calculate innTilted only for Haar::ALL mode

major time consuming part for training app is in function fillPassedSamples for negatives, 
this change make SetImage quicker, in a test of my own data, the total time for SetImage decrease from 9177666 to 5839263,
only help for Haar feature and non Haar::ALL mode which is the most commonly case

apps/traincascade/haarfeatures.cpp

@@ -100,9 +100,13 @@ void CvHaarEvaluator::setImage(const Mat& img, uchar clsLabel, int idx)
     CV_DbgAssert( !sum.empty() && !tilted.empty() && !normfactor.empty() );
     CvFeatureEvaluator::setImage( img, clsLabel, idx);
     Mat innSum(winSize.height + 1, winSize.width + 1, sum.type(), sum.ptr<int>((int)idx));
-    Mat innTilted(winSize.height + 1, winSize.width + 1, tilted.type(), tilted.ptr<int>((int)idx));
     Mat innSqSum;
-    integral(img, innSum, innSqSum, innTilted);
+    if (((const CvHaarFeatureParams*)featureParams)->mode == CvHaarFeatureParams::ALL) {
+		Mat innTilted(winSize.height + 1, winSize.width + 1, tilted.type(), tilted.ptr<int>((int)idx));
+		integral(img, innSum, innSqSum, innTilted);
+	}
+	else
+		integral(img, innSum, innSqSum);
     normfactor.ptr<float>(0)[idx] = calcNormFactor( innSum, innSqSum );
 }