refactor: don't use CV_ErrorNoReturn() internally

Author: alalek

modules/face/src/face_alignment.cpp

@@ -79,8 +79,7 @@ bool FacemarkKazemiImpl::convertToUnit(Rect r,Mat &warp){
 bool FacemarkKazemiImpl::setMeanExtreme(){
     if(meanshape.empty()){
         String error_message = "Model not loaded properly.No mean shape found.Aborting...";
-        CV_ErrorNoReturn(Error::StsBadArg, error_message);
-        return false;
+        CV_Error(Error::StsBadArg, error_message);
     }
     for(size_t i=0;i<meanshape.size();i++){
         if(meanshape[i].x>maxmeanx)
@@ -98,7 +97,7 @@ bool FacemarkKazemiImpl::calcMeanShape (vector< vector<Point2f> >& trainlandmark
     //clear the loaded meanshape
     if(trainimages.empty()||trainlandmarks.size()!=trainimages.size()) {
         // throw error if no data (or simply return -1?)
-        CV_ErrorNoReturn(Error::StsBadArg, "Number of images is not equal to corresponding landmarks. Aborting...");
+        CV_Error(Error::StsBadArg, "Number of images is not equal to corresponding landmarks. Aborting...");
     }
     meanshape.clear();
     vector<Mat> finalimages;
@@ -165,7 +164,7 @@ bool FacemarkKazemiImpl::scaleData( vector< vector<Point2f> > & trainlandmarks,
 {
     if(trainimages.empty()||trainimages.size()!=trainlandmarks.size()){
         // throw error if no data (or simply return -1?)
-        CV_ErrorNoReturn(Error::StsBadArg, "The data is not loaded properly by train function. Aborting...");
+        CV_Error(Error::StsBadArg, "The data is not loaded properly by train function. Aborting...");
     }
     float scalex,scaley;
     //scale all images and their landmarks according  to input size

modules/face/src/facemark.cpp

@@ -228,8 +228,7 @@ bool loadTrainingData(vector<String> filename,vector< vector<Point2f> >
         f1.open(filename[j].c_str(),ios::in);
         if(!f1.is_open()){
             cout<<filename[j]<<endl;
-            CV_ErrorNoReturn(Error::StsError, "File can't be opened for reading!");
-            return false;
+            CV_Error(Error::StsError, "File can't be opened for reading!");
         }
         //get the path of the image whose landmarks have to be detected
         getline(f1,img);

modules/face/src/regtree.cpp

@@ -113,8 +113,7 @@ bool FacemarkKazemiImpl:: getBestSplit(vector<Point2f> pixel_coordinates, vector
 {
     if(samples[0].shapeResiduals.size()!=samples[0].current_shape.size()){
         String error_message = "Error while generating split.Residuals are not complete.Aborting....";
-        CV_ErrorNoReturn(Error::StsBadArg, error_message);
-        return false;
+        CV_Error(Error::StsBadArg, error_message);
     }
     //This vector stores the matrices where each matrix represents
     //sum of the residuals of shapes of samples which go to the left
@@ -222,13 +221,11 @@ bool FacemarkKazemiImpl :: generateSplit(queue<node_info>& curr,vector<Point2f>
 bool FacemarkKazemiImpl :: buildRegtree(regtree& tree,vector<training_sample>& samples,vector<Point2f> pixel_coordinates){
     if(samples.size()==0){
         String error_message = "Error while building regression tree.Empty samples. Aborting....";
-        CV_ErrorNoReturn(Error::StsBadArg, error_message);
-        return false;
+        CV_Error(Error::StsBadArg, error_message);
     }
     if(pixel_coordinates.size()==0){
         String error_message = "Error while building regression tree.No pixel coordinates. Aborting....";
-        CV_ErrorNoReturn(Error::StsBadArg, error_message);
-        return false;
+        CV_Error(Error::StsBadArg, error_message);
     }
     queue<node_info> curr;
     node_info parent;
@@ -291,8 +288,7 @@ unsigned long FacemarkKazemiImpl::divideSamples (splitr split,vector<training_sa
 {
     if(samples.size()==0){
         String error_message = "Error while dividing samples. Sample array empty. Aborting....";
-        CV_ErrorNoReturn(Error::StsBadArg, error_message);
-        return 0;
+        CV_Error(Error::StsBadArg, error_message);
     }
     unsigned long i = start;
     training_sample temp;

modules/face/src/trainFacemark.cpp

@@ -54,8 +54,7 @@ bool FacemarkKazemiImpl::setTrainingParameters(String filename){
     fs.open(filename, FileStorage::READ);
     if (!fs.isOpened())
     {   String error_message = "Error while opening configuration file.Aborting..";
-        CV_ErrorNoReturn(Error::StsBadArg, error_message);
-        return false;
+        CV_Error(Error::StsBadArg, error_message);
     }
     int cascade_depth_;
     int tree_depth_;
@@ -105,8 +104,7 @@ unsigned long FacemarkKazemiImpl::  getNearestLandmark(Point2f pixel)
     if(meanshape.empty()) {
             // throw error if no data (or simply return -1?)
             String error_message = "The data is not loaded properly by train function. Aborting...";
-            CV_ErrorNoReturn(Error::StsBadArg, error_message);
-            return false;
+            CV_Error(Error::StsBadArg, error_message);
     }
     float dist=float(INT_MAX);
     unsigned long index =0;
@@ -122,8 +120,7 @@ unsigned long FacemarkKazemiImpl::  getNearestLandmark(Point2f pixel)
 bool FacemarkKazemiImpl :: getRelativePixels(vector<Point2f> sample,vector<Point2f>& pixel_coordinates,std::vector<int> nearest){
     if(sample.size()!=meanshape.size()){
         String error_message = "Error while finding relative shape. Aborting....";
-        CV_ErrorNoReturn(Error::StsBadArg, error_message);
-        return false;
+        CV_Error(Error::StsBadArg, error_message);
     }
     Mat transform_mat;
     transform_mat = estimateRigidTransform(meanshape,sample,false);
@@ -146,8 +143,7 @@ bool FacemarkKazemiImpl :: getRelativePixels(vector<Point2f> sample,vector<Point
 bool FacemarkKazemiImpl::getPixelIntensities(Mat img,vector<Point2f> pixel_coordinates,vector<int>& pixel_intensities,Rect face){
     if(pixel_coordinates.size()==0){
         String error_message = "No pixel coordinates found. Aborting.....";
-        CV_ErrorNoReturn(Error::StsBadArg, error_message);
-        return false;
+        CV_Error(Error::StsBadArg, error_message);
     }
     Mat transform_mat;
     convertToActual(face,transform_mat);
@@ -259,13 +255,11 @@ bool FacemarkKazemiImpl :: saveModel(String filename){
     ofstream f(filename.c_str(),ios::binary);
     if(!f.is_open()){
         String error_message = "Error while opening file to write model. Aborting....";
-        CV_ErrorNoReturn(Error::StsBadArg, error_message);
-        return false;
+        CV_Error(Error::StsBadArg, error_message);
     }
     if(loaded_forests.size()!=loaded_pixel_coordinates.size()){
         String error_message = "Incorrect training data. Aborting....";
-        CV_ErrorNoReturn(Error::StsBadArg, error_message);
-        return false;
+        CV_Error(Error::StsBadArg, error_message);
     }
     string s("cascade_depth");
     uint64_t len = s.size();
@@ -306,23 +300,20 @@ void FacemarkKazemiImpl::training(String imageList, String groundTruth){
     imageList.clear();
     groundTruth.clear();
     String error_message = "Less arguments than required";
-    CV_ErrorNoReturn(Error::StsBadArg, error_message);
-    return ;
+    CV_Error(Error::StsBadArg, error_message);
 }
 bool FacemarkKazemiImpl::training(vector<Mat>& images, vector< vector<Point2f> >& landmarks,string filename,Size scale,string modelFilename){
     if(!setTrainingParameters(filename)){
         String error_message = "Error while loading training parameters";
-        CV_ErrorNoReturn(Error::StsBadArg, error_message);
-        return false;
+        CV_Error(Error::StsBadArg, error_message);
     }
     vector<Rect> rectangles;
     scaleData(landmarks,images,scale);
     calcMeanShape(landmarks,images,rectangles);
     if(images.size()!=landmarks.size()){
         // throw error if no data (or simply return -1?)
         String error_message = "The data is not loaded properly. Aborting training function....";
-        CV_ErrorNoReturn(Error::StsBadArg, error_message);
-        return false;
+        CV_Error(Error::StsBadArg, error_message);
     }
     vector<training_sample> samples;
     getTestCoordinates();

modules/tracking/src/gtrTracker.cpp

@@ -58,7 +58,7 @@ Ptr<TrackerGOTURN> TrackerGOTURN::create(const TrackerGOTURN::Params &parameters
     return Ptr<gtr::TrackerGOTURNImpl>(new gtr::TrackerGOTURNImpl(parameters));
 #else
     (void)(parameters);
-    CV_ErrorNoReturn(cv::Error::StsNotImplemented , "to use GOTURN, the tracking module needs to be built with opencv_dnn !");
+    CV_Error(cv::Error::StsNotImplemented , "to use GOTURN, the tracking module needs to be built with opencv_dnn !");
 #endif
 }
 Ptr<TrackerGOTURN> TrackerGOTURN::create()