blur bug

modules/tracking/samples/benchmark.cpp

@@ -7,7 +7,7 @@
 #include <cstring>
 #include <climits>
 
-#define CMDLINEMAX 10
+#define CMDLINEMAX 30
 #define ASSESS_TILL 100
 #define LINEMAX 40
 
@@ -20,7 +20,8 @@ using namespace cv;
 
 static Mat image;
 static bool paused;
-vector<Scalar> palette;
+static bool saveImageKey;
+static vector<Scalar> palette;
 
 void print_table(char* videos[],int videoNum,char* algorithms[],int algNum,const vector<vector<char*> >& results,char* tableName);
 
@@ -67,20 +68,15 @@ static void help(){
   exit(EXIT_SUCCESS);
 }
 static void parseCommandLineArgs(int argc, char** argv,char* videos[],char* gts[],
-        int* vc,char* algorithms[],char* initBoxes[][CMDLINEMAX],int* ac){
+        int* vc,char* algorithms[],char* initBoxes[][CMDLINEMAX],int* ac,char keys[CMDLINEMAX][LINEMAX]){
 
     *ac=*vc=0;
     for(int i=1;i<argc;i++){
         if(argv[i][0]=='-'){
-            char *key=(argv[i]+1),*argument=NULL;
+            for(int j=0;j<CMDLINEMAX;j++){
-            if(std::strcmp("h",key)==0||std::strcmp("help",key)==0){
+                if(!strcmp(argv[i],keys[j])){
-                help();
+                    keys[j][0]='\0';
                 }
-            if((argument=strchr(argv[i],'='))==NULL){
-                i++;
-                argument=argv[i];
-            }else{
-                argument++;
             }
             continue;
         }
@@ -193,6 +189,8 @@ static AssessmentRes assessment(char* video,char* gt_str, char* algorithms[],cha
   int linecount=0;
   Rect2d boundingBox;
   vector<double> averageMillisPerFrame(algnum,0.0);
+  static int videoNum=0;
+  videoNum++;
 
   FILE* gt=fopen(gt_str,"r");
   if(gt==NULL){
@@ -312,6 +310,11 @@ static AssessmentRes assessment(char* video,char* gt_str, char* algorithms[],cha
               res.results[i][j]->assess(boundingBox,initBoxes[i]);
       }
       imshow( "Tracking API", image );
+      if(saveImageKey){
+          char inbuf[LINEMAX];
+          sprintf(inbuf,"image%d_%d.jpg",videoNum,frameCounter);
+          imwrite(inbuf,image);
+      }
 
       if((frameCounter+1)>=ASSESS_TILL){
           break;
@@ -342,7 +345,11 @@ int main( int argc, char** argv ){
   palette.push_back(Scalar(0,255,255));
   int vcount=0,acount=0;
   char* videos[CMDLINEMAX],*gts[CMDLINEMAX],*algorithms[CMDLINEMAX],*initBoxes[CMDLINEMAX][CMDLINEMAX];
-  parseCommandLineArgs(argc,argv,videos,gts,&vcount,algorithms,initBoxes,&acount);
+  char keys[CMDLINEMAX][LINEMAX];
+  strcpy(keys[0],"-s");
+  parseCommandLineArgs(argc,argv,videos,gts,&vcount,algorithms,initBoxes,&acount,keys);
+  saveImageKey=(keys[0][0]=='\0');
+
   CV_Assert(acount<CMDLINEMAX && vcount<CMDLINEMAX);
   printf("videos and gts\n");
   for(int i=0;i<vcount;i++){

modules/tracking/src/TLDEnsembleClassifier.cpp

@@ -48,7 +48,7 @@
 
 using namespace cv;
 
-namespace cv {namespace tld
+namespace cv{namespace tld
 {
 int TLDEnsembleClassifier::getGridSize(){
     return 15;

modules/tracking/src/trackerTLD.cpp

@@ -53,7 +53,7 @@
 #define NEG_EXAMPLES_IN_INIT_MODEL 300
 #define MAX_EXAMPLES_IN_MODEL 500
 #define MEASURES_PER_CLASSIFIER 13
-#undef BLUR_AS_VADIM
+#define BLUR_AS_VADIM
 #undef CLOSED_LOOP
 static const cv::Size GaussBlurKernelSize(3,3);
 
@@ -66,12 +66,12 @@ using namespace tld;
  *      direct formula in resamples
  * FIXME(issues)
  *      THETA_NN 0.5<->0.6 dramatic change vs video 6 !!
- * FIXME(features)
+ * TODO(features)
- *      benchmark: save photos --> two streams of photos --> better video
+ *      benchmark: two streams of photos --> better video
+ *      (try inter_area for resize)
  * TODO:
- *      schoolPC: codec, libopencv-dev
  *      fix pushbot ->pick commits -> compare_branches->all in 1->resubmit
- *      ||video(0.5<->0.6) --> debug if box size is less than 20 --> (remove ensemble self-loop) --> (try inter_area for resize)
+ *      ||video(0.5<->0.6) --> debug if box size is less than 20
  *      perfect PN
  *
  *      vadim:
@@ -446,7 +446,9 @@ timeStampPositiveNext(0),timeStampNegativeNext(0),params_(params){
             }
 
 #ifdef BLUR_AS_VADIM
-            GaussianBlur(standardPatch,blurredPatch,GaussBlurKernelSize,0.0);
+            resize(standardPatch,blurredPatch,minSize);
+            GaussianBlur(blurredPatch,blurredPatch,GaussBlurKernelSize,0.0);
+            CV_Assert(blurredPatch.cols==minSize.width && blurredPatch.rows==minSize.height);
 #else
             resample(blurredImg,RotatedRect(center,size,angle),blurredPatch);
 #endif
@@ -767,17 +769,19 @@ int Pexpert::additionalExamples(std::vector<Mat_<uchar> >& examplesForModel,std:
             size.height=(float)(closest[i].height*rng.uniform((double)0.99,(double)1.01));
             float angle=(float)rng.uniform(-5.0,5.0);
 
-#ifdef BLUR_AS_VADIM
-            GaussianBlur(standardPatch,blurredPatch,GaussBlurKernelSize,0.0);
-#else
-            resample(blurredImg,RotatedRect(center,size,angle),blurredPatch);
-#endif
-            resample(scaledImg,RotatedRect(center,size,angle),standardPatch);
             for(int y=0;y<standardPatch.rows;y++){
                 for(int x=0;x<standardPatch.cols;x++){
                     standardPatch(x,y)+=(uchar)rng.gaussian(5.0);
                 }
             }
+#ifdef BLUR_AS_VADIM
+            resize(standardPatch,blurredPatch,initSize_);
+            GaussianBlur(blurredPatch,blurredPatch,GaussBlurKernelSize,0.0);
+            CV_Assert(blurredPatch.cols==initSize_.width && blurredPatch.rows==initSize_.height);
+#else
+            resample(blurredImg,RotatedRect(center,size,angle),blurredPatch);
+#endif
+            resample(scaledImg,RotatedRect(center,size,angle),standardPatch);
             examplesForModel.push_back(standardPatch);
             examplesForEnsemble.push_back(blurredPatch);
         }