e45fd939c2
Conflicts: modules/ocl/src/cl_runtime/cl_runtime.cpp modules/ocl/src/cl_runtime/clamdblas_runtime.cpp modules/ocl/src/cl_runtime/clamdfft_runtime.cpp modules/ocl/src/cl_runtime/generator/template/clamdblas_runtime.cpp.in modules/ocl/src/cl_runtime/generator/template/clamdfft_runtime.cpp.in
154 lines
5.7 KiB
C++
154 lines
5.7 KiB
C++
/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved.
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// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// @Authors
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// Fangfang Bai, fangfang@multicorewareinc.com
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// Jin Ma, jin@multicorewareinc.com
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors as is and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#include "perf_precomp.hpp"
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#include "opencv2/objdetect/objdetect_c.h"
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using namespace perf;
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///////////// Haar ////////////////////////
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PERF_TEST(HaarFixture, Haar)
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{
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vector<Rect> faces;
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Mat img = imread(getDataPath("gpu/haarcascade/basketball1.png"), IMREAD_GRAYSCALE);
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ASSERT_TRUE(!img.empty()) << "can't open basketball1.png";
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declare.in(img);
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if (RUN_PLAIN_IMPL)
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{
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CascadeClassifier faceCascade;
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ASSERT_TRUE(faceCascade.load(getDataPath("gpu/haarcascade/haarcascade_frontalface_alt.xml")))
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<< "can't load haarcascade_frontalface_alt.xml";
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TEST_CYCLE() faceCascade.detectMultiScale(img, faces,
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1.1, 2, 0 | CV_HAAR_SCALE_IMAGE, Size(30, 30));
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SANITY_CHECK(faces, 4 + 1e-4);
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}
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else if (RUN_OCL_IMPL)
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{
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ocl::OclCascadeClassifier faceCascade;
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ocl::oclMat oclImg(img);
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ASSERT_TRUE(faceCascade.load(getDataPath("gpu/haarcascade/haarcascade_frontalface_alt.xml")))
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<< "can't load haarcascade_frontalface_alt.xml";
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OCL_TEST_CYCLE() faceCascade.detectMultiScale(oclImg, faces,
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1.1, 2, 0 | CV_HAAR_SCALE_IMAGE, Size(30, 30));
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SANITY_CHECK(faces, 4 + 1e-4);
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}
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else
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OCL_PERF_ELSE
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}
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using namespace std;
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using namespace cv;
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using namespace perf;
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using std::tr1::make_tuple;
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using std::tr1::get;
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typedef std::tr1::tuple<std::string, std::string, int> OCL_Cascade_Image_MinSize_t;
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typedef perf::TestBaseWithParam<OCL_Cascade_Image_MinSize_t> OCL_Cascade_Image_MinSize;
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PERF_TEST_P( OCL_Cascade_Image_MinSize, CascadeClassifier,
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testing::Combine(
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testing::Values( string("cv/cascadeandhog/cascades/haarcascade_frontalface_alt.xml") ),
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testing::Values( string("cv/shared/lena.png"),
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string("cv/cascadeandhog/images/bttf301.png"),
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string("cv/cascadeandhog/images/class57.png") ),
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testing::Values(30, 64, 90) ) )
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{
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const string cascasePath = get<0>(GetParam());
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const string imagePath = get<1>(GetParam());
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const int min_size = get<2>(GetParam());
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Size minSize(min_size, min_size);
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vector<Rect> faces;
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Mat img = imread(getDataPath(imagePath), IMREAD_GRAYSCALE);
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ASSERT_TRUE(!img.empty()) << "Can't load source image: " << getDataPath(imagePath);
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equalizeHist(img, img);
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declare.in(img);
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if (RUN_PLAIN_IMPL)
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{
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CascadeClassifier cc;
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ASSERT_TRUE(cc.load(getDataPath(cascasePath))) << "Can't load cascade file: " << getDataPath(cascasePath);
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while (next())
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{
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faces.clear();
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startTimer();
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cc.detectMultiScale(img, faces, 1.1, 3, 0, minSize);
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stopTimer();
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}
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}
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else if (RUN_OCL_IMPL)
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{
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ocl::oclMat uimg(img);
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ocl::OclCascadeClassifier cc;
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ASSERT_TRUE(cc.load(getDataPath(cascasePath))) << "Can't load cascade file: " << getDataPath(cascasePath);
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while (next())
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{
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faces.clear();
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ocl::finish();
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startTimer();
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cc.detectMultiScale(uimg, faces, 1.1, 3, 0, minSize);
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stopTimer();
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}
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}
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else
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OCL_PERF_ELSE
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//sort(faces.begin(), faces.end(), comparators::RectLess());
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SANITY_CHECK_NOTHING();//(faces, min_size/5);
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// using SANITY_CHECK_NOTHING() since OCL and PLAIN version may find different faces number
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}
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