Merge pull request #2 from Auron-X/TLD_fixes_&_optimizations

Tld fixes & optimizations

modules/tracking/samples/tld_test.cpp

@@ -118,7 +118,7 @@ int main()
 	//  VideoCapture cap(0);
 	//  if( !cap.isOpened() )
 	//  {
-	// cout << "Video stream error";	
+	// cout << "Video stream error";
 	//    return;
 	//  }
 	//cap >> frame;

modules/tracking/src/TrackingFunctionPF.hpp

@@ -24,7 +24,6 @@ namespace cv{
                 Mat_<double> HShist, Vhist;
             };
             TrackingHistogram _origHist;
-			
 			const TrackingFunctionPF & operator = (const TrackingFunctionPF &);
     };
 

modules/tracking/src/tldDetector.cpp

@@ -53,7 +53,7 @@ namespace cv
 		}
 
 		// Calculate posterior probability, that the patch belongs to the current EC model
- 		double TLDDetector::ensembleClassifierNum(const uchar* data)
+		double TLDDetector::ensembleClassifierNum(const uchar* data)
 		{
 			double p = 0;
 			for (int k = 0; k < (int)classifiers.size(); k++)
@@ -146,7 +146,6 @@ namespace cv
 			Rect2d maxScRect;
 
 			//Detection part
-			//To fix: use precalculated BB 
 			do
 			{
 				Mat_<double> intImgP, intImgP2;

modules/tracking/src/tldDetector.hpp

@@ -70,7 +70,6 @@ namespace cv
 		public:
 			TLDDetector(){}
 			~TLDDetector(){}
-			
 			inline double ensembleClassifierNum(const uchar* data);
 			inline void prepareClassifiers(int rowstep);
 			double Sr(const Mat_<uchar>& patch);
@@ -89,8 +88,8 @@ namespace cv
 			};
 			bool detect(const Mat& img, const Mat& imgBlurred, Rect2d& res, std::vector<LabeledPatch>& patches, Size initSize);
 		protected:
-			
-			
+
+
 
 			friend class MyMouseCallbackDEBUG;
 			void computeIntegralImages(const Mat& img, Mat_<double>& intImgP, Mat_<double>& intImgP2){ integral(img, intImgP, intImgP2, CV_64F); }

modules/tracking/src/tldEnsembleClassifier.cpp

@@ -55,8 +55,7 @@ namespace cv
 			measurements.assign(meas.begin() + beg, meas.begin() + end);
 			offset.assign(mpc, Point2i(0, 0));
 		}
-		
-		// Calculate measure locations from 15x15 grid on minSize patches 
+		// Calculate measure locations from 15x15 grid on minSize patches
 		void TLDEnsembleClassifier::stepPrefSuff(std::vector<Vec4b>& arr, int pos, int len, int gridSize)
 		{
 #if 0
@@ -92,7 +91,7 @@ namespace cv
 			}
 #endif
 		}
-		
+
 		// Calculate offsets for classifier
 		void TLDEnsembleClassifier::prepareClassifier(int rowstep)
 		{
@@ -106,7 +105,7 @@ namespace cv
 				}
 			}
 		}
-		
+
 		// Integrate patch into the Ensemble Classifier model
 		void TLDEnsembleClassifier::integrate(const Mat_<uchar>& patch, bool isPositive)
 		{
@@ -137,7 +136,7 @@ namespace cv
 				return posNum / (posNum + negNum);
 		}
 
-		// Calculate the 13-bit fern index 
+		// Calculate the 13-bit fern index
 		int TLDEnsembleClassifier::codeFast(const uchar* data) const
 		{
 			int position = 0;
@@ -188,7 +187,7 @@ namespace cv
 			stepPrefSuff(measurements, 2, size.height, gridSize);
 			stepPrefSuff(measurements, 3, size.height, gridSize);
 
-			//Compile fern classifiers 
+			//Compile fern classifiers
 			for (int i = 0, howMany = (int)measurements.size() / measurePerClassifier; i < howMany; i++)
 				classifiers.push_back(TLDEnsembleClassifier(measurements, i * measurePerClassifier, (i + 1) * measurePerClassifier));
 

modules/tracking/src/tldEnsembleClassifier.hpp

@@ -65,6 +65,5 @@ namespace cv
 			int lastStep_;
 		};
 
-	
 	}
 }
\ No newline at end of file

modules/tracking/src/tldModel.cpp

@@ -64,13 +64,12 @@ namespace cv
 
 			//Calculate the variance in initial BB
 			originalVariance_ = variance(image(boundingBox));
-			
 			//Find the scale
 			double scale = scaleAndBlur(image, cvRound(log(1.0 * boundingBox.width / (minSize.width)) / log(SCALE_STEP)),
 				scaledImg, blurredImg, GaussBlurKernelSize, SCALE_STEP);
 			GaussianBlur(image, image_blurred, GaussBlurKernelSize, 0.0);
 			TLDDetector::generateScanGrid(image.rows, image.cols, minSize_, scanGrid);
-			getClosestN(scanGrid, Rect2d(boundingBox.x / scale, boundingBox.y / scale, boundingBox.width / scale, 
+			getClosestN(scanGrid, Rect2d(boundingBox.x / scale, boundingBox.y / scale, boundingBox.width / scale,
 				boundingBox.height / scale), 10, closest);
 
 			Mat_<uchar> blurredPatch(minSize);
@@ -271,7 +270,7 @@ namespace cv
 		}
 
 
-		
+
 
 	}
 }
\ No newline at end of file

modules/tracking/src/tldModel.hpp

@@ -51,7 +51,6 @@ namespace cv
 	namespace tld
 	{
 
-		
 
 
 		class TrackerTLDModel : public TrackerModel
@@ -75,14 +74,13 @@ namespace cv
 
 		protected:
 			Size minSize_;
-			
 			TrackerTLD::Params params_;
 			void pushIntoModel(const Mat_<uchar>& example, bool positive);
 			void modelEstimationImpl(const std::vector<Mat>& /*responses*/){}
 			void modelUpdateImpl(){}
-			Rect2d boundingBox_;			
+			Rect2d boundingBox_;
 			RNG rng;
-			
+
 		};
 
 	}

modules/tracking/src/tldTracker.cpp

@@ -89,7 +89,7 @@ bool TrackerTLDImpl::initImpl(const Mat& image, const Rect2d& boundingBox)
         myBoundingBox.width *= scale;
         myBoundingBox.height *= scale;
     }
-    model = Ptr<TrackerTLDModel>(new TrackerTLDModel(params, image_gray, myBoundingBox, data->getMinSize()));    
+    model = Ptr<TrackerTLDModel>(new TrackerTLDModel(params, image_gray, myBoundingBox, data->getMinSize()));
 
     data->confident = false;
     data->failedLastTime = false;
@@ -119,7 +119,7 @@ bool TrackerTLDImpl::updateImpl(const Mat& image, Rect2d& boundingBox)
     for( int i = 0; i < 2; i++ )
     {
         Rect2d tmpCandid = boundingBox;
-        if( ( (i == 0) && !data->failedLastTime && trackerProxy->update(image, tmpCandid) ) || 
+        if( ( (i == 0) && !data->failedLastTime && trackerProxy->update(image, tmpCandid) ) ||
 			((i == 1) && (tldModel->detector->detect(imageForDetector, image_blurred, tmpCandid, detectorResults, tldModel->getMinSize()))))
         {
             candidates.push_back(tmpCandid);
@@ -292,6 +292,6 @@ void Data::printme(FILE*  port)
     dfprintf((port, "\tminSize = %dx%d\n", minSize.width, minSize.height));
 }
 
-} 
+}
 
-} 
+}

modules/tracking/src/tldTracker.hpp

@@ -49,7 +49,7 @@
 #include<algorithm>
 #include<limits.h>
 
-namespace cv 
+namespace cv
 {
 
 TrackerTLD::Params::Params(){}
@@ -60,7 +60,6 @@ void TrackerTLD::Params::write(cv::FileStorage& /*fs*/) const {}
 
 namespace tld
 {
-		
 
 class TrackerProxy
 {

modules/tracking/src/tldUtils.cpp

@@ -42,7 +42,7 @@
 #include "tldUtils.hpp"
 
 
-namespace cv 
+namespace cv
 {
 namespace tld
 {

modules/tracking/src/trackerMedianFlow.cpp

@@ -63,7 +63,7 @@ namespace cv
 /*
  * TODO:
  * add "non-detected" answer in algo --> test it with 2 rects --> frame-by-frame debug in TLD --> test it!!
- * take all parameters out 
+ * take all parameters out
  *              asessment framework
  *
  *

modules/tracking/src/trackerSamplerAlgorithm.cpp

@@ -385,7 +385,7 @@ TrackerSamplerPF::Params::Params(){
     iterationNum=20;
     particlesNum=100;
     alpha=0.9;
-    std=(Mat_<double>(1,4)<<15.0,15.0,15.0,15.0); 
+    std=(Mat_<double>(1,4)<<15.0,15.0,15.0,15.0);
 }
 TrackerSamplerPF::TrackerSamplerPF(const Mat& chosenRect,const TrackerSamplerPF::Params &parameters):
     params( parameters ),_function(new TrackingFunctionPF(chosenRect)){