mirror of
https://github.com/opencv/opencv.git
synced 2024-11-25 11:40:44 +08:00
277 lines
8.7 KiB
C++
277 lines
8.7 KiB
C++
/*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.
|
|
//
|
|
//
|
|
// Intel License Agreement
|
|
// For Open Source Computer Vision Library
|
|
//
|
|
// Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved.
|
|
// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
|
|
// Third party copyrights are property of their respective owners.
|
|
//
|
|
// @Authors
|
|
// Yao Wang, bitwangyaoyao@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 materials provided with the distribution.
|
|
//
|
|
// * The name of Intel Corporation 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 "opencv2/core/core.hpp"
|
|
#include "opencv2/objdetect/objdetect.hpp"
|
|
|
|
using namespace cv;
|
|
using namespace testing;
|
|
#ifdef HAVE_OPENCL
|
|
|
|
extern string workdir;
|
|
|
|
///////////////////// HOG /////////////////////////////
|
|
PARAM_TEST_CASE(HOG, Size, int)
|
|
{
|
|
Size winSize;
|
|
int type;
|
|
Mat img_rgb;
|
|
virtual void SetUp()
|
|
{
|
|
winSize = GET_PARAM(0);
|
|
type = GET_PARAM(1);
|
|
img_rgb = readImage(workdir + "../gpu/road.png");
|
|
if(img_rgb.empty())
|
|
{
|
|
std::cout << "Couldn't read road.png" << std::endl;
|
|
}
|
|
}
|
|
};
|
|
|
|
TEST_P(HOG, GetDescriptors)
|
|
{
|
|
// Convert image
|
|
Mat img;
|
|
switch (type)
|
|
{
|
|
case CV_8UC1:
|
|
cvtColor(img_rgb, img, CV_BGR2GRAY);
|
|
break;
|
|
case CV_8UC4:
|
|
default:
|
|
cvtColor(img_rgb, img, CV_BGR2BGRA);
|
|
break;
|
|
}
|
|
ocl::oclMat d_img(img);
|
|
|
|
// HOGs
|
|
ocl::HOGDescriptor ocl_hog;
|
|
ocl_hog.gamma_correction = true;
|
|
HOGDescriptor hog;
|
|
hog.gammaCorrection = true;
|
|
|
|
// Compute descriptor
|
|
ocl::oclMat d_descriptors;
|
|
ocl_hog.getDescriptors(d_img, ocl_hog.win_size, d_descriptors, ocl_hog.DESCR_FORMAT_COL_BY_COL);
|
|
Mat down_descriptors;
|
|
d_descriptors.download(down_descriptors);
|
|
down_descriptors = down_descriptors.reshape(0, down_descriptors.cols * down_descriptors.rows);
|
|
|
|
hog.setSVMDetector(hog.getDefaultPeopleDetector());
|
|
std::vector<float> descriptors;
|
|
switch (type)
|
|
{
|
|
case CV_8UC1:
|
|
hog.compute(img, descriptors, ocl_hog.win_size);
|
|
break;
|
|
case CV_8UC4:
|
|
default:
|
|
hog.compute(img_rgb, descriptors, ocl_hog.win_size);
|
|
break;
|
|
}
|
|
Mat cpu_descriptors(descriptors);
|
|
|
|
EXPECT_MAT_SIMILAR(down_descriptors, cpu_descriptors, 1e-2);
|
|
}
|
|
|
|
TEST_P(HOG, Detect)
|
|
{
|
|
// Convert image
|
|
Mat img;
|
|
switch (type)
|
|
{
|
|
case CV_8UC1:
|
|
cvtColor(img_rgb, img, CV_BGR2GRAY);
|
|
break;
|
|
case CV_8UC4:
|
|
default:
|
|
cvtColor(img_rgb, img, CV_BGR2BGRA);
|
|
break;
|
|
}
|
|
ocl::oclMat d_img(img);
|
|
|
|
// HOGs
|
|
if ((winSize != Size(48, 96)) && (winSize != Size(64, 128)))
|
|
winSize = Size(64, 128);
|
|
ocl::HOGDescriptor ocl_hog(winSize);
|
|
ocl_hog.gamma_correction = true;
|
|
|
|
HOGDescriptor hog;
|
|
hog.winSize = winSize;
|
|
hog.gammaCorrection = true;
|
|
|
|
if (winSize.width == 48 && winSize.height == 96)
|
|
{
|
|
// daimler's base
|
|
ocl_hog.setSVMDetector(hog.getDaimlerPeopleDetector());
|
|
hog.setSVMDetector(hog.getDaimlerPeopleDetector());
|
|
}
|
|
else if (winSize.width == 64 && winSize.height == 128)
|
|
{
|
|
ocl_hog.setSVMDetector(hog.getDefaultPeopleDetector());
|
|
hog.setSVMDetector(hog.getDefaultPeopleDetector());
|
|
}
|
|
else
|
|
{
|
|
ocl_hog.setSVMDetector(hog.getDefaultPeopleDetector());
|
|
hog.setSVMDetector(hog.getDefaultPeopleDetector());
|
|
}
|
|
|
|
// OpenCL detection
|
|
std::vector<Rect> d_found;
|
|
ocl_hog.detectMultiScale(d_img, d_found, 0, Size(8, 8), Size(0, 0), 1.05, 6);
|
|
|
|
// CPU detection
|
|
std::vector<Rect> found;
|
|
switch (type)
|
|
{
|
|
case CV_8UC1:
|
|
hog.detectMultiScale(img, found, 0, Size(8, 8), Size(0, 0), 1.05, 6);
|
|
break;
|
|
case CV_8UC4:
|
|
default:
|
|
hog.detectMultiScale(img_rgb, found, 0, Size(8, 8), Size(0, 0), 1.05, 6);
|
|
break;
|
|
}
|
|
|
|
EXPECT_LT(checkRectSimilarity(img.size(), found, d_found), 1.0);
|
|
}
|
|
|
|
|
|
INSTANTIATE_TEST_CASE_P(OCL_ObjDetect, HOG, testing::Combine(
|
|
testing::Values(Size(64, 128), Size(48, 96)),
|
|
testing::Values(MatType(CV_8UC1), MatType(CV_8UC4))));
|
|
|
|
///////////////////////////// Haar //////////////////////////////
|
|
IMPLEMENT_PARAM_CLASS(CascadeName, std::string);
|
|
CascadeName cascade_frontalface_alt(std::string("haarcascade_frontalface_alt.xml"));
|
|
CascadeName cascade_frontalface_alt2(std::string("haarcascade_frontalface_alt2.xml"));
|
|
struct getRect
|
|
{
|
|
Rect operator ()(const CvAvgComp &e) const
|
|
{
|
|
return e.rect;
|
|
}
|
|
};
|
|
|
|
PARAM_TEST_CASE(Haar, int, CascadeName)
|
|
{
|
|
ocl::OclCascadeClassifier cascade, nestedCascade;
|
|
CascadeClassifier cpucascade, cpunestedCascade;
|
|
|
|
int flags;
|
|
std::string cascadeName;
|
|
vector<Rect> faces, oclfaces;
|
|
Mat img;
|
|
ocl::oclMat d_img;
|
|
|
|
virtual void SetUp()
|
|
{
|
|
flags = GET_PARAM(0);
|
|
cascadeName = (workdir + "../../data/haarcascades/").append(GET_PARAM(1));
|
|
if( (!cascade.load( cascadeName )) || (!cpucascade.load(cascadeName)) )
|
|
{
|
|
std::cout << "ERROR: Could not load classifier cascade" << std::endl;
|
|
return;
|
|
}
|
|
img = readImage(workdir + "lena.jpg", IMREAD_GRAYSCALE);
|
|
if(img.empty())
|
|
{
|
|
std::cout << "Couldn't read lena.jpg" << std::endl;
|
|
return ;
|
|
}
|
|
equalizeHist(img, img);
|
|
d_img.upload(img);
|
|
}
|
|
};
|
|
|
|
TEST_P(Haar, FaceDetect)
|
|
{
|
|
MemStorage storage(cvCreateMemStorage(0));
|
|
CvSeq *_objects;
|
|
_objects = cascade.oclHaarDetectObjects(d_img, storage, 1.1, 3,
|
|
flags, 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());
|
|
|
|
cpucascade.detectMultiScale(img, faces, 1.1, 3,
|
|
flags,
|
|
Size(30, 30), Size(0, 0));
|
|
|
|
EXPECT_LT(checkRectSimilarity(img.size(), faces, oclfaces), 1.0);
|
|
}
|
|
|
|
TEST_P(Haar, FaceDetectUseBuf)
|
|
{
|
|
ocl::OclCascadeClassifierBuf cascadebuf;
|
|
if(!cascadebuf.load(cascadeName))
|
|
{
|
|
std::cout << "ERROR: Could not load classifier cascade for FaceDetectUseBuf!" << std::endl;
|
|
return;
|
|
}
|
|
cascadebuf.detectMultiScale(d_img, oclfaces, 1.1, 3,
|
|
flags,
|
|
Size(30, 30), Size(0, 0));
|
|
cpucascade.detectMultiScale(img, faces, 1.1, 3,
|
|
flags,
|
|
Size(30, 30), Size(0, 0));
|
|
|
|
// intentionally run ocl facedetect again and check if it still works after the first run
|
|
cascadebuf.detectMultiScale(d_img, oclfaces, 1.1, 3,
|
|
flags,
|
|
Size(30, 30));
|
|
cascadebuf.release();
|
|
|
|
EXPECT_LT(checkRectSimilarity(img.size(), faces, oclfaces), 1.0);
|
|
}
|
|
|
|
INSTANTIATE_TEST_CASE_P(OCL_ObjDetect, Haar,
|
|
Combine(Values(CV_HAAR_SCALE_IMAGE, 0),
|
|
Values(cascade_frontalface_alt/*, cascade_frontalface_alt2*/)));
|
|
|
|
#endif //HAVE_OPENCL
|