coding style

modules/tracking/src/tld_tracker.hpp

@@ -57,60 +57,67 @@ namespace cv {namespace tld
 #define dfprintf(x)
 #define dprintf(x)
 #endif
-#define MEASURE_TIME(a) {\
-    clock_t start;float milisec = 0.0;\
-    start = clock();{a} milisec = 1000.0 * (clock() - start) / CLOCKS_PER_SEC;\
-    dprintf(("%-90s took %f milis\n",#a,milisec)); }
-#define HERE dprintf(("line %d\n",__LINE__));fflush(stderr);
-#define START_TICK(name) { clock_t start;double milisec = 0.0; start = clock();
-#define END_TICK(name) milisec = 1000.0 * (clock() - start) / CLOCKS_PER_SEC;\
-    dprintf(("%s took %f milis\n",name,milisec)); }
+#define MEASURE_TIME(a)\
+{\
+    clock_t start; float milisec = 0.0; \
+    start = clock(); {a} milisec = 1000.0 * (clock() - start) / CLOCKS_PER_SEC; \
+    dprintf(("%-90s took %f milis\n", #a, milisec));\
+}
+#define HERE dprintf(("line %d\n", __LINE__)); fflush(stderr);
+#define START_TICK(name)\
+{ \
+    clock_t start; double milisec = 0.0; start = clock();
+#define END_TICK(name) milisec = 1000.0 * (clock() - start) / CLOCKS_PER_SEC; \
+    dprintf(("%s took %f milis\n", name, milisec)); \
+}
 extern Rect2d etalon;
 void myassert(const Mat& img);
 void printPatch(const Mat_<uchar>& standardPatch);
 std::string type2str(const Mat& mat);
-void drawWithRects(const Mat& img,std::vector<Rect2d>& blackOnes,Rect2d whiteOne = Rect2d(-1.0,-1.0,-1.0,-1.0));
-void drawWithRects(const Mat& img,std::vector<Rect2d>& blackOnes,std::vector<Rect2d>& whiteOnes,String fileName = "");
+void drawWithRects(const Mat& img, std::vector<Rect2d>& blackOnes, Rect2d whiteOne = Rect2d(-1.0, -1.0, -1.0, -1.0));
+void drawWithRects(const Mat& img, std::vector<Rect2d>& blackOnes, std::vector<Rect2d>& whiteOnes, String fileName = "");
 
 //aux functions and variables
-template<typename T> inline T CLIP(T x,T a,T b){return std::min(std::max(x,a),b);}
+template<typename T> inline T CLIP(T x, T a, T b){ return std::min(std::max(x, a), b); }
 /** Computes overlap between the two given rectangles. Overlap is computed as ratio of rectangles' intersection to that
  * of their union.*/
-double overlap(const Rect2d& r1,const Rect2d& r2);
+double overlap(const Rect2d& r1, const Rect2d& r2);
 /** Resamples the area surrounded by r2 in img so it matches the size of samples, where it is written.*/
-void resample(const Mat& img,const RotatedRect& r2,Mat_<uchar>& samples);
+void resample(const Mat& img, const RotatedRect& r2, Mat_<uchar>& samples);
 /** Specialization of resample() for rectangles without retation for better performance and simplicity.*/
-void resample(const Mat& img,const Rect2d& r2,Mat_<uchar>& samples);
+void resample(const Mat& img, const Rect2d& r2, Mat_<uchar>& samples);
 /** Computes the variance of single given image.*/
 double variance(const Mat& img);
 /** Computes normalized corellation coefficient between the two patches (they should be
  * of the same size).*/
-double NCC(const Mat_<uchar>& patch1,const Mat_<uchar>& patch2);
-void getClosestN(std::vector<Rect2d>& scanGrid,Rect2d bBox,int n,std::vector<Rect2d>& res);
-double scaleAndBlur(const Mat& originalImg,int scale,Mat& scaledImg,Mat& blurredImg,Size GaussBlurKernelSize, double scaleStep);
+double NCC(const Mat_<uchar>& patch1, const Mat_<uchar>& patch2);
+void getClosestN(std::vector<Rect2d>& scanGrid, Rect2d bBox, int n, std::vector<Rect2d>& res);
+double scaleAndBlur(const Mat& originalImg, int scale, Mat& scaledImg, Mat& blurredImg, Size GaussBlurKernelSize, double scaleStep);
 int getMedian(const std::vector<int>& values, int size = -1);
 
-class TLDEnsembleClassifier{
+class TLDEnsembleClassifier
+{
 public:
-    static int makeClassifiers(Size size,int measurePerClassifier,int gridSize,std::vector<TLDEnsembleClassifier>& classifiers);
-    void integrate(const Mat_<uchar>& patch,bool isPositive);
-    double posteriorProbability(const uchar* data,int rowstep)const;
-    double posteriorProbabilityFast(const uchar* data)const;
+    static int makeClassifiers(Size size, int measurePerClassifier, int gridSize, std::vector<TLDEnsembleClassifier>& classifiers);
+    void integrate(const Mat_<uchar>& patch, bool isPositive);
+    double posteriorProbability(const uchar* data, int rowstep) const;
+    double posteriorProbabilityFast(const uchar* data) const;
     void prepareClassifier(int rowstep);
 private:
-    TLDEnsembleClassifier(const std::vector<Vec4b>& meas,int beg,int end);
-    static void stepPrefSuff(std::vector<Vec4b> & arr,int pos,int len,int gridSize);
-    int code(const uchar* data,int rowstep)const;
-    int codeFast(const uchar* data)const;
+    TLDEnsembleClassifier(const std::vector<Vec4b>& meas, int beg, int end);
+    static void stepPrefSuff(std::vector<Vec4b> & arr, int pos, int len, int gridSize);
+    int code(const uchar* data, int rowstep) const;
+    int codeFast(const uchar* data) const;
     std::vector<Point2i> posAndNeg;
     std::vector<Vec4b> measurements;
     std::vector<Point2i> offset;
     int lastStep_;
 };
 
-class TrackerProxy{
+class TrackerProxy
+{
 public:
-    virtual bool init( const Mat& image, const Rect2d& boundingBox) = 0;
+    virtual bool init(const Mat& image, const Rect2d& boundingBox) = 0;
     virtual bool update(const Mat& image, Rect2d& boundingBox) = 0;
     virtual ~TrackerProxy(){}
 };