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Add Macro to decide using ocl method or not.
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@ -5,6 +5,7 @@
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#include "opencv2/nonfree/nonfree.hpp"
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#include "opencv2/ml/ml.hpp"
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#ifdef HAVE_OPENCV_OCL
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#define _OCL_SVM_ 0 //select whether using ocl::svm method or not, default is not
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#include "opencv2/ocl/ocl.hpp"
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#endif
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@ -2377,7 +2378,7 @@ static void setSVMTrainAutoParams( CvParamGrid& c_grid, CvParamGrid& gamma_grid,
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degree_grid.step = 0;
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}
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#ifdef HAVE_OPENCV_OCL
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#if defined HAVE_OPENCV_OCL && _OCL_SVM_
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static void trainSVMClassifier( cv::ocl::CvSVM_OCL& svm, const SVMTrainParamsExt& svmParamsExt, const string& objClassName, VocData& vocData,
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Ptr<BOWImgDescriptorExtractor>& bowExtractor, const Ptr<FeatureDetector>& fdetector,
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const string& resPath )
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@ -2458,7 +2459,7 @@ static void trainSVMClassifier( CvSVM& svm, const SVMTrainParamsExt& svmParamsEx
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}
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}
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#ifdef HAVE_OPENCV_OCL
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#if defined HAVE_OPENCV_OCL && _OCL_SVM_
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static void computeConfidences( cv::ocl::CvSVM_OCL& svm, const string& objClassName, VocData& vocData,
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Ptr<BOWImgDescriptorExtractor>& bowExtractor, const Ptr<FeatureDetector>& fdetector,
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const string& resPath )
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@ -2605,7 +2606,7 @@ int main(int argc, char** argv)
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for( size_t classIdx = 0; classIdx < objClasses.size(); ++classIdx )
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{
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// Train a classifier on train dataset
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#ifdef HAVE_OPENCV_OCL
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#if defined HAVE_OPENCV_OCL && _OCL_SVM_
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cv::ocl::CvSVM_OCL svm;
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#else
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CvSVM svm;
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@ -3,6 +3,8 @@
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#include "opencv2/ml/ml.hpp"
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#include "opencv2/highgui/highgui.hpp"
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#ifdef HAVE_OPENCV_OCL
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#define _OCL_KNN_ 0 // select whether using ocl::KNN method or not, default is not
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#define _OCL_SVM_ 0 // select whether using ocl::svm method or not, default is not
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#include "opencv2/ocl/ocl.hpp"
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#endif
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@ -137,7 +139,7 @@ static void find_decision_boundary_KNN( int K )
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prepare_train_data( trainSamples, trainClasses );
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// learn classifier
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#ifdef HAVE_OPENCV_OCL
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#if defined HAVE_OPENCV_OCL && _OCL_KNN_
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cv::ocl::KNearestNeighbour knnClassifier;
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Mat temp, result;
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knnClassifier.train(trainSamples, trainClasses, temp, false, K);
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@ -153,7 +155,7 @@ static void find_decision_boundary_KNN( int K )
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{
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testSample.at<float>(0) = (float)x;
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testSample.at<float>(1) = (float)y;
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#ifdef HAVE_OPENCV_OCL
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#if defined HAVE_OPENCV_OCL && _OCL_KNN_
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testSample_ocl.upload(testSample);
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knnClassifier.find_nearest(testSample_ocl, K, reslut_ocl);
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@ -180,7 +182,7 @@ static void find_decision_boundary_SVM( CvSVMParams params )
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prepare_train_data( trainSamples, trainClasses );
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// learn classifier
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#ifdef HAVE_OPENCV_OCL
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#if defined HAVE_OPENCV_OCL && _OCL_SVM_
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cv::ocl::CvSVM_OCL svmClassifier(trainSamples, trainClasses, Mat(), Mat(), params);
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#else
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CvSVM svmClassifier( trainSamples, trainClasses, Mat(), Mat(), params );
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