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90 lines
3.6 KiB
C++
90 lines
3.6 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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// Intel License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000, Intel Corporation, 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 Intel Corporation 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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using namespace cv;
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using namespace std;
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using cv::ml::SVM;
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using cv::ml::TrainData;
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//--------------------------------------------------------------------------------------------
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class CV_SVMTrainAutoTest : public cvtest::BaseTest {
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public:
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CV_SVMTrainAutoTest() {}
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protected:
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virtual void run( int start_from );
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};
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void CV_SVMTrainAutoTest::run( int /*start_from*/ )
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{
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int datasize = 100;
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cv::Mat samples = cv::Mat::zeros( datasize, 2, CV_32FC1 );
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cv::Mat responses = cv::Mat::zeros( datasize, 1, CV_32S );
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RNG rng(0);
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for (int i = 0; i < datasize; ++i)
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{
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int response = rng.uniform(0, 2); // Random from {0, 1}.
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samples.at<float>( i, 0 ) = rng.uniform(0.f, 0.5f) + response * 0.5f;
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samples.at<float>( i, 1 ) = rng.uniform(0.f, 0.5f) + response * 0.5f;
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responses.at<int>( i, 0 ) = response;
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}
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cv::Ptr<TrainData> data = TrainData::create( samples, cv::ml::ROW_SAMPLE, responses );
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cv::Ptr<SVM> svm = SVM::create();
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svm->trainAuto( data, 10 ); // 2-fold cross validation.
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float test_data0[2] = {0.25f, 0.25f};
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cv::Mat test_point0 = cv::Mat( 1, 2, CV_32FC1, test_data0 );
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float result0 = svm->predict( test_point0 );
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float test_data1[2] = {0.75f, 0.75f};
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cv::Mat test_point1 = cv::Mat( 1, 2, CV_32FC1, test_data1 );
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float result1 = svm->predict( test_point1 );
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if ( fabs( result0 - 0 ) > 0.001 || fabs( result1 - 1 ) > 0.001 )
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{
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ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
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}
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}
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TEST(ML_SVM, trainauto) { CV_SVMTrainAutoTest test; test.safe_run(); }
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