min and max params become double

modules/objdetect/include/opencv2/objdetect/objdetect.hpp

@@ -523,12 +523,12 @@ public:
         // Param gray is an input 1-channel gray image.
         // Param integrals is a vector of integrals. Hog-channels will be appended to it.
         // Param bins is a number of hog-bins
-        void appendHogBins(const cv::Mat gray, std::vector<cv::Mat>& integrals, int bins) const;
+        void appendHogBins(const cv::Mat& gray, std::vector<cv::Mat>& integrals, int bins) const;
 
         // Converts 3-channel BGR input frame in  Luv and appends each channel to the integrals.
         // Param frame is an input 3-channel BGR colored image.
         // Param integrals is a vector of integrals. Computed from the frame luv-channels will be appended to it.
-        void appendLuvBins(const cv::Mat frame, std::vector<cv::Mat>& integrals) const;
+        void appendLuvBins(const cv::Mat& frame, std::vector<cv::Mat>& integrals) const;
 
     private:
         int shrinkage;
@@ -539,7 +539,7 @@ public:
     // Param minScale is a maximum scale relative to the original size of the image on which cascade will be applyed.
     // Param scales is a number of scales from minScale to maxScale.
     // Param rejfactor is used for NMS.
-    SCascade(const float minScale = 0.4f, const float maxScale = 5.f, const int scales = 55, const int rejfactor = 1);
+    SCascade(const double minScale = 0.4, const double maxScale = 5., const int scales = 55, const int rejfactor = 1);
 
     virtual ~SCascade();
 
@@ -564,8 +564,9 @@ private:
     struct Fields;
     Fields* fields;
 
-    float minScale;
-    float maxScale;
+    double minScale;
+    double maxScale;
+
     int   scales;
     int   rejfactor;
 };

modules/objdetect/src/icf.cpp

@@ -44,7 +44,7 @@
 
 cv::SCascade::Channels::Channels(int shr) : shrinkage(shr) {}
 
-void cv::SCascade::Channels::appendHogBins(const cv::Mat gray, std::vector<cv::Mat>& integrals, int bins) const
+void cv::SCascade::Channels::appendHogBins(const cv::Mat& gray, std::vector<cv::Mat>& integrals, int bins) const
 {
     CV_Assert(gray.type() == CV_8UC1);
     int h = gray.rows;
@@ -92,7 +92,7 @@ void cv::SCascade::Channels::appendHogBins(const cv::Mat gray, std::vector<cv::M
     integrals.push_back(mag);
 }
 
-void cv::SCascade::Channels::appendLuvBins(const cv::Mat frame, std::vector<cv::Mat>& integrals) const
+void cv::SCascade::Channels::appendLuvBins(const cv::Mat& frame, std::vector<cv::Mat>& integrals) const
 {
     CV_Assert(frame.type() == CV_8UC3);
     CV_Assert(!(frame.cols % shrinkage) && !(frame.rows % shrinkage));

modules/objdetect/src/softcascade.cpp

@@ -296,10 +296,10 @@ struct cv::SCascade::Fields
     void calcLevels(const cv::Size& curr, float mins, float maxs, int total)
     {
         if (frameSize == curr && maxs == maxScale && mins == minScale && total == scales) return;
-        CV_Assert(scales > 1);
 
         frameSize = curr;
         maxScale = maxs; minScale = mins; scales = total;
+        CV_Assert(scales > 1);
 
         levels.clear();
         float logFactor = (log(maxScale) - log(minScale)) / (scales -1);
@@ -415,7 +415,7 @@ struct cv::SCascade::Fields
     }
 };
 
-cv::SCascade::SCascade(const float mins, const float maxs, const int nsc, const int rej)
+cv::SCascade::SCascade(const double mins, const double maxs, const int nsc, const int rej)
 : fields(0), minScale(mins), maxScale(maxs), scales(nsc), rejfactor(rej) {}
 
 cv::SCascade::~SCascade() { delete fields;}
@@ -462,7 +462,7 @@ void cv::SCascade::detect(cv::InputArray _image, cv::InputArray _rois, std::vect
     CV_Assert(image.type() == CV_8UC3);
 
     Fields& fld = *fields;
-    fld.calcLevels(image.size(),minScale, maxScale, scales);
+    fld.calcLevels(image.size(),(float) minScale, (float)maxScale, (float)scales);
 
     objects.clear();