fixes

modules/objdetect/include/opencv2/objdetect.hpp

@@ -313,8 +313,6 @@ public:
                          Size winStride = Size(), Size padding = Size(),
                          const std::vector<Point>& locations = std::vector<Point>()) const;
 
-    virtual bool ocl_compute(InputArray _img, Size win_stride, std::vector<float>& descriptors, int descr_format) const;
-
     //with found weights output
     CV_WRAP virtual void detect(const Mat& img, CV_OUT std::vector<Point>& foundLocations,
                         CV_OUT std::vector<double>& weights,
@@ -326,9 +324,7 @@ public:
                         double hitThreshold = 0, Size winStride = Size(),
                         Size padding = Size(),
                         const std::vector<Point>& searchLocations=std::vector<Point>()) const;
-    //ocl
-    virtual bool ocl_detect(InputArray img, std::vector<Point> &hits,
-                       double hitThreshold = 0, Size winStride = Size()) const;
+
     //with result weights output
     CV_WRAP virtual void detectMultiScale(InputArray img, CV_OUT std::vector<Rect>& foundLocations,
                                   CV_OUT std::vector<double>& foundWeights, double hitThreshold = 0,
@@ -339,9 +335,6 @@ public:
                                   double hitThreshold = 0, Size winStride = Size(),
                                   Size padding = Size(), double scale = 1.05,
                                   double finalThreshold = 2.0, bool useMeanshiftGrouping = false) const;
-    //ocl
-    virtual bool ocl_detectMultiScale(InputArray img, std::vector<Rect> &found_locations, std::vector<double>& level_scale,
-                                      double hit_threshold, Size winStride, double groupThreshold) const;
 
     CV_WRAP virtual void computeGradient(const Mat& img, CV_OUT Mat& grad, CV_OUT Mat& angleOfs,
                                  Size paddingTL = Size(), Size paddingBR = Size()) const;
@@ -361,25 +354,26 @@ public:
     CV_PROP bool gammaCorrection;
     CV_PROP std::vector<float> svmDetector;
     UMat oclSvmDetector;
+    float free_coef;
     CV_PROP int nlevels;
 
 
-   // evaluate specified ROI and return confidence value for each location
-   virtual void detectROI(const cv::Mat& img, const std::vector<cv::Point> &locations,
+    // evaluate specified ROI and return confidence value for each location
+    virtual void detectROI(const cv::Mat& img, const std::vector<cv::Point> &locations,
                                    CV_OUT std::vector<cv::Point>& foundLocations, CV_OUT std::vector<double>& confidences,
                                    double hitThreshold = 0, cv::Size winStride = Size(),
                                    cv::Size padding = Size()) const;
 
-   // evaluate specified ROI and return confidence value for each location in multiple scales
-   virtual void detectMultiScaleROI(const cv::Mat& img,
+    // evaluate specified ROI and return confidence value for each location in multiple scales
+    virtual void detectMultiScaleROI(const cv::Mat& img,
                                                        CV_OUT std::vector<cv::Rect>& foundLocations,
                                                        std::vector<DetectionROI>& locations,
                                                        double hitThreshold = 0,
                                                        int groupThreshold = 0) const;
 
-   // read/parse Dalal's alt model file
-   void readALTModel(String modelfile);
-   void groupRectangles(std::vector<cv::Rect>& rectList, std::vector<double>& weights, int groupThreshold, double eps) const;
+    // read/parse Dalal's alt model file
+    void readALTModel(String modelfile);
+    void groupRectangles(std::vector<cv::Rect>& rectList, std::vector<double>& weights, int groupThreshold, double eps) const;
 };
 
 

modules/objdetect/perf/opencl/perf_hogdetect.cpp

@@ -74,10 +74,10 @@ OCL_PERF_TEST(HOGFixture, HOG)
 {
     UMat src;
     imread(getDataPath("gpu/hog/road.png"), cv::IMREAD_GRAYSCALE).copyTo(src);
-    CV_Assert(!src.empty());
+    ASSERT_FALSE(src.empty());
 
     vector<cv::Rect> found_locations;
-    declare.in(src).time(5);
+    declare.in(src);
 
     HOGDescriptor hog;
     hog.setSVMDetector(hog.getDefaultPeopleDetector());