mirror of https://github.com/opencv/opencv.git
Open Source Computer Vision Library
https://opencv.org/
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
257 lines
8.1 KiB
257 lines
8.1 KiB
/*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 "test_precomp.hpp" |
|
#include "opencv2/core/core.hpp" |
|
#include "opencv2/objdetect/objdetect.hpp" |
|
|
|
using namespace cv; |
|
using namespace testing; |
|
#ifdef HAVE_OPENCL |
|
|
|
///////////////////// 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("gpu/hog/road.png"); |
|
ASSERT_FALSE(img_rgb.empty()); |
|
} |
|
}; |
|
|
|
OCL_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); |
|
} |
|
|
|
OCL_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 = (string(cvtest::TS::ptr()->get_data_path()) + "cv/cascadeandhog/cascades/").append(GET_PARAM(1)); |
|
ASSERT_TRUE(cascade.load( cascadeName )); |
|
ASSERT_TRUE(cpucascade.load(cascadeName)); |
|
img = readImage("cv/shared/lena.png", IMREAD_GRAYSCALE); |
|
ASSERT_FALSE(img.empty()); |
|
equalizeHist(img, img); |
|
d_img.upload(img); |
|
} |
|
}; |
|
|
|
OCL_TEST_P(Haar, FaceDetect) |
|
{ |
|
cascade.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)); |
|
|
|
EXPECT_LT(checkRectSimilarity(img.size(), faces, oclfaces), 0.1); |
|
} |
|
|
|
OCL_TEST_P(Haar, FaceDetectUseBuf) |
|
{ |
|
ocl::OclCascadeClassifierBuf cascadebuf; |
|
ASSERT_TRUE(cascadebuf.load(cascadeName)) << "could not load classifier cascade for FaceDetectUseBuf!"; |
|
|
|
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), 0.1); |
|
} |
|
|
|
INSTANTIATE_TEST_CASE_P(OCL_ObjDetect, Haar, |
|
Combine(Values(CV_HAAR_SCALE_IMAGE, 0), |
|
Values(cascade_frontalface_alt/*, cascade_frontalface_alt2*/))); |
|
|
|
#endif //HAVE_OPENCL
|
|
|