Add OpenCL SVM paths for bagofwords_classification and points_classifier samples.

samples/cpp/CMakeLists.txt

@@ -20,6 +20,10 @@ if(BUILD_EXAMPLES AND OCV_DEPENDENCIES_FOUND)
     ocv_include_directories("${OpenCV_SOURCE_DIR}/modules/gpu/include")
   endif()
 
+  if(HAVE_opencv_ocl)
+    ocv_include_directories("${OpenCV_SOURCE_DIR}/modules/ocl/include")
+  endif()
+
   if(CMAKE_COMPILER_IS_GNUCXX AND NOT ENABLE_NOISY_WARNINGS)
     set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -Wno-unused-function")
   endif()
@@ -47,6 +51,10 @@ if(BUILD_EXAMPLES AND OCV_DEPENDENCIES_FOUND)
       target_link_libraries(${the_target} opencv_gpu)
     endif()
 
+    if(HAVE_opencv_ocl)
+      target_link_libraries(${the_target} opencv_ocl)
+    endif()
+
     set_target_properties(${the_target} PROPERTIES
       OUTPUT_NAME "cpp-${sample_kind}-${name}"
       PROJECT_LABEL "(${sample_KIND}) ${name}")

samples/cpp/bagofwords_classification.cpp

+#include "opencv2/opencv_modules.hpp"
 #include "opencv2/highgui/highgui.hpp"
 #include "opencv2/imgproc/imgproc.hpp"
 #include "opencv2/features2d/features2d.hpp"
 #include "opencv2/nonfree/nonfree.hpp"
 #include "opencv2/ml/ml.hpp"
+#ifdef HAVE_OPENCV_OCL
+#include "opencv2/ocl/ocl.hpp"
+#endif
 
 #include <fstream>
 #include <iostream>
@@ -2373,9 +2377,15 @@ static void setSVMTrainAutoParams( CvParamGrid& c_grid, CvParamGrid& gamma_grid,
     degree_grid.step = 0;
 }
 
+#ifdef HAVE_OPENCV_OCL
+static void trainSVMClassifier( cv::ocl::CvSVM_OCL& svm, const SVMTrainParamsExt& svmParamsExt, const string& objClassName, VocData& vocData,
+                               Ptr<BOWImgDescriptorExtractor>& bowExtractor, const Ptr<FeatureDetector>& fdetector,
+                               const string& resPath )
+#else
 static void trainSVMClassifier( CvSVM& svm, const SVMTrainParamsExt& svmParamsExt, const string& objClassName, VocData& vocData,
                          Ptr<BOWImgDescriptorExtractor>& bowExtractor, const Ptr<FeatureDetector>& fdetector,
                          const string& resPath )
+#endif
 {
     /* first check if a previously trained svm for the current class has been saved to file */
     string svmFilename = resPath + svmsDir + "/" + objClassName + ".xml.gz";
@@ -2448,9 +2458,15 @@ static void trainSVMClassifier( CvSVM& svm, const SVMTrainParamsExt& svmParamsEx
     }
 }
 
+#ifdef HAVE_OPENCV_OCL
+static void computeConfidences( cv::ocl::CvSVM_OCL& svm, const string& objClassName, VocData& vocData,
+                               Ptr<BOWImgDescriptorExtractor>& bowExtractor, const Ptr<FeatureDetector>& fdetector,
+                               const string& resPath )
+#else
 static void computeConfidences( CvSVM& svm, const string& objClassName, VocData& vocData,
                          Ptr<BOWImgDescriptorExtractor>& bowExtractor, const Ptr<FeatureDetector>& fdetector,
                          const string& resPath )
+#endif
 {
     cout << "*** CALCULATING CONFIDENCES FOR CLASS " << objClassName << " ***" << endl;
     cout << "CALCULATING BOW VECTORS FOR TEST SET OF " << objClassName << "..." << endl;
@@ -2589,7 +2605,11 @@ int main(int argc, char** argv)
     for( size_t classIdx = 0; classIdx < objClasses.size(); ++classIdx )
     {
         // Train a classifier on train dataset
+#ifdef HAVE_OPENCV_OCL
+        cv::ocl::CvSVM_OCL svm;
+#else
         CvSVM svm;
+#endif
         trainSVMClassifier( svm, svmTrainParamsExt, objClasses[classIdx], vocData,
                             bowExtractor, featureDetector, resPath );
 

samples/cpp/points_classifier.cpp

+#include "opencv2/opencv_modules.hpp"
 #include "opencv2/core/core.hpp"
 #include "opencv2/ml/ml.hpp"
 #include "opencv2/highgui/highgui.hpp"
+#ifdef HAVE_OPENCV_OCL
+#include "opencv2/ocl/ocl.hpp"
+#endif
 
 #include <stdio.h>
 
@@ -133,7 +137,14 @@ static void find_decision_boundary_KNN( int K )
     prepare_train_data( trainSamples, trainClasses );
 
     // learn classifier
+#ifdef HAVE_OPENCV_OCL
+    cv::ocl::KNearestNeighbour knnClassifier;
+    Mat temp, result;
+    knnClassifier.train(trainSamples, trainClasses, temp, false, K);
+    cv::ocl::oclMat testSample_ocl, reslut_ocl;
+#else
     CvKNearest knnClassifier( trainSamples, trainClasses, Mat(), false, K );
+#endif
 
     Mat testSample( 1, 2, CV_32FC1 );
     for( int y = 0; y < img.rows; y += testStep )
@@ -142,9 +153,19 @@ static void find_decision_boundary_KNN( int K )
         {
             testSample.at<float>(0) = (float)x;
             testSample.at<float>(1) = (float)y;
+#ifdef HAVE_OPENCV_OCL
+            testSample_ocl.upload(testSample);
+
+            knnClassifier.find_nearest(testSample_ocl, K, reslut_ocl);
+
+            reslut_ocl.download(result);
+            int response = saturate_cast<int>(result.at<float>(0));
+            circle(imgDst, Point(x, y), 1, classColors[response]);
+#else
 
             int response = (int)knnClassifier.find_nearest( testSample, K );
             circle( imgDst, Point(x,y), 1, classColors[response] );
+#endif
         }
     }
 }
@@ -159,7 +180,11 @@ static void find_decision_boundary_SVM( CvSVMParams params )
     prepare_train_data( trainSamples, trainClasses );
 
     // learn classifier
+#ifdef HAVE_OPENCV_OCL
+    cv::ocl::CvSVM_OCL svmClassifier(trainSamples, trainClasses, Mat(), Mat(), params);
+#else
     CvSVM svmClassifier( trainSamples, trainClasses, Mat(), Mat(), params );
+#endif
 
     Mat testSample( 1, 2, CV_32FC1 );
     for( int y = 0; y < img.rows; y += testStep )
@@ -178,7 +203,7 @@ static void find_decision_boundary_SVM( CvSVMParams params )
     for( int i = 0; i < svmClassifier.get_support_vector_count(); i++ )
     {
         const float* supportVector = svmClassifier.get_support_vector(i);
-        circle( imgDst, Point(supportVector[0],supportVector[1]), 5, Scalar(255,255,255), -1 );
+        circle( imgDst, Point(saturate_cast<int>(supportVector[0]),saturate_cast<int>(supportVector[1])), 5, CV_RGB(255,255,255), -1 );
     }
 
 }