Let perf/accuracy test of ocl haar uses detectMultiScale api.

Fix image to be used by perf test.

modules/ocl/perf/perf_haar.cpp

@@ -48,49 +48,11 @@
 using namespace perf;
 
 ///////////// Haar ////////////////////////
-namespace cv
-{
-namespace ocl
-{
-
-struct getRect
-{
-    Rect operator()(const CvAvgComp &e) const
-    {
-        return e.rect;
-    }
-};
-
-class CascadeClassifier_GPU : public OclCascadeClassifier
-{
-public:
-    void detectMultiScale(oclMat &image,
-                          CV_OUT std::vector<cv::Rect>& faces,
-                          double scaleFactor = 1.1,
-                          int minNeighbors = 3, int flags = 0,
-                          Size minSize = Size(),
-                          Size maxSize = Size())
-    {
-        (void)maxSize;
-        MemStorage storage(cvCreateMemStorage(0));
-        //CvMat img=image;
-        CvSeq *objs = oclHaarDetectObjects(image, storage, scaleFactor, minNeighbors, flags, minSize);
-        vector<CvAvgComp> vecAvgComp;
-        Seq<CvAvgComp>(objs).copyTo(vecAvgComp);
-        faces.resize(vecAvgComp.size());
-        std::transform(vecAvgComp.begin(), vecAvgComp.end(), faces.begin(), getRect());
-    }
-
-};
-
-}
-}
-
 PERF_TEST(HaarFixture, Haar)
 {
     vector<Rect> faces;
 
-    Mat img = imread(getDataPath("gpu/haarcascade/basketball1.png"), CV_LOAD_IMAGE_GRAYSCALE);
+    Mat img = imread(getDataPath("gpu/haarcascade/group_1_640x480_VGA.pgm"), CV_LOAD_IMAGE_GRAYSCALE);
     ASSERT_TRUE(!img.empty()) << "can't open basketball1.png";
     declare.in(img);
 
@@ -107,7 +69,7 @@ PERF_TEST(HaarFixture, Haar)
     }
     else if (RUN_OCL_IMPL)
     {
-        ocl::CascadeClassifier_GPU faceCascade;
+        ocl::OclCascadeClassifier faceCascade;
         ocl::oclMat oclImg(img);
 
         ASSERT_TRUE(faceCascade.load(getDataPath("gpu/haarcascade/haarcascade_frontalface_alt.xml")))

modules/ocl/test/test_objdetect.cpp

@@ -218,14 +218,9 @@ PARAM_TEST_CASE(Haar, int, CascadeName)
 
 OCL_TEST_P(Haar, FaceDetect)
 {
-    MemStorage storage(cvCreateMemStorage(0));
-    CvSeq *_objects;
-    _objects = cascade.oclHaarDetectObjects(d_img, storage, 1.1, 3,
-                                            flags, Size(30, 30), Size(0, 0));
-    vector<CvAvgComp> vecAvgComp;
-    Seq<CvAvgComp>(_objects).copyTo(vecAvgComp);
-    oclfaces.resize(vecAvgComp.size());
-    std::transform(vecAvgComp.begin(), vecAvgComp.end(), oclfaces.begin(), getRect());
+    cascade.detectMultiScale(d_img, oclfaces,  1.1, 3,
+                                flags,
+                                Size(30, 30), Size(0, 0));
 
     cpucascade.detectMultiScale(img, faces,  1.1, 3,
                                 flags,

samples/ocl/facedetect.cpp

@@ -41,7 +41,7 @@ static double getTime()
 
 
 static void detect( Mat& img, vector<Rect>& faces,
-             ocl::OclCascadeClassifierBuf& cascade,
+             ocl::OclCascadeClassifier& cascade,
              double scale, bool calTime);
 
 
@@ -87,7 +87,7 @@ int main( int argc, const char** argv )
     outputName = cmd.get<string>("o");
     string cascadeName = cmd.get<string>("t");
     double scale = cmd.get<double>("c");
-    ocl::OclCascadeClassifierBuf cascade;
+    ocl::OclCascadeClassifier cascade;
     CascadeClassifier  cpu_cascade;
 
     if( !cascade.load( cascadeName ) || !cpu_cascade.load(cascadeName) )
@@ -180,7 +180,7 @@ int main( int argc, const char** argv )
 }
 
 void detect( Mat& img, vector<Rect>& faces,
-             ocl::OclCascadeClassifierBuf& cascade,
+             ocl::OclCascadeClassifier& cascade,
              double scale, bool calTime)
 {
     ocl::oclMat image(img);