/*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, 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. // 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 "perf_precomp.hpp" #if GTEST_OS_WINDOWS #ifndef NOMINMAX #define NOMINMAX #endif # include #endif // This program test most of the functions in ocl module and generate data metrix of x-factor in .csv files // All images needed in this test are in samples/gpu folder. // For haar template, haarcascade_frontalface_alt.xml shouold be in working directory void TestSystem::run() { if (is_list_mode_) { for (vector::iterator it = tests_.begin(); it != tests_.end(); ++it) { cout << (*it)->name() << endl; } return; } // Run test initializers for (vector::iterator it = inits_.begin(); it != inits_.end(); ++it) { if ((*it)->name().find(test_filter_, 0) != string::npos) { (*it)->run(); } } printHeading(); writeHeading(); // Run tests for (vector::iterator it = tests_.begin(); it != tests_.end(); ++it) { try { if ((*it)->name().find(test_filter_, 0) != string::npos) { cout << endl << (*it)->name() << ":\n"; setCurrentTest((*it)->name()); //fprintf(record_,"%s\n",(*it)->name().c_str()); (*it)->run(); finishCurrentSubtest(); } } catch (const Exception &) { // Message is printed via callback resetCurrentSubtest(); } catch (const runtime_error &e) { printError(e.what()); resetCurrentSubtest(); } } printSummary(); writeSummary(); } void TestSystem::finishCurrentSubtest() { if (cur_subtest_is_empty_) // There is no need to print subtest statistics { return; } double cpu_time = cpu_elapsed_ / getTickFrequency() * 1000.0; double gpu_time = gpu_elapsed_ / getTickFrequency() * 1000.0; double gpu_full_time = gpu_full_elapsed_ / getTickFrequency() * 1000.0; double speedup = static_cast(cpu_elapsed_) / std::max(1.0, gpu_elapsed_); speedup_total_ += speedup; double fullspeedup = static_cast(cpu_elapsed_) / std::max(1.0, gpu_full_elapsed_); speedup_full_total_ += fullspeedup; if (speedup > top_) { speedup_faster_count_++; } else if (speedup < bottom_) { speedup_slower_count_++; } else { speedup_equal_count_++; } if (fullspeedup > top_) { speedup_full_faster_count_++; } else if (fullspeedup < bottom_) { speedup_full_slower_count_++; } else { speedup_full_equal_count_++; } // compute min, max and std::sort(gpu_times_.begin(), gpu_times_.end()); double gpu_min = gpu_times_.front() / getTickFrequency() * 1000.0; double gpu_max = gpu_times_.back() / getTickFrequency() * 1000.0; double deviation = 0; if (gpu_times_.size() > 1) { double sum = 0; for (size_t i = 0; i < gpu_times_.size(); i++) { int64 diff = gpu_times_[i] - static_cast(gpu_elapsed_); double diff_time = diff * 1000 / getTickFrequency(); sum += diff_time * diff_time; } deviation = std::sqrt(sum / gpu_times_.size()); } printMetrics(is_accurate_, cpu_time, gpu_time, gpu_full_time, speedup, fullspeedup); writeMetrics(cpu_time, gpu_time, gpu_full_time, speedup, fullspeedup, gpu_min, gpu_max, deviation); num_subtests_called_++; resetCurrentSubtest(); } double TestSystem::meanTime(const vector &samples) { double sum = accumulate(samples.begin(), samples.end(), 0.); return sum / samples.size(); } void TestSystem::printHeading() { cout << endl; cout<< setiosflags(ios_base::left); #if 0 cout<(0, 0) - 1.f); }