||
std::cout << "Couldn't read test" << index << ".jpg" << std::endl;
|
||||
continue;
|
||||
}
|
||||
TEST_F(Haar, FaceDetect)
|
||||
{
|
||||
string imgName = "../../../samples/c/lena.jpg";
|
||||
Mat img = imread( imgName, 1 );
|
||||
|
||||
int i = 0;
|
||||
double t = 0;
|
||||
vector<Rect> faces;
|
||||
if(img.empty())
|
||||
{
|
||||
std::cout << "Couldn't read test" << index <<".jpg" << std::endl;
|
||||
return ;
|
||||
}
|
||||
|
||||
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)
|
||||
} ;
|
||||
int i = 0;
|
||||
double t = 0;
|
||||
vector<Rect> faces, oclfaces;
|
||||
|
||||
Mat gray, smallImg(cvRound (img.rows / scale), cvRound(img.cols / scale), CV_8UC1 );
|
||||
MemStorage storage(cvCreateMemStorage(0));
|
||||
cvtColor( img, gray, CV_BGR2GRAY );
|
||||
resize( gray, smallImg, smallImg.size(), 0, 0, INTER_LINEAR );
|
||||
equalizeHist( smallImg, smallImg );
|
||||
CvMat _image = smallImg;
|
||||
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)} ;
|
||||
|
||||
Mat tempimg(&_image, false);
|
||||
Mat gray, smallImg(cvRound (img.rows/scale), cvRound(img.cols/scale), CV_8UC1 );
|
||||
MemStorage storage(cvCreateMemStorage(0));
|
||||
cvtColor( img, gray, CV_BGR2GRAY );
|
||||
resize( gray, smallImg, smallImg.size(), 0, 0, INTER_LINEAR );
|
||||
equalizeHist( smallImg, smallImg );
|
||||
|
||||
cv::ocl::oclMat image(tempimg);
|
||||
CvSeq *_objects;
|
||||
|
||||
#if 1
|
||||
for(int k = 0; k < 10; k++)
|
||||
{
|
||||
t = (double)cvGetTickCount();
|
||||
_objects = cascade.oclHaarDetectObjects( image, storage, 1.1,
|
||||
2, 0
|
||||
| CV_HAAR_SCALE_IMAGE
|
||||
, Size(30, 30), Size(0, 0) );
|
||||
cv::ocl::oclMat image;
|
||||
CvSeq* _objects;
|
||||
image.upload(smallImg);
|
||||
_objects = cascade.oclHaarDetectObjects( image, storage, 1.1,
|
||||
3, 0
|
||||
|CV_HAAR_SCALE_IMAGE
|
||||
, Size(30,30), Size(0, 0) );
|
||||
vector<CvAvgComp> vecAvgComp;
|
||||
Seq<CvAvgComp>(_objects).copyTo(vecAvgComp);
|
||||
oclfaces.resize(vecAvgComp.size());
|
||||
std::transform(vecAvgComp.begin(), vecAvgComp.end(), oclfaces.begin(), getRect());
|
||||
|
||||
t = (double)cvGetTickCount() - t ;
|
||||
printf( "detection time = %g ms\n", t / ((double)cvGetTickFrequency() * 1000.) );
|
||||
}
|
||||
cpucascade.detectMultiScale( smallImg, faces, 1.1,
|
||||
3, 0
|
||||
|CV_HAAR_SCALE_IMAGE
|
||||
, Size(30,30), Size(0, 0) );
|
||||
EXPECT_EQ(faces.size(),oclfaces.size());
|
||||
/* 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 );
|
||||
} */
|
||||
//namedWindow("result");
|
||||
//imshow("result",img);
|
||||
//waitKey(0);
|
||||
//destroyAllWindows();
|
||||
|
||||
#else
|
||||
cpucascade.detectMultiScale( image, faces, 1.1,
|
||||
2, 0
|
||||
| CV_HAAR_SCALE_IMAGE
|
||||
, Size(30, 30), Size(0, 0) );
|
||||
|
||||
#endif
|
||||
vector<CvAvgComp> vecAvgComp;
|
||||
Seq<CvAvgComp>(_objects).copyTo(vecAvgComp);
|
||||
faces.resize(vecAvgComp.size());
|
||||
std::transform(vecAvgComp.begin(), vecAvgComp.end(), faces.begin(), getRect());
|
||||
|
||||
for( vector<Rect>::const_iterator r = faces.begin(); r != faces.end(); r++, i++ )
|
||||
{
|
||||
Mat smallImgROI;
|
||||
vector<Rect> nestedObjects;
|
||||
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 );
|
||||
}
|
||||
|
||||
#if WIN32
|
||||
sprintf(buff, "E:\\result1\\%d.jpg", index);
|
||||
imwrite(buff, img);
|
||||
#else
|
||||
sprintf(buff, "testdet_%d.jpg", index);
|
||||
imwrite(buff, img);
|
||||
#endif
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
//INSTANTIATE_TEST_CASE_P(HaarTestBase, Haar, Combine(Values(1),
|
||||
// Values(1)));
|
||||
|
||||
|
||||
#endif // HAVE_OPENCL
|
||||
|
Reference in New Issue
Block a user