Fixing alignments

modules/tracking/src/trackerKCF.cpp

@@ -144,7 +144,7 @@ namespace cv{
     params.read( fn );
   }
 
-  void TrackerKCFImpl::write( cv::FileStorage& fs ) const{
+  void TrackerKCFImpl::write( cv::FileStorage& fs ) const {
     params.write( fs );
   }
   
@@ -312,7 +312,7 @@ namespace cv{
   /* 
    * hann window filter
    */
-  void TrackerKCFImpl::createHanningWindow(OutputArray _dst, const cv::Size winSize, const int type)const{
+  void TrackerKCFImpl::createHanningWindow(OutputArray _dst, const cv::Size winSize, const int type) const {
       CV_Assert( type == CV_32FC1 || type == CV_64FC1 );
 
       _dst.create(winSize, type);
@@ -327,20 +327,15 @@ namespace cv{
       for(int j = 0; j < cols; j++)
         wc[j] = 0.5 * (1.0 - cos(coeff0 * j));
 
-      if(dst.depth() == CV_32F)
-      {
-	  for(int i = 0; i < rows; i++)
-	  {
+      if(dst.depth() == CV_32F){
+        for(int i = 0; i < rows; i++){
           float* dstData = dst.ptr<float>(i);
           double wr = 0.5 * (1.0 - cos(coeff1 * i));
           for(int j = 0; j < cols; j++)
             dstData[j] = (float)(wr * wc[j]);
         }
-      }
-      else
-      {
-	  for(int i = 0; i < rows; i++)
-	  {
+      }else{
+        for(int i = 0; i < rows; i++){
           double* dstData = dst.ptr<double>(i);
           double wr = 0.5 * (1.0 - cos(coeff1 * i));
           for(int j = 0; j < cols; j++)
@@ -355,7 +350,7 @@ namespace cv{
   /*
    * simplification of fourier transform function in opencv
    */
-  void inline TrackerKCFImpl::fft2(const Mat src, Mat & dest)const {
+  void inline TrackerKCFImpl::fft2(const Mat src, Mat & dest) const {
     std::vector<Mat> layers(src.channels());
     std::vector<Mat> outputs(src.channels());
     
@@ -368,7 +363,7 @@ namespace cv{
     merge(outputs,dest);
   }
   
-  void inline TrackerKCFImpl::fft2(const Mat src, std::vector<Mat> & dest) const{
+  void inline TrackerKCFImpl::fft2(const Mat src, std::vector<Mat> & dest) const {
     std::vector<Mat> layers(src.channels());
     dest.clear();
     dest.resize(src.channels());
@@ -383,14 +378,14 @@ namespace cv{
   /*
    * simplification of inverse fourier transform function in opencv
    */
-  void inline TrackerKCFImpl::ifft2(const Mat src, Mat & dest)const {
+  void inline TrackerKCFImpl::ifft2(const Mat src, Mat & dest) const {
     idft(src,dest,DFT_SCALE+DFT_REAL_OUTPUT);
   }
   
   /*
    * Point-wise multiplication of two Multichannel Mat data
    */
-  void inline TrackerKCFImpl::pixelWiseMult(const std::vector<Mat> src1, const std::vector<Mat>  src2, std::vector<Mat>  & dest, const int flags, const bool conjB) const{
+  void inline TrackerKCFImpl::pixelWiseMult(const std::vector<Mat> src1, const std::vector<Mat>  src2, std::vector<Mat>  & dest, const int flags, const bool conjB) const {
     dest.clear();
     dest.resize(src1.size());
     
@@ -402,7 +397,7 @@ namespace cv{
   /*
    * Combines all channels in a multi-channels Mat data into a single channel
    */
-  void inline TrackerKCFImpl::sumChannels(std::vector<Mat> src, Mat & dest) const{
+  void inline TrackerKCFImpl::sumChannels(std::vector<Mat> src, Mat & dest) const {
     dest=src[0].clone();
     for(unsigned i=1;i<src.size();i++){
       dest+=src[i];
@@ -412,7 +407,7 @@ namespace cv{
   /*
    * obtains the projection matrix using PCA
    */
-  void inline TrackerKCFImpl::updateProjectionMatrix(const Mat src, Mat & old_cov,Mat &  _proj_mtx, double pca_rate, int compressed_sz)const{
+  void inline TrackerKCFImpl::updateProjectionMatrix(const Mat src, Mat & old_cov,Mat &  _proj_mtx, double pca_rate, int compressed_sz) const {
     CV_Assert(compressed_sz<=src.channels());
     
     // compute average
@@ -451,7 +446,7 @@ namespace cv{
   /*
    * compress the features
    */
-  void inline TrackerKCFImpl::compress(const Mat _proj_mtx, const Mat src, Mat & dest)const{
+  void inline TrackerKCFImpl::compress(const Mat _proj_mtx, const Mat src, Mat & dest) const {
     Mat data=src.reshape(1,src.rows*src.cols);
     Mat compressed=data*_proj_mtx;
     dest=compressed.reshape(_proj_mtx.cols,src.rows).clone();
@@ -460,7 +455,7 @@ namespace cv{
   /*
    * obtain the patch and apply hann window filter to it
    */
-  bool TrackerKCFImpl::getSubWindow(const Mat img, const Rect _roi, Mat& patch) const{
+  bool TrackerKCFImpl::getSubWindow(const Mat img, const Rect _roi, Mat& patch) const {
 
     Rect region=_roi;
   
@@ -539,7 +534,7 @@ namespace cv{
   /*
    *  dense gauss kernel function
    */
-  void TrackerKCFImpl::denseGaussKernel(const double sigma, const Mat _x, const Mat _y, Mat & _k)const{
+  void TrackerKCFImpl::denseGaussKernel(const double sigma, const Mat _x, const Mat _y, Mat & _k) const {
     std::vector<Mat> _xf,_yf,xyf_v;
     Mat xy,xyf;
     double normX, normY;
@@ -641,7 +636,7 @@ namespace cv{
   /*
    * calculate the detection response
    */
-  void TrackerKCFImpl::calcResponse(const Mat _alphaf, const Mat _k, Mat & _response)const {
+  void TrackerKCFImpl::calcResponse(const Mat _alphaf, const Mat _k, Mat & _response) const {
     //alpha f--> 2channels ; k --> 1 channel; 
     Mat _kf;
     fft2(_k,_kf);
@@ -653,7 +648,7 @@ namespace cv{
   /*
    * calculate the detection response for splitted form
    */
-  void TrackerKCFImpl::calcResponse(const Mat _alphaf, const Mat _alphaf_den, const Mat _k, Mat & _response)const {
+  void TrackerKCFImpl::calcResponse(const Mat _alphaf, const Mat _alphaf_den, const Mat _k, Mat & _response) const {
     Mat _kf;
     fft2(_k,_kf);
     Mat spec;