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Open Source Computer Vision Library
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312 lines
9.5 KiB
312 lines
9.5 KiB
/*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) 2000-2008, Intel Corporation, all rights reserved. |
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// Copyright (C) 2008-2012, Willow Garage 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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// 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 "test_precomp.hpp" |
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#include "opencv2/core/gpumat.hpp" |
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using std::tr1::get; |
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// show detection results on input image with cv::imshow |
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//#define SHOW_DETECTIONS |
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#if defined SHOW_DETECTIONS |
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# define SHOW(res) \ |
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cv::imshow(#res, res); \ |
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cv::waitKey(0); |
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#else |
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# define SHOW(res) |
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#endif |
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static std::string path(std::string relative) |
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{ |
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return cvtest::TS::ptr()->get_data_path() + "cascadeandhog/" + relative; |
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} |
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TEST(SCascadeTest, readCascade) |
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{ |
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std::string xml = path("cascades/inria_caltech-17.01.2013.xml"); |
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cv::FileStorage fs(xml, cv::FileStorage::READ); |
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cv::softcascade::SCascade cascade; |
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ASSERT_TRUE(fs.isOpened()); |
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ASSERT_TRUE(cascade.load(fs.getFirstTopLevelNode())); |
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} |
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namespace |
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{ |
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typedef cv::softcascade::SCascade::Detection Detection; |
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cv::Rect getFromTable(int idx) |
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{ |
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static const cv::Rect rois[] = |
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{ |
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cv::Rect( 65 * 4, 20 * 4, 35 * 4, 80 * 4), |
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cv::Rect( 95 * 4, 35 * 4, 45 * 4, 40 * 4), |
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cv::Rect( 45 * 4, 35 * 4, 45 * 4, 40 * 4), |
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cv::Rect( 25 * 4, 27 * 4, 50 * 4, 45 * 4), |
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cv::Rect(100 * 4, 50 * 4, 45 * 4, 40 * 4), |
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cv::Rect( 60 * 4, 30 * 4, 45 * 4, 40 * 4), |
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cv::Rect( 40 * 4, 55 * 4, 50 * 4, 40 * 4), |
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cv::Rect( 48 * 4, 37 * 4, 72 * 4, 80 * 4), |
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cv::Rect( 48 * 4, 32 * 4, 85 * 4, 58 * 4), |
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cv::Rect( 48 * 4, 0 * 4, 32 * 4, 27 * 4) |
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}; |
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return rois[idx]; |
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} |
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void print(std::ostream &out, const Detection& d) |
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{ |
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#if defined SHOW_DETECTIONS |
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out << "\x1b[32m[ detection]\x1b[0m (" |
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<< std::setw(4) << d.x |
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<< " " |
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<< std::setw(4) << d.y |
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<< ") (" |
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<< std::setw(4) << d.w |
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<< " " |
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<< std::setw(4) << d.h |
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<< ") " |
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<< std::setw(12) << d.confidence |
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<< std::endl; |
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#else |
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(void)out; (void)d; |
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#endif |
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} |
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void printTotal(std::ostream &out, int detbytes) |
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{ |
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#if defined SHOW_DETECTIONS |
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out << "\x1b[32m[ ]\x1b[0m Total detections " << (detbytes / sizeof(Detection)) << std::endl; |
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#else |
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(void)out; (void)detbytes; |
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#endif |
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} |
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std::string itoa(long i) |
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{ |
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static char s[65]; |
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sprintf(s, "%ld", i); |
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return std::string(s); |
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} |
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#if defined SHOW_DETECTIONS |
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std::string getImageName(int level) |
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{ |
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time_t rawtime; |
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struct tm * timeinfo; |
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char buffer [80]; |
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time ( &rawtime ); |
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timeinfo = localtime ( &rawtime ); |
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strftime (buffer,80,"%Y-%m-%d--%H-%M-%S",timeinfo); |
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return "gpu_rec_level_" + itoa(level)+ "_" + std::string(buffer) + ".png"; |
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} |
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void writeResult(const cv::Mat& result, const int level) |
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{ |
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std::string path = cv::tempfile(getImageName(level).c_str()); |
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cv::imwrite(path, result); |
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std::cout << "\x1b[32m" << "[ ]" << std::endl << "[ stored in]"<< "\x1b[0m" << path << std::endl; |
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} |
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#endif |
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} |
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class SCascadeTestRoi : public ::testing::TestWithParam<std::tr1::tuple<cv::gpu::DeviceInfo, std::string, std::string, int> > |
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{ |
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virtual void SetUp() |
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{ |
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cv::gpu::setDevice(get<0>(GetParam()).deviceID()); |
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} |
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}; |
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TEST_P(SCascadeTestRoi, Detect) |
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{ |
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cv::Mat coloredCpu = cv::imread(path(get<2>(GetParam()))); |
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ASSERT_FALSE(coloredCpu.empty()); |
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cv::softcascade::SCascade cascade; |
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cv::FileStorage fs(path(get<1>(GetParam())), cv::FileStorage::READ); |
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ASSERT_TRUE(fs.isOpened()); |
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ASSERT_TRUE(cascade.load(fs.getFirstTopLevelNode())); |
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cv::gpu::GpuMat colored(coloredCpu), objectBoxes(1, 16384, CV_8UC1), rois(colored.size(), CV_8UC1); |
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rois.setTo(0); |
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int nroi = get<3>(GetParam()); |
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cv::Mat result(coloredCpu); |
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cv::RNG rng; |
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for (int i = 0; i < nroi; ++i) |
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{ |
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cv::Rect r = getFromTable(rng(10)); |
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cv::gpu::GpuMat sub(rois, r); |
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sub.setTo(1); |
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cv::rectangle(result, r, cv::Scalar(0, 0, 255, 255), 1); |
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} |
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objectBoxes.setTo(0); |
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cascade.detect(colored, rois, objectBoxes); |
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cv::Mat dt(objectBoxes); |
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typedef cv::softcascade::SCascade::Detection Detection; |
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Detection* dts = ((Detection*)dt.data) + 1; |
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int* count = dt.ptr<int>(0); |
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printTotal(std::cout, *count); |
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for (int i = 0; i < *count; ++i) |
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{ |
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Detection d = dts[i]; |
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print(std::cout, d); |
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cv::rectangle(result, cv::Rect(d.x, d.y, d.w, d.h), cv::Scalar(255, 0, 0, 255), 1); |
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} |
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SHOW(result); |
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} |
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INSTANTIATE_TEST_CASE_P(cuda_accelerated, SCascadeTestRoi, testing::Combine( |
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testing::ValuesIn(DeviceManager::instance().values()), |
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testing::Values(std::string("cascades/inria_caltech-17.01.2013.xml"), |
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std::string("cascades/sc_cvpr_2012_to_opencv_new_format.xml")), |
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testing::Values(std::string("images/image_00000000_0.png")), |
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testing::Range(0, 5))); |
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namespace { |
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struct Fixture |
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{ |
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std::string path; |
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int expected; |
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Fixture(){} |
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Fixture(std::string p, int e): path(p), expected(e) {} |
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}; |
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} |
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typedef std::tr1::tuple<cv::gpu::DeviceInfo, Fixture> SCascadeTestAllFixture; |
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class SCascadeTestAll : public ::testing::TestWithParam<SCascadeTestAllFixture> |
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{ |
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protected: |
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std::string xml; |
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int expected; |
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virtual void SetUp() |
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{ |
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cv::gpu::setDevice(get<0>(GetParam()).deviceID()); |
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xml = path(get<1>(GetParam()).path); |
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expected = get<1>(GetParam()).expected; |
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} |
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}; |
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TEST_P(SCascadeTestAll, detect) |
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{ |
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cv::softcascade::SCascade cascade; |
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cv::FileStorage fs(xml, cv::FileStorage::READ); |
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ASSERT_TRUE(fs.isOpened()); |
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ASSERT_TRUE(cascade.load(fs.getFirstTopLevelNode())); |
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cv::Mat coloredCpu = cv::imread(path("images/image_00000000_0.png")); |
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ASSERT_FALSE(coloredCpu.empty()); |
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cv::gpu::GpuMat colored(coloredCpu), objectBoxes, rois(colored.size(), CV_8UC1); |
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rois.setTo(1); |
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cascade.detect(colored, rois, objectBoxes); |
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typedef cv::softcascade::SCascade::Detection Detection; |
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cv::Mat dt(objectBoxes); |
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Detection* dts = ((Detection*)dt.data) + 1; |
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int* count = dt.ptr<int>(0); |
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printTotal(std::cout, *count); |
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for (int i = 0; i < *count; ++i) |
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{ |
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Detection d = dts[i]; |
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print(std::cout, d); |
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cv::rectangle(coloredCpu, cv::Rect(d.x, d.y, d.w, d.h), cv::Scalar(255, 0, 0, 255), 1); |
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} |
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SHOW(coloredCpu); |
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ASSERT_EQ(*count, expected); |
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} |
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TEST_P(SCascadeTestAll, detectStream) |
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{ |
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cv::softcascade::SCascade cascade; |
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cv::FileStorage fs(xml, cv::FileStorage::READ); |
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ASSERT_TRUE(fs.isOpened()); |
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ASSERT_TRUE(cascade.load(fs.getFirstTopLevelNode())); |
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cv::Mat coloredCpu = cv::imread(path("images/image_00000000_0.png")); |
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ASSERT_FALSE(coloredCpu.empty()); |
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cv::gpu::GpuMat colored(coloredCpu), objectBoxes(1, 100000, CV_8UC1), rois(colored.size(), CV_8UC1); |
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rois.setTo(cv::Scalar::all(1)); |
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cv::gpu::Stream s; |
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objectBoxes.setTo(0); |
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cascade.detect(colored, rois, objectBoxes, s); |
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s.waitForCompletion(); |
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typedef cv::softcascade::SCascade::Detection Detection; |
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cv::Mat detections(objectBoxes); |
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int a = *(detections.ptr<int>(0)); |
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ASSERT_EQ(a, expected); |
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} |
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INSTANTIATE_TEST_CASE_P(cuda_accelerated, SCascadeTestAll, testing::Combine( ALL_DEVICES, |
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testing::Values(Fixture("cascades/inria_caltech-17.01.2013.xml", 7), |
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Fixture("cascades/sc_cvpr_2012_to_opencv_new_format.xml", 1291)))); |